Tanvi Misra is a staff writer for CityLab covering immigrant communities, housing, economic inequality, and culture. She also authors Navigator, a weekly newsletter for urban explorers (subscribe here). Her work also appears in The Atlantic, NPR, and BBC.
When it comes to this condition, place matters.
One-third of adult Americans are obese. While it’s all too easy to dismiss obesity as a personal failure, doctors know it’s caused by a mix of biological and social factors. Poverty, race, access to healthy food, walkability, and access to public spaces have all been linked to the incidence of obesity—some more consistently than others.
What’s clear from the full body of research is that when it comes to this public health concern, place matters. To understand the environmental factors that contribute to the condition, the nonprofit research institute RTI International has created a new map that spotlights the at-risk population in neighborhoods across America.
"Although obesity is a national problem, many of the policies and interventions that would be most valuable in reducing obesity occur at the community or neighborhood level," Bill Wheaton, director of RTI’s Geospatial Science and Technology Program, said in a press release.
The RTI map contains three layers of data. The first shows the share of adult population that’s obese within each 250-meter grid cell in the nation. Take the New York-New Jersey metro area below. The warmer the colors, the greater the share of obese adults in that region:
The second and third layers show (using different analytical approaches) hot spots where local obesity is much higher than the nation average. Through spatial cluster analyses, the researchers at RTI point out that these hot spots aren’t just random occurrences—they’re statistically significant. In other words, there’s something happening in these particular neighborhoods that’s fueling the high obesity rates.
Check out the areas of concern around Newark and the Bronx, filtered in the second-layer map below. The warmer regions show the clusters that are highly likely to be statistically significant:
Here’s how RTI hopes the map will be used by the research community:
They can choose areas that match both the demographics AND the extent of the obesity program they are evaluating. Thus, program evaluators can measure apples to apples.