Fast food, race/ethnicity, and income: a geographic analysis

• Published in: American journal of preventive medicine 2004-10, Vol.27 (3), p.211-217
• Main Authors: Block, Jason P, Scribner, Richard A, DeSalvo, Karen B
• Format: Article
• Language: English
• Subjects: Eating; Feeding Behavior - ethnology; Food - classification; Humans; Louisiana; Multivariate Analysis; Regression Analysis; Restaurants - statistics & numerical data; Socioeconomic Factors
• ISSN: 0749-3797
• DOI: 10.1016/j.amepre.2004.06.007

Environmental factors may contribute to the increasing prevalence of obesity, especially in black and low-income populations. In this paper, the geographic distribution of fast food restaurants is examined relative to neighborhood sociodemographics. Using geographic information system software, all fast-food restaurants within the city limits of New Orleans, Louisiana, in 2001 were mapped. Buffers around census tracts were generated to simulate 1-mile and 0.5-mile "shopping areas" around and including each tract, and fast food restaurant density (number of restaurants per square mile) was calculated for each area. Using multiple regression, the geographic association between fast food restaurant density and black and low-income neighborhoods was assessed, while controlling for environmental confounders that might also influence the placement of restaurants (commercial activity, presence of major highways, and median home values). In 156 census tracts, a total of 155 fast food restaurants were identified. In the regression analysis that included the environmental confounders, fast-food restaurant density in shopping areas with 1-mile buffers was independently correlated with median household income and percent of black residents in the census tract. Similar results were found for shopping areas with 0.5-mile buffers. Predominantly black neighborhoods have 2.4 fast-food restaurants per square mile compared to 1.5 restaurants in predominantly white neighborhoods. The link between fast food restaurants and black and low-income neighborhoods may contribute to the understanding of environmental causes of the obesity epidemic in these populations.