BACKGROUND: An understanding of dietary patterns in diverse populations may guide the development of food-based, rather than nutrient-based, recommendations. OBJECTIVE: We identified and determined predictors of dietary patterns in low-income black and Hispanic adults with diagnosed diabetes. DESIGN: A food-frequency questionnaire was used to assess dietary intake in 235 adults living in the South Bronx, New York City, NY. We used principal factor analysis with promax rotation to identify dietary patterns. Multivariate linear regression models were used to test associations between demographic variables and dietary pattern scores. RESULTS: The following 5 dietary patterns were identified: pizza and sweets, meats, fried foods, fruit and vegetables, and Caribbean starch. The Caribbean starch and fruit and vegetables patterns were high in fruit and vegetables and low in trans fats. In multivariate analyses, sex, language spoken, years living in the United States, and region of birth were significant predictors of dietary patterns. Compared with English speakers, Spanish speakers were less likely to have high scores in pizza and sweets (P = 0.001), meat (P = 0.004), and fried food (P = 0.001) patterns. Participants who lived longer in the United States were less likely to have a meat (P = 0.024) or Caribbean starch pattern (P < 0.001). In Hispanics, the consumption of foods in the Caribbean starch pattern declined for each year that they lived in the United States. CONCLUSIONS: In adults with diagnosed diabetes who were living in the South Bronx, a Caribbean starch pattern, which included traditional Hispanic and Caribbean foods, was consistent with a healthier dietary pattern. In developing dietary interventions for this population, one goal may be to maintain healthy aspects of traditional diets. This trial was registered at clinicaltrials.gov as NCT00797888.
RCT Entities:
BACKGROUND: An understanding of dietary patterns in diverse populations may guide the development of food-based, rather than nutrient-based, recommendations. OBJECTIVE: We identified and determined predictors of dietary patterns in low-income black and Hispanic adults with diagnosed diabetes. DESIGN: A food-frequency questionnaire was used to assess dietary intake in 235 adults living in the South Bronx, New York City, NY. We used principal factor analysis with promax rotation to identify dietary patterns. Multivariate linear regression models were used to test associations between demographic variables and dietary pattern scores. RESULTS: The following 5 dietary patterns were identified: pizza and sweets, meats, fried foods, fruit and vegetables, and Caribbean starch. The Caribbean starch and fruit and vegetables patterns were high in fruit and vegetables and low in trans fats. In multivariate analyses, sex, language spoken, years living in the United States, and region of birth were significant predictors of dietary patterns. Compared with English speakers, Spanish speakers were less likely to have high scores in pizza and sweets (P = 0.001), meat (P = 0.004), and fried food (P = 0.001) patterns. Participants who lived longer in the United States were less likely to have a meat (P = 0.024) or Caribbean starch pattern (P < 0.001). In Hispanics, the consumption of foods in the Caribbean starch pattern declined for each year that they lived in the United States. CONCLUSIONS: In adults with diagnosed diabetes who were living in the South Bronx, a Caribbean starch pattern, which included traditional Hispanic and Caribbean foods, was consistent with a healthier dietary pattern. In developing dietary interventions for this population, one goal may be to maintain healthy aspects of traditional diets. This trial was registered at clinicaltrials.gov as NCT00797888.
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