Ledikwe Jenny H, Smiciklas-Wright Helen, Mitchell Diane C, Miller Carla K, Jensen Gordon L
Department of Nutritional Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA.
J Am Geriatr Soc. 2004 Apr;52(4):589-95. doi: 10.1111/j.1532-5415.2004.52167.x.
To characterize dietary patterns of rural older adults and relate patterns to weight and nutritional status.
Cross-sectional.
Rural Pennsylvania.
One hundred seventy-nine community-dwelling adults aged 66 to 87 years.
A home visit was conducted to collect demographic, health behavior, and anthropometric data and a blood sample. Five 24-hour dietary recall were administered. Cluster analysis classified participants into dietary patterns using food subgroup servings. Chi-square, analysis of covariance, and logistic regression were used to assess differences across clusters.
A low-nutrient-dense cluster (n=107), with higher intake of breads, sweet breads/desserts, dairy desserts, processed meats, eggs, and fats/oils, and a high-nutrient-dense cluster (n=72) with higher intake of cereals, dark green/yellow vegetables, other vegetables, citrus/melons/berries, fruit juices, other fruits, milks, poultry, fish, and beans, were identified. Those in the high-nutrient-dense cluster had lower energy intake; higher energy-adjusted intake of fiber, iron, zinc, folate, and vitamins B(6), B(12), and D; higher Healthy Eating Index scores; higher plasma vitamin B(12) levels; and a lower waist circumference. Those with a low-nutrient-dense dietary pattern were twice as likely to be obese, twice as likely to have low plasma vitamin B(12) levels, and three to 17 times more likely to have low nutrient intake.
This study provides support for recommending a high-nutrient-dense dietary pattern for older adults. Behavioral interventions encouraging diets characterized by high-nutrient-dense foods may improve weight and nutritional status of older adults.
描述农村老年人的饮食模式，并将这些模式与体重和营养状况联系起来。
横断面研究。
宾夕法尼亚州农村。
179名年龄在66至87岁的社区居住成年人。
进行家访以收集人口统计学、健康行为和人体测量数据以及血样。进行了五次24小时饮食回顾。聚类分析使用食物亚组份数将参与者分为不同的饮食模式。使用卡方检验、协方差分析和逻辑回归来评估各聚类之间的差异。
确定了一个低营养密度聚类（n = 107），其面包、甜面包/甜点、乳制甜点、加工肉类、鸡蛋和脂肪/油类的摄入量较高；以及一个高营养密度聚类（n = 72），其谷类、深绿色/黄色蔬菜、其他蔬菜、柑橘/甜瓜/浆果、果汁、其他水果、牛奶、家禽、鱼类和豆类的摄入量较高。高营养密度聚类中的人能量摄入量较低；纤维、铁、锌、叶酸以及维生素B(6)、B(12)和D的能量调整摄入量较高；健康饮食指数得分较高；血浆维生素B(12)水平较高；腰围较低。低营养密度饮食模式的人肥胖的可能性是其他人的两倍，血浆维生素B(12)水平较低的可能性是其他人的两倍，营养摄入量低的可能性是其他人的三至十七倍。
本研究为建议老年人采用高营养密度饮食模式提供了支持。鼓励以高营养密度食物为特征的饮食的行为干预措施可能会改善老年人的体重和营养状况。
