PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
June 7, 2026Diabetes0 citations

2361-P: Rural–Urban Differences in Diabetes and Obesity Prevalence in the United States, 2018–2024

View Full Paper
MEMegan O. EzeudeMHMaryam HashemianGHGretell Henríquez-Santos

Key Result

Rural residence was associated with a higher prevalence of diabetes (PR 1.10-1.18) and obesity (PR 1.16-1.20) compared to urban residence among U.S. adults.

Key Points

  • This research aims to examine how rurality affects the prevalence of diabetes and obesity across different racial and ethnic groups in the U.S.
  • Analyzed cross-sectional data from the Behavioral Risk Factor Surveillance System (2018-2024)
  • Estimated age-adjusted prevalence and prevalence ratios (PRs) using survey-weighted Poisson regression
  • Included 2,971,000 participants with 14% residing in rural areas.
  • Rural residents had a higher diabetes prevalence of 10-18% compared to urban residents (PR: 1.10-1.18)
  • Obesity prevalence in rural areas was 16-20% versus urban areas (PR: 1.16-1.20)
  • Significant differences were particularly noted among non-Hispanic Black and White adults, with the highest rates in non-Hispanic Black adults.

Study Design

Type

Cross-Sectional (n=2,971,000)

Multicenter

Yes

Structured PICO

Does rural residence affect the prevalence of diabetes and obesity in U.S. adults compared to urban residence?

P
Population
2,971,000 U.S. adults from a nationally representative survey (2018-2024) analyzed for rural-urban differences in diabetes and obesity prevalence.
E
Exposure
Rural residence
C
Comparator
Urban residence
O
Outcome
Prevalence of diabetes and obesity

Rural residents in the U.S. experience a persistently higher burden of diabetes and obesity compared to urban residents, particularly among non-Hispanic Black and White adults.

Main Result

Effect estimate: PR 1.10-1.18 (diabetes); PR 1.16-1.20 (obesity)

Abstract

Introduction and Objective: Geographic differences continue to shape chronic diseases patterns in the United States. Despite improvements in prevention and disease management, rural-urban disparities in cardiometabolic conditions persist and remain poorly characterized. This study examines the association between rurality and the prevalence of diabetes and obesity by race and ethnicity among U.S. adults. Methods: We analyzed cross-sectional data (2018-2024) of the Behavioral Risk Factor Surveillance System, a nationally representative survey of self-reported health conditions and behaviors. Survey-weighted Poisson regression with robust variance was used to estimate age-adjusted prevalence and prevalence ratios (PRs) by rurality and race stratification. Results: Among 2,971,000 participants, 14% lived in rural areas. Rural residents had a higher diabetes (10-18%) and obesity (16-20%) prevalence than urban residents (PR: 1.10-1.18; 1.16-1.20). Differences were stable over time and significant among non-Hispanic (NH) Black and White adults, with the highest prevalence among NH Black adults. Differences were variable or absent in other racial groups. Conclusion: Over the past 7 years, rural residents have experienced a higher burden of diabetes and obesity, with the most persistently large differences among NH Black and White adults. These findings underscore the critical role of place-based factors and the need for targeted efforts to improve cardiometabolic health. Disclosure M.O. Ezeude: None. M. Hashemian: None. G. Henriquez-Santos: None. V.L. Roger: None.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Ezeude et al. (2026) conducted a cross-sectional in Diabetes and obesity (n=2,971,000). Rural residence vs. Urban residence was evaluated on Prevalence of diabetes and obesity (PR 1.10-1.18 (diabetes); PR 1.16-1.20 (obesity)). Rural residence was associated with a higher prevalence of diabetes (PR 1.10-1.18) and obesity (PR 1.16-1.20) compared to urban residence among U.S. adults.

synapsesocial.com/papers/6a250ae37def13d035e1ae9fhttps://doi.org/10.2337/db26-2361-p
Ask AI
Helpful
Bookmark
Share
View Full Paper