Usual dietary intake estimation in the German National Cohort (NAKO).
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История · было → стало
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Wawro Nina, Gastell Sylvia, Mikolajczyk Rafael, Glaser Nadine, Schlesinger Sabrina, Schikowski Tamara, Karch André, Teismann Henning, Obi Nadia, Harth Volker, Weber Katharina S, Övermöhle Cara, Leitzmann Michael, Fischer Beate, Pischon Tobias, Nimptsch Katharina, Schmidt Börge, Völzke Henry, Ittermann Till, Peters Annette, Thorand Barbara, Hebestreit Antje, Wolters Maike, Katzke Verena, Jaskulski Stefanie, Sekula Peggy, Krist Lilian, Willich Stefan N, Holleczek Bernd, Hoffmeister Michael, Klett-Tammen Carolina, Meyerdierks Dörthe, Wirkner Kerstin, Conrad Johanna, Nöthlings Ute, Schulze Matthias B, Linseisen Jakob, Knüppel Sven
Аннотация
METHODS: We developed a blended approach using data from NAKO. During baseline (2014-2019) and first follow-up examinations (2019-2024), up to four 24-h food lists (24 h-FLs) and one food frequency questionnaire (FFQ) were collected. We combined these dietary intake data sources using an adapted Multiple Source Method (MSM) and supplemented them with estimated consumption amounts based on data from the German National Nutrition Survey II (NVS II, 2005-2007) to generate measurement-error-corrected estimates of dietary intake. The adapted MSM was empirically evaluated against conventional logistic linear mixed-effects model (LLMM), which can be computationally complex for large datasets due to lengthy processing times. Additionally, a simulation study evaluated how varying the number of 24 h-FLs and FFQ assessments affected the consumption probability estimates.
RESULTS: The adapted MSM showed high statistical agreement with LLMM (correlation ≥0.97). The usual intake of 90 EPIC-SOFT food groups, 124 nutrients, and energy intake was estimated for 152,304 participants (75% of the cohort) who had at least one 24 h-FL and an FFQ available. Furthermore, the simulation showed that including repeated 24 h-FLs alongside an FFQ improved the accuracy of individual consumption probability estimates, particularly when only one or two 24 h-FLs were available.
CONCLUSION: The adapted MSM offers a computationally efficient, practical alternative to LLMM, generated dietary intake estimates for over 150,000 NAKO participants to support future research. By integrating repeated 24 h-FLs, an FFQ, and external consumption data, this blended approach balances logistical feasibility with statistical precision, providing a scalable, cost-effective framework for large-scale nutritional studies.