Clustering of South Korean Adolescents’ Health-Related Behaviors by Gender: Using a Latent Class Analysis

• Main Authors: Myungah Chae, Sophia Jihey Chung
• Format: Article
• Language: English
• Published: MDPI AG 2021-03-01
• Series: International Journal of Environmental Research and Public Health
• Subjects: adolescents; gender; health-related behaviors; latent class analysis
• Online Access: https://www.mdpi.com/1660-4601/18/6/3129
• ISSN: 1661-7827; 1660-4601

Background: Health-related behaviors during adolescence could influence adolescents’ health outcomes, leading to either advantageous or deteriorative conditions. Clustering of adolescents’ health-related behaviors by gender identifies the target groups for intervention and informs the strategies to be implemented for behavioral changes. Methods: Data from 1807 adolescents in grades 7 and 10 in a city in South Korea were used. Health-related behaviors including eating habits, physical activity, hand washing, brushing teeth, drinking alcohol, smoking, and Internet use were examined. Latent class analysis (LCA) was used to identify subgroups of adolescents with regard to their health-related behaviors. Results: A four-class model was the most adequate grouping classification across genders: adolescents with (1) healthy behaviors, (2) neither health-promoting nor health-risk behaviors, (3) good hygiene behaviors, and (4) unhealthy behaviors. The majority of both male and female adolescents were classified into the healthy group. Male adolescents belonging to the healthy group were more likely to engage in vigorous physical activities, while vigorous physical activity was not important for female adolescents. The smallest group was the unhealthy group, regardless of gender; however, the proportion of boys in the unhealthy group was almost twice that of girls. Only female adolescents engaged in excessive Internet use, especially the group with neither health-promoting nor health-risk behaviors. Conclusion: To improve adolescents’ health-related behaviors, it would be more effective to develop tailored interventions considering the behavioral profiles of the target groups.