Freese Johanna, Pricop-Jeckstadt Mihaela, Heuer Thorsten, Clemens Matthias, Boeing Heiner, Knüppel Sven, Nöthlings Ute
Department of Nutrition and Food Sciences , Nutritional Epidemiology , University of Bonn , Endenicher Allee 11-13 , 53115 Bonn , Germany.
Institute for Medical Informatics and Biometry , TU-Dresden , Fetscherstr. 74 , 01307 Dresden , Germany.
J Nutr Sci. 2016 Aug 15;5:e35. doi: 10.1017/jns.2016.26. eCollection 2016.
Next to the information on frequency of food consumption, information on consumption-day amounts is important to estimate usual dietary intake in epidemiological studies. Our objective was to identify determinants of consumption-day amounts to derive person-specific standard consumption-day amounts applicable for the estimation of usual dietary intake using separate sources to assesss information on consumption probability and amount consumed. 24-h Dietary recall data from the German National Nutrition Survey II ( = 8522; aged 20-80 years) conducted between 2005 and 2007 were analysed for determinants of consumption-day amounts of thirty-eight food and beverage groups using LASSO variable selection for linear mixed-effects models. Determinants included sex, age, BMI, smoking status, years of education, household net income, living status and employment status. Most often, sex, age and smoking status were selected as predictors for consumption-day amounts across thirty-eight food groups. In contrast, living with a partner, employment status and household net income were less frequently chosen. Overall, different determinants were of relevance for different food groups. The number of selected determinants ranged from eight for coffee and juice to zero for cabbage, tea, root vegetables, leafy vegetables, fruit vegetables, legumes, offal, vegetable oils, and other fats. For the estimation of usual dietary intake in a combined approach with a 24-h food list, person-specific standard consumption-day amounts could be used. Sex, age and smoking status were shown to be the most relevant predictors in our analysis. Their impact on the estimation of usual dietary intake needs to be evaluated in future studies.
除了食物消费频率信息外，消费日摄入量信息对于在流行病学研究中估计通常的饮食摄入量也很重要。我们的目标是确定消费日摄入量的决定因素，以便得出适用于估计通常饮食摄入量的个人特定标准消费日摄入量，使用单独的来源来评估消费概率和消费量信息。对2005年至2007年进行的德国全国营养调查II（n = 8522；年龄在20 - 80岁之间）的24小时饮食回忆数据进行分析，使用套索变量选择法对线性混合效应模型确定38种食品和饮料组的消费日摄入量的决定因素。决定因素包括性别、年龄、体重指数、吸烟状况、受教育年限、家庭净收入、生活状况和就业状况。大多数情况下，性别、年龄和吸烟状况被选为38种食品组消费日摄入量的预测因素。相比之下，与伴侣同住、就业状况和家庭净收入被选中的频率较低。总体而言，不同的决定因素对不同的食品组具有相关性。所选决定因素的数量从咖啡和果汁的8个到卷心菜、茶、根茎类蔬菜、叶菜类蔬菜、果菜类蔬菜、豆类、内脏、植物油和其他脂肪的0个不等。为了结合24小时食物清单以综合方法估计通常的饮食摄入量，可以使用个人特定的标准消费日摄入量。在我们的分析中，性别、年龄和吸烟状况被证明是最相关的预测因素。它们对通常饮食摄入量估计的影响需要在未来的研究中进行评估。
