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Social media captures demographic and regional physical activity
  1. Nina Cesare1,2,
  2. Quynh C Nguyen3,
  3. Christan Grant4,
  4. Elaine O Nsoesie1,2
  1. 1Department of Global Health, Boston University School of Public Health, Boston, Massachusetts, USA
  2. 2Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA
  3. 3Department of Epidemiology and Biostatistics, University of Maryland School of Public Health, College Park, Maryland, USA
  4. 4School of Computer Science, University of Oklahoma, Norman, Oklahoma, USA
  1. Correspondence to Dr Nina Cesare; ncesare{at}


Objectives We examined the use of data from social media for surveillance of physical activity prevalence in the USA.

Methods We obtained data from the social media site Twitter from April 2015 to March 2016. The data consisted of 1 382 284 geotagged physical activity tweets from 481 146 users (55.7% men and 44.3% women) in more than 2900 counties. We applied machine learning and statistical modelling to demonstrate sex and regional variations in preferred exercises, and assessed the association between reports of physical activity on Twitter and population-level inactivity prevalence from the US Centers for Disease Control and Prevention.

Results The association between physical inactivity tweet patterns and physical activity prevalence varied by sex and region. Walking was the most popular physical activity for both men and women across all regions (15.94% (95% CI 15.85% to 16.02%) and 18.74% (95% CI 18.64% to 18.88%) of tweets, respectively). Men and women mentioned performing gym-based activities at approximately the same rates (4.68% (95% CI 4.63% to 4.72%) and 4.13% (95% CI 4.08% to 4.18%) of tweets, respectively). CrossFit was most popular among men (14.91% (95% CI 14.52% to 15.31%)) among gym-based tweets, whereas yoga was most popular among women (26.66% (95% CI 26.03% to 27.19%)). Men mentioned engaging in higher intensity activities than women. Overall, counties with higher physical activity tweets also had lower leisure-time physical inactivity prevalence for both sexes.

Conclusions The regional-specific and sex-specific activity patterns captured on Twitter may allow public health officials to identify changes in health behaviours at small geographical scales and to design interventions best suited for specific populations.

  • social media
  • public health
  • digital data
  • physical inactivity

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:

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  • Contributors EON designed the study. QCN provided data and helped guide the analyses. CG guided data management and processing. NC and EON conducted the analyses, and wrote the initial draft of the paper. All authors edited the paper.

  • Funding NC, CG and EON are supported by a grant (#73362) from the Robert Wood Johnson Foundation. QCN is supported by National Institutes of Health grant 5K01ES025433.

  • Competing interests None.

  • Patient consent for publication Not required.

  • Ethics approval The study was declared exempt by the University of Washington Institutional Review Board.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data are available upon reasonable request.

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