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Engineering >> 2021, Volume 7, Issue 2 doi: 10.1016/j.eng.2020.12.006

Hospital-Based Phenotypic Features and Treatment Outcomes of Chinese Women with Polycystic Ovary Syndrome: The Effect of Body Mass Index and Geographic Distribution

a First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin 150040, China
b Xuzhou Central Hospital, Xuzhou 221009, China

# These authors contributed equally to this work.

Received: 2019-04-13 Revised: 2020-02-15 Accepted: 2020-08-20 Available online: 2021-02-10

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Abstract

Genetic, lifestyle, and environmental factors contribute to the etiology of polycystic ovary syndrome (PCOS). Increased body mass index (BMI) exacerbates the reproductive and metabolic parameters and reduces the fecundity of women with PCOS. This is a secondary analysis of a large-sample, multicenter, randomized controlled trial conducted at 21 sites in Chinese mainland. A total of 1000 women diagnosed with PCOS were enrolled in this trial. Of these, 998 women with PCOS were included in the analysis. Increased BMI was associated with more severe menstrual irregularities, elevated testosterone level, higher prevalence of metabolic syndrome, and poorer quality of life. The rates of ovulation per woman for the normal, overweight, and obese BMI groups were 83.0%, 78.2%, and 63.6%, respectively (P < 0.001), and the rates of live birth were 23.6%, 18.1%, and 15.3% (P = 0.030). Northern PCOS patients showed more severe reproductive, glucose, and lipid profiles; less exercise; and lower total ovulation rates compared with PCOS patients from Southern China (74.8% vs 81.2%, absolute difference 6.4%, 95% confidence interval 1.2%–11.5%). The results show the typical phenotypic features of Han women with PCOS in Northern and Southern China. The women living in Northern China showed a higher BMI, more severe glycolipid metabolism profiles, and subsequently worse clinical outcomes by the same interventions than those living in Southern China. The difference in phenotypic features can be explained mostly by differences in BMI and the resulting difference in ovulation.

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