Schulze M B, Hoffmann K, Kroke A, Boeing H
Department of Epidemiology, German Institute of Human Nutrition, Potsdam-Rehbruecke, Arthur-Scheunert-Allee 114-116, 14558 Bergholz-Rehbruecke, Germany.
Br J Nutr. 2001 Mar;85(3):363-73. doi: 10.1079/bjn2000254.
Dietary pattern analysis has recently received growing attention, as it might be more appropriate in studies of diet-disease associations than the single food or nutrient approach that has dominated past epidemiological research. Factor analysis is a technique which is commonly used to identify dietary patterns within study populations. However, the ability of factor solutions to account for variance of food and nutrient intake has so far remained unclear. The present study therefore explored the statistical properties of dietary patterns with regard to the explained variance. Food intake of 8975 men and 13 379 women, assessed by a food-frequency questionnaire, was aggregated into forty-seven separate food groups. Dietary patterns were identified by principal component analysis and subsequent varimax rotation. Seven factors were retained for both men and women, which accounted for about 31 % of the total variance. The explained variance was relatively high (>40 %) for cooked vegetables, sauce, meat, dessert, cake, bread other than wholemeal, raw vegetables, processed meat, high-fat cheese, butter and margarine. Factor scores were used to investigate associations between the factors and nutrient intake. The patterns accounted for relatively large proportions of variance of energy and macronutrient intake, but for less variance of alcohol and micronutrient intake, especially of retinol, beta-carotene, vitamin E, Ca and ascorbic acid. In addition, factors were related to age, BMI, physical activity, education, smoking and vitamin and mineral supplement use.
饮食模式分析近来受到越来越多的关注,因为在饮食与疾病关联的研究中,它可能比过去主导流行病学研究的单一食物或营养素方法更为合适。因子分析是一种常用于识别研究人群中饮食模式的技术。然而,因子分析结果解释食物和营养素摄入量差异的能力至今仍不明确。因此,本研究探讨了饮食模式在解释差异方面的统计特性。通过食物频率问卷评估的8975名男性和13379名女性的食物摄入量被汇总为47个独立的食物组。通过主成分分析和随后的方差最大化旋转来识别饮食模式。男性和女性均保留了7个因子,它们占总方差的约31%。对于熟蔬菜、酱汁、肉类、甜点、蛋糕、非全麦面包、生蔬菜、加工肉类、高脂奶酪、黄油和人造黄油,解释的方差相对较高(>40%)。因子得分用于研究各因子与营养素摄入量之间的关联。这些模式在能量和常量营养素摄入量差异中占比较大,但在酒精和微量营养素摄入量差异中占比小,尤其是视黄醇、β-胡萝卜素、维生素E、钙和抗坏血酸。此外,各因子与年龄、体重指数、身体活动、教育程度、吸烟以及维生素和矿物质补充剂的使用有关。