ArticleJournal of epidemiology and community health2024
Socioeconomic status across the early life course predicts gene expression signatures of disease and senescence.
Article in Journal of epidemiology and community health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Intergenerational educational mobility and intrinsic capacity in later life: a harmonised analysis of individuals from five countries.Journal of global health · 2026Article
- Parental income in childhood and health outcomes across age groups: a register-based study from Norway.BMC medicine · 2026Article
- Proteomics sheds light on unequal aging.Nature medicine · 2025Article
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Authors and funding
6 authors.
Funding
Abstract
backgroundSocioeconomic status (SES) is associated with many chronic diseases, indicators of senescence and mortality. However, the changing salience of SES in the prediction of adult health is not well understood. Using mRNA-seq abundance data from wave V of the National Longitudinal Study of Adolescent to Adult Health (Add Health), we examine the extent to which SES across the early life course is related to gene expression-based signatures for chronic diseases, senescence and inflammation in the late 30s.
methodsWe use Bayesian methods to identify the most likely model of life course epidemiology (critical, sensitive and accumulation models) that characterises the changing importance of parental SES and SES during young (ages 27-30) and mid-adulthood (ages 36-39) in the prediction of the signatures.
resultsFor most signatures, SES is an important predictor in all periods, although parental SES or SES during young adulthood are often the most predictive. For three signatures (components of diabetes, inflammation and ageing), critical period models involving the exclusive salience of SES in young adulthood (for diabetes) or parental SES (for inflammation and ageing) are most probable. The observed associations are likely mediated by body mass index.
conclusionModels of life course patterns of SES may inform efforts to identify age-specific mechanisms by which SES is associated with health at different points in life and they also suggest an enhanced approach to prediction models that recognise the changing salience of risk factors.
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