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

Investigation of the relationship between air pollution and gestational diabetes

BACKGROUND

Gestational diabetes mellitus (GDM) can have negative effects on both the pregnancy and perinatal outcomes, as well as the long-term health of the mother and the child. It has been suggested that exposure to air pollution may increase the risk of developing GDM. This study investigated the relationship between exposure to air pollutants with gestational diabetes.

METHODS

The present study is a retrospective cohort study. We used data from a randomised community trial conducted between September 2016 and January 2019 in Iran. During this period, data on air pollutant levels of five cities investigated in the original study, including 6090 pregnant women, were available. Concentrations of ozone (O3), nitric oxide (NO), nitrogen dioxide (NO2), nitrogen oxides (NOx), sulphur dioxide (SO2), carbon monoxide (CO), particulate matter < 2.5 (PM2.5) or <10 μm (PM10) were obtained from air pollution monitoring stations. Exposure to air pollutants during the three months preceding pregnancy and the first, second and third trimesters of pregnancy for each participant was estimated. The odds ratio was calculated based on logistic regression in three adjusted models considering different confounders. Only results that had a p < .05 were considered statistically significant.

RESULTS

None of the logistic regression models showed any statistically significant relationship between the exposure to any of the pollutants and GDM at different time points (before pregnancy, in the first, second and third trimesters of pregnancy and 12 months in total) (p > .05). Also, none of the adjusted logistic regression models showed any significant association between PM10 exposure and GDM risk at all different time points after adjusting for various confounders (p > .05).

CONCLUSIONS

This study found no association between GDM risk and exposure to various air pollutants before and during the different trimesters of pregnancy. This result should be interpreted cautiously due to the lack of considering all of the potential confounders.

Gestational exposure to air pollutants perturbs metabolic and placenta-fetal phenotype

Air pollution (AP) is detrimental to pregnancies including increasing risk factors of gestational diabetes mellitus. We hypothesized that exposure to AP causes cardiovascular and metabolic disruption thereby altering placental gene expression, which in turn affects the placental phenotype and thereby embryonic/fetal development. To test this hypothesis, we investigated the impact of intra-nasal instilled AP upon gestational day 16-19 maternal mouse cardiovascular and metabolic status, placental nutrient transporters, and placental-fetal size and morphology. To further unravel mechanisms, we also examined placental total DNA 5'-hydroxymethylation and bulk RNA sequenced gene expression profiles. AP exposed pregnant mice and fetuses were tachycardic with a reduction in maternal left ventricular fractional shortening and increased uterine artery with decreased umbilical artery systolic peak velocities. In addition, they were hyperglycemic, glucose intolerant and insulin resistant, with changes in placental glucose (Glut3) and fatty acid (Fatp1 & Cd36) transporters, and a spatial disruption of cells expressing Glut10 that imports L-dehydroascorbic acid in protecting against oxidative stress. Placentas revealed inflammatory cellular infiltration with associated cellular edema and necrosis, with dilated vascular spaces and hemorrhage. Placental and fetal body weights decreased in mid-gestation with a reduction in brain cortical thickness emerging in late gestation. Placental total DNA 5'-hydroxymethylation was 2.5-fold higher, with perturbed gene expression profiles involving key metabolic, inflammatory, transcriptional, cellular polarizing and processing genes and pathways. We conclude that gestational exposure to AP incites a maternal inflammatory response resulting in features mimicking maternal gestational diabetes mellitus with altered placental DNA 5'-hydroxymethylation, gene expression, and associated injury.

Effect of fine particulate matter exposure on gestational diabetes mellitus risk: a retrospective cohort study

BACKGROUND

The literature on the association between fine particulate matter (PM2.5) exposure and gestational diabetes mellitus (GDM) risk has focused mainly on exposure during the first and second trimesters, and the research results are inconsistent. Therefore, this study aimed to investigate the associations between PM2.5 exposure during preconception, the first trimester and second trimester and GDM risk in pregnant women in Guangzhou.

METHODS

A retrospective cohort study of 26 354 pregnant women was conducted, estimating PM2.5, particulate matter with a diameter >10 µm (PM10), sulphur dioxide (SO2), carbon monoxide (CO) and ozone (O3) exposure during preconception and the first and second trimesters. Analyses were performed using Cox proportional hazards models and nonlinear distributed lag models.

RESULTS

The study found that exposure to PM2.5 or a combination of two pollutants (PM2.5+PM10, PM2.5+SO2, PM2.5+CO and PM2.5+O3) was found to be significantly associated with GDM risk (P < 0.05). In the second trimester, with significant interactions found for occupation and anaemia between PM2.5 and GDM. When the PM2.5 concentrations were ≥19.56, ≥25.69 and ≥23.87 μg/m3 during preconception and the first and second trimesters, respectively, the hazard ratio for GDM started to increase. The critical window for PM2.5 exposure was identified to be from 9 to 11 weeks before conception.

CONCLUSIONS

Our study results suggest that PM2.5 exposure during preconception and the first and second trimesters increases the risk of GDM, with the preconception period appearing to be the critical window for PM2.5 exposure.

The causal effect of exposure to air pollution on risk of adverse pregnancy outcomes: A two-sample Mendelian randomisation study

BACKGROUND

Epidemiological studies have examined the relation between air pollution (NOx, NO2, PM2.5, PM2.5-10, and PM10) and adverse pregnancy outcomes (APOs). There's increasing evidence that air pollution increases the risk of APOs. However, the results of these studies are controversial, and the causal relation remains uncertain. We aimed to assess whether a genetic causal link exists between air pollution and APOs and the potential effects of this relation.

METHODS

A novel two-sample Mendelian randomisation (MR) study used pooled data from a large-scale complete genome correlation study. The primary analysis method was inverse variance weighting (IVW), which explored the expose-outcome relationship for assessing single nucleotide polymorphisms (SNPs) associated with air pollution. Further sensitivity analysis, including MR-PRESSO, MR-Egger regression, and leave-one analysis, was used to test the consistency of the results.

RESULTS

There was a significant correlation between air pollution-related SNPs and APOs. A robust causal link was found between genetic susceptibility to air pollution and APOs.

CONCLUSIONS

Our MR analysis reveals a genetic causal relation between air pollution and APOs, which may help provide new insights into further mechanisms and clinical studies in air pollution-mediated APOs.

Association Between Individual Air Pollution (PM10, PM2.5) Exposure and Adverse Pregnancy Outcomes in Korea: A Multicenter Prospective Cohort, Air Pollution on Pregnancy Outcome (APPO) Study

BACKGROUND

Prenatal exposure to ambient air pollution is linked to a higher risk of unfavorable pregnancy outcomes. However, the association between pregnancy complications and exposure to indoor air pollution remains unclear. The Air Pollution on Pregnancy Outcomes research is a hospital-based prospective cohort research created to look into the effects of aerodynamically exposed particulate matter (PM)10 and PM2.5 on pregnancy outcomes.

METHODS

This prospective multicenter observational cohort study was conducted from January 2021 to June 2023. A total of 662 women with singleton pregnancies enrolled in this study. An AirguardK® air sensor was installed inside the homes of the participants to measure the individual PM10 and PM2.5 levels in the living environment. The time-activity patterns and PM10 and PM2.5, determined as concentrations from the time-weighted average model, were applied to determine the anticipated exposure levels to air pollution of each pregnant woman. The relationship between air pollution exposure and pregnancy outcomes was assessed using logistic and linear regression analyses.

RESULTS

Exposure to elevated levels of PM10 throughout the first, second, and third trimesters as well as throughout pregnancy was strongly correlated with the risk of pregnancy problems according to multiple logistic regression models adjusted for variables. Except for in the third trimester of pregnancy, women exposed to high levels of PM2.5 had a high risk of pregnancy complications. During the second trimester and entire pregnancy, the risk of preterm birth (PTB) increased by 24% and 27%, respectively, for each 10 μg/m3 increase in PM10. Exposure to high PM10 levels during the second trimester increased the risk of gestational diabetes mellitus (GDM) by 30%. The risk of GDM increased by 15% for each 5 μg/m3 increase in PM2.5 during the second trimester and overall pregnancy, respectively. Exposure to high PM10 and PM2.5 during the first trimester of pregnancy increased the risk of delivering small for gestational age (SGA) infants by 96% and 26%, respectively.

CONCLUSION

Exposure to high concentrations of PM10 and PM2.5 is strongly correlated with the risk of adverse pregnancy outcomes. Exposure to high levels of PM10 and PM2.5 during the second trimester and entire pregnancy, respectively, significantly increased the risk of PTB and GDM. Exposure to high levels of PM10 and PM2.5 during the first trimester of pregnancy considerably increased the risk of having SGA infants. Our findings highlight the need to measure individual particulate levels during pregnancy and the importance of managing air quality in residential environment.

Modulatory Effects of Vitamin D: A Possible Approach to Mitigate Air Pollution Related Pregnancy Complications

Approximately 99% of people on the planet breathe air that exceeds the World Health Organization's permitted threshold for pollution. South Asia is home to the world's most polluted cities. Population-based studies have suggested that women's reproductive health outcomes are worsening due to air pollution. Preeclampsia, miscarriage, gestational diabetes, high blood pressure, and unfavorable birth outcomes, including preterm birth, low birth weight, or even stillbirth are all linked to exposure to air pollution during pregnancy. It is estimated that 0.61 million deaths in India alone were related to indoor air pollution. Females frequently cook in the household using solid fuel as a primary combustion source. Women in the regions with the highest population density are disproportionately affected by high levels of poor-quality indoor air. Recently, it has been proposed that air pollution has a distinct role in the onset of vitamin D deficiency. Numerous studies have explored associations between low vitamin D level and various female reproductive health conditions since the discovery of the vitamin D receptor. It is worthy to note that some of these reproductive health conditions positively correlate with the severity of air pollution. In this study, the evidence has been synthesized on vitamin D's protective properties and dietary and pharmaceutical interventions have been discussed to show their beneficial effects in decreasing the long-term negative impacts of air pollution on women's health.

Association of prenatal exposure to PM2.5 and NO2 with gestational diabetes in Western New York

BACKGROUND

Although many studies have examined the association between prenatal air pollution exposure and gestational diabetes (GDM), the relevant exposure windows remain inconclusive. We aim to examine the association between preconception and trimester-specific exposure to PM2.5 and NO2 and GDM risk and explore modifying effects of maternal age, pre-pregnancy body mass index (BMI), smoking, exercise during pregnancy, race and ethnicity, and neighborhood disadvantage.

METHODS

Analyses included 192,508 birth records of singletons born to women without pre-existing diabetes in Western New York, 2004-2016. Daily PM2.5 and NO2 at 1-km2 grids were estimated from ensemble-based models. We assigned each birth with exposures averaged in preconception and each trimester based on residential zip-codes. We used logistic regression to examine the associations and distributed lag models (DLMs) to explore the sensitive windows by month. Relative excess risk due to interaction (RERI) and multiplicative interaction terms were calculated.

RESULTS

GDM was associated with PM2.5 averaged in the first two trimesters (per 2.5 μg/m3: OR = 1.08, 95% CI: 1.01, 1.14) or from preconception to the second trimester (per 2.5 μg/m3: OR = 1.10, 95% CI: 1.03, 1.18). NO2 exposure during each averaging period was associated with GDM risk (per 10 ppb, preconception: OR = 1.10, 95% CI: 1.06, 1.14; first trimester: OR = 1.12, 95% CI: 1.08, 1.16; second trimester: OR = 1.10, 95% CI: 1.06, 1.14). In DLMs, sensitive windows were identified in the 5th and 6th gestational months for PM2.5 and one month before and three months after conception for NO2. Evidence of interaction was identified for pre-pregnancy BMI with PM2.5 (P-for-interaction = 0.023; RERI = 0.21, 95% CI: 0.10, 0.33) and with NO2 (P-for-interaction = 0.164; RERI = 0.16, 95% CI: 0.04, 0.27).

CONCLUSION

PM2.5 and NO2 exposure may increase GDM risk, and sensitive windows may be the late second trimester for PM2.5 and periconception for NO2. Women with higher pre-pregnancy BMI may be more susceptible to exposure effects.

The Influence of Airborne Particulate Matter on the Risk of Gestational Diabetes Mellitus: A Large Retrospective Study in Chongqing, China

Emerging research findings suggest that airborne particulate matter might be a risk factor for gestational diabetes mellitus (GDM). However, the concentration-response relationships and the susceptible time windows for different types of particulate matter may vary. In this retrospective analysis, we employ a novel robust approach to assess the crucial time windows regarding the prevalence of GDM and to distinguish the susceptibility of three GDM subtypes to air pollution exposure. This study included 16,303 pregnant women who received routine antenatal care in 2018-2021 at the Maternal and Child Health Hospital in Chongqing, China. In total, 2482 women (15.2%) were diagnosed with GDM. We assessed the individual daily average exposure to air pollution, including PM2.5, PM10, O3, NO2, SO2, and CO based on the volunteers' addresses. We used high-accuracy gridded air pollution data generated by machine learning models to assess particulate matter per maternal exposure levels. We further analyzed the association of pre-pregnancy, early, and mid-pregnancy exposure to environmental pollutants using a generalized additive model (GAM) and distributed lag nonlinear models (DLNMs) to analyze the association between exposure at specific gestational weeks and the risk of GDM. We observed that, during the first trimester, per IQR increases for PM10 and PM2.5 exposure were associated with increased GDM risk (PM10: OR = 1.19, 95%CI: 1.07~1.33; PM2.5: OR = 1.32, 95%CI: 1.15~1.50) and isolated post-load hyperglycemia (GDM-IPH) risk (PM10: OR = 1.23, 95%CI: 1.09~1.39; PM2.5: OR = 1.38, 95%CI: 1.18~1.61). Second-trimester O3 exposure was positively correlated with the associated risk of GDM, while pre-pregnancy and first-trimester exposure was negatively associated with the risk of GDM-IPH. Exposure to SO2 in the second trimester was negatively associated with the risk of GDM-IPH. However, there were no observed associations between NO2 and CO exposure and the risk of GDM and its subgroups. Our results suggest that maternal exposure to particulate matter during early pregnancy and exposure to O3 in the second trimester might increase the risk of GDM, and GDM-IPH is the susceptible GDM subtype to airborne particulate matter exposure.

Human milk EV-miRNAs: a novel biomarker for air pollution exposure during pregnancy

Exposure to ambient and near-roadway air pollution during pregnancy has been linked with several adverse health outcomes for pregnant women and their babies. Emerging research indicates that microRNA (miRNA) expression can be altered by exposure to air pollutants in a variety of tissues. Additionally, miRNAs from breast tissue and circulating miRNAs have previously been proposed as a biomarker for breast cancer diagnosis and prognosis. Therefore, this study sought to evaluate the associations between pregnancy exposures to ambient (PM10, PM2.5, NO2, O3) and near-roadway air pollution (total NOx, freeway NOx, non-freeway NOx) with breast milk extracellular vesicle miRNA (EV-miRNA), measured at 1-month postpartum, in a cohort of 108 Latina women living in Southern California. We found that PM10 exposure during pregnancy was positively associated with hsa-miR-200c-3p, hsa-miR-200b-3p, and hsa-let-7c-5p, and was negatively associated with hsa-miR-378d. We also found that pregnancy PM2.5 exposure was positively associated with hsa-miR-200c-3p and hsa-miR-200b-3p. First and second trimester exposure to PM10 and PM2.5 was associated with several EV-miRNAs with putative messenger RNA targets related to cancer. This study provides preliminary evidence that air pollution exposure during pregnancy is associated with human milk EV-miRNA expression.

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.

Examining the Relationship Between Extreme Temperature, Microclimate Indicators, and Gestational Diabetes Mellitus in Pregnant Women Living in Southern California

Few studies have assessed extreme temperatures' impact on gestational diabetes mellitus (GDM). We examined the relation between GDM risk with weekly exposure to extreme high and low temperatures during the first 24 weeks of gestation and assessed potential effect modification by microclimate indicators.

Methods

We utilized 2008-2018 data for pregnant women from Kaiser Permanente Southern California electronic health records. GDM screening occurred between 24 and 28 gestational weeks for most women using the Carpenter-Coustan criteria or the International Association of Diabetes and Pregnancy Study Groups criteria. Daily maximum, minimum, and mean temperature data were linked to participants' residential address. We utilized distributed lag models, which assessed the lag from the first to the corresponding week, with logistic regression models to examine the exposure-lag-response associations between the 12 weekly extreme temperature exposures and GDM risk. We used the relative risk due to interaction (RERI) to estimate the additive modification of microclimate indicators on the relation between extreme temperature and GDM risk.

Results

GDM risks increased with extreme low temperature during gestational weeks 20--24 and with extreme high temperature at weeks 11-16. Microclimate indicators modified the influence of extreme temperatures on GDM risk. For example, there were positive RERIs for high-temperature extremes and less greenness, and a negative RERI for low-temperature extremes and increased impervious surface percentage.

Discussion

Susceptibility windows to extreme temperatures during pregnancy were observed. Modifiable microclimate indicators were identified that may attenuate temperature exposures during these windows, which could in turn reduce the health burden from 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.

Causal Associations of PM2.5 and GDM: A Two-Sample Mendelian Randomization Study

Epidemiological studies have linked particulate matter (PM2.5) to gestational diabetes mellitus (GDM). However, the causality of this association has not been established; Mendelian randomization was carried out using summary data from genome-wide association studies (GWAS). For the analysis of the causal relationship between PM2.5 and GDM, the inverse variance weighted (IVW) method was used. The exposure data came from a GWAS dataset of IEU analysis of the United Kingdom Biobank phenotypes consisting of 423,796 European participants. The FinnGen consortium provided the GDM data, which included 6033 cases and 123,000 controls. We also performed multivariate MR (MVMR), adjusting for body mass index (BMI) and smoking. As a result, we found that each standard deviation increase in PM2.5 is associated with a 73.6% increase in the risk of GDM (OR: 1.736; 95%CI: 1.226-2.457). Multivariable MR analysis showed that the effect of PM2.5 on GDM remained after accounting for BMI and smoking. Our results demonstrate a causal relationship between PM2.5 and GDM.

Air pollution exposure and the risk of macrosomia: Identifying specific susceptible months

Birth weight is an important indicator of future growth and development for newborns. Few studies investigated the potential effects of air pollutants on macrosomia and their susceptible windows. We included 38,971 singleton full-term births from Beijing HaiDian Maternal and Child Health Hospital between 2014 and 2018, and assessed the associations of air pollutants exposure during preconception and pregnancy with macrosomia as well as the corresponding susceptible windows. The concentrations of air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, CO and O₃) for participants were calculated by the data from the nearest monitoring stations. Distributed lag models (DLM) incorporating logistic regression models were used to estimate the associations between air pollutants exposure during the 3 months before conception and pregnancy period and the risk of macrosomia, identifying susceptible windows of air pollutants. Weighted quantile sum (WQS) regression was applied to estimate the joint effect of air pollutants. A 10 μg/m³ increase in PM_2.5 exposure from 3rd to 8th gestational month was positively associated with the risk of macrosomia, with the strongest effect in the 6th month (OR = 1.010, 95 % CI: 1.002-1.019). For a 10 μg/m³ increase in SO₂, the windows of significant exposure were from the 1st preconception month to the 3rd gestational month, with the strongest effect in the 2nd month (OR = 1.030, 95 % CI: 1.010-1.049). We also observed the significant positive associations were in the 5th-8th gestational months for PM₁₀, the 8th-9th gestational months for NO₂ and the 3rd-7th gestational months for CO respectively. WQS regression also indicated a positive association between co-exposure to air pollutants and macrosomia. Our results suggest air pollution exposure is associated with increased risk of macrosomia. The windows of exposure for susceptibility to the risk of macrosomia vary between air pollutants. The susceptible exposure windows were middle and late pregnancy for PM, CO and NO₂, while for SO₂, early pregnancy is the window of vulnerability. Our findings provide the evidence that air pollution exposure is an independent risk factor for macrosomia and a basis for targeted environment policy.

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 of air pollution and fine particulate matter (PM2.5) exposure with gestational diabetes: a systematic review and meta-analysis

Background

The association between air pollution (AP) and gestational diabetes mellitus (GDM), especially between different pollutants and GDM, remains controversial and debatable. Hence, we conducted this systematic review and meta-analysis to provide comprehensive evidence-based support for the association between AP and GDM.

Methods

The databases of the Cochrane Library, Embase, PubMed, and Web of Science were searched from inception to 1 April 2022, in combination with manual retrieval. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of case-control studies and cohort studies, while the Joana Brigg's Institute (JBI) critical appraisal checklist was used for the quality assessment of cross-sectional studies.

Results

We identified 35 epidemiological studies (including 33 cohort studies, 1 cross-sectional study, and 1 case-control study) covering 6,939,725 pregnant women, of whom 865,460 were GDM patients. The NOS score of all included case-control studies and cohort studies was higher than six, and one of the included cross-sectional studies was rated as high quality according to the JBI assessment. Meta-analysis showed that fine particulate matter and air pollutants [PM2.5, odds ratio (OR) =1.06, 95% confidence interval (CI): 1.05-1.08, Z =7.76, P<0.001; PM10, OR =1.06, 95% CI: 1.01-1.11, Z =2.62, P=0.009; sulfur dioxide (SO₂), OR =1.18, 95% CI: 1.10-1.26, Z = 4.69, P<0.001; nitric oxide (NO), OR =1.04, 95% CI: 1.03-1.06,Z =3.33, P=0.001; nitrogen oxides (NO_X), OR =1.07, 95% CI: 1.04-1.11, Z =3.93, P<0.001; black carbon (BC), OR =1.08, 95% CI: 1.06-1.10, Z =7.58, P<0.001] was associated with GDM. Furthermore, no significant association was observed between O₃, CO, and nitrogen dioxide (NO₂) exposure and GDM.

Conclusions

Exposure to PM2.5, PM10, SO₂, NO, NO_X, and BC significantly increases the risk of GDM. AP is a remediable environmental trigger that can be prevented by human interventions, such as lowering AP levels or limiting human exposure to air pollutants. The government should strengthen the supervision of air quality and make air quality information more transparent. Besides, living conditions are crucial during pregnancy. Living in a place with more green areas is recommended, and indoor air purification should also be enhanced.

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 air pollution alters energy balance transiently according to gender and changes gut microbiota

Introduction

The timing of maternal exposure to air pollution is crucial to define metabolic changes in the offspring. Here we aimed to determine the most critical period of maternal exposure to particulate matter (PM_2.5) that impairs offspring's energy metabolism and gut microbiota composition.

Methods

Unexposed female and male C57BL/6J mice were mated. PM_2.5 or filtered air (FA) exposure occurred only in gestation (PM_2.5/FA) or lactation (FA/PM_2.5). We studied the offspring of both genders.

Results

PM_2.5 exposure during gestation increased body weight (BW) at birth and from weaning to young in male adulthood. Leptin levels, food intake, Agrp, and Npy levels in the hypothalamus were also increased in young male offspring. Ikbke, Tnf increased in male PM_2.5/FA. Males from FA/PM_2.5 group were protected from these phenotypes showing higher O₂ consumption and Ucp1 in the brown adipose tissue. In female offspring, we did not see changes in BW at weaning. However, adult females from PM_2.5/FA displayed higher BW and leptin levels, despite increased energy expenditure and thermogenesis. This group showed a slight increase in food intake. In female offspring from FA/PM_2.5, BW, and leptin levels were elevated. This group displayed higher energy expenditure and a mild increase in food intake. To determine if maternal exposure to PM_2.5 could affect the offspring's gut microbiota, we analyzed alpha diversity by Shannon and Simpson indexes and beta diversity by the Linear Discriminant Analysis (LDA) in offspring at 30 weeks. Unlike males, exposure during gestation led to higher adiposity and leptin maintenance in female offspring at this age. Gestation exposure was associated with decreased alpha diversity in the gut microbiota in both genders.

Discussion

Our data support that exposure to air pollution during gestation is more harmful to metabolism than exposure during lactation. Male offspring had an unfavorable metabolic phenotype at a young age. However, at an older age, only females kept more adiposity. Ultimately, our data highlight the importance of controlling air pollution, especially during gestation.

PM2.5 Constituents and Onset of Gestational Diabetes Mellitus: Identifying Susceptible Exposure Windows

Fine particulate matter (PM_2.5) has been linked to gestational diabetes mellitus (GDM). However, PM_2.5 is a complex mixture with large spatiotemporal heterogeneities, and women with early-onset GDM (i.e., diagnosed before 24^th gestation week) have distinct maternal characteristics and a higher risk of worse health outcomes compared with those with late-onset GDM (i.e., diagnosed in or after 24^th gestation week). We aimed to examine differential impacts of PM_2.5 and its constituents on early- vs. late-onset GDM, and to identify corresponding susceptible exposure windows. We leveraged statewide linked electronic health records and birth records data in Florida in 2012-2017. Exposures to PM_2.5 and its constituents (i.e., sulfate [SO₄ ^2-], ammonium [NH₄ ⁺], nitrate [NO₃ ^-], organic matter [OM], black carbon [BC], mineral dust [DUST], and sea-salt [SS]) were spatiotemporally linked to pregnant women based on their residential histories. Cox proportional hazards models and multinomial logistic regression were used to examine the associations of PM_2.5 and its constituents with GDM and its onsets. Distributed non-linear lag models were implemented to identify susceptible exposure windows. Exposures to PM_2.5, SO₄ ^2-, NH₄ ⁺, and BC were statistically significantly associated with higher hazards of GDM. Exposures to PM_2.5 during weeks 1-12 of gestation were positively associated with GDM. Associations of early-onset GDM with PM_2.5 in the 1^st and 2^nd trimesters, SO₄ ^2- in the 1^st and 2^nd trimesters, and NO₃ ^- in the preconception and 1^st trimester were considerably stronger than observations for late-onset GDM. Our findings suggest there are differential associations of PM_2.5 and its constituents with early- vs. late-onset GDM, with different susceptible exposure windows. This study helps better understand the impacts of air pollution on GDM accounting for its physiological heterogeneity.

Association between ambient air pollution exposure during pregnancy and gestational diabetes mellitus: a meta-analysis of cohort studies

Numerous studies have evaluated the association between air pollution and gestational diabetes mellitus (GDM), but the findings were inconsistent. This meta-analysis aimed to provide higher grade evidence on the association of air pollution with GDM based on previous studies. PubMed, Web of science, China National Knowledge Infrastructure (CNKI), and Wanfang Data Knowledge Service Platform (Wanfang) were searched comprehensively up to September 2021. Totally, 20 eligible cohort studies were finally included, for which the pooled RR and 95% CIs were estimated. Stratified analyses by study regions and units of pollutant increase were conducted for further investigation. Sensitivity analyses were also performed to assess the robustness. The finding showed that PM_2.5, PM₁₀, NO₂, and SO₂ exposure increased the risk of GDM, while O₃ exposure reduced GDM risk. Specifically, PM_2.5 exposure in the first and second trimesters, NO₂ and SO₂ exposure in the first trimester significantly increased the risk of GDM, with the RR ranging from 1.015 to 1.032. In addition, the elevation of GDM risk induced by PM_2.5, PM₁₀, and O₃ exposure was more pronounced in Asian subjects than in American subjects. The meta-analysis provides high-quality evidence on the effect of maternal air pollution exposure on GDM in each exposure period.

Environmental health influences in pregnancy and risk of gestational diabetes mellitus: a systematic review

Background

Gestational diabetes mellitus (GDM) is one of the most common pregnancy complications globally. Environmental risk factors may lead to increased glucose levels and GDM, which in turn may affect not only the health of the mother but assuming hypotheses of "fetal programming", also the health of the offspring. In addition to traditional GDM risk factors, the evidence is growing that environmental influences might affect the development of GDM. We conducted a systematic review analyzing the association between several environmental health risk factors in pregnancy, including climate factors, chemicals and metals, and GDM.

Methods

We performed a systematic literature search in Medline (PubMed), EMBASE, CINAHL, Cochrane Library and Web of Science Core Collection databases for research articles published until March 2021. Epidemiological human and animal model studies that examined GDM as an outcome and / or glycemic outcomes and at least one environmental risk factor for GDM were included.

Results

Of n = 91 studies, we classified n = 28 air pollution, n = 18 persistent organic pollutants (POP), n = 11 arsenic, n = 9 phthalate n = 8 bisphenol A (BPA), n = 8 seasonality, n = 6 cadmium and n = 5 ambient temperature studies. In total, we identified two animal model studies. Whilst we found clear evidence for an association between GDM and air pollution, ambient temperature, season, cadmium, arsenic, POPs and phthalates, the findings regarding phenols were rather inconsistent. There were clear associations between adverse glycemic outcomes and air pollution, ambient temperature, season, POPs, phenols, and phthalates. Findings regarding cadmium and arsenic were heterogeneous (n = 2 publications in each case).

Conclusions

Environmental risk factors are important to consider in the management and prevention of GDM. In view of mechanisms of fetal programming, the environmental risk factors investigated may impair the health of mother and offspring in the short and long term. Further research is needed.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13965-5.

Associations of pregnancy complications with ambient air pollution in China

BACKGROUND

Gestational hypertension (GH), preeclampsia (PE), and gestational diabetes mellitus (GDM) are common pregnancy complications and can result in maternal and prenatal morbidity and mortality. Air pollution exposure could adversely impact pregnancy complications; however, evidence remains limited in China, where ambient air pollution is relatively severe.

OBJECTIVE

This study aims to examine the associations of GH, PE, and GDM with exposure to six air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, O₃, and CO) during pregnancy.

METHODS

Leveraging a multicenter birth cohort study among pregnant women in 24 hospitals from 15 provinces in China, we obtained data for maternal characteristics and pregnancy outcomes. We generated ambient concentrations of the six air pollutants using a combination of chemical transport model simulations with monitoring data. We used multivariable logistic regression models to estimate the effects on pregnancy complications from exposure to six air pollutants in each trimester and the entire pregnancy.

RESULTS

Among the total 3754 pregnant women in this study, the prevalences of GH, GDM, and PE were 2.6 %, 11.2 %, and 0.7 %, respectively. GH risk increased 11.9 % (95 % CI, -8.5 %, 36.8 %) and 13.8 % (1.4 %, 27.8 %) per 10 μg/m³ increases in PM_2.5 and PM₁₀ in the entire pregnancy, respectively. PM_2.5 and PM₁₀ exposures in the first trimester were significantly associated with an increased risk of GDM. Exposure to O₃, SO₂, NO₂, and CO in early pregnancy could be associated with GDM risk. Geographic region and season of conception may influence the associations of GH and PE with air pollution.

CONCLUSIONS

Ambient particulate matter pollution adversely affects GH, GDM, and PE among Chinese pregnant women. Since most regions of China still suffer from hazardous levels of air pollution, our findings indicate importance of better protecting pregnant women from the risk of air pollution.

Safe in the womb? Effects of air pollution to the unborn child and neonates

OBJECTIVE

In this brief review, the authors focus on the effects of gestational exposures to urban air pollution on fetal development and neonatal outcomes.

SOURCE OF DATA

In this review the authors used PubMed, Web of Science and SciELO research platforms, analyzing papers from the last 30 years.

SUMMARY OF THE FINDINGS

Epidemiological and experimental evidence agree that gestational exposure to air pollution in urban increases the risks for low birth weight, preterm birth, congenital malformation, intrauterine growth restriction, and neonatal mortality. Furthermore, exposures are associated with increased risks for preeclampsia, hypertension, gestational diabetes.

CONCLUSIONS

Therefore, it is time for greater involvement and engagement of the health sector in the discussion of public policies that may affect the quality of the environment, and that directly or indirectly impact the health of those who were not yet born.

Vitamin D intake modifies the association of household air pollution exposure with maternal disorders of pregnancy

To date, only three studies have investigated the association of household air pollution (HAP) exposure with pregnancy disorders. The ameliorating role of diet and nutrition in the association has never been explored. We conducted a cross-sectional study among 799 mothers who had recently given singleton birth in the Cape Coast Metropolis, Ghana. Structured questionnaire and semi-quantitative food frequency questionnaire were used to assess HAP exposure (from use of biomass fuels for cooking and garbage burning at home) and vitamin D (vitD) intake, respectively. Multivariable binary logistic regression was used to investigate the association between HAP exposure and pregnancy disorders. HAP exposure due to cooking with biomass fuels and garbage burning at home was associated with two fold (AOR = 2.15; 95% confidence interval [CI]: 1.05, 4.43) and six fold (AOR = 6.35; 95% CI: 2.43, 16.58) increased odds of hypertensive disorders of pregnancy (HDP). For gestational diabetes (GDM), the increased odds were two folds for both exposures but the 95% CI included the null value. Stove stacking was also associated with two folds increased odds of GDM (AOR = 1.83; 95% CI: 0.91, 3.68). In stratified analysis, the odds of HDP and GDM associated with biomass fuels use decreased with increasing vitD intake. All the interaction p values were, however, greater than 0.05. We provide the first evidence on the ameliorating role of vitD intake on the effect of HAP exposure on pregnancy disorders. In LMICs where solid fuel use and garbage burning at home is widespread, health workers should advise mothers during antenatal care visits to increase intake of vitamin D rich foods.

Exposure to air pollutant mixture and gestational diabetes mellitus in Southern California: Results from electronic health record data of a large pregnancy cohort

BACKGROUND

Epidemiological findings are inconsistent regarding the associations between air pollution exposure during pregnancy and gestational diabetes mellitus (GDM). Several limitations exist in previous studies, including potential outcome and exposure misclassification, unassessed confounding, and lack of simultaneous consideration of air pollution mixtures and particulate matter (PM) constituents.

OBJECTIVES

To assess the association between GDM and maternal residential exposure to air pollution, and the joint effect of the mixture of air pollutants and PM constituents.

METHODS

Detailed clinical data were obtained for 395,927 pregnancies in southern California (2008-2018) from Kaiser Permanente Southern California (KPSC) electronic health records. GDM diagnosis was based on KPSC laboratory tests. Monthly average concentrations of fine particulate matter < 2.5 μm (PM_2.5), <10 μm (PM₁₀), nitrogen dioxide (NO₂), and ozone (O₃) were estimated using kriging interpolation of Environmental Protection Agency's routine monitoring station data, while PM_2.5 constituents (i.e., sulfate, nitrate, ammonium, organic matter and black carbon) were estimated using a fine-resolution geoscience-derived model. A multilevel logistic regression was used to fit single-pollutant models; quantile g-computation approach was applied to estimate the joint effect of air pollution and PM component mixtures. Main analyses adjusted for maternal age, race/ethnicity, education, median family household income, pre-pregnancy BMI, smoking during pregnancy, insurance type, season of conception and year of delivery.

RESULTS

The incidence of GDM was 10.9% in the study population. In single-pollutant models, we observed an increased odds for GDM associated with exposures to PM_2.5, PM₁₀, NO₂ and PM_2.5 constituents. The association was strongest for NO₂ [adjusted odds ratio (OR) per interquartile range: 1.176, 95% confidence interval (CI): 1.147-1.205)]. In multi-pollutant models, increased ORs for GDM in association with one quartile increase in air pollution mixtures were found for both kriging-based regional air pollutants (NO₂, PM_2.5, and PM₁₀, OR = 1.095, 95% CI: 1.082-1.108) and PM_2.5 constituents (i.e., sulfate, nitrate, ammonium, organic matter and black carbon, OR = 1.258, 95% CI: 1.206-1.314); NO₂ (78%) and black carbon (48%) contributed the most to the overall mixture effects among all krigged air pollutants and all PM_2.5 constituents, respectively. The risk of GDM associated with air pollution exposure were significantly higher among Hispanic mothers, and overweight/obese mothers.

CONCLUSION

This study found that exposure to a mixture of ambient PM_2.5, PM₁₀, NO₂, and PM_2.5 chemical constituents was associated with an increased risk of GDM. NO₂ and black carbon PM_2.5 contributed most to GDM risk.

Association of exposure to air pollutants with gestational diabetes mellitus in Chiayi City, Taiwan

INTRODUCTION

We investigated the associations of exposure to particulate matter with an aerodynamic diameter less than 2.5 μm (PM_2.5) and several gaseous pollutants with risk of gestational diabetes mellitus (GDM) in Taiwan.

METHODS

We retrospectively identified pregnant women who underwent a two-step approach to screen for GDM between 2006 and 2014. Information on concentrations of air pollutants (including PM_2.5, sulfur dioxide [SO₂], nitrogen oxides [NO_x], and ozone [O₃]) were collected from a single fixed-site monitoring station. We conducted logistic regression analyses to determine the associations between exposure to air pollutants and risk of GDM.

RESULTS

A total of 11210 women were analyzed, and 705 were diagnosed with GDM. Exposure to PM_2.5 during the second trimester was associated with a nearly 50% higher risk of GDM (odds ratio [OR] 1.47, 95% CI 0.96 to 2.24, p=0.077). The associations were consistent in the two-pollutant model (PM_2.5 + SO₂ [OR 1.73, p=0.038], PM_2.5 + NO_x [OR 1.52, p=0.064], PM_2.5 + O₃ [OR 1.96, p=0.015]), and were more prominent in women with age <30 years and body mass index <25 kg/m² (interaction p values <0.01).

DISCUSSION

Exposure to PM_2.5 was associated with risk of GDM, especially in women who were younger or had a normal body mass index.

Air Pollution, Residential Greenness and Metabolic Dysfunction during Early Pregnancy in the INfancia y Medio Ambiente (INMA) Cohort

Despite extensive study, the role of air pollution in gestational diabetes remains unclear, and there is limited evidence of the beneficial impact of residential greenness on metabolic dysfunction during pregnancy. We used data from mothers in the Spanish INfancia y Medio Ambiente (INMA) Project from 2003–2008. We obtained spatiotemporally resolved estimates of fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) exposures in early pregnancy and estimated residential greenness using satellite-based Normal Difference Vegetation Index (NDVI) within 100, 300 and 500 m buffers surrounding the mother’s residence. We applied logistic regression models to evaluate associations between each of the three exposures of interest and (a) glucose intolerance and (b) abnormal lipid levels. We found limited evidence of associations between increases in PM_2.5 and NO₂ exposures and the metabolic outcomes. Though not statistically significant, high PM_2.5 exposure (≥25 µg/m³) was associated with increased odds of glucose intolerance (OR = 1.16, 95% CI: 0.82, 1.63) and high cholesterol (OR = 1.14, 95% CI: 0.90, 1.44). High NO₂ exposure (≥39.8 µg/m³) was inversely associated with odds of high triglycerides (OR = 0.70, 95% CI: 0.45, 1.08). Whereas NDVI was not associated with glucose intolerance, odds of high triglycerides were increased, although the results were highly imprecise. Results were unchanged when the air pollutant variables were included in the regression models. Given the equivocal findings in our study, additional investigations are needed to assess effects of air pollution and residential greenness on metabolic dysfunction during pregnancy.

PM2.5 exposure and maternal glucose metabolism in early pregnancy: Associations and potential mediation of 25-hydroxyvitamin D

Gestational diabetes mellitus (GDM) has become a new global epidemic with a rapidly increasing prevalence. Previous studies have suggested that air pollution is associated with GDM risk, but the results are inconsistent, and mechanistic studies are limited. Based on a hospital-based cohort, a total of 6374 participants were included in this study. Individual daily PM2.5 exposure at a 1-km resolution was predicted using a full-spatiotemporal-coverage model. The results of multiple linear regression showed that glycated hemoglobin (HbA1c) was significantly associated with PM2.5 both in the 1-month preconception and in the first trimester of pregnancy. Additionally, HbA1c decreased 0.437% (95% CI: -0.629, -0.244) as the serum 25-hydroxyvitamin D (25(OH)D) increased by one interquartile range (IQR) (9.2 ng/ml). An IQR increase in PM2.5 exposure was also negatively associated with serum 25(OH)D (estimated change% and 95% CI: -7.249 (-9.054, -5.408) in the 1-month preconception and - 13.069 (-15.111, -10.979) in the first trimester of pregnancy). Mediation analysis showed that serum 25(OH)D status mediated the association between HbA1c and PM2.5 exposure both in the preconception and in the first trimester (mediated percent: 2.00% and 4.05% (Sobel p＜0.001), respectively). The result suggested a vicious cycle among PM2.5 exposure, lower serum VD status and a higher HbA1c. More studies are warranted since the protective effect of 25(OH)D against glucose disorders associated with air pollution in this study was limited.

Associations between the chemical composition of PM2.5 and gestational diabetes mellitus

BACKGROUND

Fine particulate matter (PM_2.5) is a complex mixture of fine particulates with large spatiotemporal heterogeneities in chemical compositions. While PM_2.5 has been associated with gestational diabetes mellitus (GDM), little is known about the relationship between specific chemical components of PM_2.5 and GDM. We examined the associations between GDM and pregnancy exposures to PM_2.5 and its compositions, including sulfate (SO₄^2-), ammonium (NH₄⁺), nitrate (NO₃^-), organic matter (OM), black carbon (BC), mineral dust (DUST), and sea-salt (SS), and to identify critical windows of exposure.

METHODS

We used data from the 2005-2015 Florida Vital Statistics Birth Records. A well-validated geoscience-derived model was used to estimate women's pregnancy exposures to PM_2.5 and its compositions. Distributed lag models were used to examine the associations and to identify the critical windows of exposure.

RESULTS

A total of 2,078,669 women were included. In single-pollutant models, after controlling for potential confounders, positive associations between PM_2.5 and GDM were observed during the second trimester of pregnancy. We found positive associations between SO₄^2-, NH₄⁺, NO₃^-, OM and BC, with largest effect sizes observed in the 21-24 weeks of pregnancy. Negative associations were observed for DUST and SS. Consistent results for NH₄⁺, OM, DUST and SS were observed in the multi-pollutant models.

CONCLUSIONS

Exposures to PM_2.5 and its compositions (mainly NH₄⁺, OM) during the second trimester are positively associated with GDM, especially for exposures during the 21-24 weeks of pregnancy. Further studies are needed to confirm the findings and examine the underlying mechanisms.

Ambient PM gross β-activity and glucose levels during pregnancy

BACKGROUND

Exposure to ionizing radiation has been associated with insulin resistance and type 2 diabetes. In light of recent work showing an association between ambient particulate matter (PM) gross β-activity and gestational diabetes mellitus (GDM) among pregnant women, we examined pregnancy glucose levels in relation to PM gross β-activity to better understand this pathway.

METHODS

Our study included 103 participants receiving prenatal care at Beth Israel Deaconess Medical Center in Boston, MA. PM gross β-activity was obtained from US Environmental Protection Agency's RadNet program monitors, and blood glucose levels were obtained from the non-fasting glucose challenge test performed clinically as the first step of the 2-step GDM screening test. For each exposure window we examined (i.e., moving average same-day, one-week, first-trimester, and second-trimester PM gross β-activity), we fitted generalized additive models and adjusted for clinical characteristics, socio-demographic factors, temporal variables, and PM with an aerodynamic diameter ≤ 2.5 μm (PM_2.5). Subgroup analyses by maternal age and by body mass index were also conducted.

RESULTS

An interquartile range increase in average PM gross β-activity during the second trimester of pregnancy was associated with an increase of 17.5 (95% CI: 0.8, 34.3) mg/dL in glucose concentration. Associations were stronger among younger and overweight/obese participants. Our findings also suggest that the highest compared to the lowest quartile of one-week exposure was associated with 17.0 (95% CI: - 4.0, 38.0) mg/dL higher glucose levels. No associations of glucose were observed with PM gross β-activity during same-day and first-trimester exposure windows. PM_2.5 was not associated with glucose levels during any exposure window in our data.

CONCLUSIONS

Exposure to higher levels of ambient PM gross β-activity was associated with higher blood glucose levels in pregnant patients, with implications for how this novel environmental factor could impact pregnancy health.

Association between ambient air pollution and high-risk pregnancy: A 2015-2018 national population-based cohort study in Korea

BACKGROUND

Several studies have indicated that prenatal exposure to ambient air pollution is associated with an increased risk of gestational diabetes mellitus, hypertensive disorder during pregnancy, preterm birth, and stillbirth. However, no previous study has focused on the association between the number of pregnancy complications and exposure to ambient air pollution.

OBJECTIVES

To investigate the association between prenatal exposure to ambient air pollutants and the number of pregnancy complications in high-risk pregnancies.

METHODS

We collected data on gestational diabetes mellitus, hypertensive disorder during pregnancy, preterm birth, and stillbirth from the National Health Information Databases, provided by the Korean National Health Insurance Service.R To assess individual-level exposure to air pollutants, a spatial prediction model and area-averaging approach were used.

RESULTS

From 2015 to 2018, data of 789,595 high-risk pregnancies were analyzed. The ratio of gestational diabetes mellitus in the country was the highest, followed by preterm birth, hypertensive disorder during pregnancy, and stillbirth. Approximately 71.7% of pregnant women (566,143) presented with one pregnancy complication in identical pregnancies, 27.5% (216,714) presented with two, and 0.9% (6738) presented with three or more. Multiple logistic regression models with adjustments for age, residence, and income variables indicated that the risk of having two or more pregnancy complications was positively associated with the exposure to higher levels of PM₁₀ (odds ratio [OR], 1.11; 95% confidence interval [CI], 1.09-1.12) and PM_2.5 (OR, 1.14; 95% CI, 1.12-1.15). The highest quartile presented higher odds of two or more pregnancy complications compared with the lower three quartiles of PM₁₀, PM_2.5, CO, NO₂, and SO₂ exposures (p < 0.001).

CONCLUSION

The results indicate that the risk of pregnancy complications is positively associated with the exposure to the high concentrations of PM₁₀, PM_2.5, CO, NO₂, and SO₂.

Air Pollution and Risk of Placental Abruption: A Study of Births in New York City, 2008-2014

We evaluated the associations of exposure to fine particulate matter (particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) at concentrations of <12 μg/m3, 12-14 μg/m3, and ≥15 μg/m3) and nitrogen dioxide (at concentrations of <26 parts per billion (ppb), 26-29 ppb, and ≥30 ppb) with placental abruption in a prospective cohort study of 685,908 pregnancies in New York, New York (2008-2014). In copollutant analyses, these associations were examined using distributed-lag nonlinear models based on Cox models. The prevalence of abruption was 0.9% (n = 6,025). Compared with a PM2.5 concentration less than 12 μg/m3, women exposed to PM2.5 levels of ≥15 μg/m3 in the third trimester had a higher rate of abruption (hazard ratio (HR) = 1.68, 95% confidence interval (CI): 1.41, 2.00). Compared with a nitrogen dioxide concentration less than 26 ppb, women exposed to nitrogen dioxide levels of 26-29 ppb (HR = 1.11, 95% CI: 1.02, 1.20) and ≥30 ppb (HR = 1.06, 95% CI: 0.96, 1.24) in the first trimester had higher rates of abruption. Compared with both PM2.5 and nitrogen dioxide levels less than the 95th percentile in the third trimester, rates of abruption were increased with both PM2.5 and nitrogen dioxide ≥95th percentile (HR = 1.44, 95% CI: 1.15, 1.80) and PM2.5 ≥95th percentile and nitrogen dioxide <95th percentile (HR = 1.43 95% CI: 1.23, 1.66). Increased levels of PM2.5 exposure in the third trimester and nitrogen dioxide exposure in the first trimester are associated with elevated rates of placental abruption, suggesting that these exposures may be important triggers of premature placental separation through different pathways.

Association of ambient particle pollution with gestational diabetes mellitus and fasting blood glucose levels in pregnant women from two Chinese birth cohorts

BACKGROUND

Fasting blood glucose may capture the adverse effects of air pollution on pregnant women better than the incidence of gestational diabetes mellitus (GDM), but evidence on the association between air pollution and maternal glucose concentrations is limited.

OBJECTIVE

To investigate the associations between air pollutants, GDM and fasting blood glucose during pregnancy.

METHODS

We recruited 2326 pregnant women from two birth cohorts located in Guangzhou and Heshan, the Pearl River Delta region (PRD), China. PM₁₀, PM_2.5 and black carbon (BC) exposure concentrations in the first and second trimesters of pregnancy were collected at fixed-site monitoring stations for each cohort. Multiple logistic regressions were employed to estimate the associations between particle pollution and GDM. Mixed-effects models were used to evaluate the associations of air pollutants with blood glucose levels. Restricted cubic spline functions were fitted to visualize the concentration-response relationships. Distributed lag non-linear models were used to estimate week-specific lag effects of particle pollution exposure on GDM and blood glucose. Unconstrained distributed lag models with lags of 0-3 weeks were used to examine potential cumulative effects.

RESULTS

We observed positive and significant associations of PM₁₀, PM_2.5 and BC exposure with fasting glucose, particularly in the second trimester. PM₁₀, PM_2.5 and BC were strongly correlated and displayed similar cumulative (lag 0-3 weeks) associations with fasting blood glucose. Exposure to particle pollution was not associated with 1-h or 2-h blood glucose. Models estimating the association between air pollutants and GDM were consistent with statistical insignificance.

CONCLUSIONS

Based on the results of the present study, exposure to air pollution during pregnancy exerts cumulative, adverse effects on fasting glucose levels. This study provides preliminary support for the use of blood glucose levels to explore the potential health impact of air pollution on pregnant women.

Ambient air pollution exposure during pregnancy and gestational diabetes mellitus in Shenyang, China: a prospective cohort study

The prevalence of gestational diabetes mellitus (GDM) is increasing worldwide. Reports of the association between air pollution exposure and GDM have been inconsistent in previous studies. We conducted a cohort study to investigate the associations between air pollution exposure and GDM in the city of Shenyang in Northeast China for the first time. We studied interactions with different air pollutant exposures and conducted a stratified analysis according to folic acid intake, age, body mass index (BMI), primiparity, and sleep quality. We found significant associations between prenatal exposure to NO_x and SO₂ and the development of GDM during the second trimester: the largest effect on GDM was exposure to SO₂ (odds ratio (OR): 1.77, 95% confidence interval (CI): 1.23-2.56) in the largest quartile compared with the lowest quartile. Significant interactions between age, BMI, parity, sleep quality, and air pollution exposures were observed; stratified analysis showed stronger associations between GDM and high air pollutant exposure in pregnant women with older age, larger BMI, poorer sleep quality, and more parity. We found that air pollution exposure during the second trimester was significantly associated with GDM in a prospective birth cohort study in Northeast China. SO₂, oxynitride (NOX, NO₂, NO), CO, and O₃ all showed a linear trend effect on GDM. Interactions between prenatal air pollution exposure and other factors, such as age at pregnancy, BMI before pregnancy, primiparity, folic acid intake, and sleep quality, during the second trimester might exist.

Residential radon exposure and hypertensive disorders of pregnancy in Massachusetts, USA: A cohort study

BACKGROUND

Exposure to ionizing radiation has been associated with hypertension, but the relationship between residential radon exposure and hypertensive disorders of pregnancy (HDP) has not been examined.

METHODS

We used the Massachusetts Birth Registry of Vital Records from 2001 to 2015 including women with a singleton pregnancy without prior hypertension. The binary outcome (HDP) included gestational hypertension and pre-eclampsia cases and was assessed using birth certificate data. We obtained 141,665 basement radon measurements from Spruce Environmental Technologies, Inc. and modeled the monthly zip code basement radon level. We used a logistic regression model adjusted for sociodemographic covariates, maternal comorbidities, PM_2.5, season, temperature, and relative humidity. We examined effect modification by maternal age, race, and maternal education as an indicator of socio-economic status.

RESULTS

Of 975,528 women, 3.7% (36,530) of them developed HDP. Zip code level radon ranged from 22 to 333 mBq/m³. An interquartile range (IQR) increase in zip code radon level throughout pregnancy was associated with a 15% increase in the odds of HDP (95% CI 13% to 18%). In women less than 20 years old, an IQR increase in zip code level radon was associated with 38% increase in the odds of HDP (95% CI 24% to 50%), while the effect was smaller in older women. There was no effect modification by maternal race or education.

CONCLUSIONS

In this cohort, higher levels of residential radon are associated with increased odds of HDP. After stratifying by age, this effect was stronger in participants younger than 20 years old. Since the burden of hypertensive disorders of pregnancy is increasing and affects women's future cardiovascular health, identification of modifiable risk factors is of great importance.

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, PM2.5 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, PM2.5 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.

The Associations of Ambient Fine Particulate Matter Exposure During Pregnancy With Blood Glucose Levels and Gestational Diabetes Mellitus Risk: A Prospective Cohort Study in Wuhan, China

Investigators in previous studies have drawn inconsistent conclusions regarding the relationship between relatively low exposure to fine particulate matter (particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5)) and risk of gestational diabetes mellitus (GDM), while the association between high PM2.5 exposure and GDM risk has not been well studied. We investigated the association of high PM2.5 exposure during pregnancy with blood glucose levels and GDM risk in Chinese women. The present study was conducted from August 2013 to May 2016 among 3,967 pregnant women in the Tongji Maternal and Child Health Cohort in Wuhan, China. PM2.5 exposure during pregnancy for each participant was estimated by means of land-use regression models. An interquartile-range increase in PM2.5 exposure (33.84 μg/m3 for trimester 1 and 33.23 μg/m3 for trimester 2) was associated with 36% (95% confidence interval (CI): 1.15, 1.61) and 23% (95% CI: 1.01, 1.50) increased odds of GDM during trimester 1 and trimester 2, respectively. An interquartile-range increment of PM2.5 exposure during trimester 1 increased 1-hour and 2-hour blood glucose levels by 1.40% (95% CI: 0.42, 2.37) and 1.82% (95% CI: 0.98, 2.66), respectively. The same increment of PM2.5 exposure during trimester 2 increased fasting glucose level by 0.85% (95% CI: 0.41, 1.29). Our findings suggest that high PM2.5 exposure during pregnancy increases blood glucose levels and GDM risk in Chinese women.

Ambient air pollution exposure associated with glucose homeostasis during pregnancy and gestational diabetes mellitus

BACKGROUND

To investigate the effects of air pollution exposure during pregnancy on the indicators of glucose homeostasis and gestational diabetes mellitus (GDM).

METHODS

We conducted a birth cohort study in Foshan, China during 2015-2019. Oral glucose tolerance test (OGTT) was administered to each participant during pregnancy. GDM was defined according to the International Association of Diabetes and Pregnancy Study Groups criteria (IADPSG). Air pollutant (fine particulate matter (PM_2.5), particulate matter with an aerodynamic diameter of 10 μm or less (PM₁₀), sulfate dioxide (SO₂), nitrogen dioxide (NO₂) and ozone (O₃)) concentrations from the air monitoring stations in Foshan were used to estimate individual air pollutant exposure during the first two trimesters. Linear and logistic regression models were employed to estimate the associations between air pollution exposure during the first two trimesters and OGTT glucose levels and GDM.

RESULTS

Of 12,842 pregnant women, 3055 (23.8%) had GDM. A 10 μg/m³ increase in PM_2.5, PM₁₀ and SO₂ during trimester 1, trimester 2 and two trimesters were associated with 0.07 mmol/L to 0.29 mmol/L increment in OGTT-fasting glucose levels in single-pollutant model. A 10 μg/m³ increase in NO₂ and O₃ during two trimesters were associated with 0.15 mmol/L and 0.12 mmol/L decrease in OGTT-fasting glucose in single-pollutant model. However, no significant or weaker effects of O₃ during two trimesters on OGTT-fasting glucose were observed in two-pollutant models. Moreover, exposure to PM_2.5, PM₁₀ and SO₂ were associated with increased risk of GDM in both single- and two-pollutant models.

CONCLUSIONS

Our study suggests PM_2.5, PM₁₀ and SO₂ exposure during the first two trimesters might increase the risk of GDM.

Particle air pollution and gestational diabetes mellitus in Houston, Texas

BACKGROUND

There is mixed evidence implicating prenatal exposure to particulate matter <2.5 μm in aerodynamic diameter (PM2.5) in the risk of gestational diabetes mellitus (GDM) and only one study has examined exposure to PM2.5 constituents, which vary with location because of different emission sources.

METHODS

We conducted a retrospective cohort study of singleton live births in Harris County, Texas from 2008 to 2013. With data from the Texas Commission on Environmental Quality (TCEQ), we spatially interpolated maternal exposures to total and speciated PM2.5, nitrogen dioxide (NO2) and ozone (O3) over the 12-week preconception period and trimesters 1 and 2. We estimated odds ratios (OR) and 95% confidence intervals (CI) for the association between pre-conception and pregnancy exposures to total and speciated PM2.5 and odds of GDM, adjusted for temperature and maternal covariates. We also evaluated confounding from NO2 and O3 exposures in multi-pollutant models.

RESULTS

An interquartile range (IQR) increase in total PM2.5 exposure was associated with elevated odds for developing GDM over the preconception (adjusted OR = 1.09, 95% CI: 1.06, 1.12), first trimester (OR = 1.13, 95% CI: 1.10, 1.17) and second trimester (OR = 1.13, 95% CI: 1.09, 1.17) periods. Effect estimates increased with adjustment for NO2 and O3. We observed modest increases in odds of GDM for IQR increases in first trimester ammonium ion PM2.5 (OR = 1.03, 95% CI: 1.00, 1.05) and sulfate PM2.5 (OR = 1.03, 95% CI: 1.00, 1.05) exposures, as well as preconception Cr PM2.5 exposures (OR = 1.05, 95% CI: 1.02, 1.07).

CONCLUSION

Exposures to PM2.5, before and during pregnancy were associated with elevated odds of GDM. Mitigating air pollution exposures may reduce the risk of GDM and its long-term implications for maternal and child health.

Associations of greenness with gestational diabetes mellitus: The Guangdong Registry of Congenital Heart Disease (GRCHD) study

Gestational diabetes mellitus (GDM) is associated with adverse short- and long-term health outcomes among mothers and their offspring. GDM affects 0.6%-15% of pregnancies worldwide and its incidence is increasing. However, intervention strategies are lacking for GDM. Previous studies indicated a protective association between greenspace and type 2 diabetes mellitus (T2DM), while few studies have explored the association between greenness and GDM. This study aimed to investigate the association between residential greenness and GDM among women from 40 clinical centers in Guangdong province, south China. The study population comprised 5237 pregnant mothers of fetuses and infants without birth defects, from 2004 to 2016. There were n = 157 diagnosed with GDM according to World Health Organization criteria. We estimated residential greenness using the Normalized Difference Vegetation Index (NDVI), derived from satellite imagery using a spatial-statistical model. Associations between greenness during pregnancy and GDM were assessed by confounder-adjusted random effects log-binomial regression models, with participating centers as the random effect. One interquartile increments of NDVI_250m, NDVI_500m and NDVI_1000m were associated with 13% (RR = 0.87, 95%CI: 0.87-0.87), 8% (RR = 0.92, 95%CI: 0.91-0.92) and 3% (RR = 0.97, 95%CI: 0.97-0.97) lower risks for GDM, respectively. However, NDVI_3000m was not significantly associated with GDM (RR = 0.96, 95%CI: 0.78-1.19). The risk for GDM decreased monotonically with greater NDVI. The protective effect of greenness on GDM was stronger among women with lower socioeconomic status and in environments with a lower level air pollutants. Our results suggest that greenness might provide an effective intervention to decrease GDM. Greenness and residential proximity to greenspace should be considered in community planning to improve maternal health outcomes.

Prenatal exposure to ambient air pollution and adverse pregnancy outcomes in Ahvaz, Iran: a generalized additive model

OBJECTIVE

There is some evidence about the short-term effects of air pollutants on adverse pregnancy outcomes. The aim of this study was to determine the association between air pollutants and spontaneous abortion, stillbirth, gestational hypertension, preeclampsia, gestational diabetes and macrosomia in Ahvaz, which is one of the most polluted cities in the Middle East.

METHODS

Data on adverse pregnancy outcomes and air pollutants including ozone (O₃), nitric oxide (NO), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), carbon monoxide (CO), particles with a diameter of less than 10 µm (PM₁₀) and particles with a diameter less than 2.5 µm (PM_2.5) were inquired from the Health Department of Ahvaz Jundishapur University of Medical Sciences and the Environmental Protection Agency of Khuzestan Province for the years 2008-2018. A time series analysis using the generalized additive model (GAM) with up to 6-day lags was used.

RESULTS

The results showed that the SO₂ pollutant on 0, 1, 3, 4, and 6-day lags and PM₁₀ on lag 0 had direct and significant associations with spontaneous abortion. NO, NO₂ and CO on 0-6-day lags, and O₃ on 6-day lags showed direct and significant associations with preeclampsia. NO and NO₂ pollutants showed significant and direct associations with gestational diabetes, during 0- and 6-day lags. NO on 0-, 3- and 4-day lags, CO in all 0-6-day lags and PM_2.5 on 1-, 3-, 5-, and 6-day lags showed direct and significant associations with macrosomia. None of the pollutants showed significant associations with stillbirth or gestational hypertension.

CONCLUSIONS

The results of this study suggest that some air pollutants are associated with spontaneous abortion, preeclampsia, gestational diabetes and macrosomia. This study further emphasizes the need to control ambient air pollution.

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.

Fine particular matter and its constituents in air pollution and gestational diabetes mellitus

BACKGROUND

Ambient air pollution has been linked to the development of gestational diabetes mellitus (GDM). However, previous studies provided inconsistent findings and no study has examined the effects of complex chemical constituents of the particular matter on GDM, especially in developing countries. Therefore, we aim to investigate the associations of exposure to PM_2.5 (particular matter ≤ 2.5 μm) and its constituents with GDM, and to identify susceptible exposure window in a large survey in China.

METHODS

The China Labor and Delivery Survey was a cross-sectional investigation conducted in 24 provinces in China between 2015 and 2016. A random sample of all deliveries in each participating hospital was selected and detailed obstetric and newborn information was extracted from medical records. Average concentrations of PM_2.5 and six constituents (organic matter, black carbon, sulfate, nitrate, ammonium and soil dust) were estimated (1 km × 1 km) using a combined geoscience-statistical model. GDM was diagnosed based on an oral glucose tolerance test (OGTT) between 24 to 28 weeks of gestation and according to IADPSG criteria. Generalized linear mixed models were used to adjust for potential confounders.

RESULTS

A total of 54,517 subjects from 55 hospitals were included. The incidence of GDM was 10.8%. An interquartile range (IQR) increase in PM_2.5 exposure in the 2nd trimester of pregnancy was associated with an increased GDM risk in the single pollutant model, [adjusted odds ratio (aOR) = 1.11 and 95% confidence interval (CI): 1.01-1.22]. Exposure to organic matter (aOR = 1.14; 95%CI: 1.05-1.23), black carbon (aOR = 1.15; 95%CI: 1.07-1.25) and nitrate (aOR = 1.13; 95%CI: 1.02-1.24) during 2nd trimester were associated with increased risks of GDM. Associations between constituents and GDM were robust after controlling for total PM_2.5 mass and accounting for multi-collinearity.

CONCLUSIONS

Exposure to PM_2.5 in 2^nd trimester of pregnancy was associated with an increased risk of GDM. Organic matter, black carbon and nitrate may be the main culprits for the association.

Adverse birth outcomes in Victoria, Australia in association with maternal exposure to low levels of ambient air pollution

BACKGROUND

The relationship between maternal exposure to air pollution and birth outcomes is not well characterised where ambient air pollution is relatively low.

OBJECTIVES

We aimed to explore the association between maternal exposure to ambient nitrogen dioxide (NO₂) and fine particulate matter (PM_2.5) and a range of birth outcomes in Victoria, Australia. Secondary aims were to explore whether obstetric conditions, such as gestational diabetes mellitus (GDM) and hypertensive disorders of pregnancy, were effect modifiers in observed relationships.

METHODS

We included all singleton births occurring in Victoria, Australia from 1^st March 2012 to 31^st December 2015 using routinely collected government data. Outcomes included birth weight, small for gestational age (SGA), term low birth weight (tLBW), large for gestational age (LGA), and spontaneous preterm birth (sPTB). We estimated exposure to annual ambient NO₂ and PM_2.5 concentrations, assigned to maternal residence at time of birth. Confounders included maternal, meteorological and temporal variables. Multivariable linear regression and log-binomial regression were used for continuous and dichotomous outcomes, respectively.

RESULTS

There were 285,594 births during the study period. Average NO₂ exposure was 6.0 parts per billion (ppb, median 5.6; interquartile range (IQR) 3.9) and PM_2.5 was 6.9 μg/m³ (median 7.1, IQR 1.3). IQR increases in ambient NO₂ and PM_2.5 were associated with fetal growth restriction, including decrements in birth weight (NO₂ β -22.8 g; 95%CI -26.0, -19.7; PM_2.5 β -14.8 g; 95%CI -17.4, -12.2) and increased risk of SGA (NO₂ RR 1.08; 95%CI 1.06, 1.10; PM_2.5 RR 1.05; 95%CI 1.04, 1.07) and tLBW (NO₂ RR 1.06; 95%CI 1.01, 1.10; PM_2.5 RR 1.04; 95%CI 1.03, 1.08). Women with GDM and hypertensive disorders of pregnancy had greater decrements in birth weight in association with pollutant exposure.

DISCUSSION

In this exploratory study using an annual metric of exposure, maternal exposure to low-level ambient air pollution was associated with fetal growth restriction, which carries substantial public health implications.

Increased risk of gestational diabetes mellitus in women with higher prepregnancy ambient PM2.5 exposure

BACKGROUND

Air pollution is a serious environmental problem in China. This study was designed to investigate whether exposure to particulate matter with an aerodynamic diameter ≤ 2.5 μm (PM_2.5) before pregnancy is associated with gestational diabetes mellitus (GDM) and fasting glucose in China.

METHODS

We recruited subjects and collected clinical data from the Nanjing Maternity and Child Health Care Hospital from July 2016 to October 2017. A series of validated land-use regression (LUR) models were built to assess individual exposure to PM_2.5 in a 1 × 1 km area at both work and home addresses following a time-weighted pattern. Multiple linear regression and logistic regression analyses were performed to examine the association between PM_2.5 exposure and GDM and fasting glucose.

RESULTS

In total, 11,639 of 16,995 women were included in the final analysis. Among the 11,639 women, 2776 (23.85%) had GDM. Individual exposure to PM_2.5 within three months before pregnancy ranged from 21.58 to 85.92 μg/m³. Positive associations were observed among the interquartile ranges (IQRs) of exposure to PM_2.5 within three months before pregnancy and GDM (OR = 2.61, 95% CI: 1.40-4.93, p < .01) as well as fasting glucose levels (β = 0.57, 95% CI: 0.45-0.68, p < .01). The diabetogenic effects of PM_2.5 gradually increased from the first month before pregnancy, peaked in the second month and then gradually decreased until the third month when the week-specific exposure were analyzed to identify the sensitive time window.

CONCLUSION

Our study confirmed that higher exposure to PM_2.5 within three months before pregnancy is significantly associated with increased risk of GDM and elevated fasting glucose levels, reflecting the importance of preconceptional environmental exposure in the development of maternal GDM.

Prenatal Fine Particulate Matter (PM2.5) Exposure and Pregnancy Outcomes-Analysis of Term Pregnancies in Poland

Air pollution is currently one of the greatest threats to global health. Polish cities are among the most heavily polluted in Europe. Due to air pollution 43,100 people die prematurely in Poland every year. However, these data do not take into account the health consequences of air pollution for unborn children. Thus, the aim of this study was to evaluate the effects of the fine particulate matter air pollution (less than 2.5 μm in diameter) on pregnancy outcomes. An analysis of pregnant women and their children was made using a questionnaire survey from a nationwide study conducted in 2017. Questionnaires from 1095 pregnant women and data from their medical records were collected. An analysis of air pollution in Poland was conducted using the air quality database maintained by the Chief Inspectorate for Environmental Protection in Poland. A higher concentration of PM_2.5 was associated with a decrease in birth weight and a higher risk of low birthweight (i.e., <2500 g). We also observed lower APGAR scores. Thus, all possible efforts to reduce air pollution are critically needed.

Exposure to urban particulate matter and its association with human health risks

Human health and environmental risks are increasing following air pollution associated with vehicular and industrial emissions in which particulate matter is a constituent. The purpose of this review was to assess studies on the health effects and mortality induced by particles published for the last 15 years. The literature survey indicated the existence of strong positive associations between fine and ultrafine particles' exposure and cardiovascular, hypertension, obesity and type 2 diabetes mellitus, cancer health risks, and mortality. Its exposure is also associated with increased odds of hypertensive and diabetes disorders of pregnancy and premature deaths. The ever increasing hospital admission and mortality due to heart failure, diabetes, hypertension, and cancer could be due to long-term exposure to particles in different countries. Therefore, its effect should be communicated for legal and scientific actions to minimize emissions mainly from traffic sources.

Associations of exposure to fine particulate matter during pregnancy with maternal blood glucose levels and gestational diabetes mellitus: Potential effect modification by ABO blood group

BACKGROUND

Previous studies have examined the relationships between prenatal fine particulate matter (PM_2.5) exposure and gestational diabetes mellitus (GDM), but the results were inconsistent. Furthermore, the possible effect modification by ABO blood group has not been explored.

OBJECTIVES

To assess the associations of PM_2.5 exposures during pregnancy with maternal glucose levels as well as GDM, and further to evaluate the potential effect modification by ABO blood group.

METHODS

Between January 2013 and January 2015, 4783 pregnant women were enrolled in our study based on a birth cohort in Wuhan. Daily PM_2.5 exposure levels for each woman during pregnancy were estimated using a spatial-temporal land-use regression model. Linear regressions with general estimating equations (GEE) were performed to assess the associations between trimester-specific PM_2.5 exposures and maternal glucose levels. Modified Poisson regressions with GEE analyses were used to evaluate the impacts of PM_2.5 exposures during each trimester on the risk of GDM. The associations of PM_2.5 exposure during the whole study period with glucose levels and GDM were estimated using multiple linear regression model and modified Poisson regression model, respectively. We conducted a stratified analysis to explore the potential effect modification by ABO blood group.

RESULTS

Among all the 4783 participants, 394 (8.24%) had GDM. Exposure to PM_2.5 was found to be positively associated with elevated fasting glucose level during the whole study period [0.382 mg/dL, 95% confidence interval (CI): 0.179-0.586, per 10 μg/m³ increase in PM_2.5], the first trimester (0.154 mg/dL ,95% CI: 0.017-0.291) and the second trimester (0.541 mg/dL, 95% CI: 0.390-0.692). No statistically significant results were observed between PM_2.5 and 1-h and 2-h glucose levels during any study period. Increased risks of GDM for each 10 μg/m³ increase in PM_2.5 levels were observed during the whole study period [relative risk (RR): 1.120, 95% CI: 1.021-1.228] and the first trimester (RR: 1.074, 95% CI: 1.012-1.141), but not the second trimester (RR: 1.035, 95% CI: 0.969-1.106). Stratified analysis indicated that the associations of PM_2.5 exposures with GDM were more pronounced among pregnant women with blood group A, but no significant effect modifications were observed.

CONCLUSION

Our study enriched epidemiological evidence linking PM_2.5 exposures during pregnancy to elevated maternal glucose levels and increased risk of GDM. More importantly, we first highlighted that the impact of PM_2.5 on GDM might be greater among pregnant women with blood group A.

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.