A recent population-based report by JAMA Internal Medicine suggests that where you live may be a determinant of your life expectancy in the U.S.
The report also suggests that the variation of longevity among U.S. counties is explainable – wealth, education, ethnicity, health care are among the factors cited.
Why This Matters
If zip code is more of a determinant of health and longevity than genetic or DNA code, then the study presents an opportunity for targeted policy prescription.
It would also present an opportunity for targeted social investments in areas where more measurable impact can be made, in poverty, social justice, job retraining programs, and affordable health care.
Health Care Spending
Credit: Alyson Hurt/NPR
Speaking of affordable health care, a pair of other studies also suggest that the U.S., the biggest economy among nations, spends the most on care for the sick, yet lags other developed nations in terms of health outcomes.
These reports come at a time when the U.S. Congress is attempting to repeal former President Obama’s signature Affordable Health Care Act.
Among uninsured consumers who pay out-of-pocket, the poorest will forgo treatment — or they’ll have treatment and be thrown into poverty because of medical costs. That problem is mostly a given in poorer nations, though the U.S. stands out among developed nations as having medical expenditures that often are so large that many land in bankruptcy.
***
Partial Transcript of the Report
The findings on factors related to variation in life expectancy have important policy implications. In particular, policies and programs that target behavioral and metabolic risk factors have the potential to improve health in all locations but especially those that are currently most at a disadvantage, consequently reducing geographic disparities.
This is not to say that policies that target socioeconomic drivers of disparities would not also be effective, but rather that there are multiple potential routes to more equitable health outcomes for federal, state, and local policy makers to consider.
Furthermore, researchers now recognize that the relationship between socioeconomic status and health likely reflects causal pathways running in both directions (ie, from better health to higher socioeconomic status as well as from higher socioeconomic status to better health).29
Thus, policies that target inequalities in health may also in the long run be effective mechanisms for addressing inequalities in socioeconomic status as well.
This study has a number of strengths. First, this analysis used recently developed and validated small area models that have been shown to generate more precise estimates than previous methodologies.16
Second, this study did not exclude small counties or aggregate them beyond what was necessary to address historical boundary changes, allowing for a more complete accounting of geographic inequalities at the county level than previously available.
Third, in addition to life expectancy, this study considered geographic inequalities in age-specific mortality risks that have not been previously explored.
Fourth, this study is the first to systematically consider to what extent geographic inequalities in life expectancy at the county level can be explained by socioeconomic and race/ethnicity factors, behavioral and metabolic risk factors, and health care factors, both independently and in combination.
Sources: JAMA Internal Medicine, NPR, FiveThirtyEight, Ritholtz, WHO
