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

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.

Exposure to Low-Level Air Pollution and Hyperglycemia Markers during Pregnancy: A Repeated Measure Analysis

Epidemiologic evidence has emerged showing an association between exposure to air pollution and increased risks of gestational diabetes mellitus (GDM). This study examines the effect of low-level air pollution exposure on a subclinical biomarker of hyperglycemia (i.e., HbA1c) in pregnant people without diabetes before conception. We measured HbA1c in 577 samples repeatedly collected from 224 pregnant people in Rochester, NY, and estimated residential concentrations of PM2.5 and NO2 using high-resolution spatiotemporal models. We observed a U-shaped trajectory of HbA1c during pregnancy with average HbA1c levels of 5.13 (±0.52), 4.97 (±0.54), and 5.43 (±0.40)% in early-, mid-, and late pregnancy, respectively. After adjustment for the U-shaped trajectory and classic GDM risk factors, each interquartile range increase in 10 week NO2 concentration (8.0 ppb) was associated with 0.09% (95% CI: 0.02 to 0.16%) and 0.18% (95% CI: 0.08 to 0.28%) increases in HbA1c over the entire pregnancy and in late pregnancy, respectively. These associations remained robust among participants without GDM. Using separate distributed lag models, we identified a period between 8th and 14th gestational weeks as critical windows responsible for increased levels of HbA1c measured at 14th, 22nd, and 30th gestational weeks. Our results suggest that low-level air pollution contributes to hyperglycemia in medically low-risk pregnant people.

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.

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

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

Methods

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

Results

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

Discussion

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

A systematic review on the association between exposure to air particulate matter during pregnancy and the development of hypertensive disorders of pregnancy and gestational diabetes mellitus

Particulate matter (PM) is considered an intrauterine toxin that can cross the blood-placental barrier and circulate in fetal blood, affecting fetal development, and implicating placental and intrauterine inflammation, and oxidative damage. However, the relationship between PM exposure and adverse pregnancy outcomes is still unclear and our aim was to systematically review toxicological evidence on the link between PM exposure during pregnancy and the development of gestational diabetes mellitus or hypertensive disorders of pregnancy, including gestational hypertension and pre-eclampsia. PubMed and Science Direct were searched until January 2022. Of the 204 studies identified, 168 were excluded. The remaining articles were assessed in full-text, and after evaluation, 27 were included in the review. Most of the studies showed an association between PM exposure and gestational hypertension, systolic and diastolic blood pressure, pre-eclampsia, and gestational diabetes mellitus. These results should be interpreted with caution due to the heterogeneity of baseline concentrations, which ranged from 3.3 μg/m3 to 85.9 μg/m3 and from 21.8 μg/m3 to 92.2 μg/m3, respectively for PM2.5 and PM10. Moreover, critical exposure periods were not consistent among studies, with five out of ten observational studies reporting the second trimester as the critical period for hypertensive disorders of pregnancy, and ten out of twelve observational studies reporting the first or second trimester as the critical period for gestational diabetes mellitus. Overall, the findings support an association between PM exposure during pregnancy and adverse pregnancy outcomes, highlighting the need for further research to identify the critical exposure periods and underlying mechanisms.

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 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.

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

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

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.

Overview of particulate air pollution and human health in China: Evidence, challenges, and opportunities

Ambient particulate matter (PM) pollution in China continues to be a major public health challenge. With the release of the new WHO air quality guidelines in 2021, there is an urgent need for China to contemplate a revision of air quality standards (AQS). In the recent decade, there has been an increase in epidemiological studies on PM in China. A comprehensive evaluation of such epidemiological evidence among the Chinese population is central for revision of the AQS in China and in other developing countries with similar air pollution problems. We thus conducted a systematic review on the epidemiological literature of PM published in the recent decade. In summary, we identified the following: (1) short-term and long-term PM exposure increase mortality and morbidity risk without a discernible threshold, suggesting the necessity for continuous improvement in air quality; (2) the magnitude of long-term associations with mortality observed in China are comparable with those in developed countries, whereas the magnitude of short-term associations are appreciably smaller; (3) governmental clean air policies and personalized mitigation measures are potentially effective in protecting public and individual health, but need to be validated using mortality or morbidity outcomes; (4) particles of smaller size range and those originating from fossil fuel combustion appear to show larger relative health risks; and (5) molecular epidemiological studies provide evidence for the biological plausibility and mechanisms underlying the hazardous effects of PM. This updated review may serve as an epidemiological basis for China’s AQS revision and proposes several perspectives in designing future health studies.

•

Acute effects of PM are smaller in China compared with developed countries

•

Health effects caused by PM depend on particle composition, source, and size

•

There are no thresholds for the health effects of PM

•

Mechanistic studies support the biological plausibility of PM’s health effects

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.

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

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

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

Background

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

Methods

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

Results

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

Conclusions

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

Supplementary Information

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

Maternal exposure to traffic-related ambient particles and risk of gestational diabetes mellitus with isolated fasting hyperglycaemia: A retrospective cohort study in Beijing, China

BACKGROUND

Ambient particles have been associated with gestational diabetes mellitus (GDM), however, no study has evaluated the effects of traffic-related ambient particles on the risks of GDM subgroups classified by oral glucose tolerance test (OGTT) values.

METHODS

A retrospective analysis was conducted among 24,001 pregnant women who underwent regular prenatal care and received OGTT at Haidian Maternal and Child Health Hospital in Beijing, China, 2014-2017. A total of 3,168 (13.2%) pregnant women were diagnosed with GDM, including 1,206 with isolated fasting hyperglycaemia (GDM-IFH). At a fixed-location monitoring station, routinely monitored ambient particles included fine particulate matter (PM_2.5), black carbon (BC) and particles in size ranges of 5-560 nm (PNC_5-560). Contributions of PNC_5-560 sources were apportioned by positive matrix factorization model. Logistic regression model was applied to estimate odds ratio (OR) of ambient particles on GDM risk.

RESULTS

Among the 24,001 pregnancy women recruited in this study, 3,168 (13.2%) were diagnosed with GDM, including 1,206 with isolated fasting hyperglycaemia (GDM-IFH) and 1,295 with isolated post-load hyperglycaemia (GDM-IPH). We observed increased GDM-IFH risk with per interquartile range increase in first-trimester exposures to PM_2.5 (OR = 1.94; 95% Confidence Intervals: 1.23-3.07), BC (OR = 2.14; 1.73-2.66) and PNC_5-560 (OR = 2.46; 1.90-3.19). PNC_5-560 originated from diesel and gasoline vehicle emissions were found in associations with increases in GDM-IFH risk, but not in GDM-IPH risk.

CONCLUSION

Our findings suggest that exposure to traffic-related ambient particles may increase GDM risk by exerting adverse effects on fasting glucose levels during pregnancy, and support continuing efforts to reduce traffic emissions for protecting vulnerable population who are at greater risk of glucose metabolism disorder.

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.

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.

Effect of short-term ambient PM2.5 exposure on fasting blood glucose levels: A longitudinal study among 47,471 people in eastern China

As a common health indicator in physical examinations, fasting blood glucose (FBG) level measurements are widely applied as a diagnostic method for diabetes mellitus. Uncertain conclusions remained regarding the relationship between PM_2.5 exposure and FBG levels. We enrolled 47,471 subjects who participated in annual physical examinations between 2017 and 2019. We collected their general characteristics and FBG levels, and environmental factors simultaneously. We applied the generalized additive model to evaluate the impact of short-term outdoor PM_2.5 exposure on FBG levels. Among the entire population, the single-pollutant models showed that a 10 μg/m³ increase in PM_2.5 significantly contributed to 0.0030, 0.0233, and 0.0325 mmol/L increases in FBG at lag 0-7 days, lag 0-21 days, and lag 0-28 days, respectively. Accordingly, in multipollutant models, when PM_2.5 increased by 10 μg/m³, there was an elevation of 0.0361, 0.0315, 0.0357, and 0.0387 mmol/L in FBG for 8-day, 15-day, 22-day, and 29-day moving averages, respectively. Similarly, we observed a significant positive association between them in the normal population. Moreover, the effects could be modified by age in both the entire and normal populations. Decreasing the ambient PM_2.5 concentrations can alleviate the elevation of FBG, which may significantly impact the burden of diabetes mellitus.

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

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

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

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

Cardiovascular adaptations to particle inhalation exposure: molecular mechanisms of the toxicology

Ambient air, occupational settings, and the use and distribution of consumer products all serve as conduits for toxicant exposure through inhalation. While the pulmonary system remains a primary target following inhalation exposure, cardiovascular implications are exceptionally culpable for increased morbidity and mortality. The epidemiological evidence for cardiovascular dysfunction resulting from acute or chronic inhalation exposure to particulate matter has been well documented, but the mechanisms driving the resulting disturbances remain elusive. In the current review, we aim to summarize the cellular and molecular mechanisms that are directly linked to cardiovascular health following exposure to a variety of inhaled toxicants. The purpose of this review is to provide a comprehensive overview of the biochemical changes in the cardiovascular system following particle inhalation exposure and to highlight potential biomarkers that exist across multiple exposure paradigms. We attempt to integrate these molecular signatures in an effort to provide direction for future investigations. This review also characterizes how molecular responses are modified in at-risk populations, specifically the impact of environmental exposure during critical windows of development. Maternal exposure to particulate matter during gestation can lead to fetal epigenetic reprogramming, resulting in long-term deficits to the cardiovascular system. In both direct and indirect (gestational) exposures, connecting the biochemical mechanisms with functional deficits outlines pathways that can be targeted for future therapeutic intervention. Ultimately, future investigations integrating "omics"-based approaches will better elucidate the mechanisms that are altered by xenobiotic inhalation exposure, identify biomarkers, and guide in clinical decision making.