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

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.

Association between ambient particulate matter exposure and semen quality in fertile men

BACKGROUND

Several studies have suggested adverse effects of particulate matter (PM) exposure on male reproductive health; few have investigated the association between PM exposure and semen quality in a large population of fertile men.

METHODS

We evaluated 14 parameters of semen quality in 1554 fertile men in Nanjing from 2014 to 2016. Individual exposure to particular matter ≤10 μm in diameter (PM₁₀) and ≤ 2.5 μm in diameter (PM_2.5) during key periods of sperm development (0-90, 0-9, 10-14, 15-69, and 70-90 days before semen collection) were estimated by inverse distance weighting interpolation. Associations between PM exposure and semen quality were estimated using multivariable linear regression.

RESULTS

Higher 90-days average PM_2.5 was in association with decreased sperm motility (2.21% for total motility, 1.93% for progressive motility per 10 μg/m³ increase, P <  0.001) and four quantitative aspects of sperm motion (curvilinear velocity (VCL), straight line velocity (VSL), average path velocity (VAP), and amplitude of lateral head displacement (ALH), P <  0.01). The association between PM_2.5 exposure and semen quality were generally stronger for the earlier exposure window (70-90 days prior to ejaculation) than for recent exposure (0-9, 10-14, or 15-69 days). In the subgroup of men who had normal sperm parameters (n = 1019), similar results were obtained. Ninety-days PM₁₀ exposure was associated only with decreased VCL and VAP and was not related to sperm concentration.

CONCLUSIONS

Exposure to PM_2.5 adversely affects semen quality, specifically lower sperm motility, in fertile men.

Hyper-localized measures of air pollution and risk of preterm birth in Oakland and San Jose, California

BACKGROUND

US preterm-birth rates are 1.6 times higher for Black mothers than for White mothers. Although traffic-related air pollution (TRAP) may increase the risk of preterm birth, evaluating its effect on preterm birth and disparities has been challenging because TRAP is often measured inaccurately. This study sought to estimate the effect of TRAP exposure, measured at the street level, on the prevalence of preterm birth by race/ethnicity.

METHODS

We linked birth-registry data with TRAP measured at the street level for singleton births in sampled communities during 2013-2015 in Oakland and San Jose, California. Using logistic regression and marginal standardization, we estimated the effects of exposure to black carbon, nitrogen dioxide and ultrafine particles on preterm birth after confounder adjustment and stratification by race/ethnicity.

RESULTS

There were 8823 singleton births, of which 760 (8.6%) were preterm. Shifting black-carbon exposure from the 10th to the 90th percentile was associated with: 6.8%age point higher risk of preterm birth (95% confidence interval = 0.1 to 13.5) among Black women; 2.1%age point higher risk (95% confidence interval = -1.1 to 5.2) among Latinas; and inconclusive null findings among Asian and White women. For Latinas, there was evidence of a positive association between the other pollutants and risk of preterm birth, although effect sizes were attenuated in models that co-adjusted for other TRAP.

CONCLUSIONS

Exposure to TRAP, especially black carbon, may increase the risk of preterm birth for Latina and Black women but not for Asian and White women.

Residential particulate matter, proximity to major roads, traffic density and traffic volume as risk factors for preterm birth in California

BACKGROUND

While pollution from vehicle sources is an established risk factor for preterm birth, it is unclear whether distance of residence to the nearest major road or related measures like major road density represent useful measures for characterising risk.

OBJECTIVE

To determine whether major road proximity measures (including distance to major road, major road density and traffic volume) are more useful risk factors for preterm birth than other established vehicle-related measures (including particulate matter <2.5 μm in diameter (PM_2.5 ) and diesel particulate matter (diesel PM)).

METHODS

This retrospective cohort study included 2.7 million births across the state of California from 2011-2017; each address at delivery was geocoded. Geocoding was used to calculate distance to the nearest major road, major road density within a 500 m radius and major road density weighted by truck volume. We measured associations with preterm birth using risk ratios adjusted for target demographic, clinical, socioeconomic and environmental covariates (aRRs). We compared these to the associations between preterm birth and PM_2.5 and diesel PM by census tract of residence.

RESULTS

Findings showed that whereas higher mean levels of PM_2.5 and diesel PM by census tract were associated with a higher risk of preterm birth, living closer to roads or living in higher traffic density areas was not associated with higher risk. Residence in a census tract with a mean PM_2.5 in the top quartile compared with the lowest quartile was associated with the highest observed risk of preterm birth (aRR 1.04, 95% CI 1.04, 1.05).

CONCLUSIONS

Over a large geographical region with a diverse population, PM2.5 and diesel PM were associated with preterm birth, while measures of distance to major road were not, suggesting that these distance measures do not serve as a proxy for measures of particulate matter in the context of preterm birth.

Exposure to chemical components of fine particulate matter and ozone, and placenta-mediated pregnancy complications in Tokyo: a register-based study

BACKGROUND

Maternal exposure to fine particulate matter (PM_2.5) was associated with pregnancy complications. However, we still lack comprehensive evidence regarding which specific chemical components of PM_2.5 are more harmful for maternal and foetal health.

OBJECTIVE

We focused on exposure over the first trimester (0-13 weeks of gestation), which includes the early placentation period, and investigated whether PM_2.5 and its components were associated with placenta-mediated pregnancy complications (combined outcome of small for gestational age, preeclampsia, placental abruption, and stillbirth).

METHODS

From 2013 to 2015, we obtained information, from the Japan Perinatal Registry Network database, on 83,454 women who delivered singleton infants within 23 Tokyo wards (≈627 km²). Using daily filter sampling of PM_2.5 at one monitoring location, we analysed carbon and ion components, and assigned the first trimester average of the respective pollutant concentrations to each woman.

RESULTS

The ORs of placenta-mediated pregnancy complications were 1.14 (95% CI = 1.08-1.22) per 0.51 μg/m³ (interquartile range) increase of organic carbon and 1.11 (1.03-1.18) per 0.06 μg/m³ increase of sodium. Organic carbon was also associated with four individual complications. There was no association between ozone and outcome.

SIGNIFICANCE

There were specific components of PM_2.5 that have adverse effects on maternal and foetal health.

Ambient air pollution and inflammatory effects in a Canadian pregnancy cohort

Supplemental Digital Content is available in the text.

Background:

Epidemiologic studies have consistently reported associations between air pollution and pregnancy outcomes including preeclampsia and gestational diabetes. However, the biologic mechanisms underlying these relationships remain unclear as few studies have collected relevant biomarker data. We examined relationships between ambient PM_2.5 and NO₂ with markers of inflammation during pregnancy in a prospective cohort of Canadian women.

Methods:

We analyzed data from 1170 women enrolled in the Maternal-Infant Research on Environmental Chemicals study. Daily residential PM_2.5 and NO₂ exposures during pregnancy were estimated using satellite-based and land-use regression models and used to create 14-day and 30-day exposure windows before blood-draw. Inflammatory markers C-reactive protein, interleukin-6, interleukin-8, and tumor necrosis factor-α were measured in third trimester plasma samples. Multivariable linear regression was used to estimate associations for an interquartile range (IQR) increase in PM_2.5 and NO₂ and markers of inflammation, while adjusting for individual-level confounders.

Results:

Fourteen-day (IQR: 6.85 µg/m³) and 30-day (IQR: 6.15 µg/m³) average PM_2.5 exposures before blood-draw were positively associated with C-reactive protein after adjustment for covariates (24.6% [95% CI = 9.4, 41.9] and 17.4% [95% CI = 1.0, 35.0] increases, respectively). This association was found to be robust in several sensitivity analyses. Neither PM_2.5 nor NO₂ exposures were associated with interleukin-6, interleukin-8, or tumor necrosis factor-α.

Conclusion:

Exposure to ambient PM_2.5 is positively associated with maternal inflammatory pathways in late pregnancy. This may contribute to positive associations between ambient PM_2.5 and risk of adverse pregnancy outcomes.

Relationship between Land-Use Type and Daily Concentration and Variability of PM10 in Metropolitan Cities: Evidence from South Korea

Since urban areas with high air pollution are known to have higher mortality rates compared to areas with less air pollution, accurately understanding and predicting the distribution of particulate matter (PM) in cities is important for urban planning policies that seek to emphasize the health of citizens. Therefore, this study aims to investigate the relationship between PM and land use in metropolitan cities in South Korea using the land-use regression model. We use daily data from the air quality monitoring stations (AQMS) in seven cities in South Korea for the year 2018. For analysis, K-means clustering is employed to identify the land-use pattern surrounding the AQMSs and two log-lin regression models are used to investigate the effects of each land-use type on PM. The findings show a statistically significant difference in PM concentration and variability in the business, commercial, industrial, mixed, and high-density residential areas compared to parks and green areas, and that PM concentration and variability were less in mixed areas than in single land use, thus verifying the effectiveness of a mixed land-use planning strategy. Moreover, microclimatic, seasonal, and regional factors affect PM concentration and variability. Finally, to minimize exposure to PM, various policies such as mixed land use need to be established and implemented differently, depending on the season and time.

Using Bayesian time-stratified case-crossover models to examine associations between air pollution and "asthma seasons" in a low air pollution environment

Many areas of the United States have air pollution levels typically below Environmental Protection Agency (EPA) regulatory limits. Most health effects studies of air pollution use meteorological (e.g., warm/cool) or astronomical (e.g., solstice/equinox) definitions of seasons despite evidence suggesting temporally-misaligned intra-annual periods of relative asthma burden (i.e., “asthma seasons”). We introduce asthma seasons to elucidate whether air pollutants are associated with seasonal differences in asthma emergency department (ED) visits in a low air pollution environment. Within a Bayesian time-stratified case-crossover framework, we quantify seasonal associations between highly resolved estimates of six criteria air pollutants, two weather variables, and asthma ED visits among 66,092 children ages 5–19 living in South Carolina (SC) census tracts from 2005 to 2014. Results show that coarse particulates (particulate matter <10 μm and >2.5 μm: PM_10-2.5) and nitrogen oxides (NO_x) may contribute to asthma ED visits across years, but are particularly implicated in the highest-burden fall asthma season. Fine particulate matter (<2.5 μm: PM_2.5) is only associated in the lowest-burden summer asthma season. Relatively cool and dry conditions in the summer asthma season and increased temperatures in the spring and fall asthma seasons are associated with increased ED visit odds. Few significant associations in the medium-burden winter and medium-high-burden spring asthma seasons suggest other ED visit drivers (e.g., viral infections) for each, respectively. Across rural and urban areas characterized by generally low air pollution levels, there are acute health effects associated with particulate matter, but only in the summer and fall asthma seasons and differing by PM size.

Determination of local traffic emission and non-local background source contribution to on-road air pollution using fixed-route mobile air sensor network

Traffic-related air pollutants are major contributors to deteriorating urban air quality and pose a serious threat to pedestrians. From both a scientific and a regulatory standpoint, it is important and challenging to understand the contributions of local and non-local sources to accurately apportion specific sources such as traffic emissions contribution to on-road and near-road microenvironment air quality. In this study, we deployed mobile sensors on-board buses to monitor NO, NO₂, CO and PM_2.5 along ten important routes in Hong Kong. The measurements include two seasons: April 2017 and July 2017. Two types of baseline extraction methods were evaluated and applied to separate local and background concentrations. The results show NO and NO₂ are locally dominated air pollutants in spring, constituting 72%-84% and 58%-71%, respectively, with large inter-road variation. PM_2.5 and CO largely arise from background sources, which contribute 55%-65% and 73%-79% respectively. PM_2.5 displays a homogeneous spatial pattern, and the contributions show seasonal change, decreasing during summer. Regional transport pollution is the primary contributor during high pollution episodes. Isolated vehicle plumes show highly skewed concentration distributions. There are characteristic polluted segments on routes and they are most evident at rush hours. The most polluted road segments (top 10%) cluster at tunnel entrances and congested points. Some of these polluted locations were observed in Hong Kong's Low Emission Zones and suggest limitations to the existing control strategies, which only address larger buses. Our work gives new insights in the importance of regional cooperation to improve background air pollution combined with local control strategies to improve roadside air quality in Hong Kong.

Particulate matter and hypertensive disorders in pregnancy: systematic review and meta-analysis

OBJECTIVES

We aimed to quantitatively synthesize the association between maternal exposure to particulate matter (PM; including PM <2.5 μm and PM <10 μm) and hypertensive disorders in pregnancy (HDP; including gestational hypertension [GH] and pre-eclampsia) and to explore the influence of certain factors on the outcome.

STUDY DESIGN

Meta-analysis was used to quantitatively synthesize the results of similar independent studies.

METHODS

Original documents were identified by searching six electronic bibliographic databases from their inceptions to August 17, 2021. Then we performed meta-analysis to combine the effect estimates if at least three estimates reported the same exposure and outcome and used stratified analysis to evaluate the impact of exposure assessment method, data source, and study area on heterogeneity. In addition, we used the 95% prediction interval to evaluate the potential effects of exposure in random effects meta-analysis.

RESULTS

The overall meta-analysis showed that the risk of HDP was significantly associated with per 5 μg/m³ increase in PM_2.5 exposure during T1 and PM₁₀ exposure during T, with odds ratios [ORs] 1.06 (95% confidence interval [CI]: 1.01-1.12) and 1.04 (95% CI: 1.02-1.07), respectively. The results also showed that PM_2.5 exposure during T1 and T2 and PM₁₀ exposure during T1 increased the incidence of GH; the summary ORs were 1.11 (95% CI: 1.01-1.23), 1.16 (95% CI: 1.05-1.29), and 1.04 (95% CI: 1.02-1.07), respectively. Subgroup analyses showed that the pooled effects were generally significant or more apparent in studies using models to assess exposure, studies whose data derived from birth registers, and studies in Europe.

CONCLUSIONS

This meta-analysis showed that PM exposure was associated with increased HDP risks, and the association varied by study area, data source, and exposure assessment method. With the continuous improvement of research design and exposure assessment, future research may find higher risks.

Effects of air pollution on mortality of patients with chronic kidney disease: A large observational cohort study

Due to industrialization, the burden of diseases associated with air pollution is increasing. Although the risk associated with air pollution in the general population has been actively investigated, few studies have been conducted on the effects of exposure to air pollution in patients with chronic kidney disease (CKD) in East Asia. A total of 29,602 patients with CKD in Seoul participated in a retrospective cohort at three medical centers. We assessed the association of individualized exposure to five types of air pollutants (PM_2.5, PM₁₀, NO₂, SO₂, and CO) using inverse distance weighting (IDW) on mortality in CKD patients in the Cox proportional hazard model that was adjusted for sex, age, eGFR, hemoglobin, hypertension, diabetes, and area-level characteristics. During the 6.14 ± 3.96 years, 3863 deaths (13%) were observed. We confirmed the significant effects of PM_2.5 (hazard ratio [HR] 1.17, 95% confidence interval [CI] 1.07-0.29) and CO (HR 1.17, 95% CI 1.00-1.38) on mortality in CKD patients. Different associations were found when stratified by age, body mass index, smoking, and drinking status. Long-term exposure to air pollutants had negative effects on mortality in patients with CKD. These effects were prominent in patients aged over 65 years, patients with a lean body, and those who did not drink alcohol.

Retraction Note to: Ambient air pollution and adverse birth outcomes: a systematic review and meta-analysis

Retraction Note to: J Zhejiang Univ-Sci B (Biomed & Biotechnol) 2019 20(3):238-252. https://doi.org/10.1631/jzus.B1800122. The authors have retracted this article (Guo et al., 2019) because some data from the original literature had not been converted to appropriate units in the paper, which resulted in deviation of the meta-analysis results. For example, for the forest plot used to examine associations between PM₁₀ exposure and the risk of adverse birth outcomes, the estimates from Brauer et al. (2008), Pedersen et al. (2013), Zhao et al. (2015), and Hansen et al. (2006) were on the originally reported scales of 1 µg/m³, 10 µg/m³, 10 µg/m³, and Inter Quartile Range, respectively. None of these estimates had been converted to 20 µg/m³ increase scale that was stated in the article. Similar problem exists in the analysis on associations between NO₂ exposure and risk of adverse birth outcomes. Therefore, the results of the meta-analysis are misleading. All authors have agreed to this retraction and express their deepest apologies to the original authors, publishers, and readers.

Placental gene networks at the interface between maternal PM2.5 exposure early in gestation and reduced infant birthweight

BACKGROUND

A growing body of evidence links maternal exposure to particulate matter <2.5 μM in diameter (PM2.5) and deviations in fetal growth. Several studies suggest that the placenta plays a critical role in conveying the effects of maternal PM2.5 exposure to the developing fetus. These include observed associations between air pollutants and candidate placental features, such as mitochondrial DNA content, DNA methylation and telomere length. However, gaps remain in delineating the pathways linking the placenta to air pollution-related health effects, including a comprehensive profiling of placental processes impacted by maternal PM2.5 exposure. In this study, we examined alterations in a placental transcriptome-wide network in relation to maternal PM2.5 exposure prior to and during pregnancy and infant birthweight.

METHODS

We evaluated PM2.5 exposure and placental RNA-sequencing data among study participants enrolled in the Rhode Island Child Health Study (RICHS). Daily residential PM2.5 levels were estimated using a hybrid model incorporating land-use regression and satellite remote sensing data. Distributed lag models were implemented to assess the impact on infant birthweight due to PM2.5 weekly averages ranging from 12 weeks prior to gestation until birth. Correlations were assessed between PM2.5 levels averaged across the identified window of susceptibility and a placental transcriptome-wide gene coexpression network previously generated using the WGCNA R package.

RESULTS

We identified a sensitive window spanning 12 weeks prior to and 13 weeks into gestation during which maternal PM2.5 exposure is significantly associated with reduced infant birthweight. Two placental coexpression modules enriched for genes involved in amino acid transport and cellular respiration were correlated with infant birthweight as well as maternal PM2.5 exposure levels averaged across the identified growth restriction window.

CONCLUSION

Our findings suggest that maternal PM2.5 exposure may alter placental programming of fetal growth, with potential implications for downstream health effects, including susceptibility to cardiometabolic health outcomes and viral infections.

Long-term impact of ambient air pollution on preterm birth in Xuzhou, China: a time series study

Accumulating evidence witnesses the negative influence of air pollution on human health, but the relationship between air pollution and premature babies has been inconsistent. In this study, the association between weekly average concentration of air pollutants and preterm birth (PTB) was conducted in Xuzhou, a heavy industry city, in China. We constructed a distributed lag non-linear model (DLNM), an ecological study, to access the associations between ambient air pollutants and PTB in this study. Totally, 5408 premature babies were included, and the weekly average levels of PM_2.5, PM₁₀, SO₂, NO₂, O₃, and CO were 61.24, 110.21, 22.55, 40.55, 104.45, and 1.04 mg/m³, respectively. We found that PM_2.5, PM₁₀, SO₂, and NO₂ significantly increased the risk of PTB, and the susceptibility windows of these contaminants were the second trimester and third trimester (from 12 to 29 weeks). Every 10 μg/m³ increase of PM_2.5, PM₁₀, SO₂, and NO₂, the greatest relative risk (RR) values and 95% confidence interval (CI) on PTB were 1.0075 [95% CI, 1.0019-1.0131], 1.0053 [95% CI, 1.0014-1.0092], 1.0203 [95% CI, 1.0030-1.0379], and 1.0170 [95% CI, 1.0052-1.0289] in lag 16th, 18th, 19th, and 20th gestational weeks, respectively. No significant influence of O₃ and CO were found on preterm birth. Subgroup analysis showed that the risk of premature delivery was higher for younger pregnant women and in warm season. This finding shows that prenatal exposure to ambient air pollutants is associated with preterm birth, and there existed an exposure window period.

Ozone exposure during early pregnancy and preterm birth: A systematic review and meta-analysis

Exposure to ozone has been linked to reproductive outcomes, including preterm birth. In this systematic review, we summarize published epidemiologic cohort and case-control studies examining ozone exposures (estimated on a continuous scale) in early pregnancy (1st and 2nd trimesters (T1, T2)) and preterm birth using ratio measures, and perform a meta-analysis to evaluate the potential relationship between them. Studies were identified by searching PubMed and Web of Science, screened according to predefined inclusion/exclusion criteria, and evaluated for study quality. We extracted study data including effect estimates, confidence limits, study location, study years, ozone exposure assessment method, and mean or median ozone concentrations. Nineteen studies were identified and included, of which 18 examined T1 exposure (17 reported effect estimates), and 15 examined T2 exposure. Random effects meta-analysis was performed in the metafor package, R 3.5.3. The pooled OR (95% CI) for a 10 ppb increase in ozone exposure in T1 was 1.06 (1.03, 1.10) with a 95% prediction interval of 0.95, 1.19; for T2 it was 1.05 (1.02, 1.08) with a 95% prediction interval of 0.95, 1.16. Effect estimates for both exposure periods showed high heterogeneity. In meta-regression analyses of study characteristics, study location (continent) explained some (~20%) heterogeneity for T1 exposure studies, but no characteristic explained a substantial amount of heterogeneity for T2 exposure studies. Increased ozone exposure during early pregnancy is associated with preterm birth across studies.

Air pollution-associated blood pressure may be modified by diet among children in Guangzhou, China

OBJECTIVES

To assess the associations between long-term air pollution exposure and blood pressure in children, and to explore the modifying effects of diet on prehypertension and hypertension.

METHODS

We evaluated 7225 primary school children aged 6-12 years from Guangzhou, China, in 2017. The blood pressure was measured objectively. The individual 1-year average concentration of particles with an aerodynamic diameter of 2.5 μm or less or 10 μm or less (PM2.5, PM10), sulfur dioxide (SO2), and ozone (O3) before each blood pressure measurement were calculated by inverse distance weighting interpolation according to each home address. Generalized linear mixed-effects models were used to examine the health effects and potential effect modifications by diet factors after adjusting for covariates.

RESULTS

The results showed that the estimated increase in mean SBP was 0.92 mmHg (95% CI 0.05-1.79) per interquartile range increase in O3. An interquartile range increase in the 1-year mean of SO2 and O3 was associated with odds ratios of 1.26 (95% CI 1.04-1.52) and 1.20 (95% CI 1.06-1.35) for prehypertension, respectively. In addition, an interquartile range increase in PM2.5, SO2, and O3 exposure was positively associated with hypertension, with odds ratios of 1.33 (95% CI 1.11-1.61), 1.70 (95% CI 1.33-2.16), and 1.48 (95% CI 1.20-1.83), respectively. Stronger effect estimates between PM2.5, SO2, and O3 concentration on prehypertension were exhibited among subgroups of children with a higher intake of sugar-sweetened beverages.

CONCLUSION

Long-term exposure to PM2.5, SO2, and O3 were associated with higher blood pressure levels in children, and dietary intake might modify these associations.

Assessing the effectiveness of vehicle emission regulations on improving perinatal health: a population-based accountability study

BACKGROUND

Since the 1990s, extensive regulations to reduce traffic-related air pollution (TRAP) have been implemented, yet the effectiveness of these regulations has not been assessed with respect to improving infant health. In this study, we evaluate how infant health risks associated with maternal residences near highways during pregnancy have changed over time.

METHODS

We created a population-based retrospective birth cohort with geocoded residential addresses in Texan metropolitan areas from 1996 through 2009 (n = 2 259 411). We compared term birthweight (37-42 weeks of gestation) among maternal residences <300 m from a highway (high TRAP exposure) (n = 394 346) and 500-3500 m from a highway (comparison group) (n = 1 865 065). We implemented linear regressions to evaluate interactions between high TRAP exposure and birth year, adjusting for demographics, socioeconomic status and neighbourhood context. In addition, we used propensity score matching to further reduce residual confounding.

RESULTS

From 1996 to 2009, outdoor NO2 decreased by 51.3%, based on regulatory monitoring data in Texas. Among pregnant women who resided in the high TRAP zone during pregnancy, interaction terms between residential location and birth year show that birthweight increased by 1.1 g [95% confidence interval CI): 0.7, 1.5) in unadjusted models and 0.3 g (95% CI: 0.0, 0.6) in matched models. Time-stratified models also show decreasing impacts of living in high TRAP areas on birthweight when comparing infants born in 1996-97 with 2008-09. Sensitivity analyses with alternative exposure and control groups show consistent results.

CONCLUSIONS

Infant health risks associated with maternal residence near highways have reduced over time, paralleling regulatory measures to improve exhaust pipe emissions.

Residential proximity to roadways and placental-associated stillbirth: a case-control study

We conducted a retrospective case-control study of 1,097 women in Massachusetts and Rhode Island, USA, to examine the association between stillbirth related to placental abruption or placental insufficiency and maternal exposure to traffic-related air pollution. We utilized distance to nearest roadway proximity metrics as a proxy for traffic-related air pollution exposure. No meaningful increase in the overall odds of placental-associated stillbirths was observed (adjusted OR: 1.1, 95% CI: 0.5-2.8). However, mothers living within 50 m of a roadway had a 60% increased odds of experiencing a stillbirth related to placental abruption compared to mothers living greater than 200 m away. This suggestive finding was imprecise due to the small case number in the highest exposure category (95% CI: 0.6-4.0). Future studies of placental abruption with more precise exposure assessments are warranted.

Assessing the Impact of Wildfires on the Use of Black Carbon as an Indicator of Traffic Exposures in Environmental Epidemiology Studies

Epidemiological studies frequently use black carbon (BC) as a proxy for traffic-related air pollution (TRAP). However, wildfire smoke (WFS) represents an important source of BC not often considered when using BC as a proxy for TRAP. Here, we examined the potential for WFS to bias TRAP exposure assessments based on BC measurements. Weekly integrated BC samples were collected across the Denver, CO region from May to November 2018. We collected 609 filters during our sampling campaigns, 35% of which were WFS-impacted. For each filter we calculated an average BC concentration. We assessed three GIS-based indicators of TRAP for each sampling location: annual average daily traffic within a 300 m buffer, the minimum distance to a highway, and the sum of the lengths of roadways within 300 m. Median BC concentrations were 9% higher for WFS-impacted filters (median = 1.14 μg/m3, IQR = 0.23 μg/m3) than nonimpacted filters (median = 1.04 μg/m3, IQR = 0.48 μg/m3). During WFS events, BC concentrations were elevated and expected spatial gradients in BC were reduced. We conducted a simulation study to estimate TRAP exposure misclassification as the result of regional WFS. Our results suggest that linear health effect estimates were biased away from the null when WFS was present. Thus, exposure assessments relying on BC as a proxy for TRAP may be biased by wildfire events. Alternative metrics that account for the influence of "brown" carbon associated with biomass burning may better isolate the effects of traffic emissions from those of other black carbon sources.

Exposure to ambient air pollution during pregnancy and inflammatory biomarkers in maternal and umbilical cord blood: The Healthy Start study

BACKGROUND

Air pollution exposure during pregnancy has been associated with adverse pregnancy and birth outcomes. Inflammation has been proposed as a potential link. We estimated associations between air pollution exposure during pregnancy and inflammatory biomarkers in maternal and cord blood. We evaluated whether maternal inflammation was associated with infant outcomes.

METHODS

Among 515 mother-infant dyads in the Healthy Start study (2009-2014), trimester-long, 7- and 30-day average concentrations of particulate matter ≤2.5 μm (PM_2.5) and ozone (O₃) during pregnancy were estimated, using inverse-distance-weighted interpolation. Inflammatory biomarkers were measured in maternal blood in mid-pregnancy (C-reactive protein [CRP], Interleukin [IL]-6, and tumor necrosis factor-α [TNFα]) and in cord blood at delivery (CRP, IL-6, IL-8, IL-10, monocyte chemoattractant protein-1 [MCP-1], and TNFα). We used linear regression to estimate associations between pollutants and inflammatory biomarkers and maternal inflammatory biomarkers and infant weight and body composition.

RESULTS

There were positive associations between PM_2.5 during certain exposure periods and maternal IL-6 and TNFα. There were negative associations between recent O₃ and maternal CRP, IL-6, and TNFα and positive associations between trimester-long O₃ exposure and maternal inflammatory biomarkers, though some 95% confidence intervals included the null. Patterns were inconsistent for associations between PM_2.5 and O₃ and cord blood inflammatory biomarkers. No consistent associations between maternal inflammatory biomarkers and infant outcomes were identified.

CONCLUSIONS

Air pollution exposure during pregnancy may impact maternal inflammation. Further investigations should examine the health consequences for women and infants of elevated inflammatory biomarkers associated with air pollution exposure during pregnancy.

Changes in criteria air pollution levels in the US before, during, and after Covid-19 stay-at-home orders: Evidence from regulatory monitors

The widespread and rapid social and economic changes from Covid-19 response might be expected to dramatically improve air quality. However, national monitoring data from the US Environmental Protection Agency for criteria pollutants (PM_2.5, ozone, NO₂, CO, PM₁₀) provide inconsistent support for that expectation. Specifically, during stay-at-home orders, average PM_2.5 levels were slightly higher (~10% of its multi-year interquartile range [IQR]) than expected; average ozone, NO₂, CO, and PM₁₀ levels were slightly lower (~30%, ~20%, ~27%, and ~1% of their IQR, respectively) than expected. The timing of peak anomaly, relative to the stay-at-home orders, varied by pollutant (ozone: 2 weeks before; NO₂, CO: 3 weeks after; PM₁₀: 2 weeks after); but, by 5-6 weeks after stay-at-home orders, the concentration anomalies appear to have ended. For PM_2.5, ozone, CO, and PM₁₀, no US state had lower-than-expected pollution levels for all weeks during stay-at-home-orders; for NO₂, only Arizona had lower-than-expected levels for all weeks during stay-at-home orders. Our findings show that the enormous changes from the Covid-19 response have not lowered PM_2.5 levels across the US beyond their normal range of variability; for ozone, NO₂, CO, and PM₁₀ concentrations were lowered but the reduction was modest and transient.

Particulate Matter, an Intrauterine Toxin Affecting Foetal Development and Beyond

Air pollution is the 9th cause of the overall disease burden globally. The solid component in the polluted air, particulate matters (PMs) with a diameter of 2.5 μm or smaller (PM_2.5) possess a significant health risk to several organ systems. PM_2.5 has also been shown to cross the blood–placental barrier and circulate in foetal blood. Therefore, it is considered an intrauterine environmental toxin. Exposure to PM_2.5 during the perinatal period, when the foetus is particularly susceptible to developmental defects, has been shown to reduce birth weight and cause preterm birth, with an increase in adult disease susceptibility in the offspring. However, few studies have thoroughly studied the health outcome of foetuses due to intrauterine exposure and the underlying mechanisms. This perspective summarises currently available evidence, which suggests that intrauterine exposure to PM_2.5 promotes oxidative stress and inflammation in a similar manner as occurs in response to direct PM exposure. Oxidative stress and inflammation are likely to be the common mechanisms underlying the dysfunction of multiple systems, offering potential targets for preventative strategies in pregnant mothers for an optimal foetal outcome.

Characterizing long-term NO2 concentration surfaces across a large metropolitan area through spatiotemporal land use regression modelling of mobile measurements

A spatiotemporal land use regression (LUR) model optimized to predict nitrogen dioxide (NO₂) concentrations obtained from on-road, mobile measurements collected in 2015-16 was independently evaluated using concentrations observed at multiple sites across Toronto, Canada, obtained more than ten years earlier. This spatiotemporal LUR modelling approach improves upon estimates of historical NO₂ concentrations derived from the previously used method of back-extrapolation. The optimal spatiotemporal LUR model (R² = 0.71 for prediction of NO₂ data in 2002 and 2004) uses daily average NO₂ concentrations observed at multiple long-term monitoring sites and hourly average wind speed recorded at a single site, along with spatial predictors based on geographical information system data, to estimate NO₂ levels for time periods outside of those used for model development. While the model tended to underestimate samplers located close to the roadway, it showed great accuracy when estimating samplers located beyond 100 m which are probably more relevant for exposure at residences. This study shows that spatiotemporal LUR models developed from strategic, multi-day (30 days in 3 different months) mobile measurements can enhance LUR model's ability to estimate long-term, intra-urban NO₂ patterns. Furthermore, the mobile sampling strategy enabled this new LUR model to cover a larger domain of Toronto and outlying suburban communities, thereby increasing the potential population for future epidemiological studies.

Long-Term Ambient Air Pollution Exposures and Circulating and Stimulated Inflammatory Mediators in a Cohort of Midlife Adults

BACKGROUND

Chronic exposure to air pollution may prime the immune system to be reactive, increasing inflammatory responses to immune stimulation and providing a pathway to increased risk for inflammatory diseases, including asthma and cardiovascular disease. Although long-term exposure to ambient air pollution has been associated with increased circulating markers of inflammation, it is unknown whether it also relates to the magnitude of inflammatory response.

OBJECTIVES

The aim of this study was to examine associations between chronic ambient pollution exposures and circulating and stimulated levels of inflammatory mediators in a cohort of healthy adults.

METHODS

Circulating interleukin (IL)-6, C-reactive protein (CRP) (n=392), and lipopolysaccharide stimulated production of IL-1β, IL-6, and tumor necrosis factor (TNF)-α (n=379) were measured in the Adult Health and Behavior II cohort. Fine particulate matter [particulate matter with aerodynamic diameter less than or equal to 2.5 μm (PM2.5)] and constituents [black carbon (BC), and lead (Pb), manganese (Mn), zinc (Zn), and iron (Fe)] were estimated for each residential address using hybrid dispersion land use regression models. Associations between pollutant exposures and inflammatory measures were examined using linear regression; models were adjusted for age, sex, race, education, smoking, body mass index, and month of blood draw.

RESULTS

There were no significant correlations between circulating and stimulated measures of inflammation. Significant positive associations were found between exposure to PM2.5 and BC with stimulated production of IL-6, IL-1β, and TNF-α. Pb, Mn, Fe, and Zn exposures were positively associated with stimulated production of IL-1β and TNF-α. No pollutants were associated with circulating IL-6 or CRP levels.

DISCUSSION

Exposure to PM2.5, BC, Pb, Mn, Fe, and Zn was associated with increased production of inflammatory mediators by stimulated immune cells. In contrast, pollutant exposure was not related to circulating markers of inflammation. These results suggest that chronic exposure to some pollutants may prime immune cells to mount larger inflammatory responses, possibly contributing to increased risk for inflammatory disease. https://doi.org/10.1289/EHP7089.

Commuter PM exposure and estimated life-expectancy loss across multiple transportation modes in Xi'an, China

Commuters are reportedly exposed to severe traffic-related air pollution (TRAP) during their commuting trips. This study was designed and implemented to (1) compare particulate matter (PM) exposure across four common transportation modes; (2) examine and analyze various determining factors; and (3) estimate public health effects caused by commuting exposure to PM. All analyses and calculations were based on the experimental data collected from 13 volunteers, including heart-rate data on 336 commuting trips in four travel modes in Xi'an China. The results indicate highest PM exposure associated with cycling (average PM₁₀, PM_2.5 and PM_1.0 of 114.35, 72.37 and 56.51 μg/m³, respectively), followed by riding transit buses (116.29, 67.60 and 51.12 μg/m³ for the same pollutants, respectively), then taking a taxi (97.61, 58.87 and 45.11 μg/m³), and the lowest exposure onboard subways (55.86, 46.20 and 40.20 μg/m³). A multivariable linear regression model was used to examine major influences on PM concentration variations, with results corroborating significant PM variance across commuting modes, which is also affected by background pollution concentration and relative humidity. Further, years of life expectancy (YLE) loss were estimated using an inhalation dose model together with the life table method: cycling commuters experienced the greatest YLE loss (5.51-6.43 months per capita for the studied age group). During severe pollution periods, substituting other modes (like subway) for cycling could effectively avoid acute exposure. PM_2.5 levels in taxi cabins powered by CNG or methanol were comparatively lower, indicating that implementing alternative energy strategies could effectively lower traffic emissions and population exposure.

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.

Gestational exposures to outdoor air pollutants in relation to low birth weight: A retrospective observational study

Findings for impacts of outdoor air pollutants on birth outcomes were controversial. We performed a retrospective observational study in 2527 preschoolers of Shanghai, China and investigated associations of duration-averaged concentrations of outdoor sulphur dioxide (SO₂), nitrogen dioxide (NO₂), and particulate matter with an aerodynamic diameter ≤ 10 μm (PM₁₀) in different months and trimesters of gestation, with preterm birth (PB), low birth weight (LBW), term low birth weight (T-LBW), and small for gestational age (SGA). Daily concentrations of outdoor air pollutants were collected in each residence-located district. Parents reported health information. In the multivariate logistic regression analyses, exposures to outdoor NO₂ were consistently associated with the higher odds of LBW and T-LBW. These associations were generally stronger for early months than for later months of the gestation. Adjusted odds ratios generally were larger in multi-pollutant model than in single-pollutant model. Exposure to NO₂ in the first month of the gestation was significantly associated with T-LBW (adjusted OR, 95%CI: 1.91, 1.02-3.58 for increment of interquartile range (18.5 μg/m³); p-value = 0.044) in multi-pollutant model. This association was stronger in girls, renters, and children whose mothers ≥30 years-old, with household dampness-related exposures, and with parental smoking during pregnancy. Our results indicate that exposure to NO₂ during gestation perhaps is a risk factor for LBW and T-LBW, and effects of NO₂ exposures could be greater during early periods than during later periods of gestation.

Effects of PM2.5 exposure on reproductive system and its mechanisms

With the development of human society, haze has become an important form of air pollution. Haze is a mixture of fog and haze, and the main component of haze is fine particulate matter (PM_2.5), which is the most important indicator of composite air pollution. Epidemiological studies proved that PM_2.5 can break through the respiratory mucosal barrier and enter the human body, causing pathological effects on multiple systems of the body. In the past, people put more attention to PM_2.5 in the respiratory system, cardiovascular system, nervous system, etc, and relatively paid less attention to the reproductive system. Recent studies have shown that PM_2.5 will accumulate in the reproductive organs through blood-testis barrier, placental barrier, epithelial barrier and other barriers protecting reproductive tissues. In addition, PM_2.5 can disrupt hormone levels, ultimately affecting fertility. Prior studies have shown that oxidative stress, inflammation, apoptosis, and the breakdown of barrier structures are now considered to contribute to reproductive toxicity and may cause damage at the molecular and genetic levels. However, the exact mechanism remains to be elucidated. Our review aims to provide an understanding of the pathological effects of PM_2.5 on reproductive system and the existing injury mechanism.

Application of high-resolution metabolomics to identify biological pathways perturbed by traffic-related air pollution

BACKGROUND

Substantial research has investigated the adverse effects of traffic-related air pollutants (TRAP) on human health. Convincing associations between TRAP and respiratory and cardiovascular diseases are known, but the underlying biological mechanisms are not well established. High-resolution metabolomics (HRM) is a promising platform for untargeted characterization of molecular mechanisms between TRAP and health indexes.

OBJECTIVES

We examined metabolic perturbations associated with short-term exposures to TRAP, including carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), fine particulate matter (PM2.5), organic carbon (OC), and elemental carbon (EC) among 180 participants of the Center for Health Discovery and Well-Being (CHDWB), a cohort of Emory University-affiliated employees.

METHODS

A cross-sectional study was conducted on baseline visits of 180 CHDWB participants enrolled during 2008-2012, in whom HRM profiling was determined in plasma samples using liquid chromatography-high-resolution mass spectrometry with positive and negative electrospray ionization (ESI) modes. Ambient pollution concentrations were measured at an ambient monitor near downtown Atlanta. Metabolic perturbations associated with TRAP exposures were assessed following an untargeted metabolome-wide association study (MWAS) framework using feature-specific Tobit regression models, followed by enriched pathway analysis and chemical annotation.

RESULTS

Subjects were predominantly white (76.1%) and non-smokers (95.6%), and all had at least a high school education. In total, 7821 and 4123 metabolic features were extracted from the plasma samples by the negative and positive ESI runs, respectively. There are 3421 features significantly associated with at least one air pollutant by negative ion mode, and 1691 features by positive ion mode. Biological pathways enriched by features associated with the pollutants are primarily involved in nucleic acids damage/repair (e.g., pyrimidine metabolism), nutrient metabolism (e.g., fatty acid metabolism), and acute inflammation (e.g., histidine metabolism and tyrosine metabolism). NO2 and EC were associated most consistently with these pathways. We confirmed the chemical identity of 8 metabolic features in negative ESI and 2 features in positive ESI, including metabolites closely linked to oxidative stress and inflammation, such as histamine, tyrosine, tryptophan, and proline.

CONCLUSIONS

We identified a range of ambient pollutants, including components of TRAP, associated with differences in the metabolic phenotype among the cohort of 180 subjects. We found Tobit models to be a robust approach to handle missing data among the metabolic features. The results were encouraging of further use of HRM and MWAS approaches for characterizing molecular mechanisms underlying exposure to TRAP.

Forecasting PM2.5 using hybrid graph convolution-based model considering dynamic wind-field to offer the benefit of spatial interpretability

Air pollution is a complex process and is affected by meteorological conditions and other chemical components. Numerous studies have demonstrated that data-driven spatio-temporal prediction models of PM2.5 concentration are comparable with the model-driven model. However, data-driven models are usually depending on the statistical correlation between PM2.5 and other factors and have challenges in dealing with causality in complex systems. In this paper, we argue that domain knowledge should be incorporated into data-driven models to enhance prediction accuracy and make the model more physically realistic. We focus on the influence of dynamic wind-field on PM2.5 concentration distribution and fuse the pollution diffusion distance with the deep learning model based on a wind-field surface. In order to model spatial dependence between monitoring stations, which is dynamic and anisotropic because of the wind-field, we proposed a hybrid deep learning framework, dynamic directed spatio-temporal graph convolution networks (DD-STGCN). It expanded the ability to deal with space-time prediction in the continuous and dynamic wind-field. We used a directed graph time-series to describe the vertex state and topological relationship between vertices and replaced traditional Euclidean distance with wind-field diffusion distance to describe the proximity relationship between vertices. Our experiment results demonstrated that the DD-STGCN model achieved a better prediction ability than LSTM, GC-LSTM, and STGCN models. Compared to the best comparison model, MAPE, MAE, and RMSE were improved by 10.2%, 9.7%, and 9.6% in 12 h on an average, respectively. The performance of our model was further tested during a haze period. In the case that two models both considered the effect of wind, compared with the pure data-driven model, our model performed better in prediction distribution and showed the benefit of spatial interpretability provided by domain knowledge.

Air Pollution and Adverse Pregnancy and Birth Outcomes: Mediation Analysis Using Metabolomic Profiles

PURPOSE OF REVIEW

Review how to use metabolomic profiling in causal mediation analysis to assess epidemiological evidence for air pollution impacts on birth outcomes.

RECENT FINDINGS

Maternal exposures to air pollutants have been associated with pregnancy complications and adverse pregnancy and birth outcomes. Causal mediation analysis enables us to estimate direct and indirect effects on outcomes (i.e., effect decomposition), elucidating causal mechanisms or effect pathways. Maternal metabolites and metabolic pathways are perturbed by air pollution exposures may lead to adverse pregnancy and birth outcomes, thus they can be considered mediators in the causal pathways. Metabolomic markers have been used to explain the biological mechanisms linking air pollution and respiratory function, and of arsenic exposure and birth weight. However, mediation analysis of metabolomic markers has not been used to assess air pollution effects on adverse birth outcomes. In this article, we describe the assumptions and applications of mediation analysis using metabolomic markers that elucidate the potential mechanisms of the effects of air pollution on adverse pregnancy and birth outcomes. The hypothesis of mediation along specified pathways can be assessed within the structural causal modeling framework. For causal inferences, several assumptions that go beyond the data-including no uncontrolled confounding-need to be made to justify the effect decomposition. Nevertheless, studies that integrate metabolomic information in causal mediation analysis may greatly improve our understanding of the effects of ambient air pollution on adverse pregnancy and birth outcomes as they allow us to suggest and test hypotheses about underlying biological mechanisms in studies of pregnant women.

Association of maternal ozone exposure with term low birth weight and susceptible window identification

BACKGROUND

Ozone pollution keeps deteriorating in the context of climate change. Maternal ozone exposure may be associated with low birth weight (LBW), but the results are still inconsistent. The identification of the critical exposure windows, a specific period of particular susceptibility during pregnancy, remains unresolved. We aimed to evaluate whether ozone exposure was associated with term LBW and further identify the susceptible exposure windows.

METHODS

A retrospective cohort study was conducted in Guangzhou, a megacity in the most populous and economically developed city clusters in China. We included 444,096 singleton live births between January 2015 and July 2017. From 11 fixed stations, we collected daily 1-h maximum and 8-h maximum moving average ozone level (O₃-1 h and O₃-8 h) and calculated exposures for each participant based on their district of residence during pregnancy. We used traditional Logistic regression to estimate the trimester-specific association between ozone exposure and term LBW, and further estimated monthly- and weekly association by distributed lag models (DLMs) with Logistic regression. Odds ratios (ORs) and 95% confidence intervals (CIs) of term LBW were calculated for an interquartile range (IQR) increase in ozone exposure. Stratified analyses and heterogeneity tests were conducted by maternal age and infant sex.

RESULTS

The incidence of term LBW was 1.9%. During the study period, the mean O₃-1 h and O₃-8 h levels were 112.6 µg/m³ and 84.5 µg/m³, respectively. Increased O₃-1 h (IQR: 90 µg/m³) and O₃-8 h (73 µg/m³) exposure during the second trimester were associated with increased risk of term LBW. At a monthly level, the term LBW risk was associated with O₃-1 h exposure during the 4th-6th month and O₃-8 h exposure during the 6th month. By estimating the weekly-specific association, we observed that critical exposure windows were the 15th- 26th gestational weeks for O₃-1 h, and the 20th-26th weeks for O₃-8 h, respectively. Estimated ORs and 95% CIs ranged from 1.012 (1.000, 1.024) to 1.023 (1.007, 1.039). When examined by subgroups, the effects were present among women ≥ 35 years or < 25 years old and those with female babies.

CONCLUSIONS

This study provides compelling evidence that exposure to O₃ was associated with increased risk of term LBW, and gestational weeks 15th- 26th was found to be particularly susceptible. These findings provide a research basis for further mechanism examination, public health interventions, and targeted environmental policy-making.

In-car particulate matter exposure across ten global cities

Cars are a commuting lifeline worldwide, despite contributing significantly to air pollution. This is the first global assessment on air pollution exposure in cars across ten cities: Dhaka (Bangladesh); Chennai (India); Guangzhou (China); Medellín (Colombia); São Paulo (Brazil); Cairo (Egypt); Sulaymaniyah (Iraq); Addis Ababa (Ethiopia); Blantyre (Malawi); and Dar-es-Salaam (Tanzania). Portable laser particle counters were used to develop a proxy of car-user exposure profiles and analyse the factors affecting particulate matter ≤2.5 μm (PM_2.5; fine fraction) and ≤10 μm (PM_2.5-10; coarse fraction). Measurements were carried out during morning, off- and evening-peak hours under windows-open and windows-closed (fan-on and recirculation) conditions on predefined routes. For all cities, PM_2.5 and PM₁₀ concentrations were highest during windows-open, followed by fan-on and recirculation. Compared with recirculation, PM_2.5 and PM₁₀ were higher by up to 589% (Blantyre) and 1020% (São Paulo), during windows-open and higher by up to 385% (São Paulo) and 390% (São Paulo) during fan-on, respectively. Coarse particles dominated the PM fraction during windows-open while fine particles dominated during fan-on and recirculation, indicating filter effectiveness in removing coarse particles and a need for filters that limit the ingress of fine particles. Spatial variation analysis during windows-open showed that pollution hotspots make up to a third of the total route-length. PM_2.5 exposure for windows-open during off-peak hours was 91% and 40% less than morning and evening peak hours, respectively. Across cities, determinants of relatively high personal exposure doses included lower car speeds, temporally longer journeys, and higher in-car concentrations. It was also concluded that car-users in the least affluent cities experienced disproportionately higher in-car PM_2.5 exposures. Cities were classified into three groups according to low, intermediate and high levels of PM exposure to car commuters, allowing to draw similarities and highlight best practices.

Impact of air pollution exposure during various periods of pregnancy on term birth weight: a large-sample, retrospective population-based cohort study

Previous studies have suggested that maternal exposure to air pollution might affect term birth weight. However, the conclusions are controversial. Birth data of all term newborns born in Xi'an city of Shaanxi, China, from 2015 to 2018 and whose mother lived in Xi'an during pregnancy were selected form the Birth Registry Database. And the daily air quality data of Xi'an city was collected from Chinese Air Quality Online Monitoring and Analysis Platform. Generalized additive models (GAM) and 2-level binary logistic regression models were used to estimate the effects of air pollution exposure on term birth weight, the risk term low birth weight (TLBW), and macrosomia. Finally, 321521 term newborns were selected, including 4369(1.36%) TLBW infants and 24,960 (7.76%) macrosomia. The average pollution levels of PM_2.5, PM₁₀, and NO₂ in Xi'an city from 2015 to 2018 were higher than national limits. During the whole pregnancy, maternal exposure to PM_2.5, PM₁₀, SO₂, and CO all significantly reduced the term birth weight and increased the risk of TLBW. However, NO₂ and O₃ exposure have significantly increased the term birth weight, and O₃ even increased the risk of macrosomia significantly. Those effects were also observed in the first and second trimesters of pregnancy. But during the third trimester, high level of air quality index (AQI) and maternal exposure to PM_2.5, PM₁₀, SO₂, NO₂, and CO increased the term birth weight and the risk of macrosomia, while O₃ exposure was contrary to this effect. The findings suggested that prenatal exposure to air pollution might cause adverse impacts on term birth weight, and the effects varied with trimesters and pollutants, which provides further pieces of evidence for the adverse effects of air pollution exposure in heavy polluted-area on term birth weight.

Exposure assessment of indoor particulate matter during pregnancy: a narrative review of the literature

OBJECTIVE

The aim of this review was to summarize the evidence of the exposure assessment approaches of indoor particulate matter (PM) during pregnancy and to recommend future focus areas.

CONTENT

Exposure to indoor PM during pregnancy is associated with adverse birth outcomes. However, many questions remain about the consistency of the findings and the magnitude of this effect. This may be due to the exposure assessment methods used and the challenges of characterizing exposure during pregnancy. Exposure is unlikely to remain constant over the nine-month period. Pregnant females' mobility and activities vary - for example, employment status may be random among females, but among those employed, activities are likely to be greater in the early pregnancy than closer to the delivery of the child.

SUMMARY

Forty three studies that used one of the five categories of indoor PM exposure assessment (self-reported, personal air monitoring, household air monitoring, exposure models and integrated approaches) were assessed. Our results indicate that each of these exposure assessment approaches has unique characteristics, strengths, and weaknesses. While questionnaires and interviews are based on self-report and recall, they were a major component in the reviewed exposure assessment studies. These studies predominantly used large sample sizes. Precision and detail were observed in studies that used integrated approaches (i. e. questionnaires, measurements and exposure models).

OUTLOOK

Given the limitations presented by these studies, exposure misclassification remains possible because of personal, within and between household variability, seasonal changes, and spatiotemporal variability during pregnancy. Therefore, using integrated approaches (i. e. questionnaire, measurements and exposure models) may provide better estimates of PM levels across trimesters. This may provide precision for exposure estimates in the exposure-response relationship.

The mediation effect of maternal glucose on the association between ambient air pollution and birth weight in Foshan, China

Maternal blood glucose level is associated with fetal growth, therefore, its role in the associations between air pollution and birth weight deserves investigation. We examined the mediation effect of maternal blood glucose on the associations between maternal air pollution exposure and birth weight. A total of 10,904 pregnant women in Foshan, China during 2015-2019 were recruited. Oral glucose tolerance test (OGTT) was administered to each participant after late trimester 2. Air pollution data at the monitoring stations in residential districts was used to estimate exposures of each participant during trimester 1 and trimester 2. Mixed-effects linear models were used to estimate the associations between air pollution and birth weight. After controlling for ten covariates, the direct effect of PM_2.5 and SO₂ (each 10 μg/m³ increment) on birth weight was -15.7 g (95% CI: -29.4, -4.8 g) and -83.6 g (95% CI: -134.8, -33.0 g) during trimester 1. The indirect effect of PM_2.5 and SO₂ (each 10 μg/m³ increment) on birth weight by increasing maternal fasting glucose level was 6.6 g (95% CI: 4.6, 9.1 g) and 22.0 g (95% CI: 4.1, 44.0 g) during trimester 1. Our findings suggest that air pollution might affect the birth weight through direct and indirect pathway, and the indirect effect might be mediated by maternal blood glucose.

Maternal exposure to air pollution and the risk of low birth weight: A meta-analysis of cohort studies

Previous studies have evaluated the relationship between prenatal air pollution exposure and low birth weight, but the results are inconsistent. The purpose of this meta-analysis is to quantitatively analyze the relationship between maternal air pollutant exposure and low birth weight (LBW). PubMed and Web of Science databases were searched to obtain the studies on the relationship between the prenatal exposure of air pollutants and LBW that published as of June 2020. The pooled effects of air pollutant exposure and LBW were calculated using random-effect model (for studies with significant heterogeneity) or fixed-effect model (for studies without significant heterogeneity). Totally, 54 studies were included in this meta-analysis. The pooled effect of PM_2.5, PM₁₀, NO₂, CO, SO₂, and O₃ exposure on LBW were 1.081 (95% CI: 1.043, 1.120), 1.053 (95% CI: 1.030, 1.076), 1.030 (95% CI: 1.008, 1.053), 1.007 (95% CI: 1.001, 1.014), 1.125 (95% CI: 1.017, 1.244), and 1.045 (95% CI: 1.005, 1.086), respectively. NO₂ (per 10 ppb increase) and CO (per 100 ppb increase) exposure in the first trimester were positively correlated with LBW, of which the pooled effect was 1.022 (95% CI: 1.009, 1. 035) and 1.008 (95% CI: 1.004, 1.012), respectively. PM_2.5 (per 10 μg/m³ increase) exposure in the third trimester significantly affected the LBW, of which the pooled effect was 1.053 (95% CI: 1.010, 1.097). In addition, PM₁₀ (per 10 μg/m³ increase) exposure in the second trimester also significantly affected the LBW, with the pooled effect of 1.011 (95% CI: 1.005, 1.017). Prenatal exposure of the major air pollutants during the entire pregnancy could increase the risk of LBW, while the susceptible window of the pollutants varied.

Identifying critical exposure windows for ambient air pollution and semen quality in Chinese men

Emerging studies documented the association between ambient air pollution exposure and semen quality, but the critical exposure windows have not been comprehensively studied. To identify susceptible windows for associations of exposure to ambient respirable particulate matter (PM₁₀), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and ozone (O₃) with sperm concentration, sperm count, total motility, and progressive motility, we recruited 1061 men attending an infertility clinic in Wuhan, China, between 2011 and 2013. We used a distributed lag multivariate linear regression to assess the exposure-lag-response relationship between semen quality and weekly air pollution exposure. The critical exposure windows were during the 6th to 12th sperm development weeks for PM₁₀, 10th to 11th weeks for O₃, and 0 to 5th weeks for SO₂. Over the entire 12 weeks of spermatogenesis period, an interquartile range increase (IQR) increase in PM₁₀ was associated with declined sperm concentration [-45.64% (95% CI: -59.97%, -26.18%) percent decrease], declined sperm count [-49.42% (95% CI: -64.42%, -28.09%) percent decrease], reduced total motility [-12.42 (95% CI: -20.47, -4.37)], and reduced progressive motility [-8.81 (95% CI: -16.00, -1.61)], SO₂ per IQR increase was associated with reduced sperm concentration [-39.73% (95% CI: -55.96%, -17.51%) percent decrease] and total motility [-8.64 (95% CI: -16.90, -0.38)], but NO₂ and O₃ were not associated with any of the four sperm quality parameters. Our findings suggest that exposure to PM₁₀ during spermatidogenesis period, exposure to SO₂ during spermatocytogenesis period, and exposure to O₃ during spermiogenesis period were associated with impaired semen quality, which implies air pollutants impair semen quality through varied pathways.

Traffic-related metrics and adverse birth outcomes: A systematic review and meta-analysis

Given the inconsistency of epidemiologic evidence for associations between maternal exposures to traffic-related metrics and adverse birth outcomes, this manuscript aims to provide clarity on this topic. Pooled meta-estimates were calculated using random-effects analyses. Subgroup analyses were conducted by study area, study design, and Newcastle-Ottawa quality score (NOS). Funnel plots and Egger's test were conducted to evaluate the publication bias, and Fail-safe Numbers (Fail-safe N) were measured to evaluate the robustness of models. From the initial 740 studies (last search, July 11, 2019), 26 studies were included in our analysis. The pooled odds ratio for the change in small for gestational age associated with per 500 m decrease in the distance to roads was 1.016 (95% CI: 1.004, 1.029). Subgroup analyses revealed significant positive associations between term low birth weight and traffic density in higher-quality literatures with higher NOS [1.060 (95% CI: 1.002, 1.121)], cohort studies [1.020 (95% CI: 1.006, 1.033)], and studies in North America [1.018 (95% CI: 1.005, 1.131)]. The buffer of traffic density made no difference in the effect size. Traffic density seemed to be a better indicator of traffic pollution than the distance to roads.

Interaction of Air Pollutants and Meteorological Factors on Birth Weight in Shenzhen, China

BACKGROUND

This study aimed to assess if air pollutants and meteorological factors synergistically affect birth outcomes in Shenzhen, China.

METHODS

A total of 1,206,158 singleton live births between 2005 and 2012 were identified from a birth registry database. Daily average measurements of particulate matter ≤10 µm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), ambient air temperature (T), and dew point temperature (Td), a marker of humidity, were collected. Multivariable logistic regression models were used to evaluate associations between air pollution and small for gestational age (SGA), and full-term low birth weight (TLBW). We classified births into those conceived in the warm (May-October) and cold seasons (November-April) and then estimated interactions between air pollutants and meteorological factors.

RESULTS

An interquartile range (IQR) increase in PM10 exposure during the first trimester (23.1 µg/m) and NO2 during both the first and second trimesters (15.1 and 13.4 µg/m) was associated with SGA and TLBW risk; odds ratios ranged from 1.01 (95% confidence interval [CI] = 1.00, 1.02) to 1.09 (1.07, 1.12). We observed interactive effects of both air temperature and humidity on PM10 and SGA for newborns conceived in the warm season. Each IQR increase in PM10 (11.1 µg/m) increased SGA risk by 90% (95% CI = 19%, 205%), 29% (23, 34%), 61% (10, 38%), and 26% (21, 32%) when T < 5th percentile, 5th < T < 95th percentile, Td < 5th percentile, and 5th < Td < 95th percentile, respectively.

CONCLUSIONS

Our study found evidence of an interactive effect of air temperature and humidity on the relationship between PM10 exposure and SGA among newborns conceived in the warm season (May-October). Relatively low air temperature or humidity exacerbated the effects of PM10.

Estimating exposure to traffic-related PM2.5 for women commuters using vehicle and personal monitoring

Exposure to traffic-related fine particulate matter air pollution (tr-PM_2.5) has been associated with adverse health outcomes including preterm birth and low birthweight. In-vehicle exposure to tr-PM_2.5 can contribute substantially to total tr-PM_2.5 exposure. Because average commuting habits of women differ from men, a research gap is estimating in-vehicle tr-PM_2.5 exposures for women commuters. For 46 women commuters in the Washington, D.C. metro area, we measured personal exposure to PM_2.5 during all vehicle trips taken in a 48-h sampling period. We also measured 48-h integrated PM_2.5 chemical constituents including black carbon and zinc. We identified trip times using vehicle monitors, specifically on-board diagnostics data loggers and dashboard cameras. For 386 trips, we estimated associations between PM_2.5 exposure and trip characteristics using linear mixed models accounting for participant, day, and time of day. Additionally, we estimated associations between rush hour trip PM_2.5 and 48-h integrated PM_2.5 chemical constituents using linear models. Exposure to PM_2.5 during trips was 1.9 μg/m³ (95% confidence interval (CI): 0.9, 2.9) higher than non-trip exposures and rush hour trip exposures were 3.2 μg/m³ (95% CI: 1.8, 4.6) higher than non-trip exposures on average. We did not find differences in PM_2.5 exposure by trip length. Although concentrations of tr-PM_2.5 chemical constituents were generally positively associated with rush hour trip PM_2.5, associations were weak indicating that other settings contribute to total tr-PM_2.5 exposure. Our study demonstrates the utility of combining vehicle monitors and personal PM_2.5 monitors for estimating personal exposure to tr-PM_2.5. Future work will investigate whether additional data collected by vehicle monitors, such as traffic and speed, can be leveraged to better understand tr-PM_2.5 exposure among commuters.

Cohort profile: Center for Research on Early Childhood Exposure and Development in Puerto Rico

PURPOSE

Puerto Rican children experience high rates of asthma and obesity. Further, infants born in Puerto Rico are more at risk for being born prematurely compared with infants on the mainland USA. Environmental exposures from multiple sources during critical periods of child development, potentially modified by psychosocial factors, may contribute to these adverse health outcomes. To date, most studies investigating the health effects of environmental factors on infant and child health have focused on single or individual exposures.

PARTICIPANTS

Infants currently in gestation whose mother is enrolled in Puerto Rico Testsite for Exploring Contamination Threats (PROTECT) cohort, and infants and children already born to mothers who participated in the PROTECT study.

FINDINGS TO DATE

Data collection and processing remains ongoing. Demographic data have been collected on 437 mother-child pairs. Birth outcomes are available for 420 infants, neurodevelopmental outcomes have been collected on 319 children. Concentrations of parabens and phenols in maternal spot urine samples have been measured from 386 mothers. Center for Research on Early Childhood Exposure and Development mothers have significantly higher urinary concentrations of dichlorophenols, triclosan and triclocarban, but lower levels of several parabens compared with reference values from a similar population drawn from the National Health and Nutrition Examination Survey.

FUTURE PLANS

Data will continue to be collected through recruitment of new births with a target of 600 children. Seven scheduled follow-up visits with existing and new participants are planned. Further, our research team continues to work with healthcare providers, paediatricians and early intervention providers to support parent's ability to access early intervention services for participants.

Space-time hot spots of critically ill small for gestational age newborns and industrial air pollutants in major metropolitan areas of Canada

We assessed the association of spatiotemporal hot spots of critically ill small for gestational age (ciSGA) newborns and industrial air emissions. Using neonatal admission data from the Canadian Neonatal Network between 2006 and 2010 (n = 32,836 infants), we aggregated maternal residential postal codes from nineteen census metropolitan areas (CMA) into space-time cubes and applied emerging hot spot analyses. Using National Pollutant Release Inventory data (n = 161 chemicals) and Environment Canada weather station data (n = 19 sites), we estimated monthly wind-dispersion of air emissions and calculated hot spots. We associated the patterns using logistic regression, with covariates for low socioeconomic status, NO₂ pollution, and number of infants. A total of 5465 infants were identified as ciSGA and the larger CMAs had more and larger hot spots (i.e. accumulation of events in space and time). Seventy-eight industrial chemical hot spots were associated with ciSGA hot spots. The highest number of positive associations were for 28 different pollutants, which differed by CMA. Twenty-one were known or suspected developmental toxicants, such as particulate matter, carbon monoxide, heavy metals, and volatile organic compounds. Associations with hot spots of industrial chemical emissions were geographically specific and may help explain the space-time trends of ciSGA.

Flaring from Unconventional Oil and Gas Development and Birth Outcomes in the Eagle Ford Shale in South Texas

BACKGROUND

Prior studies suggest exposure to oil and gas development (OGD) adversely affects birth outcomes, but no studies have examined flaring-the open combustion of natural gas-from OGD.

OBJECTIVES

We investigated whether residential proximity to flaring from OGD was associated with shorter gestation and reduced fetal growth in the Eagle Ford Shale of south Texas.

METHODS

We conducted a retrospective cohort study using administrative birth records from 2012 to 2015 (N=23,487) and satellite observations of flaring activity during pregnancy within 5km of maternal residence. Multivariate logistic and linear regression models were used to estimate associations between four outcomes (preterm birth, small-for-gestational age, continuous gestational age, and term birthweight) and exposure to a low (1-9) or high (≥10) number of nightly flare events, as compared with no exposure, while controlling for known maternal risk factors. We also examined associations with the number of oil and gas wells within 5km using data from DrillingInfo (now Enverus).

RESULTS

Exposure to a high number of nightly flare events was associated with a 50% higher odds of preterm birth [odds ratio (OR)=1.50 (95% CI: 1.23, 1.83)] and shorter gestation [mean difference=-1.9 (95% CI: -2.8, -0.9) d] compared with no exposure. Effect estimates were slightly reduced after adjustment for the number of wells within 5km. In stratified models these associations were present only among Hispanic women. Flaring and fetal growth outcomes were not significantly associated. Women exposed to a high number of wells (fourth quartile, ≥27) vs. no wells within 5km had a higher odds of preterm birth [OR=1.31 (95% CI: 1.14, 1.49)], shorter gestation [-1.3 (95% CI: -1.9, -0.8) d], and lower average birthweight [-19.4 (95% CI: -36.7, -2.0) g].

DISCUSSION

Our study suggests exposure to flaring from OGD is associated with an increased risk of preterm birth. Our findings need to be confirmed in other populations. https://doi.org/10.1289/EHP6394.

Geovisualization and Spatial Analysis of Infant Mortality and Preterm Birth in Ohio, 2008-2015: Opportunities to Enhance Spatial Thinking

OBJECTIVES

Geovisualization and spatial analysis are valuable tools for exploring and evaluating the complex social, economic, and environmental interactions that lead to spatial inequalities in health. The objective of this study was to describe spatial patterns of infant mortality and preterm birth in Ohio by using interactive mapping and spatial analysis.

METHODS

We conducted a retrospective cohort study using Ohio vital statistics records from 2008-2015. We geocoded live births and infant deaths by using residential address at birth. We used multivariable logistic regression to adjust spatial and space-time cluster analyses that examined the geographic clustering of infant mortality and preterm birth and changes in spatial distribution over time.

RESULTS

The overall infant mortality rate in Ohio during the study period was 6.55 per 1000 births; of 1 097 507 births, 10.3% (n = 112 552) were preterm. We found significant geographic clustering of both infant mortality and preterm birth centered on large urban areas. However, when known demographic risk factors were taken into account, urban clusters disappeared and, for preterm birth, new rural clusters appeared.

CONCLUSIONS

Although many public health agencies have the capacity to create maps of health outcomes, complex spatial analysis and geovisualization techniques are still challenging for public health practitioners to use and understand. We found that actively engaging policymakers in reviewing results of the cluster analysis improved understanding of the processes driving spatial patterns of birth outcomes in the state.

The spatial modification of the non-linear effects of ambient oxides of nitrogen during pregnancy on birthweight in a South African birth cohort

Birthweight is strongly associated with infant mortality and is a major determinant of infant survival. Several factors such as maternal, environmental, clinical, and social factors influence birthweight, and these vary geographically, including across low, middle, and economically advanced countries. The aim of the study was to investigate the geographical modification of the effect of oxides of nitrogen exposure on birthweight adjusted for clinical and socio-demographic factors. Data for the study was obtained from the Mother and Child in the Environment birth cohort study in Durban, South Africa. Pregnant females were selected from public sector antenatal clinics in low socioeconomic neighborhoods. Land use regression models were used to determine household level antenatal exposure to oxides of nitrogen (NOx). Six hundred and seventy-seven births were analysed, using the geoadditive model with Gaussian distribution and identity link function. The newborns in the cohort had a mean birthweight of 3106.5 g (standard deviation (SD): 538.2 g and the maternal mean age was 26.1 years (SD: 5.7). A spatially modified NOx exposure-related effect on birthweight was found across two geographic regions in Durban. Prenatal exposure to NOx was also found to have a non-linear effect on the birthweight of infants. The study suggested that incorporating spatial variability is important to understand and design appropriate policies to reduce air pollution in order to prevent risks associated with birthweight.

Population Data BC: Supporting population data science in British Columbia

Background

Population Data BC (PopData) was established as a multi-university data and education resource to support training and education, data linkage, and access to individual level, de-identified data for research in a wide variety of areas including human and community development and well-being.

Approach

A combination of deterministic and probabilistic linkage is conducted based on the quality and availability of identifiers for data linkage. PopData utilizes a harmonized data request and approval process for data stewards and researchers to increase efficiency and ease of access to linked data. Researchers access linked data through a secure research environment (SRE) that is equipped with a wide variety of tools for analysis. The SRE also allows for ongoing management and control of data. PopData continues to expand its data holdings and to evolve its services as well as governance and data access process.

Discussion

PopData has provided efficient and cost-effective access to linked data sets for research. After two decades of learning, future planned developments for the organization include, but are not limited to, policies to facilitate programs of research, access to reusable datasets, evaluation and use of new data linkage techniques such as privacy preserving record linkage (PPRL).

Conclusion

PopData continues to maintain and grow the number and type of data holdings available for research. Its existing models support a number of large-scale research projects and demonstrate the benefits of having a third-party data linkage and provisioning center for research purposes. Building further connections with existing data holders and governing bodies will be important to ensure ongoing access to data and changes in policy exist to facilitate access for researchers

A risk-based model to assess environmental justice and coronary heart disease burden from traffic-related air pollutants

BACKGROUND

Communities need to efficiently estimate the burden from specific pollutants and identify those most at risk to make timely informed policy decisions. We developed a risk-based model to estimate the burden of black carbon (BC) and nitrogen dioxide (NO₂) on coronary heart disease (CHD) across environmental justice (EJ) and non-EJ populations in Allegheny County, PA.

METHODS

Exposure estimates in census tracts were modeled via land use regression and analyzed in relation to US Census data. Tracts were ranked into quartiles of exposure (Q1-Q4). A risk-based model for estimating the CHD burden attributed to BC and NO₂ was developed using county health statistics, census tract level exposure estimates, and quantitative effect estimates available in the literature.

RESULTS

For both pollutants, the relative occurrence of EJ tracts (> 20% poverty and/or > 30% non-white minority) in Q2 - Q4 compared to Q1 progressively increased and reached a maximum in Q4. EJ tracts were 4 to 25 times more likely to be in the highest quartile of exposure compared to the lowest quartile for BC and NO₂, respectively. Pollutant-specific risk values (mean [95% CI]) for CHD mortality were higher in EJ tracts (5.49 × 10^- 5 [5.05 × 10^- 5 - 5.92 × 10^- 5]; 5.72 × 10^- 5 [5.44 × 10^- 5 - 6.01 × 10^- 5] for BC and NO₂, respectively) compared to non-EJ tracts (3.94 × 10^- 5 [3.66 × 10^- 5 - 4.23 × 10^- 5]; 3.49 × 10^- 5 [3.27 × 10^- 5 - 3.70 × 10^- 5] for BC and NO₂, respectively). While EJ tracts represented 28% of the county population, they accounted for about 40% of the CHD mortality attributed to each pollutant. EJ tracts are disproportionately skewed toward areas of high exposure and EJ residents bear a greater risk for air pollution-related disease compared to other county residents.

CONCLUSIONS

We have combined a risk-based model with spatially resolved long-term exposure estimates to predict CHD burden from air pollution at the census tract level. It provides quantitative estimates of effects that can be used to assess possible health disparities, track temporal changes, and inform timely local community policy decisions. Such an approach can be further expanded to include other pollutants and adverse health endpoints.

The effect of nitrogen dioxide on low birth weight in women with inflammatory bowel disease: a Norwegian pregnancy cohort study (MoBa)

Background: Adverse birth outcomes are more frequent among mothers with inflammatory bowel diseases (IBDs) than non-IBD mothers. In recent studies, air pollution, such as high concentrations of nitrogen dioxide (NO₂), is reckoned as a risk factor for preterm birth in the general population. In this study, we investigated whether IBD mothers are at higher risk of preterm birth when exposed to NO₂ compared to non-IBD mothers.Methods: We used information from the Norwegian Mother, Father and Child Cohort Study (MoBa). The pregnancy cohort was linked to the Norwegian Medical Birth Registry and air-pollution exposure data available from a subset of the study cohort. The relevant outcome in this study was preterm birth. A total of 16,170 non-IBD and 92 IBD mothers were included in the study.Results: The mean exposure of NO₂ during the pregnancy was similar for IBD and non-IBD mothers, 13.7 (6.9) μg/m³ and 13.6 (4.2) μg/m³, respectively.IBD mothers with higher exposure of NO₂ in the second and third trimester were at significant risk of preterm birth compared to non-IBD mothers [OR = 1.28 (CI 95%: 1.04-1.59) and OR = 1.23 (95% CI: 1.06-1.43), respectively]. The mean NO₂ exposure was significantly higher in IBD mothers with preterm birth than in IBD mothers who delivered at term, at 19.58 (1.57) μg/m³ and 12.89 (6.37) μg/m³, respectively.Conclusions: NO₂ exposure influenced the risk of preterm birth in IBD mothers. Higher risk of preterm birth in IBD was associated with higher exposure of NO₂, suggesting vulnerability of preterm birth in IBD when exposed to NO₂.