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Accepted for/Published in: JMIR Public Health and Surveillance

Date Submitted: Jan 29, 2020
Date Accepted: May 27, 2020

The final, peer-reviewed published version of this preprint can be found here:

Twitter-Derived Social Neighborhood Characteristics and Individual-Level Cardiometabolic Outcomes: Cross-Sectional Study in a Nationally Representative Sample

Huang D, Huang Y, Khanna S, Dwivedi P, Slopen N, Green K, He X, Puett R, Nguyen Q

Twitter-Derived Social Neighborhood Characteristics and Individual-Level Cardiometabolic Outcomes: Cross-Sectional Study in a Nationally Representative Sample

JMIR Public Health Surveill 2020;6(3):e17969

DOI: 10.2196/17969

PMID: 32808935

PMCID: 7485998

Twitter-derived social neighborhood characteristics and individual level cardiometabolic outcomes: a cross-sectional study in a nationally representative sample

  • Dina Huang; 
  • Yuru Huang; 
  • Sahil Khanna; 
  • Pallavi Dwivedi; 
  • Natalie Slopen; 
  • Kerry Green; 
  • Xin He; 
  • Robin Puett; 
  • Quynh Nguyen

ABSTRACT

Background:

Social media, such as Twitter, can serve as a potential data source for public health research to characterize the social neighborhood environment. Few studies have linked Twitter-derived characteristics to individual level health outcomes.

Objective:

This study aims to assess the association between Twitter-derived social neighborhood characteristics including happiness, food and physical activity mentions with individual cardiometabolic outcomes using a nationally representative sample.

Methods:

We collected a random 1% of the geotagged tweets from April 2015 to March 2016 utilizing Twitter’s Streaming Application Interface (API). Twitter-derived zip code characteristics on happiness, food and physical activity were merged to individual outcomes from restricted-use National Health and Nutrition Examination Survey (NHANES) with residential zip codes. Separate regression analyses were performed for each of the neighborhood characteristics using NHANES 2011-2016 and 2007-2016 at year 2018.

Results:

Individuals living zip codes with the two highest tertiles of happy tweets had body mass index (BMIs) that were 0.65-0.85 kg/m2 lower than those living in zip codes with the lowest frequency. Happy tweets were also associated with 6-8% lower hypertension prevalence. Higher prevalence of food tweets was linked with an 11% lower obesity prevalence. Those living in the two highest tertiles of physical activity tweets also had lower hypertension by 8-10%.

Conclusions:

Twitter-derived social neighborhood characteristics were associated with individual level obesity and hypertension, in a nationally representative sample of U.S. adults. Twitter data may have utility in capturing neighborhood sociocultural influences on chronic conditions and Twitter may be used as a platform for chronic outcomes prevention.


 Citation

Please cite as:

Huang D, Huang Y, Khanna S, Dwivedi P, Slopen N, Green K, He X, Puett R, Nguyen Q

Twitter-Derived Social Neighborhood Characteristics and Individual-Level Cardiometabolic Outcomes: Cross-Sectional Study in a Nationally Representative Sample

JMIR Public Health Surveill 2020;6(3):e17969

DOI: 10.2196/17969

PMID: 32808935

PMCID: 7485998

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