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

Hsiao-Hsien Leon Hsu; Jamil M Lane; Lourdes Schnaas; Brent A Coull; Erika Osorio-Valencia; Yueh-Hsiu Mathilda Chiu; Ander Wilson; Allan C Just; Itai Kloog; David Bellinger; Martha M Téllez-Rojo; Robert O Wright

doi:10.1097/EE9.0000000000000291

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

Environ Epidemiol. 2024 Jan 9;8(1):e291. doi: 10.1097/EE9.0000000000000291. eCollection 2024 Feb.

Authors

Hsiao-Hsien Leon Hsu^{1

2}, Jamil M Lane¹, Lourdes Schnaas³, Brent A Coull⁴, Erika Osorio-Valencia³, Yueh-Hsiu Mathilda Chiu^{1

2}, Ander Wilson⁵, Allan C Just^{1

2}, Itai Kloog^{1

2

6}, David Bellinger^{7

8}, Martha M Téllez-Rojo⁹, Robert O Wright^{1

2}

Affiliations

¹ Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York.
² Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, New York.
³ National Institute of Perinatology, Mexico City, Mexico.
⁴ Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts.
⁵ Department of Biostatistics, Colorado State University, Fort Collins, Colorado.
⁶ Department of Geography and Environmental Development, Ben-Gurion University of the Negev, Israel.
⁷ Department of Neurology,Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts.
⁸ National Institute of Public Health, Cuernavaca, Mexico.
⁹ Department of Neurology Research, Harvard Medical School, Boston, Massachusetts.

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 ( $\hat{C E}$ = -0.35, 95% confidence interval [CI] = -0.68, -0.01), quantitative scale ( $\hat{C E}$ = -0.27, 95% CI = -0.74, -0.02), motor scale ( $\hat{C E}$ = -0.25, 95% CI = -0.44, -0.05), and verbal scale ( $\hat{C E}$ = -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.

Abstract

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