Disordered Eating Attitudes and Behaviors in Individuals with Celiac Disease and The

Disordered Eating Attitudes and Behaviors in Individuals with Celiac Disease and the

association with Quality of Life

Yara Gholmie

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy under the Executive Committee of the Graduate School of Arts and Sciences

COLUMBIA UNIVERSITY

2021

Yara Gholmie

Abstract

Disordered Eating Attitudes and Behaviors in Individuals with Celiac Disease and the

association with Quality of Life

Yara Gholmie

The only treatment for celiac disease (CeD), an autoimmune disorder triggered by the ingestion of gluten, is lifelong adherence to a gluten-free diet (GFD). CeD and the GFD have been shown to be associated with low quality of life (QoL). In some individuals, such a strict diet can lead to disordered eating attitudes and behaviors.

The purpose of this study was to better understand the extent to which disordered eating attitudes and behaviors may be common in a sample of adults diagnosed with CeD, as well as the relationship with various factors and QoL measures, including anxiety and depression. The study is a cross sectional pilot study of 50 individuals with CeD. Patients between the ages of 18 to 45 years old (mean=29.56, SD=7.40) with a biopsy-proven CeD diagnosis, following a GFD for at least a year (mean=7.20, SD=5.31) with no previous or current eating disorder diagnosis were recruited.

In this study, suggestive ED (based on EDDS) and DE (based on EPSI) were present, but low (2% suggestive diagnosis of BED, 12% suggestive diagnosis of OSFED as per DSM-V).

The distribution of the self-reported food attitudes and behaviors measures (CD-FAB scores) were spread out around the mean 36.96 (15.30) with a maximum score of 66 out of a possible 77.

The CD-FAB may have utility in identifying adults with CeD that may be at risk for disordered eating attitudes and behaviors, particularly those in the first few years after diagnosis. It likely

has limited utility in identifying suggestive EDs (as per EDDS) and DE (as per EPSI). The main factors that were associated with higher CD-FAB scores were BMI, number of symptoms, years since diagnosis, diet adherence and personality characteristics. Seven years after diagnosis seems to be an important cut-point in how participants rated food attitudes, fear responses and adaptive responses on the CDFAB scales. Higher CD-FAB scores had a significant and meaningful association with QoL scores. Participants recruited during the COVID-19 pandemic had significantly lower CD-FAB scores and higher QoL scores compared to those recruited pre- pandemic; despite not having significant differences in any other demographic characteristics.

Table of Contents

List of Tables ...... viii

List of Figures ...... xi

Acknowledgements ...... xii

Dedication ...... xiv

Chapter 1 – Introduction ...... 1

1.1 Background & Rationale ...... 2

1.2 Purpose of Study ...... 8

1.3 Research Questions ...... 9

1.4 Significance and Implications ...... 10

1.5 Scope and delimitations ...... 11

1.6 Definition of Terms ...... 11

Chapter 2 – Review of the Literature ...... 13

2.1 Celiac Disease ...... 13

2.1.1 Definition...... 13

2.1.2 Prevalence...... 13

2.1.3 Pathophysiology...... 14

2.1.4 Presentation and Risk Factors...... 15

2.1.5 Guidelines for Diagnosis...... 16 i

2.1.6 Diet and complications...... 18

2.1.7 GFD adherence and burden...... 19

2.1.8 Quality of life (QoL) in Individuals with CeD...... 21

2.1.9 Depression and Anxiety in Individuals with CeD...... 24

2.2 Eating Disorders and Disordered Eating Patterns in CeD ...... 25

2.2.1 Eating Disorders and Disordered Eating...... 25

2.2.2 Eating disorders...... 27

2.2.3 Psychological factors on Disordered eating attitudes and behaviors...... 43

2.2.4 The link to ARFID...... 44

2.2.5 Factors associated with ED or DE in CeD...... 46

2.2.6 Summary ...... 47

Chapter 3- Methods ...... 48

3.1 Overview of Study Design ...... 48

3.2 Setting and Participants ...... 48

3.3 Inclusion & Exclusion Criteria ...... 49

3.4 Enrollment & COVID-19 ...... 50

3.5 Study Measures ...... 51

3.5.1 Anthropometric measures...... 51

3.5.2 Demographic and Medical History variables...... 51

3.5.3 Eating Disorder Diagnosis Tools...... 52

3.5.4 Disordered Eating Patterns detection tool...... 53

3.5.5 Disordered Eating Patterns Specific to CeD tool...... 54

3.5.6 Measures related to celiac disease specific QoL...... 57

3.5.7 Measures of anxiety and depression...... 58

3.5.8 CeD Symptoms...... 59

3.5.9 Diet Adherence...... 59

3.5.10 Personality traits...... 61

3.6 Other measures collected but not used in this study ...... 65

3.6.1. Serology...... 65

3.6.2 Stool samples and swabs...... 65

3.6.3 24-hour dietary recalls...... 65

3.6.4 Food Avoidance...... 66

3.7 Data Analysis Plan ...... 66

3.7.1 Statistical procedures...... 66

3.7.2 Analysis of RQ1a and RQ1b ...... 67

3.7.3 Analysis for RQ2 and RQ2b ...... 68

3.7.4 Analysis for RQ3 ...... 69

3.7.5 Analysis for RQ4 ...... 70

3.7.6 Statistical Analysis pre- and during- COVID-19...... 72

3.7.7 Privacy & Data Security...... 73

Chapter 4 – Results ...... 74

4.1 Study Flow ...... 75

4.2 Demographic and patient characteristics of study sample ...... 76 iii

4.3 RQ 1: ED and DE in CeD ...... 78

4.3.1 ED in CeD ...... 78

4.3.2 DE in CeD ...... 80

4.3.3 Summary findings ...... 85

4.4 RQ2: Disordered Eating attitudes and behaviors (CD-FAB) in adults with CeD ...... 85

4.4.1 RQ2 ...... 85

4.4.2 EPSI mean scores as per CD-FAB scorers (based on tertiary split) ...... 90

4.4.3 RQ2a ...... 91

4.4.4 Summary of findings ...... 92

4.5 RQ3: Factors associated with CD-FAB ...... 93

4.5.1 Factor: Gender ...... 94

4.5.2 Factors: Age, Years since diagnosis, BMI ...... 95

4.5.3 Factors: Household income, Education level, RDN visit ...... 96

4.5.4 Factor: GI Symptoms (CDSD)...... 98

4.5.5 Factor: Personality characteristics (BFI) ...... 100

4.5.6 Factor: Diet Adherence (CDAT, Biagi) ...... 102

4.5.7 Regression analysis- Factors and CD-FAB ...... 108

4.5.8 Deeper look into Years since Diagnosis and Total CD-FAB scores...... 110

4.5.9 Summary Findings: ...... 116

4.6 RQ4: QoL, depression, and anxiety association with CD-FAB ...... 118

4.6.1 Quality of Life and CD-FAB ...... 118

4.6.2 Anxiety (state and trait) and CD-FAB ...... 121

4.6.3 Depression and CD-FAB ...... 125

4.6.4 Regression analysis: quality of Life, anxiety, depression and CD-FAB...... 127

4.6.5 Tertiary Split of CD-FAB and Quality of Life, anxiety and depression scores...... 131

4.6.6 Summary Findings: ...... 133

4.7 Pre- and During- COVID-19 Pandemic ...... 134

4.7.1 Summary Findings: ...... 140

Chapter 5 – Discussion ...... 141

5.1 Purpose and Main Findings ...... 141

5.2 ED, DE, Disordered Eating Attitudes and Behaviors and CeD ...... 146

5.3 Adherence, years since diagnosis, BMI, symptoms and CD-FAB ...... 150

5.4 Quality of Life, anxiety and depression and CD-FAB ...... 152

5.6 Limitations ...... 157

5.7 Strengths ...... 159

5.8 Implications and applications ...... 160

5.9 Future research ...... 161

Conclusion ...... 163

References ...... 164

Appendix A: Introduction Script ...... 179

Appendix B: Verbal Consent Script & Eligibility Checklist ...... 180 v

Appendix C: Consent form ...... 182

Appendix D : Demographic & Health Characteristics ...... 186

Appendix E: Diet Adherence ...... 188

Appendix F: EDDS/DSM-5 Version ...... 189

Appendix G: Symptoms Inventory (EPSI) ...... 190

Appendix H: Food Avoidance ...... 192

Appendix I: IPAQ ...... 194

Appendix J: STAI Adults...... 195

Appendix K: CD-FAB Adults ...... 197

Appendix L: The Big 5 Inventory Test ...... 198

Appendix M: CDSD ...... 200

Appendix N: CESD-R...... 201

Appendix O: CD-QoL ...... 202

Appendix P: 24-hour Recall Script ...... 203

Appendix Q- EDDS composite scores and Diagnosis ...... 207

Appendix R- Regression CD-FAB and Factors w/COVID-19 ...... 210

Appendix S- Comparing EPSI means of suggestive ED diagnosed (as per EDDS) with high CD-

FAB scorers ...... 211

vii

List of Tables

Table 1- Factors influencing GFD adherence in adults in the US (adapted from Cichewicz et

al. 2019) ...... 21

Table 2- Key Diagnostics of Eating Disorders/ DSM-V ...... 29

Table 3- Summary table, prevalence of ED and DE in CeD and GI Disorders ...... 40

Table 4- Summary of survey tools used in this study ...... 63

Table 5- Analysis of Research questions ...... 70

Table 6- Demographic and patient characteristics of study sample ...... 77

Table 7- Demographic and patient characteristics of study sample ...... 78

Table 8-Prevalence of Eating Disorders as per the EDDS ...... 79

Table 9-EPSI subscale mean scores for participants with CeD compared to mean scores of

participants in Forbush et al.’s study...... 82

Table 10- Comparison of EPSI subscale scores by Gender with College Students from Forbush

et al.’s study...... 83

Table 11- Comparison of EPSI Subscales scores in Male and Female participants with Celiac

Disease ...... 84

Table 12- Total CD-FAB Scores+ and Subscales with Cronbach’s alpha ...... 87

Table 13- Prevalence of participants scoring strongly agree, agree or agree somewhat per CD-

FAB item...... 88

Table 14- Overall CD-FAB and subscale scores of individuals with diagnosed ED and possible

OSFED...... 90

Table 15- EPSI mean scores CD-FAB Total scores tertiary split ...... 91

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Table 16- Pearson Correlations between CD-FAB total score and subscale with EPSI subscale 92

Table 17- Total CD-FAB Scores+ and Subscales by Gender ...... 94

Table 18- Pearson Correlations between CD-FAB+ and age, years since diagnosis and BMI. ... 96

Table 19-Overall CD-FAB+ and subscale scores per education level, household income ...... 97

Table 20- Overall CD-FAB and subscale scores +of participants currently seeing and RDN vs.

those who are not currently seeing an RDN...... 98

Table 21- Pearson Correlations between CD-FAB+ and GI Symptoms (CDSD) ...... 99

Table 22-Overall CD-FAB+ and subscale scores per reported symptoms ...... 99

Table 23-Pearson Correlations between CD-FAB and personality characteristics+ ...... 101

Table 24- CD-FAB Total scores tertiary split ...... 102

Table 25- Pearson Correlations between CD-FAB and Diet Adherence (CDAT) + ...... 103

Table 26- Total CD-FAB Scores and Subscales by participant’s adherence to GFD (CDAT) + 104

Table 27- Total CD-FAB Scores+ and Subscales by participant’s consumption of gluten

voluntarily (Biagi question 1) ...... 105

Table 28-Total CD-FAB Scores+ and Subscales by Responses (Biagi question 2) ...... 107

Table 29- Total CD-FAB Scores+ and Subscales by participant’s label checking for packaged

foods (Biagi question 3) ...... 108

Table 30- Factors associated with CD-FAB total and subscale scores including COVID-19

status ...... 110

Table 31-Years since Diagnosis ...... 111

Table 32- Total CD-FAB Scores+ and Subscales by lowest and highest range for years since

diagnosis...... 112

Table 33-Total CD-FAB Scores+ and Subscales by years since diagnosis at cut point of five

years...... 113

Table 34-Prevalence of participants with low and high range of years since diagnosis scoring

strongly agree, agree or agree somewhat per CD-FAB item...... 115

Table 35- Personality characteristics per years since diagnosis at cut point of five years+...... 116

Table 36-Number of symptoms per years since diagnosis at cut point of five years+...... 116

Table 37- Pearson Correlations between CD-FAB and CDQol scores+ ...... 120

Table 38- Deeper look at CD-FAB total scorers and difference between overall ...... 121

Table 39 -Pearson Correlations between CD-FAB and STAI scores+ ...... 122

Table 40- Total CD-FAB Scores and Subscales by state anxiety+ ...... 123

Table 41- Total CD-FAB Scores and Subscales by trait anxiety+ ...... 124

Table 42 -Pearson Correlations between CD-FAB and CESD scores+ ...... 126

Table 43- Total CD-FAB Scores and Subscales by depressive symptoms+ ...... 127

Table 44-QoL associated with CD-FAB total and subscale scores including COVID-19 status 129

Table 45-Anxiety and depression associated with CD-FAB total and subscale scores

including COVID-19 status ...... 131

Table 46- CD-FAB Total scores tertiary split+ ...... 132

Table 47- Demographic characteristics of study sample pre and during COVID-19 ...... 134

Table 48- Demographic characteristics of study sample pre and during COVID-19 ...... 135

Table 49- Total survey mean scores pre- and during- COVID-19 pandemic ...... 139

List of Figures

Figure 1-Proposed Framework for disordered eating attitudes and behaviors leading to eating

disorders (as per EDDS) disordered eating (as defined by EPSI) in CeD based on the CD-

FAB (adapted from (H. B. Murray et al., 2020) ...... 6

Figure 2- Disordered Eating Spectrum (adapted from (Grilo, 2006) ...... 26

Figure 3-Two Pathway model between GI disorders and disordered eating (R. Satherley et al.,

2015) ...... 34

Figure 4- Revised Pathway model of disordered eating to adapt to CeD (R. M. Satherley et al.,

2017) ...... 39

Figure 5- Study Flow ...... 76

Figure 6- CD-FAB Scores Frequency Distribution ...... 87

Figure 7- Framework for disordered eating attitudes and behaviors leading to eating disorders

and disordered eating in CeD based on the CD-FAB (adapted from (H. B. Murray et al.,

2020) ...... 145

Acknowledgements

First, I would like to express my deepest gratitude for the support I have received from the Mary Gwendolyn Laidlaw Endowed Scholarship Fund for making my journey at Teachers

College possible.

I would like to express my appreciation to my committee members, for all their time, guidance and contribution towards this dissertation.

I would like to express my deepest gratitude to:

Dr. Randi Wolf, my role model and mentor, for her invaluable advice, her continuous support and understanding throughout my time at Teachers College.

Dr. Isobel Contento for all her guidance, support and for believing in me and encouraging me to apply to the Behavioral Nutrition program at Teachers College.

Dr. Anne Lee, for all her guidance and support, and without whom I would not have been able to complete this research.

Dr. Pamela Koch, for all her help, support and words of encouragement.

Dr. Janet Schebendach, for all her advice, and for constantly answering all my questions about eating pathologies.

Pat Zybert and Nicholas Anderson for their incredible statistical help and guidance.

Voula Simhairi and Deborah Olarte, my fellow doctoral candidates and dear friends for all their support since day 1 at Teachers College.

All the PhD/EdD graduates and candidates I have had the chance to meet in this program, thank you for your beautiful and long-lasting friendships.

xii

I would also like to thank my amazing family for their love, constant encouragement and support throughout.

Mom, thank you for your unconditional love, countless sacrifices and for always pushing me to learn more. Thank you for believing in me my entire life, you are my rock.

Tatiana and Shawki, thank you for having been there for me, for encouraging me throughout this journey, for your constant support, cheering and for being the best brother and sister anyone can ask for.

Jeff, my dear partner, thank you for having been so supportive, encouraging, patient and understanding these past few months, I am grateful for your beautiful soul and kind heart.

Dad, my guardian angel, if it wasn’t for you, I wouldn’t be where I am today. Thank you daddio, for encouraging me to be the best that I can be. Your guiding hand on my shoulder, I’ve held on to it forever. You left so suddenly, and it was very difficult to finish this journey without you. But the thought of making you proud is what kept me going, this is for you Pap.

xiii

Dedication

To my beloved late father, who followed most of this journey with me,

constantly encouraging me, and

anticipating calling me Dr. Gholmie

xiv

Chapter 1 – Introduction

This chapter provides an overview of the background, rationale and significance of the

Celiac Disease and Disordered Eating Behavior Study. The purpose of this study was to explore the intersection of celiac disease (CeD) and eating attitudes and behaviors of 50 adults (ages 18 –

45 years) with biopsy-proven CeD.

CeD affects about 1% of the population in the United States (Rubio-Tapia, Ludvigsson,

Brantner, Murray, & Everhart, 2012). The prevalence has increased up to five-fold since 1950, and diagnosis rates continue to rise, a consequence of increased prevalence and improved awareness and testing (Lohi et al., 2007; Rubio-Tapia et al., 2009; Rubio-Tapia et al., 2012).

CeD is a genetically mediated autoimmune disease in which exposure to gluten causes destruction to the villous architecture of the small intestine. This results in malabsorption of nutrients and can impact almost any organ system and have multiple long-term negative effects

(Reinhardt & Fanzo, 2014). Morbidity can be severe. If untreated, CeD is associated with bone loss, infertility, neuropathy and neuropsychiatric symptoms, other autoimmune conditions, and malignancies (Cellier, Flobert, Cormier, Roux, & Schmitz, 2000; P. H. Green & Jabri, 2006; J.

A. Murray, 1999). CeD is also associated with a small, but increased mortality (Benjamin

Lebwohl, Green, Söderling, Roelstraete, & Ludvigsson, 2020).

The only treatment for CeD to date is lifelong adherence to a gluten-free diet (GFD) (J. F.

Ludvigsson et al., 2014; Rubio-Tapia, Hill, Kelly, Calderwood, & Murray, 2013). For individuals with CeD, maintaining a strict GFD requires increased control around food. 1

Behaviors and attitudes that are important components of strict GFD management may place an unhealthy emphasis on food intake resulting in disordered eating attitudes and behaviors (R. M.

Satherley, Higgs, & Howard, 2017). Reports and recent research suggest that the challenges of managing a GFD may lead to anorexic or bulimic eating behaviors (Marild et al., 2017). What is not known is the extent of disordered eating behaviors, which may be far greater than clinical eating disorders (ED), as well as factors that predict which individuals with CeD are most susceptible. There is an urgent need to provide guidance to clinicians treating individuals with

CeD on how to assess and manage patients that may be at high risk for disordered eating attitudes and behaviors while still advocating for long-term GFD adherence and quality of life

(QoL).

A central hypothesis in this research study is that disordered eating attitudes and behaviors are likely common in adults with CeD on a strict GFD. Using a cross-sectional study, the primary objective of this research was to examine the prevalence of disordered eating attitudes and behaviors in a sample of adults with CeD, as measured by a recently validated

Celiac Disease Food Attitudes and Behaviors Scale (CD-FAB). A second objective was to examine the association between the CD-FAB scores and QoL, including anxiety and depression.

The association between CD-FAB and personality characteristics, GI symptoms, gluten-free diet adherence, and body composition will also be examined.

1.1 Background & Rationale

Maintaining a strict GFD requires vigilance and control around food, and this increased vigilance has been linked to diminished QoL (Cranney et al., 2007; A. R. Lee, Ng, Diamond,

Ciaccio, & Green, 2012; Wolf et al., 2018). Although the mechanisms are unclear, studies have investigated the association between CeD and ED. One hypothesis is that some individuals experience distress in response to weight gain associated with their diagnosis and implementation of the prescribed GFD. Because they may feel the GFD is causing the unwanted weight gain, purposeful gluten ingestion may lead to restrictive or bulimic eating behaviors (R.

M. Satherley et al., 2017). Another hypothesis is that patients who are highly compliant with the

GFD and experience resolution of symptoms, anxiety around gluten cross contamination may lead to limited food choices or eating only in situations with complete control over food preparation, which, in turn, may lead to disordered eating attitudes and behaviors (R. Satherley,

Howard, & Higgs, 2015; Sverker, Hensing, & Hallert, 2005).

After diagnosis, once a GFD is initiated the intestines begin to heal and most individuals’ report resolution of symptoms. Despite these improvements, a strict GFD must be maintained

(Cranney et al., 2007; A. R. Lee et al., 2012; Wolf et al., 2018). Lee et. al. found that QoL was significantly negatively impacted in individuals on a GFD, in particular dining out, social events, work related meals, and travel (A. R. Lee et al., 2012). Cranney et al. found that 81% of individuals reported that they no longer dine out, 91% brought their own food when traveling and 38% avoided travel due to the difficulty of maintain a GFD (Cranney et al., 2007). Wolf et. al found that a higher dietary vigilance to a GFD was associated with lower QoL in adults.

Participants also reported the burden of the restrictive nature of the diet (Wolf et al., 2018). In a qualitative study by Sveker participants reported feeling isolated, always thinking about food, and concerns over the safety of their food (Sverker et al., 2005).

As various studies have reported a diminished QoL associated with CeD and the GFD, researchers are now investigating if this negative impact may have a farther-reaching impact, 3

including psychological aspects, such as ED and association with depression (Hauser, Janke,

Klump, Gregor, & Hinz, 2010; Zingone et al., 2015). In a review, Zingone et. al found that CeD has significant psychological impacts on anxiety, depression, and fatigue. Anxiety and depression may be ongoing and may affect dietary adherence; consequently, affecting overall

QoL (Zingone et al., 2015).

Recent studies have investigated the association between CeD and ED (Hauser et al.,

2010; Zingone et al., 2015). However, the presence of disordered eating attitudes and behaviors was not investigated; neither was the association with the rigid nature of the GFD, the burden of dietary adherence and the constant vigilance needed to avoid chance gluten exposure. Many professionals and researchers in the gastroenterology field have recognized that a number of patients with CeD have ED that interact with their presenting GI related symptoms. The literature is increasing on the possibility of cross over behaviors with CeD and ED; while the percentage of true ED is 1% of the population, the observed disordered eating attitudes and behaviors in CeD patients may be reflecting the newly accepted diagnosis of avoidant/restrictive food intake disorder (ARFID), which is also a diagnosis of ED in the Diagnostic and Statistical

Manual of Mental Disorders, 5th edition (DSM-5).

ARFID is a relatively new diagnosis added to the “Feeding and Eating Disorders” section of the DSM-5. The DSM-5 describes ARFID as an eating or feeding disturbance that results in persistent failure to meet nutritional needs and is associated with weight loss, nutritional deficiency, dependence on nutritional supplementation, or marked interference with psychological functioning. The feeding disturbance is presented as a lack of interest in eating or food, and that is based on the sensory characteristics of food and or concern about aversive consequences of eating (Diagnostic and statistical manual of mental disorders : DSM-5, 2013; 4

Tsang, Hayes, & Cammarata, 2020). Depression, anxiety, and fear of negative consequences from eating that are observed in individuals with GI disorders or CeD are considered psychosocial impairments related to eating/feeding problems.

ARFID amongst patients with GI symptoms is a subject of growing interest among many researchers. ARFID and Disorders of Gut-Brain Interaction (DGBI) symptoms seem to overlap making difficult to understand which is the cause and which is the effect. In a recent retrospective study, charts of patients undergoing neurogastroenterology examinations showed that ARFID symptoms are most frequently associated with fear of GI symptoms. In other words, patients diagnosed with ARFID with a fear of aversive consequences tend to restrict eating to prevent GI symptoms such as abdominal pain, diarrhea, nausea, etc. (H. B. Murray et al., 2020).

Another study showed that up to 70% of patients with functional gastrointestinal disorders

(FGID) restrict their diet (Zia, Riddle, DeCou, McCann, & Heitkemper, 2017). In the GI field, there is an increasing recognition that GI patients can have ED or disordered eating attitudes and behaviors when presenting with GI disorders. While the current study was not designed to determine prevalence of ARFID, findings may help to better understand the characteristics of patients with CeD that may be at increased risk in the future.

In a recent study of adolescents with CeD (13-17 years old) following a GFD for at least one year recruited from an urban CeD referral center, it was found that approximately half the sample (53.3%) expressed more maladaptive approaches to maintaining a GFD and those who did so, were older with lower CeD-specific pediatric QoL scores (Cadenhead et al., 2019). Those with maladaptive eating approaches were defined as those that showed greater rigidity, avoidance, and controlling behavior in how they managed a GFD (Cadenhead et al., 2019).

Cadenhead et al.’ study was limited in that it did not use validated measures of eating disordered 5

behaviors. Therefore, a modified framework is proposed to study disordered eating attitudes and behaviors leading to eating disorders (ED) (as per suggestive diagnosis of EDDS) and disordered eating (DE) pathologies (as defined by the EPSI tool) in CeD based on the CD-FAB tool (Figure

1). The EDDS is a brief self-report measure designed for diagnosing AN, BN, and BED based on the DSM-IV. The Eating Pathology Symptoms Inventory (EPSI) queries an individual’s multidimensional eating pathology. It is a 45 item self-report measure that is designed to assess the psychopathology of eating disorders (disordered eating and cognitions).

Figure 1-Proposed Framework for disordered eating attitudes and behaviors leading to eating disorders (as per EDDS) disordered eating (as defined by EPSI) in CeD based on the CD-FAB (adapted from (H. B. Murray et al., 2020)

Satherley et al. explained that those who score high on the CD-FAB may display a hypervigilance around food and limit food intake, not for weight loss but because they believe that food is dangerous to their health and may encourage gastrointestinal symptoms (R.-M.

Satherley, Howard, & Higgs, 2018). Vigilance around food cross-contact is important for patients with CeD. However, hypervigilance can become dysfunctional and may negatively impact physical and psychosocial well-being (R. M. Satherley et al., 2017)

The framework (figure 1) proposes that adults with CeD that are very adherent, extremely vigilant to their GFD may often avoid consumption of any foods prepared by others. Strict rigidity is tough, therefore they may at some point encounter relaxation of rigidity to the GFD and allow themselves to consume GF foods prepared by others. After eating, they may feel GI symptoms; the symptoms could be related to the food but might also be related to dysfunctional illness beliefs (overestimating negative consequences and holding on to the belief that all foods have cross contamination potential). They may worry that the food they consumed, prepared by others, contained gluten. In this case, greater rigidity, avoidance and controlled behavior to GFD is applied. Awareness or vigilance around food is important for CeD patients on a GFD, however this greater rigidity around food may lead to increased disordered attitudes and behaviors and may result in DE (as defined by the EPSI tool). And in order to understand how patients with

CeD develop disordered eating attitudes and behaviors from adaptive coping mechanisms,

Satherley et al. developed the Celiac Disease food attitudes and behaviors scale (CD-FAB) (R.-

M. Satherley et al., 2018). The CD-FAB helps in identifying disordered eating attitudes and behaviors resulting from beliefs around cross-contamination and food safety. The validated tool may be used either to evaluate the effectiveness of interventions on eating patterns or behaviors that will help identify people requiring additional clinical support (R.-M. Satherley et al., 2018). 7

The CD-FAB is a self-report, reliable and valid questionnaire composed of eleven questions measuring disordered eating attitudes and behaviors in CeD. Answers give an overall score, as well as three clinically relevant subscales: food attitudes, fear response and adaptive response. It is a useful tool for clinicians as it helps understand disordered eating attitudes and behaviors when treating adults with CeD (R.-M. Satherley et al., 2018).

1.2 Purpose of Study

The purpose of this study was to better understand the extent to which disordered eating attitudes and behaviors may be common in a sample of adults diagnosed with CeD, as well as the relationship of disordered eating attitudes and behaviors with various QoL measures, including anxiety and depression (see Figure 1). Long-term, the goal is to create a new paradigm for managing clinical disease by understanding how best to assess and target those that may be at greatest risk for EDs and associated morbidities. This study expands the literature because although recent studies have investigated the association between CeD and ED (Hauser et al.,

2010; Zingone et al., 2015); the presence of disordered eating attitudes and behaviors has not been investigated neither was the association with the rigid nature of the GFD, the burden of dietary adherence and the constant vigilance needed to avoid chance gluten exposure. Many professionals and researchers in the gastroenterology field have recognized that a number of patients with CeD have ED or DE that interact with their presenting GI related symptoms. DE are defined as dysfunctional eating pathologies that are outside of eating behaviors that can be diagnosable under the DSM-V. However, the observed DE in CeD patients may be reflecting the newly accepted diagnosis of avoidant/restrictive food intake disorder (ARFID), which is also a

diagnosis of ED in the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-

5).

1.3 Research Questions

Fifty adults aged 18 – 45 with biopsy confirmed CeD were recruited from the Celiac Disease

Center at Columbia University Irving Medical Center to form the study group. Consecutive age- eligible individuals with known CeD were asked to participate at the Celiac Disease Center while they waited for their doctors’ appointments. Those interested and eligible were asked to complete a variety of surveys related to eating patterns and QoL and had anthropometric measures taken. The following research questions guided the research inquiry:

- RQ1a: In adults (18 – 45 years old) with CeD, how common are eating disorders as

measured by the Eating Disorder Diagnostic Scale (EDDS)?

- RQ1b: In adults (18 – 45 years old) with CeD, how common are disordered eating as

measured by Eating Pathology Symptoms Inventory (EPSI)?

- RQ2: In adults (18 – 45 years old) with CeD, how common are disordered eating

attitudes and behaviors in CeD based on the CD-FAB?

- RQ2a: In adults (18 – 45 years old) with CeD, does the CD-FAB demonstrate construct

validity as compared to the EPSI?

- RQ3: In adults (18 – 45 years old) with CeD, what are factors (demographics, personality

characteristics, GI symptoms, gluten-free diet adherence, body composition) associated

with disordered eating attitudes and behaviors (as measured by CD-FAB)?

- RQ4: In adults (18 – 45 years old) with CeD, are disordered eating attitudes and

behaviors (as measured by the CD-FAB scores) associated with QoL, anxiety, and

depression?

1.4 Significance and Implications

Clinicians treating individuals with CeD urgently need guidance on how to assess and manage patients that may be at high risk for an ED and/or disordered eating attitudes and behaviors while still advocating for strict adherence to a GFD and maintaining QoL.

This study may also have applications to other conditions with very restrictive diets (e.g., allergies, intolerances, other GI conditions, etc.)

The results of these surveys will provide clinicians information about the prevalence of

ED and disordered eating attitudes and behaviors as well as the association of these eating behaviors to QoL, psychological aspects (depression, anxiety and personality traits) as well as dietary adherence in adults with CeD.

Disordered eating attitudes and behaviors in CeD adults may be classified under ARFID, diagnosis in DSM-5. However, there are no screening tools available yet, and clinicians in gastroenterology clinics would need guidance on how to identify those who might be at risk.

When screened early, clinicians have the potential to improve CeD patient’s QoL, and decrease burdens on the medical system. When a CeD patient with ARFID is identified, a referral to a behavioral health provider such as a psychologist (preferable a specialist in GI disorders) will be required.

1.5 Scope and delimitations

This study has several limitations. Participants recruited for the study are patients at the

Celiac Disease Center at Columbia University Irving Medical Center (CUIMC) that had scheduled appointments with their gastroenterologist and/or dietitian. Patients primarily come from New York as well as New Jersey and Connecticut.

The limitation lies in that the sample may not be generalizable to other states or other patients with CeD in other parts of the country. The sample may also not be generalizable to those with CeD not seeking medical care at a Celiac Referral Center. The study only recruited adults between the ages of 18 to 45 years, adolescents and older adults with CeD were not included in this study. The study limited participants to those with biopsy-diagnosed CeD, which excluded those with gluten intolerance or sensitivity. Finally, participants with a previous diagnosis of an ED were also excluded from the study.

1.6 Definition of Terms

AN: Anorexia Nervosa

ARFID: Avoidant/Restrictive Food Intake Disorder

BN: Bulimia Nervosa

BED: Binge Eating Disorder

BIG-5: Big-5 Personality Trait Test

CeD: Celiac Disease

CDAT: Celiac Dietary Adherence Test

CD-QoL: Celiac Disease Quality of Life

CDP-QoL: Celiac Disease Pediatric Quality of Life 11

CDSD: Celiac Disease Symptoms Diary

CES-D: Center for Epidemiological Studies Depression Sale

CES-DC: Center for Epidemiological Studies Depression Sale for Children

DE: Disordered Eating

DGBI: Disorders of Gut- Brain Interaction

DSM-5: Diagnostic and Statistical Manual of Mental Disorders, 5th edition

ED: Eating Disorders

EDDS/DSM-5: Eating Disorder Diagnostic Scale

EPSI: Eating Pathology Symptoms Inventory

ESRD: End Stage Renal Disease

FNS: Food Neophobia Scale

GERD: Gastroesophageal Reflux Disease

GFD: Gluten Free Diet

HTN: Hypertension

QoL: Quality of Life

OED: Other Eating Disorders

RDN: Registered Dietitian Nutritionist

STAI: State-Trait Anxiety Inventory

Chapter 2 – Review of the Literature

This chapter provides a brief review of CeD, factors associated with GFD adherence, and potential increased risk for disordered eating and QoL issues.

2.1 Celiac Disease

2.1.1 Definition.

Celiac disease (CeD) is a multisystem disease, in which the major site of injury is the gastrointestinal tract. This genetically mediated autoimmune disease is the most underdiagnosed.

The exposure to gluten causes destruction to the villous architecture of the small intestine, where nutrients needed to survive are absorbed (P. H. Green & Jabri, 2003; P. H. R. Green & Jones,

2016). The clinical presentation of symptoms may vary on a spectrum from asymptomatic to severe malabsorption (A. R. Lee et al., 2012). The major environmental factor responsible for the development of CeD is gluten. Gluten is the term for the prolamin storage proteins found in wheat, rye, and barley.

2.1.2 Prevalence.

CeD occurs in about 1% of people in most populations (Caio et al., 2019; Gujral,

Freeman, & Thomson, 2012; B. Lebwohl, Sanders, & Green, 2018). This would represent approximately 3 million people affected in Europe and at least an additional 3 million in the

United States (Fasano & Catassi, 2012; Rodrigo, 2006). CeD prevalence has increased up to 5- fold in the United States since 1950, and diagnosis rates continue to rise, a consequence of both 13

increased prevalence and improved awareness and testing (Lohi et al., 2007; Rubio-Tapia et al.,

2009; Rubio-Tapia et al., 2012). It was believed that CeD presented around childhood, yet now it is known to affect people of any age. The diagnosis can be made at any point across the life cycle, but it is more common between the ages of 40 to 60. Like other autoimmune disorders,

CeD arises more frequently in women than men, presenting a diagnosis ratio of 2:1 (Fasano &

Catassi, 2012; Rashtak & Murray, 2009). Long delays in diagnosis of CeD are mainly due to the lack of awareness of its wide diversity of clinical presentations (Fasano & Catassi, 2001;

"National Institutes of Health Consensus Development Conference Statement on Celiac Disease,

June 28-30, 2004," 2005). CeD prevalence is also higher in first degree relatives and in patients with Down Syndrome, type 1 diabetes mellitus or IgA deficiency (Fasano & Catassi, 2012).

2.1.3 Pathophysiology.

The key genetic elements (human leukocyte antigen (HLA)-DQ2 and HLA-DQ8), the auto-antigen (tissue transglutaminase (tTG), and the environmental trigger (gluten) are well defined which categorizes CeD as a unique autoimmune disease (Caio et al., 2019). However, similarly to other autoimmune diseases, there is a strong hereditary component associated with

CeD. This is justified by the high prevalence of CeD familial recurrence (10-15%) as well the high occurrence of the disease in monozygotic twins (75-80%) (Caio et al., 2019; Lundin &

Wijmenga, 2015).

Gluten-containing grains, such as wheat, barley and rye, were introduced to the human diet about 10,000 years ago when humans transitioned from a nomadic lifestyle to agricultural settlements (Caio et al., 2019). There are few proteins that are resistant to digestion, gluten

(made of proteins such as glutenins and gliadins) is one of them and it is consumed in substantial quantities(Caio et al., 2019). Consuming gluten containing grains, leads to an inflammatory response by the body’s own cytokines and T cells in the small intestine leading to mucosal lining damage and malabsorption of nutrients, vitamins and minerals (Caio et al., 2019; Castillo,

Theethira, & Leffler, 2015; Jelínková, Tucková, Cinová, Flegelová, & Tlaskalová-Hogenová,

2004; Lammers et al., 2011; Picarelli et al., 1999; Shan et al., 2002).

2.1.4 Presentation and Risk Factors.

CeD presented severe symptoms which include chronic diarrhea, abdominal distension, and failure to thrive. The onset of CeD symptoms may not develop until later in life; the spectrum of symptoms is wide and extends from severe malabsorption with profound nutritional deficiencies to asymptomatic (A. R. Lee et al., 2012; Rashtak & Murray, 2009). The disease symptoms may include fatigue, diarrhea, weight loss due to malabsorption, anemia, and neurological symptoms (B. Lebwohl et al., 2018). CeD affects multiple systems in the body and can manifest with a variety of symptoms and health problems, including diarrhea, weight loss, anemia, osteoporosis, cancer, depression and other autoimmune diseases (Abu Daya, Lebwohl,

Lewis, & Green, 2013; Caio et al., 2019; Fasano & Catassi, 2012; P. H. R. Green, Krishnareddy,

& Lebwohl, 2015; Rashtak & Murray, 2012). It can also be expressed as a skin rash, dermatitis herpetiformis (DH, Duhring’s disease), a chronic autoimmune skin condition characterized by the presence of severely itchy blisters and raised red skin lesions. Other signs include tooth enamel defects and hypertransaminasemia, and a wide array of neurological symptoms

(headache, paresthesia, neuroinflammation, anxiety and depression). A diagnosis of CeD can be in question when a child presents with growth retardation and short stature (Caio et al., 2019). 15

Moreover, there is increasing evidence that CeD diagnosis can be associated with cognitive deficits (“brain fog”) which denotes to a series of symptoms ranging from cognitive slowing, difficulty concentrating to problems with short and long-term memory (Croall et al., 2020).

In summary, symptoms can be present either in the intestinal form or extraintestinal.

When symptoms of malabsorption are manifested (including diarrhea, malnutrition and growth failure), patient presents with classical CeD. Patients without symptoms of malabsorption present with nonclassical CeD (Cichewicz et al., 2019; Jonas F. Ludvigsson et al., 2013).

Many diseases, autoimmune and idiopathic diseases, can be associated with CeD (type 1 diabetes mellitus, Hashimoto’s thyroiditis, selective IgA deficiency, alopecia areata, Addison’s disease chromosomal diseases, etc.). When patients present with dermatitis herpetiformis, testing for CeD should take place.

Some of the diseases associated with CeD, as well as symptoms associated with CeD are resolved once the patient starts following a GFD (Caio et al., 2019; Croall et al., 2020; Volta,

Caio, Stanghellini, & De Giorgio, 2014).

2.1.5 Guidelines for Diagnosis.

The standard diagnosis for CeD is a combination of positive duodenal biopsy (to detect mucosal changes) and positive serological tests for anti-tTG antibodies, anti-endomysium antibodies (EmA) and deamidated gliadin peptide (DGP) antibodies (Caio et al., 2019;

Cichewicz et al., 2019). To date, no antibody test will provide 100% sensitivity and specificity which calls for the need to have an intestinal biopsy in order for a correct diagnosis of CeD to be

made (Caio et al., 2019; Cichewicz et al., 2019). The sensitivity and specificity of these tests vary from one manufacturer to another (Cichewicz et al., 2019)

In the pediatric population, positive serological tests with over 10 times the cut-off for antibodies in combination, are sufficient for a diagnosis of CeD in symptomatic children without a positive family history (no duodenal biopsy is required) as per the guidelines presented by the

European Society for Pediatric Gastroenterology Hepatology and Nutrition (ESPGHAN) (Husby et al., 2012).

In a recent study, it was shown that the combination of positive anti-tTG (over 10 times the cut-off), EmA and HLA-DQ2/HLA-DQ8 (triple criteria) was accurate enough to diagnose patients with CeD in adults (Fuchs et al., 2019). Yet, several studies have reported that serology alone is not suboptimal to diagnose a patient with CeD, positive serology should be used in accordance with a positive biopsy in order to confirm a diagnosis of CeD (Caio et al., 2019;

Cichewicz et al., 2019). However, in selective patients only, biopsy may be avoided, and diagnosis is based solely on signs/symptoms and positive serology (Cichewicz et al., 2019).

In a US survey, slightly over half (57%) of patients with reported CeD (1832 patients) indicated that they were diagnosed by a gastroenterologist (Hughey et al., 2017). Other studies have shown that a correct diagnosis of CeD by a gastroenterologist can often be delayed by several years (Cichewicz et al., 2019). In 101 US patients with CeD, patients with biopsy supported CeD and no gastrointestinal complaints (no GI symptoms) had a median diagnostic delay of 3.5 years (49%); whereas patients who presented with GI symptoms had a delay of 2.3 months (51%) (Paez, Gramelspacher, Sinacore, Winterfield, & Venu, 2017). The under and delayed diagnosis of CeD can be explained by the lack of awareness of its wide diversity of

clinical presentations and a deficit in the access to gastroenterology specialists, the same applies for follow up care of these patients (Cichewicz et al., 2019; Fasano & Catassi, 2001).

2.1.6 Diet and complications.

Currently, adherence to a strict GFD is considered the first and only treatment in line for

CeD, which has been proven to relieve the symptoms in most cases and effectively prevent potential complications (Caio et al., 2019; Czaja-Bulsa & Bulsa, 2018; J. F. Ludvigsson et al.,

2014; Rashtak & Murray, 2012; Rubio-Tapia et al., 2013). The GFD resulted in clinical

(resolution of intestinal and extraintestinal symptoms), serologic (negativity of autoantibodies), and histologic (regrowth of intestinal villi) improvement (Caio et al., 2019; Catassi et al., 2007;

Rashtak & Murray, 2012). A strict GFD leads to partial protective effect concerning other potential complications of the disease (Caio et al., 2019). Yet, the only effective treatment available to date holds some disadvantages. The GFD imposes psychological stress on patients, not being able to eat out easily, the constant search for gluten free foods, the inconveniences faced in school, work and social settings can lead to isolation and stigmatization. Studies have shown that it has a negative impact on QoL, it can lead to the devolepment of psychological problems (such as low self esteem), there is a constant fear of cross-contamination and possible nutrition deficiency(Caio et al., 2019; da Conceição et al., 2020). Babio et al. showed that patients with CeD followign a GFD tend to have a more unbalanced diet then healthier controls.

Participants with CeD reported higher consumptipon of added sugar and total fat than non-CeD participants(Babio et al., 2017). The GFD implicates no gluten containing breads, flour, pasta or other foods that are usually the main source of energy, carbohydrates, and some essential micronutrients (iron, calcium, zin, magnesiusm and B vitamins) (Babio et al., 2017; de la Calle, 18

Ros, Peñalver Miras, & Nieto, 2020). Many studies have shown that there is an association between nutritional deficiency and restricitve diets such as the GFD (Kinsey, Burden, &

Bannerman, 2008). It is difficult to sustain a proper lifestyle without imposing major limitations o every day life while trying to adhere to the restrictive GFD (Babio et al., 2017; Kinos et al.,

2012).

2.1.7 GFD adherence and burden.

Contrary to fully adherent patients, nonadherent or partially adherent patients conveyed more abdominal bloating and fatigue (Barratt, Leeds, & Sanders, 2013; A. Sainsbury, Sanders, &

Ford, 2013). The persistence of villous atrophy is less frequent when patients report strict adherence to their diets. (Orlando et al., 2018). However, in one study (A. Lee & Newman,

2003), endoscopic biopsies showed that villous atrophy and chronic inflammation was still present despite a reported adherence to the GFD, which is suggestive of the difficulty of gluten avoidance. Shah et al. showed that CeD patients reported higher burden to the disease treatment

(strict GFD) compared to patients with gastroesophageal reflux disease (GERD) and hypertension (HTN) and equal burden to end stage renal disease (ESRD)(Shah et al., 2014).

Another study showed that the burden of GFD was comparable to that of type 1 diabetes mellitus

(Villafuerte-Galvez et al., 2015). Patients with CeD following dietary therapy who present with continuing symptoms seem to still have some gluten exposure (D. Leffler et al., 2007; Daniel A

Leffler et al., 2007). In a systematic review, Hall et al. showed that strict adherence rate in individuals aged 16 and older, have been reported to vary between 42 and 91% based on survey data (Hall, Rubin, & Charnock, 2009). Gluten-free foods are typically more costly than their

gluten containing counterparts, they are not always available in all settings and often offer less than optimal nutritional value (Babio et al., 2017; Villafuerte-Galvez et al., 2015). Factors influencing gluten-free diet adherence in adults in the US have been studied and presented in

Table 1 [Table 1 is adapted from (Cichewicz et al., 2019)].

Shah et al’s study showed that poor adherence to the diet was associated with low income, unemployment, current symptoms, patient’s perceived importance and burden of the

GFD (Shah et al., 2014). CeD patients who reported high burden of the treatment were more likely to adhere poorly to the diet, except for those who reported high household income. An assumption was made to explain the high burden of the diet, one with association to low education, and on the other hand to increased traveling and social outings in those with high income (Shah et al., 2014).

Adhering to a GFD means preventing the consumption of even small amounts of foods derived from wheat, rye or barely (D. Leffler et al., 2007). Individuals with CeD must learn what foods they can eat, what foods they have to avoid, what are hidden sources of gluten, how to read food labels and how to manage eating at restaurants and social situations (Wolf et al., 2018). The costly and restrictive aspect of complying with a life-long GFD may have a significant adverse impact upon the QoL of the patients. The economic burden of the GFD has been previously reported, gluten free foods have poor availibility and are more expensive than their gluten- containing coutnerparts (A. R. Lee, Ng, Zivin, & Green, 2007). Maintaining a GFD and lifestyle has a substantial financial and psychological burden on patients and their families, and a recent study has shown that the ripple effect of the GFD on the patient’s family is often unnoticed

(Russo et al., 2020).

It is important for clinicians to have an accurate measure of CeD patient’s adherence to the diet. In a prospective study looking at measures of GFD adherence in adults with CeD,

Leffler et al. explains that adherence has been gauged in a number of ways (D. Leffler et al.,

2007). Examples of the most common measures are self-reports by patients (likert scales, visual analogue scales, etc.), dietary history (24 hour recalls, food frequency questionnaires, etc.), nutritionist’s evaluation, serologic screening tests, and biopsies (D. Leffler et al., 2007). It is important to note that self-reported dietary adherence has its limitations, reporting is not always accurate leading to possible inaccurate reporting of level of adherence whether its intentional or not (D. Leffler et al., 2007).

Table 1- Factors influencing GFD adherence in adults in the US (adapted from Cichewicz et al. 2019)

Adults with greater adherence Adults with less adherence to the GFD (Jonas F. Ludvigsson et al., 2013; Rubio-Tapia et al., 2013; (Jonas F. Ludvigsson et al., 2013; Rubio-Tapia et Tonutti & Bizzaro, 2014) al., 2013; Tonutti & Bizzaro, 2014)

- Belief that purposeful gluten exposure has - High costs of GF foods important health consequences - Perceived inability to follow diet - Belief that accidental gluten exposure has important - Negative perception of own knowledge health consequences - Lower educational level - Reported greater understanding of GFD - Income <$200,000 - Greater ability to follow GFD when traveling - Increased severity of current symptoms - Greater ability to follow GFD when dining out - Lower perceived importance of - Greater ability to follow a GFD at social events treatment - Greater comfort in following a GFD at work - Belief that avoiding gluten is important for health - Ability to follow a GFD regardless of mood

(D. Leffler et al., 2007; Shah et al., 2014; Villafuerte-Galvez et al., 2015)

2.1.8 Quality of life (QoL) in Individuals with CeD.

QoL studies in CeD have markedly increased, the dilemmas experienced by teenagers and adults in their everyday lives in relation to their CeD were explored by many. Nachman et al. 21

assessed differences in QoL of patients at diagnosis and showed that treatment with a GFD improved QoL scores after 3 months (Nachman et al., 2009). Green et al. assessed patient’s perception on QoL and found that adults with CeD reported that QoL post-diagnosis and treatment with GFD improved by 77% compared to pre-diagnosis (P. H. R. Green et al., 2001).

When comparing asymptomatic patients at diagnosis (diagnosed through screening of at-risk groups, relatives of individuals who have been diagnosed with CeD) to symptomatic patients at diagnosis some studies have reported lower QoL in symptomatic patients compared to their asymptomatic counterparts (Johnston, Rodgers, & Watson, 2004; Jonas F Ludvigsson et al.,

2015; Nachman et al., 2009; Zingone et al., 2015). And similar QoL and disease adherence in asymptomatic and symptomatic patients’ post-treatment (Mahadev, Gardner, Lewis, Lebwohl, &

Green, 2016; Nachman et al., 2009). After diagnosis, studies have shown that low QoL is associated with the difficulty of having a chronic condition, the limitation enforced by the treatment and the struggle of adhering to the GFD. Patients that are less or non-adherent to the

GFD have lower QoL compared to adherent patients (Jonas F Ludvigsson et al., 2015; Marsilio et al., 2020; Zingone et al., 2015). Adherence to the GFD has been shown to be associated with a negative impact on QoL. Yet, some studies reported that this association may be more complicated and may depend on perceived, rather than actual success of dietary adherence

(Barratt, Leeds, & Sanders, 2011; Croall et al., 2020).

Sverker et al. found dilemmas experienced by adults’ women and men in five different areas which take into account food situations at work, during purchases, when travelling, and in relation to meals consumed with other people at home or outside the home. In addition, dilemmas that reflected strong emotions, for example isolation, shame and fear were also reported (Sverker et al., 2005). 22

In a study by Lee et al., 45% of adult (18 years and above) respondents reported that their physical health affected interaction with family, friends or social groups. The negative impact was found to be most strongly associated with the social domain of QoL, in particular dining out, social events, work related meals, and travel (A. R. Lee et al., 2012). Amongst the respondents who had been diagnosed for 2 to 5 years from the time they filled out the surveys, 25% of the females and 28% of the males chose not to dine out at all (A. R. Lee et al., 2012). In Lee et al.’s study, adults reported intentionally going off the diet at social activities and restaurants 85% of the time, and 63% with friends despite reporting high degree of compliance. Reasons for noncompliance with the necessary GFD was the nature of the diet being too restrictive, tasteless, too uncomfortable to follow in social settings, and too expensive (A. R. Lee et al., 2012). Wolf et al. showed that “extreme vigilance” to the strict GFD was associated with potential negative consequences and hence lower QoL than the less vigilant. Adults most hypervigilant about their diet showed more dysphoria, more reported limitations and more concerns about inadequate treatment. Extreme vigilance was also associated with greater knowledge and greater precautions to avoid all sources of gluten (Wolf et al., 2018).

The diminished QoL associated with CeD and the GFD especially in those with higher dietary adherence scores, raises concern about the potential psychological impact including the potential for disordered eating, anxiety, and depression. Zingone et al.’s review indicated that

CeD has a significant psychological impact. That anxiety and depression may be ongoing issues in CeD, and that they may affect dietary adherence and therefore further affect overall QoL

(Hauser et al., 2010; Zingone et al., 2015).

2.1.9 Depression and Anxiety in Individuals with CeD.

Anxiety and depression are common side effects in patients with untreated celiac disease

(Zingone et al., 2015). After diagnosis, and few months after starting a GFD, aspects of these conditions may improve, however some patients continue to suffer from significant psychological morbidity (Zingone et al., 2015). And these psychological symptoms may also play a role in decreased QoL and the dietary adherence of diagnosed patients.

Addolorato et al. explained that a reactive ‘‘state’’ anxiety is increased in patients with

CeD when they are diagnosed, and it was shown to decrease after one year of following a GFD in few studies (Addolorato, 2001; Zingone et al., 2015). While anxiety has been shown to decreases after following a GFD which can be explained by adaptation to the GFD and managing of CeD symptoms, few studies showed that depression is present in a higher percentage in patients after diagnosis and post one year following a GFD (Addolorato, 2001; Zingone et al.,

2015). Zingone et al. showed that anxiety and depression in celiac patients did not improve after following a GFD and Hauzer et al. explained that levels of anxiety were high in patients with

CeD, however no symptoms of depression were found (Hauser et al., 2010; Zingone et al.,

2010). The literature on depression and anxiety in patients with CeD is not consistent (Zingone et al., 2015). However, anxiety and depression after diagnosis and treatment of CeD may be related to the reduced QoL as a result of the restrictions placed by the diet and the burden of living with

CeD (A. R. Lee et al., 2012; Jonas F. Ludvigsson et al., 2018; Zingone et al., 2015). Studies showed that some patients newly diagnosed with CeD can present with sleep disorders, which remains a year after GFD treatment. The latter may be explained by depression and anxiety as well as fatigue reported by CeD patients with low QoL (Croall et al., 2020; Zingone et al., 2010).

A significant association between depression and non-adherence to treatment was found in meta-analyses conducted in other chronic diseases (diabetes, etc.); depressed patients were

1.76 to 3 times less likely to follow treatments compared to non-depressed controls (K.

Sainsbury & Marques, 2018). Depressive symptoms can act as barriers to good adherence leading to poor management of GFD in CeD patients (K. Sainsbury & Marques, 2018).

Sainsbury et al. explained in a recent meta-analysis looking at the relationship between depressive symptoms and/or depression and GFD adherence in adults with CeD that the existing evidence is limited (K. Sainsbury & Marques, 2018). Studies showed that highly self-reported depressive symptoms were associated with lower adherence to the GFD (K. Sainsbury &

Marques, 2018).

In addition, Ludvigsson et al. showed in a recent study that anxiety and depression are more common in CeD patients with mucosal healing, the association may be justified through more vigilant compliance with a GFD (Jonas F. Ludvigsson et al., 2018). Yet, more research is needed to determine the direction of causation between depression and adherence.

2.2 Eating Disorders and Disordered Eating Patterns in CeD

2.2.1 Eating Disorders and Disordered Eating.

The Academy of Nutrition and Dietetics’ explains that the most important focus of healthy eating is the total diet or overall pattern of food eaten; and that all foods can fit within this pattern if consumed in moderation with appropriate portion size and combined with physical activity (Freeland-Graves & Nitzke, 2013). Classifying specific foods as either “good” or “bad” can lead to unhealthy eating behaviors. However, it is suggested that alternative approaches are

necessary in some situations. Eating practices are dynamic and influenced by many factors such as taste and food preferences, time and convenience, environment, abundance of foods, economics, perceived product safety, culture, attitudes/beliefs (Freeland-Graves & Nitzke, 2013) and chronic diseases. Yet, this should not vary to the point that leads to nutrient deficiency or excess weight change; nor should thoughts around planning and preparing food dominate thoughts or dictate behaviors above and beyond that of other daily activities (Freeland-Graves &

Nitzke, 2013). ED and DE can be understood on a spectrum ranging from healthy eating to clinically significant ED (R. M. Satherley et al., 2017), and everything in between (outside of eating behaviors that are diagnosable under DSM-V) can be classified as DE (see figure 2).

Healthy Eating - Typical Eating - Body Acceptance - Healthy Weight Disordered Eating: - Skipping meals - Balanced Diet - Emotional Eating

- Compensatory Eating Disorders: Behaviors - Anorexia Nervosa - Fasting - Bulimia Nervosa - Weight Preoccupation - Other Specified

Feeding and Eating Disorders - Binge Eating Disorder

Figure 2- Disordered Eating Spectrum (adapted from (Grilo, 2006)

2.2.2 Eating disorders.

Eating disorders refer to a range of problems characterized by abnormal eating behaviors and beliefs about eating, weight and shape (Grilo, 2006). Current classification or diagnostic schemes include ED as disorders that have a negative impact on both the psychological and physiological well-being.

The Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (Diagnostic and statistical manual of mental disorders : DSM-5, 2013) include ED diagnoses. An ED- like any mental disorder category in the DSM-V- is a clinically meaningful behavioral or psychological pattern that is associated with distress or disability of with substantially increased risk of morbidity, disability, or mortality. Anorexia Nervosa (AN), Bulimia Nervosa (BN), Binge Eating

Disorder (BED), and Avoidant/Restrictive Food Intake Disorder (ARFID) are recognized in the current edition of the DSM-V. AN, which primarily affects adolescent girls and young women, is characterized by distorted body image and excessive dieting that leads to severe weight loss with a pathological fear of becoming fat. BN is characterized by frequent episodes of binge eating followed by inappropriate behaviors such as self-induced vomiting to avoid weight gain; there is also disturbance in the perception of one’s weight and/or body shape. BED is characterized by recurrent episodes of binge eating or overeating associated with feelings of guilt, depression and disgust towards oneself.

ARFID was introduced as a formal diagnostic category in 2013 in the DSM-5 and the definition has been revised in 2020, it is characterized by an eating or feeding disturbance (e.g., apparent lack of interest in eating or food avoidance based on the sensory characteristics of food, concern about aversive consequences of eating) as manifested by persistent failure to meet appropriate nutritional and/or energy needs and associated with one (or more) of the following: 27

significant weight loss and/or significant nutritional deficiency and/or dependence on enteral feeding or oral nutritional supplements and/or marked interference with psychosocial functioning

(Diagnostic and statistical manual of mental disorders : DSM-5, 2013; Holman & Ruedinger,

2020). ARFID is a diagnosis for a heterogeneous group of individuals of all ages who engage in avoidant or restrictive eating behaviors without weight or body image concerns (Bourne, Bryant-

Waugh, Cook, & Mandy, 2020).

The understanding of ED has stretched rapidly in the last 10 years to include BED and

ARFID in addition to AN and BN. Both BED and ARFID do not have body image concerns as core diagnostic criteria (Hay, 2020). They are distinguished by being disorders eating behaviors or patterns, the former of recurrent binge eating without regular purging and the latter of avoidance and aversion to food and eating (Diagnostic and statistical manual of mental disorders : DSM-5, 2013; Hay, 2020).

Table 2- Key Diagnostics of Eating Disorders/ DSM-V

Anorexia Bulimia Binge Eating Avoidant/Restrictive Nervosa (AN) Nervosa (BN) Disorder Food Intake (BED) Disorder (ARFID) Restriction Severe Restriction Irregular Rare Restriction Severe Restriction (all foods) Restriction (all or selected foods)

Weight Severe low body Normal or above Normal or above May be underweight weight normal weight normal weight and/or with nutrition deficiency Body Image Disturbance in the Self-evaluation is Disturbance in No body Image way in which unduly the perception of distortion present one’s body weight influenced by one’s weight of shape is body shape and and/or body experienced, weight shape but not undue influence always present. of body weight or shape on self- evaluation

Binge Eating If binge Recurrent Recurrent No binge eating present eating/purging episodes of binge episodes of binge type eating at least eating once a week for 3 months

Compensatory One or more Recurrent Rare None present Behaviors (self- compensatory compensatory compensatory induced behaviors are behaviors in behaviors vomiting, misuse present order to prevent of laxatives, weight gain diuretics, fasting, excessive exercise, etc.)

2.2.2.1 ED and autoimmune diseases: bidirectional relationship.

Dysfunction of the Immune system or autoimmune diseases can be associated with ED.

However, the nature of the relationship between the two diseases remains questionable (Hedman

et al., 2019). Hedman et al. evaluated the bidirectional relationship between autoimmune diseases and ED. The most common autoimmune diseases were CeD and type 1 diabetes. A diagnosis of type 1 diabetes increased the risk of developing other eating disorders (OED) by

112%. After a diagnosis of CeD, the risk of successive AN diagnosis in females was 50%, 89% in Crohn’s Disease and 71% in type 1 diabetes. In addition, the risk of developing OED in females was increased to 71% following a CeD diagnosis, 63% and 52% following Crohn’s

Disease and ulcerative colitis diagnosis, and 152% following a diagnosis of type 1 diabetes

(Hedman et al., 2019). When looking at ED diagnosis first, males had no diagnosis of any autoimmune disease post-diagnosis of ED. However, in females the risk of developing CeD post- diagnosis of ED was increased by 83% in females with AN and 68% in OED (Hedman et al.,

2019). The bidirectional relationship between ED and autoimmune disorders is seen in females but not in males. The latter suggests that there may either be a shared mechanism or another variable that is contributing to the link between ED and autoimmune diseases (Hedman et al.,

2019). For example, in CeD, is the strict restrictive GFD causing an adverse effect on the psychological wellbeing of individuals with CeD, leading to the development of an ED.

2.2.2.2 Disordered Eating (DE).

Disordered Eating (DE) are characterized by deviations from healthy eating and may progress into ED if not dealt with. Examples of DE are, restricting, purging, binge eating, fasting and the use of excessive physical activity in order to control weight and/or body shape (Grilo,

2006) or avoid specific symptoms caused by food. It is difficult to determine what is healthy eating or non-normative and how, when or where to draw the line. DE is damaging to physical

and psychological health however despite the fact that these “non-normative” eating patterns may meet some of the criteria for ED (AN, BN, BED), they do not meet the full diagnostic criteria of traditional ED diagnoses under the DSM-V.

2.2.2.3 ED and DE in Gastrointestinal Disease.

Gastrointestinal (GI) tract disturbances can result in GI diseases including CeD, irritable bowel syndrome (IBS) and inflammatory bowel disease (IBD). Nausea, bloating, constipation, diarrhea, changes in weight and abdominal pain are some of the common symptoms associated with GI diseases (R. Satherley et al., 2015). The treatments to avoid symptoms associated with

CeD, IBS and IBD are life-long modifications of the diet. The sole treatment of CeD to date is a life-long GFD (P. H. Green & Jabri, 2006). Whereas in IBD and IBS, dietary interventions appear to be reasonable treatment approaches but the diet modifications are complex (low

FODMAP, anti-inflammatory, etc.) and remain poorly defined (Werlang, Palmer, & Lacy, 2019).

Individuals with GI disorders (that are dietary controlled), experienced uncomfortable, embarrassing or distressing symptoms when consuming food items that were offensive before diagnosis. Once diagnosed, diets are modified and these individuals often develop reluctance to consume the offending food items; some may develop fears of being contaminated by these foods when consuming foods from unknown sources (R. Satherley et al., 2015). This fear of eating foods from unknown sources may lead people to decrease variety and increase intake restrictions, which can be described as a disordered eating attitudes and behaviors. GI disorders with dietary controls for treatment may place individuals concerned at risk for the development of DE. Gilo et al. described DE as deviations from the standard three meals a day, calling them abnormal eating behaviors (may include skipping meals, binge eating, restricting certain foods, 31

etc.) (Grilo, 2006). DE may be, but not necessarily, the start to a later development of an ED. As explained by Satherely et al. intake restrictions and GI symptoms may act as prompts that lead to the development of disordered eating attitudes and behaviors in those with CeD, IBS and IBD

(R. Satherley et al., 2015). Many published studies and case studies have showed that individuals with GI disorders exhibit DE. In addition, the prevalence of ED has been reported in numerous case studies (Baylé & Bouvard, 2003; R. Satherley et al., 2015).

In his study with 79 individuals with IBD, Aldorado et al. showed a prevalence of 37.5% of DE in patients who had Crohn’s disease (IBD) and 44.4% of DE in patients who had ulcerative colitis (Addolorato, Capristo, Stefanini, & Gasbarrini, 1997). Other studies also showed that ED and DE were common amongst individuals with IBD and IBS. DE types found included dieting, food preoccupation, oral control, bulimic thoughts, irregular meals, meal skipping, and food restraint (Fletcher, Jamieson, Schneider, & Harry, 2008; Okami et al., 2011;

Sullivan, Blewett, Jenkins, & Allison, 1997; Tang et al., 1998).

Satherley et al. showed that there is a higher risk of developing DE in individuals with GI disorders compared to the general population and even though there was evidence for different

DE, food restriction was most frequent (R. Satherley et al., 2015). One way to explain the latter is that individuals with GI disorders may be more likely to resemble the personality of someone with a restrictive eating disturbance (R. Satherley et al., 2015). Satherley et al. explains that there are two pathways that lead to increased risk of disordered eating attitudes and behaviors in patients with GI disorders, and a hypothetical framework was developed to explain the pathways

(See figure 2 (R. Satherley et al., 2015))

Both pathways start at diagnosis of the GI disorder, where the lifelong diet modification is prescribed. In the first pathway, the individual with the GI disorder had strong symptoms pre- 32

diagnosis. Following the modified diet, the individual feels better and adapts well to the diagnosis. However, the individual may develop some dysfunctional illness beliefs, this could be the result of many factors related to fear of pre-diagnosis symptoms recurring (overestimation of negative consequences, intolerance of uncertainty, a belief that all foods have cross- contamination potential, high anxiety, depression). These beliefs lead to dysfunctional focus on dietary management whereby fear of food and limited variety of food lead to the development of dysfunctional eating patterns. On the other hand, some individuals will have a poor adaptation to the GI disorder diagnosis. These individuals had significant weight loss pre-diagnosis, and the post-diagnosis diet modification is followed the weight lost is regained. Hence, they associate the modified diet to weight gain and develop psychological distress in response to weight gain.

These dysfunctional illness beliefs are associated with lack of adherence to the modified diet.

The poor dietary management can be described as dysfunctional eating patterns; trigger foods are consumed as they are associated with weight loss (R. Satherley et al., 2015). In a study by

Fletcher et al., interviewed women with IBD and IBS confessed to knowingly consume foods that had the potential to be detrimental to their conditions (Fletcher et al., 2008).

Figure 3-Two Pathway model between GI disorders and disordered eating (R. Satherley et al., 2015)

2.2.2.4 ED and DE in Celiac Disease.

There is evidence that individuals with ED are diagnosed with CeD and there is also evidence that ED are affecting individuals with CeD (Hedman et al., 2019). In fact, both disorders are prevalent and underdiagnosed; CeD and ED are commonly associated with comorbid psychological conditions. (Daniel A. Leffler, Dennis, Edwards George, & Kelly,

2007). Several cases of EDs have been reported in patients with CeD, signifying that ED may be a comorbidity related to CeD (Babio et al., 2018; Yucel, Ozbey, Demir, Polat, & Yager, 2006).

And a few studies have investigated the association between the two disorders (Babio et al.,

2018; Passananti et al., 2013; Philippi, Cardoso, Koritar, & Alvarenga, 2013; Rocha, Gandolfi, &

Santos, 2016; Wagner et al., 2015; Zingone et al., 2015).

The increased risk of ED in diabetes and undiagnosed CeD was expressed in few published studies. Babio et al. evaluated the risk of developing ED after a diagnosis of CeD and compared the latter to healthy controls. The study showed that individuals with CeD above 13 years of age had a significantly higher Eating Attitude Test (EAT-26) score compared to their healthy counterparts. The EAT is a screening questionnaire that assesses a range of attitudes and behaviors associated with AN and BN. However, unlike Karawautz et al. and Passananti et al.’s findings there was no difference between cases and controls in terms of the mean scores of the screening test or the frequency with which individuals scored over the clinical cut-off (Babio et al., 2018).

Karawautz et al. performed a systematic study on eating pathology in CeD, whereby a lifetime history and current presence of eating pathology (ED and DE) were analyzed in adolescent patients with CeD. (Karwautz et al., 2008). The study showed that in 283 adolescents with CeD 4.8% had a lifetime history of ED and 3.9% had a current ED. In addition, 10.2% had 35

a lifetime history of DE vs. 10.7% with a current DE. Finally adolescent with CeD and ED or

DE had higher scores on most eating pathology related questionnaires (of which are the Eating

Disorder Inventory (EDI-2) and Eating Disorder Examination Questionnaire (EDE-Q)) as compared to the general population (Karwautz et al., 2008). Passananti et al.’s also used the EAT score and found a significantly high score in patients who had CeD (Passananti et al., 2013).

Passananti et al.’s case control study aim was to examine the prevalence of altered eating behaviors in individuals with untreated CeD through the use of validated questionnaire such as the EPIC Food Frequency Questionnaire, EAT-26 scale, Binge Eating Staircases (BES) and EDI-

2. The study results showed that young women with CeD have a higher prevalence of ED than men with CeD (Passananti et al., 2013).

Another study by Marild et al. showed a positive association between CeD and AN, both before and after the diagnosis of CeD (women with biopsy proven CeD). The authors explained that if a woman with CeD was biopsy diagnosed before the age of 19 years, there was a 4.5-fold increase in the odds of a previous diagnosis of AN. On the other hand, there was twice a risk of developing AN after an initial diagnosis of CeD at the age of 20 years or more (Marild et al.,

2017).

Satherley et al. used the EAT-26 and Binge Eating Scale (BES) to measure disordered eating attitudes and self-reported behaviors. Findings also showed the prevalence of DE, with

15.7% scoring above the clinical cut-off for EAT-26 in individuals with CeD (R. M. Satherley,

Howard, & Higgs, 2016). The latter is lower than Karawautz et al. and Arigo et al.’s previous reports of 22-29% but significantly higher compared to healthy controls (Arigo, Anskis, &

Smyth, 2012; Karwautz et al., 2008).

Recent research found that both extreme GFD adherence and dietary transgressions were associated with DE in CeD (Daniel A. Leffler et al., 2007; Marild et al., 2017; Passananti et al.,

2013; R. M. Satherley et al., 2016). It was found that individuals with Type 1 diabetes (T1D) compared to the general population have a higher frequency of ED. It is believed the increased frequency of ED were due to the impact of the restrictive nature of the diet, the effect of a chronic medical condition on body image and self-esteem (Philippi et al., 2013) all of which correlate highly to the patients with CeD. In diabetes, individuals may withhold insulin to lose weight. The same has been observed in individuals with CeD, were gluten is consumed intentionally to facilitate weight loss (Daniel A. Leffler et al., 2007). Patients who showed signs of ED and DEs were more often noncompliant with their GFD (Karwautz et al., 2008). Wagner et al. showed that individuals with CeD and a diagnosed ED were more often non-compliant with their diet, had higher body mass index (BMI) and higher levels of depression (Wagner et al.,

2015).

Individuals with CeD have to find a balance between vigilance around following a strict

GFD and concerns around food availability and cross-contamination which have the potential to contribute towards disordered eating attitudes and behaviors (R. M. Satherley et al., 2017). For those who fail to adhere to their GFD, it has been suggested that the challenges of adapting to

CeD and managing the GFD can lead to the development of restrictive or bulimic eating behaviors (R. M. Satherley et al., 2016). Satherley et al. revised the two pathways that lead to increased risk of disordered eating attitudes and behaviors in patients with GI disorders and added a third pathway specific to CeD (See figure 3). In addition to the two pathways that applied to GI disorders, individuals with CeD may develop psychological distress in response to the diagnosis. The restrictive nature of the diet leads patients with CeD to crave gluten 37

containing food. To cope with these cravings, individuals with CeD end up consuming large quantities of gluten free foods to elevate their moods; the latter would be considered a binge eating episode (R. M. Satherley et al., 2017).

Figure 4- Revised Pathway model of disordered eating to adapt to CeD (R. M. Satherley et al., 2017)

Table 3- Summary table, prevalence of ED and DE in CeD and GI Disorders

Author (reference) Measures Used Outcomes

Title Prevalence of ED and DE in CeD (Yucel et al., 2006) Observational Diagnosis of CeD was established after an initial diagnosis of atypical Eating disorders and celiac eating disorder. Cause -and-effect disease: a case report between AN and CeD remain unclear.

(Daniel A. Leffler et al., 2007) Observational Cases demonstrate the complex ways in which CeD and ED interact The interaction between with important clinical implications eating disorders and celiac for the diagnosis and treatment of disease: an exploration of 10 both illnesses. cases

(Karwautz et al., 2008) -Eating Disorder Inventory Higher rate of ED and OED in CeD (EDI-2) patients. Higher rate of BN in CeD Eating pathology in patients. adolescents with celiac disease -Eating Disorder Examination Questionnaire (EDE-Q)

-Body Mass Index (BMI)

(Arigo et al., 2012) Eating Disorders Examination 22% of women with CeD reported Questionnaire (EDE-Q) disordered eating behaviors Psychiatric comorbidities in (restraint, eating concern, shape women with celiac disease concern and weight concern)

(Kirby Sainsbury, Mullan, & Eating Disorder Inventory Sharpe, 2013) (EDI-2) More severe gastrointestinal symptoms at diagnosis is associated Reduced quality of life in with eating disorder risk (r = 0.15, coeliac disease is more p=.01) strongly associated with depression than gastrointestinal symptoms

(Passananti et al., 2013) -Dietary interview ED appear to be more frequent in young women than in CeD men and Prevalence of eating disorders -Binge Eating Staircases, healthy controls. in adults with celiac disease Eating Disorder Inventory (EDI-2)

-Eating Attitudes Test (EAT)

(Wotton, James, & Goldacre, Retrospective, In the current study, females 2016) record-linkage admitted to hospital with AN or BN had signiﬁcantly elevated risks of Coexistence of eating Addison’s disease, celiac disease disorders and autoimmune Females admitted to hospital with diseases: record linkage of AN or BN had significantly high cohort study, UK risk of CeD

(Marild et al., 2017) Histopathology records Among 17,959 women with CeD, 353 individuals were diagnosed Celiac disease and anorexia with AN at median age of 17 years. nervosa: a nationwide study

(Babio et al., 2018) -Children Eating Attitude Test Patients with CeD above the age of (ChEAT) 13 had higher EAT scores. The Risk of eating disorders in screening tests showed no clear patients with celiac disease -Eating Attitude Test (EAT)- differences between cases and 26 control subjects in terms of the risk of ED. -Sick control fat food (SCOFF)

-Bulimia Investigatory Test Edinburgh (BITE)

-Body Shape Questionnaire (BSQ)

-Figure Drawing Scale

(Tokatly Latzer, Lerner-Geva, -Eating Attitude Test (EAT- Increased disordered eating Stein, Weiss, & Pinhas-Hamiel, 26) behaviors in adolescents with CeD. 2020) More so, in older overweight -Gluten free diet questionnaire female adolescents. Disordered eating behaviors in adolescents with celiac disease

(Hedman et al., 2019) Observational In women, AN showed a (diagnosis made using ICD-10 bidirectional approach with CeD Bidirectional relationship and DSM-IV) between eating disorders and autoimmune diseases Prevalence of ED and DE in GI disorders (Guthrie, Creed, & Whorwell, Eating Attitudes Test (EAT) Female outpatients with IBS are 1990) preoccupied with the desire to be Eating disorders in patients thinner. Their lives are controlled with irritable bowel by food and dieting behaviors. syndrome: a comparison with inflammatory bowel disease and peptic ulceration

(Addolorato et al., 1997) BMI, 7-day food diary Patients with IBS tend to have increased malnutrition Inflammatory Bowel Disease: A Study of the Association between Anxiety and Depression, Physical Morbidity, and Nutritional Status

(Sullivan et al., 1997) Eating Attitudes Test (EAT) Patients with IBS have a higher tendency to diet, have food Eating attitudes and the preoccupation, oral control and irritable bowel syndrome bulimia.

(Tang et al., 1998) Eating Disorder Inventory IBS patients who reported severe (EDI) episodes of vomiting and nausea Features of eating disorders in also endorsed bulimic-type patients with irritable bowel characteristics as measured by the syndrome Bulimia subscale of the EDI.

(Fletcher et al., 2008) 14-day food diary The theme of adverse behaviors, consisted of 2 major subthemes: "I Know This Is Bad for Me, dietary restrictions and issues with But…": A Qualitative medication. Investigation of Women with Irritable Bowel Syndrome and Inflammatory Bowel Disease: Part II

(Okami et al., 2011) Non-validated questionnaire Students with IBS skipped meals and had more irregular meals Lifestyle and psychological factors related to irritable bowel syndrome in nursing and medical school students (R. Satherley et al., 2015) Review of 9 papers The presence of disordered eating behaviors is greater in populations Disordered eating practices in with GI disorders compared to gastrointestinal disorders healthy controls.

(Melchior et al., 2020) Sick control fat food (SCOFF) The combination of IBS and ED questionnaire was associated with higher levels of Eating disorders in patients anxiety or depression and poorer with the irritable bowel quality of life. syndrome: a comparison with inflammatory bowel disease and peptic ulceration

2.2.3 Psychological factors on Disordered eating attitudes and behaviors.

The presence of disordered eating attitudes and behaviors in CeD and GI disorders was found to be associated with psychological distress, symptom severity and dietary adherence, anxiety, depression and impaired QoL (R. Satherley et al., 2015). Arigo et al. (2012) showed that a substantial subset of women with CeD showed symptoms of depression simultaneously to

DE (Arigo et al., 2012).

Polivy et al. explained that when assessing the effect of a restrictive diet such as T1D and

GFD, it was found that the impact goes beyond nutrient deprivation and the individuals exhibit a variety of cognitive, emotional, and behavioral changes. In following several of these patient groups the author noted that individuals on a restrained diet were more likely to experience episodes of overeating and binge eating. Interestingly it was noted that individuals who underwent “psychological or emotional” deprivation (avoiding a favorite food, weight loss,

GFD) experienced the same psychological effects as those who actually were food deprived. In fact, in normal eaters, food restriction may lead to binge eating reactions (J. Polivy, 1996). Yet primarily in restrained eaters, deprivation causes craving and overeating (Janet Polivy, Coleman,

& Herman, 2005). Thus, the psychological burden of a restrictive diet further impacts an individual’s nutritional status.

For those who are extremely adherent to the GFD, anxiety around gluten cross- contamination may lead to limited food choices or eating only in situations with complete control over the food preparation process, which may mimic DE (R. M. Satherley et al., 2017; Sverker et al., 2005).

Patterns of cognitions and behaviors that cause individuals to become socially isolated, to refuse attendance at social events involving food or to avoid eating in settings outside the house, 43

a marked interference with psychosocial functioning, can be considered disordered (Grilo, 2006).

A recent study conducted a cross-sectional mixed methods study with 30 adolescents with CeD and found that half of the study sample (53.3%) expressed more rigidity (vs. flexibility), avoidance (vs. trust), controlling behavior (Vs. confidence), and food preoccupation (vs. awareness) to maintaining a GFD and those who did so were older and had lower QoL scores

(Cadenhead et al., 2019). These findings highlighted the importance of understanding the extent of DE in those with CeD and the need to identify those at risk in order to promote a GFD without undermining QoL.

In Wagner et al.’s multi-centered study, it was found that female adolescents with CeD and a co-morbid ED had higher rates of depression and dietary non-compliance. Interestingly, there were no differences found in coping mechanisms between the groups with and without ED in addition to their CeD, thus indicating further investigation is warranted in this area (Wagner et al., 2015). In another study, Rocha et al. evaluated the association between CeD and presence of other psychological disorders. The authors found a higher rate of major depressive disorder in individuals with CeD compared to controls (30.0% vs 8.3%, p<0.0001). Similar results were found when panic disorder and bipolar disorder were investigated; (18.3% vs 5.4%, p<0.001 and

4.3% vs 0.4% p<0.005) respectively. The authors strongly suggest screening for CeD in individuals with affective disorders as well as screening for these disorders in the celiac population (Rocha et al., 2016).

2.2.4 The link to ARFID.

Individuals with Avoidant/Restrictive Food Intake Disorder (ARFID) experience impairing health consequences from insufficient nutritional variety and/or quantity. ARFID 44

made it to the DSM diagnostics in 2013 with the publication of DSM-5 (Diagnostic and statistical manual of mental disorders : DSM-5, 2013). The diagnosis is a reformulation and expansion of the former DSM-4 diagnosis of feeding disorder of infancy and early childhood; as the latter can occur across the lifespan (Thomas, Wons, & Eddy, 2018).

The DSM-5 describes ARFID as an eating or feeding disturbance that results in persistent failure to meet nutritional needs and is associated with one (or more) of the following: weight loss, nutritional deficiency, dependence on nutritional supplementation, or marked interference with psychological functioning. The feeding disturbance is presented as a lack of interest in eating or food, and that is based on the sensory characteristics of food and or concern about aversive consequences of eating (Diagnostic and statistical manual of mental disorders : DSM-5,

2013; Tsang et al., 2020).

Eddy et al. assessed the prevalence of ARFID in a pediatric GI sample and found that

1.5% of cases met the full criteria of ARFID diagnosis and another 2.4% met at least one criterion of ARFID (Eddy et al., 2015). When assessing marked interference with psychological functioning, there is an overlap in the factors associated with the psychological distresses observed and studied in the restrictive nature of the GFD. Depression, anxiety, and fear of negative consequences from eating that are observed in individuals with GI disorders or CeD are considered psychosocial impairments related to eating/feeding problems.

Many professionals in the gastroenterology field have recognized that a number of patients with GI disorders and/or CeD have ED or DE symptoms that interact with their presenting GI complaints. However, many will screen for ED such as AN and BN. The observed disordered eating attitudes and behaviors may be classified under ARFID, which is also a diagnosis of ED in the DSM-V. ARFID possess characteristics relevant to both feeding and ED 45

and patients diagnosed with ARFID-like feeding disturbances are usually referred to ED clinics or gastroenterology clinics (Eddy et al., 2015; Kennedy, Wick, & Keel, 2018).

2.2.5 Factors associated with ED or DE in CeD.

Based on subject studies in different studies evaluating ED or DE in CeD, factors looking at demographic, personality characteristics and body composition of CeD patients were assessed.

Some studies found that adolescent females with comorbid CeD and EDs are less compliant with their diets, have a higher body mass index (BMI) and have elevated body dissatisfaction and reported lower QoL (Hedman et al., 2019; Karwautz et al., 2008; Wagner et al., 2015). In

Passananti et al.’s study showed that women with CeD score higher than healthy controls on ascetism, perfectionism and inadequacy. This suggests that women with CeD may fit the profile of individuals who have general feelings of social insecurity (Passananti et al., 2013). Babio et al. showed that participants with high BMI was a risk factor of developing ED as well as being moderately active or active (Babio et al., 2018). especially those who are overweight, older and of a female gender. A recent cohort of 136 individuals with CeD showed that DE in adolescents with CeD is higher in older female adolescents who are overweight (Tokatly Latzer et al., 2020).

Wagner et al. explained that personality dimensions have been explored in patients diagnosed with EDs. In all EDs, elevated harm avoidance, reduced self-directedness and cooperativeness are recognized personality factors, which was also found in adolescents with

CeD (Wagner et al., 2015). When trying to identify EDs in patients with CeD, BMI and personality factors should be assessed as well (Wagner et al., 2015).

2.2.6 Summary

2.2.6.1 What is known?

Current medical guidelines state the only treatment for celiac disease is strict lifelong adherence to the GFD. Maintaining a strict GFD requires vigilance and control around food, and this increased vigilance has been linked to diminished QoL. Recent studies have investigated the association between CeD and ED. Although the mechanisms are unclear, one hypothesis is that some individuals have a great deal of distress in response to weight gain associated with their diagnosis and implementation of the prescribed GFD. Because they may feel the GFD is causing the unwanted weight gain, purposeful gluten ingestion may lead to restrictive or bulimic eating behaviors. For patients who are highly compliant with the GFD and experience resolution of symptoms, anxiety around gluten cross contamination may lead to limited food choices or eating only in situations with complete control over food preparation, which, in turn, may lead to disordered eating attitudes and behaviors. Understanding predictors of DE in individuals with

CeD is critical for effective intervention and prevention of full-blown ED, yet little is known.

2.2.6.2 What is Not Known?

The Celiac Disease and Disordered Eating Behavior Study addressed some of these gaps in the literature by exploring prevalence of CeD in a sample of adults, examines attitudes and behaviors specific to individuals with CeD that may be associated with DE, and also examines whether there is a particular profile of individuals that may be at risk.

Chapter 3- Methods

This chapter will summarize the methods of the study. This will include the study design, setting and participants, recruitment and data collection procedures, measures, and statistical analysis plan.

3.1 Overview of Study Design

This was a cross sectional study of 50 adults with biopsy-diagnosed CeD. IRB approval at CUIMC was obtained on August 1st, 2019 (Rascal IRB-AAAS550) and approval for modifications were received on December 5th, 2019. IRB approval for the study from Teachers

College was obtained on September 5th, 2019 (IRB ID: 19-479) and IRB approval for the modifications were received on January 7th, 2020.

On March 8th, 2020 IRB for both CUIMC and TC put a hold on all studies following the

Covid-19 pandemic. CIUMC allowed studies to resume around July 2020, however, TC did not approve IRB modifications to resume in-person data collection at the Celiac Disease Center of

CUIMC until October 16, 2020. Thus, data collection resumed October 16, 2020 and was completed on December 15, 2020.

3.2 Setting and Participants

The study was conducted at the Celiac Disease Center at Columbia University Irving

Medical Center in New York City (CUIMC). The Celiac Disease Center was founded in 2001 by

Dr. Peter Green, M.D., and has established itself as a leading center in the field both nationally

and internationally. Dr. Green, one of a few recognized experts on CeD in the United States, serves as Director of the Center at CUIMC. The Center serves over 4000 patients with CeD and other gluten-related disorders and provides high quality patient care for children and adults. The center has multiple adult and child gastroenterologists and two full time dietitians specialized in

CeD. Strengths in research and treatment are enhanced by the location within CUIMC, which is a major medical center in New York City providing fertile ground for innovative research and translational studies across a variety of divisions, departments, centers, and institutes. The Celiac

Disease Center at Columbia University has an active research program, a research coordinator, and an active collaborative relationship with the Program in Nutrition at Teachers College.

3.3 Inclusion & Exclusion Criteria

The target goal was 50 individuals - aged 18 to 45 years. Inclusion criteria required that participants be between the ages of 18-45 years with biopsy-diagnosed CeD. CeD was confirmed from patients’ medical records by the Celiac Disease Center clinical staff. Participants should have been following a GFD for at least a year. Exclusion criteria included serum or self- diagnosed CeD (without biopsy), a CeD diagnosis <1 year prior, and age <18 years and >45 years old, a self-reported previous diagnosis of an ED and/or self-reported current diagnosis of

ED. Participants did not benefit from taking part in this study, but participation helped better understand the eating behaviors and patterns of patients following a strict GFD. Adults agreeing to participate in the study received up to $80 in gift cards for his/her participation in this study.

They first received a $50 gift card upon completion of the surveys. A $15 gift card was mailed to him/her upon completion of each of the two 24hr food recall by phone.

3.4 Enrollment & COVID-19

Enrollment began on January 28th, 2020 and was halted early due to COVID-19 and all non-essential research activities required to stop recruitment. Enrollment resumed on October

16, 2020.

Participants were prescreened by Celiac Center dietitians and staff to determine potential age eligibility for individuals with biopsy diagnosed CeD. A chart with eligible patients’ names, the name of the doctor they were seeing, and day/time of the week they were coming in, was provided to TC students volunteering as Research Assistants. Once patients checked in with the secretary, students consecutively approached prescreened patients to gauge interest in the study.

When patient agreed to take part in the study, the students went through the eligibility checklist to make sure that the patient met all eligibility criteria. If so, then the patient signed the consent form, and the survey packet was handed to the participant for completion. The surveys were completed while the patient waited for their doctor’s appointment. Once called in to the appointment, the student waited for the patient to be done so that they could resume whatever steps in the protocol were left to do.

Height and weight were measured, along with body composition in a private room. Once patients had completed their doctor’s appointment the student walked the participant to a conference room reserved for patients to complete their surveys as well as anthropometric measurements (height, weight and body composition). The participant was asked to provide a blood sample and a stool or swab sample (to be frozen for future studies); however, the latter were optional. If the participant didn’t get the chance to complete the surveys pre-doctor appointment, they were seated at the conference room and finished post-anthropometric measurements’ completion. The participant received a $50 dollar gift card for their participation. 50

They were provided with a ruler to take home with them to assist them during the two 24-hour recall phone calls (a weekend and a weekday) they received within a month of being recruited.

Upon completion of the two 24-hour recalls, the participant received a $30 gift card that was sent to them by mail. The surveys and measurements took around 30 minutes to complete on average, it was mostly dependent on the patient’s pace to answer the survey questions.

3.5 Study Measures

3.5.1 Anthropometric measures.

Weight and body composition were measured using a Tanita Dual frequency body composition analyzer. The latter is a stand-alone scale, two pounds are subtracted (to count for clothing) before the participant has to step on barefoot. Information concerning the subject (age, gender and height) are entered. Once body composition has been assessed by the scale, a little slip prints out and the participant can step down. The Tanita scale has been found to be valid and reliable in estimating BMI and the percentage of body fat in adults (Verney, Schwartz, Amiche,

Pereira, & Thivel, 2015).

Height was measured using a stadiometer, known as the gold standard for standing height

(Gordon, Fredman, Orwig, & Alley, 2013).

3.5.2 Demographic and Medical History variables.

Age (date of birth), gender (female, male), self -described ethnicity (Hispanic, non-

Hispanic), self-described race (White, black or African American, Asian, other), education

(highest level/grade achieved), and household income (<$50,000; $50,000 to $100,000;

>100,000; prefer not to disclose) were collected.

Participants were prescreened by medical staff to determine potential age eligibility for individuals with biopsy-diagnosed CeD and the amount of years on GFD. Participants were asked to provide medical history variables to confirm the pre-screening. They were also asked if they were patients of the Celiac Disease Center at Columbia University and who their gastroenterologist was. Information about their previous or current affiliation to a registered dietitian was also collected (currently, once only, more than once, never).

3.5.3 Eating Disorder Diagnosis Tools.

The EDDS is a brief self-report measure of 23 items designed for diagnosing AN, BN and BED based on the DSM-IV. The tool involves of likert scores, dichotomous scores, frequency scores and open-ended questions (weight and height). Krabbenborg et al. showed that an overall symptom composite cut-off score of 16.5 accurately distinguished clinical female patients with ED from healthy controls (Krabbenborg et al., 2012). According to Krabbenborg et al. the cut-off score of 16.5 may be helpful in identifying patients with AN, BN and BED, but more research is needed to confirm this cut-off is useful for OSFED presentations (Krabbenborg et al., 2012). However, an instrument specific syntax provides a diagnostic score to identify suggestive AN, BN, BED and possible OSFED.

Research has provided evidence of the reliability and validity of this scale (Froreich,

Vartanian, Grisham, & Touyz, 2016; Krabbenborg et al., 2012; Perez, Van Diest, & Cutts, 2014;

Stice, Fisher, & Martinez, 2004; Stice, Telch, & Rizvi, 2000). It is important to know that the

EDDS composite score cut-offs were validated in females and not in males (Krabbenborg et al.,

2012).

Participants who had an EDDS syntax suggestive of AN, BN, or BED diagnoses were contacted by the dietitian at the Celiac Disease Center and offered a referral for following at the

Eating Disorders Clinic at CUIMC.

3.5.4 Disordered Eating Patterns detection tool.

The Eating Pathology Symptoms Inventory (EPSI) queries an individual’s multidimensional eating pathology. It is a 45 item self-report measure that is designed to assess the psychopathology of eating disorders (disordered eating and cognitions). There are 8 subscales including; body dissatisfaction (dissatisfaction with body weight and/or shape), binge eating (ingestion of large amounts of food and accompanying cognitive symptoms), cognitive restraint (cognitive efforts to limit or avoid eating, whether or not such attempts are successful), purging (self-induced vomiting, laxative use, diuretic use, and diet pill use), excessive exercise

(physical exercise that is intense and/or compulsive), restricting (concrete efforts to avoid or reduce food consumption), muscle building (desire for increased muscularity and muscle building supplement use), and negative attitudes toward obesity (negative attitudes toward individuals who are overweight or obese) (K. T. Forbush, Wildes, & Hunt, 2014) Each sub-scale is scored on a 5-point scale (0 - 4), the sums of each sub-scale describes the participants eating experiences (Kelsie T. Forbush, 2016).

Research has provided evidence of the reliability and validity of this scale (K. T. Forbush et al., 2020). Unlike many other self-reported measures of eating pathologies, Forbush et al. 53

showed that the EPSI subscales showed clear evidence for factor structure replicability in males and females (K. T. Forbush et al., 2014)

3.5.5 Disordered Eating Patterns Specific to CeD tool.

The Celiac Disease-specific food attitudes & behaviors scale (CD-FAB) is an eleven-item validated tool that queries eating attitudes and behaviors resulting from beliefs around cross contact, and food safety (i.e., handling of food, trust, risk-taking and food safety). Many of the studies looking at the association of CeD and ED or DE suggested that existing measures of DE do not identify all atypical eating patterns reported in CeD. The survey tool is unique in that its disease specific and is useful for evaluation food concern in individuals with CeD and further explore the development of DE in CeD. Answers give an overall score, as well as three clinically relevant subscales: food attitudes, fear response and adaptive response.

Food attitudes are individual concerns about eating outside the home and cross-contact with gluten-containing foods. Examples of questions related to food attitude are:

Because of my Celiac…

1- I get concerned being near others when they are eating gluten (strongly agree to strongly

disagree)

2- I am afraid to eat outside my house (strongly agree to strongly disagree)

3- I am afraid to touch gluten-containing foods (strongly agree to strongly disagree)

Fear response are individual behaviors designed to control food preparation and fear of trying new foods. Examples of questions related to fear response are:

Because of my celiac…

4- I get worried when eating with strangers (strongly agree to strongly disagree)

5- I find it hard to eat gluten-free foods that look like the gluten-containing foods that have

made me ill in the past (strongly agree to strongly disagree)

6- I will only eat food that I have prepared myself (strongly agree to strongly disagree)

7- My concerns about cross-contamination prevent me from going to social events involving

foods (strongly agree to strongly disagree)

Adaptive response suggests behaviors that allow individuals to manage their food attitudes without compromising their lifestyle. Examples of question related to adaptive response are:

Despite having Celiac Disease...

8- I enjoy going out for meals as much as I did before my diagnosis (strongly agree to

strongly disagree)

9- I am comfortable eating gluten-free food from other people’s kitchens (strongly agree to

strongly disagree)

10- Being contaminated by gluten in the past hasn’t stopped me from enjoying restaurants

(strongly agree to strongly disagree)

11- If I ask questions, I can normally find gluten-free food to eat (strongly agree to strongly

disagree)

Final scores have a possible range of 11 to 77, food attitudes subscale have a possible range of 3 to 21, fear response subscale have a possible range of 4 to 28 and adaptive response have a possible range of 4 to 28. High scores on the CD-FAB tool suggest higher disordered eating attitudes and behaviors related to CeD. And high scores on the CD-FAB are associated with psychological distress (anxiety, depression and stress) and an impaired CeD specific QoL

(R.-M. Satherley et al., 2018). 55

A mixed method approach based on three different studies helped develop the CD-FAB tool. The first study was online focus groups, participants recruited form online forums helped generate the tool’s items. Emerging themes (related to food attitudes, concerns, and eating behaviors) were used to develop items for the CD-FAB. Items were then transformed into 7- point Likert scales questions (strongly agree to strongly disagree). The items were then reviewed, and three participants with CeD (who did not take part in the focus groups) gave feedback on clarity, adequacy, and relevance of the questions. Some of the questions were removed giving a tool with 30 items rated on a 5-point scale (R.-M. Satherley et al., 2018). In study two, the 30 item CD-FAB was distributed to 157 adults (18-69 years) with self-reported biopsy confirmed diagnosis of CeD. The CD-FAB was reduced from 30 to 13 items. In the third study, the feasibility, reliability and validity of the tool were explored. Another round of 200 participants

(sufficient sample size for confirmatory factor analysis with self-reported biopsy confirmed CeD

(who did not take part in study one or two) were recruited online. Participants completed the CD-

FAB at time 1, then were invited to complete it again at time 2 (4 weeks later) (R.-M. Satherley et al., 2018). The CD-FAB has only been validated in the adult population. Correlation coefficients were used to assess test-retest reliability of the participants’ scores, test-retest correlation coefficients between the total CD-FAB scores at time 1 and time 2 were strong (r =

0.92, p < 0.001). Floor and ceiling effects ranged between 0.5 and 1%. The CD-FAB total score showed good internal consistency (Cronbach's alpha = 0.89).

Convergent validity was assessed using the Food Neophobia Scale (FNS), total CD-FAB positively correlated with the FNS (r = .274,p < 0.001) (Bland & Altman, 1986). Convergent validity has previously been used to assess food anxieties in CeD and Depression, Anxiety,

Stress Scale- 21 (DASS-21) (r = 0.188, p = 0.016) (Pliner & Hobden, 1992; R.-M. Satherley et al., 2018).

The CD-QoL was used to assess discriminative validity. Beliefs about the effectiveness of the GFD (inadequate treatment) were not related to CD-FAB scores (r = -0.002, p = 0.98), indicating good discriminant validity (R.-M. Satherley et al., 2018).

3.5.6 Measures related to celiac disease specific QoL.

The Celiac Disease Specific Quality of Life (CD-QoL) is a 20-item celiac disease specific measure to assess the quality of life in adults. The validated survey instrument is based on a Likert scale type of questions from 1 (not at all) to 5 (a great deal) (Dorn et al., 2010).

Answers will give an overall score, as well as four clinically relevant subscales: dysphoria, limitations, health concerns, and inadequate treatment. The extent to which individuals feel depressed, frightened or overwhelmed by their diagnosis of CeD is measured by dysphoria items.

The extent to which individuals feel limited by CeD when eating out with others, socializing, and traveling is measured by limitation items. The extent to which individuals feel worried about long-term health outcomes of their diagnosis for other family members and themselves is measured by health concern items. And the extent to which individuals feel there are enough treatment options for their CeD is measured by inadequate treatment items. Raw scores (20 –

100) are converted to scaled scores and have a possible range of 0 – 100 with higher scores indicating a higher degree of QoL.

A standard scale development was used to develop the CD-QoL. Factor analysis showed a strong clinically relevant four factor solution (CeD related limitations, dysphoria, health concerns and inadequate treatment) that shows face validity and high internal consistency 57

reliability (Cronbach’s alpha was higher than the cutoff of 0.7). To assess construct validity, several psychosocial questionnaires were used: the self-related health (single item health related quality of life (HRQoL) question), brief symptom inventory (BSI-18), sickness impact profile

(SIP), IBS quality of life (IBS-QoL) and the visual analogue scale (VAS) for abdominal pain.

The correlations between the CD-QoL, self-report of HRQoL, BSI-18, SIP, IBS-QoL and VAS were all in the expected direction and within the ideal range of 0.35-0.65, which also shows convergent validity. The CD‐QoL is a valid and reliable measure of health‐related QoL for patients with CeD on a GFD (Dorn et al., 2010).

3.5.7 Measures of anxiety and depression.

The State Trait Anxiety Inventory (STAI) is a two-part tool with each section comprised of 20 items (40 items in total) validated to report anxiety as an existing state (transitory, state anxiety) or a predisposition to anxious response to situations (latent, trait anxiety). State anxiety items include: “I am tense; I am worried” and “I feel calm; I feel secure.” Trait anxiety items include: “I worry too much over something that really doesn’t matter” and “I am content; I am a steady person.” The items are rated on a 4-point Likert scale from 1 (Almost Never) to 4 (Almost

Always). Item scores are added to obtain subtest total scores, the range of scores for each subtest is 20-80, and higher STAI scores indicate greater anxiety. A cut-off point above 39 suggests clinically significant symptoms for each subtest: state anxiety and trait anxiety (Julian, 2011;

"State-Trait Anxiety Inventory,").

The Center for Epidemiologic Studies Depressive Scale (CES-D) is a validated screening test for depression and depressive disorder. It measures symptoms defined by the DSM-V for a major depressive episode. The tool consists of 20 items that rate how often over the past week an 58

individual has experienced symptoms associated with depression, such as restless sleep, poor appetite, and feeling lonely. The items are rated on 4-point Likert Scale from 0 (rarely or none of the time) to 3 (most or almost all the time). Final scores have a possible range of 0-60 with higher scores indicating greater depressive symptoms. Individuals who score above Cutoff scores

(15 or greater) may be at risk for clinical depression (Lewinsohn, Seeley, Roberts, & Allen,

1997; Radloff, 1977).

3.5.8 CeD Symptoms.

The Celiac Disease Symptoms Diary (CDSD) is a disease specific patient reported outcome (PRO) daily symptom diary over a seven-day period. It was developed in line with the

US Food and Drug Administration PRO Guidance. The diary is used to assess the presence or absence of a broad range of CeD symptoms including diarrhea, constipation, abdominal pain, bloating, flatulence, nausea, rash, fatigue, headache and difficulty thinking. For the purpose of this study, a one-day diary (instead of seven days) was collected.

The CDSD scores go on a scale from 0 to 10 (0-70 if using for all 7 days) with lower scores representing fewer symptoms and higher scores indicated greater symptom severity(Adelman et al., 2012).

3.5.9 Diet Adherence.

The Celiac Disease Adherence Test (CDAT) is a clinically relevant, easily administered,

7-item instrument on a 5-point Likert scale that allows for standardized evaluation of GFD adherence. The CDAT assesses four different characteristics (celiac symptoms, self-efficacy,

reasons to follow a GFD and perceived adherence to a GFD) of adherence to the GFD. The tool requires little time to complete, is simple to administer and score; the additive total score ranges from 0 to 35. Excellent or very good adherence to a GFD is marked with scores below 13; moderate adherence with scores between 13 and 17 and finally scores above 17 indicate fair or poor adherence to the diet (D. A. Leffler et al., 2009).

The CDAT was correlated with serological variables, histological variables and interviews administered with registered dietitians (included a 3-day food record, food ingredient quiz, and clinical interview) (D. A. Leffler et al., 2009). Domains relevant to GFD adherence were identified by an expert panel of researchers. Initially the questionnaire was composed of 85 items, which was narrowed down to 41 items based on correlations with the standardized dietitian evaluation scores. Using logistic regression with a predicted accuracy of 88%, the tool was tapered down to 7 questions. The tool meets essential criteria for reliability (test-retest reliability; Pearson r=0.82) and validity (face, internal and external). Dowd et al. also displayed acceptable level of test-retest reliability in his study (Pearson r=0.61) (Dowd & Jung, 2017).

Leffler et al. (2009) explains that this GFD adherence questionnaire is superior to tissue transglutaminase serology. Lau et al. looked at GFD adherence assessment using CDAT and

Biagi questionnaires in patients with CeD and found that CDAT alone was not superior to tissue transglutaminase serology (IGA-TTG, p=.70). Whereas the combination of both CDAT and

Biagi questionnaires was significantly superior to IGA-TTG in detecting GFD adherence (p=.02)

(Lau et al., 2018).

Therefore, in addition to the 7-items, 3 additional questions, modified from Biagi’s four- questions questionnaire, were added to the CDAT(Biagi et al., 2012).

1. Do you eat gluten voluntarily? (Yes/Normal portion, Yes/Just a taste/Often,

Yes/Just a taste/rarely, No)

2. When you eat out, do you tell the person who is cooking about your disease?

(Never, Sometimes, Always)

3. Do you check labels of packaged food? (Never, Sometimes, Always)

It is important to note that in clinical settings and research studies, the tools are used alone or in conjunction with biological markers.

3.5.10 Personality traits.

The Big Five Inventory (BIF) is a validated 44 item multidimensional inventory to measure the five main dimensions of personality traits, it was developed by John, Donahue, and

Kentle in 1991 (John, Donahue, & Kentle, 1991).

This 5-point Likert scale test suggests five broad dimensions commonly used to describe the human personality: neuroticism, conscientiousness, extroversion, agreeableness and openness to experience. It consists of short phrases with relatively accessible vocabulary, and scores vary between 1 (strongly disagree) to 5 (strongly agree) (McCrae & John, 1992).

Neuroticism (subscale range: 8-40) is a measure of personality indicating the general tendency to experience negative effects such as fear, sadness, embarrassment, anger, guilt and disgust. A high score on neuroticism indicates that a person is prone to having irrational ideas, is less able to control impulses and copes poorly with stress. A low score however indicates that an individual is emotionally stable, calm, even-tempered and relaxed (John et al., 1991; Rothmann

& Coetzer, 2003).

Extraversion (subscale range: 8- 40) is a measure of sociability, assertiveness, activity and talkativeness. A high score on extraversion indicates that a person is energetic and optimistic vs a low score indicating that a person is reserved, independent and even-paced (John et al.,

1991; Rothmann & Coetzer, 2003).

Openness to Experience (subscale range: 10- 50) includes active imagination, attentiveness to inner feelings and a preference for variety. A high score on openness to experience indicates that a person is conventional in behavior and conservative in outlook. They feel more comfortable around things that are familiar vs. novel. An individual scoring low on openness to experience is curious, unconventional and willing to question authority (John et al.,

1991; Rothmann & Coetzer, 2003).

Agreeable (subscale range: 9- 45) individuals consider getting along with others important. A high score indicates that an individual is considerate, kind, generous, willing to compromise their interests with others and tend to have optimistic views. A low score indicates that the individual is disagreeable, generally unconcerned with others’ well-being, can be skeptical about others’ motives, suspicious and uncooperative (John et al., 1991; Rothmann &

Coetzer, 2003).

Conscientiousness (subscale range: 9- 45) refers to self-control and the active process of planning and organizing. A high score indicated that the individual is purposeful, strong-willed and determined. A low score on conscientiousness is associated with flexibility and spontaneity but can also mean that the person is sloppy and not reliable (John et al., 1991; Rothmann &

Coetzer, 2003).

The psychometric equivalence and external validity of the German version of the BFI was studied across age groups. Results showed a five-factor solution of personality constructs 62

that is found to be invariant across age groups. In a follow-up study, the BFI was assessed twice within a time interval of 5 months observing a moderate to high retest stability (Lang, Lüdtke, &

Asendorpf, 2001).

Table 4- Summary of survey tools used in this study

Name of Tool Measure Range and or cut-off Interpretation Eating Disorder Gives a suggestive EDDS composite cut- EDDS syntax Diagnosis Tools diagnosis of ED based off score of 16.5 suggestive of ED: (EDDS) on DSM-IV distinguishes clinical AN, BN, BED or (Krabbenborg et al., female patients with ED OSFED. 2012) An instrument specific syntax provides a diagnostic score to identify suggestive AN, BN, BED and possible OSFED Eating Pathology Designed to assess DE Results are in mean Each subscale Symptoms Inventory and cognitions. Tool has scores of subscales. describes the (EPSI) 8 subscales: Ranges of subscales: participants eating (K. T. Forbush et al., Body dissatisfaction 0 to 28 experiences 2014) Binge eating 0 to 32 Cognitive restraint 0 to 12 Purging 0 to 24 Restricting 0 to 24 Excessive Exercise 0 to 20 Muscle building 0 to 20 Negative Obesity 0 to 20 Celiac Disease Food Designed to query eating Subscale ranges and High scores are and Attitudes attitudes and behaviors overall CD-FAB scores suggestive of high Behaviors scale (CD- CeD specific. Tool has 3 are presented disordered eating FAB) factors: Overall Range between attitudes and (R.-M. Satherley et al., Overall CD-FAB 11 and 77 behaviors. 2018) Food attitudes 3 to 21 Fear response 4 to 28 Adaptive response 4 to 28 Celiac Disease Quality Designed to assess the Results are presented in Higher scores of Life (CD-QoL) quality of life in adults an overall CDQoL indicating a higher (Dorn et al., 2010) with CeD. scores and subscale degree of QoL Tool has 4 subscales: scores. Dysphoria Final scores and Limitations subscale scores have a Health concerns possible range of 0-100 Inadequate treatment

State Trait Anxiety Designed to assess state A cut-off point above Higher scores Inventory (STAI) anxiety (existing state) 39 suggests clinically indicate higher state (Julian, 2011) or trait anxiety significant symptoms and/or trait anxiety. (predisposition to for each subtest: state Those with scores anxious response) anxiety and trait anxiety above cut-off scores (greater than 39), suggest symptoms of state and/or trait anxiety Center for Designed to measure Final scores have a Higher scores Epidemiologic Studies symptoms defined by the possible range of 0-60 indicate greater Depressive Scale DSM-V for a major Cutoff scores (15 or depressive symptom. (CES-D) depressive episode. greater) Those who score (Radloff, 1977) above cutoff scores (15 or greater) may be at risk for clinical depression Celiac Disease Designed for patient to The CDSD scores go on Lower scores Symptoms Diary report daily symptom a scale from 0 to 10 (0- representing fewer (CDSD) diary. Used to assess the 70 if using for all 7 symptoms and higher (Adelman et al., 2012) presence or absence of a days) scores indicated broad range of CeD greater symptom symptoms. severity Celiac Disease Designed to assess Additive total score Excellent or very Adherence Test patient’s adherence to ranges from 0 to 35 good adherence to a (CDAT) GFD GFD is marked with (D. A. Leffler et al., scores below 13; 2009) moderate adherence with scores between 13 and 17 and finally scores above 17 indicate fair or poor adherence to the diet. Big Five Inventory Measures five Subscale ranges for Higher scores (BFI) dimensions of each personality trait indicate higher (John et al., 1991) personality traits: are: characteristic trait. Neuroticism 8 to 40 Conscientiousness 9 to 45 Extroversion 8 to 40 Agreeableness 9 to 45 Openness 10 to 50

3.6 Other measures collected but not used in this study

3.6.1. Serology.

In this study, participants were asked if they were willing to provide a blood sample.

When provided, the sample measured CeD serology was collected as part of the Celiac Disease

Eating and Attitudes study but were not used for the purpose of this dissertation.

3.6.2 Stool samples and swabs.

Participants were asked if they were willing to provide stool or swab samples. When provided, these samples were frozen, they will be analyzed at a later time for the purpose of another study looking at CeD patient’s microbiota in relation to ED and DE.

3.6.3 24-hour dietary recalls.

Two 24-hour recalls (one weekday and one weekend) were collected using the USDA

Automated Multiple-Pass Method (AMPM). The AMPM uses a five-step multiple pass approach to collect dietary information. It is a computerized method for an interviewer to collect 24-hour dietary recalls either in person or by telephone. Step one is an unstructured, uninterrupted listing of all foods and beverages consumed by the interviewee. The next three steps are more structured and require remembrance. The final probe step in an unstructured question for any other foods that may have been missed (Blanton, Moshfegh, Baer, & Kretsch, 2006).

3.6.4 Food Avoidance.

The Food Avoidance Checklist was created by the team at the Celiac Disease Center of

Columbia University Irving Medical Center. The purpose of the tool was to determine if CeD patients avoided foods besides gluten containing foods. Participants were given 15 choices and were asked to indicate who advised them to avoid the foods selected (Physicians, dietitians, functional medicine practitioners, etc.) and if a formal allergy diagnosis to the food was made.

An open-ended box was also provided for participants to indicate any other foods avoided not listed as part of the 15 choices. Participants were also asked to determine if they were following any dietary patterns for other reasons (kosher, halal, low FODMAP, etc.). At the end of the checklist, two questions assessing the frequency of thoughts about eating and or/food as well as thoughts about weight were asked and answers were collected via a 5-point likert scale (0=never;

5= always).

3.7 Data Analysis Plan

3.7.1 Statistical procedures.

Means, standard deviations (SD), and frequencies were used to describe demographic characteristics of the study sample. The total score and sub scores for each instrument were calculated according to the individual tool specifications. The mean, SD, minimum and maximum were computed for each scale and subscale; Pearson correlations, independent samples t-test or an analysis of variance (ANOVA) univariate model were used to consider whether there were significant differences in terms of the following covariates: demographics,

QoL scores, dietary adherence, personality inventory, anxiety and depression with the CD-FAB.

SPSS statistical software was used to analyze the data. Reliability was estimated with

Cronbach’s alpha as appropriate. Statistical analysis for each question was described as follows.

3.7.2 Analysis of RQ1a and RQ1b

RQ1a, in adults (18 – 45 years old) with CeD, how common are eating disorders as measured by the Eating Disorder Diagnostic Scale (EDDS)? b, in adults (18 – 45 years old) with CeD, how common are disordered eating as measured by

Eating Pathology Symptoms Inventory (EPSI)?

Research question 1 was answered using descriptive methods. Based on EDDS syntax, frequencies of AN, BN, BED and OSFED suggestive diagnoses were reported.

The mean and SD for EPSI subscales were reported. The EPSI tool in this sample showed internal consistency with a Cronbach’s Alpha of .693.

EPSI subscale mean scores were compared to means of inpatients or intensive day hospital patients (N=150) receiving treatment for an ED [AN (n=94, 62.7%), BN (n=22,14.6%),

OSFED (n=34, 22.7%)] at one of two academic medical centers located in the Midwest and

Eastern United States from Forbush et al.’s study (K. T. Forbush et al., 2014). Participants with

ED from Forbush et al.’s study had a mean age of 25.73 (SD=10.40). As well as to means of college students from a large Midwestern University ages 18-25 years from Forbush et al’s study

(K. T. Forbush et al., 2014).

Mean scores of male and female participants with CeD from this study (N=50) were compared to mean scores of male and female college students [men (N=502) and women

(N=625)] from Forbush et al.’s study.

An independent t-test was conducted to compare mean scores of male and female participants in this study for each EPSI subscale.

3.7.3 Analysis for RQ2 and RQ2b

RQ2, in adults (18 – 45 years old) with CeD, how common are disordered eating attitudes and behaviors in CeD based on the CD-FAB? a, in adults (18 – 45 years old) with CeD, does the CD-FAB demonstrate construct validity as compared to the EPSI?

Research question 2 was answered using descriptive statistics. Namely, the mean, SD, minimum, maximum were reported for the CD-FAB. Cronbach’s alpha was used as an internal consistency measure of reliability.

The frequency of participants that selected strongly agree, agree or agree somewhat to each of the 11 items presented in the CD-FAB tool was presented.

An independent t-test was conducted to compare the mean of the CD-FAB and subscale scores for this study sample to the mean scores of 41 adults with biopsy-diagnosed CeD recruited in the United Kingdom (UK) as part of Dr. Satherley’s research study (R.-M. Satherley et al.,

2018).

An independent t-test was conducted to compare the mean of the CD-FAB and subscale scores for this study sample to the CD-FAB and subscale mean scores of participants diagnosed with suggestive OSFED as per the EDDS.

A tertiary split was applied to the CD-FAB responses received in this dataset, to divide individuals into high, medium and low scorers based on the 33rd and 66th percentiles. Analysis of variance was used to compare EPSI scores across the three groups. 68

And independent t-test was conducted to compare EPSI mean scores of participants diagnosed with suggestive OSFED (as per the EDDS) with mean scores of EPSI subscales for those who scored in the highest tertile on the CD-FAB.

Theoretically, the CD-FAB and EPSI scales are measuring some similar construct related to eating disorders. To answer research question 2a, convergent validity of the CD-FAB was demonstrated by a positive correlation between the CD-FAB and restricting of EPSI. Restricting is covered by Satherley et al.’s two-way pathway model in explaining dysfunctional eating patterns of individuals diagnosed with CeD. Therefore, we would expect to see a positive correlation between high scores on restricting and high overall CD-FAB scores. Discriminative validity of the CD-FAB was demonstrated by no correlation between the CD-FAB and purging subscale of the EPSI. There is no reason for CD-FAB total scores to be associated with purging, so no relationship between these scores was anticipated.

3.7.4 Analysis for RQ3

RQ3, in adults (18 – 45 years old) with CeD, what are factors (demographics, personality characteristics, GI symptoms, gluten-free diet adherence, body composition) associated with disordered eating attitudes and behaviors (as measured by CD-FAB)?

The extent to which the CD-FAB covaried with other factors considered in this study

(demographics, personality characteristics, GI symptoms, gluten-free diet adherence, body composition) was addressed in two steps. The first step was descriptive and considered a simple correlation between the CD-FAB total and subscale scores and the other factor; mean differences on the CD-FAB were assessed with independent samples t-test or ANOVA models.

Secondly, regression models were used to predict CD-FAB total from the set of factors in a set of separate analyses.

3.7.5 Analysis for RQ4

RQ4, in adults (18 – 45 years old) with CeD, are disordered eating attitudes and behaviors (as measured by the CD-FAB scores) associated with QoL, anxiety, and depression?

Similarly to RQ3, RQ4 was answered in two steps. The first step was descriptive and considered a simple correlation between the CD-FAB total and subscale scores and anxiety, depression and QoL; mean differences on the CD-FAB were assessed with independent samples t-test or ANOVA models.

Secondly, regression models were used to predict QoL, anxiety and depression from the

CD-FAB in a set of separate analyses.

Table 5- Analysis of Research questions

Research Question Tools used Analysis

RQ1a, in adults (18 – 45 years EDDS descriptive methods. Based on old) with CeD, how common EDDS syntax, frequencies of are eating disorders as AN, BN, BED and OSFED measured by the Eating suggestive diagnoses were Disorder Diagnostic Scale reported (EDDS)? RQ1b, in adults (18 – 45 years EPSI -The mean and SD for EPSI old) with CeD, how common subscales were reported. are disordered eating as -EPSI subscale mean scores measured by Eating Pathology were compared to means from Symptoms Inventory (EPSI)? Forbush et al’s study. -Females and males mean scores were compared with independent t-test. RQ2, in adults (18 – 45 years CD-FAB -Descriptive statistics (mean, old) with CeD, how common SD, minimum, maximum).

are disordered eating attitudes -Cronbach’s alpha was used as and behaviors in CeD based an internal consistency measure on the CD-FAB? of reliability. -The frequency of agreement on each each of the 11 items in the CD-FAB. -An independent t-test was conducted to compare the mean of the CD-FAB and subscale scores to UK sample - A tertiary split was applied to the CD-FAB responses received in this dataset. - Analysis of variance was used to compare EPSI scores across the three groups. RQ2a, in adults (18 – 45 years CD-FAB and EPSI -CD-FAB and EPSI scales are old) with CeD, does the CD- measuring similar construct FAB demonstrate construct related to eating disorders. validity as compared to the -Convergent validity of the CD- EPSI? FAB was demonstrated by a positive correlation between the CD-FAB and restricting of EPSI. -Discriminative validity of the CD-FAB was demonstrated by no correlation between the CD- FAB and purging subscale of the EPSI. RQ3, in adults (18 – 45 years CD-FAB -The first step was descriptive old) with CeD, what are Demographics and considered a simple factors (demographics, BFI correlation between the CD- personality characteristics, GI CDSD FAB total and subscale scores symptoms, gluten-free diet CDAT and the other factor; mean adherence, body composition) BMI differences on the CD-FAB associated with disordered were assessed with independent eating attitudes and behaviors samples t-test or ANOVA (as measured by CD-FAB)? models. -Secondly, regression models were used to predict CD-FAB total from the set of factors in a set of separate analyses. RQ4, in adults (18 – 45 years CD-FAB -The first step was descriptive old) with CeD, are disordered STAI and considered a simple eating attitudes and behaviors CESD correlation between the CD- (as measured by the CD-FAB CDQoL FAB total and subscale scores scores) associated with QoL, and anxiety, depression and anxiety, and depression? QoL; mean differences on the CD-FAB were assessed with 71

independent samples t-test or ANOVA models. -Secondly, regression models were used to predict QoL, anxiety and depression from the CD-FAB in a set of separate analyses.

3.7.6 Statistical Analysis pre- and during- COVID-19.

Enrollment began on January 28th, 2020 and was halted early due to COVID-19 and all non-essential research activities required to stop recruitment. Enrollment resumed on October 16,

2020. The coronavirus disease 2019 (COVID-19) pandemic had a great impact in every aspect on people around the world. COVID-19 affected the economy, employment as well as public health. The uncertainty of the situation was very concerning for all. Anxiety and stress around the new disease and what could occur can be overwhelming and cause strong emotions in adults.

The lockdown as well as social distancing, lead to people feeling isolated and lonely which increased stress and anxiety. In a recent study looking at mental health impact of the COVID-19 pandemic on people with and without depressive or anxiety disorders in a Dutch case control cohort showed that people with the disorders both before and during the COVID-19 pandemic did not report greater increase in anxiety and depression symptoms during the pandemic.

However, individuals that did not have anxiety and depression symptoms pre-COVID-19 showed an increase in symptoms during the pandemic (Pan et al., 2020)

Nearly half the participants (n=22) were recruited pre-COVID-19 and the remaining

(n=28) during-COVID-19; the pandemic may have impacted the survey score results.

Demographics of participants recruited pre-pandemic will be compared to demographics of participants recruited during the pandemic. Anxiety, depression, QoL, EPSI scores and CD-FAB

mean scores of participants recruited pre-COVID-19 will be compared to mean scores of participants recruited during-COVID-19 with independent sample t-test and ANOVA models.

3.7.7 Privacy & Data Security.

The study data was de-identified and coded and kept in an encrypted endpoint device, only study personnel had access to this device. Immediately after enrollment, participants were assigned a code (A1 through A50). All surveys had the code, never the participants name. The key that linked the participants identifying information and code was kept in separate password- protected computer in a secure location that only the PI and study staff had access to. Informed consent was obtained ‘in person’ at the Celiac Center. The eligible participants were provided a private space if requested in the Celiac Disease Center where they completed the self- administered surveys. The anthropomorphic measurements were obtained in the privacy of one of the rooms at the Celiac Disease Center by study personnel.

Chapter 4 – Results

This chapter will summarize the reported results. This will include the characteristics of sample, reported results through tables and figures as well as the study flow.

The purpose of this study was to better understand the extent to which disordered eating attitudes and behaviors may be common in a sample of adults diagnosed with CeD, as well as the relationship of disordered eating attitudes and behaviors with various QoL measures, including anxiety and depression. Long-term, the goal is to create a new paradigm for managing clinical disease by understanding how best to assess and target those that may be at greatest risk for EDs, disordered eating attitudes and behaviors and associated morbidities.

Fifty adults aged 18 – 45 with biopsy confirmed CeD were recruited from the Celiac

Disease Center at Columbia University Irving Medical Center to form the study group.

Consecutive age-eligible individuals with known CeD were asked to participate at the Celiac

Disease Center while they waited for their doctors’ appointments. Those interested and eligible were asked to complete a variety of surveys related to eating patterns and QoL and had anthropometric measures taken. Using the data collected from recruited participants, the following research questions are analyzed in this chapter:

- RQ1a: In adults (18 – 45 years old) with CeD, how common are eating disorders as

measured by the Eating Disorder Diagnostic Scale (EDDS)?

- RQ1b: In adults (18 – 45 years old) with CeD, how common are disordered eating as

measured by Eating Pathology Symptoms Inventory (EPSI)?

- RQ2: In adults (18 – 45 years old) with CeD, how common are disordered eating

attitudes and behaviors in CeD based on the CD-FAB?

- RQ2a: In adults (18 – 45 years old) with CeD, does the CD-FAB demonstrate construct

validity as compared to the EPSI?

- RQ3: In adults (18 – 45 years old) with CeD, what are factors (demographics, personality

characteristics, GI symptoms, gluten-free diet adherence, body composition) associated

with disordered eating attitudes and behaviors (as measured by CD-FAB)?

- RQ4: In adults (18 – 45 years old) with CeD, are disordered eating attitudes and

behaviors (as measured by the CD-FAB scores) associated with QoL, anxiety, and

depression?

4.1 Study Flow

Enrollment began on January 28th, 2020 (pre-COVID-19 pandemic). Patients were prescreened by the Celiac Center dietitians and staff to determine potential age eligibility for individuals with biopsy diagnosed CeD. TC students, volunteering as Research Assistants, approached 29 prescreened patients to gauge interest in the study and 22 were recruited. Seven of the patients were eligible but didn’t want to take part in the study: 3 of the 7 patients were in a rush to leave the hospital and the other 4 showed no interest in participating.

Enrollment was paused in March 2020 due to COVID-19 and all non-essential research activities required to stop recruitment. Enrollment resumed on October 16, 2020 and one TC student was granted approval to resume data collection. The Celiac Center dietitians determined

33 patients with potential age eligibility and biopsy diagnosis of CeD of which 28 were recruited.

Five of the patients were eligible but didn’t want to take part in the study: 3 of the 5 patients 75

were in a rush to leave the hospital and the other 2 showed no interest in participating. A total of

50 patients (among the 62 approached, 81%) were recruited pre- and during-COVID-19 pandemic (Figure 5).

Figure 5- Study Flow

4.2 Demographic and patient characteristics of study sample

The mean age of adults recruited for this study was 29.56 years (SD= 7.40), the mean age at diagnosis was 22.76 years (SD= 9.28). Participants in this study sample have had CeD for an average of 7.2 years (SD= 5.31), 40% of participants have had the diagnosis in the last 1 to 4 years, 40% between 5 and 10 years, and 10% for more than 10 years. The Tanita scale body composition showed an average BMI of 23.25 (SD= 4.02) (Table 6).

Table 6- Demographic and patient characteristics of study sample

Adults (N=50) Mean SD Range Age 29.56 7.40 19- 45

Age at diagnosis (number of years) 22.76 9.28 4.58- 39.75

BMI (kg/m2) 23.15 4.02 16.00- 35.90

Years since diagnosis 7.20 5.31 1.00- 21.67

Overall, 10% of the participants identified as Hispanic, 94% as White, 2% as Black or

African American, 4% as Asian and 6% as other race. More than half of adults recruited in this study were college graduates (64%), 16% had some college education and 20% had a postgraduate degree. Participants with some college education had a mean age of 22.38 (6.00).

When looking at household income, 62% of adults recruited in this study had an income higher than $100,000, 22% between $50,000 and $100,000, 8% less than $50,000.

About half the participants (48%) were currently seeing a Registered Dietitian

Nutritionist (RDN), 32% had seen an RDN in the past, and 28% of participants had never seen and RDN. Five of the patients who had seen an RDN in the past, reported that they didn’t feel the need to see one today. And seven patients reported that the dietitian they saw was not helpful and did not have enough knowledge about their diagnosis. Six of the patients who had never seen a dietitian, reported that not seeing an RDN was a sign of negligence on their behalf.

Participants self-reported current GI symptoms (CDSD) in the past 24 hours prior to recruitment. The GI symptoms reported were diarrhea (N=11, 22%), constipation (N=25, 50%) abdominal pain (N=15, 30%), bloating (N=23, 46%) and nausea (N=12; 24%). Accordingly,

16% of participants reported no current symptoms, 38% reported having one symptom, 18% reported 2 symptoms, 14% reported 3 symptoms and 14% reported 4 symptoms (Table 7).

Table 7- Demographic and patient characteristics of study sample

Adults (N=50) N % Years since diagnosis 1 - 4 20 40% 5 - 10 20 40% >10 10 20% Gender Female 35 70% Male 15 30% Ethnicity Hispanic 5 10% Non- Hispanic 45 90% Race White 47 94% Black or African American 1 2% Asian 2 4% Other 3 6% Education Some college 8 16% College graduate 32 64% Postgraduate 10 20% Household income <$50,000 4 8% $50,000 to $100,000 11 22% >$100,000 31 62% Did not disclose 4 8% RDN visit RDN currently 24 48% RDN past only 16 32% RDN never 14 28% Current GI symptoms No reported symptoms 8 16% 1 reported symptom 19 38% 2 reported symptoms 9 18% 3 reported symptoms 7 14% 4 reported symptoms 7 14%

4.3 RQ 1: ED and DE in CeD

4.3.1 ED in CeD

- RQ1a: In adults (18 – 45 years old) with CeD, how common are eating disorders as

measured by the Eating Disorder Diagnostic Scale (EDDS)?

Research question 1 was answered using descriptive methods. Frequency and percentages were reported for EDDS and the mean, SD, minimum, maximum and reliability were reported for EPSI.

The EDDS is a brief self-report measure of 23 items designed for AN, BN and BED based on the DSM-V. An overall symptom composite cut-off score of 16.5 accurately distinguishes ED in females (Krabbenborg et al., 2012). The EDDS will also diagnose possible

Other Specified Feeding and Eating Disorders (OSFED) as per the DSM-V. According to

Krabbenborg et al. the cut-off score of 16.5 may be helpful in identifying patients with AN, BN and BED, but more research is needed to confirm this cut-off is useful for OSFED presentations

(Krabbenborg et al., 2012). However, an instrument specific syntax provides a diagnostic score to identify suggestive AN, BN, BED and possible OSFED.

All 50 participants with biopsy-diagnosed CeD filled out the questionnaire. One adult with CeD had a suggestive diagnosis of BED (2%), 6 had possible OSFED (12%) and all remaining 43 adults (86%) had no suggestive ED diagnosis as per the EDDS. For participants with suggestive diagnosis of possible OSFED, one had possible low frequency BN (2%) and 3 had night eating syndrome (6%) (Table 8).

Table 8-Prevalence of Eating Disorders as per the EDDS

Suggestive EDDS Diagnosis Frequency Percent (N=50) Anorexia Nervosa (AN) 0 0% Bulimia Nervosa (BN) 0 0% Binge Eating Disorder (BED) 1 2% Possible Other Specified Feeding and Eating Disorder 6 12% (OSFED) No Eating Disorder 43 86%

See appendix Q for EDDS composite scores and EDDS syntax for sample (N=50)

4.3.2 DE in CeD

- RQ1b: In adults (18 – 45 years old) with CeD, how common are disordered eating as

measured by Eating Pathology Symptoms Inventory (EPSI)?

The Eating Pathology Symptoms Inventory (EPSI) queries an individual’s multidimensional eating pathology. There are 8 sub-scales, body dissatisfaction (dissatisfaction with body weight and/or shape), binge eating (ingestion of large amounts of food and accompanying cognitive symptoms), cognitive restraint (cognitive efforts to limit or avoid eating, whether or not such attempts are successful), purging (self-induced vomiting, laxative use, diuretic use, and diet pill use), excessive exercise (physical exercise that is intense and/or compulsive), restricting (concrete efforts to avoid or reduce food consumption), muscle building (desire for increased muscularity and muscle building supplement use), and negative attitudes toward obesity (negative attitudes toward individuals who are overweight or obese).

Table 9 shows the mean score and SD of each subscale in 50 adults with biopsy diagnosed CeD. Table 9 also shows means from Forbush et al’s study for inpatients or intensive day hospital patients (N=150) receiving treatment for an ED [AN (n=94, 62.7%), BN

(n=22,14.6%), OSFED (n=34, 22.7%)] at one of two academic medical centers located in the

Midwest and Eastern United States (K. T. Forbush et al., 2014). Participants with ED from

Forbush et al.’s study had a mean age of 25.73 (SD=10.40). Table 9 also shows means of college students of a large Midwestern University [men (N=502) and women (N=625)] ages 18-25 years from Forbush et al’s study (K. T. Forbush et al., 2014).

Overall, EPSI scores of adults with CeD were relatively low. The mean score for body dissatisfaction was 9.84 (SD=7.79) for participants with CeD; Forbush et al. found that patients with a diagnosed ED had a mean score of 27.79 (SD=7.04) and that of college students was 80

17.44 (SD=7.35). The second subscale, binge eating, had a mean score of 8.12 (SD=6.54), ED patients in Forbush et al’s sudy had a mean score of 17.05 (SD=9.01) and college students had a mean of 18.74 (SD=5.43). The mean score for cognitive restraint was 4.54 (SD=2.74) compared to 12.60 (SD=3.24) in patients with ED from Forbush et al’s study and 7.64 (SD=2.96) in college students. The mean score for purging was .24 (SD=.82), compared to 11.51 (SD=6.02) in patients with ED and 6.65 (SD=1.97) in college students. The mean score for restricting was

4.86 (SD=5.36) compared to 22.31 (SD=6.27) in ED patients and 10.92 (SD=4.37) in college students. The mean score for excessive exercise was 5.57 (SD=4.96) compared to 15.18

(SD=7.50) in patients with ED and 12.43 (SD=5.20) in college students. The mean score for negative attitudes towards obesity was 3.58 (SD=4.88) in patients with CeD; compared to 15.58

(SD=6.85) in ED patients and 14.79 (SD=4.68) in college students. Finally, patients with CeD had a mean score of 2.16 (SD=2.83) for the muscle building subscale, ED patients had a mean score of 6.95 (SD=2.28) and college students had a mean score of 8.21 (SD=3.43) (K. T.

Forbush et al., 2014).

Forbush et al. explained that EPSI scale scores generally were significantly different between the ED patient and college samples (K. T. Forbush et al., 2014). Patients with ED had significantly higher scores than college studies on most EPSI scales (K. T. Forbush et al., 2014).

All EPSI subscale mean scores of adults with CeD in this study were lower than mean scores of patients with ED and college students from Forbush et al’s study. However, the EPSI eating pathologies mean scores may be suggesting that something was going on, but unclear whether this is problematic. Adults with CeD may be experiencing DE, but the specific pathology as defined and suggested by EPSI, was relatively low.

Table 9-EPSI subscale mean scores for participants with CeD compared to mean scores of participants in Forbush et al.’s study.

Forbush et al. (2014)ª N=150 N=1,127 N=50

Subscale Mean (SD) Mean (SD) Mean (SD) Study EPSI (N=50) Range Diagnosed ED College Students Sample w/CeD w/o ED Body dissatisfaction 0 to 28 27.79 (7.04) 17.44 (7.35) 9.84 (7.79)

Binge eating 0 to 32 17.05 (9.01) 18.74 (5.43) 8.12 (6.54)

Cognitive Restraint 0 to 12 12.60 (3.24) 7.64 (2.96) 4.54 (2.74)

Purging 0 to 24 11.51 (6.02) 6.65 (1.97) .24 (.82)

Restricting 0 to 24 22.31 (6.27) 10.92 (4.37) 4.86 (5.36)

Excessive Exercise 0 to 20 15.18 (7.50) 12.43 (5.20) 5.57 (4.96)

Negative Obesity 0 to 20 15.58 (6.85) 14.79 (4.68) 3.58 (4.88)

Muscle Building 0 to 20 6.95 (2.28) 1.53 (1.58) 2.16 (2.83)

ª Mean (SD) of patients with a diagnosed ED from Forbush et al’s study (K. T. Forbush et al., 2014) Diagnosed ED: inpatients or intensive day hospital patients; AN(n=94, 62.7%), BN (n=22,14.6%), OSFED (n=34, 22.7%). College students 18-25 yrs.; mean BMI males = 24.26; mean BMI females = 23.28

Table 10 compares mean scores of male and female participants with CeD from this study to mean scores of male and female college students [men (N=502) and women (N=625)] from Forbush et al.’s study. Male and female college students from Forbush et al’s study have higher means for EPSI subscales compared to male and females with CeD from this study.

However, it is important to note that college students recruited in Forbush et al.’s study were between 18 and 25 years old compared to 18 and 45 years old in this study; and the sample size in Forbush et al.’ study (N=1,127) is 22 times larger than the sample size in this study (N=50).

Table 10- Comparison of EPSI subscale scores by Gender with College Students from Forbush et al.’s study.

Mean (SD) Mean (SD) Mean (SD) Study Sample Mean (SD) Maximum Study Sample Male College w/CeD Female College attainable w/CeD Male Students Female Students EPSI subscale score (N=15) (N=502) ª (N=35) (N=625) ª Body Dissatisfaction 28 4.27 (4.04) 13.40 (5.73) 12.23 (7.81) 20.68 (6.89))

Binge Eating 32 6.87(4.84) 18.17 (5.34) 8.66 (7.15) 19.21 (5.45)

Cognitive Restraint 12 3.33 (1.59) 6.70 (2.80) 5.06 (2.98) 8.39 (2.86)

Purging 24 .00 (.00) 6.39 (1.71) .34 (.97) 6.86 (2.13)

Restricting 24 3.67 (5.34) 10.29 (4.09) 5.37 (5.36) 11.44 (4.53)

Excessive Exercise 20 5.80 (4.77) 13.10 (5.27) 5.47 (5.11) 11.90 (5.07)

Negative Obesity 20 2.80 (3.10) 15.18 (4.69) 3.91 (5.48) 14.48 (4.65)

Muscle Building 20 3.53(3.60) 9.75 (4.12) 1.57 (2.24) 6.98 (2.05)

ª Mean (SD) of patients with a diagnosed ED from Forbush et al’s study (K. T. Forbush et al., 2014) College students 18-25 yrs.; mean BMI males = 24.26; mean BMI females = 23.28

Males versus Females in CeD adults

Unlike many other self-reported measures of eating pathologies, Forbush et al. showed that the EPSI subscales showed clear evidence for replicability (factor structure replicability) in males and females (K. T. Forbush et al., 2014). In table 11, EPSI subscale scores were compared between males (N=15) and females (N=35); scores were relatively low for both genders. An independent t-test indicated that there is a significant difference between means of males and females for body dissatisfaction (t (46.09) =-4.73, p<.001). Females have higher means for body dissatisfaction then males in this study. There is a significant difference between females and males means for cognitive restraint (t (45.48) =-2.65, p=.011), and for purging (t (34.00) =-2.10, 83

p=.044). Once again, females have higher means for cognitive restraint and purging then males in this study. Yet, no significant difference was found between females and male means for binge eating, restricting, excessive exercise, negative attitudes towards obesity and muscle building (p>.05). Forbush et al.’s found significantly higher means for females compared to males in most subscales, with the exception of significantly higher means in males than females for excessive exercise, muscle building and negative attitudes toward obesity (p<.05)(K. T.

Forbush et al., 2014). Keeping in mind that overall scores are relatively low, the mean scores for muscle building for males is more than twice the mean score for females in the study sample with CeD, albeit the difference was not significant.

Table 11- Comparison of EPSI Subscales scores in Male and Female participants with Celiac Disease

Mean (SD) Mean (SD) Study Study Sample t-testa Maximum Sample w/CeD attainable w/CeD Male Female EPSI subscale score (N=15) (N=35) t df p Body Dissatisfaction 28 4.27 (4.04) 12.23 (7.81) -4.73 46.09 .000***

Binge Eating 32 6.87(4.84) 8.66 (7.15) -8.90 48 .381

Cognitive Restraint 12 3.33 (1.59) 5.06 (2.98) -2.65 45.48 .011*

Purging 24 .00 (.00) .34 (.97) -2.10 34.00 .044*

Restricting 24 3.67 (5.34) 5.37 (5.36) -1.03 48 .308

Excessive Exercise 20 5.80 (4.77) 5.47 (5.11) .21 48 .833

Negative Obesity 20 2.80 (3.10) 3.91 (5.48) -.73 48 .465

Muscle Building 20 3.53(3.60) 1.57 (2.24) 1.95 18.81 .066 *p<.05 ** p<.01 *** p<.001 aIndependent t-test comparing means of CeD males too means of CeD females

4.3.3 Summary findings

In this study, 14% of adults with CeD between the ages of 18 and 45 years had a suggestive ED; 2% had BED (N=1), 12% had OSFED (N=6). To a lesser extent, DE as measured by EPSI reported by CeD adults (18 – 45 years old) in this study, include body dissatisfaction, binge eating, cognitive restraint, restricting, negative attitudes towards obesity, excessive exercising and muscle building. However, mean EPSI scores were much lower than adults with

ED and college students between the ages of 18 and 25 years from Forbush et al.’s study. There was a significant difference between means of males and females for EPSI subscale of body dissatisfaction (p<.001), cognitive restraint (p<.05), and for purging (p<.05). Females had higher means for body dissatisfaction, cognitive restraint and purging compared to males in this study; although, overall pathology, as defined and detected by EPSI, was relatively low for both gender groups.

4.4 RQ2: Disordered Eating attitudes and behaviors (CD-FAB) in adults with CeD

4.4.1 RQ2

- RQ2: In adults (18 – 45 years old) with CeD, how common are disordered eating

attitudes and behaviors in CeD based on the CD-FAB?

Research question 2 was answered using descriptive statistics. The mean, SD, minimum, maximum were reported for the CD-FAB. Cronbach’s alpha is used as an internal consistency measure of reliability.

The Celiac Disease-specific food attitudes & behaviors scale (CD-FAB) is an eleven-item validated tool that queries eating attitudes and behaviors resulting from beliefs around cross

contamination, and food safety (i.e., handling of food, trust, risk-taking and food safety). The three subscales or factors it covers are as follows:

- Food Attitudes: described concerns around interacting with food and cross contact.

- Fear Response: described behaviors designed to control food preparation and a fear of

trying new foods

- Adaptive response: described behaviors that allowed individuals to manage their food

attitudes without compromising their lifestyle

Scoring high on the CD-FAB may display a hypervigilance around food and limit food intake. Increased CD-FAB scores where associated with impaired QoL and psychological. distress in individuals with a biopsy-confirmed diagnosis of CD (R.-M. Satherley et al., 2018).

No cut-off currently exists for the CD-FAB scale, it is a relatively new tool.

The distribution of the CD-FAB scores across this sample are spread out around the mean

36.96 (15.30) as shown in figure 6, with a maximum score of 66 out of a possible 77. The CD-

FAB subscale scores have been assessed, the mean score for food attitudes is 14.46 (7.39) with a maximum score of 17 out of a possible 21, fear response is 8.18 (4.10) with a maximum score of

27 out of 28, and adaptive response is 14.32 (5.95) with a maximum score of 27 out of 28 (Table

11).

The CD-FAB subscales and total score showed good internal consistency with

Cronbach’s Alpha above 0.7 in all cases, except for fear response (.673) subscale. Looking at the total statistics for each question in the subscale fear response, if question 5 (Because of my

Celiac Disease, I find it hard to eat gluten-free foods that look like the gluten-containing foods that have made me ill in the past) was removed, the Cronbach’s Alpha increases to .723.

Table 12- Total CD-FAB Scores+ and Subscales with Cronbach’s alpha

Range of scale and Mean (SD) Min Max Cronbach’s alpha subscales N=50

Food Attitudes 3 to 21 14.46 (7.39) 3.0 17.0 .874

Fear Response 4 to 28 8.18 (4.10) 4.0 27.0 .673*

Adaptive Response 4 to 28 14.32 (5.95) 4.0 27.0 .830

CD-FAB Total 11 to 77 36.96 (15.30) 11.0 66.0 .905

+Higher CD-FAB scores suggest worse CeD-specific food attitudes and behaviors *Cronbach’s Alpha if CD-Fab5 deleted is .723 CD-Fab5: Because of my CeD I find it hard to eat gluten-free foods that look like the gluten- containing-foods that have made me ill in the past Note: high food attitudes, fear response, adaptive response and CD-FAB total indicates high disordered eating attitudes and behaviors

Figure 6- CD-FAB Scores Frequency Distribution

Table 13 shows the number of participants that selected strongly agree, agree or agree somewhat to each of the 11 items presented in the CD-FAB tool. Because of their Celiac, 50% reported that they were afraid of eating out, 46% get worried when eating with strangers, 42% reported they were afraid to touch gluten-containing foods and 34% of participants reported they were concerned about being near others when eating gluten. Despite having CeD, 80% reported that if they asked questions, they could normally find gluten-free foods to eat, 54% reported that being contaminated by gluten in the past hasn’t stopped them from enjoying restaurants, 48% reported being comfortable eating gluten-free food from other people’s kitchens and 46% of participants enjoy going out for meals as much as they did before their diagnosis.

Table 13- Prevalence of participants scoring strongly agree, agree or agree somewhat per CD-FAB item.

Agreement CD-FAB questions (N, %)

Food Attitudes Because of my celiac… I am afraid to eat outside my house N=25, 50% I am afraid to touch gluten-containing foods N=21, 42 % I get concerned being near others when they are eating gluten N=17, 34 % Fear Response Because of my celiac… I get worried when eating with strangers N=23, 46 % My concerns about cross-contamination prevent me from going to social events N=15, 30% involving food I find it hard to eat gluten-free foods that look like the gluten-containing-foods that have made me ill in the past N=12, 24% I will only eat food that I have prepared myself N=8, 16% Adaptive Response Despite having Celiac Disease… If I ask questions, I can normally find gluten-free food to eat N=40, 80% Being contaminated by gluten in the past hasn’t stopped me from enjoying N=27, 54% restaurants I am comfortable eating gluten-free food from other people’s kitchens N=24, 48% I enjoy going out for meals as much as I did before my diagnosis N=23, 46%

The distribution of the CD-FAB and subscale scores for this study sample can be compared to the mean scores of 41 adults with biopsy-diagnosed CeD recruited in the United

Kingdom (UK) as part of Dr. Satherley’s research study (R.-M. Satherley et al., 2018).

Participants were between the ages of 18 and 69 [mean age 40.59 (18.24)], 23.1 % were male

(N=12) and 29% were female (N=29). The CD-FAB total mean score for the UK sample was

39.71 (7.26), which is slightly higher than the mean score for this study sample. An independent t-test indicated that there was no significant difference between overall CD-FAB scores of adults with CeD in this sample (n=50) and overall CD-FAB scores of participants with CeD in the UK sample [t(89) =-1.06, p=.29].

Table 14 shows the CD-FAB total and subscale scores for the participant with suggestive diagnosis of BED, and participants with suggestive diagnosis of possible OSFED as per the

EDDS. An independent t-test indicated that there was no significant difference between overall

CD-FAB scores of adults with CeD (n=50) and overall CD-FAB scores of participants with CeD with suggestive diagnosis of OSFED as per the EDDS [t(54) =-1.47, p=.147]. However, although not statistically significant, total CD-FAB scores of participants with suggestive OSFED as per the EDDS [CD-FAB total mean=46.50 (12.01)] had a meaningful higher mean score than the whole sample [CD-FAB mean score=36.96 (15.30)].This may suggest that individuals with high disordered attitudes and behaviors (based on the CD-FAB) may be sharing some similarities to those with a suggestive OSFED diagnosis and, with future research, could be used to help identify those at greatest risk

Table 14- Overall CD-FAB and subscale scores of individuals with diagnosed ED and possible OSFED.

Scores Mean (SD) Mean (SD) Mean (SD) suggestive suggestive UK sample a Sample Diagnosis of diagnosis of N=41 (n=50) BED possible OSFED (n=1) (n=6) Food attitudes 14.46 (7.39) 8.00 19.7 (5.19) 9.49 (4.57)

Fear Response 8.18 (4.10) 3.00 11.00 (4.19) 11.8 (4.57)

Adaptive Response 14.32 (5.95) 13.00 16.33 (4.84) 18.41 (6.00)

Overall CD-FAB 36.96 (15.30) 24.00 46.50 (12.01) c 39.71 (7.26) b a Mean (SD) of 41 adult participants with biopsy-diagnosed CeD in the UK, based on Satherley et al.’s study. b independent t-test between overall CD-FAB scores for this sample and overall CD-FAB scores for the UK sample t(89)=-1.06, p=.29 c independent t-test between overall CD-FAB scores for this sample and overall CD-FAB scores of participants diagnosed with OSFED sample t(54)=-1.47, p=.147 Note: high food attitudes, fear response, adaptive response and CD-FAB total indicates high disordered eating attitudes and behaviors CD-FAB scores and subscale score means of 43 participants with no suggestive diagnosis of ED as per EDDS were 35.93 (15.42) and 13.95 (7.48), 7.91 (3.96), and 14.07 (6.15) respectively. No significant differences were found when comparing means of 43 participants to means of participants with suggestive ED as per EDDS.

4.4.2 EPSI mean scores as per CD-FAB scorers (based on tertiary split)

To replicate Satherley et al.’s thesis work on the CD-FAB, further analysis was done. A tertiary split was applied to the CD-FAB responses received in this dataset, to divide individuals into high, medium and low scorers based on the 33rd and 66th percentiles. By using a tertiary split, differences in outcomes were explored between high, medium and low CD-FAB scores.

Analysis of variance was used to compare EPSI scores across the three groups. As per the tertiary split around total CD-FAB scores, 34 % (N=17) scored low between 11 to 27, 32%

(N=16) scored medium between 30 to 43 and 34% (N=17) scored high on the overall CD-FAB measure between 44 to 66. The one-way ANOVAs found that means on EPSI subscales of individuals who scored high, medium and low on the CD-FAB were not significantly different 90

(Table 15). This may suggest that individuals with the highest disordered attitudes and behaviors

(based on the CDFAB) do not seem to share characteristics with those who have the most disordered eating pathology (as described by EPSI).

Table 15- EPSI mean scores CD-FAB Total scores tertiary split CD-FAB Total Score Means ANOVA

Low Score Medium Score High score F Statistic p-value N=17 N=16 N=17 (11 - 27)a (30 - 43) a (44-66) a EPSI Subscales Body Dissatisfaction 7.88 (7.99) 10.88 (8.24) 10.82 (7.21) .81 .452 Binge Eating 8.53 (6.90) 8.06 (5.79) 7.76 (7.19) .06 .945 Cognitive Restraint 4.35 (2.94) 4.88 (2.68) 4.41(2.74) .17 .843 Purging .12 (.33) .44 (1.21) .18 (.73) .69 .51 Restricting 4.41(5.56) 3.25 (4.22) 6.82 (5.79) 2.00 .147 Excessive exercising 6.53 (5.76) 5.34 (4.64) 4.82 (4.52) .517 .600 Negative Obesity 5.18 (5.62) 3.50 (4.29) 2.06 (4.35) 1.80 .177 Muscle Building 1.53 (2.21) 2.38 (3.01) 2.59 (3.24) .653 .525

*p<.05 **p<.01 ***p<.001 a Range of CD-FAB scores within each tertile.

4.4.3 RQ2a

- RQ2a: In adults (18 – 45 years old) with CeD, does the CD-FAB demonstrate construct

validity as compared to the EPSI?

As hypothesized, the CD-FAB and EPSI scales which are theoretically measuring a similar construct related to restricting, are positively associated. Convergent validity of the CD-

FAB was demonstrated by a small positive, albeit not significant correlation between the CD-

FAB and restricting (r=.27, p=.057) subscale of EPSI. This indicated that the total CD-FAB score was similar to measures of DE related to restricting food, indicating good convergent validity.

Theoretically, the CD-FAB and EPSI scales are not measuring a similar construct related to purging. Discriminant validity of the CD-FAB was demonstrated by no correlation with purging (r=.03, p=.82). This indicated that the total CD-FAB score was not related to measures of DE related to purging, indicating good discriminant validity (Table 16).

Table 16- Pearson Correlations between CD-FAB total score and subscale with EPSI subscale

Food Attitudes Fear Response Adaptive Response CD-FAB Total

EPSI subscales r p-value r p-value r p-value r p-value

Restricting .25 a .075 .23 a .109 .23 a .117 .27 a .057

Purging .10 .48 .02 .91 -.05 .71 .03 .82

According to Cohen (1988)’s guidelines: a Pearson correlation is small (.1 < r < .3) b Pearson correlation is medium (.3

4.4.4 Summary of findings

In adults (18 to 45 years old) with CeD, the distribution of the CD-FAB scores were spread out around the mean 36.96 (15.30) with a maximum score of 66 out of a possible 77. There is no cut-off to measure disordered eating attitudes and behaviors, however as per the tertiary split around total CD-FAB scores, 34 % (N=17) scored low between 11 and 27, 32% (N=16) scored medium between 30 and 43; and 34% (N=17) scored high on the overall CD-FAB between 44 and 66.

There was no statistically significant difference between overall CD-FAB scores of adults with CeD (n=50) and overall CD-FAB scores of participants with CeD with suggestive diagnosis of OSFED as per the EDDS. However, there was a meaningful difference between the means;

CD-FAB scores of participants with suggestive OSFED [46.50 (12.01)] were 10-points higher

compared to the mean of all adults in this sample [36.96 (15.30)]. The CD-FAB mean of participants with suggestive OSFED fell into the highest tertile of CD-FAB scorers (44 to 66).

Convergent validity of the CD-FAB was demonstrated by a positive correlation between the CD-FAB and restricting (r=.27, p=.057) subscale of EPSI. Discriminant validity of the CD-

FAB was demonstrated by no correlation with purging (r=.03, p=.82).

4.5 RQ3: Factors associated with CD-FAB

- RQ3: In adults (18 – 45 years old) with CeD, what are factors (demographics, personality

characteristics, GI symptoms, GFD adherence, body composition) associated with

disordered eating attitudes and behaviors (as measured by CD-FAB)?

The aim of RQ3 was to explore the associations between CD-FAB scores and factors such as gender, age, years since diagnosis, household income, education level, RDN visit, personality characteristics, GI symptoms, GFD adherence and body composition, to gain a greater understanding of the influence of disordered eating attitudes and behaviors in CeD. The

CD-FAB total score and subscale scores were treated as dependent variables and gender, age, years since diagnosis, household income, education level, RDN visit, symptoms (CDSD scores), personality factors (BFI scores), GFD adherence (CDAT, Biagi), and body composition (Tanita scale) were treated as independent variables. The extent to which the CD-FAB varied with other factors considered in this study (gender, age, years since diagnosis, household income, education level, RDN visit, personality characteristics, GI symptoms, gluten-free diet adherence, body composition) was addressed. First, each of the covariates was tested independently with a

correlation and/or an independent t-test, then all the covariates were simultaneously tested with a regression or ANOVA model.

4.5.1 Factor: Gender

An independent-samples t-test was conducted to compare total CD-FAB scores and subscale scores of adults (18 -45 years old) between female and male. Total CD-FAB scores and subscale scores in adults with CeD are not affected by gender difference. Levene’s test indicated that the variances were equal across genders (p-value > 0.05). With equal variances assumed, the total CD-FAB mean scores were not significantly different between female and male (t (48)

=.91, p=.365). The CD-FAB subscale scores (food attitudes, fear response and adaptive response) were also not significantly different between female and male (t (48) =.91, p=.365; t

(48) =.20, p=.841 and t (48) =1.08, p=.285).

Table 17- Total CD-FAB Scores+ and Subscales by Gender

Female (N=35) Male (N=15) t-test of Means

Range of scores Mean SD Mean SD t df p-value

Food Attitudes 3 to 21 15.09 6.98 13.00 8.32 .91 48 .365

Fear Response 4 to 28 8.26 3.80 8.00 4.87 .20 48 .841

Adaptive Response 4 to 28 14.91 5.52 12.93 6.85 1.08 48 .285

CD-FAB Total 11 to 77 38.26 13.91 33.93 18.33 .91 48 .365

+Note: high food attitudes, fear response, adaptive response and CD-FAB total indicates high disordered eating attitudes and behaviors.

4.5.2 Factors: Age, Years since diagnosis, BMI

The overall CD-FAB scores and subscale scores (food attitudes and fear response) respectively, were not correlated with participant’s age at recruitment (r= .03; r=-.06, r=-.02).

The subscale scores for adaptive response were correlated with age (r=.16) suggesting that the older the individual was the higher the scores for adaptive response, however the relationship was small as per Cohen’s guidelines and not significant (p>.05) (Cohen, 1988).

There was a significant negative correlation between overall CD-FAB scores and subscale scores (food attitudes, fear response, adaptive response) and the number of years since diagnosis (r=-.49, r=-.52, r=-.42, r=-.33; p<.05). This suggested that the most recently diagnosed had higher CD-FAB scores and thus higher disordered eating attitudes and behaviors.

Conversely, those with greater number years since diagnosis had lower disordered eating attitudes and behaviors.

There was a small negative, correlation between CD-FAB total scores and subscale scores (food attitudes, fear response, adaptive response) and BMI (r=-.17, r=-.16, r=-.15, r=-.14).

This relationship suggested that the lower the participant’s BMI was the higher their CD-FAB scores; however, the negative correlations found were small as per Cohen’s guidelines and not significant (p>.05) (Cohen, 1988).

Table 18- Pearson Correlations between CD-FAB+ and age, years since diagnosis and BMI.

Food Attitudes Fear Response Adaptive Response CD-FAB Total

r p-value r p-value r p-value r p-value

Age -.06 .686 -.02 .886 .16 a .260 .03 .840

Years since Diagnosis -.52 c <.001*** -.42 a .002 ** -.33 a .018* -.49 b <.001***

BMI -.16 a .277 -.15 a .302 -.14 a .322 -.17 a .235

According to Cohen (1988)’s guidelines: a Pearson correlation is small (.1 < r < .3) b Pearson correlation is medium (.3

4.5.3 Factors: Household income, Education level, RDN visit

A one-way ANOVA was conducted to compare total CD-FAB scores and subscale scores of adults (18 -45 years old) between education levels. Total CD-FAB scores and subscale scores in adults with CeD are not affected by education levels. The total CD-FAB mean scores and subscale scores (food attitudes, fear response, adaptive response) were not significantly different between participants who had some college, are college graduates or had postgraduate training

(p>.05).

A one-way ANOVA was conducted to compare total CD-FAB scores and subscale scores of adults (18 -45 years old) between different income levels. Total CD-FAB scores and subscale scores in adults with CeD are not affected by income levels. The total CD-FAB mean scores and subscale scores (food attitudes, fear response, adaptive response) were not significantly different between participants with household incomes <$50,000, between $50,000 and $100,000 and greater than $100,000. 96

Table 19-Overall CD-FAB+ and subscale scores per education level, household income

Food Fear Adapti Overall Att. Resp. ve CD-FAB Mean Mean Resp. Mean (SD) F p (SD) F p Mean F p (SD) F p (SD) Education Level Some college 14.00 9.13 12.38 35.50 (n=8) (5.73) (3.83) (3.66) (12.21) College graduate 14.47 8.09 14.44 37.00 (n=32) (7.89) (4.30) (6.69) (16.73) Postgraduate 14.80 7.70 15.50 38.00 (n=10) (7.52) .03 .975 (3.89) .28 .757 (4.84) .62 .542 (13.82) .06 .944 Household Income <$50,000 (n=4) 20.50 9.00 18.50 48.00 (4.51) (2.45) (4.65) (11.11) $50,000 to 15.91 9.00 13.36 38.27 $100,000 (n=11) (8.92) (5.25) (7.56) (19.92) >$100,000 12.81 7.29 14.00 34.10 (n=31) (6.45) 2.57 .088 (3.31) 1.02 .370 (5.47) 1.16 .323 (12.63) 1.75 .187

+Note: high food attitudes, fear response, adaptive response and CD-FAB total indicates high disordered eating attitudes and behaviors.

Overall CD-FAB and subscale scores were compared between participants who were currently seeing a Registered Dietitian Nutritionist (RDN) (N=26, 52%) and participants that were not (N=24, 48%). Independent t-tests showed no significant difference between overall CD-

FAB and subscale scores of participants seeing and RDN vs. those that were not (table 20).

Table 20- Overall CD-FAB and subscale scores +of participants currently seeing and RDN vs. those who are not currently seeing an RDN.

Not seeing an Seeing an RDN CD-FAB Scores Range of scores RDN (N=24, 48%) (N=26, 52%) Mean (SD) t df p- Mean (SD) value Food Attitudes 3 to 21 13.31 (6.65) 15.71 (7.04) -1.152 48 .255

Fear Response 4 to 28 7.62 (4.24) 8.79 (3.93) -1.014 48 .316

Adaptive Response 4 to 28 13.35 (6.92) 15.38 (4.60) -1.210 48 .232

Overall CD-FAB 11 to 77 34.27 (17.24) 39.88 (12.60) -1.303 48 .199

+Note: high food attitudes, fear response, adaptive response and CD-FAB total indicates high disordered eating attitudes and behaviors.

4.5.4 Factor: GI Symptoms (CDSD)

The Celiac Disease Symptoms Diary (CDSD) is a disease specific tool measuring patient reported CeD symptoms. The overall CD-FAB scores were positively correlated with participants’ reported number of symptoms (r=.26). The relationship between the overall CD-

FAB and patients’ symptom counts was small as per Cohen’s (1988) guidelines and not significant. The CD-FAB subscale scores (food attitudes, fear response, adaptive response) were positively correlated with participants’ reported number of symptoms (r=.15, r=.29, r=.29). The relationship between the subscale scores and patients’ symptom counts was small as per Cohen’s

(1988) guidelines (r<.3) and not significant for food attitudes. The more symptoms patients reported the higher their CD-FAB overall scores, food attitudes, fear response and adaptive response (table 21).

Table 21- Pearson Correlations between CD-FAB+ and GI Symptoms (CDSD)

Food Attitudes Fear Response Adaptive Response CD-FAB Total

CDSD r p-value r p-value r p-value r p-value

GI Symptoms .15 a .290 .29 a .041* .29 a .043* .26 a .065

According to Cohen (1988)’s guidelines: a Pearson correlation is small (.1 < r < .3) b Pearson correlation is medium (.3

A one-way ANOVA was conducted to compare total CD-FAB scores and subscale scores

of adults (18 -45 years old) reporting different number of symptoms. Total CD-FAB scores in

adults with CeD are affected by number of symptoms [F(1,4)=3.17, p=.022]. This suggested that

participants with more reported symptoms had higher CD-FAB scores.

The food attitudes and fear response subscale scores were not significantly different

between participants who reported no symptoms and those who reported 1, 2, 3, or 4 symptoms

(p<.05).

Table 22-Overall CD-FAB+ and subscale scores per reported symptoms

Food Fear Adaptive Overall Attitudes Resp. Resp. CD-FAB Mean (SD) Mean Mean Mean F p (SD) F p (SD) F p (SD) F p Current GI symptoms None (n=8) 14.50 7.75 14.88 37.13 (5.93) (4.27) (5.30) (12.90) 1 symptom 13.58 7.26 12.32 33.16 (n=19) (7.72) (2.84) (6.04) (14.45) 2 symptoms 10.78 6.44 11.78 29.00 (n=9) (7.34) (4.16) (4.29) (13.50) 3 symptoms 20.71 11.29 19.14 51.14 (n=7) (7.59) (5.44) (6.04) (16.61) 4 symptoms 15.29 10.29 17.57 43.14 (n=7) (5.19) 2.07 .101 (3.90) 2.37 .067 (4.86) 3.09 .025* (12.39) 3.17 .022*

*p<.05 **p<.01 ***p<.001 +Note: high food attitudes, fear response, adaptive response and CD-FAB total indicates high disordered eating attitudes and behaviors. 99

4.5.5 Factor: Personality characteristics (BFI)

The Big Five Inventory (BFI) is a validated 44 item multidimensional inventory to measure the five main dimensions of personality traits. This test suggested five broad dimensions commonly used to describe the human personality: neuroticism, conscientiousness, extroversion, agreeableness and openness to experience. The overall CD-FAB and subscale scores were correlated with the five personality traits assessed through the BFI questionnaire in this study.

The overall CD-FAB scores were positively and significantly correlated with neuroticism

(r=.39, p=.005) and positively but not significantly correlated with openness (r=.22, p=.126); negatively but not significantly correlated with extroversion (r=-.16, p=.265) and conscientiousness (r=-.2, p=.136). This suggested that individuals with high overall CD-FAB scores had a high chance of scoring high on neuroticism (a high score on neuroticism indicates that a person is prone to having irrational ideas, is less able to control impulses and copes poorly with stress) and openness (a high score on openness to experience indicates that a person is conventional in behavior and conservative in outlook and feels more comfortable around things that are familiar vs. novel). On the other hand, Individuals who score high on overall CD-FAB had a high chance of scoring low on extroversion (a low score indicates that a person is reserved, independent and even-paced) and conscientiousness (a low score on conscientiousness is associated with flexibility and spontaneity).

The CD-FAB subscale scores for food attitudes, fear response and adaptive response were positively correlated with neuroticism (r=.35, r=.19, r=.43) and openness (r=.23, r=.14, r=.18); negatively correlated with extroversion (r=-.19, r=-.12, r=-.10) and conscientiousness (r=-

.17, r=-.13, r=-.26). Apart from the positive correlation between neuroticism and food attitudes and adaptive response, all other correlations were not significant (table 23). 100

Table 23-Pearson Correlations between CD-FAB and personality characteristics+

Personality Range of Food Fear Adaptive CD-FAB Total characteristics (BFI) subscale Attitudes Response Response scores r p- r p- r p- r p- value value value value Extroversion 8 to 40 -.19 a .200 -.12 a .414 -.10 a .476 -.16 a .265

Agreeableness 9 to 45 .09 .525 -.01 .959 -.12 a .415 -.00 .981

Conscientiousness 9 to 45 -.17 a .242 -.13 a .386 -.26 a .074 -.21 a .136

Neuroticism 8 to 40 .35 b .013* .19 a .177 .43 b .003** .39 b .005**

Openness 10 to 50 .23 a .104 .14 a .328 .18 a .215 .22 a .126

According to Cohen’s (1988) guidelines: a Pearson correlation is small (.1 < r < .3) b Pearson correlation is medium (.3

To replicate Satherley et al.’s thesis work on the CD-FAB, further analysis was done. As

per the tertiary split around total CD-FAB scores, 34 % (N=17) scored low between 11 and 27,

32% (N=16) scored medium between 30 and 43, and 34% (N=17) scored high between 44 and

66 on the overall CD-FAB. The one-way ANOVAs found that individuals who scored high,

medium and low on the CD-FAB differed in terms of the personality characteristic: neuroticism

[F (2, 49) = 4.95, p=.011].

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Table 24- CD-FAB Total scores tertiary split

CD-FAB Total Score Means ANOVA

Low Score Medium Score High score F p-value N=17 N=16 N=17 Statistic (11 - 27)a (30 - 43) a (44-66) a Personality characteristics+ Extroversion 29.06 (4.42) 28.69 (7.22) 27.12 (7.04) .45 .642 Agreeableness 35.47 (6.25) 36.38 (4.44) 35.65 (6.21) .12 .892 Conscientiousness 38.00 (4.02) 35.81 (4.13) 35.12 (5.09) 1.94 .155 Neuroticism 19.47 (5.97) 22.56 (6.07) 26.29 (6.90) 4.95 .011* Openness 35.94 (5.78) 36.19 (5.78) 39.71 (5.46) 2.32 .109

+ Note: higher BFI scores suggest higher characteristic *p<.05 **p<.01 ***p<.001

4.5.6 Factor: Diet Adherence (CDAT, Biagi)

The CDAT assessed adherence to the GFD in a 7-item questionnaire. Excellent or very good adherence to a GFD was marked with total scores below or equal to 13; moderate to poor adherence was marked with total scores above 13.

The CDAT scores were positively correlated with food attitudes, fear response, adaptive response and CD-FAB total scores (r=.25, r=.22, r=.21, r=.26), albeit not significant (p>.05).

Since higher CDAT scores suggest lower adherence, the direction of this relationship is suggesting that high adherence to the diet was correlated with lower CD-FAB scores (table 25).

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Table 25- Pearson Correlations between CD-FAB and Diet Adherence (CDAT) +

Food Attitudes Fear Response Adaptive Response CD-FAB Total

r p- r p- r p-value r p-

CDAT value value value

Diet adherence score .25 a .078 .22 a .129 .21 a .147 .26 a .067

+Note: high CDAT score indicate low adherence to GFD; high food attitudes, fear response, adaptive response and CD-FAB total indicates high disordered eating attitudes and behaviors According to Cohen (1988)’s guidelines: a Pearson correlation is small (.1 < r < .3) b Pearson correlation is medium (.3

From a total of 50 recruited participants, 68% (N=34) were adherent to the GFD (total score less than or equal to 13), and 32% (N=16) of participants were poorly adherent to the GFD

(total scores above 13). An independent-samples t-test was conducted to compare total CD-FAB scores and subscale scores of adults (18 - 45 years old) adherent vs. non-adherent to GFD. Total

CD-FAB scores and subscale scores (with the exception of the adaptive response subscale) in adults with CeD were affected by adherence to GFD. Levene’s test indicated that the variances were equal across adherent and poorly adherent groups (p- value > .05). With equal variances assumed, the total CD-FAB mean scores were significantly different between participants that are adherent vs. those that are poorly adherent to the GFD (t (48) =-2.19, p=.03). This suggests that participants who are poorly adherent to the diet have significantly higher CD-FAB mean scores then participants who are highly adherent to the GFD. The CD-FAB subscale scores for food attitudes and fear response were also significantly different between participants that are adherent vs. those that are poorly adherent to the GFD (t (48) =-2.11, p=.04; t (48) =-2.33, p=.02). However, the CD-FAB subscale score for adaptive response were not significantly

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different between participants that are adherent vs. those that are poorly adherent to the GFD (t

(48) =-1.38, p=.17).

Table 26- Total CD-FAB Scores and Subscales by participant’s adherence to GFD (CDAT) +

Adherence to Poor Adherence t-test of Means GFD (N=34) to GFD (N=16) Range of scores Mean SD Mean SD t df p-value

Food Attitudes 3 to 21 13.00 6.78 17.56 7.87 -2.11 48 .04*

Fear Response 4 to 28 7.29 3.49 10.06 4.74 -2.33 48 .02*

Adaptive Response 4 to 28 13.53 5.63 16.00 6.45 -1.38 48 .17

CD-FAB Total 11 to 77 33.82 13.57 43.63 17.03 -2.19 48 .03*

+Note: Excellent or very good adherence to a GFD was marked with total scores below or equal to 13, moderate to poor adherence was marked with total scores above 13; Higher CDFAB- Total and subscales suggest higher disordered eating attitudes and behaviors. *p<.05 **p<.01 ***p<.001

In this study, diet adherence was assessed using 3 additional questions from the Biagi questionnaire (Biagi et al., 2012). In the first question (Biagi 1), participants were asked if they ate gluten voluntarily (Do you eat gluten voluntarily? Yes/Normal portion, Yes/Just a taste/Often,

Yes/Just a taste/rarely, No), 92% (N=46) of participants answered No, and 8% (N=4) answered

Yes, Just a taste.

An independent-samples t-test was conducted to compare total CD-FAB scores and subscale scores of adults (18 -45 years old) who ate gluten voluntarily vs. those who didn’t. Total

CD-FAB scores and subscale scores in adults with CeD were not affected by whether participants voluntarily consumed gluten or not. Levene’s test indicated that the variances were equal across groups (p- value > 0.05). With equal variances assumed, the total CD-FAB mean

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scores were not significantly different between participants who consumed gluten voluntarily and those who didn’t (t (48) =.74, p=.463). The CD-FAB subscale scores (food attitudes, fear response and adaptive response) were also not significantly different between participants who consumed gluten voluntarily and those who didn’t (t (48) =.91, p=.370; t (48) =.09, p=.928 and t

(48) =.72, p=.474). However, caution was warranted when interpreting those results, there are only 4 participants in one group vs. 46 in the other group. There is low statistical power, a larger sample size may probably show a relationship between total CD-FAB scores and subscale scores of adults (18 -45 years old) who didn’t consume gluten voluntarily vs. those who did.

When looking at CD-FAB total scores of those who don’t consume gluten voluntarily they had higher CD-FAB scores [37.44 (15.18)] than those who did [31.50 (17.99)]. Albeit not statistically different, this may suggest that participants with higher CD-FAB scores have higher vigilance (as Biagi questions seems to measure more vigilance than adherence).

Table 27- Total CD-FAB Scores+ and Subscales by participant’s consumption of gluten voluntarily (Biagi question 1)

Don’t consume Consume t-test of Means voluntarily voluntarily (N=46) (N=4) Range of scores Mean SD Mean SD t df p-value

Food Attitudes 3 to 21 14.74 7.52 11.25 5.25 .91 48 .370

Fear Response 4 to 28 8.20 4.03 8.00 5.60 .09 48 .928

Adaptive Response 4 to 28 14.50 5.81 12.25 8.06 .72 48 .474

CD-FAB Total 11 to 77 37.44 15.18 31.50 17.99 .74 48 .463

+Note: Higher CDFAB- Total and subscales suggest higher disordered eating attitudes and behaviors.

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In the second question (Biagi 2), participants were asked if they tell the person cooking their meal about their disease when they eat out (When you eat out, do you tell the person who is cooking about your disease? Never, Sometimes, Always), 4 % (N=2) of participants answered

Never, 24 % (N=12) answered Sometimes and 72% (N=36) answered Always.

A one-way between subjects’ ANOVA was conducted to compare the effect of total CD-

FAB scores and subscales scores on participants never telling the person who is cooking,

sometimes telling the person who is cooking, and always telling the person who is cooking

about their disease. There was not a significant effect of total CD-FAB score on participants

telling the person who is cooking about their disease at the p <.05 level [(F(2, 47) = 2.16,

p=.127]. There was also not a significant effect of CD-FAB subscale (food attitudes, fear

response, adaptive response) scores on participants telling the person who is cooking about

their disease at the p <.05 level [(F(2, 47) = 2.64, p=.082; (F(2, 47) = 1.48, p=.239; (F(2, 47) =

.86, p=.431].

When looking at CD-FAB total scores of those who always tell the person cooking about their disease when eating out, they had higher CD-FAB scores [39.61 (14.31)] than those who never did [25.00 (1.41)]. Similarly to Biagi question 1, albeit not statistically different, this may suggest that participants with higher CD-FAB scores have higher vigilance (as Biagi questions seems to measure more vigilance than adherence).

106

Table 28-Total CD-FAB Scores+ and Subscales by Responses (Biagi question 2)

When you eat out, do you tell the person ANOVA cooking about your disease? Never Sometimes Always F p-value (N=2) (N=12) (N=36) Food Attitudes 9.00 (1.41) 11.08 (6.92) 15.89 (7.31) 2.64 .082 Fear Response 5.00 (2.82) 7.00 (4.37) 8.75 (3.99) 1.48 .239 Adaptive Response 11.00 (2.83) 12.92 (7.01) 14.97 (5.67) .86 .431

CD-FAB total 25.00 (1.41) 31.00 (17.44) 39.61 (14.31) 2.16 .127

+Note: Higher CDFAB- Total and subscales suggest higher disordered eating attitudes and behaviors.

In the third question (Biagi 3), participants were asked if they checked labels of packaged food (Do you check labels of packaged food? (Never, Sometimes, Always), no participants answered Never, 8% (N=4) of participants answered Sometimes, and 92% (N=46) answered Always.

An independent-samples t-test was conducted to compare total CD-FAB scores and subscale scores of adults (18 -45 years old) who sometimes checked labels vs. those who always checked labels of packaged foods. Total CD-FAB scores and subscale scores in adults with CeD were not affected by whether participants checked labels of packaged foods sometimes or always. Levene’s test indicated that the variances were equal across groups (p- value > 0.05). With equal variances assumed, the total CD-FAB mean scores were not significantly different between participants who sometimes checked labels and always checked labels of packaged foods (t (48) =-1.30, p=.201). The CD-FAB subscale scores (food attitudes, fear response and adaptive response) were also not significantly different between participants who sometimes checked labels and always checked labels of packaged foods (t (48) =-1.42,

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p=.164; t (48) =-.22, p=.829 and t (48) =-1.44, p=.156). However, caution was warranted when

interpreting those results, there are only 4 participants in one group vs. 46 in the other group.

There is low statistical power, a larger sample size may probably show a relationship between

total CD-FAB scores and subscale scores of adults (18 - 45 years old) who sometimes checked

labels vs. those who always checked labels of packaged foods.

When looking at CD-FAB total scores of those who always checked labels of packaged foods, they had higher CD-FAB scores [37.78 (14.74)] than those who sometimes did [27.50

(20.92)]. Similarly to Biagi question 1 and 2, albeit not statistically different, this may suggest that participants with higher CD-FAB scores have higher vigilance (as Biagi questions seems to measure more vigilance than adherence).

Table 29- Total CD-FAB Scores+ and Subscales by participant’s label checking for packaged foods (Biagi question 3)

Sometimes Always t-test of Means (N=4) (N=46) Range of scores Mean SD Mean SD t df p-value

Food Attitudes 3 to 21 9.50 6.56 14.89 7.36 -1.42 48 .164

Fear Response 4 to 28 7.75 5.68 8.22 4.02 -.22 48 .829

Adaptive Response 4 to 28 10.25 8.96 14.67 5.62 -1.44 48 .156

CD-FAB Total 11 to 77 27.50 20.92 37.78 14.74 -1.30 48 .201

+Note: Higher CDFAB- Total and subscales suggest higher disordered eating attitudes and behaviors.

4.5.7 Regression analysis- Factors and CD-FAB

The primary goal of RQ3 was to explore the correlates of CeD related to food attitudes and behaviors, as assessed by the CD-FAB. Multiple regression analyses were conducted to 108

assess the relationship between CD-FAB total scores and subscale scores (Food attitudes, fear response, adaptive response) and various potential predictors: gender, age, years since diagnosis, household income, education level, RDN visit, personality characteristics, GI symptoms, gluten- free diet adherence and body composition. With 56% of participants recruited during the

COVID-19 pandemic. The pandemic factor was added as a predictor in the model. Table 29 summarizes the analysis results for all four models. The first model with food attitudes as the dependent variable explained a statistically significant proportion (39.6%) of the variance in the outcome [R² = .396, F (5, 44) = 5.78, p<.001]. Among the independent variables, an association was only found between food attitudes and years since diagnosis. For each one-year increase in years since diagnosis, there is a decrease in food attitudes scores by -0.62 (p=.001).

The second model with fear response as the dependent variable explained a statistically significant proportion (27.8%) of the variance in the outcome [R² = .278, F (5, 44) = 3.93, p=.011]. Once again, among the independent variables, an association was only found between fear response and years since diagnosis. For each one-year increase in years since diagnosis, there is a decrease in fear response scores by -0.30 (p=.006).

The third model with adaptive response as the dependent variable did explain a statistically significant proportion (23.5%) of the variance in the outcome [R² = .235, F (5, 44) =

2.71, p =.032]. However, none of the independent variables showed any significant associations.

The fourth model with total CD-FAB as the dependent variable explained a statistically significant proportion (37.7%) of the variance in the outcome [R² = .377, F (5, 44) =5.33, p=.001]. Once again, among the independent variables, an association was only found between total CD-FAB and years since diagnosis. For each one-year increase in years since diagnosis, there is a decrease in total CD-FAB scores by -1.21 (p=.001). 109

Table 30- Factors associated with CD-FAB total and subscale scores including COVID-19 status

B Std. Error t p-value Predictors Model 1- Food Attitudes (constant) 20.99 5.40 3.89 .000*** Years since diagnosis -.62 .17 -3.70 .001** CDSD -.33 .76 -.43 .667 CDAT .62 .32 1.94 .059 BMI -.31 .24 -1.31 .196 COVID-19 Status+ -3.00 1.87 -1.60 .117 R2 .396 F-statistic 5.78*** Model 2- Fear Response (constant) 10.46 3.27 3.20 .003** Years since diagnosis -.30 .10 -2.89 .006** CDSD .58 .46 1.25 .217 CDAT .25 .20 1.26 .214 BMI -.18 .14 -1.26 .213 COVID-19 Status+ .25 1.14 .22 .826 R2 .278 F-statistic 3.39* Model 3- Adaptive Response (constant) 18.12 4.89 3.704 .001** Years since diagnosis -.29 .15 -1.886 .066 CDSD .75 .69 1.089 .282 CDAT .26 .29 .899 .374 BMI -.22 .22 -1.012 .317 COVID-19 Status+ -1.94 1.70 -1.144 .259 R2 .235 F-statistic 2.71* Model 4- CD-FAB Total (constant) 49.56 11.35 4.37 .000*** Years since diagnosis -1.21 .36 -3.40 .001** CDSD .99 1.60 .62 .536 CDAT 1.13 .68 1.67 .102 BMI -.71 .50 -1.43 .161 COVID-19 Status+ -4.69 3.94 -1.19 .241 R2 .377 F-statistic 5.33** *p<.05 **p<.01 ***p<.001 Note: due to small samples size, gender, age, household income, education level, RDN visit, Biagi and BFI were removed from predictor list- however when included, same results were found. The models were also run with each of the five personality characteristics from BFI individually- and again same results were found. +Covid-19 status means they were recruited either pre-or during the pandemic. When removing COVID-19-status from model, same results were found, regression table can be found in Appendix R.

4.5.8 Deeper look into Years since Diagnosis and Total CD-FAB scores.

For a deeper look into years since diagnosis and the CD-FAB scores, years since diagnosis were divided into quintiles, from lowest number of years to highest number of years

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since diagnosis. The average number of years since diagnosis in the lowest quintile was 1.58

(.44) years; compared to 16.15 (2.75) years in the highest quintile.

Table 31-Years since Diagnosis

Quintiles/Years since Diagnosis N Mean SD Min Max Lowest a 10 1.58 .44 1.00 2.33 Second a 10 3.71 .82 2.50 4.50 Third a 10 5.78 1.03 4.58 7.33 Fourth b 10 8.81 1.18 7.42 10.42 Highest b 10 16.15 2.75 12.50 21.67 Total 50 7.20 5.31 1.00 21.67 a lowest three quintiles used below range of years [1.00-7.33] b highest two quintiles used below range of years [7.42- 21.67]

An independent t-test was conducted to compare means of CD-FAB scores and subscales scores between the highest two quintiles [fourth and fifth quintile, range of years (7.42- 21.67)] and lowest three quintiles [first, second and third, range of years (1.00-7.33)]. Total CD-FAB scores and subscale scores in adults with CeD were affected by whether participants’ years since diagnosis were in the low [1.00-7.33] vs high [7.42- 21.67] range. Levene’s test indicated that the variances were equal across groups (p- value > 0.05). With equal variances assumed, the total

CD-FAB mean scores were significantly different between participants who were in the low vs. high range of years since diagnosis (t (48) =4.80, p<.001). The CD-FAB subscale scores (food attitudes, fear response and adaptive response) were also significantly different between participants who were in the low range of years vs. high range of years since diagnosis (t (48)

=5.03, p=<.001; t (48) =4.44, p=<.001 and t (48) =2.70, p=.010).

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Table 32- Total CD-FAB Scores+ and Subscales by lowest and highest range for years since diagnosis.

Low range nb of High range nb of t-test of Means years since dx years since dx [1.00-7.33] [7.42-21.67] (N=30) (N=20) Range of scores Mean SD Mean SD t df p-value

Food Attitudes 3 to 21 17.97 6.47 9.20 5.31 5.03 48 .000***

Fear Response 4 to 28 9.97 3.98 5.50 2.56 4.44 48 .000***

Adaptive Response 4 to 28 16.07 5.50 11.70 5.76 2.70 48 .010*

CD-FAB Total 11 to 77 44.00 13.04 26.40 12.20 4.80 48 .000***

*p<.05 **p<.01 ***p<.001 +Note: Higher CDFAB- Total and subscales suggest higher disordered eating attitudes and behaviors.

Further analysis was done in order to assess CD-FAB subscale and overall scores at cut points of 3 years, 4 years and 5 years since diagnosis. No significant differences were found between CD-FAB subscale and overall scores at cut points of 3 and 4 years, however, significant differences were found between scores at cut point of 5 years since diagnosis. CD-FAB subscale and overall mean scores were significantly higher for participants with less than 5 years since diagnosis. Therefore, it seemed like disordered eating attitudes and behaviors started to get better by 5 to 7 years.

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Table 33-Total CD-FAB Scores+ and Subscales by years since diagnosis at cut point of five years.

Low range nb of High range nb of t-test of Means years since dx years since dx [<5 years] [>5 years] (N=24) (N=26) Range of scores Mean SD Mean SD t df p-value

Food Attitudes 3 to 21 18.58 6.51 10.65 6.05 4.47 48 .000***

Fear Response 4 to 28 10.13 4.12 6.39 3.21 3.60 48 .001**

Adaptive Response 4 to 28 16.50 5.62 12.31 5.62 2.64 48 .011*

CD-FAB Total 11 to 77 45.21 12.82 29.35 13.50 4.25 48 .000***

*p<.05 **p<.01 ***p<.001 +Note: Higher CDFAB- Total and subscales suggest higher disordered eating attitudes and behaviors.

To explore further, Table 34 shows the percent of agreement (reported strongly agree, agree, agree somewhat) of participants in the low range of years since diagnosis and participants in the high range of years since diagnosis per CD-FAB items. Out of 50 participants, 20 were in the highest two quintiles of years since diagnosis [fourth and fifth quintile, range of years (7.42-

21.67)] and 30 were in the lowest three quintiles [first, second and third, range of years (1.00-

7.33)]. When assessing food attitudes, because of their celiac 46.7 % of participants in the lowest range of years since diagnosis were concerned about being near others when they are eating gluten vs. 15.0% in the highest range of years since diagnosis. Because of their celiac, 73.3% of participants in the lowest range of years since diagnosis are afraid to eat outside their home vs.

15.0% in the highest range of years since diagnosis. Because of their celiac 60.0% of participants in the lowest range of years since diagnosis are afraid to touch gluten-containing foods vs. 15.0% in the highest range of years since diagnosis.

When assessing fear response, because of their celiac 60.0% of participants in the lowest range of years since diagnosis get worried when eating with strangers vs. 25.0% of participants 113

in the highest range of years since diagnosis. Because of their celiac, 33.3 % of participants in lowest range of years since diagnosis find it hard to eat gluten-free foods that look like the gluten containing-foods that have made them ill in the past vs. 10.0% in the highest range of years since diagnosis. Because of their celiac, 23.3% of participants in the lowest range of years since diagnosis will only eat food that have been prepared by themselves, compared to 5.0% of participants in the highest range of years since diagnosis. Finally, 46.7% of participants in the lowest range of years since diagnosis have concerns about cross-contamination which prevents them from going to social events involving foods; compared to 5.0% in the highest range of years since diagnosis.

When assessing adaptive response, despite having celiac, 33.3 % of participants in the lowest range of years since diagnosis enjoy going out for meals as much as they did before their diagnosis; compared to 65.0% of participants in the highest range of years since diagnosis.

Despite having celiac, 40.0% of participants in the lowest range of years since diagnosis cs. 60% of participants in the highest range of years since diagnosis. Despite having celiac, 43.3% of participants in the lowest range of years since diagnosis did not stop going to restaurants following previous contamination of gluten in the past, compared to 70.0% of participants in the highest range of years since diagnosis. Finally, 76.7% of participants in the lowest range of years since diagnosis reported that if they asked questions, they can normally find gluten-free food to eat compared to 85.0% of participants in the highest range of years since diagnosis.

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Table 34-Prevalence of participants with low and high range of years since diagnosis scoring strongly agree, agree or agree somewhat per CD-FAB item.

Agreement in Agreement in CD-FAB questions Low range of High range of years since years since diagnosis diagnosis [1.00-7.33] [7.42-21.67] [N=30, %] [N=20, %] Food Attitudes Because of my celiac… I get concerned being near others when they are eating gluten N=14, 46.7 % N=3, 15.0 % I am afraid to eat outside my home N=22, 73.3 % N=3, 15.0 % I am afraid to touch gluten-containing foods N=18, 60.0 % N=3, 15.0 % Fear Response Because of my celiac… I get worried when eating with strangers N=18, 60.0 % N=5, 25.0% I find it hard to eat gluten-free foods that look like the gluten- containing-foods that have made me ill in the past N=10, 33.3% N=2, 10.0% I will only eat food that I have prepared myself N=7, 23.3 % N=1, 5.0 % My concerns about cross-contamination prevent me from going N=14, 46.7 % N=1, 5.0% to social events involving food Adaptive Response Despite having Celiac Disease… I enjoy going out for meals as much as I did before my N=10, 33.3 % N=13, 65.0 % diagnosis I am comfortable eating gluten-free food from other people’s N=12, 40.0 % N=12, 60.0% kitchens Being contaminated by gluten in the past hasn’t stopped me N=13, 43.3 % N=14, 70.0% from enjoying restaurants If I ask questions, I can normally find gluten-free food to eat N=23, 76.7 % N=17, 85.0%

Personality characteristics (as per BFI) means of adults with CeD below 5 years since diagnosis were compared to personality characteristic means of adults with CeD above 5 years since diagnosis. No significant differences were found between personality characteristics means of participants below and above 5 years since diagnosis.

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Table 35- Personality characteristics per years since diagnosis at cut point of five years+.

Low range nb of years High range nb of years t-test of Means since dx since dx [<5 years] [>5 years] (N=24) (N=26) Mean SD Mean SD t df p-value

Extroversion 27.42 7.48 29.08 4.91 .94 48 .355

Agreeableness 35.92 4.75 35.73 6.40 -.12 48 .908

Conscientiousness 35.67 4.44 36.92 4.61 .98 48 .332

Neuroticism 24.33 6.68 21.35 6.78 -1.57 48 .123

Openness 37.21 5.77 37.39 5.99 .11 48 .916

*p<.05 **p<.01 ***p<.001 +Note: Higher means suggest higher personality characteristics

Number of GI symptoms of adults with CeD below 5 years since diagnosis were compared to number of GI symptoms of adults with CeD above 5 years since diagnosis. No significant differences were found between number of GI symptoms of participants below and above 5 years since diagnosis.

Table 36-Number of symptoms per years since diagnosis at cut point of five years+.

Low range nb of years High range nb of years t-test of Means since dx since dx [<5 years] [>5 years] (N=24) (N=26) Mean SD Mean SD t df p-value

Number of GI symptoms 2.00 1.45 1.46 1.10 -1.49 48 .143

*p<.05 **p<.01 ***p<.001 +Note: Higher means suggest higher number of GI symptoms

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4.5.9 Summary Findings:

The overall CD-FAB score of adults (18-45 years old) with CeD, did not vary depending on gender, age, household income, education level, RDN visit. CD-FAB scores did vary depending on years since diagnosis, suggesting that the most recently diagnosed participants had higher CD-FAB scores. The overall CD-FAB score of adults (18-45 years old) with CeD, varied depending on BMI, suggesting that participants with lower BMI had higher CD-FAB scores.

Scores also varied depending on number of symptoms patients reported, suggesting that participants with higher number of symptoms reported (>3) had higher CD-FAB scores.

The overall CD-FAB scores of adults with CeD, varied depending on personality characteristics. Individuals with high BFI scores on neuroticism and openness, as well as low

BFI scores on extroversion and conscientiousness had higher CD-FAB scores.

Total CD-FAB scores and subscale scores (with the exception of the adaptive response subscale) in adults with CeD were affected by adherence to GFD. In this study, high adherence

(high compliance to the GFD) was associated with low CD-FAB scores. The Biagi questions, albeit not statistically different, may suggest that participants with higher CD-FAB scores have higher vigilance (as Biagi questions seems to measure more vigilance than adherence).

Finally, among all the predictors that were tested with a multivariate technique, the only independent variable that was significantly related to the CD-FAB was years since diagnosis.

The lower the number of years since diagnosis, the higher the disordered eating attitudes and behaviors (higher the CD-FAB scores).

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4.6 RQ4: QoL, depression, and anxiety association with CD-FAB

´ RQ4: In adults (18 – 45 years old) with CeD, are disordered eating attitudes and

behaviors (as measured by the CD-FAB scores) associated with QoL, anxiety, and

depression?

The aim of RQ4 was to explore the associations between CD-FAB scores and QoL, anxiety and depression outcomes, to gain a greater understanding of the influence of disordered eating attitudes and behaviors in CeD.

The CD-FAB total score and subscale scores were treated as independent variables and

QoL (CDQoL scores), anxiety (STAI scores) and depression (CESD scores) were treated as dependent variables. First, each of the covariates were tested independently with a correlation and/or an independent t-test, then all the covariates were tested simultaneously with a regression or ANOVA model.

4.6.1 Quality of Life and CD-FAB

The Celiac Disease Specific Quality of Life (CD-QoL) is a 20-item CeD specific measure to assess the QoL in adults. Answers gave an overall score, as well as four clinically relevant subscales: dysphoria, limitations, health concerns, and inadequate treatment. Final scores have a possible range of 0-100 with higher scores indicating a higher degree of QoL.

The extent to which individuals felt depressed, frightened or overwhelmed by their diagnosis of CeD was measured by dysphoria items (questions 10 to 13). The extent to which individuals felt limited by CeD when eating out with others, socializing, and traveling was measured by limitation items (questions 1, 5-7, 14-17 and 19). The extent to which individuals

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felt worried about long-term health outcomes of their diagnosis for other family members and themselves was measured by health concern items (questions 2-4, 18 and 20). And the extent to which individuals felt there are enough treatment options for their CeD was measured by inadequate treatment items (questions 8 and 9).

The overall CD-FAB scores and subscale scores were negatively correlated with overall

CDQoL scores and all subscales (dysphoria, limitations, health concerns and inadequate treatment). There was a strong highly significant negative correlation between CD-FAB total score and overall CDQoL scores (r=-.60, p<.001). Higher CD-FAB scores indicated high disordered eating attitudes and behaviors and higher CDQoL scores indicated higher degree of

QoL. Therefore, high CD-FAB scores were correlated with low QoL. The overall CD-FAB scores were also significantly negatively correlated with dysphoria (r=-.05, p<.001), limitations

(r=-.68, p<.001) and health concerns (r=-.38, p=.006). There was a small negative correlation between inadequate treatment scores and overall CD-FAB scores (r=-.21), however the correlation was not significant (p>0.05). It was important to note the insignificant p-value as

Satherly et al. used the inadequate treatment subscale of the CDQoL measure to assess discriminative validity of the CD-FAB (R.-M. Satherley et al., 2018). Inadequate treatment measured the extent to which individuals felt there are enough treatment options for their CeD.

Satherley et al. explained that there was no reason for CD-FAB total scores to be associated with treatment beliefs, and as hypothesized found no relationship between these scores [r=-.01, p=.880] (R.-M. Satherley et al., 2018).

There were strong negative significant correlations between CD-FAB subscales (food attitudes, fear response, adaptive response) and dysphoria (r=-.55, r=-.4, r=-.31, p<.05), limitations (r=-.71, r=-.54, r=-.50, p<.05). There was a negative correlation between CD-FAB 119

subscales (food attitudes, fear response, adaptive response) and health concerns (r=-.48, r=-.22,

r=-.23); however, the correlation was only significant between CD-FAB subscale food attitudes

and health concerns. Individuals with high CD-FAB scores were depressed, frightened or

overwhelmed by their diagnosis of CeD (dysphoria), felt limited by CeD when eating out with

others, socializing, and traveling (limitation) and felt worried about long-term health outcomes of

their diagnosis for other family members and themselves (health concern). High scores on the

CD-FAB have been associated with a fear of trying new foods and an impaired QoL, particularly

in social domain (R.-M. Satherley et al., 2018).

Table 37- Pearson Correlations between CD-FAB and CDQol scores+

Food Attitudes Fear Response Adaptive Response CD-FAB Total CDQoL r p r p r p r p

Dysphoria -.55 c <.001*** -.41 b .003** -.31 b .03* -.50 c <.001***

Limitations -.71 c <.001*** -.54 c <.001*** -.50 c <.001*** -.68 c <.001***

Health concerns -.48 b <.001*** -.22 a .126 -.23 a .102 -.38 b .006**

Inadequate treatment -.19 a .181 -.24 a .090 -.13 .363 -.21 a .145 Overall QoL -.66 c <.001*** -.47 b .001** -.41 b .003** -.60 c <.001***

According to Cohen’s (1988) guidelines: a Pearson correlation is small (.1 < r < .3) b Pearson correlation is medium (.3

Overall CD-FAB scores of participants scoring below and above 60 based on Dorn’s

study where 60 is a cut point indicative of good quality of life were compared (Dorn et al.,

2010). Table 38, shows that there is a significant difference among CD-FAB scores of

participants scoring above or below 60 on CDQoL, with a 20-point difference in CD-FAB mean 120

scores. The same thing was done by looking at CD-FAB scores for those who had CDQoL below

40, and high CD-FAB scores (about 49 and above) may be suggestive of meaningful low QoL.

Table 38- Deeper look at CD-FAB total scorers and difference between overall

4.6.2 Anxiety (state and trait) and CD-FAB

The State Trait Anxiety Inventory (STAI) is a two-part tool, the first part reports anxiety as an existing state, and the second reports anxiety as a trait (predisposition to anxious response to situations). Item scores are added to obtain subtest total scores, the range of scores for each subtest is 20-80, and higher STAI scores indicate greater anxiety. A cut-off point of 39 suggests clinically significant symptoms for each subtest: state anxiety and trait anxiety (Julian, 2011).

The overall CD-FAB scores and subscale scores were positively correlated with state and trait anxiety. There was a medium significant positive correlation between CD-FAB total score 121

and state anxiety (r=.33, p=.021). There was also a small positive correlation between CD-FAB total score and trait anxiety (r=.26), albeit not significant. Higher CD-FAB scores indicated high disordered eating attitudes and behaviors and higher STAI scores indicate higher degree of anxiety. Therefore, high CD-FAB scores were correlated with high state and trait anxiety.

The CD-FAB subscale scores food attitudes, fear response and adaptive response were also positively correlated with state and trait anxiety. There was a medium significant positive correlation between adaptive response and state anxiety (r=.35, p=.012). The higher the score on adaptive response (the less individuals are able to manage their food attitudes without compromising their lifestyle), the higher the state anxiety score. There is a small positive significant correlation between food attitudes and both state (r=.29, p=.039) and trait anxiety

(r=.29, p=.045). The higher the score on food attitudes (the higher the concerns around interacting with food and cross contamination), the higher the state anxiety score. Finally, there is also a small positive correlation between fear response and state anxiety (r=.18), albeit not significant. The higher the score on fear response (higher fear of trying new foods), the higher the state anxiety score.

Table 39 -Pearson Correlations between CD-FAB and STAI scores+

Food Attitudes Fear Response Adaptive Response CD-FAB Total

STAI r p-value r p-value r p-value r p-value

State Anxiety .29 a .039* .18 a .205 .35 b .012* .33 b .021*

Trait Anxiety .29 a .045* .09 .545 .26 a .066 .26 a .065

According to Cohen’s (1988) guidelines: a Pearson correlation is small (.1 < r < .3) b Pearson correlation is medium (.3

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From a total of 50 recruited participants, 60% (N=30) were below the cut-off point (score

<39) and 40% (N=20) were above the cut-off point (score >39) for state anxiety, suggesting that

40% of participants had an existing state of anxiety at the time of recruitment. An independent- sample t-test was conducted to compare total CD-FAB scores and subscale scores of adults (18 -

45 years old) with and without state anxiety. Total CD-FAB scores and subscale scores in adults with CeD were not affected by participants’ state anxiety. Levene’s test indicated that the variances were equal across groups (p- value > .05). With equal variances assumed, the total CD-

FAB mean scores were not significantly different between participants with and without state anxiety (t (48) =-1.57, p=.124). The CD-FAB subscale scores (food attitudes, fear response, adaptive response) were also not significantly different between participants with and without state anxiety (t (48) =-1.46, p=.152; t (48) =-.59, p=.560; t (48) =-1.82, p=.075).

Table 40- Total CD-FAB Scores and Subscales by state anxiety+

No state anxiety State anxiety t-test of Means (N=30) (N=20) Range of scores Mean SD Mean SD t df p-value

Food Attitudes 3 to 21 13.23 7.23 16.30 7.41 -1.46 48 .152

Fear Response 4 to 28 7.90 3.99 8.60 4.32 -.59 48 .560

Adaptive Response 4 to 28 13.10 5.49 16.15 6.29 -1.82 48 .075

CD-FAB Total 11 to 77 34.23 14.51 41.05 15.92 -1.57 48 .124

+Note: State anxiety is marked by total State anxiety score >39, higher CD-FAB- Total and subscales suggest higher disordered eating attitudes and behaviors

From a total of 50 recruited participants, 56% (N=28) were below the cut-off point (score

<39) and 44% (N=22) were above the cut-off point (score >39) for trait anxiety, suggesting that

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44% of participants had a predisposition to anxious response to situations. An independent- sample t-test was conducted to compare total CD-FAB scores and subscale scores of adults (18 -

45 years old) with and without trait anxiety. Total CD-FAB scores and subscale scores, with the exception of food attitude, in adults with CeD were not affected by participants’ trait anxiety.

Levene’s test indicated that the variances were equal across groups (p- value > 0.05). With equal variances assumed, the total CD-FAB mean scores were not significantly different between participants with and without trait anxiety (t (48) =-1.81, p=.077). The CD-FAB subscale scores for fear response and adaptive response were also not significantly different between participants with and without state anxiety (t (48) =-.98, p=.334; t (48) =-1.30, p=.200).

The CD-FAB subscale score for food attitudes were significantly different between participants with and without trait anxiety, t (48) =-2.15, p=.036), suggesting that trait anxiety had an impact on food attitudes responses in patients with CeD.

Table 41- Total CD-FAB Scores and Subscales by trait anxiety+

No trait anxiety Trait anxiety t-test of Means (N=28) (N=22) Range of scores Mean SD Mean SD t df p-value

Food Attitudes 3 to 21 12.54 6.57 16.90 7.78 -2.15 48 .036*

Fear Response 4 to 28 7.68 3.85 8.82 4.40 -.98 48 .334

Adaptive Response 4 to 28 13.36 6.38 15.55 5.24 -1.30 48 .200

CD-FAB Total 11 to 77 33.57 14.67 41.27 15.33 -1.81 48 .077

*p<.05 **p<.01 ***p<.001 +Note: Trait anxiety is marked by total trait anxiety score >39, higher CD-FAB- Total and subscales suggest higher disordered eating attitudes and behaviors

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4.6.3 Depression and CD-FAB

The Center for Epidemiologic Studies Depressive Scale (CES-D) consists of 20 items that rate how often over the past week an individual has experienced symptoms associated with depression, such as restless sleep, poor appetite, and feeling lonely. Final scores have a possible range of 0-60 with higher scores indicating a higher greater depressive symptom. Individuals who score above Cutoff scores (e.g. 16 or greater) may be at risk for clinical depression.

The overall CD-FAB scores and subscale scores were positively correlated with CESD scores. There was a small positive correlation between CD-FAB total score and CESD (r=.27).

Higher CD-FAB scores indicated high disordered eating attitudes and behaviors and higher

CESD scores indicated higher degree of clinical depression symptoms.

The CD-FAB subscale scores food attitudes, fear response and adaptive response were also positively correlated with CESD scores. There was a small positive correlation between fear response and adaptive response and CESD (r=.17, r=.20), albeit not significant. The higher the score on fear response (higher fear of trying new foods), the higher their clinical depression symptoms. The higher the score on adaptive response (the less individuals are able to manage their food attitudes without compromising their lifestyle), the higher their clinical depression symptoms. There is a medium significant positive correlation between food attitudes and CESD

(r=.30, p=.032). The higher the score on food attitudes (the higher the concerns around interacting with food and cross contamination), the higher their clinical depression symptoms.

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Table 42 -Pearson Correlations between CD-FAB and CESD scores+

Food Attitudes Fear Response Adaptive Response CD-FAB Total

CESD r p-value r p-value r p-value r p-value

Clinical Depression .30 b .032* .17 a .242 .20 a .166 .27 a .059

According to Cohen’s (1988) guidelines: a Pearson correlation is small (.1 < r < .3) b Pearson correlation is medium (.3

From a total of 50 recruited participants, 74% (N=37) were below the cut-off point (score

<15) and 26% (N=13) were above the cut-off point (score >15) for depressive symptoms, suggesting that 26% of participants may have been at risk for clinical depression. An independent-sample t-test was conducted to compare total CD-FAB scores and subscale scores of adults (18 -45 years old) with and without depressive symptoms. Total CD-FAB scores and subscale scores in adults with CeD were not affected by participants’ depressive symptoms.

Levene’s test indicated that the variances were equal across groups (p-value > 0.05). With equal variances assumed, the total CD-FAB mean scores were not significantly different between participants with and without depressive symptoms (t (48) =-1.75, p=.086). The CD-FAB subscale scores (food attitudes, fear response and adaptive response) were also not significantly different between participants with and without depressive symptoms (t (48) =-1.98, p=.064; t

(48) =-.92, p=.364; t (48) =-1.41, p=.164).

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Table 43- Total CD-FAB Scores and Subscales by depressive symptoms+

Not Depressed Depressed t-test of Means (N=37) (N=13) Range of scores Mean SD Mean SD t df p-value

Food Attitudes 3 to 21 13.27 6.46 17.84 8.98 -1.98 48 .054

Fear Response 4 to 28 7.87 3.73 9.08 5.07 -.92 48 .364

Adaptive Response 4 to 28 13.62 5.41 16.31 7.15 -1.41 48 .164

CD-FAB Total 11 to 77 34.76 13.60 43.23 18.55 -1.75 48 .086

*p<.05 **p<.01 ***p<.001 +Note: clinical depression is marked by total score >16, higher CD-FAB- Total and subscales suggest higher disordered eating attitudes and behaviors.

4.6.4 Regression analysis: quality of Life, anxiety, depression and CD-FAB.

The primary goal of RQ4 was to explore the correlates of CeD related to food attitudes and behaviors, as assessed by the CD-FAB. Multiple regression analyses were conducted to predict QoL (overall QoL, dysphoria, limitations, health concerns, inadequate treatment), anxiety

(state and trait) and depression from CD-FAB total scores.

Table 44 summarizes the analysis results for Overall QoL, dysphoria, limitations, health concerns and inadequate treatment and CD-FAB total and subscale scores. With 56% of participants recruited during the COVID-19 pandemic. The pandemic factor was added as a predictor in the model. Other potential confounders were also added to the regression models.

Multiple regression analyses were conducted to predict QoL (overall QoL, dysphoria, limitations, health concerns, inadequate treatment) from CD-FAB total scores, gender, age, years since diagnosis, reported symptoms (CDSD), diet adherence (CDAT), BMI and COVID-19 status. The table summarizes the analysis results for all four models. The first model with

Overall QoL as the dependent variable explained a statistically significant proportion (55.0%) of 127

the variance in the outcome [R² = .550, F (6, 43) = 8.75, p < .001]. Associations were found between Overall QoL and Total CD-FAB (p=.008) and diet adherence (CDAT) (p=.002). For each increase in Overall QoL scores, there is a decrease in Total CD-FAB scores by -.50, and a decrease in CDAT scores by -2.74. The second model with dysphoria as the dependent variable explained a statistically significant proportion (47.9%) of the variance in the outcome [R² = .479,

F (6, 43) = 6.59, p <.001]. Significant associations were found between dysphoria, CDAT

(p<.001) and BMI (p<.05). For each increase in dysphoria scores, there is a decrease in CDAT scores by -4.24 (p<.001). For each increase in dysphoria scores, there is an increase in BMI by

1.83 (p<.05).

The third model with limitations as the dependent variable explained a statistically significant proportion (59.7%) of the variance in the outcome [R² = .597, F (6, 43) =10.61, p

<.001]. Significant associations were found between limitations and Total CD-FAB (p<.001), and CDAT (p=.005). For each increase in limitations scores, there is a decrease in Total CD-FAB scores by -.72 and a decrease in CDAT scores by -2.52. The fourth model with health concerns as the dependent variable explained a statistically significant proportion (33.4%) of the variance in the outcome [R² = .334, F(6, 43) = 3.60, p =.006]. Significant associations were found between health concerns and COVID-19 status (p<.001). The fifth model with inadequate treatment as the dependent variable did not explain a statistically significant proportion (23.2%) of the variance in the outcome [R² = .127, F(6, 43) = 1.04, p =.411].

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Table 44-QoL associated with CD-FAB total and subscale scores including COVID-19 status

Predictors B Std. Error t p-value

Model 1- Overall QoL (constant) 91.57 16.21 5.65 .000*** Total CD-FAB -.50 .18 -2.79 .008** Yeas since diagnosis .37 .48 .77 .445 CDSD .64 1.91 .34 .738 CDAT -2.74 .83 -3.29 .002** BMI .59 .61 .98 .335 COVID-19 status+ 8.63 4.77 1.81 .078 2 R .550 F-statistic 8.75*** Model 2- Dysphoria (constant) 94.07 21.53 4.37 .000*** Total CD-FAB -.44 .24 -1.83 .074 Yeas since diagnosis .30 .63 .48 .635 CDSD .14 2.54 .05 .957 CDAT -4.24 1.10 -3.84 .000*** BMI 1.83 .81 2.26 .029 COVID-19 status+ 3.66 6.34 .58 .567 2 R .479 F-statistic 6.59*** Model 3- Limitations (constant) 98.80 16.43 6.01 .000*** Total CD-FAB -.72 .18 -3.97 .000*** Yeas since diagnosis .34 .48 .71 .480 CDSD -.27 1.94 -.14 .891 CDAT -2.52 .84 -2.99 .005** BMI .56 .62 .91 .370 COVID-19 status+ 5.05 4.84 1.04 .303 2 R .597 F-statistic 10.61*** Model 4- Health Concerns (constant) 78.21 23.84 3.28 .002** Total CD-FAB -.30 .26 -1.13 .263 Yeas since diagnosis .39 .70 .56 .581 CDSD 1.83 2.81 .65 .518 CDAT -1.87 1.22 -1.53 .134 BMI -.19 .90 -.22 .830 COVID-19 status+ 19.06 7.02 2.72 .009** 2 R .334 F-statistic 3.60** Model 5- Inadequate treatment (constant) 87.06 35.00 2.49 .017* Total CD-FAB -.15 .39 -.38 .706 Yeas since diagnosis .55 1.03 .54 .594 CDSD 2.84 4.13 .69 .496 CDAT -2.88 1.80 -1.61 .115 BMI .26 1.31 .20 .843 COVID-19 status+ 8.59 10.31 .83 .409 2 R .127 F-statistic 1.04 *p<.05 **p<.01 ***p<.001 Note: due to small samples size, gender, age, household income, education level, RDN visit, Biagi and BFI were removed from predictor list- however when included, same results were found. The models were also run with each of the five personality characteristics from BFI individually- and again same results were found. +Covid-19 status means they were recruited either pre-or during the pandemic

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Multiple regression analyses were also conducted to predict anxiety (state and trait), and clinical depression from CD-FAB total scores and subscale scores (Food attitudes, fear response, adaptive response).

Table 45 summarizes the analysis results for anxiety (state and trait) and clinical depression and CD-FAB total. With 56% of participants recruited during the COVID-19 pandemic. The pandemic factor was added as a predictor in the model. Other potential confounders were also added to the regression models. Multiple regression analyses were conducted to predict anxiety (state and trait) and depression from CD-FAB total scores, gender, age, years since diagnosis, reported symptoms (CDSD), diet adherence (CDAT), BMI and

COVID-19 status. The table summarizes the analysis results for all three models. The first model with state anxiety as the dependent variable did not explain a statistically significant proportion

(23.7%) of the variance in the outcome [R² = .237, F (6, 43) = 2.22, p=.059]. The second model with trait anxiety as the dependent variable explained a statistically significant proportion

(30.9%) of the variance in the outcome [R² = .309, F (6, 43) = 3.20, p=.011]. Significant associations were found between trait anxiety and CDAT (p=.002). For each increase in trait anxiety scores, there is an increase in CDAT scores by 1.74. This indicated that higher trait anxiety was associated with poorer adherence to GFD.

The third model with depression as the dependent variable explained a statistically significant proportion (40.3%) of the variance in the outcome [R² = .403, F (6, 43) =4.84, p

=.001]. Significant associations were found between depression and CDAT (p<.001). For each increase in depression scores, there is an increase in CDAT scores by .89. This indicated that higher depression was associated with poorer adherence to GFD.

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Table 45-Anxiety and depression associated with CD-FAB total and subscale scores including COVID-19 status

t Predictors B Std. Error p-value Model 1- State anxiety (constant) 27.12 13.02 2.08 .043* Total CD-FAB .13 .14 .90 .371 Years since diagnosis -.12 .38 -.32 .751 CDSD .21 1.54 .14 .893 CDAT 1.56 .67 2.33 .024* BMI -.52 .49 -1.06 .296 COVID-19 status+ -1.16 3.83 -.30 .763 R2 .237 F-statistic 2.22 Model 2- Trait anxiety (constant) 28.15 10.11 2.78 .008** Total CD-FAB .05 .11 .40 .692 Years since diagnosis -.02 .30 -.08 .939 CDSD -.24 1.19 -.20 .845 CDAT 1.74 .52 3.36 .002** BMI -.39 .38 -1.02 .315 COVID-19 status+ -2.24 2.98 -.75 .457 R2 .309 F-statistic 3.20* Model 3- Depression (constant) 7.76 4.09 1.90 .064 Total CD-FAB .03 .05 .55 .586 Years since diagnosis .04 .12 .33 .746 CDSD .01 .48 .02 .982 CDAT .89 .21 4.23 .000*** BMI -.19 .15 -1.20 .235 COVID-19 status+ -.49 1.20 -.41 .687 R2 .403 F-statistic 4.84** *p<.05 **p<.01 ***p<.001 Note: due to small samples size, gender, age, household income, education level, RDN visit and BFI were removed from predictor list- however when included, same results were found. The models were also run with each of the five personality characteristics from BFI individually- and again same results were found. + Covid-19 status means they were recruited either pre-or during the pandemic

4.6.5 Tertiary Split of CD-FAB and Quality of Life, anxiety and depression scores.

To replicate Satherley et al.’s thesis work on the CD-FAB, further analysis was done. As per the tertiary split around total CD-FAB scores, 34 % (N=17) scored low between 11 and 27,

32% (N=16) scored medium between 30 and 4, and 34% (N=17) scored high between 44 and 66 on the overall CD-FAB measure showing a slightly uniform dispersion in food attitudes and behaviors in CeD adults. The one-way ANOVAs found that individuals who scored high, 131

medium and low on the CD-FAB differed in terms of overall QoL [F(2, 49)=10.50, p<.001], dysphoria [F(2, 49)=6.47, p=.003] and limitations [F(2, 49)=16.3, p<.001] subscales. It is important to note that there were clinically meaningful differences in mean scores between tertiles, there is a 30-point decrease in overall QoL mean score between low and high CD-FAB scorers. High CD-FAB scorers have state and trait anxiety scores above the cut-off of 39, indicating symptoms of state and/or trait anxiety. The same applies to depression, high scorers have depression scores above the cut-off of 15, indicating greater depressive symptoms.

This suggests that adults who seem to score above 44 on the CD-FAB tool (high scorer), have lower QoL (lower dysphoria, limitations, health concerns and inadequate treatment), have symptoms of state and trait anxiety and are at greater risk for clinical depression.

Table 46- CD-FAB Total scores tertiary split+

CD-FAB Total Score Means ANOVA

Low Score Medium Score High score F p-value N=17 N=16 N=17 Statistic (11- 27) (30- 43) (44- 66) Quality of Life Overall QoL 74.49 (18.81) 66.95 (20.34) 47.04 (14.54) 10.50 <.001*** Dysphoria 85.29 (23.27) 80.08 (24.07) 57.72 (23.75) 6.47 .003** Limitations 74.02 (17.26) 65.30 (17.52) 40.48 (18.83) 16.3 <.001*** Health concerns 65.88 (24.89) 60.00 (29.66) 45.44 (18.38) 3.10 .055 Inadequate treatment 76.47 (26.83) 65.63 (40.44) 58.82 (29.90) 1.26 .294

State anxiety 32.12 (10.89) 37.50 (12.48) 42.47 (14.24) 2.86 .067

Trait anxiety 36.29 (10.55) 39.25 (9.61) 43.71 (11.06) 2.17 .125

Depression 14.65 (4.06) 13.44 (2.48) 16.76 (6.20) 2.30 .112

*p<.05 **p<.01 ***p<.001 + Note: higher QoL scores suggest better QoL; scores above 39 for state and trait anxiety, suggest symptoms of state and/or trait anxiety and those who score above 15 may be at risk for clinical depression.

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4.6.6 Summary Findings:

The overall CD-FAB scores of adults with CeD, varied depending on QoL scores, suggesting that the lower the QoL measures the higher the CD-FAB scores.

The overall CD-FAB score of adults (18-45 years old) with CeD, were positively correlated with anxiety (state and trait) and depression symptoms scores; suggesting that the higher the CD-FAB scores the higher the degree of anxiety (state and trait) and depression symptoms reported.

However, when comparing mean scores of participants with anxiety (state and trait) and depression symptoms as per questionnaire cut-offs; there were no significant differences in means of CD-FAB scores.

Associations were found between QoL and CD-FAB scores. The regression model showed that when QoL scores of adults with CeD between the ages of 18 to 45 years increase

(higher QoL), CD-FAB scores decrease (lower disordered eating attitudes and behaviors) and adherence to the GFD increases. Associations were also found between trait anxiety and CDAT scores, suggesting that higher trait anxiety was associated with poorer adherence to GFD.

Associations were also found between depression an CDAT scores, suggesting that higher depression was associated with poorer adherence to GFD.

Adults who scored high, medium and low on the CD-FAB (as per the teritiary split) differed in terms of overall QoL, and limitations subscales. It is important to note that there were clinically meaningful differences in mean scores between tertiles, there is a 30-point decrease in overall QoL mean score between low and high CD-FAB scorers. High CD-FAB scorers have state and trait anxiety scores above the cut-off of 39, indicating symptoms of state and/or trait anxiety. The same applies to depression, high scorers have depression scores above the cut-off of

15, indicating greater depressive symptoms. 133

4.7 Pre- and During- COVID-19 Pandemic

Nearly half the participants (N=22) were recruited pre-COVID-19 and the remaining

(n=28) during-COVID-19, all survey score means pre- and during-pandemic were compared using independent sample t-test and ANOVA models (Table 49).

First, demographic characteristics of participants recruited pre-COVID-19 and during-

COVID-19 were compared. In table 47, an independent-samples t-test was conducted to compare mean age, age at diagnosis, BMI and years since diagnosis of adults recruited pre vs. during the pandemic. Demographic characteristic of adults with CeD recruited pre- and during the pandemic were similar. Levene’s test indicated that the variances were equal across groups (p- value > .05). With equal variances assumed, the mean age, age at diagnosis, BMI and years since diagnosis were not significantly different between participants.

Table 47- Demographic characteristics of study sample pre and during COVID-19

Adults (N=50) Pre-COVID-19 During-COVID-19 t-test Mean (SD) Mean (SD) (N=22) (N=28) t df sig Age 29.23 (5.83) 29.89 (8.55) -.31 48 .756

Age at diagnosis 23.84 (8.26) 21.92 (10.07) .72 48 .472

BMI 22.63 (4.56) 23.56 (3.58) -.82 48 .419

Years since diagnosis 5.84 (5.14) 8.28 (5.29) -1.64 48 .108

Table 48 shows demographic characteristics of the total sample, as well as pre-COVID-

19 and during COVID-19. Using chi-square analysis, Pre-COVID-19 participant characteristics were compared to characteristics of participants recruited during COVID-19. No significant differences were found between participants recruited pre- compared to during the pandemic.

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Table 48- Demographic characteristics of study sample pre and during COVID-19

Adults (N=50) Total sample Pre-COVID-19 During COVID-19 N= 50 (%) N= 22(%) N= 28(%) Gender Female 35 (70%) 16 (72.7%) 19 (67.9%) Male 15 (30%) 6 (27.3%) 9 (32.1%) Ethnicity Hispanic 5 (10%) 2 (9.1%) 3 (10.7%) Non- Hispanic 45 (90%) 20 (90.9%) 25(89.3%) Race White 47 (94%) 19 (86.4%) 28 (100.0%) Black or African 1 (2%) 0 (0.0%) 1 (3.6%) American Asian 2 (4%) 2 (9.1%) 0 (0.0%) Other 3 (6%) 2 (9.1%) 1 (3.6%) Education Some college 8 (16%) 2 (9.1%) 6 (21.4%) College graduate 32 (64%) 16 (72.7%) 16 (72.7%) Postgraduate 10 (20%) 4 (18.2%) 6 (21.4%) Household income <$50,000 4 (8%) 3 (14.3%) 1 (4.0%) $50,000 to $100,000 11 (22%) 6 (28.6%) 5 (20.0%) >$100,000 31 (62%) 12 (57.1%) 19 (76.0%) RDN visit RDN currently 24 (48%) 9 (40.9%) 15 (53.6%) RDN past only 16 (32%) 8 (57.1%) 8 (50.0%) RDN never 14 (28%) 6 (42.9%) 8 (50.0%) Current GI symptoms No reported symptoms 8 (16%) 3 (13.6%) 5 (17.9%) 1 reported symptom 19 (38%) 6 (27.3 %) 13 (46.4%) 2 reported symptoms 9 (18%) 3 (13.6%) 6 (21.4 %) 3 reported symptoms 7 (14%) 6 (27.3%) 1 (3.6%) 4 reported symptoms 7 (14%) 4 (18.2%) 3 (10.7%)

Note: using chi-squared analysis, pre-COVID-19 and during-COVID-19 participant information were compared. There were no differences on demographics between those that participated pre- and during the pandemic.

An independent-sample t-test was conducted to compare total CD-FAB scores and subscale scores of adults (18 -45 years old) pre- and during-COVID-19. Total CD-FAB scores and subscale scores in adults with CeD were affected by the pandemic. The overall CD-FAB mean score was lower (mean=32.38, SD=14.94) during-pandemic than pre-pandemic

(mean=42.91, SD=13.90). Levene’s test indicated that the variances were equal across groups (p-

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value > 0.05). With equal variances assumed, the total CD-FAB mean scores were significantly different between participants pre- and during-COVID-19 (t (48) =2.57, p=.013). The CD-FAB subscale scores (food attitudes and adaptive response) were also significantly different between participants pre- and during-COVID-19 (t (48) =2.80, p=.007; t (48) =2.29, p=.026). The CD-

FAB subscale, fear response was not significantly different between participants pre- and during-COVID-19 (t(48) =1.20, p=.240).

An independent-samples t-test was conducted to compare overall QoL scores and subscale scores of adults (18 -45 years old) in participants pre- and during-COVID-19. Total

CDQoL scores and subscale scores in adults with CeD were affected by the pandemic. The overall CDQoL mean score was lower (mean=52.09, SD=20.88) during-pandemic than pre- pandemic (mean=71.12, SD=17.70); suggesting higher overall QoL for individuals with CeD during the pandemic. Levene’s test indicated that the variances were equal across groups (p- value > 0.05). With equal variances assumed, the total overall QoL mean scores were significantly different between participants pre- and during-COVID-19 (t (48) =-3.49, p=.001).

The CDQoL subscale scores (Dysphoria, limitations and health concerns) were also significantly different between participants pre- and during-Covid (t (48) =-2.37, p=.022; t (48) =-3.00, p=.004; t (48) =-3.79, p=<.001). The subscale, inadequate treatment was not significantly different between participants pre- and during-COVID-19 (t(48) =-1.53, p=.133).

An independent-samples t-test was conducted to compare number of symptoms reported by participants pre- and during-COVID-19. Total number of symptoms reported by adults with CeD were not affected by the pandemic. Levene’s test indicated that the variances were equal across groups (p- value > 0.05). With equal variances assumed, the number of symptoms were not significantly different between participants pre- and during-COVID-19 (t (48) =1.84, p=.072). 136

An independent-samples t-test was conducted to compare personality characteristics

(BFI) of adults (18 -45 years old) pre- and during-COVID-19. Personality characteristics scores in adults with CeD were not affected by the pandemic, with the exception of neuroticism. The mean score for neuroticism was lower (mean=20.85, SD=6.46) during- than pre-pandemic

(mean=25.23, SD=6.61); suggesting that adults with CeD were emotionally stable, calm, even- tempered and relaxed during the pandemic. Levene’s test indicated that the variances were equal across groups (p- value > 0.05). With equal variances assumed, extroversion, agreeableness, conscientiousness and openness characteristics were not significantly different between participants pre- and during-COVID-19 (t (48) =.08, p=.934; t (48) =-.91, p=.365; t (48) =-1.14, p=.261; t(48) =-1.56, p=.126). Neuroticism was significantly different between participants pre- and during-COVID-19 (t(48) =2.35, p=.023).

An independent-samples t-test was conducted to compare depressive symptoms reported by participants pre- and during-COVID-19. Overall CESD scores reported by adults with CeD were not affected by the pandemic. Levene’s test indicated that the variances were equal across groups (p- value > 0.05). With equal variances assumed, CESD scores were not significantly different between participants pre- and during-COVID-19 (t (48) =1.65, p=.105).

An independent-samples t-test was conducted to compare anxiety state and trait of participants pre- and during-COVID-19. Overall STAI scores (state and trait anxiety) reported by adults with CeD were not affected by the pandemic. Levene’s test indicated that the variances were equal across groups (p- value > 0.05). With equal variances assumed, STAI (state and trait anxiety) scores were not significantly different between participants pre- and during-COVID-19

(t (48) =1.57, p=.123; t (48) =1.87, p=.068).

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An independent-samples t-test was conducted to compare diet adherence of participants pre- and during-COVID-19. Overall CDAT scores reported by adults with CeD were not affected by the pandemic. Levene’s test indicated that the variances were equal across groups (p-value >

0.05). With equal variances assumed, CDAT scores were not significantly different between participants pre- and during-COVID-19 (t (48) =1.61, p=.114).

An independent-samples t-test was conducted to compare EPSI subscale scores of adults

(18 -45 years old) in participants pre- and during-COVID-19. EPSI subscale scores reported by adults with CeD were not affected by the pandemic, except for binge eating and restricting subscales. The EPSI subscales scores for binge eating and restricting were significantly different between participants pre- and during-COVID-19 (t(48) =2.17, p=.034; t(48) =2.21, p=.032). The

EPSI subscales scores for body dissatisfaction, cognitive restraint, purging, excessive exercise, negative obesity and muscle building were not significantly different between participants pre- and during-COVID-19 (t (48) =.93, p=.356; t (48) =.22, p=.828; t (48) =-.10, p=.924; t (48) =-

1.16, p=.254; t (48) =.129, p=.898; t (48) =1.26, p=.212).

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Table 49- Total survey mean scores pre- and during- COVID-19 pandemic

Total Pre-Covid During-Covid t-test of Means (N=22) (N=28) Range of scores Mean SD Mean SD Mean SD t df p-value CD-FAB Total 11 to 77 36.96 15.30 42.91 13.90 32.29 14.94 2.57 48 .013* Food Attitudes 3 to 21 14.46 7.39 17.55 6.72 12.04 7.07 2.80 48 .007** Fear Response 4 to 28 8.18 4.10 8.96 4.15 7.57 4.03 1.20 48 .240 Adaptive Response 4 to 28 14.32 5.95 16.41 5.79 12.68 5.64 2.29 48 .026* CDQoL Total Out of 100 62.75 21.22 52.09 20.88 71.12 17.70 -3.49 48 .001** Dysphoria Out of 100 74.25 26.20 64.77 25.63 81.70 24.59 -2.37 48 .022* Limitations Out of 100 59.83 22.73 49.75 25.80 67.75 16.49 -3.00 48 .004** Health Concerns Out of 100 57.05 25.66 43.30 25.84 67.86 20.02 -3.79 48 <.001*** Inadequate treatment Out of 100 67.00 32.90 59.09 31.85 73.21 32.93 -1.53 48 .133 CDSD Out of 4 1.72 1.29 2.09 1.38 1.43 1.17 1.84 48 .072 Big 5 Extroversion 8 to 40 28.28 6.27 28.36 7.07 28.21 5.69 .08 48 .934 Agreeableness 9 to 45 35.82 5.62 35.00 6.24 36.46 5.10 -.91 48 .365 Conscientiousness 9 to 45 36.32 4.53 35.50 5.00 36.96 4.10 -1.14 48 .261 Neuroticism 8 to 40 22.78 6.82 25.23 6.61 20.85 6.46 2.35 48 .023* Openness 10 to 50 37.30 5.82 38.73 5.69 36.18 5.78 1.56 48 .126 CESD 0 to 60 14.98 4.64 16.18 5.25 14.04 3.95 1.65 48 .105 STAI State anxiety 20 to 80 37.36 13.09 40.59 11.34 34.82 13.99 1.57 48 .123 Trait anxiety 20 to 80 39.76 10.69 42.86 10.57 37.32 10.31 1.87 48 .068 CDAT 0 to 35 11.90 3.27 12.73 3.60 11.25 2.89 1.61 48 .114 EPSI Body dissatisfaction 0 to 28 9.84 7.79 11.00 8.83 8.93 6.89 .93 48 .356 Binge eating 0 to 32 8.12 6.54 10.32 7.83 6.39 4.79 2.17 48 .034* Cognitive Restraint 0 to 12 4.54 2.74 4.64 2.38 4.46 3.04 .22 48 .828 Purging 0 to 24 .24 .82 .23 .87 .25 .80 -.10 48 .924 Restricting 0 to 24 4.86 5.36 6.68 6.26 3.43 4.10 2.21 48 .032* Excessive Exercise 0 to 20 5.57 4.96 4.66 4.38 6.29 5.34 -1.16 48 .254 Negative Obesity 0 to 20 3.58 4.88 3.68 5.03 3.50 4.85 .129 48 .898 Muscle Building 0 to 20 2.16 2.83 2.73 3.43 1.71 2.23 1.26 48 .212 *p<.05 **p<.01 ***p<.001

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4.7.1 Summary Findings:

Demographic characteristics of the sample pre- and during-COVID-19 were similar. Yet, total CD-FAB scores of adults with CeD (18-45 years old) recruited pre-COVID-19 were significantly higher compared to patients recruited during-COVID-19. Overall QoL of adults with CeD pre-COVID-19 was significantly lower compared to patients recruited during-COVID-

19. Finally, adults with CeD scored significantly higher on binge eating and restricting subscales of EPSI pre-COVID-19 compared to during-COVID-19.

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Chapter 5 – Discussion

This Chapter compares and contrasts the results found with those of other studies.

Limitations, strengths, implications, applications, and future studies that would build upon this study are also discussed.

5.1 Purpose and Main Findings

The purpose of this study was to better understand the extent to which disordered eating attitudes and behaviors were common in a sample of 50 adults (18 – 45 years old) with biopsy- diagnosed CeD, as well as the relationship of disordered eating attitudes and behaviors with various QoL measures, including anxiety and depression. Fifty adults (35 women and 15 men) with CeD, 90% white and non-Hispanic, were recruited from the Celiac Disease Center at

Columbia University Irving Medical Center (mean age=29.56, SD=7.40) and comprised the study sample.

Key Takeaway #1: Among the study sample, suggestive Eating Disorders (ED)

(based on EDDS) and Disordered Eating (DE) (based on EPSI) were present, but low. One adult had a suggestive diagnosis of BED (2%), 6 had suggestive diagnoses of possible OSFED

(12%) (2% low frequency BN and 6% night eating syndrome). Although uncommon, DE as measured by EPSI reported by adults with CeD in this study, include body dissatisfaction, binge eating, cognitive restraint, restricting, negative attitudes towards obesity, excessive exercising

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and muscle building. Females had higher means for body dissatisfaction, cognitive restraint and purging compared to males in this study sample

Key Takeaway #2: The CD-FAB is a relatively new validated tool that may have utility in identifying individuals with CeD that have disordered eating attitudes and behaviors, particularly those in the first few years after diagnosis. It likely has limited utility in identifying suggestive EDs (as per EDDS) and DE (as per EPSI). Compared to the only other study that used the CD-FAB (a UK sample), this study found similar mean CD-FAB scores. The scale had both convergent and discriminant validity. Those with suggestive diagnosis of OSFED as per the EDDS did appear to have higher CD-FAB scores compared to those in the overall sample. In contrast, those who had the most DE as measured by EPSI, did not have significantly higher CD-FAB scores. Given the weak correlations with the EDDS and EPSI, the

CD-FAB alone should not be the only determinant for an RDN to decide who may be at risk for

ED or DE as measured by EDDS and EPSI. Yet, the tool may have utility in detecting disordered eating attitudes and behaviors in adults who have been more recently diagnosed with CeD, as well as for deciding who may warrant clinical follow-up by professionals for other diagnoses such as ARFID. Adults who have been more recently diagnosed with CeD had more disordered eating attitudes and behaviors as measured by CD-FAB.

Key Takeaway #3: The main factors that were associated with higher CD-FAB scores were BMI, GI symptoms, years since diagnosis, diet adherence and personality characteristics. Other factors such as gender, household income, education level and whether they were seeing an RDN or not, did not appear to be associated with CD-FAB 142

scores. When all variables that were univariately associated with CD-FAB scores were added to a regression model, ONLY years since diagnosis continued to be significantly associated with CD-FAB scores. FIVE to SEVEN years seems to be an important cut-point whereby there were significant differences in how participants rated food attitudes, fear responses and adaptive responses on the CDFAB scales. The overall CD-FAB score of adults

(18-45 years old) with CeD, varied depending on BMI, suggesting that participants with lower

BMI had higher CD-FAB scores. Scores also varied depending on number of symptoms, suggesting that participants with higher number of symptoms reported (>3) had higher CD-FAB scores. CD-FAB scores also varied depending on years since diagnosis, suggesting that the most recently diagnosed participants had higher CD-FAB scores. Total CD-FAB scores and subscale scores in adults with CeD were higher for participants whose years since diagnosis were in the low [1.00-7.33] vs high [7.42- 21.67] range. Total CD-FAB scores and subscale scores in adults with CeD were also higher for participants whose years since diagnosis were less than 5, compared to those that were higher than 5. The overall CD-FAB scores of adults with CeD, varied depending on personality characteristics. Individuals with high BFI scores on neuroticism and openness, as well as low BFI scores on extroversion and conscientiousness had higher CD-

FAB scores. Total CD-FAB scores and subscale scores (with the exception of the adaptive response subscale) in adults with CeD were affected by adherence to GFD. In this study, high adherence (high compliance to the GFD) was associated with low CD-FAB scores. However, when all of these variables that were univariately associated with CD-FAB scores were added to a regression model, ONLY years since diagnosis continued to be significantly associated with

CD-FAB scores.

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Key Takeaway #4: Higher CD-FAB scores had a significant and meaningful association with QoL scores. Although higher CD-FAB scores were associated with higher anxiety and depression, these relationships were not significantly different. When all variables that were univariately associated with QoL, anxiety and depression were added to a regression model, CD-FAB scores were ONLY significantly associated with QoL scores. Multivariate techniques showed an association between QoL scores of adults with CeD between the ages of 18 to 45 years and CD-FAB scores. When CD-FAB scores increased (higher disordered eating attitudes and behaviors), QoL scores decreased. In addition, adults who scored high, medium and low on the CD-FAB (as per the tertiary split) differed in terms of overall QoL, and limitations subscales. It is important to note that there were clinically meaningful differences in mean scores between tertiles, such that there was a 30-point difference in overall QoL scores between low and high CD-FAB scorers. In prior studies, a decline of about 10 points was suggestive of clinical significance, and sufficient to move individuals into a worse category of self-reported QoL measures (Dorn et al., 2010). Although the difference was not statistically significant, high CD-FAB scorers have state and trait anxiety scores above the cut-off of 39, indicating symptoms of state and/or trait anxiety. The same applies to depression, high CD-FAB scorers have depression scores above the cut-off of 15, indicating greater depressive symptoms.

The proposed framework in Chapter 1, has now been modified and revised to present this study’s findings, as shown in the above 4 key takeaways.

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Figure 7- Framework for disordered eating attitudes and behaviors leading to eating disorders and disordered eating in CeD based on the CD-FAB (adapted from (H. B. Murray et al., 2020)

Key Takeaway #5: Although not the focus of this dissertation, an unexpected finding was that participants recruited during the COVID-19 pandemic had significantly

LOWER CD-FAB scores and HIGHER QoL scores, compared to those recruited pre-

COVID-19 despite not having significant differences in any other demographic characteristics. In addition, participants recruited during the pandemic also had lower anxiety and depression scores, compared to those recruited pre-COVID-19, however these did not reach statistical significance. Although it is speculated that better well-being may be

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due to the decreased stress that typically comes with eating out and social situations in a

‘typical’ non-pandemic world for those with CeD, these findings were cross-sectional and warrant further investigation.

5.2 ED, DE, Disordered Eating Attitudes and Behaviors and CeD

The distribution of the CD-FAB scores across this sample are spread out around the mean

36.96 (15.30) with a maximum score of 66 out of a possible 77. Because of their CeD, half of the sample reported that they were afraid of eating out, uncomfortable eating gluten free foods from other people’s kitchens, don’t enjoy going out as they did before their diagnosis, nearly half get worried when eating with strangers, and have stopped going to restaurants since diagnosis. Many reported they were afraid to touch gluten-containing foods and over a third reported their concern about being near others when eating gluten. These findings from the CD-FAB suggest specific areas of disordered eating attitudes and behaviors that were particularly problematic. On the other hand, 80% reported that if they asked questions, they could normally find gluten-free foods to eat. Future studies will need to learn more about those individuals that score high on the CD-

FAB and the extent to which their disordered eating attitudes and behaviors are impacting their

QoL, as it is those individuals that may be in most need for clinical follow-up care.

The study sample CD-FAB scores were compared to CD-FAB scores of 41 participants with biopsy diagnosed CeD in the UK, as part of Dr. Satherley’s research study (R.-M. Satherley et al., 2018). The CD-FAB total mean score for the UK sample was not significantly different from the mean score for this study sample. This was surprising because CeD patients in the UK have very different experiences compared to patients in the US. In the UK, patients diagnosed with CeD have prescriptions to GF foods and access to GF foods is much easier than in the US 146

(CoeliacUK, 2020) so one may have assumed the CD-FAB scores in our US sample would have been much higher than the UK sample. This could be simply a reflection of the CD-FAB detecting disordered attitudes and beliefs about fear response, adaptive response, and food attitudes and not related to accessibility of GF foods.

In this study, out of 50 participants with biopsy diagnosed CeD, 14% of adults in this study seemed to have suggestive eating pathologies under the DSM-V [one patient (2%) had a suggestive diagnosis of an eating disorder (BED) and 6 participants had suggestive diagnosis of possible OSFED (12%)]. This percentage is very close to Karawautz et al. (2008) findings; out of 210 girls with biopsy diagnosed CeD recruited in his study, 32 (~15%) had eating pathologies.

Although uncommon, adults with CeD between the ages of 18 and 45 years of age reported DE such as body dissatisfaction, binge eating, cognitive restraint, restricting and excessive exercising. However, mean scores were much lower than adults with ED and college students between the ages of 18 and 25 years from Forbush et al.’ study. Females had significantly higher means for body dissatisfaction, cognitive restraint and purging compared to males in this study (p<.05). Previous studies have also shown that women appear to be at greater risk for eating pathologies that are conventionally defined (Jacobi et al., 2011; Jacobi, Hayward, de Zwaan, Kraemer, & Agras, 2004; Striegel-Moore, Silberstein, & Rodin, 1986). Forbush et al. found significantly higher means in males than females for excessive exercise, muscle building and negative attitudes toward obesity. In this study, there were no significant difference between males and females for excessive exercise, muscle building and negative attitudes toward obesity; however, men with CeD had higher means for muscle building than females.

Karawautz et al. performed a systematic study on eating pathology in CeD, whereby a lifetime history and current presence of eating pathology (ED and DE) were analyzed in 147

adolescent patients with CeD (Karwautz et al., 2008). The study showed that in 283 adolescents with CeD 4.8% had a lifetime history of ED and 3.9% had a current ED. In addition, 10.2% had a lifetime history of DE vs. 10.7% with a current DE. Finally adolescent with CeD and ED or DE had higher scores on most eating pathology related questionnaires (of which are the Eating

Disorder Inventory (EDI-2) and Eating Disorder Examination Questionnaire (EDE-Q)) as compared to the general population (Karwautz et al., 2008). Satherley et al. used the EAT-26 and

Binge Eating Scale (BES) to measure disordered eating attitudes and self-reported behaviors.

Findings also showed the prevalence of DE, with 15.7% scoring above the clinical cut-off for

EAT-26 in individuals with CeD (R. M. Satherley, Howard, & Higgs, 2016). The latter is lower than Arigo et al.’s previous reports of 22% (39 out of 177 participants) but significantly higher compared to healthy controls (Arigo, Anskis, & Smyth, 2012, R. M. Satherley, Howard, &

Higgs, 2016)

There is evidence that individuals with CeD are diagnosed with ED and there is also evidence that DE are affecting individuals with CeD. However, published studies describe DE as a whole, rather than breaking these behaviors into subtypes. This exploratory study showed that adults with CeD (ages 18 to 45 years old) seem to have eating pathologies, a small percentage was suggestively diagnosed with an ED, and some may be experiencing DE. With EPSI subscale mean scores higher than zero, the tool may be suggesting that something was going on.

However, apart from restricting, the disordered eating attitudes and behavior reported by adults with CeD (as per the CD-FAB) did not seem to be reflected in DE pathologies measured by the

EPSI tool. Future studies will need to find a way to study common DE subtypes that are aligned with the disordered eating attitudes and behaviors perceived by the CD-FAB in adults with CeD.

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ARFID

The question is whether disordered eating attitudes and behaviors may be considered

ARFID under the DSM-V. More recently, ARFID is used to identify a group of patients who have avoidant or restrictive eating behaviors without a motive of being thinner or following body image disturbances interfering with psychosocial functioning. In a recently published systematic review Bourne et al. identified that the literature portrays ARFID as a distinct clinical diagnosis but that a better understanding of the varied mechanisms that lead patients to develop food avoidance and/or restriction is needed (Bourne et al., 2020).

Both BED and ARFID do not have body image concerns as core diagnostic criteria (Hay,

2020). They are distinguished by being disordered eating behaviors or patterns, the former of recurrent binge eating without regular purging and the latter of avoidance and aversion to food and eating (Diagnostic and statistical manual of mental disorders : DSM-5, 2013; Hay, 2020).

When assessing marked interference with psychological functioning, there seem to be an overlap in the factors associated with the psychological distresses observed and studied in the restrictive nature of the GFD. Depression, anxiety, and fear of negative consequences from eating that are observed in individuals with CeD in this study, are considered psychosocial impairments related to eating/feeding problems.

We don’t have the ability to test for ARFID as there are no current tests out there. But participants with CeD with high disordered eating attitudes and behaviors as per the CD-FAB seem to be aligned with psychological distress observed in patients with ARFID (high food attitudes, fear response, adaptive response; low overall QoL, dysphoria, limitations, health concerns and high anxiety and depression). Whether or not the CD-FAB will ultimately be able to determine those at risk for ARFID warrants further investigation. 149

5.3 Adherence, years since diagnosis, BMI, symptoms and CD-FAB

Adherence/ Vigilance

In a systematic review, Hall et al. showed that strict adherence rate in individuals aged 16 and older, have been reported to vary between 42 and 91% based on survey data (Hall et al.,

2009). In this study, 68% (N=34) were adherent to the GFD (total score less than or equal to 13 on CDAT) falling in the range of previously reported rates of other studies (Hall et al., 2009).

There was a positive correlation between CDAT scores and total CD-FAB scores suggesting that participants with lower adherence seemed to have higher CD-FAB scores, hence higher disordered eating attitudes and behaviors. This is consistent with previous studies showning that patients who showed signs of ED and DEs were more often noncompliant with their GFD

(Karwautz et al., 2008; Wagner et al., 2015).

In this study, diet adherence was also assessed using 3 additional questions from the

Biagi questionnaire (Biagi et al., 2012). In some ways the Biagi can be thought of as measuring vigilance to the GFD, not just diet adherence. Although a subtle difference, the Biagi asks about the extensiveness of label reading and informing those preparing their meals about their disease.

When looking at CD-FAB total scores of those who always tell the person cooking about their disease when eating out, they had higher CD-FAB scores [39.61 (14.31)] than those who never did [25.00 (1.41)]. Similarly, when looking at CD-FAB total scores of those who always checked labels of packaged foods, they had higher CD-FAB scores [37.78 (14.74)] than those who sometimes did [27.50 (20.92)]. This may imply that participants with higher CD-FAB scores have higher vigilance. Diet adherence seem to be indifferent from vigilance in this study, the

CD-FAB tool is in fact a measure of vigilance more so than adherence. Vigilance around food cross-contact is important for patients with CeD. However, hypervigilance can become 150

dysfunctional and may negatively impact physical and psychosocial well-being (R. M. Satherley et al., 2017).

Years since diagnosis

There was a significant negative correlation between overall CD-FAB scores and the number of years since diagnosis. This relationship suggested that the most recently diagnosed had higher CD-FAB scores, thus higher disordered eating attitudes and behaviors. When all variables that were univariately associated with CD-FAB scores were added to a regression model, only years since diagnosis continued to be significantly associated with CD-FAB scores.

Total CD-FAB scores and subscale scores in adults with CeD were higher for participants whose years since diagnosis were in the low [1.00-7.33] vs high [7.42- 21.67] range of years. Total CD-

FAB scores and subscale scores in adults with CeD were also higher for participants whose years since diagnosis were less than 5 compared to higher than 5. Five to seven years seemed to be an important cut-point whereby there were significant differences in how participants rated food attitudes, fear responses and adaptive responses on the CDFAB scales. This suggested that clinicians may want to consider priopritizing the CD-FAB in patients less than five to seven years post- diagnosis to assess disorderd eating attitudes and behaviors.

BMI

There was a negative small correlation between CD-FAB total scores and BMI. This relationship suggested that the lower the participant’s BMI (mean =23.25, SD=4.02) was the higher their CD-FAB scores. Participants with higher disorder eating attitudes and behaviors

(higher CD-FAB scores) had lower BMI and had lower number of years since diagnosis. 151

Number of GI symptoms

In this study, the higher the number of GI symptoms participants reported, the higher their disordered eating attitudes and behaviors (high CD-FAB scores). Previous studies have also shown the association between symptom severity and DE (Arigo et al., 2012; K. Sainsbury et al.,

2013; Tang et al., 1998). However, it is not clear whether symptom severity prior to diagnosis

(A. Sainsbury et al., 2013), or the frequency of symptoms during the course of CeD lead to the development of DE (Tang et al., 1998). Contrary to fully adherent patients, nonadherent or partially adherent patients conveyed more abdominal bloating and fatigue (Barratt et al., 2013;

A. Sainsbury et al., 2013). In alignment with our study findings, low adherence to the GFD has been shown to be associated with a negative impact on QoL (Barratt et al., 2013; A. Sainsbury et al., 2013).

5.4 Quality of Life, anxiety and depression and CD-FAB

Quality of Life

Adults with biopsy diagnosed CeD who revealed higher disordered eating attitudes and behaviors (as per the CD-FAB) reported higher dysphoria, hence, felt depressed, frightened or overwhelmed by their diagnosis. Participants also reported higher limitation, they felt limited by their diagnosis when eating out with others, socializing and traveling. Adults with CeD with high hypervigilance and disordered eating attitudes and behaviors also reported higher health concern, they felt worried about long-term health outcomes of their diagnosis for other family members and themselves as well as concerns about inadequate treatment. Participants with higher disordered eating attitudes and behaviors reported lower overall QoL scores. In addition, when

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comparing QoL scores of low, medium and high CD-FAB scorers (as per the tertiary split); higher CD-FAB scorers had significantly lower QoL scores compared to low and medium scorers (p<.05). When predicting overall QoL, dysphoria, limitations and health concerns from total CD-FAB scores, a significant association was found. Overall QoL, dysphoria and limitations were associated with both total CD-FAB scores and CDAT scores (diet adherence).

High scores on the CD-FAB have been associated with a fear of trying new foods and an impaired QoL, particularly in social domain (R.-M. Satherley et al., 2018)

Our study findings were aligned with previous studies reporting that less or non-adherent patients have lower QoL compared to adherent patients (Jonas F Ludvigsson et al., 2015;

Marsilio et al., 2020; Zingone et al., 2015). Wolf et. al found that a higher dietary vigilance to a

GFD was associated with lower QoL scores (Wolf et al., 2018). Participants in this study who reported lower adherence (as per the CDAT) and higher vigilance (as per the Biagi questions) to the GFD had higher disordered attitudes and behaviors (higher CD-FAB scores), and lower QoL.

Other studies found that adolescent females with comorbid CeD and EDs are less compliant with their diets and have elevated body dissatisfaction and reported lower QoL (Hedman et al., 2019;

Karwautz et al., 2008; Wagner et al., 2015). Elevated body dissatisfaction was observed in adults with CeD that had a suggestive ED as per the EDDS in this study.

Anxiety and Depression

From a total of 50 recruited participants, 40% (N=20) had an existing state of anxiety at the time of recruitment and 44% (N=22) had trait anxiety, reporting a predisposition to anxious response to situations. When comparing CD-FAB scores of participants with state and trait anxiety to those without, there was no statistically significant difference between groups.

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However, when looking at sate and trait anxiety of low, medium and high CD-FAB scorers (as per the tertiary split), high scorers had higher state and trait anxiety (above cut-off of 39) compared to low and medium scorers.

While anxiety has been shown to decrease after following a GFD which can be explained by adaptation to the GFD and managing of CeD symptoms, few studies showed that depression is present in a higher percentage in patients after diagnosis and post-one year following a GFD

(Addolorato, 2001; Zingone et al., 2015). In this study, 26% (N=13) of participants may have been at risk for clinical depression. When comparing CD-FAB scores of participants reporting clinical depression to those who hadn’t, there was no statistically significant difference between groups. However, depression scores of high CD-FAB scorers (as per the tertiary split) were higher than low and medium scorers (above cut off of 15).

Zingone et al. showed that anxiety and depression in CeD patients did not improve after following a GFD and Hauzer et al. explained that levels of anxiety were high in patients with

CeD, however no symptoms of depression were found (Hauser et al., 2010; Zingone et al.,

2010). The literature on depression and anxiety in patients with CeD is not consistent (Zingone et al., 2015). However, in alignment with our study findings, Sainsbury et al. showed that depressive symptoms can act as barriers to good adherence and depressive symptoms were associated with lower adherence to the GFD (K. Sainsbury & Marques, 2018). In this study, associations were found between trait anxiety and CDAT scores, suggesting that higher trait anxiety was associated with poorer adherence to GFD. Associations were also found between depression an CDAT scores, suggesting that higher depression was associated with poorer adherence to GFD.

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Impact of pandemic on results

When comparing QoL scores of participants recruited pre-COVID-19 (N=22) to those recruited during-COVID-19 (N=28), there was a significant difference of total QoL, dysphoria, limitations and health concerns amongst groups (p<.05). There was no significant difference of inadequate treatment pre- and during-COVID-19 (p>.05). QoL score means were higher during-

COVID-19 than they were pre-COVID-19. This suggested that participants were less depressed, frightened or overwhelmed by their diagnosis of CeD (dysphoria), felt less limited by CeD since they were not eating out with others, socializing, and traveling (limitation) and felt less worried about long-term health outcomes of their diagnosis for other family members and themselves

(health concern).

When comparing mean scores of participants recruited pre-COVID-19 (N=22) to participants recruited during-COVID-19 (N=28), there was no significant difference (p>.05) between groups. However, mean scores were lower during-COVID-19 than pre-COVID-19 suggesting that adults with CeD were less anxious during the pandemic. The same thing can be said about clinical depression symptoms, no significant difference was seen between groups

(p>.05), yet mean scores were lower during-COVID-19 than pre-COVID-19 indicating less clinical depression during the pandemic.

In a recent study looking at mental health impact of the COVID-19 pandemic on people with and without depressive or anxiety disorders in a Dutch case control cohort showed that people with the disorders both before and during the COVID-19 pandemic did not report greater increase in anxiety and depression symptoms during the pandemic. However, individuals that did not have anxiety and depression symptoms pre-COVID-19 showed an increase in symptoms during the pandemic (Pan et al., 2020). 155

5.5 Personality Characteristics and CD-FAB

This study is unique in that it’s the first to look at personality characteristics of adults with CeD and the association with disordered eating attitudes and behaviors. A recent study conducted a cross-sectional mixed methods study with 30 adolescents with CeD and found that half of the study sample (53.3%) expressed more rigidity (vs. flexibility), avoidance (vs. trust), controlling behavior (vs. confidence), and food preoccupation (vs. awareness) to maintaining a

GFD and those who did so were older and had lower QoL scores (Cadenhead et al., 2019). These findings highlighted the importance of understanding the extent of DE in those with CeD and the need to identify those at risk in order to promote a GFD without undermining QoL.

Satherley et al. showed that there is a higher risk of developing DE in individuals with GI disorders compared to the general population and even though there was evidence for different

DEP, food restriction was most frequent (R. Satherley et al., 2015). One way to explain the latter is that individuals with GI disorders may be more likely to resemble the personality of someone with a restrictive eating disturbance (R. Satherley et al., 2015) Wagner et al. explained that personality dimensions have been explored in patients diagnosed with EDs. In all EDs, elevated harm avoidance, reduced self-directedness and cooperativeness are recognized personality factors, which was also found in adolescents with CeD (Wagner et al., 2015)

According to the personality test conducted in this study (BFI), adults with CeD showing higher disordered attitudes and behaviors, were more prone to having irrational ideas, less able to control impulses and cope poorly with stress (high neuroticism), they were also more conventional in behavior and conservative in outlook and felt more comfortable around things that are familiar vs. novel (high openness). They were also more reserved, independent and even-

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paced (low extroversion) and showed less awareness with higher flexibility and spontaneity (low consciousness). These findings seem to be aligned with other studies’ results.

A recent study assessed personality characteristics in patients who had mood disorders and obsessive-compulsive disorders (OCD) and showed high neuroticism in patients with generalized anxiety and major depressive disorder and high neuroticism and low extroversion in patients with dysthymia (Bienvenu et al., 2004). Another study conducted in

Sweden on patient adherence to treatment in chronic disease showed a negative relationship between neuroticism and adherence (p<.001) and a positive relationship between conscientiousness and adherence (p<.001) (Axelsson, Brink, Lundgren, & Lötvall, 2011).

Marcia et al. found that increased neuroticism leads to decreased QoL scores and high extraversion was associated with increased QoL (Macía, Gorbeña, Gómez, Barranco, & Iraurgi,

2020) .

5.6 Limitations

This study has limitations that need to be considered. First, this study was conducted at

Columbia University Irving Medical Center, eligibility was limited to patients of the Celiac

Referral Center with biopsy-diagnosed CeD. Overall, 90% of participants identified as non-

Hipanic White, 84% had one college degree or more. When looking at household income, 62% of adults recruited in this study had an income higher than $100,000. These demographics are not uncommon from other studies that have been conducted at this referral Celiac Disease center.

However, the sample may not be generalizable to those with CeD not seeking medical care at another Celiac Referral Center.

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About half the participants (48%) were currently seeing an RDN, which can be explained by the fact that some of these patients were recruited while they were waiting for their dietitian’s appointments.

The study only recruited adults between the ages of 18 to 45 years, adolescents and older adults with CeD were not included in this study. The study limited participants to those with biopsy-diagnosed CeD, which excluded those with gluten intolerance or sensitivity. Finally, participants with a previous diagnosis of an ED were also excluded from the study.

It is important to note that all surveys tool results were self-reported. Participants filled out EDDS and EPSI survey tools on their own, questions were not followed by clinical interviews. EDDS syntax scoring was not physician friendly at all and suggestive diagnosis made from EDDS syntax were not followed by clinical interviews. Clinicians were not available to clarify how participants were interpreting questions, so interpretation of questions can be a major limitation. In addition, EDDS composite scores were validated in females and not in males, yet studies have shown that females have higher prevalence of traditional eating pathologies than males. The 22-item questionnaire measuring AN, BN and BED is based on the DSM-IV version not the latest DSM-V (Krabbenborg et al., 2012).

Dietary adherence was also self-reported, reporting is not always accurate leading to possible inaccurate reporting of level of adherence whether its intentional or not (D. Leffler et al., 2007).

The CD-FAB is a recently developed tool measuring disordered eating attitudes and behaviors of CeD. Dr. Satherley explained that the instrument may be used as an outcome measure in clinical research, enabling a greater understanding of CD-related eating patterns that are not currently captured by current tools. However, there is a need to establish clinical cut-off 158

points. In addition, the tool showed good reliability and validity on a UK population, and has not been previously used on a US population.

This study had a small sample size (N=50), the number was chosen based on the fact that the CD-FAB tool was being used for the first time since it was developped. The study was intended to be exploratory and provide pilot data for a larger trial. Ideally, we hoped to recruit 50 consecutive and eligible patients that attended their phsyician appointment at the celiac center to best estimate how common ED and DE are in the sample. We needed to approach 62 consecutive patients in order to achieve our recruitment goal of 50 (81%).

Finally, the burden of the COVID-19 pandemic followed by the unusual living and environmental circumstances of participants may have affected some of these results, as nearly half of the participants (56%), were recruited during the COVID-19 pandemic.

5.7 Strengths

This cross-sectional pilot study was conducted at the Celiac Disease Center at Columbia

University Irving Medical Center in New York City (CUIMC). The Celiac Disease Center, founded in 2001 by Dr. Peter Green, M.D., is a leading center in the field both nationally and internationally. This allowed the opportunity to confirm biopsy diagnosis of CeD in all participants with medical records.

Survey tools administered to participants were carefully chosen to assess as many factors as possible and characteristics that may predict CD-FAB scores by respecting a reasonable duration of completion for participants while waiting for their physician and dietitian’s appointments and allowed for virtually no missing data. This pilot study was able to detect which characteristics and/or factors are worthy of being explored further in future studies. 159

Finally, this is one of the first studies administering the Celiac Disease Food Attitudes and behaviors scale (CD-FAB) in the United States. The tool is relatively new and has not been explored independent of studies related to its validity and reliability.

5.8 Implications and applications

Since high CD-FAB scores were linked to low number of years since diagnosis, clinicians may want to consider prioritizing the CD-FAB in patients less than seven years post- diagnosis to assess disordered eating attitudes and behaviors. It will be important to understand the nature of this challenging period of time and the extent to which GI symptoms, elevated anitbody levels, etc. may be contributing to the high CD-FAB scores. Future research with larger samples would help identify a cut-off that clinicians can use to screen for disordered eating attitudes and behaviors. When administering the tool in a clinical setting, the cut-off will help clinicians determine if a referral to a behavioral health provider such as a psychologist

(preferably a specialist in GI disorders) will be needed. When CD-FAB scores are high, the tool should also be followed by another measure to screen for Eating Disorders under the DSM-V such as the EDDS. This will also need to be followed by a clinical interview for confirmation of the suggested diagnosis.

The observed disordered eating attitudes and behaviors (as per the CD-FAB) may be classified under ARFID, based on the revised diagnosis in DSM-5. However, until there are screening tools available for ARFID and studies that look at the relationship between CD-FAB and ARFID, it is still premature to say that clinicians should use the CD-FAB to predict who is at risk for ARFID.

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5.9 Future research

This is an exploratory study, with a small sample size. Long-term, the goal is to create a larger cohort study with a bigger and nationally representative sample size. A larger sample size may help in assessing a cut-off score for the CD-FAB tool as well as increase statistical power in the data analysis.

However, some changes may have to be applied to the methods. First, in order to assess

DE, another tool should be used as the EPSI tool did not seem to reflect disordered eating pathologies of adults with CeD.

Second, teenagers should be included in the study (ages 14 to 17 years)’s inclusion criteria. In a recent study of adolescents with CeD (13-17 years old) following a GFD for at least one year recruited from an urban CeD referral center, it was found that approximately half the sample (53.3%) expressed more maladaptive approaches to maintaining a GFD and those who did so, were older with lower CeD-specific pediatric QoL scores (Cadenhead et al., 2019).

Based on this study findings, future research should assess reasons for non-compliance with the necessary GFD of high CD-FAB scores. More research is needed to determine the time order of CD-FAB scores and QoL status.

Fourth, this study should be replicated once the pandemic comes to an end, as COVID-19 had an impact on the results found in this study.

Fifth, a qualitative study could be helpful to better understand in depth the participants rationale behind the disordered attitudes and behaviors and the extent to which they may be driven by ongoing symptoms, worry about elevated antibody levels, or other concerns.

Finally, clinicians in gastroenterology clinics need guidance on how to screen for ARFID.

There are no current tests to screen for ARFID, future research ought to be conducted in order to 161

come up with a valid and reliable tool that can be used by clinicians to screen for ARFID. In addition, it would be important to distinguish different subgroups of ARFID as those with disordered eating attitudes and behaviors as a result of CeD may be very different than other

ARFID subgroups.

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Conclusion

In this study, suggestive ED (based on EDDS) and DE (based on EPSI) were present, but low (2% suggestive diagnosis of BED, 12% suggestive diagnosis of OSFED as per DSM-V).

The distribution of the self-reported food attitudes and behaviors measures (CD-FAB scores) were spread out around the mean 36.96 (15.30) with a maximum score of 66 out of a possible 77.

The CD-FAB may have utility in identifying adults with CeD that may be at risk for disordered eating attitudes and behaviors, particularly those in the first few years after diagnosis. It likely has limited utility in identifying suggestive EDs (as per EDDS) and DE (as per EPSI). The main factors that were associated with higher CD-FAB scores were BMI, number of symptoms, years since diagnosis, diet adherence and personality characteristics. Seven years after diagnosis seems to be an important cut-point in how participants rated food attitudes, fear responses and adaptive responses on the CDFAB scales. Higher CD-FAB scores had a significant and meaningful association with QoL scores. Participants recruited during the COVID-19 pandemic had significantly lower CD-FAB scores and higher QoL scores compared to those recruited pre- pandemic; despite not having significant differences in any other demographic characteristics.

This exploratory study suggested that that participants who scored higher (in this sample the higher tertile was greater than 44) on the CD-FAB may be at higher risk for low QoL.

Clinicians may want to consider priopritizing the CD-FAB in patients less than seven years post- diagnosis to assess disorderd eating attitudes and behaviors.

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Appendix A: Introduction Script

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Appendix B: Verbal Consent Script & Eligibility Checklist

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Appendix C: Consent form

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Appendix D: Demographic & Health Characteristics

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Appendix E: Diet Adherence

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Appendix F: EDDS/DSM-5 Version

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Appendix G: Symptoms Inventory (EPSI)

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Appendix H: Food Avoidance

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Appendix I: IPAQ

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Appendix J: STAI Adults

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Appendix K: CD-FAB Adults

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Appendix L: The Big 5 Inventory Test

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Appendix M: CDSD

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Appendix N: CESD-R

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Appendix O: CD-QoL

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Appendix P: 24-hour Recall Script

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Appendix Q- EDDS composite scores and Diagnosis

ID EDDS composite scores EDDS DXa

1 0 0

2 0 0

3 0 999

4 5 0

5 0 0

6 0 0

7 0 0

8 2 5

9 0 0

10 0 0

11 0 0

12 2 8

13 32 8

14 0 0

15 5 0

16 0 0

17 0 0

18 0 0

19 10 0

20 0 0

21 0 3

22 0 0

23 0 0

207

24 0 0

25 0 0

26 0 0

27 0 0

28 0 0

29 0 0

30 0 0

31 0 0

32 0 0

33 0 0

34 0 0

35 1 0

36 1 0

37 2 0

38 0 8

39 0 0

40 0 0

41 0 0

42 0 0

43 2 0

44 10 0

45 0 0

46 0 0

47 0 0

48 0 0

208

49 0 0

50 10 999

a 1=AN, 2=BN, 3=BED, 4=Atypical AN, 5=low frequency BN, 6=low frequency BED, 7=purging disorder, 8=night eating syndrome, 999= not determined

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Appendix R- Regression CD-FAB and Factors w/COVID-19

Predictors B Std. Error t p-value

Model 1-Food Attitudes (constant) -4.63 15.57 -.30 .768 Gender -.37 2.28 -.16 .872 Age -.07 .13 -.53 .598 Years since diagnosis -.56 .19 -3.04 .004** BFI: Extroversion -.18 .20 -.95 .346 BFI: Agreeableness .34 .21 1.63 .112 BFI: Conscientiousness .01 .27 .03 .978 BFI: Neuroticism .20 .17 1.15 .257 BFI: Openness .27 .17 1.54 .132 CDSD -.14 .95 -.15 .880 CDAT .73 .41 1.79 .082 BMI -.23 .29 -.77 .444 2 R .479 F-statistic 3.18** Model 2- Fear Response (constant) 10.60 9.92 1.07 .292 Gender .06 1.4 .04 .968 Age -.04 .084 -.49 .625 Years since diagnosis -.27 .12 -2.32 .026* BFI: Extroversion -.11 .12 -.94 .351 BFI: Agreeableness .03 .14 .22 .826 BFI: Conscientiousness -.03 .17 -.17 .864 BFI: Neuroticism -.04 .11 -.40 .695 BFI: Openness .11 .11 .98 .334 CDSD .94 .61 1.6 .127 CDAT .17 .26 .64 .527 BMI -.12 .19 -.62 .538 2 R .315 F-statistic 1.59 Model 3- Adaptive Response (constant) 12.09 14.16 .85 .399 Gender -.79 2.07 -.38 .706 Age .10 .12 .82 .419 Years since diagnosis -.26 .17 -1.55 .130 BFI: Extroversion -.08 .17 -.44 .661 BFI: Agreeableness -.06 .19 -.30 .769 BFI: Conscientiousness -.14 .24 -.56 .577 BFI: Neuroticism .19 .16 1.21 .234 BFI: Openness .19 .16 1.19 .241 CDSD .89 .86 1.03 .311 CDAT -.01 .37 -.04 .971 BMI -.09 .27 -.34 .733 2 R .337 F-statistic 1.76 Model 3- CD-FAB Total (constant) 18.05 33.50 .54 .593 Gender -1.10 4.90 -.22 .824 Age -.01 .29 -.05 .962 Years since diagnosis -1.09 .40 -2.75 .009** BFI: Extroversion -.37 .41 -.91 .369 BFI: Agreeableness .32 .46 .70 .490 BFI: Conscientiousness -.16 .57 -.28 .784 BFI: Neuroticism .35 .37 .93 .359 BFI: Openness .56 .37 1.51 .140 CDSD 1.69 2.04 .83 .414 CDAT .89 .88 1.01 .321 BMI -.43 .63 -.69 .495 2 R .438 F-statistic 2.70*

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Appendix S- Comparing EPSI means of suggestive ED diagnosed (as

per EDDS) with high CD-FAB scorers

The table below shows the EPSI mean scores for the whole sample, the EPSI mean scores of all subscales for participants who had suggestive OSFED as per the EDDS (N=6), as well as mean scores of EPSI subscales for those who scored high (44 to 66) on the CD-FAB as per the tertiary split (N=17). There was a significant difference between mean scores of participants with suggestive OSFED as per the EDDS and high CD-FAB scorers for body dissatisfaction

(t(21)=2.86, p=.009) and binge eating (t(21)=2.44, p=.024). Independent t-tests showed no other significant differences between means.

Table S- EPSI means of suggestive OSFED diagnosed, high CD-FAB scorers and total CD-FAB means for this study.

Suggestive diagnosis CD-FAB OSFED High CD- scores EDDS FAB scorers t-test a Mean (SD) Mean (SD) Mean (SD) (N=50) (N=6) (N=17) t df p Body Dissatisfaction 9.84 (7.79) 20.33 (6.31) 10.82 (7.21) 2.86 21 .009** Binge Eating 8.12 (6.54) 15.67 (5.57) 7.76 (7.19) 2.44 21 .024* Cognitive Restraint 4.54 (2.74) 6.83 (2.48) 4.41 (2.74) 1.90 21 .071 Purging .24 (.82) .50 (1.22) .18 (.73) .77 21 .448 Restricting 4.86 (5.36) 7.67 (6.92) 6.82 (5.79) .29 21 .771 Excessive exercising 5.57 (4.96) 7.83 (4.62) 4.82 (4.52) 1.40 21 .178 Negative Obesity 3.58 (4.88) 7.17 (7.41) 2.06 (4.35) 2.05 21 .053 Muscle Building 2.16 (2.83) 4.17 (4.31) 2.59 (3.24) .94 21 .356 *p<.05 **p<.01 ***p<.001 a Independent t-test between participants diagnosed with possible OSFED (as per the EDDS) and high CD-FAB scorers (as per the tertiary split)

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