Income Inequality and Health Outcomes

During the last several decades, industrialized countries have experienced a growing gap between the rich and the poor. This income inequality is believed to damage health, with even modest associations between inequality and health outcomes having substantial ramifications for society as a whole. While most analyses of income inequality and health have revealed inconsistent results, a new meta-analysis published in a recent issue of British Medical Journal (BMJ) supports the link between income inequality and mortality and self-rated health.

Income inequality is measured by the Gini coefficient, a measure of income disparity within a population. The Gini coefficient ranges between 0 and 1, with 0 signifying complete income equality (everyone receives the same income) and 1 signifying complete inequality (one individual receives all the income). Most European countries have a Gini coefficient of approximately 0.3, while the United States has a Gini coefficient close to 0.4. The Gini coefficient of the entire world has been estimated at approximately 0.6.

The BMJ analysis systematically examined 9 cohort and 19 cross-sectional studies involving a total of more than 61 million subjects to describe the association between the Gini coefficient and mortality and self-reported health status. Overall, the investigators concluded that people living in regions with high income inequality (a higher Gini coefficient) had an increased risk of premature death, independent of their individual socioeconomic status, age, or gender. The increase mortality risk amounted to 8% per 0.05 increase in the Gini coefficient. There were stronger associations between income inequality and poor health in samples with a higher Gini coefficient, studies conducted after 1990, and studies with a follow-up duration of more than 7 years.

This study also seems to confirm a theoretical “threshold effect” above which the disparities in health outcomes are seen. By the authors’ estimation, the Gini must be above 0.3 before the adverse health effects are apparent. If the associations and estimations are true, the authors calculate that 1.5 million deaths could be avoided in 30 developed countries if the Gini coefficients were leveled to 0.3 or below. However, very little data is available on income inequality or health outcomes in developing nations, which would likely adjust the findings.

Income inequality is believed to damage health outcomes in two ways. First, an unequal society usually involves a considerable portion of the population that is living in poverty, and many studies have determined that poverty is bad for overall health outcomes. The greater the income inequality, the more impoverished citizens, and the more who are in poor health. The second, less easily defined, explanation is that income inequality is also detrimental to the more affluent members of society, since these citizens experience psychosocial stress from the inequality and loss of social cohesion. The public health burdens of the second situation are obviously broader, but much less quantifiable, and more controversial.

It is nearly impossible to confirm a causal relationship between income inequality and health outcomes. And no one supports the redistribution of income just to improve health outcomes. Simply improving health education and increasing access to health care of the socially and economically disadvantaged — two issues that could use improvement no matter which end of the Gini spectrum a country falls — could level the proverbial playing field. But, many policy makers support, at the very least, acknowledging the link between macroeconomic conditions and individual health outcomes when drafting economic and health care policy or legislation for local and international communities.


Kondo, N., Sembajwe, G., Kawachi, I., van Dam, R., Subramanian, S., & Yamagata, Z. (2009). Income inequality, mortality, and self rated health: meta-analysis of multilevel studies BMJ, 339 (nov10 2) DOI: 10.1136/bmj.b4471

SUBRAMANIAN, S., & KAWACHI, I. (2006). Whose health is affected by income inequality? A multilevel interaction analysis of contemporaneous and lagged effects of state income inequality on individual self-rated health in the United States Health & Place, 12 (2), 141-156 DOI: 10.1016/j.healthplace.2004.11.001

LYNCH, J., SMITH, G., HARPER, S., HILLEMEIER, M., ROSS, N., KAPLAN, G., & WOLFSON, M. (2004). Is Income Inequality a Determinant of Population Health? Part 1. A Systematic Review The Milbank Quarterly, 82 (1), 5-99 DOI: 10.1111/j.0887-378X.2004.00302.x

Ichida, Y., Kondo, K., Hirai, H., Hanibuchi, T., Yoshikawa, G., & Murata, C. (2009). Social capital, income inequality and self-rated health in Chita peninsula, Japan: a multilevel analysis of older people in 25 communities Social Science & Medicine, 69 (4), 489-499 DOI: 10.1016/j.socscimed.2009.05.006

Jennifer Gibson, PharmD

Jennifer Gibson, PharmD, is a practicing clinical pharmacist and medical writer/editor with experience in researching and preparing scientific publications, developing public relations materials, creating educational resources and presentations, and editing technical manuscripts. She is the owner of Excalibur Scientific, LLC.
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