24h movement behaviours in university students compared to working age and older adults: wearable-based evidence and cardiometabolic health implications - Ju Lynn Ong; Shuo Qin; Tara H Martin; Xin Yu Chua; Chun Siong Soon; Gizem Yilmaz; Lieng Hsi Ling; Falk Müller-Riemenschneider; Woon-Puay Koh; Michael WL Chee (BMC Medicine, 2026)
Abstract Background Physical inactivity, sedentary behaviour and inadequate sleep are established risk factors for non-communicable diseases. Although older adults are traditionally expected to be less active and more sedentary than young adults, contemporary social, occupational and educational environments may have changed this. Here, we characterised 24-hour movement behaviours (physical activity [PA], sedentary behaviour [SB], and sleep) across adulthood using wearable devices and examined their cardiometabolic correlates using a compositional data approach. Methods Data were analysed from 1,967 adults across three Singaporean cohorts: university students ( n = 500; mean[SD] age 19.9[1.3] years), working-age adults ( n = 437; 41.1[10.0] years), and community-dwelling older adults ( n = 1,030; 74.0[2.6] years). Each person contributed 4 weeks of Oura Ring recordings on time spent in PA, SB and sleep. BMI, body roundness index (BRI), pulse wave velocity (PWV), and a composite vascular health score (zComposite) were additionally assessed. Associations between reallocations of time across 24 h-movement behaviours and these cardiometabolic outcomes were estimated using compositional data regression models. Results University students accumulated the most SB (mean 633.89 min/day) and the lowest PA (320.28 min/day) and sleep (431.75 min/day), whereas older adults accumulated the least SB (500.86 min/day) and greatest PA (420.28 min/day) and sleep (455.62 min/day). Working-age adults showed profiles in-between the students and older adults (SB: 581.28 min/day; PA: 346.55 min/day; sleep: 445.77 min/day). In compositional models, reallocating 30 min per day to PA from other behaviours was associated with lower BMI (-0.13 kg/m²), BRI (-0.04), PWV (-0.05 m/s), and zComposite (-0.01). Reallocating 30 min per day from SB to other behaviours was associated with lower BMI (-0.28 kg/m²) and BRI (-0.07). Reallocating 30 min per day to sleep from other behaviours was related to lower BMI (-0.21 kg/m 2 ) and BRI (-0.05). Conclusions University students exhibited lower physical activity and higher sedentary time than older adults. Reallocation of time toward greater PA, less SB and longer sleep was associated with lower cardiometabolic risk. These findings challenge conventional expectations about age-related inactivity and highlight young adulthood as a critical, under-recognised target for interventions to promote PA and reduce SB for long-term health.