(An aside: The entire County Health Rankings and Roadmap project, a collaboration between the Wisconsin researchers and the Robert Wood Johnson Foundation, is full of interesting maps, data and observations about the differences in risk factors and health in various counties. It is well worth a browse.)

The research on inequality at the county level is new, but existing literature suggests there are relationships between income inequality and life expectancy among countries in the world. “Inequality effects, over and above average income, are pretty well established,” said S.V. Subramanian, a professor of population health and geography at Harvard, who has studied the phenomenon. We know that inequality tends to concentrate income in fewer hands, creating more low-income households — and people in low-income households don’t live as long. But what causes the drop in life expectancy is debatable.

One theory is that while money does tend to buy better health, it makes a bigger difference for people low on the income scale than those at the top. That means that having fewer very poor people in a community will improve average health more than having fewer very rich people will diminish it.

But another, more sociological theory, has to do with the communities themselves. The researchers think that places where wealthy residents can essentially buy their way out of social services may have less cohesion and investment in things like education and public health that we know affect life span. There is also literature suggesting that it’s stressful to live among people who are wealthier than you. That stress may translate into mental health problems or cardiac disease for lower-income residents of unequal places.

The researchers measured inequality by comparing the incomes of people in a given place who earned the 80th percentile in the county with the incomes of those in 20th percentile. Then they measured life expectancy using a custom measurement they developed — it counts the “potential life years lost” in each community by measuring all those who died before the age of 75, and the age at which they died. So someone who died at age 70 would have five years of potential life lost. Then they adjusted the numbers according to how old people were in the county, so counties with more old people wouldn’t look sicker than counties that were younger. The study looked at only the average life span and not that of higher-income versus lower-income residents.