Timing of Physical Activity and Associations with BMI and Weekly Physical Activity in Young Adults: A Cross-Sectional Analysis

• Published in: Research quarterly for exercise and sport Vol. 96; no. 3; pp. 573 - 579
• Main Authors: Bailey, Caitlin P., Qian, Jingyi, DiPietro, Loretta, Elmi, Angelo, Napolitano, Melissa A.
• Format: Journal Article
• Language: English
• Published: United States Routledge 01.09.2025
• Subjects: Accelerometry; Adolescent; Adult; Body Mass Index; Cross-Sectional Studies; Exercise - physiology; Female; Humans; Male; Physical activity; Sex Factors; Time Factors; timing; Young Adult; Physical activity; young adult; timing
• ISSN: 0270-1367; 2168-3824; 2168-3824
• DOI: 10.1080/02701367.2025.2463467

The timing of physical activity has been associated with weight and moderate-to-vigorous physical activity (MVPA) in adults. However, few studies have tested associations in young adults, who are biologically and behaviorally different from adults. Young adults (18–35 yr) enrolled in a weight management program provided body mass index (BMI) and 4–7days of ActiGraph accelerometer wear time at baseline. Activity time of day was divided into the following quartiles: morning (06:00–11:59), afternoon (12:00–15:59), evening (16:00–18:59), and night (19:00–00:59). The proportion of weekly MVPA minutes occurring in each time category was used to predict BMI and total weekly MVPA using linear regression models. Marginal trends were estimated for the full sample and by sex. The analytic sample (N = 408, mAge = 23.8±4.5, mBMI = 31.1±4.4) was 79% female, 49% non-Hispanic White, with a mean weekly MVPA of 311±167minutes. MVPA timing was associated with total weekly MVPA but not BMI. Afternoon MVPA was inversely associated with total weekly MVPA in women (−1.72 [95% CI: −3.19, −0.26] min). When considering only bouted MVPA as a predictor, morning (all: 1.43 [95% CI: 0.86, 2.00] min) and night (women: 0.87 [95% CI: 0.15, 1.58] min) MVPA were positively associated with total weekly MVPA. Activity-based interventions designed to improve behavioral health may be improved by providing time-based recommendations tailored to the demographic characteristics of the target population. For example, morning may be an optimal time for both female and male young adults to engage in bouted physical activity to improve total weekly activity levels