Evidence map›Paper›PMID 42436658›Full record

ArticleLancet regional health. Americas2026

The obesity-related chronic disease index (ORCDi), a novel composite metric to quantify ORCD burden: an ecological study across U.S. census tracts.

Md Roungu Ahmmad, Fazlay Faruque, Xiaoli Zhang

Abstract read
In one paragraph

Article in Lancet regional health. Americas, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Md Roungu AhmmadUSF-Health, College of Nursing, University of South Florida, Tampa, FL, USA.
Fazlay FaruqueGeospatial Health Research Lab, Department of Preventive Medicine, University of Mississippi Medical Center, Jackson, MS, USA.
Xiaoli ZhangBiostatistics Core, USF Health, College of Nursing, University of South Florida, Tampa, FL, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Obesity contributes substantially to chronic disease multimorbidity in the U.S., yet no composite metric exists to quantify the cumulative burden of obesity-related chronic diseases at the community level. We aimed to develop and validate the obesity-related chronic disease index (ORCDi) and examine its spatial distribution and associations with social vulnerability domains. Methods: We used Centers for Disease Control and Prevention (CDC) PLACES 2024 estimates for nine obesity-related conditions across 83,522 U.S. census-tracts. Principal component analysis was applied to derive the ORCDi, and chronic disease properties were assessed using Cronbach's α, Guttman's λ6, item-total correlations, Bartlett's test, and Kaiser-Meyer-Olkin (KMO) adequacy. Convergent validity was evaluated using regression models against social vulnerability indices and rural-urban commuting area (RUCA). Spatial dependence and clustering or hotspots were assessed using Global Moran's I and Local Indicators of Spatial Association (LISA). Findings: The ORCDi demonstrated internal consistency (Cronbach's α = 0.94; Guttman's λ6 = 0.97) and a coherent factor structure (KMO = 0.81; Bartlett's χ Interpretation: The ORCDi is a composite measure of obesity-related chronic disease burden at the community level. The index demonstrated significant internal consistency, substantial geographic variation, and meaningful associations with socioeconomic disadvantage and rural health disparities. Future studies should evaluate its performance in independent datasets and assess its utility for public health surveillance and resource allocation. Funding: The study was not supported by external funding.

Indexed as

Obesity-related multimorbidityORCDPrecision public healthPrincipal component analysisSocial vulnerability

Identifiers

PMID42436658
PMCPMC13355215

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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.