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Meal-timing patterns and chronic disease prevalence in two representative Austrian studies

PURPOSE: This study aimed at describing meal-timing patterns using cluster analysis and explore their association with sleep and chronic diseases, before and during COVID-19 mitigation measures in Austria. METHODS: Information was collected in two surveys in 2017 (N = 1004) and 2020 (N = 1010) in re...

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Autores principales: Santonja, Isabel, Bogl, Leonie H., Degenfellner, Jürgen, Klösch, Gerhard, Seidel, Stefan, Schernhammer, Eva, Papantoniou, Kyriaki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9980854/
https://www.ncbi.nlm.nih.gov/pubmed/36864319
http://dx.doi.org/10.1007/s00394-023-03113-z
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author Santonja, Isabel
Bogl, Leonie H.
Degenfellner, Jürgen
Klösch, Gerhard
Seidel, Stefan
Schernhammer, Eva
Papantoniou, Kyriaki
author_facet Santonja, Isabel
Bogl, Leonie H.
Degenfellner, Jürgen
Klösch, Gerhard
Seidel, Stefan
Schernhammer, Eva
Papantoniou, Kyriaki
author_sort Santonja, Isabel
collection PubMed
description PURPOSE: This study aimed at describing meal-timing patterns using cluster analysis and explore their association with sleep and chronic diseases, before and during COVID-19 mitigation measures in Austria. METHODS: Information was collected in two surveys in 2017 (N = 1004) and 2020 (N = 1010) in representative samples of the Austrian population. Timing of main meals, nighttime fasting interval, last-meal-to-bed time, breakfast skipping and eating midpoint were calculated using self-reported information. Cluster analysis was applied to identify meal-timing clusters. Multivariable-adjusted logistic regression models were used to study the association of meal-timing clusters with prevalence of chronic insomnia, depression, diabetes, hypertension, obesity and self-rated bad health status. RESULTS: In both surveys, median breakfast, lunch and dinner times on weekdays were 7:30, 12:30 and 18:30. One out of four participants skipped breakfast and the median number of eating occasions was 3 in both samples. We observed correlation between the different meal-timing variables. Cluster analysis resulted in the definition of two clusters in each sample (A17 and B17 in 2017, and A20 and B20 in 2020). Clusters A comprised most respondents, with fasting duration of 12–13 h and median eating midpoint between 13:00 and 13:30. Clusters B comprised participants reporting longer fasting intervals and later mealtimes, and a high proportion of breakfast skippers. Chronic insomnia, depression, obesity and self-rated bad health-status were more prevalent in clusters B. CONCLUSIONS: Austrians reported long fasting intervals and low eating frequency. Meal-timing habits were similar before and during the COVID-19-pandemic. Besides individual characteristics of meal-timing, behavioural patterns need to be evaluated in chrono-nutrition epidemiological studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00394-023-03113-z.
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spelling pubmed-99808542023-03-03 Meal-timing patterns and chronic disease prevalence in two representative Austrian studies Santonja, Isabel Bogl, Leonie H. Degenfellner, Jürgen Klösch, Gerhard Seidel, Stefan Schernhammer, Eva Papantoniou, Kyriaki Eur J Nutr Original Contribution PURPOSE: This study aimed at describing meal-timing patterns using cluster analysis and explore their association with sleep and chronic diseases, before and during COVID-19 mitigation measures in Austria. METHODS: Information was collected in two surveys in 2017 (N = 1004) and 2020 (N = 1010) in representative samples of the Austrian population. Timing of main meals, nighttime fasting interval, last-meal-to-bed time, breakfast skipping and eating midpoint were calculated using self-reported information. Cluster analysis was applied to identify meal-timing clusters. Multivariable-adjusted logistic regression models were used to study the association of meal-timing clusters with prevalence of chronic insomnia, depression, diabetes, hypertension, obesity and self-rated bad health status. RESULTS: In both surveys, median breakfast, lunch and dinner times on weekdays were 7:30, 12:30 and 18:30. One out of four participants skipped breakfast and the median number of eating occasions was 3 in both samples. We observed correlation between the different meal-timing variables. Cluster analysis resulted in the definition of two clusters in each sample (A17 and B17 in 2017, and A20 and B20 in 2020). Clusters A comprised most respondents, with fasting duration of 12–13 h and median eating midpoint between 13:00 and 13:30. Clusters B comprised participants reporting longer fasting intervals and later mealtimes, and a high proportion of breakfast skippers. Chronic insomnia, depression, obesity and self-rated bad health-status were more prevalent in clusters B. CONCLUSIONS: Austrians reported long fasting intervals and low eating frequency. Meal-timing habits were similar before and during the COVID-19-pandemic. Besides individual characteristics of meal-timing, behavioural patterns need to be evaluated in chrono-nutrition epidemiological studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00394-023-03113-z. Springer Berlin Heidelberg 2023-03-02 2023 /pmc/articles/PMC9980854/ /pubmed/36864319 http://dx.doi.org/10.1007/s00394-023-03113-z Text en © The Author(s) 2023 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/) .
spellingShingle Original Contribution
Santonja, Isabel
Bogl, Leonie H.
Degenfellner, Jürgen
Klösch, Gerhard
Seidel, Stefan
Schernhammer, Eva
Papantoniou, Kyriaki
Meal-timing patterns and chronic disease prevalence in two representative Austrian studies
title Meal-timing patterns and chronic disease prevalence in two representative Austrian studies
title_full Meal-timing patterns and chronic disease prevalence in two representative Austrian studies
title_fullStr Meal-timing patterns and chronic disease prevalence in two representative Austrian studies
title_full_unstemmed Meal-timing patterns and chronic disease prevalence in two representative Austrian studies
title_short Meal-timing patterns and chronic disease prevalence in two representative Austrian studies
title_sort meal-timing patterns and chronic disease prevalence in two representative austrian studies
topic Original Contribution
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9980854/
https://www.ncbi.nlm.nih.gov/pubmed/36864319
http://dx.doi.org/10.1007/s00394-023-03113-z
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