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Journal article
The U.S. diabetes belt and factors explaining the excess risk: Multifactorial modeling and machine learning analysis
Primary care diabetes, v 20(1), pp 99-105
Feb 2026
PMID: 41381318
Featured in Collection : Research Supported by Drexel Libraries' OA Programs
Abstract
Aim
Research on the epidemiology of diabetes mellitus (DM) has identified a geographically distinct region in the United States (U.S.) known as the diabetes belt (DM Belt), which represents a significant public health concern. This study aimed to examine the factors contributing to the increased risk of DM in the DM Belt compared to the non-DM Belt.
Methods
Data were analyzed from 398,243 adults aged ≥ 18 years who participated in the 2019 Behavior Risk Factor Surveillance System. DM status was based on participants’ self-reported physician-diagnosed DM. The DM Belt was defined at the state level according to the U.S. Center for Disease Control and Prevention’s classification. Logistic regression (LR) was used to estimate odds ratios for DM and assess the excess DM risk in the DM Belt versus the non-DM Belt. Random Forest (RF) and stepwise LR were employed to identify and rank key contributors to the excess DM risk.
Results
Residents of the DM Belt had a significantly higher prevalence of DM than those in the non-DM Belt (age-sex-adjusted rate: 12.5 % versus 10.5 %, p < 0.001). Low socioeconomic status (SES), physical inactivity, and hypertension were identified as the top three factors explaining the excess DM risk in the DM Belt.
Conclusions
These findings underscore the importance of an integrated approach to improving SES, promoting healthy behaviors, managing chronic conditions for reducing DM risk. Addressing these factors can help mitigate health disparities in DM risk across the U.S.
Metrics
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Details
- Title
- The U.S. diabetes belt and factors explaining the excess risk: Multifactorial modeling and machine learning analysis
- Creators
- Longjian Liu (Corresponding Author) - Drexel University, Epidemiology and BiostatisticsNathalie S May - Drexel University, MD (Doctor of Medicine) ProgramYuwei Hou - Tulane UniversityJingyi Shi - Mississippi State UniversityEdward J Gracely - Drexel University, MD (Doctor of Medicine) ProgramArthur L Frank - Drexel University, Environmental and Occupational HealthHoward J Eisen - Thomas Jefferson University
- Publication Details
- Primary care diabetes, v 20(1), pp 99-105
- Publisher
- Elsevier
- Number of pages
- 7
- Grant note
This work was partially supported by grant from the National Institute on Aging (NIA: #1R21AG082210-01), and a grant from Drexel University Areas of Research Excellence-Cell2Society Aging Research Network (#284060) . This manuscript does not necessarily reflect the opinions or views of financial support from the NIA or Drexel University.
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- MD (Doctor of Medicine) Program; Epidemiology and Biostatistics; Environmental and Occupational Health
- Web of Science ID
- WOS:001684538100001
- Scopus ID
- 2-s2.0-105025108493
- Other Identifier
- 991022138983004721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Endocrinology & Metabolism
- Primary Health Care