Objective: To identify predominant dietary patterns among Hispanic women and to determine whether adherence to dietary patterns is predicted by neighbourhood-level factors: linguistic isolation, poverty rate and the retail food environment. Design: Cross-sectional analyses of predictors of adherence to dietary patterns identified from principal component analysis of data collected using the Study of Women's Health Across the Nation FFQ. Census data were used to measure poverty rates and the percentage of Spanish-speaking families in the neighbourhood in which no person aged ≥14 years spoke English very well (linguistic isolation) and the retail food environment was measured using business listings data. Setting: New York City. Subjects: A total of 345 Hispanic women. Results: Two major dietary patterns were identified: a healthy dietary pattern loading high for vegetables, legumes, potatoes, fish and other seafood, which explained 17 % of the variance in the FFQ data and an energy-dense dietary pattern loading high for red meat, poultry, pizza, french fries and high-energy drinks, which explained 9 % of the variance in the FFQ data. Adherence to the healthy dietary pattern was positively associated with neighbourhood linguistic isolation and negatively associated with neighbourhood poverty. Presence of more fast-food restaurants per square kilometre in the neighbourhood was significantly associated with lower adherence to the healthy diet. Adherence to the energy-dense dietary pattern was inversely, but not significantly, associated with neighbourhood linguistic isolation. Conclusions: These results are consistent with the hypothesis that living in immigrant enclaves is associated with healthy dietary patterns among Hispanics. © 2011 The Authors.
CITATION STYLE
Park, Y., Neckerman, K., Quinn, J., Weiss, C., Jacobson, J., & Rundle, A. (2011). Neighbourhood immigrant acculturation and diet among Hispanic female residents of New York City. Public Health Nutrition, 14(9), 1593–1600. https://doi.org/10.1017/S136898001100019X
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