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

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.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

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.

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.

Association of Fine Particulate Matter and Its Components with Macrosomia: A Nationwide Birth Cohort Study of 336 Chinese Cities

To examine the associations between macrosomia risk and exposure to fine particulate matter (PM2.5) and its chemical components during pregnancy, we collected birth records between 2010 and 2015 in mainland China from the National Free Preconception Health Examination Project and used satellite-based models to estimate concentrations of PM2.5 mass and five main components, namely, black carbon (BC), organic carbon (OC), nitrate (NO3-), sulfate (SO42-), and ammonium (NH4+). Associations between macrosomia risk and prenatal exposure to PM2.5 were examined by logistic regression analysis, and the sensitive subgroups were explored by stratified analyses. Of the 3,248,263 singleton newborns from 336 cities, 165,119 (5.1%) had macrosomia. Each interquartile range increase in concentration of PM2.5 during the entire pregnancy was associated with increased risk of macrosomia (odds ratio (OR) = 1.18; 95% confidence interval (CI), 1.17-1.20). Among specific components, the largest effect estimates were found on NO3- (OR = 1.36; 95% CI, 1.35-1.38) followed by OC (OR = 1.23; 95% CI, 1.22-1.24), NH4+ (OR = 1.22; 95% CI, 1.21-1.23), and BC (OR = 1.21; 95% CI, 1.20-1.22). We also that found boys, women with a normal or lower prepregnancy body mass index, and women with irregular or no folic acid supplementation experienced higher risk of macrosomia associated with PM2.5 exposure.

Joint effect of ambient PM2.5 exposure and vitamin B12 during pregnancy on the risk of gestational diabetes mellitus

BACKGROUND

Evidence has indicated that the risk of gestational diabetes mellitus (GDM) was linked to PM_2.5 exposure during pregnancy, but findings on susceptible exposure windows are inconsistent. Further, previous studies have not paid attention to B₁₂ intake in the relationship between PM_2.5 exposure and GDM. The study is aimed to identify the strength and exposure periods for associations of PM_2.5 exposure with GDM, followed by exploring the potential interplay of gestational B₁₂ levels and PM_2.5 exposure on the risk of GDM.

METHODS

The participants were recruited in a birth cohort between 2017 and 2018, and 1396 eligible pregnant women who completed a 75-g oral glucose tolerance test (OGTT) were included. Prenatal PM_2.5 concentrations were estimated using an established spatiotemporal model. Logistic and linear regression analyses were used to test associations of gestational PM_2.5 exposure with GDM and OGTT-glucose levels, respectively. The joint associations of gestational PM_2.5 exposure and B₁₂ level on GDM were examined under crossed exposure combinations of PM_2.5 (high versus low) and B₁₂ (insufficient versus sufficient).

RESULTS

In the 1396 pregnant women, the median levels of PM_2.5 exposure during the 12 weeks before pregnancy, the 1st trimester, and the 2nd trimesters were 59.33 μg/m³, 63.44 μg/m³, and 64.39 μg/m³, respectively. The risk of GDM was significantly associated with a 10 μg/m³ increase of PM_2.5 during the 2nd trimester (RR = 1.44, 95 % CI: 1.01, 2.04). The percentage change in fasting glucose was also associated with PM_2.5 exposure during the 2nd trimester. A higher risk of GDM was observed among women with high PM_2.5 exposure and insufficient B₁₂ levels than those with low PM_2.5 and sufficient B₁₂.

CONCLUSION

The study supported higher PM_2.5 exposure during the 2nd trimester is significantly associated with GDM risk. It first highlighted insufficient B₁₂ status might enhance adverse effects of air pollution on GDM.

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.

An ensemble mixed spatial model in estimating long-term and diurnal variations of PM2.5 in Taiwan

Meteorology, human activities, and other emission sources drive diurnal cyclic patterns of air pollution. Previous studies mainly focused on the variation of PM_2.5 concentrations during daytime rather than nighttime. In addition, assessing the spatial variations of PM_2.5 in large areas is a critical issue for environmental epidemiological studies to clarify the health effects from PM_2.5 exposures. In terms of air pollution spatial modelling, using only a single model might lose information in capturing spatial and temporal correlation between predictors and pollutant levels. Hence, this study aimed to propose an ensemble mixed spatial model that incorporated Kriging interpolation, land-use regression (LUR), machine learning, and stacking ensemble approach to estimate long-term PM_2.5 variations for nearly three decades in daytime and nighttime. Three steps of model development were applied: 1) linear based LUR and Hybrid Kriging-LUR were used to determine influential predictors; 2) machine learning algorithms were used to enhance model prediction accuracy; 3) predictions from the selected machine learning models were fitted and evaluated again to build the final ensemble mixed spatial model. The results showed that prediction performance increased from 0.514 to 0.895 for daily, 0.478 to 0.879 for daytime, and 0.523 to 0.878 for nighttime when applying the proposed ensemble mixed spatial model compared with LUR. Results of overfitting test and extrapolation ability test confirmed the robustness and reliability of the developed models. The distance to the nearest thermal power plant, density of soil and pebbles fields, and funeral facilities might affect the variation of PM_2.5 levels between daytime and nighttime. The PM_2.5 level was higher in daytime compared with nighttime with little difference, revealing the importance of estimating nighttime PM_2.5 variations. Our findings also clarified the emission sources in daytime and nighttime, which serve as valuable information for air pollution control strategies establishment.

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.

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.

Identifying pre-conception and pre-natal periods in which ambient air pollution exposure affects fetal growth in the predominately Hispanic MADRES cohort

BACKGROUND

It is well documented that persons of color experience disproportionate exposure to environmental contaminants, including air pollution, and have poorer pregnancy outcomes. This study assessed the critical windows of exposure to ambient air pollution on in utero fetal growth among structurally marginalized populations in urban Los Angeles.

METHODS

Participants (N = 281) from the larger ongoing MADRES pregnancy cohort study were included in this analysis. Fetal growth outcomes were measured on average at 32 [Formula: see text] 2 weeks of gestation by a certified sonographer and included estimated fetal weight, abdominal circumference, head circumference, biparietal diameter and femur length. Daily ambient air pollutant concentrations were estimated for four pollutants (particulate matter less than 2.5 µm (PM_2.5) and less than 10 µm (PM₁₀) in aerodynamic diameter, nitrogen dioxide (NO₂), and 8-h maximum ozone (O₃)) at participant residences using inverse-distance squared spatial interpolation from ambient monitoring data. Weekly gestational averages were calculated from 12 weeks prior to conception to 32 weeks of gestation (44 total weeks), and their associations with growth outcomes were modeled using adjusted distributed lag models (DLMs).

RESULTS

Participants were on average 29 years [Formula: see text] 6 old and predominately Hispanic (82%). We identified a significant sensitive window of PM_2.5 exposure (per IQR increase of 6 [Formula: see text]³) between gestational weeks 4-16 for lower estimated fetal weight [Formula: see text] _averaged4-16 = -8.7 g; 95% CI -16.7, -0.8). Exposure to PM_2.5 during gestational weeks 1-23 was also significantly associated with smaller fetal abdominal circumference ([Formula: see text] _averaged1-23 = -0.6 mm; 95% CI -1.1, -0.2). Additionally, prenatal exposure to PM₁₀ (per IQR increase of 13 [Formula: see text]³) between weeks 6-15 of pregnancy was significantly associated with smaller fetal abdominal circumference ([Formula: see text] _{averaged6-15 =} -0.4 mm; 95% CI -0.8, -0.1).

DISCUSSION

These results suggest that exposure to particulate matter in early to mid-pregnancy, but not preconception or late pregnancy, may have critical implications on fetal growth.

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.

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.

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.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

Association of 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.

Associations of hyperglycemic emergency and severe hypoglycemia incidences with seasonality and ambient temperature among pregnant women with diabetes: a nested case-control study in Taiwan

Background

Associations of acute glycemic complications with season and ambient temperature have been reported in general population with diabetes. However, little is known about the risks of acute glycemic complications in relation to season and ambient temperature in pregnant women, who are likely to be even more vulnerable. This work aimed to investigate the associations of season and ambient temperature with pregnancies complicated with hyperglycemia emergency or severe hypoglycemia.

Methods

Two separate case-control studies were nested within 150,153 pregnancies by women with type 1, type 2, or gestational diabetes between 2009 and 2014 in Taiwan. Hyperglycemia emergency (mainly diabetic ketoacidosis and hyperosmolar hyperglycemic state) and severe hypoglycemia occurred in 77 and 153 diabetic pregnancies (cases), respectively. Ten control pregnancies were randomly selected for each case by matching each case pregnancy on type of diabetes (i.e., T1DM, T2DM, or GDM), maternal age on the date of acute glycemic complication occurrence (i.e., index date), and “length of gestation at risk” (i.e., period between conception and index date). Meteorological parameters were retrieved from 542 meteorological monitoring stations across Taiwan during 2008–2014. Conditional logistic regression analysis with generalized estimation equation was separately performed to estimate the covariate adjusted odds ratios (ORs) of each of the two acute glycemic complications in association with season and ambient temperature within 30 days prior to the index date.

Results

Compared to summer, winter season was associated with a significantly elevated risk of severe hypoglycemia with an OR of 1.74 (95% confidence interval (CI) 1.08–2.79). The OR of hyperglycemic emergency was also elevated in winter season at OR of 1.88, but the significance is only marginal (95% CI 0.97–3.64, p = 0.0598). Subgroup analyses further noted that such seasonal variation was also observed in pregnancies with pre-pregnancy type 1 diabetes and gestational diabetes. On the other hand, ambient temperature was not significantly associated with the two acute glycemic complications.

Conclusions

A moderately but significantly elevated risk of severe hypoglycemia was found in pregnant women with diabetes during winter season, and such increased risk was more evident in pregnancies with T1DM.

Supplementary information

The online version contains supplementary material available at https://doi.org/10.1265/ehpm.22-00003.

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.

Relationship between gestational diabetes and serum trace element levels in pregnant women from Eastern Iran: a multivariate approach

The prevalence of gestational diabetes mellitus (GDM) has increased over the recent decades. Exposure to environmental contaminants may be a risk factor for the development of GDM, but this is heavily dependent on particular circumstances. Studies on various areas linking various factors are therefore needed. We examined the associations between serum trace element levels and incidents of GDM among 102 pregnant women (diabetic n = 60 and healthy n = 42) living in Birjand (Iran). Blood serum samples were analyzed for concentrations of elements linked to particulate matter air pollution such as As, Cd, Cu, Hg, Mn, Ni, V, and Zn. Concentrations of As (8.58 vs. 3.15 μg/L), Cd (6.74 vs. 0.52 μg/L), and Hg (2.60 vs. 0.90 μg/L) were significantly higher in women with GDM. Risk difference (RD) estimation showed that As, 0.516 (0.355, 0.677); Cd, 0.719 (0.534, 0.904); and Hg, 0.505 (0.276, 0.735) increase GDM probability, while V lower that risk, -0.139 (-0.237, -0.042). With the principal component analysis, we were able to separate subjects according to their GDM status based on element levels. Such classification revealed very high efficiency with a true positive rate of 93%, according to linear discriminant analysis. GDM subjects presented higher levels of As, Cd, and Hg, indicating that these elements may disturb insulin metabolism and promote the development of GDM. Therefore, we conclude that systematic monitoring of trace elements followed by multivariate modeling in women planning pregnancy should be carried out to prevent the development of GDM.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

SO2 derivatives induce dysfunction in human trophoblasts via inhibiting ROS/IL-6/STAT3 pathway

BACKGROUND

Epidemiological studies have revealed that sulfur dioxides (SO₂) can increase the risk of pregnancy complications such as missed abortion in the first trimester, stillbirth, preterm birth, small for gestational age, gestational diabetes mellitus and preeclampsia, but the mechanisms underlying these findings remains unknown. What is known, however, is that trophoblasts, a type of fetal cell exerting vital immunologic functions to maintain a successful pregnancy, are usually involved in the pathogenic mechanism of pregnancy complications.

OBJECTIVE

To study the effect of SO₂ derivatives (bisulfite and sulfite, 1:3 M/M) on the function of trophoblasts.

METHODS

Swan.71 trophoblast cells were treated with various concentrations of SO₂ derivatives to determine the effect of SO₂ derivatives on cellular viability by CKK8. Flow cytometry was performed to analyze the effect of SO₂ derivatives on apoptosis, cell cycle and intracellular ROS. Wound healing assay and transwell assay were conducted to examine the migration and invasion of Swan.71 cells. Inflammation-related cytokines in the supernatant (IL-1β, IL-6, IL-8, IL-10 and TNF-α) were measured by IMMULITE®1000 Systems (SIEMENS). The expression level of NLRP3, Caspase1, MMP9, MMP2, STAT3, and p-STAT3 were evaluated by Western Blotting.

RESULTS

Exposure to SO₂ derivatives significantly decreased cellular viability, arrested cell cycle at S/G2/M phase and induced cell apoptosis of Swan.71 trophoblasts. In addition, the migration and invasion of Swan.71 cell were significantly inhibited. SO₂ derivatives also significantly increased IL-1β secretion while it is NLRP3/Caspase1 independent. IL-6 secretion was significant inhibited accompanied by decreased STAT3 phosphorylation and expression of MMP2 and MMP9. The intracellular ROS level was significantly suppressed by SO₂ derivatives.

CONCLUSION

SO₂ derivatives exert toxic effects on trophoblasts which results in: suppressing cellular viability and intracellular ROS level, interfering with cell proliferation through arresting cell cycle, inducing cell apoptosis, disturbing inflammation-related cytokines secretion and inhibiting motility. Decreased ROS/IL-6/STAT3 levels play a role in inhibited cell viability, cell cycle arrest, apoptosis and defective motility.

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.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Climate factors and gestational diabetes mellitus risk - a systematic review

BACKGROUND

Current and projected increases in global temperatures and extreme climate events have led to heightened interest in the impact of climate factors (i.e. ambient temperature, season/seasonality, and humidity) on human health. There is growing evidence that climate factors may impact metabolic function, including insulin sensitivity. Gestational diabetes mellitus (GDM) is a common pregnancy complication, with an estimated global prevalence of up to 14%. While lifestyle and genetic risk factors for GDM are well established, environmental factors may also contribute to GDM risk. Previous reviews have summarized the growing evidence of environmental risk factors for GDM including endocrine disrupting chemicals and ambient air pollution. However, studies of the effects of climate factors on GDM risk have not been systematically evaluated. Therefore, we conducted a systematic review to summarize and evaluate the current literature on the associations of climate factors with GDM risk.

METHODS

We conducted systematic searches in PubMed and EMBASE databases for original research articles on associations of climate factors (i.e. ambient temperature, season/seasonality, and humidity) with GDM and/or related glycemic outcomes for all publication dates through September 20th, 2020.

RESULTS

Our search identified 16 articles on the associations of ambient temperature and/or season with GDM and maternal glycemic outcomes during pregnancy, which were included in this review. Despite inconsistencies in exposure and outcome assessment, we found consistent evidence of a seasonal effect on GDM risk, with higher prevalence of GDM and higher pregnancy glucose levels in summer months. We found suggestive evidence of an association between higher ambient temperature and elevated glucose levels from GDM screening tests.

CONCLUSION

Climate factors may be associated with GDM risk. However, further research is needed to evaluate these associations and to elucidate the specific mechanisms involved.

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 (PM_2.5) in the risk of gestational diabetes mellitus (GDM) and only one study has examined exposure to PM_2.5 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 PM_2.5, 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 PM_2.5 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 PM_2.5 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 PM_2.5 (OR = 1.03, 95% CI: 1.00, 1.05) and sulfate PM_2.5 (OR = 1.03, 95% CI: 1.00, 1.05) exposures, as well as preconception Cr PM_2.5 exposures (OR = 1.05, 95% CI: 1.02, 1.07).

CONCLUSION

Exposures to PM_2.5, 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.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Sperm quality and ambient air pollution exposure: A retrospective, cohort study in a Southern province of China

BACKGROUND

Abnormal semen quality is one of the common causes of infertility. The relationship between exposure to air pollutants and semen quality is unclear.

OBJECTIVES

To evaluate the impact of ambient air pollutant exposures on semen quality.

METHODS

We analyzed 3797 semen samples from Guangdong Human Sperm Bank between May 28, 2018 and March 31, 2019. The inverse distance weighted interpolation method was used to estimate the personal exposures to CO, SO₂, NO₂, O₃, PM₁₀ and PM_2.5 during the entire period (0-90 lag days) and key periods (0-9, 10-14, 70-90 lag days) of sperm development. Linear mixed models were used to evaluate the exposure-response relationships between air pollutants and semen quality, including sperm concentration, sperm count and sperm motility, after adjusting for other covariates. The regression coefficients and 95% confidence intervals (CIs) associated with each interquartile range (IQR) increase in pollutant concentrations were estimated for each semen quality parameter.

RESULTS

Overall, we observed a significant association of decreased sperm count with the exposure to PM₁₀ (-0.2466; -0.4443, -0.0489) and PM_2.5 (-0.2910; -0.5401, -0.0419). Among the sperm quality parameters assessed, sperm count was observed more frequently to be negatively associated with ambient air pollutants (CO, NO₂, O₃, PM₁₀ and PM_2.5), especially for the period during 10-14 lag days. In addition, motility decline was significantly associated with O₃ in the late stage of sperm development. Sensitivity analyses for subgroup population yielded similar results. No significant association was found between all pollutants and sperm concentration (all P > 0.05).

CONCLUSIONS

Our results indicate that ambient air pollutants exposures during sperm development may have an adverse effect on semen quality, especially for sperm count and motility. The findings emphasize the potential to improve semen quality by reducing ambient air pollutant exposures, and the importance of taking into account the critical period of sperm development when protective measures are implemented.

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.

Associations between the incidence and mortality rates of type 2 diabetes mellitus and long-term exposure to ambient air pollution: A 12-year cohort study in northern China

BACKGROUND

Ambient air pollution has recently been related to type 2 diabetes mellitus (T2DM), a disease that has caused an economic and health burden worldwide. Evidence of an association between air pollution and T2DM was reported in the United States and Europe. However, few studies have focused on the association with high levels of air pollutants in a developing country.

OBJECTIVES

We conducted a 12-year cohort study to assess the incidence and mortality of T2DM associated with long-term exposure to PM₁₀, SO₂, and NO₂.

METHODS

A retrospective cohort with participants from four cities in northern China was conducted to assess mortality and incidence of T2DM from 1998 to 2009. Incidence of T2DM was self-reported, and incident intake of an antidiabetic drug or injection of insulin simultaneously and mortality of T2DM was obtained from a family member and double checked against death certificates provided from the local center for disease control and prevention. Individual pollution exposures were the mean concentrations of pollutants estimated from the local environmental monitoring centers over the survival years. Hazard ratios (HRs) were estimated using Cox regression models after adjusting for potential confounding factors.

RESULTS

A total of 39 054 participants were recruited into the mortality cohort, among which 59 subjects died from T2DM; 38 529 participants were analyzed in the incidence cohort, and 1213 developed new cases of T2DM. For each 10 μg/m³ increase in PM₁₀, SO₂, and NO₂, the adjusted HRs and 95% confidence interval (CI) for diabetic incidence were 1.831 (1.778, 1.886), 1.287 (1.256, 1.318), and 1.472 (1.419, 1.528), respectively. Similar results can be observed in the analysis of diabetic mortality with HRs (95% CI) up to 2.260 (1.732, 2.950), 1.130 (1.042, 1.225), and 1.525 (1.280, 1.816), respectively.

CONCLUSIONS

Our results suggested that long-term exposure to high levels of PM₁₀, SO₂, and NO₂ increase risk of incident and mortality of T2DM in China.

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

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

A population-based study on the prevalence of gestational diabetes mellitus in association with temperature in Taiwan

BACKGROUND

Previous studies showing seasonal clustering of gestational diabetes mellitus (GDM) were conducted in the temperate or frigid zones and mostly included pregnant Caucasian women. This study aims to investigate the association of ambient temperature with prevalence of GDM in Taiwan, a sub-tropic country.

METHODS

This population-based cohort study comprised women (n = 371,131) who gave births between 2013 and 2014; of which, 43,538 (11.7%) were diagnosed with GDM. The mean daily temperature and difference in temperature within a day was calculated over a 35-day period prior to GDM diagnosis or the first day of the 27th gestational week (for non-GDM subjects). Multiple logistic regression models with generalized estimation equation were performed to estimate the adjusted odds ratio (aOR) and 95% confidence interval (CI) of GDM in association with temperature.

RESULTS

After controlling for potential confounders, summer and fall were associated with higher risk of GDM diagnosis, with aOR [95% CI] of 1.05 [1.04-1.07] and 1.04 [1.02-1.06] in reference to winter. Additionally, an increase of 1 °C from 14 °C to 27 °C was associated with an aOR of 1.03 [1.02-1.03]. The aOR greatly increased to 1.54 [1.48-1.60] after 28 °C. An increase of 1 °C difference within a day was associated with a reduced aOR at 0.90 [0.87-0.92].

CONCLUSION

A higher prevalence of GDM was associated with a higher daily temperature, but with a smaller difference in temperature within a day.

Air pollution and gestational diabetes mellitus: evidence from cohort studies

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

Ambient air pollution exposure and gestational diabetes mellitus in Guangzhou, China: A prospective cohort study

BACKGROUND

Evidence concerning the effect of ambient air pollution exposure on gestational diabetes mellitus (GDM) is limited. No published studies have examined maternal weekly air pollution exposure and GDM, and the possible effect modification by folic acid supplementation has not been assessed.

OBJECTIVES

To evaluate the association between air pollution exposure and GDM at trimester and weekly levels, and to explore the potential effect modification by folic acid supplementation.

METHODS

A total of 5421 pregnant women were recruited during 2011-2014 in Guangzhou, China. Daily PM_2.5, PM₁₀, SO₂ and NO₂ levels were collected from 10 monitoring stations. Individual's exposure during pregnancy was estimated using inverse-distance weighting approach. Binary logistic regression was used to examine the trimester-specific association between air pollution exposure and GDM. Distributed lag models (DLMs) were applied to estimate maternal weekly air pollution exposure and GDM. Stratified analyses by folic acid supplementation and interaction test were performed.

RESULTS

The GDM incidence was 11.69%. An interquartile range (IQR) increase in first trimester SO₂ was associated with increased GDM risk in the single pollutant model, the adjusted odds ratio (aOR) and 95% confidence interval (CI) was 1.22 (1.02-1.47). In DLMs, an IQR increase in SO₂ during 4th to 10th gestational weeks was associated with increased GDM risk, with the strongest effect in the 7th gestational week. When stratified by maternal folic acid supplementation, first trimester exposure to SO₂ was associated with increased GDM risk among women taking folic acid supplements (aOR = 1.25, 95% CI: 1.03-1.53) and P value for interaction was 0.13. No significant effects were observed for PM_2.5, PM₁₀ and NO₂.

CONCLUSION

First trimester exposure to SO₂ was associated with increased GDM risk, especially during the 4th to 10th gestational weeks. The effect might be stronger among women taking folic acid supplements.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Acute effects of air pollutants on adverse birth outcomes in Changsha, China: A population data with time-series analysis from 2015 to 2017

Evidence for the acute effects of air pollutants on adverse birth outcomes is not yet conclusive. Furthermore, there are no investigations relating to the association between air pollutants and macrosomia. The aim of this study was to determine the relationship between air pollutants and low birth weight, preterm birth, and macrosomia in Changsha. Time-series analysis, using a generalized additive model was applied. Data about the adverse birth outcomes was collected from 78 midwifery institutions. Air pollution data including SO2, NO2, particulate matter <10 μm in diameter (PM10), particulate matter <2.5 μm in diameter (PM2.5), O3, CO, and climate data were respectively collected from the Changsha Environmental Protection Agency and the Changsha Meteorological Bureau from January 2015 to December 2017. During the study period, there were 344,880 live births to be studied. In a single pollutant model, for every increase of 10 μg/m in PM10 and PM2.5, low birth weight increased by 0.12% (95% confidence interval [CI]: 0.01-0.23%) at a lag 06 and 0.44% (95% CI: 0.35-0.53%) at a lag 3, respectively. Preterm birth increased most by 1.60% (95% CI: 1.41-1.80%) at a lag 2 for every increase of 10 μg/m in SO2. The highest increases in macrosomia associated with a 10 μg/m increase in air pollutant were 3.53% (95% CI: 3.41-3.64%) for NO2 at lag 0, 3.33% (95% CI: 3.05-3.60%) for SO2 at lag03. Multi-pollutant models showed that only PM10 increased the low birth weight and preterm birth risk effect by 3.91% (95% CI: 3.67-4.12%) and 0.25% (95% CI: 0.14-0.37%). NO2 increased macrosomia risk by 4.14% (95% CI: 3.97-4.31%) with a 10 μg/m increase. There was no association observed between the air pollutants O3 and CO and adverse birth outcomes. Pregnant women should also take steps to limit their exposure to high levels of air pollutants during the final weeks of pregnancy.

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

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

Cigarette Smoke During Breastfeeding in Rats Changes Glucocorticoid and Vitamin D Status in Obese Adult Offspring

Maternal smoking increases obesogenesis in the progeny. Obesity is associated with several hormonal dysfunctions. In a rat model of postnatal tobacco smoke exposure, we previously reported increased central fat depot and disruption of some hormonal systems in the adult offspring. As both glucocorticoids and vitamin D alter lipogenesis and adipogenesis, here we evaluated the metabolism of these two hormones in visceral adipose tissue (VAT) and liver by Western blotting, and possible associations with lipogenesis biomarkers in adult rats that were exposed to tobacco smoke during their suckling period. At postnatal day (PN) 3, dams and offspring of both sexes were exposed (S group) or not (C group) to tobacco smoke, 4 × 1 h/day. At PN180, corticosteronemia was lower in S male and higher in S female offspring, without alterations in peripheral glucocorticoid metabolism and receptor. Adrenal ACTH receptor (MC2R) was higher in both sexes of S group. Despite unchanged serum vitamin D, liver 25-hydroxylase was higher in both sexes of S group. Male S offspring had higher 1α-hydroxylase, acetyl-CoA carboxylase (ACC), and fatty acid synthase (FAS) in VAT. Both sexes showed increased ACC protein content and reduced sirtuin mRNA in liver. Male S offspring had lower liver peroxisome proliferator-activated receptor-α. Tobacco exposure during lactation induced abdominal obesity in both sexes via distinct mechanisms. Males and females seem to develop HPA-axis dysfunction instead of changes in glucocorticoid metabolism and action. Lipogenesis in VAT and liver, as well as vitamin D status, are more influenced by postnatal smoke exposure in male than in female adult rat offspring.