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Studying dietary intake in daily life through multilevel two-part modelling: a novel analytical approach and its practical application
BACKGROUND: Understanding which factors influence dietary intake, particularly in daily life, is crucial given the impact diet has on physical as well as mental health. However, a factor might influence whether but not how much an individual eats and vice versa or a factor’s importance may differ ac...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8477527/ https://www.ncbi.nlm.nih.gov/pubmed/34579744 http://dx.doi.org/10.1186/s12966-021-01187-8 |
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author | Ruf, Alea Neubauer, Andreas B. Ebner-Priemer, Ulrich Reif, Andreas Matura, Silke |
author_facet | Ruf, Alea Neubauer, Andreas B. Ebner-Priemer, Ulrich Reif, Andreas Matura, Silke |
author_sort | Ruf, Alea |
collection | PubMed |
description | BACKGROUND: Understanding which factors influence dietary intake, particularly in daily life, is crucial given the impact diet has on physical as well as mental health. However, a factor might influence whether but not how much an individual eats and vice versa or a factor’s importance may differ across these two facets. Distinguishing between these two facets, hence, studying dietary intake as a dual process is conceptually promising and not only allows further insights, but also solves a statistical issue. When assessing the association between a predictor (e.g. momentary affect) and subsequent dietary intake in daily life through ecological momentary assessment (EMA), the outcome variable (e.g. energy intake within a predefined time-interval) is semicontinuous. That is, one part is equal to zero (i.e. no dietary intake occurred) and the other contains right-skewed positive values (i.e. dietary intake occurred, but often only small amounts are consumed). However, linear multilevel modelling which is commonly used for EMA data to account for repeated measures within individuals cannot be applied to semicontinuous outcomes. A highly informative statistical approach for semicontinuous outcomes is multilevel two-part modelling which treats the outcome as generated by a dual process, combining a multilevel logistic/probit regression for zeros and a multilevel (generalized) linear regression for nonzero values. METHODS: A multilevel two-part model combining a multilevel logistic regression to predict whether an individual eats and a multilevel gamma regression to predict how much is eaten, if an individual eats, is proposed. Its general implementation in R, a widely used and freely available statistical software, using the R-package brms is described. To illustrate its practical application, the analytical approach is applied exemplary to data from the Eat2beNICE-APPetite-study. RESULTS: Results highlight that the proposed multilevel two-part model reveals process-specific associations which cannot be detected through traditional multilevel modelling. CONCLUSIONS: This paper is the first to introduce multilevel two-part modelling as a novel analytical approach to study dietary intake in daily life. Studying dietary intake through multilevel two-part modelling is conceptually as well as methodologically promising. Findings can be translated to tailored nutritional interventions targeting either the occurrence or the amount of dietary intake. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12966-021-01187-8. |
format | Online Article Text |
id | pubmed-8477527 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-84775272021-09-28 Studying dietary intake in daily life through multilevel two-part modelling: a novel analytical approach and its practical application Ruf, Alea Neubauer, Andreas B. Ebner-Priemer, Ulrich Reif, Andreas Matura, Silke Int J Behav Nutr Phys Act Methodology BACKGROUND: Understanding which factors influence dietary intake, particularly in daily life, is crucial given the impact diet has on physical as well as mental health. However, a factor might influence whether but not how much an individual eats and vice versa or a factor’s importance may differ across these two facets. Distinguishing between these two facets, hence, studying dietary intake as a dual process is conceptually promising and not only allows further insights, but also solves a statistical issue. When assessing the association between a predictor (e.g. momentary affect) and subsequent dietary intake in daily life through ecological momentary assessment (EMA), the outcome variable (e.g. energy intake within a predefined time-interval) is semicontinuous. That is, one part is equal to zero (i.e. no dietary intake occurred) and the other contains right-skewed positive values (i.e. dietary intake occurred, but often only small amounts are consumed). However, linear multilevel modelling which is commonly used for EMA data to account for repeated measures within individuals cannot be applied to semicontinuous outcomes. A highly informative statistical approach for semicontinuous outcomes is multilevel two-part modelling which treats the outcome as generated by a dual process, combining a multilevel logistic/probit regression for zeros and a multilevel (generalized) linear regression for nonzero values. METHODS: A multilevel two-part model combining a multilevel logistic regression to predict whether an individual eats and a multilevel gamma regression to predict how much is eaten, if an individual eats, is proposed. Its general implementation in R, a widely used and freely available statistical software, using the R-package brms is described. To illustrate its practical application, the analytical approach is applied exemplary to data from the Eat2beNICE-APPetite-study. RESULTS: Results highlight that the proposed multilevel two-part model reveals process-specific associations which cannot be detected through traditional multilevel modelling. CONCLUSIONS: This paper is the first to introduce multilevel two-part modelling as a novel analytical approach to study dietary intake in daily life. Studying dietary intake through multilevel two-part modelling is conceptually as well as methodologically promising. Findings can be translated to tailored nutritional interventions targeting either the occurrence or the amount of dietary intake. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12966-021-01187-8. BioMed Central 2021-09-27 /pmc/articles/PMC8477527/ /pubmed/34579744 http://dx.doi.org/10.1186/s12966-021-01187-8 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Methodology Ruf, Alea Neubauer, Andreas B. Ebner-Priemer, Ulrich Reif, Andreas Matura, Silke Studying dietary intake in daily life through multilevel two-part modelling: a novel analytical approach and its practical application |
title | Studying dietary intake in daily life through multilevel two-part modelling: a novel analytical approach and its practical application |
title_full | Studying dietary intake in daily life through multilevel two-part modelling: a novel analytical approach and its practical application |
title_fullStr | Studying dietary intake in daily life through multilevel two-part modelling: a novel analytical approach and its practical application |
title_full_unstemmed | Studying dietary intake in daily life through multilevel two-part modelling: a novel analytical approach and its practical application |
title_short | Studying dietary intake in daily life through multilevel two-part modelling: a novel analytical approach and its practical application |
title_sort | studying dietary intake in daily life through multilevel two-part modelling: a novel analytical approach and its practical application |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8477527/ https://www.ncbi.nlm.nih.gov/pubmed/34579744 http://dx.doi.org/10.1186/s12966-021-01187-8 |
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