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1.
J Nutr Educ Behav ; 44(6): 539-47, 2012.
Article in English | MEDLINE | ID: mdl-22236493

ABSTRACT

OBJECTIVE: Examine whether neighborhood characteristics of racial composition, income, and rurality were related to distribution of Supplemental Nutrition Assistance Program (SNAP)-accepting stores in Leon County, Florida. DESIGN: Cross-sectional; neighborhood and food store data collected in 2008. SETTING AND PARTICIPANTS: Forty-eight census tracts as proxy of neighborhoods in Leon County, Florida. All stores and SNAP-accepting stores were identified from a commercial business directory and a United States Department of Agriculture SNAP-accepting store list, respectively (n = 288). MAIN OUTCOME MEASURES: Proportion of SNAP-accepting stores across neighborhoods. ANALYSIS: Descriptive statistics to describe distribution of SNAP-accepting stores by neighborhood characteristics. Proportions of SNAP-accepting stores were compared by neighborhood characteristics with Wilcoxon-Mann-Whitney and Kruskal-Wallis tests. RESULTS: Of 288 available stores, 45.1% accepted SNAP benefits. Of the 48 neighborhoods, 16.7% had no SNAP-accepting stores. Proportions of SNAP-accepting grocery stores were significantly different by neighborhood racial composition and income. Primarily black neighborhoods did not have any supermarkets. Results were mixed with regard to distribution of food stores and SNAP-accepting stores by neighborhood racial composition, income, and rurality. CONCLUSIONS AND IMPLICATIONS: This study suggests disparities in distribution of SNAP-accepting stores across neighborhood characteristics of racial composition, income, and rurality.


Subject(s)
Commerce/statistics & numerical data , Food Supply/statistics & numerical data , Income , Minority Groups/statistics & numerical data , Public Assistance , Residence Characteristics/statistics & numerical data , Cross-Sectional Studies , Florida , Health Status Disparities , Humans , Rural Population , Social Environment , Socioeconomic Factors , Statistics, Nonparametric
2.
Prev Chronic Dis ; 8(6): A140, 2011 Nov.
Article in English | MEDLINE | ID: mdl-22005633

ABSTRACT

INTRODUCTION: The availability of healthful foods varies by neighborhood. We examined the availability and price of more healthful foods by store type, neighborhood income level, and racial composition in a community with high rates of diet-related illness and death. METHODS: We used the modified Nutrition Environment Measures Survey in Stores to conduct this cross-sectional study in 2008. We surveyed 73 stores (29% supermarkets, 11% grocery stores, and 60% convenience stores) in Leon County, Florida. We analyzed the price and availability of foods defined by the 2005 Dietary Guidelines for Americans as "food groups to encourage." We used descriptive statistics, t tests, analysis of variance, and χ(2) tests in the analysis. RESULTS: Measures of availability for all more healthful foods differed by store type (P < .001). Overall, supermarkets provided the lowest price for most fresh fruits and vegetables, low-fat milk, and whole-wheat bread. Availability of 10 of the 20 fruits and vegetables surveyed, shelf space devoted to low-fat milk, and varieties of whole-wheat bread differed by neighborhood income level (P < .05), but no trends were seen for the availability or price of more healthful foods by neighborhood racial composition. CONCLUSION: Store type affects the availability and price of more healthful foods. In particular, people without access to supermarkets may have limited ability to purchase healthful foods. Nutrition environment studies such as this one can be used to encourage improvements in neighborhoods that lack adequate access to affordable, healthful food, such as advocating for large retail stores, farmer's markets, and community gardens in disadvantaged neighborhoods.


Subject(s)
Commerce/statistics & numerical data , Diet/standards , Food Supply/statistics & numerical data , Food/economics , Nutrition Policy , Rural Population , Commerce/classification , Commerce/economics , Costs and Cost Analysis , Cross-Sectional Studies , Florida , Food Supply/economics , Health Behavior , Humans , Retrospective Studies , Socioeconomic Factors
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