According to a study co-developed by John W. Ayers, a research professor in San Diego State University’s Graduate School of Public Health, along with researchers from Harvard University and Boston Children’s Hospital, user “likes” and posts on Facebook may give scientists an insight into how a person’s social environment impacts the obesity epidemic.
“It is very easy to draw the link between the McDonalds down the street or the unlit sidewalks leading to that McDonalds and the obesity epidemic, but what about the largely hidden social environment that may be more strongly linked to obesity? To understand this we turned to Facebook, the world’s largest online social network, and linked these data back to actual cities and neighborhoods,” Ayers said.
User interest data
The study, which was published online in PLOS ONE connected the dots between the social environment and obesity by linking aggregated Facebook user interest data — what users post to their timeline, "like" and share with others — to the obesity levels for 189 cities in the U.S. and 34 neighborhoods in New York City.
The comparison revealed close geographic relationships between Facebook interests and obesity rates. For instance, the obesity rates were 12 percent lower in Coeur d'Alene, Idaho, which had the highest percentage of Facebook users expressing activity-related interests than in Kansas City, Mo., which had the lowest percentage of Facebook users expressing activity-related interests.
Similarly, the obesity rate in Myrtle Beach, South Carolina, which had the highest percentage of users with television-related interests in the nation, was 3.9 percent higher than in Eugene-Springfield, Ore., which had the lowest percentage.
The same patterns were reflected in the New York City neighborhood data as well, showing that the approach can scale from national- to local-level data. The obesity rate on Coney Island, which had the highest percentage of activity-related interests in the city, was 7.2 percent lower than in Southwest Queens, the neighborhood with the lowest percentage.
At the same time, the obesity rate in Northeast Bronx, the neighborhood with the highest percentage of television-related interests, was 27.5 percent higher than in Greenpoint, the neighborhood with the lowest percentage.
Together, the conclusions suggest that knowledge of people's online interests within geographic areas may help public health researchers predict, track and map obesity rates down to the neighborhood level. The findings also offer an opportunity to design geotargeted interventions directly manipulating the social environment aimed at reducing obesity rates.
Observing social norms
“We hear a lot about how the ‘built environment,’ i.e. neighborhoods that have lots of fast food places, broken sidewalks, etcetera, can lead to obesity, but until now our understanding of the social environment in the obesity epidemic has been obscured,” said Ayers.
“By going online via Facebook we can directly observe the social norms that impact how we interact with the built environment, in real-time, with low cost and without the biases that are common to traditional telephone surveys.”