142nd APHA Annual Meeting and Exposition

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#epidemiology: Ecological analysis of fast food tweets in relation to Behavioral Risk Factor Surveillance System data

142nd APHA Annual Meeting and Exposition (November 15 - November 19, 2014): http://www.apha.org/events-and-meetings/annual
Tuesday, November 18, 2014

Jay Christian, PhD, MPH , Department of Epidemiology, College of Public Health, University of Kentucky, Lexington, KY
Ate Poorthuis, MA , Department of Geography, University of Kentucky, Lexington, KY
Matthew Zook, PhD , Department of Geography, University of Kentucky, Lexington, KY
Recent public health research has described the use of Internet search engines and social media for tracking infectious disease.  Influenza, in particular, has attracted the attention of several researchers, who have developed statistical models of prevalence based upon the rate of geo-located tweets mentioning key words likely to be related to infection—“flu”, “H1N1”, “Tamiflu”, etc.  Such research has yielded encouraging results with regard to the utility of Twitter data for tracking health outcomes, but has not yet included analysis of outcomes in relation to exposures.  Furthermore, there are very few examples of researchers using Twitter to track chronic diseases or their related health behaviors. 

To explore these possibilities, we calculated the rate of geo-located tweets mentioning well-known fast food chains, for each state in the U.S., as a measure of the acceptability and popularity of fast food.  Using scatter plots and correlation coefficients, we then compared the rates of fast food tweets to the average number of fruit and vegetable servings consumed per day by respondents to the Behavioral Risk Factor Surveillance System (BRFSS).  We also conducted a parallel intra-state analysis using 41 regions of Kentucky developed specifically for aggregating BRFSS data.  Lastly, we repeated these analyses, but substituted rates of overweight and obesity for average fruit and vegetable intake.

The results of this study demonstrate that residents of U.S. states and regions of Kentucky with higher rates of fast food tweets consumed fewer fruit and vegetable servings per day on average (r=-0.52, p<0.0001; rho=-0.59, p=0.0001; respectively).   We observed weaker but still statistically significant trends in the analysis of overweight and obesity.  These results suggest analysis of Twitter data might be useful for tracking health behaviors related to chronic disease.

Learning Areas:

Assessment of individual and community needs for health education
Chronic disease management and prevention
Social and behavioral sciences

Learning Objectives:
Describe how data derived from Twitter posts can be quantified for use in tracking health behaviors. Identify U.S. states with high rates of fast food mentions on Twitter and poor dietary behaviors from BRFSS.

Keyword(s): Internet, Data Collection and Surveillance

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I have worked for over a decade as an epidemiologist, and have published several peer-reviewed articles using the BRFSS to examine health behaviors and outcomes in Kentucky and elsewhere. I conducted most analyses described in the research to be presented, and wrote the abstract submitted.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.