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Education, income, and occupational class cannot be used interchangeably in social epidemiology. Empirical evidence
Siegfried Geyer1, Orjan Hemström, Richard Peter
1Medical Sociology Unit OE 5435, Hanover Medical School, 30625 Hanover, Germany. geyer.siegfried@mh-hanover.de
Study Objective:
Education, income, and occupational class are often used interchangeably in studies showing social inequalities in health. This procedure implies that all three characteristics measure the same underlying phenomena. This paper questions this practice. The study looked for any independent effects of education, income, and occupational class on four health outcomes: diabetes prevalence, myocardial infarction incidence and mortality, and finally all cause mortality in populations from Sweden and Germany.
Design:
Sweden: follow up of myocardial infarction mortality and all cause mortality in the entire population, based on census linkage to the Cause of Death Registry. Germany: follow up of myocardial infarction morbidity and all cause mortality in statutory health insurance data, plus analysis of prevalence data on diabetes. Multiple regression analyses were performed to calculate the effects of education, income, and occupational class before and after mutual adjustments.
Setting And Participants:
Sweden (all residents aged 25-64) and Germany (Mettman district, Nordrhein-Westfalen, all insured persons aged 25-64).
Main Results:
Correlations between education, income, and occupational class were low to moderate. Which of these yielded the strongest effects on health depended on type of health outcome in question. For diabetes, education was the strongest predictor and for all cause mortality it was income. Myocardial infarction morbidity and mortality showed a more mixed picture. In mutually adjusted analyses each social dimension had an independent effect on each health outcome in both countries.
Conclusions:
Education, income, and occupational class cannot be used interchangeably as indicators of a hypothetical latent social dimension. Although correlated, they measure different phenomena and tap into different causal mechanisms.
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Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and case-control studies.