Association of community food environment and obesity among US adults: a geographical information system analysis.


Journal

Journal of epidemiology and community health
ISSN: 1470-2738
Titre abrégé: J Epidemiol Community Health
Pays: England
ID NLM: 7909766

Informations de publication

Date de publication:
02 2019
Historique:
received: 27 03 2018
revised: 19 09 2018
accepted: 17 10 2018
pubmed: 7 11 2018
medline: 3 6 2020
entrez: 7 11 2018
Statut: ppublish

Résumé

Emerging studies have investigated the contribution of food environment to obesity in the USA. However, the findings were inconsistent. Methodological explanations for the inconsistent findings included: (1) using individual store/restaurant exposure as food environment indicator, and (2) not accounting for non-stationarity assumption. This study aimed to describe the spatial distribution of obesity and examine the association between community food environment and obesity, and the variation of magnitude and direction of this association across the USA. Data from 20 897 adults who participated in the REasons for Geographic and Racial Differences in Stroke study and completed baseline assessment between January 2003 and October 2007 were eligible in analysis. Hot Spot analysis was used to assess the spatial distribution of obesity. The association between community food environment and obesity and the variation of this association across the USA were examined using global ordinary least squares regression and local geographically weighted regression. Higher body mass index (BMI) clusters were more likely to locate in socioeconomically disadvantaged, rural, minority neighbourhoods with a smaller population size, while lower BMI clusters were more likely to appear in more affluent, urban neighbourhoods with a higher percentage of non-Hispanic white residences. There was an overall significant, inverse association between community food environment and obesity (β=-0.0210; p<0.0001). Moreover, the magnitude and direction of this association varied significantly across the US regions. The findings underscored the need for geographically tailored public health interventions and policies to address unique local food environment issues to achieve maximum effects on obesity prevention.

Sections du résumé

BACKGROUND
Emerging studies have investigated the contribution of food environment to obesity in the USA. However, the findings were inconsistent. Methodological explanations for the inconsistent findings included: (1) using individual store/restaurant exposure as food environment indicator, and (2) not accounting for non-stationarity assumption. This study aimed to describe the spatial distribution of obesity and examine the association between community food environment and obesity, and the variation of magnitude and direction of this association across the USA.
METHODS
Data from 20 897 adults who participated in the REasons for Geographic and Racial Differences in Stroke study and completed baseline assessment between January 2003 and October 2007 were eligible in analysis. Hot Spot analysis was used to assess the spatial distribution of obesity. The association between community food environment and obesity and the variation of this association across the USA were examined using global ordinary least squares regression and local geographically weighted regression.
RESULTS
Higher body mass index (BMI) clusters were more likely to locate in socioeconomically disadvantaged, rural, minority neighbourhoods with a smaller population size, while lower BMI clusters were more likely to appear in more affluent, urban neighbourhoods with a higher percentage of non-Hispanic white residences. There was an overall significant, inverse association between community food environment and obesity (β=-0.0210; p<0.0001). Moreover, the magnitude and direction of this association varied significantly across the US regions.
CONCLUSIONS
The findings underscored the need for geographically tailored public health interventions and policies to address unique local food environment issues to achieve maximum effects on obesity prevention.

Identifiants

pubmed: 30397025
pii: jech-2018-210838
doi: 10.1136/jech-2018-210838
pmc: PMC9105746
mid: NIHMS1746145
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

148-155

Subventions

Organisme : NIDDK NIH HHS
ID : P30 DK056336
Pays : United States
Organisme : NINDS NIH HHS
ID : U01 NS041588
Pays : United States
Organisme : NIMHD NIH HHS
ID : U54 MD008176
Pays : United States

Informations de copyright

© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: None declared.

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Auteurs

Meifang Chen (M)

Department of Public Health, California State University, Los Angeles, California, USA.

Thomas Creger (T)

Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA.

Virginia Howard (V)

Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA.

Suzanne E Judd (SE)

Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA.

Kathy F Harrington (KF)

Department of Health Behavior, University of Alabama at Birmingham, Birmingham, USA.

Kevin R Fontaine (KR)

Department of Health Behavior, University of Alabama at Birmingham, Birmingham, USA.

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