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Updated: Jul 18, 2025

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity
Published on: March 7, 2019
Weekday and weekend physical activity patterns and their correlates among young adults
Kristin Suorsa1,2, Tuija Leskinen1,2, Suvi Rovio2,3
1Department of Public Health, Turku University Hospital, University of Turku, Turku, Finland.
Background:
Accelerometers enable assessment of within and between day variation in physical activity. The main aim was to examine weekday and weekend physical activity patterns among young adults. Additionally, correlates of the physical activity patterns were examined.
Methods:
Overall 325 adults (mean age 26.0 years, standard deviation 0.03) from the Special Turku Coronary Risk Factor Intervention Project used a wrist-worn ActiGraph accelerometer continuously for 1 week. Physical activity patterns over weekdays and weekends were identified by using the group-based trajectory modeling. Adolescent leisure time physical activity (LTPA) and sociodemographic characteristics (sex, marital and family status, education, work status, occupation, and health consciousness) were examined as possible correlates of physical activity patterns using multinomial regression analysis.
Results:
Five patterns were identified: consistently low activity (45%), active on weekday evenings and weekends (32%), consistently moderate activity (11%), active on weekdays (7%), and consistently high activity (5%). Low adolescent LTPA was associated with consistently low activity pattern in young adulthood. Women were more likely than men to belong in the more physically active groups (all other groups except active on weekdays, odds ratios between 2.26 and 6.17). Those in the active on weekdays group had lower education, were more often in the working life and in manual occupations than those in the consistently low activity group.
Conclusions:
Marked heterogeneity in physical activity patterns across the week was observed among young adults. Especially history of physical activity, sex, education, work status, and occupation were associated with different physical activity patterns.
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