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Public Health. 2017 Jul;148:120-128. doi: 10.1016/j.puhe.2017.03.013. Epub 2017 May 4.

Social media indicators of the food environment and state health outcomes.

Author information

1
Department of Health, Kinesiology, and Recreation, College of Health, University of Utah, Salt Lake City, United States. Electronic address: quynh.nguyen@health.utah.edu.
2
Department of Health, Kinesiology, and Recreation, College of Health, University of Utah, Salt Lake City, United States.
3
Center for Systems Integration and Sustainability, Michigan State University, East Lansing, United States.
4
School of Computing, University of Utah, Salt Lake City, United States.
5
Department of Geography, University of Utah, Salt Lake City, United States.
6
Department of Epidemiology and Biostatistics, UCSF School of Medicine, San Francisco, United States.

Abstract

OBJECTIVES:

Contextual factors can influence health through exposures to health-promoting and risk-inducing factors. The aim of this study was to (1) build, from geotagged Twitter and Yelp data, a national food environment database and (2) to test associations between state food environment indicators and health outcomes.

STUDY DESIGN:

This is a cross-sectional study based upon secondary analyses of publicly available data.

METHODS:

Using Twitter's Streaming Application Programming Interface (API), we collected and processed 4,041,521 food-related, geotagged tweets between April 2015 and March 2016. Using Yelp's Search API, we collected data on 505,554 unique food-related businesses. In linear regression models, we examined associations between food environment characteristics and state-level health outcomes, controlling for state-level differences in age, percent non-Hispanic white, and median household income.

RESULTS:

A one standard deviation increase in caloric density of food tweets was related to higher all-cause mortality (+46.50 per 100,000), diabetes (+0.75%), obesity (+1.78%), high cholesterol (+1.40%), and fair/poor self-rated health (2.01%). More burger Yelp listings were related to higher prevalence of diabetes (+0.55%), obesity (1.35%), and fair/poor self-rated health (1.12%). More alcohol tweets and Yelp bars and pub listings were related to higher state-level binge drinking and heavy drinking, but lower mortality and lower percent reporting fair/poor self-rated health. Supplemental analyses with county-level social media indicators and county health outcomes resulted in finding similar but slightly attenuated associations compared to those found at the state level.

CONCLUSIONS:

Social media can be utilized to create indicators of the food environment that are associated with area-level mortality, health behaviors, and chronic conditions.

KEYWORDS:

Chronic disease; Data mining; Food and nutrition; Geography; Social determinants; Social media

PMID:
28478354
PMCID:
PMC5492981
DOI:
10.1016/j.puhe.2017.03.013
[Indexed for MEDLINE]
Free PMC Article

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