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

Obesity and Nutrition as Public Health Problem (304) Machine Learning (1465) GIS (Geographic Information Systems) Applications in Public Health and Spatial Epidemiology (111) Obesity (75) Prevention and Health Promotion (987) Equity and Digital Divide (218) Demographics of Users, Social & Digital Divide (739) Chronic Conditions (270)

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 (9) Tweetations (4) Metrics

Whitney S Brakefield   1, 2 , PhD ;   Olufunto A Olusanya   2 , MPH, MD, PhD ;   Arash Shaban-Nejad   2 , MPH, PhD

1 Bredesen Center for Data Science and Engineering, University of Tennessee, Knoxville, TN, United States

2 Center for Biomedical Informatics, Department of Pediatrics, College of Medicine, University of Tennessee Health Science Center, Memphis, TN, United States

Corresponding Author:

  • Arash Shaban-Nejad, MPH, PhD
  • Center for Biomedical Informatics
  • Department of Pediatrics
  • College of Medicine, University of Tennessee Health Science Center
  • 50 N Dunlap Street, 491R
  • Memphis, TN, 38103
  • United States
  • Phone: 1 901-287-5836
  • Email: ashabann@uthsc.edu