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A Novel Approach to Improve the Estimation of a Diet Adherence Considering Seasonality and Short Term Variability – The NU-AGE Mediterranean Diet Experience

In this work we present a novel statistical approach to improve the assessment of the adherence to a 1-year nutritional intervention within the framework of the NU-AGE project. This was measured with a single adherence score based on 7-days food records, under limitations on the number of observatio...

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Autores principales: Giampieri, Enrico, Ostan, Rita, Guidarelli, Giulia, Salvioli, Stefano, Berendsen, Agnes A. M., Brzozowska, Anna, Pietruszka, Barbara, Jennings, Amy, Meunier, Nathalie, Caumon, Elodie, Fairweather-Tait, Susan, Sicinska, Ewa, Feskens, Edith J. M., de Groot, Lisette C. P. G. M., Franceschi, Claudio, Santoro, Aurelia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6413567/
https://www.ncbi.nlm.nih.gov/pubmed/30890946
http://dx.doi.org/10.3389/fphys.2019.00149
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author Giampieri, Enrico
Ostan, Rita
Guidarelli, Giulia
Salvioli, Stefano
Berendsen, Agnes A. M.
Brzozowska, Anna
Pietruszka, Barbara
Jennings, Amy
Meunier, Nathalie
Caumon, Elodie
Fairweather-Tait, Susan
Sicinska, Ewa
Feskens, Edith J. M.
de Groot, Lisette C. P. G. M.
Franceschi, Claudio
Santoro, Aurelia
author_facet Giampieri, Enrico
Ostan, Rita
Guidarelli, Giulia
Salvioli, Stefano
Berendsen, Agnes A. M.
Brzozowska, Anna
Pietruszka, Barbara
Jennings, Amy
Meunier, Nathalie
Caumon, Elodie
Fairweather-Tait, Susan
Sicinska, Ewa
Feskens, Edith J. M.
de Groot, Lisette C. P. G. M.
Franceschi, Claudio
Santoro, Aurelia
author_sort Giampieri, Enrico
collection PubMed
description In this work we present a novel statistical approach to improve the assessment of the adherence to a 1-year nutritional intervention within the framework of the NU-AGE project. This was measured with a single adherence score based on 7-days food records, under limitations on the number of observations per subject and time frame of intervention. The results of the NU-AGE dietary intervention were summarized by variations of the NU-AGE index as described in the NU-AGE protocol. Food and nutrient intake of all participants was assessed by means of 7-days food records at recruitment and after 10 to 14 months of intervention (depending on the subject availability). Sixteen food groups and supplementations covering the dietary goals of the NU-AGE diet have been used to estimate the NU-AGE index before and after the intervention. The 7-days food record is a reliable tool to register food intakes, however, as with other tools used to assess lifestyle dietary compliance, it is affected by uncertainty in this estimation due to the possibility that the observed week is not fully representative of the entire intervention period. Also, due to logistic limitations, the effects of seasonality can never be completely removed. These variabilities, if not accounted for in the index estimation, will reduce the statistical power of the analyses. In this work we discuss a method to assess these uncertainties and thus improve the resulting NU-AGE index. The proposed method is based on Hierarchical Bayesian Models. This model explicitly includes country-specific averages of the NU-AGE index, index variation induced by the dietary intervention, and country based seasonality. This information is used to evaluate the NU-AGE index uncertainty and thus to estimate the “real” NU-AGE index for each subject, both before and after the intervention. These corrections reduce the possibility of misinterpreting measurement variability as real information, improving the power of the statistical tests that are performed with the resulting index. The results suggest that this method is able to reduce the short term and seasonal variability of the measured index in the context of multicenter dietary intervention trials. Using this method to estimate seasonality and variability would allow one to obtain better measurements from the subjects of a study, and be able to simplify the scheduling of diet assessments. Clinical Trial Registration: www.ClinicalTrials.gov, identifier NCT01754012.
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spelling pubmed-64135672019-03-19 A Novel Approach to Improve the Estimation of a Diet Adherence Considering Seasonality and Short Term Variability – The NU-AGE Mediterranean Diet Experience Giampieri, Enrico Ostan, Rita Guidarelli, Giulia Salvioli, Stefano Berendsen, Agnes A. M. Brzozowska, Anna Pietruszka, Barbara Jennings, Amy Meunier, Nathalie Caumon, Elodie Fairweather-Tait, Susan Sicinska, Ewa Feskens, Edith J. M. de Groot, Lisette C. P. G. M. Franceschi, Claudio Santoro, Aurelia Front Physiol Physiology In this work we present a novel statistical approach to improve the assessment of the adherence to a 1-year nutritional intervention within the framework of the NU-AGE project. This was measured with a single adherence score based on 7-days food records, under limitations on the number of observations per subject and time frame of intervention. The results of the NU-AGE dietary intervention were summarized by variations of the NU-AGE index as described in the NU-AGE protocol. Food and nutrient intake of all participants was assessed by means of 7-days food records at recruitment and after 10 to 14 months of intervention (depending on the subject availability). Sixteen food groups and supplementations covering the dietary goals of the NU-AGE diet have been used to estimate the NU-AGE index before and after the intervention. The 7-days food record is a reliable tool to register food intakes, however, as with other tools used to assess lifestyle dietary compliance, it is affected by uncertainty in this estimation due to the possibility that the observed week is not fully representative of the entire intervention period. Also, due to logistic limitations, the effects of seasonality can never be completely removed. These variabilities, if not accounted for in the index estimation, will reduce the statistical power of the analyses. In this work we discuss a method to assess these uncertainties and thus improve the resulting NU-AGE index. The proposed method is based on Hierarchical Bayesian Models. This model explicitly includes country-specific averages of the NU-AGE index, index variation induced by the dietary intervention, and country based seasonality. This information is used to evaluate the NU-AGE index uncertainty and thus to estimate the “real” NU-AGE index for each subject, both before and after the intervention. These corrections reduce the possibility of misinterpreting measurement variability as real information, improving the power of the statistical tests that are performed with the resulting index. The results suggest that this method is able to reduce the short term and seasonal variability of the measured index in the context of multicenter dietary intervention trials. Using this method to estimate seasonality and variability would allow one to obtain better measurements from the subjects of a study, and be able to simplify the scheduling of diet assessments. Clinical Trial Registration: www.ClinicalTrials.gov, identifier NCT01754012. Frontiers Media S.A. 2019-03-05 /pmc/articles/PMC6413567/ /pubmed/30890946 http://dx.doi.org/10.3389/fphys.2019.00149 Text en Copyright © 2019 Giampieri, Ostan, Guidarelli, Salvioli, Berendsen, Brzozowska, Pietruszka, Jennings, Meunier, Caumon, Fairweather-Tait, Sicinska, Feskens, de Groot, Franceschi and Santoro. http://creativecommons.org/licenses/by/4.0/ 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.
spellingShingle Physiology
Giampieri, Enrico
Ostan, Rita
Guidarelli, Giulia
Salvioli, Stefano
Berendsen, Agnes A. M.
Brzozowska, Anna
Pietruszka, Barbara
Jennings, Amy
Meunier, Nathalie
Caumon, Elodie
Fairweather-Tait, Susan
Sicinska, Ewa
Feskens, Edith J. M.
de Groot, Lisette C. P. G. M.
Franceschi, Claudio
Santoro, Aurelia
A Novel Approach to Improve the Estimation of a Diet Adherence Considering Seasonality and Short Term Variability – The NU-AGE Mediterranean Diet Experience
title A Novel Approach to Improve the Estimation of a Diet Adherence Considering Seasonality and Short Term Variability – The NU-AGE Mediterranean Diet Experience
title_full A Novel Approach to Improve the Estimation of a Diet Adherence Considering Seasonality and Short Term Variability – The NU-AGE Mediterranean Diet Experience
title_fullStr A Novel Approach to Improve the Estimation of a Diet Adherence Considering Seasonality and Short Term Variability – The NU-AGE Mediterranean Diet Experience
title_full_unstemmed A Novel Approach to Improve the Estimation of a Diet Adherence Considering Seasonality and Short Term Variability – The NU-AGE Mediterranean Diet Experience
title_short A Novel Approach to Improve the Estimation of a Diet Adherence Considering Seasonality and Short Term Variability – The NU-AGE Mediterranean Diet Experience
title_sort novel approach to improve the estimation of a diet adherence considering seasonality and short term variability – the nu-age mediterranean diet experience
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6413567/
https://www.ncbi.nlm.nih.gov/pubmed/30890946
http://dx.doi.org/10.3389/fphys.2019.00149
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