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Modeling the effects of prenatal PM2.5 exposure on development of school-aged children using functional regression
Paolo Girardi1, Libera Ylenia Mastromatteo2, Silvia Lanfranchi2
1Department of Environmental Science, Informatics and Statistics, Ca' Foscari University of Venice, Via Torino, 155, Mestre, Italy.
Abstract:
Emerging evidence suggests that prenatal exposure to fine particulate matter (PM2.5) may adversely affect child neurodevelopment. However, studies evaluating the multidimensional nature and timing of these effects remain limited. This study investigated the association between prenatal PM2.5 exposure and child developmental outcomes in a cohort of Italian school-age children, with a focus on identifying critical exposure windows during gestation and recent WHO-recommended thresholds. Data were drawn from an observational study in Italy conducted between 2021-2022. Child development was assessed at school-age using the Developmental Profile 4 (DP-4), covering five key domains: physical, adaptive behavior, cognitive, social-emotional, and communication. Prenatal PM2.5 exposure was estimated using the satellite reanalysis dataset, and penalized functional regression models were applied to evaluate time-varying associations across pregnancy. Models adjusted for a wide range of maternal, paternal, child, and family-related confounders. Higher exposure to PM2.5 during pregnancy was significantly associated with lower total DP-4 scores. The strongest effects were observed in the cognitive and socio-emotional domains, and for exposure from the fifth month of pregnancy onward. With respect to the WHO-recommended threshold of 5μg/m3, children exhibited an average reduction of about 3 points in total developmental scores. Prenatal exposure to PM2.5, particularly during mid-to-late pregnancy, is associated with deficits in key domains of child development. These findings underscore the importance of stringent air quality standards to protect fetal brain development, especially in highly polluted regions.
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