Exploring the associations between chronotype, meal frequency, and physical activity: A population-based study in adults.

ABSTRACT

Chronotype is an established concept designed to capture the internal clock's phase in real-life conditions. It is vital in many aspects of daily life and can interfere considerably with numerous factors in a given population. Recognizing nonmodifiable and modifiable factors is crucial for identifying covariates of interest when studying the link between chronotype and health status. To date, chronotype and its related factors have not been extensively investigated. The present study aimed to explore the association of chronotypes with meal frequency, physical activity, and demographic factors among the Saudi population. This cross-sectional web-based questionnaire involved 1369 adults (aged 18 years and above) from the general public in Saudi Arabia and was conducted between March and May 2019. Chronotype was assessed using the reduced version of the original Horne and Ostberg morningness-eveningness questionnaire (MEQ). Meal frequencies and demographics data (age, gender, marital status, place of residence, educational level, employment status, income) were obtained. Physical activity level was also obtained using the international physical activity questionnaire. The MEQ scores group individuals into three categories morning-type, neither-type, and evening-type. The neither-type individuals represented 41.6% (95% confidence interval [CI], 37.5% - 45.6%) of the study population, followed by the morning-type (34.1%; 95% [CI], 29.8% - 38.4%), then the evening-type (24.3%, 95% [CI], 19.6% - 28.9%). Chronotype was significantly associated with age, marital status, employment status and monthly income (All p < 0.05). Significant associations between chronotype with meal frequencies (number of meals per day, breakfast frequency, lunch frequency, and dinner frequency) and physical activity were also observed (All p < 0.05). This study highlights that meal frequencies and physical activity levels are associated with chronotype distribution. Furthermore, demographics, including age, marital status, employment status, and income, were associated with chronotype distribution.