11. Mixed Effects Modeling of Multi-site Data-Health Behaviors Among Adolescents in Hong Kong, Macao, Taipei, Wuhan and Zhuhai

An important approach for global health and epidemiology research is to collect and use data from multiple study-sites within one or between various cultures to address high impact medical and health issues. When multisite data are used, it is challenge to deal with data heterogeneity, since such heterogeneity cannot be efficiently addressed using conventional multivariate regression methods. In this chapter, we describe application of mixed effects modeling, a statistical method designated for analyzing longitudinal trials, in analyzing cross-sectional multisite data. We demonstrate the application using data collected among middle and high school students in five Chinese cities (n = 13,950), including Hong Kong, Macau, Taipei, Wuhan, and Zhuhai. Data for lifestyle (sedentary, dietary, physical activity) and addictive behaviors (cigarette smoking, alcohol consumption and participation in gamble) were analyzed as outcomes. Factors at the individual and contextual level, as well as interventions between the two were associated with the outcome variables. Findings of this study indicate that although sharing a similar mainstream Chinese culture, these adolescent participants were significantly different from each other with regard to engagement in health-related behavior and the differences were associated with both individual- and contextual-level factors.