Li He1, Xiaoyan Li2, Weidong Wang3, Youfa Wang4, Haiyan Qu5, Yang Zhao6,7, Danhua Lin8. 1. College of Physical Education and Sports, Beijing Normal University, Beijing, China. 2. Institute of Developmental Psychology, Beijing Normal University, Beijing, China. 3. School of Sociology and Population Studies, Renmin University of China, Beijing, China. 4. Global Health Institute, School of Public Health, Xi'an Jiaotong University, Xi'an, China. 5. Department of Health Services Administration, University of Alabama at Birmingham, Birmingham, USA. 6. The George Institute for Global Health at Peking University Health Science Centre, Beijing, China. 7. WHO Collaborating Centre on Implementation Research for Prevention & Control of NCDs, Melbourne, VIC, Australia. 8. Institute of Developmental Psychology, Beijing Normal University, Beijing, China. danhualin@bnu.edu.cn.
Abstract
BACKGROUND: Influence of migration on externalized behavioral problems (e.g., aggressive) among adolescents has been well assessed, yet lifestyle behaviors of migrant, left-behind and local adolescents have been largely overlooked by researchers and policy-makers. Therefore, this study aimed to identify clustering of multiple lifestyle behaviors and their associations with migrant status among Chinese adolescents. METHODS: A cross-sectional survey was conducted in 2015 in Beijing, and Wuhu city (Anhui province). Adolescents self-reported age, gender, family economic status, migrant situation, and lifestyle behaviors (i.e., physical activity, screen time, sleep, smoke, soft-drink, alcohol, fruit and vegetable consumption) via a battery of validated questionnaires. Latent class analysis was conducted to identify behavioral clusters using Mplus 7.1. ANOVA, and multivariable logistic regression were used to examine associations between migrant situations and behavioral clusters using SPSS 22. RESULTS: Three distinct behavioral clusters were exhibited among 1364 students (mean age: 13.41 ± 0.84 years): "low risk" (N = 847), "moderate risk" (N = 412) and "high risk" (N = 105). The "high-risk" cluster had the highest prevalence of adolescents not meeting healthy behavioral recommendations. There were no significant differences in the prevalence of high-risk lifestyle among migrant, left-behind, rural local and urban local adolescents. But migrant adolescents had the lowest prevalence of low-risk lifestyle, followed by left-behind, rural and urban local adolescents. Moreover, compared with urban local, migrant (OR = 2.72, 95%CI: 1.88,3.94), left-behind (OR = 2.28, 95%CI: 1.46, 3.55), and rural local (OR = 1.76, 95%CI:1.03,3.01) adolescents had a higher risk of moderate-risk lifestyle. CONCLUSIONS: Clustering of assessed lifestyle behaviors differed by the migrant status. Particularly, migrant and left-behind adolescents were more likely to have moderate-risk lifestyle compared with their counterparts. Interventions that promote moderate to vigorous physical activity and consumption of fruits and vegetables simultaneously are needed among them.
BACKGROUND: Influence of migration on externalized behavioral problems (e.g., aggressive) among adolescents has been well assessed, yet lifestyle behaviors of migrant, left-behind and local adolescents have been largely overlooked by researchers and policy-makers. Therefore, this study aimed to identify clustering of multiple lifestyle behaviors and their associations with migrant status among Chinese adolescents. METHODS: A cross-sectional survey was conducted in 2015 in Beijing, and Wuhu city (Anhui province). Adolescents self-reported age, gender, family economic status, migrant situation, and lifestyle behaviors (i.e., physical activity, screen time, sleep, smoke, soft-drink, alcohol, fruit and vegetable consumption) via a battery of validated questionnaires. Latent class analysis was conducted to identify behavioral clusters using Mplus 7.1. ANOVA, and multivariable logistic regression were used to examine associations between migrant situations and behavioral clusters using SPSS 22. RESULTS: Three distinct behavioral clusters were exhibited among 1364 students (mean age: 13.41 ± 0.84 years): "low risk" (N = 847), "moderate risk" (N = 412) and "high risk" (N = 105). The "high-risk" cluster had the highest prevalence of adolescents not meeting healthy behavioral recommendations. There were no significant differences in the prevalence of high-risk lifestyle among migrant, left-behind, rural local and urban local adolescents. But migrant adolescents had the lowest prevalence of low-risk lifestyle, followed by left-behind, rural and urban local adolescents. Moreover, compared with urban local, migrant (OR = 2.72, 95%CI: 1.88,3.94), left-behind (OR = 2.28, 95%CI: 1.46, 3.55), and rural local (OR = 1.76, 95%CI:1.03,3.01) adolescents had a higher risk of moderate-risk lifestyle. CONCLUSIONS: Clustering of assessed lifestyle behaviors differed by the migrant status. Particularly, migrant and left-behind adolescents were more likely to have moderate-risk lifestyle compared with their counterparts. Interventions that promote moderate to vigorous physical activity and consumption of fruits and vegetables simultaneously are needed among them.
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