Prenatal and childhood exposure to ambient air pollution and cognitive function in school-age children: Examining sensitive windows and sex-specific associations

A multi-resolution ensemble model of three decision-tree-based algorithms to predict daily NO2 concentration in France 2005-2022

Understanding and managing the health effects of Nitrogen Dioxide (NO2) requires high resolution spatiotemporal exposure maps. Here, we developed a multi-stage multi-resolution ensemble model that predicts daily NO2 concentration across continental France from 2005 to 2022. Innovations of this work include the computation of daily predictions at a 200 m resolution in large urban areas and the use of a spatio-temporal blocking procedure to avoid data leakage and ensure fair performance estimation. Predictions were obtained after three cascading stages of modeling: (1) predicting NO2 total column density from Ozone Monitoring Instrument satellite; (2) predicting daily NO2 concentrations at a 1 km spatial resolution using a large set of potential predictors such as predictions obtained from stage 1, land-cover and road traffic data; and (3) predicting residuals from stage 2 models at a 200 m resolution in large urban areas. The latter two stages used a generalized additive model to ensemble predictions of three decision-tree algorithms (random forest, extreme gradient boosting and categorical boosting). Cross-validated performances of our ensemble models were overall very good, with a ten-fold cross-validated R2 for the 1 km model of 0.83, and of 0.69 for the 200 m model. All three basis learners participated in the ensemble predictions to various degrees depending on time and space. In sum, our multi-stage approach was able to predict daily NO2 concentrations with a relatively low error. Ensembling the predictions maximizes the chance of obtaining accurate values if one basis learner fails in a specific area or at a particular time, by relying on the other learners. To the best of our knowledge, this is the first study aiming to predict NO2 concentrations in France with such a high spatiotemporal resolution, large spatial extent, and long temporal coverage. Exposure estimates are available to investigate NO2 health effects in epidemiological studies.

Association of Exposure to Ambient Air Pollutants With Cognitive Performance and Dementia Risk and the Mediating Role of Pulmonary Function: Evidence From the UK Biobank

BACKGROUND

The pathways by which air pollution affects cognition remain to be explored. This study aimed to explore how single air pollutants [including nitrogen oxide (NOX), nitrogen dioxide (NO2), particulate matter with a diameter of 2.5 micrometers (PM2.5), PM10, and PM2.5-10], and air pollution mixture could affect cognitive function and the incidence of dementia, and determine whether pulmonary function (PF) could play a mediating role in the relationship.

METHODS

Multiple statistical methods were employed to evaluate association of 5 air pollutants (NOX, NO2, PM2.5, PM10, and PM2.5-10) with cognitive function. Bootstrap method was used to estimate mediating role of PF in the association of air pollutants with cognition or the incidence of dementia.

RESULTS

A mixture of air pollutants was associated with performance on 5 cognitive tests, and global cognition (p < .05). Significantly negative association was also identified between mixture of air pollutants and PF (β= -0.020, 95% confidence interval (CI) = -0.029 to -0.011). In addition, as PF scores increase, performance on all cognitive tests significantly improve, although the risk of dementia correspondingly decreases. It was noted that PF was shown to mediate the effects of air pollution mixtures on all cognitive tests as well as global cognition. For global cognition, PF mediated 6.08% of the association. PF was also found to have a mediating role in the association between NOX, NO2, PM2.5, and the risk of dementia.

CONCLUSIONS

Mixed air pollution may impact cognitive function, with PF potentially mediating this relationship.

Placental DNA methylation signatures of prenatal air pollution exposure and potential effects on birth outcomes: an analysis of three prospective cohorts

BACKGROUND

Pregnancy air pollution exposure (PAPE) has been linked to a wide range of adverse birth and childhood outcomes, but there is a paucity of data on its influence on the placental epigenome, which can regulate the programming of physiological functions and affect child development. This study aimed to investigate the association between prenatal air pollutant exposure concentrations and changes in placental DNA methylation patterns, and to explore the potential windows of susceptibility and sex-specific alterations.

METHODS

This multi-site study used three prospective population-based mother-child cohorts: EDEN, PELAGIE, and SEPAGES, originating from four French geographical regions (Nancy, Poitiers, Brittany, and Grenoble). Pregnant women were included between 2003 and 2006 for EDEN and PELAGIE, and between 2014 and 2017 for SEPAGES. The main eligibility criteria were: being older than 18 years, having a singleton pregnancy, and living and planning to deliver in one of the maternity clinics in one of the study areas. A total of 1539 mother-child pairs were analysed, measuring placental DNA methylation using Illumina BeadChips. We used validated spatiotemporally resolved models to estimate PM2·5, PM10, and NO2 exposure over each trimester of pregnancy at the maternal residential address. We conducted a pooled adjusted epigenome-wide association study to identify differentially methylated 5'-C-phosphate-G-3' (CpG) sites and regions (assessed using the Infinium HumanMethylationEPIC BeadChip array, n=871), including sex-specific and sex-linked alterations, and independently validated our results (assessed using the Infinium HumanMethylation450 BeadChip array, n=668).

FINDINGS

We identified four CpGs and 28 regions associated with PAPE in the total population, 469 CpGs and 87 regions in male infants, and 150 CpGs and 66 regions in female infants. We validated 35% of the CpGs available. More than 30% of the identified CpGs were related to one (or more) birth outcome and most significant alterations were enriched for neural development, immunity, and metabolism related genes. The 28 regions identified for both sexes overlapped with imprinted genes (four genes), and were associated with neurodevelopment (nine genes), immune system (seven genes), and metabolism (five genes). Most associations were observed for the third trimester for female infants (134 of 150 CpGs), and throughout pregnancy (281 of 469 CpGs) and the first trimester (237 of 469 CpGs) for male infants.

INTERPRETATION

These findings highlight the molecular pathways through which PAPE might affect child health in a widespread and sex-specific manner, identifying the genes involved in the major physiological functions of a developing child. Further studies are needed to elucidate whether these epigenetic changes persist and affect health later in life.

FUNDING

French Agency for National Research, Fondation pour la Recherche Médicale, Fondation de France, and the Plan Cancer.

Relation of prenatal and postnatal PM2.5 exposure with cognitive and motor function among preschool-aged children

The literature informing susceptible periods of exposure on children's neurodevelopment is limited. We evaluated the impacts of pre- and postnatal fine particulate matter (PM2.5) exposure on children's cognitive and motor function among 1303 mother-child pairs in the Spanish INMA (Environment and Childhood) Study. Random forest models with temporal back extrapolation were used to estimate daily residential PM2.5 exposures that we averaged across 1-week lags during the prenatal period and 4-week lags during the postnatal period. The McCarthy Scales of Children's Abilities (MSCA) were administered around 5 years to assess general cognitive index (GCI) and several subscales (verbal, perceptual-performance, memory, fine motor, gross motor). We applied distributed lag nonlinear models within the Bayesian hierarchical framework to explore periods of susceptibility to PM2.5 on each MSCA outcome. Effect estimates were calculated per 5 μg/m3 increase in PM2.5 and aggregated across adjacent statistically significant lags using cumulative β (βcum) and 95% Credible Intervals (95%CrI). We evaluated interactions between PM2.5 with fetal growth and child sex. We did not observe associations of PM2.5 exposure with lower GCI scores. We found a period of susceptibility to PM2.5 on fine motor scores in gestational weeks 1-9 (βcum = -2.55, 95%CrI = -3.53,-1.56) and on gross motor scores in weeks 7-17 (βcum = -2.27,95%CrI = -3.43,-1.11) though the individual lags for the latter were only borderline statistically significant. Exposure in gestational week 17 was weakly associated with verbal scores (βcum = -0.17, 95%CrI = -0.26,-0.09). In the postnatal period (from age 0.5-1.2 years), we observed a window of susceptibility to PM2.5 on lower perceptual-performance (β = -2.42, 95%CrI = -3.37,-1.46). Unexpected protective associations were observed for several outcomes with exposures in the later postnatal period. We observed no evidence of differences in susceptible periods by fetal growth or child sex. Preschool-aged children's motor function may be particularly susceptible to PM2.5 exposures experienced in utero whereas the first year of life was identified as a period of susceptibility to PM2.5 for children's perceptual-performance.

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

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 (PM2.5) on children's cognition in a birth cohort in Mexico.

Methods

Analysis included 553 full-term (≥37 weeks gestation) children. Prenatal daily PM2.5 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 PM2.5 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 PM2.5 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 PM2.5 across pregnancy showed significant associations with general cognitive index (C E ^ = -0.35, 95% confidence interval [CI] = -0.68, -0.01), quantitative scale (C E ^ = -0.27, 95% CI = -0.74, -0.02), motor scale (C E ^ = -0.25, 95% CI = -0.44, -0.05), and verbal scale (C E ^ = -0.2, 95% CI = -0.43, -0.02). No significant sex interactions were observed.

Conclusions

Prenatal exposure to PM2.5, 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.

Sensitive periods for exposure to indoor air pollutants and psychosocial factors in association with symptoms of psychopathology at school-age in a South African birth cohort

Background

Gestation and the first few months of life are important periods for brain development. During these periods, exposure to environmental toxicants and psychosocial stressors are particularly harmful and may impact brain development. Specifically, exposure to indoor air pollutants (IAP) and psychosocial factors (PF) during these sensitive periods has been shown to predict childhood psychopathology.

Objectives

This study aims to investigate sensitive periods for the individual and joint effects of IAP and PF on childhood psychopathology at 6.5 years.

Methods

We analyzed data from the Drakenstein Child Health Study (N=599), a South African birth cohort. Exposure to IAP and PF was measured during the second trimester of pregnancy and 4 months postpartum. The outcome of childhood psychopathology was assessed at 6.5 years old using the Childhood Behavior Checklist (CBCL). We investigated individual effects of either pre-or postnatal exposure to IAP and PF on CBCL scores using adjusted linear regression models, and joint effects of these exposures using quantile g-computation and self-organizing maps (SOM). To identify possible sensitive periods, we used a structured life course modeling approach (SLCMA) as well as exposure mixture methods (quantile g-computation and SOM).

Results

Prenatal exposure to IAP or PFs, as well as the total prenatal mixture assessed using quantile g-computation, were associated with increased psychopathology. SLCMA and SOM models also indicated that the prenatal period is a sensitive period for IAP exposure on childhood psychopathology. Depression and alcohol were associated in both the pre-and postnatal period, while CO was associated with the postnatal period.

Discussion

Pregnancy may be a sensitive period for the effect of indoor air pollution on childhood psychopathology. Exposure to maternal depression and alcohol in both periods was also associated with psychopathology. Determining sensitive periods of exposure is vital to ensure effective interventions to reduce childhood psychopathology.