Albert Einstein College of Medicine, Bronx, NY, USA.
Am J Clin Nutr. 2013 Apr;97(4):878-85. doi: 10.3945/ajcn.112.051185. Epub 2013 Feb 27.
An understanding of dietary patterns in diverse populations may guide the development of food-based, rather than nutrient-based, recommendations.
We identified and determined predictors of dietary patterns in low-income black and Hispanic adults with diagnosed diabetes.
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.
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.
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.
了解不同人群的饮食模式可能有助于制定基于食物而非营养素的建议。
我们确定并确定了诊断患有糖尿病的低收入黑人和西班牙裔成年人饮食模式的预测因素。
使用食物频率问卷评估 235 名居住在纽约市南布朗克斯的成年人的饮食摄入情况。我们使用主成分分析和 promax 旋转来识别饮食模式。使用多元线性回归模型来测试人口统计学变量与饮食模式评分之间的关联。
确定了以下 5 种饮食模式:披萨和甜食、肉类、油炸食品、水果和蔬菜以及加勒比淀粉。加勒比淀粉和水果和蔬菜模式富含水果和蔬菜,反式脂肪含量低。在多元分析中,性别、使用的语言、在美国生活的年数和出生地是饮食模式的重要预测因素。与讲英语的人相比,讲西班牙语的人不太可能在披萨和甜食(P = 0.001)、肉类(P = 0.004)和油炸食品(P = 0.001)模式中获得高分。在美国生活时间较长的参与者不太可能出现肉类(P = 0.024)或加勒比淀粉模式(P < 0.001)。在西班牙裔中,他们在美国生活的每一年,食用加勒比淀粉模式的食物量都会减少。
在居住在南布朗克斯的诊断患有糖尿病的成年人中,一种包含传统西班牙裔和加勒比食物的加勒比淀粉模式与更健康的饮食模式一致。在为这一人群制定饮食干预措施时,一个目标可能是保持传统饮食的健康方面。这项试验在 clinicaltrials.gov 上注册为 NCT00797888。