The Third World in Your Own Backyard
by Jason S. Brinkley, PhD, MA, MS
On the Brink addresses topics related to data, analytics, and visualizations on personal health and public health research. This column explores current practices in the health arena and how both the data and mathematical sciences have an impact. (The opinions and views represented here are the author’s own and do not reflect any group for which the author has an association.)
America is often viewed by other countries as having an ego problem. Indeed, we tend to live up to the stereotype when we use phrases like “American Exceptionalism” and “America First” in our political speak. Even in our social discourse, we poke fun at the different types of problems we face versus other countries with hashtags boasting #FirstWorldProblems. It isn’t all hype though; America does have the world’s largest economy while leading and innovating in a multitude of areas and continuing to be a top destination for visitors and migrants alike. America does, however, suffer from regional imbalances and huge disparities; look hard enough and we can find places in the United States that have things in common with the developing world.
Today’s “On the Brink” plays a game similar to my first post where we looked at what kills us. I plan to cherrypick statistics from different areas to highlight specific poor health outcomes that are akin to or worse than outcomes from regions of the developing world, which Americans sometimes look down upon. While on average the United States is doing well in many areas, these examples highlight our need for continued improvement.
Let’s start with life expectancy. While overall US life expectancy is estimated at a relatively robust 78.9 years, we find that that estimate varies wildly across regions. In fact, the life expectancy of West Virginians is near the bottom, estimated at 75.4 years. By contrast, World Health Organization estimates that the life expectancy of individuals born in Iran is 75.5 years. If it is surprising to find similar life expectancies, consider that for males born in McDowell County, West Virginia, life expectancy is an abysmal 63.5 years (on par with Cambodia). Robert Wood Johnson Foundation brings together data that suggest that Wyoming, Mingo, and McDowell Counties have a very large number of premature deaths and years of potential life lost.
Next consider teenage birth rate, an outcome measure that the US already tends to perform more poorly on than other countries in the developed world. Luna County, New Mexico, is a rural area right on the US/Mexico border. With a population of roughly 25 thousand residents, Luna also boasts one of the highest teenage birth rates in the nation with 94 per 1,000 females aged 15 to 19 giving birth. By contrast, recent estimates from Kenya, Nicaragua, and the Dominican Republic are all in the same vein with rates of 90, 88, and 97 per 1,000 teen females respectively. In Luna’s defense, there are recent signs that the rate is dropping and there are disagreements in measurement.
Other poor outcomes include low birth weight with Coahoma County, Mississippi, showing a rate of 19%, putting it on par with UNICEF estimates for Nigeria (at 15%) and Haiti (at 23%). These phenomena not only affect the young and the old but also the in-between. Note that with the recent opioid epidemic, recorded drug overdose rankings of the top 20 US counties cut across six states with 9 counties in West Virginia, 6 in Kentucky, 2 in Tennessee, and 1 each in New Mexico, Utah, and Colorado. All 20 counties have drug overdose rates higher than Colombia, Bahamas, and Sri Lanka.
There is a slew of potential methodological issues in this exercise, including the idea that I’m comparing some of the poorest outcomes in the United States to overall averages or general rates for other countries. Also there are questions about measurement and trustworthiness of the reporting in some of these various data sources. These issues notwithstanding, there is a clear need for ongoing work to improve US disparities. This only highlights specific areas, and we certainly don’t make robust comparisons on measures such as quality of life. But as someone born in the mountains of southern West Virginia, the notion that the ending date there is the same as Iran hits close to home. Looks like it’s time to schedule a follow-up with my primary care provider.
Jason S. Brinkley, PhD, MS, MA is a Senior Researcher and Biostatistician at Abt Associates Inc. where he works on a wide variety of data for health services, policy, and disparities research. He maintains a research affiliation with the North Carolina Agromedicine Institute and serves on the executive committee for the NC Chapter of the American Statistical Association and the Southeast SAS Users Group. Follow him on Twitter. [Full Bio]
Previous posts by this author:
- The Unrealistic Gold Standard
- Does MACRA Signal the Beginning of the End for Medicare Claims Data?
- Think You Aren’t Extraordinary? Odds Are You’re Wrong
- Mapping by Words
- Are We Asking Too Much From Surveys?
- Making Better Comparisons
- What Kills Us?
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- Students of Public Health2022.12.01Deadline Extended to Nominate a Student Who Rocked Public Health in 2022
- JPHMP Direct Voices2022.10.19Preview Issue for Public Health Workforce Interests and Needs Survey
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