Quatromoni P A, Copenhafer D L, Demissie S, D'Agostino R B, O'Horo C E, Nam B-H, Millen B E
Department of Social and Behavioral Sciences, Boston University School of Public Health, MA 02118, USA.
J Epidemiol Community Health. 2002 May;56(5):381-8. doi: 10.1136/jech.56.5.381.
To examine the internal validity of a dietary pattern analysis and its ability to discriminate clusters of people with similar dietary patterns using independently assessed nutrient intakes and heart disease risk factors.
Population based study characterising dietary patterns using cluster analysis applied to data from the semiquantitative Framingham food frequency questionnaire collected from 1942 women ages 18-76 years, between 1984-88.
Framingham, Massachusetts.
Of 1942 women included in the cluster analysis, 1828 (94%) were assigned to one of the five dietary pattern clusters: Heart Healthy, Light Eating, Wine and Moderate Eating, High Fat, and Empty Calorie. Dietary patterns differed substantially in terms of individual nutrient intakes, overall dietary risk, heart disease risk factors, and predicted heart disease risk. Women in the Heart Healthy cluster had the most nutrient dense eating pattern, the lowest level of dietary risk, more favourable risk factor levels, and the lowest probability of developing heart disease. Those in the Empty Calorie cluster had a less nutritious dietary pattern, the greatest level of dietary risk, a heavier burden of heart disease risk factors, and a relatively higher probability of developing heart disease. Cluster reproducibility using discriminant analysis showed that 80% of the sample was correctly classified. The cluster technique was highly sensitive and specific (75% to 100%).
These findings support the internal validity of a dietary pattern analysis for characterising dietary exposures in epidemiological research. The authors encourage other researchers to explore this technique when investigating relations between nutrition, health, and disease.
使用独立评估的营养素摄入量和心脏病风险因素,检验饮食模式分析的内部有效性及其区分具有相似饮食模式人群组的能力。
基于人群的研究,运用聚类分析对1984年至1988年间从18至76岁的1942名女性收集的半定量弗雷明汉食物频率问卷数据进行饮食模式特征分析。
马萨诸塞州弗雷明汉。
在纳入聚类分析的1942名女性中,1828名(94%)被分配到五个饮食模式组之一:心脏健康型、清淡饮食型、葡萄酒与适度饮食型、高脂肪型和空热量型。各饮食模式在个体营养素摄入量、总体饮食风险、心脏病风险因素以及预测的心脏病风险方面存在显著差异。心脏健康型组的女性饮食模式营养密度最高,饮食风险水平最低,风险因素水平更有利,患心脏病的概率最低。空热量型组的女性饮食模式营养较差,饮食风险水平最高,心脏病风险因素负担较重,患心脏病的概率相对较高。使用判别分析的聚类可重复性显示,80%的样本被正确分类。聚类技术具有高度敏感性和特异性(75%至100%)。
这些发现支持饮食模式分析在流行病学研究中表征饮食暴露的内部有效性。作者鼓励其他研究人员在调查营养、健康和疾病之间的关系时探索这项技术。