Early-life socioeconomic status (SES) is associated with adult chronic disease, but it is unclear whether this effect is mediated entirely via adult SES or whether there is a direct effect of adverse early-life SES on adult disease. Major challenges in evaluating these alternatives include imprecise measurement of early-life SES and bias in conventional regression methods to assess mediation. In particular, conventional regression approaches to direct effect estimation are biased when there is time-varying confounding of the association between adult SES and chronic disease by chronic disease risk factors.
First-reported heart disease, diabetes, and stroke diagnoses were assessed in a national sample of 9760 Health and Retirement Study participants followed biennially from 1992 through 2006. Early-life and adult SES measures were derived using exploratory and confirmatory factor analysis. Early-life SES was measured by parental education, father's occupation, region of birth, and childhood rural residence. Adult SES was measured by respondent's education, occupation, labor force status, household income, and household wealth. Using marginal structural models, we estimated the direct effect of early-life SES on chronic disease onset that was not mediated by adult SES. Marginal structural models were estimated with stabilized inverse probability-weighted log-linear models to adjust for risk factors that may have confounded associations between adult SES and chronic disease.
During follow-up, 24%, 18%, and 9% of participants experienced first onset of heart disease, diabetes, and stroke, respectively. Comparing those in the most disadvantaged with the least disadvantaged quartile, early-life SES was associated with coronary heart disease (risk ratio = 1.30 [95% confidence interval = 1.12–1.51]) and diabetes (1.23 [1.02–1.48]) and marginally associated with stroke via pathways not mediated by adult SES.
Our results suggest that early-life socioeconomic experiences directly influence adult chronic disease outcomes.
From the aInstitute for Health and Social Policy and Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, QC Canada; and Departments of bSociety, Human Development, and Health, cEpidemiology, and dBiostatistics, Harvard School of Public Health, Boston, MA.
Submitted 15 March 2011; accepted 25 October 2011.
Supported by the Robert Wood Johnson Health & Society Scholars Program (to A.N.); the American Heart Association (10SDG264024 to M.M.G.); and the National Institutes of Health (HD060696 to T.J.V.). The authors reported no other financial interests related to this research.
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Editors' note:A commentary on this article appears on page 233.
Correspondence: Arijit Nandi, Institute for Health and Social Policy & Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, 1130 Pine Ave West, Montreal, QC H3A 1A3 Canada. E-mail: email@example.com.