Prenatal Ambient Air Pollutant Mixture Exposure and Neurodevelopment in Urban Children in the Northeastern United States
Harris Jamal1, Yueh-Hsiu Mathilda Chiu2, Ander Wilson4, Hsiao-Hsien Leon Hsu2, Nicole Mathews3, Itai Kloog2, David Bellinger5, Naim Xhani2, Robert Wright2, Brent Coull6, Rosalind Wright2
1Augusta University/University of Georgia Medical Partnership, Medical College of Georgia, 2Department of Environmental Medicine and Public Health, 3The Kravis Children's Hospital, Department of Pedicatrics, Icahn School of Medicine at Mount Sinai, 4Department of Statistics, Colorado State University, 5Department of Neurology and Psychiatry, Boston Children's Hospital, 6Department of Biostatistics, Harvard T.H. Chan School of Public Health
Objective:
To examine associations between prenatal maternal exposure to a mixture of seven air pollutants using daily estimates of exposure, including two gaseous pollutants (NO2, O3) and five PM2.5 constituents (OC, EC, NO3−, SO42−, NH4+), and neurocognitive outcomes, including memory and attention domains, in early school-aged children from an urban pregnancy cohort in the Northeastern United States (US). 
Background:
Studies examining prenatal air pollution (AP) exposure and child neurodevelopment largely focus on single pollutants. We assessed effects of prenatal exposure to a mixture of pollutants on children’s cognition.
Design/Methods:

Analyses included 236 children born at ≥37 weeks gestation in the Northeastern US. Maternal residence-specific daily exposure to nitrogen dioxide (NO2), ozone (O3), and constituents of fine particles [elemental carbon (EC), organic carbon (OC), nitrate (NO3−), sulfate (SO42−), ammonium (NH4+)] were estimated using satellite-based hybrid or global 3-D chemical-transport models. Attention (Conners' CPT-II, WRAML-2), and general memory (WRAML-2) were assessed at 6.5±0.98 years. Time-weighted pollutant exposure levels were estimated using Bayesian Kernel Machine Regression Distributed Lag Models. Resulting weighted exposures were used in Weighted Quantile Sum regressions adjusted for sex, maternal age, education, and temperature.


Results:

Mothers were primarily Hispanic and/or Black (81%) reporting ≤12 years education (68%). The prenatal AP mixture predicted decreased WRAML-2 memory-related attention/concentration (β=-1.03, 95%CI=-1.78 to -0.27) and general memory (β=-0.64, 95%CI=-1.40 to 0.00) and increased CPT-II omission errors (β=1.55, 95%CI=0.34–2.77). Associations with omission errors were stronger in boys; associations with memory-related indices were stronger among girls. Traffic-related pollutants including SO42−, NO2, and EC were major contributors.


Conclusions:

Prenatal exposure to an AP mixture predicted adverse child cognitive outcomes in a sex-and domain-specific manner. Identification of APs within a mixture driving health effects in a particular geographic region can provide insight on source-specific effects, inform targeted regulatory and prevention policies, and assist clinicians in providing tailored patient education and counseling.


10.1212/WNL.0000000000209014
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