If you are born in the Buckeye-Woodhill neighborhood on the east side of Cleveland, your life expectancy will be 65 years. Meanwhile, if you are born in Shaker Heights, less than two miles away, your life expectancy is 89 years.
What’s the difference between these two neighborhoods? Among other things, poverty.
A 2019 report from the Center for Community Solutions details the relationship between poverty and life expectancy in Ohio neighborhoods, finding a strong negative relationship between poverty rates and life expectancy at birth.
While we have information on how poverty interacts with life expectancy, we don’t have a great estimate of how many people die every year because of poverty. A new study out this week by an international team of policy researchers and sociologists tries to estimate this number.
In “Novel Estimates of Mortality Associated With Poverty in the US,” researchers David Brady from the University of California, Riverside’s School of Public Policy, Ulrich Kohler from the University of Potsdam in Germany, and Hui Zheng from Ohio State University estimate the impact of poverty on mortality by looking at a cohort dataset of income and comparing it to a similar dataset on mortality.
By combining these two datasets, the researchers were able to estimate not only how many people were dying because of poverty, but how quickly they were dying. The chart below shows how quickly people die at different ages due to being in poverty. As the line goes down, it shows the percentage of the cohort still alive at different ages as expressed on the horizontal axis. So for instance, at age 60, about 90% of people in poverty are still alive.
A detectable trend starts in the 40s, with people in poverty dying quicker than those not in poverty. The gap is wide between the two groups over the next few decades, with 10% of people in poverty dead by age 60, a figure not matched by those not in poverty until they are nearly 75. Death rates for the two groups don’t converge until both groups are nearly 90, at which point about half the population of both people in poverty and not in poverty have died.
The figure below compares how many deaths poverty is associated with in the United States compared to other major causes of death. Notably, according to this estimate poverty ranks as the fourth-highest cause of death in the U.S., only behind heart disease, cancer, and smoking and similar to causes of death like dementia and obesity that kill hundreds of thousands of Americans a year.
Notably, poverty also kills many more Americans per year than headline-grabbing causes of death like drug overdose, suicide, firearms, and homicide.
The researchers found that someone in poverty is anywhere from 26-60% more likely to die in a given year than someone not living in poverty. Someone living in chronic poverty over the past ten years had anywhere from a 45-102% higher chance of dying.
These findings have big implications for public policy. The United States has consistently had a higher poverty rate and shorter lifespans than a number of other similar countries–the link between the two phenomena may help explain this trend. Similarly, this may help explain why racial minority groups have higher rates of poverty and lower life expectancy than non-Hispanic whites in the U.S.
Lastly, the authors offer that cost-benefit analysis of anti-poverty programs should incorporate mortality impacts into the benefits of programs that alleviate poverty. This seems like a natural use of this research. If pulling people out of poverty has health impacts, especially on the scale of mortality reduction, those benefits should be monetized along with other important benefits of the policy.
This is another example of how anti-poverty programs can rise beyond the equality-efficiency tradeoff. If a program that reduces poverty also has health impacts, that is a win-win for society on the dimension of these two social goals. And that is an insight that needs to be a part of our analysis.