Socioeconomic Correlates of Sedentary Behavior in Adolescents: Systematic Review and Meta-Analysis
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SYSTEMATIC REVIEW
Socioeconomic Correlates of Sedentary Behavior in Adolescents: Systematic Review and Meta-Analysis Gregore I. Mielke1,2 • Wendy J. Brown2 • Bruno P. Nunes1,3 • Inacio C. M. Silva1 Pedro C. Hallal1
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Ó The Author(s) 2016. This article is published with open access at Springerlink.com
Abstract Background The body of evidence on associations between socioeconomic status (SES) and sedentary behaviors in adolescents is growing. Objectives The overall aims of our study were to conduct a systematic review and meta-analysis of this evidence and to assess whether (1) the associations between SES and sedentary behavior are consistent in adolescents from lowmiddle-income and from high-income countries, (2) the associations vary by domain of sedentary behavior, and (3) the associations vary by SES measure. Methods We performed a systematic literature search to identify population-based studies that investigated the association between SES and sedentary behavior in adolescents (aged 10–19 years). Only studies that presented risk estimates were included. We conducted meta-analyses using random effects and univariate meta-regression and calculated pooled effect sizes (ES).
Electronic supplementary material The online version of this article (doi:10.1007/s40279-016-0555-4) contains supplementary material, which is available to authorized users. & Gregore I. Mielke [email protected] 1
Postgraduate Program in Epidemiology, Federal University of Pelotas, Rua Marechal Deodoro 1160, 3rd floor, Pelotas 96020-220, Brazil
2
School of Human Movement and Nutrition Sciences, University of Queensland, Brisbane, QLD, Australia
3
Department of Nursing, Federal University of Pelotas, Pelotas, Brazil
Results Data from 39 studies were included; this provided 106 independent estimates for meta-analyses. Overall, there was an inverse association between SES and sedentary behavior (ES 0.89; 95 % confidence interval [CI] 0.81–0.98). However, the direction of the association varied: in high-income countries, SES was inversely associated with sedentary behavior (ES 0.67; 95 % CI 0.62–0.73), whereas in low-middle-income countries, there was a positive association between SES and sedentary behavior (ES 1.18; 95 % CI 1.04–1.34). In high-income countries, the associations were strongest for screen time (ES 0.68; 95 % CI 0.62–0.74) and television (TV) time (ES 0.58; 95 % CI 0.49–0.69), whereas in low-middle-income countries, the associations were strongest for ‘other’ screen time (i.e., computer, video, study time, but not including TV time) (ES 1.38; 95 % CI 1.07–1.79). All indicators of SES were negatively associated with sedentary behavior in high-income countries, but only resources (income and assets indexes) showed a significant positive association in low-middle-income countries. Conclusion The associations between SES and sedentary behavior are different in high- and low-middle-income countries, and vary by domain of sedentary behavior. These findings suggest that different approaches may be required when developin
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