A Test of Revisionist Narratives of History in Pre- Famine Ireland

“Well-Formed and Vigorous Bodies?” A Test of Revisionist Narratives of History in Pre- Famine Ireland

DISSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University

Melissa Ann Clark

Graduate Program in Anthropology

The Ohio State University

2020

Dissertation Committee:

Professor Debbie Guatelli-Steinberg, co-advisor

Professor Mark Hubbe, co-advisor

Professor Julie Field

Professor Douglas E. Crews

Copyrighted by

Melissa Ann Clark

2020

Abstract

Irish scholarship over the last 50 years has focused on the debate between revisionist and post-revisionist arguments. Revisionists have argued that the effects of

British colonization have been overstated to fuel the Irish nationalist agenda in their quest to separate from England. They cite contemporaneous (c. AD 1600-1900) accounts of

Irish health, in which the Irish are described as having ‘well-formed and vigorous bodies.’ Post-revisionists, conversely, argue that revisionists minimize the cultural and historical trauma of catastrophic events associated with British colonialism. The purpose of this dissertation is to test the veracity of contemporary accounts of superb Irish health, and in so doing, evaluate the foundational assumptions of. Health was assessed using two skeletal indicators, namely, age-at-death and linear enamel hypoplasia, a developmental defect of tooth enamel associated with systemic physiological stressors, such as malnutrition or febrile disease.

Results show that there was no clear difference in survivorship between the late medieval and post-medieval period in the English Pale, the part of Ireland under intense colonial rule. However, people in the post-medieval period did have more LEH consistent with more childhood stressors than people in the late medieval period. Additionally, there was greater sub-group variation in the expression of skeletal health indicators during the post-medieval period, suggesting greater health disparities during this time period.

Intersecting marginalized identities (i.e., age, class and gender) appear to have been key ii contributors to that variation. Women of childbearing age exhibited decreased survivorship in the post-medieval period, as did individuals from the poorest of the communities studied. These results show that the revisionist/post-revisionist debate needs to be contextualized within an intersectional framework.

These results also show that the role of British colonization was not to have one uniform effect on health throughout the English Pale. Rather, British colonization produced extreme inequality by catalyzing industrialization and concentrating wealth into the hands of a few elite. This inequality granted people differing access to resources and exposed them to different types and degrees of stressors, depending on their gender and social class. Marginalized identities became embodied through decreased survivorship and increased number and width of linear enamel hypoplasia. This embodiment could have reinforced overarching ideologies of capitalism and racism by demonstrating to the primarily Anglo-Protestant upper class the perceived physical inferiority of the lower class. Future studies should continue to explore the role of embodiment of intersecting marginalized identities in the construction of beliefs about the deserving and underserving poor within the context of laissez faire capitalism.

Second, scholars should continue to explore the revisionist/post-revisionist debate while applying intersectionality theory. In this case, applying intersectionality theory made it evident that the effect of British colonization was to increase inequality rather than uniformly affecting Irish health. Finally, researchers should also continue to explore the potential epigenetic effects of poverty that could have contributed to mass mortality during the Irish Famine.

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Acknowledgments

I would like to thank Dr. Guatelli-Steinberg and Dr. Mark Hubbe for their guidance, patience, and expertise, as well as the members of my committee, Dr. Julie Field and Dr.

Doug Crews. I am grateful to the staff at the National Museum of Ireland, in particular

Eimear Ashe and Dr. Nessa O’Connor for allowing me to access the skeletal remains, and to Dr. Rachel Scott for her ideas. I would also like to thank my mother, Catherine Clark, for encouraging me to pursue my goals and putting my education ahead of her needs. I am indebted to Chief Charles LoBello and Bluecoats, Inc. for providing my family with financial assistance for the last twenty years. I am especially grateful to Chief LoBello for paying to help my mother with transportation so that I could focus on school. Without his help, and the help of Bluecoats, Inc., I would not have been able to finish graduate school. Finally, I owe my career to my father, Detective Robert Clark, whose line-of-duty death gave my brother, sister, and me the chance to go to college and graduate school through state compensation. This is not a reality we take lightly. He valued humbleness and modesty, but I think he would be proud of what we have overcome and the people we grew up to be.

Vita

May 2009 ...... Olmsted Falls High School

2013 ...... B.A. Anthropology, B.A. International

Studies, The Ohio State University

2015 ...... M.Sc. Osteology and Paleopathology,

University of Bradford

2015 to present ...... Graduate Teaching Associate, Department

of Anthropology, The Ohio State University

Publications

Clark, M.A., Simon, A., Hubbe, M. (2020) Aging methods and population structures:

Does transition analysis call for a re-examination of bioarchaeological data? International

Journal of Osteoarchaeology 30(2):206.

Clark, M.A., Bargielski, R., Reich, D. (2019) Adult paleopathology as an indicator of childhood social roles: A case study of Perthes disease in a Native Ohio female.

International Journal of Osteoarchaeology 2019:1-9.

Clark, M.A., Guatelli-Steinberg, D. (2018) A third molar from Rathfarnham, Dublin and the patterning cascade model. International Journal of Osteoarchaeology

Clark, M.A., Guatelli-Steinberg, D, Hubbe, M., Stout, S. (2016) Quantification of maxillary dental arcade curvature and the estimation of biological ancestry in forensic anthropology. Journal of Forensic Sciences 61(1):141-146

Fields of Study

Major Field: Anthropology

Table of Contents

Abstract ...... ii

Acknowledgments ...... iv

Vita ...... v

Chapter 1: Introduction ...... 1

Chapter 2: Theoretical Background ...... 10

Historical Overview ...... 10

Biocultural Political Economy ...... 14

Developmental Origins of Health and Disease (DOHaD) Hypothesis ...... 18

Chapter 3: Historical Background ...... 33

Early Medieval Ireland ...... 36

Late Medieval Ireland ...... 41

Post-Medieval Ireland ...... 49

Biocultural Political Economy of Irish History ...... 67

Emergence of Irish Nationalism, Revisionism, and Post-Revisionism ...... 69

Chapter 4: Methodological Background ...... 75

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Health in Bioarchaeology ...... 75

Teeth as Indicators of Past Health ...... 85

Chapter 5: Materials ...... 94

Ardreigh ...... 95

Coombe/Cork St...... 97

Dominican Priory ...... 104

Upper Magdalene ...... 108

Essex St. West ...... 113

Graney East ...... 113

Hanbury Lane ...... 114

Holy Trinity ...... 114

Johnstown ...... 117

Mercer Hospital ...... 119

North King St...... 125

Smithfield ...... 130

St. Mary’s Crypts ...... 131

St. Mary d’Urso ...... 132

Trim Castle ...... 136

Chapter 6: Methods ...... 138

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Comparison of Survivorship Across Contemporaneous Sites ...... 146

Comparison of Survivorship Between Sexes by Time Period ...... 147

Comparison of survivorship between post-medieval boys and girls ...... 148

Comparison of Survivorship Between Time Periods by Sex ...... 149

Hypothesis 1a ...... 150

Hypothesis 2 ...... 151

Comparison of Variance in Number of LEH Between Time Periods ...... 154

Comparison of the Number of LEH Among Age Cohorts by Time Period ...... 155

Comparison of Variance in LEH Number Among Age Cohorts by Time Periods .. 156

Comparison of LEH Number Between Sexes by Time Period ...... 157

Comparison of LEH Number Between Time Periods by Sex ...... 158

Comparison of LEH Number Between Contemporaneous Sites ...... 159

Comparison of Variance in LEH Number Between Contemporaneous Sites ...... 160

Comparison of LEH Widths Between Time Periods ...... 160

Comparison of LEH Width Between Contemporaneous Sites ...... 163

Comparison of Variance of LEH Width Between Contemporaneous Sites ...... 164

Comparison of LEH Width Between Time Periods by Sex ...... 165

Comparison of LEH Width Between Time Periods by Sex ...... 166

Association Between LEH Number and Age-at-Death ...... 166

Association Between LEH Width and Age-at-Death ...... 167

Chapter 7: Age Results ...... 169

Comparison of Survivorship Across Contemporaneous Sites ...... 174

Comparison of Survivorship Between Sexes by Time Period ...... 188

Comparison of Survivorship Between Post-Medieval Boys and Girls ...... 193

Comparison of Survivorship Between Time Periods by Sex ...... 196

Hypothesis 1a Results ...... 198

Chapter 8: LEH Results ...... 201

Comparison of LEH Number in the Late Medieval Period Between Age Cohorts . 210

Comparison of Variance in LEH Number Between Age Cohorts in the Late

Medieval Period ...... 212

Comparison of LEH Number Between Age Cohorts in the Post-Medieval Period . 212

Comparison of Variance in LEH Number Between Age Cohorts in the Post-

Medieval Period ...... 214

Comparison of LEH Number Between Sexes by Time Period ...... 215

Comparison of LEH Number Between Time Periods by Sex ...... 221

Comparison of LEH Number Across Contemporaneous Sites ...... 223

Comparison of Variance in Number Across Contemporaneous Sites ...... 227

Comparison of LEH Width Between Time Periods ...... 227

Comparison of LEH Width Across Contemporaneous Sites ...... 231

Comparison of Variance in LEH Width Across Contemporaneous Sites ...... 242

Comparison of LEH Width Between Sexes ...... 242

Did the width of LEH differ between males and females in the post-medieval period?

...... 246

Comparison of LEH Width Between Time Periods by Sex ...... 248

Association Between LEH Number and Age-at-Death ...... 249

Association Between LEH Width and Age-at-Death ...... 249

Chapter 9: Discussion ...... 255

Social and Historical Factors ...... 256

Stressful Childhoods ...... 256

Inter-site variation resulting from violence or disease ...... 258

Intra-site variation resulting from differences in sex ...... 262

Changes in childrearing practices ...... 268

Selective enforcement of the Penal Laws and religious diversity ...... 269

Unequal effects of colonization and industrialization across social strata ...... 272

Hypothesis 1a: There will be no difference between the age-at-death distributions

calculated using transition analysis and the skeletal remains in this dissertation, and

those calculated using contemporary burial records from approximately the same

location...... 280 xi

Methodological Factors ...... 281

In addition to social and historical factors, a variety of methodological limitations

could have contributed to the results in this dissertation. These are discussed below. 281

Error in Sex Assessment ...... 282

Reliance on point values for age-at-death ...... 282

Differences in location ...... 283

Overlap in time period ...... 283

Chapter 10: Conclusion ...... 285

Works Cited ...... 292

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List of Tables

Table 1: Some of the foods prepared in upper class homes in the post-medieval period . 60

Table 2: Table of sites and sample numbers from each ...... 95

Table 3: Pre- and post- publication burial numbers and original data for Dominican

Priory ...... 105

Table 4: Skeletal data in Murphy (1997) ...... 109

Table 5: Data collected from Buckley in Murphy (1997) ...... 111

Table 6: Radiocarbon Dates for Johnstown Burials ...... 117

Table 7: Summary of Results from Buckley and Hayden (2002) ...... 121

Table 8: Time period assignments for Mercer’s Hospital made using a random number generator ...... 125

Table 9: Known hanging victims at Smithfield. 1D’Alton (1838), 2Exshaw (1742) ...... 131

Table 10: Summary of skeletal data for St. Mary d’Urso by Loreen Buckley ...... 135

Table 11: Age cohorts for LEH analysis ...... 154

Table 12: Sex data by time period ...... 170

Table 13: Sex assessment data by site ...... 170

Table 14: Maximum likelihood age estimates from transition analysis for both time periods ...... 170

Table 15: Shapiro-Wilk normality test for maximum likelihood age-at-death ...... 171 xiii

Table 16: Log-rank test for late medieval and post-medieval survival curves ...... 172

Table 17: Descriptive statistics for maximum likelihood age-at-death for all sites ...... 174

Table 18: Shapiro-Wilk test for normality for late medieval sites ...... 179

Table 19: Shapiro-Wilk normality test for post-medieval sites ...... 180

Table 20: Modal survival times for all sites ...... 181

Table 21: Log-rank test comparing survivorship among late medieval sites ...... 182

Table 22: Pairwise comparisons for Ardreigh ...... 183

Table 23: Pairwise comparisons for Dominican Priory/Upper Magdalene ...... 184

Table 24: Pairwise comparisons for Essex St. West ...... 184

Table 25: Pairwise comparisons for Graney East ...... 185

Table 26: Pairwise comparisons for Hanbury Lane ...... 185

Table 27: Pairwise comparisons for Holy Trinity ...... 185

Table 28: Pairwise comparisons for Johnstown ...... 186

Table 29: Pairwise comparison for Mercer Hospital ...... 186

Table 30: Log-rank test comparing survivorship in post-medieval sites ...... 187

Table 31: Pairwise comparisons for Coombe/Cork St...... 188

Table 32: Pairwise comparisons for Mercer's Hospital ...... 188

Table 33: Pairwise comparison for North King St...... 188

Table 34: Descriptive statistics for late medieval males and females ...... 189

Table 35: Shapiro-Wilk normality test for late medieval males and females ...... 189

Table 36: Log-rank test for late medieval males and females ...... 190

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Table 37: Descriptive statistics for maximum likelihood age estimates for post-medieval males and females ...... 191

Table 38: Shapiro-Wilk normality test for post-medieval males and females ...... 191

Table 39: Log-rank test comparing survivorship between post-medieval males and females ...... 193

Table 40: Descriptive statistics for age-at-death of children in Dublin from 1700-1799 194

Table 41: Log-rank test for survivorship of children in Dublin 1700-1799 ...... 196

Table 42: Log-rank test comparing survivorship of late medieval and post-medieval males ...... 197

Table 43: Log-rank test comparing survivorship between late medieval and post-medieval females ...... 198

Table 44: Descriptive statistics for adult age-at-death data collected from burial records

...... 199

Table 45: Log-rank test comparing survivorship between transition analysis and burial records ...... 200

Table 46: Number of matching LEH, sex, and age cohorts for late medieval period ..... 201

Table 47: Number of matching LEH, sex, and age cohort for post-medieval period ..... 204

Table 48: Shapiro-Wilk normality test for number of LEH in the late medieval and post- medieval periods ...... 207

Table 49: Descriptive statistics for LEH by time period ...... 208

Table 50: Mann-Whitney U test comparing number of LEH between time periods by age cohort ...... 209

Table 51: Late medieval LEH frequency by age cohort ...... 210

Table 52: Shapiro-Wilk normality test for late medieval LEH by age cohort ...... 211

Table 53: ANOVA comparing LEH among late medieval age cohorts ...... 212

Table 54: Results of Levene's test of equality of variance for late medieval age cohorts

...... 212

Table 55: Descriptive statistics for LEH in post-medieval period by age cohort ...... 213

Table 56: Shapiro-Wilk test for normality for LEH in the post-medieval period by age cohort ...... 214

Table 57: ANOVA comparing LEH among post-medieval age cohorts ...... 214

Table 58: Levene's test of equality of variance for LEH across age cohorts in post- medieval period ...... 215

Table 59: Late medieval LEH frequency by sex ...... 215

Table 60: Shapiro-Wilk normality test for late medieval LEH by sex ...... 218

Table 61: Mann-Whitney U test comparing number of LEH between late medieval males and females ...... 218

Table 62: Descriptive statistics for LEH for post-medieval males and females ...... 218

Table 63: Shapiro-Wilk normality test for post-medieval males and females ...... 221

Table 64: Mann-Whitney U test comparing number of LEH between post-medieval males and females ...... 221

Table 65: Mann-Whitney U test comparing LEH number between late medieval and post- medieval males by age cohort ...... 222

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Table 66: Mann-Whitney U test comparing LEH number in late medieval and post- medieval females by age cohort ...... 222

Table 67: Descriptive statistics for LEH number for late medieval sites ...... 223

Table 68: Descriptive statistics for LEH number for post-medieval sites ...... 224

Table 69: ANOVA comparing LEH number among late medieval and post-medieval sites

...... 225

Table 70: ANOVA comparing LEH number among late medieval sites by cohort ...... 226

Table 71: ANOVA comparing LEH number among post-medieval sites by cohort ...... 226

Table 72: Levene's test of equality of variance for late medieval and post-medieval sites

...... 227

Table 73: Descriptive statistics for LEH width by tooth type and time period ...... 228

Table 74: Shapiro-Wilk normality test for LEH width by tooth type and time period ... 228

Table 75: Mann-Whitney U test comparing LEH width between time periods by tooth type ...... 231

Table 76: Descriptive statistics for LEH width by tooth type and site ...... 231

Table 77: Shapiro-Wilk normality test for LEH width by site and tooth type ...... 233

Table 78: ANOVA comparing LEH width across sites by tooth type ...... 240

Table 79: ANOVA comparing LEH width across sites ...... 240

Table 80: Pairwise comparisons of LEH width for Coombe/Cork St...... 241

Table 81: Pairwise comparison of LEH width for Mercer's Hospital ...... 241

Table 82: Pairwise comparisons of LEH width for Smithfield ...... 241

xvii

Table 83: Levene's test of equality of variance for LEH width in late medieval and post- medieval sites ...... 242

Table 84: Descriptive statistics for LEH width for late medieval males and females ..... 243

Table 85: Shapiro-Wilk normality test of LEH width for late medieval males and females by tooth type ...... 245

Table 86: Mann-Whitney U test comparing LEH width of late medieval males and females ...... 246

Table 87: Descriptive statistics of LEH width for males and females in the post-medieval period ...... 246

Table 88: Shapiro-Wilk normality test for LEH width in post-medieval period by tooth type and sex ...... 247

Table 89: Mann-Whitney U test comparing LEH width for post-medieval males and females ...... 248

Table 90: Mann-Whitney U test comparing LEH width for males between time periods

...... 248

Table 91: Mann-Whitney U test comparing LEH width for females between time periods

...... 249

Table 92: Pearson product moment correlation for LEH width and age-at-death ...... 252

Table 93: Summary of results ...... 253

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List of Figures

Figure 1: Representation of the negative feedback loop between GC and CHR/ACTH .. 21

Figure 2: The role of stress in epigenetic modification ...... 29

Figure 3: Conditions required for the formation of an LEH ...... 89

Figure 4: Map of the Ireland showing the locations of counties Dublin, Kildare, Louth, and Meath, which constituted the English Pale. Image from Wikimedia Commons under the Creative Commons Attribution Share Alike 3.0 Unported license. Modifications: added the names of the counties and highlighted the Dublin, Kildare, Louth, and Meath in gray...... 94

Figure 5: St. Luke’s Church and surrounding graveyard c. 1818. Watercolor painting from National Gallery of Ireland...... 99

Figure 6: St. Luke's Church in John Rocque's map of 1758. The Parish of St. Luke’s was located south of Coombe St. and between two branches of the Poddle River, marked by

Crooked Staff Place to the west, and Blackpitts to the east. Newmarket borders the parish to the south. Image modified from Shaffrey Associates Architects and colleagues (2003).

North is up...... 100

Figure 7: Map of St. Luke’s Parish from Brooking’s 1728 Map of Dublin. Image from

Frazer, n.d. North is down...... 101

xix

Figure 8: Distribution of social classes between parishes. Image from Sheridan-Quantz

(2001)...... 103

Figure 9: Map of excavation 94E007 from Murphy (1997) ...... 109

Figure 10: The restored Holy Trinity Church in Carlingford. Image from the National

Inventory of Architectural Heritage...... 115

Figure 11: Location of Holy Trinity Church in Carlingford (circled). Image by Ordnance

Survey Ireland. North is up...... 116

Figure 12: Engraving of St. Michan’s Church in 1834. From the Dublin Penny Journal,

Vol. 2, accessed from dublincity.ie ...... 127

Figure 13: Site location of St. Mary d'Urso. Image from Halpin (1996) Figure 2...... 133

Figure 14: Summary of hypotheses and questions ...... 139

Figure 15: Methods used to test hypothesis 1 ...... 140

Figure 16: Methods used to assess survivorship within time periods ...... 146

Figure 17: Methods used to test for differences in survivorship between sexes ...... 147

Figure 18: Methods used to assess differences in survivorship between girls and boys . 148

Figure 19: Methods used to test for differences in survivorship within sexes ...... 149

Figure 20: Methods used to test for differences in ages using transition analysis and contemporary burial records ...... 150

Figure 21: Summary of methods used to test hypothesis 2 ...... 151

Figure 22: Example of a Leica image of a tooth cast (North King Street, B160, LLC) .. 153

Figure 23: Methods used to test for variance in number of LEH ...... 154

Figure 24: Methods used to test for differences in LEH number between age cohorts .. 155

Figure 25: Methods used to test for differences in variance between age cohorts ...... 156

Figure 26: Methods used to test for differences in number of LEH between sexes ...... 157

Figure 27: Methods used to test for differences in number of LEH within sexes ...... 158

Figure 28: Methods to assess differences in number of matching LEH across sites ...... 159

Figure 29: Methods used to test for differences in variance in the number LEH between time periods ...... 160

Figure 30: Methods used to test for differences in LEH width between time periods .... 160

Figure 31: Methods used to test for difference in LEH width across sites ...... 163

Figure 32: Methods used to test for differences in variance of LEH width across sites . 164

Figure 33: Methods used to test for differences in LEH width between sexes ...... 165

Figure 34: Methods used to test for differences in LEH width within sexes ...... 166

Figure 35: Methods used to test for association between number of LEH and age-at-death

...... 166

Figure 36: Methods used to test for an association between LEH width and age-at-death

...... 167

Figure 37: Age-at-death histograms for late medieval and post-medieval periods ...... 171

Figure 38: Kaplan-Meier survival curves for late medieval and post-medieval periods . 172

Figure 39: Gompertz fit survival model compared to medieval and post-medieval samples

...... 173

Figure 40: Age-at-death box plots for all sites ...... 175

Figure 41: Histogram for Ardreigh age-at-death ...... 176

Figure 42: Histogram for age-at-death at Dominican Priory/Upper Magdalene ...... 176

xxi

Figure 43: Histogram for age-at-death at Hanbury Lane ...... 177

Figure 44: Histogram for age-at-death at Johnstown ...... 177

Figure 45: Histogram for age-at-death at Mercer Hospital ...... 178

Figure 46: Histogram for age-at-death at Smithfield ...... 178

Figure 47: Histogram for age-at-death at Coombe/Cork St...... 179

Figure 48: Histogram of age-at-death at North King St...... 180

Figure 49: Kaplan-Meier survival curves for all sites ...... 181

Figure 50: Kaplan-Meier survival curves for late medieval sites ...... 182

Figure 51: Kaplan-Meier survival curves for post-medieval sites ...... 187

Figure 52: Histograms for age-at-death of late medieval males and females ...... 189

Figure 53: Kaplan-Meier survival curves for late medieval males and females ...... 190

Figure 54: Histogram for age-at-death for post-medieval males and females ...... 192

Figure 55: Kaplan-Meier survival curves for post-medieval males and females ...... 193

Figure 56: Histogram for age-of-death of boys buried in Dublin between 1700-1799 ... 194

Figure 57: Histogram of age-at-death for girls buried in Dublin between 1700-1799 .... 195

Figure 58: Kaplan-Meier survival curves for children buried in Dublin 1700-1799 ...... 196

Figure 59: Kaplan-Meier survival curves for late medieval and post-medieval males ... 197

Figure 60: Kaplan-Meier survival curves for late medieval and post-medieval females 198

Figure 61: Kaplan-Meier survival curves for transition analysis and burial records ...... 199

Figure 62: Histogram of LEH for late medieval individuals ...... 204

Figure 63: Histogram of LEH in post-medieval period ...... 207

Figure 64: Box-plot of LEH in late medieval period by age cohort ...... 211

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Figure 65: Box-plot of LEH in post-medieval period by age cohort ...... 213

Figure 66: Box-plot of late medieval LEH by sex ...... 216

Figure 67: Histogram of LEH for late medieval males ...... 217

Figure 68: Histogram of LEH for late medieval females ...... 217

Figure 69: Box-plot of LEH in post-medieval period by sex ...... 219

Figure 70: Histogram of LEH for post-medieval males ...... 220

Figure 71: Histogram of LEH for post-medieval females ...... 220

Figure 72: Box-plot of number of LEH for late medieval sites ...... 224

Figure 73: Box-plots for number of LEH for post-medieval sites ...... 225

Figure 74: Histogram of LEH width for late medieval incisors ...... 229

Figure 75: Histogram of LEH width for post-medieval incisors ...... 229

Figure 76: Histogram of LEH width for late medieval canines ...... 229

Figure 77: Histogram of LEH width for post-medieval canines ...... 230

Figure 78: Histogram of LEH width for late medieval premolars ...... 230

Figure 79: Histogram of LEH width for post-medieval premolars ...... 230

Figure 80: Histogram of LEH width for canines from Ardreigh ...... 235

Figure 81: Histogram of LEH width for canines from Coombe/Cork St...... 235

Figure 82: Histogram of LEH width for canines from Dominican Priory ...... 235

Figure 83: Histogram of LEH width for Johnstown canines ...... 236

Figure 84: Histogram of LEH width for Mercer Hospital canines ...... 236

Figure 85: Histogram of LEH width for North King St. canines ...... 236

Figure 86: Histogram of LEH width for Smithfield canines ...... 236

xxiii

Figure 87: Histogram of LEH width for St. Mary d'Urso canines ...... 236

Figure 88: Histogram of LEH width for Ardreigh incisors ...... 237

Figure 89: Histogram of LEH width for Coombe/Cork St. incisors ...... 237

Figure 90: Histogram of LEH width for Dominican Priory incisors ...... 237

Figure 91: Histogram of LEH width for Johnstown incisors ...... 237

Figure 92: Histogram of LEH width for Mercer Hospital incisors ...... 238

Figure 93: Histogram of LEH width for North King St. Incisors ...... 238

Figure 94: Histogram of LEH width for Smithfield incisors ...... 238

Figure 95: Histogram of LEH width for Ardreigh premolars ...... 238

Figure 96: Histogram of LEH width for Coombe/Cork St. premolars ...... 239

Figure 97: Histogram of LEH width for Mercer Hospital premolars ...... 239

Figure 98: Histogram of LEH width for North King St. premolars ...... 239

Figure 99: Histogram of LEH width for Smithfield premolars ...... 239

Figure 100: Box-plots of LEH width for male and female canines from both time periods

...... 243

Figure 101: Box-plots of LEH width for male and female incisors from both time periods

...... 244

Figure 102: Box-plot of LEH widths for premolars from both time periods ...... 244

Figure 103: Scatterplot of LEH width and age-at-death ...... 250

Figure 104: Scatterplot of late medieval LEH width for LEH width <0.5mm and age-at- death ...... 251

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Figure 105: Scatterplot of post-medieval LEH width for LEH <0.5mm and age-at-death

...... 251

Figure 106: Summary of how political economy and intersectionality contribute to the effects of colonization ...... 290

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Chapter 1: Introduction

The Great Famine (1845-1852) marks one of the most significant events in modern Irish history (Geber, 2015:2) As such, it is central to the formation of Irish cultural memory (Frawley,

2014). It also represents one of the most devastating famines in the modern world (Curran and

Fröling, 2010). Prior to the Famine, Ireland was experiencing a growth in population greater than any other country in Europe. Between the years 1845 and 1852, however, Ireland lost at least one million people through death and another one million to emigration, amounting to about one- quarter of its population (Boyle and O’Grada, 1986). Stories of the Famine abounded in contemporary texts, where the severity of the humanitarian disaster is evident. In her observations on the Famine, Asenath Nicholson (1998:117-118) wrote,

“A cabin was seen closed one day a little out of town when a man had the

curiosity to open it, and in a dark corner found a family of the father, mother,

and two children, lying in close compact. The father was considerably

decomposed; the mother, it appeared, had died last and probably fastened the

door, which was always the custom when all hope was extinguished, to get into

the darkest corner and die where passers-by could not see them.”

The effects of the Famine on Ireland’s population (i.e., population decline and stagnation) were not reversed until 2018 (Kenny and Burke-Kennedy, 2018), and the cultural memory of the

Famine persists (Frawley, 2014), but the reasons behind it have not been fully elucidated. The

1 catastrophic scale of the disaster is recognized as multi-factorial. Complete dependence on the potato by the lower classes made the population vulnerable to the potato blight, which first appeared in Ireland in 1845. Despite years of repeated potato failures, the Irish were required to sell and export what crops remained. Barley, for example, was used to pay rent rather than compensate for the lost potato harvest (Woodham-Smith, 1964). Finally, laissez faire economics and Victorian attitudes toward the poor that equated poverty with immorality prevented sufficient intervention by the British government (Woodham-Smith, 1964). It was widely believed that people had free will and could be financially successful should they so choose, and those who remained poor were only limited by their own poor work ethic. This overarching laissez faire capitalist ideology therefore contributed to the lack of intervention by the British government (Woodham-Smith, 1964).

One possible cause of the large-scale mortality that has not yet been investigated is the health of the Irish prior to the Famine. While it is often assumed that such events kill indiscriminately, recent studies in bioarchaeology have shown that catastrophic events such as famine and disease are selective (DeWitte, 2010, 2014a, Yaussy et al., 2016), killing individuals who are most frail (Yaussy et al., 2016). Moreover, recent studies have found that the effects of poor health are intergenerational. In other words, stress events that contribute to poor health in a parent can produce epigenetic modifications in the offspring that result in increased frailty in the subsequent generation (Gowland, 2015). Thus, it would be expected that widespread poor health in the periods preceding the Famine contributed to the large-scale mortality of the disaster.

Irish health in the years leading up to the Famine has long been a subject of debate. While a number of authors comment on the astonishing well-being of the Irish, Irish nationalists in the

19th and 20th century argued that the Irish were in a state of poverty and nearly constant

2 starvation in an attempt to gain support for the formation of an Irish Free State and ultimately, separation from Britain. (O’Mahony and Delanty, 2001). In other words, some historians have argued that the narrative of Irish victimization was used as a tool to support a political movement. It therefore remains unclear if the Irish were otherwise healthy in the period leading up to the Famine, or if British colonization negatively impacted population health and made the

Irish more vulnerable to disease and starvation.

Between the late medieval and post medieval, early modern periods, Ireland experienced several social and economic transitions that might have contributed to changes in population health. These transitions occurred first, because of increasing pressure to export goods and resources to England and continental Europe (Engler et al., 2013). Second, social and economic transitions were driven by intensified colonization efforts following the Irish uprisings in the 17th century (Moody and Martin, 1995). The British government reacted to these uprisings by instituting laws that served to divide Irish society into two main social classes, specifically, an upper class that was predominantly Protestant and a lower class of cottiers (i.e., a rural, impoverished class) that was predominantly Catholic (Moody and Martin, 1995:203, O’Connell,

2007). At the same time, a rising population both in Ireland and abroad demanded greater and faster production. To meet these demands, more land was brought under cultivation, rents were raised by absentee landlords, and a wider variety and greater quantity of crops were exported

(e.g., Dobbs, 1727, Ireland House of Lords, 1757, Great Britain Customs Establishment, 1785a)

(Clarkson and Crawford, 2001:59, O’Connell, 2007), and fewer were imported (Ireland House of

Commons, 1774, Great Britain Customs Establishment, 1785b, 1785c, Great Britain Board of

Trade, 1785). This resulted in an increased relative income and dietary diversity for the upper

3 class, and a decreased relative income and dietary diversity for the cottier class, which came to rely almost solely on potatoes (Mac Con Iomaire, 2009).

The potato was first introduced to Europe from South America by the Spanish in the sixteenth century (Brown, 1993, Hawkes and Francisco-Ortega, 1993) but it was nearly 150 years before it made its way into the diet of Europeans (Brown, 1993). Initially apprehensive of the potato as a food source, many Europeans believed that the potato was a narcotic or a poison because of its apparent similarity to nightshade (Brown, 1993, De Jong, 2016). Some distrusted the potato because of its absence in the Bible (Salaman, 1985, De Jong, 2016) Others believed it caused leprosy because of the potato’s rough and splotchy skin (Brown, 1993, De Jong 2016).

Finally, some people believed that the potatoes would induce sexual arousal (Brown, 1993, De

Jong, 2016), bringing shame to anyone who ate them (Brown, 1993).

As potato cultivation in Europe improved, it gradually began to be viewed as a source of food in times of scarcity, especially as population growth in Europe began to skyrocket (De

Jong, 2016). Part of its utility during famines was due to the fact that unlike other crops (e.g., wheat) that were easily lost to fluctuations in weather, the potato was relatively resilient (Brown,

1993, De Jong, 2016). In fact, its resilience was described by Spanish conquistadors as far back as AD 1570, who noted that the Inca successfully harvested potatoes in regions without irrigation systems (Brown, 1993). Additionally, because the potato crop grows underground, it could not be easily burned or destroyed by enemy armies during times of war (Brown, 1993, Salaman,

1985, De Jong, 2016). Such resilience seemed to make the potato the ideal crop for many Irish families, who occupied small plots of land frequently located in marginal locations with poor soil quality (Brown, 1993). As the Irish occupied increasingly smaller and more marginal plots of land, the potato became the sole source of food for many families (Mac Con Iomaire, 2009).

Despite a reliance on a single crop, contemporary (e.g., Twiss, 1776, Young, 1778,

Wakefield, 1812, Mason, 1816, Phillips, 1822, Murray, 1827, Sinclair, 1828) and modern (e.g.,

Clarkson and Crawford, 2001 O’Tuathaigh, 2007) writers have often commented on the seemingly remarkable health of the Irish. For example, Phillips (1822:95) writes, “The lower classes of Irish subsist almost entirely on [the potato], and I do not know a stronger or more healthy people in the world.” Moreover, the rise in population in pre-Famine Ireland has often been attributed to the value of the potato and milk diet (O’Neill, 1984:188). During the 19th century, Ireland was experiencing a population growth of 1.6-1.7% per year, a rate faster than any other country in Europe (McGregor, 1992). One writer commented on the apparently extraordinary fertility of Irish women, citing incidences of multiple births and continued reproduction through age forty (Moryson in Clarkson and Crawford, 2001). Similarly, contemporary writer John Dunton comments about the number of children in rural households,

“Poor people are as athletic in their form, as robust, and as capable of

enduring labour as any upon earth…when I see the people of a country…with

well formed vigorous bodies and their cottages swarming with children; when

I see their men athletic, and their women beautiful, I know not how to believe

them subsisting on an unwholesome food” (Dunton in Clarkson and Crawford,

2001).

However, the reportedly robust health of the Irish should be questioned first, because reliance on a single crop increases susceptibility to famine and may have resulted in more frequent periods of starvation or semi-starvation compared to the medieval period, during which the Irish enjoyed a greater diversity of food. Second, the reportedly robust health of the Irish should be questioned because intensified colonization efforts likely exposed a large portion of

5 the population to a greater number of stressors through differential living conditions that resulted from decreased relative wealth and institutionalized discrimination. The Penal Laws, for example, included a number of discriminatory statutes that aimed to eradicate Catholicism from

Ireland and ensure support for the British monarchy by placing social, economic, and political restrictions on the Irish Catholics, thereby increasing the wealth gap between the upper and lower classes (Moody and Martin, 1995:218). Additionally, discrimination itself has been shown to lead to adverse health outcomes in modern populations. For example, studies have shown that individuals who face discrimination experience increased blood pressure (Steffen et al., 2003,

Brondolo et al., 2008), increased occurrence of coronary artery calcification (Lewis et al., 2006), cardiovascular disease (Cooper et al., 2001), higher body mass indices (Gee et al., 2008), an increased rate of breast cancer (Taylor et al., 2007), and an increased occurrence of depression

(Williams et al., 2008), and stroke (Williams, 1999, Geronimus, 2001). Discrimination has also been shown to increase the occurrence of low birth weight (Collins et al., 2003, Mustello et al.,

2004, Grady, 2006, Lauderdale, 2006, Srinivas et al., 2011) and preterm birth (Dole et al., 2004,

Srinivas et al., 2011). While these conditions are not visible in skeletal remains, they are indicative of physiological stress that can occur as a result of social inequality and psychosocial stress. Because intensified colonization efforts led to decreased relative wealth and increased psychosocial stress for much of the Irish population, the written reports of the robust health of the Irish in the post medieval period should be questioned.

The primary objective of this dissertation is therefore to test the veracity of modern narratives and historical accounts of health in post medieval Ireland and potentially add another dimension to the understanding of Irish history in the period leading up to the Great Famine.

These accounts will be tested first, by comparing the bioarchaeological analysis of enamel

6 defects and age-at-death during the late medieval and post medieval periods within the English

Pale (i.e., the region of Ireland under direct British control during the post medieval period and comprised of counties Dublin, Kildare, Louth, and Meath). Second, skeletal indicators of health will be compared to contemporary descriptions of Ireland and Irish health held in Dublin at the

National Archives and the National Library of Ireland. These results will then be interpreted according to both revisionist and post-revisionist historical frameworks to demonstrate how contemporary political arenas shape the interpretation of bioarchaeological data.

If it is found that population health improved between the late medieval and post medieval periods, this study will corroborate historical records, and potentially lend credence to the revisionist historical perspective. However, if it is found that the population health declined during the late medieval and post medieval periods, it can be inferred that historical records and modern revisionist narratives should be reconsidered as value-oriented, and not, as revisionists claim, purely empirical and value-free. Finally, if it is found that health declined between the late medieval and post medieval periods, it will suggest that widespread intergenerational population frailty could have contributed to the catastrophic mortality scale of the Great Famine.

Bioarchaeological studies of health have suffered from a lack of theory connecting local health to the broader regional and international sociopolitical circumstances and ideology

(Goodman and Leatherman, 1998, Hicks and Leonard, 2014). Thus, while numerous studies have successfully linked skeletal data to proximate determinants of health, such as nutrition and exposure to diseases, fewer have been able to connect these data to ultimate determinants of health (e.g., social, political, and economic systems, ideology) (Goodman and Leatherman,

1998). Biocultural political economy is one framework through which skeletal lesions can be linked to both proximate and ultimate determinants of health, thereby allowing bioarchaeologists

7 to answer questions about past cultures. By testing the veracity of written accounts of post medieval Ireland against skeletal data, this dissertation will reveal relationships between contemporary ideology, international sociopolitical circumstances, structural inequality, and knowledge production in the post medieval period.

In addition to theoretical limitations, studies of health in the past have also suffered from a number of methodological challenges. First, bioarchaeologists have struggled to draw conclusions about population health using skeletal remains that by definition represent the least healthy members of society. Second, bioarchaeologists have struggled to measure health in skeletal remains that do not show signs of pathological conditions unless those conditions affect the skeleton, either in their nature or duration. Third, bioarchaeologists have struggled to interpret skeletal stress markers and articulate how stress relates to health. The first methodological goal of this dissertation is therefore to draw conclusions about health in the past using frameworks from modern human biology, and to test the association between early life stress and longevity.

Bioarchaeologists also face methodological difficulties in adult age estimation, thereby further complicating measurements and interpretations of health. Adult age estimation in skeletal remains is difficult for a number of reasons. First, degenerative change is much more variable than developmental change in terms of its time of onset, progression, and anatomical region affected. Second, age mimicry, a phenomenon in which the age of a sample from which a method is derived is projected onto the target sample, makes it difficult to identity true population age structures. Third, the parts of the skeleton that are most useful for estimating age are also those that are the least likely to be preserved. Transition analysis is a method that was devised to help mitigate some of these problems, but it is unclear if it is more effective than other

8 age estimation methods. The second methodological goal of this dissertation is therefore to compare a population age structure produced using transition analysis to one produced using burial records.

In sum, the goals of this dissertation are as follows:

1. Compare written accounts of health in post-medieval Ireland, which support revisionist

arguments, to skeletal data.

2. Interpret written accounts and skeletal data using a biocultural political economy

framework to identify the dialectical relationship between health and ideology in the

post-medieval period.

• How is ideology biologically embodied in post-medieval Ireland?

• How does biology reinforce ideology?

3. Test the ability of transition analysis to reveal population age-at-death structure.

• Is the population age-at-death structure produced using transition analysis

significantly different from that produced using burial records?

Chapter 2: Theoretical Background

Historical Overview

Bioarchaeology is a subfield of anthropology that uses human remains to study past societies (Stojanowski and Duncan, 2015). Its very definition, therefore, would seem to require that bioarchaeologists adopt a biocultural framework. The human remains are biological, and they can be used to answer questions that are cultural in nature. However, bioarchaeology did not initially develop as a biocultural discipline. In its early stages, the study of human remains followed the same theoretical trajectory as archaeology, which was largely descriptive and typological. It is not until after physical anthropology developed its own biocultural perspective that bioarchaeology became biocultural.

The term “biocultural” was adopted in the 1970s, but the idea was used occasionally a few decades prior. In what is considered a landmark publication in biocultural anthropology,

Frank Livingstone (1958) described the biological and cultural interactions during the intensification of agriculture in West Africa. This publication was significant because it was one of the first to describe the coevolution of culture and human biology and the subsequent development of new adaptations and new stressors (Livingstone, 1958). A few years later,

Packer (1961) wrote that the social and cultural environment of a person needs to be considered in conjunction with the broader physical environment when making interpretations about health.

He points to the importance of the home, proximity to other people within and outside of the household, as well as broader forces such as climate, and their impact on health (Packer, 1961).

In doing so, he describes the impact of the environment on the body’s stress response and how, in the effort to respond to natural stressors, human culture creates new stressors, thereby creating a perpetual struggle between stress and response (Packer, 1961). Goodman and Leatherman

(1998) classify these and similar, contemporary studies as ecological biocultural anthropology.

The goal of these studies was primarily to understand the link between human biology, cultural adaptation, and the physical, natural environment.

In the 1960s, physical anthropologists began to move away from the conceptualization of human biology as immutable and genetically determined. Instead, they began to recognize and explore the plasticity of human biology and development. The concept of developmental plasticity was demonstrated by studies that linked altitude, socioeconomic status, and stature

(Friasancho and Baker, 1970, Stinson, 1982, Greksa et al., 1984, Leonard, 1989).

Unlike physical anthropology, which by the mid-20th century was beginning to employ a biocultural approach, bioarchaeology was still emerging as a discipline. While anthropologists had been studying human remains long before bioarchaeology was conceived as a discipline, it was not named as such until Jane Buikstra first used the term to describe the study of human remains in an archaeological context in 1977 (Larsen, 2018). Prior to this, the main goal of anthropologists studying human remains was typology and racial classification (Larsen, 2018).

These studies were usually conducted independently of the archaeological context. After the introduction of processual archaeology (Binford, 1968, 1981), which shifted the focus of archaeology from typology to culture and developing a science of the archaeological record, it became standard for human remains to be interpreted within their archaeological context

(Stojanowski and Duncan, 2015, Larsen, 2018). Within a processual archaeological framework,

11 these bioarchaeological studies sought to understand culture as a response to environmental circumstances (O’Brien et al., 2005:63).

At the same time Jane Buikstra was defining bioarchaeology as a discipline, George

Armelagos and colleagues were shifting the focus of studies of human remains from description and typology to hypothesis testing within cultural contexts. One of the major achievements of this era in bioarchaeology was the use of Selye’s 1978 stress model to understand bioarchaeological data. According to Selye (1978), the body’s stress response comprises three phases mediated by non-specific hormones. In the first phase, hormones are secreted through the

HPA-axis, as described in the previous section. In the second phase of the stress response, these hormones direct physiological responses in multiple systems to maintain homeostasis. In the third phase of the stress response, according to Selye (1978), the body becomes fatigued. At this point, resistance to subsequent stressors declines if the first two phases of the stress response are activated as a result of prolonged, repeated, or severe stressors.

According to Goodman and colleagues (1988), the Selyean stress model, while useful for explaining responses to isolated stressors, is limited in its usefulness when considering the reality of multiple, interacting stressors. They note that an adaptation to one stressor might be disadvantageous in coping with a different stressor (Goodman et al., 1988). For example, living in a house is a cultural adaptation that allows one to cope with heat of cold stress and keeps people sheltered from inclement weather. However, living in a house can create additional stressors, such as exposure to conflict and infectious diseases through living in close proximity to other people, exposure to lead and toxic substances through inadequate housing regulations and landlord accountability, and exposure to crime, gang violence, and low-quality public education through the segregation of real estate, among many others. To overcome this limitation,

Goodman and colleagues (1988) suggests that bioarchaeologists examine the role of culture in both creating and buffering stressors. In other words, Goodman et al. (1988) advocated the use of biocultural anthropology in bioarchaeology.

Despite this suggestion, the schism between cultural anthropology and physical anthropology grew through the end of the 20th century (Goodman and Leatherman, 1998).

Cultural anthropologists struggled to acknowledge the biological and evolutionary consequences of sociopolitical circumstances, and likewise, physical anthropologists and bioarchaeologists struggled to connect biology and evolution to cultural theory (Goodman and Leatherman, 1998).

Additionally, Goodman and Leatherman (1998) write that the adaptationist framework of ecological bicultural anthropology was viewed by cultural anthropologists as reductionist and risked labeling subjugated peoples as less fit, thereby justifying the further subjugation of oppressed groups. Cultural anthropologists moved away from the use of evolutionary theory and biology in studies of societies. Over time, cultural anthropologists adopted an increasingly humanistic and interpretive approach, and physical anthropologists adopted an increasingly materialist and scientific approach (Goodman and Leatherman, 1998).

One consequence of the late twentieth century schism between cultural and physical anthropology was that while physical anthropologists succeeded in understanding the links between proximate stressors and biological responses, they have been less able to connect variation in biological responses among living people to broader cultural changes (Goodman and

Leatherman, 1998). The disconnect between cultural theory and physical anthropology exacerbated the challenges of bioarchaeologists, who were tasked with linking past cultural and sociopolitical circumstances to skeletal biology and explaining how these circumstances imprint themselves on the dead using human remains and their archaeological context and then using

13 human remains to test hypotheses about culture in the past. Biocultural political economy is one theoretical framework that can be used to link cultural change to human biology and therefore provide anthropologists with a way to interpret skeletal data in a culturally meaningful way

(Goodman and Leatherman, 1998).

Biocultural Political Economy

The overarching goal of biocultural political economy is to examine how global systems and culture history work with local systems and local culture history to affect human behavior and shape underlying biological variation. Goodman and Leatherman (1998) identify several themes within biocultural political economy. Each of these themes contributes to the understanding of interactions between global and local systems, culture history, and human biological variation (Goodman and Leatherman, 1998). First, studies in biocultural political economy examine the effect of social relations on biological variation. Instead of focusing on static indicators of social status, a biocultural political economy approach requires that anthropologists identify dynamic social processes that lead to variation in social relations and socioeconomic status (Goodman and Leatherman, 1998). Because these social processes affect the social relations that influence resource production and distribution, social relations affect biological variation (Goodman and Leatherman, 1998). Understanding sociopolitical context can therefore help identify the ultimate (i.e., political, economic, social, and ideological) causes of variation in human biology rather than just the proximate causes (i.e., exposure to diseases, toxic housing materials, etc.) (Brooke Thomas, 1998).

Second, a biocultural political economy framework highlights the relationship between local and global relations (Goodman and Leatherman, 1998). According to this theory, dynamic

14 regional and international processes interact with local social processes to change the local environment (Goodman and Leatherman, 1998). The change in environment that manifests as a result of these regional and international processes predicates local biological and behavioral adaptations (Goodman and Leatherman, 1998). In other words, macroscale social change induces microscale adaptations. Thus, a knowledge of local and global history is required to understand biological and behavioral adaptations (Goodman and Leatherman, 1998).

Third, a biocultural political economy framework asserts that people have varying degrees of agency to change and shape their local environments through resistance and revolutions that challenge the status quo. Thus, the biocultural political economy perspective adopts a Marxian conflict-driven impetus of social change. Moreover, the degree of agency and individual response to environmental conditions is dependent on identities of race, gender, and social class, among others (Goodman and Leatherman, 1998). Identities dictate the appropriateness of a response to a given circumstance. That is, a response for one person might be deemed inappropriate for another person of another race, gender, or class (Goodman and

Leatherman, 1998). Furthermore, the effectiveness of a response varies; one person’s response to an environmental circumstance might be adaptive for that individual, but the same response might be harmful or inappropriate for another (Goodman and Leatherman, 1998). Additionally, responsive behaviors can have unintended or unanticipated consequences. Thus, while a biocultural political economy framework allows for individual agency, it also allows for the limitations in control of consequences and scope of behaviors (Goodman and Leatherman, 1998).

Fourth, biocultural political economy changes the conceptualization of an adaptation within anthropological theory, by highlighting its role in evolutionary theory as variable and dynamic (Goodman and Leatherman, 1998). Just as biological adaptations are only adaptations

15 for a specific set of environmental circumstances, so too are behavioral adaptations. A cultural adaptation that combats a stressor in one political, social, or economic circumstance may be disadvantageous in another. Thus, behavioral and biological adaptations must be considered in terms of their environmental and sociopolitical contexts (Goodman and Leatherman, 1998).

Finally, a biocultural political economy framework borrows again from Marxism by linking ideology, control of knowledge, and power over people and resources. Ideology has been defined both as the set of beliefs that either change or maintain the social order (Wolf, 1982) and the means by which society is reproduced (Leone et al., 1987:284). Proponents of Marxism argue that ideology masks inequality and exploitation by making it appear natural (Leone et al.,

1987:284). For example, the myth of the American Dream is a representation of American ideology that equates virtue and morality with hard work and self-motivation and ultimately, success for the deserving entrepreneur. Conversely, immorality, laziness, and crime are equated with poverty; poor people are poor because they did not try hard enough. Within this ideological framework, wealth and poverty are natural attributes of individual character. If some people are seen as poor because they are lazy, then people who subscribe to this ideology will not see them as deserving of relief efforts (e.g., welfare). Without intervention or radical systemic change, the poor are confined to low-income neighborhoods with low-income schools, and access to quality education is denied, therefore denying them knowledge of the underlying social structure and capitalist exploitation that benefits from their labor. In this way, ideology reproduces hegemony, which in turn, reproduces ideology (Johnson, 2006:122).

Historic bioarchaeologists (i.e., those who study societies for whom primary textual data are available) are in a unique position to answer questions about ideology, sociopolitical circumstances, and biology in the past, but to do so, they must first move beyond simply

16 comparing skeletal data to written data (Perry, 2007). Until the mid-1990s, bioarchaeological data were only been used when written sources are sparse or unavailable, having been deemed by historians and bioarchaeologists alike to be inferior to textual data. In this way, studies of human remains have been supplemental, not central to studies of life in the past (Perry 2007). While contemporary written sources are an invaluable source of information (e.g., birth and death records, first-person narrative accounts), they, like bioarchaeology, are inherently biased.

Historical data about life in Ireland from primary sources is particularly biased because of the language divide between the upper and lower social classes. The upper classes spoke, read, and wrote almost entirely in English, while the lower classes spoke, read, and wrote in Irish. Printed books and newspapers were available in English, but Irish was absent from printed sources.

Consequently, the experiences recorded in written records are largely those of the English speaking upper classes (McBride, 2009:60). Political movements, religious and national allegiances, and periods of violence have also shaped the writing of Irish history (Perry, 2010), as will be described further in the subsequent chapters. Thus, the use of skeletal data used cannot be used simply as a supplement to textual data. Rather, bioarchaeologists should use these primary sources to formulate their research questions and guide their interpretations (Perry,

2007).

A historiographical approach to reading these accounts is therefore integral to a political economy framework within historical bioarchaeology. Not only can texts be used to develop the social, political, and economic background, but they can also be used to identify biases reflective of contemporary ideology. If the written records contradict the skeletal data, it is important to know how the sources are biased, who is writing the biased sources, and why. These biases can

17 reveal the dominant, and perhaps competing, ideologies of the society at the time the sources were written.

Developmental Origins of Health and Disease (DOHaD) Hypothesis

While biocultural political economy does explain health in terms of ideology and sociopolitical circumstances, it falls short of explaining how ideology and sociopolitical circumstances contribute to heritable changes in phenotype. However, when combined with the

Developmental Origins of Health and Disease hypothesis (DOHaD), a biocultural political economy approach can reveal how ideology and sociopolitical circumstances contribute to human evolution.

According to the DOHaD hypothesis, early stressors promote adverse health outcomes in adulthood (Barker and Osmond, 1986, Barker et al., 1989, Martyn et al., 1995, Barker et al.,

2000). Though earlier studies, particularly those by Selye (1976), did propose a link between stress and health, Barker and colleagues were the first to identify a measurable outcome (i.e., cardiovascular disease) demonstrating the connection between developmental stress and health

(Kuzawa and Sweet, 2009). Subsequent studies in humans and animals have supported this hypothesis.

There are two proposed physiological processes by which early stress is thought to promote adverse health outcomes, namely, allostasis and epigenetic modification. Allostasis is the process by which the body maintains physiological equilibrium (Lefmann and Combs-Orme,

2014). It relies on the nervous, endocrine, and immune systems to detect and respond to stimuli and adapt to short-term challenges (Danese and McEwen, 2012). These responses to stressors are so crucial to survival that they are evolutionarily conserved across taxa (Schulkin, 2011).

However, while these responses are integral to promoting short-term survival in the face of a present threat, they can lead to cumulative physiological damage across multiple systems and loss of resilience (i.e., adaptability, Juster et al., 2010).

When the body is confronted with a perceived stressor (e.g., threats from a predator, heat/cold stress, malnutrition, undernutrition, trauma, interpersonal conflict, etc.), the hypothalamic-pituitary-adrenal (HPA) axis is activated (Edes and Crews, 2017). The HPA axis responds by releasing corticotropin-releasing hormone (CRH) from the paraventricular nuclei in the hypothalamus (Panagiotakopoulos and Neigh, 2014). CRH travels from the hypothalamus to the anterior pituitary gland (Panagiotakopoulos and Neigh, 2014, Edes and Crews, 2016). The anterior pituitary then releases adrenocorticotropin-releasing hormone (ACTH). The release of

ACTH from the anterior pituitary promotes secretion of mineralcorticoids (e.g., aldosterone) and glucocorticoids (e.g., cortisol) from the adrenal cortices of the kidneys (Edes and Crews, 2017).

From the adrenal cortices, these mineralcorticoids and glucocorticoids enter systemic circulation by binding to corticosteroid-binding globulin. Importantly, only glucocorticoids that are not bound to corticosteroid-binding globulin (CBG) can cross the cell membrane. The concentration of CBG therefore contributes to the bioavailability of glucocorticoids. Free glucocorticoids, on the other hand, regulate functions such as blood pressure and basal metabolism (Edes and Crews,

2017) by crossing through cell barriers via MDR-P-glycoprotein and binding to glucocorticoid receptors in the cytosol of somatic cells (Saaltink and Vreugdenhil, 2014).

The HPA axis also activates the sympathetic-adrenal-medullary (SAM) axis. The adrenal medulla releases catecholamines (e.g., epinephrine and norepinephrine) (Edes and Crews, 2017).

The secretion of catecholamines from the adrenal medulla results in an increase in blood pressure, an increase in heart rate, a release of free fatty acids, and a decreased blood flow to

19 systems that are not immediately essential. Moreover, catecholamines act on the amygdala to promote emotional memory, thereby preparing the body to anticipate a response to the same stressor in the future (Edes and Crews, 2017). The secretion of mineralcorticoids and glucocorticoids from the adrenal cortices, and the secretion of catecholamines from the adrenal medulla therefore prepare the body to either flee from a perceived threat or fight, and at the same time, prepare the body to face similar stressors in the future (Edes and Crews, 2017).

In addition to the HPA and SAM axes, the posterior pituitary gland is activated when confronted with a stressor. The posterior pituitary gland regulates blood pressure through the secretion of antidiuretic hormone (ADH) (Edes and Crews, 2017). Like the secretion of mineralcorticoids, glucocorticoids, and catecholamines, the secretion of ADH prepares the body to either stay and fight a perceived threat or flee from it (Edes and Crews, 2017).

Allostasis, while it promotes a response to a stressor, also promotes recovery by returning physiological systems to their baseline activity (Edes and Crews, 2017) in part by maintaining an appropriate concentration of circulating glucocorticoids. When an individual is not actively confronted with a stressor, glucocorticoids and the HPA-axis maintain homeostasis through a negative feedback loop in which production and circulation of glucocorticoids inhibits the secretion of CRH and ACTH (Error! Reference source not found.) (Edes and Crews, 2017).

Figure 1: Representation of the negative feedback loop between GC and CHR/ACTH However, as exposure to stressors is prolonged, the ability of the body to maintain appropriate glucocorticoid circulation and return to its baseline physiological activity diminishes, thereby promoting dysregulation across multiple systems (e.g., metabolic, cardiovascular, inflammatory, etc.) (Edes and Crews, 2017).

Prolonged, repeated, and/or intense stress responses can promote dysregulation across multiple systems through either the direct or indirect action of glucocorticoids. First, stress has been found to be associated with decreased concentrations of CBG (Marques et al., 2010).

Without adequate CBG, the concentration of free glucocorticoid steroids increases, and because

21 they are not bound, they are easily able to cross cellular membranes, where they can then bind to the glucocorticoid receptors within the cytoplasm (Marques et al., 2010). At this point the glucocorticoids can modify cell behavior, metabolism, and mRNA transcription, ultimately promoting senescent biology and leading to systemic dysregulation.

Second, chronic and/or intense stress can impair immune function. For example, glucocorticoids can inhibit the production of tumor necrosis factor alpha (TNF-∝) by macrophages (Joyce et al., 1997, Steer et al., 2000). Because TNF-∝ is the primary catalyst in a cascade of inflammatory cytokines and hormones secreted as part of the immune response, prolonged allostasis can affect multiple aspects of immunity and the inflammatory response through the interaction between glucocorticoids and TNF-∝. Glucocorticoid production is also associated with elevated transforming growth factor "-I (TGF-"-I), which helps to regulate cell proliferation by inducing apoptosis. Elevated TGF-"-I production can impair immune function by inhibiting lymphocyte-activated killer T cells (Gold, 1999, Krukowski et al., 2011). TGF-"-I has also been implicated in cancer development. While it would seem that TGF-"-I would reduce the risk of cancer by inducing apoptosis in tumor cells, the increased production of TGF-

"-I is actually associated with a diminished inhibitory response, thereby enabling the proliferation of cancer cells (Gold, 1999, Krukowski et al., 2011). Additionally, these inflammatory responses extend to the hippocampus, where they are thought to promote psychopathological conditions (Murphy et al., 2017).

In turn, the production of inflammatory cytokines can alter the bioavailability of glucocorticoids by reducing the expression of MDR-Pglycoprotein, which transports cortisol through epithelial tissue barriers such as those found in the liver, colon, lungs, and blood-brain barrier (Marques et al., 2010). Inflammatory cytokines (e.g., IL-1", TNF-∝) have also been

22 shown to upregulate 11 " hydroxysteroid dehydrogenase type I (11 " HSD-1) and downregulate

11 " hydroxysteroid dehydrogenase type II (11 " HSD-2), both enzymes that contribute to the bioavailability of cortisol (Marques et al., 2010). 11 " HSD-1 is an enzyme that catalyzes the chemical reaction that changes the inactive human glucocorticoid cortisone to active cortisol

(Marques et al., 2010). Thus, an increase in inflammatory cytokines can increase the bioavailability of cortisol by elevating 11 " HSD-1 levels (Marques et al., 2010). 11 " HSD-2, on the other hand, catalyzes the oxidation of cortisol to convert it to its inactive form, cortisone, thereby further increasing the bioavailability of circulating cortisol and creating a positive feedback loop between the HPA-axis and immune response (Marques et al., 2010).

Finally, chronic and/or intense stress can contribute to dysregulation of the central nervous system. For example, the density of glucocorticoid receptors in the cytoplasm of hippocampal cells has been found to alter the morphology and position of neuronal and glial cells within the hippocampus, although the precise mechanism by which this happens remains unknown (Saaltink and Vreugdenhil, 2014).

The effect of stress on the HPA-axis is amplified in children, in part because growth of the hippocampus is rapid between conception and ages four to five years. By six months, glucose utilization by hippocampal cells has largely reached its adult level, and the density of synapses within the hippocampus of a six-month-old infant is also similar to that of an adult Seress and

Ábrahám, 2008). Following these developments, the hippocampus undergoes two phases of particularly rapid neurogenesis between eight and sixteen months and 12-15 months (Bauer,

2008). By age five, hippocampal development slows significantly. After this point, the hippocampus is refined through adolescence via myelination and the pruning of unnecessary synapses to allow for more efficient communication between neurons (Eckenhoff and Rakic,

1991, Arnold and Trojanowski, 1996, Bauer, 2008, Ábrahám et al., 2010). As a central component of the body’s stress response, the hippocampus has more glucocorticoid and mineralcorticoid receptors than any other cells in the human body. The rapid neurogenesis and maturation of the hippocampus in early childhood, as well as its density of mineralcorticoid and glucocorticoid receptors means that stress that occurs during early childhood can lead to permanent dysregulation of the HPA-axis (Filipović et al., 2005). Indeed, studies have shown that stress that occurs early in postnatal development is associated with under- or over- responsiveness of the HPA-axis. For example, early life stress induced through maternal separation in mice has been found to be associated with decreased glucocorticoid receptor mRNA and elevated fear and anxiety in adulthood (Arnett et al., 2015). Numerous other animal studies have corroborated the link between early life stress and adult phenotype (e.g., Bailey and

Coe, 1999, Igosheva et al., 2004, Schmidt et al., 2005, Fabricus et al., 2008, George et al., 2010,

Loria et al., 2010a, 2010b, Uchida et al., 2010, Harris and Seckl, 2011, Schmidt et al., 2011,

Heim and Binder, 2012, Kember et al., 2012, Loria et al., 2013a, 2013b, Nishi et al., 2013 Ho et al., 2016). While the results of animal studies cannot be directly used to identify causal relationships between stress and health outcomes in humans, such studies are nonetheless significant because of the strict evolutionary conservation of the HPA-mediated stress response

(Schulkin, 2011).

These animal studies have been supported by human studies. Klengel and Binder (2013), for example, found that child abuse was associated with changes in the hippocampal glucocorticoid receptors, while trauma during adulthood had no effect. Similarly, numerous studies have found that neglect and physical, emotional, and sexual abuse in childhood are all associated with adverse adult health outcomes, including elevated blood pressure, obesity,

24 cancer, chronic lung disease, liver disease, heart disease, increased BMI and waist circumference, among others (Felitti et al., 1998, Heim et al., 2000, Dong et al., 2004, Danese et al., 2007, 2009, Noll et al., 2007, Goodwin and Stein, 2004, Stein et al., 2010, Carroll et al.,

2013, Midei et al., 2013, Thomas et al., 2013, Su et al., 2014, 2015). Other childhood stressors associated with adverse health outcomes in adulthood include separation from parents (Alastalo et al., 2013), divorce (Lamont et al., 2000, Pretty et al., 2013), low socioeconomic status

(Lehman et al. 2009, Evans et al., 2013), death of one or both parents (Lamont et al., 2000, Tykra et al., 2008, Pretty et al., 2013) or other family member (Anda et al., 2009), parental or family member illness (Felitti et al., 1998), parent criminal behavior (Felitti et al., 1998), and domestic violence (Felitti et al., 1998).

While many of the effects of developmental stress (e.g., TNF-∝, TGF-"-I, relative quantity of glucocorticoid receptor mRNA, 11 " HSD-1, 11 " HSD-2, etc.) are not directly observable outside of a laboratory, the manifestations of these cellular changes have been well- documented. (e.g., Huang et al., 2010, Bercovich et al., 2014, Li and Lumey, 2017). For example, in their study of Jewish adults born under Nazi rule, Bercovich and colleagues (2014) found that adults who were born during the Third Reich suffered from significantly more non- communicable diseases (e.g., diabetes, hypertension, cardiovascular disease, angina pectoris, anxiety, depression, migraines, stomach ulcers, and cancer) than the control group. Similarly, a study of adults born during the Chinese Famine of 1959-1961 found that children born during this period suffered from higher rates of hypertension (Huang et al, 2010), hyperglycemia, diabetes, and schizophrenia as adults than those born after the Chinese Famine (Li and Lumey,

2017).

Stress early in development can therefore contribute to increased vulnerability to future stressors, reduced physical and mental health in adulthood, decreased resilience, and ultimately, an elevated risk of all-cause mortality (Seeman et al., 2001, Borrell et al., 2010).

The second means by which early stress can affect adult health and longevity is epigenetic modification, although it is important to note that allostasis and epigenetic modification are by no means mutually exclusive. Rather, they work together to promote short-term survival and evolutionary fitness. In this way, the effects of historical trauma can be inherited (Kealohi Satu

Conching and Thayen, 2019).

Epigenetic modifications are those that change the expression of DNA without changing the nucleotide sequences by altering the folding of chromatin or the wrapping of DNA fibers around histone tails (Kuzawa and Sweet, 2009). One of the roles of chromatin is to maintain the shape of the chromosomes and to keep them within the confines of the nucleus through protein- induced folding (Kuzawa and Sweet, 2009). In order for the transcription factors to access the nucleotide sequences so that the gene can be expressed, the chromosome must unwind at the site of the gene (Kuzawa and Sweet, 2009). If the chromatin is tightly folded at the site of the gene, it is difficult for the transcription factor to access the gene, and its expression is limited (Kuzawa and Sweet, 2009). Conversely, if the chromatin is not tightly folded at the site of a gene, then it is easier for the transcription factor to access the gene, and it is easier for the gene to be expressed

(Kuzawa and Sweet, 2009). By controlling the folding of chromatin, epigenetic markers contribute to the degree of gene expression (Kuzawa and Sweet, 2009). For example, the addition of a methyl group to the local promoter area of a cytosine and guanine-rich region of

DNA changes the charge of the molecule and causes the chromatin to fold very tightly, thereby

26 preventing the transcription factor from accessing the gene and ultimately preventing the gene’s expression (Kuzawa and Sweet, 2009).

Epigenetic modifications can also take place by changing how tightly DNA is wrapped around histone proteins (Kuzawa and Sweet, 2009). For example, if a methyl group is added to a histone tail, then the DNA will be tightly wrapped around the histone protein by changing the charge of the proteins, again limiting the transcription factor’s access to the gene (Kuzawa and

Sweet, 2009). Conversely, if an acetyl group is added to a histone tail, then the DNA fibers are less tightly wrapped around the histone protein, and the transcription factor is more easily able to access the gene, thereby promoting its expression (Kuzawa and Sweet, 2009).

Yet a third way by which epigenetic modifications change the phenotype is by producing non-coding RNA in the nucleus (Kuzawa and Sweet, 2009). This non-coding RNA blocks the transcription factor from the gene, thereby preventing its expression (Kuzawa and Sweet, 2009).

During meiosis and mitosis, epigenetic markers (e.g., methyl and acetyl groups) are copied along with the nucleotides, and are therefore present in daughter cells (Kuzawa and

Sweet, 2009). In this way, epigenetic modifications that occur to the DNA during the life of the individual cause heritable modifications to the phenotype (Kuzawa and Sweet, 2009).

The HPA-mediated stress response has been directly implicated in heritable phenotypic changes through epigenetic modification (Krukowski et al., 2011). For example, glucocorticoids have been found in some cell types to inhibit acetylation and consequently, gene expression

(Krukowski et al., 2011) after binding to the glucocorticoid receptor, which can act as an mRNA transcription factor. The epigenetic marker can then be copied with the rest of the DNA and passed down to offspring thereby promoting the expression of phenotypic adaptations to the local environment without altering the DNA sequence (Hicks and Leonard, 2014).

In addition to promoting epigenetic modifications within the somatic and sex cells of an individual, stress can also promote epigenetic modifications intergenerationally by transmitting stress hormones across the placenta to a developing fetus. During typical development, the relatively high concentration of 11 " HSD-2 in the placenta buffers the fetus from elevations in maternal glucocorticoid concentration by converting active cortisol to inactive cortisone

(Kuzawa and Sweet, 2009). However, the fetus is not completely protected from maternal hormonal fluctuations. There are two, often simultaneous means by which the fetus can be exposed to maternal cortisol. First, as described above, inflammatory responses following a stress event can downregulate 11 " HSD-2, and a decrease in placental 11 " HSD-2 exposes the fetus to more maternal cortisol (Cottrell and Seckl, 2009). This is particularly problematic for children born into a low socioeconomic status, as stressors associated with poverty have been found to be associated with decreased 11 " HSD-2 (Appleton et al., 2013). Second, if enough cortisol is produced during a stress event, it can breach the placental barrier because the free cortisol molecules exceed the number of 11 " HSD-2 molecules (Cottrell and Seckl, 2009). This transmission of maternal glucocorticoids to the fetus through the placenta is thought to be one of the primary means by which information about the maternal environment is passed from the mother to the fetus (Cottrell and Seckl, 2009). While this process does promote short-term survival by preparing the fetus to cope with stressors present in the maternal environment, fetal exposure to glucocorticoids have been shown to be associated with poorer postnatal health (e.g.,

Cottrell and Seckl, 2009). In this way, stress during antenatal development contributes to adult health in accordance with the DOHaD. These processes are summarized in Figure 2.

Figure 2: The role of stress in epigenetic modification

Stress (e.g., oxygen or nutrient deprivation) during fetal development can also affect adult health by restricting intrauterine growth and promoting the “thrifty phenotype” (i.e., a lowered metabolism that promotes conservation of nutritional resources in a deprived environment) (Hales and Barker, 1992). The promotion of the thrifty phenotype through deprivation is an epigenetic adaptation that prepares the fetus to confront deprivation after birth.

In other words, if the maternal environment is one of deprivation through famine or other sources of food insecurity, then the fetus is programmed to cope with a deprived environment. In a deprived environment, the thrifty phenotype would become more common in the population because infants without the thrifty phenotype would be less able to conserve energy and be more likely to die of starvation before reproductive age. One means by which maternal nutritional deprivation can contribute to the expression of the thrifty phenotype in the fetus is through epigenetic change in the interaction between glucocorticoids and the growth hormone-IGF-1

(GH-IGF1) axis. Like ACTH, GH is released from the anterior pituitary gland (Álvarez-Nava

29 and Lanes, 2017). The subsequent binding of GH to growth hormone receptors (GHR) stimulates the production of IGF-1 by activating its transcription. Through its interaction with IGF-1, GH contributes to a wide range of somatic functions, including carbohydrate, lipid, and protein metabolism (Álvarez-Nava and Lanes, 2017). In a stressed or nutrient-deprived environment, the concentration of fetal IGF-1 is reduced (Langford et al., 1994), and metabolic functions are subsequently altered.

If the postnatal environment is not one of deprivation, however, then the fetus with a thrifty phenotype is faced with an evolutionary mismatch. In societies with abundant calories, it has been widely demonstrated that maternal deprivation during the first trimester of pregnancy, low birth weight, and early childhood nutrition deprivation are correlated with metabolic syndrome (i.e., diabetes, cardiovascular disease, abdominal adiposity, and high cholesterol) and poor adult health (e.g., Roseboom et al., 2001, Nelson, 2009, Fall, 2011, Shi et al., 2018), although some studies have found no association (Lumey et al., 2012, Ekamper et al., 2015). For example, in a longitudinal study, Roseboom and colleagues (2001) found that adults who were in utero during the Dutch Hunger Winter of 1944-1945 were more likely to develop metabolic syndrome later in life. While these individuals had been developing in utero during a time when food supplies to the Netherlands were cut off, food supplies returned to normal after the end of

WWII, and these children grew up in a food secure environment (Roseboom et al., 2001). The propensity to develop metabolic syndrome has been interpreted as an example of the thrifty phenotype leading to adverse health outcomes when the postnatal environment does not match the maternal-fetal environment (Roseboom et al., 2001).

The source of the correlation between metabolic syndrome and fetal deprivation is likely a combination of both direct fetal tissue damage from deprivation (Smith and Ryckman, 2015)

30 and epigenetic modification to fetal cells mediated by maternal glucocorticoids (Cottrell and

Seckl, 2009) that prepare the fetus to face a food-insecure environment.

While the environment can change from deprived to food-secure, the thrifty phenotype does not change. Rather, the individual with a thrifty phenotype retains a slower metabolism and conserves energy even though nutrients are readily and consistently available (Gowland, 2015).

This mismatch results in metabolic syndrome, but because the effects of metabolic syndrome are also age-dependent, the affected individual typically survives to reproductive age (Gowland,

2015). The thrifty phenotype is therefore retained in the population even when the local environment is not one of deprivation (Gowland, 2015). In this way, maternal stress can cause heritable changes in the fetal phenotype and therefore affect intergenerational health (Gowland,

2015).

In sum, the DOHaD hypothesis asserts that stress during development contributes to adult frailty by altering metabolic, neuroendocrine, and immune systems that influence adult phenotype. According to this hypothesis, people who experience greater stress as fetuses, infants, and children will have higher frailty at earlier adult ages and an overall greater risk or mortality than those who experienced less stress during development (Barker and Osmond, 1986, Barker et al., 1989, Martyn et al., 1995, Barker et al., 2000).

The DOHaD hypothesis, together with a biocultural political economy framework, provides a means to explain how ideology and sociopolitical circumstances contribute to heritable changes in phenotype. In a complex web of interdependent parts, ideology shapes global and local systems of production, consumption, and politics, which in turn shape and reproduce ideology (Goodman and Leatherman, 1998). Global and local systems shape social behavior and interpersonal relationships, which shape and reproduce global and local systems

(Goodman and Leatherman, 1998). Social behavior and interpersonal relationships shape biology

(Goodman and Leatherman, 1998) because differential exposure to stressors between social strata contribute to heritable changes to the phenotype through epigenetic modifications and changes to glucocorticoid feedback systems (Kuzawa and Sweet, 2009). Historical bioarchaeologists are particularly situated to adopt this framework because written records can provide insight into the ideologies that contribute to biology. In the next chapter, the historical circumstances that shaped both ideology and biology through differential exposure to stressors in

Ireland will be described.

Chapter 3: Historical Background

Understanding historical processes is integral to the biocultural political economy framework. First, cultural constructs such as race, class, and gender are not static, and changes to these concepts produce and are affected by changes in social relations (Goodman and

Leatherman, 1998). For example, in Ireland, race was initially constructed through familial origin; people could be English, Anglo-Irish, or Irish. Following the Reformation, these racial identities became more dependent on religion and allegiance to England; people could be papists or loyalists, and later, Catholics, Protestants, or Dissenters. Now, race in Ireland is still largely constructed around religion; people can be Catholic, Protestant, or Travelers, who are, for the most part, also Catholic. Thus, for bioarchaeologists to understand skeletal data within a biocultural political economy framework, it is necessary for them to identify changes in cultural constructs and social relations over time.

Second, one of the core tenets of biocultural political economy is the understanding that social and evolutionary processes are neither unilineal nor progressive. That is, biocultural political economy rejects pure functionalism and interprets sociopolitical circumstances as interdependent, dynamic systems (Goodman and Leatherman, 1998). For example, as will be shown later, the racialization of religion in Ireland cannot be understood without considering the challenges to monarchies in Western Europe more broadly, and consequently, the variation in exposure to stressors based on race also cannot be understood without these considerations.

Moreover, in its rejection of pure functionalism, biocultural political economy recognizes that biological and behavioral adaptations are only adaptations for a specific environment in which they provide a selective advantage. Once the environment changes, behaviors and biological traits are no longer necessarily adaptive. For example, while a “thrifty phenotype” might buffer a person against famine in a deprived environment, the same exact phenotype can put that person at risk for metabolic conditions in an affluent environment. It is therefore necessary that bioarchaeologists identify changes in the local, regional, and global environment that contribute to biological and behavioral adaptations.

Third, given its use of dialectical materialism and conflict as the impetus for social change, bioarchaeologists need to identify the conflicts that predicate social change (e.g., the

Reformation and English Civil War), and in turn, shape biological and behavioral adaptations through environmental change (e.g., colonization as a promotor of urbanization).

Finally, biocultural political economy requires an understanding of history because sociopolitical relationships are reproduced through knowledge production (Goodman and

Leatherman, 1998). An understanding of who is producing knowledge and what their motives are for doing so are therefore crucial to revealing ideologies that shape and maintain social relationships and sociopolitical circumstances. For example, the writing of most Irish historical accounts in English, not Irish, can show how English was the language of the educated, suggesting an Anglo-identity was more valuable in pre-Famine Ireland than an Irish one. In another example, nationalist writing in the late 19th-century focused on blaming the British for the Famine, a focus that revisionist historians argue was adopted to promote the nationalist political agenda. Thus, as producers of knowledge and anthropologists, bioarchaeologists must

34 be reflective and transparent in how contemporary political circumstances and ideologies affect research designs and data interpretation.

Irish history has long contributed to the ideologies that shape Irish local and international politics, interpersonal relationships, and identity. In turn, Irish ideologies and allegiances have long shaped the writing of Irish history. Following outbreaks of violence in Northern Ireland in the 1970s, a revisionist movement in Irish history has reshaped the narrative of Irish national identity and challenged the portrayal of Ireland as a victim of English colonization (O’Mahony and Delanty, 2001:8-12). While nationalists argue that the problems in Ireland were a consequence of several hundred years of invasions, revisionists posit that the problems that plagued Ireland were largely the product of internal conflicts between complex, heterogenous cultural groups within Ireland (O’Mahony and Delanty, 2001:10). Critics of revisionism (post- revisionists), on the other hand, say that there is an underlying element of truth to the popular myth of Irish resistance to foreign invaders, and that revisionists disregard the reality of colonial exploitation (O’Mahony and Delany, 2001:10). The conflict between these two intellectual movements continues to affect Irish politics, and each political party subscribes to a different version of these movements (O’Mahony and Delany, 2001:11). The dominant political party,

Fianna Fáil, is the populist, conservative party associated with nationalism (O’Mahony and

Delany, 2001:11), and as such is likely influenced by nationalist and post-revisionist histories.

The opposing political party, Fine Gael, is associated with anti-nationalist and revisionist histories, as is the Democratic Left (O’Mahony and Delany, 2001:11). Interpretations of Irish history therefore continue to influence politics and modern national identity (O’Mahony and

Delany, 2001:12).

For the purposes of the present study, three historical periods will be discussed, namely, the early medieval, late medieval, and post-medieval periods. Because this dissertation examines health between the late medieval and post-medieval periods, these two will be discussed extensively. Because ideology and socioeconomic status are embodied through heritable changes in phenotype that result from differential exposure to stressors, it is necessary to identify circumstances such as nutrition and housing that either alleviate the impact of stressors or provide exposure to new ones. Consequently, food and housing will be detailed for each time period. Finally, because modern historical narratives, academic and otherwise, have been consistently shaped by violence and peace negotiations in the late-twentieth and early twenty- first centuries, this period will be discussed as well.

Early Medieval Ireland

Early medieval Ireland (AD 400- 1150) was a strictly and complex hierarchical, kin- based, rural society (McCormick, 2014) with a barter economy (O Croinin 2016:111). There were multiple social classes including slaves, laborers, workmen, entertainers, multiple grades of freemen, nobles, and three types of kings (Moody and Martin, 1995:50-51). High kings ruled over a province (Connacht, Leinster, Munster, and Ulster) and oversaw the two lower kings

(Moody and Martin 1995:55, MacCotter, 2008, O Croinin, 2016:64-85). Kings oversaw the nobility, who oversaw the freeman, and the freemen were essentially clients of the nobility.

The status of the nobility was determined by how many clients (i.e., freeman) were working for them, and the status of the freeman was determined by how many head of cattle he owned

(McCormick, 2014).

There were at least eight grades of freeman, and the grade or level of the freeman determined his participation in legal and social processes. Beneath the freemen were the peasants, and lastly, the lowest social class was that of the slave and concubine. The nobility would give cattle, land, and equipment to the freemen, who would then deliver a yearly return of products such as bread, wheat, bacon, milk, butter, onions (McCormick, 2014). At the bottom of the social hierarchy were slaves, who like cattle, comprised part of the main currency during this period (Woolf, 2018). In all, it is estimated that there were about 150 kingdoms in early medieval

Ireland, each with its own similarly structured community, which was enforced through the legal tract Críth Gablach that outlined the entitlements and social responsibilities of each social class.

Hospitality was central to Irish culture in the early medieval period, and its documentation in the Críth Gablach, provides invaluable insight into the complexities of the

Irish social hierarchy (Peters, 2016:85). Additionally, food was integral to the maintenance of social status and reinforced class as a social norm, a trend that would continue into the modern period. The use of food as a social class enforcer was so critical that the Críth Gablach explicitly states to which types of foods people of varying social classes were entitled. For example, the lowest level freeman, the fer midboth I was entitled to only milk, cheese, or cereal when visiting someone else’s home (Peters, 2016:86). The third lowest level freeman, the ócaire, was entitled to the same provisions as the fer midboth I but with the addition of a choice of side dishes such as a loaf of bread or soured milk (Peters, 2015:86). The freeman one grade up from the ócaire, the aithech aca threba a deich was entitled to the same provisions as the ócaire but was permitted to request butter, onions, or salt if the visit took place on a Sunday (Peters, 2016:88).

The four highest grade freemen, the bóaire frebsa, mruigfer, fer fothlai, and aire coisring were entitled to the previously listed provisions, but unlike the lower levels of commoners, these

37 freemen were expected to be served meat (Peters, 2016:88-89). There are comparatively few laws governing the foods to which women and children were entitled, but it was recognized that their nutritional needs were different from men. One particular law states that a man could be fined for denying a pregnant woman the food that she craved (Peters, 2015:91).

These laws, while they did serve to maintain a strict and complex social hierarchy, did allow variation for perceived need. As described above, pregnant women were entitled to different foods than men. Similarly, while lower level freemen were generally not entitled to butter, they could request it when ill, and it was expected that this request would be granted because it was recognized that the nutritional needs during times of sickness were different than those in times of relative health (Peters, 2016:90). Another legal tract, the Bretha Crólige, states that the sick are also entitled to fresh meat and celery, regardless of social status (Peters,

2016:90, O Croinin, 2016:115). It was recommended that sick children be fed littíu, a type of wheaten porridge prepared with fresh milk, honey, and egg yolks, as well as butter and curds

(Sexton, 1998:77). Tiuglagin, a mixture of meal, water or milk, and butter, was recommended for sick adults, and brotchán, a mixture of meal and water or milk was recommended for menstruating nuns (Sexton, 1998:78). This variation is notable for two reasons. First, it highlights the understanding in early medieval Ireland that nutritional needs varied depending on physical state and well-being. Second, the reservation of certain food types for children suggests a collective cultural understanding of childhood as a period of life distinct from adulthood.

The social status of children, while not as clearly stated in legal tracts as the status of adults, is still perceptible through occasional mentions in these legal documents. Typically, the social status of the child was dependent on the social status of the father. Fosterage was a common practice during this period, and at age seven, a child could be sent to another home of

38 equal status to the father to be raised (Peters, 2016:92). The types of food served to the child while in the care of a foster family were governed by a set of rules similar to those that entitled the child’s father to food when visiting. It was still recognized within the fosterage system, however, that children’s nutritional needs differed from those of adults (Peters, 2016:92). While a low-ranking adult freeman might be entitled to milk, a child of a low-ranking freeman would be entitled to littíu while in fosterage (Peters, 2016:92). Only the types of foods served in addition to the littíu would vary in accordance with the father’s social status. If the child was a son of a freeman, then the foster parents would be expected to include salted butter with the littíu. If the fostered child was the son of a noble, the foster parents would be expected to serve him fresh butter with the littíu, and if the child was a son of a king, then the foster parents would be expected to serve him littíu with honey (Peters, 2016:92).

Milk was an important dietary component across all levels of the social hierarchy, and most livestock were reared for milk production instead of meat production. The widespread consumption of dairy milk is supported by the density of female cattle remains found during archaeological excavations of ringforts (Kerr, 2014, McCormick, 2014, 2015). Goats were also used for milk, albeit to a lesser extent than cows (Peters, 2016:93).

Meat was not as central to the early medieval Irish diet as milk products, but its consumption was still moderately prevalent. Cows were kept for milk, and beef was rarely eaten

(Peters, 2016:105). Sheep, while reared primarily for their wool (and occasionally milk), were also eaten as either mutton or lamb (Kerr, 2014, Peters, 2016:95). Pigs were generally reserved for feasting (Kerr, 2014), and hens were kept for their eggs (Peters, 2016:104). Geese were a high-status food, and their consumption was reserved for kings and nobles (Peters, 2016:104).

Across all social strata, cereal was an important part of the diet in early medieval Ireland.

Numerous tools associated with cereal cultivation, such as those used for plowing, milling, and drying, have been recovered from early medieval sites (McClatchie et al., 2015). Additionally, archaeobotanical evidence shows that cereal production was diverse and included barley, common bristle, and wild oats, flax, rye, and bread wheat (McClatchie et al., 2015). Peas and broad beans were also cultivated (McClatchie et al., 2015). According to the eighth century legal document Bretha Déin Chécht, barley and oats were relatively low-status foods, while bread wheat was ascribed the highest status, followed by rye, spelt wheat, and emmer wheat

(McClatchie et al., 2015).

Cereals were used for baking bread, but written documents show that they were also incorporated into a number of porridges and gruels. Porridge was often mixed with water, buttermilk, whey-water, egg yolks, and salted or fresh butter depending on the type of porridge being prepared (Sexton, 1998:77). Porridge and gruel in the early medieval period were often eaten with either preserved (salted) or fresh butter, honey, or fruit (McClatchie et al., 2015) such as apples, strawberries, plums, and blackberries (O Croinin 2016:118). The cereals that were not eaten could be used for making beer, and the straw was used for animal fodder and the construction of thatch roofs (Clarkson and Crawford, 2001).

It was typical in the early medieval period for each household to have a vegetable plot, and vegetables (e.g., onions) and legumes (e.g., peas, beans) grown in these plots were often consumed to prevent sickness (O Croinin 2016:115), to supplement the standard diet, and to compensate for shortfalls during times of famine (Peters, 2016:95-96).

The gathering of wild foods was common, particularly among peasants. Wild garlic, radishes, nettles, nuts, berries (e.g., strawberries, rowan berries, sloes, blackberries, and

40 bilberries), and apples have been frequently mentioned in early Irish texts (Peters, 2016:97).

Fishing was not as common, despite Ireland’s extensive network of lakes, rivers, and streams, primarily because fishing rights dictated by social standing, and land with river or estuary access was highly valued (Peters, 2016:99-100). The collection of shellfish was far more common among peasants and lower freemen, though shellfish were not central to the diet except in times of scarcity (Peters, 2015:101).

Despite the diversity of food, early medieval Ireland was not immune to shortages. The wet climate of the country limited the window for threshing and winnowing, and it was difficult to store grain, which was vulnerable to both mold and fire (O Croinin 2016:115).

After early medieval Ireland, the next period in Irish history is the Viking Age (c. 800-1066), though it should be remembered that the island was subject to numerous Viking invasions in the early medieval period, and indeed, the Viking Age overlaps in chronology with the early medieval period (AD 400-1150) (Woolf, 2018). While this period is brief, the Scandinavian contribution to Irish society is significant and includes the development of the important port cities of Dublin, Limerick, and Waterford (Woolf, 2018). Initially, the Vikings had a distinct ethnic identity in Ireland, but by the time of the Anglo-Norman invasion, the Scandinavian

Hiberno-Norse ethnic identity had merged with that of the native Irish (Woolf, 2018).

Late Medieval Ireland

The Anglo-Norman invasion of Ireland was more a process of negotiation than it was a series of battles (Vincent, 2018), and the late medieval period rarely experienced the Irish versus

English conflict characteristic of the post medieval period (Hartland, 2018). In the late 12th century, the King of Leinster, Dairmait Mac Murchada, was exiled and asked for the help of

King Henry II of England in regaining the kingdom of Leinster (Veach, 2018). King Henry II allowed Mac Murchada to recruit his Welsh subjects, including Richard fitz Gilbert, better known as Strongbow, who was promised Dairmait Mac Murchada’s daughter and heir in exchange for Strongbow’s successful military service (Veach, 2018). After his marriage to Aoífe and Mac Murchada’s death in 1171, Strongbow became the first Anglo-Norman ruler of a kingdom in Ireland, much to the disdain of Henry II (Veach, 2018). Henry II forced Strongbow to relinquish his new position as the king of Leinster, demoting him to the status of a fief, thereby making Strongbow once again a subject of Henry II and cementing Leinster as an

English territory (Veach, 2018). Soon thereafter, most Irish rulers submitted to Henry II’s authority and superior military technology, except for the high king of Ireland, Ruaidrí Ua

Conchobair in Connacht in the west (Veach, 2018).

Henry II’s time in Ireland was limited because he also ruled over most of France, which was considered to be more important than the culturally inferior people of Ireland (Veach, 2018).

Despite his absence, Henry II wanted to maintain control in Ireland, so he granted the pre- existing Irish kingdoms to members of his military aristocracy (Veach, 2018). The members of the military aristocracy became known as lords, and solidified English rule in Ireland through the construction of castles, fortified towns, and rural boroughs (e.g., see Ardreigh in Materials), as well as the transplantation of English monasteries (Veach, 2018). In exchange for the protection of the local lord and fortified town as well as certain rights and privileges, residents of the rural boroughs were loyal to the lord (Keeley and Seaver, 2000).

In addition to changes to social structure, the Anglo-Norman occupation resulted in changes to the economy and subsistence. The Anglo-Norman occupation resulted in rapid urban development (Lyons, 2016:115) and catalyzed the commercialization of Irish agriculture and

42 increased cereal production after the introduction of fallow field crop rotation, which also served to protect against periodic crop shortages (Murphy, 2018). Combined with the expansion of cultivation area (Murphy, 2018), this innovation dramatically increased cereal production that not only fulfilled the dietary needs of the island, but also provided enough for export (Maple,

1989). In fact, Ireland became one of the major sources of wheat products for England and its kingdoms in the late medieval period (Murphy, 2018). Wheat, while it had been considered a luxury food in the early medieval period, flourished under Anglo-Norman agricultural innovation and became commonplace during the late medieval period (Lyons, 2016:135). The manorial mills in Ireland were far more successful than those in England (Murphy, 2018). The increasing success of cereal-based agriculture did not detract from pastoralism (Murphy, 2018). As described in the previous section, pastoralism was important to the early medieval Irish economy and continued to be important in the late medieval period (Murphy, 2018). Wool, oats, and cheese were important sources of income and were sold both domestically and as exports

(Murphy, 2018). Other crops such as legumes and rye were primarily reserved for household consumption (Murphy, 2018). Overall, the range of foods available to the Irish diversified significantly during the late medieval period, largely as a result of increasing urbanization and commercialization (Lyons, 2016:115).

Both textual data and archaeological evidence demonstrate the diversification of food during this period. The expansion of cities and their accompanying cesspits provide a particularly detailed source of information about dietary diversification (Lyons, 2016:132). Unlike the subsequent time period, most people in late medieval Ireland enjoyed a well-balanced diet with ample vitamins and minerals (Lyons, 2016:132). Legumes are frequently recovered from cesspit excavations, and excavations of seasonal cesspits show that consumption of legumes was more

43 frequent in the winter months. Legumes would have provided an importance source of protein and vitamins B, C, and K, especially during the winter, as they could be easily dried and stored

(Lyons, 2016:142).

As in the early medieval period, berries and apples were the main fruits consumed during the late medieval period and were often included as side-dishes or toppings for oatmeal for all social classes. Excavations of urban cesspits have produced large quantities of seeds, including cherries, sloes, rose seeds, rowan, blackberry, bilberry, apple, bramble, strawberry, and haws

(Lyons, 2016:150-151). In addition to being served as side-dishes or toppings, fruit could be preserved as jam and eaten in the winter months (Lyons, 2016:153). Pears were a relatively new addition to the Irish diet, and were usually consumed in the form of baked puddings and pies

(Lyons, 2016:151). Like fruit, hazelnuts were also a common component of the Irish diet across all social strata, and would have provided a source of fat and protein (Lyons, 2016:152).

Vegetables and herbs were also common for all social classes, and excavations of late medieval sites have produced evidence of celery, watercress, cabbage, mustard, garlic, and turnip consumption (Lyons, 2016:156). Textual and archaeological evidence points to the use of fennel, dill, black mustard, and mint as seasonings for salads and fish (Lyons, 2016:157).

The Anglo-Norman occupation resulted in a diversification of food by connecting Ireland with trade routes to the Mediterranean and central Europe. Grapes, figs, raisins, and almonds from the Mediterranean became popular seasonal items for the wealthy, who would incorporate them into their otherwise monotonous diet of fish and cereal during Advent and Lent (Lyons,

2016:160). Figs were the cheapest Mediterranean import, and so were available to the lower classes as well (Lyons, 2016:161). Walnuts imported from France and Germany were also popular among the upper classes (Lyons, 2016:163).

Despite the diversification of food available to all social classes, access to some foods was still used as means to reinforce the social hierarchy. As was common in continental Europe, game hunting rights became limited. While cattle, sheep, and pig were legally the only sources of meat available to the lower classes, the elite were entitled to hunting rights, and could therefore include rabbit and deer in their diets (Beglane, 2016:167).

Over time, the identities of the native Irish and the invading English eventually all but merged, as they had after the Viking invasions (Veach, 2018). A tenuous peace was forged when

Henry II and Ruaidrí Ua Conchobair both signed the Treaty of Windsor, which required that displaced Irish farmers be returned to their original lands (Veach, 2018). In 1185, Henry II made his youngest son John king of Ireland (Veach, 2018). Unlike Henry II, John struggled to maintain alliances with both his barons and Irish kings. John even granted the kingdom of Connacht to his friend William de Burgh who was already a political figure in Munster (Veach, 2018). Richard,

Henry II’s other son, enlisted the service of Walter de Lacy, lord of Meath after the assassination of Hugh de Lacy, to defeat de Burgh in Munster in 1199 (Veach, 2018). After Richard’s death and John’s ascension to the throne, the position of de Burgh was again reversed, returning

Munster to English possession (Veach, 2018). King John then used Walter de Lacy to usurp John de Courcy’s authority in Ulster in 1204 (Veach, 2018).

After English rule over the kingdoms of Ireland had been achieved, John sought to create a direct government between himself and his subjects without the use of lords as middle men

(Veach, 2018). After a brief rebellion by the lords of Leinster, Meath, Limerick, and Ulster,

John’s rule over Ireland was cemented, English law was firmly established as the sole government in Ireland, and Ireland essentially became an English colony (Veach, 2018).

Ireland experienced a brief hiatus in English rule after the death of King John in 1216, when William Marshal became the regent of England and granted some authority back to the

Irish barons (Veach, 2018). Later, after a series of rebellions, Henry III granted Ulster back to

Hugh de Lacy, but managed to ensure through arranged marriages that parts of Meath and

Leinster remained under the control of Henry III’s appointees (Veach, 2018). While Henry III had re-granted some authority back to Irish lords, he also granted all of Ireland to his son,

Edward I (Hartland, 2018). In bequeathing the entirety of Ireland to Edward I, Henry III undermined his previous decision to permit limited self-government (Hartland, 2018). Beginning in 1264, this limited self-government took the form of an Irish Parliament independent of the

English Parliament, although the king was still entitled to make decisions about Ireland without consulting either parliament (Hartland, 2018).

The king began to fear that the English settlers would perceive the benefits of Irish law to be greater than those of English law (Smith, 2018). If they did so, then there would be an elevated risk of rebellion by the English settlers, whom they feared would support the Yorkist plots to overthrow the English throne (Moody and Martin, 1995:167-168). This fear was fueled by the increasing instability in Ireland as loyal subjects and their funds were funneled into the conflicts in Flanders, Scotland, and into the Hundred Years War, and millions across Europe fell victim to the Black Death (Simms, 2018, Smith, 2018). In response to this fear, parliament passed the Statutes of Kilkenny in 1366, which sought to guarantee justice for English subjects living in Ireland under English law (Jackson, 1970, Smith, 2018). Additionally, the Statutes of

Kilkenny limited the interactions of the English and native Irish (the Gael) (Jackson, 1970,

Smith, 2018). Rulers were no longer able to forge alliances via marriage, and so marriage between the English and Irish was limited. English settlers were forbidden from speaking the

Irish language and from dressing or riding horses in a manner similar to the Irish (Jackson, 1970,

Moody and Martin, 1995:168, Smith, 2018). Representatives of the king sent to Ireland and

English settlers were forbidden from insulting each other, but despite these efforts to unite the

English in Ireland, the settlers (Old English, or “English rebels”) and representatives (New

English) continued to distrust each other (Smith, 2018). Meanwhile, the Gael and English settlers became more integrated, and Gael literature and politics experienced a resurgence largely centered around Kildare (Maginn, 2018, Simms, 2018).

The Statutes of Kilkenny are the first set of laws put in place to govern Irish behavior for the purpose of preventing rebellion. More laws would follow the Yorkist plots. The Yorkist plots involved the two rival houses in the ruling Plantagenet family, namely, the House of York and the House of Lancaster (Moody and Martin, 1995:167-168). The House of York (1385-1485) collapsed with the death of Richard III, who was defeated in the War of Roses by Henry VII, a

Lancasterian Tudor (Moody and Martin, 1995:167-168). After the death of Richard III and the abandonment of the throne by Edward IV, Henry VII ascended the throne. Meanwhile in Ireland,

Yorkist Pretender Edward IV was again crowned king of England (Moody and Martin,

1995:167-168, Maginn, 2018). In a demonstration of support for Edward IV, Earl of Kildare

Thomas Fitzgerald invaded England to overthrow Henry VII (Moody and Martin, 1995:167-

168). When this failed, a second Yorkist Pretender Perkin Warbeck attempted to ascend the

English throne by gaining support in Kildare (Moody and Martin, 1995:167-168). It soon became clear that Ireland was proving to be a continual threat to England by facilitating Yorkists

(Moody and Martin, 1995:167-168). Henry VII’s goal thereafter was to make Ireland loyal and obedient (Moody and Martin, 1995:168).

The Tudors emerged victorious from the Yorkist plots, and the hold of England over

Ireland intensified under the reign of Henry VIII and Elizabeth I of the House of Tudor (Hayes-

McCoy, 2011:151). In the years leading up to Henry VIII’s coronation as king of Ireland, the

English monarchy lived in constant fear of Irish rebellion. One major concern was that other

European powers, and in particular Catholic Spain, would use Ireland as a base from which to launch military action against England (Hayes-McCoy, 2011:151). After the Reformation,

England’s position in Ireland grew increasingly insecure as the monarchy vied with papal authority for power in the British Isles (Hayes-McCoy, 2011:153). Indeed, by autumn of 1534,

Spain had arranged to send troops to Maynooth, Co. Kildare, to aid in the rebellion by Thomas

Fitzgerald, Anglo-Irish leader and Earl of Kildare (Lennon, 2005:108-110). The Fitzgeralds were defeated in 1541, and Henry VIII was declared king of Ireland soon thereafter (Hayes-McCoy,

2011:153).

Henry VIII was succeeded by his nine-year-old son Edward VI in 1547. Edward VI tried to introduce additional English policies and enforce the Anglican religion in Ireland, but his efforts were met with resistance (Hayes-McCoy, 2011:156-157). Edward VI fell ill in 1553, and before he could remove his Catholic half-sister Mary I from his line of succession, he died.

During Mary I’s short reign from 1553 to 1558, her main goal was to reverse the Anglicization of the British Isles. Mary I achieved this goal by once again officially making Catholicism the religion of England (Hayes-McCoy, 2011:157) and by routinely burning Protestants and dissenters (Puritans and Presbyterians) at the stake.

Mary I was succeeded by her half-sister Elizabeth I, who was excommunicated from the

Catholic Church in 1579 (Hayes-McCoy, 2011:158). Her excommunication inspired Catholic

Italy and Spain to continue to back Irish Catholic rebels. In order to stifle these rebellions,

Elizabeth I began the process of plantation, which removed Catholic Irish/Old English landowners from their property and replaced them with Protestant colonists loyal to Elizabeth I

(Hayes-McCoy, 2011:158). Transplantation was particularly intense in Ulster because they had not been affected by Anglicization as severely as the other Irish provinces (Hayes-McCoy,

2011:159). Even though their rebellion was assisted by the Spanish, the last Irish rulers of Ulster were defeated at the Battle of Kinsale in 1603 (Hayes-McCoy, 2011:162).

Post-Medieval Ireland

The English Civil War marks the end of the late medieval period in the British Isles, as societies struggled to negotiate the position of their governments within the landscape of

Enlightenment thought. The English Civil War was also instrumental in the construction of Irish social groups, namely, the division between Catholics and Protestants (O’Mahony and Delanty,

2001:35). After the English Civil War, the Catholic Gael and the Old English would merge to form one united Catholic front (O’Mahony and Delanty, 2001:35).

The English Civil War and emergence of the English Commonwealth once again distracted from England’s efforts in Ireland, and Catholics in Ireland were further divided

(Clarke, 2011:168). The Old English in Ireland were tentatively prepared to support King

Charles I, who had declared war on the English parliament on one side of the civil war, while the

Gael pledged their allegiance to Rome (Clarke, 2011:168). The Gael believed that their support of papal authority would convert Ireland once again to Catholicism and return confiscated lands back to the Irish (Clarke, 2011:168). Furthermore, both the Gael and the Old English settlers grew increasingly frustrated with the changes to their social and economic status that resulted from the transplantation of the Parliament-backed New English (Moody and Martin, 1995:196-

197). At the conclusion of the English Civil War, the English Parliament tried and executed

Charles I, who had been supported by the Old English in Ireland. The Old English also opposed the English Parliament because of its endorsement of transplantation and allied themselves once again with the Gael in Ulster, Meath, and Leinster to mount an insurrection in 1641 (Moody and

Martin, 1995:196-197, Clarke, 2011:168).

The Rebellion of 1641 ended in 1649 when Oliver Cromwell and his army arrived in

Drogheda under the direction of the Protestant English parliament (Moody and Martin,

1995:196-197, Clarke, 2011:173). Cromwell sought not only to suppress the rebellion of the

Catholic Old English and Gael, but also to exact revenge on behalf of the English

Commonwealth on the Old English for their support of Charles I during the civil war (Clarke,

2001:173). In his defeat of both the Gael and the Old English, Cromwell’s army killed 3,000 people at Drogheda (Reilly, 1999:2) and an additional 1,500 at Wexford (Reilly, 1999:161). In an additional effort to suppress and prevent rebellions, the English Parliament passed the Act of

Settlement in 1662. This act removed land from Royalists, who were mostly Catholics, and granted it to Protestants. The Act of Settlement, while it was put in place to prevent rebellion, fueled further resentment toward the English parliament because the Old English and Gael were permitted to stay on the land, but instead of owning it as they had previously, they now had to work on it for the New English Protestants (Moody and Martin, 1995:203, Bainard, 2001).

After the Cromwellian Wars, religion became racialized (McVeigh and Rolston, 2007). The Old

English and the Gael became synonymous with Irish Catholics, and “New English” became synonymous Protestants. Protestants therefore perceived Catholics to be a threat to the English monarchy, and England sought to eradicate Catholicism from Ireland. One way of converting

Ireland from Catholicism was to create legal incentives for converting to Protestantism, which

50 until this point, had been merely incidental. In other words, while Protestants did enjoy the benefits of English legislation prior to the Cromwellian Wars, such as the process of transplantation, there were no laws that explicitly gave additional rights to Protestants while taking them away from Catholics. This changed when the Test Act was passed in 1673, which prevented anyone who would not deny transubstantiation (the belief that through the sacrament of Communion, the Eucharist literally became the body of Christ) from holding public office.

This is significant because transubstantiation is one of the few differences between the Catholic and early Protestant doctrine and is one of the main tenets of the Catholic religion. To deny transubstantiation is to deny Catholicism. The Test Act therefore forbade Catholics from holding public office (Elias, 1914:63).

Officially, the Test Act should have prevented James II, Duke of York and a devout

Catholic, from ascending the throne. When his brother, King Charles II, however, died unexpectedly in 1685, James II became the king of England despite his Catholic faith (Moody and Martin, 1995:207). When James II became king of England and consequently ruled over

Ireland, the Irish Catholics believed that he would reverse the Act of Settlement and that their socioeconomic positions would improve (Moody and Martin, 1995:207). While James II had no intention of reversing the Act of Settlement, his appointed head of the Irish army and Earl of

Tyrconnell, Richard Talbot, dismissed Protestants from their positions of power (Moody and

Martin, 1995:208). Consequently, Protestants became suspicious of James II and invited James

II’s Calvinist son-in-law, William of Orange, to mount an insurrection and replace him on the throne (Elias, 1914:72-73, Moody and Martin, 1995:209). James II fled to France to seek the protection of the Catholic king of France, Louis XIV. Meanwhile support for James II remained in Ireland, where people still believed he would overturn the Act of Settlement. James II arrived

51 in Ireland in March 1689, where he met William of Orange to battle for the English crown in the

Battle of the Boyne. William of Orange defeated James II, and his victory was confirmed in 1691

(Jackson, 1970, Moody and Martin, 1995:212-215, O’Mahony and Delanty, 2001:138).

The opposition of the Irish to the English monarchy in yet another insurrection fueled fears of subsequent rebellions. The fear of Gaelic insurrection is well-documented, albeit exaggerated (e.g., Hussey and O’Conner, 1641, P.G., 1678, J.R. and W.A., 1679, Oates, 1680,

Wells, 1688, Stephens, 1712, Temple, 1746, Clergyman of the Church of England, 1778), as part of a developing nationalist English propaganda movement. It is at this time that anti-Irish rhetoric becomes a defining characteristic of English identity among the New English in Ireland.

As such, there is no shortage of descriptions of atrocities said to be committed by the Irish, which serve to both build English colonial identity and to retroactively justify the Cromwellian

Wars. Many of these accounts were written, but many more were reinforced and repeated in the public through sermons, which were the main means of disseminating political information

(McBride, 2009:297). As sermons, these speeches also capitalized on Christian ideology, often comparing the plight of the English Protestants to the deliverance of God’s chose people from

Egypt in the Old Testament (McBride, 2009:198). Thus, the dominant ideology was one of a moral, industrious, Protestant class appointed by God to convert the wild, lazy, immoral Irish, and stories of the murderous Catholics were widely circulated.

One author describes the Irish as blood-sucking, naked cannibals and invites the reader to,

“Witness their stripping stark naked, Men, Women, and Children, even

Children sucking their poor Mothers Brests; whereby multitudes of all sorts,

Ages, and Sexes in the extremities of that cold season of Frost and Snow, have

most lamentably perished; Women being dragged up and down Naked; Women

in Child-bed, drawn out thence and cast into Prison; one delivered of a Child,

while she was hanging; one ripped up and two Children taken out of her, and

all cast and eaten up by Swine. One stabb’d in the Breast, her Child sucking.

An In[f]ant cruelly murthered, whom they found sucking his dead Mother,

slain by them the day before. A Child of fourteen years of Age taken from this

Mother, in her sight cast into a Bog-pit, and held under water while he was

drowned… (J.R. and W.A., 1679)”

Similarly, Sir Titus Oates writes,

“Protestants…were Murthered and Massacred [by Catholics] throughout the

whole Kingdom; Women were Ripped up alive, young Children dashed against

the Pavement, Embrio’s torn from the bleeding Womb, Hoary Hairs stained

with Blood, Churches Robbed, Houses Fired, Women Ravished, Virgins

Deflowred, and then Murthered with the most exquisite Torments (Oates,

1680)”

While these accounts are exaggerated, the ruling class was indeed constantly challenged by insurrections on multiple fronts, although most of these were localized, agrarian rebellions against tithes and high rents (McBride, 2009:319). In response to fears of insurrection, both real and exaggerated, the English parliament passed a collection of discriminatory laws against

Catholicism. These laws became known as the Penal Laws, and the goals of the Penal Laws were twofold. First, through the Penal Laws, the English parliament sought to prevent Catholics from becoming powerful enough to mount an effective insurrection, both politically and militarily.

The second goal of the Penal Laws was to eradicate Catholicism from Ireland because the ruling class believed that Catholicism made the Irish less economically productive (McBride,

2009:90). It was believed that the number of holy days, on which Catholics did not work, was excessive and detrimental to the economy (McBride, 2009:90). A parliament member from

Carrcikfergus estimated that £325,000 was lost annually through the observance of holy days

(McBride, 2009:90). Moreover, they argued that the observation of Lent made the Irish less healthy, and therefore, less productive (McBride, 2009:91). Members of parliament also attributed widespread poverty to Catholicism and argued that the Irish would be less impoverished if they did not have to regularly pay for the upkeep of the church and for penances

(McBride, 2009:91). Finally, those who did not oppose Catholicism for political or economic reasons opposed to it for moral reasons. They believed that Catholicism encouraged superstition, witchcraft, and idol worship, which were all considered sins according to the Protestant church.

Over time, the Penal Laws forbade the Irish from practicing Catholicism, receiving or giving an education, entering into a profession, holding public office, participating in trade, owning weapons, living within five miles of a town, owning a horse worth more than five pounds, buying or leasing land, inheriting land from a Protestant, renting land worth more than thirty shillings per year, earning more than one third of the rent on a given plot of land, going on a pilgrimage, visiting a holy well, or being the guardian of a child. Additionally, the Penal Laws required that the Irish attend Protestant church and take an oath of allegiance (Jackson, 1970,

Moody and Martin, 1995:218, McBride, 2009:198-199). They also required that land already held by Catholics had to be subdivided among all of the sons when the father died, unless the oldest son converted to Protestantism, in which case the oldest son would inherit all of the land

(Macauly, 2016). This practice ensured that Catholic landholdings would grow increasingly

54 small with ever generation (Macauly, 2016). Catholics and Protestants were prohibited from intermarrying, and a Catholic priest could be charged with the capital crime of treason for officiating a wedding between a Catholic and a Protestant (Luddy, 2017:346). For a short time in

1724, priests were outlawed altogether, and any priest or person found providing shelter to a priest could be charged with treason and sentenced to be hanged, drawn, and quartered

(McBride, 2009:222). A similar bill had been passed in 1697, the Bishops’ Banishment Act, which ordered that every Catholic clergy member be exiled. The Bishops’ Banishment Act was designed to eradicate Catholicism by preventing the ordination of priests, as new priests could only be ordained by existing priests (McBride, 2009:218). In addition to the laws that were passed, a number of bills were introduced in parliament to further suppress the growth of

Catholicism. One of the most infamous bills was one introduced in 1719, which would have required the castration of all unregistered priests in Ireland (McBride, 2009:201). While these bills were never passed, they served as a reminder to Catholics of their social status, and that parliament had the ability to pass these bills if Catholics chose to rebel (McBride, 2009:217).

Such psychosocial stress has been shown in modern populations to adversely affect health by interacting with the body’s stress response. For example, in their study of Latin

American immigrants in Oregon, McClure and colleagues (2010) found that fasting glucose was higher in women who reported higher levels of perceived discrimination. Because the stress response is adaptive, it can be assumed that the biological response to discrimination in the past is similar to that biological response today, and in that way was one means by which social status was embodied.

These discriminatory laws were deliberately designed to limit the property ownership and political presence of Catholics and to prevent them from challenging the colonial power structure

(Macauly, 2016). While not consistently enforced, they were significant in that they reinforced the Protestant, political, and economic ideology of the ruling class by reminding Catholics of their social status (McBride, 2009:216-217). Some Catholics did retain their positions in the ruling class, and even more enjoyed the comforts of the middle class (McBride, 2009). The persistence of a middle class supports the arguments of revisionists, who assert that the Penal

Laws have been exaggerated to construct a national identity (O’Mahony and Delanty, 2001,

McBride, 2009:215, Kelly, 2011). Indeed, nineteenth and twentieth century nationalists capitalized on a sense of Irish victimhood after the Reformation (e.g., Cobbett, 1829, Moran,

1899, Madden, 1906, MacManus, 1921:455) (O’Mahony and Delanty, 2001, McBride,

2009:215, Kelly, 2011).

By limiting the political presence and land ownership of Catholics, the Penal Laws created an upper class that was predominantly Protestant, and a lower class that was predominantly Catholic (Moody and Martin, 1995:203, Ruane and Todd, 2017:178). While the majority of Protestants were among the poor prior to the mid-eighteenth century (McBride,

2009:131), they were proportionally overrepresented among the landowning class (Solar,

2017:27). While two-thirds of the population was Catholic, 90% of the landowning class was

Protestant (O’Connell, 2007). Among the upper class were the (often absentee) landlords and traders, and among the lower class were tenants, cottiers, and spailpíní, or seasonal laborers

(McBride, 2009:132). Tenants typically shared about thirty to forty acres for cattle grazing among five or six families and managed most of the land in Ireland through long-term leases

(Solar, 2017:28). Cottiers were typically single families who occupied an acre of land for growing potatoes and might have grazing rights in a pasture in exchange for labor for the tenant farmer (Solar, 2017:29). Spailpíní were seasonal migrant workers who traveled within Ireland or

England (McBride, 2009:132). Landlords relied on the labor of the tenants, cottiers, and spailpíní to keep up with the demands of the growing population and market economy, particularly the increasing demands of the British grain market and high birth rate in Ireland (Clarkson and

Crawford, 2001:59).

In the post-medieval period, Ireland experienced unprecedented population growth

(Clarkson and Crawford, 2009:59, Daly 2017:39), which increased the domestic demand for grain. At the same time, there was an increase in exports of meat, butter, and grain. To keep pace, production needed to increase and consumption needed to decrease (Clarkson and

Crawford, 2009:59). The amount of land under cultivation did increase, and so did production, but this increase resulted from an influx of English and Scottish immigrants after the

Cromwellian conquest following the Rebellion of 1641, and not from increased land ownership by the native population. Additionally, some land was kept by private landowners for gardens, parks, and forests, making more of the land that could have been cultivated inaccessible to many of the Irish (Solar, 2017:25).

As the British market economy grew, so did the incomes of the upper class, who charged higher rents as British demands for Irish crops increased (O’Connell, 2007). Ostensibly, Ireland was experiencing a period of economic growth. Between the 1730s and 1815, the national income increased from £15 million to £75 million, and the per capita income increased from £4 to £11 (Clarkson and Crawford, 2001:29). The lower classes, however, did not experience the same economic growth, and in fact, grew relatively and absolutely poorer. According to Sir

William Petty, the top 14% of the population in the 1670s had incomes four times larger than the lower 86% (Clarkson and Crawford, 2001:29). This relationship was maintained through the

1790s, during which time the richest 10% had incomes greater than four times that of the bottom

60%, who lived on less than £5 per year. The remaining 30% in the 1790s was the middle class

(Clarkson and Crawford, 2001:29-30). By 1800, the cottier class had grown and ceased to rely on cash, instead relying on access to small plots of land on which they could grow potatoes

(Clarkson and Crawford, 2001:29-30).

A rising income allowed for increasing diversity of food among landlords and traders, who enjoyed a diet similar to the diet of the aristocracy in England (Clarkson and Crawford,

2001:57). Their diet was also similar to that of early medieval Ireland in that it contained meat, poultry, fish, dairy products, bread and grains, fruit, vegetables, and alcohol. It also contained the relatively new additions of coffee, tea, and sugar (Clarkson and Crawford, 2001:29), all of which were enjoyed with frequency at “parties, and balls and suppers every night in the week” among the upper classes of Dublin (Young, 1779).

As in the preceding periods, food was a symbol of social class in the post-medieval period, and hospitality continued to be an important cultural component. The diversity of food

(e.g., Table 1) available to the upper class, and the opulence with which it was presented to guests is perhaps one of the clearest manifestations of rising social inequality and the increasing wealth gap. During this time, it also became popular for women to record their recipes, providing historians with a written record of favored foods (Shanahan, 2016:198). Main courses would have consisted of both savory and sweet dishes, prepared by a head cook and kitchen staff

(Shanahan, 2016:200, Sexton, 2016:265). Sugar was growing in popularity, and consequently, recipe books were filled with a variety of desserts including cakes, whipped desserts, jellies, biscuits, and macaroons (Shanahan, 2016:202-203). The use of food as a means of communicating social status to peers was so central to social identity that these recipes were often kept secret, and women would go to great lengths to hire cooks trained on the continent to

58 gain a competitive advantage over other wealthy households (Sexton, 2016:265). Social status was also communicated by preparing rich foods high in fat, such as creams (Sexton, 2016:275), and meat, which made up the largest portion of the elite diet in post-medieval Ireland (Adelman,

2017:235). The servants who staffed these wealthy households had a far less elaborate diet, although it was more than adequate when compared to that of the lower classes. House staff were entitled to three meals a day, and records from the Marquis of Kildare’s household book from

1758 indicate that house staff would have consumed several different types of meat, vegetables, bread, butter, and fish (Sexton, 2016:290). Similar to the cottier class, servants typically spoke

Irish instead of English, which would have been the language of the landed family (McBride,

2009:60). Thus, social status was also directly observable and embodied through language.

Table 1: Some of the foods prepared in upper class homes in the post-medieval period

Upper Class Foods Bread Biscuits, French bread, French rolls, ginger bread, soda bread, wheat bread, white bread

Fruit (fresh, Apples, apricots, barberries, blackberries, cherries, currants, damsons, elderberries, figs, dried, gooseberries, lemons, melons, nectarines, oranges, pears, plums, quinces, raspberries, candied, strawberries preserved

Pickled Bass, eels, cauliflower, cockles, herring, kidney beans, lobster, mullet, mushrooms, mussels, foods oysters, pike, salmon, sturgeon, trout, turbot,

Sauces Almond butter, anchovie paste, blood, brown fricassee, brown sauce, butter, crab sauce, cream, cream cheese, eel fricassee, egg fricassee, fish paste, fish sauce, gravy, lobster sauce, new milk, oyster liquor, oyster sauce, pike fricassee, puff paste, rabbit fricassee, rose water, vinegar, white fricassee

Savory Bacon, beef, broiled pigeon, buttered crab, calf’s head pie, carrot pudding, chestnut pudding, chicken, chicken pie, crayfish soup, dressed carp, dressed eel, dressed pike, duck, eel pie, egg pie, goose pie, green pea soup, hake, ham, ham pie, hare pie, hashed calf’s head, kid pie, kidney, lamb, lamb pie, lobster pie, lobster soup, mince pie, mutton, mutton pie, mutton stew, oatmeal, onion soup, oyster omelet, oyster pie, oyster pottage, oyster sausages, oyster soup, oyster-stuffed chicken, oyster-stuffed mutton, pigs’ feet, potato pancakes, potato pie, potato pudding, pork, roasted calf’s head, roast duck, roast goose, roasted lobster, salmon pie, Scotch collops, shrimp, stewed carp, stewed beef rump, stewed ox cheek, tongue, turkey, turnips, turnip soup, veal, veal fillet, vegetable soup

Sides Anchovies, boiled eggs, boiled potatoes, buttermilk cheese, cabbage, carrots, fried oysters, ginger, olives, onions, parsnips, rice pudding, stewed cucumbers, walnuts

Sweet Almond cake, almond cheesecake, almond cream, apple loaf cake, apple pudding, Bath cake, bread pudding, brown bread pudding, cheesecake, custard, icing, lemon cake, lemon cheesecake, lemon and orange cheesecake, lemon cream, lemon pudding, macaroons, macaroon cheese cake, oatmeal pudding, orange cake, orange custard, orange-flower bread, orange pudding, pancakes, plum cake, plum tarts, queen cakes, raspberry cream, saffron cake, seed cake, Shrewsbury cake, strawberry cake, whipped cream

Beverages Balm wine, beer, bitter drafts, black currant wine, cherry brandy, coffee, cowslip wine, elderberry wine, ginger wine, gooseberry wine, lemonade, mead, orange spirits, orange wine, peach brandy, port wine, punch, tea, whiskey, raspberry brandy

In addition to diet, social class was also physically represented in housing, and in the contribution of housing to health, social class was again embodied. Moreover, just as elaborate dishes were used to display one’s social rank, estate houses called Big Houses were also built to display social class both to impress one’s peers and superiors, and to reinstate the control of the landlord over his property (Dooley, 2017:161). This separation of the social classes was

60 maintained both on the property and within the Big House itself. Designated corridors and basements were constructed specifically for the servants so that all but the highest ranking servants would not be seen or interact with the family (Dooley, 2017:162). As displays of wealth,

Big Houses were opulently decorated with fashionable and expensive art, books, and other items associated with the Enlightenment. The construction of these elaborate houses exploded after the implementation of the Penal Laws, which had transferred land from Catholics to Protestants.

Their construction and maintenance was funded primarily through the ever-increasing rents that landlords charged tenant farmers and cottiers (Dooley, 2017:161). For many, the Big Houses came to symbolize dispossession, and as colonial symbols, became targets of violence in the nineteenth and twentieth centuries (Dooley, 2017:162).

The life of an elite inside the Big House, indulging in elaborate meals while surrounded with expensive works of art was unattainable, and perhaps unimaginable, for the lower classes, whose situation grew ever more desperate until the Great Famine. First, while the upper class enjoyed a diversification of food, the consolidation of wealth in the upper class, the shrinking relative income of the lower class, and a greater demand for exports meant that the lower classes experienced decreased dietary diversity. Rising demands for exports diverted resources from domestic consumption, even during periods of scarcity (Solar, 2017:34, Engler et al., 2013).

Meanwhile, the potato was becoming more popular in Ireland. Because potatoes were useful for increasing soil fertility, the demand for potatoes rose with the demand for grain.

Unlike grain, potatoes were difficult to store and were not exported and commercialized in the same way that cereal was (Crawford, 1984). Additionally, the potato requires very little preparation, and can be eaten simply by boiling. Because cottiers frequently possessed only a pot

61 as their sole cooking implement, boiled potatoes were one of the only foods that could be prepared in the home (Adelman, 2017:235).

By the mid-eighteenth century, many of the poor were completely dependent on the potato, occasionally supplemented with milk, buttermilk, herrings, or nettles depending on the season. When potatoes were not available, oatmeal was the sole food for the poor. In the years immediately preceding the famine, dependence on the potato was complete, as milk was being sold for butter rather than consumed by the household (Jackson, 1970, Clarkson and Crawford,

2001:77). Moreover, the consolidation of fishing and hunting rights for exclusive use among the upper classes made wild game and fish inaccessible for most people (Adelman, 2017:235).

According to Clarkson and Crawford (2001), Adelman (2017:234), and Solar (2017:34-35), potatoes eaten in large quantities offer a nutritious diet. They provide energy through starch, as well as potassium, magnesium, iron, vitamins C, B6, and B3, and dietary fiber (Andre et al.,

2014), but are notably deficient in vitamin A (Crawford, 1984). The nutritional value of the potato diet was also opined by contemporary writers. Sinclair (1828) praises the potato for its use as food for both people and livestock, and as fertilizer, and even a treatment for upset stomachs.

When combined with buttermilk, the diet was well-rounded in proteins, carbohydrates, vitamins, and minerals (Crawford, 1984) However, because the consumption of milk decreased as it was sold for butter production (Clarkson and Crawford, 2001:77), the diet of the Irish lower classes gradually became devoid of protein.

In addition to the potential of nutritional inadequacy, dependence on a single crop made the majority of the population in Ireland vulnerable to periods of semi-starvation and famine.

The potato made the Irish particularly susceptible to famine because unlike in the cold, dry climate of the Andes, it could not be stored between seasons in the wet climate of Ireland and did

62 not last for more than ten months (Geber and Murphy, 2012). Starvation and semi-starvation were common for at least a few months out of the year, even when the potato crop was successful (Crawford, 1984). Subsistence crises are documented in 1728-1729, 1740-1741, 1782-

1784, 1817, 1822, 1831, 1835-1837, and 1842 (Faulkner, 1731, 1741, Twiss, 1775, Stourton,

1827, Bish, 1834, Crawford, 1984, Kelly, 1992), and spikes in Dublin food prices and burial registers suggest additional scarcity in the 1760s, 1772-1774, 1794-1796, and 1800-1801 (Daly,

2017:40). The famine of 1740-1741 that resulted from unusually cold weather was particularly catastrophic and affected all of Europe. Conservative estimates suggest that 310,000 of the 2.4 million people living in Ireland at the time died during the 1740-1741 famine (Cox, 2017:264).

While famines did occur prior to the 18th century, the majority of the population was not reliant upon one crop. In an ominous warning that would foreshadow the fate of the Irish in the

19th century, George Faulkner (1731) begs the Lord Archbishop of Cashel for money to build granaries to combat inflation and famine, which he fears will condemn Ireland to ruin and an

“eternity of poverty.” Similarly, Woodward (1772) and Steven (1822) later warn of inevitable famine and subsequent disease that Steven (1822) predicts will kill “tens of thousands.”

The socioeconomic divisions of post medieval Ireland are also evident in the differences in housing between the upper and lower classes. While the upper class enjoyed the comforts of the Big House, tenant farmers had small, efficient houses, and cottiers lived in enclosures that scarcely resembled a house at all. Tenant farmers with at least twenty acres of land typically owned a cottage. These cottages were long rectangular structures divided into two to four rooms.

The occasional upstairs loft provided a separation between people and animals, thereby reducing the risk of disease transmission. The walls were made of stone and lime-washed mud plaster, and

63 together with the thatched roof kept the home reasonably dry. A window and chimney provided an escape for smoke and a source of fresh air (Rowley, 2017:215-216).

The difference in social class and growing social inequality is best demonstrated by comparing the Big House to the Irish hovel occupied by cottiers. Cottiers typically inhabited unsanitary hovels, which comprised one third of all houses in Ireland by 1841 (Rowley,

2017:213). Standard hovels were dug into the side of the road, using the roadside ditch for walls and reinforced with cow dung. Hovels had neither windows nor chimneys, so an opening dug into the front that was used as a doorway was the only way for smoke to escape from the fire that would be lit in the center for both heat and food preparation (Rowley, 2017:215). The only furniture in a hovel was usually the family cooking pot, which could be flipped over and used a table (Adelman, 2017:235). While in the earlier periods, families could build their own furniture, rapid deforestation for intensified cereal cultivation meant that timber was rarely available, except for on preserved hunting grounds (Rowley, 2017:215). There were no separate spaces within hovels, so families and animals all shared the one-room enclosure, and slept together on earthen floors (Rowley, 2017:214-215). These inhabitations were well documented by Arthur

Young (1779) who wrote,

“There are a great many cabins, usually by the roadside or in the ditch, which

have no potato gardens at all…A wandering family will fix themselves under a

dry bank, and with a few sticks, furze, fern, etc. make up a hovel much worse

than any English pigstye, support themselves how they can, by work, begging,

and stealing; if the neighbourhood wants hands, or takes no notice of them, the

hovel grows into a cabin” (183-184).

He later elaborates on housing in the Irish countryside by writing,

“The cottages of the Irish, which are called cabins, are the most miserable

looking hovels that can well be conceived; they generally consist of only one

room. Mud kneaded with straw is the common material of the walls; these have

only a door, which lets in light instead of a window, and should let the smoke

out instead of a chimney, but they had rather keep it in…The roofs of the

cabins are rafters, raised from the tops of the mud walls, and the covering

varies; some are thatched with straw, potato stalks, or with heath, others only

covered with sods of turf. The bad repair of these roofs are kept in, a hole in

the thatch being often mended with turf, and weeds sprouting from every part,

gives them the appearance of a weedy dunghill, especially when the cabin is

not built with regular walls, but supported on one, or perhaps on both sides by

the banks of a broad dry ditch; the roof then seems a hillock, upon which

perhaps a pig grazes…The furniture of the cabins is as bad as the architecture,

in very many consisting only of a pot for boiling their potatoes, a bit of table,

and one or two broken stools; beds are not found universally, the family lying

on straw, equally partook of by cows, calves, and pigs, though the luxury of

styes is coming in in Ireland, which excludes the poor pigs from the warmth of

the bodies of their master and mistress” (Young, 1779:187-188).

These housing conditions undoubtedly disproportionately exposed the cottier class to stressors, especially when compared to the upper class. Living in close proximity to each other and to livestock would have increased their exposure to lice and pathogens (e.g., Bifolchi et al.,

2014, Lupindu et al., 2015) and intermittent famine and damp enclosures would have further elevated their risk for diseases such as smallpox, typhus, typhoid, tuberculosis, and dysentery as

65 malnutrition contributed to low immunity (Daly, 2017:39). Diarrheal illnesses were particularly prevalent for all age groups during food shortages because people would eat seaweed and decomposing animals out of desperation (Daly, 2017:46). In addition to infectious diseases, the poor would have been at a higher risk for mental illnesses such as depression and anxiety, which have been shown to increase during times of food insecurity (Hadley and Patil, 2006, Hadley et al., 2008, Maes et al., 2010, Cole and Tembo, 2011). Infants born during these periods were also more likely to have low birth weights (Bryan Borders et al., 2007), putting them at risk for additional adverse health outcomes and vulnerability to disease if they survived to adulthood.

Even in times of relative food security, children of all social classes were still at a high risk of death from infectious disease; many died from smallpox, tuberculosis, and gastroenteritis

(Buckley and Riordan, 2017:328). Urban poor and illegitimate children were vulnerable to the standard range of infectious diseases, but were also at risk of infanticide and abandonment. Irish infants were particularly vulnerable to infanticide and abandonment because of food insecurity, the social stigma of pregnancy out of wedlock, and the illegalization of abortifacients. By 1725, the frequency of child abandonment was so high that the Dublin workhouse, previously established to take in children between five and sixteen years, allowed the admission of children under the age of five, and its name was changed to the Dublin Foundling Hospital and

Workhouse (Buckley and Riordan, 2017:336). Despite these initial efforts, conditions in the

Foundling Hospital and Workhouse were not much better than life outside the workhouse.

Infants and children in the workhouses were subject to abuse, malnutrition, rampant disease, and exposure to rats, fleas, and lice inside cold, dirty, and damp rooms (Buckley and Riordan,

2017:336). The workhouse was initially developed with the plan that children would attend school while in the workhouse, but in actuality, children rarely received any education while

66 institutionalized (Buckley and Riordan, 2017:337). In 1737 and 1743, officials estimated that infant mortality inside Dublin Foundling Hospital and Workhouse was 75% (Buckley and

Riordan, 2017:336), a number that is highly suggestive of the early life experiences of many institutionalized children in post-medieval Ireland.

Biocultural Political Economy of Irish History

This review of Irish history within a biocultural political economy framework has demonstrated that each new historical period was preceded by local conflict situated within a broader context of global conflict. The power struggles among the early Irish kingdoms, the

English monarchy, and the Anglo-Norman lords were particularly instrumental in the colonization and subsequent shifting of local systems of government, production, and consumption. Later, the separation of the Anglican Church from Rome, the 1641 Irish Rebellion, and the Cromwellian Wars were instrumental in the writing of the Penal Laws and shaping of the social hierarchy in post-medieval Ireland. Each of these regional and local conflicts were situated within the broader context of global imperialist power struggles, particularly among Western

European powers including England, Spain, and France.

These conflicts were influenced by, and in turn contributed to, an overarching ideology.

The separation of the Anglican Church from Rome was especially instrumental in the shaping of ideology in Western Europe during the early post-medieval period. Initially, the separation of the

Anglican Church from Rome was fueled by the belief of a sovereign monarch, whose authority was granted directly by God and not indirectly through the Pope. This ideology, in addition to the belief in a superior English culture and economy led many English to believe that they had a moral obligation to change the religion and behavior of the Irish Catholics.

Later, the Enlightenment represented an ideological shift in which the monarch was no longer viewed as a direct appointee by God. Rather, people began to believe that power of the monarch was at the mercy of the people, and that the monarch’s power should be checked by a parliamentary body. This ideological shift fueled further conflict because Catholics had generally been loyal to monarchs whose power was sanctioned by the Pope. Catholics were therefore perceived as posing a threat to the unalienable rights of the populous to check the power of the monarch.

These ideological shifts contributed to regional politics by influencing the laws written to prevent perceived threats to these belief systems. For example, the Penal Laws were written to prevent a Catholic uprising, which many feared that if successful, would challenge the right of the populous to check the power of the monarch through a representative parliament. Local and regional political systems controlled access to knowledge by dictating who was and was not entitled to education and which languages were worthy of print, and in doing so, reproduced the predominant ideology. Moreover, laws that controlled land ownership further contributed to the reproduction of the predominant ideology of a superior Protestant class by pushing the predominantly Catholic lower classes further into poverty. An impoverished lower class of

Catholics seemed to prove their perceived natural inferiority, thereby maintaining the dominant ideology and perpetuating a cycle of poverty.

Global, regional, and local systems of production, consumption, and politics operationalized ideology, and in doing so, exposed people of differing socioeconomic statuses to different stressors by influencing what people ate and where they lived. According to the

DOHaD, exposure to stressors, particularly in early development, can result in heritable changes to phenotype. It is therefore possible that differential exposure to stressors during the post-

68 medieval period resulting from shifting ideologies and sociopolitical and economic circumstances contributed to heritable changes in health that made the population more vulnerable to death during the Great Famine.

Emergence of Irish Nationalism, Revisionism, and Post-Revisionism

While by the time of the Act of Union in 1801 Catholics were still prohibited from holding higher offices, sitting in Parliament, or serving as colonels or captains in the army and navy, respectively, most of the Penal Laws had been repealed and Catholics were permitted to vote (Whyte, 1995:248-250). Catholic politician Daniel O’Connell capitalized on the Catholic right to vote by creating the Catholic Association in 1823. By charging Irish Catholics one penny per month, he stimulated widespread interest in a revolutionary movement and facilitated the development of a united Catholic voting body. Members of the Catholic Association turned out en masse to vote in the 1828 election for Daniel O’Connell. As a Catholic, O’Connell could not sit in parliament, but there was no specific law forbidding him from running as a candidate

(Whyte, 1995:252). This show of force by the Catholic Association pressured liberal heads of

British government into introducing a successful bill of Catholic Emancipation in 1829 (Whyte,

1995:254-5). In the 12 years that liberals held the majority in Parliament, the Catholic Church regained some of the power that had been lost in the preceding centuries, and Catholicism emerged as a central characteristic to Irish nationalist identity (Cusack, 2001).

When conservatives regained the majority in Parliament, liberals feared that they would overturn Catholic Emancipation. In the last few years before the Famine, O’Connell founded the

Repeal Association with the goal of forming Ireland’s own parliament and preventing the repeal of Catholic Emancipation. The Repeal Association relied on Catholic clergy as community

69 organizers (Whyte, 1995:256), and in doing so, cemented the relationship between Catholicism and Irish nationalism. The start of the Famine in 1845 and O’Connell’s death in 1847 marked the end of the repeal movement.

After the Famine, those who had survived generally equated the union of Britain and

Ireland with poverty, tragedy, and other national grievances that they perceived to have been ignored. This spurred the foundation of yet another nationalist organization, the Irish Republican

Brotherhood (I.R.B.)/Fenian organization (Moody, 1995:276). The Fenian movement differed from O’Connell’s movements in that while most members were Catholic, they were also critical of the Church and advocated for separation of church and State (Moody, 1995:279). The Fenian movement gained popularity among the Irish diaspora in America, and under the leadership of

Charles Stewart Parnell, morphed into an Irish political party. As the leader of the Irish political party, Parnell advocated for Home Rule until his death in 1891 (Moody, 1995, 290-92). A second attempt to pass a bill for Home Rule was made by W.E. Gladstone in 1893, but while this bill passed the House of Commons, it failed in the House of Lords (Moody, 1995:293).

The nationalist movement was evident not just in politics, but in literature, language, and sports as well (O’Mahony and Delanty, 1998, McCartney, 1995:294-7). A number of nationalist

Irish poets and other writers worked to revive and romanticize stories of early Ireland, before the arrival of the English, thereby hoping to create an entire new national literary genre. Similarly, members of the Gaelic League strove to once again make Irish the national language of Ireland, and the Gaelic Athletic Association sought to revive national games like rugby. This nationalist cultural revival was fueled by widespread nationalist sentiment across Europe, where it was generally agreed that culturally-distinct groups should be permitted to be politically independent states (McCartney, 1995:297). Contemporary political groups influenced by the Gaelic Revival

70 movement included Sinn Féin who asserted that the 1801 Act of Union had been illegal

(McCarthey, 1995:298).

For some, the revival of Irish heroes and legends served to memorialize nineteenth century nationalists like O’Connell and Parnell as real-life Cú Chulainns. Cú Chulainn is a character from an Irish epic poem. Son of the god Lugh and a mortal mother, Cú Chulainn is born with superhuman strength. The king Conchobar sees Cú Chulainn playing a game of hurling where the two meet. Later, a druid named Cathbad prophesizes that whoever takes the king’s weapons will have a short but famous life. Seven-year-old is handed weapon after weapon, but each of them break under his superhuman strength until he is finally handed

Conchobar’s weapons. He goes on to defend Ulster from an invasion by Connacht. To avenge the deaths of those he killed during his defense of Ulster, Cú Chulainn is mortally wounded, but before he dies, he ties himself to a stone so that he can die standing and facing his enemies. To

Gaelic revivalists and other nationalists, O’Connell, Parnell, and other nationalist political figures were mythologized as akin to Cú Chulainn, defender of the Ulster, the last Gaelic stronghold (Veldeman, 2009, Lee, 2019).

Meanwhile, opponents of the I.R.B. and Sinn Féin were organizing in the North. The

Ulster Volunteers were formed in 1913 and planned to defend Ulster against the Irish nationalists should home rule become the law. Also known as Orangemen, the Ulster Volunteers swore their loyalty to England and celebrated the memory of William of Orange, the Protestant English king who had defeated the Catholic James II at the Battle of the Boyne.

Fearing that they would die in World War I before home rule was achieved, the I.R.B. initiated an insurrection before the end of the War (McCartney, 1995:306-7). This insurrection, known as the 1916 Easter Rising, began when members of the I.R.B. and the Irish Citizen Army

71 seized strategic locations in Dublin and declared the existence of an independent Irish Republic.

The insurrection was quickly stopped when the British government declared martial law (Foy and Barton, 2011, McGarry, 2011). In all, it is estimated that over 400 people were killed, most of whom were civilians killed by the heavy artillery of the British Army (McGarry, 2011).

Thousands of people were injured, thousands more arrested, and ninety of the rebels were executed. Instead of suppressing the home rule movement, the overwhelming response of the

British Army resulted in yet more support for Sinn Féin and other nationalist organizations

(McCarthey, 1995:310).

The period following the Easter Rising and the continued support of Sinn Féin was characterized by violence in the forms of guerrilla warfare, targeted assassinations, arsons, ambushes, and raids (McCarthey, 1995:311). A peace treaty was signed in 1921 between Britain and Ireland when Britain granted Ireland the right to home rule (McCarthey, 1995:312) and established the Irish Free State (McCraken, 1995:315), but kept the Irish Free State within the

British Commonwealth (Lynch, 1995:329). While members of Sinn Féin supported the Anglo-

Irish Treaty, members of an opposing nationalist organization, the Irish Republican Army

(I.R.A.), believed that Ireland needed to completely end its relationship with Great Britain

(Perry, 2010).

A period of relative peace followed, but in the meantime, Protestants in Northern Ireland, which had been given the option to opt out of the Irish Free State, continued to reject home rule on the basis that they believed it was Catholic home rule, not Irish (McCracken, 1995:313).

Generally, Catholics supported a united Irish Free State, and Protestants supported keeping

Northern Ireland under British rule (Whyte, 1995:343). The divide between the two groups continued to grow through the twentieth century and was institutionalized through intermarriage

72 prohibitions, separate education, and segregated housing (Whyte, 1995:343), separated by barbed wire fences (Cochrane, 2013:70). Discrimination against Catholics prompted the formation of the Northern Ireland Civil Rights Association (NICRA) in the 1960s (Perry, 2010), and hostilities between republicans and loyalists spurred the formation of several paramilitary groups including the Provisional Irish Republican Army (Provisional I.R.A.), Ulster Defence

Association (UDA), and the revival of the Ulster Volunteers (Cochrane, 2013:68). Tensions between republican and loyalist paramilitaries resulted in years of increasingly severe episodic violence. The year 1970 saw 213 shootings and 170 bombings in Northern Ireland with 25 fatalities. These incidents increased in 1971 to 1,700 shootings, 1,500 bombings, and 174 fatalities, and in 1972 to 10,500 shootings, 1,800 bombings, and 476 fatalities, including those that occurred on Bloody Friday (Cochrane, 2013:70). Following Bloody Friday, the British

Army sent an additional 22,000 troops to Northern Ireland, marking a nearly twenty-year period of direct rule (Cochrane, 2013:79). A ceasefire was declared in 1994, but intermittent violence continued to break out in 1996-1997. Finally, in 1998, the Good Friday Agreement marked the end of the armed conflict in Northern Ireland, and in 2005, the I.R.A. ruling body promised to rely on democratic processes rather than violence to achieve its goals (Perry, 2010).

Irish historians and other academics in the last decades of the twentieth century blamed nationalist historical narratives (e.g., Jackson, 1970) for the violence that characterized the 1920s and 1970s. In an effort to ensure that such violence would not be repeated, academics sought to create a version of Irish history free of values moral triumph, and perhaps most importantly, free of the nationalist narrative of Ireland as a victim of over 700 years of British oppression

(O’Mahony and Delanty, 1998, Perry, 2010). This revisionist history sought to examine

73 historical materials through a purely empirical lens and reflect on the construction of Irish liberation as nationalist mythology (Curtin, 1996, Perry, 2010).

Revisionist historians (e.g., Edwards and Williams, 1957, O’Mahony and Delanty, 1998) dominated Irish academia through the 1990s, but in the mid-1990s, a school of post-revisionists emerged (O’Mahony and Delanty, 1998). These post-revisionists argued that in ignoring

Ireland’s struggles against Britain, revisionists were actually supporting British imperialism and excusing violence against Irish civilians. Moreover, post-revisionists argued that revisionists dismissed the cultural trauma of cataclysmic events such as the Great Famine (Perry, 2010).

Bioarchaeology can contribute to the revisionist and post-revisionist debate by revealing the biological effects of historical circumstances.

Chapter 4: Methodological Background

According to the biocultural political economy framework, global, regional, and local systems of politics, production, and consumption contribute to the embodiment of belief systems by exposing people of different socioeconomic statuses to different stressors. Moreover, the

Developmental Origins of Health and Disease (DOHaD) hypothesis suggests that exposure to stressors during early development can contribute to adverse health outcomes in adulthood.

However, observation of health in bioarchaeology is problematic because health cannot be directly inferred from human remains. This chapter will therefore first review the challenges of inferring health from skeletal remains. Second, this chapter will highlight the ways in which stress contributes to health. Finally, this chapter will describe how bioarchaeologists can draw conclusions about health from skeletal remains.

Health in Bioarchaeology

One of the limitations of using skeletal remains to draw conclusions about cultural and sociopolitical circumstances in the past is that the nature of skeletal remains makes it difficult to infer health. As skeletons in the bioarchaeological record belong to the deceased and are often incomplete, bioarchaeologists are only able to glimpse a fraction of a person’s life as manifested through their skeletal biology. Thus, while the biocultural perspective highlights the link between culture and health, bioarchaeologists have long struggled to make inferences about health in the past, thereby further limiting their ability to draw conclusions about past cultural circumstances.

This struggle began with the use of skeletal indicators as direct signs of health or status in the populations from which the skeletons were derived (e.g., Lanphear, 1990 Danforth et al., 1994,

Hodges, 1997). This perspective treated health as the absence of visible illness, a viewpoint that was challenged by researchers such as Bocquet-Appel and Masset (1982). Their critiques culminated in the landmark publication by Wood and colleagues in 1992 in what became known as the osteological paradox. According to Wood et al. (1992), there are several problems that confound the relationship between the skeletal sample and its associated population, namely, demographic non-stationarity, selective mortality, and individual level heterogeneity in frailty.

In pointing out demographic non-stationarity, Wood and colleagues (1992) argued that traditional bioarchaeological studies assume that populations are static. In reality, they argue, populations are constantly experiencing migration and/or changes in mortality and fertility. This is particularly problematic when evaluating the prevalence of skeletal lesions or the number of deceased infants. For example, if a population is growing, the prevalence of skeletal lesions will increase simply because there are relatively more people who have the potential to fall victim to the conditions that produce the skeletal lesions. Similarly, if a population is growing, the life expectancy will appear to decline simply because there are more infants and young children in the cemetery, not because of increased mortality risk, but because of increased fertility. An increase in fertility means there are more children who have the potential to fall victim to the typical threats of childhood (Wood et al., 1992).

The second challenge, selective mortality, is the idea that an individual or subgroup of a population is unlikely to be representative of the population level risk of mortality. Instead, it is individuals who have the highest frailty who are most likely to die at a given age, and therefore,

76 it is the individuals with the highest frailty who comprise a given age group within a skeletal sample (Wood et al., 1992).

The third challenge is hidden heterogeneity in frailty. That is, individuals have unequal risks of death and vulnerability to diseases and other stressors (Wood et al., 1992). This means that the individuals exhibiting skeletal lesions had skeletons that were most vulnerable to those lesions. In other words, it is possible a condition may produce a physiological reaction that results in a skeletal lesion in one person and not another. This heterogenous frailty results from hormonal differences, variation in nutritional status, heterogenous environmental conditions, immune system differences, parental circumstances, among others (Wood et al., 1992).

The message that many bioarchaeologists seemed to take away from the osteological paradox is that the presence of skeletal lesions cannot be used to infer poor health. Some bioarchaeologists chose to adamantly argue against the osteological paradox (e.g., Cohen, 1994).

Other bioarchaeologists chose to ignore its existence entirely, as noted by Sołtysiak (2015) and

DeWitte and Stojanowski (2015). Others, instead of using the arguments published by Wood and colleagues (1992) to draw more nuanced conclusions about health in the past, replaced the term

“health” with “stress.” That is, instead of treating the absence of skeletal lesions as indicators of good health as they had done before, bioarchaeologists used the presence of skeletal lesions as indicators of stress. This was usually done without articulating the connection between stress and health, and populations were studied as either more or less stressed (e.g., Malville, 1997,

DeLeon, 2007, Hoover and Matsumura, 2008, Petersone-Gordina et al., 2013).

There are additional challenges to making inferences about health in the past that are described in other works beyond the limitations articulated by Wood and colleagues (1992). For instance, health is often affected by conditions and circumstances that do not leave any trace on

77 the skeleton. In most cases, acute stressors are unable to produce skeletal lesions, either because the individual does not survive, or because the stressor is of such a short duration that the skeleton does not respond (Goodman et al., 1988, DeWitte and Stojanowski, 2015).

Yet another challenge to bioarchaeology is the fact that health, in part, is culturally defined (DeWitte and Stojanowski, 2015). Because societies differ in what they consider to be healthy or unhealthy, the skeletal lesions on a skeleton might not correspond to a socially identified condition. This is exemplified in a study by Piperata and colleagues (2014) on the association between anemia status and self-perceived health. While they hypothesized that individuals with anemia would also report perceptions of poor health, they that the majority of the individuals in their study who reported poor health were not anemic (Piperata et al., 2014).

The dissonance between socially and biologically identified conditions could cause bioarchaeologists to ascribe more cultural meaning to an observed condition than the condition merited during life. Because the definition of health is in part, self-defined, then such dissonance limits the ability of bioarchaeologists to interpret health given its current definition.

Finally, the bioarchaeology of children is faced with its own set of challenges, and because this dissertation operationalizes indicators of childhood stress to infer health, it is important to address these limitations. First, the concept of childhood itself varies across time and between cultures, and even in bioarchaeology itself (Lewis, 2007:4). The challenge for bioarchaeologists is therefore to correlate biological data with culturally meaningful time periods. For example, if stable isotope analyses suggest a high quantity of marine resources in the diet of a ten-year-old, this finding cannot inform interpretations of childhood diet unless that ten-year-old was socially understood to be a child and not an adult during the time period and society in which he or she lived. In other words, even if a bioarchaeologist compares a skeletal

78 trait like stable isotopes between 10-year-olds from different sites, it can only be inferred that isotope levels were similar or different between 10-year-olds, not among individuals socially identified as children. Second, children are far less likely to leave written accounts of themselves or maintain written records (Buckley and Riordan, 2017:326), which poses a unique challenge to historical bioarchaeologists. Third, the bioarchaeology of children has lagged behind bioarchaeology as a whole until a wave of feminist theory in the 1990s suggested that children played a meaningful role in past societies (Thompson et al., 2014:1-2). Prior to the 1990s, bioarchaeologists used children only when they could not otherwise explain the presence of certain artifacts, or when conducting studies of past fertility and growth Thompson et al.,

2014:5). That is, if there was an assemblage of poorly made tools, bioarchaeologists would assume they were made by children, and only then would their presence be taken into account

(Thompson et al., 2014:5). Finally, the children present in the bioarchaeological record represent only a small subset of children in the population. Unless children die, they are otherwise invisible in the bioarchaeological record. While child mortality was high in the past, it cannot be assumed that subadult skeletal remains are representative of the living children in a given society

(Wood et al., 1992).

Despite these challenges, some bioarchaeologists have tried to address the limitations of the osteological paradox (DeWitte and Stojanowski, 2015) and the bioarchaeology of children

(e.g., Beaumont et al., 2015) in their methodologies (DeWitte and Stojanowsi, 2015). One means of addressing the limitations of the osteological paradox, particularly for the bioarchaeology of children, is to treat skeletal subadults as non-survivors (DeWitte and Stojanowski, 2015) and adult skeletons as survivors, or members of a population who survived childhood (e.g.,

Beaumont et al., 2015). While these studies are limited in providing direct evidence of adult

79 health, the conceptualization of adults as children who survived can aid in understandings of childhood health.

Others have adopted frameworks from modern human biology to link health, frailty, and stress (Reitsema and Kyle McIllvaine, 2014 ) (e.g., Marklein et al., 2016, Gawilkowska-Sroka et al., 2017, Marklein and Crews, 2017). For example, bioarchaeologists (e.g., Watts, 2015,

Marklein et al., 2016, Gawilkowska-Sroka et al., 2017, Marklein and Crews, 2017) have begun to frame their research in terms of the DOHaD and allostasis.

According to the DOHaD hypothesis, early exposure to stress can affect adult and intergenerational health by creating heritable changes to phenotype across multiple organ systems through prolonged allostasis (re-calibration of multiple organ systems to cope with a stressor) (Gillman, 2005). These phenotypic changes can modify how the body responds to subsequent stressors and can result in under- or over-responsiveness of the HPA axis (Edes and

Crews, 2017), and changes to brain development and the immune system (Vaiserman 2015).

Consequently, prolonged allostasis can contribute to allostatic load and limit the body’s ability to overcome stressors and therefore make the individual more vulnerable to subsequent morbidity and mortality (Edes and Crews, 2017).

Among living people, allostatic load is measured using allostatic load indices, which can also predict an individual’s vulnerability to disability and mortality (Grunewald et al., 2009).

These indices generally comprise deficits (e.g., cognitive decline, grip strength, unwanted weight loss) and multiple biomarkers that can include systolic and/or diastolic blood pressure (e.g.,

Kubzansky et al., 1999, Singer and Ryff, 1999, Seeman et al., 2001, Karlamangla et al., 2002,

Seeman et al., 2002, Crimmins et al., 2003, Evans, 2003, Schnorpfeil et al., 2003, Weinstein et al., 2003, Hellhammer et al., 2004, Grunewald et al., 2006, Crimmins et al., 2007, Grunewald et

80 al., 2012), BMI (e.g., Crimmins et al., 2003, Goldman et al., 2005, Geronimus et al., 2006,

Crews, 2007, Crimmins et al., 2009, Grunewald et al., 2012), cardiovascular fitness (e.g.,

Worthman and Panter-Brick, 2009), cholesterol (Seeman et al. 2001, Seeman et al., 2002,

Crimmins et al., 2003, Geronimus et al., 2006, Grunewald et al., 2012), cortisol (e.g., Seeman et al., 1997, Singer and Ryff, 1999, Seeman et al., 2001, Grunewald et al., 2006, Grunewald et al.,

2012), glucose (e.g., Kubzansky et al., 1999, Seplaki et al., 2004, 2005, Grunewald et al., 2012), heart rate (e.g., Von Thiele et al., 2006, Seeman et al., 2008, Hasson et al., 2009, Maloney et al.,

2009, Grunewald et al., 2012), insulin (e.g., Goldman et al., 2005, Crews, 2007, Maloney et al.,

2009), insulin resistance (e.g., Li et al., 2007, Grunewald et al., 2012), peak respiratory flow

(e.g., Crimmins et al., 2003, Seeman et al., 2004, Allsworth et al., 2005, Lindfors et al., 2006,

Johansson et al., 2007), pressor response (Von Thiele et al., 2006), pulse (e.g., Crimmins et al.,

2007, 2009), subscapular skin folds (e.g., Crews, 2007) and waist-hip ratio (e.g., Seeman et al.,

1997, 2001, 2002, 2008, Grunewald et al., 2012) that are noted during clinical examinations.

Clearly, these biomarkers cannot be measured in skeletal samples but bioarchaeologists can use frailty, as indicated by stress markers, to draw inferences about stress that could have contributed to allostatic load and to overall health. Importantly, identifying frailty through stress markers is not necessarily straightforward in the skeleton because according to the osteological paradox, stress markers, or their absence, can be indicators of both frailty (i.e., vulnerability) and resilience (i.e., adaptive success) (Wood et al., 1992, Kyle et al., 2018). If stress markers are absent, then it could be because the person died before evidence of the stressor could appear on the skeleton (Wood et al., 1992). In this case, the absence of a stress marker would be an indicator of frailty (Kyle et al., 2018). It is also possible that the absence of a stress marker indicates that the person was not exposed to the stressor at all (Wood et al., 1992, Kyle et al.,

2018). In this case, the absence of a stress marker would not necessarily indicate either frailty or resilience. If a stress marker in the skeleton is present, it shows that the person was exposed to a stressor, experienced it, and overcame it long enough for a stress marker to form. In this case, the stress marker would be an indicator of resilience. While they can be indicators of both resilience and frailty, the way in which skeletal stress markers are interpreted is dependent on the biocultural context (Kyle et al., 2018), including economic, historical, political, and social factors.

Thus, in conjunction with the conceptualization of adults as children who survived and a rich historical record, the allostatic loading framework and DOHaD hypothesis can provide means by which to infer childhood health and assess frailty in the past if the following assumptions are made:

1. Childhood stress contributes to adult health.

2. Stressors that occur during childhood and fetal development can lead to the learned

over- or under- responsiveness of physiological stress response through

catecholamine-mediated emotional imprinting and epigenetic modification of

glucocorticoid receptors.

3. Dysregulation (i.e., over- or under-responsiveness) limits the body’s ability to

overcome later challenges, thereby increasing the risk of death.

4. Therefore, children who experience more stress than their peers become adults who

are less able to overcome stressors and more likely to succumb to death before other

members of their age cohort.

Thus, according to the DOHaD hypothesis and allostatic load framework, it is expected that adults who died younger experienced more stress as children than adults who died at older

82 ages, if independent factors such as accidents, infectious disease outbreaks, and violence are excluded. Indeed, multiple studies among living people have found that children who experienced adverse life events (e.g., abuse, domestic violence) (Brown et al., 2009, Kelly-Irving et al., 2013, Chen et al., 2016, Lee et al., 2019) or illness (Buck and Simpson, 1992) were more likely to die earlier as adults relative to people who had not shared those early adverse experiences, even when socioeconomic status was controlled for. Similarly, numerous studies have found an association between impaired fetal growth, which is symptomatic of prenatal stress, and decreased longevity (e.g., Duray, 1996, Moore et al., 1997) (Humphrey and King,

2000). Slowing of fetal growth can contribute to decreased longevity by impairing organ growth

(e.g., lungs, heart, pancreas, etc.), thereby contributing to disruptions across multiple organ, metabolic, and immune systems (Humphrey and King, 2000) (e.g., Dutz et al., 1975, Chandra,

1991).

However, the role of childhood stress in adult longevity is not completely causal. For example Lee and colleagues (2019) write that adults from unsupportive families and from families with poor role models in which children are more likely to be exposed to psychosocial stress in the first place are less able to develop appropriate socioemotional responses to stressful situations. Consequently, it could be that people who experienced adverse childhood events without exposure to a model of an appropriate stress response are less able to cope with stressful situations as adults (Lee et al., 2019). Thus, it could be that the failure to learn socially and emotionally appropriate stress responses amplifies the individual’s perception of a stressful event, and therefore the stress events that occur in adulthood contribute more to decreased longevity than the original childhood experiences themselves (Lee et al., 2019). Moreover, in their study of the relationship between early psychosocial stressors, socioeconomic deprivation,

83 supportive personal relationships, optimism, and longevity, Lee and colleagues (2019) found that optimism protected individuals who had experienced adverse childhood events against decreased longevity. In other words, when adults maintained a sense of optimism, they did not experience a shortened life, event when they had experienced stressful events as children (Lee et al., 2019).

Studies of morbidity and mortality among adults with known early life circumstances provide the most reliable means by which to elucidate the relationship between early life stress, adult health outcomes, and longevity, but even conclusions drawn from these studies are limited to populations with well-documented early life health records (Humphrey and King, 2000).

Thus, it is unclear if the association between early life stress and longevity is universal. Studies of the relationship between early life stress and longevity in past populations are even more limited because the type, cause, and duration of early stress in an individual is usually unknown, as is the cause of death (Humphrey and King, 2000).

Despite these limitations, studies of past populations suggest a relationship between early stress and longevity (e.g., Rose et al., 1978, White, 1978, Cook and Buikstra, 1979, Clark et al.,

1986, Goodman and Armelagos, 1988, Duray, 1996, Palubeckaitë et al,. 2002, Kemkes-

Grottenhaler, 2005, Steckel, 2005, Boldsen, 2007, Stodder, 1997, Watts, 2013). For example,

Clark and colleagues (1986) found that adults with smaller neural canals (an indicator of developmental stress) had a younger age-at-death. In another study, Rose and colleagues (1978) found that individuals with at least one Wilson band died between 11.8 to 25 years earlier than individuals with no Wilson bands. Similarly, Steckel (2005) found that individuals with at least two linear enamel hypoplasia (LEH) died earlier than those without LEH, and Palubeckaitë and colleagues (2002) found that individuals with more numerous or more severe LEH died earlier than those with fewer or less severe LEH. However, some studies have found no relationship

84 between LEH and longevity (Saunders and Keenleyside, 1999), and others have found a positive correlation between LEH and age-at-death (e.g., Lewis, 2002, Bennike et al., 2005, Garcia,

2007).

While results have been mixed, the DOHaD hypothesis suggests that because early life stress disrupts multiple developing systems, it can be expected that early life stress is associated with decreased longevity. That is, it can be expected that adults who died younger experienced more stress that contributed to childhood health and overall frailty. In this way, it should be possible for age-at-death in skeletal remains to be operationalized as an indirect measure of frailty and childhood health that can be used to infer allostatic load.

Teeth as Indicators of Past Health

In addition to disrupting development of the HPA-axis and compromising adult longevity

(Edes and Crews, 2017), childhood stress can also disrupt dental development (e.g., Goodman and Rose, 1990). Bioarchaeologists can, and often do, therefore use dental defects (e.g., linear enamel hypoplasia) to make inferences about childhood health (e.g., Paulubeckaitė et al., 2006,

Oxenham, 2008, Šlaus, 2008, Geber, 2014, 2015, Watts, 2015, Novak et al., 2017, Kyle et al.,

2018, Primeau et al., 2018, 2019, Minozzi et al., 2020). Stress markers in dental enamel are particularly useful when investigating childhood stress because unlike bone, enamel does not remodel. Thus, disruptions to enamel growth caused by physiological stress during development remain visible as enamel defects on a tooth into adulthood, provided that they are not erased by dental wear. Teeth therefore provide yet another way to interpret the adult skeleton as an “ex- child;” furthermore dental defects present on the adult skeleton are representative of childhood

85 stress, and therefore provide another indirect measurement of allostatic load in childhood because they represent a time in the person’s life when their body had to confront a stressor.

Linear enamel hypoplasias (LEH), like other types of enamel defects, have been used to make inferences about stress during childhood and will be used as indicators of childhood stress in this dissertation. Because LEH represent deviations from normal enamel development, it is necessary to first review normal enamel development.

Amelogenesis (i.e., enamel formation) occurs in three phases (Nanci, 2013:128). The first phase of amelogenesis is the secretion of a protein matrix (Hillson, 2002:148). Ribosomes on the membrane of the rough endoplasmic reticulum (rough ER) of the ameloblast (i.e., enamel forming cell) translate mRNA for enamel proteins, namely, amelogenin, ameloblastin, enamelin, matrix metalloproteinase 20 (MMP20), and tuftelin (Smith 1998, Sierant and Bartlett, 2012).

Proteins travel to the cisternae of the rough ER and through the Golgi complex where they are packaged into condensing vacuoles. The hydrophobic lipid bilayer of the condensing vacuoles allows them to move through the ameloblast, carrying proteins and water toward the Tome’s

(i.e., apical) process to become secretory granules (Smith, 1998, Bartlett, 2013, Nanci 2013:144).

The proteins then become partially mineralized as they are secreted in the extracellular space against the dentine mantle to form microstructures called enamel rods (Smith, 1998) that represent the path of the ameloblasts during this secretory phase of enamel formation.

The second phase of amelogenesis is mineralization via hydroxyapatite crystal deposition

(Hillson, 2002:148), which is facilitated by three of the proteins secreted during the initial phase of amelogenesis: amelogenin, enamelin, and ameloblastin. These proteins are secretory calcium- binding phosphoproteins (SCPPs) which guide calcium phosphate (CaPO4) from the bloodstream to the extracellular matrix. Simultaneously, the ameloblasts retract their Tome’s processes,

86 decrease their secretory activity, and increase ion transport activity, resulting in crystallization of the enamel rods (Smith, 1998, Moffatt et al., 2014).

The final phase of amelogenesis is maturation. The maturation phase is characterized by the degradation of proteins by serine proteinase (KlK4) that cleave amelogenins into smaller peptide units (Smith et al., 2009), which are then resorbed by the ameloblasts (Smith, 1998). This allows the rod and interrod crystallites to expand and harden. As the rods expand, they compress the remaining Tome’s processes, which are eventually obliterated (Nanci, 2013:138).

These rods are generally perpendicular to the dentin, but their course changes throughout the crown. In the cervical enamel, for example, the rods run horizontally, whereas in the cuspal enamel, the rods run more vertically. In both the cervical and cuspal enamel, the rods bend slightly in their course (Nanci, 2013:155). Rod formation follows a diurnal rhythm, a pattern that is reflected in daily cross-striations, or short period lines that run perpendicular to enamel prisms.

These short period lines represent 24 hours of enamel development (Risnes, 1986, Smith, 2006,

Smith and Tafforeau, 2008, Antoine et al., 2009), i.e., a circadian rhythm (Mahoney et al., 2016).

Structural alterations of the enamel rods are thought to results in striae of Retzius (Nanci,

2013:156). These are long-period incremental markings in enamel (Witzel et al., 2008:400-401) that represent one layer of enamel (Mahoney et al., 2016) and manifest on the surface of the tooth as perikymata (Guatelli-Steinberg, 2001). In humans, these long-period lines form according to regular periodicity of 6-12 days across individuals, but with all the teeth of each individual adhering to a single periodicity (FitzGerald, 1998).

Enamel defects are classified as pits, horizontal grooves (LEH), vertical grooves, or missing enamel (Hillson, 2002). For the purposes of the present study, only LEH will be described here. LEH are non-specific indicators of stress caused by disease, malnutrition, trauma,

87 and/or inherited conditions (Goodman and Rose, 1990) that disrupts the ameloblasts during the secretory phase (Suckling et al., 1986). It is thought that during a stress event, ameloblasts reduce enamel secretion (Witzel et al., 2008). If the individual survives, enamel growth continues normally after the stress event passes, but a line or groove of reduced enamel thickness remains. Consequently, LEH are often used in anthropology as indicators of health among hominin ancestors and in archaeological and modern human populations (Skinner and Goodman,

1992:153) (e.g., Rose and Armelagos, 1978, White, 1978, May et al., 1993, Skinner, 1996,

Guatelli-Steinberg, 2004, Slauš, 2008, Geber, 2014) as well as in non-human primate populations (e.g., Guatelli-Steinberg, 2000, Hannibal and Guatelli-Steinberg, 2005, Guatelli-

Steinberg and Benderlioglu, 2006, Guatelli-Steinberg et al., 2012).

Not all stress events, however, produce an LEH. The formation of an LEH is dependent on the age of the ameloblasts affected, the duration and timing of a stress event, the severity of the stress event, and possibly, sex (Figure 3).

Figure 3: Conditions required for the formation of an LEH

The age of the ameloblasts at the time of the stress event influences the formation of LEH by affecting whether or not the ameloblasts resume activity after a stress event. Witzel and colleagues (2008) found that the ameloblasts that were still young enough to possess the distal portion of their Tome’s process resumed secretory activity after the end of the stress event.

During the maturation phase of amelogenesis, the Tomes’ processes are gradually eliminated as the enamel rods expand into the space occupied by the Tomes’ processes (Nanci, 2013:138).

After the removal of the Tomes’ processes, the ameloblasts are no longer able to resume the secretion of enamel, and an LEH will not form. Additionally, if the ameloblasts on the enamel front are entering the transition state prior to the maturation stage (i.e., if the secretory ameloblasts are older) they may apoptose, therefore decreasing the number of ameloblasts on the

89 enamel front that are capable of resuming secretory activity after a stress event (Witzel et al.,

2008). Thus, late state secretory ameloblasts are the most vulnerable to stress events because they can apoptose or lose their Tomes’ processes (Witzel et al., 2008).

Second, the formation of an LEH is dependent on the timing of the stress event, and in particular, whether the enamel being formed at a given time is appositional or imbricational.

Appositional enamel develops in increments on the occlusal surface of the tooth in the form of stacked domes. The angle of the striae lies about 15 degrees to the surface of the tooth (Hillson and Bond, 1997), and therefore, the striae do not present on the surface of the tooth because the trajectory of the ameloblasts is not perpendicular to the enamel surface. Thus, if the stress event occurs during appositional enamel formation, an LEH will not develop.

Imbricational enamel, on the other hand, occurs in the mid-crown where the angle of the striae of Retzius increases to 30-40 degrees to the surface of the tooth, and so this enamel does reach the surface of the tooth (Hillson and Bond, 1997). Thus, if the stress event occurs during imbricational enamel formation, an LEH may develop (Hillson and Bond, 1997, Witzel et al.,

2008). The angle of the striae of Retzius is even larger in the cervical region of the tooth. Here, it approaches 60 degrees and reaches the surface of the tooth (Hillson and Bond, 1997).

The change in the angle of the striae of Retzius between the occlusal, mid-crown, and cervical portion of the tooth change the spacing between adjacent striae of Retzius. In the occlusal crown, where the angles of the striae of Retzius are small, and the distance between striae of Retzius is about 30-40μm (Hillson and Bond,1997). As enamel develops from the occlusal surface, the distance between the striae of Retzius decreases until it reaches about 15-

20μm in the cervical region (Hillson and Bond, 1997). The number of striae of Retzius in a given portion of the crown is dependent upon this spacing. The small angles and large distances

90 between the striae of Retzius in the occlusal crown means that there are only approximately 35 striae of Retzius in the occlusal crown. Conversely, the large angles and small distances between the striae of Retzius in the cervical crown of human teeth means that there are approximately

100-300 striae of Retzius in the cervical crowns of anterior teeth (Hillson and Bond, 1997:95-

96). If the ameloblasts are exposed to stressors during imbricational enamel formation in the cervical crown, there are more striae of Retzius that can be affected than if ameloblasts are exposed to stressors during the formation of the occlusal crown. Thus, if the stressor occurs at an age where cervical imbricational enamel is forming, (i.e., later in the tooth’s development) then an LEH can form because the striae of Retzius emerge onto the enamel surface as perikymata.

Conversely, if the stressor occurs at an age where occlusal, appositional enamel is forming (i.e., earlier in the tooth’s development), then LEH cannot form because there are no striae of Retzius emerging onto the tooth’s surface.

The timing of a stress event also affects which teeth will be exposed to the stressor. There are more enamel knots in posterior teeth (i.e., premolars and molars) around which the development of appositional enamel takes place than there are in anterior teeth (i.e., incisors and canines). As described above, the geometry of appositional enamel development limits the number of striae of Retzius that can intersect with the surface of the tooth. It is therefore possible that up to 50% of enamel in molars can be exposed to a stressor but never develop an LEH because the affected enamel plane never reaches the surface (Hillson and Bond, 1997). If a stress event occurs during molar enamel development (i.e. later in a child’s growth, except for the first permanent molar) (AlQahtani et al., 2010), then it is less likely to result in an LEH. Conversely, if a stress event occurs during anterior tooth formation (i.e., earlier in a child’s growth), it is

91 more likely to result in an LEH. This logic is consistent with previous studies that have found that LEH are more likely to be present on anterior teeth than posterior teeth (Goodman, 1989).

The development of an LEH is also contingent upon the severity of the stress event.

Witzel et al. (2008) propose a model based on three severity threshold levels. If a stress event is severe enough to surpass the first threshold, matrix secretion will be slightly reduced, the Tomes’ process will maintain its shape, and prism morphology will be normal. The maintenance of the

Tomes’ process allows the ameloblast to resume normal secretory activity after the stress event ends, if the child survives. If the severity of a stress event surpasses the second threshold, matrix secretion is severely impaired, the Tomes’ process will not maintain its distal portion, and the enamel is aprismatic. If the severity of the stress event surpasses the third threshold, the ameloblasts cease all matrix secretion (Witzel et al., 2008). Stress events that meet the second or third threshold are able to form an LEH because the Tomes’ processes are not maintained

(Witzel et al., 2008).

While health cannot be directly observed in skeletal remains, and while age-at-death and

LEH are not perfect indicators of health, they provide one way of inferring health in past populations when interpreted within a biocultural political economy framework. As described previously, ideological, social, political, and economic circumstances contribute to a person’s exposure to stressors. If the stressor is confronted during a time in which anterior teeth are forming, then it may become represented in an LEH. Bioarchaeologists can then use these LEH to make inferences about differences in stress across various social groups, and in doing so, draw broader conclusions about ideological, social, political, and economic circumstances.

Therefore, to test if the health of the Irish observed in the bioarchaeological record reflects contemporary written accounts of Irish health, the following hypotheses are tested:

1. A significantly greater proportion of the population from English Pale alive during the

late medieval period will have survived to older ages than did people in the English Pale

during the post-medieval period. This is based on data showing that childhood stress may

permanently damage the neuroendocrine stress response and thereby decrease resilience

to future stressors (Edes and Crews 2017). People in the English Pale during the post-

medieval period experienced more stress that was visible on their skeletons than did

people in the English Pale during the late medieval period, and they also experienced

shorter lives.

Additionally, this dissertation evaluates the effectiveness of transition analysis in age-at- death distribution reconstruction by comparing the age-at-death distribution from post- medieval Dublin using both transition analysis and burial records. The following hypothesis will be tested:

a. There will be no difference between the age-at-death distributions calculated

using transition analysis of skeletal remains and those calculated using

contemporary burial records from approximately the same location.

2. Individuals from the post-medieval English Pale will exhibit significantly more frequent

LEH than individuals from the late medieval English Pale because LEH are positively

associated with systemic stress (Goodman and Rose 1990) including malnutrition

(Blakey and Armelagos 1985, Hargreaves et al. 1989, Goodman et al. 1991, Goodman

and Rose 1991, May et al. 1993, Zhou and Corruccini 1998) and disease (Santos and

Coimbra 1999). This expectation is based on the proliferation of the potato diet, an

increase in structural inequality, and a widening wealth gap.

Chapter 5: Materials

Individuals (Table 2) from 15 sites within the English Pale were evaluated (Figure 4).

Table 2: Table of sites and sample numbers from each

SITE EXCAVATION COUNTY PERIOD N NUMBER ARDREIGH 00E0156 Kildare Late medieval 87 COOMBE/CORK ST. 93E00066 Dublin Post-medieval 89 DOMINICAN PRIORY 02E0462 Louth Late medieval 23 ESSEX ST. WEST 9E0245 Dublin Late medieval 1 GRANEY EAST 99E0052 Kildare Late medieval 2 HANBURY LANE 98E0199 Dublin Late medieval 11 HOLY TRINITY 92E0037 Louth Late medieval 2 JOHNSTOWN 02E0462 Meath Late medieval 90 MERCER HOSPITAL 1991:042 Dublin Late medieval & 26 post-medieval NORTH KING ST. 98E0088 Dublin Post-medieval 206 SMITHFIELD 00E0272 Dublin Late medieval/ Post- 10 medieval ST. MARY’S CRYPTS Dublin Post-medieval 1 ST. MARY D’URSO 95E0112 Louth Late medieval 4 TRIM CASTLE 95E77-- Meath Post-medieval 4 UPPER MAGDALENE 1991:095, 94E007 Louth Late medieval 10

Ardreigh

Excavation at Ardreigh (also spelled Ardree) took place in 2000 and then again in June

2006 ahead of residential development (Keeley and Opie, 2002, Bennett, 2007). Ardreigh was a medieval borough, a settlement established by a lord whose subjects have rights, privileges, and obligations specific to that borough, such as limited self-government and property rights (Keeley and Seaver, 2000), though there is evidence of human settlement as early as 8000 BC (Moloney et al., n.d.). Ardreigh was granted to Thomas le Fleming by Strongbow, lord of Leinster, in AD

1176 (Keeley and Seaver, 2000). In 1182, Hugh de Lacy, lord of Meath, built a castle on land granted to the Abbey of St. Thomas in 1199 (Keeley and Seaver, 2000). The church was referenced in documents before the land was transferred to the Abbey of St. Thomas, however, and it was therefore part of the grant given to the abbey (Keeley and Seaver, 2000).

Archaeological evidence in the form of wattle and daub structures, hearths, and corn- drying kilns suggests that the people buried at the site at Ardreigh lived during the late medieval

95 period and likely lived and worked at the nearby settlement and industry site just to the south of the cemetery (Keeley and Opie, 2002). Botanical evidence collected from medieval soil layers suggests that people consumed hazelnuts, which would have been collected from the surrounding forests (Moloney et al., n.d.). Botanical evidence also suggests the production (and possible subsequent consumption) of wheat, barley, oats, and peas (Moloney et al., n.d.). The presence of kilns and quern stones suggests that these grains were being processed into flour (Moloney et al., n.d.) Wild plants such as goosefoot, mayweed, bistort, and sedges were likely also collected from the surrounding landscape and used as either food or medicine (Moloney et al., n.d.). Middens contained a variety of animal bones including cattle, sheep/goat, horse, pig, dog, and cat

(Moloney et al., n.d.). The cattle would have provided milk and meat, as well as bone that could be shaped into tools and dice and skins that could be used to make leather (Moloney et al., n.d.).

Sheep would have provided wool and meat (Moloney et al., n.d.).

Artifacts recovered from Ardreigh help to reconstruct daily life in the community.

Numerous tools such as spindle whorls, bone needles, pins, and thimbles indicate not only textile production at Ardreigh, but production of the tools at Ardreigh as well (Moloney et al., n.d.).

Pottery, however, does not appear to have been produced on-site. Rather, the pottery present at

Ardreigh was brought in from Dublin and France and sold at local fairs and markets (Moloney et al., n.d.). Highly decorated combs, brooches, buckles, and other clothing items suggest that the people of Ardreigh attended to their appearances, and tuning pegs, figurines and dice suggest that they also had at least some time for leisure activities (Moloney et al., n.d.).

The cemetery was largely attritional, though some of the graves did include more than one individual. This suggests that there were occasional periods of disease that necessitated the frequent and expedient burial of the borough’s deceased residents (Keeley and Opie, 2002).

Individuals buried at Ardreigh include men, women, and children (Moloney et al., n.d.). The majority of finds recovered from grave fills were late medieval in date. These included a 13th-

15th century plated ring brooch and Leinster cooking ware and other ceramics dating from the

12th to 14th century. The most recent burial was that of Charles Lennox, who was found with a farthing minted between 1625 and 1642 (Keeley and Opie, 2002). No burials appear to have taken place after this time. These artifacts suggest that the cemetery was heavily used between the 12th and 15th century with occasional continued use into the mid-17th century (Keeley and

Opie, 2002). Joint diseases and osteoarthritis was common; tuberculosis and leprosy were also present (Molony et al., n.d.). One individual, a child, exhibited a circular, antemortem cut to the skull consistent with trepanation (Molony et al., n.d.). One individual (an adult male) was buried with a scallop shell that was perforated so that it could be worn around the neck (Molony et al., n.d.). Such perforated shells were obtained only by going on a pilgrimage to the shrine of St.

James in Santiago de Compostela, Spain (Molony et al., n.d.). Because their sale outside of the shrine was forbidden by the Catholic Church (Moloney et al., n.d.), this person must have either gone on the pilgrimage himself or received the shell from someone who did.

There were a total of 1,259 burials found during the excavation and of these, 1,060 were late medieval (Moloney et al., n.d.). One-hundred of these are included in this dissertation. Time prohibited the analysis of all 1,259 burials.

Coombe/Cork St.

The site at Coombe/Cork St. is immediately adjacent to the church of St. Luke the

Evangelist (Figure 5), built in 1715-1716 by Surveyor General Thomas Burgh (Shaffrey

Associates Architects et al., 2003). The site is the graveyard for St. Luke’s Church, which was

97 established by an Act of Parliament in 1707 that divided the parish of St. Nicholas Without into the Parish of St. Luke’s and St. Patrick’s Cathedral (Shaffrey Associates Architects et al., 2003).

The parish community of St. Luke’s was bound to the north by the ancient roadway An

Com (Coombe St., or the Coombe), and to the west and east by two branches of the Poddle River that line Crooked Staff Place (later renamed Ardee St.) and Blackpitts, respectively (Frazer, n.d.,

Shaffrey Associates Architects et al., 2003) (Figure 6 and Figure 7). Contained within St. Luke’s

Parish are Newmarket and Weavers’ Square (Frazer, n.d.). The area was originally developed in the medieval period, as residential, religious, and commercial activity expanded along major roadways like the Coombe (Frazer, n.d.). Developers in the 17th and 18th centuries were attracted to the area because they could establish commercial buildings near Dublin City Center without having to abide by the same regulations as they would if they built within the walls of Dublin city proper (Frazer, n.d.). The location between the two branches of the Poddle River also permitted unrestricted access to a source of water (Frazer, n.d.).

Figure 5: St. Luke’s Church and surrounding graveyard c. 1818. Watercolor painting from National Gallery of Ireland.

Figure 6: St. Luke's Church in John Rocque's map of 1758. The Parish of St. Luke’s was located south of Coombe St. and between two branches of the Poddle River, marked by Crooked Staff Place to the west, and Blackpitts to the east. Newmarket borders the parish to the south. Image modified from Shaffrey Associates Architects and colleagues (2003). North is up.

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Figure 7: Map of St. Luke’s Parish from Brooking’s 1728 Map of Dublin. Image from Frazer, n.d. North is down.

Excavation revealed 168 intact burials and extensive deposits of disarticulated human bone. The cemetery for St. Luke’s was in use until 1800 (excavations.ie) and the earliest burials are recorded in 1716 (Shaffrey Associates Architects et al., 2003), suggesting that the people buried at Coombe/Cork St. lived between 1650 and 1800. According to early church records, people buried here included weavers, tanners, skinners, brewers, butchers, carpenters, shearmen, ropemakers, apothecaries, and textile workers, mostly of Protestant faith (Shaffrey Associates

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Architects et al., 2003). They likely lived in residential buildings within the landscape of commercial buildings described above. The residential buildings characteristic of this area were known as Dutch Billys (Frazer, n.d.). These single-family row houses were made mostly of brick, were often two to three stories, and chimneys were shared between pairs of houses (Frazer, n.d.). While cellars were not characteristic of Dutch Billys, crawlspaces under the houses appear to have served to store dairy products until they were ready to be sold (Frazer, n.d).

During the 1600s, these houses were separated into tenements, each housing five to six families

(Frazer, n.d.). Protestant middlemen were able to lease these tenements for up to 61 years, while

Catholics were permitted to lease for no more than 31 years, and these middlemen were permitted to sublease their tenements, often by the week (Frazer, n.d.). Over time, the wealthier business owners moved to more rural areas outside of Dublin City center, and workers stayed in the tenements (Frazer, n.d.). Consequently, industrial wealth and power became concentrated in the hands of a few entrepreneurs outside of Dublin, and the many laborers whose lives were affected by the decision-making of a few were concentrated in urban Dublin (Frazer, n.d.). These laborers were affected by wage-reductions, layoffs, and disease outbreaks, as well as poor building maintenance by the absent landlords (Frazer, n.d.). Archaeological evidence supports the neglect of these buildings, revealing failed water pipes, blocked doorways, and fragile stairwells (Frazer, n.d.).

While the residents grew relatively poorer, new poor inhabitants were drawn to the parish by the low rents in the tenement houses (Frazer, n.d.). In a 1798 census, 7,241 residents were counted in the parish of St. Luke, and of these, 6,839 were recorded as being “lower class”

(Frazer, n.d.). By 1805, it was estimated that the average number of people per household was between 15 and 16 (Frazer, n.d.). The proportion of lower class individuals in the parish of St.

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Luke was recorded in 1798 as being the highest of any parish in the city of Dublin (Figure 8), and Wright (1821:173) remarks that it is known as “the poorest Parish in Dublin.”

Figure 8: Distribution of social classes between parishes. Image from Sheridan-Quantz (2001).

The parish of St. Luke was religiously diverse. In 1718, it was estimated that there 2,438

Protestants (including conforming Huguenots), 823 dissenters (e.g., Baptists, Moravians, and

Methodists), and 1,106 Catholics (Frazer, n.d.). While St. Luke’s is associated with Huguenots, as demonstrated by the dedication of the bell to “…the Glory of God and in Memory of the coming of the Huguenots 1685,” there were no Huguenot names on any of the gravestones at the time they were recorded (Shaffrey Associates Architects et al., 2003). It is more likely that the

103 local Huguenot population was buried further down the road off of Kevin St. and not at St.

Luke’s (Shaffrey Associates Architects et al., 2003). Instead, it has been suggested that the burials at St. Luke’s are from the neighboring Cork St. Fever Hospital (Shaffrey Associates

Architects et al., 2003). This possibility is supported by the disproportionate number of children buried in the cemetery (Shaffrey Associates Architects et al., 2003). However, Cork St. Fever

Hospital was founded in 1801 (Royal College of Physicians of Ireland, 2015), and burial at St.

Luke’s ceased by 1800 (excavations.ie), so this is unlikely.

A small number of burials were contained in crypts; the relative absence of these burials is attributed to widespread poverty within the parish (Shaffrey Associates Architects et al.,

2003). Use of the church itself continued until 1975 (Shaffrey Associates Architects et al., 2003).

Dominican Priory

The site known as the “Dominican Priory” was first excavated between May and June of

1991 by the Archaeological Development Services ahead of expansion of St. Brigid’s

Educational Centre on Upper Magdalene Street in Drogheda (Halpin and Buckley, 1995). The site is situated within the late medieval Dominican Priory of St. Mary Magdalen founded in 1224

AD (Halpin and Buckley, 1995), and possibly on the site of an earlier church (c. 1206 AD) also referred to as St. Mary Magdalen. Between 1224 and 1400, the Domincan Priory maintained a high status in the county, but by the time of the dissolution in 1540, the priory had largely fallen into ruins (Halpin and Buckley, 1995).

Unfortunately, the burial numbers described in the site report do not match the burial numbers assigned to the skeletons documented at the National Museum of Ireland, as these were changed prior to publication. The new burial numbers for the individuals included in this

104 dissertation and the corresponding old burial numbers (assigned prior to publication) are given in

Table 3 (Elise Alonzi, personal communication). The pre-publication numbers are those used in this dissertation. Original sex and age data by Halpin and Buckley (1995) are also given in Table

Table 3: Pre- and post- publication burial numbers and original data for Dominican Priory

Pre-Publication Publication Sex Age (young, Additional Notes Number(s) Number middle, older) 1 17 M adult osteoarthritis of hips, right wrist, 5th lumbar vertebra, 1 Schmorl’s node 4 12 F adult LEH on incisors, canines, LMP2, ULP2, LRM1, ULM2, some arthritic ribs 5 1 M older ossification of thyroid, osteoarthritis of right hip, clavicles, left shoulder, left knee, ribs, and vertebrae 7 3 M older LEH on lower incisors and LRC, ossified thyroid, osteoarthritis of left shoulder, vertebrae, 1st ribs 10 9 M adult spina bifida occulta, Schmorl’s nodes 15 22 M adult reactive bone on lower lumbar vertebrae 21 60 M adult LEH on upper incisor and canine, LRC, osteophytosis of L3-5 23 54 M young LEH on all canines and P1s, pitting of M1s, Schmorl’s nodes on T12 and L1 27 19 M adult LEH on upper premolars, Schmorl’s nodes 30 52 M middle LEH on ULC, ULI1, URI1, URP1, LRP1, spina bifida occulta 34 45 F adult LEH on ULI1, URI1, ULP1, URP1, LLC, LRC, LLP1, LRP1 38 53 40A 27 F middle Osteoarthritis of acromio-clavicular joints, vertebrae, ribs 40B 28 M adult Vertebral arthritis 42 25 M old LEH on 1 upper incisor, URP1, ULP1 46 59 F old osteoarthritis of left elbow, vertebrae, and 2 ribs, Schmorl’s nodes on lower thoracic and upper lumbar vertebrae 48 35 PrM young 49B 63 M adult? perimortem (?) fractures to 3 ribs 50 37 M adult stone-lined, roofed grave, LEH on all teeth 51 66 I 16-18 years cribra orbitalia of left orbit 52B 65 M adult LEH on all canines, URP1, LLP1, LRP1, ULP2, URP2 56 67 F middle LEH on all canines and first molars, fracture to right clavicle, Colles fracture to right radius, osteoarthritis of both hips and shoulders, T12, L4, L5, and some ribs 59 68 M adult LEH on most teeth, new bone formation on acetabulum and ilium 61 32 M middle LEH on ULI2, ULI1, LLI2, LLI1, LLC, ossified thyroid, antemortem fracture to left clavicle and 2 ribs,

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arthritis of both hips, auricular surfaces, vertebrae, and ribs, scoliosis

Additionally, the boxes containing the human remains were vandalized during a break-in of the original storage facility. Consequently, the bones were re-boxed by interns, but some of the remains could not be reassigned (Elise Alonzi, personal communication). Many of the burials are described as truncated (Halpin and Buckley, 1995), likely a consequence of high burial density and intercutting of burials. This further limited the number of samples available for this study.

According to Halpin and Buckley (1995), at least two of the burials (31 and 37 in the excavation publication) were likely high-status, as indicated by the presence of stone-lined graves. This is consistent with the overall high-status of the site. The grave of burial 37 (B50 in this study) was nearly completely intact and included a lintelled cover (Halpin and Buckley,

1995), also indicative of a high-status burial. Burial 52 (post-publication number 30) is described as having a copper alloy and iron buckle on the pelvis, consistent with a priest’s clothing worn at the time of burial (Halpin and Buckley, 1995). This was the only artifact found in direct association with a burial, though pottery sherds dating from the 13th-14th century were present in many of the grave fills (Halpin and Buckley, 1995).

All excavated burials (n=61) appear to have been interred during the 13th and 14th centuries (Halpin and Buckley, 1995). It is therefore possible that the cemetery fell out of use before the priory fell into ruins in the 1400s, but the latest date of the burials could also be an artifact of sampling bias (Halpin and Buckley, 1995). Two burials underwent radiocarbon dating; these were burial 28 (sample UB-3449) and 38 (sample UB-3450) in the excavation report.

Burial 28 had a calibrated 2σ (95%) radiocarbon date of 1050-1274 AD, and burial 38 had a calibrated 2σ radiocarbon date of 1167-1260 AD (Halpin and Buckley, 1995). Historical

106 context further reduces these date ranges because no burials had been present on the grounds at the time of the town’s foundation in 1180 AD. The most likely time range for the burial of these two individuals is therefore c. 1200-1274 (Halpin and Buckley, 1995).

According to Halpin and Buckley (1995), most of the burials excavated were adult males

(n=32). By comparison, there were relatively few women (n=14), children (n=11), and infants

(n=1) (Halpin and Buckley, 1995), and it is likely that the one infant burial is a post-medieval cillín burial based on the presence of post-medieval ceramic material in the grave fill. The ratio of men to women and adults to children is consistent with a typical monastic cemetery; however,

Halpin and Buckley (1995) note that the occasional presence of women and children suggests that lay members of the community were also buried at the site. This is not dissimilar to the neighboring parish church of St. Mary d’Urso, which permitted the burial of lay people in exchange for a fee. Because both the Dominican Priory of St. Mary Magdalen and St. Mary d’Urso were overseen by the Llanthony canons, it is likely that the rule applied to St. Mary

Magdalen as well (Halpin and Buckley, 1995). It is also possible that the children present on the site were young members of the religious community, as all juveniles were estimated to be over the age of ten years (Halpin and Buckley, 1995).

A complete osteoarchaeological analysis was performed by Buckley (Halpin and

Buckley, 1995). She found that males buried at the Dominican Priory of St. Mary Magdalen fell within the typical range of stature for that time period. Females were found to be shorter, though she notes that this is possibly a sampling error. General pathological conditions included dental disease, one case of spina bifida, porotic hyperostosis (n=1), cribra orbitalia (n=2, both children) periostitis of the lower legs (n=3), degenerative disease of the vertebrae (n=30), Schmorl’s nodes

(n=11), osteoarthritis (16% of adults), and diffuse idiopathic skeletal hyperostosis (n=1) (Halpin

107 and Buckley, 1995). Two instances of osteomyelitis were identified, but both of these were present in disarticulated bone and could not be associated with any one particular burial. Four adults exhibited antemortem fractures (Halpin and Buckley, 1995).

Seventy-three percent of individuals with dentition present exhibited linear enamel hypoplasia on more than one tooth. According to Halpin and Buckley (1995), this is a relatively high rate of LEH when compared to a neighboring high-status priory, Tintern Abbey (Buckley,

1991). Buckley estimates the stress events that likely caused the LEH to have occurred between ages one and six for most affected individuals (Halpin and Buckley, 1995). The highest rate of

LEH occurred between ages two and four, which Buckley attributes to weaning (Halpin and

Buckley, 1995).

According to Halpin and Buckley (1995), these findings suggest that most people buried on the site participated in some form of manual labor, though those of higher status did not. The relatively low prevalence of dental caries suggests a diet that included few refined carbohydrates

(Halpin and Buckley, 1995). Most pathological conditions (e.g., LEH, porotic hyperostosis, and cribra orbitalia) appeared to have arisen in childhood (Halpin and Buckley, 1995).

Upper Magdalene

A second phase of excavation took place in 1994 (Figure 9). This only archaeological site excavated from Upper Magdalene Street where burials were found appears to be the Dominican

Priory of St. Mary Magdalene, described above. Additionally, the burial numbers in Murphy

(1997), which describes a 1994 excavation at the Dominican Priory of St. Mary Magdalene, match the burial numbers of the individuals from the Upper Magdalene sample in this dissertation. The presence of only one archaeology site containing human remains on Upper

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Magdalene Street and the numbering system of the burials suggests that the skeletons from the

Dominican Priory and from Upper Magdalene were both part of the Dominican Priory of St.

Mary Magdalene. These samples will therefore be presented and discussed together for the remaining chapters of this dissertation. Observations of skeletal remains are published in Murphy

(1997), and are reproduced in the table below (Table 4).

Figure 9: Map of excavation 94E007 from Murphy (1997)

Table 4: Skeletal data in Murphy (1997)

Burial Sex Age Location Grave Pathological Characteristics & Notes Contents B1 F Adult Inside the nave of the head of nail, Schmorl’s nodes; osteochondritis church, under the 14th-15th c. dessicans of first proximal right church floor floor tiles pedal phalanx; severe osteoarthritis to right MTI

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Burial Sex Age Location Grave Pathological Characteristics & Notes Contents B2 M older adult Inside the south 13th-14th c. osteoarthritis of both hips, knees, transept of the church pottery, shoulders, wrists, thoracic vertebrae; but outside the nave mosaic tiles healed antemortem fractures of 4 right ribs; Schmorl’s nodes; periostitis of left and right tibiae and right fibula; shorter left humerus than right, with notable swelling at the distal metaphysis; exostosis of anterior and posterior right fibula; LEH on LLI, LLC, and LLP consistent with stress events occurring between ages 2 and 5. B3 juvenile within the original 14th-15th c. nave wall floor tiles B4 juvenile outside south wall of 13th-14th c. spina bifida occulta the church pottery; iron comb; iron nail B5 juvenile B6 M young adult iron nail porotic hyperostosis on both parietals; LEH on lower incisors and canines, the URC, URP1, URP2, and LLM2 formed between 3-6 years B7 F middle-aged Inside a mortar-lined 13th-14th c. mild degenerative joint change to grave outside the pottery, floor hips, knees, shoulders, and right nave wall shared with tile, 15th-16th elbow; severe arthritis on 1 middle B8 c. pottery; manual phalanx; osteoarthritis of oyster shell some right ribs and vertebrae; pendant, B8 Schmorl’s nodes; LEH on upper canine and M1 formed between 3-5 years B8 M older adult Inside a mortar-lined 13th-14th c. markedly robust; robust muscle grave outside the floor tile attachments; “excessive osteophyte nave wall shared with fragments formation” on vertebrae; Paget’s B7, below B8 disease; osteoarthritis of sacra-iliac joints, hips, knees, left shoulder, both wrists, right elbow, MTV, and both ankles; Schmorl’s nodes B9 M middle-aged Inside a stone-lined 14th c. severe osteoarthritis of cervical grave within the copper-alloy vertebrae; degeneration of thoracic church wall buckle and lumbar vertebrae; mild arthritis in right shoulder and elbow, one right metacarpal; Schmorl’s nodes; LEH on canines, premolars, and ULM2 formed between 3-5 years B10 juvenile Inside the church 1 piece of 14th-15th c. pottery

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In addition to individual burials, the 1994 excavation also revealed an abundance of disarticulated bone, identified in Murphy (1997) by feature number. These are presented in Table

5. In this dissertation, disarticulated skulls are treated as burials because like burials, each skull represents one individual. The disarticulated skulls were not individually labeled at the time of observation, so the numbering system for these skulls in this dissertation is different than the numbers in Murphy (1997). An attempt to match them is made in Table 5 below.

Table 5: Data collected from Buckley in Murphy (1997)

Summary of Disarticulated Bone Data by Buckley (1997) Feature Number MNI Pathological Characteristics & Notes F1 9 severe osteoarthritis of knees in 2 femora from 2 different individuals; severe osteoarthritis of 1 proximal tibia; healed antemortem fracture of 1 femoral shaft F2 2 F3 1 F6 1 F7 19 LEH present on canines in 1 of 2 mandibles F8 2 F9 1 F12 1 1 cervical vertebra with severe osteoarthritis F20 4 F23 4 possibly skull belonging to Burial 4; severe cribra orbitalia on both orbits F25 Skull A 1 LEH on all left premolars in Skull A formed between 3-4 years F25 Skull B 1 Skull B was a juvenile F34 Mix of juvenile and adult long bones, skulls F34 Skull 1 1 older adult male (could correspond to F34 disarticulated skull E in this dissertation) F34 Skull 2 1 adult female (could correspond to F34 disarticulated skull B or D) F34 Skull 3 1 possible male skull (corresponds to F34 disarticulated skull A) F34 Skull 4 1 probable adult female (could correspond to F34 disarticulated skull B or D) F34 Skull 5 1 probable adult female; cribra orbitalia on both orbits F34 Skull 6 1 male; frontal, temporal, and parietal F34 Skull 7 1 adult male; full cranium (could correspond to F34 disarticulated skull E) F34 Skull 8 1 adult female; cribra orbitalia on both orbits (could correspond to F34 disarticulated skull B or D) F34 Skull 9 1 adult male; 2 button osteomas (corresponds to F34 disarticulated skull C) F34 Skull 10 1 adult male; cranium without maxilla (could correspond to F34 disarticulated skull E) F38 2 F39 2 F40 4 long bones, mandibles, maxillae, and 4 crania were present F40 Skull 1 1 male; LEH on upper canines and premolars formed between 3-5 years (could correspond to F40 Skull H) F40 Skull 2 1 older adult male (corresponds to F34 disarticulated skull F)

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F40 Skull 3 1 poorly preserved parietals and frontal (could correspond to F40 Skull H) F40 Skull 4 1 adult male (could correspond to F40 Skull H) F41 6 LEH present on incisors and canines of one of the mandibles, formed between 2-5 years F42 2 At least 1 adult and 1 juvenile; severe cribra orbitalia on juvenile frontal bone F44 3 2 humerii likely belonging to the same individual had severe osteoarthritis at the elbow; 2 ilia had severe osteoarthritis at the acetabulum; 1 distal metacarpal also had severe osteoarthritis

All burials were aligned west to east in the typical Christian fashion, with either the arms extended along the side or the hands folded over the pelvis (Murphy, 1997). The locations of the burials show that many of the individuals excavated had been wealthy, or in the case of the juveniles, had come from wealthy families. As was typical practice during the time, only individuals for whom a substantial fee had been paid could be buried within a church.

Grave goods and linings were also consistent with high-status individuals. Burials 1, 4 and 6 were found with iron nails, which likely had been parts of coffins (Murphy, 1997). Burial 7 was found with a shell pendant around his neck (Murphy, 1997), similar to the one found with another adult male burial from Ardreigh, suggesting again that this man must have either gone on a pilgrimage to St. James in Santiago de Compostela (Moloney et al., n.d.), Spain, or knew someone who had. Burials 7 and 8 were found in a mortar-lined grave, and Burial 9 was found in a stone-lined grave within the church (Murphy, 1997). Burial 9 was also found with a copper- alloy buckle consistent with the type worn by 14th century clergy, suggesting that Burial 9 was a cleric (Murphy, 1997).

The skeletal evidence described by Buckley (1997) shows that high-status and wealth did not protect the community from the hazards of medieval life. Cribra orbitalia was present on six individuals, porotic hyperostosis was present on two, and osteoarthritis was common (Buckley,

1997), which suggests some exposure to nutrient deficiency and a life characterized by manual labor. The rate of dental caries was relatively low (Buckley, 1997), suggesting a diet low in

112 carbohydrates. One burial (B2) had antemortem fractures to four ribs, consistent with a fall onto a hard surface (Buckley, 1997). One person (B8) had Paget’s disease, a condition that typically occurs after the age of 50 and results in excessive and irregular osteoblastic activity (Ortner and

Putschar, 1985, Buckley, 1997). At the time of publication, B8 was one of only two burials in

Ireland identified as having Paget’s disease (Buckley, 1997).

Essex St. West

Essex St. West was excavated by Linzi Simpson with Margaret Gowen & Co., Ltd. from

December 6th 1993-March 3rd 1994 and again from March 2nd-6th, 1995 to determine the extent of an adjacent Viking and Anglo-Norman wall (Bennett, 1996:19). The Viking period in Dublin began around AD 1100 and was quickly followed by an Anglo-Norman period beginning in AD

1170 following the Anglo-Norman invasion (Simpson, 1995). One human skull and several cervical vertebrae were excavated (Simpson, 1995). Perimortem sharp force trauma on the first and fourth cervical vertebrae and on the right mastoid process are consistent with decapitation

(Simpson, 1995). According to the project bioarchaeologist, Linzi Simpson, the skull was likely mounted on a sword or spike and displayed on the wall, as was common during this period

(Simpson, 1995).

Graney East

The remains at Graney East were excavated in February and July 1999 during monitoring of soil stripping ahead of development for a proposed quarry (Byrne, 1999). The site is adjacent to a nearby 13th century nunnery, a 17th century house, a holy cross, and a holy well (Bennett,

2007:126-127). Eleven out of the twelve pottery sherds recovered were from the late medieval

113 period, dating to between the 12th and 14th centuries (McCutcheon, 2001). Two skeletons were exposed and excavated, and these were originally analyzed by Clare Mullins (Mullins, 2001).

Both skeletons are included in the late medieval sample for the present study.

Hanbury Lane

Hanbury Lane was excavated in 1999 by Claire Walsh with Archaeological Projects, Ltd.

(Bennett, 2000:69). While the site is near a monastery, the low burial density within this 13th century cemetery and its location outside of the nearby abbey suggests that the graveyard was an informal one (Bennett, 2000)

Holy Trinity

The remains at Holy Trinity were excavated as part of a restoration project for Holy

Trinity Church in Carlingford, Co. Louth (excavations.ie) (Figure 10), which is now the local historical center, indicated on the map in Figure 11. Twenty burials were found during excavation, as well as 32 disarticulated skeletons. The twenty burials included 10 males, six females, and four children (excavations.ie). One skeleton exhibited antemortem sharp force trauma consistent with a sword wound, and another exhibited antemortem sharp force trauma consistent with trephination (excavations.ie). Two bones were radiocarbon dated. One of these had a calibrated date of 1517-1666 AD, and the other had a calibrated date of 1442-1650 AD

(excavations.ie).

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Figure 10: The restored Holy Trinity Church in Carlingford. Image from the National Inventory of Architectural Heritage.

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Figure 11: Location of Holy Trinity Church in Carlingford (circled). Image by Ordnance Survey Ireland. North is up.

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Johnstown

Johnstown was excavated from April to October 2002 ahead of a proposed motorway linking Kinnegad, Enfiled, and Kilcock after a geophysical survey in January 2002 indicated the presence of an enclosure (Clarke, 2002). The excavation revealed two burial grounds, though there is no evidence of an associated religious site (Clarke, 2002). In all, 461 skeletons were revealed (Fibiger, 2004). Linda Clarke (2002) writes that most of the burials from the first cemetery were from the early medieval period, but according to the same document in which this argument is made, the artifacts contained within the grave fills included ceramics from the 13th-

14th century, although Souterrain ware (a type of unglazed pottery characteristic of medieval cooking) from the 9th-11th century was also found. As it is impossible for a ceramic type to be included in the grave fill before it is invented, the graves are likely from the late medieval period.

The preservation of the skeletons is also more consistent with a late medieval site than with an early medieval site. The second cemetery is one that had been identified in oral tradition as a cillín, a type of cemetery for unbaptized infants used until the mid-20th century (Clarke, 2002).

Radiocarbon dates were obtained for 21 burials (Fibiger, 2004). Of those, five are included in this dissertation (Table 6).

Table 6: Radiocarbon Dates for Johnstown Burials

Radiocarbon Dates for Johnstown Burials Included in this Dissertation Burial Number Calibrated Radiocarbon Date 142 AD 1190-1290 145 AD 1230-1300 280 AD 1060-1280 295 AD 1290-1440 485 AD 1160-1300

The people buried at the first cemetery likely lived and worked in the nearby settlement site, which contained at least one structure, middens, smelting pits, and a variety of artifacts

117 including a decorated ring pin, shroud pins, bone needles, knife blades, loom weights, coins, and animal bone (Clarke, 2002). Skeletal evidence suggest lives characterized by high childhood mortality, manual labor, and occasional violence. According to Fibiger (2004), half of the medieval burials (including both early medieval and late medieval) were infants and children, and of these, 55% died between the ages of four and eight years, suggesting that children were particularly vulnerable during this time. Degenerative joint disease was common and affected all adult age ranges, supporting the conclusion that manual labor was a common way of life for the people in this community (Fibiger, 2004). One individual (Burial 151) had a dislocated shoulder

(Fibiger, 2004), which, while it could have been caused either by manual labor or by accident.

One individual was diagnosed with tuberculosis, but the burial number of this individual is not provided in Fibiger (2004). Three individuals exhibited signs of interpersonal conflict. B26 likely died as a result of a slashed throat, which would have caused the observed perimortem sharp force injuries to the anterior cervical vertebral bodies (Fibiger, 2004). B145 died a similarly violent death, which produced the twenty perimortem sharp force injuries to the face, head, neck, shoulder, and hand (Fibiger, 2004). Alternatively, my own observation of the skeleton revealed the possibility of postmortem dismemberment, as most of the sharp force injuries were confined to the joints. Finally, B142 survived an interpersonal conflict and exhibited well-healed sharp and blunt force trauma to the skull consistent with a blow from either a battle axe or sword

(Fibiger, 2004). My own observations corroborated this interpretation. Notably, while the wound was well-healed, Fibiger (2004) writes that there would certainly have been lasting neurological effects such as a personality change or altered senses.

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Mercer Hospital

Mercer’s Hospital was excavated in 1991 by Alan Hayden and is located on Digges Lane in Dublin ahead of continued development near the site of the former Mercer Hospital and the current College of Surgeons (Buckley and Hayden, 2002). Its location lay outside the city wall, southeast of the city center (Buckley and Hayden, 2002). This site is not to be confused with a neighboring St. Stephen’s, the successor to the earlier St. Stephen’s Church built on Upper

Mount St. (Belcher, 1868). Excavation revealed remnants of St. Stephen’s Church, its associated graveyard, and a contemporaneous leper hospital (excavations.ie) by the name of St. Stephen’s

Hospital (Buckley and Hayden, 2002, Dublin City Council, 2013).

St. Stephen’s Hospital was founded in AD 1192, and records indicate it was still there in

1541. By AD 1230, it was known as the Leper House of St. Stephen (Dublin City Council,

2013), suggesting it was used to care for victims of leprosy in the late medieval period. By 1601 it was comprised of three castles and a precinct hall, and by 1610 it was described as having a church and churchyard (Dublin City Council, 2013). This church had fallen into disrepair by the

1660s, and funds were collected to finance a new parish church, which was soon incorporated into the prestigious estate of Francis Aungier, Earl of Longford (Dublin City Council, 2013).

While the church fell out of use, the site continued to be used as a graveyard until 1665 when it was ordered that the graveyard be closed (though use of the graveyard did not necessarily stop)

(Buckley and Hayden, 2002).

The land was then given to James Knight to build a small house for ‘poor decayed

Christians,’ but he failed to build the house (Buckley and Hayden, 2002). It is unclear what he meant by “poor decayed Christians.” The land was then leased to Mary Mercer in 1724 for the construction of a pauper hospital (Buckley and Hayden, 2002). Construction of the hospital was

119 completed in 1734, when it was opened (Buckley and Hayden, 2002). Need for the hospital continued to grow, and it was expanded in 1740 (Buckley and Hayden, 2002). The original building was soon demolished to make room for a larger hospital, which was completed in 1757

(Buckley and Hayden, 2002). It is possible that the graveyard was still in use at this time, as it is indicated in a 1756 map (Buckley and Hayden, 2002). Mercer Hospital remained open until 1983

(Buckley and Hayden, 2002).

Five burials (burials 20, 21 and 23-25) were recovered from Level IIa, north of the stone terrace (feature 127) overlying a ditch that had likely been used to mark the limits of the property

(Buckley and Hayden, 2002). None of these burials were cut by the ditch or the stone terrace

(Buckley and Hayden, 2002), suggesting that the ditch and stone terrace predated the burials.

North Leinster and Wiltshire pottery recovered from the ditch corroborate written records that indicate the initial building on the site dated to the later 12th- early 13th centuries (Buckley and

Hayden, 2002). The burials were simple, Christian burials, each oriented west to east, arms extended to the sides or crossed over the pelvis, with no signs of coffins or shroud pins (Buckley and Hayden, 2002).

Overlying level IIa was a layer of cultivated soil (level IIb) which appears to have built up between the 1300s and 1600s (Buckley and Hayden, 2002). Level IIc cut the cultivated soil layer (level IIb) at the southern part of the site (Buckley and Hayden, 2002). Contained within level IIc were three burials (burials 16, 17, and 22) (Buckley and Hayden, 2002). Site stratigraphy therefore indicates that burials 20, 21 and 23-25 predate burials 16, 17, and 22.

Pottery recovered from level IIc are date from the 1300s-1400s (Hayden and Buckley, 2002), suggesting that level IIc was approximately contemporaneous with level IIb, with occasional burials being dug into the cultivated soil layer.

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The terrace was covered by a later layer of cultivated soil (Level III), into which the graves for burials 19 and 26 were cut (Buckley and Hayden, 2002). No bones survived in grave

26, but evidence of a grave survives. Immediately overlying the later layer of cultivated soil

(Level III) were fragments of 17th-century pottery and clay pipes, suggested that this layer represents a time period between the 14th-17th centuries (Buckley and Hayden, 2002).

A complete skeletal report is provided in Buckley and Hayden (2002). Unfortunately, the burial numbers used in Buckley and Hayden (2002) and the numbers used at the National

Museum of Ireland are different. The individuals examined in this dissertation cannot be linked to individuals in the report at this time.

The burials in Buckley and Hayden (2002) are divided into two groups, namely, 13th-14th century burials (B16, 17, and 20-25 in the report) and 18th-19th century burials (B2-5 in the report). However, while the individual burials cannot be matched to the individuals in this dissertation, the information compiled from the collection as a whole can be used to paint a more detailed picture of the lives of people buried at Mercer’s Hospital. The findings by Buckley and

Hayden (2002) are presented in Table 7.

Table 7: Summary of Results from Buckley and Hayden (2002)

Summary of Results from Buckley and Hayden (2002) Burial Age Sex Time Period Grave Contents Pathological Characteristics & Notes 2 infant 18th-19th c. skull and vertebrae 2 13th-14th c. diffuse idiopathic skeletal hyperostosis; healed cribra orbitalia of left orbit 3 18-21 18th-19th c. articulated vertebrae, years partial mandible and maxilla 4 18th-19th c. some vertebrae, lower ribs 5 16-20 18th-19th c. upper torso porotic hyperostosis; Schmorl’s nodes years on lower thoracic vertebrae 6 36-45 M 17th-18th c. nearly complete heavy dental wear; severe skeleton osteoarthritis of left hip, mild arthritic changes to right hip, right acromio- clavicular joint and vertebrae; healed fracture of left patella; pseudoarthrosis 121

Summary of Results from Buckley and Hayden (2002) Burial Age Sex Time Period Grave Contents Pathological Characteristics & Notes of right scapula and false joint surface, possibly the result of shoulder dislocation 7 36-45 F 17th-18th c. nearly complete LEH estimated to have formed skeleton between 3-4 years; cribria orbitalia; mild osteophytosis of middle thoracic vertebrae; arthritic changes to lower ribs, left femur, and left patella; bilateral squatting facets on tibiae 9 36-45 F 17th-18th c. pelvis and legs only lateral squatting facet of right tibia; very mild arthritic changes to right knee 10 9-15 17th-18th c. nearly complete months skeleton 11 neonate 17th- 18th c. upper torso 12 neonate 17th-18th c. mostly complete skeleton 13 young 17th-18th c. arms, legs, pelvis, ribs, LEH estimated to have formed adult and skull between 1-4 years; pitted hypoplasia of lower canines and URI2; circular osteolytic lesions to T3-7, degenerative changes to T8-10 consistent with osteomyelitis, tyberulosis, or aortic aneurysm, but lack of reactive bone is most consistent with tuberculosis and is consistent with other traits on the skeleton including cranial lesions, destruction of joint surfaces in the left hand, and loss of cortex in ribs; notable lack of muscle insertions consistent with disability in the period leading up to death 15 neonate 17th-18th c. nearly complete skeleton 16 middle I 13th-14th c. lower legs only adult 17 26-45 M 13th-14th c. torso only healed periostitis of internal surfaces of two right ribs; mild osteophytosis of middle thoracic vertebrae; Schmol’s nodes of lower thoracic vertebrae and L4 18 middle F 17th c. upper torso only LEH estimated to have formed adult between 2-3 years and 4-5 years of age 19 neonate 14th-17th c. nearly complete skeleton 20 older M 13th-14th c. but nearly complete severe osteoarthritis between cervical predating skeleton vertebrae 3-4; bilateral osteoarthritis of B16-17, 22 shoulders, sternoclavicular joints, wrists, hips, knees, ankles, some metacarpophalangeal and interphalangeal joints; fusion of three cervical vertebrae and right side of T10-T11; bilateral fusion of the

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Summary of Results from Buckley and Hayden (2002) Burial Age Sex Time Period Grave Contents Pathological Characteristics & Notes superior sacrum to the ilia consistent with diffuse idiopathic skeletal hyperostosis; ossification of the linea aspera, attachments for the Achillies’ tendon, and iliac crests; LEH estimated to have formed between 1-5 years 21 36-45 M 13th-14th c. but skull, right shoulder, LEH estimated to have formed predating upper vertebrae between 2-4 years B16-17, 22 22 older M 13th-14th c. skull and left torso severe osteoarthritis of all cervical only; shaft of a broken vertebrae; mild osteophytosis of lower high-cross shaft, cervical vertebrae, ossified thyroid, 1 apparently used as a observable LEH estimated to have grave marker formed between 3-4 years; severe dental wear 23 36-45 M 13th-14th c. but skull and left torso LEH estimated to have formed predating between 2-4 years B16-17, 22 24 26-45 F 13th-14th c. but mostly complete mild osteoarthritis of upper lumbar predating skeleton vertebrae; squatting facet of right B16-17, 22 fibula 25 36-45 M 13th-14th c. but incomplete torso, Possibly healed trepanation if skull predating pelvis, proximal femora F136 belongs to B25; osteophytosis of B16-17, 22 all lumbar vertebrae; Schmorl’s nodes of T8-T12, L1

Linear enamel hypoplasia were observed in all individuals with teeth from the 13th-14th centuries (n=5) (Buckley and Hayden, 2002). According to Buckley and Hayden (2002), all but one of the five individuals had between one and two LEH, and one individual had five.

Unilateral cribra orbitalia was present on the left orbit of one individual (B2), an older adult male

(Buckley and Hayden, 2002). One individual (B17), an adult male, exhibited healed periostitis of two right ribs consistent with pneumonia or pleurisy; no signs of tuberculosis were observed in this individual (Buckley and Hayden, 2002). However, tuberculosis is likely in B13, whose burial dates from about the 17th-18th century (Buckley and Hayden, 2002). For this individual, tuberculosis is the most likely diagnosis because the individual exhibits osteolytic circular lesions to the thoracic vertebrae, destruction of some rib bone and the joints in the left hand, and osteolytic cranial lesions (Buckley and Hayden, 2002). There were few muscle attachments

123 noted, which Buckley and Hayden (2002) write is consistent with a long period of decline prior to death. Overall trends in Buckley and Hayden’s (2002) observations suggest the burials buried at Mercer Hospital experienced stress events in early childhood (1-5 years) that manifested in

LEH. As adults, these people likely engaged in manual labor, indicated by frequent osteoarthritis, osteophytosis, and the incidence of squatting facets (Buckley and Hayden, 2002).

The burial numbers of individuals that could have been included in this dissertation are bolded in Table 7, and the time period group is indicated by color. To be included in this dissertation, individuals had to be adults with at least one of the elements used for aging (i.e., pubic symphysis, auricular surface, cranial sutures) and/or at least two anterior teeth present.

Burials described in Buckley and Hayden (2002) that are possibly included in this dissertation are B6-7, B9, B13, B17-18, and B20-25. Of these, five are from the late medieval period, and seven are from the post-medieval period.

It is possible that the post-medieval burial B13 in Buckley and Hayden (2002) corresponds to SK1015 in this dissertation because this individual is described as having pitted hypoplasia on a canine and incisor, and SK1015 is the only individual in the sample from Mercer

Hospital in this dissertation who exhibited pitted hypoplasia, which were observed on one canine and one incisor. Additionally, both B6 and SK1015 were found to be young adults. It is possible that the post-medieval burial B7 in Buckley and Hayden (2002) corresponds to either SK1012 or

SK1108 in this dissertation because this individual is described as having cribra orbitalia, which was noted on only two skeletons from Mercer Hospital in this dissertation (SK1012 and

SK1108). However, Buckley and Hayden (2002) estimate B7 to be a late middle adult, and

SK1012 and SK1108 were found in this dissertation to be young adults.

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Because the burial numbers in the publication were unable to be matched to the museum numbers (except for SK1015, which is probably B7), a random number generator was used to assign the individuals from Mercer’s Hospital to either the late medieval or post-medieval category. These are presented in Table 8.

Table 8: Time period assignments for Mercer’s Hospital made using a random number generator

Time Period Assignments for Mercer’s Hospital Burial Assigned Time Period SK 1002 late medieval SK 1012 late medieval SK 1015 post-medieval SK 1027 post-medieval SK 1028 late medieval SK 1052 post-medieval SK 1066 late medieval SK 1075 post-medieval SK 1076 post-medieval SK 1082 late medieval SK 1083 late medieval SK 1102 late medieval SK 1108 post-medieval SK 1111 post-medieval SK 1114 post-medieval SK 1128 post-medieval SK 1151 post-medieval SK 1152 post-medieval SK 1153 late medieval SK 1154 post-medieval SK 1158 late medieval SK 1160 post-medieval SK 1162 late medieval SK 1165 late medieval SK 1167 post-medieval SK 1169 late medieval SK 1172 post-medieval SK 1178 late medieval

North King St.

The site of North King St. was excavated beginning in September 1999 by Dermot Nelis,

IAC, Ltd. ahead of development for a community center (Bennett, 2000:71-72). The site is located in an area previously known as Little Green and/or Abbey Green (Bennett, 2000) and is

125 the former site of the Benedictine Abbey of St. Mary (Office of the Irish Builder, 1892). The land outside the abbey was originally granted to the city in 1213 for use as a common pasture. It was used as a common grazing area until the early 18th century, when the land within the northern extent of the pasture was designated as the site of a future church (Bennett, 2000).

The rest of the land belonging to the abbey was divided after the dissolution of the monasteries by King Henry VIII in the mid 16th century (Unpublished Excavation Report, 98E0088). The parcel of land previously given to the city of Dublin for common grazing was used as a residence for the Barons of Mellifont in the early and mid-17th century, and the land to the east was given to the Earl of Drogheda. By the end of the 17th century, most of the land had been designated for the proposed church and churchyard of St. Michan’s (Unpublished Excavation Report, 98E0088)

(Figure 12).

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Figure 12: Engraving of St. Michan’s Church in 1834. From the Dublin Penny Journal, Vol. 2, accessed from dublincity.ie

Until 1707, St. Michan’s was the only parish in Dublin north of the River Liffey (Wright,

1821, Ronan, 1948, Fagan, 1991). By April 1727, congregation growth required the division of

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St. Michan’s parish into three churches (namely, St. Michan’s, St. Mary’s, and St. Paul) (Ronan,

1948, Fagan, 1991) and the construction of a new, larger church (Unpublished Excavation

Report, 98E0088). The entrance to St. Michan’s was located on North King St. (Young, 1940). It is therefore probable that the people excavated from the North King St. site were worshipers at

St. Michan’s and members of the same parish.

While most of the parish documents were lost in the 1922 fire at Dublin’s Public Record

Office, some of the vestry minute books survived. According to the surviving vestry minute books, the congregation was largely impoverished, so much so that the attending members of a

1764 vestry meeting state that they are unable to raise taxes on the parish (Vestry Minute Book

1760-1776, f73:74 in Unpublished Excavation Report, 98E0088). According to Whitelaw

(1805), 78.6% of the population of St. Michan’s parish in 1798 was identified as lower class, while only 15% was identified as upper or middle class. Many people buried in the graveyard at

North King Street were buried at the expense of the church, supporting the conclusion that a large proportion of the congregation was impoverished (Unpublished Excavation Report,

98E0088). These individuals were buried in “charity coffins,” so the use of coffins (Young,

1940) in Dublin at this time cannot be linked to socioeconomic status. However, the relative degree of poverty is recorded as less than poverty in the contemporary parish of St. Luke’s

(represented in this dissertation by the Coombe/Cork St. sample) (Sheridan-Quantz, 2001).

While several notable wealthy patrons did attend St. Michan’s, the neighborhood surrounding the church presented the contrasting lifeways of the very rich and very poor. It included gentlemen’s houses, tenement houses, and businesses (Young, 1940). Young (1940) also describes poverty in the parish of St. Michan’s as being widespread, though the church

128 wardens worked to alleviate poverty by establishing a charity school within the parish and issuing badges to local mendicants, making it legal for them to beg (Young, 1940).

According to Young (1940), the number of foundling children also indicates the degree of poverty within the parish of St. Michan’s. Church records list the number of burials of children found abandoned and deceased around the parish (Young, 1940). Records also show that the number of children sent to workhouses from St. Michan’s parish comprise a large proportion of the total number of children sent to workhouses in the city of Dublin (Young,

1940), though it should be noted here that St. Michan’s contained a large share of the city’s total population (described below). For example, in the year 1730, there were 265 children sent to workhouses from the city of Dublin; 58 of these were from St. Michan’s parish (Young, 1940).

Most foundling children did not survive to be sent to the workhouses. Rather, most of them died within a month of their abandonment (Young, 1940).

St. Michan’s parish was one of the more crowded areas in Dublin, and in 1695, 1,101 houses were recorded, representing one sixth of the city population (Young, 1940). By 1718, the number of houses recorded in the three parishes of St. Michan, St. Paul, and St. Mary, into which the parish of St. Michan had been divided, was 3,214 and represented about one-third of the city’s population (Young, 1940). By 1798, the parish population had grown to 18,092 (Jordan,

2013).

While the first reference to burial in the vestry minute books does not occur until 1761, burials are recorded in the decades before in the Church Warden’s account books. The earliest reference to burials is found in the Church Warden’s accounts for the year 1743 (Unpublished

Excavation Report, 98E0088). According to the 1743 Church Warden’s account, a man by the name of William Fremand paid cash for the “burying a Corps [sic] at Little Green” Church

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Warden’s Account Book 1723-1761 f251 in Unpublished Excavation Report, 98E0088). There are no references to burials in any document, including the Church Warden’s accounts and the vestry minute books, after 1764. This suggests that the cemetery was used primarily between

1743 and 1764, though it could have been used sporadically in the years before and the years after (Unpublished Excavation Report, 98E0088).

By 2000, 430 articulated skeletons and 120 disarticulated human bones had been excavated (Bennett, 2000). Most of these individuals were buried during the period of official cemetery use by the church, though a later phase of burials was identified. These later burials were exclusively the remains of infants and neonates, suggesting that the site was used as a cilín after the use of the site as a formal cemetery ended (Unpublished Excavation Report, 98E0088).

It is estimated that about 60% of the population of St. Michan’s was Protestant, and 40% was

Catholic (Fagan, 1991), suggesting that a slight majority of these burials were those of Catholics.

Smithfield

Excavation at this site began in March 2002 and lasted until 2003 (excavations.ie).

Smithfield is located in Dublin near Smithfield Market at the old site of Oxmantown Green, and is within the square surrounded by Queen Street, North King Street, Smithfield Terrace, and

Haymarket (excavations.ie). In 1664, the site of Oxmantown Green was auctioned off in parcels of land to local tenants and developers. Prior to this, however, Smithfield appears to have been used as an informal burial ground. Twenty-seven burials were revealed during the excavation, but not all of them were buried with a west-east alignment typical of a Christian burial. It is suggested that these burials represent either hanging victims from the nearby gallows

(excavations.ie). The Oxmantown Gallows are recorded as one of the two main execution sites

130 for soldiers, militiamen, religious dissenters, and convicted criminals in the 18th-century (The

Irish Builder, 1895). Records of those executed at the site still exist, and it is not impossible

(though it is unlikely) that some of the names listed correspond to the burials excavated from

Smithfield (see Table 9 for examples).

Table 9: Known hanging victims at Smithfield. 1D’Alton (1838), 2Exshaw (1742)

Name Year of Execution Reason for Execution Doctor Dermot Hurley, Archbishop of Cashel1 Late 1500s Religious dissent Charles Carty2 1742 Robbery Thomas Dolan2 1742 Robbery James Griffith2 1742 Robbery Stephen Jones2 1742 Robbery Charles McDaniel2 1742 Robbery William Spain2 1742 Robbery

Alternatively, these burials could be victims of one of several uprisings that occurred on site during the 16th and 17th centuries (excavations.ie). One such uprising, for example, took place in 1649 and was led by Parliamentary Leader Colonel Jones against the Marquis of

Ormand at Castleknock (D’Alton 1838).

St. Mary’s Crypts

St. Mary’s Crypts are located on Mary St. between Wolfe Tone St. and Jervis St. in

Dublin (Wright, 1821, Bennett, 2000:77). The site was excavated in May 1998, during which time six underground crypts containing human burials in lead coffins and disarticulated human bone were found (Bennett, 2000:77). St. Mary’s is one of three parishes into which St. Michan’s was subdivided. In 1697, rapid population growth required that the parish of St. Michan’s be divided into three neighboring parishes, namely, St. Michan’s, St. Paul’s, and St. Mary’s (Ronan,

1948, Fagan, 1991, Igoe, 2001), as described above. The skeletons excavated from North King

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St. are also from this group of parishes, likely representing the parish of St. Michan’s (see above)

(Igoe, 2001).

Compared to the parish of St. Michan’s (represented in this dissertation by the North

King St. sample), the parish of St. Mary was relatively wealthier, with only slightly over 50% of inhabitants being recorded as belonging to the lower class (Sheridan-Quantz, 2001). Usher

(2012) describes St. Mary’s as one of the wealthiest parishes in Dublin. More than a quarter of inhabitants were recorded as belonging to the upper or middle class (Sheridan-Quantz, 2001), a proportion which is nearly double the percentage of upper or middle class residents of St.

Michan’s parish.

The graveyard at St. Mary’s was used between 1700 and 1855 (Igoe, 2001), and during this time, Fagan (1991) estimates that the number of Catholics amounted to at least one-third of the population of the parish. Numerous people of wealth and local prominence were buried here, including the founder of Mercer’s Hospital (described above), bishops, and a lieutenant (Wright,

1821).

St. Mary d’Urso

St. Mary d’Urso was excavated in 1989 by Eoin Halpin and then in 1995 by Donald

Murphy ahead of development for a local Garda station (Bennett, 1996:60-61) in Drogheda

(Halpin, 1996). The site is bound to the north by Old Abbey Lane, to the east by Dominick

Street, and to the south by the River Boyne (Figure 13) (Halpin, 1996). The town wall would have bounded the site to the west (Halpin, 1996). The rapid development of the town of

Drogheda in the 12th and 13th centuries on previously unoccupied land is consistent with a period of intense Anglo-Normal colonization (Halpin, 1996). The site is the location of a former late

132 medieval hospital and priory (Bennett, 1996:60-61) dating from about the 13th century

(excavations.ie).

Figure 13: Site location of St. Mary d'Urso. Image from Halpin (1996) Figure 2.

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The hospital was founded at some point between AD 1206 and 1214 by wealthy

Drogheda resident Ursus de Swemele (Halpin, 1996). The hospital was located outside of the town walls, which was a typical practice in medieval Ireland (Halpin, 1996).

The hospital was permitted to perform some sacraments on patients and inmates, but these were largely limited to confession. Burials were performed for free, and all funds collected on the main feast days in the Catholic calendar (e.g., Feast of the Ascension) were required to be sent to the local church, not the hospital (Halpin, 1996). While these rules limited the money that the hospital could collect from services, the hospital was in relatively good financial standing during the 1200s, and by AD 1228, it had become a priory, a monastic site with landholdings

(Halpin, 1996). These landholdings would have provided sufficient income to keep the hospital/priory in operation and amounted to 260 acres of land outside of the town of Drogheda,

18 properties within the town, and more than 120 acres of land outside of Drogheda but in Co.

Louth (Halpin, 1996). Tenants who lived on these lands would have been required to pay rent

(Halpin, 1996). By the time of the dissolution, St. Mary d’Urso was the most valuable monastic establishment in Co. Louth (Halpin, 1996).

There were two areas of excavation. The first area to be excavated (Area 1) was located on the southeast part of the site and amounted to about 350 square meters (Halpin, 1996). There were three phases of activity in Area 1 (Halpin, 1996). Phase I was characterized by a ditch, into which a burial was placed (Halpin, 1996). The burial was that of an adult female and was consistent with a Christian burial, but was damaged by later construction of a pit and stone fireplace (Halpin, 1996). Pottery consistent with the 13th-14th centuries was found in the grave fill (Halpin, 1996). The second phase was characterized by a layer of re-deposited soil, basement rooms, pits, and a drain (Halpin, 1996). The last phase in Area 1 was characterized by brick

134 drains and buildings consistent with contemporary 18th and 19th century commercial buildings

(Halpin, 1996).

The second area to be excavated (Area 2) was located south of the medieval church and revealed the presence of numerous monastic buildings. The finding of monastic buildings corroborates the presence of multiple buildings indicated as ruins in an 1836 map. Several graves were identified on the west side of these monastic buildings. These were described as two adult females and one adult male.

Despite the wealth of St. Mary d’Urso, the building materials appear to be locally sourced from limestone quarries in Drogheda (Halpin, 1996). Similarly, most of the medieval pottery was locally produced. These included bowls, cooking pots, storage jars, and decorated jugs

(Campbell, 1996). Some medieval pottery, however, was imported (e.g., Saintonge and other

French pottery, English pottery). Sherds of imported ceramics were almost exclusively from jugs

(Campbell, 1996), suggesting that wine was also being imported.

The burials were analyzed by Loreen Buckley, and all four are included in this dissertation. Buckley’s (1996) findings are presented in Table 10.

Table 10: Summary of skeletal data for St. Mary d’Urso by Loreen Buckley

Summary of Results from Buckley (1996) Burial Sex Age Time Period Pathological Characteristics & Notes 1102 F 25-35 13th-14th c. mild arthrosis of some thoracic and lumbar vertebrae and corresponding ribs; LEH present on all remaining teeth 5049 M 25-35 13th-14th c. LEH on mandibular teeth; exostoses of foramen magnum; retention of metopic suture 5050 F 35-45 13th-14th c. Scoliosis; osteoma and severe osteophytosis on L5; mild osteophytosis of other lumbar vertebrae; osteoarthritis of shoulders and knees; os acromiale of the left shoulder; caries; LEH on canines, first premolars, URI2, LRM3; unusually narrow greater sciatic notch, but all other skeletal indicators are female; exostoses of foramen magnum; retention of metopic suture 5051 F 18-25 exostoses of foramen magnum; possible scoliosis; LEH present on all remaining teeth; caries; retention of metopic suture

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Buckley (1996) suggests that the burials from Area 2 (SK 5049, 5050, and 5051) could be a family because all retain the metopic suture. The presence of arthritic changes to the shoulders and the os acromiale of the left shoulder of SK 5050 are consistent with archery or some other task placing stress on the shoulder joints (Buckley, 1996). The prevalence of dental caries suggests a diet rich in carbohydrates, and the presence of LEH in all individuals suggests a period of stress (e.g., infection, dietary deficiency) in childhood (Buckley, 1996).

Trim Castle

Trim Castle was excavated in the 1970s and then again from April 10th, 1995 to January

12, 1996 in accordance with conservation efforts from the Office of Public Works (Bennett,

1996:73-75, Hayen, 2011). The focus of the second phase of excavation was the interior and exterior of the keep, along the eastern and north-eastern curtain wall, and within the Great Hall

(Bennett, 1996). Excavation showed that the site of Trim Castle was used as early as the prehistoric period, albeit minimally (Bennett, 1996, Hayden, 2011). The site saw further development in the early medieval period with the construction of post, wattle, and daub buildings. After the Anglo-Norman invasion, a ringfort with an earthen bank and timber palisade surrounded by a ditch was constructed in 1172 (Bennett, 1996, Hayden, 2011). Construction of the stone castle began in 1175 and continued into the 1200s (Sweetman et al., 1978, Bennett,

1996). The castle saw a series of renovations between the 14th and 17th centuries, and by the 18th century, the castle had fallen into disuse and disrepair, and the stones were robbed for local construction (Bennett, 1996). Archaeological evidence demonstrates frequent use of kilns in the post-medieval period (Sweetman et al., 1978). Relatively few pieces of post-medieval pottery

136 were found, and these were largely confined to the fills of the towers of the castle curtain wall

(Sweetman et al., 1978).

The burials in this dissertation date to about the 18th-19th century (Bennett, 1996, Hayden,

2011). Other burials were excavated, and these dated to about the twelfth to fourteenth centuries

(Hayden, 2011). These individuals were not included in this study.

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Chapter 6: Methods

To evaluate potential differences in health between the late medieval and post medieval period, two main hypothesis were tested. One methodological hypothesis was also tested. While testing these hypotheses, a number of additional questions arose. These are illustrated in Figure

14: Summary of hypotheses and questions. In this chapter, the methods for testing each hypothesis are described. The methods used to answer additional questions are outlined after the relevant hypothesis. That is, methods used to answer questions pertaining to age-at-death are outlined within the section for the first hypothesis, and methods used to answer questions pertaining to LEH are outlined within the section for the second hypothesis. A summary of methods is given at the beginning of each section (Figure 15-Figure 36). All statistical tests were performed in SPSS unless otherwise noted.

138

Figure 14: Summary of hypotheses and questions

139

Hypothesis 1: A greater proportion of the population from the late medieval English Pale will have survived to older ages than from the post-medieval English Pale.

•Buikstra & Assess sex Ubelaker (1994)

Estimate age •Milner & Boldsen (2002) •Mean •Median Calculate descriptive •Minimum statistics •Maximum •Standard deviation Illustrate data •Histogram

Test for normality •Shapiro-Wilk

•Kaplan-Meier Compare •Log rank survivorship •Compare to Gompertz model

Figure 15: Methods used to test hypothesis 1

Sex assessment was required before age estimation. Sex was assessed using a combination of cranial and pelvic traits (e.g., greater sciatic notch, ischiopubic ramus, subpubic angle, subpubic concavity, sacral curvature, mental eminence, supraorbital ridge, mastoid process) after Buikstra and Ubelaker (1994). Nearly all individuals were sexed using at least two indicators. “Probable” and “possible” males were classified as “males,” and “probable” and

“possible” females were classified as “females.

Age estimation in adult skeletal remains is difficult for a variety of reasons. First, unlike the juvenile skeleton, changes to the adult skeleton are degenerative, not developmental (Boldsen

140 et al., 2002). Consequently, while predictable growth patterns allow for the reasonably precise and accurate estimation of age in subadult skeletons, degenerative changes are highly variable and therefore less predictable (Boldsen et al., 2002, Cunha et al., 2009). Genetic, epigenetic, hormonal, and environmental conditions cause degenerative changes to vary in the time of onset, the anatomical regions affected, and the rate of change (Manolagas et al., 2013, Almeida et al.,

2017, Couoh, 2017). Because these changes are cumulative, the error range is positively correlated with age (e.g., Hens et al., 2008, Wittwer-Backofen et al., 2008, Savall et al., 2016). In other words, the age estimations for younger individuals have smaller error ranges because these individuals have accumulated less degenerative change than older individuals, for whom error ranges are much higher (Buckberry, 2015).

Second, age estimates are affected by varying degrees of preservation between individuals and skeletal elements (Cappella et al., 2017). For example, while the cranium is less fragile and therefore often better preserved than the pubic symphysis, cranial sutures are far less reliable as age indicators than the pubic symphysis (Cappella et al., 2017).

Third, adult age estimation is further complicated by age mimicry, a phenomenon in which the age structure of the reference population (i.e., the population from which the method was derived) is imposed upon the target sample (i.e., the population for which age is being estimated) making it appear as though the age-at-death distribution for the two groups is the same (Bocquet-Appel and Masset, 1982, Boldsen et al., 2002, Buckberry, 2015). For example, when Murray and Murray (1991) tested the auricular surface aging method by Lovejoy and colleagues (1985) on the Terry Collection, they found that a large proportion of individuals died between the ages of 30-40 even though at the time of the study, more than one-third of the individuals in the Terry Collection were at least 61-years-old when they died. The age-at-death

141 distribution in the target sample was therefore more similar to the Hanmann-Todd collection, from which the auricular surface method was constructed, than it was to the actual composition of the Terry Collection. While at the time Murray and Murray (1991) insisted that age mimicry did not affect their results, these findings suggest otherwise.

In addition to providing increasingly wide age ranges and producing age mimicry, the reliance on traditional estimation methods that were constructed using populations with peak mortality between young and middle adulthood reduces the number of older adults detected in archaeological populations (Milner and Boldsen, 2012). To help mitigate these problems,

Boldsen and colleagues (2002) developed the Anthropological Database, Odense University

(ADBOU), a program that uses transition analysis to estimate age in adult skeletons. ADBOU uses skeletal traits on the cranium, auricular surface, and pubic symphysis to calculate the likelihood that an individual died within a specified age range given that the individual exhibits a combination of skeletal traits (Boldsen et al., 2002).

While transition analysis has been shown to be more accurate than other age estimation methods (e.g., Lovejoy et al., 1985, Meindl and Lovejoy, 1985, Isçan and Loth, 1986a, 1986b)

(Godde and Hens, 2012, Maaranen and Buckberry, 2016) and better at revealing older individuals in archaeological populations (Bullock et al., 2013), Milner and Boldsen (2012) found that the pubic symphysis remains the most accurate age indicator. However, because the pubic symphysis is fragile and often poorly preserved, transition analysis was used as the primary means of age estimation in this study. Cranial sutures, the auricular surfaces, and pubic symphyses were photographed and scored using the transition analysis scoring sheet by Boldsen and colleagues (2002) from http://math.mercyhurst.edu/~sousley/Software/. Scores (Appendix

A) were entered into ADBOU using the “white ancestry” hazard for males, females, or

142 individuals of unknown sex in archaeological populations to produce a maximum likelihood

(ML) age estimate and a 95% confidence interval for each individual.

The pubic symphysis was used as the secondary means of age estimation after Brooks and Suchey (1990). Because the pubic symphysis is fragile and subject to poor preservation, and because it is a component of transition analysis, it was not used as the primary means of estimating age. However, because transition analysis is not necessarily more accurate than traditional age estimation methods on all populations (Xanthopoulou et al., 2018, Clark et al.,

2020) or for populations with no known-age reference population (Milner and Boldsen, 2012), it was decided to use the Brooks and Suchey (1990) method in addition to transition analysis.

When present and preserved, the pubic symphyses were photographed and later scored according to Brooks and Suchey (1990) so that the recent observations for transition analysis would not affect the scores for the pubic symphysis and lead to confirmation bias.

Third, fusion of the medial clavicle, first sacral vertebra, and superior ilium, as well as the development and eruption of the third molar and ossification of the thyroid were used as tertiary age indicators. The transition analysis and 95% confidence intervals were checked against the Brooks and Suchey (1990) pubic symphysis and tertiary age indicators.

Permission to photograph human remains was granted by Dr. Nessa O’Conner at the National

Museum of Ireland.

Descriptive statistics (i.e., mean, median, minimum, maximum, and standard deviation) of the maximum likelihood age-at-death were performed on 257 individuals from the late medieval period and 351 individuals from the post-medieval period. Histograms were constructed for each time period to illustrate the age-at-death distributions. A Shapiro-Wilk test was used to test whether or not each age-at-death distribution was normal.

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Survival functions, i.e., S(t), were estimated by constructing Kaplan-Meier curves for all medieval and post-medieval sites, medieval males and females, and post-medieval males and females to compare survivorship in each group. The survival function produces the percentage of the population that survived beyond a given point (Kumar Goel et al., 2010). For example, if S(t) at age 55 was 0.615, then 61.5% of that population survived at least until the age of 55.

The Kaplan-Meier survival estimate was produced using the following equation (Kaplan and

Meier, 1958):

* !(#) = & '1 − , + -./-

The modal survival time is the point at which !(#) crosses 0 = 0.50. Kaplan-Meier survival curves were compared using log rank tests and hazard ratios (Altman, 1991). Log rank tests were performed using the following equation and comparing the value to the 45 distribution with one degree of freedom (n-1):

5 5 (67 − 87) (6 − 8 ) + : : 87 8:

Where 67 is the number of observed deaths in group A, or,

*<=#ℎ? @+ ABCDE F 6 = 7 #C#=G *<=#ℎ? @+ ABCDE F =+* H

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EA is the sum of the expected number of failures in group A across all time periods, or

+ + + I(* J 7) (* J 7) (* J 7) + -K, + -5… + -N

Where d is number of deaths in groups A and B at time t, na is the number of individuals at risk in group A at time t. EB is the sum of the expected number of failures in group B across all time periods and is calculated in the same manner as EA.

Finally, the Kaplan-Meier survival curves for each site were compared to the Gompertz mortality model, which controls for the exponential increase in the risk of mortality with age using the following function (Gompertz, 1825):

Where λ is the initial mortality rate providing the shape of the function, e is Euler’s constant, Υ the exponential increase in risk of death with senescence, providing the rate of change of the function (Ricklefs and Scheurlein, 2002), and t is the age at death. The Gompertz model of mortality was chosen over the Gompertz-Makeham because Makeham’s constant accounts for the risk of death in childhood independent of senescence (Hallén, 2009), and there are no children included in this sample. The Kaplan-Meier survival curves were compared to the

Gompertz mortality model using R after DeWitte (2014a).

The results of the initial age-at-death comparison prompted a number of additional questions.

These are:

1. Was survivorship different across sites within each time period?

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2. Did survivorship differ between adult males and females in the late medieval period?

3. Did survivorship differ between adult males and females in the post-medieval period?

4. Did survivorship differ between boys and girls in the post-medieval period?

5. Did survivorship for adult males change between the late medieval and post-medieval

periods?

6. Did survivorship for adult females change between the late medieval and post-

medieval periods?

Comparison of Survivorship Across Contemporaneous Sites

Was survivorship different across sites within each time period?

•Mean Calculate •Median descriptive statistics •Minimum •Maximum •Standard deviation •Boxplots Illustrate data •Histograms

Test for normality •Shapiro-Wilk

•Kaplan-Meier curves Compare •Calculate modal survivorship survival time •Log rank test •Pairwise comparisons

Figure 16: Methods used to assess survivorship within time periods

First, descriptive statistics were calculated for each site within both time periods. These data were illustrated using boxplots and histograms. A Shapiro-Wilk test was performed for each site to test for normality. Then, Kaplan Meier curves were constructed to visually compare

146 survivorship across sites. The modal survival time for each site was estimated by identifying the age at which S(t)=0.50 for all sites where the number of individuals was at least five.

Survivorship was compared by performing a log rank test for all late medieval sites and a log rank test for all post-medieval sites. In instances where the log rank test indicated differences, post-hoc pairwise comparisons were performed to identify which sites differed from each other

(Figure 16).

Comparison of Survivorship Between Sexes by Time Period

Did survivorship differ between adult males and females in the late medieval period? Did survivorship differ between adult males and females in the post-medieval period?

•Mean Calculate •Median descriptive statistics •Minimum •Maximum •Standard deviation •Boxplots Illustrate data •Histograms

Test for normality •Shapiro-Wilk

•Kaplan-Meier curves Compare •Calculate modal survivorship survival time •Log rank test •Pairwise comparisons

Figure 17: Methods used to test for differences in survivorship between sexes

Descriptive statistics were calculated for males and females in the late medieval period and post-medieval period. Individuals for whom sex was indeterminate were excluded. Data were illustrated using histograms, and survivorship was illustrated using Kaplan-Meier curves.

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Log rank tests were performed to test for differences in survivorship between late medieval males and females and between post-medieval males and females (Figure 17).

Comparison of survivorship between post-medieval boys and girls

Did survivorship differ between boys and girls in the post-medieval period?

Record names & age-at-death •Irish Burial Index

Infer gender •Mean •Median Calculate descriptive •Minimum statistics •Maximum •Standard deviation Illustrate data •Histograms

Compare •Kaplan-Meier survivorship curves •Log rank test

Figure 18: Methods used to assess differences in survivorship between girls and boys

To test for differences in survivorship between boys and girls in the post-medieval period, burial records were collected from the Irish Burial Index via ancestry.com. The names and ages of all children 14 years and younger who died between 1700 and 1799 and whose burials were recorded in this index were collected. While gender is often inferred from skeletal remains when written records are not available, gender in this case was inferred from names.

Children with characteristically female names (e.g., Eleanor) were classified as girls, and children with characteristically male names (e.g., William) were classified as boys. Children with gender-neutral names (e.g., Frances) and children for whom no name was recorded were

148 excluded. In all, descriptive statistics were calculated for 514 children buried in Dublin between

1700 and 1799. These data were illustrated in histograms. Kaplan-Meier curves were constructed to visually compare survivorship between boys and girls. A log rank test was used to test for differences in the survivorship of boys and girls (Figure 18).

Comparison of Survivorship Between Time Periods by Sex

Did survivorship for adult males change between the late medieval and post-medieval periods?

Did survivorship for adult females change between the late medieval and post-medieval periods?

•Kaplan-Meier curves Compare •Calculate modal survival survivorship time •Log rank test •Pairwise comparisons

Figure 19: Methods used to test for differences in survivorship within sexes

To compare survivorship for males and females between time periods, Kaplan Meier curves were constructed to visually compare survivorship between late medieval and post- medieval males and between late medieval and post-medieval females. A log-rank test was performed to test for differences in survivorship for each sex between time periods (Figure 19).

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Hypothesis 1a

There will be no difference between the age-at-death distribution calculated using transition analysis and the skeletal remains in this dissertation and those calculated using contemporary burial records from approximately the same location.

Record names & age-at-death •Irish Burial Index

•Mean •Median •Minimum Calculate descriptive statistics •Maximum •Standard deviation

Compare survivorship •Kaplan-Meier curves •Log rank test

Figure 20: Methods used to test for differences in ages using transition analysis and contemporary burial records

A search the Irish Burial Index, 1600-1927 via ancestry.com was used to compile a list of all individuals 15 years of age or older buried in Co. Dublin between 1700 and 1799 with either a recorded age-at-death or a birth and death date from which an age-at-death could be counted

(n=2,088) (Appendix B). Descriptive statistics were calculated for these individuals. Kaplan-

Meier curves were constructed to visually compare survivorship between the data collected from the burial records and the data collected from skeletal remains. A log-rank test was performed to test for differences in survivorship between the data collected from burial records and data collected from skeletal remains (Figure 20).

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Hypothesis 2

Individuals from the post-medieval English Pale will exhibit more LEH than individuals from the late medieval English Pale.

•Make Collect data impressions •Make casts •Take pictures

Count LEH •Mean Group into age •Median cohorts •Mode •Minimum Calculate descriptive •Maximum statistics •Standard deviation

Illustrate data •Histograms

Test for normality •Shapiro Wilk •Mann- Compare Whitney LEH U test

Figure 21: Summary of methods used to test hypothesis 2

To compare the number of LEH between the late medieval and post-medieval English

Pale, teeth from 201 individuals were selected for dental analysis. Anterior teeth were selected based on their degree of wear to ensure that only teeth where the majority of the crown is preserved were included. Teeth that were severely worn or that had crowns obscured by calculus were excluded for analysis. A few individuals were excluded because either the enamel was too fragile to make impressions, or because the process of making impressions would have caused the calculus to break.

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Dental impressions were made using Coltene’s President Jet Light Body dental impression material at the Collections Resource Centre in Swords, Co. Dublin, Ireland.

Permission to photograph teeth and make impressions and casts was granted by Dr. Nessa

O’Conner. Casts of the impressions were made using Struer’s Epofix at The Ohio State

University’s Bioarchaeology Laboratory. These were dyed red to enhance visibility. Casts were examined under a Leica photographic microscope, which also collected images of the casts as they were examined (e.g., Figure 22). The order in which the casts were examined was random to minimize bias when observing teeth from the same individual. Each tooth and the location, width, and shape of each LEH was sketched. After all teeth had been examined under the microscope and their defects recorded, the sketches of the LEH were transferred to the recording template from Buikstra and Ubelaker (1994) (Appendix D) using Adobe Photoshop where the width of the LEH is approximately proportional to the number of pixels used to draw the LEH on the template. This permitted the LEH within the same individual to be matched to each other. It was necessary to match LEH within the same individual (rather than simply counting the total number of LEH) because LEH that are present on more than one tooth with overlapping development schedules are more likely to be representative of systemic stress than of localized trauma to the tooth germ (Hillson, 1992).

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Figure 22: Example of a Leica image of a tooth cast (North King Street, B160, LLC) Analysis of LEH is made complicated by dental wear (Hillson, 1996), even in cases such as this where teeth that were very worn were excluded. Over time, dental wear obliterates the tooth crown, eliminating LEH that might have been present. Moreover, dental wear tends to increase with age. The observation of LEH is therefore affected by the age of the individual. In other words, an individual who exhibits minimal dental wear can be expected to have more LEH than an individual with severe dental wear simply because there is more of the crown present.

However, because age affects wear, it can also be expected that the individual who has less wear and more LEH will have died at a younger age than the individual who has more wear, if all other factors are equal. It is therefore necessary to 1) only evaluate teeth for LEH if they have adequate crown preservation and 2) compare LEH between age cohorts.

Individuals were separated into age cohorts (Table 11) using the maximum-likelihood age estimate produced using transition analysis or using the pubic symphysis after Brooks and

Suchey (1990).

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Table 11: Age cohorts for LEH analysis

Age Cohort Age Range 1 15-29 2 30-44 3 45-59 4 60 and up

First, matching LEH in each individual were counted. Second, descriptive statistics for the number of matching LEH were calculated for each age cohort in the late medieval and post- medieval periods. The frequencies of the number of matching LEH per individual were illustrated in histograms. After a Shapiro-Wilk test was used to assess normality, a Mann-

Whitney U test was performed to compare the mean number of matching LEH in each individual in the late medieval period to the mean number of matching LEH in each individual in the post- medieval period, while controlling for age cohort (Figure 21).

Comparison of Variance in Number of LEH Between Time Periods

Did the variance in the number of LEH change between the late medieval and post-medieval periods?

Compare variance •Levene's test

Figure 23: Methods used to test for variance in number of LEH

Levene’s test of equality of variances was used to compare the variance in the number of matching LEH per individual in the late medieval and post-medieval periods (Figure 23).

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Comparison of the Number of LEH Among Age Cohorts by Time Period

Did the number of matching LEH differ between age cohorts in the late medieval periods? Did the number of matching LEH differ between age cohorts in the post-medieval period?

•Mean •Median Calculate descriptive statistics •Mode •Minimum •Maximum •Standard deviation

Illustrate data •Boxplots

Test for normality •Shapiro-Wilk

Compare LEH •ANOVA

Figure 24: Methods used to test for differences in LEH number between age cohorts To compare the number of matching LEH per individual within each age cohort and time period, descriptive statistics were calculated for each age cohort in the late medieval and post-medieval periods. These were illustrated with box-plots, and normality was assessed using a Shapiro-Wilk test. Finally, an ANOVA was performed to compare the mean number of matching LEH per individual between age cohorts in the late medieval period and in the post-medieval period

(Figure 24).

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Comparison of Variance in LEH Number Among Age Cohorts by Time Periods

Did the variance in the number of LEH differ between age cohorts in the late medieval period?

Did the variance in the number of LEH differ between age cohorts in the post-medieval period?

Compare variance •Levene's test

Figure 25: Methods used to test for differences in variance between age cohorts

To test for differences in variance between age cohorts, Levene’s test of equality of variances was performed on age cohorts from the late medieval period and on age cohorts from the post- medieval period (Figure 25).

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Comparison of LEH Number Between Sexes by Time Period

Did males and females in the late medieval period have different numbers of matching LEH? Did males and females in the post-medieval period have different numbers of matching LEH?

•Mean •Median Calculate descriptive statistics •Mode •Minimum •Maximum •Standard deviation

Illustrate data •Boxplots

Test for normality •Shapiro-Wilk

Compare LEH •ANOVA

Figure 26: Methods used to test for differences in number of LEH between sexes

First, descriptive statistics were calculated for late medieval males and females and for post-medieval males and females. These were illustrated with box plots. Then, a Shapiro-Wilk test was performed to determine if the distributions were normal. Finally, a Mann-Whitney U test was performed to compare the mean number of matching LEH for late medieval males and females and the mean number of matching LEH for post-medieval males and females (Figure

26).

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Comparison of LEH Number Between Time Periods by Sex

Did the number of matching LEH change for males between the late medieval period and post- medieval periods? Did the number of matching LEH change for females in the late medieval and post-medieval periods?

Compare LEH •Mann-Whitney U test

Figure 27: Methods used to test for differences in number of LEH within sexes

To test for changes in the number of LEH between time periods for each sex, a Mann-

Whitney U test was performed comparing late medieval and post-medieval males and late medieval and post-medieval females for each age cohort (Figure 27).

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Comparison of LEH Number Between Contemporaneous Sites

Did the number of matching LEH differ across medieval and post-medieval sites?

•Mean Calculate descriptive •Median statistics •Mode •Minimum •Maximum •Standard deviation

Illustrate data •Boxplots

Compare LEH •ANOVA

Figure 28: Methods to assess differences in number of matching LEH across sites

First, descriptive statistics were calculated for each late medieval and post-medieval site.

These data were illustrated in box-plots. An ANOVA was used to test for differences in the mean number of matching LEH among late medieval sites and in the mean number of matching LEH among post-medieval sites (Figure 28).

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Comparison of Variance in LEH Number Between Contemporaneous Sites

Did the variance in the number of matching LEH differ across sites in the late medieval and post-medieval periods?

Compare variance •Levene's test

Figure 29: Methods used to test for differences in variance in the number LEH between time periods

Levene’s test of equality of variances was used to test for differences in variance in late medieval sites and in post-medieval sites (Figure 29).

Comparison of LEH Widths Between Time Periods

Did the width of LEH change between time periods?

Measure LEH •ImageJ

•Mean Group by tooth type •Median •Mode Calculate descriptive •Minimum statistics •Maximum •Standard deviation

Illustrate data •Histograms

Test for normality •Shapiro Wilk

Compare LEH •Mann- widths Whitney U test

Figure 30: Methods used to test for differences in LEH width between time periods

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Because perikymata represent growth increments lasting about 6-12 days (see Chapter 4), it is possible to measure the duration of a stress event that produced an LEH by counting the perikymata within an LEH (Hilson and Bond, 1997). While counting perikymata might be the most accurate way to measure event duration (Hilson and Bond, 1997), perikymata are often worn away or are not captured by the dental impression materials frequently used in archaeological studies (Guatelli-Steinberg, 2004, 2008, Hubbard et al., 2009). In this study, many of the perikymata were indeed worn away, only partially visible, or had not been captured by the Coltene’s President Light Body dental impression material and/or Struer’s Epofix.

Consequently, using perikymata to compare the duration of stress events between groups would reduce the sample size so far that no meaningful conclusions could be drawn, a problem not uncommon for bioarchaeologists (Hubbard et al., 2009).

Because of these limitations, researchers have used the width of LEH to infer the duration of stress events (e.g., Blakey and Armelagos, 1985, Hutchinson and Larsen, 1988, Goodman and

Rose, 1990). However, the spacing of perikymata differs across the crown, meaning that the number of perikymata within each LEH is dependent on both the duration of the stress event and on the region of the crown in which the LEH formed (Hillson and Bond, 1997). The spacing of perikymata at the incisal part of the crown is often greater than or about 100 microns (Hillson and Bond, 1997). This is wider than the perikymata in the mid-crown, where the perikymata are about 70 microns apart, and wider than the perikymata in the cervical crown, which are less than or around 50 microns apart (Hillson and Bond, 1997). It could therefore be expected that LEH that form earlier, that is, near the cusp, would be wider than those that form later, in the cervical crown. Consequently, if width were examined without controlling for the region of the tooth, it would appear that a stress event producing an earlier LEH lasted longer than one that formed a

161 later LEH. In actuality, the two LEH would not be directly comparable because the distribution of perikymata toward the cusp would produce a wider LEH in the incisal region than in the cervical region based simply on the differences in perikymata density between the two regions.

One way of limiting the effect of perikymata spacing when comparing widths of LEH is to restrict measurements to one region of the tooth (Hubbard et al., 2009). In other words, the effect of perikymata spacing can be reduced by only comparing the widths of LEH in the incisal portion of one tooth to LEH in the incisal portion of another tooth (Hubbard et al., 2009).

Similarly, measurements taken from the mid-crown of a tooth should only be compared to measurements from the mid-crown of other teeth, and measurements taken from the cervical region of a tooth should only be compared to measurements from the cervical region of other teeth (Hubbard et al., 2009).

In addition to affecting perikymata density, the region of the tooth also affects variation in perikymata spacing. According to Hubbard and colleagues (2009), the variation in perikymata spacing is greater in the incisal portion of the crown than in the mid-crown or cervical regions. In this dissertation, measurement of LEH width was limited to the cervical region because the cervical region of the tooth has less variation in perikymata spacing (Hubbard et al., 2009) and is least likely to be affected by dental attrition. Measurements were taken in Image J.

LEH widths were then grouped by tooth type (i.e., incisor, canine, premolar) to control for any possible effects of differences in tooth geometry (e.g., the angle at which the striae of Retzius intersect with the surface of the tooth). This was also important because Hubbard and colleagues

(2009) found that variation in perikymata spacing differs not only between regions of the same tooth, but between different tooth types as well.

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Descriptive statistics were calculated for each tooth type in the late medieval period and post-medieval period. Data were illustrated in histograms, and a Shapiro-Wilk test was used to test for normality. Finally, a Mann-Whitney U test was performed to determine whether or not there were differences in the mean width of LEH in late medieval and post-medieval incisors, late medieval and post-medieval canines, and late medieval and post-medieval premolars (Figure

30).

Comparison of LEH Width Between Contemporaneous Sites

Did the widths of LEH differ across sites in each time period?

•Mean Calculate descriptive •Median statistics •Mode •Minimum •Maximum •Standard deviation

Illustrate data •Histograms

•ANOVA Compare LEH •Pairwise comparisons

Figure 31: Methods used to test for difference in LEH width across sites

Descriptive statistics were calculated to test for differences in LEH width across late medieval and post-medieval sites. Data were illustrated in histograms. An ANOVA was used to test for differences in the mean width of matching cervical LEH between sites from each time

163 period while controlling for tooth type. Pairwise comparisons were then performed to identify which sites differed in LEH width (Figure 31).

Comparison of Variance of LEH Width Between Contemporaneous Sites

Did the variance of width of LEH differ across late medieval and post-medieval sites?

Compare variance •Levene's test

Figure 32: Methods used to test for differences in variance of LEH width across sites

Levene’s test of equality of variances was used to test for differences in variance in late medieval sites and in variance in post-medieval sites (Figure 32).

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Comparison of LEH Width Between Time Periods by Sex

Did the width of LEH differ between males and females in the late medieval period? Did the width of LEH differ between males and females in the post-medieval period?

•Mean •Median Calculate descriptive •Mode statistics •Minimum •Maximum •Standard deviation

Illustrate data •Boxplots

Test for normality •Shapiro- Wilk

Compare LEH width •Mann-Whitney U test

Figure 33: Methods used to test for differences in LEH width between sexes

First, descriptive statistics were calculated for the width of matching LEH in each tooth type for males and females in the late medieval period and for males and females in the post- medieval period. Data were illustrated using boxplots. Then, normality was assessed using a

Shapiro-Wilk test. Finally, a Mann-Whitney U test was performed to test for differences between the mean width of cervical LEH in incisors, canines, and premolars in late medieval males and females and between the mean width of cervical LEH in incisors, canines, and premolars in post- medieval males and females (Figure 33).

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Comparison of LEH Width Between Time Periods by Sex

Did the width of LEH change between late medieval and post-medieval males? Did the width of

LEH change for females between late medieval and post-medieval females?

•Mann-Whitney U test Compare LEH width

Figure 34: Methods used to test for differences in LEH width within sexes

A Mann-Whitney U test was used to test for differences in the mean width of matching cervical LEH in males from the late medieval and post-medieval periods, and in the mean width of matching cervical LEH in females from the late medieval and post-medieval periods, controlling for tooth type (Figure 34).

Association Between LEH Number and Age-at-Death

Was the number of LEH associated with age-at-death?

•Pearson product moment Test for relationship correlation coefficient

Figure 35: Methods used to test for association between number of LEH and age-at-death

As described in Chapter 2, the DOHaD hypothesis posits that childhood stress is associated with reduced adult longevity (Gillman, 2007). This is one of the reasons that adult

166 age-at-death was used as a proxy for allostatic load in this dissertation. Indeed, studies have found associations between the number of LEH and adult age-at-death, where individuals with a greater number of LEH, and therefore more stress events manifesting as LEH, died at earlier ages than those with fewer LEH (e.g., Stodder, 1997, Šlaus et al., 2002, Palubeckaité et al., 2002,

King et al., 2005, Boldsen, 2007, Armelagos et al., 2009, Armoroso et al., 2014, Miszkiewicz,

2015, Kyle et al., 2018, Yaussy and DeWitte, 2018). These studies appear to support the hypothesis that childhood stress results in decreased longevity by altering the responsiveness of multiple somatic systems. Others, however, have found no association between LEH and adult longevity (e.g., Watts, 2015).

To test if the number of LEH was associated with age-at-death for the samples in this dissertation, a Pearson correlation test was performed (Figure 35).

Association Between LEH Width and Age-at-Death

Was the width of LEH associated with age-at-death?

Illustrate data •Scatterplot

Test for association •Pearson's correlation

Figure 36: Methods used to test for an association between LEH width and age-at-death

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Since the number of observable LEH is at least in part, dependent on the degree of wear, and because older individuals tend to have more dental wear than younger individuals, the number of LEH is not necessarily an effective way to evaluate the association between childhood stress and longevity. Here, LEH width was used as an indicator of the duration of stress events, and it was hypothesized that wider LEH would be associated with decreased longevity.

Scatterplots were used to visually assess the relationship between the width of matching cervical LEH for each tooth type and age-at-death. The relationship between LEH width and age-at-death was assessed for both time periods combined, and then for each time period separately. Pearson’s product-moment correlation coefficient was used to test for an association between the width of cervical LEH and age-at-death in all individuals and then for late medieval and post-medieval individuals (Figure 36).

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Chapter 7: Age Results

Stress, particularly during childhood, can cause changes to a person’s phenotype that promote survival in the short-term, but can lead to neuroendocrine, metabolic, and immune dysfunction that impair the body’s ability to overcome subsequent challenges and contribute to decreased longevity (Danese and McEwen, 2012, Edes and Crews, 2017). Consequently, it can be expected that individuals who experience more stress suffer poorer health and die at earlier ages than those who experience less (Barker and Osmond, 1986, Barker et al., 1989, Martyn et al., 1995, Barker et al., 2000). To test the veracity of contemporary accounts of Irish health and the merit of revisionist historical narratives that assert that the Irish condition was improved by

English colonization, it is necessary to evaluate health in the periods immediately before and during intensified colonization efforts. Furthermore, because health cannot be directly tested from skeletal remains, inferences about health must be made indirectly using indicators of health present on skeletal remains. Here, age-at-death is operationalized as an indicator of health in the late medieval and post-medieval periods in the English Pale.

The results in this chapter therefore test the following hypothesis:

Hypothesis 1: A greater proportion of the population from the late medieval English Pale will have survived to older ages than from the post-medieval English Pale.

Before each age estimation, the sex of each individual was assessed. Sex assessment data are presented in Table 12.

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Table 12: Sex data by time period

Sex Assessment Data by Time Period M Probable M Possible M Indeterminate Possible F Probable F F Late Medieval 89 1 2 48 6 13 98 Post-medieval 105 8 8 64 9 12 145

Sex assessment data for each site are presented in Table 13. This was required for transition analysis and age estimation after Brooks and Suchey (1990).

Table 13: Sex assessment data by site

Sex Assessment Data by Site M Probable Possible Indeterminate Possible Probable F M M F F Ardreigh 37 2 0 18 2 4 36 Coombe/Cork St. 24 3 4 18 1 3 42 Dominican Priory/Upper 16 1 1 10 1 3 8 Magdalene Essex St. West 1 0 0 0 0 0 0 Graney East 0 0 0 0 0 1 1 Hanbury Lane 5 0 0 3 0 1 2 Holy Trinity 1 0 0 1 0 0 0 Johnstown 28 1 1 12 1 3 38 Mercer Hospital 5 0 0 7 1 1 15 North King St. 69 5 4 38 7 9 94 Smithfield 6 0 1 5 0 0 1 St. Mary’s Crypt 0 0 0 0 0 0 1 St. Mary d’Urso 0 0 0 0 0 1 3 Trim Castle 3 0 0 0 0 0 1

Table 14: Maximum likelihood age estimates from transition analysis for both time periods

Maximum Likelihood Age Estimates N Min. Max. Mean Median Std. Medieval 236 15 85 49.74 41.85 27.80 Post-medieval 319 15 86 51.46 57.30 25.69

Maximum likelihood age estimates are presented in Table 14. Histograms (Figure 37) for the maximum likelihood age-at-death for the late medieval period and post medieval period show that the data are not normally distributed, but are bimodal.

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Figure 37: Age-at-death histograms for late medieval and post-medieval periods

A Shapiro-Wilk test was used to further assess normality by testing the null hypothesis that the data are normally distributed (Table 15) Results show the maximum likelihood age-at-death data for the late medieval (p<0.01) and post-medieval (p<0.01) periods are not normally distributed.

Table 15: Shapiro-Wilk normality test for maximum likelihood age-at-death

Shapiro-Wilk Normality Test by Time Period Time Period H0 N Statistic df Sig. Reject H0 Late Medieval The distribution of the maximum 236 0.847 236 <0.01 Yes likelihood age-at-death for the late medieval period is normal. Post Medieval The distribution of the maximum 319 0.846 319 <0.01 Yes likelihood age-at-death for the post medieval period is normal.

Survivorship between the late medieval and post-medieval periods was assessed by constructing Kaplan-Meier survival curves (Figure 38). A log-rank test showed that there was no difference in survivorship (p=0.716) (Table 16).

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Figure 38: Kaplan-Meier survival curves for late medieval and post-medieval periods

Table 16: Log-rank test for late medieval and post-medieval survival curves

Log-Rank Test for Late Medieval & Post Medieval Survival Curves H0 Chi-Square Df Sig. Reject H0 Log-Rank (Mantel- There is no difference in 0.132 1 0.716 No Cox) the number of observed deaths between the late medieval and post- medieval period

A Gompertz model was constructed for the late medieval and post-medieval periods using the maximum likelihood age-at-death in R. Figure 39 shows that the skeletal mortality patterns for the late medieval period or post-medieval period appear to differ from the Gompertz model.

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Figure 39: Gompertz fit survival model compared to medieval and post-medieval samples

These results prompted additional investigation. Specifically, the following additional questions were addressed:

1. Was survivorship different in skeletal samples across sites within each time period?

2. Did survivorship differ between adult males and females in the late medieval period?

3. Did survivorship differ between adult males and females in the post-medieval period?

4. Did survivorship differ between boys and girls in the post-medieval period?

5. Did survivorship for adult males change between the late medieval and post-medieval

periods?

6. Did survivorship for adult females change between the late medieval and post-medieval

periods?

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Comparison of Survivorship Across Contemporaneous Sites

Was survivorship different in skeletal samples across sites within each time period?

Descriptive statistics for the maximum likelihood age-at-death are presented in Table 17. A boxplot was used to depict the descriptive statistics for the maximum likelihood age-at-death for individuals across all sites (Figure 40).

Table 17: Descriptive statistics for maximum likelihood age-at-death for all sites

Maximum Likelihood Age Estimates N Min. Max. Mean Median Std. Ardreigh 87 15 83.7 43.71 36 23.63 Coombe/Cork St. 89 15 83.5 45.45 37.4 26.18 Dominican Priory/Upper Magdalene 33 15 81.3 53.45 72.8 27.26 Essex St. West 1 n/a n/a n/a n/a n/a Graney East 2 n/a n/a n/a n/a n/a Hanbury Lane 11 22 79.9 43.25 31.5 23.40 Holy Trinity 1 n/a n/a n/a n/a n/a Johnstown 82 15 85.1 57.93 72.15 76.0 Mercer Hospital 26 15 84.2 47.13 41.85 27.14 North King St. 206 15 85.6 55.25 66.75 24.82 Smithfield 10 15 78.4 35.38 27.65 23.96 St. Mary’s Crypt 1 n/a n/a n/a n/a n/a St. Mary d’Urso 4 n/a n/a n/a n/a n/a Trim Castle 4 n/a n/a n/a 25.40 n/a Upper Magdalene 10 15 77.7 26.61 19.8 19.37

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Figure 40: Age-at-death box plots for all sites

Histograms for the maximum likelihood age-at-death for each site in the late medieval period and post-medieval periods are presented in Figure 41-Figure 46 and Figure 47 - Figure 48, respectively. These histograms show that the data are bimodal and not normally distributed.

Subsequent Shapiro-Wilk tests confirmed that none of the age-at-death distributions in late medieval sites (

Table 18) or post-medieval sites (Table 19) are normally distributed.

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Figure 41: Histogram for Ardreigh age-at-death

Figure 42: Histogram for age-at-death at Dominican Priory/Upper Magdalene

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Figure 43: Histogram for age-at-death at Hanbury Lane

Figure 44: Histogram for age-at-death at Johnstown

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Figure 45: Histogram for age-at-death at Mercer Hospital

Figure 46: Histogram for age-at-death at Smithfield

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Table 18: Shapiro-Wilk test for normality for late medieval sites

Shapiro-Wilk Normality Test in the Late Medieval Period by Site Site H0 N Statistic df Sig. Reject H0 Ardreigh The maximum likelihood age-at- 87 0.849 87 <0.01 Yes death data for individuals buried at Ardreigh are normally distributed. Dominican The maximum likelihood age-at- 33 0.761 33 <0.01 Yes Priory/Upper death data for individuals buried at Magdalene the Dominican Priory/Upper Magdalene are normally distributed. Hanbury Lane The maximum likelihood age-at- 11 0.811 11 0.013 Yes death data for individuals buried at Hanbury Lane are normally distributed. Johnstown The maximum likelihood age-at- 82 0.829 82 <0.01 Yes death data for individuals buried at Johnstown are normally distributed. Mercer’s The maximum likelihood age-at- 26 0.825 26 <0.01 Yes Hospital death data for individuals buried at Mercer’s Hospital are normally distributed.

Figure 47: Histogram for age-at-death at Coombe/Cork St.

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Figure 48: Histogram of age-at-death at North King St.

Table 19: Shapiro-Wilk normality test for post-medieval sites

Shapiro-Wilk Normality Test in the Post Medieval Period by Site Site H0 N Statistic df Sig. Reject H0 Coombe/Cork The maximum likelihood age-at-death 89 0.830 89 <0.01 Yes St. data for individuals buried at Coombe/Cork St. are normally distributed. North King St. The maximum likelihood age-at-death 206 0.845 206 <0.01 Yes data for individuals buried at North King St. are normally distributed. Smithfield The maximum likelihood age-at-death 10 0.774 10 0.007 Yes data for individuals buried at Smithfield are normally distributed.

Kaplan-Meier survival curves were also constructed in SPSS to compare survivorship across all sites (Figure 49) and between each late medieval (Figure 50) and post-medieval site

(Figure 50) and to identify the modal survival time (i.e., where y=0.5) for each site (Table 20).

Sites where the number of individuals were fewer than five were not included in the graphs.

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Figure 49: Kaplan-Meier survival curves for all sites

Table 20: Modal survival times for all sites

Modal Survival Time Across Sites Site Period Modal Survival Time Ardreigh late medieval 40 Coombe/Cork St. post medieval 35 Dominican Priory/Upper late medieval 75 Magdalene Johnstown late medieval 75 Hanbury Lane late medieval 35 Mercer’s Hospital late medieval/post medieval 40 North King St. post medieval 70 Smithfield post medieval 30

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Figure 50: Kaplan-Meier survival curves for late medieval sites

Table 21: Log-rank test comparing survivorship among late medieval sites

Log-Rank Test for Late Medieval Survival Curves by Site H0 Chi-Square df Sig. Reject H0 Log-Rank (Mantel- There is no difference in the 46.775 13 <0.01 Yes Cox) survival distributions among late medieval sites.

A log-rank test was used to test the null hypothesis that there were no differences in survival distributions among late medieval sites (Figure 50, Table 21), and between post- medieval sites (Figure 51, Table 30). Results of the log-rank test comparing survival distributions between late medieval sites (Table 21) show that the null hypothesis should be rejected (p< 0.01), indicating that there are differences among the late medieval sites. A post-hoc pairwise comparison was performed to identify precisely which sites have differing survival distributions (Table 22-Table 29). Results of the post-hoc pairwise comparison show differences in survivorship between Ardreigh and Essex St. West (p=0.028), Ardreigh and Johnstown

(p<0.01), Ardreigh and St. Mary d’Urso (p=0.0.005), Dominican Priory and St. Mary d’Urso

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(p<0.01), Essex St. West and Hanbury Lane (p=0.001), Essex St. West and Johnstown (p<0.01),

Essex St. West and St. Mary d’Urso (p<0.01), Mercer’s Hospital and St. Mary d’Urso (p=0.019),

Johnstown and Mercer’s Hospital (p=0.041), Johnstown and St. Mary d’Urso (p<0.01), and

Mercer’s Hospital and St. Mary d’Urso (p=0.019).

There were fewer than five individuals from Essex St. West and St. Mary d’Urso, so the modal survival time could not be estimated. Consequently, these samples were excluded.

Comparisons of modal survival times between sites for which the null hypothesis could be rejected indicate the directionality of the differences (Table 20). Survivorship at Johnstown

(modal S(t)=75) was greater than at Ardreigh (modal S(t)=40) and Mercer’s Hospital (modal

S(t)=40).

Table 22: Pairwise comparisons for Ardreigh

Pairwise Comparisons for Ardreigh H0 Chi-Square Sig. Reject H0 Dominican There is no difference in the survival 0.484 0.487 No Priory/Upper distributions between Ardreigh and the Magdalene Dominican Priory/Upper Magdalene. Essex St. West There is no difference in the survival 4.808 0.028 Yes distributions between Ardreigh and Essex St. West. Graney East There is no difference in the survival 0.434 0.510 No distributions between Ardreigh and Graney East. Hanbury Lane There is no difference in the survival 0.105 0.746 No distributions between Ardreigh and Hanbury Lane. Holy Trinity There is no difference in the survival 0.035 0.853 No distributions between Ardreigh and Holy Trinity. Johnstown There is no difference in the survival 10.661 <0.01 Yes distributions between Ardreigh and Johnstown. Mercer’s Hospital There is no difference in the survival 0.185 0.667 No distributions between Ardreigh and Mercer’s Hospital. St. Mary d’Urso There is no difference in the survival 8.023 0.005 Yes distributions between Ardreigh and St. Mary d’Urso.

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Table 23: Pairwise comparisons for Dominican Priory/Upper Magdalene

Pairwise Comparisons for Dominican Priory/Upper Magdalene H0 Chi-Square Sig. Reject H0 Essex St. West There is no difference in the survival 6.051 0.014 Yes distributions between Dominican Priory and Essex St. West. Graney East There is no difference in the survival 0.092 0.761 No distributions between Dominican Priory and Graney East. Hanbury Lane There is no difference in the survival 4.357 0.037 Yes distributions between Dominican Priory and Hanbury Lane. Holy Trinity There is no difference in the survival 1.933 0.164 No distributions between Dominican Priory and Holy Trinity. Johnstown There is no difference in the survival 0.608 0.436 No distributions between Dominican Priory and Johnstown. Mercer’s Hospital There is no difference in the survival 2.125 0.145 No distributions between Dominican Priory and Mercer’s Hospital. St. Mary d’Urso There is no difference in the survival 15.379 <0.01 Yes distributions between Dominican Priory and St. Mary d’Urso.

Table 24: Pairwise comparisons for Essex St. West

Pairwise Comparisons for Essex St. West H0 Chi-Square Sig. Reject H0 Graney East There is no difference in the survival 0.059 0.808 No distributions between Essex St. West and Graney East. Hanbury Lane There is no difference in the survival 11.000 0.001 Yes distributions between Essex St. West and Hanbury Lane. Holy Trinity There is no difference in the survival 1.000 0.317 No distributions between Essex St. West and Holy Trinity. Johnstown There is no difference in the survival 0.001 <0.01 Yes distributions between Essex St. West and Johnstown. Mercer’s Hospital There is no difference in the survival 1.572 0.210 No distributions between Essex St. West and Mercer’s Hospital. St. Mary d’Urso There is no difference in the survival 0.000 <0.01 Yes distributions between Essex St. West and St. Mary d’Urso.

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Table 25: Pairwise comparisons for Graney East

Pairwise Comparisons for Graney East H0 Chi-Square Sig. Reject H0 Hanbury Lane There is no difference in the survival 0.947 0.330 No distributions between Graney East and Hanbury Lane. Holy Trinity There is no difference in the survival 0.059 0.808 No distributions between Graney East and Holy Trinity. Johnstown There is no difference in the survival 0.010 0.919 No distributions between Graney East and Johnstown. Mercer’s Hospital There is no difference in the survival 0.275 0.600 No distributions between Graney East and Mercer’s Hospital. St. Mary d’Urso There is no difference in the survival 1.123 0.289 No distributions between Graney East and St. Mary d’Urso.

Table 26: Pairwise comparisons for Hanbury Lane

Pairwise Comparisons for Hanbury Lane H0 Chi-Square Sig. Reject H0 Holy Trinity There is no difference in the survival 0.068 0.074 No distributions between Hanbury Lane and Holy Trinity. Mercer’s Hospital There is no difference in the survival 0.046 0.830 No distributions between Hanbury Lane and Mercer Hospital. St. Mary d’Urso There is no difference in the survival 4.430 0.035 Yes distributions between Hanbury Lane and St. Mary d’Urso.

Table 27: Pairwise comparisons for Holy Trinity

Pairwise Comparisons for Holy Trinity H0 Chi-Square Sig. Reject H0 Johnstown There is no difference in the survival 0.223 0.637 No distributions between Holy Trinity and Johnstown. Mercer’s Hospital There is no difference in the survival 0.008 0.927 No distriutions between Holy Trinity and Mercer’s Hospital. St. Mary d’Urso There is no difference in the survival 2.000 0.157 No distributions between Holy Trinity and St. Mary d’Urso.

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Table 28: Pairwise comparisons for Johnstown

Pairwise Comparisons for Johnstown H0 Chi-Square Sig. Reject H0 Mercer’s Hospital There is no difference in the survival 2.267 0.132 No distributions between Johnstown and Mercer’s Hospital. St. Mary d’Urso There is no difference in the survival 24.448 <0.01 Yes distributions between Johnstown and St. Mary

Table 29: Pairwise comparison for Mercer Hospital

Pairwise Comparisons for Mercer’s Hospital H0 Chi-Square Sig. Reject H0 St. Mary d’Urso There is no difference in the survival 5.475 0.019 Yes distributions between Mercer’s Hospital and St. Mary d’Urso.

Results of the log-rank test comparing the post-medieval sites of Coombe/Cork St.,

Mercer Hospital, North King St., and Smithfield (Table 30) show that the null hypothesis should be rejected (p=0.008), indicating that the survival distributions, and therefore overall survivorship, for these sites are different.

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Figure 51: Kaplan-Meier survival curves for post-medieval sites

Table 30: Log-rank test comparing survivorship in post-medieval sites

Log-Rank Test for Post-Medieval Survival Curves by Site H0 Chi-Square Df Sig. Reject H0 Log-Rank (Mantel- There is no difference in the 3.163 5 0.008 Yes Cox) survival distributions among post-medieval sites.

A post-hoc pairwise comparison was performed to identify which post-medieval sites have differing survival distributions (Table 31- Table 33). Results show that there are differences between Coombe/Cork St. and North King St. (p=0.019) and between North King St. and

Smithfield (p=0.039). The modal survival times (Table 20) indicate the directionality of these differences. Coombe/Cork St. had a lower modal survival time (40 years) than North King St.

(70 years). Similarly, Smithfield had a lower modal survival time (30 years) than North King St.

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Table 31: Pairwise comparisons for Coombe/Cork St.

Pairwise Comparisons for Coombe/Cork St. H0 Chi-Square Sig. Reject H0 North King St. There is no difference in the survival 5.475 0.019 Yes distributions between Coombe/Cork St. and St. North King St. Mercer’s Hospital There is no difference in the survival 0.114 0.736 No distributions between Coombe/Cork St. and Mercer’s Hospital. Smithfield There is no difference in the survival 0.591 0.442 No distributions between Coombe/Cork St. and Smithfield.

Table 32: Pairwise comparisons for Mercer's Hospital

Pairwise Comparisons for Mercer’s Hospital H0 Chi-Square Sig. Reject H0 North King St. There is no difference in the survival 0.114 0.736 No distributions between Mercer’s Hospital and North King St. Smithfield There is no difference in the survival 0.440 0.507 No distributions between Mercer’s Hospital and Smithfield.

Table 33: Pairwise comparison for North King St.

Pairwise Comparisons for North King St. H0 Chi-Square Sig. Reject H0 Smithfield There is no difference in the survival 4.278 0.039 Yes distributions between North King St. and Smithfield.

Comparison of Survivorship Between Sexes by Time Period

Did survivorship differ between adult males and females in the late medieval period?

Descriptive statistics for the maximum likelihood age-at-death for males and females in the late medieval period are presented in Table 34. “Probable” and “possible” females were classified as “female,” and “probable” and “possible” males were classified as “male.”

Individuals for whom sex was indeterminate were excluded. Histograms for the maximum likelihood age-at-death for males and females in the late medieval period show that the data are not normally distributed (Figure 52). This was confirmed with a Shapiro-Wilk test (Table 35).

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Table 34: Descriptive statistics for late medieval males and females

Maximum Likelihood Age Estimates N Min. Max. Mean Median Std. Late medieval males 92 15 85.90 48.78 41.70 24.20 Late medieval females 114 15 83.70 47.28 37.40 25.87

Figure 52: Histograms for age-at-death of late medieval males and females

Table 35: Shapiro-Wilk normality test for late medieval males and females

Shapiro-Wilk Normality Test in the Late Medieval Period by Sex Sex H0 N Statistic df Sig. Reject H0 Males The maximum likelihood age-at-death 92 0.857 92 <0.01 Yes data for late medieval males are normally distributed. Females The maximum likelihood age-at-death 114 0.835 114 <0.01 Yes data for late medieval females are normally distributed.

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Kaplan-Meier survival curves were constructed in Microsoft Excel to compare survivorship between late medieval males and females (Figure 53). Log-rank tests were performed in SPSS to test the null hypothesis that there is no difference in the number of observed deaths (i.e., survivorship) between late medieval males and females. The null hypothesis could not be rejected when comparing late medieval males and females (Table 36)

(p=0.495)

Figure 53: Kaplan-Meier survival curves for late medieval males and females

Table 36: Log-rank test for late medieval males and females

Log-Rank Test for Late Medieval Males & Late Medieval Female Survival Curves H0 Chi-Square Df Sig. Reject H0 Log-Rank (Mantel- There is no difference in the 0.465 1 0.495 No Cox) number of observed deaths between late medieval males and females.

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Did survivorship differ between adult males and females in the post-medieval period?

Descriptive statistics for the maximum likelihood age-at-death for males and females in the post-medieval period are presented in Table 37. “Probable” and “possible” females were classified as “female,” and “probable” and “probable” males were classified as “male.”

Individuals for whom sex was indeterminate were excluded. Histograms for the maximum likelihood age-at-death for males and females in the post-medieval period show that the data are not normally distributed (Figure 54). This was confirmed with a Shapiro-Wilk test (Table 38).

Table 37: Descriptive statistics for maximum likelihood age estimates for post-medieval males and females

Maximum Likelihood Age Estimates N Min. Max. Mean Median Std. Post-medieval males 120 15 85.50 54.74 64.50 24.34 Post-medieval females 164 15 85.60 48.30 51.75 26.39

Table 38: Shapiro-Wilk normality test for post-medieval males and females

Shapiro-Wilk Normality Test in the Post Medieval Period by Sex Sex H0 N Statistic df Sig. Reject H0 Males The maximum likelihood age-at-death 120 0.843 120 <0.01 Yes data for post-medieval males are normally distributed. Females The maximum likelihood age-at-death 164 0.843 164 <0.01 Yes data for post-medieval females are normally distributed.

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Figure 54: Histogram for age-at-death for post-medieval males and females

Kaplan-Meier survival curves were constructed to compare survivorship between post-medieval males and females (Figure 55). Log-rank tests were performed in SPSS to test the null hypothesis that there is no difference in the number of observed deaths (i.e., survivorship) between post- medieval males and females. The null hypothesis could not be rejected (Table 39) (p=0.082)

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Figure 55: Kaplan-Meier survival curves for post-medieval males and females

Table 39: Log-rank test comparing survivorship between post-medieval males and females

Log-Rank Test for Post-Medieval Males & Post-Medieval Female Survival Curves H0 Chi-Square df Sig. Reject H0 Log-Rank (Mantel-Cox) There is no difference in the 3.018 1 0.082 No number of observed deaths between post-medieval males and females.

Comparison of Survivorship Between Post-Medieval Boys and Girls

Did survivorship differ between boys and girls in the post-medieval period?

Skeletal data for children were not collected for this dissertation. However, as part of an exploration into the differences between adult survival curves produced using transition analysis and those produced using historical records, genealogical data had been collected from the Irish

Burial Index, 1600-1927 via ancestry.com. The names and ages of 601 children fourteen years of age and younger who were buried in Dublin between 1700 and 1799 were recorded. Unlike studies of skeletal remains, where gender is often inferred from sex, gender here was inferred

193 using names. Children with gender-neutral names (e.g., Frances) and children whose names were not recorded were excluded, resulting in a sample size of 514 children (Appendix X). Descriptive statistics are presented in Table 40. Histograms show that the data are not normally distributed

(Figure 56 - Figure 57)

Table 40: Descriptive statistics for age-at-death of children in Dublin from 1700-1799

Descriptive Statistics for Childhood Age-at-Death Sample N Min. Max. Mean Median Standard Deviation All 514 0 14 4.47 3.00 3.818 Boys 275 0 14 4.43 3.00 3.947 Girls 239 0 14 4.52 4.00 3.670

Figure 56: Histogram for age-of-death of boys buried in Dublin between 1700-1799

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Figure 57: Histogram of age-at-death for girls buried in Dublin between 1700-1799

Kaplan-Meier survival curves were produced to compare survivorship between post- medieval boys and girls (Figure 58). A log-rank test was performed to test the null hypothesis that there is no difference in the number of observed deaths between post-medieval boys and girls (p=0.917) (Table 41).

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Figure 58: Kaplan-Meier survival curves for children buried in Dublin 1700-1799

Table 41: Log-rank test for survivorship of children in Dublin 1700-1799

Log-Rank Test for Post-Medieval Boys and Girls H0 Chi-Square Df Sig. Reject H0 Log-Rank (Mantel-Cox) There is no difference in the 0.011 1 0.917 No number of observed deaths between post-medieval boys and girls.

Comparison of Survivorship Between Time Periods by Sex

Did survivorship for adult males change between the late medieval and post-medieval periods?

Kaplan-Meier survival curves were constructed to compare survivorship between late medieval males and post-medieval males (Figure 59). A log-rank test was performed in SPSS to test the null hypothesis that there is no difference in survivorship between late medieval males and post-medieval males. The null hypothesis could not be rejected when comparing late medieval and post-medieval males (Table 42) (p=0.256)

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Figure 59: Kaplan-Meier survival curves for late medieval and post-medieval males

Table 42: Log-rank test comparing survivorship of late medieval and post-medieval males

Log-Rank Test for Late Medieval & Post-Medieval Male Survival Curves H0 Chi-Square Df Sig. H0 Log-Rank (Mantel-Cox) There is no difference in the number 1.288 1 0.256 No of observed deaths between late medieval and post-medieval males.

Did survivorship for adult females change between the late medieval and post-medieval periods?

Kaplan-Meier survival curves were constructed to compare survivorship between late medieval females and post-medieval females (Figure 60). A log-rank test was performed in SPSS to test the null hypothesis that there is no difference in survivorship between late medieval males and post-medieval females (Table 43). The null hypothesis could not be rejected when comparing late medieval and post-medieval females (Table 43) (p=0.857)

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Figure 60: Kaplan-Meier survival curves for late medieval and post-medieval females

Table 43: Log-rank test comparing survivorship between late medieval and post-medieval females

Log-Rank Test for Late Medieval & Post-Medieval Female Survival Curves H0 Chi-Square Df Sig. Reject H0 Log-Rank (Mantel-Cox) There is no difference in the 0.032 1 0.857 No number of observed deaths between late medieval and post- medieval females.

Hypothesis 1a Results

There will be no difference between the age-at-death distributions calculated using transition analysis and the skeletal remains in this dissertation and those calculated using contemporary burial records from approximately the same location.

Actual age-at-death data for post-medieval Dublin were collected by making a list of all individuals 15 years of age or older who were buried in Co. Dublin between 1700 and 1799

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(Appendix C). Descriptive statistics for age-at-death data from burial records are presented in

Table 44.

Table 44: Descriptive statistics for adult age-at-death data collected from burial records

Descriptive Statistics for Age-at-Death Burial Records N Min Max Mean Median Standard Deviation 2084 15 107 50.29 50 19.136

These ages were used to construct a Kaplan-Meier survival curve, which in Figure 61 is compared to the Kaplan-Meier survival curve constructed using the maximum likelihood age-at- death for post-medieval skeletons that comprise the sample for this dissertation.

Figure 61: Kaplan-Meier survival curves for transition analysis and burial records

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Survival distributions were compared using a log-rank test (Table 45) to test the null hypothesis that there is no difference in the number of deaths at each age between data compiled using burial records and data compiled using transition analysis.

Table 45: Log-rank test comparing survivorship between transition analysis and burial records

Log-Rank Test for Post-Medieval Skeletal Data and Burial Records H0 Chi-Square df Sig. Reject H0 Log-Rank (Mantel- There is no difference in the 10.362 1 <0.01 Yes Cox) number of observed deaths between post-medieval skeletal data and post-medieval burial records.

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Chapter 8: LEH Results

Linear enamel hypoplasia (LEH) are skeletal indicators of childhood stress (Goodman and Rose, 1990), and because childhood stress contributes to adult health and mortality outcomes

(Barker and Osmond, 1986, Barker et al., 1989, Martyn et al., 1995, Barker et al., 2000), LEH can be used to make inferences about health in bioarchaeological populations (e.g., Rose and

Armelagos, 1978).

The results in this chapter therefore test the following hypothesis:

Hypothesis 2: Individuals from the post-medieval English Pale will exhibit more LEH than individuals from the late medieval English Pale.

The number of matching LEH (e.g., one LEH in the cervical region of each upper central incisor) for each individual for the late medieval and post-medieval periods are presented in

Table 46 and Table 47. Histograms (Figure 62 and Figure 63) show that the data for both time periods are likely skewed left and not normally distributed.

Table 46: Number of matching LEH, sex, and age cohorts for late medieval period

Number of Matching LEH Per Late Medieval Individual Site Individual Sex Number of Matching Age Cohort LEH Ardreigh F94 M 0 2 Ardreigh SK 216 I 1 Ardreigh F 300 M 1 1 Ardreigh F 328 M 1 2 Ardreigh F 336 F 0 1 Ardreigh F 344 I 2 Ardreigh F 353 M 2 4 Ardreigh F 354 F 3 1 Ardreigh F 367 F 2

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Number of Matching LEH Per Late Medieval Individual Site Individual Sex Number of Matching Age Cohort LEH Ardreigh F 371 F 1 1 Ardreigh F 379 F 4 1 Ardreigh F 380 M 3 2 Ardreigh F 381 I 0 1 Ardreigh F 383 I 1 Ardreigh F 384 M 1 4 Ardreigh F 508A I 0 4 Ardreigh F 539 F 1 1 Ardreigh F 545 F 1 Ardreigh F 578 PF 2 1 Ardreigh F 586 M 2 4 Ardreigh F 701 F 3 1 Ardreigh F 802 I 3 1 Ardreigh F 853 M 0 2 Ardreigh F 1326 I 3 Ardreigh F 1403 M 2 3 Ardreigh F 1408 F 2 1 Ardreigh F 1414 F 2 4 Ardreigh F 1416 F 0 1 Ardreigh F 1429 M 0 2 Ardreigh F 1438 F 2 1 Ardreigh F 1448 M 1 1 Ardreigh F 1521 F 3 2 Ardreigh F 1525 I 2 Ardreigh F 1561 F 1 2 Ardreigh F 1570 M 1 4 Ardreigh F 1965 M 6 2 Dominican Priory/Upper B4 F 3 1 Magdalene Dominican Priory/Upper B9 M 1 2 Magdalene Dominican Priory/Upper B21 M 0 4 Magdalene Dominican Priory/Upper B23 I 4 Magdalene Dominican Priory/Upper B34 I 2 Magdalene Dominican Priory/Upper B51 I 0 Magdalene Dominican Priory/Upper B52B M 2 4 Magdalene Essex St. West Skull F 2 1 Hanbury Lane Box 1 SK 50 M 3 4 Holy Trinity Disarticulated I 3 mandible Johnstown B2 F 0 4 Johnstown B89 F 2 1 Johnstown B114 F 2 4 Johnstown B145 M 3 1 Johnstown B153 F 1 4 Johnstown B224 F 3 2

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Number of Matching LEH Per Late Medieval Individual Site Individual Sex Number of Matching Age Cohort LEH Johnstown B235 F 2 2 Johnstown B249 PM 1 1 Johnstown B255 M 2 4 Johnstown B280 M 2 2 Johnstown B295 F 4 1 Johnstown B331 F 2 1 Johnstown B343 M 3 1 Johnstown B360 F 1 2 Johnstown B362 F 3 1 Johnstown B369 I 2 4 Johnstown B372 I 2 Johnstown B379 M 1 1 Johnstown B400 F 4 4 Johnstown B468 M 1 2 Johnstown B485 I 5 2 Johnstown B486 F 0 1 Mercer’s Hospital SK1002 I 4 Mercer’s Hospital SK1008 I 3 Mercer’s Hospital SK1027 M 2 1 Mercer’s Hospital SK1028 F 3 1 Mercer’s Hospital SK1160 I 6 Mercer’s Hospital SK1162 I 3 Mercer’s Hospital SK1169 F 1 3 St. Mary d’Urso F1102 PrF 2 2 St. Mary d’Urso F5050 F 2 St. Mary d’Urso F5051 F 0 1

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Figure 62: Histogram of LEH for late medieval individuals

Table 47: Number of matching LEH, sex, and age cohort for post-medieval period

Number of Matching LEH Per Post-Medieval Individual Site Individual Sex Number of Matching Age Cohort LEH Coombe/Cork St. B716 I 5 Coombe/Cork St. B722 F 2 1 Coombe/Cork St. B724 M 1 1 Coombe/Cork St. B733 F 2 1 Coombe/Cork St. B737 I 3 3 Coombe/Cork St. B759 F 2 1 Coombe/Cork St. B761 I 3 Coombe/Cork St. B763 PrM 1 4 Coombe/Cork St. B767 I 2 Coombe/Cork St. B772 M 3 1 Coombe/Cork St. B777 PrF 0 1 Coombe/Cork St. B783 PrF 0 4 Coombe/Cork St. B790 F 5 3 Coombe/Cork St. B791 F 4 1 Coombe/Cork St. B793 I 3 Coombe/Cork St. B797 I 0 4 Coombe/Cork St. B810 F 2 2 Coombe/Cork St. B811 M 1 1 Coombe/Cork St. B821 M 1 2 Coombe/Cork St. B823 F 0 2 Coombe/Cork St. B828 M 0 4 Coombe/Cork St. B831 PrM 0 4 Coombe/Cork St. B832 I 4 Coombe/Cork St. B834 F 0 1 Coombe/Cork St. B839 F 1 4

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Number of Matching LEH Per Post-Medieval Individual Site Individual Sex Number of Matching Age Cohort LEH Coombe/Cork St. B842 F 2 1 Coombe/Cork St. B847 M 4 3 Coombe/Cork St. B849 I 3 Mercer’s Hospital SK 1015 M 3 1 Mercer’s Hospital SK 1027 M 2 1 Mercer’s Hospital SK 1154 F 0 2 Mercer’s Hospital SK 1160 I 6 North King St. B1 M 2 North King St. B3 I 5 1 North King St. B6 F 0 4 North King St. B10 I 0 North King St. B13 M 1 4 North King St. B18 F 1 1 North King St. B26 I 0 North King St. B27 F 4 1 North King St. B28 I 4 0 North King St. B34 M 3 1 North King St. B36 F 2 North King St. B39 F 3 4 North King St. B40 PrF 3 4 North King St. B43 F 1 1 North King St. B49 F 0 1 North King St. B80 F 2 1 North King St. B50 I 0 North King St. B55 M 2 2 North King St. B59 F 3 4 North King St. B63 M 4 4 North King St. B69 M 3 4 North King St. B71 I 3 North King St. B83 F 5 4 North King St. B95 F 2 1 North King St. B97 I 3 North King St. B99 M 2 2 North King St. B104 M 3 4 North King St. B110 M 2 4 North King St. B111 F 4 1 North King St. B115 M 1 2 North King St. B117 M 0 4 North King St. B120 F 0 4 North King St. B122 M 2 4 North King St. B142 F 2 1 North King St. B144 M 5 1 North King St. B145 F 4 4 North King St. B156 F 6 1 North King St. B166 F 2 1 North King St. B173 F 2 4 North King St. B178 PrF 3 4 North King St. B179 PM 1 4 North King St. B196 F 3 2 North King St. B200 F 2 1 North King St. B205 PrF 5 4 205

Number of Matching LEH Per Post-Medieval Individual Site Individual Sex Number of Matching Age Cohort LEH North King St. B207 F 3 1 North King St. B215 I 4 1 North King St. B216 PM 1 2 North King St. B218 F 4 2 North King St. B228 F 6 4 North King St. B229 F 2 4 North King St. B230 F 4 1 North King St. B234 F 4 1 North King St. B240 F 2 4 North King St. B242 F 2 1 North King St. B248 F 5 4 North King St. B251 I 2 North King St. B259 F 0 2 North King St. B262 I 4 North King St. B263 M 3 2 North King St. B269 F 1 1 North King St. B272 I 3 North King St. B278 F 2 4 North King St. B281 F 3 North King St. B284 F 4 4 North King St. B285 M 2 4 North King St. B288 F 2 4 North King St. B296 F 1 4 North King St. B306 I 5 North King St. B315 F 6 1 North King St. B316 I 3 2 North King St. B318 PrF 4 1 North King St. B319 M 4 4 North King St. B320 F 2 4 North King St. B322 I 0 4 North King St. B327 M 4 2 North King St. B328 I 2 4 North King St. B330 F 2 2 North King St. B346 M 1 2 North King St. B356 F 6 4 Smithfield B4 M 3 1 Smithfield B7 I 1 Smithfield B9 I 2 2 Smithfield B10 M 2 1 Smithfield B15 F 2 4 Smithfield B19 I 4 Smithfield B20 I 1 Smithfield B22 PF 4 1 Trim Castle SK 1003 M 2 1 Trim Castle SK 1006 M 0 1 Trim Castle SK 1201 M 0 2 Trim Castle SK 1202 F 3 1

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Figure 63: Histogram of LEH in post-medieval period

Normality was tested using a Shapiro-Wilk test (Table 48), which tests the null hypothesis that the data do not deviate from the normal distribution. The Shapiro-Wilk test shows that neither the late medieval and post-medieval LEH distributions are normally distributed (p<0.001).

Table 48: Shapiro-Wilk normality test for number of LEH in the late medieval and post-medieval periods

Shapiro-Wilk Normality Test by Time Period Time Period H0 N Statistic df Sig. Reject H0 Late Medieval The distribution of the number of 76 0.921 76 <0.001 Yes matching LEH in the late medieval period is normal. Post Medieval The distribution of the number of 122 0.940 122 <0.001 Yes matching LEH in the post medieval period is normal.

Descriptive statistics (i.e., minimum, maximum, mean, median, mode, and standard distribution) were calculated for the late medieval and post-medieval time periods and are presented in Table 49.

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Table 49: Descriptive statistics for LEH by time period

Matching LEH Frequency by Time Period N Min. Mean Median Mode Max. Standard Deviation Late Medieval 76 0 1.86 2.00 2 6 1.320 Post-Medieval 122 0 2.44 2.00 2 6 1.606

Because the Shapiro-Wilk test showed that the data are not normally distributed, a Mann-

Whitney U test was used to compare the median number of matching LEH between the late medieval and post medieval period. The Mann-Whitney U test tests the hypothesis that there is no difference between the medians of two independent groups. Results show that there are differences in the number of matching LEH between the late medieval and post medieval periods

(p=0.012), suggesting that individuals in the post-medieval had more LEH than individuals in the late medieval period.

Individuals were assigned to age cohorts (Table 11). Cohort 1 was comprised of individuals estimated to be between the ages of 15 and 29 using either the maximum likelihood value from transition analysis (Milner and Boldsen, 2002) or the mean pubic symphysis age

(Brooks and Suchey, 1990) (see age data, Appendix A). The second cohort was comprised of individuals aged approximately 30-44, the third 45-59, and the last cohort was comprised of individuals aged approximately 60 or older. Descriptive statistics for each cohort separated by time period are presented in Table 51 and Table 55, and their corresponding box plots are presented in Figure 64 and Figure 65.

A Mann-Whitney U test was performed to test for differences in medians between the late medieval and post-medieval periods, controlling for age cohort (Table 50). For example, the first age cohort in the late medieval period was compared to the first age cohort in the post-

208 medieval period. Results show that there are no differences in the median number of matching

LEH between the late medieval and post-medieval periods when age is controlled.

Table 50: Mann-Whitney U test comparing number of LEH between time periods by age cohort

Mann-Whitney U Test for Late Medieval & Post Medieval Periods, by Cohort H0 Total N Sig. Reject H0 The median number of matching LEH in cohort 1 is the same in the late 66 0.069 No medieval & post-medieval periods. The median number of matching LEH in cohort 2 is the same in the late 35 0.660 No medieval & post-medieval periods. The median number of matching LEH in cohort 3 is the same in the late 5 1.000 No medieval & post-medieval periods. The median number of matching LEH in cohort 4 is the same in the late 54 0.230 No medieval & post-medieval periods.

These results prompted additional questions. Specifically:

1. Did the number of LEH differ between age cohorts in the late medieval period?

2. Did the variance in the number of LEH differ between age cohorts in the late medieval

period?

3. Did the number of LEH differ between age cohorts in the post-medieval period?

4. Did the variance in the number of LEH differ between age cohorts in the post-medieval

period?

5. Did males and females in the late medieval period have different numbers of matching

LEH?

6. Did males and females in the post-medieval period have different numbers of matching

LEH?

7. Did the number of matching LEH change for males between the late medieval and post-

medieval periods?

8. Did the number of matching LEH change for females between the late medieval and post-

medieval periods?

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9. Did the number of matching LEH differ across late medieval and post-medieval sites?

10. Did the variance in the number of matching LEH differ across sites in the late medieval

and post-medieval periods?

11. Did the width of matching LEH change between time periods?

12. Did the width of matching LEH differ across late medieval and post-medieval sites?

13. Did the variance of LEH width change between the late medieval and post-medieval

period?

14. Did the width of LEH differ between males and females in the late medieval period?

15. Did the width of LEH differ between males and females in the post-medieval period?

16. Did the width of LEH change between late medieval and post-medieval males?

17. Did the width of LEH change between late medieval and post-medieval females?

18. Was LEH width associated with age-at-death?

Comparison of LEH Number in the Late Medieval Period Between Age Cohorts

Did the number of LEH differ between age cohorts in the late medieval period?

Descriptive statistics for the number of LEH in the late medieval period by age cohort are presented in Table 51. The corresponding boxplot can be viewed in Figure 64.

Table 51: Late medieval LEH frequency by age cohort

Late Medieval Matching LEH Frequency by Age Cohort Age Cohort N Min. Mean Median Mode Max. Standard Deviation 1 28 0 1.86 2.00 3 4 1.297 2 18 0 1.78 1.00 1 6 1.700 3 1 2 2.00 2.00 1 2 N/A 4 15 0 1.60 2.00 2 4 1.121

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Figure 64: Box-plot of LEH in late medieval period by age cohort

A Shapiro-Wilk test was performed for each age cohort in the late medieval period to assess normality (Table 52). Results show that the data are not normally distributed in the first two age cohorts (p=0.009 and p=0.023, respectively). The small sample size (n=2) prohibited the assessment of normality for the third age cohort in the late medieval period. The null hypothesis could not be rejected for the fourth age cohort in the late medieval period (n=0.39), suggesting that the data are normally distributed.

Table 52: Shapiro-Wilk normality test for late medieval LEH by age cohort

Late Medieval Shapiro-Wilk Normality Test by Age Cohort Age Cohort H0 N Statistic Df Sig. Reject H0 1 The distribution of the number of matching 28 0.888 28 0.004 Yes LEH in cohort 1 is normal. 2 The distribution of the number of matching 18 0.861 18 0.011 Yes LEH in cohort 2 is normal. 3 The distribution of the number of matching 1 N/A N/A N/A N/A LEH in cohort 3 is normal. 4 The distribution of the number of matching 15 0.892 15 0.021 Yes LEH in cohort 4 is normal.

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An ANOVA was performed to test for differences in the means among the age cohorts in the late medieval period (Table 53). Results show that there were no differences in the means among the age cohorts in the late medieval period (p=0.948).

Table 53: ANOVA comparing LEH among late medieval age cohorts

ANOVA Comparing LEH Among Late Medieval Age Cohorts df Mean Square F Sig. Reject H0 Between Age Cohorts There is no difference in 3 0.233 0.121 0.948 No the mean number of matching LEH among cohorts.

Comparison of Variance in LEH Number Between Age Cohorts in the Late Medieval

Period

Did the variance in the number of LEH differ between age cohorts in the late medieval period?

Levene’s test of equality of variances was used to the null hypothesis that the variance for the number of LEH is the same across all age cohorts in the late medieval period. Results show that there are no differences in the variance in the number of matching LEH for age cohorts in the late medieval period (p=0.302) (Table 54).

Table 54: Results of Levene's test of equality of variance for late medieval age cohorts

Levene’s Test of Equality of Variances for Late Medieval Age Cohorts H0 Statistic Sig. Reject H0 Based on Mean There is no difference in the error variance for the 1.223 0.302 No number of matching LEH across all age cohorts.

Comparison of LEH Number Between Age Cohorts in the Post-Medieval Period

Did the number of LEH differ between age cohorts in the post-medieval period?

Descriptive statistics for the number of LEH in the post-medieval period by age cohort are presented in Table 55. The corresponding boxplot can be viewed in Figure 65.

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Table 55: Descriptive statistics for LEH in post-medieval period by age cohort

Post Medieval Matching LEH Frequency by Age Cohort Age Cohort N Min. Mean Median Mode Max. Standard Deviation 1 38 0 2.63 2.00 2 6 1.651 2 17 0 1.82 2.00 1 4 1.328 3 4 1 3.25 3.50 3 5 1.000 4 39 0 2.26 2.00 2 6 1.766

Figure 65: Box-plot of LEH in post-medieval period by age cohort

A Shapiro-Wilk test was performed for each age cohort in the post-medieval period to assess normality. Results of the Shapiro-Wilk test (Table 56) for the post-medieval period show that the data for the first and fourth age cohorts are not normally distributed (p=0.045 and p=0.011, respectively). The null hypothesis could not be rejected for the second age cohort of the post medieval period, suggesting that the data for the number of matching LEH are normally distributed. A small sample size (n=4) for the third age cohort in the post-medieval period prohibited assessment of normality. 213

Table 56: Shapiro-Wilk test for normality for LEH in the post-medieval period by age cohort

Post Medieval Shapiro-Wilk Normality Test by Age Cohort Age Cohort H0 N Statistic df Sig. Reject H0 1 The distribution of the number of matching 38 0.937 38 <0.01 Yes LEH in cohort 1 is normal. 2 The distribution of the number of matching 17 0.923 17 0.200 No LEH in cohort 2 is normal. 3 The distribution of the number of matching 4 1.000 4 N/A N/A LEH in cohort 3 is normal. 4 The distribution of the number of matching 39 0.922 39 0.004 Yes LEH in cohort 4 is normal.

An ANOVA was performed to test for differences in means among the age cohorts in the post-medieval period (Table 57). Results show that there are no differences in the means among the age cohorts in the post-medieval period (p=0.252).

Table 57: ANOVA comparing LEH among post-medieval age cohorts

ANOVA Comparing LEH Among Post-Medieval Age Cohorts H0 Df Mean Square F Sig. Reject H0 Between Age Cohorts There is no difference 4 3.479 1.365 0.252 No in the mean number of matching LEH across cohorts.

Comparison of Variance in LEH Number Between Age Cohorts in the Post-Medieval

Period

Did the variance in the number of LEH differ between age cohorts in the post-medieval period?

Levene’s test of equality of variance ( Table 58) showed that there are no differences in variance in the number of matching

LEH among age cohorts in the post-medieval period (p=0.600).

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Table 58: Levene's test of equality of variance for LEH across age cohorts in post-medieval period

Levene’s Test of Equality of Variances for Post Medieval Age Cohorts H0 Statistic Sig. Reject H0 Based on Mean There is no difference in the error variance in 0.626 0.600 No number of matching LEH across age cohorts.

Comparison of LEH Number Between Sexes by Time Period

Did males and females in the late medieval period have different numbers of matching LEH?

Descriptive statistics for the number of matching LEH by sex in the late medieval period are presented in Table 59, and the corresponding boxplot can be viewed in Figure 66.

Table 59: Late medieval LEH frequency by sex

Late Medieval LEH Frequency by Sex Sex N Min. Mean Median Mode Max. Standard Deviation Males 26 0 1.69 1.50 1 6 1.379 Females 35 0 1.83 2.00 2 4 1.200

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Figure 66: Box-plot of late medieval LEH by sex

Histograms suggest that the data for late medieval males are not normally distributed

(Figure 67), but the data for late medieval females are (Figure 68). However, a Shapiro-Wilk test shows that the data for neither late medieval males nor late medieval females are normally distributed (Table 60).

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Figure 67: Histogram of LEH for late medieval males

Figure 68: Histogram of LEH for late medieval females

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Table 60: Shapiro-Wilk normality test for late medieval LEH by sex

Shapiro-Wilk Normality Test for the Late Medieval Period by Sex Time Period H0 N Statistic Df Sig. Reject H0 Males The distribution of the number of LEH 26 0.871 26 0.004 Yes among late medieval males is normal. Females The distribution of the number of LEH 35 0.914 35 0.010 Yes among late medieval females is normal.

Because the Shapiro-Wilk test demonstrated that the data were not normally distributed, a

Mann-Whitney U test was used to test the null hypothesis that there is no difference in the median number of LEH between males and females in the late medieval period (Table 61). The null hypothesis was not rejected (p=0.490), suggesting that there is no difference in the average

LEH prevalence for males and females in the late medieval period.

Table 61: Mann-Whitney U test comparing number of LEH between late medieval males and females

Mann-Whitney U Test for Late Medieval Males and Females H0 Total N Sig. Reject H0 There is no difference in the median number of LEH between late 61 0.509 No medieval males and females.

Did males and females in the post-medieval period have different numbers of matching LEH?

Descriptive statistics for the number of matching LEH by sex in the post-medieval period are presented in Table 62, and the corresponding boxplot can be viewed in Figure 69.

Table 62: Descriptive statistics for LEH for post-medieval males and females

Post Medieval LEH Frequency by Sex Sex N Min. Mean Median Mode Max. Standard Deviation Males 31 0 2.03 2.00 1 5 1.354 Females 60 0 2.65 2.00 2 6 1.655

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Figure 69: Box-plot of LEH in post-medieval period by sex

Histograms show that the data for both sexes in the post-medieval periods are skewed (Figure 70 - Figure 71). A Shapiro-Wilk test shows that the data are not normally distributed ( Table 63).

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Figure 70: Histogram of LEH for post-medieval males

Figure 71: Histogram of LEH for post-medieval females

Table 63: Shapiro-Wilk normality test for post-medieval males and females

Shapiro-Wilk Normality Test for the Post Medieval Period by Sex Sex H0 N Statistic Df Sig. Reject H0 Males The distribution of the number of LEH 31 0.934 31 0.055 Yes among post-medieval males is normal. Females The distribution of the number of LEH 60 0.937 57 0.004 Yes among post-medieval females is normal.

According to the Shapiro-Wilk test, the data were not normally distributed.

Consequently, a Mann-Whitney U test was used to test the null hypothesis that there is no difference in the median number of LEH between males and females in the post-medieval period

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(Table 64). The null hypothesis was not rejected (p=0.092), suggesting that there is no difference in the average LEH prevalence for males and females in the late medieval period.

Table 64: Mann-Whitney U test comparing number of LEH between post-medieval males and females

Mann-Whitney U Test for Post Medieval Males and Females H0 Total N Sig. Reject H0 There is no difference in the median number of LEH between post 91 0.092 No medieval males and females.

Comparison of LEH Number Between Time Periods by Sex

Did the number of matching LEH change for males between the late medieval and post-medieval periods?

Because the data were not normally distributed, a Mann-Whitney U Test was used to test for differences in the median number of matching LEH between late medieval and post-medieval males for each age cohort (Table 65). Results show that in no age cohort could the null hypothesis be rejected, indicating that there was no change in the number of LEH in males between the late medieval and post-medieval periods.

Table 65: Mann-Whitney U test comparing LEH number between late medieval and post-medieval males by age cohort

Mann-Whitney U Test for Late Medieval and Post-Medieval Males by Cohort Cohort H0 Total N Sig. Reject H0 1 There is no difference in the median number of LEH between late 16 0.382 No medieval and post-medieval males in the first age cohort. 2 There is no difference in the median number of LEH between late 14 0.491 No medieval and post-medieval males in the second age cohort. 3 There is no difference in the median number of LEH between late 2 0.317 No medieval and post-medieval males in the third age cohort. 4 There is no difference in the median number of late medieval and 28 0.911 No post-medieval males in the fourth age cohort.

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Did the number of matching LEH change for females between the late medieval and post- medieval periods?

A Mann-Whitney U Test was used to test for differences in the mean number of matching

LEH between late medieval and post-medieval males for each age cohort (Table 66). Results show that in no age cohort could the null hypothesis be rejected, indicating that there was no change in the number of matching LEH for females between the late medieval and post-medieval periods.

Table 66: Mann-Whitney U test comparing LEH number in late medieval and post-medieval females by age cohort

Mann-Whitney U Test for Late Medieval and Post-Medieval Females by Cohort Cohort H0 Total N Sig. Reject H0 1 There is no difference in the mean number of LEH between late 46 0.144 No medieval and post-medieval females in the first age cohort. 2 There is no difference in the mean number of LEH between late 14 0.791 No medieval and post-medieval females in the second age cohort. 3 There is no difference in the mean number of LEH between late 1 N/A N/A medieval and post-medieval females in the third age cohort. 4 There is no difference in the mean number of late medieval and 28 0.270 No post-medieval females in the fourth age cohort.

Comparison of LEH Number Across Contemporaneous Sites

Did the number of matching LEH differ across late medieval and post-medieval sites?

LEH data were also compared among sites in each time period. Descriptive statistics for late medieval sites are presented in Table 67, and descriptive statistics for post-medieval period sites are presented in Table 68. The corresponding box plots are presented in Figure 72 and

Figure 73. Several late medieval sites were excluded from the box plot (Figure 72) because they only had a sample size of one.

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Table 67: Descriptive statistics for LEH number for late medieval sites

Late Medieval LEH Frequency by Site Site N Min. Mean Median Mode Max. Standard Deviation Ardreigh 36 0 1.64 1.50 1 6 1.313 Dominican 7 0 1.71 2.00 0 4 1.496 Priory/Upper Magdalene Essex St. West 1 2 2.00 2.00 2 2 N/A Hanbury Lane 1 3 3.00 3.00 3 3 N/A Holy Trinity 1 3 3.00 3.00 3 3 N/A Johnstown 21 0 2.14 2.00 2 5 2.276 Mercer’s 7 1 3.14 3.00 3 6 1.573 Hospital St. Mary 3 0 1.33 2.00 2 2 1.155 d’Urso

Figure 72: Box-plot of number of LEH for late medieval sites

Table 68: Descriptive statistics for LEH number for post-medieval sites

Post Medieval LEH Frequency by Site Site N Min. Mean Median Mode Max. Standard Deviation Coombe/Cork 28 0 1.93 2.00 0 5 1.585 St. Mercer’s 4 0 2.75 2.50 - 6 2.50 Hospital North King 79 0 2.63 2.00 2 6 1.611 St.

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Smithfield 8 1 2.38 2.00 2 4 1.188 Trim Castle 4 0 1.25 1.00 0 3 1.500

Figure 73: Box-plots for number of LEH for post-medieval sites

An ANOVA was used to test the null hypothesis that there is no difference between the mean number of matching LEH across sites from both time periods (Table 69). Results show that the null hypothesis cannot be rejected, and that there is no difference between the mean number of LEH across late medieval sites (p=0.532) or post-medieval sites (p=0.500).

Table 69: ANOVA comparing LEH number among late medieval and post-medieval sites

ANOVA Comparing LEH Among Late Medieval & Post-Medieval Sites H0 df Mean Square F Sig. Reject H0 Between late medieval There is no difference 8 1.654 0.938 0.492 No sites in the mean number of LEH across late medieval sites. Between post medieval There is no difference 4 3.336 1.307 0.272 No sites in the mean number of LEH across post- medieval sites

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The mean number of LEH between sites was then compared controlling for age cohort by performing an ANOVA to test the null hypothesis that there were no differences in the mean number of LEH across sites (Table 70). For example, the mean number of LEH in cohort 1 was compared across all late medieval sites. The null hypothesis could not be rejected for any of the age cohorts in the late medieval period.

Table 70: ANOVA comparing LEH number among late medieval sites by cohort

ANOVA Comparing LEH Among Late Medieval Sites by Cohort Cohort H0 df Mean Square F Sig. Reject H0 1 There is no difference in the mean 6 1.360 0.360 0.276 No number of LEH across late medieval sites for cohort 1. 2 There is no difference in the mean 4 1.444 0.433 0.782 No number of LEH across late medieval sites for cohort 2. 3 There is no difference in the mean N/A 0.000 0.000 1.000 N/A number of LEH across late medieval sites for cohort 3. 4 There is no difference in the mean 3 1.144 0.889 0.477 No number of LEH across late medieval sites for cohort 4

Similarly, an ANOVA showed that there were no differences in the mean number of LEH among age cohorts across post-medieval sites (Table 71).

Table 71: ANOVA comparing LEH number among post-medieval sites by cohort

ANOVA Comparing LEH Among Post-Medieval Sites by Cohort Cohort H0 df Mean Square F Sig. Reject H0 1 There is no difference in the mean 4 3.322 1.451 0.239 No number of LEH across post-medieval sites for cohort 1. 2 There is no difference in the mean 3 2.268 1.499 0.261 No number of LEH across post-medieval sites for cohort 2. 3 There is no difference in the mean 1 6.750 6.750 0.122 N/A number of LEH across post-medieval sites for cohort 3. 4 There is no difference in the mean 4 13.201 5.390 0.090 No number of LEH across post-medieval sites for cohort 4

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Comparison of Variance in Number Across Contemporaneous Sites

Did the variance in the number of matching LEH differ across sites in the late medieval and post-medieval periods?

Results of Levene’s test of equality of variances indicated that despite the wide range of sample sizes, the null hypothesis of homogeneity of variance for the number of matching LEH across late medieval sites could not be rejected (Table 72). Similarly, the null hypothesis of homogeneity of variance for the number of matching LEH across post-medieval sites could not be rejected (Table 72).

Table 72: Levene's test of equality of variance for late medieval and post-medieval sites

Levene’s Test of Equality of Variances for Late Medieval and Post-Medieval Sites Time Period H0 Statistic Sig. Reject H0 Late Medieval There are no differences in the variances 0.130 0.971 No for the number of LEH across sites in the late medieval period. Post Medieval There are no differences in the variances 0.374 0.826 No for the number LEH across sites in the post medieval period.

Comparison of LEH Width Between Time Periods

Did the width of LEH change between the late medieval and post-medieval periods?

Descriptive statistics (mean, median, minimum, and maximum) for the width of matching cervical LEH in millimeters by tooth type and time period are presented in

Table 73. Histograms are presented in Figure 74 - Figure 79.

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Table 73: Descriptive statistics for LEH width by tooth type and time period

Descriptive Statistics for LEH Width (mm) by Tooth Type and Time Period Period Number of Min. Max. Mean Median Standard LEH Deviation Incisors Late 168 0.017 1.110 0.198 0.134 0.186 medieval Post- 328 0.019 1.534 0.242 0.151 0.253 medieval Canines Late 96 0.012 3.678 0.259 0.130 0.467 medieval Post- 279 0.020 4.245 0.260 0.164 0.402 medieval Premolars Late 22 0.026 0.851 0.251 0.233 0.193 medieval Post- 48 0.033 0.952 0.203 0.156 0.183 medieval

A Shapiro-Wilk test was used to test the null hypothesis that the width of matching cervical LEH in each time period and tooth type were normally distributed (Table 74). The null hypothesis was rejected in all tooth types from both time periods.

Table 74: Shapiro-Wilk normality test for LEH width by tooth type and time period

Shapiro-Wilk Normality Test by Time Period Time Period H0 N Statistic Df Sig. Reject H0 Late Medieval The distribution of the widths of matching 168 0.767 168 <0.01 Yes Incisors cervical LEH in incisors from the late medieval period is normal. Late Medieval The distribution of the widths of matching 96 0.404 96 <0.01 Yes Canines cervical LEH in canines from the late medieval period is normal. Late Medieval The distribution of the widths of matching 22 0.882 22 0.013 Yes Premolars cervical LEH in premolars from the late medieval period is normal. Post Medieval The distribution of the widths of matching 328 0.708 328 <0.01 Yes Incisors cervical LEH in incisors from the post medieval period is normal. Post Medieval The distribution of the widths of matching 279 0.430 279 <0.01 Yes Canines cervical LEH in canines from the post medieval period is normal. Post Medieval The distribution of the widths of matching 48 0.702 48 <0.01 Yes Premolars cervical LEH in premolars from the post medieval period is normal.

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Figure 74: Histogram of LEH width for late medieval incisors

Figure 75: Histogram of LEH width for post-medieval incisors

Figure 76: Histogram of LEH width for late medieval canines

228

Figure 77: Histogram of LEH width for post-medieval canines

Figure 78: Histogram of LEH width for late medieval premolars

Figure 79: Histogram of LEH width for post-medieval premolars

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Because the data were not normally distributed, a Mann-Whitney U test was used to test the null hypothesis that there is no difference in the median width of cervical LEH for each tooth type between time periods (Table 75). Results show that the null hypothesis was not rejected for canines and premolars, but it could possibly be rejected for incisors. These results suggest that the median width of cervical LEH in late medieval incisors (median = 0.134 mm) and post- medieval incisors (median = 0.151 mm) could be different (p=0.053). The average width of LEH in incisors appears to have increased between the late medieval and post-medieval periods.

Table 75: Mann-Whitney U test comparing LEH width between time periods by tooth type

Mann-Whitney U Test for Mean Width of Cervical LEH between Time Periods H0 Total N Sig. Reject H0 There is no difference in the median width of matching cervical LEH in 375 0.194 No canines between the late medieval period and post-medieval period. There is no difference in the median width of matching cervical LEH 496 0.053 Maybe in incisors between the late medieval period and post-medieval period. There is no difference in the median width of matching cervical LEH in 70 0.201 No premolars between the late medieval period and post-medieval period.

Comparison of LEH Width Across Contemporaneous Sites

Did the widths of LEH differ across sites in each time period?

Descriptive statistics were also calculated for the width of matching cervical LEH in millimeters by tooth type and site, and these results are displayed in Table 76.

Table 76: Descriptive statistics for LEH width by tooth type and site

Descriptive Statistics for LEH Width (mm) by Tooth Type and Site Site Number of Min. Max. Mean Median Standard LEH Deviation Canines Ardreigh 34 0.12 3.678 0.326 0.104 0.699 Coombe/Cork St. 58 0.23 0.824 0.142 0.114 0.135 Dominican 6 0.061 0.289 0.119 0.089 0.085 Priory/Upper Magdalene Essex St. West 3 0.068 0.137 0.110 0.125 0.0369 Hanbury Lane 2 0.096 0.106 0.101 0.101 0.007

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Holy Trinity 1 0.170 0.170 0.170 0.170 N/A Johnstown 34 0.500 1.770 0.257 0.130 0.342 Mercer’s 17 0.036 0.761 0.200 0.096 0.216 Hospital North King St. 195 0.020 2.341 0.268 0.188 0.276 Smithfield 11 0.067 0.360 0.190 0.163 0.109 St. Mary d’Urso 11 0.076 0.363 0.205 0.206 0.086 Trim Castle 3 0.116 4.245 2.682 3.69 2.240 Incisors Ardreigh 73 0.036 0.769 0.220 0.142 0.185 Coombe/Cork St. 54 0.019 0.911 0.132 0.091 0.136 Dominican 20 0.035 0.508 0.131 0.094 0.116 Priory/Upper Magdalene Essex St. West 0 - - - - - Hanbury Lane 2 0.218 0.246 0.232 0.232 0.020 Holy Trinity 2 0.926 1.111 1.01 1.02 0.131 Johnstown 61 0.025 0.827 0.194 0.153 0.164 Mercer’s 27 0.017 1.377 0.232 0.111 0.366 Hospital North King St. 241 0.019 1.534 0.262 0.165 0.255 Smithfield 19 0.047 0.420 0.176 0.154 0.114 St. Mary d’Urso 3 0.106 0.421 0.316 0.421 0.182 Trim Castle 0 - - - - - Premolars Ardreigh 14 0.026 0.491 0.226 0.233 0.157 Coombe/Cork St. 20 0.047 0.253 0.135 0.134 0.069 Dominican 1 0.127 0.127 0.127 0.127 N/A Priory/Upper Magdalene Essex St. West 0 - - - - - Hanbury Lane 2 0.308 0.389 0.349 0.349 0.057 Holy Trinity 0 - - - - - Johnstown 3 0.080 0.298 0.187 0.183 0.109 Mercer’s 5 0.151 0.851 0.371 0.300 0.279 Hospital North King St. 16 0.033 0.952 0.258 0.171 0.282 Smithfield 8 0.061 0.441 0.238 0.230 0.125 St. Mary d’Urso 1 0.116 0.116 0.116 0.116 - Upper 1 0.127 0.127 0.127 0.116 - Magdalene

A Shapiro-Wilk test was used to test the null hypothesis that the widths of matching cervical LEH in each tooth type from each site are normally distributed (Table 77). Results show that the null hypothesis can be rejected for canines (p<0.01) and incisors (p<0.01) from

Ardreigh, canines (p<0.01) and incisors (p<0.01) from Coombe/Cork St., canines (p= 0.005) and incisors (p<0.01) from Dominican Priory, canines (p<0.01) and incisors (p<0.01) from

Johnstown, canines (p<0.01) and incisors (p<0.01) from Mercer’s Hospital, canines (p<0.01),

231 incisors (p<0.01), and premolars (p<0.01) from North King St., and incisors (p<0.01) from St.

Mary d’Urso. Histograms were constructed for all sites in which the number of widths by tooth type was at least five (Figure 80 - Figure 99).

Table 77: Shapiro-Wilk normality test for LEH width by site and tooth type

Shapiro-Wilk Normality Test by Site Time Period H0 N Statistic df Sig. Reject H0 Ardreigh The distribution of the widths of 73 0.812 73 <0.01 Yes Incisors matching cervical LEH in incisors from Ardreigh is normal. Ardreigh The distribution of the widths of 34 0.417 34 <0.01 Yes Canines matching cervical LEH in canines from Ardreigh is normal. Ardreigh The distribution of the widths of 14 0.929 14 0.295 No Premolars matching cervical LEH in premolars from Ardreigh is normal. Coombe/Cork The distribution of the widths of 54 0.623 54 <0.01 Yes St. Incisors matching cervical LEH in incisors from Coombe/Cork St. is normal. Coombe/Cork The distribution of the widths of 58 0.706 58 <0.01 Yes St. Canines matching cervical LEH in canines from Coombe/Cork St. is normal. Coombe/Cork The distribution of the widths of 20 0.910 20 0.064 No St. Premolars matching cervical LEH in premolars from Coombe/Cork St. is normal. Dominican The distribution of the widths of 20 0.702 20 <0.01 Yes Priory/Upper matching cervical LEH in incisors from Magdalene the Dominican Priory is normal. Incisors Dominican The distribution of the widths of 6 0.693 6 0.005 Yes Priory/Upper matching cervical LEH in canines from Magdalene the Dominican Priory is normal. Canines Dominican The distribution of the widths of 0 - - - - Priory/ Upper matching cervical LEH in premolars Magdalene from the Dominican Priory is normal. Premolars Essex St. West The distribution of the widths of 0 - - - - Incisors matching cervical LEH in incisors from Essex St. West is normal. Essex St. West The distribution of the widths of 3 0.876 3 0.312 No Canines matching cervical LEH in canines from Essex St. West is normal. Essex St. West The distribution of the widths of 0 - - - - Premolars matching cervical LEH in premolars from Essex St. West is normal. Hanbury Lane The distribution of the widths of 2 - - - - Incisors matching cervical LEH in incisors from Hanbury Lane is normal.

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Hanbury Lane The distribution of the widths of 2 - - - - Canines matching cervical LEH in canines from Hanbury Lane is normal. Hanbury Lane The distribution of the widths of 2 - - - - Premolars matching cervical LEH in premolars is normal. Holy Trinity The distribution of the widths of 2 - - - - Incisors matching cervical LEH in incisors from Holy Trinity is normal. Holy Trinity The distribution of the widths of 0 - - - - Canines matching cervical LEH in canines from Holy Trinity is normal. Holy Trinity The distribution of the widths of 0 - - - - Premolars matching cervical LEH in premolars from Holy Trinity is normal. Johnstown The distribution of the widths of 27 0.823 27 <0.01 Yes Incisors matching cervical LEH in incisors from Johnstown is normal. Johnstown The distribution of the widths of 34 0.537 34 <0.01 Yes Canines matching cervical LEH in canines from Johnstown is normal. Johnstown The distribution of the widths of 3 0.999 3 0.939 No Premolars matching cervical LEH in premolars from Johnstown is normal. Mercer’s The distribution of the widths of 27 0.534 27 <0.01 Yes Hospital matching cervical LEH in incisors from Incisors Mercer’s Hospital is normal. Mercer’s The distribution of the widths of 16 0.703 16 <0.01 Yes Hospital matching cervical LEH in canines from Canines Mercer’s Hospital is normal. Mercer’s The distribution of the widths of 5 0.801 5 0.082 No Hospital matching cervical LEH in premolars Premolars from Mercer’s Hospital is normal. North King St. The distribution of the widths of 241 0.741 241 <0.01 Yes Incisors matching cervical LEH in incisors from North King St. is normal. North King St. The distribution of the widths of 195 0.653 195 <0.01 Yes Canines matching cervical LEH in canines from North King St. is normal. North King St. The distribution of the widths of 16 0.705 16 <0.01 Yes Premolars matching cervical LEH in premolars from North King St. is normal. Smithfield The distribution of the widths of 19 0.911 19 0.078 Incisors matching cervical LEH in incisors from Smithfield is normal. Smithfield The distribution of the widths of 11 0.897 11 0.172 No Canines matching cervical LEH in canines from Smithfield is normal. Smithfield The distribution of the widths of 8 0.980 8 0.962 No Premolars matching cervical LEH in premolars from Smithfield is normal. St. Mary d’Urso The distribution of the widths of 3 0.650 3 <0.01 Yes Incisors matching cervical LEH in incisors from St. Mary d’Urso is normal.

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St. Mary d’Urso The distribution of the widths of 11 0.961 11 0.779 No Canines matching cervical LEH in canines from St. Mary d’Urso is normal. St. Mary d’Urso The distribution of the widths of 0 - - - - Premolars matching cervical LEH in premolars from St. Mary d’Urso is normal. Trim Castle The distribution of the widths of 0 - - - - Incisors matching cervical LEH in incisors from Trim Castle is normal. Trim Castle The distribution of the widths of 3 0.850 3 0.239 No Canines matching cervical LEH in canines from Trim Castle is normal. Trim Castle The distribution of the widths of 0 - - - - Premolars matching cervical LEH in premolars from Trim Castle is normal.

Figure 80: Histogram of LEH width for canines from Ardreigh

Figure 81: Histogram of LEH width for canines from Coombe/Cork St.

Figure 82: Histogram of LEH width for canines from Dominican Priory

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Figure 83: Histogram of LEH width for Johnstown canines

Figure 84: Histogram of LEH width for Mercer Hospital canines

Figure 85: Histogram of LEH width for North King St. canines

Figure 86: Histogram of LEH width for Smithfield canines

Figure 87: Histogram of LEH width for St. Mary d'Urso canines

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Figure 88: Histogram of LEH width for Ardreigh incisors

Figure 89: Histogram of LEH width for Coombe/Cork St. incisors

Figure 90: Histogram of LEH width for Dominican Priory incisors

Figure 91: Histogram of LEH width for Johnstown incisors

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Figure 92: Histogram of LEH width for Mercer Hospital incisors

Figure 93: Histogram of LEH width for North King St. Incisors

Figure 94: Histogram of LEH width for Smithfield incisors

Figure 95: Histogram of LEH width for Ardreigh premolars

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Figure 96: Histogram of LEH width for Coombe/Cork St. premolars

Figure 97: Histogram of LEH width for Mercer Hospital premolars

Figure 98: Histogram of LEH width for North King St. premolars

Figure 99: Histogram of LEH width for Smithfield premolars

An ANOVA was used to test the null hypothesis that there is no difference in the mean width of cervical LEH for each tooth type across sites (Table 78). Results show that the null hypothesis can be rejected for canines (p<0.01) and incisors (p<0.01), suggesting that the mean width of matching cervical LEH in canines and incisors are different across sites. Post-hoc tests could not be performed for all sites because some sites had fewer than 2 cases when the data were split according to tooth type.

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Table 78: ANOVA comparing LEH width across sites by tooth type

ANOVA Comparing Mean Width of Matching Cervical LEH Across Sites by Tooth Type H0 Df Mean Square F Sig. Reject H0 There is no difference in the mean width 11 1.724 13.381 <0.01 Yes of matching cervical LEH in canines across sites. There is no difference in the mean width 9 0.270 5.361 <0.01 Yes of matching cervical LEH in incisors across sites. There is no difference in the mean widths 8 0.042 1.258 0.282 No of matching cervical LEH in premolars across sites.

To increase the number of cases and permit the performance of post-hoc tests to identify precisely which sites differ, an ANOVA was run without controlling (i.e., splitting) the data by tooth type (Table 79).

Table 79: ANOVA comparing LEH width across sites

ANOVA Comparing Mean Width of Matching Cervical LEH Across Sites H0 Df Mean Square F Sig. Reject H0 There is no difference in the mean width of 7 0.174 1.827 0.082 No matching cervical LEH in all teeth across late medieval sites. There is no difference in the mean width 4 4.921 66.803 <0.01 Yes of matching cervical LEH in all teeth across post-medieval sites. Results show that the null hypothesis can be rejected (p<0.01) for pairwise comparisons between post-medieval sites but not for late medieval sites (p=0.156). This suggests that there are differences in the means of the widths of matching cervical LEH across post-medieval sites. A post-hoc Bonferroni test (Table 80 - Table 82) was used to identify which post-medieval sites differed while minimizing the risk of a Type I error (i.e., falsely rejecting the null hypothesis)

(Gray and Kinnear, 2012). Differences in the mean width of matching cervical LEH were found between Coombe/Cork St. and North King St. (p<0.01), between Coombe/Cork St. and Trim

Castle (p<0.01), between Mercer’s Hospital and Trim Castle (p<0.01), and between Smithfield and Trim Castle (p<0.01). However, the differences between Coombe/Cork St., Mercer’s

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Hospital, and Smithfield, and Trim Castle could be the result of a small sample size for Trim

Castle, which had only three measurements. Therefore, the only differences that will be considered further are those between Coombe/Cork St. and North King St.

Table 80: Pairwise comparisons of LEH width for Coombe/Cork St.

Post-Hoc Bonferroni Pairwise Comparisons of Mean Width of Matching Cervical LEH for Coombe/Cork St. Site H0 Sig. Reject H0 Mercer’s Hospital There is no difference in the mean widths of 0.061 No matching cervical LEH between Coombe/Cork St. and Mercer’s Hospital. North King St. There is no difference in the mean widths of <0.01 Yes matching cervical LEH between Coombe/Cork St. and North King St. Smithfield There is no difference in the mean widths of 1.000 No matching cervical LEH between Coombe/Cork St. and Smithfield. Trim Castle There is no difference in the mean widths of <0.01 Yes matching cervical LEH between Coombe/Cork St. and Trim Castle.

Table 81: Pairwise comparison of LEH width for Mercer's Hospital

Post-Hoc Bonferroni Pairwise Comparisons of Mean Width of Matching Cervical LEH for Mercer’s Hospital Site H0 Sig. Reject H0 North King St. There is no difference in the mean widths of 1.000 No matching cervical LEH between Mercer’s Hospital and North King St. Smithfield There is no difference in the mean widths of 1.000 No matching cervical LEH between Mercer’s Hospital and Smithfield Trim Castle There is no difference in the mean widths of <0.01 Yes matching cervical LEH between Mercer’s Hospital and Smithfield.

Table 82: Pairwise comparisons of LEH width for Smithfield

Post-Hoc Bonferroni Pairwise Comparisons of Mean Width of Matching Cervical LEH for Smithfield Site H0 Sig. Reject H0 Trim Castle There is no difference in the mean widths of <0.01 Yes matching cervical LEH between Smithfield and Trim Castle.

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Comparison of Variance in LEH Width Across Contemporaneous Sites

Did the variance in the width of LEH differ across late medieval and post-medieval sites?

Levene’s test of equality of variances was performed for all sites for late medieval and post-medieval sites. Results of Levene’s test of equality of variances indicated that despite the wide range of sample sizes, the null hypothesis of homogeneity of variance for the number of matching LEH could not be rejected (Table 83) for the late medieval period (p=0.099). However, the null hypothesis of homogeneity of variance for the number of matching LEH across post- medieval sites was rejected (Table 83) (p<0.01). This suggests that the variance in the width of

LEH is significantly different across post-medieval sites.

Table 83: Levene's test of equality of variance for LEH width in late medieval and post-medieval sites

Levene’s Test of Equality of Error Variances for Late Medieval and Post Medieval Sites Time Period H0 Df Statistic Sig. Reject H0 Late Medieval There are no differences in the error 7 1.454 0.184 No variances for the mean widths of matching cervical of LEH across sites in the late medieval period. Post Medieval There are no differences in the variances 4 62.313 <0.01 Yes for the mean widths of matching cervical LEH across sites in the post medieval period.

Comparison of LEH Width Between Sexes

Did the width of LEH differ between males and females in the late medieval period?

Descriptive statistics for the width of LEH in males and females in the late medieval period are presented in

Table 84. Corresponding boxplots are presented in Figure 100 - Figure 102.

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Table 84: Descriptive statistics for LEH width for late medieval males and females

Width of Matching Cervical LEH in Males and Females in the Late Medieval Period Period Sex Tooth Type N Min. Mean Median Max. Standard Deviation Late M canine 21 0.43 0.275 0.135 2.152 0.460 Medieval incisor 42 0.031 0.248 0.162 1.111 0.294 premolar 7 0.105 0.169 0.127 0.280 0.070 F canine 50 0.012 0.184 0.129 0.669 0.120 incisor 83 0.017 0.180 0.126 0.764 0.147 premolar 12 0.026 0.216 0.149 0.491 0.173

Figure 100: Box-plots of LEH width for male and female canines from both time periods

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Figure 101: Box-plots of LEH width for male and female incisors from both time periods

Figure 102: Box-plot of LEH widths for premolars from both time periods

A Shapiro-Wilk test was performed to test the null hypothesis that the widths of matching cervical LEH were normally distributed late medieval males and females (Table 85). Results 243 show that the widths for neither sex were normally distributed for incisors and canines, or for premolars in females. The data for male premolars were normally distributed.

Table 85: Shapiro-Wilk normality test of LEH width for late medieval males and females by tooth type

Shapiro-Wilk Normality Test for Widths of Matching Cervical LEH for Late Medieval Males and Females Sex Tooth Type H0 Statistic df Sig. Reject H0 incisors The distribution of widths of LEH in 0.746 42 <0.01 Yes incisors from late medieval males is normal. The distribution of widths of LEH in 0.427 22 <0.01 Yes canines canines from late medieval males is Males normal.

premolars The distribution of widths of LEH in 0.829 5 0.137 No premolars from late medieval males is normal.

incisors The distribution of widths of LEH in 0.807 50 <0.01 Yes incisors from late medieval females is normal.

Females canines The distribution of widths of LEH in 0.807 50 <0.01 Yes canines from late medieval females is normal.

premolars The distribution of widths of LEH in 0.879 12 0.086 No premolars from late medieval females is normal.

Because the Shapiro-Wilk test indicated that the data were not normally distributed, a

Mann-Whitney U test was performed to test the null hypothesis that there were no differences in the median width of matching cervical LEH for each tooth type between late medieval males and females (Table 86). The null hypothesis could not be rejected for any tooth type, indicating that there are no differences in the mean width of LEH in males and females in the late medieval period.

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Table 86: Mann-Whitney U test comparing LEH width of late medieval males and females

Mann-Whitney U Test Comparing Median LEH Width for Late Medieval Males and Females Tooth Type H0 Sig. Reject H0 Incisors There is no difference in the median width of matching cervical LEH in 0.206 No incisors of males and females in the late medieval period.

Canines There is no difference in the median width of matching cervical 0.027 Yes LEH in canines of males and females in the late medieval period.

premolars There is no difference in the median width of matching cervical LEH in 0.959 No premolars of males and females in the late medieval period.

Did the width of LEH differ between males and females in the post-medieval period?

Descriptive statistics for the width of LEH in males and females in the late medieval period are presented in Table 87. Corresponding boxplots are presented in the previous section and can be viewed in Figure 100 - Figure 102.

Table 87: Descriptive statistics of LEH width for males and females in the post-medieval period

Width of Matching Cervical LEH in Males and Females in the Post-Medieval Period Period Sex Tooth Type N Min. Mean Median Max. Standard Deviation Post M incisor 71 0.022 0.312 0.151 1.377 0.345 Medieval canine 66 0.035 0.315 0.183 1.508 0.309 premolar 8 0.071 0.153 0.125 0.253 0.073 F incisor 177 0.019 1.534 0.173 4.245 0.489 canine 156 0.020 0.276 0.173 4.245 0.489 premolar 20 0.037 0.266 0.225 0.952 0.253

A Shapiro-Wilk test was performed to test the null hypothesis that the widths of matching cervical LEH were normally distributed post-medieval males and females (

Table 88). Results show that the widths for neither sex were normally distributed.

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Table 88: Shapiro-Wilk normality test for LEH width in post-medieval period by tooth type and sex

Shapiro-Wilk Normality Test for Widths of Matching Cervical LEH in Post-Medieval Males and Females Sex Tooth Type H0 Statistic df Sig. Reject H0 incisors The distribution of widths of LEH in 0.719 71 <0.01 Yes incisors from post medieval males is normal. The distribution of widths of LEH in 0.757 66 <0.01 Yes Males canines canines from post medieval males is normal.

premolars The distribution of widths of LEH in 0.835 8 0.068 No premolars from post medieval males is normal.

incisors The distribution of widths of LEH in 0.736 177 <0.01 Yes incisors from post medieval females is normal.

Females canines The distribution of widths of LEH in 0.371 156 <0.01 Yes canines from post medieval females is normal.

premolars The distribution of widths of LEH in 0.724 20 <0.01 Yes premolars from post medieval females is normal.

Because the Shapiro-Wilk test indicated that the data were not normally distributed, a

Mann-Whitney U test was performed to test the null hypothesis that there were no differences in the median width of matching cervical LEH for each tooth type between post-medieval males and females (Table 89).

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Table 89: Mann-Whitney U test comparing LEH width for post-medieval males and females

Mann-Whitney U Test Comparing Median LEH Width for Post-Medieval Males and Females Tooth Type H0 Sig. Reject H0 Incisors There is no difference in the median width of matching cervical LEH in 0.845 No incisors of males and females in the post-medieval period. Canines There is no difference in the median width of matching cervical LEH in 0.112 No canines of males and females in the post-medieval period.

premolars There is no difference in the median width of matching cervical LEH in 0.500 No premolars of males and females in the post-medieval period.

Comparison of LEH Width Between Time Periods by Sex

Did the width of LEH change between late medieval and post-medieval males?

A Mann-Whitney U test was performed to test the null hypothesis that there were no differences in the median width of matching cervical LEH for each tooth type between late medieval and post-medieval males (Table 90). Results show that the null hypothesis could not be rejected for any tooth type. This indicates that there was no change in the width of LEH in males between the late medieval and post-medieval periods.

Table 90: Mann-Whitney U test comparing LEH width for males between time periods

Mann-Whitney U Test Comparing Median LEH Width for Males Between Periods Tooth Type H0 Sig. Reject H0 Incisors There is no difference in the median width of matching 0.529 No cervical LEH in male incisors between the late medieval and post-medieval periods. Canines There is no difference in the median width of matching 0.108 No cervical LEH in male canines between the late medieval and post-medieval periods.

premolars There is no difference in the median width of matching 0.524 No cervical LEH in male premolars between the late medieval and post-medieval periods.

Did the width of LEH change between late medieval and post-medieval females?

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The widths of matching cervical LEH were compared for females between time periods.

Descriptive statistics are presented in Table 91, and corresponding box plots are presented in

Figure 100 - Figure 102. Results show that the null hypothesis cannot be rejected for any tooth type for females. This suggests that there was no change in LEH width for females between the late medieval and post-medieval periods.

Table 91: Mann-Whitney U test comparing LEH width for females between time periods

Mann-Whitney U Test Comparing Median LEH Width for Females Between Periods Tooth Type H0 Sig. Reject H0 Incisors There is no difference in the median width of matching 0.148 No cervical LEH in female incisors between the late medieval and post-medieval periods. Canines There is no difference in the median width of matching 0.212 No cervical LEH in female canines between the late medieval and post-medieval periods. Premolars There is no difference in the median width of matching 0.863 No cervical LEH in female premolars between the late medieval and post-medieval periods.

Association Between LEH Number and Age-at-Death

Was the number of LEH associated with age-at-death?

A Pearson’s product-moment correlation coefficient was calculated to test for a relationship between the number of LEH and longevity. Results showed that there was no association between the number of LEH and age-at-death (r=0.003).

Association Between LEH Width and Age-at-Death

Was LEH width associated with age-at-death?

Scatterplots were made to visually assess the relationship between the width of matching cervical LEH and age-at-death, for both periods combined (Figure 103) and controlling for time

248 period (Figure 104 - Figure 105). Visual examination suggests no correlation between the width of LEH and age-at-death for when data from both time periods are combined. Visual examination also suggests a weak positive correlation between LEH width and age-at-death in the late medieval period, and a weak negative correlation between LEH width and age-at-death in the post-medieval period.

Figure 103: Scatterplot of LEH width and age-at-death

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Figure 104: Scatterplot of late medieval LEH width for LEH width <0.5mm and age-at-death

Figure 105: Scatterplot of post-medieval LEH width for LEH <0.5mm and age-at-death

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Pearson’s correlations were performed to test the relationship between LEH width and age-at-death (Table 92). No correlation between LEH width and age-at-death was found under any condition.

Table 92: Pearson product moment correlation for LEH width and age-at-death

Pearson’s Correlations for LEH Width & Age-at-Death H0 N Sig. Reject H0 There is no association between LEH width and age-at-death when all teeth 716 0.481 No from both time periods are combined. There is no association between LEH width and age-at-death in canines in 289 0.447 No both time periods. There is no association between LEH width and age-at-death in incisors in 381 0.625 No both time periods. There is no association between LEH width and age-at-death in premolars 46 0.642 No in both time periods. There is no association between LEH width and age-at-death in all tooth 232 0.598 No types from the late medieval period. There is no association between LEH width and age-at-death in canines 74 0.091 No from the late medieval period. There is no association between LEH width and age-at-death in incisors 140 0.418 No from the late medieval period. There is no association between LEH width and age-at-death in premolars 18 0.296 No from the late medieval period. There is no association between LEH width and age-at-death in all tooth 484 0.141 No types from the post-medieval period. There is no association between LEH width and age-at-death in canines 215 0.098 No from the post-medieval period. There is no association between LEH width and age-at-death in incisors 241 0.562 No from the post-medieval period. There is no association between LEH width and age-at-death in premolars 28 0.126 No from the post-medieval period. There is no association between LEH width and age-at-death in all tooth 197 0.783 No types from both time periods for males. There is no association between LEH width and age-at-death in all tooth 463 0.259 No types from both periods for females. There is no association between LEH width and age-at-death in canines 81 0.469 No from both periods for males. There is no association between LEH width and age-at-death in incisors 104 0.629 No from both periods for males. There is no association between LEH width and age-at-death in premolars 12 0.914 No from both periods for males. There is no association between LEH width and age-at-death in canines 19 0.591 No from late medieval males. There is no association between LEH width and age-at-death in incisors 52 0.132 No from late medieval males. There is no association between LEH width and age-at-death in premolars 7 0.586 No from late medieval males. There is no association between LEH width and age-at-death in canines 62 0.145 No from post-medieval males.

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There is no association between LEH width and age-at-death in incisors 52 0.113 No from post-medieval males. There is no association between LEH width and age-at-death in premolars 7 0.586 No from post-medieval males. There is no association between LEH width and age-at-death in canines 185 0.358 No from both periods for females. There is no association between LEH width and age-at-death in incisors 252 0.306 No from both periods for females. There is no association between LEH width and age-at-death in premolars 26 0.577 No from both periods for females. There is no association between LEH width and age-at-death in canines 45 0.367 No from late medieval females. There is no association between LEH width and age-at-death in incisors 86 0.449 No from late medieval females. There is no association between LEH width and age-at-death in premolars 11 0.559 No from late medieval females. There is no association between LEH width and age-at-death in canines 140 0.156 No from post-medieval females. There is no association between LEH width and age-at-death in incisors 166 0.054 No from post-medieval females. There is no association between LEH width and age-at-death in premolars 15 0.257 No from post-medieval females.

Table 93: Summary of results

Summary of Results Hypothesis 1: A greater proportion of the population from the late medieval English Pale will have survived to older ages than from the post-medieval English Pale. • This hypothesis was not supported. There was no difference in survivorship between the late medieval and post-medieval periods. Was survivorship different across sites within each time period? • Yes. People buried in Johnstown survived to older ages than those buried at Mercer’s Hospital and Ardreigh. People buried at North King St. survived to older ages than those buried at Coombe/Cork St. and Smithfield. Did survivorship differ between adult males and females in the late medieval period? • No (p=0.495). Did survivorship differ between adult males and females in the post-medieval period? • No (p=0.082). But, there are notable differences in the survival curves even if they are not statistically significant. Did survivorship differ between boys and girls in the post-medieval period? • No (p=0.917) Did survivorship for adult males change between the late medieval and post-medieval periods? • No (p=0.256) Did survivorship for adult females change between the late medieval and post-medieval periods? • No (p=0.857) Hypothesis 1a: There will be no difference between the age-at-death distributions calculated using transition analysis and the skeletal remains in this dissertation, and those calculated using contemporary burial records from approximately the same location. • This hypothesis was neither supported nor refuted. Hypothesis 2: Individuals from the post-medieval English Pale will exhibit more LEH than individuals from the late medieval English Pale. • This hypothesis was supported. When all individuals were grouped together and age was not controlled for, people in the post-medieval period had more LEH (mean=2.63) than

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those in the late medieval period (mean=1.86), and the difference was statistically significant (p=0.012). Did the number of LEH differ between age cohorts in the late medieval period? • No (p=0.948). Did the variance in the number of LEH differ between age cohorts in the late medieval period? • No (p=0.302). Did the number of LEH differ between age cohorts in the post-medieval period? • No (p=0.252). Did the variance in the number of LEH differ between age cohorts in the post-medieval period. • No (p=0.600). Did males and females in the late medieval period have different numbers of matching LEH? • No (p=0.509). Did males and females in the post-medieval period have different numbers of matching LEH? • No (p=0.092). Did the number of matching LEH change for males between the late medieval and post-medieval periods? • No. There were no differences in the number of matching LEH in males between the late medieval and post-medieval periods when age was controlled for. Did the number of matching LEH change for females between the late medieval and post-medieval periods? • No. There were no differences in the number of matching LEH in females between the late medieval and post-medieval periods when age was controlled for. Did the number of matching LEH differ across late medieval and post-medieval sites? • No. There were no differences in the number of LEH among late medieval sites (p=0.492) or post-medieval sites (p=0.372). Did the width of matching LEH differ between time periods? • It is possible that the width of LEH in incisors increased between the late medieval and post- medieval periods (p=0.053). The mean LEH width in late medieval incisors was 0.134 mm, and the mean LEH width in the post-medieval incisors was 0.151 mm. Did the width of matching LEH differ across late medieval and post-medieval sites? • Yes. The width of LEH differed among post-medieval sites (p<0.01). People buried at North King St. had wider LEH than those buried at Coombe/Cork St. (p<0.01). The mean LEH width for individuals buried at North King St. was 0.263 mm, and the mean LEH width for individuals buried at Coombe/Cork St. was 0.136 mm. Did the variance of LEH width differ across late medieval and post-medieval sites? • Yes. The variance of LEH width differed across post-medieval sites (p<0.01). Did the width of LEH differ between males and females in the late medieval period? • Yes. The mean width of LEH in canines from males was larger (0.275 mm) than the mean width of LEH in canines from females (0.184 mm) (p=0.027). Did the width of LEH differ between males and females in the post-medieval period? • No. There were no differences in mean width of LEH between males and females when tooth type was controlled for. Did the width of LEH change between late medieval males and post-medieval males? • No. There were no differences in the mean width of LEH in males in the late medieval period and the post-medieval period across all tooth types. Did the width of LEH change between late medieval females and post-medieval females? • No. There were no differences in the mean width of LEH in females in the late medieval period and the post-medieval period across all tooth types. Was the number of LEH associated with age-at-death? • No. There was no correlation between the number of LEH and age-at-death. Was LEH width associated with age-at-death? • No. LEH width was not associated with age-at-death.

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Chapter 9: Discussion

The purpose of this dissertation was to test the veracity of contemporary accounts (e.g.,

Twiss, 1776, Young, 1778, Wakefield, 1812, Mason, 1816, Phillips, 1822, Murray, 1827,

Sinclair, 1828) of remarkably good health in post-medieval Ireland. In addition to one methodological hypothesis (1a), the following hypotheses were tested:

1. A greater proportion of the population from the late medieval English Pale will have

survived to older ages than those from the post-medieval English Pale.

2. Individuals from the post-medieval English Pale will exhibit more LEH than individuals

from the late medieval English Pale.

Only the second of these hypotheses was supported. People from the post-medieval period did not die earlier than people from the late medieval period, but they did exhibit more LEH.

At first glance, this would appear to corroborate the contemporary accounts of Irish health and revisionist historical narratives asserting that the negative effects of British colonization have been overstated as part of a nationalist agenda because one could infer that people in the post- medieval period were better able to withstand the stresses of childhood, and so were able to form more LEH than their late medieval counterparts. However, this conclusion is not supported by the biocultural and historical context. Rather, historical sources and archaeological data suggest that childhood became more stressful during the post-medieval period, and that the children who suffered from the highest frailty are not represented as adults in the bioarchaeological record.

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This would account for the absence of difference in survivorship and the increase in LEH between the two time periods.

There are a number of biocultural factors that could have contributed to these results:

I. Stressful Childhoods

II. Inter-site variation resulting from violence or disease

III. Intra-site variation resulting from sex differences

IV. Changes in childrearing practices

V. Selective enforcement of the Penal Laws and religious diversity

VI. Unequal effects of colonization and industrialization across social

strata

There are also a number of methodological factors that should be considered. These are as follows:

A. Error in sex assessment

B. Reliance on point values for age-at-death

C. Differences in location

D. Overlap in time period

Social and Historical Factors

Stressful Childhoods

There were no differences in survivorship observed between the late medieval and post- medieval periods; however, individuals from the post-medieval period did exhibit more LEH

255 than individuals from the late medieval period. When the biocultural context is considered, this suggests that childhood in the post-medieval period was more stressful than in the late medieval period. While there have yet been no direct comparisons of childhood stress between the two periods, the difficulty of childhood in industrializing urban environments like post-medieval

Dublin has been well-documented. In crowded and damp living conditions, children confronted a daily onslaught of exposure to infectious diseases such as smallpox, tuberculosis, and gastroenteritis (Buckley and Riordan, 2017:328) that spread quickly through the Dutch Billies where families of up to 15 people lived in small apartments (Frazer, n.d.). They also confronted a number of household hazards, including fragile stairways, and collapsed and obstructed entryways (Frazer, n.d.). In buildings with absentee landlords, children may have also suffered from lack of access to clean water, an additional risk factor for infectious disease, as archaeologists have found evidence of failed water pipes in post-medieval residential structures in Dublin (Frazer, n.d.).

Those who were abandoned to foundling hospitals or were separated from their families in the workhouses fared even worse. In addition to infectious disease, these children frequently suffered from abuse and neglect, were malnourished, and lived in dirty, crowded conditions among rats, fleas, and lice that furthered the spread of disease (Buckley and Riordan, 2017:336).

Further, it has recently been made very clear that family separation is an extreme stressor in its own right (Miranda and Legha, 2019, Todres and Fink, 2020) and was an added stressor for these children that those outside of institutions did not experience. While it cannot be known if any of the individuals in the skeletal sample for this dissertation spent their childhoods in institutions, it is certainly possible given how many people lived and died in the foundling hospitals and how many of them were from St. Michan’s parish (the parish represented by the

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North King Street sample). As described in Chapter 3 of the 265 total children sent to workhouses in 1730, nearly a quarter of them were from the parish of St. Michan (Young, 1940).

Together, archaeological evidence, accounts of post-medieval life in and outside of institutions, and the greater number of LEH in the post-medieval sample suggest that childhood was more stressful during the post-medieval period than in the late medieval period, and in doing so, support the post-revisionist narrative of Irish history.

Inter-site variation resulting from violence or disease

It is possible that differences between sites within the same time period are so large that they are obscuring any potential differences in age-at-death between time periods. This possibility is supported by the differences in sites within the late medieval period and within the post-medieval period. The late medieval site of Johnstown had a later modal survival time

(S(t)=75 years) than the late medieval site of Ardreigh, in which the modal survival time was 35 years. The modal survival time at Johnstown was also greater than the modal survival time for the individuals from Mercer’s Hospital who had been randomly assigned to the late medieval period (modal S(t)=40 years). Similarly, there was significant variation in survivorship between post-medieval sites.

Individuals from North King St. survived to older ages (modal S(t)=70 years) than individuals from both Coombe/Cork St. (modal S(t)=40) and Smithfield (modal S(t)=30 years).

Individuals buried at Coombe/Cork St. survived to older ages than individuals buried at

Smithfield, though the comparatively low survivorship of people buried at Smithfield is unsurprising given that these individuals were likely soldiers, militiamen, or convicted criminals who had been executed at the nearby Oxmantown gallows or who died in a violent uprising (The

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Irish Builder, 1895, excavations.ie). While there was no evidence of hanging on the skeletal remains examined, this does not exclude the possibility that those observed had been executed at the gallows. Death by hanging is designed to be swift. In ideal circumstances of complete hangings, the victim’s neck is broken (Encyclopaedia Britannica), which should produce visible perimortem fractures to the cervical vertebrae (Hellier and Connoly, 2009) and/or hyoid

(Ubelaker, 1992). However, the types of injuries that occur (e.g., cervical fracture vs. suffocation, vertebral/carotid artery rupture) are highly dependent on the placement of the knot and the height from which the person is dropped (Hellier and Connoly, 2009). Given that recommendations for drop heights and knot positions in judicial hangings in the United Kingdom were not published until 1875 (Hellier and Connoly, 2009), at least 75 years after the burials at

Smithfield took place, it is not improbable that the individuals included in this dissertation were indeed victims of hanging, despite the absence of visible perimortem cervical fractures. In either scenario, a battlefield or hanging death would produce the relatively low survivorship observed.

It is therefore possible that the inclusion of individuals who died from capital punishment or interpersonal conflict obscured changing patterns of health between the late medieval and post- medieval periods as indicated by overall survivorship. This is because people who fall victim to such violence die from the event before they can experience decreased longevity associated with increased allostatic load. Indeed, the individuals buried at Smithfield were not the only victims of violence. The person from Essex St. West, for instance, suffered from periomortem sharp force trauma indicative of decapitation and the mounting of their head on a spike, likely on the town wall (Simpson, 1995). Signs of violence were also prevalent on remains from Johnstown. As described in Chapter 5, Burial 26 likely died from having their throat cut, which would be consistent with the perimortem sharp force trauma to the anterior cervical vertebrae. Another

258 individual from Johnstown, B145, also likely met a violent end. He had 20 perimortem sharp force injuries to the head, face, neck, and shoulder (Fibiger, 2004). While the location of these cut marks is consistent with dismemberment, it is extremely unlikely that a person from a largely

(if unofficially) Catholic country would be dismembered after dying of natural causes.

Notably, not everybody who was injured through interpersonal violence died as a result of their wounds. Burial 142 exhibited an injury to his head and face that resulted from a combination of sharp and blunt force, such as a battle axe or sword (Fibiger, 2004). This injury was well-healed, indicating that B142 survived for many years after the injury.

Despite signs of violence in the community buried at Johnstown, the individuals at this site still experienced greater survivorship than those at Ardreigh, where there were no skeletal signs of interpersonal violence. This is not to say, however, that the people are Ardreigh never fell victim to violence. Some injuries resulting from violence affect the soft tissue without damaging the bone. While the cemetery was mostly attritional, there were some graves at

Ardreigh that contained more than one individual (Keely and Opie, 2002). According to Keely and Opie (2002), this suggests that there were periodic infectious diseases that required a rapid burial of multiple people at one time. It is unknown if any of the burials from the graves containing multiple people were included in this dissertation. If victims of infectious disease outbreaks were included in this dissertation, then it would certainly explain the relatively low modal survival time at Ardreigh (S(t)=35). Because the rapidly spreading diseases that would result in mass graves (e.g., plague) often kill their victims before any skeletal changes can occur

(Wood et al., 1992), there are no skeletal indicators that could either support or refute this possibility.

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Furthermore, without access to site maps and burial recording forms showing the proximity of the skeletons to each other, it is impossible to know if any of the individuals from the mass graves were included in this sample.

Interestingly, there is a noticeable difference in the modal survival time between the two sites with either observable skeletal evidence of interpersonal violence (Johnstown) or documented evidence of interpersonal violence (Smithfield) (The Irish Builder, 1895). While the two sites are from different time periods and are therefore not directly comparable, it is striking that 50% of the population at Johnstown survived to age 75, but 50% of the population buried at

Smithfield were dead by age 35. Because of the vastly different modal survival times in these two sites, it is unclear precisely what the effect of interpersonal violence is on the overall survival patterns of the sample as a whole. It could be that violence had a lesser effect on overall survivorship at Johnstown because victims of violence represent a smaller proportion of the cemetery than did victims of violence at Smithfield. The cemetery at Johnstown was part of a medieval settlement and contained men, women, children, and infants (Fibiger, 2004). These burials spanned several centuries (Fibiger, 2004), so it is unlikely that all 491 of them were victims of interpersonal violence. The site at Smithfield, on the other hand, was a site known for the burial of hanging victims, and possibly, of victims of small battles (excavations.ie). It would therefore be unexpected for any of the people buried there to have died natural deaths. It is also possible that the certainty of death was greater for the people buried at Smithfield than at

Johnstown. At least one person from Johnstown (B142) survived his injuries. This would not have been an option for people condemned to death by hanging. If the people buried at

Smithfield died as a result of a battle in the 1500-1600s, then they would have been more likely to be shot than attacked with a battle axe or sword, the probable weapons used to injure the

260 victims of interpersonal conflict at the medieval site of Johnstown, since guns were invented after the people buried at Johnstown died. It is possible that these two modes of inflicting injury have different fatality rates. It does not appear then, that violence is the sole cause of differences in survivorship when it occurs. Rather, the mode of violence (e.g., sword, hanging, gunshot) and the intent of the violence (e.g., battle causalities vs. execution) are also important factors to consider.

Intra-site variation resulting from differences in sex

In addition to variation in survivorship between sites, it is also possible that there was variation within sites that could have obscured changes in survivorship between the late medieval and post-medieval periods. One source of intra-site variation could be sex. Figure 53 shows almost complete overlap in the Kaplan-Meier survival curves for males and females in the late medieval period. Figure 55, on the other hand, shows substantial differences in the Kaplan-

Meier survival curves between males and females in the post-medieval period. While the results of the log-rank test were not statistically significant, the visible difference in the survival curves and the fact that the results of the log-rank test (p=0.082) were close to the threshold for statistical significance (p=0.05) merit further exploration. As can be seen in Figure 55, the modal survival time for males and females in the post-medieval period was approximately 55 years.

Prior to 55 years, however, women appear to have experienced relatively lower survivorship than men, with the greatest difference presenting between the ages of about 20 and 35 years. While a little over 80% of men survived to age 25, only slightly over 60% of women survived to the same age (Figure 55). A similar divergence occurs after age 55, though the difference is not as stark as it is in early adulthood. Slightly less than 50% of adult men survived to age 70, and

261 about 30% of women survived to the same age (Figure 55). The two survival curves converge again at age 85, when survivorship is 0% for both men and women.

While it does not explain differences in survivorship between ages 55 and 85, one possible cause of the comparatively lower survivorship for women in their twenties and early thirties could be maternal mortality. This is supported by the absence of difference in LEH number (p=0.092) and overall width (p=0.845), in post-medieval adult males and females, and an absence of difference in survivorship between boys and girls, as estimated from post-medieval burial records (Figure 58) (p=0.845). Together, these results suggest that the differences in male and female survivorship did not result from differential treatment of boys and girls in childhood.

Unfortunately, there are no accurate reports of maternal mortality before about 1750 (Loudon,

1986, De Brouwere, 2007). One estimate puts maternal mortality in London at about 21 per

1,000 between 1657 and 1750 (Eccles, 1977), but others estimate it to be anywhere from 7.5 per

1,000 to 39 per 1,000 (Loudon, 1986).

The population in Ireland during the post-medieval period grew at an unprecedented rate

(Ó Gráda, 1979). People married younger, and fecundity increased (Ó Gráda, 1979). It is therefore possible that if maternal mortality rose in the post-medieval period, it did so simply as a result of increased fecundity. Women were having more children, and in doing so, could have increased their risk of death in childbirth simply because the number of times they were vulnerable to such a death increased.

Changing practices in childbirth between the late medieval and post-medieval periods might also have contributed to differences in survivorship in men and women between the ages of 20 and 35 in the post-medieval period. Childbirth between 1671 and 1795 grew increasingly medicalized. More women gave birth at hospitals instead of at home and were attended by male

262 midwives and physicians instead of the traditional female midwives (Allotey, 2011). Women from upper class families sometimes preferred to have their children delivered by a male doctor because it was more fashionable (Allotey, 2011). Poor women, on the other hand, sought refuge in charitable lying-in hospitals, where they would at least be guaranteed food and warm shelter, privileges often not afforded to them in their everyday lives (Adair, 1910).

There is debate about the effect of lying-in hospitals on maternal mortality. Many historians have claimed that lying-in hospitals were instrumental in the spread of puerperal fever

(Streptococcus pyogenes), which was often fatal before the invention of antibiotics (Cody, 2004).

Others, however, have written that deaths in lying-in hospitals were less frequent than maternal deaths outside of the hospitals, and that in 18th century Britain, cases of puerperal fever were relatively rare (DeLacy, 1989).

Puerperal fever spread through even small lacerations or tears in the vagina, especially when attending midwives and physicians did not wash their hands. Women with puerperal fever would experience lightheadedness, severe abdominal pain, vomiting, fever, convulsions, thirst, rapid pulse, headaches, edema, suppression of milk production, delirium, and in many cases, death (Cody, 2004, Hallett, 2005). Overcrowded hospitals and unwashed hands and obstetric instruments provided the perfect breeding ground for the Streptococcus bacteria. In the British

Lying-In Hospital in London, for example, 40 women would be housed together at any given time (De Browene, 2007). Moreover, it was not uncommon for doctors to dissect a body and then attend a birth without washing their hands or instruments (De Browene, 2007).

Epidemics of puerperal fever were recorded in continental Europe by 1652, and were noted in Dublin in 1770 (De Browene, 2007), falling well within the timeline of the post- medieval samples in this dissertation. Epidemic puerperal fever was more fatal than sporadic

263 cases and resulted in 70-80% of infected women dying during outbreaks. Comparatively, women who contracted sporadic puerperal fever faced a mortality rate of 25-30% (Hallett, 2005).

Additionally, women in lying-in hospitals were vulnerable to diseases other than puerperal fever, such as typhoid and pneumonia, brought into the hospital by other patients (Loudon, 1986).

Women also faced possible death from hemorrhage, eclampsia, or pre-eclampsia, though women in hospitals did not appear to have suffered from these at a greater rate than the general population (Cody, 2004).

A third potential cause of maternal mortality in 18th-century Dublin that could have contributed to the apparent difference in survivorship of men and women between the ages of

20-35 is urban overcrowding. As is the case for many modern-day slums (Rice and Rice, 2009), the poor were attracted to post-medieval Dublin by the opportunity for jobs and cheap rent in tenement houses, such as those in St. Luke’s parish (corresponding to the site at Coombe/Cork

St.) (Frazer, n.d.). As described in Chapter 5, most of the residents of St. Luke’s parish were poor, and families were crowded into the sublet Dutch Billies (Frazer, n.d.). While residents of the parish of St. Michan’s (corresponding to the North King St. site) were relatively better off than the residents of St. Luke’s, the majority of them still lived in poverty (Figure 8, Frazer, n.d.). Because the growing size of the population into three parishes in 1727 (Ronan, 1948,

Fagan, 1991), at least some degree of urban overcrowding and damp housing would have made people more vulnerable to diseases such as smallpox, typhus, typhoid, scarlet fever, tuberculosis, and dysentery (Daly, 2017), all of which were common in post-medieval Dublin (Jordan, 2014).

Residents of St. Luke’s and St. Michan’s parish would have been made even more vulnerable to these infectious diseases because of decreased immunity resulting from malnutrition (Rice and

Rice, 2009).

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The housing conditions in St. Luke’s parish, as indicated by archaeological evidence of faulty water pipes and structurally unsound building (Frazer, n.d.), match housing conditions in modern urban slums, which are characterized by overcrowding, limited access to clean water, and buildings lacking structural integrity (Rice and Rice, 2009). People in modern urban slums are more likely to experience malnutrition, higher infant and maternal mortality, and overall decreased longevity (Rice and Rice, 2009). Women often face more of these health disadvantages than men, in part because these conditions contribute to increased maternal mortality (Rice and Rice, 2009).

While the precise cause of the spread of infectious disease was unknown at the time, the first lying-in hospital in Dublin, The Rotunda Lying-In hospital, was built to try to reduce maternal mortality in Dublin urban slums (Adair, 1910). Doctor Bartholemew Mosse, founder of

The Rotunda Lying-In hospital, described the often fatal conditions in which women in 18th- century Dublin gave birth. He writes,

“The misery of the poor women of Dublin at the time of their lying-in could

scarcely be conceived by anyone who had not been an eye witness of the

wretched circumstances. Their lodgings were generally in cold garrets, open

to the wind, or in damp cellars, subject to floods from excessive rain, destitute

of attendance, medicine, and often of proper food by which hundreds perished,

with their little infants (Mosse in Adair, 1910:10).”

If the difference in survivorship between 20-35-year-old men and women is indeed due to an elevated risk of maternal mortality, then it could be that the conditions in the overcrowded

265 urban slums of St. Luke’s (and possibly, St. Michan’s) that the founders of lying-in hospitals were trying to mitigate were the main contributors to maternal mortality, not the lying-in hospitals themselves.

Finally, an additional potential cause of the differences in survivorship between men and women could be the trauma of family separation. As one of the most densely populated and poorest parishes in Dublin, the number of people who entered workhouses from St. Michan’s was larger than for other parishes. Upon entering these workhouses, families were separated; women were sent to one wing of the workhouse, men to another, and the children to a third.

Thus, husbands and wives were separated, and mothers were separated from their children. This separation frequently lasted the rest of their lives, as many people (especially children) who entered the workhouses died there. The effects of this trauma on women have been shown in popular media such as Call the Midwife, but have also been documented among Native Canadian women who were forcibly separated from their children (Kenny et al., 2019). It is not unlikely given the large number of people from St. Michan’s who spent time in the workhouses that some of the people in the North King Street sample were victims of the practice of family separation.

The parish of St. Luke’s, from which the Coombe/Cork St. skeletal sample is derived, was even poorer, and it is likely that many from St. Luke’s also experienced life (and/or death) in the workhouses. The practice of family separation, and its documented traumatic toll on mothers, could also explain the differences in survivorship between men and women in the post-medieval period.

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Changes in childrearing practices

Another cultural factor that could have contributed to the lack of clear differences between the late medieval and post-medieval periods were changes in childrearing practices.

Now regarded as more harmful than beneficial, these childrearing practices could have eliminated any potential health improvements for the upper classes during the post-medieval period. In a study of health among children across London cemeteries of varying social statuses,

Newman and Gowland (2017) found that children of different social statuses had similar health markers (e.g., stunted growth). They suggest that the reason for this similarity could be the harmful but fashionable infant care practices adopted by the upper class (Newman and Gowland,

2017). These practices included replacing breastmilk with artificial infant food or cow’s milk and keeping infants inside and away from fresh air and sunlight (Newman and Gowland, 2017).

Breastfeeding declined among the upper classes in the 18th-19th centuries in London because it was considered unfashionable (Newman and Gowland, 2017). Many lower class women, on the other hand, continued to breastfeed, as long as they did not work outside the home, though exclusive breastfeeding would have been insufficient after six months of age (Newman and

Gowland, 2017). Lower class women who did work outside of the home experienced a decline in breastfeeding similar to that of upper class women, but lower class working women would stop breastfeeding soon after birth because they had to work long hours outside the home and away from their infants, not because it was more fashionable (Newman and Gowland, 2017).

Breastfeeding would have protected against the poor sanitation in London, and exposure to sunlight would have reduced the risk of Rickets (Newman and Gowland, 2017).

The role of changing childrearing practices that accompanied industrialization in post- medieval Dublin is a subject that merits further investigation. If the changes in childrearing

267 practices between the late medieval and post-medieval periods resulted in poorer health for all social classes, then the differences between the late medieval and post-medieval periods should be more visible, not less. However, changing childrearing practices could account for the difference in LEH number and the width of LEH in cervical width between the late medieval and post-medieval period (p=0.053). The average width of cervical LEH in incisors from individuals who lived in the late medieval period was 0.198mm, and the average width of cervical LEH in incisors from individuals who lived in the post-medieval period was 0.242mm. Because the central incisors begin calcifying at 3-4 months, and the lateral incisors begin calcifying between

3-4 months (mandibular) and 10-12 months (maxillary) (Logan and Kronfeld, 1933), changes in infant care practices could have produced the differences in number and width between the two periods. If upper class mothers stopped breastfeeding because it was unfashionable, or if lower class working mothers stopped breastfeeding because they had to work outside the home, then it could be expected that the infants who were consuming artificial infant food or cow’s milk were not receiving the immunological benefits of breast milk and were therefore experiencing longer periods of illness or malnutrition that could have produced the wider LEH in the cervical regions of the incisors. Conversely, it is possible that infants in the post-medieval period were better able to withstand longer periods of stress than infants in the late medieval period, though given documented changes in British childcare practices and the hazards of industrialization and urbanization (described further below), the former possibility is more likely.

Selective enforcement of the Penal Laws and religious diversity

Another cultural factor that could have contributed to the mixed findings in health changes between the late medieval and post-medieval period is the selective enforcement of the

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Penal Laws and the religious diversity in post-medieval Dublin. As described in Chapter 3, the goals of the Penal Laws were to protect the British monarchy by suppressing the political and economic capital of Catholics, who were perceived to be hostile to British colonial rule, and to make the Catholic population more economically productive by eliminating observance of Holy

Days (McBride, 2009). These laws limited sources of Catholic upward social mobility by restricting property ownership, employment, and inheritance (McBride, 2009), but the extent to which these laws were enforced has been a subject of debate (Shaffrey Associates Architects et al., 2003).

Revisionists have argued that the effects of the Penal Laws have been overstated by historians such as Cobbett (1829), Moran (1899), Madden (1906), and McManus (1921) to justify nationalist movements (O’Mahony and Delanty, 2001). Revisionists have pointed to the selective enforcement of the Penal Laws, arguing that they targeted “unacceptable” Catholics while excluding those deemed to be “acceptable” by the Protestant ruling class (Hill, 1984).

While stories of priest hunters (e.g., Archdeacon, 1844) would lead one to believe that

Catholicism was completely outlawed and that all Catholics were severely punished, church records actually show a level of permissiveness toward Catholics in Dublin. These records show that there were a number of Catholic communities in post-medieval Dublin, including those from the parishes of St. Nicholas Without, St. Brides, St. Kevins, and St. Luke’s (Shaffrey Associates

Architects et al., 2003). There was even a Catholic mass house near St. Luke’s on Ash Street, where worshipers from the Carmelite Catholic community of Whitefrirary Street were known to have held Mass (Shaffrey Associates Architects et al., 2003).

Moreover, while interpreting the historical significance of the Penal Laws, religious diversity in Dublin is often overlooked (Ní Mhungaile, 2008). Catholics were not the only

269 minority religion in Dublin, as indicated by records of an Anabaptist meeting house and a

Hugenot burial ground (Schaffrey Associates Architects et al., 2003). The presence of religious diversity could have reduced the psychosocial effects of the Penal Laws. Even if not consistently or effectively enforced, it is possible that codified discrimination in the form of the Penal Laws contributed to a sense of inferiority and victimization. Discrimination in modern populations has been shown to be associated with adverse health effects resulting from changes to the responsiveness of the neuroendocrine system after exposure to persistent and/or severe stressors

(Williams, 1999, Williams et al., 2003, Williams et al., 2010, Freeman Anderson, 2012).

However, exposure to a critical mass of other members of racial minorities has been shown to reduce the risk of adverse health effects associated with discrimination (Brondolo et al., 2009).

This risk reduction occurs, in part, because of a collective cultural identity built around discrimination that acts as a buffer. When part of the collective cultural identity is one of victimization and oppression, members are able to recognize that the discrimination that they face is not a reflection of them as individuals, but is a product of broader historical circumstances

(Branscombe et al., 1999, Mossakowski, 2003, Sellers and Shelton, 2003, Cross, 2005). In this way, community reduces the perception of discrimination as a stressor. Community can also buffer the effects of discrimination by providing members with a body of cultural knowledge in which they can share information about coping strategies (Hughes et al., 2006).

Because race in post-medieval Ireland was constructed around religion, it is possible that the number of religious minorities (i.e., Catholics and Dissenters) in post-medieval Dublin created the critical mass necessary to buffer the psychosocial effects characteristic of discrimination. This buffering could have offset the risk of decreased longevity that victims of

270 discrimination often face, producing the similar survivorship curves in the late medieval and post-medieval period.

Unequal effects of colonization and industrialization across social strata

While social and economic stratification was present in Ireland long before British colonization (Graham, 1979), it will be argued here that British colonization and industrialization catalyzed the more extreme inequality characteristic of the post-medieval period. This inequality, in turn, could have contributed to the mixed support for the hypotheses tested.

The role of colonization as a catalyst for inequality has been demonstrated in other instances of colonialism, and in Latin America in particular (Frankeme, 2010). Large land grants for the production of cash crops in Latin America concentrated land and wealth into the hands of a few elite (Frankeme, 2010), just as large land grants for the production of crops for export and the extraction of rent concentrated land and wealth into the hands of a few elite in Ireland

(Moody and Martin, 1995). Additionally, just as land holdings in Ireland were offered in exchange for loyalty to the British monarchy (Moody and Martin, 1995), landholdings in Latin

America were offered as rewards for loyalty to the Spanish monarchy (Frankuma, 2010). At the same time, the Catholic church in Latin America made rules about land inheritance (Frankuma,

2010), not dissimilar to the rules for land inheritance set out by the Penal Laws. These colonial practices created structural conditions that favored inequitable economic growth (Frankuma,

2010).

Colonial practices such as land grants, the production of crops for export, and extractive rents spurred the rising inequality characteristic of industrialization and urbanization in Western

Europe. Perhaps paradoxically, the most urbanized modern countries are those with the highest

271 standards of living, but the residents of the most impoverished areas within the cities of these urbanized countries have a far lower standard of living and are least likely to benefit from urbanization (Rice and Rice, 2009), demonstrating that the benefits of industrialization are not distributed equally across social groups.

The inequitable distribution of the benefits of industrialization in Western Europe are described at length by Allen (2019). Allen (2019) describes economic transitions among several social classes in England and Wales between 1688-1867, including the landed class, the bourgeoise, the lower middle class, workers, farmers, and the poor. Throughout industrialization, the landed class maintained its proportion of about 2% of the total population in England and

Wales, while the bourgeoise (including large-scale entrepreneurs, bankers, merchants, lawyers, government officials, and investors) grew from about 3% of the population to 8-9% of the population (Allen, 2019). At the same time, the number of workers increased four-fold (Allen,

2019). Conversely, the number of farmers decreased as a result of the concentration of farming into larger and larger landholdings, and the amount of income earned by these farmers relative to workers doubled during the same time period (Allen, 2019). At the same time, there was no improvement in standard of living or increase in income among the poor in England and Wales

(Allen, 2019). The bourgiosie, on the other hand, enjoyed a rise in annual income from £145 in

1759 to £525 in 1798 (Allen, 2019).

As industrialization further intensified in the second half of the 18th century, so too did inequality. The poorest 80% of English and Welsh society earned 50% of the total income between 1688 and 1759; by 1798, the same fraction of the population made only 35% of the available income (Allen, 2019). Wealth became more and more concentrated into the hands of an increasingly few elite (Allen, 2019). Between 1688 and 1759, the richest 20% of the population

272 earned 50% of all available income, but by 1798, this 50% was going to the richest 9% of the population (Allen, 2019).

Unfortunately, researchers do not have access to such detailed financial records in Ireland because the archives, which held records of Irish government from approximately AD 1200-

1800, were destroyed in an explosion in 1922 when the Free State army attacked the Public

Records Office, where anti-treaty forces were storing their ammunition (Crowe, 2010). However, inferences can be made about inequality in the post-medieval period by observing dietary and housing differences between social classes and coupling these observations with records from neighboring counties such as those presented by Allen (2019). The few records that do exist demonstrate extreme inequality.

Similar to other industrializing nations, Ireland as a country was growing wealthier during the 18th century, with a national income rising from £15 million in 1730 to £75 million in

1815 (Clarkson and Crawford, 2001:29). Also similar to other industrializing nations, this growing wealth was not shared by all members of Irish society. As described in Chapter 3, the living conditions of the upper class and lower classes grew markedly divergent in the post- medieval period, just as they did in England and Wales. These divergent conditions, while not observable through extensive records similar to those available in England, are clearly seen in differences in diet and housing. The upper classes in Ireland enjoyed a broad diet that included meat, poultry, fish, dairy products, breads, grains, fruits, vegetables, sweets, alcohol, tea, and coffee (Clarkson and Crawford, 2001:29, Shanahan, 2016, Sexton, 2016). The poor, on the other hand, came to consume a diet based almost exclusively on potatoes (Clarkson and Crawford,

2001:77).

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The upper classes in Ireland also enjoyed life in opulent estate houses, known as Big

Houses, funded by income made from charging rents on their landholdings (Dooley, 2017:161).

As demand for Irish crops increased, landlords were able to charge higher and higher rents

(O’Connell, 2007), just as has happened in Latin American counties (Frankema, 2010). The lower classes, unlike the upper classes, lived in either one-room hovels in the Irish countryside

(Rowley, 2017), in the tenement houses in Dublin (Frazer, n.d.), or in the most dreaded circumstances, the workhouse (Buckley and Riordan, 2017).

Finally, the very few surviving records demonstrate extreme inequality. By the 1670s, the top 14% of the population in Ireland had incomes four times larger than those of the lower 86%

(Clarkson and Crawford, 2001:29). By the 1790s, the economic conditions in Ireland mirrored almost exactly those in England and Wales described by Allen (2019), with the richest 10% of the population earning four times the income of the bottom 60% (Clarkson and Crawford,

2001:29-30). By 1800, the poorest members of the Irish population made no cash income

(Clarkson and Crawford, 2001:29-30).

The above data show that colonization catalyzes social inequality during industrialization by concentrating wealth into the hands of the elite members of society who are loyal to the colonizing power (e.g., England, Spain). The structures put in place through colonialism prevent equitable economic growth by limiting the upward socioeconomic mobility of the lower classes.

As international policy shifted from colonialism to industrialization and (neo)liberalism, the practices of colonialism that have primed the social structure for inequality are further built upon, creating even further divides in the life experiences of the rich and poor.

It is possible that it is this very inequality that prevented differences in health from being observed, though some differences are still apparent. First, the physical separation of the upper

274 and lower classes in to rural and urban areas could have contributed to the failure to identify clear differences in health between the late medieval and post-medieval periods. Second, the dissonance between biological and chronological age that is often experienced by those living in extreme poverty could have contributed to the failure to identify differences in survivorship by making it appear that people in the post-medieval period survived to older ages than they actually did.

During the 1700s, the wealthy business owners who had previously lived in Dublin moved out of the city and into the surrounding countryside (Frazer, n.d.). At the same time, the working class and poor were increasingly attracted to Dublin by the cheap rents of the subdivided and sublet buildings that had previously been home to the wealthy entrepreneurs who had moved to the countryside (Frazer, n.d.). This resulted in a physical separation between the rich and poor. Notably, the post-medieval samples for this dissertation were exclusively from the city of Dublin, meaning that the people who benefited from colonialism and industrialization by achieving a higher social status were likely not part of the post-medieval sample. Additionally, only three parishes are recorded in 1798 as having a lower class making up less than 50% of the population (Sheridan-Quantz, 2001). These are St. George, St. Anne, and St. Peter (Figure 8)

(Sheridan-Quantz, 2001), and sites from none of these parishes were included in the post- medieval sample. Had individuals from these parishes been included, status differences between post-medieval sites might have been more apparent. At the time of data collection, no skeletal remains from the parishes of St. George, St. Anne, or St. Peter were available for study.

Despite the absence of high status sites from the post-medieval period, there are still apparent differences in survivorship and LEH width. People buried at the Coombe/Cork St. site, who were probably members of St. Luke’s parish, survived on average to younger ages (modal

275

S(t)=40) than individuals buried at the North King St. site (modal S(t)=70), who were probably members of St. Michan’s parish. These differences are consistent with decreased longevity associated with widespread poverty. St. Luke’s parish was the poorest in Dublin, and the proportion of people recorded as upper or middle class in St. Luke’s parish in 1798 is close to

0% (Sheridan-Quantz, 2001). While most of the residents of St. Michan’s parish were lower class, a larger proportion of them were upper or middle class than in St. Luke’s, amounting to about 15% of the parish population (Sheridan-Quantz, 2001). These differences in class, coupled with the statistically significant differences in survivorship between the Coombe/Cork St. and

North King St. sites suggests that on average, people in St. Luke’s parish were exposed to more of the stressors like overcrowding, poor sanitation, disease, and malnutrition that put people in poor, urban environments at risk for decreased longevity. The differences in survivorship between Coombe/Cork St. and Smithfield and between North King St. and Smithfield, on the other hand, are likely a product of the people buried at Smithfield dying from conflict or execution and are unlikely to be the result of status differences.

While people buried at the Coombe/Cork St. site experienced lower average survivorship than people buried at the North King St. site, people buried at North King St. had, on average, wider cervical LEH (mean width = 0.263 mm) than people buried at the Coombe/Cork St. site

(mean width =0.136mm) (p<0.01). One possible reason for this difference is that children growing up in St. Luke’s parish experienced stressors of shorter duration than children growing up in St. Michan’s parish. However, as described in Chapter 4, biocultural and historical context can shape our interpretations of the presence of skeletal stress markers (Kyle et al., 2018), and economic records provide the context with which to interpret the wider LEH in the North King

Street sample. Given the near complete poverty of St. Luke’s parish and exposure to hazards

276 such as poor sanitation and overcrowding, it is more likely that children growing up in St.

Michan’s parish were better able to combat childhood stressors characteristic of urban life than children growing up in St. Luke’s parish. The wider LEH in adults from St. Michan’s suggest that as children, they did not succumb to prolonged illnesses or periods of malnutrition as quickly as children in St. Luke’s, who could have died as a result of these stressors and thus, before adulthood.

Differences in survivorship in the late medieval period are harder to interpret. People buried at the Johnstown site survived, on average, to older ages (modal S(t)=75) than people buried at Ardreigh (modal S(t)=35), though as described in previous sections, this difference could be the result of the possible inclusion of individuals from catastrophic graves at Ardreigh.

Both Ardreigh and Johnstown are rural sites, so the difference in survivorship cannot be a consequence of differences in urban and rural locality. Johnstown and Ardreigh revealed a variety of artifacts (Moloney et al., n.d., Clarke, 2002), though those found at Ardreigh suggest a higher status than those at Johnstown and included elaborately decorated combs, brooches, and leisure items (Moloney et al., n.d.). One individual at Ardreigh appeared to be of high status, afforded to him by the shell pendant around his neck marking a pilgrimage to Santiago de

Compostela (Moloney et al., n.d.). Despite the higher-status artifacts at Ardreigh, people buried at Ardreigh still experienced lower average survivorship than those buried at Johnstown. The difference in survivorship in this case therefore appears to be due not to social status, but a sampling error. Future researchers should assess survivorship using a larger proportion of the individuals excavated from Ardreigh than those included in this sample to reduce the effects of possibly including a large fraction of individuals from catastrophic burials.

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The difference in survivorship between Johnstown and Mercer Hospital is also difficult to interpret because the individuals randomly assigned to the late medieval period may not actually have lived during the late medieval period. The burials at Mercer Hospital span several centuries and include people from both the late medieval and post-medieval periods. If the burials randomly assigned to the late medieval period actually lived during the late medieval period, then those people would likely have been associated with either St. Stephen’s Church or St.

Stephen’s leper hospital (Buckley and Hayden, 2002, Dublin City Council, 2013). If the burials are associated with St. Stephen’s hospital, then death by infectious disease (e.g., leprosy, tuberculosis) could explain the lower survivorship at Mercer Hospital than at Johnstown. If, however, the burials assigned to the late medieval period actually lived during the post-medieval period, then a number of other factors could have contributed to the difference in survivorship, such as intensified urbanization described elsewhere in this dissertation.

In addition to the physical separation between the upper and lower classes that prevented the inclusion of a range of social statuses in the post-medieval sample, the potential difference in health between the late medieval and post-medieval periods could have been obscured by dissonance between biological and chronological age. Crimmins and colleagues (2009) found that people living in poverty experienced more rapid biological aging than those who did not live in poverty, and Couoh (2016) documented differences between chronological age and biological age of skeletons. Other studies have found that prolonged exposure to stressors, such as discrimination and poverty contribute to accelerated cellular aging (Adams, 2005, Geronimus et al., 2010) and decreased bone mineral density (Gough and Godde, 2019). It is therefore possible that the intensification of poverty in post-medieval Dublin contributed to accelerated biological

278 aging, making skeletal remains of individuals appear older than they actually were and masking any differences in survivorship.

Hypothesis 1a: There will be no difference between the age-at-death distributions calculated using transition analysis and the skeletal remains in this dissertation, and those calculated using contemporary burial records from approximately the same location.

The final goal of this dissertation was to test the effectiveness of transition analysis as a tool to reconstruct population age-at-death distributions. Results were inconclusive. On the one hand, the log-rank test indicated substantial differences between the two Kaplan-Meier survival curves (p<0.01). Transition analysis appears to have underestimated age before the age of 50, suggesting that transition analysis overestimates the number of people who die in young and middle adulthood. On the other, the Kaplan-Meier curves crossed each other (Figure 61), thereby violating the assumption of proportional hazards, and both have modal survival times of 50 years.

There several reasons that could account for these inconclusive results. First, there was a substantial difference in sample size that could have made the log-rank statistically significant without actual differences between the two groups. The number of ages estimated using transition analysis was 319, and the number of ages collected from burial records was 2,084. The second reason could be the different parishes from which the data were collected. As shown above, the parish, or area of residency, is an important contributor to age-at-death. For example, people from St. Luke’s parish survived, on average, to younger ages than people from St.

Michan’s parish. The data for transition analysis was collected from the skeletal samples

279 primarily from St. Luke’s (Coombe/Cork St.) and St. Michan’s (North King St.), and included a small number of skeletons from Smithfield and St. Mary’s. The data collected from burial records, however, came primarily from the parish of St. Werburgh, but also included some people from St. Anne’s and St. Matthew’s. Just over 20% of the population of St. Anne’s was lower class in 1798, about 15% were servants, and the remaining were upper and middle class

(Sheridan-Quantz, 2001). St. Werburgh, which made up most of the sample for the burial record data, was also wealthier than St. Luke’s and St. Michan’s (Sheridan-Quantz, 2001). Just over

50% of people in St. Werburgh were lower class, and the other 50% were from the upper and middle classes (Sheridan-Quantz, 2001). Comparatively, almost all of the people in St. Luke’s parish were lower class, as were most of the people from St. Michan’s (Sheridan-Quantz, 2001).

The site that would be most comparable to St. Werburgh’s and St. Anne’s is St. Mary’s, but only one person from St. Mary’s Crypts was included in the sample, compared to the hundreds of individuals from St. Luke’s and St. Michan’s.

The differences in the survivorship, if they do exist, are likely due to differences in socioeconomic status in the two samples. To effectively test the use of transition analysis the reconstruction of population-level survivorship, samples of comparable socioeconomic status need to be evaluated. The stark differences in socioeconomic status in the transition analysis sample and the sample from the burial records almost impossible to interpret in terms of the effectiveness of transition analysis.

Methodological Factors

In addition to social and historical factors, a variety of methodological limitations could have contributed to the results in this dissertation. These are discussed below.

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Error in Sex Assessment

Incorrectly classifying individuals as male or female could have affected not only comparisons between men and women, but also could have affected overall age-at-death distributions as well. Incorrect classifications of sex, could have affected age-at-death distributions because the maximum likelihood age-at-death in the ADBOU software is at least partially dependent on selection of the correct prior distribution for sex. Similarly, use of the

Brooks and Suchey (1990) pubic symphysis aging method requires classification of an individual as either male or female. While most of the sex assessments in this dissertation matched those performed by Loreen Buckley, who analyzed the skeletons from Coombe/Cork St., the

Dominican Priory/Upper Magdalene, Mercer’s Hospital, and St. Mary d’Urso, the classification of many of the individuals from Smithfield as female supports this possibility because as either an execution or battlefield burial ground, it would be expected that most of these skeletons would be those of men.

Reliance on point values for age-at-death

The second possible methodological limitation that could have contributed to the failure to support the two main hypotheses tested is the reliance on point-value estimates instead of age ranges. However, if age ranges were included instead of just point values, then this would likely have resulted in even more overlap in survivorship, not less. Thus, it is unlikely in this case that reliance on point values for age-at-death contributed to the lack of differences in survivorship.

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Differences in location

The third methodological limitation that could have contributed to the inability to completely support or refute the two main hypotheses is the difference in location for the sites between the two time periods. While the sites from the late medieval period are from a range of counties within the English Pale, including Meath, Kildare, and Louth, the sites from the post- medieval period were exclusively from Dublin. This is because there were no sites identified as post-medieval from the other counties in the Pale available for study at the time of data collection. Consequently, many of the individuals in the late medieval sample would have lived in rural areas and towns, whereas those in the post-medieval sample would have lived in the highly urbanized city of Dublin. Several bioarchaeological studies (e.g., Redfern et al., 2015,

Gamble et al., 2017, Krenz-Niedbała and Łukasik, 2017, Rohnbogner and Lewis, 2017, Walter and DeWitte, 2017), while not conducted on Irish skeletons, have shown substantial differences in health between rural and urban sites, suggesting that the two are not directly comparable.

Others, however, have found little to no difference in contemporaneous rural and urban sites

(e.g., Somers et al., 2017).

Overlap in time period

It is also possible that the cemeteries are too close in date, and that the individuals buried within in them are not representative of either the late medieval or post-medieval periods. For example, the site at Mercer’s Hospital contained burials from a wide temporal range, spanning from the 13th-century to the 19th-century (Buckley and Hayden, 2002). Except for one individual

(SK 1015), none of the burials from Mercer’s Hospital included in this dissertation could be reliably assigned to a time period. Similarly, the burials from Smithfield could be from either the

282 late medieval or post-medieval period, as burials there took place in the 16th-century (late medieval) and 17th-century (post-medieval) (excavations.ie).

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Chapter 10: Conclusion

Most of the historical writing about Ireland has focused on the divide between nationalist and anti-nationalist scholarship (McDonnell, 2013). While revisionists have argued that the effects of British colonization on Irish health have been overstated and mythologized as part of a nationalist agenda (O’Mahony and Delanty, 1998, Perry, 2010), post-revisionists have asserted that revisionists ignore the cultural trauma of catastrophic events (e.g., the Cromwellian Wars, the Great Famine) that were, at least partially, contributed to by British colonialization

(O’Mahony and Delanty, 1998). Both of these arguments are dichotomous and lack dimensionality, which likely contributed to the difficulty in the interpretation of the results of this dissertation when considered only in terms of revisionist vs. post-revisionist. First, there was no clear difference in survivorship between the late medieval period and post-medieval period when these groups were treated as homogenous, representative samples. When separated by sex and parish, however, clear differences in survivorship between sub-groups were revealed.

Notably, survivorship in St. Luke’s parish (Coombe/Cork St.) was significantly shorter than survivorship in St. Michan’s parish (North King St.), a difference that is likely a result of differences in socioeconomic status between the two parishes. Survivorship was also different between Coombe/Cork St. and Smithfield, but unlike the difference between Coombe/Cork St. and North King St., this difference was more likely due to the forms of interpersonal violence that took place at the Smithfield site (i.e., combat and capital punishment).

284

There were also differences in survivorship between men and women in the post- medieval period that approached statistical significance and would have been overlooked had the sample not been further divided by sex. Since these women were from the same parishes as the men in the post-medieval sample, it was not solely social class that was causing the differences in survivorship. Rather, it was likely a combination of social class, which exposed women to poor sanitation, overcrowding, and disease, as well as childbirth, which together could have resulted in higher maternal mortality in the post-medieval period than in the medieval period.

Taken together with the burial records of boys and girls in Dublin, and the absence of differences in LEH between men and women in the post-medieval period, a rise in maternal mortality is the most likely possibility. This shows not only the importance of considering different intersecting identities (here, class and gender), but also the importance of using multiple lines of evidence to reconstruct life circumstances that could have contributed to the bioarchaeological results.

Differences in survivorship between sites were not limited to the post-medieval period.

There were significant differences in survivorship between Johnstown and Ardreigh, and between Johnstown and Mercer Hospital. When taken together with archaeological evidence

(i.e., the presence of mass graves and high-status grave goods at Ardreigh) and historical documentation (i.e., the records of St. Stephen’s leper hospital at the Mercer Hospital site), the differences in survivorship in the late medieval period appear to be the result of rates of infectious disease, not class, as was the case for the post-medieval period.

While there were no differences in survivorship between the two time periods, the number of LEH indicative of childhood stress events did increase during the post medieval period. This could suggest that health actually improved in the post-medieval period, and that

285 perhaps more people were able to survive childhood stressors, therefore supporting the revisionist narrative of Irish history. Such an interpretation, however, would be inconsistent with the biocultural context of the time. It is more likely, given the historical, political, and social context, that life in the post-medieval period was harder for children than it had been in the late medieval period. This further demonstrates that an intersectionality lens is required to interpret the effects of colonization on Irish health. Using this lens, it becomes evident that women and children suffered the most from the structural violence imposed by British colonization.

Additionally, there were several differences in LEH width. LEH on canines from males who lived during the late medieval period were wider than the LEH on canines from females who lived in the same places at the same time. This could either mean that boys were exposed to more stressors that produced LEH during the late medieval period, or they were better able to withstand longer periods of stress. This difference requires more investigation in future studies, but is nonetheless important because it again shows the importance considering different social identities instead of treating a sample as homogenous and representative of a single time period.

The second difference in LEH width was the relatively greater width of LEH in people from St. Michan’s parish (North King St.) compared to those from St. Luke’s parish

(Coombe/Cork St.). There were no differences by sex, suggesting that here the main contributing identify to the difference was social class, not gender. As is the case for the greater width of LEH in late medieval boys compared to girls, it is unclear if these wider LEH are a mark of frailty by signifying greater exposure to stressors, or are a mark of resilience, signifying a greater ability of the body to resist such stressors. Given the biocultural context, however, the difference in LEH width, where the individuals from St. Michan’s parish have wider LEH than those from St.

Luke’s parish, is likely due to high childhood mortality in the nearly universally poor parish of

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St. Luke’s. The living conditions in St. Luke’s could have made it difficult for the children there to overcome prolonged periods of stress. Additional research is required to identify the meaning of the difference in LEH width between these parishes, but it again shows the importance of considering social identities.

Rather than focusing on the debate between revisionist and post-revisionist arguments, which homogenize the Irish population, Irish historians and bioarchaeologists should continue to explore the role of British colonization with a framework of intersectionality theory. According to intersectionality theory, marginalized identities like race, class, and gender interact to expose individuals to different degrees of social inequality and to maintain these systems of inequality over time (Yaussy, 2019). Intersectionality theory, while frequently used in studies of living people, has rarely been used explicitly in bioarchaeology (Yaussy, 2019). As demonstrated here, intersectionality theory can change how bioarchaeologists study health by linking local identities with large-scale power structures (Yaussy, 2019), such as colonialism and industrialization.

When intersectionality theory is not applied, the lack of clear differences between the late medieval and post-medieval periods appear to support revisionist arguments that the impact of

British colonization on health has been overstated. When intersectionality theory is applied, however, the differences in the impact of British colonization across identities of class and gender are revealed. Rather than having one uniform effect across the entirety of the Irish population, British colonization appears to have affected health by acting as a catalyst for industrialization, which concentrated wealth into the hands of a relatively few elite. The concentration of wealth gave people of different social statuses highly divergent degrees of access to resources, thereby exposing them to different types of stressors. While members of the upper class had access to a wide range of foods, cash income, and warm, dry housing, people of

287 the lower class had access to only one type of food (potatoes), had little to no cash income, and lived in urban slums or rural hovels that were often cold and damp. Women of both social statuses would have been vulnerable to death during childbirth (especially during epidemics of puerperal fever), but women who lived in urban slums without access to food or a sanitary place to give birth would have likely been more vulnerable to death in childbirth. Men, on the other hand, would have been more vulnerable to death as a result of interpersonal conflict or capital punishment. If gender is not considered, then the different stressors that each group was exposed to would go overlooked, and the revisionist argument would be supported.

Age also proved to be an important social identity. While there were no differences in survivorship between the late medieval period and post-medieval period, the number of LEH increased. This suggests that while health status might not have changed for adults as a whole

(i.e., when no attempt to differentiate by gender is made), children suffered from more hardships in the post-medieval period than in the late medieval periods. With an intersectionality lens, it becomes clear that British colonization contributed to the declining health of women, children, and the poor during the post-medieval period.

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Figure 106: Summary of how political economy and intersectionality contribute to the effects of colonization Finally, bioarchaeologists adopting a biocultural political economy framework must take into account stressors beyond resource acquisition. As discussed in the previous chapter, stressors can include not just decreasing dietary diversity and malnutrition (the main stressors under a political economy framework), but can include disease, crowded and damp living conditions, discrimination, institutionalization, and family separation.

Contrary to initial expectations, the effect of British colonization was not to have a uniform, adverse effect on health across the majority of Irish population. Rather, these results,

289 interpreted using an intersectionality framework, show that the effect of British colonization was ultimately to exacerbate differences between social strata (summarized in Figure 106). In particular, age, class and gender disparities in access to resources, exposure to stressors, and health became more extreme. In conclusion, the intersectionality of race, class, gender, and local/international politics and economic systems need to be considered together as part of a biocultural political economy framework to make meaningful contributions to the revisionist/post-revisionist debate.

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Works Cited

Ábrahám, H., Vincze, A., Jewgenow, I., Veszprémi, B., Kravják, A., Gömöri, É., Seress, L.

(2010) Myelination in the human hippocampal formation from midgestation to adulthood.

International Journal of Developmental Neuroscience 28(5):401-410.

Adair, S.F. (1910) Rotunda Lying-In Hospital (Founded 1745, chartered 1756) and auxiliary hospital: A short history of facts regarding this institution. Dublin: Browne & Nolan, Ltd.

Adams, J., White, M., Forman, D. (2005) Is the rate of biological aging, as measured by age at diagnosis of cancer, socioeconomically patterned? Journal of Epidemiology and Community

Health 59(2):146-151.

Adelman, J. (2017) Food in Ireland since 1740. Health and welfare. In: Biagini, E.F., Daly, M.E., eds. The Cambridge Social History of Modern Ireland. Cambridge: Cambridge University Press.

233-243.

Alastalo, H., Räikkönen, K., Pesonen, A.K., Osmond, C., Barker, D.J.P., Heinonen, K., Kajantie,

E., Eriksson, J.G. (2013) Early life stress and blood pressure levels in late adulthood. Journal of

Human Hypertension 27:90-94.

291

Allen, R.C. (2019) Class structure and inequality during the Industrial Revolution: Lessons from

England’s social tables, 1688-1867. The Economic History Review 72(1):88-125.

Allotey, J.C. (2011) English midwives’ responses to the medicalization of childbirth (1671-

1795). Midwifery 27(4):532-538.

Allsworth, J.E., Weitzen, S., Boardman, L.A. (2005) Early age at menarche and allostatic load:

Data from the Third National Health and Nutrition Examination Survey. Annals of

Epidemiology 14:438.

Almeida, M., Laurent, M.R., Dubois, V., Claessens, F., O’Brien, C.A., Bouillon, R.,

Vanderschueren, D., Manolagas, S.C. (2017) Estrogens and androgens in skeletal physiology and pathophysiology. Physiological Reviews 97(1):135-187.

Altman, D.G. (1991) Practical Statistics for Medical Research. London: Chapman and Hall.

AlQahtani, S.J., Hector, M.P., Liversidge, H.M. (2010) Brief communication: The London dental atlas of tooth development and eruption. American Journal of Physical Anthropology 142:481-

490.

Álvarez-Nava, F., Lanes, R. (2017) GH/IGF-1 signaling and current knowledge of epigenetics; A review and considerations on possible therapeutic options. International Jounal of Molecular

Sciences 18(1624).

292

Amoroso, A., Garcia, S.J., Cardoso, H.F. (2014) Age at death and linear enamel hypoplasias:

Testing the effects of childhood stress and adult socioeconomic circumstances in premature mortality. American Journal of Human Biology 26:461-468.

Anda, R.F., Dong, M., Brown, D.W., Felitti, V.J., Giles, W.H., Perry, G.S., Valerie, E.J., Dube,

S.R. (2009) The relationship of adverse childhood experiences to a history of premature death of family members. BMC Public Health 9:106.

Andre, C.M., Legay, S., Iammarino, C., Ziebel, J., Guignard, C., Larondelle, Y. Hausman, J-F.,

Evers D., Miranda L.M. (2014) The potato in the human diet: A complex matrix with potential health benefits. Potato Research 57:201-214.

Antoine, D., Hillson, S., Dean, M.C. (2009) The developmental clock of dental enamel: A test for the periodicity of prism cross-striations in modern humans and an evaluation of the most likely sources of error in histological studies of this kind. Journal of Anatomy 214(1):45-55.

Appleton, A.A., Armstrong, D.A., Lesseur, C., Lee, J., Padbury, J.F., Lester B.M., Marsit, C.J.

(2013) Patterning in placental 11-B hydroxysteroid dehydrogenase methylation according to prenatal socioeconomic adversity. PLoS One 8:e74691.

Archdeacon, M. (1844) An Irish Tale of the Penal Times. Dubin: James Duffy.

293

Armelagos, G.J., Goodman, A.H., Harper, K.N., Klakey, M.L. (2009) Enamel hypoplasia and early mortality: Bioarchaeological support for the Barker hypothesis. Evolutionary Anthropology

18:261-271.

Arnett, M.G., Pan, M.S., Doak, W., Cyr, P.E.P., Muglia, L.M., Muglia, L.J. (2015) The role of glucocorticoid receptor-dependent activity in the amygdala central nucleus and reversibility of early-life stress programmed behavior. Translational Psychiatry 5:e542.

Arnold, S.E., Trojanowski, J.Q. (1996) Human fetal hippocampal development:

Cytoarchitecture, myeloarchitectural, and neuronal morphologic features. Journal of

Comparative Neurology 367(2):274.

Bailey, M.T., Coe, C.L. (1999) Maternal separation disrupts the integrity of the intestinal microflora in infant rhesus monkeys. Developmental Psychobiology 35:146-155.

Bainard, T. (2001) Parlour entertainment in the evening? Histories of the 1640s. In: Ó Siochrú, ed. Kingdoms in Crisis: Ireland in the 1640s. Dublin: Four Courts Press.

Barker, D.J.P., Osmond, C. (1986) Childhood respiratory infection and adult chronic bronchitis in England and Wales. British Medical Journal 293:1271-1275.

294

Barker, D.J.P., Osmond, C., Golding, J., Kuh, D., Wadsworth, M.E.J. (1989) Growth in utero, blood pressure in childhood and adult life, and mortality from cardiovascular disease. British

Medieval Journal 298:564-567.

Barker, D.J.P., Shiell, A.W., Barker, M.E., Law, C.M. (2000) Growth in utero and blood pressure levels in the next generation. Journal of Hypertension 18(7):843-846.

Bartlett, J.D. (2013) Dental enamel development: Proteinases and their enamel matrix substrates.

ISRN Dentistry Article ID 684607.

Bauer, P.J. (2008) Toward a neuro-developmental account of the development of declarative memory. Developmental Psychobiology 50(1):19-31.

Beaumont, J., Montgomery, J., Buckberry, J., Jay, M. (2015) Infant mortality and isotopic complexity: New approaches to stress, maternal health, and weaning. American Journal of

Physical Anthropology 157:441-457.

Beglane, F. (2016) The social significance of game in the diet of later medieval Ireland. In:

FitzPatrick, E., Kelly, J., eds. Food and Drink in Ireland. Dublin: Royal Irish Academy. 167-196.

Belcher, T.W. (1868) Notes on the mediaeval leper hospitals of Ireland. Dublin Quarterly

Journal of Medical Science, 36-46.

295

Bennett, I. (1996) Excavations 1995: Summary Accounts of Archaeological Excavations in

Ireland. Wordwell, Ltd.: Bray, Co. Wicklow, Ireland.

Bennett, I. (1998) Excavations 1997: Summary Accounts of Archaeological Excavations in

Ireland. Wordwell, Ltd.: Bray, Co. Wicklow, Ireland.

Bennett, I. (2000) Excavations 1999: Summary Accounts of Archaeological Excavations in

Ireland. Wordwell, Ltd.: Bray, Co. Wicklow, Ireland.

Bennett, I. (2003) Excavations 2002: Summary Accounts of Archaeological Excavations in

Ireland. Wordwell, Ltd.: Bray, Co. Wicklow, Ireland.

Bennett, I. (2007) Excavations 2006: Summary Accounts of Archaeological Excavations in

Ireland. Wordwell, Ltd.: Bray, Co. Wicklow, Ireland.

Bercovich, E., Keinan-Boker, L., Shasha, S.M. (2014) Long-term health effects in adults born during the Holocaust. The Israel Medical Association Journal 16(4):203-207.

Bewick, V., Cheek, L., Ball, J. (2004) Statistics Review 12: Survival Analysis. Critical Care

8(5):389-394.

296

Bielenberg, A., O’Hagan, J. (2017) Consumption and living conditions, 1750-2016. Health and welfare. In: Biagini, E.F., Daly, M.E., eds. The Cambridge Social History of Modern Ireland.

Cambridge: Cambridge University Press. 195-211.

Bifolchi, N., Michel, P., Talbot, J., Svenson, L. (2014) Weather and livestock risk factors for

Escherichira coli O157 human infection in Alberta, Canada. Epidemiology and Infection

142(11):2302-2313.

Binford, L.R. (1968) Archaeological Perspectives. In: Binford, S.R., Binford, L.R., eds. New

Perspectives in Archaeology. Aldine. 5-32.

Binford, L.R., (1981) Bones: Ancient Men and Modern Myths. Academic Press.

Bish, T. (1834) A Plea for Ireland; Submitting the Outline of a Proposition for Holding the Court and Parliament at Occasional Intervals, in Dublin. In a Letter to the Right Hon. Lord Althorp,

Chancellor the Exchequer. London. J.M. Richardson and J. Cumming.

Blakey, M.L., Armelagos, G.J. (1985) Deciduous enamel defects in prehistoric Americans from

Dickson Mounds: Prenatal and postnatal stress. American Journal of Physical Anthropology

66:371-380.

Bocquet-Appel, J.P., Masset, C. (1982) Farewell to paleodemography. Journal of Human

Evolution 11:321-333.

297

Boldsen, J.L. (2007) Early childhood stress and adult age mortality- A study of dental enamel hypoplasia in the medieval Danish village of Tirup. American Journal of Physical Anthropology

132:59-66.

Boldsen, J., Milner, G.R., Konigsberg, L.W., Wood, J.W. (2002) Transition analysis: a new method for estimating age from skeletons. Paleodemography: Age Distributions from Skeletal

Samples. Hoppa, R.D and Vaupel, J.W., eds. Cambridge: Cambridge University Press, 73-106.

Borrell, L.N., Dallo, F.J., Nguyen, N. (2010) Racial/ethnic disparities in all-cause mortality in

US adults: The effect of allostatic load. Public Health Reports 125:810-817.

Boyle, P.P., O’Grada, C. (1986) Fertility trends, excess mortality, and the Great Irish Famine.

Demography 23(4):543-562.

Branscombe, N.R., Schmitt, M.T., Harvey, R.D. (1999) Perceiving pervasive discrimination among African Americans: Implications for group identification and well-being. Journal of

Personality and Social Psychology 77(1):135-149.

Brondolo, P.P., Libby, D.J., Denton, E-G., Beatty, D.L., Schwartz, J., Sweeny, M. Tobin, J.N.,

Cassells, A., Pickering, T.G., Gerin, W. (2008) Racism and ambulatory blood pressure in a community sample. Psychosomatic Medicine 70:49-56.

298

Brondolo, E., Brady ver Halen, N., Pencille, M., Beatty, D., Contrada, R.J. (2009) Coping with racism: A selective review of the literature and a theoretical and methodological critique. Journal of Behavioral Medicine 32:64-88.

Brooke Thomas, R. (1998) Chapter 2: The Evolution of Human Adaptability Paradigms: Toward a Biology of Poverty. In: Goodman, A.H., Leatherman, T.L., eds. Building a New Biocultural

Synthesis. Ann Arbor: University of Michigan Press.

Brooks, S.T., Suchey, J.M. (1990) Skeletal age determination based on the os pubis: A comparison of the Acsadi-Nemeskeri and Suchey-Brooks methods. Human Evolution 5:227-238.

Brown, C.R. (1993) Origin and history of the potato. American Potato Journal 70(5):363-373.

Brown, D.W., Anda, R.F., Tiemeier, H., Felitti, V.J., Edwards, V.J., Croft, J.B., Giles, W.H.

(2009) Adverse childhood experiences and the risk of premature mortality. American Journal of

Preventative Medicine 37:389-396.

Bryant Borders, A.E., Grobman, W.A., Amsden, L.B., Holl, J.L. (2007) Chronis stress and low birth weight neonates in a low-income population of women. Obstetrics & Gynecology

109(2):331.

Buck, C., Simpson, H. (1992) Infant diarrhea and subsequent mortality from heart disease and cancer. Journal of Epidemiology and Community Health 36:27-30.

299

Buckberry, J. (2015) The (mis)use of adult age estimates in osteology. Annals of Human Biology

42(4):323-331.

Buckley, L. (1996) Human Bone Report. In: Halpin, E. Excavations at St. Mary d’Urso,

Drogheda, County Louth. Journal of the County Louth Archaeological and Historical Society

23(4):452-509.

Buckley, L. (1997) Human Bone Report. In: Murphy, D. Archaeological excavations at the

Magdalene Tower, Drogheda, County Louth. Journal of the County Louth Archaeological and

Historical Society 24(1):75-128.

Buckley, L., Hayden, A. (2002) Excavations at St. Stephen’s leper hospital, Dublin: A summary account and an analysis of burials. Medieval Dublin III: Proceedings of the Friends of Medieval

Dublin Symposium 2001: 151-194.

Buckley, S.A., Riordan, S. (2017) Childhood since 1740. In: Biagini, E.F., Daly, M.E., eds. The

Cambridge Social History of Modern Ireland. Cambridge: Cambridge University Press. 327-343.

Buikstra, J.E. (1977) Biocultural dimensions of archeological study: A regional perspective. In:

Blakely, R.L., ed. Biocultural adaptation in prehistoric America. Athens: University of Georgia

Press. 67-84.

300

Buikstra, J.E., Ublaker, D.H. (1994) Standards for Data Collection from Human Skeletal

Remains. Fayetteville, Arkansas: Arkansas Archaeological Survey Report Number 44.

Bullock, M., Márquez, L., Hernández, P., Ruíz, F. (2013) Paleodemographic age-at-death distributions of two Mexican skeletal collections: A comparison of transition analysis and traditional aging methods. American Journal of Physical Anthropology 152:67-78.

Byrne, M.E. (1999) Graney East, Castledermot, Co. Kildare. Results of archaeological monitoring. Interim Report No. 1. Byrne, Mullins & Associates, Archaeological Consultants.

Caldiji, C., Tannenbaum, B., Sharma, S., Francis D., Plotsky, P.M., Meaney, M.J. (1998)

Maternal care during infancy regulates the development of neural systems mediating the expression of fearfulness in the rat. Proceedings of the National Academy of Science 95:5335-

5340.

Campbell, K. (1996) Ceramic Report. In: Halpin, E. Excavations at St. Mary d’Urso, Drogheda,

County Louth. Journal of the County Louth Archaeological and Historical Society 23(4):452-

509.

Cappella, A., Cummaudo, M., Arrigoni, E., Collini, F., Cattaneo, C. (2017) The issue of age estimation in a modern skeletal population: Are even the more modern current aging methods satisfactory for the elderly? Journal of Forensic Sciences 62(1):12-17.

301

Carroll, J.E., Gruenwald, T.L., Taylor, S.E., Janicki-Deverts, D., Matthews, K.A., Seeman, T.E.

(2013) Childhood abuse, parental warmth, and adult multisystem biological risk in the coronary artery risk development in young adults study. Proceedings of the National Academy of Sciences

110:17149-17153.

Chandra, R.K. (1991) Interactions between early nutrition and the immune system. In: Bock,

G.R., ed. The childhood environment and adult disease. Ciba Foundation Symposium 156.

Chichester. John Wiley, Sons. Ltd: 77-89.

Chen, E., Turiano, N.A., Mroczek, D.K., Miller, G.E. (2016) Association of reports of childhood abuse and all-cause mortality rates in women. JAMA Psychiatry 73:920-927.

Clark, G.A., Hall, N.R., Armelagos, G.J., Borkan, G.A., Panjabi, M.M., Wetzel, F.T. (1986) Poor growth prior to early childhood: Decreased health and life-span in the adult. American Journal of

Physical Anthropology 70:145-160.

Clark, M.A., Simon, A., Hubbe, M. (2020) Aging methods and age-at-death distributions: Does transition analysis call for a re-examination of bioarchaeological data? International Journal of

Osteoarchaeology 30(2):206.

Clark, A.L., Tayles, N., Halcrow, S.E. (2014) Aspects of health in prehistoric mainland

Southeast Asia: Indicators of stress in response to the intensification of rice agriculture.

American Journal of Physical Anthropology 153(3):484-495.

302

Clarke, A. (2011) The Colonisation of Ulster and the Rebellion of 1641:1603-60. . In: Moody,

T.W., and Martin, F.X., eds. The Course of Irish History. New Edition. Cork: Mercier Press.

Clarke, L. (2002) Archaeological Consultancy Services Contract 2 Strat. Report Archaeological

Excavation at Johnstown 1 County Meath License Number 02E0462.

Clarkson, L., Crawford M. (2001) Feast and Famine: Food and Nutrition in Ireland 1500-1920.

Oxford University Press.

Clergyman of the Church of England (1778) An antidote to popery. London.

Cobbett, W. (1829) A History of the Protestant Reformation in England and Ireland: Showing how that Event has Impoverished the Main Body of the People in those Countries. New York:

Published by P.J. Kenedy, Publisher to the Holy Apostolic See, Excelsior Catholic Publishing

House, 1902. Available from University of Minnesota. Web. 9 October 2018.

Cochrane, F. (2013) Northern Ireland: The Reluctant Peace. Yale University Press.

Cody, L.F. (2004) Living and dying in Georgian lying-in hospitals. Bulletin of the History of

Medicine 78(2):309-348.

303

Cole, S.M., Tembo, G. (2011) The effect of food insecurity on mental health: Panel evidence from rural Zambia. Social Science Medicine 73:1071-1079.

Collins, N. (2010) Dublin County Council. Dublin City Archaeological Archive. DCAA.01.15.

Collins, J.W. Jr., David R.J., Handler, A., Wall, S.N., Andes, S., Sassoon, B. (2003) Very low birth weight in African American infants: The effect of maternal lifetime exposure to interpersonal racial discrimination. American Journal of Epidemiology 157(11):S103(1).

Cohen, M.N. (1994) The osteological paradox reconsidered. Current Anthropology 35(5):629-

631.

Cook, D.C., Buikstra, J.E. (1979) Health and differential survival in prehistoric populations:

Prenatal dental defects. American Journal of Physical Anthropology 51:649-664.

Cooper, R.S., Kennelly, J.F., Durazo-Arvizu, R., Oh, H.J., Kaplan, G., Lynch, J. (2001)

Relationship between premature mortality and socioeconomic factors in black and white populations of US metropolitan areas. Public Health Report 116:464-473.

Cottrell, E.C., Seckl, J.R. (2009) Prenatal stress, glucocorticoids and the programming of adult disease. Frontiers in Behavioral Neuroscience 3:19.

304

Couoh, L.R. (2017) Differences between biological and chronological age-at-death in human skeletal remains: A change in perspective. American Journal of Physical Anthropology

163(4):671-695.

Cox, C. (2017) Health and welfare. In: Biagini, E.F., Daly, M.E., eds. The Cambridge Social

History of Modern Ireland. Cambridge: Cambridge University Press. 261-281.

Crawford, E.M. (1984) Dearth, diet, and disease in Ireland, 1850: A case study of nutritional deficiency. Medical History 28:151-161.

Crews, D.E. (2007) Composite estimates of physiological stress, age, and diabetes in American

Samoans. American Journal of Physical Anthropology 133:1028-1034.

Crimmins, E.M., Johnston, M., Hayward, M., Seeman, T. (2003) Age differences in allostatic load: An index of physiological dysregulation. Experimental Gerontology 38:731.

Crimmins, E.M., Kim, J.K., Alley, D.E., Karlamangla, A., Seeman, T. (2007) Hispanic paradox in biological risk profiles. American Journal of Public Health 97:1305-1310.

Crimmins, E.M., Kim, J.K., Seeman, T.E. (2009) Poverty and biological risk: The earlier “aging” of the poor. Journals of Gerontology Series A: Biological and Medical Sciences 64:286-292.

Cross, W.E., Jr. (2005) Ethnicity, Race, and Identity. Chicago: IL: University of Chicago Press.

305

Crowe, C. (2012) Ruin of Public Record Office marked loss of great archive. The Irish Times. 30

June 2012.

Cunha, E., Baccino, E., Martille, L., Ramsthaler, F., Prieto, J., Schuliar, Y., Lynnerup, N.,

Cattaneo, C. (2009) The problem of aging human remains and living individuals: A review.

Forensic Science International 193(1):1-13.

Curran, D., Fröling, M. (2010) Large-scale mortality shocks and the Great Irish Famine 1845-

1852. Economic Modelling, 27:1302-1314.

Curtin, N.J. (1996) “Varieties of Irishness:” Historical revisionism, Irish style. Journal of British

Studies 35:195-219.

Cusack, T. (2001) A ‘countryside bright with cosy homesteads’: Irish nationalism and the cottage landscape. Journal of National Identities 3(3):221-238.

D’Alton, J. (1838) The History of the County of Dublin. Hodges and Smith, College Green.

Daly, M.E. (2017) Famines and famine relief, 1740-2000. In: Biagini, E.F., Daly, M.E., eds. The

Cambridge Social History of Modern Ireland. Cambridge: Cambridge University Press. 38-52.

306

Danese, A., McEwen, B.S. (2012) Adverse childhood experiences, allostasis, allostatic load, and age-related disease. Psychology and Behavior 106:29-39.

Danese, A., Moffitt, T.E., Harrington, H., Milne, B.J., Polanczyk, G., Pariante, C.M., Poulton,

R., Caspi, A. (2009) Adverse childhood experiences and adult risk factors for age-related disease: Depression, inflammation, and clustering of metabolic risk markers. Archives of

Pediatric Adolescent Medicine 163:1135-1143.

Danese, A., Pariante, C.M., Taylor, A., Poulton, R. (2007) Childhood maltreatment predicts adult inflammation in a life-course study. Proceedings of the National Academy of Science 104:1319-

1324.

Danforth, M.E., Cook, D.C. (1994) The human remains from the Carter Ranch Pueblo, Arizona:

Health in isolation. American Antiquity 59(1):88-101.

de Beaumont, G. (1839) Ireland: Social, Political, and Religious. London: R. Bentley.

De Brouwere, V. (2007) The comparative study of maternal mortality over time: The role of the professionalization of childbirth. Social History of Medicine 20(3):541-562.

DeLacy, M. (1989) Puerperal fever in eighteenth century Britain. Bulletin of the History of

Medicine 63:521-556.

307

De Leon, V.B. (2007) Fluctuating asymmetry and stress in a medieval Nubian population.

American Journal of Physical Anthropology 132:520-534.

De Jong, H. (2016) Impact of the potato on society. American Journal of Potato Research

93:415-429.

DeWitte, S.N. (2010) Sex differentials in frailty in medieval England. American Journal of

Physical Anthropology 143:285-297.

DeWitte, S.N. (2014a) Mortality risk and survival in the aftermath of the medieval Black Death.

PLOS One 9(5):e96513.

DeWitte, S.N. (2014b) Differential survival among individuals with active and healed periosteal new bone formation. International Journal of Paleopathology 7:38-44.

DeWitte, S.N. (2015) The osteological paradox 20 years later: Past perspectives, future directions. Journal of Archaeological Research 23:397-450.

Dobbs, A. (1727) An Essay on the Trade and Improvement of Ireland. Printed by A. Rhames for

J. Smith and W. Bruce. Dublin.

308

Dole, N., Savitz, D.A., Siega-Riz, A.M., Hertiz-Picciotto, I., McMahon, M.J., Buekens, P. (2004)

Psychosocial factors and preterm birth among African American and white women in central

North Carolina. American Journal of Public Health 94:1358-1365.

Dong, M., Giles, W.H., Felitti, V.J., Dube, S.R., Williams, J.E., Chapman, D.P., Anda, R.F.

(2004) Insights into causal pathways for ischemic heart disease: Adverse childhood experiences study. Circulation 110:1761-1766.

Dooley, T. (2017) The Big House. In: Biagini, E.F., Daly, M.E., eds. The Cambridge Social

History of Modern Ireland. Cambridge: Cambridge University Press. 161-176.

Doyle, I. (2000) Interim Report on Excavations at Davis Place, Dublin 8. Margaret Gowen &

Co., Ltd.

Dublin City Council (2013) Aungier Street: Revitalising an historic neighbourhood. Dublin.

Duray, S.M. (1996) Dental indicators of stress and reduced age at death in prehistoric Native

Americans. American Journal of Physical Anthropology 99:275-286.

Dutz, W., Rossipal, E., Ghavami, H., Vessal, K., Kohout, E., Post, C. (1976) Persistent cell mediated immune-deficiency following infantile stress during the first 6 months of life.

European Journal of Pediatrics 122:117-126.

309

Eccles, A. (1977) Obstetrics in the seventeenth and eighteenth centuries and its implication for maternal and infant mortality. Bulletin of the History of Medicine 20:8-11.

Eckenhoff, M.F., Rakic, P. (1991) A quantitative analysis of synaptogenesis in the molecular layer of the dentate gyrus in the rhesus monkey. Developmental Brain Research 64:129-135.

Edwards, R.D., Williams, T.D. (1957) The Great Famine. New York: New York University

Press.

Edes, A.N., Crews, D.E. (2017) Allostatic load and biological anthropology. American Journal of Physical Anthropology. DOI 10.1002/ajpa23146.

Ekamper, P., van Poppel, F.W.A., Stein, A.D., Bijwaard, G.E., Lumey, L.H. (2015) Prenatal famine exposure and adult mortality from cancer, cardiovascular disease, and other causes through age 63 years. American Journal of Epidemiology 181(4):271-279.

Elias, E.L. (1914) In Stewart Times. New York: Thomas Y. Crowell Company Publishers.

Engler, S., Lutherbacher, J., Mauelshagen, F., Werner, J. (2014) The Irish Famine of 1740-1741:

Causes and effects. Climate of the Past Discussions 9:1013-1052.

310

Evans, G.W., Exner-Cortens, D., Kim, P., Bartholomew, D. (2013) Childhood poverty and blood pressure reactivity to and recovery from an acute stressor in late adolescence: The mediating role of family conflict. Psychosomatic Medicine 75:691-700.

Excavations.ie: Database of Irish Excavation Reports. An Roinn Cultúir, Oidhreachta agus

Gaeltachta/Department of Culture, Heritage, and the Gaeltacht. https://excavations.ie/. Accessed

2018-2019.

Exshaw, E. (1742). The London Magazine and Monthly Chronologer, 1742. Dublin: 104.

Fabricus, K., Wörtwein, G., Pakkenberg, B. (2008) The impact of maternal separation on adult mouse behavior and on the total neuron number in the mouse hippocampus. Brain Structure and

Function 212;403-416.

Fagan, P. (1991) The population of Dublin in the eighteenth century with particular reference to the proportions of Protestants and Catholics. Eighteenth-Century Ireland/Iris an dá chultúr 6:121-

156.

Fall, C.H.D. (2011) Evidence for the intra-uterine programming of adiposity in later life. Annals of Human Biology 38(4):410-428.

311

Faulkner, G. (1731) Reflections upon the present unhappy circumstances of Ireland in a letter to

His Grace the Lord Arch Bishop of Cashel with a proposal for Publick Granaries, as the principal means whereby to retrieve our affairs. Dublin. Essex Street.

Faulkner, G. (1741) The Groans of Ireland: In a Letter to a Member of Parliament. Dublin.

Felitti, V.J., Anda, R.F., Nordenberg, D., Williamson, D.F., Spitz, A.M., Edwards, V., Koss,

M.P., Marks, J.S. (1998) Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: The adverse childhood experiences (ACE) study. American

Journal of Preventative Medicine 14:245-258.

Fibiger, L. (2004) Minor aliments, furious fights, and deadly diseases: Investigating life in

Johnstown, County Meath, AD 400-1700. Recent Archaeological Discoveries on National Road

Schemes. Accessed 12 Dec 19 from https://pdfs.semanticscholar.org/dfda/31bf025f740f6ea7cbb07362bec191c1114b.pdf

Filipović, D., Gavrilović, Dronjak, S., Radojcić, M.B. (2005) Brain glucocorticoid receptor and heat shock protein 70 levels in rats exposed to acute, chronic, or combined stress.

Neuropsychobiology 51:107-114.

Foy, M.T., Barton, B. (2011) The Easter Rising. The History Press: Stroud, Gloucestershire.

312

Frankuma, E. (2010) The colonial roots of land inequality: Geography, factor endowments, or institutions? The Economic History Review 63(2):418-451.

Frawley, O. (2014) Memory Ireland: The Famine and the Troubles. Volume. 3. Syrcuse:

Syracuse University Press.

Frazer, William. Newmarket and Weaver’s Square, An Margadh Nua agus Cearnóg na bhFíodóirí. Dublin City Planning. n.d. http://www.dublincity.ie/sites/default/files/content/Planning/HeritageConservation/Documents/N ewmarketFinal.pdf

Freeman Anderson, K. (2012) Diagnosing discrimination: Stress from perceived racism and the mental and physical health effects. Sociological Inquiry 83(1):55-81.

Frisancho, A.R., Baker, P.T. (1970) Altitude and growth: A study of the patterns of physical growth of a high altitude Peruvian Quechua population. American Journal of Physical

Anthropology 32(2):279-292.

Gamble, J.A., Boldsen, J.L., Hoppa, R.D. (2017) Stressing out in medieval Denmark: An investigation of dental enamel defects and age at death in two medieval Danish cemeteries.

International Journal of Paleopathology 17:52-66.

313

Garcia, S. (2007) Maleitas do corpo em tempos medievais: Indicadores paleodemográficos, de stresse e paleopatológicos numa série osteológica urbana de Leiria, PhD in Biological

Anthropology. Coimbra: Departmento de Antropologia, Universidade de Coimbra.

Gawlikowska-Sroka, A., Dabrowski, P., Szczurowski, J., Dzieciolowska-Baran, Staniowski, T.

(2017) Influence of physiological stress on the presence of hypoplasia and fluctuating asymmetry in a medieval population from the village of Sypniewo. International Journal of Paleopathology

19:43-52.

Geber, J. (2014) Skeletal manifestations of stress in child victims of the Great Irish Famine

(1845-1852): Prevalence of enamel hypoplasia, Harris lines, and growth retardation. American

Journal of Physical Anthropology 155(1):149-161.

Geber, J. (2015) Victims of Ireland’s Great Famine. Gainesville: University Press of Florida.

Gee, G.C., Ro, A., Gavin, A., Takeuchi, D.T. (2008) Disentangling the effects of racial and weight discrimination on body mass index and obesity among Asian Americans. American

Journal of Public Health 98:493-500.

George, E.D., Bordner, K.A., Elwafi, H.M., Simen, A.A. (2010) Maternal separation with early weaning: A novel mouse model of early life neglect. BMC Neuroscience 11(23).

314

Geronimus, A.T. (2001) Understanding and eliminating racial inequalities in women’s health in the United States: The role of the weathering conceptual framework. Journal of American

Medical Women’s Association 56:133-136, 149-150.

Geronimus, A.T., Hicken, M.T., Pearson, J.A., Seashols, S.J., Brown, K.J., Cruz, T.D. (2010) Do

US black women experience stress-related accelerated biological aging? Human Nature

21(1):19-38.

Gillman, M.W. (2005) Developmental origins of health and disease. New England Journal of

Medicine 353(17):1848-1850.

Gillman, M. (2007). Meeting report on the 3rd International Congress on Developmental Origins of Health and Disease (DOHaD). Pediatric Research 61(5 Pt 1):625-629.

Godde, K., Hens, S.M. (2012) Age-at-death estimation in an Italian historical sample: A test of the Suchey-Brooks and transition analysis methods. American Journal of Physical Anthropology

149(2):259-265.

Gold, L.I. (1999) The role for transforming growth factor-beta (TGF-beta) in human cancer.

Critical Reviews in Oncology 10(4):303-360.

315

Gompertz, B. (1825) On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies. Philosophical Transactions of the

Royal Society of London B: Biological Sciences 182:513-85.

Goodman, A.H. (1989) Dental enamel hypoplasias in prehistoric populations. Advances in

Dental Research 3(2):265-71.

Goodman, A.H., Armelagos, G.J. (1988) Childhood stress and decreased longevity in a prehistoric population. American Anthropologist 90(4):936-944.

Goodman, A.H., Brooke Thomas, R., Swedlund, A.C., Armelagos, G.J. (1988) Biocultural perspectives on stress in prehistoric, historical, and contemporary population research. Yearbook of Physical Anthropology 31:169-202.

Goodman, A.H., Leatherman, T.L., eds. (1998) Building a New Biocultural Synthesis: Political-

Economic Perspectives on Human Biology. Ann Arbor: University of Michigan Press.

Goodman, A.H., Rose, J.C. (1990) Assessment of systemic physiological perturbations from dental enamel hypoplasias and associated histological structures. American Journal of Physical

Anthropology 33:59-110.

Goodwin, R.D., Stein, M.B. (2004) Association between childhood trauma and physical disorders among adults in the United States. Psychological Medicine 34(4):509-520.

316

Gough, M., Godde, K. (2019) Accelerated aging: The role of socioeconomic, social, demographic, and biological factors on bone mineral density. Research on Aging 41(5):443-466.

Gowland, R.L. (2015) Entangled lives: Implications of the developmental origins of health and disease hypothesis for bioarchaeology and the life course: American Journal of Physical

Anthropology 158:530-540.

Grady, S.C. (2006) Racial disparities in low birthweight and the contribution of residential segregation: A multilevel analysis. Social Science Medicine 63(12):3013-29.

Graham, B. (1979) The evolution of urbanization in medieval Ireland. Journal of Historical

Geography 5(2):111-126.

Gray, C.D., Kinnear, P.R. (2012) IBM SPSS 19 Statistics Made Simple. New York: Psychology

Press.

Great Britain Customs Establishment (1785a). An account of the exports from Ireland to Africa and America, for five years ending the 25th Marth 1784: Distinguishing the quantities, and rates of values, with the rates of duties in the last year. The Making of the Modern World. Web. 4

December 2017.

317

Greenwood, M. (1926) The natural duration of cancer. Reports on Public Health and Medical

Subjects. London: Her Majesty’s Stationary Office 33:1-26.

Greksa, L.P., Spielvogel, H., Paredes-Fernandez, L., Paz-Zamora, M., Caceres, E. (1984) The growth of urban children at high altitude. American Journal of Physical Anthropology 65(3):315-

322.

Grunewald, T.L., Seemand, T.E., Ryff, C.D., Karlamangla, A.S., Singer, B.H. (2006)

Combinations of biomarkers predictive of later life mortality. Proceedings of the National

Academy of Science 103:14158.

Guatelli-Steinberg, 2000. Linear enamel hypoplasia in gibbons (Hylobates lar carpenteri).

American Journal of Physical Anthropology 11(3):395-410.

Guatelli-Steinberg, D. (2004) Analysis and significance of linear enamel hypoplasia in Plio-

Pleistocene hominins. American Journal of Physical Anthropology 123(3):199-215.

Guatelli-Steinberg, D. (2008) Using perikymata to estimate the duration of growth disruptions in fossil hominin teeth. Dental anthropology: Applications and methods. In: Irish, J., Nelson, G., eds. Cambridge: Cambridge University Press 71-86.

318

Guatelli-Steinberg, D., Benderlioglu, Z. (2006) Brief communication: Linear enamel hypoplasia and the shift from irregular to regular provisioning in Cayo Santiago rhesus monkeys (Macaca mulatta). American Journal of Physical Anthropology 131(3):416-419.

Guatelli-Steinberg, D., Ferrell, R.J., Spence, J. (2012) Linear enamel hypoplasia as an indicator of physiological stress in great apes: Reviewing evidence in light of enamel growth variation.

American Journal of Physical Anthropology 148(2):191-204.

Guatelli-Steinberg, D., Lukacs, J.R. (1999) Interpreting sex differences in enamel hypoplasia in human and non-human primates: Developmental, environmental, and cultural considerations.

Yearbook of Physical Anthropology 42:73-126.

Hadley, C., Patil, C.L. (2006) Food insecurity in rural Tanzania is associated with maternal anxiety and depression. American Journal of Human Biology 18:359-368.

Hadley, C., Tegegn, A., Tessema, F., Cowans, J.A., Asefa, M., Galea, S. (2008) Food insecurity, stressful life events, and symptoms of depression in east Africa: Evidence from the Gilgel Gibe growth and development study. Journal of Epidemiological Communication Health 62:980-986.

Halpin, A., Buckley, L. (1995) Archaeological excavations at the Dominican Priory, Drogheda,

Co. Louth. Proceedings of the Royal Irish Academy. Section C: Archaeology, Celtic Studies,

History, Linguistics, Literature 95C(5):175-253.

319

Halpin, E. (1996) Excavations at St. Mary d’Urso, Drogheda, County Louth. Journal of the

County Louth Archaeological and Historical Society 23(4):452-509.

Hales, C.N., Barker, D.J.P. (1992) Type 2 (non-insulin-dependent) diabetes mellitus: The thrifty phenotype hypothesis. Diabetologia 35:595-601.

Hallén, A. (2009) Makeham’s addition to the Gompertz law re-evaluated. Biogerontology

10(4):517-522.

Hallett, C. (2005) The attempt to understand puerperal fever in the eighteenth and early nineteenth centuries. The influence of inflammation theory. Medical History 49(1):1-28.

Harris, A., Seckl, J. (2011) Glucocorticoids, prenatal stress and the programming of disease.

Hormones and Behavior 59:279-289.

Hartland, B. (2018) In: Smith, B., ed. The Cambridge History of Ireland. Cambridge University

Press. 600-1550. Web 8 October 2018.

Hasson, D., von Thiele Schwarcz, U., Lindfors, P. (2009) Self-rated health and allostatic load in women working in two occupational stressors. Journal of Health and Psychology 14:568.

Hawkes, J.G., Francisco-Ortega, J. (1993) The early history of the potato in Europe. Euphytica

70:1-7.

320

Hayden, A.R. (2011) Trim Castle, Co. Meath: Excavations 1995-8. Archaeological Monograph

Series 6. Government of Ireland. Dublin.

Hays-McCoy, G.A. (2011) The Tudor Conquest: 1534-1603. In: Moody, T.W., and Martin, F.X., eds. The Course of Irish History. New Edition. Cork: Mercier Press.

Heim, C., Binder, E.B. (2012) Current research trends in early life stress and depression: Review of human studies on sensitive periods, gene-environment interactions, and epigenetics.

Experimental Neurology 233:102-111.

Heim, C.M., Newport, D.J., Heit, S., Graham, Y.P., Wilcox, M., Bonsall, R., Miller, A.H.,

Nemeroff, C.B. (2000) Pituitary-adrenal and automatic responses to stress in women after sexual and physical abuse in childhood. Journal of the American Medical Association 284:592-597.

Hellhammer, J., Scholtz, W., Stone, A.A., Pirke, K.M., Hellhammer, D. (2004) Allostatic load, perceived stress, and health: A prospective study in two age groups. Annals of the New York

Academy of Science 1032:8.

Hellier, C., Connolly, R. (2009) Cause of death in judicial hanging. A review and case study.

Medicine, Science, and the Law 49(1):18-26.

321

Hens, S.M., Rastelli, E., Belcastro, G. (2008) Age estimation from the human os coxa: A test on a documented Italian collection. Journal of Forensic Sciences 53(5):1040-1043.

Hill, J. (1984) National festivals, the state, and ‘Protestant Ascendancy’ in Ireland, 1790-1829.

Irish Historical Studies 24(93):30-51.

Hillson, S. Dental Anthropology. Cambridge: Cambridge University Press.

Hillson, S., Bond, S. (1997) Relationship of enamel hypoplasia to the pattern of tooth crown growth: A discussion. American Journal of Physical Anthropology 104:89-103.

Ho, D.H., Burch, M.L., Musall, B., Musall, J.B., Hyndman, K.A., Pollock, J.S. (2016) Early life stress in male mice induces superoxide production and endothelial dysfunction in adulthood.

American Journal of Physiology Heart and Circulation 310:H1267-74.

Hodges, D.C. (1987) Health and agricultural intensification in the prehistoric valley of Oaxaca,

Mexico. American Journal of Physical Anthropology 73(3):323-332.

Holmes, A.R., Biagini, E.F. (2017) Protestants. In: Biagini, E.F., Daley, M.E., eds. The

Cambridge Social History of Ireland. Cambridge: Cambridge University Press. 88-111.

322

Hoover, K.C., Matsumura, H. Temporal variation and interaction between nutritional and developmental instability in prehistoric Japanese populations. American Journal of Physical

Anthropology 137(4):469-478.

Huang, C., Li, Z., Wang, M., Martorell, R. (2010) Early life exposure to the 1959-1961 Chinese famine has long-term health consequences. The Journal of Nutrition 140(10):1874-1878.

Hubbard, A., Guatelli-Steinberg, D., Sciulli, P.W. (2009) Under restrictive conditions, can the widths of linear enamel hypoplasias be used as relative indicators of stress episode duration?

American Journal of Physical Anthropology 138:177-189.

Hughes, D., Rodriguez, J., Smith, E.P., Johnson, D.J., Stevenson, H.C., Spicer, P. (2006)

Parents’ ethnic-racial socialization practices: A review of research and directions for future study. Developmental Psychology 42(5):747-770.

Humphrey, L.T., King, T. (2000) Childhood stress: A lifetime legacy. Anthropologie

XXXVVV/1:33-49.

Hussey, A., O’Conner, W. (1641) A discovery to the prayse of God, and joy of all true hearted

Protestants, of a late intended plot by the papists to subdue the Protestants. London.

Hutchinson, D.L., Larsen, C.S. (1988) Determination of stress episode duration from linear enamel hypoplasias: A case from St. Catherines Island, Georgia. Human Biology 60:93-110.

323

Igoe, V. (2001) Dublin Burial Grounds & Graveyards. Wolfhound Press, Ltd. Dublin.

Igosheva, N., Klimova, O., Anishchenko, T., Glover, V. (2004) Prenatal stress alters cardiovascular responses in adult rats. Journal of Physiology 557:273-285.

Ireland Parliament House of Commons. Report from the committee appointed to inquire into the effects which the several premiums paid for flax-seed, imported and exported; the inland carriage coastways of corn, meal, and flour to Dubli. Reported by Mr. Forster Sabatti 12 die martii, 1774,

Dublin, 1774. Slavery and Anti-Slavery. Gale. Ohio State University Libraries 12 December

2017.

Ireland Parliament House of Lords. A report from the Lords committees appointed to enquire into the state of tillage in this kingdom; and to consider some methods of improving the same, and of better supplying the city of Dublin with wheat: Made by the Earl of Clanbrassil, and agreed to by the House on Friday the 16th day of December, 1757.

Isçan, Y.M., Loth, S.R. (1986a) Determination of age from the sternal rib in white females- A test of the phase method. Journal of Forensic Science 31(1):990-999.

Isçan, Y.M., Loth, S.R. (1986b) Determination of age from the sternal rib in white males- A test of the phase method. Journal of Forensic Science 31(1):122-132.

324

J.R. and W.A. (1679) A brief account of the several plots, conspiracies, and Hellish attempts of the bloody-minded papists, against the princes and kingdoms of England, Scotland, and Ireland, from the Reformation to this present year, 1678. As also their cruel practices in France against the Protestants in the massacre of Paris & C. with a more particular account of their plots in relation to the late Civil War, and their contrivances of the Death of King Charles the First, of blessed memory. London, printed for J.R. and W.A. Web 9 October 2018.

Jackson, T.A. (1970) Ireland Her Own: An Outline History of the Irish Struggle for National

Freedom and Independence. New York, NY: International Publishers.

Johansson, G., Huang, Q., Lindofrs, P. (2007) A life-span perspective on women’s careers, health, and well-being. Social Science Medicine 65:685.

Johnson, M. (2006) On the nature of theoretical archaeology and archaeological theory.

Archaeological Dialogues 13(2):117-132.

Jordan, T.E. (2013) Housing as quality of life: Dublin, 1798-1821. In: Jordan, T.E. Studies in the

Quality of Life in Victorian Britain and Ireland. Springer Science & Business Media.

Jordan, T.E. (2014) Dublin’s seventeeth century parishes and the quality of life. Social Indices

Research 118:819-833.

325

Joyce, D.A., Steer, J.H., Abraham, L.J. (1997) Glucocorticoid modulation of human monocyte/macrophage function: Control of TNF-alpha secretion. Inflammatory Research

46(11):447-51.

Juster, R.P., McEwen, B.S., Lupien, S.J. (2010) Allostatic load biomarkers of chronic stress and impact on health and cognition. Neuroscience and Biobehavioral Reviews 35(1):2-16.

Kaestner, R., Pearson, J.A., Keene, D., Geronimus, A.T. (2009) Stress, allostatic load, and health of Mexican immigrants. Social Science Quarterly 90(5):1089-1111.

Kaplan, E.L., Meier, P. (1958) Nonparametric estimation from incomplete observations. Journal of the American Statistical Association 53(282):457-481.

Karlamangla, A.S., Singer, B.H., McEwen, B.S., Rowe, J.W., Seeman, T.E., (2002) Allostatic load as a predictor of functional decline: MacArthur studies of successful aging. Journal of

Clinical Epidemiology 55:696.

Karlamangla, A.S., Singer, B.H., Seeman, T.E. (2006) Reduction in allostatic load in older adults is associated with lower all-cause mortality risk: MacArthur studies of successful aging.

Psychosomatic Medicine 68:500.

326

Kealohi Sato Conching, A., Thayer, Z. (2019) Biological pathways for historical trauma to affect health: A conceptual model focusing on epigenetic modifications. Social Science & Medicine

230:74-82.

Keeley, V.J., Opie, H. (2002) Interim Report Archaeological Excavation L18 Re-Alignment

Ardreigh, Co. Kildare Medieval Cemetery and Settlement. Valerie J. Keeley Ltd.,

Archaeological Consultancy.

Keeley, V.J., Seaver, M. (2000) Archaeological Investigations Ardree, Co. Kildare. Valerie J.

Keeley Ltd., Archaeological Consultancy.

Kelly, J. (2011) The Historiography of the Penal Laws. In: Bergin, J., Magennis, E., Ní

Mhunghaile, L., Walsh, P., eds. New Perspectives on the Penal Laws. Dublin. Eighteenth

Century Ireland Society.

Kelly-Irving, M., Lepage, B., Dediu, D., Bartley, M., Blane, D., Grosclaude, P., Delpierre, C.

(2013) Adverse childhood experiences and premature all-cause mortality. European Journal of

Epidemiology 28:721-734.

Kember, R.L., Dempster, E.L., Lee, T.H., Schalkwyk, L.C., Mill, J., Fernandes, C. (2012)

Maternal separation is associated with strain-specific responses to stress and epigenetic alterations to Nr3c1, Avp, and Nr4a1 in mouse. Brain Behavior 2:455-467.

327

Kemkes-Grottenthaler, A. (2005) The short die young: The interrelationship between stature and longevity- Evidence from skeletal remains. American Journal of Physical Anthropology

128:340-347.

Kenny, C., Burke-Kennedy, E. (2018) ‘Brain drain’ reversed as Ireland sees highest immigration since 2008. The Irish Times. Wednesday 29 August 2018.

King, T., Humphrey, L.T., Hilson, S. (2005) Linear enamel hypoplasias as indicators of systematic physiological stress: Evidence from two known age-at-death and sex populations from postmedieval London. American Journal of Physical Anthropology 128:547-559.

Klengel, T., Binder, E.B. (2013) Allele-specific epigenetic modification: A molecular mechanism for gene-environment interactions in stress-related psychiatric disorders?

Epigenomics 5(2):109-112.

Krenz-Niedbała, M., Łukasik, S. (2017) Skeletal evidence for otitis media in mediaeval and post- mediaeval children from Poland, Central Europe. International Journal of Osteoarchaeology

27(3):375-386.

Krukowski, K., Eddy, J., Loster Kosik, K., Konley, T., Witek Janusek, L., Mathews, H.L. (2011)

Glucocorticoid dysregulation of natural killer cell function through epigenetic modification.

Brain, Behavior, and Immunity 25:239-249.

328

Kubzansky, L.D., Kawachi, I., Sparrow, D. (1999) Socioeconomic status, hostility, and risk factor clustering in the Normative Aging Study: Any help from the concept of allostatic load?

Annals of Behavioral Medicine 212:330.

Kumar Goel, M., Khanna, P., Kishore J. (2010) Understanding survival analysis: Kaplan-Meier estimate. International Journal of Ayurveda Research 1(4):276-278.

Kuzawa, C.W., Sweet, E. (2009) Epigenetics and the embodiment of race: Developmental origins of US racial disparities in cardiovascular health. American Journal of Human Biology

21:2-15.

Kyle, B., Reitsema, L.J., Tyler, J., Fabbri, P.F., Vassallo, S. (2018) Examining the osteological paradox: Skeletal stress in mass graves versus civilians at the Greek colony of Himera (Sicily)

American Journal of Physical Anthropology 167(1):161-172.

Lamont, D., Parker, L., White, M., Unwin, N., Bennett, S.M., Cohen, M., Richardson, D.,

Dickinson, H.O., Adamson, A., Alberti, K.G., Craft, A.W. (2000) Risk of cardiovascular disease measured by carotid intima-media thickness at age 49-51: Lifecourse study. British Medical

Journal 320(7230)273-278.

Langford, K., Blum, W., Nicolaides, K., Jones, J., McGregor, A., Miell, J. (1994) The pathophysiology of the insulin-like growth factor axis in fetal growth failure: A basis for programming by undernutrition? European Journal of Clinical Investigation 24(12):851-856.

329

Lanphear, K.M. (1990) Frequency and distribution of enamel hypoplasias in a historic skeletal sample. American Journal of Physical Anthropology 81(1):35-43.

Larsen, C.S. (2018) Bioarchaeology in perspective: From classifications of the dead to the conditions of the living. American Journal of Physical Anthropology 165:865-878.

Lauderdale, D.S. (2006) Birth outcomes for Arabic-named women in California before and after

September 11. Demography 43(1):185-201.

Lee, M.J. (2019) The Warped One: Nationalist adaptations of the Cuchulain myth. PhD dissertation. University of South Carolina.

Leffman, T., Combs-Orme, T. (2014) Prenatal stress, poverty, and child outcomes. Child and

Adolescent Social Work Journal 31:577-590.

Lehman, B.J., Taylor, S.E., Kiefe, C.I., Seeman, T.E. (2009) Relationship of early life stress and psychological functioning to blood pressure in the CARDIA study. Health Psychology 28:338-

346.

Lennon, C. (2005) Sixteenth Century Ireland. Dublin: Gill & Macmillan Ltd.

330

Leonard, W.R. (1989) Nutritional determinants of high-altitude growth in Nuñoa, Peru.

American Journal of Physical Anthropology 80(3):341-352.

Leone, M.P., Potter, B., Shackel, P.A., Blakey, M.L., Bradley, R., Durrans, B., Gero, J.M.,

Grigoriev, G.P., Hodder, I., Lanata, J.L., Levy T.E., Silberman, N.A., Paynter, R., Rivera, M.A.,

Wylie, A. (1987) Towards a critical archaeology. Current Anthropology 28:283-302.

Lewis, M.E. (2002) Urbanisation and child health in medieval and post-medieval England. BAR

British Series 339. Oxford: Arcaeopress.

Lewis, M.E. (2007) The Bioarchaeology of Children: Perspectives from Biological and Forensic

Anthropology. Cambridge: Cambridge University Press.

Lewis, T.T., Everson-Rose, S.A., Powell, L.H., Matthews, K.A., Brown, C., Karavolos, K.,

Sutton-Tyrrell, K., Jacobs, E., Wesley, D.M. (2006) Chronic exposure to everyday discrimination and coronary artery calcification in African American women: The SWAN Heart

Study. Psychosomatic Medicine 68:362-368.

Li, C., Lumey, L.H. (2017) Exposure to the Chinese famine of 1959-61 in early life and long- term health conditions: A systematic review and meta-analysis. International Journal of

Epidemiology 46(4):1157-1170.

331

Li, W., Zhang, J.Q., Sun, J., Ke, J.H., Dong, Z.Y., Wang, S. (2007) Job stress related to glycol- lipid allostatic load, adiponectin, and visfatin. Stress Health 23:257.

Lindofrs, P., Lundberg, O., Lundberg, U. (2006) Allostatic load and clinical risk as related to sense of coherence in middle-aged women. Psychosomatic Medicine 68:801.

Livingstone, F.B. (1958) Anthropological implications of sickle cell gene distribution in West

Africa. American Anthropologist 60(3):533-562.

Logan, W.H.G., Kronfeld, R. (1933) Development of the human jaws and surrounding structures from birth to the age of fifteen years. Journal of the American Dental Association 20(3):379-427.

Loria, A.S., D’Angelo, G., Pollock, D.M., Pollock, J.S. (2010a) Early life stress downregulates endothelin receptor expression and enhances acute stress-mediated blood pressure responses in adult rats. American Journal of Physiology Regulatory, Integrative, and Comparative Physiology

229:R185-R191.

Loria, A.S., Pollock, D.M., Pollock, J.S. (2010b) Early life stress sensitizes rats to angiotensin II- induced hypertension and vascular inflammation in adults life. Hypertension 55:494-499.

Loria, A.S., Brands, M.W., Pollock, D.M., Pollock, J.S. (2013a) Early life stress sensitizes the renal and systemic sympathetic system in rats. American Journal of Physiology Renal

Physiology 305:F390-F395.

332

Loria, A.S., Yamamoto, T., Pollock, D.M., Pollock, J.S. (2013b) Early life stress induces renal dysfunction in adult male rats but not female rats. American Journal of Physiology Regulatory,

Integrative, and Comparative Physiology 304:R121-R129.

Loudon, J. (1986) Deaths in childbed from the eighteenth century to 1935. Medical History

30(1):1-41.

Lovejoy, O.C., Meindl, R.S., Pryzbeck, T.R., Mensforth, R.P. (1985) Chronological metamorphosis of the auricular surface of the ilium: A new method for the determination of adult skeletal age at death. American Journal of Physical Anthropology 68(1):15-28.

Luddy, M. (2017) Marriage, sexuality, and the law in Ireland. In: Biagini, E.F., Daly, M.E., eds.

The Cambridge Social History of Modern Ireland. Cambridge: Cambridge University Press. 344-

362.

Lumey, L.H., Martini, L.H., Myerson, M., Stein, A.D., Prineas, R.J. (2012) No relation between coronary artery disease or electrocardiographic markers of disease in middle age and prenatal exposure to the Dutch famine of 1944-5. Heart 98(22):1653.

Lupindu, A.M., Dalsgaard, A., Msoffe, P.L.M., Ngowi, H.A. (2015) Transmission of antibiotic- resistant Escherichia coli between cattle, humans and the environment in the peri-urban livestock keeping communities in Morogoro, Tanzania. Preventative Veterinary Medicine 118(4):477-482.

333

Lynch, P. (1995) The Irish Free State and the Republic of Ireland. In: Moody, T.W. & Martin,

F.X., eds. The Course of Irish History. Radio Telefís Éireann. Lanham, Maryland: Roberts

Rinehart Publishers.

Lyons, S. (2016) Food plants, fruits, and foreign foodstuffs: The archaeological evidence from urban medieval Ireland. In: FitzPatrick, E., Kelly, J., eds. Food and Drink in Ireland. Dublin:

Royal Irish Academy. 111-166.

Maaranen, N., Buckberry J. (2016) Detecting the elderly- exploring age using transition analysis.

Poster presented at: 22nd Annual Meeting of the European Association of Archaeologists.

Macauly, A. (2016) The Catholic Church and the Campaign for Emancipation in Ireland and

England. Dublin: Four Courts Press.

Mac Con Iomaire, M. (2009) The potato in Irish cuisine and culture. Journal of Culinary Science and Technology 7(2-3):152-167.

Mason, W.S. (1816) A Statistical Account of Parochial Survey of Ireland. Dublin: Hibernia Press

Office.

MacCotter, P. (2008) Medieval Ireland: Territorial, Political, and Economic Divisions. Four

Courts Press:Dublin, Ireland.

334

MacManus, S. (1921) The Story of the Irish Race. 4th ed. Greenwich, CT: Konecky & Konecky.

Maes, K.C., Hadley, C., Tesfaye, F., Shifferaw, S. (2010) Food insecurity and mental health:

Surprising trends among community health volunteers in Addis Ababa, Ethiopia during the 2008 food crisis. Social Science Medicine 70:1450-1457.

Maloney, E.M., Boneva, R., Nater, U.M., Reeves, W.C. (2009) Chronic fatigue syndrome and high allostatic load: Results from a population-based case-control study in Georgia.

Psychosomatic Medicine.

Maloney, E.M., Gurbaxani, B.M., Jones, J.F., de Souza Coelho, L., Pennachin, C., Goertzel,

B.N. (2006) Chronic fatigue syndrome and high allostatic load. Pharmacogenomics 7:467.

Malville, N.J. (1997) Enamel hypoplasia in ancestral Puebloan populations from Southwestern

Colorado: I permanent dentition. American Journal of Physical Anthropology 102(3):351-367.

Maple, J.T. (1989) Anglo-Norman conquest of Ireland and the Irish economy: Stagnation or stimulation? The Historian 52(1):61-81.

Manolagas, S.C., O’Brien, C.A., Almeida, M. (2013) The role of estrogen and androgen receptors in bone health and disease. Nature Reviews Endocrinology 9(12):699-712.

335

Marklein, K.E., Crews, D.E. (2017) Frail or hale: Skeletal frailty indices in medieval London skeletons. American Journal of Physical Anthropology 12(5):e0176025.

Marklein, K.E., Leahy, R.E., Crews, D.E. (2016) In sickness and in death: Assessing frailty in human skeletal remains. American Journal of Physical Anthropology 161(2):208-225.

Marques, A.H., Silverman, M.N., Stenberg, E.M. (2010) Glucocorticoid dysregulations and their clinical correlates. Annals of the New York Academy of Science 1179:1-18.

Martyn, C.N., Barker, D.J.P., Jespersen, S., Greenwald, S., Osmond, C., Berry, C. (1995)

Growth in utero, adult blood pressure, and arterial compliance. British Heart Journal 73:116-121.

Mason, W.S. (1816) A Statistical Account or Parochial Survey of Ireland. Dublin: Hibernia Press

Office.

May, R.L., Goodman, A.H., Meindl, R.S. (1993) Response of bone and enamel formation to nutritional supplementation and morbidity among malnourished Guatemalan children. American

Journal of Physical Anthropology 92(1):37-51.

McBride, I. (2009) Eighteenth Century Ireland: The Isle of Slaves. Dublin: Gill and MacMillan,

Ltd.

336

McCartney, D. (1995) From Parnell to Pearse. In: Moody, T.W. & Martin, F.X., eds. The Course of Irish History. Radio Telefís Éireann. Lanham, Maryland: Roberts Rinehart Publishers.

McClatchie, M. (2014) The Plant Remains from Early Medieval Ireland. In: Early Medieval

Agriculture, Livestock, and Cereal Production in Ireland, AD 400-1100. BAR International

Series 247 Archaeopress. Oxford, England.

McClatchie, M., McCormick, F., Kerr, T.R., O’Sullivan (2015) Early medieval farming and food production: A review of the archaeobotanical evidence from archaeological excavations.

Vegetation History and Archaeobotany 24:179-186.

McClure, H.H., Snodgrass, J.J., Martinez, G.R., Jr., Eddy, J.M., Jimenez, R.A., Isioridia, L.E.

(2010) Discrimination, psychosocial stress, and health among Latin American immigrants in

Oregon. American Journal of Human Biology 22(3):421-423.

McCormick, F. (2014) Agriculture, settlement, and society in early medieval Ireland. Quaternary

International 346:119-130.

McCracken, J.L. (1995) Northern Ireland, 1921-66. In: Moody, T.W. & Martin, F.X., eds. The

Course of Irish History. Radio Telefís Éireann. Lanham, Maryland: Roberts Rinehart Publishers.

McCutcheon, C. (2001) A note on some pottery from Graney East, Castledermot, Co. Kildare.

Appendix III. In: Bryne, M.E., ed. Graney East, Castledermot, Co. Kildare Report on

337

Archaeological Monitoring and Testing. Byrne, Mullins, & Associates Archaeological

Consultants.

McDonnell, C. Irishmen in the British Service during the French Revolutionary Wars, 1793-

1802. 2013. National University of Ireland, Maynooth. PhD dissertation.

McGarry, F. (2011) The Rising. Oxford University Press.

McGregor, P. (1992) The labor market and the distribution of landholdings in pre-Famine

Ireland. Explorations in Economic History 29:477-493.

McVeigh, R., Rolston, B. (2007) From Good Friday to Good Relations: Sectarianism, Racism, and the Northern Irish State. Race and Class 48(4):1-23.

Meindl, R.S., Lovejoy, O.C. (1985) Ectocranial suture closure: A revised method for the determination of the skeletal age at death based on the lateral-anterior sutures. American Journal of Physical Anthropology 68(1):57-66.

Midei, A.J., Matthews, K.A., Chang, Y.F., Bromberger, J.T. (2013) Childhood physical abuse is associated with incident metabolic syndrome in mid-life women. Health Psychology 32(2):121-

127.

338

Milner, G.R., Boldsen, J.L. Transition analysis: A validation study with known-age modern

American skeletons. American Journal of Physical Anthropology 148:98-110.

Minozzi, S., Caldarini, C., Pantano, W., Giannantonio, S., Catalano, P., Giuffra, V. (2020)

Enamel hypoplasia and health conditions through social status in the Roman Imperial Age (First to third centuries, Rome, Italy). International Journal of Osteoarchaeology 30(1):53-64.

Miranda, J., Legha, R. (2019) The consequences of family separation at the border and beyond.

Journal of the American Academy of Child and Adolescent Psychiatry 58(1):139-140.

Miszkiewicz, J.J. (2015) Linear enamel hypoplasia and age-at-death at medieval (11th-16th centuries) St. Gregory’s Priory and Cemetery, Canterbury, UK. International Journal of

Osteoarchaeology 25:79-87.

Moffatt, P., Wazen, R.M., Dos Santos Neves, J., Nanci, A. (2014) Characterisation of secretory calcium-binding phosphoprotein-proline-glutamine-rich 1: A novel basal lamina component expressed at cell-tooth interfaces. Cell Tissue Research 358:843-855.

Moloney, C., Baker, L., Millar, J., Shiels, D. (n.d.) Guide to the Excavations at Ardreigh, County

Kildare. Rubicon Heritage Services Ltd.

Moody, T.W., Martin, F.X. (1995) The Course of Irish History. Lanham, Maryland: Roberts

Rhinehart Publishers.

339

Moore, S.E., Cole, T.J., Poskitt, E.M., Sonko, B.J., Whitehead, R.G., McGregor, I.A., Prentice,

A.M. (1997) Season of birth predicts mortality in rural Gambia. Nature 388:434.

Moran, P.F. (1899) The Catholics of Ireland Under the Penal Laws in the Eighteenth Century.

London: Catholic Truth Society.

Mossakowski, K.N. (2003) Coping with perceived discrimination: Does ethnic identity protect mental health? Journal of Helath and Social Behavior 44(3):318-331.

Mullins, C. (2001) A report on the human remains from Graney East, Castledermot, Co. Kildare.

Appendix II. In: Byrne, M., ed. Graney East, Castledermot, Co. Kildare Report on

Archaeological Monitoring and Testing. Byrne, Mullins & Associates Archaeological

Consultants.

Murray, K.A., Murray, T. (1991) A test of the auricular surface aging technique. Journal of

Forensic Sciences 36:1162-1169.

Mulock, T. (1812) Short Practical Considerations on Scarcity and on the Plans for Remedying

Deficient Subsistence in Great Britain and Ireland. Dublin.

Murphy, D. (1997) Archaeological excavations at the Magdalene Tower, Drogheda, County

Louth. Journal of the County Louth Archaeological and Historical Society 24(1):75-128.

340

Murphy, M. (2018) Chapter 14: The Economy. In: Smith, B., ed. The Cambridge History of

Ireland. Cambridge University Press. 385-414.

Murphy, M.O., Cohn, D.M., Loria, A.S. (2017) Developmental origins of cardiovascular disease:

Impact of early life stress in humans and rodents. Neuroscience and Biobehavioral Reviews

74:453-465.

Murray, J. (1827) The Real State of Ireland in 1827.

Mustello, S., Krieger, N., Gunderson, E.P., Signey, S., McCreath, H., Kiefe, C.I. (2004) Self- reported experiences of racial discrimination and black-white differences in preterm and low- birthweight deliveries: The CARDIA Study. American Journal of Public Health 94:2125-2131.

Nanci, A. (2008) Ten Cate’s Oral Histology: Development, Structure, and Function. St. Louis:

Mosby, Inc.

Nanci, A. (2013) Ten Cate’s Oral Histology. 8th ed. St. Louis: Elsevier Mosby.

Nelson, R.G. (2009) Adult health outcomes and their implications for experiences of childhood nutritional stress in Jamaica. American Journal of Human Biology 21(5):671-678.

341

Newman, S.L., Gowland, R.L. (2017) Dedicated followers of fashion? Bioarchaeological perspectives on socioeconomic status, inequality, and health in urban children from the Industrial

Revolution (18th-19thc.), England. International Journal of Osteoarchaeology 27:217-229.

Ní Mhunghaile, L. (2008) Anglo-Irish antiquarianianism and the transformation of Irish Identity.

In: Valone, D.A. and Bradbury, J.M., eds. Anglo-Irish Identities, 1571-1845. Bucknell

University Press.

Nicholson, A. (1998) Annals of the Famine in Ireland. Murphy, M., ed. Dublin: Lilliput Press.

Nishi, M., Horii-Hayashi, N., Sasagawa, T., Matsunaga, W. (2013) Effects of early life stress on brain activity: Implications from maternal separation models in rodents. General and

Comparative Endocrinology 181:306-309.

Noll, J.G., Zeller, M.H., Trickett, P.K., Putnam, F.W. (2007) Obesity risk for female victims of childhood sexual abuse: A prospective study. Pediatrics 120(1):e61-e67.

Novak, M., Howcroft, R., Pinhasi, R. (2017) Child health in five early medieval Irish sites: A multidisciplinary approach. International Journal of Osteoarchaeology 27(3):398-408.

O’Brien, M.J., Lyman, R.L., Schiffer, M.B. (2005) A New Perspective in Arch(a)eology: In:

Archaeology as a Process: Processualism and its Progeny. University of Utah Press. 36-65.

342

O Croinin, D. (2016) Early Medieval Ireland. Routledge.

O’Connell, M. (2007) Irish Politics and Social Conflict in the Age of the American Revolution.

University of Pennsylvania Press.

Ó Gráda, C. (1979) The population of Ireland 1700-1900: A survey. Annales de Démographie

Historique:281-299.

O’Mahony, P., Delanty, G. (2001) Rethinking Irish History: Nationalism, Identity, and Ideology.

Palgrave. Great Britain, Chippenham, Wiltshire.

O’Neill, K. (1984) Family and Farm in Pre-Famine Ireland: The Parish of Killashandra. Madison and London: University Wisconsin Press.

O’Tuathaigh, G. (2007) Ireland Before the Famine 1798-1848. Dublin: Gill & Macmillian.

Ortner, D., Putschar, W. (1985) Identification of Pathological Conditions in Human Skeletal

Remains. Washington DC: Smithsonian Institution Press.

Oxenham, M., Matsumura, H., Domett, K., Thuy, N.K., Dung, N.K., Cuong, N.L., Huffer, D.,

Muller, S. (2008) Health and the experience of childhood in Late Neolithic Vietnam. Asian

Perspectives 47(2):190-209.

343

P.G. (1678) An account of the blood massacre in Ireland acted by the instigation of the Jesuits, priests, and friars who were promoters of those horrible murthers executed by the Irish papists upon the English Protestants. London. Available from EEBO. Web. 9 October 2018.

Packer, A.D. (1961) The health of the Australian native. Oceania 32(1):60-70.

Palubeckaité, Z., Jankauskas, R., Boldsen, J. (2002) Enamel hypoplasia in Danish and Lithuanian late medieval/early modern samples: A possible reflection of child morbidity and mortality patterns. International Journal of Osteoarchaeology 12:189-201.

Paulubeckaitė, Ž., Jankauskas, R., Ardagna, Y., Marcia, Y., Rigeade, C., Signoli, M., Dutour, O.

(2006) Dental status of Napoleon’s Great Army’s (1812) mass burial of soldiers in Vilnius:

Childhood peculiarities and adult dietary habits. International Journal of Osteoarchaeology

16(4):355-365.

Panagiotakopolous, L., Neigh, G.N. (2014) Development of the HPA-axis: Where and when do sex differences manifest? Frontiers in Neuroendocrinology 35:285-302.

Perry, M.A. (2007) Is bioarchaeology a handmaiden to history? Developing a historical bioarchaeology. Journal of Anthropological Archaeology 26:486-515.

Perry, R. (2010) Revising Irish history: The Northern Ireland conflict and the war of ideas.

Journal of European Studies 40(4):329-354.

344

Peters, C.N. (2016) ‘He is not entitled to butter:’ the diet of peasants and commoners in early medieval Ireland. In: FitzPatrick, E., Kelly, J., eds. Food and Drink in Ireland. Dublin: Royal

Irish Academy. 79-110.

Petersone-Gordina, E., Gerhards, G., Jakob, T. Nutrition-related health problems in a wealthy

17-18th century German community in Jelgava, Latvia. International Journal of Paleopathology

3(1):30-38.

Phillips, H. (1822) History of Cultivated Vegetables; Comprising their botanical, medicinal, edible, and chemical qualities; natural history and relation to art, science, and commerce.

London: Henry Colburn and Co.

Piperata, B.A., Hubbe, M., Schmeer, K.M. (2014) Intra-population variation in anemia status and its relationship to economic status and self-perceived health in the Mexican Family Life Survey:

Implications for bioarchaeology. American Journal of Physical Anthropology 155(2):210-220.

Primeau, C., Homøe, P., Lynnerup, N. (2018) Childhood health as reflected in adult urban and rural samples from medieval Denmark. HOMO 69(1-2):6-16.

Primeau, C., Homøe, P., Lynnerup, N. (2019) Temporal changes in childhood health during the medieval Little Ice Age in Denmark. International Journal of Paleopathology 27:80-87.

345

Redfern, R.C., DeWitte, S.N., Pearce, J., Hamlin, C., Egging Dinwiddy, K. (2015) Urban-rural differences in Roman Dorset, England: A bioarchaeological perspective on Roman settlements.

American Journal of Physical Anthropology 157(1):107-120.

Reilly, T. (1999) Cromwell: An Honourable Enemy. Brandon. Dingle, Co. Kerry, Ireland.

Reitsema, L.J., Kyle McIllvaine, B. (2014) Reconciling “stress” and “health” in physical anthropology: What can bioarchaeology learn from other sub-disciplines? American Journal of

Physical Anthropology 46:439-446.

Ricklefs, R.E., Scheuerlein, A. (2002) Biological implications of the Weibull and Gompertz models of aging. The Journals of Gerontology: Series A 57(1):B69-B76.

Risnes, S. (1986) Enamel apposition rate and the prism periodicity in human teeth. European

Journal of Oral Sciences 94(5):394-404.

Rohnbogner, A., Lewis, M.A. (2017) Poundbury Camp in context- A new perspective on the lives of children from urban and rural Roman England. American Journal of Physical

Anthropology 162(2):208-228.

Ronan, Rev. M. (1948) The Parish of St. Michan. Printed by Dollard, Printingouse, Dublin,

Limited.

346

Rose, J.C., Armelagos, G.J., Lallo, J.W. (1978) Histological enamel indicators of childhood stress in prehistoric skeletal samples. American Journal of Physical Anthropology 49:511-516.

Roseboom, T.J., van der Meulen, J.H.P., Ravelli, A.C.J. (2001) Effects of prenatal exposure to the Dutch famine on adult disease in later life: An overview. Molecular Cell Endocrinology

185:93-98.

Rowley, E. (2017) Housing in Ireland, 1740-2016. Health and welfare. In: Biagini, E.F., Daly,

M.E., eds. The Cambridge Social History of Modern Ireland. Cambridge: Cambridge University

Press. 212-232.

Royal College of Physicians of Ireland (2015). Cork Street Fever Hospital and Cherry Orchard

Hospital. ACC/2013/4.

Ruane, J., Todd, J. (2017) Changing role of the middle class. In: Biagini, E.F., Daly, M.E., eds.

The Cambridge Social History of Modern Ireland. Cambridge: Cambridge University Press.

Saaltink, D.J., Vreugdenhil, E. (2014) Stress, glucocorticoid receptors, and adult neurogenesis: A balance between excitation and inhibition. Cellular and Molecular Life Sciences 71(13):2499-

2515.

Salaman, R.N. (1985) The history and social influence of the potato. In: Revised Impression.

J.G. Hawkes, ed. Cambridge: Cambridge University Press.

347

Saunders, S.R., Keenleyside, A. (1999) Enamel hypoplasia in a Canadian historic sample.

American Journal of Human Biology 11:513-524.

Savall, F., Rerolle, C., Herin, F., Dedouit, F., Rouge, D., Telmon, N., Saint-Martin, P. (2016)

Reliability of the Suchey-Brooks method for a French contemporary population. Forensic

Science International 266:586.e1

Schmidt, M.V., Schmidt, M., Levine, S., Oitzl, M.S., van der Mark, M., Müller, M.B., Holsboer,

F., de Kloet, E.R. (2005) Glucocorticoid receptor blockade disinhibits pituitary-adrenal activity during the stress hyporesponsive period of the mouse. Endocrinology 146:1458-1464.

Schmidt, M.V., Wang, X.,D., Meijer, O.C. (2011) Early life stress paradigms in rodents:

Potential animal models of depression? Psychopharmacology 214:131-140.

Schulkin, J. (2011) Evolutionary conservation of glucocorticoids and corticotropin releasing hormone: Behavioral and physiological adaptations. Brain Research 1392:27-46.

Seeman, T.E., Crimmins, E., Huang, M.H., Singer B., Bucur, A., Grunewald, T., Berkman, L.F.,

Reuben, D.B. (2004) Cumulative biological risk and socio-economic differences in mortality:

MacArthur studies of successful aging. Social Science Medicine 58:1985.

348

Seeman, T.E., Glei, D., Goldman, N., Weinstein M., Singer B., Lin, Y.H. (2004) Social relationships and allostatic load in Taiwanese elderly and near elderly. Social Science Medicine

59:2245.

Seeman, T.E., McEwen, B.S., Rowe, J.W., Singer, B.H. (2001) Allostatic load as a marker of cumulative biological risk: MacArthur studies of successful aging. Proceedings of the National

Academy of Sciences of the United States of America 98(8):4770-4775.

Seeman, T.E., Singer, B.H., Rowe, J.W., Horwitz, R.I., McEwen, B.S. (1997) Price of adaptation- allostatic load and its health consequences. Archives of Internal Medicine 157:2259-

2268.

Seeman, T.E., Singer, B.H., Ryff, C.D., Dienberg Love, G., Levy-Storms, L. (2002) Social relationships, gender, and allostatic load across two age cohorts. Psychosomatic Medicine

64:395.

Seeman, M., Stein Merkin, S., Karlamangla, A., Kortez, B. (2014) Social status and biological dysregulation: The “status syndrome” and allostatic load. Social Science & Medicine 118:143-

151.

Sellers, R.M., Shelton, N.J. (2003) The role of racial identity in perceived racial discrimination.

Journal of Personality and Social Psychology 84(5):1079-1092.

349

Selye, H. (1978) The Stress of Life, Revised Edition. San Francisco: McGraw-Hill.

Seplaki, C.L., Goldman, N., Glei, D. Weinstein, M. (2005) A comparative analysis of measurement approaches for physiological dysregulation in an older population. Experimental

Gerontology 40:438.

Seplaki, C.L., Goldman, N., Weinstein, M., Lin, Y.H. (2006) Measurement of cumulative physiological dysregulation in an older population. Demography 43:165.

Seress, L., Ábrahám, H. (2008) Pre- and postnatal morphological development of the human hippocampal formation. In: Nelson, C.A., Luciana, M., eds. Handbook of Developmental

Cognitive Neuroscience, 2nd ed. Cambridge, Massachusetts. The MIT Press. 187-209.

Sexton, R. (1998) In: Sheehan, J., Michael, M.A. Early Medieval Munster: Archaeology,

History, and Society. Cork: Cork University Press.

Sexton, R. (2016) Food and culinary cultures in pre-Famine Ireland. In: FitzPatrick, E., Kelly, J., eds. Food and Drink in Ireland. Dublin: Royal Irish Academy. 257-306.

Shaffrey Associates Architects, Montague, J., Archaeological Projects, Ltd., Levinge-

Shackleton, D., (2003) St. Luke’s Conservation Plan plean Caomhnaith San Lúcás: An Action of the Dublin City Heritage Plan Gniomh de chuid Phlean Oidhreachta Chathair Bhaile Átha

Cliath. The Heritage Council.

350

Sheridan-Quants, E. (2001) The multi-centered metropolis: The social topography of eighteenth- century Dublin. Proceedings of the British Academy 107:265-95.

Shi, Z., Nicholls, S.J., Taylor, A.W., Magliano, D.J. (2018) Early life exposure to Chinese famine modifies the association between hypertension and cardiovascular disease. Journal of

Hypertension 36(1):54-60.

Sierant, M.L., Bartlett, J.D. (2012) Stress response pathways in ameloblasts: Implications for amelogenesis and dental fluorosis. Cell 1:631-645.

Simms, K. (2018) Chapter 10: The Political Recovery of Gaelic Ireland. In: Smith, B., ed. The

Cambridge History of Ireland. Cambridge University Press. 272-299.

Simpson, L. (1995) Archaeology in Temple Bar: Excavations at Essex Street West, Dublin.

Temple Bar Archaeological Report No. 2. Dublin.

Sinclair, J. (1828) On the Culture and Uses of Potatoes. Edinburgh. Printed for William

Blackwood.

Singer, B., Ryff, C.D. (1999) Hierarchies of life histories and associated health risks. Annals of the New York Academy of Science 896:96.

351

Skinner, M. (1996) Developmental stress in immature hominines from Late Pleistocene Eurasia:

Evidence from enamel hypoplasia. Journal of Archaeological Science 23(6):833-852.

Šlaus, M. (2008) Osteological and dental markers of health in the transition from the late antique to the early medieval period in Croatia. American Journal of Physical Anthropology 136(4):455-

469.

Šlaus, M., Kollmann, D., Novak, S.A., Novak, M. (2002) Temporal trends in demographic profiles and stress levels in medieval (6th-13th century) population samples from continental

Croatia. Basic Sciences 43:598-605.

Smith, B. (2018) Chapter 9: Disaster and Opportunity 1320-1540. In: Smith, B., ed. The

Cambridge History of Ireland. Cambridge University Press. 244-271.

Smith, C.E. (1998) Cellular and chemical events during enamel maturation. Critical Reviews in

Oral Biology & Medicine 9(2):128-161.

Smith, C.J., Ryckman, K.K. (2015) Epigenetic and developmental influences on the risk of obesity, diabetes, and metabolic syndrome. Diabetes, Metabolic Syndrome, and Obesity: Targets and Therapy 8:295-302.

Smith, T.M. (2006) Experimental determination of the periodicity of incremental features in enamel. Journal of Anatomy 208(1):99-113.

352

Solan, P.M. (2017) Occupation, poverty, and social class in pre-Famine Ireland, 1740-1850.

Health and welfare. In: Biagini, E.F., Daly, M.E., eds. The Cambridge Social History of Modern

Ireland. Cambridge: Cambridge University Press. 25-37.

Sołtysiak, A. (2015) The osteological paradox, selective mortality, and stress markers revisited.

Current Anthropology 56:4.

Somers, J., Cooper, C., Alterauge, A., Lösch, S. (2017) A medieval/early modern Alpine population from Zweisimmen, Switzerland: A comparative study of anthropology and palaeopathology. International Journal of Osteoarchaeology 27(6):958-972.

Srinivas, S.K., Bastek, J., McShea, A., Foreman, M., Elovitz, M.A. (2011) Unraveling the racial disparity in preterm birth: Experiences of discrimination are associated with preterm and low birth weight in black women. American Journal of Obstetrics and Gynecology 204(1):S209-210.

Steckel, R.H. (2005) Young adult mortality following severe physiological stress in childhood:

Skeletal evidence. Economics and Human Biology 3:314-328.

Steer, J.H., Kroeger, K.M., Abraham, L.J., Joyce, D.A. (2000) Glucocorticoids suppress tumor necrosis factor-alpha expression by human monocytic THP-1 cells by suppressing transactivation through adjacent NF-kappa B and c-Jun activating transcription factor-2 binding sites in the promoter. Journal of Biological Chemistry 16(24):18432-40

353

Steffen, P.R., McNeilly, M., Anderson, N., Sherwood, A. (2003) Effects of perceived racism and anger inhibition on ambulatory blood pressure in African Americans. Psychosomatic Medicine

65:750-756.

Stein, D.J., Chiu, W.T., Hwang, I., Kessler, R.C., Sampson, N., Alonso, J., Borges, G., Bromet,

E., Bruffaerts, R., de Girolamo, G., Florescu, S., Gureje, O., He, Y., Kovess-Masfety, V.,

Levinson, D., Matschinger, H., Mneineh, Z., Nakamura, Y., Ormel, J., Williams, D.R., Posada-

Villa, J., Sagar, R., Scott, K.M., Tomov, T., Viana, M.C. (2010) Cross-national analysis of the associations between traumatic events and suicidal behavior: Findings from the WHO World

Mental Health Surveys. PLoS One 5(5):e10574.

Stephens, W. (1712) A sermon against popery: Prech’d to the Protestants of Ireland now residing in London, at their anniversary meeting on October 23, 1711. Printed for A. Baldwin, Warwich-

Lane, England.

Steven, R. (1822) Remarks on the present state of Ireland with hints for ameliorating the condition and promoting the education and moral improvement of the peasantry of that country the result of a visit during the summer and autumn of 1821 with an appendix containing and outline of the system of education pursued in the schools of the London Hibernian Society. 2nd ed. London.

354

Stinson, S. (1982) The effect of high altitude on the growth of children of high socioeconomic status in Bolivia. American Journal of Physical Anthropology 59(1):61-71.

Stodder, A.L.W. (1997) Subadult stress, morbidity, and longevity in Latte Period populations on

Guam, Mariana Islands. American Journal of Physical Anthropology 104(3):363-380.

Stojanowski, C.M., Duncan, W.N. (2016) Engaging bodies in the public imagination:

Bioarchaeology as social science, science, and humanities. American Journal of Human Biology

27:51-60.

Stourton, Honorable Lord (1827) A letter to the Right Hon. George Canning on the nature of absenteeism and its influence on the State of Ireland, in reply to an article of the Edinburgh

Review, (Nov. 1825). Printed for J. Mawman.

Su, S., Wang, X., Kapuku, G.K., Treiber, F.A., Pollock, D.M., Harshfield, G.A., McCall, W.V.,

Pollock, J.S. (2014) Adverse childhood experiences are associated with detrimental hemodynamics and elevated circulating endothelin-1 in adolescents and young adults.

Hypertension 64:201-207.

Su, S., Wang, X., Pollock, J.S., Treiber, F.A, Xu, X., Snieder, H., McCall, W.V., Stefanek, M.,

Harshfield, G.A. (2015) Adverse childhood experiences and blood pressure trajectories from childhood to young adulthood: The Georgia stress and heart study. Circulation 131:1674-1681.

355

Suckling, G., Elliot, D.C., Thurley, D.C. (1986) The macroscopic appearance and associated histological changes in the enamel organ of hypoplastic lesions of sheep incisor teeth resulting from induced parasitism. Archives of Oral Biology 31(7):427-439.

Sweetman, D., Mitchell, G.F., Mansfield, R.J., Dolley, M. (1978) Archaeological excavations at

Trim Castle, Co. Meath, 1971-74. Proceedings of the Royal Irish Academy: Archaeology,

Culture, History, Literature 78:127-198.

Swiss, J. (1828) On the Culture and Uses of Potatoes. Edinburgh. Printed for William

Blackwood.

Taylor, T.R., Williams, C.D., Makambi, K.H., Moutoun, C., Harrell, J.P., Cozier, Y., Palmer,

J.R., Rosenberg, L., Adams-Campbell, L.L. (2007) Racial discrimination and breast cancer incidence in US black women: The Black Women’s Health Study. American Journal of

Epidemiology 166:46-64.

Temple, Sir J. (1646) The Irish Rebellion. London: Samuel Gellibrand.

The Irish Builder (1895) Old Dublin mansion houses: Their lordly occupiers in the last century-

The Gallows (near St. Stephen’s Green). Vol. 37. Dublin: 36.

Thomas, C., Hyppönen, E., Power, C. (2008) Obesity and type 2 diabetes risk in midadult life:

The role of childhood adversity. Pediatrics 121(5):e1240-1249.

356

Thompson, J.L., Alfonso-Durruty, M.P., Crandall, J.J. (2014) Tracing Childhood:

Bioarchaeological Investigations of Early Lives in Antiquity. Gainesville: University of Press

Florida.

Titus, O. (1680) A balm presented to these nations, England, Scotland, and Ireland to cure the wounds of the bleeding Protestants, and open the eyes of the deluded papists, that are ignorant of the truth. Or, a seasonable antidote against the errors of popery and pernitious doctrines of the

Church of Rome. Publisher not identifiable. Available from William Andrews Clark Memorial

Library, University of California, Los Angelos.

Tordes, J., Fink, D.V. (2020) The trauma of Trump’s family separation and child detention actions: A children’s rights perspective. Washington Law Review 95(1):3777-427.

Twiss, R. (1776) A tour of Ireland in 1775. Finnegan, R., ed. University College Dublin Press.

Tyrka, A.R., Wier, L., Price, L.H., Ross, N.S., Carpenter, L.L. (2008) Childhood parental loss and adult psychopathology: Effects of loss characteritics and contextual factors. International

Journal of Psychiatry Medicine 38(3):329-344.

Ubelaker, D. (1992) Hyoid fracture and strangulation. Journal of Forensic Sciences 37(5):1216-

1222.

357

Uchida, S., Hara, K., Kobayashi, A., Funato, H., Hobara, T., Otsuki, K., Yamagata, H., McEwen,

B.S., Wantabe, Y. (2010) Early life stress enhances behavioral vulnerability to stress through the activation of REST4-mediated gene transcription in the medial prefrontal cortex of rodents.

Journal of Neuroscience 30:15007-15018.

Unpublished Excavation Report, 98E0088. Stratigraphic Report on an Archaeological

Excavation at 189-194 North King Street Dublin 7.

Usher, R. (2012). Protestant Dublin, 1660-1760: Architecture and Iconography. Palgrave

Macmillan: Hampshire, United Kingdom.

Vaiserman, A.M. (2015) Epigenetic programming by early-life stress: Evidence from human populations. Developmental Dynamics 244:254-265.

Veach, C. (2018) Chapter 6: Conquest and Conquerors. In: Smith, B., ed. The Cambridge

History of Ireland. Cambridge University Press. 157-182. Web. 8 October 2018.

Veldeman, M.C. (2009) Cultural nationalism in late nineteenth-century Ireland, a step towards political separatism? Equalvalences 36(1-2):145-155.

Vincent, N. (2018) Chapter 7: Angevin Ireland. In: Smith, B., ed. The Cambridge History of

Ireland. Cambridge University Press. 185-221. Web. 8 October 2018.

358

Von Thiele, U., Lindfors, P., Lundberg, U.(2006) Self-rated recovery from work stress and allostatic load in women. Journal of Psychosomatic Research 61:237.

Wakefield, D.R. (1812) An Account of Ireland, Statistical and Political. London: Longman,

Hurst, Rees, Orme, and Brown.

Walter, B.S., DeWitte, S.N. (2017) Urban and rural mortality and survival in medieval England.

Annals of Human Biology 44(4):338-348.

Watts, R. (2013) Childhood development and adult longevity in an archaeological population from Barton-upper-Humber, Lincolnshire, England. International Journal of Paleopathology

3(2):95.

Watts, R. (2015) The long-term impact of developmental stress: Evidence from later medieval and post-medieval London (AD 1117-1853). American Journal of Physical Anthropology

158:569-580.

Wells, J. (1688) A true relation of the horrid and bloody massacre in Scotland, by the Irish

Papists; who landed sixty miles from Edinburgh, putting all to Fire and Sword in their way to that City. London: Published by J. Wells in St. Paul’s Alley in St. Paul’s Church-yard. Available from EEBO. Web. 9 October 2018.

359

White, T. (1978) Early hominid enamel hypoplasia. American Journal of Physical Anthropology

49:79-83.

Whitelaw, J. (1805) An essay on the population of Dublin, 1798. Dublin.

Whyte, J.H. (1995) The age of Daniel O’Connell. In: Moody, T.W. & Martin, F.X., eds. The

Course of Irish History. Radio Telefís Éireann. Lanham, Maryland: Roberts Rinehart Publishers.

Wiley, A.S., Cullin, J.M. (2016) What do anthropologists mean when they use the term biocultural? American Anthropologist 118(3):554-569.

Williams, D.R. (1999) Race, socioeconomic status, and health: The added effects of racism and discrimination. Annals of the New York Academy of Sciences 896:173-188.

Williams, D.R., Mohammed, S.A., Leavell, J., Collins, C. (2010) Race, socioeconomic challenges, and research opportunities. Annals of the New York Academy of Sciences 1186:69-

101.

Williams, D.R., Neighbors, H.W., Jackson, J.S. (2003) Racial/ethnic discrimination and health:

Findings from community studies. American Journal of Public Health 93(2).

Wittwer-Backofen, U., Buckberry, J., Czarnetzki, A., Doppler, S., Grupe, G., Hotz, G., Kemkes,

A., Larsen, C.S., Prince, D., Wahl, J., Fabig, A., Weise, S. (2008) Basics in paleodemography: A

360 comparison of age indicators applied to the early medieval skeletal sample of Lauchheim.

American Journal of Physical Anthropology 137:384-396.

Witzel, C., Kierdorf, U., Schultz, M., Kierdorf, H. (2008) Insights from the inside: Histological analysis of abnormal enamel microstructure associated with hypoplastic enamel defects in human teeth. American Journal of Physical Anthropology 136:400-414.

Wolfe, E.R. (1982) Europe and the People Without History. California: University of California

Press.

Wood, J.W., Milner, G.R., Harpending, H.C., Weiss, K.M. (1992) The osteological paradox:

Problems of inferring prehistoric health from skeletal samples. Current Anthropology 33(4):343-

370.

Woodham-Smith, C. (1962) The Great Hunger: Ireland 1845-1849. London: Penguin Books.

Woodward, R. (1772) An Argument in Support of the Right of the Poor in the Kingdom of

Ireland, to a National Provision; in the Appendix to which, an Attempt is made to settle a measure of the contribution due from each man to the poor, on the footing of justice. Printed by

S. Powell, Dame Street, Dublin.

Woolf, A. (2018) Chapter 4: The Scandinavian intervention. In: Smith, B., ed. The Cambridge

History of Ireland. Cambridge University Press. 107-130. Web. 8 October 2018.

361

Wright, G.P. (1821) An Historical Guide to Ancient and Modern Dublin. London: Baldwin,

Cradock, and Joy.

Xanthopoulou, P., Valakos, E., Youlatos, D., Nikita, E. (2018) Assessing the accuracy of cranial and pelvic ageing methods on human skeletal remains from a modern Greek assemblage.

Forensic Science International 286:266e1-266.38.

Yaussy, S.L. (2019) The intersections of industrialization: Variation in skeletal indicators of frailty by age, sex, and socioeconomic status in 18th and 19th century England. American Journal of Physical Anthropology 170:116-130.

Yaussy, S.L., DeWitte, S.N., Redfern, R.C. (2016) Frailty and famine: Patterns of mortality and physiological stress among victims of famine in medieval London. American Journal of Physical

Anthropology 160:272-283.

Yaussy, S.L., DeWitte, S.N. (2018) Patterns of frailty in non-adults from medieval London.

International Journal of Paleopathology 22:1-7.

Young, A. (1778) A Tour in Ireland with General Observations on the Present State of that

Kingdom Made in the Years 1776, 1777, and 1778. Maxwell, C., ed. (1925) Cambridge

University Press.

362

Young, C.E.J. (1940). St. Michan’s Parish in the eighteenth century. Dublin Historical Record

3(1):1-7.

Young, H., Jaspars, S. (1995) Nutrition, disease, and death in times of famine. Disasters

19(2):94-109.

Appendices are available as supplemental files on OhioLink.

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