Residential traffic exposure and pregnancy-related outcomes: a prospective birth cohort study

Ambient air pollution and hypertensive disorders of pregnancy in Rome

BACKGROUND

Ambient air pollution has been associated with hypertensive disorders of pregnancy (HDP), but few studies rely on assessment of fine-scale variation in air quality, specific subtypes and multi-pollutant exposures.

AIM

To study the impact of long-term exposure to individual and mixture of air pollutants on all and specific subtypes of HDP.

METHODS

We obtained data from 130,470 liveborn singleton pregnacies in Rome during 2014-2019. Spatiotemporal land-use random-forest models at 1 km spatial resolution assigned to the maternal residential addresses were used to estimate the exposure to particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), and ozone (O3).

RESULTS

For PM2.5, PM10 and NO2, there was suggestive evidence of increased risk of preeclampsia (PE, n = 442), but no evidence of increased risk for all subtypes of HDP (n = 2297) and gestational hypertension (GH, n = 1901). For instance, an interquartile range of 7.0 μg/m3 increase in PM2.5 exposure during the first trimester of pregnancy was associated with an odds ratio (OR) of 1.06 (95% confidence interval: 0.81, 1.39) and 1.04 (0.92, 1.17) after adjustment for NO2 and the corresponding results for a 15.7 μg/m3 increase in NO2 after adjustment for PM2.5 were 1.11 (0.92, 1.34) for PE and 0.83 (0.76, 0.90) for HDP. Increased risks for HDP and GH were suggested for O3 in single-pollutant models and for PM after adjustment for NO2, but all other associations were stable or attenuated in two-pollutant models.

CONCLUSIONS

The results of our study suggest that PM2.5, PM10 and NO2 increases the risk of PE and that these effects are robust to adjustment for O3 while the increased risks for GH and HDP suggested for O3 attenuated after adjustment for PM or NO2. Additional studies are needed to evaluate the effects of source-specific component of PM on subtypes as well as all types of HDP which would help to target preventive actions.

Effects of Air Pollution Exposure during Preconception and Pregnancy on Gestational Diabetes Mellitus

This study aimed to investigate the association between air pollution and gestational diabetes mellitus (GDM) in small- and medium-sized cities, identify sensitive periods and major pollutants, and explore the effects of air pollution on different populations. A total of 9820 women who delivered in Handan Maternal and Child Health Hospital in the Hebei Province from February 2018 to July 2020 were included in the study. Logistic regression and principal component logistic regression models were used to assess the effects of air pollution exposure during preconception and pregnancy on GDM risk and the differences in the effects across populations. The results suggested that each 20 μg/m3 increase in PM2.5 and PM10 exposure during preconception and pregnancy significantly increased the risk of GDM, and a 10 μg/m3 increase in NO2 exposure during pregnancy was also associated with the risk of GDM. In a subgroup analysis, pregnant women aged 30-35 years, nulliparous women, and those with less than a bachelor's education were the most sensitive groups. This study provides evidence for an association between air pollution and the prevalence of GDM, with PM2.5, PM10, and NO2 as risk factors for GDM.

Ambient air pollution and gestational diabetes mellitus: An updated systematic review and meta-analysis

OBJECTIVE

We aimed to evaluate the relationship between the composition of particulate matter (PM) and gestational diabetes mellitus (GDM) by a comprehensively review of epidemiological studies.

METHODS

We systematically identified cohort studies related to air pollution and GDM risk before February 8, 2023 from six databases (PubMed, Embase, Web of Science Core Collection, China National Knowledge Infrastructure, Wanfang Data Knowledge Service Platform and Chongqing VIP Chinese Science and Technology Periodical databases). We calculated the relative risk (RR) and its 95% confidence intervals (CIs) to assess the overall effect by using a random effects model.

RESULTS

This meta-analysis of 31 eligible cohort studies showed that exposure to PM_2.5, PM₁₀, SO₂, and NO₂ was associated with a significantly increased risk of GDM, especially in preconception and first trimester. Analysis of the components of PM_2.5 found that the risk of GDM was strongly linked to black carbon (BC) and nitrates (NO₃^-). Specifically, BC exposure in the second trimester and NO₃^- exposure in the first trimester elevated the risk of GDM, with the RR of 1.128 (1.032-1.231) and 1.128 (1.032-1.231), respectively. The stratified analysis showed stronger correlations of GDM risk with higher levels of pollutants in Asia, except for PM_2.5 and BC, which suggested that the specific composition of particulate pollutants had a greater effect on the exposure-outcome association than the concentration.

CONCLUSIONS

Our study found that ambient air pollutant is a critical factor for GDM and further studies on specific particulate matter components should be considered in the future.

Early pregnancy particulate matter exposure, pre-pregnancy adiposity and risk of gestational diabetes mellitus in Finnish primiparous women: An observational cohort study

AIMS

To evaluate the association between the exposure of particulate matter with an aerodynamic diameter of ≤ 2.5μm (PM_2.5) and with an aerodynamic diameter of ≤ 10μm (PM₁₀) over the first trimester and the risk of gestational diabetes mellitus (GDM), and to assess whether maternal pre-pregnancy body mass index (BMI) modified the GDM risk.

METHODS

All Finnish primiparous women without previously diagnosed diabetes who delivered between 2009 and 2015 in the city of Vantaa, Finland, composed the study cohort (N = 6189). Diagnosis of GDM was based on a standard 75 g 2-hour oral glucose tolerance test. The average daily concentration of PM_2.5 and PM₁₀ over the first trimester was calculated individually for each woman. The relationship between exposure of PM_2.5 and PM₁₀ and GDM was analyzed with logistic models.

RESULTS

No association was observed between the average daily concentrations of PM_2.5 and PM₁₀ over the first trimester and the GDM risk. When simultaneously taking BMI and PM₁₀ into account both mean daily PM₁₀ concentration (p = 0.047) and pre-pregnancy BMI (p = 0.016) increased GDM risk independently and an interaction (p = 0.013) was observed between PM₁₀ concentration and pre-pregnancy BMI.

CONCLUSIONS

Even globally low PM₁₀ exposure level together with elevated maternal pre-pregnancy BMI seems to increase the GDM risk.

Association between air pollution exposure and gestational diabetes mellitus in pregnant women: a retrospective cohort study

The global prevalence of gestational diabetes mellitus (GDM) is increasing annually, and previous research reports on the relationship between exposure to air pollutants and GDM are not completely consistent. We investigated the association between air pollutant exposure and GDM in pregnant women in a retrospective cohort study in Guangzhou. We found that in the first trimester, exposure to PM_2.5 and CO showed a significant association with GDM. In the second trimester, exposure to PM₁₀ was significantly associated with GDM. In the third trimester, exposure to PM_2.5, PM₁₀, NO₂, SO₂, and CO at IQR4 (odds ratio [OR] = 1.271, 95% confidence interval [CI]: 1.179-1.370; OR = 1.283, 95% CI: 1.191-1.383; OR = 1.230, 95% CI: 1.145-1.322; OR = 1.408, 95% CI: 1.303-1.522; OR = 1.150, 95% CI: 1.067-1.240, respectively) compared with IQR1 was positively associated with GDM. However, exposure to NO₂ was negatively associated with GDM in the first and second trimesters, and O₃ was negatively associated with GDM in the second and third trimesters. We found that the correlation between air pollutants and GDM in different trimesters of pregnancy was not completely consistent in this retrospective cohort study. During pregnancy, there may be an interaction between air pollutant exposure and other factors, such as pregnant women's age, occupation, anemia status, pregnancy-induced hypertension status, and pregnancy season.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Modeling spatial variation of gaseous air pollutants and particulate matters in a Metropolitan area using mobile monitoring data

Geo-statistical models have been applied to assess fine-scale air pollution exposures in epidemiological studies. Many of the models were developed for criteria air pollutants rather than others that have not been regulated (e.g., ultrafine particles, black carbon, and benzene) which may also be harmful to human health. We aim to develop spatial models for regulated and non-regulated air pollutants using 6 algorithms and compare their prediction performances. A mobile platform with fast-response monitors was used to measure gaseous air pollutants (nitrogen dioxides, carbon monoxide, sulfur dioxides, ozone, benzene, toluene, methanol) and particulate matters (black carbon, surface area, count- and volume-concentrations of ultrafine particles) in Beijing, China for 30 days from July to October 2008. Mobile monitoring data for model building were spatially aggregated into 130 road segments of approximately 600-m interval on the sampling routes after temporal adjustment of background concentrations. The best models for the air pollutants were dominated by traffic variables, which explained more than 60% of the spatial variations (range: 0.61 for methanol to 0.88 for ozone) based on the highest cross-validation R² and the lowest root mean square error among different algorithms. Amongst the 6 algorithms, the spatial models using partial least squares regression (PLS, a dimension reduction algorithm) and random forest (RF, a machine learning algorithm) algorithms outperformed the models with other algorithms. Exposure predictions from the best models varied substantially with distinct spatial patterns between the air pollutants. Predictions with multiple modeling algorithms were moderately correlated with each other for the same pollutant at the fine-scale grids across the city. Exposure models, especially based on PLS and RF algorithms, captured the spatial variation of short-term average concentrations, had adequate predictive validity, and could be applied to assess toxic air pollutant exposures in human health studies.

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.

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.

The relationship between the neighborhood built and social environment and hypertensive disorders of pregnancy: A scoping review

BACKGROUND

Theory and limited empirical research suggest that the neighborhood environment influences maternal health outcomes. The goal of this scoping review is to summarize extant research considering the impact of the built and social environment of resident neighborhood on hypertensive disorders of pregnancy (HDP) globally.

METHODS

We performed a systematic search of the literature using four databases, PubMed, Web of Science, CINAHL, and Embase on July 15, 2020. We excluded articles not in English, that did not consider one or more HDP as a primary or secondary outcome, and that did not include an element of the neighborhood built or social environment as an exposure. We applied a modified version of the Effective Public Health Practice Project Quality Assessment Tool for Quantitative Studies to evaluate quality of included studies.

RESULTS

Our search identified 11,385 unique abstracts for screening. Following exclusions, we included 64 articles in the final review. The majority of articles measured an element of the built environment (70.3% (44)), most commonly traffic-related air pollution (42.2% (27)). A third of articles (31.3% (20)) considered an element of the neighborhood social environment, most commonly neighborhood deprivation (10.9% (7)). Global quality ratings were mostly moderate (29.7% (19)) or weak (68.8% (44)), primarily due to inattention to neighborhood-level confounding.

CONCLUSION

Critical gaps remain in understanding how the resident neighborhood may impact HDP. Future research should focus on designing high-quality studies incorporating elements of both the built and social environment to holistically understand how context may impact maternal health.

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.

Preconception air pollution exposure and glucose tolerance in healthy pregnant women in a middle-income country

BACKGROUND

Preconception exposure to air pollution has been associated with glucose tolerance during pregnancy. However, the evidence in low and middle-income countries (LMICs) is under debate yet. Therefore, this study aimed to assess the relationship between exposure to ambient particulate matter (PM) and traffic indicators with glucose tolerance in healthy pregnant women in Sabzevar, Iran (2019).

METHODS

Two-hundred and fifty healthy pregnant women with singleton pregnancies and 24-26 weeks of gestations participated in our study. Land use regression (LUR) models were applied to estimate the annual mean of PM₁, PM_2.5 and PM₁₀ at the residential address. Traffic indicators, including proximity of women to major roads as well as total streets length in 100, 300 and 500 m buffers around the home were calculated using the street map of Sabzevar. The oral glucose tolerance test (OGTT) was used to assess glucose tolerance during pregnancy. Multiple linear regression adjusted for relevant covariates was used to estimate the association of fasting blood glucose (FBG), 1-h and 2-h post-load glucose with PMs and traffic indicators.

RESULTS

Exposure to PM₁, PM_2.5 and PM₁₀ was significantly associated with higher FBG concentration. Higher total streets length in a 100 m buffer was associated with higher FBG and 1-h glucose concentrations. An interquartile range (IQR) increase in proximity to major roads was associated with a decrease of - 3.29 mg/dL (95% confidence interval (CI): - 4.35, - 2.23, P-value < 0.01) in FBG level and - 3.65 mg/dL (95% CI, - 7.01, - 0.28, P-value = 0.03) decrease in 1-h post-load glucose.

CONCLUSION

We found that higher preconception exposure to air pollution was associated with higher FBG and 1-h glucose concentrations during pregnancy.

Vehicular traffic density and cognitive performance in the ELSA-Brasil study

BACKGROUND

Despite the knowledge about the deleterious effects of air pollutants and their influence on mortality and morbidity due to respiratory and cardiovascular diseases, little is known about the relationship between atmospheric pollutants and neurological diseases. Recently, studies from high-income countries have suggested an association between exposures to air pollutants with cognitive impairment. Thus, we investigated the association of air pollution with cognitive performance in the participants of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil).

METHODS

Cognitive function was evaluated using the word list, the verbal fluency, and the trail making tests (TMT). Pollutant exposure was evaluated indirectly using the distance-weighted traffic density (DWTD) of participants' residence and workplace. We investigated the cross-sectional association between DWTD and cognitive test scores using adjusted linear regression models for sociodemographic and clinical variables.

RESULTS

3050 were included (mean age = 52.1 ± 9.2 years old, 56.5% women, and 63.6% white). In the simple linear regression models, participants in the higher tertile of combined DWTD (residence and workplace) presented better cognitive performance in all tests when compared to participants in the lower tertile. The DWTD was not associated with cognitive performance in adjusted linear models especially when adjusted for socioeconomic variables (age, sex, education, and race). We found similar results when we investigated the association of cognitive performance with DTWD near participants' workplace and residence separately.

CONCLUSION

Air pollutants were not associated with worse cognitive performance in a large sample of middle-aged and older adults.

Ambient particle radioactivity and gestational diabetes: A cohort study of more than 1 million pregnant women in Massachusetts, USA

BACKGROUND

Exposure to ionizing radiation increases the risk of chronic metabolic disorders such as insulin resistance and type 2 diabetes. Internal ionizing radiation from inhaled radioactive aerosol may contribute to the associations between fine particulate matter (PM_2.5) and gestational diabetes mellitus (GDM).

METHODS

We used the Massachusetts Registry of Vital Records to study 1,061,937 pregnant women from 2001 to 2015 with a singleton pregnancy without pre-existing diabetes. Gross β activity measured by seven monitors of the U.S. Environmental Protection Agency's RadNet monitoring network was utilized to represent ambient particle radioactivity (PR). We obtained GDM status from birth certificates and used logistic regression analyses adjusted for socio-demographics, maternal comorbidities, PM_2.5, temperature and relative humidity. We also examined effect modification by smoking habits.

RESULTS

Ambient particle radioactivity exposure during first and second trimester of pregnancy was associated with higher odds of GDM (OR: 1.18 (95% CI 1.10 to 1.22). Controlling for PM_2.5 did not substantially change the effects of PR on GDM. In women that reported being former or current smokers, the association between PR and GDM was null. In the full cohort, the overall effect of PM_2.5 on GDM without adjusting for PR was not significant.

CONCLUSION

This is the first population-based study to examine the association between particle radioactivity and gestational diabetes mellitus - one of the most common pregnancy-related diseases with lifelong effects for the mother and the fetus. This finding has important public health policy implications because it enhances our understanding about the toxicity of PR, a modifiable risk factor, which to date, has been considered only as an indoor and occupational air quality risk.

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.

Predicting Traffic-Related Air Pollution Using Feature Extraction from Built Environment Images

This study develops a set of algorithms to extract built environment features from Google aerial and street view images, reflecting the microcharacteristics of an urban location as well as the different functions of buildings. These features were used to train a Bayesian regularized artificial neural network (BRANN) model to predict near-road air quality based on measurements of ultrafine particles (UFPs) and black carbon (BC) in Toronto, Canada. The resulting models [adjusted R² of 75.87 and 79.10% for UFP and BC and root mean squared error (RMSE) of 21,800 part/cm³ and 1300 ng/m³ for UFP and BC] were compared with similar ANN models developed using the same predictors, but extracted from traditional geographic information system (GIS) databases [adjusted R² of 58.74 and 64.21% for UFP and BC and RMSE values of 23,000 part/cm³ and 1600 ng/m³ for UFP and BC]. The models based on feature extraction exhibited higher predictive power, thus highlighting the greater accuracy of the proposed methods compared to GIS layers that are solely based on aerial images. A comparison with other neural network approaches as well as with a traditional land-use regression model demonstrates the strength of the BRANN model for spatial interpolation of air quality.

Ambient air pollution and gestational diabetes mellitus: A review of evidence from biological mechanisms to population epidemiology

Gestational diabetes mellitus (GDM) is a serious complication of pregnancy that could cause adverse health effects on both mothers and fetuses, and its prevalence has been increasing worldwide. Experimental and epidemiological studies suggest that air pollution may be an important risk factor of GDM, but conclusions are inconsistent. To provide a comprehensive overview of ambient air pollution on GDM, we summarized existing evidence concerning biological linkages between maternal exposure to air pollutants and GDM based on mechanism studies. We also performed a quantitative meta-analysis based on human epidemiological studies by searching English databases (Pubmed, Web of Science and Embase) and Chinese databases (Wanfang, CNKI). As a result, the limited mechanism studies indicated that β-cell dysfunction, neurohormonal disturbance, inflammation, oxidative stress, imbalance of gut microbiome and insulin resistance may be involved in air pollution-GDM relationship, but few studies were performed to explore the direct biological linkage. Additionally, a total of 13 epidemiological studies were included in the meta-analysis, and the air pollutants considered included PM_2.5, PM₁₀, SO₂, NO₂ and O₃. Most studies were retrospective and mainly conducted in developed regions. The results of meta-analysis indicated that maternal first trimester exposure to SO₂ increased the risk of GDM (standardized odds ratio (OR) = 1.392, 95% confidence intervals (CI): 1.010, 1.773), while pre-pregnancy O₃ exposure was inversely associated with GDM risk (standardized OR = 0.981, 95% CI: 0.977, 0.985). No significant effects were observed for PM_2.5, PM₁₀ and NO₂. In conclusion, additional mechanism studies on the molecular level are needed to provide persuasive rationale underlying the air pollution-GDM relationship. Moreover, other important risk factors of GDM, including maternal lifestyle and road traffic noise exposure that may modify the air pollution-GDM relationship should be considered in future epidemiological studies. More prospective cohort studies are also warranted in developing countries with high levels of air pollution.

Relationship betweentemporal distribution of air pollution exposure and glucose homeostasis during pregnancy

BACKGROUND

Mounting evidence has demonstrated that air pollution exposure is associated with the increased prevalence of gestational diabetes mellitus (GDM). However, the long-term exposure effect and the time window of the maximum effect of these air pollutants on GDM and glucose homeostasis during pregnancy are unclear.

METHODS

We conducted this study on 5427 nondiabetic pregnant women who were admitted from three hospitals in Hefei City, China, between 2015 and 2018. The data regarding the average exposure to particulate matter (PM), sulfur dioxide (SO₂), and ozone (O₃) were estimated in a fixed monitoring station in Hefei. We used logistic regression and multiple linear regression to assess the effects of air pollutants on GDM and glucose homeostasis.

RESULTS

Of the 5427 participants, 1119 (20.6%) had GDM. We found prepregnancy exposure to air pollutants was associated with the risk of GDM in the single pollutant model [odds and 95% confidence interval (CI) of GDM for an interquartile range (IQR) increase was 1.24 (1.06-1.45) for PM_2.5, 1.42 (1.26-1.59) for PM₁₀, 1.21 (1.10-1.33) for SO₂ and1.19 (1.08-1.31) for O₃]. The risk of GDM before pregnancy was higher with long-term exposure to high-concentration pollutants compared with the risk in pregnant women who were not exposed to high-concentration pollutants (χ² = 41.52, p for trend <0.0001); the ORs and 95% CI values for the exposure times of 1, 2, and 3 months were 1.28 (0.96-1.72), 1.52 (1.06-2.19), and 1.69 (1.11-2.57), respectively. The results showed a positive effect of exposure to higher-concentration air pollutants 1 year before pregnancy on glucose homeostasis during pregnancy. The time windows of the maximum effect of PM_2.5, PM₁₀, SO₂, and O₃ on GDM were different. The time windows of the maximum effect of PM_2.5, PM₁₀, and SO₂ were 6 months, 5 months, and 1 month before the last menstrual period (LMP) and 3 months after the LMP, respectively. The time windows of the maximum effect of air pollution on glucose homeostasis indicators from the 2-h 75-g oral glucose tolerance test were similar to the abovementioned results.

CONCLUSIONS

Prepregnancy long-term air pollution exposure was associated with a higher risk of developing GDM by affecting glucose metabolism. The time window of the maximum effect of PM on GDM and glucose metabolism indicators was observed earlier than that of SO₂ and O₃.

Maternal Exposure to Ambient Air Pollution and Pregnancy Complications in Victoria, Australia

The relationship between maternal exposure to ambient air pollution and pregnancy complications is not well characterized. We aimed to explore the relationship between maternal exposure to ambient nitrogen dioxide (NO₂) and fine particulate matter (PM_2.5) and hypertensive disorders of pregnancy, gestational diabetes mellitus (GDM) and placental abruption. Using administrative data, we defined a state-wide cohort of singleton pregnancies born between 1 March 2012 and 31 December 2015 in Victoria, Australia. Annual average NO₂ and PM_2.5 was assigned to maternal residence at the time of birth. 285,594 singleton pregnancies were included. An IQR increase in NO₂ (3.9 ppb) was associated with reduced likelihood of hypertensive disorders of pregnancy (RR 0.89; 95%CI 0.86, 0.91), GDM (RR 0.92; 95%CI 0.90, 0.94) and placental abruption (RR 0.81; 95%CI 0.69, 0.95). Mixed observations and smaller effect sizes were observed for IQR increases in PM_2.5 (1.3 µg/m³) and pregnancy complications; reduced likelihood of hypertensive disorders of pregnancy (RR 0.95; 95%CI 0.93, 0.97), increased likelihood of GDM (RR 1.02; 95%CI 1.00, 1.03) and no relationship for placental abruption. In this exploratory study using an annual metric of exposure, findings were largely inconsistent with a priori expectations and further research involving temporally resolved exposure estimates are required.

Air pollution and gestational diabetes mellitus: evidence from cohort studies

Exposure to different air pollutants has been linked to type 2 diabetes mellitus, but the evidence for the association between air pollutants and gestational diabetes mellitus (GDM) has not been systematically evaluated. We systematically retrieved relevant studies from PubMed, Embase, and the Web of Science, and performed stratified analyses and regression analyses. Thirteen studies were analyzed, comprising 1 547 154 individuals from nine retrospective studies, three prospective studies, and one case-control study. Increased exposure to particulate matter ≤2.5 µm in diameter (PM_2.5) was not associated with the increased risk of GDM (adjusted OR 1.03, 95% CI 0.99 to 1.06). However, subgroup analysis showed positive correlation of PM_2.5 exposure in the second trimester with an increased risk of GDM (combined OR 1.07, 95% CI 1.00 to 1.13). Among pollutants other than PM_2.5, significant association between GDM and nitrogen dioxide (NO₂) (OR 1.05, 95% CI 1.01 to 1.10), nitrogen oxide (NO_x) (OR 1.03, 95% CI 1.01 to 1.05), and sulfur dioxide (SO₂) (OR 1.09, 95% CI 1.03 to 1.15) was noted. There was no significant association between exposure to black carbon or ozone or carbon monoxide or particulate matter ≤10 µm in diameter and GDM. Thus, systematic review of existing evidence demonstrated association of exposure to NO₂, NO_x, and SO₂, and the second trimester exposure of PM_2.5 with the increased risk of GDM. Caution may be exercised while deriving conclusions from existing evidence base because of the limited number and the observational nature of studies.

Prenatal exposure to traffic and ambient air pollution and infant weight and adiposity: The Healthy Start study

BACKGROUND

Prenatal exposures to ambient air pollution and traffic have been associated with adverse birth outcomes, and may also lead to an increased risk of obesity. Obesity risk may be reflected in changes in body composition in infancy.

OBJECTIVE

To estimate associations between prenatal ambient air pollution and traffic exposure, and infant weight and adiposity in a Colorado-based prospective cohort study.

METHODS

Participants were 1125 mother-infant pairs with term births. Birth weight was recorded from medical records and body composition measures (fat mass, fat-free mass, and adiposity [percent fat mass]) were evaluated via air displacement plethysmography at birth (n = 951) and at ~5 months (n = 574). Maternal residential address was used to calculate distance to nearest roadway, traffic density, and ambient concentrations of fine particulate matter (PM_2.5) and ozone (O₃) via inverse-distance weighted interpolation of stationary monitoring data, averaged by trimester and throughout pregnancy. Adjusted linear regression models estimated associations between exposures and infant weight and body composition.

RESULTS

Participants were urban residents and diverse in race/ethnicity and socioeconomic status. Average ambient air pollutant concentrations were generally low; the median, interquartile range (IQR), and range of third trimester concentrations were 7.3 μg/m³ (IQR: 1.3, range: 3.3-12.7) for PM_2.5 and 46.3 ppb (IQR: 18.4, range: 21.7-63.2) for 8-h maximum O_3. Overall there were few associations between traffic and air pollution exposures and infant outcomes. Third trimester O₃ was associated with greater adiposity at follow-up (2.2% per IQR, 95% CI 0.1, 4.3), and with greater rates of change in fat mass (1.8 g/day, 95% CI 0.5, 3.2) and adiposity (2.1%/100 days, 95% CI 0.4, 3.7) from birth to follow-up.

CONCLUSIONS

We found limited evidence of an association between prenatal traffic and ambient air pollution exposure and infant body composition. Suggestive associations between prenatal ozone exposure and early postnatal changes in body composition merit further investigation.

Human epidemiological evidence about the association between air pollution exposure and gestational diabetes mellitus: Systematic review and meta-analysis

BACKGROUND

Previous studies have shown that ambient air pollution exposure can increase the risk of type 2 diabetes mellitus (T2DM) significantly. In consideration of the common underlying pathophysiologic mechanisms, exposure to air pollution may also increase the risk of gestational diabetes mellitus (GDM), but the current evidence was inconsistent and has not well been systematically reviewed. Our goal was to perform a systematic review and meta-analysis assessing the association between air pollution exposure and GDM.

METHODS

An extensive literature search was conducted in selected electronic databases for related human epidemiological studies published in English language. Summary effect estimates were calculated using random-effect models for a) risk per unit increase in continuous air pollutant concentration and b) risk of high versus low exposure level in individual study if each exposure that had been examined in ≥2 studies. We evaluated the heterogeneity using Cochran's Q test and quantified it by I² statistic. Publication bias was also evaluated through the funnel plot when sufficient number of studies are available.

RESULTS

A total of 11 studies evaluating the association between GDM and exposure to air pollution were identified finally. The summary odds ratio (OR) for incidence of GDM following a 10 μg/m³ increase in PM_2.5 exposure during the second trimester was 1.04 (95% Confidence Interval (CI): 1.01, 1.09) and in NO_x during the first trimester was 1.03 (95%CI: 1.00, 1.07) per 10 ppb increase, while for high versus low SO₂ exposure during the second trimester was 1.25 (95%CI: 1.02, 1.53). High heterogeneity among study-specific results in majority of the analyses were observed, and attributed to different exposure assessment methods, populations, study locations, and covariates adjustment. Publication bias cannot be excluded because of the inclusion of small number of studies.

CONCLUSIONS

The present study supports the evidence that air pollution exposure increases the risk the GDM, albeit the existence of high heterogeneity. Further studies are necessary to elaborate the suggestive associations. These results are of public health significance since worsening air pollution in developing countries has been expected to increase the risk of GDM development.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Associations of gestational diabetes mellitus with residential air pollution exposure in a large Southern California pregnancy cohort

BACKGROUND

Studies of effects of air pollution on gestational diabetes mellitus (GDM) have not been consistent, and there has been little investigation of effects of exposure preceding pregnancy. In previous studies, the temporal relationship between exposure and GDM onset has been difficult to establish.

METHODS

Data were obtained for 239,574 pregnancies between 1999 and 2009 in a population-based health care system with comprehensive electronic medical records. Concentrations of ambient nitrogen dioxide (NO₂), particulate matter (PM) ≤2.5 μm in aerodynamic diameter (PM_2.5) and ≤10 μm (PM₁₀), and ozone (O₃) during preconception and the first trimester of pregnancy at the residential birth address were estimated from regulatory air monitoring stations. Odds ratios (ORs) of GDM diagnosed in the second and third trimesters in association with pollutant exposure were estimated using generalized estimating equation models adjusted for birth year, medical center service areas, maternal age, race/ethnicity, education, census-tract household income, and parity.

RESULTS

In single-pollutant models, preconception NO₂ was associated with increased risk of GDM (OR = 1.10 per 10.4 ppb, 95% confidence interval [CI]: 1.07, 1.13). First trimester NO₂ was weakly associated with GDM, and this was not statistically significant (OR = 1.02 per 10.4 ppb, 95% CI: 0.99, 1.05). Preconception NO₂ associations were robust in multi-pollutant models adjusted for first trimester NO₂ with another co-pollutant from both exposure windows. In single-pollutant models, preconception PM_2.5 and PM₁₀ associations were associated with increased risk of GDM (OR = 1.04 per 6.5 μg/m³, 95% CI: 1.01, 1.06; OR = 1.03 per 16.1 μg/m³, 95% CI: 1.00, 1.06, respectively), but these effect estimates were not robust to adjustment for other pollutants. In single-pollutant models, preconception and first trimester O₃ were associated with reduced risk of GDM (OR = 0.94 per 15.7 ppb, 95% CI: 0.92, 0.95; OR = 0.95 per 15.7 ppb, 95% CI: 0.94, 0.97), associations that were robust to adjustment for co-pollutants.

CONCLUSIONS

Maternal exposure to NO₂ during the preconception trimester may increase risk of GDM.

Ambient air pollution during pregnancy and risk of gestational diabetes in New York City

BACKGROUND

Emerging evidence suggests a potential association between ambient air pollution and risk of gestational diabetes mellitus (GDM), but results have been inconsistent. Accordingly, we assessed the associations between ambient fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) levels with risk of GDM.

METHODS

Using linked data from birth certificates, hospital discharge diagnoses, and air pollution estimates informed by the New York City Community Air Survey, we fit conditional logistic regression models to evaluate the association between residential levels of PM_2.5 and NO₂ with risk of GDM among 256,372 singleton live births of non-smoking mothers in New York City born 2008-2010, adjusting for sociodemographic factors and stratified on zip code of maternal address.

RESULTS

GDM was identified in 17,065 women, yielding a risk of GDM in the study sample of 67 per 1000 deliveries. In single pollutant models, 1st and 2nd trimester PM_2.5 was associated with a lower and higher risk of GDM, respectively. In models mutually adjusting for PM_2.5 levels in both trimesters, GDM was associated with PM_2.5 levels in the 2nd trimester (OR: 1.06, 95% CI: 1.02, 1.10 per interquartile range increase in PM_2.5), but not the 1st trimester (OR: 0.99, 95% CI: 0.96, 1.02). Conversely, GDM was associated with NO₂ during the 1st trimester (OR: 1.05, 95% CI: 1.01, 1.09), but not the 2nd trimester (OR: 1.02, 95% CI: 0.98, 1.06). The positive associations between pollutants and GDM were robust to different model specifications. PM_2.5 in the 2nd trimester was more strongly associated with GDM among mothers who were aged <35 years and not Medicaid recipients. NO₂ in the 1st trimester was more strongly associated with GDM among overweight and parous women.

CONCLUSIONS

In this large cohort of singleton births in New York City, NO₂ in the 1st trimester and PM_2.5 in the 2nd trimester were associated with higher odds of GDM, while 1st trimester PM_2.5 was weakly and inconsistently associated with lower odds of GDM.

Traffic-related Air Pollution and Pregnancy Loss

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Preeclampsia and Hypertension During Pregnancy in Areas with Relatively Low Levels of Traffic Air Pollution

Objectives Air pollution exposure may contribute to the development of preeclampsia and hypertension during pregnancy. However, the evidence for such a relation is still limited. We investigated the associations between exposure for moderate to low levels of air pollution during pregnancy and preeclampsia and gestational hypertension in selected urban and county areas of Norway. Methods This study used a sub-group of 17,533 women in the Norwegian Mother and Child Cohort Study. Air pollution levels at residential addresses were estimated using land use regression models and back-extrapolated to the period of each pregnancy. Information on preeclampsia and gestational hypertension were obtained from the Medical Birth Registry of Norway and information on lifestyle factors was collected from questionnaires completed by the women during pregnancy. Results Moderate mean levels of NO₂ (13.6 ± 6.9 µg/m³) at residential address during pregnancy were not associated with preeclampsia and pregnancy hypertension. We found no statistically significant associations per 10 µg/m³ change in NO₂ exposure and preeclampsia (adjusted OR 0.89, 95% CI 0.74, 1.08) or hypertension during pregnancy (adjusted OR 0.91, 95% CI 0.78, 1.06). Conclusions for Practice In this large Norwegian pregnancy cohort, we found no statistically significant associations for moderate to low levels of pregnancy NO₂ exposure and preeclampsia or hypertension during pregnancy.

Association between air pollution and type 2 diabetes: an updated review of the literature

Air pollution and type 2 diabetes mellitus (T2DM) are critical public health issues worldwide. A large number of epidemiological studies have highlighted the adverse effects of air pollution on diabetes, and include risk profiles for different exposure durations, study design types, subgroup populations, and effects of air pollution components. We researched PubMed, Google Scholar, and Web of Science to identify studies on the association between air pollution and T2DM from January 2009 to January 2019. The aim of this review is to provide a brief overview of epidemiological and experimental studies on air pollution associated with T2DM from the latest research, which may provide practical information about this relationship and possible mechanisms. Current cumulative evidence appears to suggest that T2DM-related biomarkers increase with increasing exposure duration and concentration of air pollutants. The chemical constituents of the air pollutant mixture may affect T2DM to varying degrees. The suggested mechanisms whereby air pollutants induce T2DM include increased inflammation, oxidative stress, and endoplasmic reticulum stress.

Air pollution, land use, and complications of pregnancy

BACKGROUND

Mounting evidence suggests that the natural and built environment can affect human health, but relatively few studies have considered links between features of the residential natural and built environment other than air pollution and complications of pregnancy.

OBJECTIVES

To quantify the impact of features of the maternal residential natural and built environments on risk of gestational diabetes mellitus (GDM), gestational hypertension and preeclampsia among 61,640 women who delivered at a single hospital in Rhode Island between 2002 and 2012.

METHODS

We estimated residential levels of ambient fine particulate matter (PM_2.5) and black carbon (BC) using spatiotemporal models, neighborhood green space using remote sensing and proximity to recreational facilities, and neighborhood blue space using distance to coastal and fresh water. We used logistic regression to separately estimate the association between each feature and GDM, gestational hypertension, and preeclampsia, adjusting for individual and neighborhood markers of socioeconomic status.

RESULTS

GDM, gestational hypertension, and preeclampsia were diagnosed in 8.0%, 5.0%, and 3.6% of women, respectively. We found 2nd trimester PM_2.5 (OR = 1.08, 95% CI: 1.00, 1.15 per interquartile range increase in PM_2.5) and living close to a major roadway (1.09, 95% CI: 1.00, 1.19) were associated with higher odds of GDM, while living <1 km from the coast was associated with lower odds of GDM (0.87, 95% CI: 0.78, 0.96). Living <500 m from a recreational facility was associated with lower odds of gestational hypertension (0.89, 95% CI: 0.80, 0.99). None of these features were associated with odds of preeclampsia. Results were qualitatively similar in mutually-adjusted models and sensitivity analyses.

CONCLUSIONS

In this small coastal US state, risk of GDM was positively associated with PM_2.5 and proximity to busy roadways, and negatively associated with proximity to blue space, highlighting the importance of the natural and built environment to maternal health.

The association of traffic-related air and noise pollution with maternal blood pressure and hypertensive disorders of pregnancy in the HOME study cohort

Traffic-related air and noise pollution may increase the risk for cardiovascular disorders, especially among susceptible populations like pregnant women. The objective of this study was to evaluate the association of exposure to traffic-related air pollution and traffic noise with blood pressure in pregnant women. We extracted systolic blood pressure (SBP) and diastolic blood pressure (DBP) at ≥20 weeks gestation, as well as hypertensive disorders of pregnancy from medical records in the HOME Study, a prospective pregnancy and birth cohort from Cincinnati, OH (n = 370). We estimated exposure to elemental carbon attributable to traffic (ECAT),1 a marker of traffic-related air pollution, at women's residences at ~20 weeks gestation using a validated land use regression model and traffic noise using a publicly available transportation noise model. We used linear mixed models and modified Poisson regression adjusted for covariates to examine associations of ECAT and traffic noise with blood pressure and hypertensive disorders of pregnancy risk, respectively. In adjusted models, we found a 1.6 (95% CI = 0.02, 3.3; p = 0.048) mm Hg increase in SBP associated with an interquartile range increase in ECAT concentration; the association was stronger after adjusting for traffic noise (1.9 mm Hg, 95% = 0.1, 3.7; p = 0.035). ECAT concentrations were not significantly associated with DBP or hypertensive disorders of pregnancy, and traffic noise was not associated with SBP, DBP, or hypertensive disorders of pregnancy. There was no evidence of a joint effect of traffic noise and ECAT on any outcome. In this cohort, higher residential traffic-related air pollution exposure at ~20 weeks gestation was associated with higher SBP in late pregnancy. It is important for future studies of traffic-related air or noise pollution to jointly consider both exposures and neighborhood characteristics given their correlation and potential cumulative impact on cardiovascular health.

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.

Environmental risk factors associated with low birth weight: The case study of the Haifa Bay Area in Israel

BACKGROUND

Low birth weight (LBW) is known to be associated with infant mortality and postnatal health complications. Previous studies revealed strong relationships between LBW rate and several socio-demographic factors, including ethnicity, maternal age, and family income. However, studies of association between LBW rate and environmental risk factors remain infrequent.

STUDY METHODS

We retrieved a geo-referenced data set, containing 7216 individual records of children born in 2015 in the Haifa Bay Area in Israel. Using this dataset, we analysed factors affecting LBW prevalence by applying two alternative techniques: analysis of LBW rates in small census area (SCAs) and more recently developed double kernel density (DKD) relative risk (RR) estimates.

RESULTS

In the SCA models, LBW rate was found to be associated with proximity to petrochemical industries (B=-0.26, 95%CI=-0.30, -0.22), road density (B=0.05, 95%CI=0.02, 0.08), distance to the seashore (B=0.17, 95%CI=0.14, 0.22), PM_2.5 (B=0.06, 95%CI=0.04, 0.09) and NO_x (B=0.10, 95%CI=0.06, 0.13) exposure estimates. Although similar factors emerged in the DKD models as well, in most cases, the effects of these factors in the latter models were found to be stronger: proximity to petrochemical industries (B=-0.48, 95%CI= -0.51, -0.30), road density (B=0.05, 95%CI=0.02, 0.08), distance to the seashore (B=0.24, 95%CI=0.21, 0.27), PM_2.5 (B=0.08, 95%CI=0.05, 0.10) and NO_x (B=0.20, 95%CI=0.17, 0.23) exposure estimates. In addition, elevation above the sea level was found to be statistically significant in spatial dependence models estimated for both DKD and SCA rates (P < 0.01).

CONCLUSION

The analysis revealed an excess LBW rate in residential areas located close to petrochemical industries and a protective effect of seashore proximity and elevation above the sea level on the LBW rate. We attribute the latter finding to the moderating effect of elevated seashore locations on outdoor temperatures during the hot summer season.

Chemical and non-chemical stressors affecting childhood obesity: a systematic scoping review

Childhood obesity in the United States has doubled over the last three decades and currently affects 17% of children and adolescents. While much research has focused on individual behaviors impacting obesity, little research has emphasized the complex interactions of numerous chemical and non-chemical stressors found in a child's environment and how these interactions affect a child's health and well-being. The objectives of this systematic scoping review were to (1) identify potential chemical stressors in the context of non-chemical stressors that impact childhood obesity; and, (2) summarize our observations for chemical and non-chemical stressors in regards to child-specific environments within a community setting. A review was conducted to identify chemical and non-chemical stressors related to childhood obesity for the childhood life stages ranging from prenatal to adolescence. Stressors were identified and grouped into domains: individual behaviors, family/household behaviors, community stressors, and chemical exposures. Stressors were related to the child and the child's everyday environments and used to characterize child health and well-being. This review suggests that the interactions of chemical and non-chemical stressors are important for understanding a child's overall health and well-being. By considering these relationships, the exposure science research community can better design and implement strategies to reduce childhood obesity.

Maternal Exposure to Air Pollutants and Risk of Gestational Diabetes Mellitus in Taiwan

Mounting evidence has shown an increased risk of gestational diabetes mellitus (GDM) in association with elevated exposure to air pollution. However, limited evidence is available concerning the effect of specific air pollutant(s) on GDM incidence. We conducted this case-control study on 6717 mothers with GDM diagnosed in 2006–2013 and 6717 age- and year of delivery-matched controls to further address the risk of GDM in relation to specific air pollutant. Both cases and controls were selected from a cohort of 1-million beneficiaries of Taiwan’s National Health Insurance program registered in 2005. Maternal exposures to mean daily air pollutant concentration, derived from 76 fixed air quality monitoring stations within the 12-week period prior to pregnancy and during the 1st and 2nd trimesters, were assessed by the spatial analyst method (i.e., ordinary kriging) with the ArcGIS software. After controlling for potential confounders and other air pollutants, an increase in pre-pregnancy exposure of 1 inter-quartile range (IQR) for PM_2.5 and SO₂ was found to associate with a significantly elevated odds ratio (OR) of GDM at 1.10 (95% confidence interval (CI) 1.03–1.18 and 1.37 (95% CI 1.30–1.45), respectively. Exposures to PM_2.5 and SO₂ during the 1st and 2nd trimesters were also associated with significantly increased ORs, which were 1.09 (95% CI 1.02–1.17) and 1.07 (95% CI 1.01–1.14) for PM_2.5, and 1.37 (95% CI 1.30–1.45) and 1.38 (95% CI 1.31–1.46) for SO₂. It was concluded that higher pre- and post-pregnancy exposures to PM_2.5 and SO₂ for mothers were associated with a significantly but modestly elevated risk of GDM.

Gestational diabetes mellitus and exposure to ambient air pollution and road traffic noise: A cohort study

BACKGROUND

Road traffic is a main source of air pollution and noise. Both exposures have been associated with type 2 diabetes, but associations with gestational diabetes mellitus (GDM) have been studied less.

OBJECTIVES

We aimed to examine single and joint associations of exposure to air pollution and road traffic noise on GDM in a prospective cohort.

METHODS

We identified GDM cases from self-reports and hospital records, using two different criteria, among 72,745 singleton pregnancies (1997-2002) from the Danish National Birth Cohort. We modeled nitrogen dioxide (NO₂) and noise from road traffic (L_den) exposure at all pregnancy addresses.

RESULTS

According to the two diagnostic criteria: the Danish clinical guidelines, which was our main outcome, and the WHO standard during recruitment period, a total of 565 and 210 women, respectively, had GDM. For both exposures no risk was evident for the common Danish criterion of GDM. A 10-μg/m³ increase in NO₂ exposure during first trimester was, however, associated with an increased risk of WHO-GDM (adjusted odds ratio (OR)=1.24; 95% confidence interval (CI): 1.03, 1.49). The corresponding OR associated with a 10-dB higher road traffic noise level was 1.15 (0.94 to 1.18). In mutually adjusted models the OR for NO₂ remained similar 1.22 (0.98, 1.53) whereas that for road traffic noise decreased to 1.03 (0.80, 1.32). Significant associations were also observed for exposure averaged over the 2nd and 3rd trimesters and the full pregnancy.

CONCLUSIONS

No risk was evident for the common Danish criterion of GDM. NO₂ was associated with higher risk for GDM according to the WHO criterion, which might be due to selection bias.

Gestational diabetes mellitus was related to ambient air pollutant nitric oxide during early gestation

BACKGROUND

Ambient air pollution has been linked to the risk of gestational diabetes mellitus (GDM). However, evidence of this association is limited, and no study has examined the effects of nitric oxide (NO).

OBJECTIVE

This study investigated the association between air pollution exposure during gestation and GDM.

METHODS

The Taiwan Birth Cohort Study database was used to examine the association between the risk of GDM and all routinely monitored air pollutants among 21,248 women who were pregnant during 2004-2005. We further employed a two-pollutant model for confirming the effect of each pollutant on GDM.

RESULTS

After the exclusion criteria were applied, 19,606 women were included in the final analysis. Among them, 378 (1.9%) had been diagnosed as having GDM. These women were older and had higher BMIs than the women without GDM. The risks of GDM onset were significantly associated with NO exposure during the first [adjusted OR (aOR): 1.05, 95% confidence interval (CI): 1.02-1.08] and second (aOR: 1.05, 95%CI: 1.02-1.08) trimesters. Under the two-pollutant model, the effect of NO exposure was also significant during the first (aOR: 1.05, 95%CI: 1.02-1.08) and second (aOR: 1.05, 95%CI: 1.02-1.09) trimesters.

CONCLUSION

The results indicated that exposure to higher NO levels during pregnancy increases the risk of GDM.

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.

Association between particulate matter 2.5 and diabetes mellitus: A meta-analysis of cohort studies

Aims/Introduction

The present meta‐analysis was carried out to assess the association between exposure to the level of atmospheric particulate matter 2.5 (PM2.5; fine particulate matter with aerodynamic diameter less than 2.5 μm) and type 2 diabetes mellitus or gestational diabetes mellitus (GDM).

Materials and Methods

We searched the Medline, EMBASE, Cochrane and Web of Science databases to obtain articles according to the responding literature search strategies. Among a total of 279 identified articles, 55 were reviewed in depth, of which 10 articles (11 cohort studies) satisfied the inclusion criteria. Only cohort studies that disclosed the association between PM2.5 and type 2 diabetes mellitus or GDM were included in this article. A fixed‐effects model was selected if P > 0.1 and I² < 50%; otherwise, a random‐effects model would be used to calculate the total effect value. Subgroup analysis was further carried out according to the types of diabetes mellitus (type 2 diabetes mellitus and GDM). The relative risk was used to estimate the association between PM2.5 and diabetes mellitus.

Results

The positive associations between PM2.5 and the incidence of type 2 diabetes mellitus were found in the long‐term exposure period (relative risk 1.25, 95% confidence interval 1.10–1.43), which showed that with every 10‐μg/m³ increase in PM2.5, the risk of type 2 diabetes mellitus would increase by 25% in the long‐term exposure. Although the significant associations were not identified between maternal exposure to PM2.5 and GDM in the first trimester, the second trimester and the entire pregnancy periods, we could conclude that maternal exposure to PM2.5 in the entire pregnancy period would be more likely to lead to developing GDM (relative risk 1.162, 95% confidence interval 0.806–1.675) than the other two periods.

Conclusions

Long‐term exposure to PM2.5 would be more likely to lead to developing type 2 diabetes mellitus, but more studies would be required to confirm the association between PM2.5 and GDM. It might be a wise to take effective measures to reduce PM2.5 exposure in vulnerable populations, especially for pregnant women.

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

INTRODUCTION

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

Association of temporal distribution of fine particulate matter with glucose homeostasis during pregnancy in women of Chiayi City, Taiwan

BACKGROUND

To investigate the effects of fine particulate matter (PM_2.5) on the indicators of glucose homeostasis during pregnancy.

METHODS

A total of 3589 non-diabetic pregnant women who underwent a 3-h 100-g oral glucose tolerance test (OGTT) were enrolled from a tertiary teaching hospital in Chiayi City, Taiwan between 2006 and 2014. Fasting, 1-h, 2-h, and 3-h glucose levels after an OGTT were used as indicators of glucose homeostasis. PM_2.5 and other air pollution data were obtained from one fixed-site monitoring station (Chiayi City station) operated by Taiwan Environmental Protection Administration (EPA). We used mixed models for indicators of glucose homeostasis to estimate the effects of PM_2.5. The models were adjusted for individual-specific effects (nulliparous status, age, body mass index, season, and year) and the moving averages of temperature and relative humidity in the corresponding study period.

RESULTS

There were significant relationships between PM_2.5 and the glucose homeostasis indicators, including fasting, 1-h, 2-h, and 3-h glucose levels in the single-pollutant covariate-adjusted model. The pre-screening 1-month to 1-year moving averages of IQR increases in PM_2.5 were significantly associated with elevated fasting OGTT glucose levels (1.32-5.87mg/dL). The two-pollutant covariate-adjusted models had similar results.

CONCLUSIONS

We found positive associations between PM_2.5 and OGTT glucose levels during pregnancy. The association was especially pronounced for the fasting and 1-h glucose levels. PM_2.5 exposure in the second trimester may enhance this effect. Exposure to PM_2.5 was associated with glucose homeostasis during pregnancy.

The influence of the built environment on adverse birth outcomes

Adverse birth outcomes are associated with neonatal morbidity and mortality, and higher risk for coronary heart disease, non-insulin-dependent diabetes and hypertension in adulthood. Although there has been considerable research investigating the association between maternal and environmental factors on adverse birth outcomes, one risk factor, not fully understood, is the influence of the built environment. A search of MEDLINE, Scopus, and Cochrane was conducted to find articles assessing the influence of the built environment on preterm birth (PTB), low birth weight (LBW), and small-for-gestational-age (SGA). In total, 41 studies met our inclusion criteria, and were organized into nine categories: Roadways, Greenness, Power Plants, Gas Stations/Wells, Waste Management, Power Lines, Neighborhood Conditions, Food Environment, and Industry. The most common built environmental variable was roads/traffic, encompassing 17/41 (41%) of the articles reviewed, of which 12/17 (71%) found a significant small to moderate association between high traffic exposure and adverse birth outcomes.

A Statewide Nested Case-Control Study of Preterm Birth and Air Pollution by Source and Composition: California, 2001-2008

BACKGROUND

Preterm birth (PTB) has been associated with exposure to air pollution, but it is unclear whether effects might vary among air pollution sources and components.

OBJECTIVES

We studied the relationships between PTB and exposure to different components of air pollution, including gases and particulate matter (PM) by size fraction, chemical composition, and sources.

METHODS

Fine and ultrafine PM (respectively, PM2.5 and PM0.1) by source and composition were modeled across California over 2000-2008. Measured PM2.5, nitrogen dioxide, and ozone concentrations were spatially interpolated using empirical Bayesian kriging. Primary traffic emissions at fine scale were modeled using CALINE4 and traffic indices. Data on maternal characteristics, pregnancies, and birth outcomes were obtained from birth certificates. Associations between PTB (n = 442,314) and air pollution exposures defined according to the maternal residence at birth were examined using a nested matched case-control approach. Analyses were adjusted for maternal age, race/ethnicity, education and neighborhood income.

RESULTS

Adjusted odds ratios for PTB in association with interquartile range (IQR) increases in average exposure during pregnancy were 1.133 (95% CI: 1.118, 1.148) for total PM2.5, 1.096 (95% CI: 1.085, 1.108) for ozone, and 1.079 (95% CI: 1.065, 1.093) for nitrogen dioxide. For primary PM, the strongest associations per IQR by source were estimated for onroad gasoline (9-11% increase), followed by onroad diesel (6-8%) and commercial meat cooking (4-7%). For PM2.5 composition, the strongest positive associations per IQR were estimated for nitrate, ammonium, and secondary organic aerosols (11-14%), followed by elemental and organic carbon (2-4%). Associations with local traffic emissions were positive only when analyses were restricted to births with residences geocoded at the tax parcel level.

CONCLUSIONS

In our statewide nested case-control study population, exposures to both primary and secondary pollutants were associated with an increase in PTB.

CITATION

Laurent O, Hu J, Li L, Kleeman MJ, Bartell SM, Cockburn M, Escobedo L, Wu J. 2016. A statewide nested case-control study of preterm birth and air pollution by source and composition: California, 2001-2008. Environ Health Perspect 124:1479-1486; http://dx.doi.org/10.1289/ehp.1510133.

Air pollution exposure and preeclampsia among US women with and without asthma

Maternal asthma and air pollutants have been independently associated with preeclampsia but rarely studied together. Our objective was to comprehensively evaluate preeclampsia risk based on the interaction of maternal asthma and air pollutants. Preeclampsia and asthma diagnoses, demographic and clinical data came from electronic medical records for 210,508 singleton deliveries. Modified Community Multiscale Air Quality models estimated preconception, first and second trimester and whole pregnancy exposure to: particulate matter (PM)<2.5 and <10µm, ozone, nitrogen oxides (NOx), sulfur dioxide (SO2) and carbon monoxide (CO); PM2.5 constituents; volatile organic compounds (VOCs) and polycyclic aromatic hydrocarbons (PAHs). Asthma-pollutant interaction adjusted relative risks (RR) and 95% confidence intervals (CI) for preeclampsia were calculated by interquartile range for criteria pollutants and high exposure (≥75th percentile) for PAHs and VOCs. Asthmatics had higher risk associated with first trimester NOx and SO2 and whole pregnancy elemental carbon (EC) exposure than non-asthmatics, but only EC significantly increased risk (RR=1.11, CI:1.03-1.21). Asthmatics also had a 10% increased risk associated with second trimester CO. Significant interactions were observed for nearly all VOCs and asthmatics had higher risk during all time windows for benzene, ethylbenzene, m-xylene, o-xylene, p-xylene and toluene while most PAHs did not increase risk.

Air pollution exposure and gestational diabetes mellitus among pregnant women in Massachusetts: a cohort study

BACKGROUND

Rodent and human studies suggest an association between air pollution exposure and type 2 diabetes mellitus, but the extent to which air pollution is associated with gestational diabetes mellitus (GDM) is less clear.

METHODS

We used the Massachusetts Registry of Vital Records to study primiparous women pregnant from 2003-2008 without pre-existing diabetes. We used satellite-based spatiotemporal models to estimate first and second trimester residential particulate (PM2.5) exposure and geographic information systems to estimate neighborhood traffic density. We obtained GDM status from birth records. We performed logistic regression analyses adjusted for sociodemographics on the full cohort and after stratification by maternal age and smoking habits.

RESULTS

Of 159,373 women, 5,381 (3.4 %) developed GDM. Residential PM2.5 exposure ranged 1.3-19.3 μg/m(3) over the second trimester. None of the exposures were associated with GDM in the full cohort [e.g. OR 0.99 (95 % CI: 0.95, 1.03) for each interquartile range (IQR) increment in second trimester PM2.5]. There were also no consistent associations after stratification by smoking habits. When the cohort was stratified by maternal age, women less than 20 years had 1.36 higher odds of GDM (95 % CI: 1.08, 1.70) for each IQR increment in second trimester PM2.5 exposure.

CONCLUSIONS

Although we found no evidence of an association between air pollution exposure and GDM among all women in our study, greater exposure to PM2.5 during the second trimester was associated with GDM in the youngest age stratum.

Does maternal exposure to benzene and PM10 during pregnancy increase the risk of congenital anomalies? A population-based case-control study

A few studies have suggested an association between maternal exposure to ambient air pollution from vehicular traffic and risk of congenital anomalies in the offspring, but epidemiologic evidence is neither strong nor entirely consistent. In a population-based case-control study in a Northern Italy community encompassing 228 cases of birth defects and 228 referent newborns, we investigated if maternal exposure to PM10 and benzene from vehicular traffic during early pregnancy, as estimated through a dispersion model, was associated with excess teratogenic risk. In conditional logistic regression analysis, and with adjustment for the other pollutant, we found that higher exposure to PM10 but not benzene was associated with increased risk of birth defects overall. Anomaly categories showing the strongest dose-response relation with PM10 exposure were musculoskeletal and chromosomal abnormalities but not cardiovascular defects, with Down syndrome being among the specific abnormalities showing the strongest association, though risk estimates particularly for the less frequent defects were statistically very unstable. Further adjustment in the regression model for potential confounders did not considerably alter the results. All the associations were stronger for average levels of PM10 than for their maximal level. Findings of this study give some support for an excess teratogenic risk following maternal exposure during pregnancy to PM10, but not benzene. Such association appears to be limited to some birth defect categories.

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

Introduction

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

Approach

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

Main results and interpretation

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

Association of Atmospheric Particulate Matter and Ozone with Gestational Diabetes Mellitus

BACKGROUND

Ambient air pollution has been linked to the development of gestational diabetes mellitus (GDM). However, evidence of the association is very limited, and no study has estimated the effects of ozone.

OBJECTIVE

Our aim was to determine the association of prenatal exposures to particulate matter ≤ 2.5 μm (PM2.5) and ozone (O3) with GDM.

METHODS

We used Florida birth vital statistics records to investigate the association between the risk of GDM and two air pollutants (PM2.5 and O3) among 410,267 women who gave birth in Florida between 2004 and 2005. Individual air pollution exposure was assessed at the woman's home address at time of delivery using the hierarchical Bayesian space-time statistical model. We further estimated associations between air pollution exposures during different trimesters and GDM.

RESULTS

After controlling for nine covariates, we observed increased odds of GDM with per 5-μg/m3 increase in PM2.5 (ORTrimester1 = 1.16; 95% CI: 1.11, 1.21; ORTrimester2 = 1.15; 95% CI: 1.10, 1.20; ORPregnancy = 1.20; 95% CI: 1.13, 1.26) and per 5-ppb increase in O3 (ORTrimester1 = 1.09; 95% CI: 1.07, 1.11; ORTrimester2 = 1.12; 95% CI: 1.10, 1.14; ORPregnancy = 1.18; 95% CI: 1.15, 1.21) during both the first trimester and second trimester as well as the full pregnancy in single-pollutant models. Compared with the single-pollutant model, the ORs for O3 were almost identical in the co-pollutant model. However, the ORs for PM2.5 during the first trimester and the full pregnancy were attenuated, and no association was observed for PM2.5 during the second trimester in the co-pollutant model (OR = 1.02; 95% CI: 0.98, 1.07).

CONCLUSION

This population-based study suggests that exposure to air pollution during pregnancy is associated with increased risk of GDM in Florida, USA.

CITATION

Hu H, Ha S, Henderson BH, Warner TD, Roth J, Kan H, Xu X. 2015. Association of atmospheric particulate matter and ozone with gestational diabetes mellitus. Environ Health Perspect 123:853-859; http://dx.doi.org/10.1289/ehp.1408456.

Association between wood cooking fuel and maternal hypertension at delivery in central East India

OBJECTIVE

Smoke from burning of biomass fuels has been linked with adverse pregnancy outcomes and hypertension among nonpregnant subjects; association with hypertension during pregnancy has not been well studied. We evaluated whether the use of wood cooking fuel increases the risk of maternal hypertension at delivery compared to gas which burns with less smoke.

METHODS

Information on fuel use and blood pressure was available for analysis from a cross-sectional survey of 1369 pregnant women recruited at delivery in India.

RESULTS

Compared to gas users, women using wood as fuel had on average lower mean arterial pressure (adjusted effect size - 2.0 mmHg; 95% CI: -3.77, -0.31) and diastolic blood pressure (adjusted effect size -1.96 mmHg; 95% CI: -3.60, -0.30) at delivery. Risk of hypertension (systolic >139 mmHg or diastolic >89 mmHg) was 14.6% for wood users compared to 19.6% for gas users although this did not reach significance after adjustment, using propensity score techniques, for factors that make wood and gas users distinct (adjusted prevalence ratio 0.76; 95% CI: 0.49, 1.17).

CONCLUSIONS

Combustion products from the burning of biomass fuels are similar to those released with tobacco smoking, which has been linked with a reduced risk for preeclampsia. The direction of our findings suggests the possibility of a similar effect for biomass cook smoke. Whether clean cooking interventions being promoted by international advocacy organizations will impact hypertension in pregnancy warrants further analysis as hypertension remains a leading cause of maternal death worldwide and cooking with biomass fuels is widespread.