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Meal-timing patterns and chronic disease prevalence in two representative Austrian studies
Isabel Santonja1, Leonie H Bogl2,3, Jürgen Degenfellner2
1Department of Epidemiology, Center for Public Health, Medical University of Vienna, Vienna, Austria. isabel.santonja@meduniwien.ac.at.
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.
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