Designing a Food Frequency Questionnaire for a Vegetarian Population in Germany by Means of Mixed-Integer Linear Programming.

Background: Food frequency questionnaires (FFQs) are important tools for dietary assessment in large epidemiological studies, playing a crucial role in evaluating the relationship between diet and health. However, adapting the food lists in FFQs to align with specific study objectives or target popu...

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Publicado en:Nutrients Vol. 18; no. 10; pp. 1587 - 1603
Autores principales: Blaurock, Julia, Heuer, Thorsten, Gedrich, Kurt
Formato: equations & formulas research tables/charts Journal Article
Publicado: MDPI May2026
Acceso en línea:Ver este registro en EBSCOhost
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      dt: May2026
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        atl: Designing a Food Frequency Questionnaire for a Vegetarian Population in Germany by Means of Mixed-Integer Linear Programming.
      aug:
        au:
          Blaurock, Julia
          Heuer, Thorsten
          Gedrich, Kurt
        affil: Research Group Public Health Nutrition, ZIEL—Institute for Food & Health, Technical University of Munich, Weihenstephaner Berg 1, 85354 Freising, Germany
      sug:
        subj:
          Vegetarianism Germany
          Nutritional Assessment
          Diet
          Questionnaires
          Conceptual Framework
          Program Development
          Portion Size
          Food Intake
          Human
          Secondary Analysis
          Germany
          Pilot Studies
          Nutrients
          Descriptive Statistics
          Linear Regression
          Confidence Intervals
          Data Analysis Software
          Male
          Female
          Adolescence
          Adult
          Middle Age
          Aged
          Aged, 80 and Over
          Funding Source
          Adolescent: 13-18 years
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Aged: 65+ years
          Aged, 80 & over
          Male
          Female
      ab: Background: Food frequency questionnaires (FFQs) are important tools for dietary assessment in large epidemiological studies, playing a crucial role in evaluating the relationship between diet and health. However, adapting the food lists in FFQs to align with specific study objectives or target populations presents a considerable challenge. Methods: The present study develops a framework using mixed-integer linear programming (MILP) to minimize the food list of an FFQ using a vegetarian population in Germany as a proof of concept. Constraints of the optimization ensured that the selected food items have a certain nutrient coverage and variance coverage, as well as an appropriate aggregation level. Nutrient intake for three scenarios for FFQs was compared with 24 h recalls (24HR) using R2, calculated through linear regression. The three scenarios were: 1. FFQ reflecting the effect of categorizing portion sizes, 2. FFQ reflecting the effect of selecting food items, 3. FFQ reflecting the effect of categorizing portion sizes and selecting food items. Results: Length of minimized FFQs increased with a higher proportion of nutrient coverage and variance coverage. Including aggregation of food items produced shorter FFQs than FFQs that only contain food items at a lower aggregation level. R2 values across the three scenarios showed that the FFQ captured most of the between-person variation in nutrient intake that was observed in the 24HR. Conclusions: MILP offers a reliable and data-driven framework for compiling optimized FFQs.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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