Poor ovarian response is associated with air pollutants: A multicentre study in China

BackgroundHuman evidence on the association between air pollution and ovarian response is scarce. Poor ovarian response (POR) with an incidence of 5–35% is a tricky problem in IVF treatment.MethodsIn this large-scale multicentre study, we included 2186 women with POR (< 4 oocytes retrieved) and 7033 women with a normal ovarian response (10–15 oocytes retrieved), who underwent their first in vitro fertilization treatment in five cities in northern China during 2015–2020. Average concentrations of six air pollutants (PM2.5, PM10, O3, NO2, CO, and SO2) during different exposure windows (5 days, 1, 3, 6, and 12 months) before oocyte pick up (OPU) were calculated using data from the air monitoring station nearest to the residential site as approximate individual exposure. Logistic regression models were employed to assess the association between exposure to air pollutants and the risk of POR. Stratification analyses were conducted based on female age. Sensitivity analyses were performed in poor responders identified by Bologna criteria and women with unexpected POR.FindingsWe detected that increased SO2 exposure during all exposure windows before OPU was associated with a higher risk of POR, especially for women ≤ 30 years old. In the stratified analysis, the effect sizes were larger for the unexpected poor ovarian response.InterpretationThe findings provide human evidence for adverse effects of exposure to ambient air pollutants on ovarian response and underscore the need to reduce ambient air pollution exposure in women of reproductive age to protect human fertility.FundingThis study was granted from the National Key Research and Development Program (2018YFC1004203), the Major Special Construction Plan for Discipline Construction Project of China Medical University (3110118033), the Shengjing Freelance Researcher Plan of Shengjing Hospital of China Medical University, and the National Natural Science Foundation of China (82071601), the Central Government Special Fund for Local Science and Technology Development (2020JH6/10500006).