A lower life expectancy in a state is associated with a higher share in the state voting for Trump. The chart above shows the simple correlation, using state-wide averages, between the life expectancy in a state and Trump’s share of the vote in that state in the 2020 presidential election. States where life expectancy is relatively low saw, on average, a higher share of their population voting for Trump. Life expectancy was especially low in a set of mostly Southern states that also had a high share voting for Trump (the bottom right corner of the chart).
The figures on life expectancy come from a recently issued set of estimates produced by the CDC. The CDC estimates are geographically highly detailed, providing estimates down to the census tract level, but I have only used here the overall state-wide averages. Due to their fine level of geographic detail, the CDC estimates are averaged over several years (2010 to 2015) to smooth out year-to-year statistical noise. But life expectancy figures generally change only slowly over time (2020 was an exception, due to Covid-19), so figures for 2010-15 will provide a good estimate of what should be considered normal for life expectancy currently (i.e. with the exception of the Covid-19 impact). The presidential election results are from Wikipedia, where the Trump share is his share in the overall vote in each state (including third party and other minor candidates).
The correlation is a strong one. The regression equation (shown in the chart) for the relationship has an R-squared of 0.45. This means that if one simply knew the life expectancy in a state, one could predict 45% of the variation in the share across the states that would vote for Trump. This is high for such a simple cross-section relationship. The negative slope of the equation (-0.11) means that every percentage point increase in the share of the vote for Trump is associated with a 0.11 year lower life expectancy. Or put another way, a state with a life expectancy that is one year less than in another is associated with an expected 9 percentage point higher share of those voting for Trump (where 9 is roughly equal to 1 / 0.11).
Why this correlation? Note that it is not saying that a high or low life expectancy in itself would necessarily be driving a tendency to vote for Trump or not. Rather, a number of factors that enter into the determination of life expectancy are quite possibly also factors in common with the views of Trump supporters. Life expectancy depends on personal factors and decisions (smoking, diet and exercise, obesity, vaccinations, whether to wear a mask to protect oneself and others to reduce the spread of a deadly disease), as well as on decisions made by state and local governments chosen by that electorate (such as on access to health care, e.g. whether Medicaid should be available for the poor). Life expectancy also depends on income levels and for any given average income level on income inequality.
And it will depend on the social norms of the region, such as car driving habits (speeding) and access to guns. Of the factors reducing life expectancy in the US between 2014 and 2017 (mostly offsetting factors that would have, by themselves, led to a higher life expectancy) unintentional injuries accounted for just over half (50.6%) while suicides and homicides accounted for a further 15% (suicide 7.8% and homicide 7.5%). That is, these non-medical factors accounted for two-thirds of the factors that had a negative impact on life expectancy in this period.
Few would question that better health is better than poorer health. The high correlation seen here between life expectancy and the degree of Trump support suggests that there are significant commonalities in the various states between behaviors (both personal and social) that lead to poorer health outcomes and support for Trump.
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