{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["7(2)"],"submitter":["Hsu HL"],"pubmed_abstract":["Research linking prenatal ambient air pollution with childhood lung function has largely considered one pollutant at a time. Real-life exposure is to mixtures of pollutants and their chemical components; not considering joint effects/effect modification by co-exposures contributes to misleading results.<h4>Methods</h4>Analyses included 198 mother-child dyads recruited from two hospitals and affiliated community health centers in Boston, Massachusetts, USA. Daily prenatal pollutant exposures were estimated using satellite-based hybrid chemical-transport models, including nitrogen dioxide(NO<sub>2</sub>), ozone(O<sub>3</sub>), and fine particle constituents (elemental carbon [EC], organic carbon [OC], nitrate [NO<sub>3</sub> <sup>-</sup>], sulfate [SO<sub>4</sub> <sup>2-</sup>], and ammonium [NH<sub>4</sub> <sup>+</sup>]). Spirometry was performed at age 6.99 ± 0.89 years; forced expiratory volume in 1s (FEV<sub>1</sub>), forced vital capacity (FVC), and forced mid-expiratory flow (FEF<sub>25-75</sub>) z-scores accounted for age, sex, height, and race/ethnicity. We examined associations between weekly-averaged prenatal pollution mixture levels and outcomes using Bayesian Kernel Machine Regression-Distributed Lag Models (BKMR-DLMs) to identify susceptibility windows for each component and estimate a potentially complex mixture exposure-response relationship including nonlinear effects and interactions among exposures. We also performed linear regression models using time-weighted-mixture component levels derived by BKMR-DLMs adjusting for maternal age, education, perinatal smoking, and temperature.<h4>Results</h4>Most mothers were Hispanic (63%) or Black (21%) with ≤12 years of education (67%). BKMR-DLMs identified a significant effect for O<sub>3</sub> exposure at 18-22 weeks gestation predicting lower FEV<sub>1</sub>/FVC. Linear regression identified significant associations for O<sub>3,</sub> NH<sub>4</sub> <sup>+</sup>, and OC with decreased FEV<sub>1</sub>/FVC, FEV<sub>1</sub>, and FEF<sub>25-75</sub>, respectively. There was no evidence of interactions among pollutants.<h4>Conclusions</h4>In this multi-pollutant model, prenatal O<sub>3</sub>, OC, and NH<sub>4</sub> <sup>+</sup> were most strongly associated with reduced early childhood lung function."],"journal":["Environmental epidemiology (Philadelphia, Pa.)"],"pagination":["e249"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10097575"],"repository":["biostudies-literature"],"pubmed_title":["Prenatal Ambient Air Pollutant Mixture Exposure and Early School-age Lung Function."],"pmcid":["PMC10097575"],"pubmed_authors":["Wilson A","Kloog I","Wright RJ","Schwartz J","Coull BA","Hsu HL","Wright RO"],"additional_accession":[]},"is_claimable":false,"name":"Prenatal Ambient Air Pollutant Mixture Exposure and Early School-age Lung Function.","description":"Research linking prenatal ambient air pollution with childhood lung function has largely considered one pollutant at a time. Real-life exposure is to mixtures of pollutants and their chemical components; not considering joint effects/effect modification by co-exposures contributes to misleading results.<h4>Methods</h4>Analyses included 198 mother-child dyads recruited from two hospitals and affiliated community health centers in Boston, Massachusetts, USA. Daily prenatal pollutant exposures were estimated using satellite-based hybrid chemical-transport models, including nitrogen dioxide(NO<sub>2</sub>), ozone(O<sub>3</sub>), and fine particle constituents (elemental carbon [EC], organic carbon [OC], nitrate [NO<sub>3</sub> <sup>-</sup>], sulfate [SO<sub>4</sub> <sup>2-</sup>], and ammonium [NH<sub>4</sub> <sup>+</sup>]). Spirometry was performed at age 6.99 ± 0.89 years; forced expiratory volume in 1s (FEV<sub>1</sub>), forced vital capacity (FVC), and forced mid-expiratory flow (FEF<sub>25-75</sub>) z-scores accounted for age, sex, height, and race/ethnicity. We examined associations between weekly-averaged prenatal pollution mixture levels and outcomes using Bayesian Kernel Machine Regression-Distributed Lag Models (BKMR-DLMs) to identify susceptibility windows for each component and estimate a potentially complex mixture exposure-response relationship including nonlinear effects and interactions among exposures. We also performed linear regression models using time-weighted-mixture component levels derived by BKMR-DLMs adjusting for maternal age, education, perinatal smoking, and temperature.<h4>Results</h4>Most mothers were Hispanic (63%) or Black (21%) with ≤12 years of education (67%). BKMR-DLMs identified a significant effect for O<sub>3</sub> exposure at 18-22 weeks gestation predicting lower FEV<sub>1</sub>/FVC. Linear regression identified significant associations for O<sub>3,</sub> NH<sub>4</sub> <sup>+</sup>, and OC with decreased FEV<sub>1</sub>/FVC, FEV<sub>1</sub>, and FEF<sub>25-75</sub>, respectively. There was no evidence of interactions among pollutants.<h4>Conclusions</h4>In this multi-pollutant model, prenatal O<sub>3</sub>, OC, and NH<sub>4</sub> <sup>+</sup> were most strongly associated with reduced early childhood lung function.","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Apr","modification":"2025-04-04T12:43:55.397Z","creation":"2025-04-04T12:43:55.397Z"},"accession":"S-EPMC10097575","cross_references":{"pubmed":["37064424"],"doi":["10.1097/EE9.0000000000000249"]}}