Usual Dietary Intake Estimation Based on a Combination of Repeated 24-H Food Lists and a Food Frequency Questionnaire in the KORA FF4 Cross-Sectional Study
Usual Dietary Intake Estimation Based on a Combination of Repeated 24-H Food Lists and a Food Frequency Questionnaire in the KORA FF4 Cross-Sectional Study
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DOI：
10.3389/fnut.2019.00145
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发表时间：
2019-09-06
影响因子：
5
通讯作者：
Linseisen, Jakob
中科院分区：
文献类型：
--
作者：
Mitry, Patricia;Wawro, Nina;Linseisen, Jakob
背景：日常膳食摄入量的估计在流行病学研究中是一个挑战。我们采用了混合的方法，结合了重复的24小时食物清单（24HFL）和食物频率问卷（FFQ）提供的优势。方法：至少有两个基于网络的24HFL和一个FFQ完成了821名参与者在KORA FF4研究。使用logistic混合模型估计消费概率，调整协变量和FFQ消费频率数据。根据第二次巴伐利亚食品消费调查（BVS II）的结果，预测每个参与者的食物摄入量。通过结合消费概率和估计消费量，估计每个参与者的日常食物摄入量。这些结果进行了比较，得到的结果不考虑FFQ信息的消费概率估计，以及传统的FFQ data.Results：混合方法的食物组摄入量的结果往往高于FFQ为基础的结果。两种方法之间的组内相关系数在0.21和0.86之间。两种方法的比较得出基于五分位数的加权kappa值，范围从一般（0.34）到极好的一致性（0.84）。省略FFQ信息的消费概率模型明显影响结果在组水平上，虽然个人的摄入量数据略有影响，在大多数情况下，为part.Conclusions：混合方法的基础上的膳食摄入量数据不同的FFQ为基础的结果在绝对值和分类，根据五分位数。混合方法的应用已被证明是营养流行病学中一种可能的工具，与已发表的研究相比，混合方法产生了合理的估计。列入FFQ信息是有价值的，特别是在不规则消费的食物方面。一项包括饮食摄入生物标志物的验证研究是必要的。
Background: Estimation of usual dietary intake poses a challenge in epidemiological studies. We applied a blended approach that combines the strengths provided by repeated 24-h food lists (24HFLs) and a food frequency questionnaire (FFQ).Methods: At least two web-based 24HFLs and one FFQ were completed by 821 participants in the KORA FF4 study. Consumption probabilities were estimated using logistic mixed models, adjusting for covariates and the FFQ data on consumption frequency. Intake amount of a consumed food item was predicted for each participant based on the results of the second Bavarian Food Consumption Survey (BVS II). By combining consumption probability and estimated consumption amount, the usual food intake for each participant was estimated. These results were compared to results obtained without considering FFQ information for consumption probability estimation, as well as to conventional FFQ data.Results: The results of the blended approach for food group intake were often higher than the FFQ-based results. Intraclass correlation coefficients between both methods ranged between 0.21 and 0.86. Comparison of both methods resulted in weighted kappa values based on quintiles ranging from fair (0.34) to excellent agreement (0.84). Omission of FFQ information in the consumption probability models distinctly affected the results at the group level, though individual intake data were slightly affected, for the most part.Conclusions: Usual dietary intake data based on the blended approach differs from the FFQ-based results both in absolute terms and in classification according to quintiles. The application of the blended approach has been demonstrated as a possible tool biomarkersin nutritional epidemiology, as a comparison with published studies showed that the blended approach yields reasonable estimates. The inclusion of the FFQ information is valuable especially with regard to irregularly consumed foods. A validation study including biomarkers of dietary intake is warranted.