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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Detalles Bibliográficos
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:
Original Contribution
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
Descripción
Sumario: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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