The higher the percentage of people in a city, town or neighbourhood
with Facebook interests suggesting a healthy, active lifestyle, the lower that
area's obesity rate.
At the same time, areas with a large percentage of Facebook
users with television-related interests tend to have higher rates of obesity.
Such are the conclusions of a study by Boston Children's Hospital researchers
comparing geotagged Facebook user data with data from national and New York
City-focused health surveys.
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 neighbourhood level, while
offering an opportunity to design geotargeted online interventions aimed at
reducing obesity rates.
How the research was
The study team, led by Rumi Chunara, PhD, and John
Brownstein, PhD, of Boston Children's Hospital's Informatics Program (CHIP),
published their findings on in PLOS ONE.
The amount of data available from social networks like
Facebook makes it possible to efficiently carry out research in cohorts of a
size that has until now been impractical. It also allows for deeper research
into the impact of the societal environment on conditions like obesity, research
that can be challenging because of cost, difficulties in gathering sufficient
sample sizes and the slow pace of data analysis and reporting using traditional
reporting and surveillance systems.
"Online social networks like Facebook represent a new
high-value, low-cost data stream for looking at health at a population
level," according to Brownstein, who runs the Computational Epidemiology
Group within CHIP.
"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."
To connect the dots between Facebook interests and obesity,
Chunara, Brownstein and their colleagues obtained aggregated Facebook user
interest data—what users post to their timeline, "like" and share
with others on Facebook—from users nationally and just within New York City.
They then compared the percentages of users interested in
healthy activities or television with data from two telephone-based health
surveys: the US Centers for Disease Control and Prevention's Behavioral Risk
Factor Surveillance System-Selected Metropolitan/Micropolitan Area Risk Trends
(BRFSS-SMART), and New York City's EpiQuery Community Health Survey (CHS). Both
surveys record geotagged data on body mass index, a reliable measure of
What the study found
The comparison revealed close geographic relationships
between Facebook interests and obesity rates. For instance, the BRFSS-SMART
obesity rates were 12% lower in the location in the United States where the
highest percentage of Facebook users expressing activity-related interests
(Coeur d'Alene, Idaho) compared that in the location with the lowest percentage
(Kansas City, Mo.-Kan.). Similarly, the obesity rate in the location with the
highest percentage of users with television-related interests nationally
(Myrtle Beach-Conway-North Myrtle Beach, S.C.) was 3.9% higher than the
location with the lowest percentage (Eugene-Springfield, Ore.).
The same correlation was reflected in the New York City neighbourhood
data as well, showing that the approach can scale from national- to local-level
data. The CHS-reported obesity rate on Coney Island, which had the highest
percentage of activity-related interests in the city, was 7.2 percent lower
than Southwest Queens, the neighbourhood with the lowest percentage. At the
same time, the obesity rate in Northeast Bronx, the neighbourhood with the
highest percentage of television-related interests, was 27.5 percent higher
than that in the neighbourhood with the lowest percentage (Greenpoint).
"The data show that in places where Facebook users have
more activity-related interests, there is a lower prevalence of obesity and
overweight," said Chunara, an instructor in Brownstein's group. "They
reveal how social media data can augment public health surveillance by giving
public health researchers access to population-level information that they
can't otherwise get."
The study also bolsters the case for using social media as a
means of delivering targeted interventions aimed at reducing rates of obesity
and other chronic diseases, as applicable.