Income inequality, mortality, and self rated health: meta-analysis of multilevel studies

doi:10.1136/bmj.b4471

Published 10 November 2009, doi:10.1136/bmj.b4471
Cite this as: BMJ 2009;339:b4471

Research

Income inequality, mortality, and self rated health: meta-analysis of multilevel studies

Naoki Kondo, assistant professor, research fellow¹^,2, Grace Sembajwe, research fellow³, Ichiro Kawachi, professor and chair², Rob M van Dam, assistant professor⁴, S V Subramanian, associate professor², Zentaro Yamagata, professor¹

¹ Department of Health Sciences, Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi, 1110 Shimokato, Chuo-Shi, Yamanashi, 409-3898 Japan, ² Department of Society, Human Development, and Health, Harvard School of Public Health, 677 Huntington Avenue, SPH 3, Floor 7, Boston, Massachusetts 02115, USA, ³ Center for Community-Based Research, Dana-Farber Cancer Institute, Boston, Massachusetts 02115, USA, ⁴ Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts 02115, USA

Correspondence to: Naoki Kondo, Department of Health Sciences, Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi, 1110 Shimokato, Chuo-Shi, Yamanashi, 409-3898 Japan nkondo{at}yamanashi.ac.jp

Objective To provide quantitative evaluations on the associationbetween income inequality and health.

Design Random effects meta-analyses, calculating the overallrelative risk for subsequent mortality among prospective cohortstudies and the overall odds ratio for poor self rated healthamong cross sectional studies.

Data sources PubMed, the ISI Web of Science, and the NationalBureau for Economic Research database.

Review methods Peer reviewed papers with multilevel data.

Results The meta-analysis included 59 509 857 subjects in ninecohort studies and 1 280 211 subjects in 19 cross sectionalstudies. The overall cohort relative risk and cross sectionalodds ratio (95% confidence intervals) per 0.05 unit increasein 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-regressionsshowed stronger associations between income inequality and thehealth outcomes among studies with higher Gini ( $≥$ 0.3), conductedwith data after 1990, with longer duration of follow-up (>7years), and incorporating time lags between income inequalityand outcomes. By contrast, analyses accounting for unmeasuredregional characteristics showed a weaker association betweenincome inequality and health.

Conclusions The results suggest a modest adverse effect of incomeinequality on health, although the population impact might belarger if the association is truly causal. The results alsosupport the threshold effect hypothesis, which posits the existenceof a threshold of income inequality beyond which adverse impactson health begin to emerge. The findings need to be interpretedwith caution given the heterogeneity between studies, as wellas the attenuation of the risk estimates in analyses that attemptedto control for the unmeasured characteristics of areas withhigh levels of income inequality.

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