ArticleJournal of ovarian research2024
The discriminatory capability of anthropometric measures in predicting reproductive outcomes in Chinese women with PCOS.
Article in Journal of ovarian research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Identification of predictors of the ovarian response to clomiphene citrate in infertile women with polycystic ovary syndrome: AFrontiers in endocrinology · 2026Trial
- Construction and validation of a machine learning model for predicting early pregnancy in patients with polycystic ovary syndrome: a retrospective cohort study.Journal of ovarian research · 2026Article
- Development and validation of a LASSO logistic regression based nomogram for predicting live births in women with polycystic ovary syndrome: a retrospective cohort study.Frontiers in endocrinology · 2025Article
- Gut microbiota and metabolic dysregulation in polycystic ovary syndrome: effects of acupuncture as an adjunct toFrontiers in microbiology · 2025Article
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Authors and funding
11 authors.
Funding
Abstract
objectiveObesity 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.
methodsA 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).
resultsAmong 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.
conclusionsOur 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.
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