Female Mortality on the Rise in Many U.S. Counties
A recent article in Health Affairs by David Kindig and Erika Cheng examined trends in male and female mortality rates from 1992–1996 to 2002–2006 in 3,140 US counties. What they found is a worrisome trend of female mortality on the rise in 42.8% of counties, depicted in red on the map reposted on the left. The situation with male mortality rates is much better, increasing in only 3.4% of counties. Historically, overall U.S. life expectancy has been increasing steadily over the decades, but a large subgroup of women was apparently left behind, “despite increasing medical care expenditures and public health efforts”, Kindig and Cheng point out. A strong regional pattern emerges from this map: many of the counties with worsened female mortality are found in southern states and the Midwest. In contrast, virtually no county in New England showed a decline.
It is not clear what could explain this pattern. One of the readers commented that this map bears strong resemblance to a recent voting map, with “red” counties with worsening female mentality corresponding to “red” pro-Republican areas. As can be seen from the maps on the left, an uncanny similarity between the two maps indeed exists, especially if one adds the green-colored areas on the mortality map to the red ones. However, not all patterns found on the election map are replicated on the mortality map. For example, the heavily African-American Democrat-voting belt that stretches through the southern states posts worsening female mortality rates just like the surrounding Republican-voting areas. Moreover, several Republican-voting counties in central Texas, northern Utah, southeastern New Mexico, California’s Central Valley, and elsewhere exhibit substantial improvement in female mortality.
The authors of the study looked at a number of factors that might explain why female morality went up in some counties but down in others. A somewhat surprising finding was that the availability of medical care—measured by the number of primary care providers or percentage of uninsured—didn’t really make a difference. “Female mortality rates were not predicted by any of the medical care factors,” they write. As the maps on the left indicate, there is a correlation between declining longevity among women and such health problems as obesity, diabetes, and stroke in much of the Southeast; however, elsewhere it falls apart. Nor is it clear why these issues have a particularly strong impact on female life expectancy. Socioeconomic factors, however, seem to be better predictors of female mortality. Kindig and Cheng found “significant associations between mortality rates and some of these factors, such as smoking rates for both sexes. But socioeconomic factors such as the percentage of a county’s population with a college education and the rate of children living in poverty had equally strong or stronger relationships to fluctuations in mortality rates”.
As Bill Gardner, a psychologist who studies the mental health service system for children, points out, these figures are worrisome not only because they depict a shocking pattern of female hardship in many communities, but also because they raise questions about children’s health. “The mental and physical health of mothers is a key determinant in children’s growth and development”, Garnder writes, “but when women are not able to maintain their own health, how well can they nurture their children?”