While such claims on some level make sense intuitively, they’re usually talked about in a manner that’s more anecdotal than empirical. So along those lines, the urban policy website Planetizen has gone a step further by analyzing the evidence that may suggest that cars are driving up rates of obesity and diabetes. And what they found was that throughout the heavy traffic regions of the U.S., people tended to be indeed heavier.
But that doesn’t necessarily prove anything. Let’s take a look.
To examine the link between driving and health, the researchers used commuting statistics from the Census Bureau collected from 2005 to 2009 and represented the information visually on various maps. The researchers wanted to see if a connection can be made by comparing them. In the maps above, you can see obesity and diabetes hot spots, which tended to be concentrated east of Texas and below the northeastern states.
Here now is a map that shows which regions has the most commuters who drive to work.
While the two maps do not match up exactly, there does appear to be correlation. But remember: correlation doesn’t necessarily mean causation. In the next few maps you’ll see quite a few confounding variables exist. For instance, biking is also popular in regions where obesity and diabetes is rampant. Socio-economic status may also potentially play a role.
What this analysis shows is that it’s ultimately really difficult, if not entirely inconclusive, to isolate one cause for obesity like a greater reliance on driving. However, it appears that cars may be one contributing factor among many others that all add up eventually.
Here’s what the researchers concluded:
As the Oct. 2011 article pointed out, the relationship between sedentary travel and health outcomes can be misleading when additional contributing factors are not taken into account. While it is not our intent to claim a direct causal link between transportation modes and obesity rates, it is hard to deny the existence of some geographic patterns.
The next avenue of study would be to determine how much of this pattern is actually attributable to transportation mode, versus the other factors we explored here, such as education and income, which are known to be key causal factors in health outcomes. Numerous other factors may have a cumulatively significant effect.
In addition to commute mode, these geographic patterns might be explained in part by factors such as:
- food choices
- sedentary hobbies
- unemployment rates
- regional culture
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