RESUMO
Background: Time spent on screen devices affects sleep quality and duration leading to several health impairments in youth. Although physical activity (PA) benefits sleep patterns and decreases screen time in adolescents, it is unclear whether the relationship between sleep quality/duration and screen time could be influenced by PA levels. Objective: To analyze the association between sleep quality and duration with screen time in Brazilian adolescents according PA levels. Methods: The sample included 1010 adolescents aged 13.2 ± 2.4 years (n = 556 females - 55 % of the sample). Sleep quality and sleep duration, and PA were assessed by Mini Sleep and Baecke questionnaires, respectively. Participants in the highest quartile were classified as physically active. Screen time was analyzed by the self-reported number of hours spent on different screen devices (i.e., television, computer, videogame, and cellphone/tablet). Participants in the highest tertile were classified as having high screen time. Sex, age, and body mass index were considered covariates in binary logistic regression models. Results: Poor sleep quality was observed in 52.3 % of the sample, whereas 46.6 % reported sleeping less than eight hours/day. High screen time was associated with poor sleep quality (OR = 1.45; 95 %CI = 1.01-2.12) and insufficient sleep duration (OR = 1.52; 95 %CI = 1.01-2.03) in adolescents insufficiently active. There were no associations between screen time and sleep parameters in active adolescents. Conclusion: High screen time was associated with poor sleep quality and insufficient sleep duration only in insufficiently active adolescents. These results suggest that high PA levels may contribute to improving sleep patterns in pediatric population.
RESUMO
BACKGROUND: The role of sociodemographic factors in the association between early sports participation (ESP) and sedentary behavior is unclear. We analyzed the association of ESP with sedentary behavior and identified the influence of sociodemographic factors in adulthood. METHODS: A sample of 264 community-dwelling adults was randomly assessed (42.6 [17.0] y old, 57.6% women). Sociodemographic factors (age, gender, and socioeconomic status) and ESP (retrospectively) were assessed by questionnaire. Sedentary behavior was measured by accelerometer and self-reported for domains identification. The association between ESP and sedentary behavior domains and sociodemographic factors was analyzed by Poisson regression and presented in prevalence ratio (PR). Sociodemographic factors were separately included as covariates to identify their role in the main association analysis. RESULTS: The ESP prevalence was 56.4% (n = 149). ESP participants included a higher proportion of men (59.7% vs 20.0%), had a lower age (36.8 [15.3] vs 50.8 [15.9]), and included a smaller proportion of individuals with low socioeconomic status (24.8% vs 43.5%) compared with those without ESP. The ESP was inversely associated with older age (PR = 0.58, P < .001 for middle aged; PR = 0.34, P < .001 for older participants), female gender (PR = 0.79, P < .001), low socioeconomic status (PR = 0.63, P = .036), and TV watching (PR = 0.67, P = .011). ESP was associated with driving (PR = 1.50, P = .028), office/paper work (PR = 1.63, P = .012), and using a cellphone (PR = 1.60, P = .009). The age was the main confounding factor of association between ESP and sedentary behavior, followed by socioeconomic status. No mediation role was identified. CONCLUSION: The ESP was associated with mentally active behavior domains and inversely associated with mentally passive sedentary behavior domains, but this association was majorly affected by sociodemographic factors, mainly by age.