It has been known since the time of Condorcet, over 200 years ago, that poverty is bad for you – an income effect. Studies have also shown an association between relative poverty and life expectancy – a relative income effect. It has become common to interpret these associations as evidence that relative poverty causes poor health, net of absolute wealth. Previous studies are trumped by the largest association study ever conducted, based on nearly 1.4 trillion person years of observation and 1.4 billion de-identified tax records across the United States of America. Beat that! So, what did it find?
- The association between wealth and longevity (the income effect) is confirmed. The difference in male life expectancy at age 40 differs by a colossal 15 years between the top and bottom 1% on the income scale. Interestingly, there is no threshold above which the association fades; rather the reverse.
- Inequality has increased in recent years because life expectancy has increased faster among people on high incomes than among those on low incomes.
- Differences in mortality adjusted for race and ethnicity and net of income varies by geographic area. In other words, the differences in life expectancy between rich and poor itself differs by geographic area.
- Differences in income effect by area are mostly explained by differences in health behaviour (rather than, for example, access to healthcare).
The finding that different areas have very different survival rates net of income, allows the effect of numerous other variables on the income effects (absolute and relative) to be explored. Some places have large gradients in wealth, others smaller. The existence of a relative income effect is confirmed by a negative correlation between inequality (measured by the Gini co-efficient) and longevity. But this is an artefact of the concave nature of the relationship between income and life expectancy. In fact, among the lowest quartile by income there is no correlation between wealth disparity and health, whereas, ironically, it is strongest among the upper quartile. So the idea that it is the poor who exhibit the strongest relative income effect is completely wrong. In fact, poor people have healthier behaviours and live longer when they live in rich cities alongside a highly-educated, high income populations than in poorer cities with ‘better’ Gini co-efficients. Perhaps this is because rich cities can raise more in tax at a given tax rate. Slum formation is more rapid in cities with a high Gini co-efficient. This is sometimes interpreted as a high Gini causing poverty, rather than the more plausible interpretation that rational internal migrants gravitate to richer cities. These data are important because they call into doubt the simplistic idea that all we have to do to right the world’s wrongs is to tax rich people more heavily.
— Richard Lilford, CLAHRC WM Director
- Benzeval M, Bond L, Campbell M, et al. How Does Money Influence Health? York: Joseph Rowntree Foundation. 2014.
- Wilkinson RG, Pickett KE. Income inequality and population health: a review and explanation of the evidence. Soc Sci Med. 2006; 62(7): 1768-84.
- Chetty R, Stepner M, Abraham S, et al. The Association Between Income and Life Expectancy in the United States, 2001-2014. JAMA. 2016; 315(6):1750-66.