This paper is in the following e-collection/theme issue:

Obesity and Nutrition as Public Health Problem (281) Machine Learning (1401) GIS (Geographic Information Systems) Applications in Public Health and Spatial Epidemiology (95) Obesity (62) Prevention and Health Promotion (899) Equity and Digital Divide (176) Demographics of Users, Social & Digital Divide (685) Chronic Conditions (219)

Published on in Vol 8, No 8 (2022): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37039, first published .
Association Between Neighborhood Factors and Adult Obesity in Shelby County, Tennessee: Geospatial Machine Learning Approach

Association Between Neighborhood Factors and Adult Obesity in Shelby County, Tennessee: Geospatial Machine Learning Approach

Association Between Neighborhood Factors and Adult Obesity in Shelby County, Tennessee: Geospatial Machine Learning Approach

Authors of this article:

Whitney S Brakefield1, 2 Author Orcid Image ;   Olufunto A Olusanya2 Author Orcid Image ;   Arash Shaban-Nejad2 Author Orcid Image
Article Authors Cited by (6) Tweetations (5) Metrics

Journals

  1. Vo A, Tao Y, Li Y, Albarrak A. The Association Between Social Determinants of Health and Population Health Outcomes: Ecological Analysis. JMIR Public Health and Surveillance 2023;9:e44070 View
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  4. Salerno P, Qian A, Dong W, Deo S, Nasir K, Rajagopalan S, Al‐Kindi S. County‐level socio‐environmental factors and obesity prevalence in the United States. Diabetes, Obesity and Metabolism 2024;26(5):1766 View
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  6. Kumsa F, Fowke J, Hashtarkhani S, White B, Shrubsole M, Shaban-Nejad A. The association between neighborhood obesogenic factors and prostate cancer risk and mortality: the Southern Community Cohort Study. Frontiers in Oncology 2024;14 View