The discriminatory capability of anthropometric measures in predicting reproductive outcomes in Chinese women with PCOS

IF 3.8 3区医学 Q1 REPRODUCTIVE BIOLOGY

Journal of Ovarian Research Pub Date : 2024-09-13 DOI:10.1186/s13048-024-01505-1

Qing Xia, Qi Wu, Jiaxing Feng, Hui He, Wangyu Cai, Jian Li, Jing Cong, Hongli Ma, Liyan Jia, Liangzhen Xie, Xiaoke Wu

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Abstract

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. 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). 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. 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.

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人体测量指标在预测中国多囊卵巢综合征女性生殖结局方面的鉴别能力

肥胖是多囊卵巢综合征（PCOS）妇女的常见特征，可能会严重影响生殖功能。然而，对于哪种肥胖因素更适合预测生殖功能，目前还众说纷纭。本研究旨在探讨人体测量指标在预测中国多囊卵巢综合征女性生殖结局方面的鉴别能力。研究共纳入了 PCOSAct 中的 998 名多囊卵巢综合征女性。采用逻辑回归模型计算几率比（ORs）和 95% 置信区间（95% CIs），以评估人体测量指标（包括体重指数（BMI）、腰围（WC）、臀围（HC）、腰臀比（WHR）和腰高比（WHTR））对生殖结局的影响。根据接收者操作特征曲线下面积（AUC）、阿凯克信息准则（AIC）和综合判别改进（IDI）对模型的判别能力进行了评估和比较。在多囊卵巢综合征妇女中，不同五分位人体测量指标与预测生殖结果之间存在分级关系，包括WHR、BMI与生殖结果之间的线性关系，以及腰围、WHtR与活产、怀孕和排卵之间的线性关系。然而，只有臀围与排卵之间存在线性关系。C 统计量比较和 IDI 分析表明，在模型中，BMI 与排卵、WHR 与活产、怀孕和受孕之间的关系呈显著的优势趋势。在生殖结果的多变量模型中，肥胖变量的组合提高了辨别能力。我们的研究结果表明，体重指数能更好地预测排卵，而 WHR 能更好地预测活产、妊娠和受孕，而肥胖变量的组合有助于提高生殖结果的区分度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Ovarian Research REPRODUCTIVE BIOLOGY-

CiteScore

6.20

自引率

2.50%

发文量

125

审稿时长

>12 weeks

期刊介绍： Journal of Ovarian Research is an open access, peer reviewed, online journal that aims to provide a forum for high-quality basic and clinical research on ovarian function, abnormalities, and cancer. The journal focuses on research that provides new insights into ovarian functions as well as prevention and treatment of diseases afflicting the organ. Topical areas include, but are not restricted to: Ovary development, hormone secretion and regulation Follicle growth and ovulation Infertility and Polycystic ovarian syndrome Regulation of pituitary and other biological functions by ovarian hormones Ovarian cancer, its prevention, diagnosis and treatment Drug development and screening Role of stem cells in ovary development and function.