Chae Myungah, Han Kihye
College of Nursing, Chung-Ang University, Seoul 06974, Korea.
Healthcare (Basel). 2021 Mar 4;9(3):282. doi: 10.3390/healthcare9030282.
Through a latent class analysis approach, we can classify individuals and identify subgroups according to health behavior patterns, and find evidence for the development of customized intervention programs to target high-risk groups. Our study aimed to explore differences in latent classes of health behaviors in adolescents by region (urban vs. rural areas) in a Korean city. This cross-sectional secondary analysis utilized data collected from all first graders' student health checkups in middle school and high school in a city of the largest island in Korea in 2016 (n = 1807). Health behavior indicators included both healthy (consuming breakfast regularly, consuming vegetables daily, consuming milk daily, consuming fast food on a limited basis, engaging in vigorous physical activities, brushing teeth, and practicing hand hygiene) and unhealthy (drinking, smoking, and overusing the internet) behaviors. Nutritional and diet behaviors were important factors for classifying healthy and unhealthy adolescents in both regions. Approximately 11% of rural students belonged to the risky group, which was characterized by a high level of drinking alcohol and smoking. These results suggest that when developing health policies for adolescents, customized policy-making and education based on the targeted groups' behavioral patterns could be more effective than a uniform approach.
通过潜在类别分析方法，我们可以根据健康行为模式对个体进行分类并识别亚组，为制定针对高危人群的定制化干预方案找到依据。我们的研究旨在探讨韩国一个城市中青少年健康行为潜在类别在地区（城市与农村）上的差异。这项横断面二次分析利用了2016年韩国最大岛屿上一个城市所有初中和高中一年级学生健康检查收集的数据（n = 1807）。健康行为指标包括健康行为（定期吃早餐、每天吃蔬菜、每天喝牛奶、有限度食用快餐、进行剧烈体育活动、刷牙和保持手部卫生）和不健康行为（饮酒、吸烟和过度使用互联网）。营养和饮食行为是两个地区健康和不健康青少年分类的重要因素。约11%的农村学生属于风险组，其特征是饮酒和吸烟程度较高。这些结果表明，在制定青少年健康政策时，基于目标群体行为模式的定制化政策制定和教育可能比统一方法更有效。
