Background: Physical activity, sleep, and sedentary behaviors compose 24-h movement behaviors and have been independently associated with depressive symptoms. However, it is not clear whether it is the movement behavior itself or other contextual factors that are related to depressive symptoms. The objective of the present study was to examine the associations between self-reported and accelerometer-measured movement behaviors and depressive symptoms in adolescents.
Methods: Cross-sectional data from 610 adolescents (14-18 years old) were used. Adolescents answered questions from the Center for Epidemiological Studies Depression scale and reported time spent watching videos, playing videogames, using social media, time spent in various physical activities, and daytime sleepiness. Wrist-worn accelerometers were used to measure sleep duration, sleep efficiency, sedentary time, and physical activity. Mixed-effects logistic regressions were used.
Results: Almost half of the adolescents (48%) were classified as being at high risk for depression (score ≥20). No significant associations were found between depressive symptoms and accelerometer-measured movement behaviors, self-reported non-sport physical activity, watching videos, and playing videogames. However, higher levels of self-reported total physical activity (odd ratio (OR) = 0.92, 95% confidence interval (95%CI): 0.86-0.98) and volume of sports (OR = 0.88, 95%CI: 0.79-0.97), in minutes, were associated with a lower risk of depression, while using social media for either 2.0-3.9 h/day (OR = 1.77, 95%CI: 1.58-2.70) or >3.9 h/day (OR = 1.67, 95%CI: 1.10-2.54), as well as higher levels of daytime sleepiness (OR = 1.17, 95%CI: 1.12-1.22), were associated with a higher risk of depression.
Conclusion: What adolescents do when they are active or sedentary may be more important than the time spent in the movement behaviors because it relates to depressive symptoms. Targeting daytime sleepiness, promoting sports, and limiting social media use may benefit adolescents.
Senior Scientist, CHEO Research Institute