Genetic influences were strongest in education and weakest in income, and always strongest among those with the most advantaged socioeconomic background, independent of the socioeconomic indicator used

Socioeconomic Background and Gene–Environment Interplay in Social Stratification across the Early Life Course. Jani Erola, Hannu Lehti, Tina Baier, Aleksi Karhula. European Sociological Review, jcab026, August 4 2021. https://doi.org/10.1093/esr/jcab026

Abstract: To what extent are differences in education, occupational standing, and income attributable to genes, and do genetic influences differ by parents’ socioeconomic standing? When in a children’s life course does parents’ socioeconomic standing matter for genetic influences, and for which of the outcomes, fixed at the different stages of the attainment process, do they matter most? We studied these research questions using Finnish register-based data on 6,529 pairs of twins born between 1975 and 1986. We applied genetically sensitive variance decompositions and took gene–environment interactions into account. Since zygosity was unknown, we compared same-sex and opposite-sex twins to estimate the proportion of genetic variation. Genetic influences were strongest in education and weakest in income, and always strongest among those with the most advantaged socioeconomic background, independent of the socioeconomic indicator used. We found that the shared environment influences were negligible for all outcomes. Parental social background measured early during childhood was associated with weaker interactions with genetic influences. Genetic influences on children’s occupation were largely mediated through their education, whereas for genetic influences on income, mediation through education and occupational standing made little difference. Interestingly, we found that non-shared environment influences were greater among the advantaged families and that this pattern was consistent across outcomes. Stratification scholars should therefore emphasize the importance of the non-shared environment as one of the drivers of the intergenerational transmission of social inequalities.

Discussion and Conclusions

In this article, we have presented our findings on the gene–environment interplay over the early life course in education, occupational standing, and income. In summary, our study highlights five findings. First, our baseline findings for education, occupational status, and income show that the relative importance of shared environmental influences was negligible. This challenges previous findings on the substantial influence of the shared environment on education (Branigan, McCallum and Freese, 2013). The results differ from those of earlier studies in Finland studying older cohorts but are similar to those in Norway involving more recent cohorts with similar institutional settings (Silventoinen et al., 2004; Nisén et al., 2013; Ørstavik et al., 2014; Lyngstad, Ystrøm and Zambrana, 2017). For income, the result is in line with a previous Finnish study (Hyytinen et al., 2019). There have been no previous studies on genetic influences in ISEI in Finland, and, to our knowledge, very few elsewhere.

Second, we find that genetic influences are strongest among the most advantaged families. This partly confirms our first hypothesis: There is no linear relationship between the strength of genetic influences and the quality of the family environment, and the differences between the other groups of families are small. Thus, the enhancement mechanism seems to work principally at the top end of the social spectrum. A similar pattern has been found in previous studies studying the social stratification of genetic influences using twin data (Baier and Lang, 2019).

Third, the social stratification of genetic influences is to some extent depending on the age at which parental SES is observed. In contrast to our expectations, parental social background measured early during childhood led to weaker interactions with genetic influences. This finding is an important addition to previous research on the role of socioeconomic rearing environment at different stages of the early life course. It suggests that the average contribution SES would be more or less constant across childhood and youth (Erola, Jalonen and Lehti, 2016). If gene-environment interactions were not taken into account, we would miss the life-course-specific pattern. It may be that parents have not reached their final level of socioeconomic attainment during children’s early childhood, and once parents have achieved that, their status reflects more accurately their genetic potential. If this is the case, the differences we observe in the association between family background and genetic influences according to children’s age can follow from gene–environment correlation related to parent’s socioeconomic attainment. For future research, the results suggest that in order to fully account for stratification according to parental educational and socioeconomic characteristics in genetic influences, one should prefer indicators of parental SES that are observed later than during early childhood.

Fourth, in line with our third hypothesis, we found that the contribution of socioeconomic parental characteristics to genetic influences is stronger the earlier the maturity of an outcome is reached. More specifically, parental characteristics matter mostly for the genetic influences in education, and for occupational standing mostly because it is mediated by their children’s education. Notably, in the case of income, stratification by parental characteristics was weak even before their children’s own education was considered. This is striking: It suggests that nearly all of the factors behind parents’ success or failure in terms of their observed socioeconomic outcomes cannot on average explain that much of how their children succeed economically by age 32–36.

Finally, the results showed the stronger importance of the non-shared environment among the children of parents of high SES. This result was consistent across the three outcomes as well as the indicators of parental SES, and aligned with previous studies showing that socioeconomic outcomes within families differ more strongly among advantaged children (Goldstein and Warren, 2000; Heflin and Pattillo, 2006). A possible explanation can be borrowed from research on stratified parenting (Lareau, 2011; Kalil, Ryan and Corey, 2012) showing that parents of higher social status make more child-specific investments based on their children’s individual talents or particular weaknesses that can accentuate differences among their children (Baier, 2019). However, similar findings could also result from the multiplicative processes if advantaged parents or the children themselves prefer differential treatment. For example, the same innate talent in math could lead to different educational and career pathways and could encourage careers in either business or academia.

Our results also contribute to the broader discussion on equality of opportunity. As comparative research has shown that social background matters relatively little in Finland, this could lead one to expect that the genetic influences in attainment should also be particularly strong. To some extent, the results are in line with this: The shared environment alone matters very little compared to the results on older birth cohorts in Finland (Silventoinen et al., 2004; Branigan, McCallum and Freese, 2013; Nisén et al., 2013). However, there is an addition: the comparison of outcomes shows that a negligible impact of shared environmental influences does not mean that only the impact of genes would automatically become stronger; it can also change the differences due to the non-shared environment. To date, the role of non-shared environmental influences has barely been discussed in the literature on genetic influences in socioeconomic attainment (as a notable exception, see Beam and Turkheimer, 2013). These channels nonetheless appear to be relevant for intergenerational socioeconomic transmission processes.

A caveat regarding the data is that we could not follow income as long as would have been preferable (until over age 40); we only covered log mean income from at age 32–36. It may be that the stronger role of genes in the incomes of the highly educated parents we observe now reflects their children’s improved chances to fulfil their own genetic potential, rather than the parents’ investments for their children. If this is the case, the genetic influences on income would become even stronger later. Furthermore, the immediate family context is not the only environment that we are exposed to during childhood and youth. Extended families, schools, or neighbourhoods could have also contributed to the gene–environment interplay. Also a detailed analysis of gender differences was beyond the scope of our study.

Moreover, it may be that our method of estimating genetic influences by comparing same and different sex twins led to a bias in the results; for instance, previous twin studies on education in Finland have found a substantive effect of shared influences that we did not observe. Testing our hypotheses with increasingly available molecular genomic data could shed light on the mechanisms involved; for instance, in the context of the third hypothesis on mediation, direct measures for genetic influences relevant for education, occupation, and income would allow us to test directly to what extent the same genetic influences contribute to each outcome.

In sum, the results underline the value of studying the gene–environment interplay for a better understanding of intergenerational socioeconomic inequalities. Clearly, genetic inheritance plays a key role in this and should be more strongly integrated into stratification research. Importantly, the results show that our theoretical assumptions about the relationship between social inequalities, genes, and shared and non-shared environments are still relatively underdeveloped, especially regarding the importance and role of the non-shared environment. In the future, one of the key tasks of research on intergenerational social mobility and attainment should be the development of better theories on the relationship between gene–environment interplay and its implications for equality of opportunity. The latter goal calls for comparisons of results by applying similar research designs across multiple nations.