ArticleScientific reports2017
Twitter-derived neighborhood characteristics associated with obesity and diabetes.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Non-traditional data sources in obesity research: a systematic review of their use in the study of obesogenic environments.International journal of obesity (2005) · 2023Pooled it
- Environmental factors affecting the BMI of older adults in the Philippines spatially assessed using machine learning.Heliyon · 2025Article
- Neighborhood built environment, obesity, and diabetes: A Utah siblings study.SSM - population health · 2024Article
- Content and User Engagement of Health-Related Behavior Tweets Posted by Mass Media Outlets From Spain and the United States Early in the COVID-19 Pandemic: Observational Infodemiology Study.JMIR infodemiology · 2023Article
- Community characteristics and the risk of non-communicable diseases in Ghana.PLOS global public health · 2023Article
- Mediterranean Diet Social Network Impact along 11 Years in the Major US Media Outlets: Thematic and Quantitative Analysis Using Twitter.International journal of environmental research and public health · 2022Article
- Social media analytics in nutrition research: a rapid review of current usage in investigation of dietary behaviours.Public health nutrition · 2021Review
- [Medical applications of social networks. Specific aspects of the COVID-19 pandemic].Medicine · 2020Article
- Insulin pricing and other major diabetes-related concerns in the USA: a study of 46 407 tweets between 2017 and 2019.BMJ open diabetes research & care · 2020Article
- Uncovering the relationship between food-related discussion on Twitter and neighborhood characteristics.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- Article
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Authors and funding
11 authors.
Funding
Abstract
Neighborhood characteristics are increasingly connected with health outcomes. Social processes affect health through the maintenance of social norms, stimulation of new interests, and dispersal of knowledge. We created zip code level indicators of happiness, food, and physical activity culture from geolocated Twitter data to examine the relationship between these neighborhood characteristics and obesity and diabetes diagnoses (Type 1 and Type 2). We collected 422,094 tweets sent from Utah between April 2015 and March 2016. We leveraged administrative and clinical records on 1.86 million individuals aged 20 years and older in Utah in 2015. Individuals living in zip codes with the greatest percentage of happy and physically-active tweets had lower obesity prevalence-accounting for individual age, sex, nonwhite race, Hispanic ethnicity, education, and marital status, as well as zip code population characteristics. More happy tweets and lower caloric density of food tweets in a zip code were associated with lower individual prevalence of diabetes. Results were robust in sibling random effects models that account for family background characteristics shared between siblings. Findings suggest the possible influence of sociocultural factors on individual health. The study demonstrates the utility and cost-effectiveness of utilizing existing big data sources to conduct population health studies.
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