Physical activity and sleep profiles in Finnish men and women

Abstract

Background.

Physical activity (PA) and sleep are related to cardiovascular diseases (CVD) and their risk factors. The interrelationship between these behaviors has been studied, but there remain questions regarding the association of different types of PA, such as occupational, commuting, and leisure time to sleep, including quality, duration and sufficiency. It is also unclear to what extent sleep affects peoples’ PA levels and patterns. Our aim is to investigate the interrelationship between PA and sleep behaviors in the Finnish population, including employment status and gender. Methods. The study comprised population based data from the FINRISK 2012 Study. A stratified, random sample of 10,000 Finns, 25 to 74 years-old, were sent a questionnaire and an invitation to a health examination. The participation rate was 64% (n = 6,414). Latent class analysis was used to search for different underlying profiles of PA and sleep behavior in men and women, respectively. Models with one through five latent profiles were fitted to the data. Based on fit indicators, a four-class model for men and women, respectively, was decided to be the best fitted model. Results.

Four different profiles of PA and sleep were found in both men and women. The most common profile of men comprised 45% of the total participants, and in women, 47%. These profiles were distinguished by probabilities for high leisure time PA and sleep, subjectively rated as sufficient, as well as sleep duration of 7–7.9 hours. The least common profiles represented 5% (men) and 11% (women) of the population, and were characterized by probabilities for physical inactivity, short sleep, and evening type for women and morning type for men. There was also one profile in both genders characterized by likelihood for both high occupational PA and subjectively experienced insufficient sleep. Conclusions.

The use of latent class analysis in investigating the interrelationship between PA and sleep is a novel perspective. The method provides information on the clustering of behaviors in people and the profiles found suggest an accumulative nature of leisure time PA, and better sleep. Our data also suggest that high levels of occupational PA are associated with shorter and poorer sleep.