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

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.

Association of ambient PM2.5 and its components with in vitro fertilization outcomes: The modifying role of maternal dietary patterns

Despite the associations of dietary patterns and air pollution with human reproductive health have been demonstrated, the interaction of maternal preconception diet and PM2.5 and its components exposure on in vitro fertilization (IVF) treatment outcomes has not been investigated. A total of 2688 couples from an ongoing prospective cohort were included. Principle component analysis with varimax rotation was performed to determine dietary patterns. One-year and 85-day average PM2.5 and its components exposure levels before oocyte retrieval were estimated. Generalized linear regression models were conducted to assess the association of dietary patterns and PM2.5 and its components exposure with IVF outcomes. Interactive effects of dietary patterns on the association between PM2.5 and its components and IVF outcomes were evaluated by stratified analyses based on different dietary patterns. A positive association between the "Fruits-Vegetables-Dairy" pattern and normal fertilization (p-trend = 0.009), Day 3 available embryos (p-trend = 0.048), and top-quality embryos (p-trend = 0.041) was detected. Conversely, women with higher adherence to the "Puffed food-Bakery-Candy" pattern were less likely to achieve Day 3 available embryos (p-trend = 0.042) and top-quality embryos (p-trend = 0.030), clinical pregnancy (p-trend = 0.049), and live birth (p-trend = 0.020). Additionally, increased intake of animal organs and seafood improved the odds of live birth (p-trend = 0.048). Exposure to PM2.5, SO42-, organic matter (OM), and black carbon (BC) had adverse effects on embryo development and pregnancy outcomes. Furthermore, our findings indicated that the effects of PM2.5 components exposure on normal fertilization and embryo quality were modified by the "Grains-Tubers-Legumes". Moreover, moderate intake of animal organs and seafood appeared to attenuate the effect of NO3- and NH4+ on the risk of early abortion. Our findings provide human evidence of the interaction between dietary patterns and PM2.5 exposure on IVF outcomes during preconception, implicating the potential for dietary interventions in infertile women to improve reproductive outcomes under conditions of unavoidable ambient air-pollutant exposure.

The association between PM2.5 components and blood pressure changes in late pregnancy: A combined analysis of traditional and machine learning models

BACKGROUND

PM2.5 is a harmful mixture of various chemical components that pose a challenge in determining their individual and combined health effects due to multicollinearity issues with traditional linear regression models. This study aimed to develop an analytical methodology combining traditional and novel machine learning models to evaluate PM2.5's combined effects on blood pressure (BP) and identify the most toxic components.

METHODS

We measured late-pregnancy BP of 1138 women from the Heshan cohort while simultaneously analyzing 31 PM2.5 components. We utilized multiple linear regression modeling to establish the relationship between PM2.5 components and late-pregnancy BP and applied Random Forest (RF) and generalized Weighted Quantile Sum (gWQS) regression to identify the most toxic components contributing to elevated BP and to quantitatively evaluate the cumulative effect of the PM2.5 component mixtures.

RESULTS

The results revealed that 16 PM2.5 components, such as EC, OC, Ti, Fe, Mn, Cu, Cd, Mg, K, Pb, Se, Na+, K+, Cl-, NO3-, and F-, contributed to elevated systolic blood pressure (SBP), while 26 components, including two carbon components (EC, OC), fourteen metallics (Ti, Fe, Mn, Cr, Mo, Co, Cu, Zn, Cd, Na, Mg, Al, K, Pb), one metalloid (Se), and nine water-soluble ions (Na+, K+, Mg2+, Ca2+, NH4+, Cl-, NO3-, SO42-, F-), contributed to elevated diastolic blood pressure (DBP). Mn and Cr were the most toxic components for elevated SBP and DBP, respectively, as analyzed by RF and gWQS models and verified against each other. Exposure to PM2.5 component mixtures increased SBP by 1.04 mmHg (95% CI: 0.33-1.76) and DBP by 1.13 mmHg (95% CI: 0.47-1.78).

CONCLUSIONS

Our study highlights the effectiveness of combining traditional and novel models as an analytical strategy to quantify the health effects of PM2.5 constituent mixtures.

High-Resolution Spatiotemporal Modeling for PM2.5 Major Components in the Pearl River Delta and Its Implications for Epidemiological Studies

Distinguishing the effects of different fine particulate matter components (PMCs) is crucial for mitigating their effects on human health. However, the sparse distribution of locations where PM is collected for component analysis makes it challenging to investigate the relevant health effects. This study aimed to investigate the agreement between data-fusion-enhanced exposure assessment and site monitoring data in estimating the effects of PMCs on gestational diabetes mellitus (GDM). We first improved the spatial resolution and accuracy of exposure assessment for five major PMCs (EC, OM, NO3-, NH4+, and SO42-) in the Pearl River Delta region by a data fusion model that combined inputs from multiple sources using a random forest model (10-fold cross-validation R2: 0.52 to 0.61; root mean square error: 0.55 to 2.26 μg/m3). Next, we compared the associations between exposures to PMCs during pregnancy and GDM in a hospital-based cohort of 1148 pregnant women in Heshan, China, using both site monitoring data and data-fusion model estimates. The comparative analysis showed that the data-fusion-based exposure generated stronger estimates of identifying statistical disparities. This study suggests that data-fusion-enhanced estimates can improve exposure assessment and potentially mitigate the misclassification of population exposure arising from the utilization of site monitoring data.

Exposure to urban ambient particles (PM2.5) before pregnancy affects the expression of endometrial receptive markers to embryo implantation in mice: Preliminary results

Air pollution (AP) is one of the main recent concerns in reproductive healthy due to its potential to promote negative outcomes during pregnancy and male and female fertility. Several studies have demonstrated that AP exposure has been linked to increased embryonic implantation failures, alterations in embryonic, fetal and placental development. For a well-succeeded implantation, both competent blastocyst and receptive endometrium are required. Based on the lack of data about the effect of AP in endometrial receptivity, this study aimed to evaluate he particulate matter (PM) exposure impact on uterine receptive markers in mice and associate the alterations to increased implantation failures due to AP. For this study, ten dams per group were exposed for 39 days to either filter (F) or polluted air (CAP). At fourth gestational day (GD4), females were euthanized. Morphological, ultrastructural, immunohistochemical and molecular analysis of uterine and ovarian samples were performed. CAP-exposed females presented a reduced number of corpus luteum; glands and epithelial cells were increased with pinopodes formation impairment. Immunohistochemistry analysis revealed decreased LIF protein levels. These preliminary data suggests that PM exposure may exert negative effects on endometrial receptivity by affecting crucial parameters to embryonic implantation as uterine morphological differentiation, corpus luteum quantity and LIF expression during implantation window.

Gestational and Postpartum Exposure to PM2.5 Components and Glucose Metabolism in Chinese Women: A Prospective Cohort Study

Pregnant women are physiologically prone to glucose intolerance, while the puerperium represents a critical phase for recovery. However, how air pollution disrupts glucose homeostasis during the gestational and early postpartum periods remains unclear. This prospective cohort study conducted an oral glucose tolerance test and measured the insulin levels of 834 pregnant women in Guangzhou, with a follow-up for 443 puerperae at 6-8 weeks postpartum. Residential PM2.5 and five chemical components were estimated by an established spatiotemporal model. The adjusted linear model showed that an IQR increase in gestational PM2.5 exposure was associated with an increase of 0.17 mmol/L (95% CI: 0.06, 0.28) in fasting plasma glucose (FPG) and 0.24 (95% CI: 0.05, 0.42) in the insulin resistance index. Postpartum PM2.5 exposure was linked to a 0.17 mmol/L (95% CI: 0.05, 0.28) elevation in FPG per IQR, with a strengthened association found in women with gestational diabetes (Pinteraction = 0.003). In the quantile-based g-computation model, NO3- consistently contributed to the combined effect of PM2.5 components on gestational and postpartum FPG. This study was the first to suggest that PM2.5 components were associated with exacerbated gestational insulin resistance and elevated postpartum FPG. Targeted interventions reducing the emissions of toxic PM2.5 components are essential to improving maternal glucose metabolism.

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.

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.

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.

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.

Carbohydrate intake quality and gestational diabetes mellitus, and the modifying effect of air pollution

Background

Nutritional management is the cornerstone of gestational diabetes mellitus (GDM) prevention. High quality instead of low quantity of carbohydrate intake has been paying attention in controlling glycemia. Air pollution exposure can be interacted with dietary sourced nutrients, which may modify the associations with GDM. This study aims to explore the associations between overall quality of carbohydrate intake and GDM as well as the modifying effect of prenatal air pollution exposure.

Methods

Carbohydrate quality index (CQI) was calculated was calculated by summing scores of the four components; Land use regression prediction models were used to assess the air pollution exposure levels. GDM definition was based on 75 g glucose tolerance test results. Associations between pre-pregnancy CQI, pre-natal air pollution as well as the modifying effect on GDM were explored based on a birth cohort in China.

Results

A total of 3,183 participants were included, of which 784 (24.63%) were diagnosed with GDM. Higher pre-pregnancy CQI was associated with a lower incidence of GDM [odds ratio (OR) = 0.75, 95% confidence interval (CI): 0.56-0.99, P _{for trend} = 0.04], especially for higher fasting blood glucose related GDM (OR = 0.66, 95% CI: 0.47, 0.91). Higher air pollution exposure before and during pregnancy was associated with a greater risk of GDM. Higher exposure to particulate matter with an aerodynamic diameter of < 2.5 μm (P _{for interaction} < 0.01), particulate matter with an aerodynamic diameter of < 10 μm (P _{for interaction} < 0.01), and sulfur dioxide (P _{for interaction} = 0.02) during pregnancy decreased the beneficial effect of high pre-pregnancy CQI on GDM.

Conclusion

CQI related dietary interventions pre-pregnancy to prevent GDM incidence should be considered. Women who are planning to be pregnant should avoid high exposure to air pollution during pregnancy.

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.

Ozone exposure induced risk of gestational diabetes mellitus

Numerous studies have shown that air pollution seems to be able to cause many diseases. Considering the possible mechanism of action and the same growth trend, the present study is designed to examine whether and how air pollutants, especially ozone (O₃) exposure, are associated with the incidence of gestational diabetes mellitus (GDM). By a retrospective cohort, we analyzed the records of 45439 pregnant women from 2013 to 2018 and matched them to maternal exposure to O₃. We found that the increased odds of GDM is associated with increased O₃ concentrations from the 1st month before pregnancy to the 3rd month during pregnancy. Specially, the odds ratios (ORs) of these associations were largest in the 1st month before pregnancy, suggesting that the effect of O₃ pollution on GDM occurred in pre-pregnancy period. Moreover, the exposure-response plot in the 1st month before pregnancy showed that the odds of GDM increased with the increasing concentration of O₃. Our findings provide the evidence that O₃ exposure in both pre-pregnancy and pregnancy period elevates the odds of GDM, suggesting that more intensive air pollution controls are needed to improve the health of pregnant women and their offspring.

The impact of prolonged exposure to air pollution on the incidence of chronic non-communicable disease based on a cohort in Tianjin

Evidence on the associations of prolonged ambient pollutants exposure with chronic non-communicable diseases among middle-aged and elderly residents is still limited. This prospective cohort study intends to investigate the long-term effects of ambient pollution on hypertension and diabetes incidence among relatively older residents in China. Individual particulate matter exposure levels were estimated by satellite-based model. Individual gaseous pollutants exposure levels were estimated by Inverse Distance Weighted model. A Cox regression model was employed to assess the risks of hypertension and diabetes morbidity linked to air pollutants exposures. The cross-product term of ambient pollutants exposure and covariates was further added into the regression model to test whether covariates would modify these air pollution-morbidity associations. During the period from 2014 to 2018, a total of 97,982 subjects completed follow-up. 12,371 incidents of hypertension and 2034 of diabetes occurred. In the multi-covariates model, the hazard ratios (HR) and 95% confidence interval (CI) were 1.49 (1.45-1.52), 1.28 (1.26-1.30), 1.17 (1.15-1.18), 1.21 (1.17-1.25) and 1.33 (1.31-1.35) for hypertension morbidity per 10 μg/m³ increment in PM₁, PM_2.5, PM₁₀, NO₂ and SO₂, respectively. For diabetes onsets, the HR (95% CI) were 1.17 (1.11-1.23), 1.09 (1.04-1.13), 1.06 (1.02-1.09), 1.02 (0.95-1.10), and 1.24 (1.19-1.29), respectively. In addition, for hypertension analyses, the effect estimates were more pronounced in the participants with age <60 years old, BMI ≥24 kg/m², and frequent alcohol drinking. These findings provided the evidence on elevated risks of morbidity of hypertension and diabetes associated with prolonged ambient pollutants exposure at relatively high levels.

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.

Association between ambient air pollution and hospital admissions, length of hospital stay and hospital cost for patients with cardiovascular diseases and comorbid diabetes mellitus: Base on 1,969,755 cases in Beijing, China, 2014-2019

BACKGROUND

Evidence on the effects of the air pollutants on the hospital admissions, hospital cost and length of stay (LOS) among patients with comorbidities remains limited in China, particularly for patients with cardiovascular diseases and comorbid diabetes mellitus (CVD-DM).

METHODS

We collected daily data on CVD-DM patients from 242 hospitals in Beijing between 2014 and 2019. Generalized additive model was employed to quantify the associations between admissions, LOS, and hospital cost for CVD-DM patients and air pollutants. We further evaluated the attributable risk posed by air pollutants to CVD-DM patients, using both Chinese and WHO air quality guidelines as reference.

RESULTS

Per 10 ug/m³ increase of particles with an aerodynamic diameter < 2.5 μm (PM_2.5), particles with an aerodynamic diameter < 10 μm (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbonic oxide (CO) and ozone (O₃) corresponded to a 0.64% (95% CI: 0.57 to 0.71), 0.52% (95% CI: 0.46 to 0.57), 0.93% (95% CI: 0.67 to 1.20), 0.98% (95% CI: 0.81 to 1.16), 1.66% (95% CI: 1.18 to 2.14) and 0.53% (95% CI: 0.45 to 0.61) increment for CVD-DM patients' admissions. Among the six pollutants, particulate pollutants (PM_2.5 and PM₁₀) in most lag days exhibited adverse effects on LOS and hospital cost. For every 10 ug/m³ increase in PM_2.5 and PM₁₀, the absolute increase with LOS will increase 62.08 days (95% CI: 28.93 to 95.23) and 51.77 days (95% CI:22.88 to 80.66), respectively. The absolute increase with hospital cost will increase 105.04 Chinese Yuan (CNY) (95% CI: 49.27 to 160.81) and 81.76 CNY (95% CI: 42.01 to 121.51) in PM_2.5 and PM₁₀, respectively. Given WHO 2021 air quality guideline as the reference, PM_2.5 had the maximum attributable fraction of 3.34% (95% CI: 2.94% to 3.75%), corresponding to an avoidable of 65,845 (95% CI: 57,953 to 73,812) patients with CVD-DM.

CONCLUSION

PM_2.5 and PM₁₀ are positively associated with hospital admissions, hospital cost and LOS for patients with CVD-DM. Policy changes to reduce air pollutants exposure may reduce CVD-DM admissions and substantial savings in health care spending and LOS.

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 residing greenness and long-term exposure to air pollution with glucose homeostasis markers

BACKGROUND

Although long-term exposure to higher air pollutants and lower residing greenness related to disorders of glucose homeostasis have been reported, their interaction effects on glucose homeostasis in developing countries remained unclear.

METHODS

A total of 35, 482 participants were obtained from the Henan Rural Cohort (n = 39, 259). Exposure to air pollutants (PM₁, PM_2.5, PM₁₀ and NO₂) were predicted by using a spatiotemporal model-based on satellites data. Residing greenness was reflected by Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) which were derived from satellites data. Independent associations of single or mixture of air pollutant or residing greenness with glucose homeostasis markers were analyzed by quantile regression models and quantile g (qg)-computation method, respectively. Furthermore, interaction effects of residing greenness and air pollution on glucose homeostasis markers were analyzed by generalized additive models.

RESULTS

Positive associations of single or mixture of air pollutants (PM₁, PM_2.5, PM₁₀ or NO₂) with fasting plasma glucose (FPG) were observed, while negative associations of single or mixture of air pollutants with insulin or HOMA-β were observed. Residing greenness was negatively associated with FPG but positively related to insulin or HOMA-β. Quantile regression revealed the heterogeneity were observed in the associations the residing greenness or air pollutants with glucose homeostasis markers (insulin or HOMA-β) across deciles of the glucose homeostasis markers distributions. Furthermore, joint associations of single air pollutant and residing greenness on glucose homeostasis markers were found.

CONCLUSIONS

The results indicated that exposure to air pollution had negative effect on glucose homeostasis markers and these effects may be modified by living in higher green space. These findings suggest that increased residing greenness and air pollution control may have joint effect on decreased the risk of diabetes.

CLINICAL TRIAL REGISTRATION

The Henan Rural Cohort study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699, http://www.chictr.org.cn/showproj.aspx?proj=11375).