Diabetes, obesity, and recommended fruit and vegetable consumption in relation to food environment sub-types: a cross-sectional analysis of Behavioral Risk Factor Surveillance System, United States Census, and food establishment data.

Auteur(s) :
Frankenfeld CL., Leslie TF., Makara MA.
Date :
Mai, 2015
Source(s) :
BMC PUBLIC HEALTH.. #15:1 p491
Adresse :
Department of Global and Community Health, George Mason University, Fairfax, VA, 22030, USA. cfranken@gmu.edu

Sommaire de l'article

BACKGROUND: Social and spatial factors are an important part of individual and community health. The objectives were to identify food establishment sub-types and evaluate prevalence of diabetes, obesity, and recommended fruit and vegetable consumption in relation to these sub-types in the Washington DC metropolitan area.

METHODS: A cross-sectional study design was used. A measure of retail food environment was calculated as the ratio of number of sources of unhealthier food options (fast food, convenience stores, and pharmacies) to healthier food options (grocery stores and specialty food stores). Two categories were created: ≤ 1.0 (healthier options) and > 1.0 (unhealthier options). k-means clustering was used to identify clusters based on proportions of grocery stores, restaurants, specialty food, fast food, convenience stores, and pharmacies. Prevalence data for county-level diabetes, obesity, and consumption of five or more fruits or vegetables per day (FV5) was obtained from the Behavioral Risk Factor Surveillance System. Multiple imputation was used to predict block-group level health outcomes with US Census demographic and economic variables as the inputs.

RESULTS: The healthier options category clustered into three sub-types: 1) specialty food, 2) grocery stores, and 3) restaurants. The unhealthier options category clustered into two sub-types: 1) convenience stores, and 2) restaurants and fast food. Within the healthier options category, diabetes prevalence in the sub-types with high restaurants (5.9 %, p = 0.002) and high specialty food (6.1 %, p = 0.002) was lower than the grocery stores sub-type (7.1 %). The high restaurants sub-type compared to the high grocery stores sub-type had significantly lower obesity prevalence (28.6 % vs. 31.2 %, p < 0.001) and higher FV5 prevalence (25.2 % vs. 23.1 %, p < 0.001). Within the larger unhealthier options category, there were no significant differences in diabetes, obesity, or higher FV5 prevalence across the two sub-types. However, restaurants (including fast food) sub-type was significantly associated with lower diabetes and obesity, and higher FV prevalence compared to grocery store sub-type.

CONCLUSIONS: These results suggest that there are sub-types within larger categories of food environments that are differentially associated with adverse health outcomes. These observations support the specific food establishment composition of an area may be an important component of the food establishment-health relationship.

Source : Pubmed