Literature DB >> 16905727

Education, income, and occupational class cannot be used interchangeably in social epidemiology. Empirical evidence against a common practice.

Siegfried Geyer1, Orjan Hemström, Richard Peter, Denny Vågerö.   

Abstract

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.

Entities:  

Mesh:

Year:  2006        PMID: 16905727      PMCID: PMC2566032          DOI: 10.1136/jech.2005.041319

Source DB:  PubMed          Journal:  J Epidemiol Community Health        ISSN: 0143-005X            Impact factor:   3.710


  24 in total

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