Evidence map›Paper›PMID 41390713›Full record

ArticleInternational journal of health geographics2025

Understanding regional disparities in obesity: a multiscale geographically weighted analysis in the United States.

Jonah K Amponsah, Jeffrey A Thompson, Shellie D Ellis

Abstract read
In one paragraph

Article in International journal of health geographics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Disparities of children's obesogenic environments in Louisiana.International journal of health geographics · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jonah K AmponsahCarbone Cancer Center, School of Medicine and Public Health, University of Wisconsin-Madison, 600 Highland Ave, Clinical Science Center, Madison, WI, 53792-0001, USA. amponsah2@wisc.edu.
Jeffrey A ThompsonDepartment of Biostatistics and Data Science, University of Kansas Medical Center, 3901 Rainbow Blvd, Kansas City, KS, 66160, USA.
Shellie D EllisInstitute for Clinical and Translational Research, School of Medicine and Public Health, University of Wisconsin-Madison, 750 Highland Ave, Clinical Science Center, Madison, WI, 53792-0001, USA.

Funding

RADx-UP: Improving the Response of Local Urban and Rural Communities to Disparities in Covid-19 TestingUL1TR002366 · NCATS · UNIVERSITY OF KANSAS MEDICAL CENTER · PI Mario Castro, JAMES STEVEN LEEDER · 2017 to 2026
$44.3M
Transgenic & Gene-Targeting Shared ResourceP30CA168524 · NCI · UNIVERSITY OF KANSAS MEDICAL CENTER · PI ROY A. JENSEN · 2012 to 2026
$40.1M
Using Integrated Omics to Identify Dysfunctional Genetic Mechanisms Influencing Schizophrenia and Sleep DisturbancesP20GM130423 · NIGMS · UNIVERSITY OF KANSAS MEDICAL CENTER · PI Kalyani Pyaram, Steven Allan Soper · 2019 to 2026
$21.5M
NCATS NIH HHS UL1 TR002366NCI NIH HHS P30 CA168524NIGMS NIH HHS P20 GM130423
6 · The paper itself

Abstract

Obesity varies markedly across U.S. counties, and global models often miss place-specific determinants. While prior studies document higher prevalence in nonmetropolitan areas, the geographic variation in its determinants-known as spatial heterogeneity-remains underexplored. We linked age-adjusted adult obesity prevalence with socioeconomic indicators, and behavioral risks for 3106 contiguous counties. A global OLS model served as a baseline, followed by estimation of Multiscale Geographically Weighted Regression (MGWR). MGWR outperformed global OLS (adjusted [Formula: see text]: 0.801 vs. 0.566; AICc: 13,580.92 vs. 15,764.21), confirming non-stationarity and revealing covariate-specific scales. Metropolitan status was generally protective, but its effect attenuated or reversed in parts of the West. Income and educational attainment are broadly inverse with minimal dispersion across counties, suggesting near-global behavior in this specification. Short sleep shows a strong positive association with little spread, while binge drinking is positive and slightly more variable. Employment is narrowly positive with almost no spatial dispersion. Bandwidth diagnostics separate near-global from local processes: metro and employment operate at large bandwidths, education and binge drinking at meso scales, and income, short sleep, and marriage at finer scales. As a benchmark, metro-only models showed a uniformly protective but locally varying metro effect that attenuated once socioeconomic and behavioral covariates were included. Findings confirm non-stationarity and argue for a two-tier translation: system-level policies for near-global factors and community-tailored interventions for localized risks, with attention to Western metropolitan vulnerabilities and Southeastern rural constraints.

Indexed as

Health Status DisparitiesObesityAdultFemaleHumansMaleMiddle AgedPrevalenceSocioeconomic FactorsSpatial AnalysisUnited StatesYoung AdultCounty-level analysisMGWRObesityRegional disparitiesSocioecological modelSpatial analysis

Identifiers

PMID41390713
PMCPMC12822080

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.