Sensitive development windows of prenatal air pollution and cognitive functioning in preschool age Mexican children

Abstract

Introduction: Neurotoxicity resulting from air pollution is of increasing concern. Considering exposure timing effects on neurodevelopmental impairments may be as important as the exposure dose. We used distributed lag regression to determine the sensitive windows of prenatal exposure to fine particulate matter (PM_2.5) on children's cognition in a birth cohort in Mexico.

Methods: Analysis included 553 full-term (≥37 weeks gestation) children. Prenatal daily PM_2.5 exposure was estimated using a validated satellite-based spatiotemporal model. McCarthy Scales of Children's Abilities (MSCA) were used to assess children's cognitive function at 4-5 years old (lower scores indicate poorer performance). To identify susceptibility windows, we used Bayesian distributed lag interaction models to examine associations between prenatal PM_2.5 levels and MSCA. This allowed us to estimate vulnerable windows while testing for effect modification.

Results: After adjusting for maternal age, socioeconomic status, child age, and sex, Bayesian distributed lag interaction models showed significant associations between increased PM_2.5 levels and decreased general cognitive index scores at 31-35 gestation weeks, decreased quantitative scale scores at 30-36 weeks, decreased motor scale scores at 30-36 weeks, and decreased verbal scale scores at 37-38 weeks. Estimated cumulative effects (CE) of PM_2.5 across pregnancy showed significant associations with general cognitive index ($\widehat{CE}$ = -0.35, 95% confidence interval [CI] = -0.68, -0.01), quantitative scale ($\widehat{CE}$ = -0.27, 95% CI = -0.74, -0.02), motor scale ($\widehat{CE}$ = -0.25, 95% CI = -0.44, -0.05), and verbal scale ($\widehat{CE}$ = -0.2, 95% CI = -0.43, -0.02). No significant sex interactions were observed.

Conclusions: Prenatal exposure to PM_2.5, particularly late pregnancy, was inversely associated with subscales of MSCA. Using data-driven methods to identify sensitive window may provide insight into the mechanisms of neurodevelopmental impairment due to pollution.

Keywords: Air pollution; Neurodevelopment; Particulate matter; Prenatal exposure; Sensitive windows.

Figure 1.

Predicted PM_2.5 levels in Mexico City. Fine particulate matter (aerodiameter <2.5 μm; PM_2.5) estimated by spatiotemporal land-use regression (LUR) model incorporating satellite data (Just 2014) (R² = 0.74). The model utilizes moderate-resolution imaging spectroradiometer satellite-derived aerosol optical depth (AOD) measurements to derive daily values, and it incorporates day-specific calibrations of AOD data using ground PM_2.5 measurements from 12 monitoring stations, LUR, and meteorological variables reported by the Servicio Meteorológico Nacional (SMN).

Figure 2.

Week-specific associations between weekly prenatal PM_2.5 levels across gestation and McCarthy Scales of Children’s Abilities (MSCA) score. Time-varying association between PM_2.5 exposure over pregnancy and MSCA score modeled by Bayesian distributed lag interaction models. Models were adjusted for maternal age, child age, socioeconomic status, maternal IQ, and maternal blood lead; child’s sex was tested for effect estimates heterogeneity in the model and not stratified by sex. Y axis represents the change in MSCA scaled score associated with a 1 μg/m³ increase in PM_2.5.

Figure 3.

Prenatal PM_2.5 levels across gestation and McCarthy Scales of Children’s Abilities (MSCA) score. Cumulative association and 95% confidence intervals between 1 μg/m³ increase in PM_2.5 exposure over pregnancy and MSCA score modeled by Bayesian distributed lag interaction models. Models were adjusted for maternal age, child age, socioeconomic status, maternal IQ, and maternal blood lead; child’s sex was tested for effect estimates heterogeneity in the model and not stratified by sex. Y axis represents the change in MSCA scaled score associated with a 1 μg/m³ increase in PM_2.5.