Prospective association between 24-hour movement behaviors and mental health among overweight/obese college students: a compositional data analysis approach - Shuai Wang; Shuai Wang; Wei Liang; Huiqi Song; Ning Su; Lin Zhou; Yanping Duan; Ryan E. Rhodes; Huaxuan Liu; Yi-de Yang; Wing Chung Patrick Lau; Julien Steven Baker (Frontiers Media S.A., 2023)
Background24-h movement behaviors, including light physical activity (LPA), moderate-to-vigorous physical activity (MVPA), screen-based sedentary behavior (SSB), non-screen-based sedentary behavior (NSB) and sleep are crucial components affecting mental health. This study aimed to examine the associations of movement behaviors with mental health outcomes among overweight/obese college students using a compositional data analysis approach.MethodsUsing a prospective design, 437 Chinese college students (20.1 ± 1.7 years, 51.7% female) completed a two-wave online data collection, where demographics and movement behaviors (LPA, MVPA, SSB, NSB, sleep) were collected at baseline, while depression, anxiety and stress were measured at the 2-month follow-up (Apr-Jul 2022). Compositional data analyses were implemented using R.ResultsDepression, anxiety, and stress were negatively associated with time spent in MVPA and sleep (p < 0.001) and positively associated with time spent in SSB and NSB (p < 0.001). Reallocating 15 min to MVPA from LPA, SSB and NSB predicted improvements in depression (LPA: −0.234 unit; SSB: −0.375 unit; NSB: −0.249 unit), anxiety (LPA: −0.092 unit; SSB: −0.284 unit; NSB: −0.165 unit), and stress (LPA: −0.083 unit; SSB: −0.312 unit; NSB: −0.191 unit). For dose-response relationships of 5-55 min isotemporal substitution, when time was reallocated to MVPA from LPA, NSB, and SSB, the estimated detriments to mental health were larger in magnitude than the estimated benefits of time reallocation from MVPA to LPA, NSB, and SSB.ConclusionThe findings emphasize the importance of participating in MVPA to improve mental health in overweight/obese college students during the post-COVID-19 era. The compositional analysis produced clear targets for the time allocation of these behaviors for future interventions and policymaking.