Prenatal exposure to criteria air pollutants and associations with congenital anomalies: A Lebanese national study

Maternal exposure to air pollution has been associated with a higher birth defect (BD) risk. Previous studies suffer from inaccurate exposure assessment methods, confounding individual-level variations, and classical analytical modelling. This study aimed to examine the association between maternal exposure to criteria air pollutants and BD risk. A total of 553 cases and 10,214 controls were identified from private and public databases. Two subgroups were then formed: one for a matched case-control design, and another for Feature Selection (FS) analysis. Exposure assessment was based on the mean air pollutant-specific levels in the mother’s residential area during the specific BD gestational time window of risk (GTWR) and other time intervals. Multivariate regression models outcomes consistently showed a significant protective effect for folic acid intake and highlighted parental consanguinity as a strong BD risk factor. After adjusting for these putative risk factors and other covariates, results show that maternal exposure to PM₂.₅ during the first trimester is significantly associated with a higher overall BD risk (OR:1.05, 95%CI:1.01–1.09), and with a higher risk of genitourinary defects (GUD) (OR:1.06, 95%CI:1.01–1.11) and neural tube defects (NTD) (OR:1.10, 95%CI:1.03–1.17) during specific GTWRs. Maternal exposure to NO₂ during GTWR exhibited a significant protective effect for NTD (OR:0.94, 95%CI:0.90–0.99), while all other examined associations were not statistically significant. Additionally, maternal exposure to SO₂ during GTWR showed a significant association with a higher GUD risk (OR:1.17, 95%CI:1.08–1.26). When limiting selection to designated monitor coverage radiuses, PM₂.₅ maintained significance with BD risk and showed a significant gene-environment interaction for GUD (p = 0.018), while NO₂ protective effect expanded to other subtypes. On the other hand, FS analysis confirmed maternal exposure to PM₂.₅ and NO₂ as important features for GUD, CHD, and NTD. Our findings, set the basis for building a novel BD risk prediction model.