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| Women's life expectancy in 2009 - from http://www.healthmetricsandevaluation.org/tools/data-visualization/life-expectancy-county-and-sex-us-1989-2009#/news-events/news |
Although women on average live longer than men, a
recent county-by-county report by the Institute for Health Metrics andEvaluation (IHME) has shown that women’s life expectancy is improving at a much
slower rate than men’s across the United States. It was reported that “Between 1989 and 2009, the researchers found that men's
life expectancy increased by an average of 4.6 years. But women's life
expectancy only increased by an average of 2.7 years.”
Even more
interesting, I think, is the regional variation in life expectancy. The gap
between the counties with the highest life expectancy and lowest life
expectancy is growing. For example, “in
Collier, Florida, women live 85.8 years on average. In McDowell, West Virginia,
they live to be 74.1. That’s an 11.7-year gap. In 1989, the gap was 8.7 years.” This essentially means that in some U.S. counties
life expectancies reflect some of the highest rates in the world, while other
counties in the same country have life expectancies that closer reflect those
of developing nations.
The quote that
struck me most in this article came from professor Ali Mokdad who said, “It’s tragic that in a country as
wealthy as the United States and with all the medical expertise we have that so
many girls will live shorter lives than their mothers.” In
the 21st century, the fact that women’s life expectancy in hundreds
of U.S. counties has either remained stagnant or has actually lowered is troubling
and begs the question ‘what do these increasing gaps, between both genders and
regions, reflect?’ Do these statistics reflect differences in the physical health
between men and women (sex) or in social roles and expectations (gender)?
Variation in socioeconomic status may explain regional differences in life
expectancy, but how does this explain the improvement gap between men and
women?
To check out county-by-county changes in life
expectancies between 1989 and 2009, check out the following map http://www.healthmetricsandevaluation.org/tools/data-visualization/life-expectancy-county-and-sex-us-1989-2009#/news-events/news
How does your county stack up? Why might this be?
It was crazy to me to see the map for how much worse the south is for women as compared to men. There are some areas in the south predominantly that men have a shorter life as well but seeing just how much of the southern part of the map is red for females in 2009 is unbelievable. I would say that it probably has to do with the diet that many people in the south have with eating predominantly fried foods. My county is Suffolk County NY, which has had numbers going up yet along with much of my state, not only for females but for males as well. I would also assume that the numbers do not seem as bad for the males as their lifelines were not as long to begin with. Although I am happy to see that men are starting to have comparable lifespans in certain areas such as parts of NY where I am from. I think that life expectancy does have to do with some of the gender roles such as men are supposed to be the tough ones who do not go to the doctor which could leave a disease that could be treated go until a point that it could no longer be contained. Most illnesses when found early have a better survival rate.
ReplyDeleteI was going to say...I wonder if diet is one of the issues too. In general in the United States, we're pretty unhealthy, but it is interesting to see the red mostly in southern states where, like Jen said, fried foods and such are more popular than up north. Also, the morbidity rate for women in the United States (and around the world really) has for some time been higher than the morbidity rate for men; meaning women may in general be living longer than men but they are living longer while suffering from illnesses or disabilities, which certainly at times can have to do with gender roles/issues such as chronic diseases that affect women more than men. It would be interesting to see a similar map looking at morbidity to determine if changes in regards to men and women's morbidity are happening in a similar way.
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