生态学研究
不平等
联想(心理学)
经济不平等
地理
生态学
国家(计算机科学)
人口学
人口经济学
社会经济学
经济
社会学
生物
心理学
数学
人口
算法
数学分析
心理治疗师
作者
James R. Dunn,Gum‐Ryeong Park,Robbie Brydon,Michael R. Veall,Lyndsey Rolheiser,Michael Wolfson,Arjumand Siddiqi,Nancy A. Ross
标识
DOI:10.1136/jech-2024-222262
摘要
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.
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