Sick leave and disability pensioning. Demographic, social, and genetic risk factors

Some people have a higher risk of long-term sickness absence and work disability than others. This study examined why. The data set contained information on almost 30 000 Norwegian twins (including more than 10 000 couples) born between 1926 and 1991, which were linked with data from public registers. The purpose of the study was to investigate how important genes are in relation to the environment, both to be able to explain differences between individuals and to explain why sickness absence and disability benefits are associated with certain features. Furthermore, we wanted to use the possibilities inherent in a twin design to investigate which specific demographic and health factors have a possible causal relationship with sickness absence and disability benefits. The results from the study show that the degree of genetic impact on absence from work (both sickness absence and disability) appears to be relatively stable throughout working life, from 18-66 years, where genes could explain between 33 and 45% of individual variation. Furthermore, we found that it is apparently the same genetic factors that explained absence from work across age groups, despite large differences in the degree of absence and probable underlying medical causes. Environmental impacts, on the other hand, were mainly age-specific, and it was individual environmental factors that explained the variation and not environmental factors that were familial (common to the twins). With regard to specific risk factors, we found that previous musculoskeletal problems, but not previous symptoms of mental distress, increased the risk of sickness absence during pregnancy. We have also investigated the significance of educational attainment and health behavior for sickness absence. These results are currently being evaluated in a peer-reviewed journal.

Resultatene fra prosjektet forventes først og fremst til å bidra til utvikling av forståelsen for årsaker til sykefravær og for å fremme nye hypoteser i dette forskningsfeltet. Spesielt viser resultatene fra denne studien at genetiske faktorer spiller en vesentlig rolle i årsaksmekanismene som leder til sykefravær. Vi tror dette er viktig blant annet for å begrense sosiale stigma rundt sykefravær og uføretrygd, og til mer målrettede tiltak.

This study aims at identifying causes of individual variation in sick leave (SL) and disability pensioning (DP) by following over time a population based sample of 10,000 twin pairs from the Norwegian Twin Panel, linking registry and questionnaire data to the twin material. We will identify predictors of SL and DP from registry data on education, income, age, birth cohort, sex, occupation, and life events, and from questionnaire data on somatic and mental health and life style. This will be done with trad itional epidemiological methods and with a co-twin control design, which allows controlling the effects of life-events for unmeasured genetic factors and social background. Further, we will investigate the relative importance of genetic, shared and unique environmental contributions to SL/DP, overall and due to specific groups of diagnoses. This may tell us why SL/DP is especially common in some groups, and why it has increased. Societal variation will be explored by comparing Nordic countries. Finally, w e will investigate genetic and environmental covariance between SL/DP and other characteristics, for example various diagnoses and forms of workforce absence, and whether the same factors influence SL at different times in life. The current study stands o ut from most previously conducted studies by its ability to investigate effects of specific environmental variables within a genetically informed data material. We are able to identify genetic effects, in addition to effects of environment shared by the t wins (family environment), the effects of environmental factors unique to the individual, and covariance between forms of absenteeism. By using genetic epidemiological designs this study will elucidate important mechanisms of causality between e.g. social inequality and absenteeism. Better understanding the causal mechanisms behind SL and DP may help finding modifiable factors and help individuals to cope with job demands, resulting in reduced work force absence.