Obesity and Weather
3:40 pm
Wed June 25, 2014

Study: The Hottest and Coldest U.S. Places are Also the Fattest

Rising summer temperatures could lead to expanded waistlines, according to a study announced today by University of Texas researchers.

Research from Paul von Hippel, an assistant professor at the LBJ School of Public Affairs, has shown that adults living in counties with the highest and lowest temperatures are the least active and by extension, the most obese. This especially holds true for areas with humid summers and dark winters.

Hippel and co-author Rebecca Benson, a UT doctoral student, studied each of the 3,000 counties in the United States, assessing different variables that could predict why some counties were more obese than others. Many of the counties in the Southeast account for areas with the highest rates of obesity. The mountain West, with cool, dry summers, represents the lowest proportion of obese adults.

Hippel concedes it seems obvious that weather would play a significant role in adults’ workout habits, but he says his study looked at other seemingly obvious assumptions that didn’t pan out. He says terrain is one expectation that doesn’t actually affect activity level as much as one might presume.

“For every example like Colorado, where you’ve got high mountains and very active adults who are rarely obese, you’ve got another example like West Virginia, which also has mountains but has lower levels of activity and higher levels of obesity,” he says.

City planners must do a better job considering year-round temperatures during project plans according to Hippel. He cites ample shade along the Lady Bird Lake hike and bike trail as promoting healthy activity during summer months – but he also notes examples that fail to consider regional climates.

“If you live in a hot, muggy area, you’ve got to think about what citizens are going to be willing to do in the summer,” he says. “So just painting a stripe on some hot asphalt and thinking that people are going to use it for biking, it may not be realistic. It might work in February. It might not work in July.”

Hippel and Benson’s study controlled for demographics that could affect the results including income, ethnicity, and unemployment. The study appears in the American Journal of Public Health.