潜在类别分析在成年女性妇科病高危人群识别中的应用

目的 初步确立成年女性妇科病患病风险的潜在类别，并探究各类别的特征区别及患病风险差异。方法 采用两阶段调查抽取成都市区18～60岁女性成年人进行匿名自填式问卷调查，共回收364份有效问卷。运用潜在类别分析对研究对象特征进行分类比较。结果 当潜在类别数目为2时模型拟合最佳，因两类人群的妇科病患病率不同，可分为低风险型和高风险型两个类别，患病率分别为14.1%和45.1%（OR = 4.987,P＜0.05）。高风险型人群相对较为年长、较低学历、已婚、非学生、多无独居经历，性与生殖健康知识水平较低，发生过性行为者相对较多，性态度较为保守 (P＜0.05)。结论 利用所构建的潜在类别模型，可识别出妇科病患病高危人群，为完善和制定有重点、有针对性的干预措施提供依据，以改善女性生殖健康水平、降低高危人群妇科病患病率。

Application of latent class analysis in the identification of high-risk female adults population of gynecological diseases

Objective The study aimed to preliminarily establish latent class of gynecological diseases among female adults,and to explore the differences in characteristics and risk of gynecological diseases of females in each category. Methods A two-stage survey with an anonymous self-administered questionnaire was conducted to investigate female adults aged 18-60 in the urban of Chengdu. A total of 364 valid questionnaires were collected. Latent class analysis(LCA) was used to classify the characteristics of the objects. Results The model fitted well with 2 latent classes. Female adults could be divided into low-risk class and high-risk class according to the difference of gynecological diseases prevalence in the two classes(14.1%vs 45.1%, OR= 4.987, P <0.05). Compared with females in low-risk class, high-risk class had more married non-student females who were also older with lower education, fewer non-individual life experiences, lower levels of sexual and reproductive health knowledge, more sexual behaviors experiences, and more conservative sexual attitudes(P <0.05).Conclusion Using the latent class model constructed, high-risk groups of gynecological diseases can be identified, which can contribute to formulate targeted interventions to improve female reproductive health and reduce the prevalence of gynecological diseases in high-risk groups.