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.