Increased risk of gestational diabetes mellitus in women with higher prepregnancy ambient PM2.5 exposure

Investigation of the relationship between air pollution and gestational diabetes

BACKGROUND

Gestational diabetes mellitus (GDM) can have negative effects on both the pregnancy and perinatal outcomes, as well as the long-term health of the mother and the child. It has been suggested that exposure to air pollution may increase the risk of developing GDM. This study investigated the relationship between exposure to air pollutants with gestational diabetes.

METHODS

The present study is a retrospective cohort study. We used data from a randomised community trial conducted between September 2016 and January 2019 in Iran. During this period, data on air pollutant levels of five cities investigated in the original study, including 6090 pregnant women, were available. Concentrations of ozone (O3), nitric oxide (NO), nitrogen dioxide (NO2), nitrogen oxides (NOx), sulphur dioxide (SO2), carbon monoxide (CO), particulate matter < 2.5 (PM2.5) or <10 μm (PM10) were obtained from air pollution monitoring stations. Exposure to air pollutants during the three months preceding pregnancy and the first, second and third trimesters of pregnancy for each participant was estimated. The odds ratio was calculated based on logistic regression in three adjusted models considering different confounders. Only results that had a p < .05 were considered statistically significant.

RESULTS

None of the logistic regression models showed any statistically significant relationship between the exposure to any of the pollutants and GDM at different time points (before pregnancy, in the first, second and third trimesters of pregnancy and 12 months in total) (p > .05). Also, none of the adjusted logistic regression models showed any significant association between PM10 exposure and GDM risk at all different time points after adjusting for various confounders (p > .05).

CONCLUSIONS

This study found no association between GDM risk and exposure to various air pollutants before and during the different trimesters of pregnancy. This result should be interpreted cautiously due to the lack of considering all of the potential confounders.

Weekly-specific ambient PM1 before and during pregnancy and the risk of gestational diabetes mellitus

BACKGROUND

Exposure to fine or respirable particulate matter has been linked to an elevated risk of gestational diabetes mellitus (GDM). However, the association between exposure to particulate matter with an aerodynamic diameter ≤ 1 μm (PM1) and GDM has not been explored.

METHODS

We conducted a cohort study involving 60,173 pregnant women from nine hospitals in Beijing, China, from February 2015 to April 2021. Daily concentrations of PM1 and ozone were obtained from a validated spatiotemporal artificial intelligence model. We used a modified Poisson regression combined with distributed lag models to estimate the association between weekly-specific PM1 exposure and the risk of GDM after adjusting for individual-level covariates.

RESULTS

Among the 51,299 pregnant women included in the final analysis, 4008 were diagnosed with GDM. Maternal exposure to PM1 during preconception and gestational periods was generally associated with an increased risk of GDM. The most pronounced associations were identified during the 12th week before pregnancy, the 5th-8th weeks of the first trimester, and the 23rd-24th weeks of the second trimester. Each 10 μg/m3 increase in PM1 was associated with a relative risk of GDM of 1.65 (95 % CI: 1.59, 1.72) during the preconception period, 1.67 (95 % CI: 1.61, 1.73) in the first trimester, 1.52 (95 % CI: 1.47, 1.58) in the second trimester, and 2.54 (95 % CI: 2.45, 2.63) when considering the first and second trimester combined.

CONCLUSIONS

Exposure to PM1 before and during pregnancy was associated with an increased risk of GDM, particularly during the 12 weeks before pregnancy and gestational weeks 5-8 and 23-24.

Variations in the LINGO2 and GLIS3 Genes and Gene-Environment Interactions Increase Gestational Diabetes Mellitus Risk in Chinese Women

Gestational diabetes mellitus (GDM) has been found to be a common complication in pregnant women, known to escalate the risk of negative obstetric outcomes. In our study, we genotyped 1,566 Chinese pregnant women for two single nucleotide polymorphisms (SNPs) in the LINGO2 gene and one SNP in the GLIS3 gene, utilizing targeted next-generation sequencing. The impact of two interacting genes, and the interaction of genes with the environment─including exposure to particulate matter (PM2.5), ozone (O3), and variations in prepregnancy body mass index (BMI)─on the incidence of GDM were analyzed using logistic regression. Our findings identify the variants LINGO2 rs10968576 (P = 0.022, OR = 1.224) and rs1412239 (P = 0.018, OR = 1.231), as well as GLIS3 rs10814916 (P = 0.028, OR = 1.172), as risk mutations significantly linked to increased susceptibility to GDM. Further analysis underscores the crucial role of gene-gene and gene-environment interactions in the development of GDM among Chinese women (P < 0.05). Particularly, the individuals carrying the rs10968576 G-rs1412239 G-rs10814916 C haplotype exhibit increased susceptibility to GDM during the prepregnancy period when interacting with PM2.5, O3, and BMI (P = 8.004 × 10-7, OR = 1.206; P = 6.3264 × 10-11, OR = 1.280; P = 9.928 × 10-7, OR = 1.334, respectively). In conclusion, our research emphasizes the importance of the interaction between specific gene variations─LINGO2 and GLIS3─and environmental factors in influencing GDM risk. Notably, we found significant associations between these gene variations and GDM risk across various environmental exposure periods.

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.

Prenatal exposure to fine particulate matter chemical constituents and the risk of stillbirth and the mediating role of pregnancy complications: A cohort study

Evidence on the association of fine particulate matter (PM2.5) exposure with stillbirth is limited and inconsistent, which is largely attributed to differences in PM2.5 constituents. Studies have found that the hazards of certain PM2.5 constituents to the fetus are comparable to or even higher than total PM2.5 mass. However, few studies have linked PM2.5 constituents to stillbirth. Moreover, the mediating role of pregnancy complications in PM2.5-related stillbirth remains unclear. To our knowledge, this study was the first to explore the individual and mixed associations of PM2.5 and its constituents with stillbirth in China. After matching the concentrations of PM2.5 and its constituents (sulfate [SO42-], nitrate [NO3-], ammonium [NH4+], organic matter [OM], and black carbon [BC]) for participants according to their geographical location, there were 170,507 participants included in this study. We found that stillbirth was associated with exposure to PM2.5 and its constituents in the year before pregnancy and during the entire pregnancy, and the associations in trimester 1 were strongest. The risk of stillbirth increased sharply when PM2.5 and its constituents during pregnancy exceeded the median concentrations. Moreover, stillbirth was associated with exposure to the mixtures of SO42-, NO3-, NH4+, OM, and BC before and during pregnancy (trimesters 1 and 2). Meanwhile, two-pollutant models also suggested stillbirth was associated with PM2.5 and its constituents in the year before and during pregnancy. The associations of PM2.5 and its constituents with stillbirth were stronger in mothers with advanced age and without cesarean delivery history. Additionally, hypertensive disorders in pregnancy, gestational diabetes, and placental abruption mediated the association of PM2.5 with stillbirth. Therefore, enhanced protection against PM2.5 for pregnant women before and during pregnancy and targeted interventions for pregnancy complications and anthropogenic sources of PM2.5 constituents are important to reduce stillbirth risk.

The Influence of Airborne Particulate Matter on the Risk of Gestational Diabetes Mellitus: A Large Retrospective Study in Chongqing, China

Emerging research findings suggest that airborne particulate matter might be a risk factor for gestational diabetes mellitus (GDM). However, the concentration-response relationships and the susceptible time windows for different types of particulate matter may vary. In this retrospective analysis, we employ a novel robust approach to assess the crucial time windows regarding the prevalence of GDM and to distinguish the susceptibility of three GDM subtypes to air pollution exposure. This study included 16,303 pregnant women who received routine antenatal care in 2018-2021 at the Maternal and Child Health Hospital in Chongqing, China. In total, 2482 women (15.2%) were diagnosed with GDM. We assessed the individual daily average exposure to air pollution, including PM2.5, PM10, O3, NO2, SO2, and CO based on the volunteers' addresses. We used high-accuracy gridded air pollution data generated by machine learning models to assess particulate matter per maternal exposure levels. We further analyzed the association of pre-pregnancy, early, and mid-pregnancy exposure to environmental pollutants using a generalized additive model (GAM) and distributed lag nonlinear models (DLNMs) to analyze the association between exposure at specific gestational weeks and the risk of GDM. We observed that, during the first trimester, per IQR increases for PM10 and PM2.5 exposure were associated with increased GDM risk (PM10: OR = 1.19, 95%CI: 1.07~1.33; PM2.5: OR = 1.32, 95%CI: 1.15~1.50) and isolated post-load hyperglycemia (GDM-IPH) risk (PM10: OR = 1.23, 95%CI: 1.09~1.39; PM2.5: OR = 1.38, 95%CI: 1.18~1.61). Second-trimester O3 exposure was positively correlated with the associated risk of GDM, while pre-pregnancy and first-trimester exposure was negatively associated with the risk of GDM-IPH. Exposure to SO2 in the second trimester was negatively associated with the risk of GDM-IPH. However, there were no observed associations between NO2 and CO exposure and the risk of GDM and its subgroups. Our results suggest that maternal exposure to particulate matter during early pregnancy and exposure to O3 in the second trimester might increase the risk of GDM, and GDM-IPH is the susceptible GDM subtype to airborne particulate matter exposure.

Seasonal variation and its interaction with pre-pregnancy BMI for GDM: a large population-based study in Tianjin, China

To evaluate the independent association of seasonal variation with GDM incidence in Tianjin, China, and to test whether there is an additive interaction between seasonal variation and pre-pregnancy body mass index (BMI) on GDM incidence. A population-based observational cohort study was conducted using the healthcare records data from Tianjin, China. Logistic regression was used to obtain odds ratios (ORs) and 95% confidence intervals (CIs). Additive interaction between pre-pregnancy BMI groups and seasons was estimated by using relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and synergy index (S). Among the 112,639 pregnant women, 20.8% developed GDM at 24-28 weeks of gestation. The multivariable adjusted ORs and 95% CIs were 1.00, 1.00 (0.96-1.05), 1.15 (1.09-1.20) and 1.22 (1.16-1.29) respectively based on seasons (spring, summer, autumn and winter). Compared with the spring/summer and pre-pregnant BMI < 24 kg/m2 group, co-presence of autumn/winter and pre-pregnancy BMI ≥ 24 kg/m2 increased the OR from 1.00 to 2.70 (95% CI 2.28-3.20), with a significant additive interaction: RERI (0.32, 95% CI 0.19-0.45), S (1.21, 95% CI 1.12-1.31) and AP (0.11, 95% CI 0.07-0.16). Autumn/winter is an independent risk factor for GDM incidence, and can significantly amplify the obesity-associated risk for GDM incidence. The underlying mechanism warrants further investigations. We suggest that seasonality is an additional factor when interpreting OGTT results for the diagnosis of GDM.

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.

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.

Environmental Pollution and the Risk of Developing Metabolic Disorders: Obesity and Diabetes

To meet the increased need for food and energy because of the economic shift brought about by the Industrial Revolution in the 19th century, there has been an increase in persistent organic pollutants (POPs), atmospheric emissions and metals in the environment. Several studies have reported a relationship between these pollutants and obesity, and diabetes (type 1, type 2 and gestational). All of the major pollutants are considered to be endocrine disruptors because of their interactions with various transcription factors, receptors and tissues that result in alterations of metabolic function. POPs impact adipogenesis, thereby increasing the prevalence of obesity in exposed individuals. Metals impact glucose regulation by disrupting pancreatic β-cells, causing hyperglycemia and impaired insulin signaling. Additionally, a positive association has been observed between the concentration of endocrine disrupting chemicals (EDCs) in the 12 weeks prior to conception and fasting glucose levels. Here, we evaluate what is currently known regarding the link between environmental pollutants and metabolic disorders. In addition, we indicate where further research is required to improve our understanding of the specific effects of pollutants on these metabolic disorders which would enable implementation of changes to enable their prevention.

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.

Critical windows of exposure to air pollution and gestational diabetes: assessing effect modification by maternal pre-existing conditions and environmental factors

BACKGROUND

Ambient air pollution has been associated with gestational diabetes (GD), but critical windows of exposure and whether maternal pre-existing conditions and other environmental factors modify the associations remains inconclusive.

METHODS

We conducted a retrospective cohort study of all singleton live birth that occurred between April 1^st 2006 and March 31^st 2018 in Ontario, Canada. Ambient air pollution data (i.e., fine particulate matter with a diameter ≤ 2.5 μm (PM_2.5), nitrogen dioxide (NO₂) and ozone (O₃)) were assigned to the study population in spatial resolution of approximately 1 km × 1 km. The Normalized Difference Vegetation Index (NDVI) and the Green View Index (GVI) were also used to characterize residential exposure to green space as well as the Active Living Environments (ALE) index to represent the active living friendliness. Multivariable Cox proportional hazards regression models were used to evaluate the associations.

RESULTS

Among 1,310,807 pregnant individuals, 68,860 incident cases of GD were identified. We found the strongest associations between PM_2.5 and GD in gestational weeks 7 to 18 (HR = 1.07 per IQR (2.7 µg/m³); 95% CI: 1.02 - 1.11)). For O₃, we found two sensitive windows of exposure, with increased risk in the preconception period (HR = 1.03 per IQR increase (7.0 ppb) (95% CI: 1.01 - 1.06)) as well as gestational weeks 9 to 28 (HR 1.08 per IQR (95% CI: 1.04 -1.12)). We found that women with asthma were more at risk of GD when exposed to increasing levels of O₃ (p- value for effect modification = 0.04). Exposure to air pollutants explained 20.1%, 1.4% and 4.6% of the associations between GVI, NDVI and ALE, respectively.

CONCLUSION

An increase of PM_2.5 exposure in early pregnancy and of O₃ exposure during late first trimester and over the second trimester of pregnancy were associated with gestational diabetes whereas exposure to green space may confer a protective effect.

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.

Risk of De Novo Hypertensive Disorders of Pregnancy After Exposure to PM1 and PM2.5 During the Period From Preconception to Delivery: Birth Cohort Study

BACKGROUND

Particulate matter (PM) is detrimental to the respiratory and circulatory systems. However, no study has evaluated the lag effects of weekly exposure to fine PM during the period from preconception to delivery on the risk of hypertensive disorders of pregnancy (HDPs).

OBJECTIVE

We set out to investigate the lag effect windows of PM on the risk of HDPs on a weekly scale.

METHODS

Data from women with de novo HDPs and normotensive pregnant women who were part of the Peking University Retrospective Birth Cohort, based on the hospital information system of Tongzhou district, were obtained for this study. Meteorological data and data on exposure to fine PM were predicted by satellite remote sensing data based on maternal residential address. The de novo HDP group consisted of pregnant women who were diagnosed with gestational hypertension or preeclampsia. Fine PM was defined as PM2.5 and PM1. The gestational stage of participants was from preconception (starting 12 weeks before gestation) to delivery (before the 42nd gestational week). A distributed-lag nonlinear model (DLNM) was nested in a Cox regression model to evaluate the lag effects of weekly PM exposure on de novo HDP hazard by controlling the nonlinear relationship of exposure-reaction. Stratified analyses by employment status (employed or unemployed), education level (higher or lower), and parity (primiparity or multiparity) were performed.

RESULTS

A total of 22,570 pregnant women (mean age 29.1 years) for whom data were available between 2013 and 2017 were included in this study. The prevalence of de novo HDPs was 6.7% (1520/22,570). Our findings showed that PM1 and PM2.5 were significantly associated with an elevated hazard of HDPs. Exposure to PM1 during the 5th week before gestation to the 6th gestational week increased the hazard of HDPs. A significant lag effect of PM2.5 was observed from the 1st week before gestation to the 6th gestational week. The strongest lag effects of PM1 and PM2.5 on de novo HDPs were observed at week 2 and week 6 (hazard ratio [HR] 1.024, 95% CI 1.007-1.042; HR 1.007, 95% CI 1.000-1.015, respectively, per 10 μg/m3 increase). The stratified analyses indicated that pregnant women who were employed, had low education, and were primiparous were more vulnerable to PM exposure for de novo HDPs.

CONCLUSIONS

Exposure to PM1 and PM2.5 was associated with the risk of de novo HDPs. There were significant lag windows between the preconception period and the first trimester. Women who were employed, had low education, and were primiparous were more vulnerable to the effects of PM exposure; more attention should be paid to these groups for early prevention of de novo HDPs.

PM2.5 Constituents and Onset of Gestational Diabetes Mellitus: Identifying Susceptible Exposure Windows

Fine particulate matter (PM_2.5) has been linked to gestational diabetes mellitus (GDM). However, PM_2.5 is a complex mixture with large spatiotemporal heterogeneities, and women with early-onset GDM (i.e., diagnosed before 24^th gestation week) have distinct maternal characteristics and a higher risk of worse health outcomes compared with those with late-onset GDM (i.e., diagnosed in or after 24^th gestation week). We aimed to examine differential impacts of PM_2.5 and its constituents on early- vs. late-onset GDM, and to identify corresponding susceptible exposure windows. We leveraged statewide linked electronic health records and birth records data in Florida in 2012-2017. Exposures to PM_2.5 and its constituents (i.e., sulfate [SO₄ ^2-], ammonium [NH₄ ⁺], nitrate [NO₃ ^-], organic matter [OM], black carbon [BC], mineral dust [DUST], and sea-salt [SS]) were spatiotemporally linked to pregnant women based on their residential histories. Cox proportional hazards models and multinomial logistic regression were used to examine the associations of PM_2.5 and its constituents with GDM and its onsets. Distributed non-linear lag models were implemented to identify susceptible exposure windows. Exposures to PM_2.5, SO₄ ^2-, NH₄ ⁺, and BC were statistically significantly associated with higher hazards of GDM. Exposures to PM_2.5 during weeks 1-12 of gestation were positively associated with GDM. Associations of early-onset GDM with PM_2.5 in the 1^st and 2^nd trimesters, SO₄ ^2- in the 1^st and 2^nd trimesters, and NO₃ ^- in the preconception and 1^st trimester were considerably stronger than observations for late-onset GDM. Our findings suggest there are differential associations of PM_2.5 and its constituents with early- vs. late-onset GDM, with different susceptible exposure windows. This study helps better understand the impacts of air pollution on GDM accounting for its physiological heterogeneity.

Ozone exposure induced risk of gestational diabetes mellitus

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

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.

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

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

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

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

Maternal exposure to ambient PM2.5 and term birth weight: A systematic review and meta-analysis of effect estimates

Effect estimates of prenatal exposure to ambient PM_2.5 on change in grams (β) of birth weight among term births (≥37 weeks of gestation; term birth weight, TBW) vary widely across studies. We present the first systematic review and meta-analysis of evidence regarding these associations. Sixty-two studies met the eligibility criteria for this review, and 31 studies were included in the meta-analysis. Random-effects meta-analysis was used to assess the quantitative relationships. Subgroup analyses were performed to gain insight into heterogeneity derived from exposure assessment methods (grouped by land use regression [LUR]-models, aerosol optical depth [AOD]-based models, interpolation/dispersion/Bayesian models, and data from monitoring stations), study regions, and concentrations of PM_2.5 exposure. The overall pooled estimate involving 23,925,941 newborns showed that TBW was negatively associated with PM_2.5 exposure (per 10 μg/m³ increment) during the entire pregnancy (β = -16.54 g), but with high heterogeneity (I² = 95.6%). The effect estimate in the LUR-models subgroup (β = -16.77 g) was the closest to the overall estimate and with less heterogeneity (I² = 18.3%) than in the other subgroups of AOD-based models (β = -41.58 g; I² = 95.6%), interpolation/dispersion models (β = -10.78 g; I² = 86.6%), and data from monitoring stations (β = -11.53 g; I² = 97.3%). Even PM_2.5 exposure levels of lower than 10 μg/m³ (the WHO air quality guideline value) had adverse effects on TBW. The LUR-models subgroup was the only subgroup that obtained similar significant of negative associations during the three trimesters as the overall trimester-specific analyses. In conclusion, TBW was negatively associated with maternal PM_2.5 exposures during the entire pregnancy and each trimester. More studies based on relatively standardized exposure assessment methods need to be conducted to further understand the precise susceptible exposure time windows and potential mechanisms.

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.

Systematic review and meta-analysis on the association between seasonal variation and gestational diabetes mellitus

Recently, there is growing evidence that ambient temperature and seasonal changes are related to the incidence of gestational diabetes mellitus (GDM). Thereby, this study was conducted to evaluate the association between seasonal changes and ambient temperature and GDM. We conducted a systematic search in PubMed, ISI Web of Science, Scopus, Google Scholar, and Cochrane Collaboration for human studies available until the end of 2020. We used the following keywords to identify relevant articles: "Diabetes, Gestational" (MeSH), "Glucose Tolerance Test" (MeSH), "Glucose intolerance" (MeSH), "Pregnancy outcome" (MeSH), "Birth outcome", "Seasons" (MeSH), "Weather" (MeSH), "Ambient Temperature," "Climate Change" (MeSH). Meta-analyses by using STATA software were conducted for analyzing data. Due to the high heterogeneity between included studies, a random-effects model was used. Subgroup analysis, meta-regression, and sensitivity analysis were used to define a source of heterogeneity. We found 13 studies related to the association between ambient temperature and season changes and GDM, which 11 of them were included in meta-analyses. Despite inconsistencies in outcome assessment across studies, we found a significant positive association between seasons of GDM screening and risk of GDM (pooled OR=1.12; 95% CI (1.03, 1.21)). The funnel plot and Egger's test showed that there was no significant publication bias among these studies (p=0.51). In general, season changes showed a significant positive relationship with prevalence of GDM. However, due to the unknown exact mechanism on this association, further studies should be conducted.

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.

Parental Preconception Exposures to Outdoor Neighbourhood Environments and Adverse Birth Outcomes: A Protocol for a Scoping Review and Evidence Map

Parental preconception exposures to built and natural outdoor environments could influence pregnancy and birth outcomes either directly, or via a range of health-related behaviours and conditions. However, there is no existing review summarising the evidence linking natural and built characteristics, such as air and noise pollution, walkability, greenness with pregnancy and birth outcomes. Therefore, the planned scoping review aims to collate and map the published literature on parental preconception exposures to built and natural outdoor environments and adverse pregnancy and birth outcomes. We will search electronic databases (MEDLINE, EMBASE, Scopus) to identify studies for inclusion. Studies will be included if they empirically assess the relationship between maternal and paternal preconception exposures to physical natural and built environment features that occur outdoors in the residential neighbourhood and adverse pregnancy and birth outcomes. Two reviewers will independently screen titles and abstracts, and then the full text. Data extraction and assessment of study quality will be performed by one researcher and checked by a second researcher. Results will be summarised in a narrative synthesis, with additional summaries presented as tables and figures. The scoping review will be disseminated via a peer-reviewed publication, at academic conferences, and published on a website.

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.

Fine particular matter and its constituents in air pollution and gestational diabetes mellitus

BACKGROUND

Ambient air pollution has been linked to the development of gestational diabetes mellitus (GDM). However, previous studies provided inconsistent findings and no study has examined the effects of complex chemical constituents of the particular matter on GDM, especially in developing countries. Therefore, we aim to investigate the associations of exposure to PM_2.5 (particular matter ≤ 2.5 μm) and its constituents with GDM, and to identify susceptible exposure window in a large survey in China.

METHODS

The China Labor and Delivery Survey was a cross-sectional investigation conducted in 24 provinces in China between 2015 and 2016. A random sample of all deliveries in each participating hospital was selected and detailed obstetric and newborn information was extracted from medical records. Average concentrations of PM_2.5 and six constituents (organic matter, black carbon, sulfate, nitrate, ammonium and soil dust) were estimated (1 km × 1 km) using a combined geoscience-statistical model. GDM was diagnosed based on an oral glucose tolerance test (OGTT) between 24 to 28 weeks of gestation and according to IADPSG criteria. Generalized linear mixed models were used to adjust for potential confounders.

RESULTS

A total of 54,517 subjects from 55 hospitals were included. The incidence of GDM was 10.8%. An interquartile range (IQR) increase in PM_2.5 exposure in the 2nd trimester of pregnancy was associated with an increased GDM risk in the single pollutant model, [adjusted odds ratio (aOR) = 1.11 and 95% confidence interval (CI): 1.01-1.22]. Exposure to organic matter (aOR = 1.14; 95%CI: 1.05-1.23), black carbon (aOR = 1.15; 95%CI: 1.07-1.25) and nitrate (aOR = 1.13; 95%CI: 1.02-1.24) during 2nd trimester were associated with increased risks of GDM. Associations between constituents and GDM were robust after controlling for total PM_2.5 mass and accounting for multi-collinearity.

CONCLUSIONS

Exposure to PM_2.5 in 2^nd trimester of pregnancy was associated with an increased risk of GDM. Organic matter, black carbon and nitrate may be the main culprits for the association.