EP637 - ECE_1605 - Body mass index and waist-to-hip ratio patterns in women with and without polycystic ovary syndrome: evidence from an unselected population

Abstract

Polycystic ovary syndrome (PCOS) is a heterogeneous endocrine disorder among women of reproductive age, often linked to obesity, yet how body mass index (BMI) and waist-hip ratio (WHR) vary across PCOS phenotypes in unselected populations remains unclear. Therefore, this study aimed to examine BMI and WHR patterns in a large multiethnic cohort of women with and without PCOS. A community-based study from eight countries across four continents was included. The primary outcomes were BMI and WHR. Correlations between variables were assessed using Spearman’s rank correlation coefficient, and multicollinearity was evaluated using the variance inflation factor (VIF). Clinical features were compared between non-PCOS and PCOS, and stratified across PCOS phenotypes: classic (hyperandrogenism [HA], ovulatory dysfunction [OD], and/or polycystic ovary morphology [PCOM]), phenotype C (HA and PCOM), and phenotype D (OD and PCOM). Multiple linear and logistic regression analyses were used. This study comprised 9240 women representing 11 ethnic groups, of whom 45.2% were Asian Chinese (Han), followed by 22.2% Persians. Overall, 11.4% of participants were women diagnosed with PCOS, with nearly half exhibiting the classic phenotypes (48.4%). Among women with PCOS, 58.0% had normal BMI, 18.5% were overweight, and 11.7% were obese, while 12% had WHR defined central obesity. Classic and phenotype C were statistically associated with higher BMI, whereas the odds of central obesity were higher in women with classic and phenotype D subtypes. Our findings indicate that in unselected populations, the majority of women with PCOS exhibit a normal BMI, in contrast to clinic-based cohorts, where obesity is markedly overrepresented. Classic and phenotype C were characterized with increased overall adiposity, whereas classic and phenotype D were distinguished by central fat accumulation, highlighting distinct patterns of body fat distribution across PCOS phenotypes. Longitudinal, population-based studies integrating multi-omic data are essential for unraveling BMI-related heterogeneity to advance precision diagnosis and management in PCOS.