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

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.

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.

Maternal obesity and diabetes during pregnancy and early autism screening score at well-child visits in standard clinical practice

LAY ABSTRACT

Early intervention and treatment can help reduce disability in children diagnosed with autism spectrum disorder. Screening for autism spectrum disorder in young children identifies those at increased likelihood of diagnosis who may need further support. Previous research has reported that exposure to maternal obesity and diabetes during pregnancy is associated with higher likelihood of autism spectrum disorder diagnosis in children. However, little is known about whether these maternal conditions are associated with how very young children score on autism spectrum disorder screening tools. This study examined associations between exposure to maternal obesity and diabetes during pregnancy and offspring scores on the Quantitative Checklist for Autism in Toddlers, an autism spectrum disorder screening questionnaire administered between 18-24 months at well-child visits. A higher score on the Quantitative Checklist for Autism in Toddlers suggests a higher likelihood of autism spectrum disorder; children with scores 3 or greater are referred to developmental pediatricians for evaluation. Our study found that children of mothers with obesity or diabetes during pregnancy had higher scores than children whose mothers did not have these conditions. Associations with maternal obesity and gestational diabetes diagnosed at or before 26 weeks of pregnancy were also present in children who did not have later autism spectrum disorder diagnoses, suggesting that exposure to these conditions during early pregnancy may be associated with a broad range of social and behavioral abilities. Identifying associations between maternal health conditions and early Quantitative Checklist for Autism in Toddlers screening scores could influence future screening and provision of support for children of mothers with these conditions.

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.

Telomere Length in Patients with Gestational Diabetes Mellitus and Normoglycemic Pregnant Women: a Systematic Review and Meta-analysis

We performed a systematic review and meta-analysis of studies assessing telomere length in blood leukocytes or mononuclear cells in women with gestational diabetes mellitus (GDM) and normoglycemic pregnant women (NPW) and their infants. The review protocol was registered in PROSPERO (CRD42022300950). Searches were conducted in PubMed, Embase, LILACS, CNKI, and Wang Fang, from inception through November 2022. The primary outcomes were maternal and offspring telomere length. The Newcastle-Ottawa Scale was used to assess the quality of included studies. Random-effect meta-analyses were applied to estimate standardized mean differences (SMDs) and their 95% confidence interval (CI). The meta-analysis of four studies showed no significant maternal telomere length difference (SMD = -0.80, 95% CI: -1.66, 0.05) in women with GDM compared to NPW. In the sensibility analysis omitting one study with a small sample of women, the telomere length becomes significantly reduced in women with GDM (SMD = -1.10, 95% CI: -2.18, -0.02). GDM patients had increased glucose (SMD = 0.28, 95% CI: 0.09, 0.46) and glycosylated hemoglobin than NPW (SMD = 0.62, 95% CI: 0.23, 1.01) while total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides did not display differences between women with and without GDM. There was no significant difference in cord blood telomere length in offspring from women with GDM and NPW (SMD = 0.11, 95% CI: -0.52, 0.30). Cord blood insulin levels (SMD = 0.59, 95% CI: 0.33, 0.85) and birthweight (SMD = 0.59, 95% CI: 0.39, 0.79) were higher in offspring from pregnant women with GDM than in those from NPW. There were no significant differences in maternal and offspring telomere length between pregnancies with and without GDM.

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.

Effects of air pollution on adverse birth outcomes and pregnancy complications in the U.S. state of Kansas (2000-2015)

Neonatal mortality and morbidity are often caused by preterm birth and lower birth weight. Gestational diabetes mellitus (GDM) and gestational hypertension (GH) are the most prevalent maternal medical complications during pregnancy. However, evidence on effects of air pollution on adverse birth outcomes and pregnancy complications is mixed. Singleton live births conceived between January 1st, 2000, and December 31st, 2015, and reached at least 27 weeks of pregnancy in Kansas were included in the study. Trimester-specific and total pregnancy exposures to nitrogen dioxide (NO2), particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5), and ozone (O3) were estimated using spatiotemporal ensemble models and assigned to maternal residential census tracts. Logistic regression, discrete-time survival, and linear models were applied to assess the associations. After adjustment for demographics and socio-economic status (SES) factors, we found increases in the second and third trimesters and total pregnancy O3 exposures were significantly linked to preterm birth. Exposure to the second and third trimesters O3 was significantly associated with lower birth weight, and exposure to NO2 during the first trimester was linked to an increased risk of GDM. O3 exposures in the first trimester were connected to an elevated risk of GH. We didn't observe consistent associations between adverse pregnancy and birth outcomes with PM2.5 exposure. Our findings indicate there is a positive link between increased O3 exposure during pregnancy and a higher risk of preterm birth, GH, and decreased birth weight. Our work supports limiting population exposure to air pollution, which may lower the likelihood of adverse birth and pregnancy outcomes.

Association between exposure to air pollution during preconception and risk of gestational diabetes mellitus: The role of anti-inflammatory diet

BACKGROUND

Regarding the association between the sensitive time-windows of air pollution (AP) exposure and gestational diabetes mellitus (GDM), epidemiological findings are inconsistent. The dietary inflammatory potential has been implicated in the development of GDM, but it is unclear whether an anti-inflammatory diet during pregnancy reduces the association between AP and GDM.

OBJECTIVE

We aimed to characterize the sensitive time-windows of AP to GDM risk. Further, to verify whether a maternal anti-inflammatory diet can reduce the risk of AP-induced GDM, by inhibiting inflammation.

METHODS

A total of 8495 pregnant women were included between 2015 and 2021 in the Maternal & Infants Health in Hefei study. Weekly mean AP exposure to fine particles (PM2.5 and PM10), SO2, and NO2 was estimated from the data of Hefei City Ecology and Environment Bureau. High-sensitivity C-reactive protein (hs-CRP) concentrations were measured to evaluate systemic inflammation. The empirical dietary inflammatory pattern (EDIP) score based on a validated food frequency questionnaire was used to assess the dietary inflammatory potential of pregnant women. Logistic regression models with distributed lags were used to identify the sensitive time-window for the effect of AP on GDM. Mediation analysis estimated the mediated effect of hs-CRP, linking AP with GDM. Stratified analysis was used to investigate the potential effect of anti-inflammatory diet on GDM risk.

RESULTS

The increased risks of GDM were found to be positively associated with exposure to PM2.5 (OR = 1.11, 95% CI:1.07-1.15), PM10 (OR = 1.12, 95% CI:1.09-1.16), and SO2 (OR = 1.42, 95% CI:1.25-1.60) by distributed lag models, and the critical exposure windows were 21st to 28th weeks of preconception. The proportion of association between PM2.5, PM10, and SO2 with GDM mediated by hs-CRP was 25.9%, 21.1%, and 19.4%, respectively, according to mediation analysis. In the stratified analyses by EDIP, the association between AP and GDM was not statistically significant among women those with anti-inflammatory diets.

CONCLUSIONS

Exposure to AP, especially in 21st to 28th week of preconception, is associated with risk of GDM, which is partly mediated by hs-CRP. Adherence to the anti-inflammatory dietary pattern may reduce the risk of AP-induced GDM.

Ambient air pollution and maternal cardiovascular health in pregnancy

In this review, we summarise the current epidemiological and experimental evidence on the association of ambient (outdoor) air pollution exposure and maternal cardiovascular health during pregnancy. This topic is of utmost clinical and public health importance as pregnant women represent a potentially susceptible group due to the delicate balance of the feto-placental circulation, rapid fetal development and tremendous physiological adaptations to the maternal cardiorespiratory system during pregnancy.Several meta-analyses including up to 4 245 170 participants provide robust evidence that air pollutants, including particulate matter, nitrogen oxides and others, have adverse effects on the development of hypertensive disorders of pregnancy, gestational diabetes mellitus and cardiovascular events during labour. Potential underlying biological mechanisms include oxidative stress with subsequent endothelial dysfunction and vascular inflammation, β-cell dysfunction and epigenetic changes. Endothelial dysfunction can lead to hypertension by impairing vasodilatation and promoting vasoconstriction. Air pollution and the consequent oxidative stress can additionally accelerate β-cell dysfunction, which in turn triggers insulin resistance leading to gestational diabetes mellitus. Epigenetic changes in placental and mitochondrial DNA following air pollution exposures can lead to altered gene expression and contribute to placental dysfunction and induction of hypertensive disorders of pregnancy.The maternal and fetal consequences of such cardiovascular and cardiometabolic disease during pregnancy can be serious and long lasting, including preterm birth, increased risk of type 2 diabetes mellitus or cardiovascular disease later in life. Acceleration of efforts to reduce air pollution is therefore urgently needed to realise the full health benefits for pregnant mothers and their children.

Preconceptional and prenatal exposure to air pollutants and risk of gestational diabetes in the MADRES prospective pregnancy cohort study

Background

Air pollution has been associated with gestational diabetes mellitus (GDM). We aim to investigate susceptible windows of air pollution exposure and factors determining population vulnerability.

Methods

We ascertained GDM status in the prospective Maternal and Developmental Risks from Environmental and Social Stressors (MADRES) pregnancy cohort from Los Angeles, California, USA. We calculated the relative risk of GDM by exposure to ambient particulate matter (PM10; PM2.5), nitrogen dioxide (NO2), and ozone (O3) in each week from 12 weeks before to 24 weeks after conception, adjusting for potential confounders, with distributed lag models to identify susceptible exposure windows. We examined effect modification by prenatal depression, median-split pre-pregnancy BMI (ppBMI) and age.

Findings

Sixty (9.7%) participants were diagnosed with GDM among 617 participants (mean age: 28.2 years, SD: 5.9; 78.6% Hispanic, 11.8% non-Hispanic Black). GDM risk increased with exposure to PM2.5, PM10, and NO2 in a periconceptional window ranging from 5 weeks before to 5 weeks after conception: interquartile-range increases in PM2.5, PM10, and NO2 during this window were associated with increased GDM risk by 5.7% (95% CI: 4.6-6.8), 8.9% (8.1-9.6), and 15.0% (13.9-16.2), respectively. These sensitive windows generally widened, with greater effects, among those with prenatal depression, with age ≥28 years, or with ppBMI ≥27.5 kg/m2, than their counterparts.

Interpretation

Preconception and early-pregnancy are susceptible windows of air pollutants exposure that increased GDM risk. Prenatal depression, higher age, or higher ppBMI may increase one's vulnerability to air pollution-associated GDM risk.

Funding

National Institutes of Health, Environmental Protection Agency.

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.

Maternal particulate matter exposure and gestational diabetes mellitus: a population-based cohort study

BACKGROUND

Gestational diabetes mellitus prevalence is steadily increasing worldwide, posing a significant threat to the short-term and long-term health of both mother and offspring. Because particulate matter air pollution has been reported to affect glucose metabolism, it was suggested that maternal particulate matter exposure may be associated with the development of gestational diabetes mellitus; however, the evidence is limited and inconsistent.

OBJECTIVE

This study aimed to determine the association between maternal exposure to particulate matter of diameter ≤2.5 µm and of diameter of ≤10 µm and the risk of gestational diabetes mellitus, to identify critical windows of susceptibility and to evaluate effect modification by ethnicity.

STUDY DESIGN

A retrospective cohort study was conducted including pregnancies of women who delivered at a large tertiary medical center in Israel between 2003 and 2015. Residential particulate matter levels were estimated by a hybrid spatiotemporally resolved satellite-based model at 1 km spatial resolution. Multivariable logistic analyses were applied to study the association between maternal particulate matter exposure in different pregnancy periods and gestational diabetes mellitus risk, while adjusting for background, obstetrical, and pregnancy characteristics. Analyses were also stratified by ethnicity (Jewish and Bedouin).

RESULTS

The study included 89,150 pregnancies, of which 3245 (3.6%) were diagnosed with gestational diabetes mellitus. First trimester exposure to both particulate matter of diameter ≤2.5 µm (adjusted odds ratio per 5 μg/m3, 1.09; 95% confidence interval, 1.02-1.17) and particulate matter of diameter of ≤10 µm (adjusted odds ratio per 10 μg/m3, 1.11; 95% confidence interval, 1.06-1.17) was significantly associated with increased risk for gestational diabetes mellitus. In the stratified analyses, the association with first trimester particulate matter of diameter of ≤10 µm exposure was consistent among pregnancies of both Jewish and Bedouin women, whereas the association with first trimester particulate matter of diameter ≤2.5 µm exposure was significant among pregnancies of Jewish women only (adjusted odds ratio per 5 μg/m3, 1.09; 95% confidence interval, 1.00-1.19), as well as association with preconception particulate matter of diameter of ≤10 µm exposure (adjusted odds ratio per 10 μg/m3, 1.07; 95% confidence interval, 1.01-1.14). No association was found between second trimester particulate matter exposure and gestational diabetes mellitus risk.

CONCLUSION

Maternal exposure to both particulate matter of diameter ≤2.5 µm and diameter of 10 µm or less during the first trimester of pregnancy is associated with gestational diabetes mellitus, suggesting that the first trimester is a particular window of susceptibility to the effect of particulate matter exposure on gestational diabetes mellitus risk. The effects found in this study differed by ethnic group, emphasizing the importance of addressing ethnic disparities when assessing environmental impacts on health.

Third trimester as the susceptibility window for maternal PM2.5 exposure and preterm birth: A nationwide surveillance-based association study in China

Maternal PM_2.5 exposure has been identified as a potential risk factor for preterm birth, yet the inconsistent findings on the susceptible exposure windows may be partially due to the influence of gaseous pollutants. This study aims to examine the association between PM_2.5 exposure and preterm birth during different susceptible exposure windows after adjusting for exposure to gaseous pollutants. We collected 2,294,188 records of singleton live births from 30 provinces of China from 2013 to 2019, and the gridded daily concentrations of air pollutants (including PM_2.5, O₃, NO₂, SO₂, and CO) were derived by using machine learning models for assessing individual exposure. We employed logistic regression to develop single-pollutant models (including PM_2.5 only) and co-pollutant models (including PM_2.5 and a gaseous pollutant) to estimate the odds ratio for preterm birth and its subtypes, with adjustment for maternal age, neonatal sex, parity, meteorological conditions, and other potential confounders. In the single-pollutant models, PM_2.5 exposure in each trimester was significantly associated with preterm birth, and the third trimester exposure showed a stronger association with very preterm birth than that with moderate to late preterm birth. The co-pollutant models revealed that preterm birth might be significantly associated only with maternal exposure to PM_2.5 in the third trimester, and not with exposure in the first or second trimester. The observed significant associations between preterm birth and maternal PM_2.5 exposure in the first and second trimesters in single-pollutant models might primarily be influenced by exposure to gaseous pollutants. Our study provides evidence that the third trimester may be the susceptible window for maternal PM_2.5 exposure and preterm birth. The association between PM_2.5 exposure and preterm birth could be influenced by gaseous pollutants, which should be taken into consideration when evaluating the impact of PM_2.5 exposure on maternal and fetal health.

Association between maternal exposure to air pollution and gestational diabetes mellitus in Taiyuan, North China

BACKGROUND

The effect of air pollution on human health has been a major concern, especially the association between air pollution and gestational diabetes mellitus (GDM).

METHODS

In this study, we conducted a retrospective cohort study in Taiyuan, a typical energy production base in China. This study included 28,977 pairs of mothers and infants between January 2018 and December 2020. To screen for GDM, oral glucose tolerance test (OGTT) was performed in pregnant women at 24-28 weeks of gestation. Logistic regression was used to assess the trimester-specific association between 5 common air pollutants (PM₁₀, PM_2.5, NO₂, SO₂, and O₃) and GDM, and the weekly-based association was also assessed using distributed lag non-linear models (DLNMs). Odds ratios (ORs) with 95 % confidence intervals (CIs) were calculated for the association between GDM and each air pollutant.

RESULTS

The overall incidence of GDM was 3.29 %. PM_2.5 was positively associated with GDM over the second trimester (OR [95 % CI], 1.105 [1.021, 1.196]). O₃ was positively associated with GDM in the preconception period (OR [95 % CI], 1.125 [1.024, 1.236]), the first trimester (OR [95 % CI], 1.088 [1.019, 1.161]) and the 1st + 2nd trimester (OR [95 % CI], 1.643 [1.387, 1.945]). For the weekly-based association, PM_2.5 was positively associated with GDM at 19-24 weeks of gestation, with the strongest association at week 24 (OR [95 % CI], 1.044 [1.021, 1.067]). PM₁₀ was positively associated with GDM at 18-24 weeks of gestation, with the strongest association at week 24 (OR [95 % CI], 1.016 [1.003, 1.030]). O₃ was positively associated with GDM during the 3rd week before conception to the 8th gestational week, with the strongest association at week 3 of gestation (OR [95 % CI], 1.054 [1.032, 1.077]).

CONCLUSION

The findings are important for the development of effective air quality policies and the optimization of preventive strategies for preconception and prenatal care.

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.

The effect of ambient ozone exposure on three types of diabetes: a meta-analysis

BACKGROUND

Ozone as an air pollutant is gradually becoming a threat to people's health. However, the effect of ozone exposure on risk of developing diabetes, a fast-growing global metabolic disease, remains controversial.

OBJECTIVE

To evaluate the impact of ambient ozone exposure on the incidence rate of type 1, type 2 and gestational diabetes mellitus.

METHOD

We systematically searched PubMed, Web of Science, and Cochrane Library databases before July 9, 2022, to determine relevant literature. Data were extracted after quality evaluation according to the Newcastle Ottawa Scale (NOS) and the agency for healthcare research and quality (AHRQ) standards, and a meta-analysis was used to evaluate the correlation between ozone exposure and type 1 diabetes mellitus (T1D), type 2 diabetes mellitus (T2D), and gestational diabetes mellitus (GDM). The heterogeneity test, sensitivity analysis, and publication bias were performed using Stata 16.0.

RESULTS

Our search identified 667 studies from three databases, 19 of which were included in our analysis after removing duplicate and ineligible studies. Among the remaining studies, three were on T1D, five were on T2D, and eleven were on GDM. The result showed that ozone exposure was positively correlated with T2D [effect size (ES) = 1.06, 95% CI: 1.02, 1.11] and GDM [pooled odds ratio (OR) = 1.01, 95% CI: 1.00, 1.03]. Subgroup analysis demonstrated that ozone exposure in the first trimester of pregnancy might raise the risk of GDM. However, no significant association was observed between ozone exposure and T1D.

CONCLUSION

Long-term exposure to ozone may increase the risk of T2D, and daily ozone exposure during pregnancy was a hazard factor for developing GDM. Decreasing ambient ozone pollution may reduce the burden of both diseases.

The relationship between air pollutants and gestational diabetes: an updated systematic review and meta-analysis

PURPOSE

Air pollution is an environmental stimulus that may predispose pregnant women to gestational diabetes mellitus (GDM). This systematic review and meta-analysis were conducted to investigate the relationship between air pollutants and GDM.

METHODS

PubMed, Web of Science, and Scopus were systematically searched for retrieving English articles published from January 2020 to September 2021, investigating the relationship of exposure to ambient air pollution or levels of air pollutants with GDM and related parameters, including fasting plasma glucose (FPG), insulin resistance, and impaired glucose tolerance. Heterogeneity and publication bias were evaluated using I-squared (I2), and Begg's statistics, respectively. We also performed the subgroup analysis for particulate matters (PM2.5, PM10), Ozone (O3), and sulfur dioxide (SO2) in the different exposure periods.

RESULTS

A total of 13 studies examining 2,826,544 patients were included in this meta-analysis. Compared to non-exposed women, exposure to PM2.5 increases the odds (likelihood of occurrence outcome) of GDM by 1.09 times (95% CI 1.06, 1.12), whereas exposure to PM10 has more effect by OR of 1.17 (95% CI 1.04, 1.32). Exposure to O3 and SO2 increases the odds of GDM by 1.10 times (95% CI 1.03, 1.18) and 1.10 times (95% CI 1.01, 1.19), respectively.

CONCLUSIONS

The results of the study show a relationship between air pollutants PM2.5, PM10, O3, and SO2 and the risk of GDM. Although evidence from various studies can provide insights into the linkage between maternal exposure to air pollution and GDM, more well-designed longitudinal studies are recommended for precise interpretation of the association between GDM and air pollution by adjusting all potential confounders.

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.

Associations of ozone exposure with gestational diabetes mellitus and glucose homeostasis: Evidence from a birth cohort in Shanghai, China

BACKGROUND

Associations between individual exposure to ozone (O₃) and gestational diabetes mellitus (GDM) have rarely been investigated, and critical windows of O₃ exposure for GDM have not been identified.

OBJECTIVES

We aimed to explore the associations of gestational O₃ exposure with GDM and glucose homeostasis as well as to identify the potential critical windows.

METHODS

A total of 7834 pregnant women were included. Individual O₃ exposure concentrations were evaluated using a high temporal-spatial resolution model. Each participant underwent an oral glucose tolerance test (OGTT) to screen for GDM between 24 and 28 gestational weeks. Multiple logistic and multiple linear regression models were used to estimate the associations of O₃ with GDM risks and with blood glucose levels of OGTT, respectively. Distributed lag nonlinear models (DLNMs) were used to estimate the critical windows of O₃ exposure for GDM.

RESULTS

Nearly 13.29 % of participants developed GDM. After controlling for covariates, we observed increased GDM risks per IQR increment of O₃ exposure in the first trimester (OR = 1.738, 95 % CI: 1.002-3.016) and the first two trimesters (OR = 1.576, 95 % CI: 1.005-2.473). Gestational O₃ exposure was positively associated with increased fasting blood glucose (the first trimester: β = 2.964, 95 % CI: 1.529-4.398; the first two trimesters: β = 1.620, 95 % CI: 0.436-2.804) and 2 h blood glucose (the first trimester: β = 6.569, 95 % CI: 1.775-11.363; the first two trimesters: β = 6.839, 95 % CI: 2.896-10.782). We also observed a concentration-response relationship of gestational O₃ exposure with GDM risk, as well as fasting and 2 h blood glucose levels. Additionally, 5-10 gestational weeks was identified as a critical window of O₃ exposure for GDM development.

CONCLUSION

In summary, we found that gestational O₃ exposure disrupts glucose homeostasis and increases the risk of GDM in pregnant women. Furthermore, 5-10 gestational weeks could be a critical window for the effects of O₃ exposure on GDM.

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.

Ambient air pollution during pregnancy and DNA methylation in umbilical cord blood, with potential mediation of associations with infant adiposity: The Healthy Start study

BACKGROUND

Prenatal exposure to ambient air pollution has been associated with adverse offspring health outcomes. Childhood health effects of prenatal exposures may be mediated through changes to DNA methylation detectable at birth.

METHODS

Among 429 non-smoking women in a cohort study of mother-infant pairs in Colorado, USA, we estimated associations between prenatal exposure to ambient fine particulate matter (PM2.5) and ozone (O3), and epigenome-wide DNA methylation of umbilical cord blood cells at delivery (2010-2014). We calculated average PM2.5 and O3 in each trimester of pregnancy and the full pregnancy using inverse-distance-weighted interpolation. We fit linear regression models adjusted for potential confounders and cell proportions to estimate associations between air pollutants and methylation at each of 432,943 CpGs. Differentially methylated regions (DMRs) were identified using comb-p. Previously in this cohort, we reported positive associations between 3rd trimester O3 exposure and infant adiposity at 5 months of age. Here, we quantified the potential for mediation of that association by changes in DNA methylation in cord blood.

RESULTS

We identified several DMRs for each pollutant and period of pregnancy. The greatest number of significant DMRs were associated with third trimester PM2.5 (21 DMRs). No single CpGs were associated with air pollutants at a false discovery rate <0.05. We found that up to 8% of the effect of 3rd trimester O3 on 5-month adiposity may be mediated by locus-specific methylation changes, but mediation estimates were not statistically significant.

CONCLUSIONS

Differentially methylated regions in cord blood were identified in association with maternal exposure to PM2.5 and O3. Genes annotated to the significant sites played roles in cardiometabolic disease, immune function and inflammation, and neurologic disorders. We found limited evidence of mediation by DNA methylation of associations between third trimester O3 exposure and 5-month infant adiposity.

Association of ambient fine particulate matter exposure with gestational diabetes mellitus and blood glucose levels during pregnancy

BACKGROUND

Previous studies have examined the associations between ambient fine particulate matter (PM_2.5) exposure and gestational diabetes mellitus (GDM). However, limited studies explored the relationships between PM_2.5 exposure and blood glucose levels during pregnancy, especially in highly polluted areas.

OBJECTIVES

To examine the associations of prenatal ambient PM_2.5 exposure with GDM and blood glucose levels, and to identify the sensitive exposure windows in a highly air-polluted area.

METHODS

From July 2016 to October 2017, a birth cohort study was conducted in Beijing, China. Participants were interviewed in each trimester regarding demographics, lifestyle, living and working environment, and medical conditions. Participant's daily ambient PM_2.5 levels from 3 m before last menstrual period (LMP) to the third trimester was estimated by a hybrid spatiotemporal model. Indoor air quality index was calculated based on environmental tobacco smoke, ventilation, cooking, painting, pesticide, and herbicide use. Distributed lag non-linear model was applied to explore the sensitive weeks of PM_2.5 exposure.

RESULTS

Of 165 pregnant women, 23 (13.94%) developed GDM. After adjusting for potential confounders, PM_2.5 exposure during the 1^st trimester was associated with higher odds of GDM (10 μg/m³ increase: OR = 1.89, 95% CI: 1.04-3.49). Each 10 μg/m³ increase in PM_2.5 during the 2^nd trimester was associated with 17.70% (2.21-33.20), 15.99% (2.96-29.01), 18.82% (4.11-33.52), and 17.10% (3.28-30.92) increase in 1-h, 2-h, Δ1h-fasting (1-h minus fasting), and Δ2h-fasting (2-h minus fasting) blood glucose levels, respectively. PM_2.5 exposure at 24^th-27^th weeks after LMP was associated with increased GDM risk. We identified sensitive exposure windows of 21^st-24^th weeks for higher 1-h and 2-h blood glucose levels and of 20^th-22^nd weeks for increased Δ1h-fasting and Δ2h-fasting.

CONCLUSIONS

Ambient PM_2.5 exposure during the second trimester was associated with higher odds of GDM and higher blood glucose levels. Avoiding exposure to high air pollution levels during the sensitive windows might prevent women from developing GDM.

Maternal obesity, diabetes, preeclampsia, and asthma during pregnancy and likelihood of autism spectrum disorder with gastrointestinal disturbances in offspring

LAY ABSTRACT

Autism spectrum disorder is heterogeneous and often accompanied by co-occurring conditions. Previous studies have shown that maternal health conditions during pregnancy including obesity, diabetes, preeclampsia, and asthma were associated with increased likelihood of autism. However, little has been done examining the likelihood associated with autism with co-occurring conditions. This study assessed these maternal health conditions in relationship to autism and gastrointestinal disturbances, a common co-occurring condition in children diagnosed with autism. Data included 308,536 mother-child pairs from one integrated health care system with comprehensive electronic medical records. Among the study cohort, 5,131 (1.7%) children had a diagnosis of autism by age 5. Gastrointestinal disturbances were present in 35.4% of children diagnosed with autism and 25.1% of children without autism diagnoses. Our results showed that each of the four maternal health conditions during pregnancy was associated with increased likelihood of gastrointestinal disturbances, autism without gastrointestinal disturbances, and autism with gastrointestinal disturbances. For all four maternal health conditions, the association was greatest for likelihood of autism with gastrointestinal disturbances. Given that children diagnosed with autism are more likely to have gastrointestinal disturbances and over 80% of gastrointestinal disturbances in this cohort were diagnosed prior to autism diagnosis, this study suggests that there may be common biological pathways between autism and gastrointestinal disturbances impacted by these maternal exposures. Future studies are warranted to assess associations between different exposures and autism with other co-occurring conditions to increase our understanding of autism 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.

Number of parous events affects the association between physical exercise and glycemic control among women with gestational diabetes mellitus: A prospective cohort study

BACKGROUND

Multiparous women are at a higher risk of gestational diabetes mellitus (GDM) than primiparas. Physical activity during pregnancy has been shown to be beneficial for GDM, but there is little evidence on the association between physical activity and glycemic control among women with GDM, whether primiparas or multiparas. Thus, the objective of the present study was to examine the association between physical activity and glycemic control in women with GDM and to determine what, if any, effects result from number of parous events.

METHODS

A prospective cohort of 1162 women with GDM was recruited, with 604 multiparas (51.98%). The general linear model was used to calculate the risk difference and its 95% confidence interval (95%CI) to quantify the impact of parous events on glycemic control in pregnancy as well as the association between physical activity time and glycemic control.

RESULTS

Among 1162 women with GDM, the median daily activity time was 65 min (interquartile range (IQR): 45-90 min), and the abnormal plasma glucose (PG) percentage, calculated as number of abnormal PG tests divided by the total number of PG tests, was 40.00% (IQR: 22.22%-66.67%). The percentage of abnormal PG was stabilized and statistically lower with daily physical activity time exceeding 60 min among primiparas (IQR: 30.89%-44.43%) and exceeding 90 min among multiparas (ranged from 27.76% to 38.82%). After adjusting for potential confounders, primiparas tended to have a lower percentage of abnormal PG than do multiparas (rate difference = -0.39, 95%CI: -3.61 to 2.84). The same amount of physical activity time was significantly less effective for multiparas than for primiparas (trend p-value < 0.01).

CONCLUSION

In women with GDM, being multiparous is associated with less effective glycemic control through physical activity, such that multiparas need more physical activity to achieve glycemic control at a similar level to primiparas.

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.

Short-term exposure to ambient air pollution and pneumonia hospital admission among patients with COPD: a time-stratified case-crossover study

Background

Pneumonia is a major contributor to hospital admission for patients with chronic obstructive pulmonary disease (COPD). However, evidence for acute effects of ambient air pollution exposure on pneumonia hospital admission among patients with COPD is scarce. We aimed to examine the association between short-term exposure to ambient air pollution and pneumonia hospital admission among patients with COPD.

Methods

We enrolled COPD cases aged ≥ 60 years old and further filtered those who were admitted into hospitals from pneumonia during 2016–2019 in Guangdong province, China for main analysis. A time-stratified case-crossover design was applied to investigate the association and conditional logistic regression model was used for data analysis. We performed inverse distance weighting method to estimate daily individual-level exposure on particulate matter with an aerodynamic diameter ≤ 2.5 μm (PM_2.5), particulate matter with an aerodynamic diameter ≤ 10 μm (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and ozone (O₃) based on personal residential addresses.

Results

We included 6473 pneumonia hospital admissions during the study period. Each interquartile range (IQR) increase in PM_2.5 (lag 2; IQR, 22.1 μg/m³), SO₂ (lag 03; IQR, 4.2 μg/m³), NO₂ (lag 03; IQR, 21.4 μg/m³), and O₃ (lag 04; IQR, 57.9 μg/m³) was associated with an odds ratio in pneumonia hospital admission of 1.043 (95% CI: 1.004–1.083), 1.081 (95% CI: 1.026–1.140), 1.045 (95% CI: 1.005–1.088), and 1.080 (95% CI: 1.018–1.147), respectively. Non-linear trends for PM_2.5, PM₁₀, and SO₂ were observed in the study. Sex, age at hospital admission, and season at hospital admission did not modify the associations.

Conclusions

We found significantly positive associations of short-term exposure to PM_2.5, SO₂, NO₂, and O₃ with pneumonia hospital admission among COPD patients. It provides new insight for comprehensive pneumonia prevention and treatment among COPD patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-01989-9.

Associations of PM2.5 exposure with blood glucose impairment in early pregnancy and gestational diabetes mellitus

Exposure to fine particulate matter (PM_2.5) during pregnancy has been linked to the risk of gestational diabetes mellitus (GDM), while conclusions are inconsistent. In this study we aimed to estimate the effects of prenatal PM_2.5 exposure with blood glucose in early pregnancy and the GDM risk. Participants were recruited from the SH-IPMCH-BTH cohort (n = 41,929), a study of air pollution and birth outcome. All participants provided serum samples for analyses of fasting blood glucose (FBG) and HbA1c during early pregnancy. GDM was diagnosed using an oral glucose tolerance test (OGTT) with the time interval of 1 h. Prenatal exposure to PM_2.5 was estimated using gap-filled satellite exposure assessments in Shanghai, China. Both FBG and HbA1c levels were significantly and positively associated with PM_2.5 exposure during early pregnancy. A 10 μg/m³ increase of PM_2.5 exposure from early to middle pregnancy was associated with the risk of GDM (first trimester OR=1.09, 95% CI: 1.02, 1.16; second trimester OR=1.09, 95% CI: 1.03, 1.16; first two trimester OR=1.15, 95%CI: 1.04, 1.28). The combined effects were greater among elevated FBG and HbA1c women with higher PM_2.5 exposure in middle trimester (P for interaction=0.037 and 0.001, respectively). This study found that exposure to PM_2.5 exposure in the 1^st and 2^nd trimesters was related to GDM. FBG and HbA1c played roles in the relationship between PM_2.5 exposure in the 2^nd trimester and GDM.

Combined effects of air pollutants on gestational diabetes mellitus: A prospective cohort study

Exposures to multiple air pollutants during pregnancy have been associated with the risk of gestational diabetes mellitus (GDM). However, their combined effects are unclear. We aimed to evaluate the combined associations of five air pollutants from pre-pregnancy to the 2nd trimester with GDM. This study included 20,113 participants from the Born in Guangzhou Cohort Study (BIGCS). The inverse distance-weighted models were used to estimate individual air pollutant exposure, namely ozone (O₃), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), particulate matter less than 10 μm in diameter (PM₁₀), and less than 2.5 μm in diameter (PM_2.5). We estimated stage-specific associations of air pollutants with GDM using generalized estimating equation, and departures from additive joint effects were assessed using the relative excess risk (RERI) and the joint relative risk (JRR). Of the 20,113 participants, 3440 women (17.1%) were diagnosed with GDM. In the adjusted model, increased concentrations of O₃ and SO₂ 3-6 months before pregnancy were associated with GDM occurrence, as well as O₃ and PM₁₀ in the 1st trimester, the adjusted relative risk (95% confident intervals) [RRs (95%CI)] ranged from 1.05 (1.00, 1.09) to 1.21 (1.04, 1.40). The largest JRR for GDM was the combination of SO₂, NO₂, and PM₁₀ in the 1st trimester (JRR = 1.32, 95% CI: 1.10, 1.59). The JRR for O₃ and SO₂ was less than their additive joint effects [RERI = -0.25 (-0.47, -0.04), P for interaction = 0.048]. Associations of air pollutants with GDM differed somewhat by pre-pregnancy BMI and season. This study added new evidence to the current understanding of the combined effects of multiple air pollutants on GDM. Public health strategies were needed to reduce the adverse effects of air pollution exposure on pregnant women.

Association of abnormal-glucose tolerance during pregnancy with exposure to PM2.5 components and sources

Maternal exposure to PM_2.5 has been associated with abnormal glucose tolerance during pregnancy, but little is known about which constituents and sources are most relevant to glycemic effects. We conducted a retrospective cohort study of 1148 pregnant women to investigate associations of PM_2.5 chemical components with gestational diabetes mellitus (GDM) and impaired glucose tolerance (IGT) and to identify the most harmful sources in Heshan, China from January 2015 to July 2016. We measured PM_2.5 using filter-based method and analyzed them for 28 constituents, including carbonaceous species, water-soluble ions and metal elements. Contributions of PM_2.5 sources were assessed by positive matrix factorization (PMF). Logistic regression model was used to estimate composition-specific and source-specific effects on GDM/IGT. Random forest algorithm was applied to evaluate the relative importance of components to GDM and IGT. PM_2.5 total mass and several chemical constituents were associated with GDM and IGT across the early to mid-gestation periods, as were the PM_2.5 sources fossil fuel/oil combustion, road dust, metal smelting, construction dust, electronic waster, vehicular emissions and industrial emissions. The trimester-specific associations differed among pollutants and sources. The third and highest quartile of elemental carbon, ammonium (NH₄⁺), iron (Fe) and manganese (Mn) across gestation were consistently associated with higher odds of GDM/IGT. Maternal exposures to zinc (Zn), titanium (Ti) and vehicular emissions during the first trimester, and vanadium (V), nickel (Ni), road dust and fossil fuel/oil combustion during the second trimester were more important for GDM/IGT. This study provides important new evidence that maternal exposure to PM_2.5 components and sources is significantly related to elevated risk for abnormal glucose tolerance during pregnancy.

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.

Child serum metabolome and traffic-related air pollution exposure in pregnancy

BACKGROUND

Maternal exposure to traffic-related air pollution during pregnancy has been shown to increase the risk of adverse birth outcomes and childhood disorders. High-resolution metabolomics (HRM) has previously been employed to identify metabolic responses to traffic-related air pollution in adults, including pregnant women. Thus far, no studies have examined metabolic effects of air pollution exposure in utero on neonates.

METHODS

We retrieved stored neonatal blood spots for 241 children born in California between 1998 and 2007. These children were randomly selected from all California birth rolls to serve as birth-year matched controls for children with retinoblastoma identified from the California cancer registry for a case control study of childhood cancer. We estimated prenatal traffic-related air pollution exposure (particulate matter less than 2.5 μm (PM_2.5)) during the third-trimester using the California Line Source Dispersion Model, version 4 (CALINE4) based on residential addresses recorded at birth. We employed untargeted HRM to obtain metabolic profiles, and metabolites associated with air pollution exposure were identified using partial least squares (PLS) regression and linear regressions. Biological effects were characterized using pathway enrichment analyses adjusting for potential confounders including maternal age, race/ethnicity, and education.

RESULTS

In total we extracted 4038 and 4957 metabolite features from neonatal blood spots in hydrophilic interaction (HILIC) chromatography (positive ion mode) and C18 reverse phase columns (negative ion mode), respectively. After controlling for confounding factors, partial least square regression (Variable Importance in Projection (VIP) ≥ 2) selected 402 HILIC positive and 182 C18 negative features as statistically significantly associated with increasing third trimester PM_2.5 exposure. Using pathway enrichment analysis, we identified metabolites in oxidative stress and inflammation pathways as being altered, primarily involving lipid metabolism.

CONCLUSION

The metabolite features and pathways associated with air pollution exposure in neonates suggest that maternal exposure during late pregnancy contributes to oxidative stress and inflammation in newborn children.

In utero exposure to near-roadway air pollution and autism spectrum disorder in children

IMPORTANCE

Previous studies have reported associations between in utero exposure to regional air pollution and autism spectrum disorders (ASD). In utero exposure to components of near-roadway air pollution (NRAP) has been linked to adverse neurodevelopment in animal models, but few studies have investigated NRAP association with ASD risk.

OBJECTIVE

To identify ASD risk associated with in utero exposure to NRAP in a large, representative birth cohort.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective pregnancy cohort study included 314,391 mother-child pairs of singletons born between 2001 and 2014 at Kaiser Permanente Southern California (KPSC) hospitals. Maternal and child data were extracted from KPSC electronic medical records. Children were followed until: clinical diagnosis of ASD, non-KPSC membership, death, or December 31, 2019, whichever came first. Exposure to the complex NRAP mixture during pregnancy was assessed using line-source dispersion models to estimate fresh vehicle emissions from freeway and non-freeway sources at maternal addresses during pregnancy. Vehicular traffic load exposure was characterized using advanced telematic models combining traditional traffic counts and travel-demand models with cell phone and vehicle GPS data. Cox proportional-hazard models estimated hazard ratios (HR) of ASD associated with near-roadway traffic load and dispersion-modeled NRAP during pregnancy, adjusted for covariates. Non-freeway NRAP was analyzed using quintile distribution due to nonlinear associations with ASD.

EXPOSURES

Average NRAP and traffic load exposure during pregnancy at maternal residential addresses.

MAIN OUTCOMES

Clinical diagnosis of ASD.

RESULTS

A total of 6,291 children (5,114 boys, 1,177 girls) were diagnosed with ASD. The risk of ASD was associated with pregnancy-average exposure to total NRAP [HR(95% CI): 1.03(1.00,1.05) per 5 ppb increase in dispersion-modeled NOx] and to non-freeway NRAP [HR(95% CI) comparing the highest to the lowest quintile: 1.19(1.11, 1.27)]. Total NRAP had a stronger association in boys than in girls, but the association with non-freeway NRAP did not differ by sex. The association of freeway NRAP with ASD risk was not statistically significant. Non-freeway traffic load exposure demonstrated associations with ASD consistent with those of NRAP and ASD.

CONCLUSIONS

In utero exposure to near-roadway air pollution, particularly from non-freeway sources, may increase ASD risk in children.

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.

The relationship between hair metabolites, air pollution exposure and gestational diabetes mellitus: A longitudinal study from pre-conception to third trimester

BACKGROUND

Gestational diabetes mellitus (GDM) is a metabolic condition defined as glucose intolerance with first presentation during pregnancy. Many studies suggest that environmental exposures, including air pollution, contribute to the pathogenesis of GDM. Although hair metabolite profiles have been shown to reflect pollution exposure, few studies have examined the link between environmental exposures, the maternal hair metabolome and GDM. The aim of this study was to investigate the longitudinal relationship (from pre-conception through to the third trimester) between air pollution exposure, the hair metabolome and GDM in a Chinese cohort.

METHODS

A total of 1020 women enrolled in the Complex Lipids in Mothers and Babies (CLIMB) birth cohort were included in our study. Metabolites from maternal hair segments collected pre-conception, and in the first, second, and third trimesters were analysed using gas chromatography-mass spectrometry (GC-MS). Maternal exposure to air pollution was estimated by two methods, namely proximal and land use regression (LUR) models, using air quality data from the air quality monitoring station nearest to the participant's home. Logistic regression and mixed models were applied to investigate associations between the air pollution exposure data and the GDM associated metabolites.

RESULTS

Of the 276 hair metabolites identified, the concentrations of fourteen were significantly different between GDM cases and non-GDM controls, including some amino acids and their derivatives, fatty acids, organic acids, and exogenous compounds. Three of the metabolites found in significantly lower concentrations in the hair of women with GDM (2-hydroxybutyric acid, citramalic acid, and myristic acid) were also negatively associated with daily average concentrations of PM_2.5, PM₁₀, SO₂, NO₂, CO and the exposure estimates of PM_2.5 and NO_2, and positively associated with O₃.

CONCLUSIONS

This study demonstrated that the maternal hair metabolome reflects the longitudinal metabolic changes that occur in response to environmental exposures and the development of GDM.

Human Serum Albumin Cys34 Adducts in Newborn Dried Blood Spots: Associations With Air Pollution Exposure During Pregnancy

Background: Increasing evidence suggests that exposure to air pollution during pregnancy is associated with adverse pregnancy outcomes. However, biomarkers associated with air pollution exposure are widely lacking and often transient. In addition, ascertaining biospecimens during pregnacy to assess the prenatal environment remains largely infeasible. Objectives: To address these challenges, we investigated relationships between air pollution exposure during pregnancy and human serum albumin Cys34 (HSA-Cys34) adducts in newborn dried blood spots (DBS) samples, which captures an integration of perinatal exposures to small reactive molecules in circulating blood. Methods: Newborn DBS were obtained from a state archive for a cohort of 120 children born at one Kaiser Permanente Southern California (KPSC) hospitals in 2007. These children were selected to maximize the range of residential air pollution exposure during the entire pregnancy to PM2.5, PM10, NO2, O3, based on monthly estimates interpolated from regulatory monitoring sites. HSA-Cys34 adducts were selected based on previously reported relationships with air pollution exposure and oxidative stress. Results: Six adducts measured in newborn DBS samples were associated with air pollution exposures during pregnancy; these included direct oxidation products, adducts formed with small thiol compounds, and adducts formed with reactive aldehydes. Two general trends were identified: Exposure to air pollution late in pregnancy (i.e., in the last 30 days) was associated with increased oxidative stress, and exposure to air pollution earlier in pregnancy (i.e., not in the last 30 days) was associated with decreased oxidative stress around the time of birth. Discussion: Air pollution exposure occurring during pregnancy can alter biology and leave measurable impacts on the developing infant captured in the newborn DBS adductome, which represents a promising tool for investigating adverse birth outcomes in population-based studies.

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.

Dietary patterns and associations between air pollution and gestational diabetes mellitus

The prevalence of gestational diabetes mellitus (GDM) has been increasing worldwide. Dietary patterns and air pollution are closely related to the occurrence of GDM. No previous study has explored the interaction effect of air pollution exposure and dietary patterns on GDM. We explored the interaction effect between main dietary patterns and pre-pregnancy exposure to air pollution on the development of GDM based on a prospective birth cohort in Northeast China. A total of 2244 participants were included in this study. Factor analysis was used to identify dietary patterns. We found that long-term exposure to nitrogen dioxide (NO₂) and carbon monoxide (CO) before pregnancy was significantly associated with an increased risk of GDM; the animal foods pattern significantly modified these associations. The sub-group analysis showed that compared with a lower intake in the animal foods pattern (NO₂, odds ratio [OR] = 1.07, 95% confidence interval [CI]: 0.84, 1.35; CO, OR = 1.05, 95% CI: 0.81, 1.34), higher intake in the animal foods pattern (NO₂, OR = 1.41, 95% CI: 1.09, 1.83; CO, OR = 1.36, 95% CI: 1.05, 1.76) before pregnancy increased the hazardous effects of NO₂ and CO on GDM development. The intake of animal blood, animal organs, preserved eggs, and processed meat products in animal food pattern could all aggravate the effect of exposure to air pollution due to NO₂ and CO on GDM. Our study demonstrated that there was a significant interaction effect between animal foods pattern and exposure to air pollution on GDM. These results provide further scientific evidence of the associations among air pollution, dietary intake, and GDM, and may help as well as the prevention of GDM.

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

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

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

BACKGROUND

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

METHODS

Two-hundred and fifty healthy pregnant women with singleton pregnancies and 24-26 weeks of gestations participated in our study. Land use regression (LUR) models were applied to estimate the annual mean of PM1, 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.

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.

Transportation noise and gestational diabetes mellitus: A nationwide cohort study from Denmark

BACKGROUND

Few studies have investigated whether road traffic noise is associated with gestational diabetes mellitus (GDM), and have yielded inconsistent findings. We aimed to investigate whether maternal exposure to residential transportation noise, before and during pregnancy, was associated with GDM in a nationwide cohort.

METHODS

From the Danish population (2004-2017) we identified 629,254 pregnancies using the Danish Medical Birth Register. By linkage with the National Patient Registry, we identified 15,973 pregnancies complicated by GDM. Road traffic and railway noise (L_den) at the most and least exposed façades for all residential addresses from five years before pregnancy until birth were estimated for all. Analyses were conducted using generalized estimating equation models with adjustment for various individual and area-level sociodemographic covariates gathered from Danish registries, as well as green space and air pollution (PM_2.5) estimated for all addresses.

RESULTS

We found no positive associations between road traffic noise at either façade and GDM. For railway noise, a 10 dB increase in railway noise at the most and least exposed façades during the first trimester was associated with GDM, with an odds ratio (OR) of 1.06 (95% confidence interval (CI): 1.03-1.10) and 1.07 (95% CI: 1.02-1.13), respectively. We found indications of higher odds of GDM among women exposed to both high road traffic and railway noise at the least exposed facade during the first trimester (OR: 1.24; 95% CI: 1.07-1.44).

CONCLUSION

In conclusion, this nationwide study suggests that railway noise but not road traffic noise might be associated with GDM.

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.

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.

Association between ambient air pollution and pregnancy complications: A systematic review and meta-analysis of cohort studies

BACKGROUND

Pregnancy complications, such as gestational diabetes mellitus (GDM) and hypertensive disorders of pregnancy (HDP), have a great impact on public health. Exposure to ambient air pollution during pregnancy may cause pregnancy complications. The aim of our study is to explore the risk of trimester-specific maternal exposure to air pollutants on complications of pregnancy.

METHODS

PubMed, EMBASE, Web of Science, and Cochrane were systematically searched for cohort studies published before October 27, 2019 which reported the association between ambient air pollutants (PM_2.5, PM₁₀, CO, NO, NO₂, NO_x, O₃, and SO₂) and pregnancy complications (GDM, HDP, preeclampsia, and gestational hypertension) during different exposure windows. A meta-analysis was applied to combine relative risks (RRs) and their confidence intervals (CIs) from eligible studies. Quality assessment was conducted and Egger test was used to evaluate the publication bias. All statistical analyses were performed by STATA software (Version 15, StataCorp, College Station, Texas, USA).

RESULTS

This meta-analysis consisted of 33 cohort studies conducted on 22,253,277 pregnant women. Meta-analyses showed during the first trimester, there were significant associations of PM₁₀ with gestational hypertension (RR = 1.07, 95% CI: 1.02-1.12 per 10 μg/m³, I² = 0.0%), of SO₂ with GDM (RR = 1.04, 95% CI: 1.00-1.08 per 1 ppb increment, I² = 54.1%), of PM_2.5 with preeclampsia (RR = 0.97, 95% CI: 0.95-1.00 per 5 μg/m³, I² = 4.1%). During the entire pregnancy, PM_2.5 significantly increased the risk of hypertensive disorders of pregnancy (RR = 1.18, 95% CI: 1.02-1.34 per 5 μg/m³, I² = 85.1%). Egger test indicated that wide-scale publication bias was unlikely.

CONCLUSION

Maternal exposure to ambient air pollutants is associated with pregnancy complications especially during the first trimester. Further large multicenter cohort studies considering different constituents of pollutants, levels of disease severity, sensitive populations, and various exposure windows are warranted in the future research.

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.