Heterogeneity and associated factors of patients with polycystic ovary syndrome health behaviors: a latent class analysis

Author:

liu Ying,Guo Yunmei,Ding Rui,Yan Xin,Tan Huiwen,Wang Xueting,Wang Yousha,Wang LianHong

Abstract

Abstract Objective Using latent class to analyze whether there are subtypes of health behaviors in patients with PCOS can be addressed using targeted interventions. Methods October 2021 to June 2022, 471 PCOS patients were surveyed using the Health Promoting Lifestyle Profile Questionnaire. Latent class analysis (LCA) was used to identify subgroups of PCOS patients. Subsequent multinomial latent variable regressions identified factors that were associated with health behaviors. Results A three-class subtypes was the optimum grouping classification: (1)High healthy behavior risk; (2)high healthy responsibility and physical activity risk; (3)low healthy behavior risk. The multinomial logistic regression analysis revealed that (1)Single (OR = 2.061,95% CI = 1.207–3.659), Education level is primary school or below (OR = 4.997,95%CI = 1.732–14.416), participants is student (OR = 0.362,95%=0.138–0.948), participants with pregnancy needs (OR = 1.869,95%=1.009–3.463) were significantly more likely to be in the high healthy behavior risk subtypes; (2)The older the age (OR = 0.953,95%=0.867–1.047) and the larger the WC (OR = 0.954,95%=0.916–0.993), participants is married (OR = 1.126,95%=0.725–1.961), participants is employed ( OR = 1.418,95%=0.667–3.012) were significantly more likely to be in the high health responsibility and physical activity risk subtypes. Conclusion Patients with PCOS are a heterogeneous population with potential subtypes that may be suitable for customized multi-level care and targeted interventions.

Funder

the health commission of Guizhou Province, China

the science and technology department of Guizhou Province, China

Zunyi Science and Technology Planning Project

Publisher

Springer Science and Business Media LLC

Subject

General Medicine,Endocrinology, Diabetes and Metabolism

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