Abstract
OBJECTIVE: Obesity is a common feature in women with polycystic ovary syndrome (PCOS) and potentially significantly influences reproductive function. However, opinions are divided as to which factor is a more appropriate obesity predictor of reproductive outcomes. The aim of this study was to investigate the discriminatory capability of anthropometric measures in predicting reproductive outcomes in Chinese women with PCOS. METHODS: A total of 998 women with PCOS from PCOSAct were included. Logistic regression models were used to compute the odds ratios (ORs) and 95% confidence interval (95% CIs) to assess the effect of anthropometric measures, including body mass index (BMI), waist circumference (WC), hip circumference (HC), the waist‒hip ratio (WHR) and the waist‒height ratio (WHtR), on reproductive outcomes. The discrimination abilities of the models were assessed and compared based on the area under the receiver operating characteristic curve (AUC), Akaike's information criterion (AIC) and integrated discrimination improvement (IDI). RESULTS: Among PCOS women, there was a graded association between anthropometric measures and predicted reproductive outcomes across quintiles of anthropometric measures, including a linear association among WHR, BMI and reproductive outcomes and among waist circumference, WHtR and live birth, pregnancy, and ovulation. However, only a linear association was noted between the hip and ovulation. C-statistic comparisons and IDI analyses revealed a trend towards a significant superiority of BMI for ovulation and WHR for live birth, pregnancy and conception in the models. Combining obesity variables improved discrimination in the multivariable models for reproductive outcomes. CONCLUSIONS: Our findings support that BMI is a better predictor of ovulation and that the WHR is a better predictor of live birth, pregnancy and conception, whereas the combination of obesity variables contributes to the discrimination of reproduction.