The “Deaths of Despair” narrative is wrong: It’s time to be a little ruder about this (Matthew Yglesias, Oct 10, 2023, Slow Boring)
Over the past few years, Anne Case and Angus Deaton have unleashed upon the world a powerful meme that seems to link together America’s troublingly bad life expectancy outcomes with a number of salient social and political trends like the unexpected rise of Donald Trump.
Their “deaths of despair” narrative linking declining life expectancy to populist-right politics and to profound social and economic decay has proven to be extremely powerful. But their analysis suffers from fundamental statistical flaws that critics have been pointing out for years and that Case and Deaton just keep blustering through as if the objections don’t matter. Beyond that, they are operating within the confines of a construct — “despair” — that has little evidentiary basis. The rise in deaths of despair turns out to overwhelmingly be a rise in opioid overdoses. This increase is not happening in European countries that have not only been buffeted by the same broad economic trends as the United States, but are also seeing the rise of right-populist backlash politics. […]
Novosad, Rafkin, and Asher have provided a compelling analysis of a very concentrated problem of worsening health outcomes for the worst-off Americans. Case and Deaton, by contrast, have delivered a very misleading portrait of worsening health outcomes for the majority of Americans that (because they mistakenly think it’s a majority) they attribute to broad economic forces that exist internationally but which for some reason only cause “despair” in the United States. And then it gets worse, because as Matthews argues (citing Raj Chetty’s Opportunity Insights Project data), the growing disparities are located in specific parts of the country:
While it’s true that rich people in America live significantly longer than poor people, that’s much less true in New York City. It’s not true in California as a whole. Heavily urban areas with high education levels see a modest relationship between income and death rates. More-rural, less-educated areas, by contrast, see a very strong relationship between the two.
Areas with smaller mortality gaps tend to be places, the researchers find, with lower rates of smoking and higher rates of exercise, which makes sense when you consider that the variation in death rates between cities is driven not by factors like car crashes or suicide but conditions like heart disease and cancer, which are themselves driven in part by lifestyle conditions. Local unemployment rates and other indicators of the health of the local labor market did not seem to be associated with longevity, nor did income inequality. These aren’t firmly causal findings, to be clear, but they might be suggestive of potential causes to investigate.
Conveniently, there’s a new piece out in the Washington Post by Lauren Weber, Dan Diamond, and Dan Keating that I think explains this geographic variation very well: Places that adopt nanny state policies to improve public health get better public health.