Analysis of factors influencing polycystic ovary syndrome in women of reproductive age based on directed acyclic graphs

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Abstract

Polycystic ovary syndrome (PCOS) is a common gynecological endocrine disorder in women of reproductive age that seriously affects both their physical and mental health. The pathogenesis of PCOS is complex and not yet fully understood, and it is crucial to control for bias and analyze the risk factors for its development in order to provide a basis for developing preventive strategies. A case–control study design was used. Patients first diagnosed with PCOS from January 2024 to June 2024 at the First Affiliated Hospital of the University of South China, the Second Affiliated Hospital of the University of South China, and the Affiliated Nanhua Hospital of University of South China were selected as the case group (n = 210). Non-PCOS women attending during the same period were selected as the control group (n = 420). Information was collected using self-administered questionnaires, including the Pittsburgh Sleepiness Scale (PSQI), the Generalized Anxiety Disorder 7 (GAD-7) scale, and the Patient Health Questionnaire (PHQ-9). A directed acyclic graph was used for variable screening. Propensity score matching controlled for confounding variables, and multifactorial logistic regression analysis identified risk factors for PCOS. Multifactorial logistic regression analysis showed that obesity [OR = 4.088, 95% CI (2.580, 6.476), P < 0.001], alcohol consumption [OR = 2.305, 95% CI (1.320, 4.024), P = 0.003], family history of PCOS [OR = 6.468, 95% CI (1.986, 21.067), P = 0.002], low birth weight [OR = 0.637, 95% CI (0.438, 0.927), P = 0.018], and anxiety [OR = 4.905, 95% CI (2.768, 8.693), P < 0.001] were risk factors for PCOS development. BMI ≥ 25 kg/m2, alcohol consumption, family history of PCOS, low birth weight, and anxiety are risk factors for the development of PCOS. Targeted measures should be implemented to address these factors, reducing the incidence of PCOS and promoting female reproductive endocrine health.

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Yu, H., Guo, Y., Ling, Y., Su, Y., & Li, Z. (2025). Analysis of factors influencing polycystic ovary syndrome in women of reproductive age based on directed acyclic graphs. Scientific Reports, 15(1). https://doi.org/10.1038/s41598-025-20980-0

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