Do academic ability and social background influence each other in shaping educational attainment? The case of the transition to secondary education in Germany

Genetic and environmental contributions to the subjective burden of social isolation during the COVID-19 pandemic

BACKGROUND

Feelings of loneliness and the burden of social isolation were among the most striking consequences of widespread containment measures, such as "social distancing", during the COVID-19 pandemic. Because of the potential impact on people's health, there has been increased interest in understanding the mechanisms and factors that contributed to feelings of loneliness and the burdens of social isolation. However, in this context, genetic predisposition has been largely ignored as an important factor. This is problematic because some of the phenotypic associations observed to date may in fact be genetic. The aim of this study is, therefore, to examine the genetic and environmental contributions to the burden of social isolation at two time points during the pandemic. In addition, we examine whether risk factors identified in previous studies explain genetic or environmental contributions to the burden of social isolation.

METHODS

The present study is based on a genetically sensitive design using data from the TwinLife panel study, which surveyed a large sample of adolescent and young adult twins during the first (N = 798) and the second (N = 2520) lockdown in Germany.

RESULTS

We find no substantive differences in genetic and environmental contributions to social isolation burden over the course of the pandemic. However, we find the determinants highlighted as important in previous studies can explain only a small proportion of the observed variance in the burden of social isolation and mainly explained genetic contributions.

CONCLUSIONS

While some of the observed associations appear to be genetic, our findings underscore the need for further research, as the causes of individual differences in burden of social isolation remain unclear.

The aetiology of educational attainment: A nuclear twin family study into the genetic and environmental influences on school leaving certificates

BACKGROUND

Educational attainment is connected to many important life outcomes, and the previous research has already focused on identifying its genetic and environmental components. However, most of these studies used twin data only and did not incorporate information from other family members. Twin studies typically decompose the phenotypic variance into genetic, shared, and unique environment components. In this study design, the shared environment component encompasses the influence of parents and the shared environments of twins and siblings independent of parents (e.g., teachers, schools, and peers). The classical twin design (CTD) conflates these influences as part of the shared environment. This shortcoming can be overcome using the nuclear twin family design (NTFD), which enables separation of the parental and shared twin/sibling environmental components.

AIMS

The aim of this study was to broaden the understanding of the aetiology of educational attainment using the nuclear twin family design to provide a detailed account of the genetic and environmental effects on the type of school leaving certificate.

SAMPLE

The data of 1,048 monozygotic and 916 dizygotic same-sex twins, their biological parents, and non-twin full biological siblings of the German project TwinLife were used in the nuclear twin family design.

METHODS

Structural equation modelling (SEM) techniques were used to analyse the variance-covariance patterns of the ordinal outcome variable.

RESULTS

Genetic influences were found to make up around 60% of variance, whilst environmental influences shared by all siblings, educational influences shared by the twins only, and non-shared environmental influences explained the remaining variance in equal amounts. Environmental transmission from parent to offspring was found to be negligible.

CONCLUSION

Through its advanced design, our study extends the previous work enabling more detailed and robust estimations of sources of variance and contributes to a better understanding of the complex aetiology of educational attainment.