State-level association between income inequality and mortality in the USA, 1989-2019: ecological study.
Journal Articles
Overview
Research
Identity
Additional Document Info
View All
Overview
abstract
BACKGROUND: Prior studies have shown a positive relationship between income inequality and population-level mortality. This study investigates whether the relationship between US state-level income inequality and all-cause mortality persisted from 1989 to 2019 and whether changes in income inequality were correlated with changes in mortality rates. METHODS: We perform repeated cross-sectional regressions of mortality on state-level inequality measures (Gini coefficients) at 10-year intervals. We also estimate the correlation between within-state changes in income inequality and changes in mortality rates using two time-series models, one with state- and year-fixed effects and one with a lagged dependent variable. Our primary regressions control for median income and are weighted by population. MAIN OUTCOME MEASURES: The two primary outcomes are male and female age-adjusted mortality rates for the working-age (25-64) population in each state. The secondary outcome is all-age mortality. RESULTS: There is a strong positive correlation between Gini and mortality in 1989. A 0.01 increase in Gini is associated with more deaths: 9.6/100 000 (95% CI 5.7, 13.5, p<0.01) for working-age females and 29.1 (21.2, 36.9, p<0.01) for working-age males. This correlation disappears or reverses by 2019 when a 0.01 increase in Gini is associated with fewer deaths: -6.7 (-12.2, -1.2, p<0.05) for working-age females and -6.2 (-15.5, 3.1, p>0.1) for working-age males. The correlation between the change in Gini and change in mortality is also negative for all outcomes using either time-series method. These results are generally robust for a range of income inequality measures. CONCLUSION: The absence or reversal of correlation after 1989 and the presence of an inverse correlation between change in inequality and change in all-cause mortality represents a significant reversal from the findings of a number of other studies. It also raises questions about the conditions under which income inequality may be an important policy target for improving population health.
