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Correlation Isn't Causation, But...
The correlation between diabetes and obesity rates on the one hand, and sedentary lifestyles/car commuting on the other, is certainly fascinating.
Two researchers at Planetizen created county-by-county maps of diabetes, obesity, and car-commuting rates across the United States, and found that the former two conditions correlate strongly with the latter, with diabetes, obesity, and car commuting, including carpools, most prevalent in the Southeast US and Appalachia.
First, obesity:
Diabetes:
And commute modes, with higher percentages of people who drive to work represented in yellow, orange, and red.
Similarly, the rates of biking and walking to work tend to be inversely proportional to obesity and diabetes rates, and higher median incomes and education levels correlate to lower rates of obesity and diabetes. In general. As Planetizen notes,
Interestingly, unemployment is the one negative factor Planetizen looked at that does not correlate with obesity. And, again, correlation does not necessarily imply causation. Obesity and diabetes rates among residents of the Appalachians and Deep South could be impacted just as heavily by factors like lack of access to fresh food, stress, regional culture, and sedentary hobbies as they are by the fact that those residents are more likely to drive. Still, the correlation definitely a part of the story.
Commuting statistics are from the Census Bureau, and obesity and diabetes stats are from the Centers for Disease Control.
Two researchers at Planetizen created county-by-county maps of diabetes, obesity, and car-commuting rates across the United States, and found that the former two conditions correlate strongly with the latter, with diabetes, obesity, and car commuting, including carpools, most prevalent in the Southeast US and Appalachia.
First, obesity:
Diabetes:
And commute modes, with higher percentages of people who drive to work represented in yellow, orange, and red.
Similarly, the rates of biking and walking to work tend to be inversely proportional to obesity and diabetes rates, and higher median incomes and education levels correlate to lower rates of obesity and diabetes. In general. As Planetizen notes,
Although this map does not look exactly the same as the obesity and diabetes maps, there are some striking similarities. Throughout the Appalachians and the deep South, there is a pattern that we could call the “non-active transportation belt,” where the percentages of commuters who drive are highest. It covers a similar area to the “diabetes belt,” but also extends somewhat into Indiana, Ohio, and Michigan. Considering that one-third of the higher diabetes risk associated with living in the diabetes belt can be attributed to the modifiable risk factors of sedentary lifestyle and obesity, this map certainly suggests that commute mode may play an important part in the existence of the diabetes belt.
Interestingly, unemployment is the one negative factor Planetizen looked at that does not correlate with obesity. And, again, correlation does not necessarily imply causation. Obesity and diabetes rates among residents of the Appalachians and Deep South could be impacted just as heavily by factors like lack of access to fresh food, stress, regional culture, and sedentary hobbies as they are by the fact that those residents are more likely to drive. Still, the correlation definitely a part of the story.
Commuting statistics are from the Census Bureau, and obesity and diabetes stats are from the Centers for Disease Control.
