Optimization of a Food List for Food Frequency Questionnaires Using Mixed Integer Linear Programming: A Proof of Concept Based on Data from the Second German National Nutrition Survey.
Food Frequency Questionnaires (FFQs) are important instruments to assess dietary intake in large epidemiological studies. To determine dietary intake correctly, food lists need to be adapted depending on the study aim and the target population. The present work compiles food lists for an FFQ with Mi...
| Publicado en: | Nutrients Vol. 15; no. 24; pp. 5098 - 5116 |
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| Autores principales: | , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
MDPI
Dec2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=174469963&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 174469963 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 20726643 B0TT jtl: Nutrients issn: 20726643 maglogo: N pubinfo: dt: Dec2023 vid: 15 iid: 24 pid: 97109 pub: MDPI artinfo: ui: 174469963 174469963 174469963 10.3390/nu15245098 174469963 ppf: 5098 ppct: 18 formats: tig: atl: Optimization of a Food List for Food Frequency Questionnaires Using Mixed Integer Linear Programming: A Proof of Concept Based on Data from the Second German National Nutrition Survey. 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: Food Habits Questionnaires Evaluation Systems Analysis Eating Population Instrument Validation Human Pilot Studies Comparative Studies Surveys Validation Studies Female Male Adolescence Adult Middle Age Funding Source Adolescent: 13-18 years Adult: 19-44 years Middle Aged: 45-64 years Female Male ab: Food Frequency Questionnaires (FFQs) are important instruments to assess dietary intake in large epidemiological studies. To determine dietary intake correctly, food lists need to be adapted depending on the study aim and the target population. The present work compiles food lists for an FFQ with Mixed Integer Linear Programming (MILP) to minimize the number of foods in the food list. The optimized food lists were compared with the validated eNutri FFQ. The constraints of the MILP aimed to identify food items with a high nutrient coverage in a population and with a high interindividual variability. The optimization was based on data from the second German National Nutrition Survey. The resulting food lists were shorter than the one used in the validated eNutri FFQ. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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