Cluster Analysis of Sleep Time and Adolescent Health Risk Behaviors

Abstract

Adolescents are prone to multiple health risk behaviors. These might lead to insufficient sleep, which is inconducive to adolescent growth. Therefore, this study explored the impact of a cluster of adolescent health risk behaviors on sleep time, providing a reference for designing relevant intervention measures. From November to December 2019, a stratified cluster sampling method was used to sample middle and high schools in 4 functional districts of Chongqing, China. A total of 8546 participants were selected for a questionnaire survey. Two-step clustering helped identify the health risk behavior clusters. Multivariate logistic regression models helped examine the association between the different clusters and sleep time. The rate of insufficient sleep was 65.8%. Three types of clusters were identified, namely (1) high-risk (poor) cluster (17.3%), (2) low physical activity (medium) cluster (55.1%), and (3) low-risk (good) cluster (27.6%). The high-risk and low physical activity clusters showed that the adjusted OR values of 1.471 (1.266-1.710) and 1.174 (1.052-1.310) were significantly associated with insufficient sleep (P