How much do your genes and upbringing determine your success? A landmark Norwegian study untangles the complex interplay between genetics, family, and social policies in shaping who thrives.
Study: The genetic and environmental composition of socioeconomic status in Norway. Image Credit: WinWin artlab / Shutterstock
In a recent article published in the journal Nature Communications, researchers examined the environmental and genetic contributions to four key indicators of socioeconomic status (SES) in Norway, namely wealth, income, occupational prestige, and educational attainment. Their findings indicate that genetic variation consistently explained more of the differences in educational attainment and occupational prestige, with education generally showing the highest genetic influence.
Family-shared environmental factors, on the other hand, contributed more to variations in educational attainment and wealth. The study notes that its estimates might be most applicable to a middle-class to upper-middle-class Norwegian population due to sample characteristics. The authors also note that their findings may not be generalizable to more socioeconomically diverse or non-European populations.
Background
SES is closely linked to important life outcomes, including subjective well-being, mortality, and health. Therefore, understanding the genetic and environmental underpinnings of SES is a major research focus. However, SES is a broad and inconsistently measured construct, with one review identifying 149 unique indicators.
Researchers typically focus on a common core of four key SES indicators: wealth, income, occupational prestige, and educational attainment. Despite their frequent use, systematic comparisons of their genetic and environmental foundations remain limited. Heritability, defined as the percentage of trait variation due to genetic factors, can be estimated using family- or genotype-based methods.
However, these methods often produce diverging estimates, with family-based studies generally showing higher heritability. Variability across populations, age groups, and measurement methods further complicates these differences. Many studies also rely on self-reported SES data, which can introduce significant biases. There is also a notable gap in studies focusing on wealth, despite its centrality and unequal distribution, even in egalitarian societies.
About the study
This study used registry-based, objective data from a homogeneous Norwegian sample. It utilized multiple heritability methods within a single population to ensure consistency and reduce error, aiming to disentangle and compare the role of environmental and genetic factors in SES indicators.
Data from over 170,000 Norwegian adults between 35 and 45 was drawn from national population registers. The researchers selected this age range to capture stable SES information while ensuring consistency across indicators.
The study minimized measurement error and biases associated with self-reported data by using administrative records for wealth, occupational prestige, income, and educational attainment. For income, wealth, and occupational prestige, indicators were averaged over an 11-year period (from ages 35 to 45), while educational attainment was the highest recorded within this timeframe, allowing for reliable and objective estimates.
To examine the environmental and genetic components of SES, the study applied four heritability estimation methods: two family-based and two genotype-based methods. To ensure comparability, these methods were applied to subsamples drawn from the same underlying population. The researchers also conducted multivariate analyses to evaluate the degree of overlapping environmental and genetic influences across the four SES indicators, using structural equation modeling and dimension-reduction techniques.
Norway was chosen for its extensive welfare systems, which reduce environmental variability and enhance the relative impact of genetic differences. The country's universal education and healthcare access, strong social protections, and high intergenerational mobility create a context where SES differences are less affected by economic barriers.
Key research questions focused on estimating the relative contributions of genetic, non-shared, and shared environmental factors, the variance across methods, and the overlap in influences among the four SES indicators.
Findings
This study used four heritability estimation methods to assess the contributions of environment and genetics to education, occupation, wealth, and income. Researchers found statistically significant heritability estimates across all methods and indicators, with education showing the highest genetic influence.
Wealth heritability was similar to income in family-based estimates (25% vs. 30%) but higher than income in genotype-based estimates (12% vs. 6.5%). Estimates varied with assumptions about shared environmental correlations, especially among cousins.
Shared environmental effects were substantial for education and wealth but sensitive to modeling choices. Genetic correlations among the four indicators ranged from moderate to high (0.35–0.96), suggesting both shared and distinct genetic influences.
Principal component analyses revealed a unidimensional structure for genetic and shared environmental components, but a more complex pattern for non-shared environments. Specifically, individual environments linked longer education with lower income.
The findings indicate large family-shared contributions to SES but also highlight the influence of individual-specific environmental factors, with varying degrees of overlap across the four socioeconomic indicators. The authors also note that genotype-based heritability estimates may be inflated by population stratification and indirect genetic effects, which are particularly relevant when interpreting population-level results.
Conclusions
This study provides comprehensive heritability estimates for key SES indicators in Norway using robust registry data and diverse methods. Education showed the highest contributions from genetics, consistent with findings from the United Kingdom.
Shared environments significantly influenced education and wealth, especially when cousin correlations were modeled realistically.
The study’s strengths include large sample sizes, rigorous comparisons across methods, and novel wealth estimates. However, limitations include reliance on population-level estimates that may be inflated by indirect genetic effects and assumptions about shared environments. Furthermore, the authors suggest that the common approach of using a single composite SES index may fail to capture a substantial proportion of individual-specific environmental effects and that such an index should be used with informed deliberation.
Researchers stressed ethical considerations in interpreting their findings, namely that genetic influence does not imply determinism; socioeconomic outcomes are shaped by social contexts and policies. Heritability is not fixed; it is a population statistic that cannot be applied to individuals and varies across contexts.
Overall, the results underscore the complexity of SES development, shaped by genetics, shared family environments, and individual-specific factors. Future research should explore finer-grained indicators and refine methods for modeling environmental effects within extended families.
Journal reference:
- The genetic and environmental composition of socioeconomic status in Norway. Ebeltoft, J.C., Eilertsen, E.M., Cheesman, R., Ayorech, Z., Van Hootegem, A., Lyngstad, T.H., Ystrom, E. Nature Communications (2025). DOI: 10.1038/s41467-025-58961-6 https://www.nature.com/articles/s41467-025-58961-6