Emily Matchar at Smithsonian: “About 40 percent of American adults are obese, defined as having a body mass index (BMI) over 30. But obesity is not evenly distributed around the country. Some cities and states have far more obese residents than others. Why? Genetics, stress, income levels and access to healthy foods are play a role. But increasingly researchers are looking at the built environment—our cities—to understand why people are fatter in some places than in others.
New research from the University of Washington attempts to take this approach one step further by using satellite data to examine cityscapes. By using the satellite images in conjunction with obesity data, they hope to uncover which urban features might influence a city’s obesity rate.
The researchers used a deep learning network to analyze about 150,000 high-resolution satellite image of four cities: Los Angeles, Memphis, San Antonio and Seattle. The cities were selected for being from states with both high obesity rates (Texas and Tennessee) and low obesity rates (California and Washington). The network extracted features of the built environment: crosswalks, parks, gyms, bus stops, fast food restaurants—anything that might be relevant to health.
“If there’s no sidewalk you’re less likely to go out walking,” says Elaine Nsoesie, a professor of global health at the University of Washington who led the research.
The team’s algorithm could then see what features were more or less common in areas with greater and lesser rates of obesity. Some findings were predictable: more parks, gyms and green spaces were correlated with lower obesity rates. Others were surprising: more pet stores equaled thinner residents (“a high density of pet stores could indicate high pet ownership, which could influence how often people go to parks and take walks around the neighborhood,” the team hypothesized).
A paper on the results was recently published in the journal JAMA Network Open….(More)”.