Monday, April 29, 2013

Could Facebook Assist Public Health Efforts to Track Obesity?

Analyzing Facebook users' interests could help public health researchers predict, track and map obesity rates in specific cities, towns and neighborhoods across the United States, a new study says. This type of information could be used to design targeted online programs meant to reduce obesity rates in specific locations, the researchers said. They analyzed data about the interests of Facebook users nationally and in New York City and compared that with data from a national health survey and another survey conducted in New York City. Areas with higher percentages of people with interests linked to a healthy, active lifestyle tend to have lower obesity rates, while areas with greater percentages of people with TV-related interests tend to have higher rates of obesity, according to the study, which was published April 24, 2013, in the journal PLoS ONE. Among the specific findings were the following: 1. Nationally, the obesity rate was 12 percent lower in the location with the highest percentage of Facebook users with activity-related interests (Coeur d'Alene, Idaho) than in the location with the lowest percentage (Kansas City, in both Missouri and Kansas). 2. The obesity rate was nearly 4 percent higher in the location with the highest percentage of Facebook users with TV-related interests (the Myrtle Beach/Conway/North Myrtle Beach area of South Carolina) than in the location with the lowest percentage (Eugene/Springfield, Oregon). 3. In New York City, the obesity rate was about 7 percent lower in the neighborhood with the highest percentage of Facebook users with activity-related interests (Coney Island, in Brooklyn) than the one with the lowest percentage (southwest Queens). 4. The obesity rate in the New York City neighborhood with the highest percentage of Facebook users with TV-related interests (northeast Bronx) was 28 percent higher than in the neighborhood with the lowest percentage (Greenpoint, in Brooklyn). "Online social networks like Facebook represent a new high-value, low-cost data stream for looking at health at a population level," study co-leader John Brownstein, who runs the computational epidemiology group at Boston Children's Hospital's informatics program, said in a hospital news release. The tight correlation between Facebook users' interests and obesity data suggest that this kind of social-network analysis could help generate real-time estimates of obesity levels in an area, help target public health campaigns that would promote healthy behavior change and assess the success of those campaigns.

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