Ambient air pollution and birth weight in full-term infants in Atlanta, 1994-2004

Associations between birth outcomes and maternal PM2.5 exposure in Shanghai: A comparison of three exposure assessment approaches

BACKGROUND

Few studies have estimated effects of maternal PM_2.5 exposure on birth outcomes in China due to the lack of historical air pollution data.

OBJECTIVES

We estimated the associations between maternal PM_2.5 exposure and birth outcomes using gap-filled satellite estimates in Shanghai, China.

METHODS

We obtained birth registration records of 132,783 singleton live births during 2011-2014 in Shanghai. PM_2.5 exposures were assessed from satellite-derived estimates or central-site measurements. Linear and logistic regressions were used to estimate associations with term birth weight and term low birth weight (LBW), respectively. Logistic and discrete-time survival models were used to estimate associations with preterm birth. Effect modification by maternal age and parental education levels was investigated.

RESULTS

A 10 μg/m³ increase in gap-filled satellite-based whole-pregnancy PM_2.5 exposure was associated with a -12.85 g (95% CI: -18.44, -7.27) change in term birth weight, increased risk of preterm birth (OR 1.27, 95% CI: 1.20, 1.36), and increased risk of term LBW (OR 1.22, 95% CI: 1.06, 1.41). Sensitivity analyses during 2013-2014, when ground PM_2.5 measurements were available, showed that the health associations using gap-filled satellite PM_2.5 concentrations were higher than those obtained using satellite PM_2.5 concentrations without accounting for missingness. The health associations using gap-filled satellite PM_2.5 had similar magnitudes to those using central-site measurements, but with narrower confidence intervals.

CONCLUSIONS

The magnitude of associations between maternal PM_2.5 exposure and adverse birth outcomes in Shanghai was higher than previous findings. One reason could be reduced exposure error of the gap-filled high-resolution satellite PM_2.5 estimates.

Associations between maternal exposure to air pollution and birth outcomes: a retrospective cohort study in Taizhou, China

Previous studies from Western country settings had shown correlation between maternal exposure to air pollution and pregnancy outcomes; however, the evidence is difficult to clearly interpret. We aimed to investigate the association of maternal exposure to air pollution expressed as particulate matter (PM_2.5, PM₁₀) and nitrogen dioxide (NO₂). The exposure was assessed for the 1st, 2nd, and 3rd trimester and related to the birth outcomes. During each trimester of gestation, the effect of PM_2.5, PM₁₀, and NO₂ exposure as well as the entire pregnancy on the preterm birth, low birth weight, and term babies' birth weight was explored. The dataset of 26,998 delivered live births between January 1, 2013 and May 31, 2016, were collected from the Taizhou Maternal and Child Care Service Center. Air monitoring data were collected from the Taizhou Municipal Environmental Monitoring Center for the same period. We used multi-variable logistic and linear regression analyses to investigate the correlation of air pollution to maternal and outcomes of birth. In models of adjusted single pollutant for second trimester, NO₂ concentration was positively correlated with term low birth weight and preterm birth [aRR for an interquartile range increase: 1.59 (1.44, 1.75); 1.27 (1.12, 1.44)]; likewise, a 1 μg/m³ increase in NO₂ was correlated with a reduction in birth weight 2.94 g (P < 0.001) in linear models. Each of PM_2.5 and PM₁₀ concentration was also associated with preterm birth [aRR for an interquartile range increase 1.30 (1.21, 1.38); 1.39 (1.27, 1.52)]. In co-pollutant models, the results were similar. Maternal exposure to air pollutant in Taizhou was associated with an increased risk of preterm birth and reduction in birth weight. We reported a potential link between maternal exposure to air pollution and negative outcomes of birth in Taizhou, China.

Errors associated with the use of roadside monitoring in the estimation of acute traffic pollutant-related health effects

Near-road monitoring creates opportunities to provide direct measurement on traffic-related air pollutants and to better understand the changing near-road environment. However, how such observations represent traffic-related air pollution exposures for estimating adverse health effect in epidemiologic studies remains unknown. A better understanding of potential exposure measurement error when utilizing near-road measurement is needed for the design and interpretation of the many observational studies linking traffic pollution and adverse health. The Dorm Room Inhalation to Vehicle Emission (DRIVE) study conducted near-road measurements of several single traffic indicators at six indoor and outdoor sites ranging from 0.01 to 2.3 km away from a heavily-trafficked (average annual daily traffic over 350,000) highway artery between September 2014 to January 2015. We examined spatiotemporal variability trends and assessed the potential for bias and errors when using a roadside monitor as a primary traffic pollution exposure surrogate, in lieu of more spatially-refined, proximal exposure indicators. Pollutant levels measured during DRIVE showed a low impact of this highway hotspot source. Primary pollutant species, including NO, CO, and BC declined to near background levels by 20-30 m from the highway source. Patterns of correlation among the sites also varied by pollutant and time of day. NO₂, specifically, exhibited spatial trends that differed from other single-pollutant primary traffic indicators. This finding provides some indication of limitations in the use of NO₂ as a primary traffic exposure indicator in panel-based health effect studies. Interestingly, roadside monitoring of NO, CO, and BC tended to be more strongly correlated with sites, both near and far from the road, during morning rush hour periods, and more weakly correlated during other periods of the day. We found pronounced attenuation of observed changes in health effects when using measured pollutant from the near-road monitor as a surrogate for true exposure, and the magnitude varied substantially over the course of the day. Caution should be taken when using near-road monitoring network observations, alone, to investigate health effects of traffic pollutants.

Prenatal Exposure to Nitrogen Oxides and its Association with Birth Weight in a Cohort of Mexican Newborns from Morelos, Mexico

Background

The Child-Mother binomial is potentially susceptible to the toxic effects of pollutants because some chemicals interfere with placental transfer of nutrients, thus affecting fetal development, and create an increased the risk of low birth weight, prematurity and intrauterine growth restriction.

Objective

To evaluate the impact of prenatal exposure to nitrogen oxides (NO_x) on birth weight in a cohort of Mexican newborns.

Methodology

We included 745 mother-child pair participants of the POSGRAD cohort study. Information on socio-demographic characteristics, obstetric history, health history and environmental exposure during pregnancy were readily available and the newborns’ anthropometric measurements were obtained at delivery. Prenatal NO_x exposure assessment was evaluated using a Land-Use Regression predictive models considering local monitoring from 60 sites on the State of Morelos. The association between prenatal exposure to NO_x and birth weight was estimated using a multivariate linear regression models.

Results

The average birth weight was 3217 ± 439 g and the mean of NO_x concentration was 21 ppb (Interquartile range, IQR = 6.95 ppb). After adjusting for maternal age and other confounders, a significant birthweight reduction was observed for each IQR of NO_x increase (ß = –39.61 g, 95% CI: –77.00; –2.21; p = 0.04).

Conclusions

Our results provides evidence that prenatal NO_x exposure has a negative effect on birth weight, which may influence the growth and future development of the newborn.

Lagged kernel machine regression for identifying time windows of susceptibility to exposures of complex mixtures

The impact of neurotoxic chemical mixtures on children's health is a critical public health concern. It is well known that during early life, toxic exposures may impact cognitive function during critical time intervals of increased vulnerability, known as windows of susceptibility. Knowledge on time windows of susceptibility can help inform treatment and prevention strategies, as chemical mixtures may affect a developmental process that is operating at a specific life phase. There are several statistical challenges in estimating the health effects of time-varying exposures to multi-pollutant mixtures, such as: multi-collinearity among the exposures both within time points and across time points, and complex exposure-response relationships. To address these concerns, we develop a flexible statistical method, called lagged kernel machine regression (LKMR). LKMR identifies critical exposure windows of chemical mixtures, and accounts for complex non-linear and non-additive effects of the mixture at any given exposure window. Specifically, LKMR estimates how the effects of a mixture of exposures change with the exposure time window using a Bayesian formulation of a grouped, fused lasso penalty within a kernel machine regression (KMR) framework. A simulation study demonstrates the performance of LKMR under realistic exposure-response scenarios, and demonstrates large gains over approaches that consider each time window separately, particularly when serial correlation among the time-varying exposures is high. Furthermore, LKMR demonstrates gains over another approach that inputs all time-specific chemical concentrations together into a single KMR. We apply LKMR to estimate associations between neurodevelopment and metal mixtures in Early Life Exposures in Mexico and Neurotoxicology, a prospective cohort study of child health in Mexico City.

Residential Greenness and Birthweight in the State of Massachusetts, USA

Natural vegetation, or greenness, may benefit maternal health and consequently, fetal growth, by providing opportunities for physical activity and psychological restoration, and decreasing detrimental environmental exposures. We retrieved Massachusetts Birth Registry data from 2001⁻2013 and investigated the association between residential greenness and birthweight in full-term births (&ge;37 weeks gestation). We calculated average residential greenness during pregnancy using 250 m normalized difference vegetation index (NDVI) from satellites. We estimated associations between greenness and continuous birthweight, term low birthweight (TLBW: <2500 g), and small for gestational age (SGA: <10th percentile of birthweight stratified by sex and gestational age) adjusted for individual and neighborhood covariates and considered nonlinearity and effect modification. Higher greenness exposure was associated with higher birthweight with stronger associations in the lower than higher range of greenness. Greenness was associated with lower odds of TLBW (OR 0.98; 95% CI 0.97, 0.99 per 0.1 increase in NDVI) and SGA (OR 0.98; 95% 0.97, 0.99) and associations varied by population density (TLBW) and socioeconomic status (TLBW, SGA). Our results suggest that greenness is beneficial to fetal growth exhibited by higher birthweight and lower odds of TLBW and SGA. Unlike prior studies, associations with TLBW and SGA appeared stronger among those with higher socioeconomic status.

Mortality and morbidity in populations in the vicinity of coal mining: a systematic review

BACKGROUND

Evidence of the association of coal mining with health outcomes such as increased mortality and morbidity in the general population has been provided by epidemiological studies in the last 25 years. Given the diverse sources of data included to investigate different health outcomes in the exposed populations, the International Classification of Diseases (ICD) can be used as a single classification standard to compare the findings of studies conducted in different socioeconomic and geographic contexts. The ICD classifies diagnoses of diseases and other disorders as codes organized by categories and chapters.

OBJECTIVES

Identify the ICD codes found in studies of morbidity and/or mortality in populations resident or in proximity of coal mining and assess the methods of these studies conducting a systematic review.

METHODS

A systematic database search of PubMed, EMBASE and Scopus following the PRISMA protocol was conducted to assess epidemiological studies from 1990 to 2016. The health outcomes were mapped to ICD codes and classified by studies of morbidity and/or mortality, and the categories and chapters of the ICD.

RESULTS

Twenty-eight epidemiological studies with ecological design from the USA, Europe and China were included. The exposed populations had increased risk of mortality and/or morbidity by 78 ICD diagnosis categories and 9 groups of ICD categories in 10 chapters of the ICD: Neoplasms, diseases of the circulatory, respiratory and genitourinary systems, metabolic diseases, diseases of the eye and the skin, perinatal conditions, congenital and chromosomal abnormalities, and external causes of morbidity. Exposed populations had non-increased risk of 9 ICD diagnosis categories of diseases of the genitourinary system, and prostate cancer.

CONCLUSIONS

There is consistent evidence of the association of coal mining with a wide spectrum of diseases in populations resident or in proximity of the mining activities. The methods of the studies included in this review can be integrated with individual-level and longitudinal studies to provide further evidence of the exposure pathways linked to increased risk in the exposed populations.

Modeling the health effects of time-varying complex environmental mixtures: Mean field variational Bayes for lagged kernel machine regression

There is substantial interest in assessing how exposure to environmental mixtures, such as chemical mixtures, affect child health. Researchers are also interested in identifying critical time windows of susceptibility to these complex mixtures. A recently developed method, called lagged kernel machine regression (LKMR), simultaneously accounts for these research questions by estimating effects of time-varying mixture exposures, and identifying their critical exposure windows. However, LKMR inference using Markov chain Monte Carlo methods (MCMC-LKMR) is computationally burdensome and time intensive for large datasets, limiting its applicability. Therefore, we develop a mean field variational Bayesian inference procedure for lagged kernel machine regression (MFVB-LKMR). The procedure achieves computational efficiency and reasonable accuracy as compared with the corresponding MCMC estimation method. Updating parameters using MFVB may only take minutes, while the equivalent MCMC method may take many hours or several days. We apply MFVB-LKMR to PROGRESS, a prospective cohort study in Mexico. Results from a subset of PROGRESS using MFVB-LKMR provide evidence of significant positive association between second trimester cobalt levels and z-scored birthweight. This positive association is heightened by cesium exposure. MFVB-LKMR is a promising approach for computationally efficient analysis of environmental health datasets, to identify critical windows of exposure to complex mixtures.

Elevated biomarkers of sympatho-adrenomedullary activity linked to e-waste air pollutant exposure in preschool children

Air pollution is a risk factor for cardiovascular disease (CVD), and cardiovascular regulatory changes in childhood contribute to the development and progression of cardiovascular events at older ages. The aim of the study was to investigate the effect of air pollutant exposure on the child sympatho-adrenomedullary (SAM) system, which plays a vital role in regulating and controlling the cardiovascular system. Two plasma biomarkers (plasma epinephrine and norepinephrine) of SAM activity and heart rate were measured in preschool children (n = 228) living in Guiyu, and native (n = 104) and non-native children (n = 91) living in a reference area (Haojiang) for >1 year. Air pollution data, over the 4-months before the health examination, was also collected. Environmental PM_2.5, PM₁₀, SO₂, NO₂ and CO, plasma norepinephrine and heart rate of the e-waste recycling area were significantly higher than for the non-e-waste recycling area. However, there was no difference in plasma norepinephrine and heart rate between native children living in the non-e-waste recycling area and non-native children living in the non-e-waste recycling area. PM_2.5, PM₁₀, SO₂ and NO₂ data, over the 30-day and the 4-month average of pollution before the health examination, showed a positive association with plasma norepinephrine level. PM_2.5, PM₁₀, SO₂, NO₂ and CO concentrations, over the 24 h of the day of the health examination, the 3 previous 24-hour periods before the health examination, and the 24 h after the health examination, were related to increase in heart rate. At the same time, plasma norepinephrine and heart rate on children in the high air pollution level group (≤50-m radius of family-run workshops) were higher than those in the low air pollution level group. Our results suggest that air pollution exposure in e-waste recycling areas could result in an increase in heart rate and plasma norepinephrine, implying e-waste air pollutant exposure impairs the SAM system in children.

Developing Multipollutant Exposure Indicators of Traffic Pollution: The Dorm Room Inhalation to Vehicle Emissions (DRIVE) Study

Introduction

The Dorm Room Inhalation to Vehicle Emissions (DRIVE2) study was conducted to measure traditional single-pollutant and novel multipollutant traffic indicators along a complete emission-to-exposure pathway. The overarching goal of the study was to evaluate the suitability of these indicators for use as primary traffic exposure metrics in panel-based and small-cohort epidemiological studies.

Methods

Intensive field sampling was conducted on the campus of the Georgia Institute of Technology (GIT) between September 2014 and January 2015 at 8 monitoring sites (2 indoors and 6 outdoors) ranging from 5 m to 2.3 km from the busiest and most congested highway artery in Atlanta. In addition, 54 GIT students living in one of two dormitories either near (20 m) or far (1.4 km) from the highway were recruited to conduct personal exposure sampling and weekly biomonitoring. The pollutants measured were selected to provide information about the heterogeneous particulate and gaseous composition of primary traffic emissions, including the traditional traffic-related species (e.g., carbon monoxide [CO], nitrogen dioxide [NO2], nitric oxide [NO], fine particulate matter [PM2.5], and black carbon [BC]), and of secondary species (e.g., ozone [O3] and sulfate as well as organic carbon [OC], which is both primary and secondary) from traffic and other sources. Along with these pollutants, we also measured two multipollutant traffic indicators: integrated mobile source indicators (IMSIs) and fine particulate matter oxidative potential (FPMOP). IMSIs are derived from elemental carbon (EC), CO, and nitrogen oxide (NOx) concentrations, along with the fractions of these species emitted by gasoline and diesel vehicles, to construct integrated estimates of gasoline and diesel vehicle impacts. Our FPMOP indicator was based on an acellular assay involving the depletion of dithiothreitol (DTT), considering both water-soluble and insoluble components (referred to as FPMOPtotal-DTT). In addition, a limited assessment of 18 low-cost sensors was added to the study to supplement the four original aims.

Results

Pollutant levels measured during the study showed a low impact by this highway hotspot source on its surrounding vicinity. These findings are broadly consistent with results from other studies throughout North America showing decreased relative contributions to urban air pollution from primary traffic emissions. We view these reductions as an indication of a changing near-road environment, facilitated by the effectiveness of mobile source emission controls. Many of the primary pollutant species, including NO, CO, and BC, decreased to near background levels by 20 to 30 m from the highway source. Patterns of correlation among the sites also varied by pollutant and time of day. NO2 exhibited spatial trends that differed from those of the other single-pollutant primary traffic indicators. We believe this was caused by kinetic limitations in the photochemical chemistry, associated with primary emission reductions, required to convert the NO-dominant primary NOx, emitted from automobiles, to NO2. This finding provides some indication of limitations in the use of NO2 as a primary traffic exposure indicator in panel-based health effect studies. Roadside monitoring of NO, CO, and BC tended to be more strongly correlated with sites, both near and far from the road, during morning rush hour periods and often weakly to moderately correlated during other time periods of the day. This pattern was likely associated with diurnal changes in mixing and chemistry and their impact on spatial heterogeneity across the campus. Among our candidate multipollutant primary traffic indicators, we report several key findings related to the use of oxidative potential (OP)-based indicators. Although earlier studies have reported elevated levels of FPMOP in direct exhaust emissions, we found that atmospheric processing further enhanced FPMOPtotal-DTT, likely associated with the oxidation of primary polycyclic aromatic hydrocarbons (PAHs) to quinones and hydroxyquinones and with the oxidization and water solubility of metals. This has important implications in terms both of the utility of FPMOPtotal-DTT as a marker for exhaust emissions and of the importance of atmospheric processing of particulate matter (PM) being tied to potential health outcomes. The results from the personal exposure monitoring also point to the complexity and diversity of the spatiotemporal variability patterns among the study monitoring sites and the importance of accounting for location and spatial mobility when estimating exposures in panel-based and small-cohort studies. This was most clearly demonstrated with the personal BC measurements, where ambient roadside monitoring was shown to be a poor surrogate for exposures to BC. Alternative surrogates, including ambient and indoor BC at the participants' respective dorms, were more strongly associated with personal BC, and knowledge of the participants' mean proximity to the highway was also shown to explain a substantial level of the variability in corresponding personal exposures to both BC and NO2. In addition, untargeted metabolomic indicators measured in plasma and saliva, which represent emerging methods for measuring exposure, were used to extract approximately 20,000 and 30,000 features from plasma and saliva, respectively. Using hydrophilic interaction liquid chromatography (HILIC) in the positive ion mode, we identified 221 plasma features that differed significantly between the two dorm cohorts. The bimodal distribution of these features in the HILIC column was highly idiosyncratic; one peak consisted of features with elevated intensities for participants living in the near dorm; the other consisted of features with elevated intensities for participants in the far dorm. Both peaks were characterized by relatively short retention times, indicative of the hydrophobicity of the identified features. The results from the metabolomics analyses provide a strong basis for continuing this work toward specific chemical validation of putative biomarkers of traffic-related pollution. Finally, the study had a supplemental aim of examining the performance of 18 low-cost CO, NO, NO2, O3, and PM2.5 pollutant sensors. These were colocated alongside the other study monitors and assessed for their ability to capture temporal trends observed by the reference monitoring instrumentation. Generally, we found the performance of the low-cost gas-phase sensors to be promising after extensive calibration; the uncalibrated measurements alone, however, would likely not have led to reliable results. The low-cost PM sensors we evaluated had poor accuracy, although PM sensor technology is evolving quickly and warrants future attention.

Conclusions

An immediate implication of the changing near-road environment is that future studies aimed at characterizing hotspots related to mobile sources and their impacts on health will need to consider multiple approaches for characterizing spatial gradients and exposures. Specifically and most directly, the mobile source contributions to ambient concentrations of single-pollutant indicators of traffic exposure are not as distinguishable to the degree that they have been in the past. Collectively, the study suggests that characterizing exposures to traffic-related pollutants, which is already difficult, will become more difficult because of the reduction in traffic-related emissions. Additional multi-tiered approaches should be considered along with traditional measurements, including the use of alternative OP measures beyond those based on DTT assays, metabolomics, low-cost sensors, and air quality modeling.

Risk factors associated with low birth weight in the Americas: literature review

Introducción. El bajo peso al nacer (BPN) es uno de los principales factores de riesgo que afecta la morbimortalidad infantil en todo el mundo; cerca de 1/3 de las muertes neonatales son atribuibles a este.Objetivo. Revisar los artículos más relevantes sobre BPN en las Américas en el periodo de 2010-2016.Materiales y métodos. Revisión narrativa de literatura. La información se obtuvo de las bases de datos PubMed, SciELO, LILACS, Portal Regional da BVS, con el uso de los descriptores DeCS y MeSH.Resultados. La mayoría de los estudios fueron publicados entre el 2012 y el 2015. De los 27 artículos publicados, 11 (40.7%) fueron atribuidos a factores sociodemográficos, 9 (33.3%) a riesgos ambientales, 3 (11.1%) a factores conductuales, 2 (7.4%) a controles prenatales o por cobertura y 2 (7.4%) se interrelacionaban con otros factores de riesgo.Conclusión. La mayoría de los estudios coinciden en la asociación de factores sociodemográficos, biológicos y conductuales. Los estudios que refieren la asociación de BPN con factores de riesgo ambientales están tomando fuerza.

Measurement Error Correction for Predicted Spatiotemporal Air Pollution Exposures

BACKGROUND

Air pollution cohort studies are frequently analyzed in two stages, first modeling exposure then using predicted exposures to estimate health effects in a second regression model. The difference between predicted and unobserved true exposures introduces a form of measurement error in the second stage health model. Recent methods for spatial data correct for measurement error with a bootstrap and by requiring the study design ensure spatial compatibility, that is, monitor and subject locations are drawn from the same spatial distribution. These methods have not previously been applied to spatiotemporal exposure data.

METHODS

We analyzed the association between fine particulate matter (PM2.5) and birth weight in the US state of Georgia using records with estimated date of conception during 2002-2005 (n = 403,881). We predicted trimester-specific PM2.5 exposure using a complex spatiotemporal exposure model. To improve spatial compatibility, we restricted to mothers residing in counties with a PM2.5 monitor (n = 180,440). We accounted for additional measurement error via a nonparametric bootstrap.

RESULTS

Third trimester PM2.5 exposure was associated with lower birth weight in the uncorrected (-2.4 g per 1 μg/m difference in exposure; 95% confidence interval [CI]: -3.9, -0.8) and bootstrap-corrected (-2.5 g, 95% CI: -4.2, -0.8) analyses. Results for the unrestricted analysis were attenuated (-0.66 g, 95% CI: -1.7, 0.35).

CONCLUSIONS

This study presents a novel application of measurement error correction for spatiotemporal air pollution exposures. Our results demonstrate the importance of spatial compatibility between monitor and subject locations and provide evidence of the association between air pollution exposure and birth weight.

The Effect of Nitric Oxide Pollution on Oxidative Stress in Pregnant Women Living in Durban, South Africa

The purpose of the study was to evaluate the effect nitric oxide (NO _x ) pollution had on maternal serum 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-OHdG) levels and neonatal outcomes in pregnant women living in Durban, South Africa (SA). Women, in their third trimester with singleton pregnancies, were recruited from the heavily industrialised south (n = 225) and less industrialised north (n = 152). Biomarker levels of serum 8-OHdG concentrations were analysed, and the women were genotyped for glutathione-S-transferases pi 1 (GSTP1) and glutathione-S-transferases mu 1 (GSTM1) polymorphisms. The level of NO _x pollution in the two regions was determined by using land use regression modelling. The serum 8-OHdG was shown to correlate significantly with NO _x levels; this relationship was strengthened in the south (p < 0.05). This relationship was still observed after adjusting for maternal characteristics. GSTP1 was significantly associated with the south region, where the variant (AG+GG) genotype was associated with increased 8-OHdG levels as a result of NO _x exposure (p < 0.05). GSTM1 null genotype was associated with a positive correlation between NO _x and 8-OHdG levels (p < 0.05). NO _x levels were found marginally to reduce gestational age (p < 0.05) with mothers carrying male neonates. Variant GSTP1 and living in the north were factors that contributed to gestational age reduction (p < 0.05). Our study demonstrated that NO _x exposure resulted in increased 8-OHdG levels in pregnant women living in Durban, SA, which led to gestational age reduction. The GSTP1 variant increased susceptibility of individuals to harmful effects of NO _x .

Impact of London's road traffic air and noise pollution on birth weight: retrospective population based cohort study

Objective To investigate the relation between exposure to both air and noise pollution from road traffic and birth weight outcomes.Design Retrospective population based cohort study.Setting Greater London and surrounding counties up to the M25 motorway (2317 km²), UK, from 2006 to 2010.Participants 540 365 singleton term live births.Main outcome measures Term low birth weight (LBW), small for gestational age (SGA) at term, and term birth weight.Results Average air pollutant exposures across pregnancy were 41 μg/m³ nitrogen dioxide (NO₂), 73 μg/m³ nitrogen oxides (NO_x), 14 μg/m³ particulate matter with aerodynamic diameter <2.5 μm (PM_2.5), 23 μg/m³ particulate matter with aerodynamic diameter <10 μm (PM₁₀), and 32 μg/m³ ozone (O₃). Average daytime (L_Aeq,16hr) and night-time (L_night) road traffic A-weighted noise levels were 58 dB and 53 dB respectively. Interquartile range increases in NO₂, NO_x, PM_2.5, PM₁₀, and source specific PM_2.5 from traffic exhaust (PM_{2.5 traffic exhaust}) and traffic non-exhaust (brake or tyre wear and resuspension) (PM_{2.5 traffic non-exhaust}) were associated with 2% to 6% increased odds of term LBW, and 1% to 3% increased odds of term SGA. Air pollutant associations were robust to adjustment for road traffic noise. Trends of decreasing birth weight across increasing road traffic noise categories were observed, but were strongly attenuated when adjusted for primary traffic related air pollutants. Only PM_{2.5 traffic exhaust} and PM_2.5 were consistently associated with increased risk of term LBW after adjustment for each of the other air pollutants. It was estimated that 3% of term LBW cases in London are directly attributable to residential exposure to PM_2.5>13.8 μg/m³during pregnancy.Conclusions The findings suggest that air pollution from road traffic in London is adversely affecting fetal growth. The results suggest little evidence for an independent exposure-response effect of traffic related noise on birth weight outcomes.

Potential for Bias When Estimating Critical Windows for Air Pollution in Children's Health

Evidence supports an association between maternal exposure to air pollution during pregnancy and children's health outcomes. Recent interest has focused on identifying critical windows of vulnerability. An analysis based on a distributed lag model (DLM) can yield estimates of a critical window that are different from those from an analysis that regresses the outcome on each of the 3 trimester-average exposures (TAEs). Using a simulation study, we assessed bias in estimates of critical windows obtained using 3 regression approaches: 1) 3 separate models to estimate the association with each of the 3 TAEs; 2) a single model to jointly estimate the association between the outcome and all 3 TAEs; and 3) a DLM. We used weekly fine-particulate-matter exposure data for 238 births in a birth cohort in and around Boston, Massachusetts, and a simulated outcome and time-varying exposure effect. Estimates using separate models for each TAE were biased and identified incorrect windows. This bias arose from seasonal trends in particulate matter that induced correlation between TAEs. Including all TAEs in a single model reduced bias. DLM produced unbiased estimates and added flexibility to identify windows. Analysis of body mass index z score and fat mass in the same cohort highlighted inconsistent estimates from the 3 methods.

Maternal exposure to air pollutants during the first trimester and foetal growth in Japanese term infants

Evidence supporting an inverse association between maternal exposure to air pollutants and foetal growth has been accumulating. However, the findings from Asian populations are limited, and the question of critical windows of exposure remains unanswered. We examined whether maternal exposure to air pollutants, in particular exposure during the first trimester (an important period of placental development), was associated with foetal growth in Japanese term infants. From the Japan Perinatal Registry Network database, we received birth data for 29,177 term singleton births in western Japan (Kyushu-Okinawa Districts) between 2005 and 2010. Exposure was expressed in terms of average concentrations of air pollutants (ozone, suspended particulate matter, nitrogen dioxide, and sulphur dioxide), as measured at the nearest monitoring stations to the respective delivery hospitals of the pregnant women, during the entire pregnancy and each trimester. As proxy markers of foetal growth restriction, we used small for gestational age (SGA), and adverse birth weight (low birth weight in addition to SGA). For pollutant exposure during the entire pregnancy, we did not observe the association with SGA and adverse birth weight. In the single-trimester model for the first trimester, however, we found a positive association between ozone exposure, and SGA (odds ratio [OR] per 10 ppb increase = 1.07, 95% confidence interval [CI] = 1.01-1.12) and adverse birth weight (OR = 1.07; 95% CI = 1.01-1.14). This association persisted in the multi-trimester model, and no association for exposure during the second or third trimester was observed. Exposure to other pollutants during each trimester was not associated with these outcomes. In conclusion, maternal exposure to ozone during the first trimester was independently associated with an elevated risk of poor foetal growth.

Exposure to fine particulate matter during pregnancy and risk of term low birth weight in Jinan, China, 2014-2016

BACKGROUND

Existing studies exploring the association between low birth weight (LBW) and maternal fine particulate matter (aerodynamic diameter<2.5μm, PM_2.5) exposure have presented equivocal results, and one of the possible reasons for this finding might be due to relatively low maternal exposures. In addition, relatively narrow maternal exposure windows to PM_2.5 have not been well established for LBW.

METHODS

We employed a nested matched case-control design among 43,855 term births in a large maternity and child care hospital in Jinan, China. A total of 369 cases were identified, and four controls per case matched by maternal age were randomly selected among those with normal birth weight (n=1,476) from 2014 to 2016. Ambient air monitoring data on continuous measures of PM_2.5, nitrogen dioxide (NO₂), and sulfur dioxide (SO₂) (24-h average concentrations) from 2013 to 2016 were collected from thirteen local monitoring stations. An inverse distance weighting method based on both home and work addresses was adopted to estimate the individual daily exposures to these air pollutants during pregnancy by weighting the average of the twelve nearest monitoring stations within 30km of each 100m×100m grid cell by an inverse squared distance, and then the average exposure concentrations for gestational months, trimesters and the entire pregnancy were calculated. Adjusted conditional logistic regression models were used to estimate the odds ratios (ORs) per 10μg/m³ increment in PM_2.5 and by PM_2.5 quartiles during different gestational periods.

RESULTS

In this study, the estimated mean values of PM_2.5, NO₂, and SO₂ exposure during the entire pregnancy were 88.0, 54.6, and 63.1μg/m³, respectively. Term low birth weight (TLBW) increased in association with per 10μg/m³ increment in PM_2.5 for the 8th month [OR=1.13, 95% confidence interval (CI): 1.04, 1.22], the 9th month (OR=1.06, 95% CI: 0.99, 1.15), the third trimester (OR=1.17, 95% CI: 1.05, 1.29), and the entire pregnancy (OR=1.38, 95% CI: 1.07, 1.77) in models adjusted for one pollutant (PM_2.5). In models categorizing the PM_2.5 exposure by quartiles, comparing the second, third, and highest with the lowest PM_2.5 exposure quartile, the PM_2.5 was positively associated with TLBW during the 8th month (OR: 1.77, 95% CI: 1.09, 2.88; OR: 1.77, 95% CI: 1.03, 3.04; OR: 1.92, 95% CI: 1.04, 3.55, respectively) and for the 9th month, only association for exposure in the third versus the lowest quartile was significant (OR: 1.91, 95% CI: 1.02, 3.58).

CONCLUSIONS

The study provides evidence that exposure to PM_2.5 during pregnancy might be associated with the risk of TLBW in the context of very high pollution level of PM_2.5, and the 8th and 9th months were identified as potentially relevant exposure windows.

Highly Acidic Ambient Particles, Soluble Metals, and Oxidative Potential: A Link between Sulfate and Aerosol Toxicity

Soluble transition metals in particulate matter (PM) can generate reactive oxygen species in vivo by redox cycling, leading to oxidative stress and adverse health effects. Most metals, such as those from roadway traffic, are emitted in an insoluble form, but must be soluble for redox cycling. Here we present the mechanism of metals dissolution by highly acidic sulfate aerosol and the effect on particle oxidative potential (OP) through analysis of size distributions. Size-segregated ambient PM were collected from a road-side and representative urban site in Atlanta, GA. Elemental and organic carbon, ions, total and water-soluble metals, and water-soluble OP were measured. Particle pH was determined with a thermodynamic model using measured ionic species. Sulfate was spatially uniform and found mainly in the fine mode, whereas total metals and mineral dust cations were highest at the road-side site and in the coarse mode, resulting in a fine mode pH < 2 and near neutral coarse mode. Soluble metals and OP peaked at the intersection of these modes demonstrating that sulfate plays a key role in producing highly acidic fine aerosols capable of dissolving primary transition metals that contribute to aerosol OP. Sulfate-driven metals dissolution may account for sulfate-health associations reported in past studies.

Ozone and hypertensive disorders of pregnancy in Florida: Identifying critical windows of exposure

INTRODUCTION

Ozone (O₃) has been linked to hypertensive disorders of pregnancy (HDP). However, inconsistent results have been reported, and no study has examined the critical exposure windows during pregnancy.

MATERIALS AND METHODS

We used Florida birth vital statistics records to investigate the association between HDP and O₃ exposure among 655,529 pregnancies with conception dates between 2005 and 2007. Individual O₃ exposure was assessed at mothers' home address at the time of delivery using the Hierarchical Bayesian space-time statistical model. We examined the association during three predefined exposure windows including trimester 1, trimester 2, and trimesters 1&2, as well as in each week of the first two trimesters using distributed lag models.

RESULTS

Pregnancies with HDP had a higher mean exposure to O₃ (39.07 in trimester 1, 39.02 in trimester 2, and 39.06 in trimesters 1&2, unit: ppb) than those without HDP (38.65 in trimester 1, 38.57 in trimester 2, and 38.61 in trimesters 1&2, unit: ppb). In the adjusted logistic regression model, increased odds of HDP were observed for each 5 ppb increase in O₃ (OR_Trimester1=1.04, 95% CI: 1.03, 1.06; OR_Trimester2=1.03, 95% CI: 1.02, 1.04; OR_Trimester1&2=1.07, 95% CI: 1.05, 1.08). In the distributed lag models, elevated odds of HDP were observed with increased O₃ exposure during the 1st to 24th weeks of gestation, with higher odds during early pregnancy.

CONCLUSIONS

O₃ exposure during pregnancy is related to increased odds of HDP, and early pregnancy appears to be a potentially critical window of exposure.

Effect of Fine Particulate Matter (PM2.5) on Rat Placenta Pathology and Perinatal Outcomes

Background

Fine particulate matter with aerodynamic diameters smaller than 2.5 μm (PM_2.5) has been reported to cause adverse effects on human health. Evidence has shown the association between PM_2.5 exposure and adverse perinatal outcomes, and the most common method is epidemiological investigation. We wished to investigate the impact of PM_2.5 on placenta and prenatal outcomes and its related mechanisms in a rat model.

Material/Methods

Pregnant rats were exposed to a low PM_2.5 dose (15 mg/kg) with intratracheal instillation at pregnant day 10 and day 18, while the controls received an equivalent volume normal saline. All rats received cesarean section 24 h after the last intratracheal instillation and were sacrificed with anesthesia. Blood routine tests (BRT) and interleukin-6 (IL-6) were detected for analyzing inflammation and blood coagulation. Placenta tissue sections underwent pathologic examination, and the levels of homogenate glutathione peroxidase (GSH-Px) and methane dicarboxylic aldehyde (MDA) were determined for oxidative stress estimation.

Results

Increased absorbed blastocysts, and lower maternal weight gain and fetal weight were found in the PM_2.5 exposure group compared to controls (p<0.05). Exposure to PM_2.5 caused a significant increase of blood mononuclear cells (PBMC), platelets, and IL-6 levels (P<0.01). There were no differences in GSH-Px and MDA of placenta homogenate between the 2 groups (P>0.05). Placenta pathological examination demonstrated thrombus and chorioamnionitis in the PM_2.5 exposure group.

Conclusions

PM_2.5 exposure can result in placental pathological changes and adverse perinatal outcomes. The placental inflammation and hypercoagulability with vascular thrombosis may play important roles in placental impairment, but oxidative stress appears to be less important.

Validity of the Emission Weighted Proximity Model in estimating air pollution exposure intensities in large geographic areas

BACKGROUND

Accurate estimates of air pollution exposure intensities are important to support environmental epidemiology analyses that require data covering large geographic areas over multiple years. The Emission Weighted Proximity Model (EWPM) and the National-Scale Air Toxics Assessment (NATA) are two viable approaches for obtaining estimate exposure intensities. The advantages of the EWPM include its simplicity and significantly lower costs of implementation. However, very limited data are available regarding the validity of the results from the EWPM and how these results would fare when compared with those from the NATA.

METHODS

This study evaluates the validity of the estimated exposure intensities from the EWPM through a correlation analysis with ground monitoring data obtained by the Texas Commission on Environmental Quality (TCEQ). The monitoring data used in the comparison included 27 non-criteria air pollutants at 48 monitoring sites in Texas in 2005. In addition, this study compares the results from the EWPM with those from NATA using the TCEQ data as a gold standard.

RESULTS

Analysis results suggest that estimated exposure intensities from the EWPM and the NATA were comparable when the intensities from both approaches are used to categorize environmental exposure intensities into different levels in relative terms.

CONCLUSION

These findings suggest that the EWPM is a valid alternative approach to the NATA in situations where epidemiological analysis requires both environmental data and health outcome data that cover a large geographic area over multiple years.

Exposure to coarse particulate matter during gestation and birth weight in the U.S

Few studies have explored the relationship between coarse particles (PM10-2.5) and adverse birth outcomes. We examined associations between gestational exposure of PM10-2.5 and birth weight. U.S. birth certificates data (1999-2007) were acquired for 8,017,865 births. Gestational and trimester exposures of PM10-2.5 were estimated using co-located PM10 and PM2.5 monitors ≤35km from the population-weighted centroid of mothers' residential counties. A linear regression model was applied, adjusted by potential confounders. As sensitivity analyses, we explored alternative PM10-2.5 estimations, adjustment for PM2.5, and stratification by regions. Gestational exposure to PM10-2.5 was associated with 6.6g (95% Confidence Interval: 5.9, 7.2) lower birth weight per interquartile range increase (7.8μg/m(3)) in PM10-2.5 exposures. All three trimesters showed associations. Under different exposure methods for PM10-2.5, associations remained consistent but with different magnitudes. Results were robust after adjusting for PM2.5, and regional analyses showed associations in all four regions with larger estimates in the South. Our results suggest that PM10-2.5 is associated with birth weight in addition to PM2.5. Regional heterogeneity may reflect differences in population, measurement error, region-specific emission pattern, or different chemical composition within PM10-2.5. Most countries do not set health-based standards for PM10-2.5, but our findings indicate potentially important health effects of PM10-2.5.

Low birth weight and air pollution in California: Which sources and components drive the risk?

INTRODUCTION

Intrauterine growth restriction has been associated with exposure to air pollution, but there is a need to clarify which sources and components are most likely responsible. This study investigated the associations between low birth weight (LBW, <2500g) in term born infants (≥37 gestational weeks) and air pollution by source and composition in California, over the period 2001-2008.

METHODS

Complementary exposure models were used: an empirical Bayesian kriging model for the interpolation of ambient pollutant measurements, a source-oriented chemical transport model (using California emission inventories) that estimated fine and ultrafine particulate matter (PM2.5 and PM0.1, respectively) mass concentrations (4km×4km) by source and composition, a line-source roadway dispersion model at fine resolution, and traffic index estimates. Birth weight was obtained from California birth certificate records. A case-cohort design was used. Five controls per term LBW case were randomly selected (without covariate matching or stratification) from among term births. The resulting datasets were analyzed by logistic regression with a random effect by hospital, using generalized additive mixed models adjusted for race/ethnicity, education, maternal age and household income.

RESULTS

In total 72,632 singleton term LBW cases were included. Term LBW was positively and significantly associated with interpolated measurements of ozone but not total fine PM or nitrogen dioxide. No significant association was observed between term LBW and primary PM from all sources grouped together. A positive significant association was observed for secondary organic aerosols. Exposure to elemental carbon (EC), nitrates and ammonium were also positively and significantly associated with term LBW, but only for exposure during the third trimester of pregnancy. Significant positive associations were observed between term LBW risk and primary PM emitted by on-road gasoline and diesel or by commercial meat cooking sources. Primary PM from wood burning was inversely associated with term LBW. Significant positive associations were also observed between term LBW and ultrafine particle numbers modeled with the line-source roadway dispersion model, traffic density and proximity to roadways.

DISCUSSION

This large study based on complementary exposure metrics suggests that not only primary pollution sources (traffic and commercial meat cooking) but also EC and secondary pollutants are risk factors for term LBW.

Spatial variations in the associations of term birth weight with ambient air pollution in Georgia, USA

Birth weight is an important indicator of overall infant health and a strong predictor of infant morbidity and mortality, and low birth weight (LBW) is a leading cause of infant mortality in the United States. Numerous studies have examined the associations of birth weight with ambient air pollution, but the results were inconsistent. In this study, a spatial statistical technique, geographically weighted regression (GWR) is applied to explore the spatial variations in the associations of birth weight with concentrations of ozone (O3) and fine particulate matter (PM2.5) in the State of Georgia, USA adjusted for gestational age, parity, and six other socioeconomic, behavioral, and land use factors. The results show considerable spatial variations in the associations of birth weight with both pollutants. Significant positive, non-significant, and significant negative relationships between birth weight and concentrations of each air pollutant are all found in different parts of the study area, and the different types of the relationships are affected by the socioeconomic and urban characteristics of the communities where the births are located. The significant negative relationships between birth weight and O3 indicate that O3 is a significant risk factor of LBW and these associations are primarily located in less-urbanized communities. On the other hand, PM2.5 is a significant risk factor of LBW in the more-urbanized communities with higher family income and education attainment. These findings suggest that environmental and health policies should be adjusted to address the different effects of air pollutants on birth outcomes across different types of communities to more effectively and efficiently improve birth outcomes.

Air pollution modelling for birth cohorts: a time-space regression model

BACKGROUND

To investigate air pollution effects during pregnancy or in the first weeks of life, models are needed that capture both the spatial and temporal variability of air pollution exposures.

METHODS

We developed a time-space exposure model for ambient NO2 concentrations in Bern, Switzerland. We used NO2 data from passive monitoring conducted between 1998 and 2009: 101 rural sites (24,499 biweekly measurements) and 45 urban sites (4350 monthly measurements). We evaluated spatial predictors (land use; roads; traffic; population; annual NO2 from a dispersion model) and temporal predictors (meteorological conditions; NO2 from continuous monitoring station). Separate rural and urban models were developed by multivariable regression techniques. We performed ten-fold internal cross-validation, and an external validation using 57 NO2 passive measurements obtained at study participant's homes.

RESULTS

Traffic related explanatory variables and fixed site NO2 measurements were the most relevant predictors in both models. The coefficient of determination (R(2)) for the log transformed models were 0.63 (rural) and 0.54 (urban); cross-validation R(2)s were unchanged indicating robust coefficient estimates. External validation showed R(2)s of 0.54 (rural) and 0.67 (urban).

CONCLUSIONS

This approach is suitable for air pollution exposure prediction in epidemiologic research with time-vulnerable health effects such as those occurring during pregnancy or in the first weeks of life.

The associations between birth weight and exposure to fine particulate matter (PM2.5) and its chemical constituents during pregnancy: A meta-analysis

We performed this meta-analysis to estimate the associations of maternal exposure to PM2.5 and its chemical constituents with birth weight and to explore the sources of heterogeneity in regard to the findings of these associations. A total of 32 studies were identified by searching the MEDLINE, PUBMED, Embase, China Biological Medicine and Wanfang electronic databases before April 2015. We estimated the statistically significant associations of reduced birth weight (β = -15.9 g, 95% CI: -26.8, -5.0) and LBW (OR = 1.090, 95% CI: 1.032, 1.150) with PM2.5 exposure (per 10 μg/m(3) increment) during the entire pregnancy. Trimester-specific analyses showed negative associations between birth weight and PM2.5 exposure during the second (β = -12.6 g) and third (β = -10.0 g) trimesters. Other subgroup analyses indicated significantly different pooled-effect estimates of PM2.5 exposure on birth weight in studies with different exposure assessment methods, study designs and study settings. We further observed large differences in the pooled effect estimates of the PM2.5 chemical constituents for birth weight decrease and LBW. We concluded that PM2.5 exposure during pregnancy was associated with lower birth weight, and late pregnancy might be the critical window. Some specific PM2.5 constituents may have larger toxic effects on fetal weight. Exposure assessment methods, study designs and study settings might be important sources of the heterogeneity among the included studies.

Geographic Variation in the Association between Ambient Fine Particulate Matter (PM2.5) and Term Low Birth Weight in the United States

BACKGROUND

Studies on the association between prenatal exposure to fine particulate matter ≤ 2.5 μm in aerodynamic diameter (PM2.5) and term low birth weight (LBW) have resulted in inconsistent findings. Most studies were conducted in snapshots of small geographic areas and no national study exists.

OBJECTIVES

We investigated geographic variation in the associations between ambient PM2.5 during pregnancy and term LBW in the contiguous United States.

METHODS

A total of 3,389,450 term singleton births in 2002 (37-44 weeks gestational age and birth weight of 1,000-5,500 g) were linked to daily PM2.5 via imputed birth days. We generated average daily PM2.5 during the entire pregnancy and each trimester. Multi-level logistic regression models with county-level random effects were used to evaluate the associations between term LBW and PM2.5 during pregnancy.

RESULTS

Without adjusting for covariates, the odds of term LBW increased 2% [odds ratio (OR) = 1.02; 95% CI: 1.00, 1.03] for every 5-μg/m(3) increase in PM2.5 exposure during the second trimester only, which remained unchanged after adjusting for county-level poverty (OR = 1.02; 95% CI: 1.01, 1.04). The odds did change to null after adjusting for individual-level predictors (OR = 1.00; 95% CI: 0.99, 1.02). Multi-level analyses, stratified by census division, revealed significant positive associations of term LBW and PM2.5 exposure (during the entire pregnancy or a specific trimester) in three census divisions of the United States: Middle Atlantic, East North Central, and West North Central, and significant negative association in the Mountain division.

CONCLUSIONS

Our study provided additional evidence on the associations between PM2.5 exposure during pregnancy and term LBW from a national perspective. The magnitude and direction of the estimated associations between PM2.5 exposure and term LBW varied by geographic locations in the United States.

Adverse Reproductive Health Outcomes and Exposure to Gaseous and Particulate-Matter Air Pollution in Pregnant Women

Introduction

There is growing epidemiologic evidence of associations between maternal exposure to ambient air pollution and adverse birth outcomes, such as preterm birth (PTB). Recently, a few studies have also reported that exposure to ambient air pollution may also increase the risk of some common pregnancy complications, such as preeclampsia and gestational diabetes mellitus (GDM). Research findings, however, have been mixed. These inconsistent results could reflect genuine differences in the study populations, the study locations, the specific pollutants considered, the designs of the study, its methods of analysis, or random variation. Dr. Jun Wu of the University of California– Irvine, a recipient of HEI’s Walter A. Rosenblith New Investigator Award, and colleagues have examined the association between air pollution and adverse birth and pregnancy outcomes in California women. In addition, they examined the effect modification by socioeconomic status (SES) and other factors.

Approach

A retrospective nested case–control study was conducted using birth certificate data from about 4.4 million birth records in California from 2001 to 2008. Wu and colleagues analyzed data on low birth weight (LBW) at term (infants born between 37 and 43 weeks of gestation and weighing less than 2500 g), PTB (infants born before 37 weeks of gestation), and preeclampsia (including eclampsia) of the mother during the pregnancy. In addition, they obtained data on GDM for the years 2006– 2008. In the analyses, all outcomes were included as binary variables. Maternal residential addresses at the time of delivery were geocoded, and a large suite of air pollution exposure metrics was considered, such as (1) regulatory monitoring data on concentrations of criteria pollutants NO2, PM2.5 (particulate matter ≤ 2.5 μm in aerodynamic diameter), and ozone (O3) estimated by empirical Bayesian kriging; (2) concentrations of primary and secondary PM2.5 and PM0.1 components and sources estimated by the University of California–Davis Chemical Transport Model; (3) traffic-related ultrafine particles and concentrations of carbon monoxide (CO) and nitrogen oxides (NOx) estimated by a modified CALINE4 air pollution dispersion model; and (4) proximity to busy roads, road length, and traffic density calculated for different buffer sizes using geographic information system tools. In total, 50 different exposure metrics were available for the analyses. The exposure of primary interest was the mean of the entire pregnancy period for each mother. For the health analyses, controls were randomly selected from the source population. PTB controls were matched on conception year. Term LBW, preeclampsia, and GDM were analyzed using generalized additive mixed models with inclusion of a random effect per hospital. PTB analyses were conducted using conditional logistic regression, with no adjustment for hospital. The main results— adjusted for race and education as categorical variables and adjusted for maternal age and median household income at the census-block level—were derived from single-pollutant models.

Main results and interpretation

In its independent review of the study, the HEI Health Review Committee concluded that Wu and colleagues had conducted a comprehensive nested case–control study of air pollution and adverse birth and pregnancy outcomes. The very large data set and the extensive exposure assessment were strengths of the study. The study documented associations between increases in various air pollution metrics and increased risks of PTB, whereas the evidence was weaker overall for term LBW; in addition, decreases in many air pollution metrics were associated with an increased risk of preeclampsia and GDM, an unexpected result. The investigators suggested that underreporting in the registry data, especially in lower-SES groups, might have caused the many negative associations found for preeclampsia and GDM. In addition, poor geocoding was listed as a potential explanation, affecting in particular the results that were based on measures of proximity to busy roads and traffic density in the smallest buffer size (50 m). However, those issues were not fully explored. In general, the Committee thought that the analysis of road traffic indicators in the 50 m buffer was hampered by the lack of contrast and that the results are therefore difficult to interpret. Some other issues with the analytical approaches should be considered when interpreting the results. Only a subset of controls was used, to reduce computational demands. Hence, some models did not converge, especially in the subgroup analyses. Most of the results in the report were based on analyses using single-pollutant models, which is a reasonable approach but ignores that people are exposed to complex mixtures of pollutants. The Committee believed that the few two-pollutant models that were run provided important insights: these models showed the strongest association for PM2.5 mass, whereas components and source-specific positive associations largely disappeared after adjusting for PM2.5 mass. This study adds to the ongoing debate about whether some particle components and sources are of greater public health concern than others.

Elemental Constituents of Particulate Matter and Newborn's Size in Eight European Cohorts

BACKGROUND

The health effects of suspended particulate matter (PM) may depend on its chemical composition. Associations between maternal exposure to chemical constituents of PM and newborn's size have been little examined.

OBJECTIVE

We aimed to investigate the associations of exposure to elemental constituents of PM with term low birth weight (LBW; weight < 2,500 g among births after 37 weeks of gestation), mean birth weight, and head circumference, relying on standardized fine-scale exposure assessment and with extensive control for potential confounders.

METHODS

We pooled data from eight European cohorts comprising 34,923 singleton births in 1994-2008. Annual average concentrations of elemental constituents of PM ≤ 2.5 and ≤ 10 μm (PM2.5 and PM10) at maternal home addresses during pregnancy were estimated using land-use regression models. Adjusted associations between each birth measurement and concentrations of eight elements (copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc) were calculated using random-effects regression on pooled data.

RESULTS

A 200-ng/m3 increase in sulfur in PM2.5 was associated with an increased risk of LBW (adjusted odds ratio = 1.36; 95% confidence interval: 1.17, 1.58). Increased nickel and zinc in PM2.5 concentrations were also associated with an increased risk of LBW. Head circumference was reduced at higher exposure to all elements except potassium. All associations with sulfur were most robust to adjustment for PM2.5 mass concentration. All results were similar for PM10.

CONCLUSION

Sulfur, reflecting secondary combustion particles in this study, may adversely affect LBW and head circumference, independently of particle mass.

CITATION

Pedersen M, Gehring U, Beelen R, Wang M, Giorgis-Allemand L, Andersen AM, Basagaña X, Bernard C, Cirach M, Forastiere F, de Hoogh K, Gražulevičienė R, Gruzieva O, Hoek G, Jedynska A, Klümper C, Kooter IM, Krämer U, Kukkonen J, Porta D, Postma DS, Raaschou-Nielsen O, van Rossem L, Sunyer J, Sørensen M, Tsai MY, Vrijkotte TG, Wilhelm M, Nieuwenhuijsen MJ, Pershagen G, Brunekreef B, Kogevinas M, Slama R. 2016. Elemental constituents of particulate matter and newborn's size in eight European cohorts. Environ Health Perspect 124:141-150; http://dx.doi.org/10.1289/ehp.1409546.

Effects of Environmental Exposures on Fetal and Childhood Growth Trajectories

Delayed fetal growth and adverse birth outcomes are some of the greatest public health threats to this generation of children worldwide because these conditions are major determinants of mortality, morbidity, and disability in infancy and childhood and are also associated with diseases in adult life. A number of studies have investigated the impacts of a range of environmental conditions during pregnancy (including air pollution, endocrine disruptors, persistent organic pollutants, heavy metals) on fetal and child development. The results, while provocative, have been largely inconsistent. This review summarizes up to date epidemiologic studies linking major environmental pollutants to fetal and child development and suggested future directions for further investigation.

Ambient Air Pollution and Newborn Size and Adiposity at Birth: Differences by Maternal Ethnicity (the Born in Bradford Study Cohort)

BACKGROUND

Exposure to ambient air pollution has been associated with reduced size of newborns; however, the modifying effect of maternal ethnicity remains little explored among South Asians.

OBJECTIVES

We investigated ethnic differences in the association between ambient air pollution and newborn's size.

METHOD

Pregnant women were recruited between 2007 and 2010 for the Born in Bradford cohort study, in England. Exposures to particulate matter (≤ 10 μm, PM10; ≤ 2.5 μm, PM2.5), PM2.5 absorbance, and nitrogen oxides (NOx, NO2) were estimated using land-use regressions models. Using multivariate linear regression models, we evaluated effect modification by maternal ethnicity ("white British" or "Pakistani origin," self-reported) on the associations of air pollution and birth weight, head circumference, and triceps and subscapular skinfold thickness.

RESULTS

A 5-μg/m3 increase in mean third trimester PM2.5 was associated with significantly lower birth weight and smaller head circumference in children of white British mothers (-43 g; 95% CI: -76, -10 and -0.28 cm; 95% CI: -0.39, -0.17, respectively), but not in children of Pakistani origin (9 g; 95% CI: -17, 35 and -0.08 cm; 95% CI: -0.17, 0.01, respectively) (p(int) = 0.03 and < 0.001). In contrast, PM2.5 was associated with significantly larger triceps and subscapular skinfold thicknesses in children of Pakistani origin (0.17 mm; 95% CI: 0.08, 0.25 and 0.21 mm; 95% CI: 0.12, 0.29, respectively), but not in white British children (-0.02 mm; 95% CI: -0.14, 0.01 and 0.06 mm; 95% CI: -0.06, 0.18, respectively) (p(int) = 0.06 and 0.11). Patterns of associations for PM10 and PM2.5 absorbance according to ethnicity were similar to those for PM2.5, but associations of the outcomes with NO2 and NOx were mostly nonsignificant in both ethnic groups.

CONCLUSIONS

Our results suggest that associations of ambient PM exposures with newborn size and adiposity differ between white British and Pakistani origin infants.

CITATION

Schembari A, de Hoogh K, Pedersen M, Dadvand P, Martinez D, Hoek G, Petherick ES, Wright J, Nieuwenhuijsen MJ. 2015. Ambient air pollution and newborn size and adiposity at birth: differences by maternal ethnicity (the Born in Bradford study cohort). Environ Health Perspect 123:1208-1215; http://dx.doi.org/10.1289/ehp.1408675.

Area-level socioeconomic deprivation, nitrogen dioxide exposure, and term birth weight in New York City

Numerous studies have linked air pollution with adverse birth outcomes, but relatively few have examined differential associations across the socioeconomic gradient. To evaluate interaction effects of gestational nitrogen dioxide (NO2) and area-level socioeconomic deprivation on fetal growth, we used: (1) highly spatially-resolved air pollution data from the New York City Community Air Survey (NYCCAS); and (2) spatially-stratified principle component analysis of census variables previously associated with birth outcomes to define area-level deprivation. New York City (NYC) hospital birth records for years 2008-2010 were restricted to full-term, singleton births to non-smoking mothers (n=243,853). We used generalized additive mixed models to examine the potentially non-linear interaction of nitrogen dioxide (NO2) and deprivation categories on birth weight (and estimated linear associations, for comparison), adjusting for individual-level socio-demographic characteristics and sensitivity testing adjustment for co-pollutant exposures. Estimated NO2 exposures were highest, and most varying, among mothers residing in the most-affluent census tracts, and lowest among mothers residing in mid-range deprivation tracts. In non-linear models, we found an inverse association between NO2 and birth weight in the least-deprived and most-deprived areas (p-values<0.001 and 0.05, respectively) but no association in the mid-range of deprivation (p=0.8). Likewise, in linear models, a 10 ppb increase in NO2 was associated with a decrease in birth weight among mothers in the least-deprived and most-deprived areas of -16.2g (95% CI: -21.9 to -10.5) and -11.0 g (95% CI: -22.8 to 0.9), respectively, and a non-significant change in the mid-range areas [β=0.5 g (95% CI: -7.7 to 8.7)]. Linear slopes in the most- and least-deprived quartiles differed from the mid-range (reference group) (p-values<0.001 and 0.09, respectively). The complex patterning in air pollution exposure and deprivation in NYC, however, precludes simple interpretation of interactive effects on birth weight, and highlights the importance of considering differential distributions of air pollution concentrations, and potential differences in susceptibility, across deprivation levels.

Exposure to cooking fuels and birth weight in Lanzhou, China: a birth cohort study

BACKGROUND

Early studies have suggested that biomass cooking fuels were associated with increased risk of low birth weight (LBW). However it is unclear if this reduced birth weight was due to prematurity or intrauterine growth restriction (IUGR).

METHODS

In order to understand the relationship between various cooking fuels and risk of LBW and small for gestational age (SGA), we analyzed data from a birth cohort study conducted in Lanzhou, China which included 9,895 singleton live births.

RESULTS

Compared to mothers using gas as cooking fuel, significant reductions in birth weight were observed for mothers using coal (weight difference = 73.31 g, 95 % CI: 26.86, 119.77) and biomass (weight difference = 87.84 g, 95 % CI: 10.76, 164.46). Using biomass as cooking fuel was associated with more than two-fold increased risk of LBW (OR = 2.51, 95 % CI: 1.26, 5.01), and the risk was mainly seen among preterm births (OR = 3.43, 95 % CI: 1.21, 9.74). No significant associations with LBW were observed among mothers using coal or electromagnetic stoves for cooking.

CONCLUSIONS

These findings suggest that exposure to biomass during pregnancy is associated with risk of LBW, and the effect of biomass on LBW may be primarily due to prematurity rather than IUGR.

Maternal exposure to fine particulate matter (PM2.5) and pregnancy outcomes: a meta-analysis

A growing body of evidence has investigated the association between maternal exposure to PM2.5 (particulate matter with aerodynamic diameter 2.5 μm) during pregnancy and adverse pregnancy outcomes. However, the results of those studies are not consistent. To synthetically quantify the relationship between maternal exposure to PM2.5 during pregnancy and pregnancy outcomes (the change in birth weight, low birth weight (LBW), preterm birth (PTB), small for gestational age (SGA), and stillbirth), a meta-analysis of 25 published observational epidemiological studies that met our selection criteria was conducted. Results suggested a 10 μg/m(3) increase in PM2.5 was positively associated with LBW (odds ratio (OR) = 1.05; 95 % confidence interval (CI), 1.02-1.07), PTB (OR = 1.10; 95 % CI, 1.03-1.18), and SGA (OR = 1.15; 95 % CI, 1.10-1.20) based on entire pregnancy exposure, and pooled estimate of decrease in birth weight was 14.58 g (95 % CI, 9.86-19.31); however, there was no evidence of a statistically significant effect of per 10 μg/m(3) increase in PM2.5 exposure on the risk of stillbirth (OR = 1.18; 95 % CI, 0.69-2.04). With respect to three different gestation periods, no significant risks were found in PTB, stillbirth, and the first trimester on the change of birth weight with a 10 μg/m(3) increase in PM2.5. In this study, a comprehensive quantitative analysis of the results show that PM2.5 can increase the risk of LBW, PTB, and SGA; pregnant women need to take effective measures to reduce PM2.5 exposure.

A meta-analysis of exposure to particulate matter and adverse birth outcomes

OBJECTIVES

The objective of this study was to conduct a systematic review to provide summarized evidence on the association between maternal exposure to particulate air pollution and birth weight (BW) and preterm birth (PTB) after taking into consideration the potential confounding effect of maternal smoking.

METHODS

We systematically searched all published cohort and case-control studies examining BW and PTB association with particulate matter (PM, less than or equal to 2.5μm and 10.0 μm in diameter, PM2.5 and PM10, respectively) from PubMed and Web of Science, from January 1980 to April 2015. We extracted coefficients for continuous BW and odds ratio (OR) for PTB from each individual study, and meta-analysis was used to combine the coefficient and OR of individual studies. The methodological quality of individual study was assessed using a standard protocol proposed by Downs and Black. Forty-four studies met the inclusion criteria.

RESULTS

In random effects meta-analyses, BW as a continuous outcome was negativelyassociated with 10 μg/m(3) increase in PM10 (-10.31 g; 95% confidence interval [CI], -13.57 to -3.13 g; I-squared=0%, p=0.947) and PM2.5 (-22.17 g; 95% CI, -37.93 to -6.41 g; I-squared=92.3%, p <0.001) exposure during entire pregnancy, adjusted for maternal smoking. A significantly increased risk of PTB per 10 μg/m(3) increase in PM10 (OR, 1.23; 95% CI, 1.04 to 1.41; I-squared=0%, p =0.977) and PM2.5 (OR, 1.14; 95% CI, 1.06 to 1.22; I-squared=92.5%, p <0.001) exposure during entire pregnancy was observed. Effect size of change in BW per 10 μg/m(3) increase in PM tended to report stronger associations after adjustment for maternal smoking.

CONCLUSIONS

While this systematic review supports an adverse impact of maternal exposure to particulate air pollution on birth outcomes, variation in effects by exposure period and sources of heterogeneity between studies should be further explored.

Maternal exposure to fine particulate pollution during narrow gestational periods and newborn health in Harris County, Texas

It remains unclear when the fetus is most susceptible to the effects of particulate air pollution. We conducted a population-based study in a large urban area to evaluate associations between preterm birth (PTB) and fetal growth and exposures to fine particles (PM(2.5)) during narrow periods of gestation. We identified 177,816 births during 2005-2007 among mothers who resided in Harris County, Texas at the time of delivery. We created three mutually exclusive categories of mildly (33-36 completed weeks of gestation), moderately (29-32 weeks of gestation), and severely (20-28 weeks of gestation) PTB, and among full term infants, we identified those who were born small for their gestational age. Using routine air monitoring data, we generated county-level daily time series of estimated ambient air levels of PM2.5 and then computed exposure metrics during every 4 weeks of a mother's pregnancy. We evaluated associations in each 4-week period using multiple logistic regression. A 10 μg/m(3) increase in PM(2.5) exposure in the first 4 weeks of pregnancy significantly increased the odds of mildly, moderately and severely PTB by 16, 71 and 73 %, respectively. Associations were stronger when infants with birth defects were excluded. Our findings indicate an association between PM(2.5) and PTB, with stronger associations for moderately and severely PTB infants. Efforts should continue to implement stricter air quality standards and improve ambient air quality.

Sources and contents of air pollution affecting term low birth weight in Los Angeles County, California, 2001-2008

BACKGROUND

Low birth weight (LBW, <2500 g) has been associated with exposure to air pollution, but it is still unclear which sources or components of air pollution might be in play. The association between ultrafine particles and LBW has never been studied.

OBJECTIVES

To study the relationships between LBW in term born infants and exposure to particles by size fraction, source and chemical composition, and complementary components of air pollution in Los Angeles County (California, USA) over the period 2001-2008.

METHODS

Birth certificates (n=960,945) were geocoded to maternal residence. Primary particulate matter (PM) concentrations by source and composition were modeled. Measured fine PM, nitrogen dioxide and ozone concentrations were interpolated using empirical Bayesian kriging. Traffic indices were estimated. Associations between LBW and air pollution metrics were examined using generalized additive models, adjusting for maternal age, parity, race/ethnicity, education, neighborhood income, gestational age and infant sex.

RESULTS

Increased LBW risks were associated with the mass of primary fine and ultrafine PM, with several major sources (especially gasoline, wood burning and commercial meat cooking) of primary PM, and chemical species in primary PM (elemental and organic carbon, potassium, iron, chromium, nickel, and titanium but not lead or arsenic). Increased LBW risks were also associated with total fine PM mass, nitrogen dioxide and local traffic indices (especially within 50 m from home), but not with ozone. Stronger associations were observed in infants born to women with low socioeconomic status, chronic hypertension, diabetes and a high body mass index.

CONCLUSIONS

This study supports previously reported associations between traffic-related pollutants and LBW and suggests other pollution sources and components, including ultrafine particles, as possible risk factors.

The association of PM(2.5) with full term low birth weight at different spatial scales

There is interest in determining the relationship between fine particulate matter air pollution and various health outcomes, including birth outcomes such as term low birth weight. Previous studies have come to different conclusions. In this study we consider whether the effect may vary by location and gestational period. We also compare results when using different spatial resolutions for the air concentration estimates. Among the seven states considered, New Jersey and New York had the highest PM2.5 levels (average full gestation period exposures of 13 µg/m(3)) and the largest rate of low birth weight births (2.6 and 2.8%, respectively); conversely Utah and Minnesota had the lowest PM2.5 levels (9 µg/m(3)) and the lowest rates of low birth weight births (2.1 and1.9%, respectively). There is an association between PM2.5 exposure and low birth weight in New York for the full gestation period and all three trimesters, in Minnesota for the full gestation period and the first and third trimesters, and in New Jersey for the full gestation period and the first trimester. When we pooled the data across states, the OR for the full gestation period was 1.030 (95% CI: 1.022-1.037) and it was highest for the first trimester (OR 1.018; CI: 1.013-1.022) and decreasing during the later trimesters. When we used a finer spatial resolution, the strengths of the associations tended to diminish and were no longer statistically significant. We consider reasons why these differences may occur and their implications for evaluating the effects of PM2.5 on birth outcomes.

The Association between Airborne PM2.5 Chemical Constituents and Birth Weight-Implication of Buffer Exposure Assignment

Several papers reported associations between airborne fine particulate matter (PM_2.5) and birth weight, though findings are inconsistent across studies. Conflicting results might be due to (1) different PM_2.5 chemical structure across locations, and (2) various exposure assignment methods across studies even among the studies that use ambient monitors to assess exposure. We investigated associations between birth weight and PM_2.5 chemical constituents, considering issues arising from choice of buffer size (i.e. distance between residence and pollution monitor). We estimated the association between each pollutant and term birth weight applying buffers of 5 to 30km in Connecticut (2000-2006), in the New England region of the U.S. We also investigated the implication of the choice of buffer size in relation to population characteristics, such as socioeconomic status. Results indicate that some PM_2.5 chemical constituents, such as nitrate, are associated with lower birth weight and appear more harmful than other constituents. However, associations vary with buffer size and the implications of different buffer sizes may differ by pollutant. A homogeneous pollutant level within a certain distance is a common assumption in many environmental epidemiology studies, but the validity of this assumption may vary by pollutant. Furthermore, we found that areas close to monitors reflect more minority and lower socio-economic populations, which implies that different exposure approaches may result in different types of study populations. Our findings demonstrate that choosing an exposure method involves key tradeoffs of the impacts of exposure misclassification, sample size, and population characteristics.

The Association between Airborne PM2.5 Chemical Constituents and Birth Weight-Implication of Buffer Exposure Assignment

Several papers reported associations between airborne fine particulate matter (PM_2.5) and birth weight, though findings are inconsistent across studies. Conflicting results might be due to (1) different PM_2.5 chemical structure across locations, and (2) various exposure assignment methods across studies even among the studies that use ambient monitors to assess exposure. We investigated associations between birth weight and PM_2.5 chemical constituents, considering issues arising from choice of buffer size (i.e. distance between residence and pollution monitor). We estimated the association between each pollutant and term birth weight applying buffers of 5 to 30km in Connecticut (2000-2006), in the New England region of the U.S. We also investigated the implication of the choice of buffer size in relation to population characteristics, such as socioeconomic status. Results indicate that some PM_2.5 chemical constituents, such as nitrate, are associated with lower birth weight and appear more harmful than other constituents. However, associations vary with buffer size and the implications of different buffer sizes may differ by pollutant. A homogeneous pollutant level within a certain distance is a common assumption in many environmental epidemiology studies, but the validity of this assumption may vary by pollutant. Furthermore, we found that areas close to monitors reflect more minority and lower socio-economic populations, which implies that different exposure approaches may result in different types of study populations. Our findings demonstrate that choosing an exposure method involves key tradeoffs of the impacts of exposure misclassification, sample size, and population characteristics.

Calibrating MODIS aerosol optical depth for predicting daily PM2.5 concentrations via statistical downscaling

There has been a growing interest in the use of satellite-retrieved aerosol optical depth (AOD) to estimate ambient concentrations of PM2.5 (particulate matter <2.5 μm in aerodynamic diameter). With their broad spatial coverage, satellite data can increase the spatial-temporal availability of air quality data beyond ground monitoring measurements and potentially improve exposure assessment for population-based health studies. This paper describes a statistical downscaling approach that brings together (1) recent advances in PM2.5 land use regression models utilizing AOD and (2) statistical data fusion techniques for combining air quality data sets that have different spatial resolutions. Statistical downscaling assumes the associations between AOD and PM2.5 concentrations to be spatially and temporally dependent and offers two key advantages. First, it enables us to use gridded AOD data to predict PM2.5 concentrations at spatial point locations. Second, the unified hierarchical framework provides straightforward uncertainty quantification in the predicted PM2.5 concentrations. The proposed methodology is applied to a data set of daily AOD values in southeastern United States during the period 2003-2005. Via cross-validation experiments, our model had an out-of-sample prediction R(2) of 0.78 and a root mean-squared error (RMSE) of 3.61 μg/m(3) between observed and predicted daily PM2.5 concentrations. This corresponds to a 10% decrease in RMSE compared with the same land use regression model without AOD as a predictor. Prediction performances of spatial-temporal interpolations to locations and on days without monitoring PM2.5 measurements were also examined.

Associations between prenatal exposure to air pollution, small for gestational age, and term low birthweight in a state-wide birth cohort

A range of health effects, including adverse pregnancy outcomes, have been associated with exposure to ambient concentrations of particulate matter (PM) and ozone (O3). The objective of this study was to determine whether maternal exposure to fine particulate matter (PM2.5) and O3 during pregnancy is associated with the risk of term low birthweight and small for gestational age infants in both single and co-pollutant models. Term low birthweight and small for gestational age were determined using all birth certificates from North Carolina from 2003 to 2005. Ambient air concentrations of PM2.5 and O3 were predicted using a hierarchical Bayesian model of air pollution that combined modeled air pollution estimates from the EPA׳s Community Multi-Scale Air Quality (CMAQ) model with air monitor data measured by the EPA׳s Air Quality System. Binomial regression, adjusted for multiple potential confounders, was performed. In adjusted single-pollutant models for the third trimester, O3 concentration was positively associated with small for gestational age and term low birthweight births [risk ratios for an interquartile range increase in O3: 1.16 (95% CI 1.11, 1.22) for small for gestational age and 2.03 (95% CI 1.80, 2.30) for term low birthweight]; however, inverse or null associations were observed for PM2.5 [risk ratios for an interquartile range increase in PM2.5: 0.97 (95% CI 0.95, 0.99) for small for gestational age and 1.01 (95% CI 0.97, 1.06) for term low birthweight]. Findings were similar in co-pollutant models and linear models of birthweight. These results suggest that O3 concentrations in both urban and rural areas may be associated with an increased risk of term low birthweight and small for gestational age births.

Maternal occupation and term low birth weight in a predominantly latina population in los angeles, california

OBJECTIVES

Focusing on Latinas, we investigated whether maternal occupations during pregnancy increase term low birth weight (TLBW) (less than 2500 g; 37 weeks or more).

METHODS

In a case-control study (n = 1498) nested within a 2003 birth cohort (n = 58,316) in Los Angeles County, California (65% Latina), we assessed the influence of maternal occupation on TLBW, using Occupational Codes based on the 2000 US Census Occupational Classification System.

RESULTS

Odds ratios (ORs) for TLBW were increased among women working during pregnancy in "transportation and material moving operations" (adjusted OR = 3.28; 95% confidence interval = 1.00 to 10.73), "food preparation and serving occupations" (adjusted OR = 3.03, 95% confidence interval = 1.21 to 7.62), or "production occupations" (adjusted OR = 2.63, 95% confidence interval = 1.01 to 6.82) compared with "office occupations;" 73% to 93% of women working in these higher-risk jobs were immigrant Latinas.

CONCLUSIONS

Working conditions in various jobs held mainly by first-generation immigrant Latinas increase risks for TLBW and need to be addressed to develop strategies to reduce TLBW.

Ambient fine particulate matter, nitrogen dioxide, and term birth weight in New York, New York

Building on a unique exposure assessment project in New York, New York, we examined the relationship of particulate matter with aerodynamic diameter less than 2.5 μm and nitrogen dioxide with birth weight, restricting the population to term births to nonsmokers, along with other restrictions, to isolate the potential impact of air pollution on growth. We included 252,967 births in 2008-2010 identified in vital records, and we assigned exposure at the residential location by using validated models that accounted for spatial and temporal factors. Estimates of association were adjusted for individual and contextual sociodemographic characteristics and season, using linear mixed models to quantify the predicted change in birth weight in grams related to increasing pollution levels. Adjusted estimates for particulate matter with aerodynamic diameter less than 2.5 μm indicated that for each 10-µg/m(3) increase in exposure, birth weights declined by 18.4, 10.5, 29.7, and 48.4 g for exposures in the first, second, and third trimesters and for the total pregnancy, respectively. Adjusted estimates for nitrogen dioxide indicated that for each 10-ppb increase in exposure, birth weights declined by 14.2, 15.9, 18.0, and 18.0 g for exposures in the first, second, and third trimesters and for the total pregnancy, respectively. These results strongly support the association of urban air pollution exposure with reduced fetal growth.

Effects of fine particulate matter and its constituents on low birth weight among full-term infants in California

Relationships between prenatal exposure to fine particles (PM2.5) and birth weight have been observed previously. Few studies have investigated specific constituents of PM2.5, which may identify sources and major contributors of risk. We examined the effects of trimester and full gestational prenatal exposures to PM2.5 mass and 23 PM2.5 constituents on birth weight among 646,296 term births in California between 2000 and 2006. We used linear and logistic regression models to assess associations between exposures and birth weight and risk of low birth weight (LBW; <2500g), respectively. Models were adjusted for individual demographic characteristics, apparent temperature, month and year of birth, region, and socioeconomic indicators. Higher full gestational exposures to PM2.5 mass and several PM2.5 constituents were significantly associated with reductions in term birth weight. The largest reductions in birth weight were associated with exposure to vanadium, sulfur, sulfate, iron, elemental carbon, titanium, manganese, bromine, ammonium, zinc, and copper. Several of these PM2.5 constituents were associated with increased risk of term LBW. Reductions in birth weight were generally larger among younger mothers and varied by race/ethnicity. Exposure to specific constituents of PM2.5, especially traffic-related particles, sulfur constituents, and metals, were associated with decreased birth weight in California.

Spatial and temporal estimation of air pollutants in New York City: exposure assignment for use in a birth outcomes study

BACKGROUND

Recent epidemiological studies have examined the associations between air pollution and birth outcomes. Regulatory air quality monitors often used in these studies, however, were spatially sparse and unable to capture relevant within-city variation in exposure during pregnancy.

METHODS

This study developed two-week average exposure estimates for fine particles (PM2.5) and nitrogen dioxide (NO2) during pregnancy for 274,996 New York City births in 2008-2010. The two-week average exposures were constructed by first developing land use regression (LUR) models of spatial variation in annual average PM2.5 and NO2 data from 150 locations in the New York City Community Air Survey and emissions source data near monitors. The annual average concentrations from the spatial models were adjusted to account for city-wide temporal trends using time series derived from regulatory monitors. Models were developed using Year 1 data and validated using Year 2 data. Two-week average exposures were then estimated for three buffers of maternal address and were averaged into the last six weeks, the trimesters, and the entire period of gestation. We characterized temporal variation of exposure estimates, correlation between PM2.5 and NO2, and correlation of exposures across trimesters.

RESULTS

The LUR models of average annual concentrations explained a substantial amount of the spatial variation (R2 = 0.79 for PM2.5 and 0.80 for NO2). In the validation, predictions of Year 2 two-week average concentrations showed strong agreement with measured concentrations (R2 = 0.83 for PM2.5 and 0.79 for NO2). PM2.5 exhibited greater temporal variation than NO2. The relative contribution of temporal vs. spatial variation in the estimated exposures varied by time window. The differing seasonal cycle of these pollutants (bi-annual for PM2.5 and annual for NO2) resulted in different patterns of correlations in the estimated exposures across trimesters. The three levels of spatial buffer did not make a substantive difference in estimated exposures.

CONCLUSIONS

The combination of spatially resolved monitoring data, LUR models and temporal adjustment using regulatory monitoring data yielded exposure estimates for PM2.5 and NO2 that performed well in validation tests. The interaction between seasonality of air pollution and exposure intervals during pregnancy needs to be considered in future studies.

Postnatal sulfur dioxide exposure reversibly alters parasympathetic regulation of heart rate

Perinatal sulfur dioxide exposure disrupts parasympathetic regulation of cardiovascular activity. Here, we examine the relative risks of prenatal versus postnatal exposure to the air pollutant and the reversibility of the cardiovascular effects. Two groups of animals were used for this study. For prenatal exposure, pregnant Sprague-Dawley dams were exposed to 5 parts per million sulfur dioxide for 1 hour daily throughout gestation and with their pups after birth to medical-grade air through 6 days postnatal. For postnatal exposure, dams were exposed to air, and after delivery along with their pups to 5 parts per million sulfur dioxide through postnatal day 6. ECGs were recorded from pups on postnatal day 5 to examine changes in heart rate. Whole-cell patch-clamp electrophysiology was used to examine changes in neurotransmission to cardiac vagal neurons in the nucleus ambiguus on sulfur dioxide exposure. Postnatal sulfur dioxide exposure diminished glutamatergic neurotransmission to cardiac vagal neurons by 40.9% and increased heart rate, whereas prenatal exposure altered neither of these properties. When postnatal exposure concluded on postnatal day 5, excitatory neurotransmission remained decreased through day 6 and returned to basal levels by day 7. ECGs showed that heart rate remained elevated through day 6 and recovered by day 7. On activation of the parasympathetic diving reflex, the response was significantly blunted by postnatal sulfur dioxide exposure through day 7 but recovered by day 8. Postnatal, but not prenatal, exposure to sulfur dioxide can disrupt parasympathetic regulation of cardiovascular activity. Neonates can recover from these effects within 2 to 3 days of discontinued exposure.