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The added value of food frequency questionnaire (FFQ) information to estimate the usual food intake based on repeated 24-hour recalls

BACKGROUND: Statistical methods to model the usual dietary intake of foods in a population generally ignore the additional information on the never-consumers. The objective of this study is to determine the added value of Food Frequency Questionnaire (FFQ) data allowing distinguishing the never-cons...

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Autores principales: Ost, Cloë, De Ridder, Karin A. A., Tafforeau, Jean, Van Oyen, Herman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5662101/
https://www.ncbi.nlm.nih.gov/pubmed/29093816
http://dx.doi.org/10.1186/s13690-017-0214-8
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author Ost, Cloë
De Ridder, Karin A. A.
Tafforeau, Jean
Van Oyen, Herman
author_facet Ost, Cloë
De Ridder, Karin A. A.
Tafforeau, Jean
Van Oyen, Herman
author_sort Ost, Cloë
collection PubMed
description BACKGROUND: Statistical methods to model the usual dietary intake of foods in a population generally ignore the additional information on the never-consumers. The objective of this study is to determine the added value of Food Frequency Questionnaire (FFQ) data allowing distinguishing the never-consumers from the non-consumers while modeling the usual intake distribution. METHODS: Three food items with a different proportion of never-consumers were selected from the database of the Belgian food consumption survey of 2004 (N = 3200). The usual intake distribution for these food items was modeled with the Statistical Program for Analysis of Dietary Exposure (SPADE) and modeling parameters were extracted. These parameters were used to simulate (a) a new database with two 24-h recalls per respondent and (b) a “true” usual intake distribution. The usual intake distribution from the new database was obtained by modeling the 24-h recalls with SPADE, once without and once with the inclusion of the FFQ data on the never-consumers. Ratios were calculated for the different percentiles of the usual intake distribution: the modeled usual intake (g/day) (for both SPADE with and without the inclusion of FFQ data on never-consumers) was divided by the corresponding percentile of the simulated “true” usual intake (g/day). The closer the ratio is to one, the better the model fits the data. RESULTS: Inclusion of the FFQ information to identify the never-consumers did not improve the estimation of the higher percentiles of the usual intake distribution. However, taking into account this FFQ information improved the estimation of the lower percentiles of the usual intake distribution even when the proportion of never-consumers was low. CONCLUSIONS: The inclusion of FFQ information to identify the never-consumers is beneficial when interested in the whole usual intake distribution or in the lower percentiles only, no matter how low the proportion of never-consumers for that food item may be. However, when interest is only in the higher percentiles of the usual intake distribution, inclusion of FFQ information to identify the never-consumers will have no benefit. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13690-017-0214-8) contains supplementary material, which is available to authorized users.
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spelling pubmed-56621012017-11-01 The added value of food frequency questionnaire (FFQ) information to estimate the usual food intake based on repeated 24-hour recalls Ost, Cloë De Ridder, Karin A. A. Tafforeau, Jean Van Oyen, Herman Arch Public Health Methodology BACKGROUND: Statistical methods to model the usual dietary intake of foods in a population generally ignore the additional information on the never-consumers. The objective of this study is to determine the added value of Food Frequency Questionnaire (FFQ) data allowing distinguishing the never-consumers from the non-consumers while modeling the usual intake distribution. METHODS: Three food items with a different proportion of never-consumers were selected from the database of the Belgian food consumption survey of 2004 (N = 3200). The usual intake distribution for these food items was modeled with the Statistical Program for Analysis of Dietary Exposure (SPADE) and modeling parameters were extracted. These parameters were used to simulate (a) a new database with two 24-h recalls per respondent and (b) a “true” usual intake distribution. The usual intake distribution from the new database was obtained by modeling the 24-h recalls with SPADE, once without and once with the inclusion of the FFQ data on the never-consumers. Ratios were calculated for the different percentiles of the usual intake distribution: the modeled usual intake (g/day) (for both SPADE with and without the inclusion of FFQ data on never-consumers) was divided by the corresponding percentile of the simulated “true” usual intake (g/day). The closer the ratio is to one, the better the model fits the data. RESULTS: Inclusion of the FFQ information to identify the never-consumers did not improve the estimation of the higher percentiles of the usual intake distribution. However, taking into account this FFQ information improved the estimation of the lower percentiles of the usual intake distribution even when the proportion of never-consumers was low. CONCLUSIONS: The inclusion of FFQ information to identify the never-consumers is beneficial when interested in the whole usual intake distribution or in the lower percentiles only, no matter how low the proportion of never-consumers for that food item may be. However, when interest is only in the higher percentiles of the usual intake distribution, inclusion of FFQ information to identify the never-consumers will have no benefit. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13690-017-0214-8) contains supplementary material, which is available to authorized users. BioMed Central 2017-10-30 /pmc/articles/PMC5662101/ /pubmed/29093816 http://dx.doi.org/10.1186/s13690-017-0214-8 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology
Ost, Cloë
De Ridder, Karin A. A.
Tafforeau, Jean
Van Oyen, Herman
The added value of food frequency questionnaire (FFQ) information to estimate the usual food intake based on repeated 24-hour recalls
title The added value of food frequency questionnaire (FFQ) information to estimate the usual food intake based on repeated 24-hour recalls
title_full The added value of food frequency questionnaire (FFQ) information to estimate the usual food intake based on repeated 24-hour recalls
title_fullStr The added value of food frequency questionnaire (FFQ) information to estimate the usual food intake based on repeated 24-hour recalls
title_full_unstemmed The added value of food frequency questionnaire (FFQ) information to estimate the usual food intake based on repeated 24-hour recalls
title_short The added value of food frequency questionnaire (FFQ) information to estimate the usual food intake based on repeated 24-hour recalls
title_sort added value of food frequency questionnaire (ffq) information to estimate the usual food intake based on repeated 24-hour recalls
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5662101/
https://www.ncbi.nlm.nih.gov/pubmed/29093816
http://dx.doi.org/10.1186/s13690-017-0214-8
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