Traffic-related atmospheric pollutants levels during pregnancy and offspring's term birth weight: a study relying on a land-use regression exposure model

Meta-analysis of fine particulate matter exposure during pregnancy and birth weight: Exploring sources of heterogeneity

BACKGROUND

Several meta-analyses assessed the relationship between exposure to PM with aerodynamic diameter ≤ 2.5 μm (PM2.5) during pregnancy and birth weight (BW), but results were inconsistent and substantial unexplained heterogeneity was reported. We aimed to investigate the above association and to explore sources of heterogeneity across studies.

METHODS

We systematically reviewed the current worldwide evidence examining the association between PM2.5 and BW. The review protocol was registered on the PROSPERO website (CRD42020188996) and followed PRISMA guidelines. We extracted association measures for BW and low birth weight (LBW, BW < 2500 g) from each study to evaluate pooled summary measures and to explore sources of between-study heterogeneity.

FINDINGS

Of the 2677 articles identified, 84 met the inclusion criteria (~42 M births). Our random effects meta-analyses revealed substantial heterogeneity among included studies (I2 = 98.4 % and I2 = 77.7 %, for BW and LBW respectively). For LBW, the heterogeneity decreased (I2 = 59.7 %) after excluding four outlying studies, with a pooled odds ratio 1.07 (95 % confidence interval, CI: 1.05, 1.09) per a 10-μg/m3 increase in mean PM2.5 exposure over the entire pregnancy. Further subgroup analysis revealed geographic heterogeneity with higher association in Europe (1.34, (1.16, 1.55)) compared to Asia (1.06, (1.03, 1.10)) and US (1.07, (1.04, 1.10)).

CONCLUSION

The association between PM2.5 and birth weight varied depending on several factors. The sources of heterogeneity between studies included modifiers such as study region and period. Hence, it is advisable not to pool summary measures of PM2.5-BW associations and that policy would be informed by local evidence.

Association of longitudinal pet ownership with wheezing in 3-year-old children using the distributed lag model: the Japan Environment and Children's Study

BACKGROUND

Time-varying exposures like pet ownership pose challenges for identifying critical windows due to multicollinearity when modeled simultaneously. The Distributed Lag Model (DLM) estimates critical windows for time-varying exposures, which are mainly continuous variables. However, applying complex functions such as high-order splines and nonlinear functions within DLMs may not be suitable for situations with limited time points or binary exposure, such as in questionnaire surveys.

OBJECTIVES

(1) We examined the estimation performance of a simple DLM with fractional polynomial function for time-varying binary exposures through simulation experiments. (2) We evaluated the impact of pet ownership on childhood wheezing onset and estimate critical windows.

METHODS

(1) We compared logistic regression including time-varying exposure in separate models, in one model simultaneously, and using DLM. For evaluation, we employed bias, empirical standard error (EmpSE), and mean squared error (MSE). (2) The Japan Environment and Children's Study (JECS) is a prospective birth cohort study of approximately 100,000 parent-child pairs, registered across Japan from 2011 to 2014. We applied DLM to the JECS data up to age 3. The estimated odds ratios (OR) were considered to be within critical windows when they were significant at the 5% level.

RESULTS

(1) DLM and the separate model exhibited lower bias compared to the simultaneously model. Additionally, both DLM and the simultaneously model demonstrated lower EmpSEs than the separate model. In all scenarios, DLM had lower MSEs than the other methods. Specifically, where critical windows is clearly present and exposure correlation is high, DLM showed MSEs about 1/2 to 1/200 of those of other models. (2) Application of DLM to the JECS data showed that, unlike other models, a significant exposure effect was observed only between the ages of 0 and 6 months. During that periods, the highest ORs were 1.07 (95% confidence interval, 1.01 to 1.14) , observed between the ages of 2 and 5 months.

CONCLUSIONS

(1) A simple DLM improves the accuracy of exposure effect and critical windows estimation. (2) 0-6 months may be the critical windows for the effect of pet ownership on the wheezing onset at 3 years.

Pathogenesis of PM2.5-Related Disorders in Different Age Groups: Children, Adults, and the Elderly

The effects of PM2.5 on human health fluctuate greatly among various age groups, influenced by a range of physiological and immunological reactions. This paper compares the pathogenesis of the disease caused by PM2.5 in people of different ages, focusing on how children, adults, and the elderly are each susceptible to it because of differences in their bodies. Regarding children, exposure to PM2.5 is linked to many negative consequences. These factors consist of inflammation, oxidative stress, and respiratory problems, which might worsen pre-existing conditions and potentially cause neurotoxicity and developmental issues. Epigenetic changes can affect the immune system and make people more likely to get respiratory diseases. On the other hand, exposures during pregnancy can change how the cardiovascular and central nervous systems develop. In adults, the inhalation of PM2.5 is associated with a wide range of health problems. These include respiratory difficulties, reduced pulmonary function, and an increased susceptibility to illnesses such as asthma, chronic obstructive pulmonary disease (COPD), and lung cancer. In addition, exposure to PM2.5 induces systemic inflammation, cardiovascular diseases, insulin resistance, and neurotoxic consequences. Evident disturbances in the immune system and cognitive function demonstrate the broad impact of PM2.5. The elderly population is prone to developing respiratory and cardiovascular difficulties, which worsen their pre-existing health issues and raise the risk of cognitive decline and neurological illnesses. Having additional medical conditions, such as peptic ulcer disease, significantly increases the likelihood of being admitted to hospital.

Monthly average air pollution models using geographically weighted regression in Europe from 2000 to 2019

Detailed spatial models of monthly air pollution levels at a very fine spatial resolution (25 m) can help facilitate studies to explore critical time-windows of exposure at intermediate term. Seasonal changes in air pollution may affect both levels and spatial patterns of air pollution across Europe. We built Europe-wide land-use regression (LUR) models to estimate monthly concentrations of regulated air pollutants (NO2, O3, PM10 and PM2.5) between 2000 and 2019. Monthly average concentrations were collected from routine monitoring stations. Including both monthly-fixed and -varying spatial variables, we used supervised linear regression (SLR) to select predictors and geographically weighted regression (GWR) to estimate spatially-varying regression coefficients for each month. Model performance was assessed with 5-fold cross-validation (CV). We also compared the performance of the monthly LUR models with monthly adjusted concentrations. Results revealed significant monthly variations in both estimates and model structure, particularly for O3, PM10, and PM2.5. The 5-fold CV showed generally good performance of the monthly GWR models across months and years (5-fold CV R2: 0.31-0.66 for NO2, 0.4-0.79 for O3, 0.4-0.78 for PM10, 0.46-0.87 for PM2.5). Monthly GWR models slightly outperformed monthly-adjusted models. Correlations between monthly GWR model were generally moderate to high (Pearson correlation >0.6). In conclusion, we are the first to develop robust monthly LUR models for air pollution in Europe. These monthly LUR models, at a 25 m spatial resolution, enhance epidemiologists to better characterize Europe-wide intermediate-term health effects related to air pollution, facilitating investigations into critical exposure time windows in birth cohort studies.

Air pollution prediction and backcasting through a combination of mobile monitoring and historical on-road traffic emission inventories

An important challenge for studies of air pollution and health effects is the derivation of historical exposures. These generally entail some form of backcasting, which refers to a range of approaches that aim to project a current surface into the past. Accurate backcasting is conditional upon the availability of historical data for predictor variables and the ability to capture spatial and temporal trends in these variables. This study proposes a method to backcast traffic-related air pollution surfaces developed using land-use regression models by including temporal variability of traffic and emissions and trends in concentrations measured at reference stations. Nitrogen dioxide (NO2) concentrations collected in the City of Toronto using the Urban Scanner mobile platform were adjusted for historical trends captured at reference stations. The Bayesian Estimator of Abrupt change, Seasonal change, and Trend (BEAST), a powerful tool for time series decomposition, was employed to isolate seasonal variations, annual trends, and abrupt changes in NO2 at reference stations, hence decomposing the signal. Exposure surfaces were generated for a period extending from 2006 to 2020, exhibiting decreases ranging from 10 to 50 % depending on the neighborhood, with an average of 20.46 % across the city. Yearly surfaces were intersected with mobility patterns of Torontonians extracted from travel survey data for 2006 and 2016, illustrating strong spatial gradients in the evolution of NO2 over time, with larger decreases along major roads and highways and in the central core. These findings demonstrate that air pollution improvements throughout the 14 years are inhomogeneous across space.

Development of Spatio-Temporal Land Use Regression Models for Fine Particulate Matter and Wood-Burning Tracers in Temuco, Chile

Biomass burning is common in much of the world, and in some areas, residential wood-burning has increased. However, air pollution resulting from biomass burning is an important public health problem. A sampling campaign was carried out between May 2017 and July 2018 in over 64 sites in four sessions, to develop a spatio-temporal land use regression (LUR) model for fine particulate matter (PM) and wood-burning tracers levoglucosan and soluble potassium (Ksol) in a city heavily impacted by wood-burning. The mean (sd) was 46.5 (37.4) μg m-3 for PM2.5, 0.607 (0.538) μg m-3 for levoglucosan, and 0.635 (0.489) μg m-3 for Ksol. LUR models for PM2.5, levoglucosan, and Ksol had a satisfactory performance (LOSOCV R2), explaining 88.8%, 87.4%, and 87.3% of the total variance, respectively. All models included sociodemographic predictors consistent with the pattern of use of wood-burning in homes. The models were applied to predict concentrations surfaces and to estimate exposures for an epidemiological study.

Mitigation strategies for controlling urban particulate pollution from traffic congestion: Road expansion and road public transport

The mismatch between urban transportation demands and local transportation supplies in municipal regions may cause serious traffic congestion and high vehicle exhaust emissions (VEEs). Although it has been found that road expansion and the provision of road public transport can mitigate traffic congestion and VEEs, the effectiveness of these public strategies in alleviating traffic congestion-related VEEs has been empirically compared in few studies. With the use of a panel dataset for 260 prefecture-level cities in China from 2013 to 2018, we fill this gap via empirically examining the effects of several popular strategies that promote the efficiency of urban road transportation, including road expansion and road public transport provision, on urban air pollution of fine particulate matter (PM2.5). Then we further investigate metrics measured by passenger and freight volumes based on local urban road coverage that can suitably reflect the mismatch degree between local transportation demands and supplies. The empirical results indicated a positive and statistically significant correlation between urban PM2.5 levels and road expansion but not between PM2.5 levels and road public transport, suggesting that road expansion may unintentionally increase the transportation volume and thus local PM2.5 levels. Importantly, we found that the passenger and freight volumes per unit road length are negatively and significantly correlated with the local particulate pollution concentration across different model specifications, while the passenger and freight volumes of road transportation do not directly affect local PM2.5 levels. We also employed a series of robustness tests to overcome the concerns associated with measurement errors, omitted variable biases, model misspecifications and endogeneity, and consistent results were obtained. These results indicated that when facing limited public budgets, the passenger and freight volumes per unit road length should be considered to measure the effectiveness of road infrastructure investments in alleviating local particulate pollution caused by traffic congestion.

MXene-Decorated Nylon Mesh Filters for Improvement of Indoor Air Quality by PM2.5 Filtration

Air pollution is a problem that is increasing day by day and poses a threat on a global scale. Particulate matter (PM) is one of the air pollutants that is the biggest concern regarding air quality. In order to control PM pollution, highly effective air filters are required. This is especially necessary for PM with a diameter of less than 2.5 micrometers (PM_2.5), which poses a health risk to humans. In this study, we demonstrate for the first time the use of a two-dimensional titanium carbide (Ti₃C₂) MXene nanosheets-decorated nylon mesh (MDNM) as a low cost and highly efficient PM_2.5 filter. This study develops a proof-of-concept method to capture PM_2.5. Thanks to their high specific surface area and active surface-terminating groups, conductive MXene nanosheets have made nylon mesh filters promising candidates for air filtration. The developed filters used electrostatic force to capture PM_2.5 and showed high removal efficiency (90.05%) when an ionizer was used and under an applied voltage of 10 V, while a commercial high-efficiency particulate air (HEPA) filter had a removal efficiency of 91.03% measured under identical conditions. The proposed filters, which stand out with their low energy consumption, low pressure drop (∼14 Pa), and cost-effectiveness, have the potential to be a strong competitor to conventional PM filter systems used in many fields.

Ambient Air Pollution and All-Cause and Cause-Specific Mortality in an Analysis of Asian Cohorts

INTRODUCTION

Much of what is currently known about the adverse effects of ambient air pollution comes from studies conducted in high-income regions, with relatively low air pollution levels. The aim of the current project is to examine the relationship between exposure to ambient air pollution (as predicted from satellite-based models) and all-cause and cause-specific mortality in several Asian cohorts.

METHODS

Cohorts were recruited from the Asia Cohort Consortium (ACC). The geocoded residences of participants were assigned levels of ambient particulate material with aerodynamic diameter of 2.5 μm or less (PM2.5) and nitrogen dioxide (NO2) utilizing global satellite-derived models and assigned for the year of enrollment (or closest available year). The association between ambient exposure and mortality was established with Cox proportional hazard models, after adjustment for common confounders. Both single- and two-pollutant models were generated. Model robustness was evaluated, and hazard ratios were calculated for each cohort separately and combined via random effect meta-analysis for pooled risk estimates.

RESULTS

Six cohort studies from the ACC participated: the Community-based Cancer Screening Program (CBCSCP, Taiwan), the Golestan Cohort Study (Iran), the Health Effects for Arsenic Longitudinal Study (HEALS, Bangladesh), the Japan Public Health Center-based Prospective Study (JPHC), the Korean Multi-center Cancer Cohort Study (KMCC), and the Mumbai Cohort Study (MCS, India). The cohorts represented over 340,000 participants.

Mean exposures to PM2.5 ranged from 8 to 58 μg/m3. Mean exposures to NO2 ranged from 7 to 23 ppb. For PM2.5, a positive, borderline nonsignificant relationship was observed between PM2.5 and cardiovascular mortality. Other relationships with PM2.5 tended toward the null in meta-analysis. For NO2, an overall positive relationship was observed between exposure to NO2 and all cancers and lung cancer. A borderline association between NO2 and nonmalignant lung disease was also observed. The findings within individual cohorts remained consistent across a variety of subgroups and alternative analyses, including two-pollutant models.

CONCLUSIONS

In a pooled examination of cohort studies across Asia, ambient PM2.5 exposure appears to be associated with an increased risk of cardiovascular mortality and ambient NO2 exposure is associated with an increased cancer (and lung cancer) mortality. This project has shown that satellite-derived models of pollution can be used in examinations of mortality risk in areas with either incomplete or missing air pollution monitoring.

Early-life residential green spaces and traffic exposure in association with young adult body composition: a longitudinal birth cohort study of twins

BACKGROUND

Globally, the rapid increase of obesity is reaching alarming proportions. A new approach to reduce obesity and its comorbidities involves tackling the built environment. Environmental influences seem to play an important role, but the environmental influences in early life on adult body composition have not been thoroughly investigated. This study seeks to fill the research gap by examining early-life exposure to residential green spaces and traffic exposure in association with body composition among a population of young adult twins.

METHODS

As part of the East Flanders Prospective Twin Survey (EFPTS) cohort, this study included 332 twins. Residential addresses of the mothers at time of birth of the twins were geocoded to determine residential green spaces and traffic exposure. To capture body composition, body mass index, waist-to-hip ratio (WHR), waist circumference, skinfold thickness, leptin levels, and fat percentage were measured at adult age. Linear mixed modelling analyses were conducted to investigate early-life environmental exposures in association with body composition, while accounting for potential confounders. In addition, moderator effects of zygosity/chorionicity, sex and socio-economic status were tested.

RESULTS

Each interquartile range (IQR) increase in distance to highway was found associated with an increase of 1.2% in WHR (95%CI 0.2-2.2%). For landcover of green spaces, each IQR increase was associated with 0.8% increase in WHR (95%CI 0.4-1.3%), 1.4% increase in waist circumference (95%CI 0.5-2.2%), and 2.3% increase in body fat (95%CI 0.2-4.4%). Stratified analyses by zygosity/chorionicity type indicated that in monozygotic monochorionic twins, each IQR increase in land cover of green spaces was associated with 1.3% increase in WHR (95%CI 0.5-2.1%). In monozygotic dichorionic twins, each IQR increase in land cover of green spaces was associated with 1.4% increase in waist-circumference (95%CI 0.6-2.2%).

CONCLUSIONS

The built environment in which mothers reside during pregnancy might play a role on body composition among young adult twins. Our study revealed that based on zygosity/chorionicity type differential effects of prenatal exposure to green spaces on body composition at adult age might exist.

Developmental Programming in Animal Models: Critical Evidence of Current Environmental Negative Changes

The Developmental Origins of Health and Disease (DOHaD) approach answers questions surrounding the early events suffered by the mother during reproductive stages that can either partially or permanently influence the developmental programming of children, predisposing them to be either healthy or exhibit negative health outcomes in adulthood. Globally, vulnerable populations tend to present high obesity rates, including among school-age children and women of reproductive age. In addition, adults suffer from high rates of diabetes, hypertension, cardiovascular, and other metabolic diseases. The increase in metabolic outcomes has been associated with the combination of maternal womb conditions and adult lifestyle-related factors such as malnutrition and obesity, smoking habits, and alcoholism. However, to date, "new environmental changes" have recently been considered negative factors of development, such as maternal sedentary lifestyle, lack of maternal attachment during lactation, overcrowding, smog, overurbanization, industrialization, noise pollution, and psychosocial stress experienced during the current SARS-CoV-2 pandemic. Therefore, it is important to recognize how all these factors impact offspring development during pregnancy and lactation, a period in which the subject cannot protect itself from these mechanisms. This review aims to introduce the importance of studying DOHaD, discuss classical programming studies, and address the importance of studying new emerging programming mechanisms, known as actual lifestyle factors, during pregnancy and lactation.

Life Course of Asthma

Asthma is a heterogeneous chronic airway disease that can vary over a lifetime. Although broad categories of asthma by severity and type have been constructed, there remains a tremendous opportunity to discover an approach to managing asthma with additional factors in mind. Many in the field have suggested and are pursuing a novel paradigm shift in how asthma might be better managed, considering the life course of exposures, management priorities, and predicted trajectory of lung function growth. This approach will require a more holistic view of prenatal, postnatal, adolescence, hormonal and gender aspects, and the aging process. In addition, the environment, externally and internally, including in one's genetic code and epigenetic changes, are factors that affect how asthma progresses or becomes more stable in individuals. This chapter focuses on the various influences that may, to differing degrees, affect people with asthma, which can develop at any time in their lives. Shifting the paradigm of thought and strategies for care and advocating for public policies and health delivery that focus on this philosophy is paramount to advance asthma care for all.

Impacts of traffic-related particulate matter pollution on semen quality: A retrospective cohort study relying on the random forest model in a megacity of South China

BACKGROUND

Emerging evidence shows the detrimental impacts of particulate matter (PM) on poor semen quality. High-resolution estimates of PM concentrations are conducive to evaluating accurate associations between traffic-related PM exposure and semen quality.

METHODS

In this study, we firstly developed a random forest model incorporating meteorological factors, land-use information, traffic-related variables, and other spatiotemporal predictors to estimate daily traffic-related PM concentrations, including PM_2.5, PM₁₀, and PM₁. Then we enrolled 1310 semen donors corresponding to 4912 semen samples during the study period from January 1, 2019, and December 31, 2019 in Guangzhou city, China. Linear mixed models were employed to associate individual exposures to traffic-related PM during the entire (0-90 lag days) and key periods (0-37 and 34-77 lag days) with semen quality parameters, including sperm concentration, sperm count, progressive motility and total motility.

RESULTS

The results showed that decreased sperm concentration was associated with PM₁₀ exposures (β: -0.21, 95 % CI: -0.35, -0.07), sperm count was inversely related to both PM_2.5 (β: -0.19, 95 % CI: -0.35, -0.02) and PM₁₀ (β: -0.19, 95 % CI: -0.33, -0.05) during the 0-90 days lag exposure window. Besides, PM_2.5 and PM₁₀ might diminish sperm concentration by mainly affecting the late phase of sperm development (0-37 lag days). Stratified analyses suggested that PBF and drinking seemed to modify the associations between PM exposure and sperm motility. We did not observe any significant associations of PM₁ exposures with semen parameters.

CONCLUSION

Our results indicate that exposure to traffic-related PM_2.5 and PM₁₀ pollution throughout spermatogenesis may adversely affect semen quality, especially sperm concentration and count. The findings provided more evidence for the negative associations between traffic-related PM exposure and semen quality, highlighting the necessity to reduce ambient air pollution through environmental policy.

In-utero personal exposure to PM2.5 impacted by indoor and outdoor sources and birthweight in the MADRES cohort

BACKGROUND

In-utero exposure to outdoor particulate matter with aerodynamic diameter less than 2.5 μm (PM_2.5) is linked with low birthweight. However, previous results are mixed, likely due to measurement error introduced by estimating personal exposure from ambient data. This study investigated the effect of total personal PM_2.5 exposure on birthweight and whether it differed when it was more heavily impacted by sources of indoor vs outdoor origin in the MADRES cohort study.

METHODS

Personal PM_2.5 exposure was measured in 205 pregnant women in the 3rd trimester using 48 h integrated, filter-based sampling. Linear regression was used to test the association between personal PM_2.5 exposure and birthweight, adjusting for key covariates. Interactions of PM_2.5 with variables representing indoor sources of PM_2.5, home ventilation, or time spent indoors tested whether the effect of total PM_2.5 on birthweight varied when it was more impacted by sources of indoor vs outdoor origin.

RESULTS

In a sample of largely Hispanic (81%) pregnant women, total personal PM_2.5 was not significantly associated with birthweight (β = 38.6 per 1SD increase in PM_2.5; 95% CI:-21.1, 98.2). This association however, differed by home type (single family home: 156.9 (26.9, 287.0), 2-4 attached units:-16.6 (-111.9, 78.7), 5+ units:-62.6 (-184.9, 59.6), missing: 145.4 (-4.1, 294.9), interaction p = 0.028) and by household air conditioner use (none of the time: -27.6 (-101.5, 46.3) vs. some of the time: 139.9 (42.9, 237.0), interaction p = 0.008) Additionally, the effect of personal PM_2.5 on birthweight varied by time spent indoors (none or little of the time: - 45.1 (-208.3, 118.1) vs. most or all of the time: 57.1 (-7.3, 121.6), interaction p = 0.255).

CONCLUSIONS

While no significant association between total personal PM_2.5 exposure and birthweight was found, there was evidence that multi-unit housing (vs. single-family homes), candle and/or incense smoke, and greater outdoor source contributions to personal PM_2.5 were more strongly associated with lower birthweight.

Maternal exposure to black carbon and nitrogen dioxide during pregnancy and birth weight: Using machine-learning methods to achieve balance in inverse-probability weights

BACKGROUND

Low birth weight is associated with increased risks of health problems in infancy and later life. Among the epidemiological analyses suggesting an association between air pollution and birth weight, few have estimated the effects of black carbon (BC) or together with nitrogen dioxide (NO₂), and even fewer studies have used causal modelling.

METHODS

We examined 1,119,011 birth records between 2001/01/01 and 2015/12/31 from the Massachusetts Birth Registry to investigate causal associations between prenatal exposure to BC and NO₂ and birth weight. We calculated mean residential BC and NO₂ exposures 0-30, and 31-280 days prior to birth from validated spatial-temporal models. We fit generalized propensity score models with gradient boosting tuned by a new algorithm to achieve covariate balance, then fit marginal structural models with stabilized inverse-probability weights.

RESULTS

Throughout pregnancy, the average birth weight would drop by 17.0 g (95% CI: 15.4, 18.6) for an IQR increase of 0.14 μg/m³ in BC and would independently drop by 19.9 g (95% CI: 18.6, 21.3) for an IQR increase of 9.8 ppb in NO₂. Most of the negative effects of BC on birth weight are from 0 to 30 days before the delivery date. The estimated odds ratio of low birth weight for every IQR increase during the entire pregnancy was 1.131 (95% CI: 1.106, 1.156) for BC and 1.082 (95% CI: 1.062, 1.103) for NO₂.

CONCLUSIONS

We found that prenatal exposures to both BC and NO₂ were associated with lower birth weight.

Exposure to Traffic Density during Pregnancy and Birth Weight in a National Cohort, 2000-2017

The variation on birth weight is associated with several outcomes early on in life and low birth weight (LBW) increases the risk of morbidity and mortality. Some environmental exposures during pregnancy, such as particulate matters and other traffic-related pollutants can have a significant effect on pregnant women and fetuses. The aim of this study is to estimate the effect of exposure to traffic density during pregnancy over birth weight in Spain, from 2000–2017. This was a retrospective, cross-sectional study using the information from Spain Birth Registry Statistics database. The traffic density was measured using the Annual average daily traffic. Multivariate linear regression models using birth weight and traffic density were performed, as well as a logistic regression model to estimated Odds ratios for LBW and GAM models to evaluate the non-linear effect. Our findings showed that increases in traffic density were associated with reduction of birth weight and increases of LBW risk. Moreover, exposure to high and very-high traffic-density during pregnancy were associated with reduction of birth weight and increase on LBW risk comparing with exposure to low number of cars trespassing the neighborhoods. The results of this study agree with previous literature and highlights the need of effective policies for reducing traffic density in residential neighborhoods of cities and towns.

Exposure to Ambient Air Pollutant PM10 in the Second Trimester of Pregnancy Is Associated with Preterm Birth: A Birth-Based Health Information Cohort Study

Objectives

We evaluated the effects of exposure to high concentrations of particulate matter (PM)10 on preterm birth (PTB) and identified a critical concentration of PM10 that could lead to PTB via a birth-based health information cohort study.

Methods

We conducted a birth-based cohort study consisting of nonanomalous singleton births at 22-42 weeks. PTB was defined as babies born alive before 37 weeks of pregnancy. Pregnancy period exposure averages were estimated for PM10 based on the China National Environmental Monitoring Centre (CNEMC). Pregnant women who lived within 50 km of the monitor station were recruited into this study. Logistic regression analyses were performed to determine the association between PTB and exposure to PM10 at different pregnancy periods with adjustment for confounding factors.

Results

The relative frequency of PTB was 8.7% in the study cohort of 5,291 singleton live births. A total of 1137 women had a high level of PM10 exposure (≥60 μg/m3) in the second trimester of pregnancy. The average concentrations of PM10 in the first, second, and third trimesters of pregnancy and throughout pregnancy were 53.8 μg/m3, 54.2 μg/m3, 55.6 μg/m3, and 54.3 μg/m3, respectively. The generalized additive model (GAM) analysis showed that there was a nonlinear correlation between PM10 and PTB in the second trimester of pregnancy (P < 0.001). The adjusted odds ratio between PTB and low concentration PM10 exposure (PM10 < 60 μg/m3) in the second trimester of pregnancy was 1.01 (95% CI 0.95-1.05). However, high PM10 exposure (PM10 ≥ 60 μg/m3) in the second trimester of pregnancy had an increased PTB risk even after adjustment for coexisting risk factors with an adjusted odds ratio of 1.78 (95% CI 1.69-1.87), and the incidence of PTB increased with an increase in PM10 exposure.

Conclusions

Our research discovered that exposure to high levels of PM10 increases the risk of PTB and the second trimester is the most vulnerable gestational period to ambient air pollution exposure. PM10 concentrations more than 60 μg/m3 are detrimental to pregnant women in their second trimester. This study has implications for health informatics-oriented healthcare decision support systems.

Air pollution exposure impairs lung function in infants

Aim

To assess associations between air pollution exposure and infant lung function.

Methods

Healthy infants from Stockholm were recruited to two cohorts (n = 99 and n = 78). Infant spirometry included plethysmography and raised volume forced expiratory flows. In pooled analyses, lung function at ~6 months of age was related to time‐weighted average air pollution levels at residential addresses from birth until the lung function test. The pollutants included particulate matter with an aerodynamic diameter < 10 μm (PM₁₀) or <2.5 μm and nitrogen dioxide.

Results

There were significant inverse relations between air pollution exposure during infancy and forced expiratory volume at 0.5 s (FEV_0.5) as well as forced vital capacity (FVC) for all pollutants. For example, the decline was 10.1 ml (95% confidence interval 1.3–18.8) and 10.3 ml (0.5–20.1) in FEV_0.5 and FVC, respectively, for an interquartile increment of 5.3 μg/m³ in PM₁₀. Corresponding associations for minute ventilation and functional residual capacity were 43.3 ml/min (−9.75–96.3) and 0.84 ml (−4.14–5.82).

Conclusions

Air pollution exposure was associated with impaired infant lung function measures related to airway calibre and lung volume, suggesting that comparatively low levels of air pollution negatively affect lung function in early life.

Maternal exposure to ambient PM2.5 and term birth weight: A systematic review and meta-analysis of effect estimates

Effect estimates of prenatal exposure to ambient PM_2.5 on change in grams (β) of birth weight among term births (≥37 weeks of gestation; term birth weight, TBW) vary widely across studies. We present the first systematic review and meta-analysis of evidence regarding these associations. Sixty-two studies met the eligibility criteria for this review, and 31 studies were included in the meta-analysis. Random-effects meta-analysis was used to assess the quantitative relationships. Subgroup analyses were performed to gain insight into heterogeneity derived from exposure assessment methods (grouped by land use regression [LUR]-models, aerosol optical depth [AOD]-based models, interpolation/dispersion/Bayesian models, and data from monitoring stations), study regions, and concentrations of PM_2.5 exposure. The overall pooled estimate involving 23,925,941 newborns showed that TBW was negatively associated with PM_2.5 exposure (per 10 μg/m³ increment) during the entire pregnancy (β = -16.54 g), but with high heterogeneity (I² = 95.6%). The effect estimate in the LUR-models subgroup (β = -16.77 g) was the closest to the overall estimate and with less heterogeneity (I² = 18.3%) than in the other subgroups of AOD-based models (β = -41.58 g; I² = 95.6%), interpolation/dispersion models (β = -10.78 g; I² = 86.6%), and data from monitoring stations (β = -11.53 g; I² = 97.3%). Even PM_2.5 exposure levels of lower than 10 μg/m³ (the WHO air quality guideline value) had adverse effects on TBW. The LUR-models subgroup was the only subgroup that obtained similar significant of negative associations during the three trimesters as the overall trimester-specific analyses. In conclusion, TBW was negatively associated with maternal PM_2.5 exposures during the entire pregnancy and each trimester. More studies based on relatively standardized exposure assessment methods need to be conducted to further understand the precise susceptible exposure time windows and potential mechanisms.

Dynamics of skin microvascular blood flow in 4-6-year-old children in association with pre- and postnatal black carbon and particulate air pollution exposure

BACKGROUND

A growing body of evidence indicates that cardiovascular health in adulthood, particularly that of the microcirculation, could find its roots during prenatal development. In this study, we investigated the association between pre- and postnatal air pollution exposure on heat-induced skin hyperemia as a dynamic marker of the microvasculature.

METHODS

In 139 children between the ages of 4 and 6 who are followed longitudinally within the ENVIRONAGE birth cohort, we measured skin perfusion by Laser Doppler probes using the Periflux6000. Residential black carbon (BC), particulate (PM₁₀ and PM_2.5) air pollution, and nitrogen dioxide (NO₂) levels were modelled for each participant's home address using a high-resolution spatiotemporal model for multiple time windows. We assessed the association between skin hyperemia and pre- and postnatal air pollution using multiple regression models while adjusting for relevant covariates.

RESULTS

Residential BC exposure during the whole pregnancy averaged (IQR) 1.42 (1.22-1.58) µg/m³, PM₁₀ 18.88 (16.64 - 21.13) µg/m³, PM_2.5 13.67 (11.5 - 15.56) µg/m³ and NO₂ 18.39 (15.52 - 20.31) µg/m³. An IQR increment in BC exposure during the third trimester of pregnancy was associated with an 11.5 % (95% CI: -20.1 to -1.9; p = 0.020) lower skin hyperemia. Similar effect estimates were retrieved for PM₁₀, PM_2.5 and NO₂ (respectively 13.9 % [95% CI: -21.9 to -3.0; p = 0.003], 17.0 % [95% CI: -26.7 to -6.1; p = 0.004] and 12.7% [95 % CI: -22.2 to -1.9; p = 0.023] lower skin hyperemia). In multipollutant models, PM_2.5 showed the strongest inverse association with skin hyperemia. Postnatal exposure to BC, PM₁₀, PM_2.5 or NO₂, was not associated with skin hyperemia at the age of 4 to 6, and did not alter the previous reported prenatal associations when taken into account.

CONCLUSION

Our findings support that BC, particulate air pollution, and NO₂ exposure, even at low concentrations, during prenatal life, can have long-lasting consequences for the microvasculature. This proposes a role of prenatal air pollution exposures over and beyond postnatal exposure in the microvascular alterations which were persistent into childhood.

Mobility in post-pandemic economic reopening under social distancing guidelines: Congestion, emissions, and contact exposure in public transit

COVID-19 has raised new challenges for transportation in the post-pandemic era. The social distancing requirement, with the aim of reducing contact risk in public transit, could exacerbate traffic congestion and emissions. We propose a simulation tool to evaluate the trade-offs between traffic congestion, emissions, and policies impacting travel behavior to mitigate the spread of COVID-19 including social distancing and working from home. Open-source agent-based simulation models are used to evaluate the transportation system usage for the case study of New York City. A Post Processing Software for Air Quality (PPS-AQ) estimation is used to evaluate the air quality impacts. Finally, system-wide contact exposure on the subway is estimated from the traffic simulation output. The social distancing requirement in public transit is found to be effective in reducing contact exposure, but it has negative congestion and emission impacts on Manhattan and neighborhoods at transit and commercial hubs. While telework can reduce congestion and emissions citywide, in Manhattan the negative impacts are higher due to behavioral inertia and social distancing. The findings suggest that contact exposure to COVID-19 on subways is relatively low, especially if social distancing practices are followed. The proposed integrated traffic simulation models and air quality estimation model can help policymakers evaluate the impact of policies on traffic congestion and emissions as well as identifying hot spots, both temporally and spatially.

Maternal Ambient Exposure to Atmospheric Pollutants during Pregnancy and Offspring Term Birth Weight in the Nationwide ELFE Cohort

Background: Studies have reported associations between maternal exposure to atmospheric pollution and lower birth weight. However, the evidence is not consistent and uncertainties remain. We used advanced statistical approaches to robustly estimate the association of atmospheric pollutant exposure during specific pregnancy time windows with term birth weight (TBW) in a nationwide study. Methods: Among 13,334 women from the French Longitudinal Study of Children (ELFE) cohort, exposures to PM_2.5, PM₁₀ (particles < 2.5 µm and <10 µm) and NO₂ (nitrogen dioxide) were estimated using a fine spatio-temporal exposure model. We used inverse probability scores and doubly robust methods in generalized additive models accounting for spatial autocorrelation to study the association of such exposures with TBW. Results: First trimester exposures were associated with an increased TBW. Second trimester exposures were associated with a decreased TBW by 17.1 g (95% CI, −26.8, −7.3) and by 18.0 g (−26.6, −9.4) for each 5 µg/m³ increase in PM_2.5 and PM₁₀, respectively, and by 15.9 g (−27.6, −4.2) for each 10 µg/m³ increase in NO₂. Third trimester exposures (truncated at 37 gestational weeks) were associated with a decreased TBW by 48.1 g (−58.1, −38.0) for PM_2.5, 38.1 g (−46.7, −29.6) for PM₁₀ and 14.7 g (−25.3, −4.0) for NO₂. Effects of pollutants on TBW were larger in rural areas. Conclusions: Our results support an adverse effect of air pollutant exposure on TBW. We highlighted a larger effect of air pollutants on TBW among women living in rural areas compared to women living in urban areas.

Label-free detection of uptake, accumulation, and translocation of diesel exhaust particles in ex vivo perfused human placenta

Background

Pregnant women and developing fetuses comprise a particularly vulnerable population as multiple studies have shown associations between prenatal air pollution exposure and adverse pregnancy outcomes. However, the mechanisms underlying the observed developmental toxicity are mostly unknown, in particular, if pollution particles can cross the human placenta to reach the fetal circulation.

Results

Here, we investigated the accumulation and translocation of diesel exhaust particles (DEPs), as a model particle for combustion-derived pollution, in human perfused placentae using label-free detection by femtosecond pulsed laser illumination. The results do not reveal a significant particle transfer across term placentae within 6 h of perfusion. However, DEPs accumulate in placental tissue, especially in the syncytiotrophoblast layer that mediates a wealth of essential functions to support and maintain a successful pregnancy. Furthermore, DEPs are found in placental macrophages and fetal endothelial cells, showing that some particles can overcome the syncytiotrophoblasts to reach the fetal capillaries. Few particles are also observed inside fetal microvessels.

Conclusions

Overall, we show that DEPs accumulate in key cell types of the placental tissue and can cross the human placenta, although in limited amounts. These findings are crucial for risk assessment and protection of pregnant women and highlight the urgent need for further research on the direct and indirect placenta-mediated developmental toxicity of ambient particulates.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12951-021-00886-5.

Exposure to air pollutants and risk of congenital anomalies: A systematic review and metaanalysis

BACKGROUND

Congenital malformations are considered as one of the significant causes of preterm as well as neonatal morbidity and mortality. Literature suggests the association of diverse congenital deformities with maternal exposure to air pollutants. However, the evidence is still inconclusive on the manifestation of these during pregnancy. Thus, systematic review was done on the available epidemiological studies studying the effect of air pollutants on congenital malformations. Furthermore, the meta-analysis was conducted for several combinations of air pollutants and congenital defects.

METHODS

Twenty six epidemiological studies were extracted from the databases and examined for association of risk of congenital defects with air pollutant concentrations. Metaanalysis was done if the risk estimates of the same anomaly and pollutant group were reported in at least three studies.

RESULTS

Each study reported a statistically significant increased risk of congenital malformation with some air pollutant, amid the several tested combinations. Our meta-analysis reported that nitrogen dioxide and PM_2.5 were associated with the risk of pulmonary valve stenosis with OR = 1.74 and OR = 1.42 respectively. The risk of developing tetralogy of Fallot (TOF) was observed to be associated with PM_2.5 with OR = 1.52_. SO₂ exposure was related to a high risk of the ventricular septal defect (VSD) with OR = 1.15 and orofacial defects (OR = 1.27).

CONCLUSION

It is evidenced that ambient air pollutants have some effect on congenital malformations. Standard case definitions, improved methods of exposure, and better control of confounders will improve future research in this area.

Association between the pregnancy exposome and fetal growth

BACKGROUND

Several environmental contaminants were shown to possibly influence fetal growth, generally from single exposure family studies, which are prone to publication bias and confounding by co-exposures. The exposome paradigm offers perspectives to avoid selective reporting of findings and to control for confounding by co-exposures. We aimed to characterize associations of fetal growth with the pregnancy chemical and external exposomes.

METHODS

Within the Human Early-Life Exposome project, 131 prenatal exposures were assessed using biomarkers and environmental models in 1287 mother-child pairs from six European cohorts. We investigated their associations with fetal growth using a deletion-substitution-addition (DSA) algorithm considering all exposures simultaneously, and an exposome-wide association study (ExWAS) considering each exposure independently. We corrected for exposure measurement error and tested for exposure-exposure and sex-exposure interactions.

RESULTS

The DSA model identified lead blood level, which was associated with a 97 g birth weight decrease for each doubling in lead concentration. No exposure passed the multiple testing-corrected significance threshold of ExWAS; without multiple testing correction, this model was in favour of negative associations of lead, fine particulate matter concentration and absorbance with birth weight, and of a positive sex-specific association of parabens with birth weight in boys. No two-way interaction between exposure variables was identified.

CONCLUSIONS

This first large-scale exposome study of fetal growth simultaneously considered >100 environmental exposures. Compared with single exposure studies, our approach allowed making all tests (usually reported in successive publications) explicit. Lead exposure is still a health concern in Europe and parabens health effects warrant further investigation.

Air pollution and pregnancy outcomes based on exposure evaluation using a land use regression model: A systematic review

This review systematically assessed those studies investigating the association between air pollution and birth outcomes using land use regression (LUR) models for exposure assessment. Fifty-four studies were identified which were published between 2007 and 2019. Most of these were conducted in America, Spain and Canada, while only five were conducted in China. One hundred and ninety-seven LUR models were developed for different pollutants. The main pollutants that these studies assessed were NO₂ and PM_2.5, and the main pregnancy outcomes investigated were preterm birth (PTB), small for gestational age (SGA) and birth weight. Studies consistently found that NO₂ exposure during pregnancy was associated with reduced fetal growth and development. The effect of NO₂ on other adverse pregnancy outcomes is unclear. In addition, it was found that increased PM_2.5 (aerodynamic equivalent diameter ≤ 2.5 um) exposure during pregnancy reduced birth weight. The effect of PM_2.5 on other adverse pregnancy outcomes is also unclear. The relationship between other pollutants and adverse pregnancy outcomes is uncertain based on the existing research. Exposure assessment with LUR modeling has been widely used in Europe and North America, but used less in China. Future studies are recommended to use LUR modeling for individual exposure evaluation in China to better characterize the relationship between air pollution and adverse pregnancy outcomes. In addition, further research is required given that a lot of the associations looked at in the review were inconclusive.

Spatial heterogeneity in the association between particulate matter air pollution and low birth weight in South Korea

As many studies showed the spatial heterogeneity in the association between particulate matter (PM) air pollution and low birth weight (LBW), few studies focused on the variation of local associations at the national scale and related areal characteristics. This study aimed to explore different approaches to estimating local effects of PM with an aerodynamic diameter ≤10 μm (PM₁₀) on LBW across 235 districts in South Korea, to investigate the spatial pattern of local associations, and to examine the relationship with local socio-demographic and environmental characteristics. LBW was identified in 5,692,650 mothers from birth certificate data for 2001-2013. We estimated individual annual-average concentrations of PM₁₀ at centroids of mothers' residential districts by using a previously-validated prediction model. Then, we estimated district-specific odds ratios of LBW for PM₁₀ using modified geographically weighted logistic regression. Here, we applied four approaches with different neighborhood definitions: the distance-based approach within 20- and 40-km bandwidth and the hybrid approach replacing with adjacent districts for urban districts <100 km². In addition, we compared district-specific socioeconomic indicators and emission estimates across three groups of districts that showed significantly positive, no, and significantly negative associations. Medians of district-specific estimates of four approaches were similar to the global estimate and between each other. However, their variability differed with some unreasonably high estimates when a small distance was applied as the neighborhood definition, although spatial pattern was generally similar among the four. The hybrid approach based on the different neighborhood definition by urban and rural areas provided stable risk estimates. Higher risk districts in rural areas were found in more socioeconomically-deprived areas, whereas urban areas showed higher risk districts when their air pollution emissions were higher. Our approach and findings will help identify high risk areas and enhance understanding of geographic determinants.

Adverse Birth Outcomes Related to NO2 and PM Exposure: European Systematic Review and Meta-Analysis

There is a growing number of international studies on the association between ambient air pollution and adverse pregnancy outcomes, and this systematic review and meta-analysis has been conducted focusing on European countries, to assess the crucial public health issue of this suspected association on this geographical area. A systematic literature search (based on Preferred Reporting Items for Systematic reviews and Meta-Analyses, PRISMA, guidelines) has been performed on all European epidemiological studies published up until 1 April 2020, on the association between maternal exposure during pregnancy to nitrogen dioxide (NO₂) or particular matter (PM) and the risk of adverse birth outcomes, including: low birth weight (LBW) and preterm birth (PTB). Fourteen articles were included in the systematic review and nine of them were included in the meta-analysis. Our meta-analysis was conducted for 2 combinations of NO₂ exposure related to birth weight and PTB. Our systematic review revealed that risk of LBW increases with the increase of air pollution exposure (including PM₁₀, PM_2.5 and NO₂) during the whole pregnancy. Our meta-analysis found that birth weight decreases with NO₂ increase (pooled beta = −13.63, 95% confidence interval (CI) (−28.03, 0.77)) and the risk of PTB increase for 10 µg/m3 increase in NO₂ (pooled odds ratio (OR) = 1.07, 95% CI (0.90, 1.28)). However, the results were not statistically significant. Our finding support the main international results, suggesting that increased air pollution exposure during pregnancy might contribute to adverse birth outcomes, especially LBW. This body of evidence has limitations that impede the formulation of firm conclusions. Further studies, well-focused on European countries, are called to resolve the limitations which could affect the strength of association such as: the exposure assessment, the critical windows of exposure during pregnancy, and the definition of adverse birth outcomes. This analysis of limitations of the current body of research could be used as a baseline for further studies and may serve as basis for reflection for research agenda improvements.

Improving spatial prediction of health risk assessment for Hg, As, Cu, and Pb in soil based on land-use regression

Heavy-metal pollution is a significant health and environmental concern in areas of rapid industrialization in China. The accuracy of spatial mapping of pollutant is the main constraint on spatial prediction of health risks. Our study addressed the possibility of improving spatial prediction accuracy of risk assessment. We developed land-use regression (LUR) models for Hg, As, Cu, and Pb based on surface soil sampling, land-use data, and soil properties. The regression results suggested that LUR was more accurate than ordinary kriging method. Spatial prediction accuracy of Hg, As, Cu, and Pb were improved by 15%, 59%, 36%, and 20%, respectively. Then, spatial distribution of health risk was assessed by using distributions of heavy metal and exposure parameters. Chronic risk of children was controlled by distribution of Pb and carcinogenic controlled by As. The result indicated that Pb and As were the main sources of health risk for children in Kunshan. Chronic and carcinogenic risk maps could clearly show where we should pay attention to and control the risk. This study provided a simple approach to draw spatially explicit maps of health risk which were useful for pollution control and public health risk management.

Estimating daily PM2.5 concentrations in New York City at the neighborhood-scale: Implications for integrating non-regulatory measurements

Previous PM_2.5 related epidemiological studies mainly relied on data from sparse regulatory monitors to assess exposure. The introduction of non-regulatory PM_2.5 monitors presents both opportunities and challenges to researchers and air quality managers. In this study, we evaluated the advantages and limitations of integrating non-regulatory PM_2.5 measurements into a satellite-based daily PM_2.5 model at 100 m resolution in New York City in 2015. Two separate machine learning models were developed, one using only PM_2.5 data from the US Environmental Protection Agency (EPA), and the other with measurements from both EPA and the New York City Community Air Survey (NYCCAS). The EPA-only model obtained a cross-validation (CV) R² of 0.85 while the EPA + NYCCAS model obtained a CV R² of 0.73. With the help of the NYCCAS measurements, the EPA + NYCCAS model predicted distinctly different PM_2.5 spatial patterns and more pollution hotspots compared with the EPA model, and its predictions were >15% higher than the EPA model along major roads and in densely populated areas. Our results indicated that satellite AOD and non-regulatory PM_2.5 measurements can be fused together to capture neighborhood-scale PM_2.5 levels and previous studies may have underestimated the disease burden due to PM_2.5 in densely populated areas.

Maternal exposure to air pollutants and birth weight in Tehran, Iran

BACKGROUND

Air pollution can cause various health outcomes, especially in susceptible groups including pregnant women. Low birth weight (LBW) is among the adverse birth outcomes and is one of the main causes of infant mortality. The aim of this study was to assess the association between air pollutants and LBW in Tehran, Iran.

METHODS

In this case-control study, 2144 babies born in three hospitals of Tehran (Iran) during 2011 to 2012 whose mothers were the residents of this city in last 5 years were considered. Of these, 468 infants with birth weight < 2500 g and 1676 with birth weight ≥ 2500 g were regarded as case and control groups, respectively. Gestational age was also considered for definition of cases (small for gestational age (SGA)) and controls (appropriate for gestational age). Land use regression models were used to assess exposure to particulate matter ≤10 μm in aerodynamic diameter (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂) and volatile organic compounds (benzene, toluene, ethylbenzene, o-xylene, m-xylene, p-xylene (BTEX), and total BTEX) during pregnancy. Logistic regression model was applied to assess the association between air pollutants and LBW.

RESULTS

The concentrations of air pollutants were very high but similar in cases and controls. After adjustment for potential confounding variables, no statistically significant association was observed between air pollutants and LBW. The adjusted odds ratios (95% confidence interval) for PM₁₀, SO₂, and benzene were 0.999 (0.994-1.005), 0.998 (0.993-1.003), and 0.980 (0.901-1.067), respectively.

CONCLUSIONS

No association was found between LBW and air pollutants. Further studies with more rigorous designs and access to more comprehensive information are suggested to assess the effect of other air pollutants, such as CO, O₃, PM_2.5, ultrafine particles, and oxidative potential of particles on birth outcomes.

Ambient black carbon particles reach the fetal side of human placenta

Particle transfer across the placenta has been suggested but to date, no direct evidence in real-life, human context exists. Here we report the presence of black carbon (BC) particles as part of combustion-derived particulate matter in human placentae using white-light generation under femtosecond pulsed illumination. BC is identified in all screened placentae, with an average (SD) particle count of 0.95 × 10⁴ (0.66 × 10⁴) and 2.09 × 10⁴ (0.9 × 10⁴) particles per mm³ for low and high exposed mothers, respectively. Furthermore, the placental BC load is positively associated with mothers’ residential BC exposure during pregnancy (0.63–2.42 µg per m³). Our finding that BC particles accumulate on the fetal side of the placenta suggests that ambient particulates could be transported towards the fetus and represents a potential mechanism explaining the detrimental health effects of pollution from early life onwards.

Exposure to air pollution during pregnancy has been associated with impaired birth outcomes. Here, Bové et al. report evidence of black carbon particle deposition on the fetal side of human placentae, including at early stages of pregnancy, suggesting air pollution could affect birth outcome through direct effects on the fetus.

Assessment of Traffic-Related Air Pollution: Case Study of Pregnant Women in South Texas

Population groups vulnerable to adverse effects of traffic-related air pollution correspond to children, pregnant women and elderly. Despite these effects, literature is limited in terms of studies focusing on these groups and a reason often cited is the limited information on their mobility important for exposure assessment. The current study presents a method for assessing individual-level exposure to traffic-related air pollution by integrating mobility patterns tracked by global positioning system (GPS) devices with dynamics of air pollutant concentrations. The study is based on a pool of 17 pregnant women residing in Hidalgo County, Texas. The traffic-related particulate matter with diameter of less than 2.5 micrometer (PM_2.5) emissions and air pollutant concentrations are predicted using MOVES and AERMOD models, respectively. The daily average traffic-related PM_2.5 concentration was found to be 0.32 µg/m³, with the highest concentration observed in transit (0.56 µg/m³), followed by indoors (0.29 µg/m³), and outdoor (0.26 µg/m³) microenvironment. The obtained exposure levels exhibited considerable variation between time periods, with higher levels during peak commuting periods, close to the US–Mexico border region and lower levels observed during midday periods. The study also assessed if there is any difference between traffic-related dynamic exposure, based on time-varying mobility patterns, and static exposure, based solely on residential locations, and found a difference of 9%, which could be attributed to the participants’ activity patterns being focused mostly indoors.

Ambient PM2.5 and clinically recognized early pregnancy loss: A case-control study with spatiotemporal exposure predictions

BACKGROUND

Experimental research suggests that fine particulate matter (PM_2.5) exposure might affect embryonic development. However, only few population-based studies have investigated the impact of maternal exposure to PM_2.5 on the early pregnancy loss.

OBJECTIVES

To estimate associations between clinically recognized early pregnancy loss (CREPL) and exposure to ambient PM_2.5 at individual residences during peri-conception periods, with the aim to identify susceptible exposure time windows.

METHODS

CREPL cases and normal early pregnancy controls (of similar age and gravidity presenting within one week, a total of 364 pairs) were recruited between July 2017 and July 2018 among women residing in Tianjin, China. Average ambient PM_2.5 concentrations of ten exposure windows (4 weeks, 2 weeks and 1 week before conception; the first, second, third and fourth single week, the first and second 2-week periods, and the entire 4-week period after conception) at the women's residential addresses were estimated using temporally-adjusted land use regression models. Associations between PM_2.5 exposures at specific peri-conception time windows and CREPL were examined using conditional logistic regression models, adjusted for covariates.

RESULTS

Based on adjusted models, CREPL was significantly associated with a 10 μg/m³ increase in PM_2.5 exposure during the second week after conception (OR = 1.15; 95% CI: 1.04, 1.27; p = 0.005), independent of effects at other time windows. There was also an association of CREPL with PM_2.5 during the entire 4-week period after conception (OR = 1.22; 95% CI: 1.02, 1.46; p = 0.027). There was little evidence for associations with exposure during pre-conception exposure windows.

CONCLUSIONS

Maternal exposures to ambient PM_2.5 during a critical time window following conception are associated with CREPL, with the second week after conception possibly being the exposure window of most vulnerability. Future studies should focus on replicating these findings and on pathogenic mechanisms.

Traffic-related Air Pollution and Pregnancy Loss

BACKGROUND

Traffic-related air pollution has been linked to multiple adverse pregnancy outcomes. However, few studies have examined pregnancy loss, targeting losses identified by hospital records, a large limitation as it does not capture events not reported to the medical system.

METHODS

We used a novel variation of the time-series design to determine the association, and identify the critical window of vulnerability, between week-to-week traffic-related air pollution and conceptions resulting in live births, using nitrogen dioxide (NO2) as a traffic emissions tracer. We used information from all live births recorded at Beth Israel Deaconess Medical Center in Boston, MA (2000-2013) and all live births in Tel Aviv District, Israel (2010-2013).

RESULTS

In Boston (68,969 live births), the strongest association was during the 15th week of gestation; for every 10 ppb of NO2 increase during that week, we observed a lower rate of live births (rate ratio [RR] = 0.87; 95% confidence interval [CI], 0.78, 0.97), using live birth-identified conceptions to infer pregnancy losses. In the Tel Aviv District (95,053 live births), the strongest estimate was during the 16th gestational week gestation (RR = 0.82; 95% CI, 0.76, 0.90 per 10 ppb of NO2).

CONCLUSIONS

Using weekly conceptions ending in live birth rather than identified pregnancy losses, we comprehensively analyzed the relationship between air pollution and all pregnancy loss throughout gestation. The observed results, with remarkable similarity in two independent locations, suggest that higher traffic-related air pollution levels are associated with pregnancy loss, with strongest estimates between the 10th and 20th gestational weeks.

Nitrogen dioxide air pollution and preterm birth in Shanghai, China

BACKGROUND

Nitrogen dioxide (NO₂) is a typical indicator of traffic-related air pollution, and few studies with exposure assessment of high resolution have been conducted to explore its association with preterm birth in China.

OBJECTIVES

To investigate the association between NO₂ exposure based on a land use regression (LUR) model and preterm birth in Shanghai, China.

METHODS

A retrospective cohort study was performed among 25,493 singleton pregnancies in a major maternity hospital in Shanghai, China, from 2014 to 2015. A temporally adjusted LUR model was used to predict the prenatal exposure to NO₂ based on residence address of each gravida. Logistic regression was performed to evaluate the associations of ambient NO₂ exposure with preterm birth during six exposure periods, including the entire pregnancy, the first trimester, the second trimester, the third trimester, the last month, and the last week before delivery. Sensitivity analysis with a matched case-control design was conducted to test the robustness of the association between NO₂ exposure and preterm birth.

RESULTS

The average NO₂ concentrations during the entire pregnancy was 48.23 µg/m³ among all participants. A 10 µg/m³ increase in NO₂ concentrations was associated with preterm birth, with an adjusted odds ratio of 1.03 (95% confidence interval [CI]: 0.96,1.10) for exposures during the entire pregnancy, 1.00 (95%CI: 0.95,1.06) in the first trimester, 1.01 (95%CI: 0.96,1.07) in the second trimester, 1.07 (95%CI: 1.02,1.13) in the third trimester, 1.10 (95%CI: 1.04,1.15) and 1.05 (95%CI: 1.00,1.09) in the month and week before delivery, respectively. The results of the matched case-control analysis were generally consistent with those of main analyses.

CONCLUSION

NO₂ may increase the risk of preterm birth, especially for exposures during the third trimester, the month and the week before delivery in Shanghai, China.

Ambient air pollution and pregnancy outcomes: A comprehensive review and identification of environmental public health challenges

There is a growing number of studies on the association between ambient air pollution and adverse pregnancy outcomes, but their results have been inconsistent. Consequently, a comprehensive review of this research area is needed. There was a wide variability in studied pregnancy outcomes, observed gestational windows of exposure, observed ambient air pollutants, applied exposure assessment methods and statistical analysis methods Gestational duration, preterm birth, (low) birth weight, and small for gestational age/intrauterine growth restriction were most commonly investigated pregnancy outcomes. Gestational windows of exposure typically included were whole pregnancy period, 1st, 2nd, 3rd trimester, first and last gestational months. Preterm birth was the outcome most extensively studied across various gestational windows, especially at the beginning and at the end of pregnancy. Particulate matter, nitrogen dioxide, ozone, and carbon monoxide were the most commonly used markers of ambient air pollution. Continuous monitoring data were frequently combined with spatially more precisely modelled estimates of exposure. Exposure to particulate matter and ozone over the entire pregnancy was significantly associated with higher risk for preterm birth: the pooled effect estimates were 1.09 (1.03-1.16) per 10 μg/m³ increase in particulate matter with an aerodynamic diameter of 10 µm or less (PM₁₀)_,1.24 (1.08-1.41) per 10 μg/m³ increase in particulate matter with an aerodynamic diameter of 2.5 µm or less (PM_2.5), and 1.03 (1.01-1.04) per 10 ppb increase in ozone. For pregnancy outcomes other than PTB, ranges of observed effect estimates were reported due to smaller number of studies included in each gestational window of exposure. Further research is needed to link the routine pregnancy outcome data with spatially and temporally resolved ambient air pollution data, while adjusting for commonly defined confounders. Methods for assessing exposure to mixtures of pollutants, indoor air pollution exposure, and various other environmental exposures, need to be developed.

Spatiotemporal land use random forest model for estimating metropolitan NO2 exposure in Japan

Adequate spatial and temporal estimates of NO₂ concentrations are essential for proper prenatal exposure assessment. Here, we develop a spatiotemporal land use random forest (LURF) model of the monthly mean NO₂ over four years in a metropolitan area of Japan. The overall objective is to obtain accurate NO₂ estimates for use in prenatal exposure assessments. We use random forests to convey the non-linear relationship between NO₂ concentrations and predictor variables, and compare the prediction accuracy with that of a linear regression. In addition, we include the distance decay effect of emission sources on NO₂ concentrations for more efficient model construction. The prediction accuracy of the LURF model is evaluated through a leave-one-monitor-out cross validation. We obtain a high R² value of 0.79, which is better than that of the conventional land use regression model using linear regression (R² of 0.73). We also evaluate the LURF model via a temporal and overall cross validation and obtain R² values of 0.84 and 0.92, respectively. We successfully integrate temporal and spatial components into our model, which exhibits higher accuracy than spatial models constructed individually for each month. Our findings illustrate the advantage of using a LURF to model the spatiotemporal variability of NO₂ concentrations.

The value of using seasonality and meteorological variables to model intra-urban PM2.5 variation

A yearlong air monitoring campaign was conducted to assess the impact of local temperature, relative humidity, and wind speed on the temporal and spatial variability of PM_2.5 in El Paso, Texas. Monitoring was conducted at four sites purposely selected to capture the local traffic variability. Effects of meteorological events on seasonal PM_2.5 variability were identified. For instance, in winter low-wind and low-temperature conditions were associated with high PM_2.5 events that contributed to elevated seasonal PM_2.5 levels. Similarly, in spring, high PM_2.5 events were associated with high-wind and low-relative humidity conditions. Correlation coefficients between meteorological variables and PM_2.5 fluctuated drastically across seasons. Specifically, it was observed that for most sites correlations between PM_2.5 and meteorological variables either changed from positive to negative or dissolved depending on the season. Overall, the results suggest that mixed effects analysis with season and site as fixed factors and meteorological variables as covariates could increase the explanatory value of LUR models for PM_2.5.

Is There an Association Between Ambient Air Pollution and Bladder Cancer Incidence? Analysis of 15 European Cohorts

BACKGROUND

Ambient air pollution contains low concentrations of carcinogens implicated in the etiology of urinary bladder cancer (BC). Little is known about whether exposure to air pollution influences BC in the general population.

OBJECTIVE

To evaluate the association between long-term exposure to ambient air pollution and BC incidence.

DESIGN, SETTING, AND PARTICIPANTS

We obtained data from 15 population-based cohorts enrolled between 1985 and 2005 in eight European countries (N=303431; mean follow-up 14.1 yr). We estimated exposure to nitrogen oxides (NO2 and NOx), particulate matter (PM) with diameter <10μm (PM10), <2.5μm (PM2.5), between 2.5 and 10μm (PM2.5-10), PM2.5absorbance (soot), elemental constituents of PM, organic carbon, and traffic density at baseline home addresses using standardized land-use regression models from the European Study of Cohorts for Air Pollution Effects project.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

We used Cox proportional-hazards models with adjustment for potential confounders for cohort-specific analyses and meta-analyses to estimate summary hazard ratios (HRs) for BC incidence.

RESULTS AND LIMITATIONS

During follow-up, 943 incident BC cases were diagnosed. In the meta-analysis, none of the exposures were associated with BC risk. The summary HRs associated with a 10-μg/m3 increase in NO2 and 5-μg/m3 increase in PM2.5 were 0.98 (95% confidence interval [CI] 0.89-1.08) and 0.86 (95% CI 0.63-1.18), respectively. Limitations include the lack of information about lifetime exposure.

CONCLUSIONS

There was no evidence of an association between exposure to outdoor air pollution levels at place of residence and risk of BC.

PATIENT SUMMARY

We assessed the link between outdoor air pollution at place of residence and bladder cancer using the largest study population to date and extensive assessment of exposure and comprehensive data on personal risk factors such as smoking. We found no association between the levels of outdoor air pollution at place of residence and bladder cancer risk.

Land use regression modelling estimating nitrogen oxides exposure in industrial south Durban, South Africa

BACKGROUND

The South Durban (SD) area of Durban, South Africa, has a history of air pollution issues due to the juxtaposition of low-income communities with industrial areas. This study used measurements of oxides of nitrogen (NO_x) to develop a land use regression (LUR) model to explain the spatial variation of air pollution concentrations in this area.

METHODS

Ambient NO_x was measured over two two-week sampling periods at 32 sites using Ogawa badges. Following the ESCAPE approach, an annual adjusted average was calculated for these results and regressed against pre-selected geographic predictor variables in a multivariate regression model. The LUR model was then applied to predict the NO_x exposure of a sample of pregnant women living in South Durban.

RESULTS

Measured NO_x levels ranged from 22.3-50.9μg/m³ with a median of 36μg/m³. The model developed accounts for 73% of the variance in ambient NO_x measurements using three input variables (length of minor roads within a 1000m radius, length of major roads within a 300m radius, and area of open space within a 1000m radius). Model cross validation yielded a R² of 0.59. Subsequent participant exposure estimates indicated exposure to ambient NO_x ranged from 19.9-53.2μg/m³, with a mean of 39μg/m³.

DISCUSSION AND CONCLUSION

This is the first study to develop a land use regression model that predicts ambient concentrations of NO_x in a South African context. The findings of this study indicate that the participants in the South Durban are exposed to high levels of NO_x that can be attributed mainly to traffic.

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.

Capturing the sensitivity of land-use regression models to short-term mobile monitoring campaigns using air pollution micro-sensors

The development of reliable measures of exposure to traffic-related air pollution is crucial for the evaluation of the health effects of transportation. Land-use regression (LUR) techniques have been widely used for the development of exposure surfaces, however these surfaces are often highly sensitive to the data collected. With the rise of inexpensive air pollution sensors paired with GPS devices, we witness the emergence of mobile data collection protocols. For the same urban area, can we achieve a 'universal' model irrespective of the number of locations and sampling visits? Can we trade the temporal representation of fixed-point sampling for a larger spatial extent afforded by mobile monitoring? This study highlights the challenges of short-term mobile sampling campaigns in terms of the resulting exposure surfaces. A mobile monitoring campaign was conducted in 2015 in Montreal; nitrogen dioxide (NO₂) levels at 1395 road segments were measured under repeated visits. We developed LUR models based on sub-segments, categorized in terms of the number of visits per road segment. We observe that LUR models were highly sensitive to the number of road segments and to the number of visits per road segment. The associated exposure surfaces were also highly dissimilar.

Individual exposure to nitrogen dioxide and adverse pregnancy outcomes in Kaunas study

Several epidemiological studies have found some evidence suggesting that exposure to air pollutants during pregnancy increases the risk of adverse birth outcomes. In this cohort study, we assessed individual maternal exposure to nitrogen dioxide (NO₂) during pregnancy and examined the association between the exposure and pregnancy outcomes, such as low birth weight (LBW), term low birth weight (TLBW), small for gestational age (SGA) and preterm birth (PB). 3292 women living in Kaunas city, Lithuania, data and their singleton newborns were included in the study. Exposure to NO₂ was assigned to each individual subject during pregnancy based on residential address using an AIRVIRO dispersion model and geographic information system (GIS). The results of the logistic regression analysis showed that LBW risk increased statistically significantly with increasing exposure to NO₂. Increased maternal exposure to NO₂ tended to increase the risk for TLBW, SGA and PB.

Particulate matter (PM10) exposure, birth and fetal-placental weight and umbilical arterial pH: results from a prospective study

OBJECTIVE

This prospective study aims to analyze the relation between particulate matter (PM₁₀) exposure during pregnancy and birth weight (BW), placental weight (PW) and umbilical artery PH (UAPH).

STUDY DESIGN

Population included 3614 women born in Italy, living in Lombardia Region, consecutively admitted to the Clinica Mangiagalli for an elective cesarean section from January 2004 through December 2006. Outdoor air quality data were provided by the Department of the Regional Environmental Protection Agency and obtained by a network of fixed monitoring stations representatively distributed in eight geographical areas.

RESULTS AND CONCLUSION

Birth weight was negatively associated with exposure to PM₁₀ concentration during the first trimester of pregnancy (mean change -22.2 g, 95%CI -8.7 to -35.7, p = 0.0013). Placental weight and umbilical artery PH were not associated with exposure to PM₁₀ concentration. Fetal weight was negatively associated with exposure to PM₁₀ concentration during the first trimester of pregnancy.

Infants' indoor and outdoor residential exposure to benzene and respiratory health in a Spanish cohort

Benzene exposure represents a potential risk for children's health. Apart from being a known carcinogen for humans (group 1 according to IARC), there is scientific evidence suggesting a relationship between benzene exposure and respiratory problems in children. But results are still inconclusive and inconsistent. This study aims to assess the determinants of exposure to indoor and outdoor residential benzene levels and its relationship with respiratory health in infants. Participants were 1-year-old infants (N = 352) from the INMA cohort from Valencia (Spain). Residential benzene exposure levels were measured inside and outside dwellings by means of passive samplers in a 15-day campaign. Persistent cough, low respiratory tract infections and wheezing during the first year of life, and covariates (dwelling traits, lifestyle factors and sociodemographic data) were obtained from parental questionnaires. Multiple Tobit regression and logistic regression models were performed to assess factors associated to residential exposure levels and health associations, respectively. Indoor levels were higher than outdoor ones (1.46 and 0.77 μg/m³, respectively; p < 0.01). A considerable percentage of dwellings, 42% and 21% indoors and outdoors respectively, surpassed the WHO guideline of 1.7 μg/m³ derived from a lifetime risk of leukemia above 1/100 000. Monitoring season, maternal country of birth and parental tobacco consumption were associated with residential benzene exposure (indoor and outdoors). Additionally, indoor levels were associated with mother's age and type of heating, and outdoor levels were linked with zone of residence and distance from industrial areas. After adjustment for confounding factors, no significant associations were found between residential benzene exposure levels and respiratory health in infants. Hence, our study did not support the hypothesis for the benzene exposure effect on respiratory health in children. Even so, it highlights a public health concern related to the personal exposure levels, since a considerable number of children surpassed the abovementioned WHO guideline for benzene exposure.

The Influence of Meteorological Factors and Atmospheric Pollutants on the Risk of Preterm Birth

Atmospheric pollutants and meteorological conditions are suspected to be causes of preterm birth. We aimed to characterize their possible association with the risk of preterm birth (defined as birth occurring before 37 completed gestational weeks). We pooled individual data from 13 birth cohorts in 11 European countries (71,493 births from the period 1994-2011, European Study of Cohorts for Air Pollution Effects (ESCAPE)). City-specific meteorological data from routine monitors were averaged over time windows spanning from 1 week to the whole pregnancy. Atmospheric pollution measurements (nitrogen oxides and particulate matter) were combined with data from permanent monitors and land-use data into seasonally adjusted land-use regression models. Preterm birth risks associated with air pollution and meteorological factors were estimated using adjusted discrete-time Cox models. The frequency of preterm birth was 5.0%. Preterm birth risk tended to increase with first-trimester average atmospheric pressure (odds ratio per 5-mbar increase = 1.06, 95% confidence interval: 1.01, 1.11), which could not be distinguished from altitude. There was also some evidence of an increase in preterm birth risk with first-trimester average temperature in the -5°C to 15°C range, with a plateau afterwards (spline coding, P = 0.08). No evidence of adverse association with atmospheric pollutants was observed. Our study lends support for an increase in preterm birth risk with atmospheric pressure.

Back-extrapolated and year-specific NO2 land use regression models for Great Britain - Do they yield different exposure assessment?

Robust methods to estimate historic population air pollution exposures are important tools for epidemiological studies evaluating long-term health effects. We developed land use regression (LUR) models for NO2 exposure in Great Britain for 1991 and explored whether the choice of year-specific or back-extrapolated LUR yields 1) similar LUR variables and model performance, and 2) similar national and regional address-level and small-area concentrations. We constructed two LUR models for 1991using NO2 concentrations from the diffusion tube monitoring network, one using 75% of all available measurement sites (that over-represent industrial areas), and the other using 75% of a subset of sites proportionate to population by region to study the effects of monitoring site selection bias. We compared, using the remaining (hold-out) 25% of monitoring sites, the performance of the two 1991 models with back-extrapolation of a previously published 2009 model, developed using NO2 concentrations from automatic chemiluminescence monitoring sites and predictor variables from 2006/2007. The 2009 model was back-extrapolated to 1991 using the same predictors (1990 & 1995) used to develop 1991 models. The 1991 models included industrial land use variables, not present for 2009. The hold-out performance of 1991 models (mean-squared-error-based-R(2): 0.62-0.64) was up to 8% higher and ~1μg/m(3) lower in root mean squared error than the back-extrapolated 2009 model, with best performance from the subset of sites representing population exposures. Year-specific and back-extrapolated exposures for residential addresses (n=1.338,399) and small areas (n=10.518) were very highly linearly correlated for Great Britain (r>0.83). This study suggests that year-specific model for 1991 and back-extrapolation of the 2009 LUR yield similar exposure assessment.