A cohort study of traffic-related air pollution impacts on birth outcomes

Identifying windows of susceptibility for maternal exposure to ambient air pollution and preterm birth

Maternal exposure to ambient air pollution has been associated with preterm birth (PTB), however, entire pregnancy or trimester-specific associations were generally reported, which may not sufficiently identify windows of susceptibility. Using birth registry data from Guangzhou, a megacity of southern China (population ~14.5 million), including 469,975 singleton live births between January 2015 and July 2017, we assessed the association between weekly air pollution exposure and PTB in a retrospective cohort study. Daily average concentrations of PM_2.5, PM₁₀, NO₂, SO₂, and O₃ from 11 monitoring stations were used to estimate district-specific exposures for each participant based on their district residency during pregnancy. Distributed lag models (DLMs) incorporating Cox proportional hazard models were applied to estimate the association between weekly maternal exposure to air pollutant and PTB risk (as a time-to-event outcome), after controlling for temperature, seasonality, and individual-level covariates. We also considered moderate PTB (32-36 gestational weeks) and very PTB (28-31 gestational weeks) as outcomes of interest. Hazard ratios (HRs) and 95% confidential intervals (95% CIs) were calculated for an interquartile range (IQR) increase in air pollutants during the study period. An IQR increase in PM_2.5 exposure during the 20th to 28th gestational weeks (27.0 μg/m³) was significantly associated with PTB risk, with the strongest effect in the 25th week (HR = 1.034, 95% CI:1.010-1.059). The significant exposure windows were the 19th-28th weeks for PM₁₀, the 18th-31st weeks for NO₂, and the 23rd-31st weeks for O₃, respectively. The strongest associations were observed in the 25th week for PM₁₀ (IQR = 37.0 μg/m³; HR = 1.048, 95% CI:1.034-1.062), the 26th week for NO₂ (IQR = 29.0 μg/m³; HR = 1.060, 95% CI:1.028-1.094), and in the 28th week for O₃ (IQR = 90.0 μg/m³; HR = 1.063, 95% CI:1.046-1.081). Similar patterns were observed for moderate PTB (32-36 gestational weeks) and very PTB (28-31 gestational weeks) for PM_2.5, PM₁₀, NO₂ exposure, but the effects were greater for very PTB. We did not observe any association between pregnancy SO₂ exposure and the risk of PTB. Our results suggest that middle to late pregnancy is the most susceptible air pollution exposure window for air pollution and PTB among women in Guangzhou, China.

Investigation of association between environmental and socioeconomic factors and preterm birth in California

BACKGROUND

Preterm birth (PTB),2 defined as birth at gestational age <37 weeks, is a major public health concern. Infants born prematurely, comprising of about 10% of the US newborns, have elevated risks of neonatal mortality and a wide array of health problems. Although numerous clinical, genetic, environmental and socioeconomic factors have been implicated in PTB, very few studies investigate the impacts of multiple pollutants and social factors on PTB using large scale datasets.

OBJECTIVES

To evaluate association between environmental and socioeconomic factors and PTB in California.

METHODS

We linked the birth cohort file maintained by the California Office of Statewide Health Planning and Development from 2009 to 2012 years across 1.8 million births and the CalEnviroScreen 3.0 dataset from California Communities Environmental Health Screening Tool at the census tract level for 56 California counties. CalEnviroScreen contains 7 exposure and 5 environmental effects variables that constitute the Pollution Burden variable, and 5 socioeconomic variables. We evaluated relationships between environmental exposures and the risk of PTB using hierarchical clustering analyses and GIS-based visualization. We also used logistic regression to evaluate the relationship between specific pollutant and exposure indicators and PTB, accounted for socio-demographic determinants such as maternal race/ethnicity, maternal age, maternal education and payment of delivery costs.

RESULTS

There exists geographic variability in PTB for groups of counties with similar environmental and social exposure profiles. We found an association between Pollution Burden, particulate matter ≤2.5 μm (PM2.5), and Drinking Water Scores and PTB (adjusted odds ratios were 1.03 (95% Confidence Interval (CI): 1.01, 1.04), 1.03 (95% CI: 1.02,1.04), and 1.04 (95% CI: 1.03,1.05), respectively). Additional findings suggest that certain drinking water contaminants such as arsenic and nitrate are associated with PTB in California.

CONCLUSIONS

CalEnviroScreen data combined with birth records offer great opportunity for revealing novel exposures and evaluating cumulative exposures related to PTB by providing useful environmental and social information. Certain drinking water contaminants such as arsenic and nitrate are potentially associated with PTB in California and should be investigated further. Small association signals may involve sizeable population impacts.

Associations between maternal residential proximity to air emissions from industrial facilities and low birth weight in Texas, USA

BACKGROUND

Most previous studies examining associations between maternal exposures to air pollutants during pregnancy and low birth weight (LBW) in offspring focused on criteria air pollutants (PM_2.5, PM₁₀, O₃, NO₂, SO₂, CO, and Pb). The relationship between non-criteria air pollutants and LBW is understudied and requires greater coverage.

OBJECTIVES

This study investigated associations between maternal residential exposure to industrial air pollutants during pregnancy and LBW in offspring.

METHODS

This study used a case-control study design that included 94,106 term LBW cases and 376,424 controls. It covered 78 air pollutants common to both the Toxics Release Inventory (TRI) and ground air quality monitoring databases in Texas during 1996-2008. A modified version of the Emission Weighted Proximity Model (EWPM), calibrated with ground monitoring data, was used to estimate maternal residential exposure to industrial air pollutants during pregnancy. Binary logistic regression analyses were performed to calculate odds ratios (ORs) reflecting the associations of maternal exposure to industrial air pollutants and LBW in offspring, adjusted for child's sex, gestational weeks, maternal age, education, race/ethnicity, marital status, prenatal care, tobacco use during pregnancy, public health region of maternal residence, and year of birth. In addition, the Bonferroni correction for multiple comparisons was applied to the results of logistic regression analysis.

RESULTS

Relative to the non-exposed reference group, maternal residential exposure to benzene (adjusted odds ratio (aOR) 1.06, 95% confidence interval (CI) 1.04, 1.08), benzo(g,h,i)perylene (aOR 1.04, 95% CI 1.02, 1.07), cumene (aOR 1.05, 95% CI 1.03, 1.07), cyclohexane (aOR 1.04, 95% CI 1.02, 1.07), dichloromethane (aOR 1.04, 95% CI 1.03, 1.07), ethylbenzene (aOR 1.05, 95% CI 1.03, 1.06), ethylene (aOR 1.06, 95% CI 1.03, 1.09), mercury (aOR 1.04, 95% CI 1.02, 1.07), naphthalene (aOR 1.03, 95% CI 1.01, 1.05), n-hexane (aOR 1.06, 95% CI 1.04, 1.08), propylene (aOR 1.06, 95% CI 1.03, 1.10), styrene (aOR 1.06, 95% CI 1.04, 1.08), toluene (aOR 1.05, 95% CI 1.03, 1.07), and zinc (fume or dust) (aOR 1.10, 95% CI 1.06, 1.13) was found to have significantly higher odds of LBW in offspring. When the estimated exposures were categorized into four different groups (zero, low, medium, and high) in the analysis, eleven of the fourteen air pollutants, with the exception of benzo(g,h,i)perylene, ethylene, and propylene, remained as significant risk factors.

CONCLUSIONS

Results indicate that maternal residential proximity to industrial facilities emitting any of the fourteen pollutants identified by this study during pregnancy may be associated with LBW in offspring. With the exception of benzene, ethylbenzene, toluene, and zinc, the rest of the fourteen air pollutants are identified as LBW risk factors for the first time by this study. Further epidemiological, biological, and toxicological studies are suggested to verify the findings from this study.

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.

Industrial air pollution and low birth weight: a case-control study in Texas, USA

Many studies have investigated associations between maternal residential exposures to air pollutants and low birth weight (LBW) in offspring. However, most studies focused on the criteria air pollutants (PM_2.5, PM₁₀, O₃, NO₂, SO₂, CO, and Pb), and only a few studies examined the potential impact of other air pollutants on LBW. This study investigated associations between maternal residential exposure to industrial air emissions of 449 toxics release inventory (TRI) chemicals and LBW in offspring using a case-control study design based on a large dataset consisting of 94,106 LBW cases and 376,424 controls in Texas from 1996 to 2008. Maternal residential exposure to chemicals was estimated using a modified version of the emission-weighted proximity model (EWPM). The model takes into account reported quantities of annual air emission from industrial facilities and the distances between the locations of industrial facilities and maternal residence locations. Binary logistic regression was used to compute odds ratios measuring the association between maternal exposure to different TRI chemicals and LBW in offspring. Odds ratios were adjusted for child's sex, birth year, gestational length, maternal age, education, race/ethnicity, and public health region of maternal residence. Among the ten chemicals selected for a complete analysis, maternal residential exposures to five TRI chemicals were positively associated with LBW in offspring. These five chemicals include acetamide (adjusted odds ratio [aOR] 2.29, 95% confidence interval [CI] 1.24, 4.20), p-phenylenediamine (aOR 1.63, 95% CI 1.18, 2.25), 2,2-dichloro-1,1,1-trifluoroethane (aOR 1.41, 95% CI 1.20, 1.66), tributyltin methacrylate (aOR 1.20, 95% CI 1.06, 1.36), and 1,1,1-trichloroethane (aOR 1.11, 95% CI 1.03, 1.20). These findings suggest that maternal residential proximity to industrial air emissions of some chemicals during pregnancy may be associated with LBW in offspring.

Spatial modeling of daily concentrations of ground-level ozone in Montreal, Canada: A comparison of geostatistical approaches

Ground-level ozone (O₃) is a powerful oxidizing agent and a harmful pollutant affecting human health, forests and crops. Estimating O₃ exposure is a challenge because it exhibits complex spatiotemporal patterns. The aim in this study was to provide high-resolution maps (100 × 100 m) of O₃ for the metropolitan area of Montreal, Canada. We assessed the kriging with external drift (KED) model to estimate O₃ concentration by synoptic weather classes for 2010. We compared these results with ordinary kriging (OK), and a simple average of 12 monitoring stations. We also compared the estimates obtained for the 2010 summer with those from a Bayesian maximum entropy (BME) model reported in the literature (Adam-Poupart et al., 2014). The KED model with road and vegetation density as covariates showed good performance for all six synoptic classes (daily R² estimates ranging from 0.77 to 0.92 and RMSE from 2.79 to 3.37 ppb). For the summer of 2010, the model using KED demonstrated the best results (R² = 0.92; RMSE = 3.14 ppb), followed by the OK model (R² = 0.85, RMSE = 4 ppb). Our results showed that errors appear to be substantially reduced with the KED model. This may increase our capacity of linking O₃ levels to health problems by means of improved assessments of ambient exposures. However, future work integrating the temporal dependency in the data is needed to not overstate the performance of the KED model.

Bringing health into transportation and land use scenario planning: Creating a National Public Health Assessment Model (N-PHAM)

There is mounting evidence linking land development and transportation investments to physical activity with resulting implications for chronic disease prevention. Links between the physical environment and health have traditionally focused on harmful exposures such as air pollution, noise, and traffic injury. Given limited funds and competition for how and where investments are made, there is a need to prioritize and target resources to maximize health benefits that can include activity related chronic disease prevention. The ability to apply this evidence to decision making has been limited by the complexity and inconsistency of research methods, and lack of a direct connection with the planning contexts in which decisions are made. Scenario planning tools provide a method to apply evidence with spatial planning decisions at a range of geographic scales. The US Environmental Protection Agency commissioned the development of a National Public Health Assessment Model (N-PHAM). This project utilized built and natural environment data at the block-group level and large population surveys to model the relationships of the environment with several health outcomes for a range of age and income groups. N-PHAM is the first health assessment tool that can connect to multiple existing scenario planning platforms utilizing nationally available data and can be consistently applied nationally. Such tools can empower communities to choose investments that have the greatest potential to improve public health and quality of life, reduce health care costs, and address environmental justice related disparities.

Residential mobility of pregnant women and implications for assessment of spatially-varying environmental exposures

Health studies on spatially-varying exposures (e.g., air pollution) during pregnancy often estimate exposure using residence at birth, disregarding residential mobility. We investigated moving patterns in pregnant women (n = 10,116) in linked cohorts focused on Connecticut and Massachusetts, U.S., 1988-2008. Moving patterns were assessed by race/ethnicity, age, marital status, education, working status, population density, parity, income, and season of birth. In this population, 11.6% of women moved during pregnancy. Movers were more likely to be younger, unmarried, and living in urban areas with no previous children. Among movers, multiple moves were more likely for racial/ethnic minority, younger, less educated, unmarried, and lower income women. Most moves occurred later in pregnancy, with 87.4% of first moves in the second or third trimester, although not all cohort subjects enrolled in the first few weeks of pregnancy. Distance between first and second residence had a median value of 5.2 km (interquartile range 11.3 km, average 57.8 km, range 0.0-4277 km). Women moving larger distances were more likely to be white, older, married, and work during pregnancy. Findings indicate that residential mobility may impact studies of spatially-varying exposure during pregnancy and health and that subpopulations vary in probability of moving, and timing and distance of moves.

Residential mobility during pregnancy in Urban Gansu, China

BACKGROUND

Studies on environmental exposures during pregnancy commonly use maternal residence at time of delivery, which may result in exposure misclassification and biased estimates of exposure and disease association. Studies on residential mobility during pregnancy are needed in various populations to aid studies of the environmental exposure and birth outcomes. However, there is still a lack of studies investigating residential mobility patterns in Asian populations.

METHODS

We analyzed data from 10,542 pregnant women enrolled in a birth cohort study in Lanzhou, China (2010-2012), a major industrial city. Multivariate logistic regression was used to evaluate residential mobility patterns in relation to maternal complications and birth outcomes.

RESULTS

Of the participants, 546 (5.2%) moved during pregnancy; among those who moved, 40.5%, 34.8%, and 24.7% moved during the first, second, and third trimester, respectively. Most movers (97.3%) moved once with a mean distance of 3.75 km (range: 1-109 km). More than half (66.1%) of the movers moved within 3 km, 13.9% moved 3-10 km, and 20.0% moved > 10 km. Pregnant women who were > 30 years or multiparous, or who had maternal complications were less likely to have moved during pregnancy. In addition, movers were less likely to deliver infants with birth defects, preterm births, and low birth weight.

CONCLUSIONS

Residential mobility was significantly associated with several maternal characteristics and complications during pregnancy. The study also showed a lower likelihood of adverse birth outcomes among movers than non-movers, suggesting that moving might be related to reduce exposure to environmental hazards. These results confirm the hypothesis that residential mobility may be important with respect to exposure misclassification and that this misclassification may vary by subpopulations.

Using a Clustering Approach to Investigate Socio-Environmental Inequality in Preterm Birth-A Study Conducted at Fine Spatial Scale in Paris (France)

Background & Objectives: Today, to support public policies aiming to tackle environmental and health inequality, identification and monitoring of the spatial pattern of adverse birth outcomes are crucial. Spatial identification of the more vulnerable population to air pollution may orient health interventions. In this context, the objective of this study is to investigate the geographical distribution of the risk of preterm birth (PTB, gestational age ≤36 weeks) at the census block level in in city of Paris, France. We also aimed to assess the implication of neighborhood characteristics including air pollution and socio-economic deprivation. Material & Methods: Newborn health data are available from the first birth certificate registered by the Maternal and Child Care department of Paris. All PTB from January 2008 to December 2011 were geocoded at the mother residential census block. Each census block was assigned a socioeconomic deprivation level and annual average ambient concentrations of NO₂. A spatial clustering approach was used to investigate the spatial distribution of PTB. Results: Our results highlight that PTB is non-randomly spatially distributed, with a cluster of high risk in the northeastern area of Paris (RR = 1.15; p = 0.06). After adjustment for socio-economic deprivation and NO₂ concentrations, this cluster becomes not statistically significant or shifts suggesting that these characteristics explain the spatial distribution of PTB; further, their combination shows an interaction in comparison with SES or NO₂ levels alone. Conclusions: Our results may inform the decision makers about the areas where public health efforts should be strengthened to tackle the risk of PTB and to choose the most appropriate and specific community-oriented health interventions.

Comparison of land use regression models for NO2 based on routine and campaign monitoring data from an urban area of Japan

BACKGROUND

Typically, land use regression (LUR) models have been developed using campaign monitoring data rather than routine monitoring data. However, the latter have advantages such as low cost and long-term coverage. Based on the idea that LUR models representing regional differences in air pollution and regional road structures are optimal, the objective of this study was to evaluate the validity of LUR models for nitrogen dioxide (NO₂) based on routine and campaign monitoring data obtained from an urban area.

METHOD

We selected the city of Suita in Osaka (Japan). We built a model based on routine monitoring data obtained from all sites (routine-LUR-All), and a model based on campaign monitoring data (campaign-LUR) within the city. Models based on routine monitoring data obtained from background sites (routine-LUR-BS) and based on data obtained from roadside sites (routine-LUR-RS) were also built. The routine LUR models were based on monitoring networks across two prefectures (i.e., Osaka and Hyogo prefectures). We calculated the predictability of the each model. We then compared the predicted NO₂ concentrations from each model with measured annual average NO₂ concentrations from evaluation sites.

RESULTS

The routine-LUR-All and routine-LUR-BS models both predicted NO₂ concentrations well: adjusted R²=0.68 and 0.76, respectively, and root mean square error=3.4 and 2.1ppb, respectively. The predictions from the routine-LUR-All model were highly correlated with the measured NO₂ concentrations at evaluation sites. Although the predicted NO₂ concentrations from each model were correlated, the LUR models based on routine networks, and particularly those based on all monitoring sites, provided better visual representations of the local road conditions in the city.

CONCLUSION

The present study demonstrated that LUR models based on routine data could estimate local traffic-related air pollution in an urban area. The importance and usefulness of data from routine monitoring networks should be acknowledged.

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.

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.

Air pollutants and early origins of respiratory diseases

Air pollution is a global health threat and causes millions of human deaths annually. The late onset of respiratory diseases in children and adults due to prenatal or perinatal exposure to air pollutants is emerging as a critical concern in human health. Pregnancy and fetal development stages are highly susceptible to environmental exposure and tend to develop a long-term impact in later life. In this review, we briefly glance at the direct impact of outdoor and indoor air pollutants on lung diseases and pregnancy disorders. We further focus on lung complications in later life with early exposure to air pollutants. Epidemiological evidence is provided to show the association of prenatal or perinatal exposure to air pollutants with various adverse birth outcomes, such as preterm birth, lower birth weight, and lung developmental defects, which further associate with respiratory diseases and reduced lung function in children and adults. Mechanistic evidence is also discussed to support that air pollutants impact various cellular and molecular targets at early life, which link to the pathogenesis and altered immune responses related to abnormal respiratory functions and lung diseases in later life.

Residential proximity to major roadways and traffic in relation to outcomes of in vitro fertilization

BACKGROUND

Emerging data from animal and human studies suggest that traffic-related air pollution adversely affects early pregnancy outcomes; however evidence is limited.

OBJECTIVE

We examined whether residential proximity to major roadways and traffic, as proxies for traffic-related air pollution, are associated with in vitro fertilization (IVF) outcomes.

METHODS

This analysis included 423 women enrolled in the Environment and Reproductive Health (EARTH) Study, a prospective cohort study, who underwent 726 IVF cycles (2004-2017). Using geocoded residential addresses collected at study entry, we calculated the distance to nearest major roadway and the traffic density within a 100 m radius. IVF outcomes were abstracted from electronic medical records. We used multivariable generalized linear mixed models to evaluate the associations between residential proximity to major roadways and traffic density and IVF outcomes adjusting for maternal age, body mass index, race, education level, smoking status, and census tract median income.

RESULTS

Closer residential proximity to major roadways was statistically significantly associated with lower probability of implantation and live birth following IVF. The adjusted percentage of IVF cycles resulting in live birth for women living ≥400 m from a major roadway was 46% (95% CI 36, 56%) compared to 33% (95% CI 26, 40%) for women living <50 m (p-for-comparison, 0.04). Of the intermediate outcomes, there were suggestive associations between living closer to major roadways and slightly higher estradiol trigger concentrations (p-trend = 0.16) and lower endometrial thickness (p-trend = 0.06). Near-residence traffic density was not associated with outcomes of IVF.

CONCLUSION

Closer residential proximity to major roadways was related to reduced likelihood of live birth following IVF.

Is ambient air pollution associated with onset of sudden infant death syndrome: a case-crossover study in the UK

OBJECTIVES

Air pollution has been associated with increased mortality and morbidity in several studies with indications that its effect could be more severe in children. This study examined the relationship between short-term variations in criteria air pollutants and occurrence of sudden infant death syndrome (SIDS).

DESIGN

We used a case-crossover study design which is widely applied in air pollution studies and particularly useful for estimating the risk of a rare acute outcome associated with short-term exposure.

SETTING

The study used data from the West Midlands region in the UK.

PARTICIPANTS

We obtained daily time series data on SIDS mortality (ICD-9: 798.0 or ICD-10: R95) for the period 1996-2006 with a total of 211 SIDS events.

PRIMARY OUTCOME MEASURES

Daily counts of SIDS events.

RESULTS

For an IQR increase in previous day pollutant concentration, the percentage increases (95% CI) in SIDS were 16 (6 to 27) for PM₁₀, 1 (-7 to 10) for SO₂, 5 (-4 to 14) for CO, -17 (-27 to -6) for O₃, 16 (2 to 31) for NO₂ and 2 (-3 to 8) for NO after controlling for average temperature and national holidays. PM₁₀ and NO₂ showed relatively consistent association which persisted across different lag structures and after adjusting for copollutants.

CONCLUSIONS

The results indicated ambient air pollutants, particularly PM₁₀ and NO₂, may show an association with increased SIDS mortality. Thus, future studies are recommended to understand possible mechanistic explanations on the role of air pollution on SIDS incidence and the ways in which we might reduce pollution exposure among infants.

Integrating travel behavior with land use regression to estimate dynamic air pollution exposure in Hong Kong

BACKGROUND

Epidemiological studies typically use subjects' residential address to estimate individuals' air pollution exposure. However, in reality this exposure is rarely static as people move from home to work/study locations and commute during the day. Integrating mobility and time-activity data may reduce errors and biases, thereby improving estimates of health risks.

OBJECTIVES

To incorporate land use regression with movement and building infiltration data to estimate time-weighted air pollution exposures stratified by age, sex, and employment status for population subgroups in Hong Kong.

METHODS

A large population-representative survey (N = 89,385) was used to characterize travel behavior, and derive time-activity pattern for each subject. Infiltration factors calculated from indoor/outdoor monitoring campaigns were used to estimate micro-environmental concentrations. We evaluated dynamic and static (residential location-only) exposures in a staged modeling approach to quantify effects of each component.

RESULTS

Higher levels of exposures were found for working adults and students due to increased mobility. Compared to subjects aged 65 or older, exposures to PM_2.5, BC, and NO₂ were 13%, 39% and 14% higher, respectively for subjects aged below 18, and 3%, 18% and 11% higher, respectively for working adults. Exposures of females were approximately 4% lower than those of males. Dynamic exposures were around 20% lower than ambient exposures at residential addresses.

CONCLUSIONS

The incorporation of infiltration and mobility increased heterogeneity in population exposure and allowed identification of highly exposed groups. The use of ambient concentrations may lead to exposure misclassification which introduces bias, resulting in lower effect estimates than 'true' exposures.

Urban Green Space and Its Impact on Human Health

Background: Over half of the world's population now lives in urban areas, and this proportion is expected to increase. While there have been numerous reviews of empirical studies on the link between nature and human health, very few have focused on the urban context, and most have examined almost exclusively cross-sectional research. This review is a first step toward assessing the possibility of causal relationships between nature and health in urban settings. Methods: Through systematic review of published literature, we explored the association between urban green space and human health. Results: We found consistent negative association between urban green space exposure and mortality, heart rate, and violence, and positive association with attention, mood, and physical activity. Results were mixed, or no association was found, in studies of urban green space exposure and general health, weight status, depression, and stress (via cortisol concentration). The number of studies was too low to generalize about birth outcomes, blood pressure, heart rate variability, cancer, diabetes, or respiratory symptoms. Conclusions: More studies using rigorous study design are needed to make generalizations, and meta-analyses, of these and other health outcomes possible. These findings may assist urban managers, organizations, and communities in their efforts to increase new or preserve existing green space.

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.

Spatiotemporal prediction of daily ambient ozone levels across China using random forest for human exposure assessment

In China, ozone pollution shows an increasing trend and becomes the primary air pollutant in warm seasons. Leveraging the air quality monitoring network, a random forest model is developed to predict the daily maximum 8-h average ozone concentrations ([O₃]_MDA8) across China in 2015 for human exposure assessment. This model captures the observed spatiotemporal variations of [O₃]_MDA8 by using the data of meteorology, elevation, and recent-year emission inventories (cross-validation R² = 0.69 and RMSE = 26 μg/m³). Compared with chemical transport models that require a plenty of variables and expensive computation, the random forest model shows comparable or higher predictive performance based on only a handful of readily-available variables at much lower computational cost. The nationwide population-weighted [O₃]_MDA8 is predicted to be 84 ± 23 μg/m³ annually, with the highest seasonal mean in the summer (103 ± 8 μg/m³). The summer [O₃]_MDA8 is predicted to be the highest in North China (125 ± 17 μg/m³). Approximately 58% of the population lives in areas with more than 100 nonattainment days ([O₃]_MDA8>100 μg/m³), and 12% of the population are exposed to [O₃]_MDA8>160 μg/m³ (WHO Interim Target 1) for more than 30 days. As the most populous zones in China, the Beijing-Tianjin Metro, Yangtze River Delta, Pearl River Delta, and Sichuan Basin are predicted to be at 154, 141, 124, and 98 nonattainment days, respectively. Effective controls of O₃ pollution are urgently needed for the highly-populated zones, especially the Beijing-Tianjin Metro with seasonal [O₃]_MDA8 of 140 ± 29 μg/m³ in summer. To the best of the authors' knowledge, this study is the first statistical modeling work of ambient O₃ for China at the national level. This timely and extensively validated [O₃]_MDA8 dataset is valuable for refining epidemiological analyses on O₃ pollution in China.

Exposures to fine particulate matter (PM2.5) and birthweight in a rural-urban, mother-child cohort in Tamil Nadu, India

BACKGROUND

Exposure to PM_2.5 (fine particulate matter <less than 2.5µm in aerodynamic diameter) related to ambient and household air pollution has been associated with low birthweight. Few of these studies, however, have been conducted in high exposure settings that are commonly encountered in low and middle income countries (LMICs).

OBJECTIVES

We examined whether PM_2.5 exposures during pregnancy were associated with birthweight in an integrated rural-urban, mother-child cohort in the state of Tamil Nadu, India.

METHODS

We recruited 1285 pregnant women in the first trimester of pregnancy from primary health care centers and urban health posts and followed them until birth to collect antenatal care data and birthweight. We estimated pregnancy period PM _2.5 exposures through direct serial measurements of 24-h household PM_2.5 concentrations, performed across each trimester. Mothers also completed detailed questionnaires to provide data on covariates related to household, socio-economic, demographic and maternal health characteristics. The association between PM_2.5 exposures and birth weight was assessed using linear and logistic regression models that controlled for potential confounders.

RESULTS

A 10-μg/m³ increase in pregnancy period PM_2.5 exposures was associated with a 4g (95% CI: 1.08g, 6.76g) decrease in birthweight and 2% increase in prevalence of low birthweight [odds ratio(OR) = 1.02; 95%CI:1.005,1.041] after adjusting for gestational age, infant sex, maternal BMI, maternal age, history of a previous low birth weight child, birth order and season of conception.

CONCLUSIONS

The study provides some of the first quantitative effects estimates for linking rural-urban PM_2.5 exposures and birthweight in India, adding important evidence for this association from high exposure settings in LMICs, that also experience dual health burdens from ambient and household air pollution. Study results also point to the need for considering maternal PM_2.5 exposures alongside other risk factors for low birthweight in India.

Temporal trends in air pollution exposure inequality in Massachusetts

Mounting evidence over the past several decades has demonstrated inequitable distribution of pollutants of ambient origin between sociodemographic groups in the United States. Most environmental inequality studies to date are cross-sectional and used proximity-based methods rather than modeled air pollution concentrations, limiting the ability to examine trends over time or the factors that drive exposure inequalities. In this paper, we use 1km² modeled PM_2.5 and NO₂ concentrations in Massachusetts over an 8-year period and Census demographic data to quantify inequality between sociodemographic groups and to develop a more nuanced understanding of the drivers and trends in longitudinal air pollution inequality. Annual-average population-weighted PM_2.5 and NO₂ concentrations were highest for urban non-Hispanic black populations (11.8µg/m³ in 2003 and 8.4µg/m³ in 2010, vs. 11.3µg/m³ and 8.1µg/m³ for urban non-Hispanic whites) and urban Hispanic populations (15.9 ppb in 2005 and 13.0 ppb in 2010, vs. 13.0 ppb and 10.2 ppb for urban non-Hispanic whites), respectively. While population groups experienced similar absolute decreases in exposure over time, disparities in population-weighted concentrations increased over time when quantified by the Atkinson Index, a relative inequality measure. Exposure inequalities were approximately one order of magnitude greater for NO₂ compared to PM_2.5, were more pronounced in urban compared to rural geographies, and between racial/ethnic groups compared to income and educational attainment groups. Our results also revealed similar longitudinal PM_2.5 and NO₂ inequality trends using Census 2000 and Census 2010 data, indicating that spatio-temporal shifts in air pollution may best explain observed trends in inequality. These findings enhance our understanding of factors that contribute to persistent inequalities and underscore the importance of targeted exposure reduction strategies aimed at vulnerable populations and neighborhoods.

Maternal Exposure to PM2.5 during Pregnancy Induces Impaired Development of Cerebral Cortex in Mice Offspring

Air pollution is a serious environmental health problem closely related to the occurrence of central nervous system diseases. Exposure to particulate matter with an aerodynamic diameter less than or equal to 2.5 µm (PM_2.5) during pregnancy may affect the growth and development of infants. The present study was to investigate the effects of maternal exposure to PM_2.5 during pregnancy on brain development in mice offspring. Pregnant mice were randomly divided into experimental groups of low-, medium-, or high-dosages of PM_2.5, a mock-treated group which was treated with the same amount of phosphate buffer solution (PBS), and acontrol group which was untreated. The ethology of offspring mice on postnatal days 1, 7, 14, 21, and 30, along with neuronal development and apoptosis in the cerebral cortex were investigated. Compared with the control, neuronal mitochondrial cristae fracture, changed autophagy characteristics, significantly increased terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) positive cell rate, and mRNA levels of apoptosis-related caspase-8 and caspase-9 were found in cerebral cortex of mice offspring from the treatment groups, with mRNA levels of Bcl-2 and ratio of Bcl-2 to Bax decreased. Treatment groups also demonstrated enhanced protein expressions of apoptosis-related cleaved caspase-3, cleaved caspase-8 and cleaved caspase-9, along with declined proliferating cell nuclear antigen (PCNA), Bcl-2, and ratio of Bcl-2 to Bax. Open field experiments and tail suspension experiments showed that exposure to high dosage of PM_2.5 resulted in decreased spontaneous activities but increased static accumulation time in mice offspring, indicating anxiety, depression, and social behavioral changes. Our results suggested that maternal exposure to PM_2.5 during pregnancy might interfere with cerebral cortex development in mice offspring by affecting cell apoptosis.

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.

Evaluation of Traffic Density Parameters as an Indicator of Vehicle Emission-Related Near-Road Air Pollution: A Case Study with NEXUS Measurement Data on Black Carbon

An important factor in evaluating health risk of near-road air pollution is to accurately estimate the traffic-related vehicle emission of air pollutants. Inclusion of traffic parameters such as road length/area, distance to roads, and traffic volume/intensity into models such as land use regression (LUR) models has improved exposure estimation. To better understand the relationship between vehicle emissions and near-road air pollution, we evaluated three traffic density-based indices: Major-Road Density (MRD), All-Traffic Density (ATD) and Heavy-Traffic Density (HTD) which represent the proportions of major roads, major road with annual average daily traffic (AADT), and major road with commercial annual average daily traffic (CAADT) in a buffered area, respectively. We evaluated the potential of these indices as vehicle emission-specific near-road air pollutant indicators by analyzing their correlation with black carbon (BC), a marker for mobile source air pollutants, using measurement data obtained from the Near-road Exposures and Effects of Urban Air Pollutants Study (NEXUS). The average BC concentrations during a day showed variations consistent with changes in traffic volume which were classified into high, medium, and low for the morning rush hours, the evening rush hours, and the rest of the day, respectively. The average correlation coefficients between BC concentrations and MRD, ATD, and HTD, were 0.26, 0.18, and 0.48, respectively, as compared with −0.31 and 0.25 for two commonly used traffic indicators: nearest distance to a major road and total length of the major road. HTD, which includes only heavy-duty diesel vehicles in its traffic count, gives statistically significant correlation coefficients for all near-road distances (50, 100, 150, 200, 250, and 300 m) that were analyzed. Generalized linear model (GLM) analyses show that season, traffic volume, HTD, and distance from major roads are highly related to BC measurements. Our analyses indicate that traffic density parameters may be more specific indicators of near-road BC concentrations for health risk studies. HTD is the best index for reflecting near-road BC concentrations which are influenced mainly by the emissions of heavy-duty diesel engines.

Associations between socio-demographic characteristics and chemical concentrations contributing to cumulative exposures in the United States

Association rule mining (ARM) has been widely used to identify associations between various entities in many fields. Although some studies have utilized it to analyze the relationship between chemicals and human health effects, fewer have used this technique to identify and quantify associations between environmental and social stressors. Socio-demographic variables were generated based on U.S. Census tract-level income, race/ethnicity population percentage, education level, and age information from the 2010-2014, 5-Year Summary files in the American Community Survey (ACS) database, and chemical variables were generated by utilizing the 2011 National-Scale Air Toxics Assessment (NATA) census tract-level air pollutant exposure concentration data. Six mobile- and industrial-source pollutants were chosen for analysis, including acetaldehyde, benzene, cyanide, particulate matter components of diesel engine emissions (namely, diesel PM), toluene, and 1,3-butadiene. ARM was then applied to quantify and visualize the associations between the chemical and socio-demographic variables. Census tracts with a high percentage of racial/ethnic minorities and populations with low income tended to have higher estimated chemical exposure concentrations (fourth quartile), especially for diesel PM, 1,3-butadiene, and toluene. In contrast, census tracts with an average population age of 40-50 years, a low percentage of racial/ethnic minorities, and moderate-income levels were more likely to have lower estimated chemical exposure concentrations (first quartile). Unsupervised data mining methods can be used to evaluate potential associations between environmental inequalities and social disparities, while providing support in public health decision-making contexts.

Association between exposure to particulate matter during pregnancy and birthweight: a systematic review and a meta-analysis of birth cohort studies

Studies of the associations between maternal exposure to particulate matter (PM) and risk of adverse effects on fetal growth are inconsistent and inconclusive. This question can be well answered by carefully designed birth cohort studies; however, so far the evidence from such studies has not come to the same conclusion. We sought to evaluate the association between maternal exposures to PM and low birthweight (LBW) enrolling 14 studies from 11 centers, and to explore the influence of trimester and exposure assessment methods on between-center heterogeneity in this association. Data were derived from PubMed, Embase, Google Scholar, CNKI, and WanFang database, references from relevant articles, and results from published studies until March 2017. Using a random-effects meta-analysis, we combined the coefficient and odds ratios (OR) of individual studies conducted among 14 birth cohort studies. Random-effect meta-analysis results suggested that a 17% and 6% increase in risk of LBW was relevant to a 10 mg/m3 rise in PM2.5 and PM10 exposure concentrations at the 3rd trimester (pooled odds ratios (OR), 1.17 and 1.06; 95% confidence interval (CI), 0.94-1.46 and 0.97-1.15, respectively), but the null value was included in our 95% CI. Our results showed that exposure to PM2.5 and PM10 during pregnancy has a positive relevance to LBW based on birth cohort studies. However, neither reached formal statistical significance. Negative impacts on outcomes of birth is implied by maternal exposure to PM. Further mechanistic researches are needed to explain the connection between PM pollution and LBW.

Maternal ambient air pollution, preterm birth and markers of fetal growth in Rhode Island: results of a hospital-based linkage study

BACKGROUND

Maternal exposure to ambient air pollution has been associated with higher risk of preterm birth and reduced fetal growth, but heterogeneity among prior studies suggests that additional studies are needed in diverse populations and settings. We examined the associations between maternal ambient air pollution levels, risk of preterm birth and markers of fetal growth in an urban population with relatively low exposure to air pollution.

METHODS

We linked 61 640 mother-infant pairs who delivered at a single hospital in Providence, Rhode Island, from 2002 to 2012 to birth certificate and hospital discharge data. We used spatial-temporal models and stationary monitors to estimate exposure to fine particulate matter (PM_2.5) and black carbon (BC) during pregnancy. Using generalised linear models, we evaluated the association between pollutant levels, risk of preterm birth and markers of fetal growth.

RESULTS

In adjusted models, an IQR (2.5 µg/m³) increase in pregnancy-average PM_2.5 was associated with ORs of preterm birth of 1.04 (95% CI 0.94 to 1.15) and 0.86 (0.76 to 0.98) when considering modelled and monitored PM_2.5, respectively. An IQR increase in modelled and monitored PM_2.5 was associated with a 12.1 g (95% CI -24.2 to -0.1) and 15.9 g (95% CI -31.6 to -0.3) lower birth weight. Results for BC were highly sensitive to choice of exposure metric.

CONCLUSION

In a population with relatively low exposures to ambient air pollutants, PM_2.5 was associated with reduced birth weight but not with risk of preterm birth.

Changes in Transportation-Related Air Pollution Exposures by Race-Ethnicity and Socioeconomic Status: Outdoor Nitrogen Dioxide in the United States in 2000 and 2010

BACKGROUND

Disparities in exposure to air pollution by race-ethnicity and by socioeconomic status have been documented in the United States, but the impacts of declining transportation-related air pollutant emissions on disparities in exposure have not been studied in detail.

OBJECTIVE

This study was designed to estimate changes over time (2000 to 2010) in disparities in exposure to outdoor concentrations of a transportation-related air pollutant, nitrogen dioxide (NO2), in the United States.

METHODS

We combined annual average NO2 concentration estimates from a temporal land use regression model with Census demographic data to estimate outdoor exposures by race-ethnicity, socioeconomic characteristics (income, age, education), and by location (region, state, county, urban area) for the contiguous United States in 2000 and 2010.

RESULTS

Estimated annual average NO2 concentrations decreased from 2000 to 2010 for all of the race-ethnicity and socioeconomic status groups, including a decrease from 17.6 ppb to 10.7 ppb (-6.9 ppb) in nonwhite [non-(white alone, non-Hispanic)] populations, and 12.6 ppb to 7.8 ppb (-4.7 ppb) in white (white alone, non-Hispanic) populations. In 2000 and 2010, disparities in NO2 concentrations were larger by race-ethnicity than by income. Although the national nonwhite-white mean NO2 concentration disparity decreased from a difference of 5.0 ppb in 2000 to 2.9 ppb in 2010, estimated mean NO2 concentrations remained 37% higher for nonwhites than whites in 2010 (40% higher in 2000), and nonwhites were 2.5 times more likely than whites to live in a block group with an average NO2 concentration above the WHO annual guideline in 2010 (3.0 times more likely in 2000).

CONCLUSIONS

Findings suggest that absolute NO2 exposure disparities by race-ethnicity decreased from 2000 to 2010, but relative NO2 exposure disparities persisted, with higher NO2 concentrations for nonwhites than whites in 2010. https://doi.org/10.1289/EHP959.

IL-1β haplotype influences the effect of NOx exposure on gestational age in the South African MACE birth cohort

OBJECTIVE

Cytokines, molecules within the immune system that affect either a pro- or anti-inflammatory response, have previously been shown to influence birth outcomes. The maternal cytokine gene-environment interactions are thought to alter their expression, potentially influencing susceptibility to adverse birth outcomes. The aim of this study was to determine the association between the maternal interleukin-1β (IL-1β) haplotype and expression variation with oxides of nitrogen (NO_x) levels, and thereafter investigate the IL-1β haplotype-specific effects of NO_x exposure levels, IL-1β mRNA expression and other variables on gestational age.

MATERIAL AND METHODS

Using the prospective Mother and Child in the Environment (MACE) birth cohort in Durban, South Africa, 335 participants were genotyped for the IL-1β haplotype. Previous studies showed that three single nucleotide polymorphisms (SNPs), IL-1β-1464G/C, -511C/T and -31C/T, constitute the IL-1β functional haplotype. These SNPs were genotyped using a restriction fragment length polymorphism assay, while IL-1β mRNA expression was measured using a quantitative real-time polymerase chain reaction assay. Individual estimates of NO_x exposure were obtained by land use regression modelling. A multivariate linear regression analysis was employed to test for significant effects on gestational age.

RESULTS

IL-1β mRNA expression was found to possess a haplotype-dependent effect ( p = 0.0001) and its expression levels positively correlated with NO_x levels ( r = 0.34; p = 0.006). In the high haplotype model, a unit increase in NO_x exposure level was associated with a decrease in gestational age by 1 week ( p = 0.02). Furthermore, gestational age decreased by 0.9 weeks for every unit increase of IL-1β mRNA expression level ( p = 0.025). HIV-1 positivity was associated with a 0.2-week decrease in gestational age ( p = 0.035) in the intermediate haplotype model and a 0.4-week decrease in the high haplotype model ( p = 0.044).

CONCLUSION

These data have implications for better understanding the effect of prenatal NO_x exposure on gestational age and demonstrate the role of the IL-1β haplotype in modulating the effects of NO_x exposure.

The Tyr113His T/C rs1051740 and 'very slow' phenotype of the EPHX1 gene alters miR-26b-5p and miR-1207-5p expression in pregnancy

BACKGROUND

Environmental insults and microsomal epoxide hydrolase 1 (EPHX1) single nucleotide polymorphisms (SNPs), Tyr113His T/C rs1051740 and His139Arg A/G rs2234922, aberrantly alters microRNA (miR) expression and are linked to low birthweights (LBW).

OBJECTIVES

To investigate the interplay between pollution, EPHX1 SNPs and miRs during pregnancy and associated LBW outcomes.

METHODS

South African pregnant women (n=241) were recruited in the MACE birth cohort study in Durban, a city with high levels of industry and traffic related pollutants. EPHX1 SNPs were genotyped using PCR-RFLP and grouped into their respective phenotypes, i.e. normal (N), slow (S), very slow (VS) and fast (F). EPHX1, miR-26b-5p, miR-193b-3p and miR-1207-5p expression were determined using quantitative PCR.

RESULTS

Mothers with the Tyr113His SNP had low iron levels [TT vs. TC+CC: mean difference (MD)=0.67g/dl; p=0.0167], LBW [TT vs. TC+CC: MD=189.30g; p=0.0067], and low EPHX1 expression; p<0.0001. miR-26b-5p and miR-1207-5p expression were significantly higher in the CC genotypes compared to TT+TC groups; p<0.0001. The opposite trend occurred for miR-193b-3p; p=0.0045. Mothers with the VS phenotype had low iron levels [N vs. VS and VS vs. F: MD=2.03 and -1.96g/dl; p=0.0021, respectively], decreased gestational age [VS vs. F: MD=-2.14weeks; p=0.0051, respectively], and LBW [N vs. VS, VS vs. F and S vs. VS: MD=1000, -940.30 and 968.80g; p<0.0001, respectively]; F phenotype had the highest EPHX1 expression [N vs. F, VS vs. F and S vs. F: MD=-1.067, -1.854 and -1.379; p=0.0002, respectively]; and N phenotype had low miR-26b-5p [N vs. VS: MD=-0.6100; p=0.0159] and miR-1207-5p [N vs. VS and VS vs. F: MD=-0.834 and 1.103; p=0.0007, respectively] expression. miR-193b-3p expression between phenotypes remained unchanged.

CONCLUSION

The Tyr113His T/C variant of rs1051740 and VS phenotype alters EPHX1, miR-26b-5p and miR-1207-5p expression, and contributes towards low blood iron levels and LBW.

Different exposure levels of fine particulate matter and preterm birth: a meta-analysis based on cohort studies

The previous studies estimated the association between PM_2.5 (particulate matter with aerodynamic diameter less than or equal to 2.5 μm) exposure during pregnancy and preterm birth, only considered and highlighted the hazard effects of high levels of air pollutant exposure, and underestimated that low levels of pollutant exposure might also affect pregnancy outcome. We conducted a meta-analysis of 11 cohort studies, a total of more than 1,500,000 subjects. The results of these studies were pooled by exposure levels and study periods. PM_2.5 exposure during pregnancy was positively associated with preterm birth (OR = 1.15, 95% CI = 1.07-1.23), and during the first trimester of pregnancy, low levels of PM_2.5 exposure were also positively associated with preterm birth (OR = 1.17, 95% CI = 1.04-1.30). It is important to protect pregnant women from PM_2.5 exposures, especially during their first trimester of pregnancy even when the ambient PM_2.5 concentration is relatively low. More relevant health policy should be carried out to prevent hazard effect of air pollutants.

Asthma Trajectories in a Population-based Birth Cohort. Impacts of Air Pollution and Greenness

RATIONALE

The heterogeneity of asthma phenotypes may explain inconsistencies in observed associations with environmental exposures.

OBJECTIVES

To identify trajectories of childhood asthma and to characterize the potential impact of residential greenness and air pollution on asthma trajectory subgroups.

METHODS

Linked administrative databases of medical visits were used to define the occurrence and recurrence of asthma over a 10-year follow-up period within a population-based birth cohort of more than 65,000 children. Group-based trajectory modeling was used to identify unique asthma trajectories. Weighted multinomial regression was used to assess the relationship between asthma trajectories and risk factors, including environmental exposures.

MEASUREMENTS AND MAIN RESULTS

Group-based trajectory modeling distinguished four trajectories: one with no asthma representing 88.8% of the cohort, one with transient asthma (5.6% of the cohort), and two trajectories with chronic asthma with early (<1 yr; 1.5%) and late (<3 yr; 4.1%) onset during early childhood. These trajectories differed with respect to socioeconomic markers and modifiable risk factors, including maternal smoking and breastfeeding initiation. After accounting for sex, parity, breastfeeding, term birth weight, household income, maternal education, delivery mode, and smoking, an interquartile increase in nitrogen dioxide exposure increased the risk of membership in the early and late-onset chronic asthma trajectories, relative to subjects without asthma, by 50% and 20%, respectively (weighted risk ratio, 1.5 and 1.2; 95% confidence interval, 1.2-1.9 and 1.0-1.4). Greenness was not associated with any of the asthma trajectories.

CONCLUSIONS

Traffic-related air pollution increased the probability of a chronic asthma trajectory.

Comparison of spatiotemporal prediction models of daily exposure of individuals to ambient nitrogen dioxide and ozone in Montreal, Canada

BACKGROUND

In previous studies investigating the short-term health effects of ambient air pollution the exposure metric that is often used is the daily average across monitors, thus assuming that all individuals have the same daily exposure. Studies that incorporate space-time exposures of individuals are essential to further our understanding of the short-term health effects of ambient air pollution.

OBJECTIVES

As part of a longitudinal cohort study of the acute effects of air pollution that incorporated subject-specific information and medical histories of subjects throughout the follow-up, the purpose of this study was to develop and compare different prediction models using data from fixed-site monitors and other monitoring campaigns to estimate daily, spatially-resolved concentrations of ozone (O₃) and nitrogen dioxide (NO₂) of participants' residences in Montreal, 1991-2002.

METHODS

We used the following methods to predict spatially-resolved daily concentrations of O₃ and NO₂ for each geographic region in Montreal (defined by three-character postal code areas): (1) assigning concentrations from the nearest monitor; (2) spatial interpolation using inverse-distance weighting; (3) back-extrapolation from a land-use regression model from a dense monitoring survey, and; (4) a combination of a land-use and Bayesian maximum entropy model. We used a variety of indices of agreement to compare estimates of exposure assigned from the different methods, notably scatterplots of pairwise predictions, distribution of differences and computation of the absolute agreement intraclass correlation (ICC). For each pairwise prediction, we also produced maps of the ICCs by these regions indicating the spatial variability in the degree of agreement.

RESULTS

We found some substantial differences in agreement across pairs of methods in daily mean predicted concentrations of O₃ and NO₂. On a given day and postal code area the difference in the concentration assigned could be as high as 131ppb for O₃ and 108ppb for NO₂. For both pollutants, better agreement was found between predictions from the nearest monitor and the inverse-distance weighting interpolation methods, with ICCs of 0.89 (95% confidence interval (CI): 0.89, 0.89) for O₃ and 0.81 (95%CI: 0.80, 0.81) for NO₂, respectively. For this pair of methods the maximum difference on a given day and postal code area was 36ppb for O₃ and 74ppb for NO₂. The back-extrapolation method showed a higher degree of disagreement with the nearest monitor approach, inverse-distance weighting interpolation, and the Bayesian maximum entropy model, which were strongly constrained by the sparse monitoring network. The maps showed that the patterns of agreement differed across the postal code areas and the variability depended on the pair of methods compared and the pollutants. For O₃, but not NO₂, postal areas showing greater disagreement were mostly located near the city centre and along highways, especially in maps involving the back-extrapolation method.

CONCLUSIONS

In view of the substantial differences in daily concentrations of O₃ and NO₂ predicted by the different methods, we suggest that analyses of the health effects from air pollution should make use of multiple exposure assessment methods. Although we cannot make any recommendations as to which is the most valid method, models that make use of higher spatially resolved data, such as from dense exposure surveys or from high spatial resolution satellite data, likely provide the most valid estimates.

Residential Proximity to Roadways and Ischemic Placental Disease in a Cape Cod Family Health Study

Exposure to air pollution may adversely impact placental function through a variety of mechanisms; however, epidemiologic studies have found mixed results. We examined the association between traffic exposure and placental-related obstetric conditions in a retrospective cohort study on Cape Cod, MA, USA. We assessed exposure to traffic using proximity metrics (distance of residence to major roadways and length of major roadways within a buffer around the residence). The outcomes included self-reported ischemic placental disease (the presence of at least one of the following conditions: preeclampsia, placental abruption, small-for-gestational-age), stillbirth, and vaginal bleeding. We used log-binomial regression models to estimate risk ratios (RR) and 95% confidence intervals (CI), adjusting for potential confounders. We found no substantial association between traffic exposure and ischemic placental disease, small-for-gestational-age, preeclampsia, or vaginal bleeding. We found some evidence of an increased risk of stillbirth and placental abruption among women living the closest to major roadways (RRs comparing living <100 m vs. ≥200 m = 1.75 (95% CI: 0.82-3.76) and 1.71 (95% CI: 0.56-5.23), respectively). This study provides some support for the hypothesis that air pollution exposure adversely affects the risk of placental abruption and stillbirth; however, the results were imprecise due to the small number of cases, and may be impacted by non-differential exposure misclassification and selection bias.

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.

Systematic literature review of reproductive outcome associated with residential proximity to polluted sites

This study aims to assess the evidence on adverse pregnancy outcome associated with living close to polluted industrial sites, and identify the strengths and weaknesses of published epidemiological studies. A systematic literature search has been performed on all epidemiological studies published in developed countries since 1990, on the association between residential proximity to industrial sites (hazardous waste sites, industrial facilities and landfill sites) and adverse pregnancy outcome (low birth weight, preterm birth, small for gestational age, intrauterine growth retardation, infant mortality, congenital malformation). Based on 41 papers, our review reveals an excess risk of reproductive morbidity. However, no studies show significant excess risk of mortality including fetal death, neonatal or infant mortality and stillbirth. All published studies tend to show an increased risk of congenital abnormalities, yet not all are statistically significant. All but two of these studies revealed an excess risk of low birth weight. Results for preterm birth, small for gestational age and intrauterine growth retardation show the same pattern. There is suggestive evidence from the post-1990 literature that residential proximity to polluted sites (including landfills, hazardous waste sites and industrial facilities) might contribute to adverse reproductive outcomes, especially congenital malformations and low birth weight-though not mortality. This body of evidence has limitations that impede the formulation of firm conclusions, and new, well-focused studies are called for. The review findings suggest that continued strengthening of rules governing industrial emissions as well as industrial waste management and improved land use planning are needed.

Effects of Prenatal PM10 Exposure on Fetal Cardiovascular Malformations in Fuzhou, China: A Retrospective Case-Control Study

BACKGROUND

Maternal exposure to ambient air pollution has been associated with an increased risk of congenital heart defects in offspring; however, the results are inconsistent.

OBJECTIVES

We investigated whether there is an association between prenatal exposure to particulate matter with diameter ≤10μm (PM₁₀) during early pregnancy and fetal cardiovascular malformations.

METHODS

The gravidae from a hospital-based case–control study in Fuzhou, China, during 2007–2013 were assigned 10-d or 1-mo averages of daily PM₁₀ using an air monitor–based inverse distance weighting method during early pregnancy. A total of 662 live-birth or selectively terminated cases and 3,972 live-birth controls were enrolled. The exposure was considered as a categorical variable. A multivariable logistic regression model was constructed to quantify the adjusted odds ratios (aORs) of the exposure to PM₁₀ and the risks of fetal cardiovascular malformations.

RESULTS

PM₁₀ levels were positively associated with the risks of atrial septal defect (aORs ranging from 1.29 to 2.17), patent ductus arteriosus [aORs = 1.54, 1.63; 95% confidence intervals (CIs): 1.17, 2.23; 1.06, 3.24], overall fetal cardiovascular malformations (aOR = 1.28; 95% CI: 1.03, 1.61), ventricular septal defect (aOR = 1.19; 95% CI: 1.00, 1.43), and tetralogy of Fallot (aOR = 1.44; 95% CI: 1.01, 2.19) in the various observed periods scaled by 10 d or 1 mo in the first and second gestation months. The strongest associations were observed for exposure to PM₁₀ in the second quartile, whereas the associations were attenuated when higher concentrations of PM₁₀ in the third and fourth quartiles of the exposure were evaluated. No correlations of PM₁₀ levels with these cardiovascular malformations in the other time periods of gestation were observed.

CONCLUSIONS

Our findings suggest some positive associations between maternal exposure to ambient PM₁₀ during the first two months of pregnancy and fetal cardiovascular malformations. https://doi.org/10.1289/EHP289.

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.

Preterm birth associated with maternal fine particulate matter exposure: A global, regional and national assessment

Reduction of preterm births (<37 completed weeks of gestation) would substantially reduce neonatal and infant mortality, and deleterious health effects in survivors. Maternal fine particulate matter (PM_2.5) exposure has been identified as a possible risk factor contributing to preterm birth. The aim of this study was to produce the first estimates of ambient PM_2.5-associated preterm births for 183 individual countries and globally. To do this, national, population-weighted, annual average ambient PM_2.5 concentration, preterm birth rate and number of livebirths were combined to calculate the number of PM_2.5-associated preterm births in 2010 for 183 countries. Uncertainty was quantified using Monte-Carlo simulations, and analyses were undertaken to investigate the sensitivity of PM_2.5-associated preterm birth estimates to assumptions about the shape of the concentration-response function at low and high PM_2.5 exposures, inclusion of provider-initiated preterm births, and exposure to indoor air pollution. Globally, in 2010, the number of PM_2.5-associated preterm births was estimated as 2.7 million (1.8-3.5 million, 18% (12-24%) of total preterm births globally) with a low concentration cut-off (LCC) set at 10μgm^-3, and 3.4 million (2.4-4.2 million, 23% (16-28%)) with a LCC of 4.3μgm^-3. South and East Asia, North Africa/Middle East and West sub-Saharan Africa had the largest contribution to the global total, and the largest percentage of preterm births associated with PM_2.5. Sensitivity analyses showed that PM_2.5-associated preterm birth estimates were 24% lower when provider-initiated preterm births were excluded, 38-51% lower when risk was confined to the PM_2.5 exposure range in the studies used to derive the effect estimate, and 56% lower when mothers who live in households that cook with solid fuels (and whose personal PM_2.5 exposure is likely dominated by indoor air pollution) were excluded. The concentration-response function applied here derives from a meta-analysis of studies, most of which were conducted in the US and Europe, and its application to the areas of the world where we estimate the greatest effects on preterm births remains uncertain. Nevertheless, the substantial percentage of preterm births estimated to be associated with anthropogenic PM_2.5 (18% (13%-24%) of total preterm births globally) indicates that reduction of maternal PM_2.5 exposure through emission reduction strategies should be considered alongside mitigation of other risk factors associated with preterm births.

A Review of the Human Health Impacts of Unconventional Natural Gas Development

PURPOSE OF REVIEW

This review summarizes the recent epidemiologic literature examining health outcomes in communities living close to unconventional natural gas development (UNGD) and identifies areas requiring further study.

RECENT FINDINGS

To date, these studies have been primarily retrospective in design and used self-report of health symptoms or electronic health databases to obtain outcome information. Proximity to UNGD is often used as a surrogate for exposure. There is preliminary evidence linking respiratory outcomes, including asthma exacerbations, and birth outcomes, such as reduced fetal growth and preterm birth, to UNGD; however, results differ across study populations and regions.

SUMMARY

Although small, the current body of literature suggests that living near UNGD may have negative health consequences for surrounding communities, but additional work using more granular estimates of exposure or personalized monitoring is urgently needed.

Impact of Particulate Matter Exposure and Surrounding "Greenness" on Chronic Absenteeism in Massachusetts Public Schools

Chronic absenteeism is associated with poorer academic performance and higher attrition in kindergarten to 12th grade (K-12) schools. In prior research, students who were chronically absent generally had fewer employment opportunities and worse health after graduation. We examined the impact that environmental factors surrounding schools have on chronic absenteeism. We estimated the greenness (Normalized Difference Vegetation Index (NDVI)) and fine particulate matter air pollution (PM_2.5) within 250 m and 1000 m respectively of each public school in Massachusetts during the 2012–2013 academic year using satellite-based data. We modeled chronic absenteeism rates in the same year as a function of PM_2.5 and NDVI, controlling for race and household income. Among the 1772 public schools in Massachusetts, a 0.15 increase in NDVI during the academic year was associated with a 2.6% (p value < 0.0001) reduction in chronic absenteeism rates, and a 1 μg/m³ increase in PM_2.5 during the academic year was associated with a 1.58% (p value < 0.0001) increase in chronic absenteeism rates. Based on these percentage changes in chronic absenteeism, a 0.15 increase in NDVI and 1 μg/m³ increase in PM_2.5 correspond to 25,837 fewer students and 15,852 more students chronically absent each year in Massachusetts respectively. These environmental impacts on absenteeism reinforce the need to protect green spaces and reduce air pollution around schools.

Clean air matters: an overview of traffic-related air pollution and pregnancy

The right to a healthy pregnancy and to giving birth in a safe environment is source of comprehensive research. Decent birth facilities, respect, and no discrimination are already recognized as fundamental rights, but an accurate look at the outdoor environment is required. Air pollution is a dangerous factor to pregnant women and newborns, many of whom highly exposed to traffic-related atmospheric pollutants in urban areas. Such exposure can lead to low birth weight and long-lasting effects, such as respiratory diseases and premature death. Thus, this commentary, based on the analysis of literature, presents the importance of the exposome concept and of epigenetics in identifying the role of the environment for better health conditions of pregnant women and newborns. In the final considerations, this study proposes the deepening of the subject and the mobilization in this regard, with a human rights-based approach to environmental health and to the increased awareness of pregnant women on the risks of air pollution and its effects on health.

Childhood hematologic cancer and residential proximity to oil and gas development

BACKGROUND

Oil and gas development emits known hematological carcinogens, such as benzene, and increasingly occurs in residential areas. We explored whether residential proximity to oil and gas development was associated with risk for hematologic cancers using a registry-based case-control study design.

METHODS

Participants were 0-24 years old, living in rural Colorado, and diagnosed with cancer between 2001-2013. For each child in our study, we calculated inverse distance weighted (IDW) oil and gas well counts within a 16.1-kilometer radius of residence at cancer diagnosis for each year in a 10 year latency period to estimate density of oil and gas development. Logistic regression, adjusted for age, race, gender, income, and elevation was used to estimate associations across IDW well count tertiles for 87 acute lymphocytic leukemia (ALL) cases and 50 non-Hodgkin lymphoma (NHL) cases, compared to 528 controls with non-hematologic cancers.

FINDINGS

Overall, ALL cases 0-24 years old were more likely to live in the highest IDW well count tertiles compared to controls, but findings differed substantially by age. For ages 5-24, ALL cases were 4.3 times as likely to live in the highest tertile, compared to controls (95% CI: 1.1 to 16), with a monotonic increase in risk across tertiles (trend p-value = 0.035). Further adjustment for year of diagnosis increased the association. No association was found between ALL for children aged 0-4 years or NHL and IDW well counts. While our study benefited from the ability to select cases and controls from the same population, use of cancer-controls, the limited number of ALL and NHL cases, and aggregation of ages into five year ranges, may have biased our associations toward the null. In addition, absence of information on O&G well activities, meteorology, and topography likely reduced temporal and spatial specificity in IDW well counts.

CONCLUSION

Because oil and gas development has potential to expose a large population to known hematologic carcinogens, further study is clearly needed to substantiate both our positive and negative findings. Future studies should incorporate information on oil and gas development activities and production levels, as well as levels of specific pollutants of interest (e.g. benzene) near homes, schools, and day care centers; provide age-specific residential histories; compare cases to controls without cancer; and address other potential confounders, and environmental stressors.

Integrated assessment of air pollution by metals and source apportionment using ryegrass (Lolium multiflorum Lam.) in southern Brazil

One of the biggest environmental problems existing today is air pollution, which is characterized by the presence of toxic gases and metal pollutants, the latter of which is generally associated with emissions of particulate matter (PM) from industries or automotive vehicles. Biomonitoring is a method that can be used to assess air pollution levels because it makes it possible to determine what effects these air pollutants cause in living organisms and their responses. The species Lolium multiflorum Lam., known as ryegrass, is considered a good bioindicator of metals, since it accumulates these substances during exposure. This study proposes to conduct an integrated assessment of air quality using two different monitoring methodologies: biomonitoring with L. multiflorum and active monitoring in areas with different levels of urbanization and industrialization. Concentrations found in ryegrass plants revealed high levels of Pb, Cr, Zn, and Cu, indicating that vehicular and industrial emissions were the main sources of pollution. Analysis of PM also revealed soot and biogenic particles, which can transport metals. Therefore, with the proposed method, the anthropogenic impact on air pollution in the investigated area could be clearly demonstrated.