Abstract

Doc number: 76

Abstract

Background: Polycystic ovary syndrome (PCOS) is a common condition estimated to affect 5.61% of Chinese women of reproductive age, but little is known about the prevalence and predictors in Chinese PCOS patients. This study aimed to determine the prevalence and predictors of the metabolic abnormalities in Chinese women with and without PCOS.

Methods: A large-scale national epidemiological investigation was conducted in reproductive age women (19 to 45 years) across China. 833 reproductive aged PCOS women, who participated in the healthcare screening, were recruited from ten provinces in China. Clinical history, ultrasonographic exam (ovarian follicle), hormonal and metabolic parameters were the main outcome measures.

Results: The prevalence of metabolic syndrome (MetS) as compared in PCOS and non-PCOS women from community were 18.2% vs 14.7%, and IR (insulin resistance) were 14.2% vs 9.3% (p < 0.001) respectively. After adjusting for age, the indicators (central obesity, hypertension, fasting insulin, SHBG, dyslipinaemia) for metabolic disturbances were significantly higher in PCOS than in non-PCOS groups. Using multivariate logistic regression, central obesity and FAI were risk factors, while SHBG was a protective factor on the occurrence of Mets and IR in PCOS women (OR: 1.132, 1.105 and 0.995).

Conclusions: The risk factors of the metabolic syndrome and insulin resistance were BMI and FAI for PCOS women, respectively. The decrease of SHBG level was also a risk factor for insulin resistance in both PCOS and metabolic disturbance.

Details

Title
Prevalence and predictors of metabolic abnormalities in Chinese women with PCOS: a cross- sectional study
Author
Li, Rong; Yu, Geng; Yang, Dongzi; Li, Shangwei; Lu, Shulan; Wu, Xiaoke; Wei, Zhaolian; Song, Xueru; Wang, Xiuxia; Fu, Shuxin; Qiao, Jie
Pages
76
Publication year
2014
Publication date
2014
Publisher
BioMed Central
e-ISSN
14726823
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
1564481275
Copyright
© 2014 Li et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.