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Causal Effects of Prenatal Exposure to PM_2.5 on Child Development and the Role of Unobserved Confounding.

ABSTRACT: Prenatal exposure to airborne particles is a potential risk factor for infant neuropsychological development. This issue is usually explored by regression analysis under the implicit assumption that all relevant confounders are accounted for. Our aim is to estimate the causal effect of prenatal exposure to high concentrations of airborne particles with a diameter < 2.5 µm (PM2.5) on children's psychomotor and mental scores in a birth cohort from Gipuzkoa (Spain), and investigate the robustness of the results to possible unobserved confounding. We adopted the propensity score matching approach and performed sensitivity analyses comparing the actual effect estimates with those obtained after adjusting for unobserved confounders simulated to have different strengths. On average, mental and psychomotor scores decreased of -2.47 (90% CI: -7.22; 2.28) and -3.18 (90% CI: -7.61; 1.25) points when the prenatal exposure was ?17 ?g/m³ (median). These estimates were robust to the presence of unmeasured confounders having strength similar to that of the observed ones. The plausibility of having omitted a confounder strong enough to drive the estimates to zero was poor. The sensitivity analyses conferred solidity to our findings, despite the large sampling variability. This kind of sensitivity analysis should be routinely implemented in observational studies, especially in exploring new relationships.

SUBMITTER: Tozzi V

PROVIDER: S-EPMC6888495 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Causal Effects of Prenatal Exposure to PM<sub>2.5</sub> on Child Development and the Role of Unobserved Confounding.

Tozzi Viola V Lertxundi Aitana A Ibarluzea Jesus M JM Baccini Michela M

International journal of environmental research and public health 20191109 22

Prenatal exposure to airborne particles is a potential risk factor for infant neuropsychological development. This issue is usually explored by regression analysis under the implicit assumption that all relevant confounders are accounted for. Our aim is to estimate the causal effect of prenatal exposure to high concentrations of airborne particles with a diameter < 2.5 µm (PM2.5) on children's psychomotor and mental scores in a birth cohort from Gipuzkoa (Spain), and investigate the robustness o ...[more]

PMID: 31717528

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Project description:BackgroundChildhood exposure to air pollution has been linked with maladaptive cognitive development; however, less is known about the association between prenatal fine particulate matter (PM2.5) exposure and childhood behavior.ObjectivesOur aim was to assess the association between prenatal PM2.5 exposure and behavioral development in 4-6 year old children residing in Mexico City.MethodsWe used data from 539 mother-child pairs enrolled in a prospective birth cohort in Mexico City. We estimated daily PM2.5 exposure using a 1 km2 satellite-based exposure model and averaged over each trimester of pregnancy. We assessed childhood behavior at 4-6 years of age using the parent-completed Behavioral Assessment Scale for Children (BASC-2) composite scores and subscales. We used linear regression models to estimate change in BASC-2 T-scores with trimester specific 5-μg/m3 increases in PM2.5. All models were mutually adjusted for PM2.5 exposures during the other trimesters, maternal factors including age, education, socioeconomic status, depression, and IQ, child's age at study visit, and season. We additionally assessed sex-specific effects by including an interaction term between PM2.5 and sex.ResultsHigher first trimester PM2.5 exposure was associated with reduced Adaptive Skills scores (β: -1.45, 95% CI: -2.60, -0.30). Lower scores on the Adaptive Skills composite score and subscales indicate poorer functioning. For PM2.5 exposure during the first trimester, decrements were consistent across adaptive subscale scores including Adaptability (β: -1.51, 95% CI: -2.72, -0.30), Social Skills (β: -1.63, 95% CI: -2.90, -0.36), and Functional Communication (β: -1.21, 95% CI: -2.21, -0.21). The association between 1st trimester PM2.5 and depression was stronger in males than females (β for males: 1.52, 95% CI: -0.41, 3.45; β for females: -0.13, 95% CI: -1.99, 1.72; p-int: 0.07).ConclusionsExposure to PM2.5 during early pregnancy may be associated with impaired behavioral development in children, particularly for measures of adaptive skills. These results suggest that air pollution impacts behavioral domains as well as cognition, and that the timing of exposure may be critical.

Project description:BackgroundExposure to air pollution is associated with increased blood pressure (BP) in adults and children. Some evidence suggests that air pollution exposure during the prenatal period may contribute to adverse cardiorenal health later in life. Here we apply a distributed lag model (DLM) approach to identify critical windows that may underlie the association between prenatal particulate matter ? 2.5 ?m in diameter (PM2.5) exposure and children's BP at ages 4-6 years.MethodsParticipants included 537 mother-child dyads enrolled in the Programming Research in Obesity, GRowth Environment, and Social Stress (PROGRESS) longitudinal birth cohort study based in Mexico City. Prenatal daily PM2.5 exposure was estimated using a validated satellite-based spatio-temporal model and BP was measured using the automated Spacelabs system with a sized cuff. We used distributed lag models (DLMs) to examine associations between daily PM2.5 exposure and systolic and diastolic BP (SBP and DBP), adjusting for child's age, sex and BMI, as well as maternal education, preeclampsia and indoor smoking report during the second and third trimester, seasonality and average postnatal year 1 PM2.5 exposure.ResultsWe found that PM2.5 exposure between weeks 11-32 of gestation (days 80-226) was significantly associated with children's increased SBP. Similarly, PM2.5 exposure between weeks 9-25 of gestation (days 63-176) was significantly associated with increased DBP. To place this into context, a constant 10 ?g/m3 increase in PM2.5 sustained throughout this critical window would predict a cumulative increase of 2.6 mmHg (CI: 0.5, 4.6) in SBP and 0.88 mmHg (CI: 0.1, 1.6) in DBP at ages 4-6 years. In a stratified analysis by sex, this association persisted in boys but not in girls.ConclusionsSecond and third trimester PM2.5 exposure may increase children's BP in early life. Further work investigating PM2.5 exposure with BP trajectories later in childhood will be important to understanding cardiorenal trajectories that may predict adult disease. Our results underscore the importance of reducing air pollution exposure among susceptible populations, including pregnant women.

Project description:It is well recognized that exposure to fine particulate matter (PM2.5) affects health adversely, yet few studies from South America have documented such associations due to the sparsity of PM2.5 measurements. Lima's topography and aging vehicular fleet results in severe air pollution with limited amounts of monitors to effectively quantify PM2.5 levels for epidemiologic studies. We developed an advanced machine learning model to estimate daily PM2.5 concentrations at a 1 km2 spatial resolution in Lima, Peru from 2010 to 2016. We combined aerosol optical depth (AOD), meteorological fields from the European Centre for Medium-Range Weather Forecasts (ECMWF), parameters from the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), and land use variables to fit a random forest model against ground measurements from 16 monitoring stations. Overall cross-validation R2 (and root mean square prediction error, RMSE) for the random forest model was 0.70 (5.97 μg/m3). Mean PM2.5 for ground measurements was 24.7 μg/m3 while mean estimated PM2.5 was 24.9 μg/m3 in the cross-validation dataset. The mean difference between ground and predicted measurements was -0.09 μg/m3 (Std.Dev. = 5.97 μg/m3), with 94.5% of observations falling within 2 standard deviations of the difference indicating good agreement between ground measurements and predicted estimates. Surface downwards solar radiation, temperature, relative humidity, and AOD were the most important predictors, while percent urbanization, albedo, and cloud fraction were the least important predictors. Comparison of monthly mean measurements between ground and predicted PM2.5 shows good precision and accuracy from our model. Furthermore, mean annual maps of PM2.5 show consistent lower concentrations in the coast and higher concentrations in the mountains, resulting from prevailing coastal winds blown from the Pacific Ocean in the west. Our model allows for construction of long-term historical daily PM2.5 measurements at 1 km2 spatial resolution to support future epidemiological studies.

Project description:RationalePM2.5-induced adverse effects on respiratory health may be driven by epigenetic modifications in airway cells. The potential impact of exposure duration on epigenetic alterations in the airways is not yet known.ObjectivesWe aimed to study associations of fine particulate matter PM2.5 exposure with DNA methylation in nasal cells.MethodsWe conducted nasal epigenome-wide association analyses within 503 children from Project Viva (mean age 12.9 y), and examined various exposure durations (1-day, 1-week, 1-month, 3-months and 1-year) prior to nasal sampling. We used residential addresses to estimate average daily PM2.5 at 1 km resolution. We collected nasal swabs from the anterior nares and measured DNA methylation (DNAm) using the Illumina MethylationEPIC BeadChip. We tested 719,075 high quality autosomal CpGs using CpG-by-CpG and regional DNAm analyses controlling for multiple comparisons, and adjusted for maternal education, household smokers, child sex, race/ethnicity, BMI z-score, age, season at sample collection and cell-type heterogeneity. We further corrected for bias and genomic inflation. We tested for replication in a cohort from the Netherlands (PIAMA).ResultsIn adjusted analyses, we found 362 CpGs associated with 1-year PM2.5 (FDR < 0.05), 20 CpGs passing Bonferroni correction (P < 7.0x10-8) and 10 Differentially Methylated Regions (DMRs). In 445 PIAMA participants (mean age 16.3 years) 11 of 203 available CpGs replicated at P < 0.05. We observed differential DNAm at/near genes implicated in cell cycle, immune and inflammatory responses. There were no CpGs or regions associated with PM2.5 levels at 1-day, 1-week, or 1-month prior to sample collection, although 2 CpGs were associated with past 3-month PM2.5.ConclusionWe observed wide-spread DNAm variability associated with average past year PM2.5 exposure but we did not detect associations with shorter-term exposure. Our results suggest that nasal DNAm marks reflect chronic air pollution exposure.

Project description:BackgroundAs one of the environmental risk factors for human health, atmospheric fine particulate matter (PM2.5) contributes to cognitive deterioration in addition to respiratory and cardiovascular injuries. Recently, increasing evidence implicates that PM2.5 inhalation can affect neurological functions in offspring, but the sex-specific outcomes and the underlying biological processes are largely unknown.ObjectivesTo observe the influence of prenatal PM2.5 exposure on cognitive performance in offspring, to elucidate the neuronal morphological alterations and possible transcriptional regulation based on mRNA-sequencing (mRNA-Seq) data after birth, and to determine the key components of PM2.5 contributing to the adverse effects.MethodsPregnant C57BL/6J mice were exposed to sterile saline or PM2.5 suspension. Morris water maze test was used to assess the cognitive function in weanling offspring. Microscopic observation was applied to detect neuronal morphogenesis in vivo and in vitro. The cortex tissues from male offspring were collected on postnatal days (PNDs) 1, 7, and 21 for mRNA-Seq analysis. The organic and inorganic components of PM2.5 were separated to assess their contributions using primary cultured neurons.ResultsPrenatal PM2.5 exposure impaired spatial learning and memory in weanling male mice, but not female mice. The sex-specific outcomes were associated with mRNA expression profiles of the cortex during postnatal critical windows, and the annotations in Gene Ontology (GO) of differentially expressed genes (DEGs) revealed that the exposure persistently disrupted the expression of genes involved in neuronal features in male offspring. Consistently, axonal growth impairment and dendritic complexity reduction were observed. Importantly, Homeobox A5 (Hoxa5), a critical transcription factor regulating all of the neuronal morphogenesis-associated hub genes on PNDs 1, 7, and 21, significantly decreased in the cortex of male offspring following PM2.5 exposure. In addition, both inorganic and organic components were harmful to axonal and dendritic growth, with organic components exhibiting stronger inhibition than inorganic ones.ConclusionPrenatal PM2.5 exposure affected spatial learning and memory in male mice by disrupting Hoxa5-mediated neuronal morphogenesis, and the organic components, including polycyclic aromatic hydrocarbons (PAHs), posed more adverse effects than the inorganic components.

Dataset Information

Causal Effects of Prenatal Exposure to PM_2.5 on Child Development and the Role of Unobserved Confounding.

Publications

Causal Effects of Prenatal Exposure to PM<sub>2.5</sub> on Child Development and the Role of Unobserved Confounding.

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Causal Effects of Prenatal Exposure to PM2.5 on Child Development and the Role of Unobserved Confounding.

Publications

Causal Effects of Prenatal Exposure to PM<sub>2.5</sub> on Child Development and the Role of Unobserved Confounding.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

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Causal Effects of Prenatal Exposure to PM_2.5 on Child Development and the Role of Unobserved Confounding.