BackgroundFine particulate matter (PM2.5) is noxious to female reproductive development and facilitates the occurrence of subsequent diseases. Early menopause is initiative factor of female aging. But due to the lack of historical exposure of PM2.5, we could not gain insight into the linkage between ambient PM2.5 exposure and early menopause. MethodsWe conducted a community-based retrospective cross-sectional study and pooled 1173 postmenopausal women. The machine learning algorithm of LightGBM was processed to derive the historical concentrations of PM2.5 based on aerography of 1956–2022. The quantile g-computation and binary logistic regression were employed to estimate the mixed and single associations between PM2.5 and early menopause. ResultsThe visibility topped the most important feature for derivations of historical PM2.5 concentrations. The R2 of 10-fold cross-validation and predictive capability during processing were all above 0.8. The prevalence of early menopause was 7.3 %. Each 10 µg/m3 PM2.5 increased the prevalence of early menopause during prior 2 years exposure (OR: 1.49, 95 %CI: 1.03–2.16) and spring and autumn (OR: 1.28, 95 %CI: 1.07–1.54). After adjusting the reverse effects of temperature, the prior 2 years exposure of PM2.5 remained positively associated with early menopause in the fourth quantile vs the first quantile (OR: 3.36, 95 %CI: 1.53–7.36) in the spring and autumn. The higher BMI (OR: 1.40, 95 %CI: 1.14–1.72), waistline (OR: 1.42, 95 %CI: 1.09–1.85) and unfavourable dietary habits of less meat (OR: 1.72, 95 %CI: 1.11–2.68), more fried food (OR: 2.39, 95 %CI: 1.15–4.99) elevated the prevalence of early menopause. ConclusionsThe accurate environmental exposure assessment of historical PM2.5 vigorously promoted the researches on the relationship between PM2.5 and early menopause. It sounds the alarm on female infertility menace associated with particulate matter especially during the turbulent 2 years before menopause.
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