Literature DB >> 22012964

Income inequality and health: the role of population size, inequality threshold, period effects and lag effects.

Naoki Kondo1, Rob M van Dam, Grace Sembajwe, S V Subramanian, Ichiro Kawachi, Zentaro Yamagata.   

Abstract

BACKGROUND: Income inequality has been associated with worse health outcomes in several but not all studies. The heterogeneity across studies may be explained by the variations in the size of area or population over which income inequality was evaluated. Moreover, the studies above a certain inequality threshold, conducted more recently, and incorporating a time lag may have stronger associations between income inequality and health. The authors investigated if the strength of the association between income inequality and health was altered by these factors.
METHODS: The authors conducted a multivariate meta-regression analysis using nine multilevel cohort studies on income inequality and mortality and 14 multilevel cross-sectional studies on income inequality and self-rated health.
RESULTS: Among cross-sectional studies, studies evaluating country-level inequality (average population>24 million) were more likely to show a stronger association between income inequality and poor health compared with those evaluating income inequality within small average populations (<820 000). There were no significant differences in the effect size of inequality-health association relating to the differences in the population size within a country across which income inequality was evaluated in both cross-sectional and cohort studies. The authors found that the threshold effects, period effects and lag effects were independent of the population size.
CONCLUSIONS: Income inequality at the country level may have stronger adverse contextual effects on health than inequality in smaller areas, perhaps by best reflecting social stratification in a society. Furthermore, we found that threshold, period and lag effects were independent of area unit for evaluating inequality, which may have important policy implications.

Mesh:

Year:  2011        PMID: 22012964     DOI: 10.1136/jech-2011-200321

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


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