Income inequality, mortality, and self rated health: meta-analysis of multilevel studies. (10th November 2009)

• Record Type: Journal Article
• Authors: Kondo, Naoki; Sembajwe, Grace; Kawachi, Ichiro; van Dam, Rob M; Subramanian, S V; Yamagata, Zentaro
• Is Part Of: BMJ. Volume 339(2009)
• Publication Date: 2009-11-10
• Subjects: Medicine -- Periodicals; Medicine -- Periodicals; Medicine; Periodicals; 610
• DOI: 10.1136/bmj.b4471
• Languages: English
• ISSNs: 0007-1447

Abstract

Abstract : Objective To provide quantitative evaluations on the association between income inequality and health. Design Random effects meta-analyses, calculating the overall relative risk for subsequent mortality among prospective cohort studies and the overall odds ratio for poor self rated health among cross sectional studies. Data sources PubMed, the ISI Web of Science, and the National Bureau for Economic Research database. Review methods Peer reviewed papers with multilevel data. Results The meta-analysis included 59 509 857 subjects in nine cohort studies and 1 280 211 subjects in 19 cross sectional studies. The overall cohort relative risk and cross sectional odds ratio (95% confidence intervals) per 0.05 unit increase in Gini coefficient, a measure of income inequality, was 1.08 (1.06 to 1.10) and 1.04 (1.02 to 1.06), respectively. Meta-regressions showed stronger associations between income inequality and the health outcomes among studies with higher Gini (≥0.3), conducted with data after 1990, with longer duration of follow-up (>7 years), and incorporating time lags between income inequality and outcomes. By contrast, analyses accounting for unmeasured regional characteristics showed a weaker association between income inequality and health. Conclusions The results suggest a modest adverse effect of income inequality on health, although the population impact might be larger if the association is truly causal. The results also support the threshold effect hypothesis, which posits the existence of a threshold of income inequality beyond which adverse impacts on health begin to emerge. The findings need to be interpreted with caution given the heterogeneity between studies, as well as the attenuation of the risk estimates in analyses that attempted to control for the unmeasured characteristics of areas with high levels of income inequality.