Did you catch the Journal of the American Medical Association article on the Association Between Income and Life Expectancy in the US, 2001-2014?
Spoilers: there is one. This piece tries to break it down further using deidentified tax records to look at race, income, sex, ethnicity, and more. The sample size is magnificently large: 1.4 billion (not a typo) people. Here are the key findings from the abstract:
The gap in life expectancy between the richest 1% and poorest 1% of individuals was 14.6 years (95% CI, 14.4 to 14.8 years) for men and 10.1 years (95% CI, 9.9 to 10.3 years) for women. Second, inequality in life expectancy increased over time. Between 2001 and 2014, life expectancy increased by 2.34 years for men and 2.91 years for women in the top 5% of the income distribution, but by only 0.32 years for men and 0.04 years for women in the bottom 5% (P < .001 for the differences for both sexes). Third, life expectancy for low-income individuals varied substantially across local areas. In the bottom income quartile, life expectancy differed by approximately 4.5 years between areas with the highest and lowest longevity. Changes in life expectancy between 2001 and 2014 ranged from gains of more than 4 years to losses of more than 2 years across areas. Fourth, geographic differences in life expectancy for individuals in the lowest income quartile were significantly correlated with health behaviors such as smoking (r = −0.69, P < .001), but were not significantly correlated with access to medical care, physical environmental factors, income inequality, or labor market conditions. Life expectancy for low-income individuals was positively correlated with the local area fraction of immigrants (r = 0.72, P < .001), fraction of college graduates (r = 0.42, P < .001), and government expenditures (r = 0.57, P < .001).
This is an important and potentially useful effort. It doesn’t get us much detail on what could be done differently clinically or in terms of access to health care–indeed, access to health care seems less influential than health behaviors–but as a careful look at social determinants of health it is a critical piece of any attempt to make death, well, more fair.
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Click through to the above link for detailed results, and bear in mind that the results of a single study, however magnificent the sample size, are not sufficient. Other people might crunch the same data set differently, or different data sets might show different results and contain different measures (tax records are a pretty narrow set of data).
None of us are getting out of here alive. But who goes first, and why? Do we want to accept a world in which some of us go unjustly early? Where are the levers we can move the most?
