What question did this study set out to answer?

The study aims to investigate how pollutants and hormones contribute to the risk of polycystic ovarian syndrome (PCOS).

January 22, 2026Journal of Ovarian Research0 citationsOpen Access

Prediction of exposure to pollutants and hormones on the risk of polycystic ovarian syndrome

WHWeiming HouUnited States Air Force JDJing DongShenyang Center for Disease Control and Prevention YYYuxin YaoChina Medical University

Key Points

The study aims to investigate how pollutants and hormones contribute to the risk of polycystic ovarian syndrome (PCOS).
Evaluated hormone levels (AMH, Alb) in women with PCOS.
Applied back-propagation neural network for predictive modeling.
Analyzed the impact of environmental pollutants (PM₂.₅) and air pressure on PCOS.
Found elevated AMH and Alb levels in women diagnosed with PCOS.
Demonstrated the back-propagation neural network effectively predicts PCOS influenced by environmental factors.
Indicated a potential link between pollutant exposure and worsened hormonal status for PCOS.

Abstract

Significant elevations in levels of AMH and Alb were detected in women with PCOS. The back-propagation (BP) neural network demonstrated good PCOS predictive performance for the models mediated by environmental factors (PM₂.₅, air pressure). This suggests that these factors may probably exacerbate the effects of sexual function (FSH, PRL, T, AMH) and liver function indicators (Alb, PA) on the risk of developing PCOS. Our results support a potential association between environmental factor exposure and the consequences of PCOS in women.

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Cite This Study

Hou et al. (Tue,) studied this question.

synapsesocial.com/papers/6971be10642b1836717e2aa7 https://doi.org/https://doi.org/10.1186/s13048-026-01981-7

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