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Article: Twitter-derived neighborhood characteristics associated with obesity and diabetes

TitleTwitter-derived neighborhood characteristics associated with obesity and diabetes
Authors
Issue Date2017
Citation
Scientific Reports, 2017, v. 7, n. 1, article no. 16425 How to Cite?
AbstractNeighborhood 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.
Persistent Identifierhttp://hdl.handle.net/10722/324032
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorNguyen, Quynh C.-
dc.contributor.authorBrunisholz, Kimberly D.-
dc.contributor.authorYu, Weijun-
dc.contributor.authorMcCullough, Matt-
dc.contributor.authorHanson, Heidi A.-
dc.contributor.authorLitchman, Michelle L.-
dc.contributor.authorLi, Feifei-
dc.contributor.authorWan, Yuan-
dc.contributor.authorVanderslice, James A.-
dc.contributor.authorWen, Ming-
dc.contributor.authorSmith, Ken R.-
dc.date.accessioned2023-01-13T03:01:01Z-
dc.date.available2023-01-13T03:01:01Z-
dc.date.issued2017-
dc.identifier.citationScientific Reports, 2017, v. 7, n. 1, article no. 16425-
dc.identifier.urihttp://hdl.handle.net/10722/324032-
dc.description.abstractNeighborhood 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.-
dc.languageeng-
dc.relation.ispartofScientific Reports-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleTwitter-derived neighborhood characteristics associated with obesity and diabetes-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1038/s41598-017-16573-1-
dc.identifier.pmid29180792-
dc.identifier.pmcidPMC5703998-
dc.identifier.scopuseid_2-s2.0-85035355584-
dc.identifier.volume7-
dc.identifier.issue1-
dc.identifier.spagearticle no. 16425-
dc.identifier.epagearticle no. 16425-
dc.identifier.eissn2045-2322-
dc.identifier.isiWOS:000416308200033-

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