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

BMJ 2009; 339 doi: (Published 11 November 2009) Cite this as: BMJ 2009;339:b4471
  1. Naoki Kondo, assistant professor1, research fellow2,
  2. Grace Sembajwe, research fellow3,
  3. Ichiro Kawachi, professor and chair2,
  4. Rob M van Dam, assistant professor4,
  5. S V Subramanian, associate professor2,
  6. Zentaro Yamagata, professor1
  1. 1Department of Health Sciences, Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi, 1110 Shimokato, Chuo-Shi, Yamanashi, 409-3898 Japan
  2. 2Department of Society, Human Development, and Health, Harvard School of Public Health, 677 Huntington Avenue, SPH 3, Floor 7, Boston, Massachusetts 02115, USA
  3. 3Center for Community-Based Research, Dana-Farber Cancer Institute, Boston, Massachusetts 02115, USA
  4. 4Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts 02115, USA
  1. 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}
  • Accepted 31 August 2009


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.


  • Contributors: NK conceived the study, gathered data, completed the analysis, drafted the initial manuscript, and conceptualised ideas. GS participated in the data acquisition, data extraction, and drafting of the manuscript. IK helped in the conceptualisation of the study and drafting of the manuscript. RMvD contributed to the supervision of the statistical analysis and drafting of the manuscript. SVS participated in the conceptualisation of ideas and the supervision of the analysis. ZY supervised the research project and analysis. All authors, external and internal, had full access to all of the data in the study and can take responsibility for the integrity of the data and the accuracy of the data analysis. NK is guarantor.

  • Funding: This study is supported by the Pfizer Health Research Foundation. NK is a recipient of the fellowship award by the Abe Fellowship Program administered by the Social Science Research Council and the American Council of Learned Societies in cooperation with and funded by the Japan Foundation Center for Global Partnership. SVS is supported by the National Institute of Health Career Development Award (NHLBI 1k25 HL081275). These sponsors were not involved in study design and the collection, analysis, and interpretation of data and the writing of the article and the decision to submit it for publication.

  • Competing interest: None declared.

  • Ethical approval: Not required.

  • Data sharing: No additional data available.

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