潜在类别模型在健康行为研究中的应用

Application of latent class model in health behavior study

目的探讨潜在类别模型在广州市社区居民健康行为模式研究中的应用。方法运用潜在类别分析方法识别吃早餐、充足睡眠、适量运动、健康体检和不吸烟等5种健康行为的人群行为模式,根据健康行为模式对人群聚类后,进一步比较不同人群的人口学特征及健康知识得分。结果识别出健康行为模式(69.60%)和次健康行为模式(30.40%)两类人群。和健康行为模式人群相比,次健康行为模式人群中低年龄者较多、男性、单身比例较高、初中文化程度、工人农民和个体户等职业人群比例较多,行政技术人员和离退休人员较少。除常见传染病预防知识得分外,健康行为模式人群的其余各类健康知识得分均高于次健康行为模式人群。结论潜在类别模型可用于人群健康行为模式研究,揭示健康行为干预的重点人群和内容,为制定干预措施提供依据。

Objective To investigate the application of latent class model in patterns of health behavior in Guang- zhou citizens. Methods Latent class analysis （LCA） was used to indentify patterns of health behavior among eating breakfast, enough sleep, moderate exercise, check up and nonsmoking, and to classify the individuals. Further studies were conducted to compare demographic characteristics and health knowledge in different subgroups. Results Two sub- groups of health behabior were identified which included ＂healthy behavioral patterns＂ （69. 60% ） and ＂unhealthy behav- ioral patterns＂ （ 30. 40% ）. Individuals in unhealthy behavioral patterns were more younger, male, single, junior middle school and less workers/self-employed than those in healthy behavioral patterns. Except common infectious disease preven- tion, scores of other health knowledge in healthy behavioral patterns were higher than those of unhealthy behavioral pat- terns. Conclusions Latent class model can be applied in patterns of health behavior to indicate the key health behavior in- tervention and provide evidence for the intervention measures.