Air pollution and gestational diabetes mellitus: evidence from cohort studies

The impact of environmental pollution on metabolic health and the risk of non-communicable chronic metabolic diseases in humans

AIMS

This review aims to provide a comprehensive overview to understand the role of pollution in the development of noncommunicable diseases (NCDs), with a focus on metabolic diseases.

DATA SYNTHESIS

In the context of NCDs, the incidence of metabolic diseases such as obesity and diabetes are increasing at an alarming rate. In addition to the well-known role of the so-called "obesogenic" environment, characterized by unhealthy diet and physical inactivity, great attention has been paid in recent years to the effects of pollution. Indeed, progressive urbanization has been associated with increased exposure to pollutants. The harmful effects of some pollutants on the endocrine system have been known for decades, but data on the metabolic impact of pollution are rather recent. Pollution in its various forms promotes a systemic inflammatory state, insulin resistance, and oxidative stress, which appear to be closely associated with increased risk of NCD, particularly obesity and diabetes.

CONCLUSIONS

In conclusion, urbanization has so far had a predominantly negative impact on collective health, but a better understanding of the mechanisms linking pollution to metabolic health is crucial to implement preventive strategies, including careful urban planning to improve community health, understood not only as the absence of disease but also as psychological and social well-being, overcoming the risks associated with urbanization.

The association between air pollution and three types of diabetes: An umbrella review of systematic reviews and meta-analyses

BACKGROUND

Despite numerous meta-analyses showing an association between air pollutants and diabetes, there is considerable heterogeneity between studies.

OBJECTIVES

This study aims to evaluate the cumulative evidence regarding the association between air pollution and type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM), and gestational diabetes mellitus (GDM) through systematic reviews and meta-analyses.

METHODS

Following the PRISMA 2020 guidance, a comprehensive review across three databases, including Web of Science, Embase, and PubMed, from inception to September 30, 2024. The quality of the included systematic reviews was assessed using the AMSTAR 2 tool. The research protocol has been registered in PROSPERO (CRD42024594953).

RESULTS

A total of 19 meta-analyses were identified in this review, including two articles investigating the impact of air pollution on T1DM, nine on T2DM, and ten on GDM. Due to limited data, no significant relationship between air pollution and T1DM was found. There is evidence that exposure to particulate matter (PM2.5 and PM10) may significantly increase the risk of T2DM. However, meta-analyses concerning GDM exhibit a less consistent association between air pollution and GDM risk, which varies by pollutant and duration of exposure.

CONCLUSION

Results suggest that exposure to air pollution may increase diabetes risk to some extent, particularly for T2DM. However, due to limited available studies, further prospective cohort studies are warranted to elucidate the role of air pollutants in diabetes, particularly for T1DM. Additionally, understanding potential mechanisms by which air pollution affects diabetes is crucial for future investigations.

Radon Exposure and Gestational Diabetes

Importance

Understanding environmental risk factors for gestational diabetes (GD) is crucial for developing preventive strategies and improving pregnancy outcomes.

Objective

To examine the association of county-level radon exposure with GD risk in pregnant individuals.

Design, Setting, and Participants

This multicenter, population-based cohort study used data from the Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be (nuMoM2b) cohort, which recruited nulliparous pregnant participants from 8 US clinical centers between October 2010 and September 2013. Participants who had pregestational diabetes or were missing data on GD or county-level radon measurements were excluded from the current study. Data were analyzed from September 2023 to January 2024.

Exposures

County-level radon data were created by the Lawrence Berkeley National Laboratory based on the Environmental Protection Agency's short- and long-term indoor home radon assessments. Radon exposure was categorized into 3 groups: less than 1, 1 to less than 2, and 2 or more picocuries (pCi)/L (to convert to becquerels per cubic meter, multiply by 37). Because radon, smoking, and fine particulate matter air pollutants (PM2.5) may share similar biological pathways, participants were categorized by joint classifications of radon level (<2 and ≥2 pCi/L) with smoking status (never smokers and ever smokers) and radon level with PM2.5 level (above or below the median).

Main Outcomes and Measures

The main outcome was GD, identified based on glucose tolerance testing and information from medical record abstraction. Multiple logistic regression models were used to assess the association between radon exposure and GD.

Results

Among the 9107 participants, mean (SD) age was 27.0 (5.6) years; 3782 of 9101 (41.6%) had ever used tobacco. The mean (SD) county-level radon concentration was 1.6 (0.9) pCi/L, and 382 participants (4.2%) had GD recorded. After adjusting for potential confounders, individuals living in counties with the highest radon level (≥2 pCi/L) had higher odds of developing GD compared with those living in counties with the lowest radon level (<1 pCi/L) (odds ratio [OR], 1.37; 95% CI, 1.02-1.84); after additional adjustment for PM2.5, the OR was 1.36 (95% CI, 1.00-1.86). Elevated odds of GD were also observed in ever smokers living in counties with a higher (≥2 pCi/L) radon level (OR, 2.09; 95% CI, 1.41-3.11) and participants living in counties with higher radon and PM2.5 levels (OR, 1.93; 95% CI, 1.31-2.83), though no statistically significant interactions were observed.

Conclusions and Relevance

This cohort study suggests that higher radon exposure is associated with greater odds of GD in nulliparous pregnant individuals. Further studies are needed to confirm the results and elucidate the underlying mechanisms, especially with individual-level residential radon exposure assessment.

The relationship of short-term exposure to meteorological factors on diabetes mellitus mortality risk in Hefei, China: a time series analysis

OBJECTIVES

The study aims to explore whether short-term exposure to meteorological factors has a potential association with the risk of diabetes mellitus (DM) mortality.

METHODS

During the period 2015-2018, we collected daily data on meteorological factors and deaths of diabetic patients in Hefei. A total of 1101 diabetic deaths were recorded. We used structural equation modeling to initially explore the relationships among air pollutants, meteorological variables, and mortality, and generalized additive modeling (GAM) and distributional lag nonlinear modeling (DLNM) to explore the relationship between meteorological factors and the mortality risk of DM patients. We also stratified by age and gender. The mortality risk in diabetic patients was expressed by relative risks (RR) and 95% confidence intervals (CI) for both single and cumulative days.

RESULTS

Single-day lagged results showed a high relative humidity (RH) (75th percentile, 83.71%), a fairly high average temperature (T mean) (95th percentile, 30.32 °C), and an extremely low diurnal temperature range (DTR) (5th percentile, 3.13 °C) were positively related to the mortality risk of DM. Stratified results showed that high and very high levels of T mean were significantly positively linked to the mortality risk of DM among females and the elderly, while very high levels of DTR were linked to the mortality risk in men and younger populations.

CONCLUSION

In conclusion, this study found that short-duration exposure to quite high T mean, high RH, and very low DTR were significantly positively related to the mortality risk of DM patients. For women and older individuals, exposure to high and very high T mean environments should be minimized. Men and young adults should be aware of daily temperature changes.

Effect of environmental air pollutants on placental function and pregnancy outcomes: a molecular insight

Air pollution has become a major health concern, particularly for vulnerable populations such as the elderly, children, and pregnant women. Studies have reported a strong association between prenatal exposure to air pollutants and adverse pregnancy outcomes, including lower birth weight, reduced fetal growth, and an increased frequency of preterm births. This review summarizes the harmful effects of air pollutants, such as particulate matter, on pregnancy and outlines the mechanistic details associated with these adverse outcomes. Particulate pollutant matter may be able to cross the placenta barrier, and alterations in placental functions are central to the detrimental effects of these pollutants. In addition to associations with preeclampsia and gestational hypertension, air pollutants also induce oxidative stress, inflammation, and epigenetic alteration in the placenta. These pollutants can also affect placental homeostasis and endocrine function, contributing to pregnancy complications and possible transgenerational effects. Prenatal air pollution exposure has been linked to reduced cognitive and motor function in infants and newborns, increasing the predisposition to autism spectrum disorders and other neuropsychiatric disorders. This review also summarizes the use of various animal models to study the harmful effects of air pollution on pregnancy and postnatal outcomes. These findings provide valuable insight into the molecular events associated with the process and can aid in risk mitigation and adopting safety measures. Implementing effective environmental protocols and taking appropriate steps may reduce the global disease burden, particularly for developing nations with poor regulatory compliance and large populations of pregnant women.

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

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

The impact of PM2.5 and its constituents on gestational diabetes mellitus: a retrospective cohort study

BACKGROUND

There is increasing evidence that exposure to PM2.5 and its constituents is associated with an increased risk of gestational diabetes mellitus (GDM), but studies on the relationship between exposure to PM2.5 constituents and the risk of GDM are still limited.

METHODS

A total of 17,855 pregnant women in Guangzhou were recruited for this retrospective cohort study, and the time-varying average concentration method was used to estimate individual exposure to PM2.5 and its constituents during pregnancy. Logistic regression was used to assess the relationship between exposure to PM2.5 and its constituents and the risk of GDM, and the expected inflection point between exposure to PM2.5 and its constituents and the risk of GDM was estimated using logistic regression combined with restricted cubic spline curves. Stratified analyses and interaction tests were performed.

RESULTS

After adjustment for confounders, exposure to PM2.5 and its constituents (NO3-, NH4+, and OM) was positively associated with the risk of GDM during pregnancy, especially when exposure to NO3- and NH4+ occurred in the first to second trimester, with each interquartile range increase the risk of GDM by 20.2% (95% CI: 1.118-1.293) and 18.2% (95% CI. 1.107-1.263), respectively. The lowest inflection points between PM2.5, SO42-, NO3-, NH4+, OM, and BC concentrations and GDM risk throughout the gestation period were 18.96, 5.80, 3.22, 2.67, 4.77 and 0.97 µg/m3, respectively. In the first trimester, an age interaction effect between exposure to SO42-, OM, and BC and the risk of GDM was observed.

CONCLUSIONS

This study demonstrates a positive association between exposure to PM2.5 and its constituents and the risk of GDM. Specifically, exposure to NO3-, NH4+, and OM was particularly associated with an increased risk of GDM. The present study contributes to a better understanding of the effects of exposure to PM2.5 and its constituents on the risk of GDM.

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

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

Climate change, air pollution and maternal and newborn health: An overview of reviews of health outcomes

Background

Climate change represents a fundamental threat to human health, with pregnant women and newborns being more susceptible than other populations. In this review, we aimed to describe the current landscape of available epidemiological evidence on key climate risks on maternal and newborn health (MNH).

Methods

We sought to identify published systematic and scoping reviews investigating the impact of different climate hazards and air pollution on MNH outcomes. With this in mind, we developed a systematic search strategy based on the concepts of 'climate/air pollution hazards, 'maternal health,' and 'newborn health,' with restrictions to reviews published between 1 January 2010 and 6 February 2023, but without geographical or language restriction. Following full text screening and data extraction, we synthesised the results using narrative synthesis.

Results

We found 79 reviews investigating the effects of climate hazards on MNH, mainly focussing on outdoor air pollution (n = 47, 59%), heat (n = 24, 30%), and flood/storm disasters (n = 7, 9%). Most were published after 2015 (n = 60, 76%). These reviews had consistent findings regarding the positive association of exposure to heat and to air pollution with adverse birth outcomes, particularly preterm birth. We found limited evidence for impacts of climate-related food and water security on MNH and did not identify any reviews on climate-sensitive infectious diseases and MNH.

Conclusions

Climate change could undermine recent improvements in maternal and newborn health. Our review provides an overview of key climate risks to MNH. It could therefore be useful to the MNH community to better understand the MNH needs for each climate hazard and to strengthen discussions on evidence and research gaps and potential actions. Despite the lack of comprehensive evidence for some climate hazards and for many maternal, perinatal, and newborn outcomes, we observed repeated findings of the impact of heat and air pollutants on birth outcomes, particularly preterm birth. It is time for policy dialogue to follow to specifically design climate policy and actions to protect the needs of MNH.

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

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

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

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

Ambient fine particulate matter and pregnancy outcomes: An umbrella review

The available evidence on the effects of ambient fine particulate matter (PM2.5) and pregnancy outcomes (birth outcomes and pregnancy complications) has increased substantially. The purpose of this umbrella review is to refine the evidence of the association between birth outcome (birth defects) and PM2.5; and summarize the credibility of existing research on the association between pregnancy complications and PM2.5. We searched PubMed, Web of Science, Embase, and Cochrane databases for relevant systematic reviews and meta-analyses up to March 16, 2022 in accordance with PRISMA guidelines. Two independent investigators conducted data extraction. AMSTAR 2 and GRADE assessment criteria were used to evaluate the methodological and evidence quality. We performed subgroup analyses by trimesters of pregnancy. The review protocol for this study has been registered in PROSPERO (CRD42022325550). This umbrella review identified a total of 41 systematic reviews, including 28 articles evaluating the influence of PM2.5 on birth outcomes and 13 on pregnancy complications. Positive associations between perinatal PM2.5 exposure and adverse birth outcomes were found, including low birth weight, preterm birth, stillbirth, small for gestational age, and birth defects. Pregnant women exposed to PM2.5 had a significantly higher risk of developing hypertensive disorder of pregnancy, gestational diabetes mellitus, gestational hypertension, and preeclampsia. The findings of subgroup analysis demonstrated that the effects of ambient PM2.5 exposure on pregnancy outcomes varied by trimesters. The findings of this extensive umbrella review provide convincing proof that exposure to ambient PM2.5 raises the risks of unfavorable birth outcomes and pregnancy complications. Some associations show considerable disparity between trimesters. These findings have implications for strengthen perinatal health care on air pollution and improving intergenerational equity.

Bayesian spatiotemporal modelling for disease mapping: an application to preeclampsia and gestational diabetes in Florida, United States

Morbidities generally show patterns of concentration that vary by space and time. Disease mapping models are useful in estimating the spatiotemporal patterns of disease risks and are therefore pivotal for effective disease surveillance, resource allocation, and the development of prevention strategies. This study considers six spatiotemporal Bayesian hierarchical models based on two spatial conditional autoregressive priors. It could serve as a guideline on the development and application of Bayesian hierarchical models to assess the emerging risk trends, risk clustering, and spatial inequality trends, with estimation of covariables' effects on the interested disease risk. The method is applied to the Florida Birth Record data between 2006 and 2015 to study two cardiovascular risk factors: preeclampsia and gestational diabetes. High-risk clusters were detected in North Central Florida for preeclampsia and in Central Florida for gestational diabetes. While the adjusted disease trend was stable, spatial inequality peaked in 2011-2012 for both diseases. Exposure to PM2.5 at first or/and second trimester increased the risk of preeclampsia and gestational diabetes, but the magnitude is less severe compared to previous studies. In conclusion, this study underscores the significance of selecting appropriate disease mapping models in estimating the intricate spatiotemporal patterns of disease risk and suggests the importance of localized interventions to reduce health disparities. The result also identified an opportunity to study potential risk factors of preeclampsia, as the spike of risk in North Central Florida cannot be explained by current covariables.

Climate and Environmental Change: A Generation at Risk

ABSTRACT

Climate and environmental changes have been described as the biggest global health threat of the 21st century, with the potential to cause immediate harm in early life with important lifelong effects, and important consequences for future generations. Pregnant women and children are increasingly being recognized as vulnerable populations in the context of climate change. The effects can be direct or indirect through heat stress, extreme weather events, and air pollution, potentially affecting both the immediate and long-term health of pregnant women and newborns through a broad range of mechanisms. Climate and environmental changes have wide-ranging effects on a woman's reproductive life including sexual maturation and fertility, pregnancy outcomes, lactation, breastfeeding, and menopause. A comprehensive overview of these impacts is presented as well as opportunities for interventions for nurses practicing in perinatal, neonatal, midwifery, and pediatric specialties.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Ambient air pollution and gestational diabetes mellitus: An updated systematic review and meta-analysis

OBJECTIVE

We aimed to evaluate the relationship between the composition of particulate matter (PM) and gestational diabetes mellitus (GDM) by a comprehensively review of epidemiological studies.

METHODS

We systematically identified cohort studies related to air pollution and GDM risk before February 8, 2023 from six databases (PubMed, Embase, Web of Science Core Collection, China National Knowledge Infrastructure, Wanfang Data Knowledge Service Platform and Chongqing VIP Chinese Science and Technology Periodical databases). We calculated the relative risk (RR) and its 95% confidence intervals (CIs) to assess the overall effect by using a random effects model.

RESULTS

This meta-analysis of 31 eligible cohort studies showed that exposure to PM_2.5, PM₁₀, SO₂, and NO₂ was associated with a significantly increased risk of GDM, especially in preconception and first trimester. Analysis of the components of PM_2.5 found that the risk of GDM was strongly linked to black carbon (BC) and nitrates (NO₃^-). Specifically, BC exposure in the second trimester and NO₃^- exposure in the first trimester elevated the risk of GDM, with the RR of 1.128 (1.032-1.231) and 1.128 (1.032-1.231), respectively. The stratified analysis showed stronger correlations of GDM risk with higher levels of pollutants in Asia, except for PM_2.5 and BC, which suggested that the specific composition of particulate pollutants had a greater effect on the exposure-outcome association than the concentration.

CONCLUSIONS

Our study found that ambient air pollutant is a critical factor for GDM and further studies on specific particulate matter components should be considered in the future.

Thyroid dysfunction during gestation and gestational diabetes mellitus: a complex relationship

PURPOSE

Gestational diabetes mellitus (GDM) and thyroid dysfunction during gestation (GTD) are the two most prevalent endocrinopathies during pregnancy. The aim of the present review is to provide an overview of the peculiar aspects of GDM and GTD, to highlight the potential interactions and clinical consequences of these two frequent clinical conditions.

METHODS

A literature review regarding GDM and GTD was carried out with particular interest on meta-analyses and human studies dealing with the (i) shared risk factors between GDM and GTD, (ii) the epidemiological link between GTD and GDM, (iii) physiopathologic link between GTD and GDM, (iv) clinical consequences of GDM and GTD, and (v) post-partum implications of GDM and GTD.

RESULTS

The association between GDM and GTD is common and may be explained by the insulin-resistance state due to maternal GTD, to alterations in the placentation process or to the many shared risk factors. Discrepant results of epidemiologic studies can be explained, at least in part, by the changes in diagnostic criteria and screening strategies throughout the years for both conditions. GDM and GTD impact pregnancy outcome and have post-partum long-term consequences, but more studies are needed to prove an additional adverse effect.

CONCLUSIONS

Based on the epidemiological and physio-pathological link between GDM and GTD, it could be suggested that a diagnosis of GTD could lead to screen GDM and the other way round.

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.

Early pregnancy particulate matter exposure, pre-pregnancy adiposity and risk of gestational diabetes mellitus in Finnish primiparous women: An observational cohort study

AIMS

To evaluate the association between the exposure of particulate matter with an aerodynamic diameter of ≤ 2.5μm (PM_2.5) and with an aerodynamic diameter of ≤ 10μm (PM₁₀) over the first trimester and the risk of gestational diabetes mellitus (GDM), and to assess whether maternal pre-pregnancy body mass index (BMI) modified the GDM risk.

METHODS

All Finnish primiparous women without previously diagnosed diabetes who delivered between 2009 and 2015 in the city of Vantaa, Finland, composed the study cohort (N = 6189). Diagnosis of GDM was based on a standard 75 g 2-hour oral glucose tolerance test. The average daily concentration of PM_2.5 and PM₁₀ over the first trimester was calculated individually for each woman. The relationship between exposure of PM_2.5 and PM₁₀ and GDM was analyzed with logistic models.

RESULTS

No association was observed between the average daily concentrations of PM_2.5 and PM₁₀ over the first trimester and the GDM risk. When simultaneously taking BMI and PM₁₀ into account both mean daily PM₁₀ concentration (p = 0.047) and pre-pregnancy BMI (p = 0.016) increased GDM risk independently and an interaction (p = 0.013) was observed between PM₁₀ concentration and pre-pregnancy BMI.

CONCLUSIONS

Even globally low PM₁₀ exposure level together with elevated maternal pre-pregnancy BMI seems to increase the GDM risk.

Association between air pollution exposure and gestational diabetes mellitus in pregnant women: a retrospective cohort study

The global prevalence of gestational diabetes mellitus (GDM) is increasing annually, and previous research reports on the relationship between exposure to air pollutants and GDM are not completely consistent. We investigated the association between air pollutant exposure and GDM in pregnant women in a retrospective cohort study in Guangzhou. We found that in the first trimester, exposure to PM_2.5 and CO showed a significant association with GDM. In the second trimester, exposure to PM₁₀ was significantly associated with GDM. In the third trimester, exposure to PM_2.5, PM₁₀, NO₂, SO₂, and CO at IQR4 (odds ratio [OR] = 1.271, 95% confidence interval [CI]: 1.179-1.370; OR = 1.283, 95% CI: 1.191-1.383; OR = 1.230, 95% CI: 1.145-1.322; OR = 1.408, 95% CI: 1.303-1.522; OR = 1.150, 95% CI: 1.067-1.240, respectively) compared with IQR1 was positively associated with GDM. However, exposure to NO₂ was negatively associated with GDM in the first and second trimesters, and O₃ was negatively associated with GDM in the second and third trimesters. We found that the correlation between air pollutants and GDM in different trimesters of pregnancy was not completely consistent in this retrospective cohort study. During pregnancy, there may be an interaction between air pollutant exposure and other factors, such as pregnant women's age, occupation, anemia status, pregnancy-induced hypertension status, and pregnancy season.

Chemical Compounds and Ambient Factors Affecting Pancreatic Alpha-Cells Mass and Function: What Evidence?

The exposure to different substances present in the environment can affect the ability of the human body to maintain glucose homeostasis. Some review studies summarized the current evidence about the relationships between environment and insulin resistance or beta-cell dysfunction. Instead, no reviews focused on the relationships between the environment and the alpha cell, although in recent years clear indications have emerged for the pivotal role of the alpha cell in glucose regulation. Thus, the aim of this review was to analyze the studies about the effects of chemical, biological, and physical environmental factors on the alpha cell. Notably, we found studies focusing on the effects of different categories of compounds, including air pollutants, compounds of known toxicity present in common objects, pharmacological agents, and compounds possibly present in food, plus studies on the effects of physical factors (mainly heat exposure). However, the overall number of relevant studies was limited, especially when compared to studies related to the environment and insulin sensitivity or beta-cell function. In our opinion, this was likely due to the underestimation of the alpha-cell role in glucose homeostasis, but since such a role has recently emerged with increasing strength, we expect several new studies about the environment and alpha-cell in the near future.

Airway pollution and smoking in reproductive health

Environmental exposure refers to contact with chemical, biological, or physical substances found in air, water, food, or soil that may have a harmful effect on a person's health. Almost all of the global population (99%) breathe air that contains high levels of pollutants. Smoking is one of the most common forms of recreational drug use and is the leading preventable cause of morbidity and mortality worldwide. The small particles from either ambient (outdoor) pollution or cigarette smoke are inhaled to the lungs and quickly absorbed into the bloodstream. These substances can affect virtually every organ in our body and have been associated with various respiratory, cardiovascular, endocrine, and also reproductive morbidities, including decreased fertility, adverse pregnancy outcomes, and offspring long-term morbidity. This review summarizes the latest literature reporting the reproductive consequences of women exposed to ambient (outdoor) air pollution and cigarette smoking.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Maternal Exposure to Fine Particulate Matter and Its Chemical Components Increasing the Occurrence of Gestational Diabetes Mellitus in Pregnant Japanese Women

INTRODUCTION

PM2.5 exposure is a suspected risk factor for diabetes. It is hypothesized that maternal PM2.5 exposure contributes to the development of gestational diabetes mellitus (GDM). The association between PM2.5 exposure and GDM is controversial and limited evidence is available for the exposure to PM2.5 chemical components. We investigated the association between maternal exposure to total PM2.5 mass and its components, particularly over the first trimester (early placentation period), and GDM.

METHODS

Data were obtained from the Japan Perinatal Registry Network database, which includes all live births and stillbirths after 22 weeks of gestation at 39 cooperating hospitals in 23 Tokyo wards (2013-2015). At one fixed monitoring site, we performed daily filter sampling of fine particles and measured daily concentrations of carbon and ion components. The average concentrations of total PM2.5 and its components over the 3 months before pregnancy and the first (0-13 gestational weeks) and second (14-27 gestational weeks) trimesters were calculated and assigned to each woman. We estimated the odds ratios (ORs) of GDM in a multilevel logistic regression model.

RESULTS

Among 82,773 women (mean age at delivery = 33.7 years) who delivered singleton births, 3,953 (4.8%) had GDM. In the multiexposure period model, an association between total PM2.5 exposure and GDM was observed for exposure over the first trimester (OR per interquartile range (IQR = 3.63 μg/m3) increase = 1.09; 95% confidence interval (CI) = 1.02-1.16), but not for the 3 months before pregnancy or the second trimester. For PM2.5 components, only organic carbon exposure over the first trimester was positively associated with GDM (OR per IQR (0.51 μg/m3) increase = 1.10; 1.00-1.21).

CONCLUSIONS

This is the first evidence that exposure to total PM2.5 and one of its components, organic carbon, over the first trimester increases GDM occurrence in Japan.

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

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

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.

Exposure to source-specific air pollution and risk for type 2 diabetes: a nationwide study covering Denmark

BACKGROUND

Only few epidemiological studies have investigated whether chronic exposure to air pollution from different sources have different impacts on risk of diabetes. We aimed to investigate associations between air pollution from traffic versus non-traffic sources and risk of type 2 diabetes in the Danish population.

METHODS

We estimated long-term exposure to traffic and non-traffic contributions of particulate matter with a diameter <2.5 µg (PM2.5), elemental carbon (EC), ultrafine particles (UFP) and nitrogen dioxide (NO2) for all persons living in Denmark for the period 2005-17. In total, 2.6 million persons aged >35 years were included, of whom 148 020 developed type 2 diabetes during follow-up. We applied Cox proportional hazards models for analyses, using 5-year time-weighted running means of air pollution and adjustment for individual- and area-level demographic and socioeconomic covariates.

RESULTS

We found that 5-year exposure to all particle measures (PM2.5, UFP and EC) and NO2 were associated with higher type 2 diabetes risk. We observed that for UFP, EC and potentially PM2.5, the pollution originating from traffic was associated with higher risks than the non-traffic contributions, whereas for NO2 similar hazard ratios (HR) were observed. For example, in two-source models, hazard ratios (HRs) per interquartile change in traffic UFP, EC and PM2.5 were 1.025, 1.045 and 1.036, respectively, whereas for non-traffic UFP, EC and PM2.5, the HRs were 1.013, 1.018 and 1.001, respectively.

CONCLUSIONS

Our finding of stronger associations with particulate matter from traffic compared with non-traffic sources implies that prevention strategies should focus on limiting traffic-related particulate matter air pollution.

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 PM2.5 during Pregnancy and Fetal Growth in Eastern Massachusetts, USA

BACKGROUND

Prior studies have examined the association between fine particulate matter [PM ≤2.5μm in aerodynamic diameter (PM2.5)] and fetal growth with either limited spatial or temporal resolution.

OBJECTIVES

In this study, we examined the association between PM2.5 exposure during pregnancy and fetal growth measures (ultrasound parameters and birth weight) in a pregnancy cohort using spatiotemporally resolved PM2.5 in Eastern Massachusetts, USA.

METHODS

We used ultrasound measures of biparietal diameter (BPD), head circumference, femur length, and abdominal circumference (AC), in addition to birth weight, from 9,446 pregnancies that were delivered at the Beth Israel Deaconess Medical Center from 2011-2016. We used linear mixed-effects models to examine the associations of PM2.5 in two exposure windows (the first 16 wk of pregnancy and the cumulative exposure up until the assessment of fetal growth) with anatomic scans (ultrasound measures at<24 wk), growth scans (ultrasound measures at≥24wk), and birth weight. All models were adjusted for sociodemographic characteristics, long-term trends, and temperature.

RESULTS

Higher PM2.5 exposure in the first 16 wk was associated with smaller fetal growth measures, where associations were particularly strong for BPD, AC, and birth weight. For example, a 5-μg/m3 increase in PM2.5 was associated with a lower mean BPD z-score of -0.19 (95% CI: -0.31, -0.06) before 24 wk, a lower mean AC z-score of -0.15 (95% CI: -0.28, -0.01) after 24 wk, and a lower mean birth weight z-score of -0.11 (95% CI: -0.20, -0.01). Analyses examining the associations with cumulative PM2.5 exposure up until the assessment of fetal growth produced attenuated associations.

CONCLUSIONS

Higher gestational exposure to PM2.5 was associated with smaller fetal growth measures at levels below the current national standards. https://doi.org/10.1289/EHP9824.

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.

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

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

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

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Ambient PM gross β-activity and glucose levels during pregnancy

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Particle air pollution and gestational diabetes mellitus in Houston, Texas

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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