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      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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          Abstract

          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 in 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.

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          Estimating usual food intake distributions by using the multiple source method in the EPIC-Potsdam Calibration Study.

          Ulrich Harttig, J Haubrock, Sven Knüppel … (2011)
          Estimating usual food intake distributions from short-term quantitative measurements is critical when occasionally or rarely eaten food groups are considered. To overcome this challenge by statistical modeling, the Multiple Source Method (MSM) was developed in 2006. The MSM provides usual food intake distributions from individual short-term estimates by combining the probability and the amount of consumption with incorporation of covariates into the modeling part. Habitual consumption frequency information may be used in 2 ways: first, to distinguish true nonconsumers from occasional nonconsumers in short-term measurements and second, as a covariate in the statistical model. The MSM is therefore able to calculate estimates for occasional nonconsumers. External information on the proportion of nonconsumers of a food can also be handled by the MSM. As a proof-of-concept, we applied the MSM to a data set from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Calibration Study (2004) comprising 393 participants who completed two 24-h dietary recalls and one FFQ. Usual intake distributions were estimated for 38 food groups with a proportion of nonconsumers > 70% in the 24-h dietary recalls. The intake estimates derived by the MSM corresponded with the observed values such as the group mean. This study shows that the MSM is a useful and applicable statistical technique to estimate usual food intake distributions, if at least 2 repeated measurements per participant are available, even for food groups with a sizeable percentage of nonconsumers.
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            Modeling data with excess zeros and measurement error: application to evaluating relationships between episodically consumed foods and health outcomes.

            Dennis Buckman, W DODD, D Midthune … (2009)
            Dietary assessment of episodically consumed foods gives rise to nonnegative data that have excess zeros and measurement error. Tooze et al. (2006, Journal of the American Dietetic Association 106, 1575-1587) describe a general statistical approach (National Cancer Institute method) for modeling such food intakes reported on two or more 24-hour recalls (24HRs) and demonstrate its use to estimate the distribution of the food's usual intake in the general population. In this article, we propose an extension of this method to predict individual usual intake of such foods and to evaluate the relationships of usual intakes with health outcomes. Following the regression calibration approach for measurement error correction, individual usual intake is generally predicted as the conditional mean intake given 24HR-reported intake and other covariates in the health model. One feature of the proposed method is that additional covariates potentially related to usual intake may be used to increase the precision of estimates of usual intake and of diet-health outcome associations. Applying the method to data from the Eating at America's Table Study, we quantify the increased precision obtained from including reported frequency of intake on a food frequency questionnaire (FFQ) as a covariate in the calibration model. We then demonstrate the method in evaluating the linear relationship between log blood mercury levels and fish intake in women by using data from the National Health and Nutrition Examination Survey, and show increased precision when including the FFQ information. Finally, we present simulation results evaluating the performance of the proposed method in this context.
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              Taking advantage of the strengths of 2 different dietary assessment instruments to improve intake estimates for nutritional epidemiology.

              Raymond J Carroll, Douglas Midthune, Amy Subar … (2012)
              With the advent of Internet-based 24-hour recall (24HR) instruments, it is now possible to envision their use in cohort studies investigating the relation between nutrition and disease. Understanding that all dietary assessment instruments are subject to measurement errors and correcting for them under the assumption that the 24HR is unbiased for usual intake, here the authors simultaneously address precision, power, and sample size under the following 3 conditions: 1) 1-12 24HRs; 2) a single calibrated food frequency questionnaire (FFQ); and 3) a combination of 24HR and FFQ data. Using data from the Eating at America's Table Study (1997-1998), the authors found that 4-6 administrations of the 24HR is optimal for most nutrients and food groups and that combined use of multiple 24HR and FFQ data sometimes provides data superior to use of either method alone, especially for foods that are not regularly consumed. For all food groups but the most rarely consumed, use of 2-4 recalls alone, with or without additional FFQ data, was superior to use of FFQ data alone. Thus, if self-administered automated 24HRs are to be used in cohort studies, 4-6 administrations of the 24HR should be considered along with administration of an FFQ.
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                Author and article information

                Contributors
                Journal
                Journal ID (nlm-ta): Front Nutr
                Journal ID (iso-abbrev): Front Nutr
                Journal ID (publisher-id): Front. Nutr.
                Title: Frontiers in Nutrition
                Publisher: Frontiers Media S.A.
                ISSN (Electronic): 2296-861X
                Publication date (Electronic): 06 September 2019
                Publication date Collection: 2019
                Volume: 6
                Electronic Location Identifier: 145
                Affiliations
                [1] 1Institute of Epidemiology II, Helmholtz Zentrum Munich, German Research Center for Environmental Health (GmbH) , Munich, Germany
                [2] 2German Center for Diabetes Research (DZD e.V.) , Düsseldorf, Germany
                [3] 3Chair of Epidemiology, Ludwig-Maximilians-Universität München, UNIKA-T , Augsburg, Germany
                [4] 4FGK Clinical Research GmbH , Munich, Germany
                [5] 5Department of Nutrition and Food Sciences, University of Bonn , Bonn, Germany
                [6] 6Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE) , Nuthetal, Germany
                [7] 7ZIEL Institute for Food and Health, Technical University of Munich , Freising, Germany
                Author notes

                Edited by: Angela M. Zivkovic, University of California, Davis, United States

                Reviewed by: Jean-Philippe Krieger, University of Gothenburg, Sweden; Scott W. Keith, Thomas Jefferson University, United States

                *Correspondence: Jakob Linseisen jakob.linseisen@ 123456helmholtz-muenchen.de

                This article was submitted to Nutrition Methodology, a section of the journal Frontiers in Nutrition

                Article
                DOI: 10.3389/fnut.2019.00145
                PMC ID: 6743021
                PubMed ID: 31552261
                SO-VID: c9323e6e-2787-46fb-a94f-40dfff3cbbe6
                Copyright © Copyright © 2019 Mitry, Wawro, Six-Merker, Zoller, Jourdan, Meisinger, Thierry, Nöthlings, Knüppel, Boeing and Linseisen.
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                Date received : 20 September 2018
                Date accepted : 23 August 2019
                Page count
                Figures: 3, Tables: 5, Equations: 0, References: 46, Pages: 14, Words: 10226
                Funding
                Funded by: Bundesministerium für Bildung und Forschung 10.13039/501100002347
                Award ID: FK 01EA1409E
                Award ID: FK 2814ERA02E
                Categories
                Subject: Nutrition
                Subject: Original Research

                Keywords: dietary assessment,food list,food frequency questionnaire,kora,epidemiology
                Data availability:
                Keywords: dietary assessment, food list, food frequency questionnaire, kora, epidemiology

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