America is a land of immigrants and this differences in the hereditary genetic make-up naturally results in significant variation of health across the population. Second, pockets of affluences and poverty are spread across the geographic regions within US. These socio-economic factors influence the public policy decisions in the local counties in terms of resources for health.
Researchers at the Institute for Health Metrics and Evaluation (IHME) at the University of Washington, in collaboration with researchers at Imperial College London, found that between 2000 and 2007, more than 80% of counties fell in standing against the average of the 10 nations with the best life expectancies in the world, known as the international frontier.
When compared to the international frontier for life expectancy, US counties range from being 16 calendar years ahead to more than 50 behind for women. For men, the range is from 15 calendar years ahead to more than 50 calendar years behind. This means that some counties have a life expectancy today that nations with the best health outcomes had in 1957.
Interestingly, the authors point out that the relatively low life expectancies in the US cannot be explained by the size of the nation, racial diversity, or economics. Instead, the authors point to high rates of obesity, tobacco use, and other preventable risk factors for an early death as the leading drivers of the gap between the US and other nations.
Nationwide, women fare more poorly than men. The researchers found that women in 1,373 counties – about 40% of US counties – fell more than five years behind the nations with the best life expectancies. Men in about half as many counties – 661 total – fell that far.
Black men and women have lower life expectancies than white men and women in all counties. Life expectancy for black women ranges from 69.6 to 82.6 years, and for black men, from 59.4 to 77.2 years. In both cases, no counties are ahead of the international frontier, and some are more than 50 years behind. The researchers were not able to analyze other race categories because of low population levels in many counties.