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National Adolescent School-based Health Survey - PeNSE 2015: Sedentary behavior and its correlates
Roberta Mendes Abreu Silva1, Amanda Cristina de Souza Andrade2,3,4, Waleska Teixeira Caiaffa3,4
1Multidisciplinary Institute in Health, Anísio Teixeira Campus, Federal University of Bahia, Vitória da Conquista, Bahia, Brazil.
Objective:
To investigate the association between sedentary behavior (SB) and sociodemographic, social support, behavioral, and health variables among Brazilian adolescents.
Methods:
The 2015 National Adolescent School-based Health Survey (PeNSE) was a cross-sectional study consisting of 102,072 Brazilian ninth-graders (mainly aged 13-15 years). SB was defined as the time (in hours) watching television, using a computer, playing video games, talking to friends, or doing other activities in a sitting position. For analysis purposes, SB was categorized into different cut-offs as per the sample distribution quartiles: >2 versus <2 (25th percentile); >4 versus <4 (50th 26 percentile) and >6 versus <6 (75th 27 percentile). We employed Poisson univariate and multivariate regression analyses with robust variance and hierarchical entry of variables for each cut-off point.
Results:
The prevalence rates of each SB cut-off point were 68.15% (CI: 67.44-68.86), 44.15% (CI: 43.40-44.90) and 24.97% (CI:24.37-25.57) for >2, >4 and >6 hours, respectively. The following characteristics were positively and significantly associated with each SB cut-off point in the final models: females, current employment, higher household economic status and higher maternal schooling, lower levels of parents checking homework, tobacco and alcohol use, soft drink and fruit consumption, and regular, poor or very poor self-assessed health status. Conversely, students who self-declared brown were less likely to be classified as a SB cut-off point. Significant associations with age, report of close friends, and physical activity varied by different SB cut-off points.
Conclusion:
Understanding the SB correlates in their different dimensions contributes to the identification of subgroups of adolescents with higher SB prevalence, which is crucial in the development and improvement of public policies. The demographic and behavioral characterization of these groups can guide the development of future intervention strategies, considering the school and family contexts of these adolescents.
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