Heterogeneity and associated factors of patients with polycystic ovary syndrome health behaviors: a latent class analysis.
BMC Endocr Disord
; 23(1): 135, 2023 Jun 25.
Article
in En
| MEDLINE
| ID: mdl-37357262
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.Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Polycystic Ovary Syndrome
Type of study:
Prognostic_studies
/
Risk_factors_studies
Limits:
Female
/
Humans
/
Pregnancy
Language:
En
Journal:
BMC Endocr Disord
Year:
2023
Document type:
Article
Affiliation country:
China