Elucidating the associations among objective smartphone use metrics, physical activity, and sedentary behavior in physically active university students: A cross-sectional study.

Abstract

Introduction: Clarifying the behavioral mechanisms linking lifestyle factors to movement patterns is essential for advancing health promotion and preventing chronic disease. Although smartphone use has been linked to sedentary behavior (SB), evidence remains limited when both variables are assessed objectively, particularly among physically active populations. Objective: This study investigated the association between device-derived smartphone metrics and accelerometer-based movement behaviors in physically active university students, while also examining their potential utility as markers of sedentary patterns relevant to cardiometabolic health. Material and methods: A cross-sectional study was conducted in 44 Physical Education students (75.0% men; 21.8 ± 2.1 years) who met the World Health Organization PA recommendations. Screen time and unlock frequency were recorded over seven days using built-in smartphone applications, while SB, light-intensity PA (LPA), and moderate-to-vigorous PA were assessed with hip-worn triaxial accelerometers. Anthropometric and cardiovascular parameters were also measured. Correlation and exploratory moderation analyses were performed. Results: Participants averaged 349 ± 101 min/day of screen time and 122 ± 50 unlocks/day. Screen time was not associated with SB or PA. In contrast, unlock frequency was positively associated with SB (r = .311, p = .040), LPA (r = .311, p = .040), and combined SB + LPA (r = .421, p = .004), but not with anthropometric or cardiovascular indicators. Moderation analysis suggested that the association between unlock frequency and SB was significant only at higher waist-to-height ratio values (WtHR ≥ 0.505). Discussion: The absence of associations with screen time may reflect the portable and multifunctional nature of smartphones, which allows their use in both sedentary and active contexts, so that total usage aggregates heterogeneous behaviors. In contrast, unlock frequency captures how often ongoing activities are interrupted to engage with the device, which may be more closely linked to the accumulation of low-intensity movement patterns. Conclusions: Unlock frequency may be a more informative digital indicator of sedentary patterns than screen time in active young adults. These preliminary findings support incorporating digital behavior metrics into future research and health-promotion strategies targeting SB.