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Home , Inbreeding

The effect of inbreeding on longevity, and disability

Background Children of consanguineous relationships are likely to have an increased level of homo-zygotic which cause a greater risk for the manifestation of recessive genetic disorders. In the study area chosen here, Skellefteå in Sweden, the level of consanguineous where relatively high. We can also trace the family history back several hundred years making it possible to create pedigrees for the and to calculate the level of inbreeding. This makes the studied area suitable for investigating the effect of inbreeding. Many genetic disease, both autosomal recessive and autosomal dominant, have a rather high frequency in Skellefteå. Earlier studies have shown an effect of inbreeding on fertility and lifespan. An example of this is Helgason et al., 2008 who showed that for the Icelandic population there was an effect on fertility and lifespan of an individual from the level of inbreeding. This study complement such studies by analyzing the effect of inbreeding on fertility and longevity in a Swedish setting and by adding the outcome variable disability which has not been considered in a historical context before. Bittles, A. and I. Egerbladh (2005) discuss the potential effect of inbreeding on genetic disorders in the Skellefteå region but do not explicitly link inbreeding and disabilities using data as we attempt in this study. The aim of the paper is thus to investigate if inbreeding had any effects on individuals living in Skellefteå during the 19th century. In particular the effect on longevity, fertility and disabilities will be investigated.

Method The degree of inbreeding is measured by the inbreeding coefficient which is a measure that increases the more inbred an individual is and is denoted as F (Ballou, 1983). To exemplify, Full siblings get an F of 1/4, First 1/16, Second Cousins 1/64 and Third Cousins 1/256. F is then related, as an explanatory variable, to outcomes indicating longevity, fertility and presence of disabilities. Longevity is measured as life-length (number of lived days) and the modeling approach will be Cox regression. Fertility will be measured by number of children a person has and the modeling approach will be based on Poisson regression and related methods. The effect on disability will be analyzed both by using the presence of disability as the outcome and by analyzing different disability groups separately. Here the modeling approach will be logistic regression.

Data The data sources consist of parish registers stored at the Demographic Data Base (DDB) at Umeå University and these registers provide digitized and linked parish records comprised by original registers for parishioners’ birth, baptism, , out- or in-migration, death, burial and the catechetical examination records. The registers are extracted and digitized from chosen parishes in Sweden during the seventeenth and nineteenth centuries and are linked on individual level, which give us extensive demographic information about each parishioners life. (Vikström et.al., 2006) The catechetical examination registers are the major source for identifying disabilities and for following individuals over a lifetime to note fertility and longevity. These registers were collected on yearly basis due to the obligation for the ministers to keep records of the parishioners’ knowledge of the catechism and their reading ability, first stated in the Church law of 1686. (Nilsdotter, 2014) In these records the ministers also made other notes, such as marks of impairments (lytesmarkeringar), which document disabilities among the parishioners. These notes report limits in peoples’ physical and mental function. The ministers’ marks of impairments are used to identify the disabled individuals and to separate them from the non-disabled cases. (Haage, 2012) The data extracted consists of observations of individuals which at some point in their lives lived in Skellefteå during the time the church records were kept. Table 1 contains the number of people and their inbreeding coefficient and Figure 1 histograms over observed inbreeding coefficients. The variables available are the date of birth, the individuals id, the individuals parents ids, what kind of entry into/exit from the church records, which date the entry is made and which sex each individual is. From these variables the following variables can be identified or calculated: day of birth, age of death, number of children, individual inbreeding coefficient (IIC), and mean inbreeding coefficient of children (MICC). Table 1: Number and proportion of individuals in data depending on their inbreeding coefficient.

Figure 1: Distribution of inbreeding coefficients for individuals.

Results

1.Longevity Figure 2 shows the Kaplan-Meier curves for the genders and different inbreeding groups. It shows a higher mortality for men and for the more inbreed groups. The Cox regression model presented in Table 2 confirms this with a significant effect on the lifespan from the level of inbreeding an individual has. An individual whose parents are second cousins or more closely related has a higher risk of dying than individuals with no inbreeding. The estimated β coefficients for the two levels were 0.1640 and 0.2573 for second cousins and first cousins respectively. By taking the exponent of these coefficients we get estimates of the probability of dying relative to the base level of not being inbred. Doing this shows that the probability of dying for second cousins compared to individuals with no inbreeding is 1.1782 times higher given that they are of the same sex. In the same way for first cousins the probability of dying is 1.2934 times higher. Helgason et al. 2008 showed that for the Icelandic population the life expectancy of children of couples who were related as second cousins or closer was shorter than for couples with less inbreeding. Since both their study and this study of the population of Skellefteå during the 19th century one could argue that these results a good indication of how inbreeding affects the lifespan of individuals. The risk of dying also lower for women compared to men as expected where the estimated β coefficient was -0.1128.

Figure 2. Kaplan-Meier plot for categorical covariates. Table 2. Results of Cox regression

2. Fertility Using Poisson regression, no effect of inbreeding on the fertility of the women were found. The results of the regression is not shown, instead the descriptives in Figure 3 are shown which might indicate a slightly higher fertility, though not significant, in consanguineous relationships where the inbreeding is low but above zero. This indicates that inbreeding did not have a major affect on fertility in Skellefteå during the 19th century which is unlike the results of Helgason et al. 2008 on the Icelandic population which showed that the mean number of children increase in consanguineous relationships. Figure 3. Fertility and level of inbreeding

3. Disabilities This part is yet to be finalized but we suspect that we might see an increasing propensity for disability with increasing inbreeding coefficient. Logistic regression will here be used for the analysis.

References Ballou, J. (1983). Calculating inbreeding coeicients from pedigrees. and conservation: a reference for managing wild and plant , 509-520.

Bittles, A. and I. Egerbladh (2005). The inluence of past and on genetic disorders in northern sweden. Annals of 69(5), 549-558.

Pär Vikström, Anders Brändström and Sören Edvinsson, “Longitudinal Databases: Sources for Analyzing the Life-Course,” History and Computing, 14 (2006): 109–128. Haage, Helena. (2012) “Identifying Disability using Nineteenth Century Parish Registers.” (Unpublished paper Umeå University2012).

Helgason, A., S. Pálsson, D. F. Guðbjartsson, K. Stefánsson, et al. (2008). An association between the kinship and fertility of human couples. Science 319 (5864), 813#816.

Nilsdotter Jeub, Ulla (2009) Parish Records, Digitalised Material from Demographic Data Base. (Umeå: Umeå University 2009), accessed November 24, 2014, http://www.ddb.umu.se/digitalAssets/37/37716_parishrecords.pdf.