Evidence map›Paper›PMID 40921070›Full record

ArticleJMIR public health and surveillance2025

Impact of Commercial Food Environments on Local Type 2 Diabetes Burden: Cross-Sectional and Ecological Multimodeling Study.

Kurubaran Ganasegeran, Mohd Rizal Abdul Manaf, Lance A Waller, Nazarudin Safian, Muhammad Faid Mohd Rizal, Wye Lee Chiew, Feisul Mustapha, Khairul Nizam Abdul Maulud

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Observational
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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

8 authors.

Kurubaran Ganasegeran *Department of Public Health Medicine, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.ORCID 0000-0002-9480-1815
Mohd Rizal Abdul Manaf *Department of Public Health Medicine, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.ORCID 0000-0002-0813-8376
Lance A Waller *Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, United States.ORCID 0000-0001-5002-8886
Nazarudin SafianDepartment of Public Health Medicine, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.ORCID 0000-0001-5962-3518
Muhammad Faid Mohd RizalEarth Observation Centre (EOC), Institute of Climate Change, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia.ORCID 0009-0005-1402-8818
Wye Lee ChiewPenang State Health Department, Ministry of Health Malaysia, Georgetown, Penang, Malaysia.ORCID 0000-0002-8654-4222
Feisul MustaphaPerak State Health Department, Ministry of Health Malaysia, Ipoh, Perak, Malaysia.ORCID 0000-0003-3497-341X
Khairul Nizam Abdul MauludEarth Observation Centre (EOC), Institute of Climate Change, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia.ORCID 0000-0002-9215-2778

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNeighborhoods resulting from rapid urbanization processes are often saturated with eateries for local communities, potentially increasing exposure to unhealthy foods and creating diabetogenic residential habitats.

objectiveWe examined the association between proximity of commercial food outlets to local neighborhood residences and type 2 diabetes (T2D) cases to explore how local T2D rates vary by location and provide policy-driven metrics to monitor food outlet density as a potential control for high local T2D rates.

methodsThis cross-sectional ecological study included 11,354 patients with active T2D aged ≥20 years geocoded using approximate neighborhood residence aggregated to area-level rates and counts by subdistricts (mukims) in Penang, northern Malaysia. We used the National Diabetes Registry complemented with data from medical records across 29 primary care clinics throughout the state. Food establishment data were retrieved from the Open Data Portal sourced through the Penang GeoHub, and urbanization indicators were retrieved from MyCensus 2020. We executed point-level proximity- and density-based area-level analysis through multimodel aspatial and spatial regression methods.

resultsOur final hierarchical linear regression revealed that the distance to food complexes, hawker markets, kopitiams (a type of coffee shop), 24-7 convenience stores, fast food outlets, and public markets showed statistically significant associations (P<.05) with the age and BMI of patients with T2D. In the multiscale geographically weighted regression model, the adjusted R

conclusionsThe reported variations provide insights into the associations between high neighborhood T2D rates and the density of a range of food outlets. We observed that these associations varied by place, providing insight into potential monitoring and policy considerations. This work provides evidence for interpretation at the individual and aggregate levels, shifting public health interventions from a generic to a targeted approach and prompting township planners to restructure food outlet accessibility or availability in local neighborhoods and to develop health behavior interventions for local communities for healthy food purchase and consumption.

Indexed as

CommerceDiabetes Mellitus, Type 2Food SupplyNeighborhood CharacteristicsAdultAgedCross-Sectional StudiesFemaleHumansMalaysiaMaleMiddle AgedResidence CharacteristicsRestaurantsattributable fractiondiabeteshealthlocal eateriesneighborhoodpoliciesspatialtownshipurbanization

Identifiers

PMID40921070
PMCPMC12455153

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LicenceCC BY
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Registered trials

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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.