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

The causal effect of exposure to air pollution on risk of adverse pregnancy outcomes: A two-sample Mendelian randomisation study

BACKGROUND

Epidemiological studies have examined the relation between air pollution (NOx, NO2, PM2.5, PM2.5-10, and PM10) and adverse pregnancy outcomes (APOs). There's increasing evidence that air pollution increases the risk of APOs. However, the results of these studies are controversial, and the causal relation remains uncertain. We aimed to assess whether a genetic causal link exists between air pollution and APOs and the potential effects of this relation.

METHODS

A novel two-sample Mendelian randomisation (MR) study used pooled data from a large-scale complete genome correlation study. The primary analysis method was inverse variance weighting (IVW), which explored the expose-outcome relationship for assessing single nucleotide polymorphisms (SNPs) associated with air pollution. Further sensitivity analysis, including MR-PRESSO, MR-Egger regression, and leave-one analysis, was used to test the consistency of the results.

RESULTS

There was a significant correlation between air pollution-related SNPs and APOs. A robust causal link was found between genetic susceptibility to air pollution and APOs.

CONCLUSIONS

Our MR analysis reveals a genetic causal relation between air pollution and APOs, which may help provide new insights into further mechanisms and clinical studies in air pollution-mediated APOs.

Long-term exposure to air pollution on cardio-respiratory, and lung cancer mortality: a systematic review and meta-analysis

Air pollution is a major cause of specific deaths worldwide. This review article aimed to investigate the results of cohort studies for air pollution connected with the all-cause, cardio-respiratory, and lung cancer mortality risk by performing a meta-analysis. Relevant cohort studies were searched in electronic databases (PubMed/Medline, Web of Science, and Scopus). We used a random effect model to estimate the pooled relative risks (RRs) and their 95% CIs (confidence intervals) of mortality. The risk of bias for each included study was also assessed by Office of Health Assessment and Translation (OHAT) checklists. We applied statistical tests for heterogeneity and sensitivity analyses. The registration code of this study in PROSPERO was CRD42023422945. A total of 88 cohort studies were eligible and included in the final analysis. The pooled relative risk (RR) per 10 μg/m3 increase of fine particulate matter (PM2.5) was 1.080 (95% CI 1.068-1.092) for all-cause mortality, 1.058 (95% CI 1.055-1.062) for cardiovascular mortality, 1.066 (95%CI 1.034-1.097) for respiratory mortality and 1.118 (95% CI 1.076-1.159) for lung cancer mortality. We observed positive increased associations between exposure to PM2.5, PM10, black carbon (BC), and nitrogen dioxide (NO2) with all-cause, cardiovascular and respiratory diseases, and lung cancer mortality, but the associations were not significant for nitrogen oxides (NOx), sulfur dioxide (SO2) and ozone (O3). The risk of mortality for males and the elderly was higher compared to females and younger age. The pooled effect estimates derived from cohort studies provide substantial evidence of adverse air pollution associations with all-cause, cardiovascular, respiratory, and lung cancer mortality.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40201-024-00900-6.

Maternal health outcomes associated with ambient air pollution: An umbrella review of systematic reviews and meta-analyses

A growing body of literature demonstrated an association between exposure to ambient air pollution and maternal health outcomes with mixed findings. The objective of this umbrella review was to systematically summarize the global evidence on the effects of air pollutants on maternal health outcomes. We adopted the Joanna Briggs Institute (JBI) methodology and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting standards for this umbrella review. We conducted a comprehensive search across six major electronic databases and other sources to identify relevant systematic reviews and meta-analyses (SRMAs) published from the inception of these databases up to June 30, 2023. Out of 2399 records, 20 citations matched all pre-determined eligibility criteria that include SRMAs focusing on exposure to air pollution and its impact on maternal health, reported quantitative measures or summary effects, and published in peer-reviewed journals in the English language. The risk of bias of included SRMAs was evaluated based on the JBI critical appraisal checklist. All SRMAs reported significant positive associations between ambient air pollution and several maternal health outcomes. Specifically, particulate matter (PM), SO2, and NO demonstrated positive associations with gestational diabetes mellitus (GDM). Moreover, PM and NO2 showed a consistent positive relationship with hypertensive disorder of pregnancy (HDP) and preeclampsia (PE). Although limited, available evidence highlighted a positive correlation between PM and gestational hypertension (GH) and spontaneous abortion (SAB). Only one meta-analysis reported the effects of air pollution on maternal postpartum depression (PPD) where only PM10 showed a significant positive relationship. Limited studies were identified from low- and middle-income countries (LMICs), suggesting evidence gap from the global south. This review necessitates further research on underrepresented regions and communities to strengthen evidence on this critical issue. Lastly, interdisciplinary policymaking and multilevel interventions are needed to alleviate ambient air pollution and associated maternal health disparities.

Association of prenatal exposure to PM2.5 and NO2 with gestational diabetes in Western New York

BACKGROUND

Although many studies have examined the association between prenatal air pollution exposure and gestational diabetes (GDM), the relevant exposure windows remain inconclusive. We aim to examine the association between preconception and trimester-specific exposure to PM2.5 and NO2 and GDM risk and explore modifying effects of maternal age, pre-pregnancy body mass index (BMI), smoking, exercise during pregnancy, race and ethnicity, and neighborhood disadvantage.

METHODS

Analyses included 192,508 birth records of singletons born to women without pre-existing diabetes in Western New York, 2004-2016. Daily PM2.5 and NO2 at 1-km2 grids were estimated from ensemble-based models. We assigned each birth with exposures averaged in preconception and each trimester based on residential zip-codes. We used logistic regression to examine the associations and distributed lag models (DLMs) to explore the sensitive windows by month. Relative excess risk due to interaction (RERI) and multiplicative interaction terms were calculated.

RESULTS

GDM was associated with PM2.5 averaged in the first two trimesters (per 2.5 μg/m3: OR = 1.08, 95% CI: 1.01, 1.14) or from preconception to the second trimester (per 2.5 μg/m3: OR = 1.10, 95% CI: 1.03, 1.18). NO2 exposure during each averaging period was associated with GDM risk (per 10 ppb, preconception: OR = 1.10, 95% CI: 1.06, 1.14; first trimester: OR = 1.12, 95% CI: 1.08, 1.16; second trimester: OR = 1.10, 95% CI: 1.06, 1.14). In DLMs, sensitive windows were identified in the 5th and 6th gestational months for PM2.5 and one month before and three months after conception for NO2. Evidence of interaction was identified for pre-pregnancy BMI with PM2.5 (P-for-interaction = 0.023; RERI = 0.21, 95% CI: 0.10, 0.33) and with NO2 (P-for-interaction = 0.164; RERI = 0.16, 95% CI: 0.04, 0.27).

CONCLUSION

PM2.5 and NO2 exposure may increase GDM risk, and sensitive windows may be the late second trimester for PM2.5 and periconception for NO2. Women with higher pre-pregnancy BMI may be more susceptible to exposure effects.

Ambient 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.

The connection between six common air pollution particles and adult brain tumors: a meta-analysis of 26,217,930 individuals

Environmental air pollutants (black carbon (BC), nitrogen oxides (NOx), particulate matter with diameter < 2.5 μm (PM2.5), nitrogen dioxide (NO2), particulate matter with diameter <10 μm (PM10), and ozone (O3)) are one of the major menaces to mankind's health globally. This analysis reviews the association between exposure to these air pollutants and the chance of developing brain tumors in adults (total brain tumors, malignant brain tumors, and benign brain tumors). Studies published by April 2022 were searched. Raw effect sizes were converted to standardized effect sizes per 10 μg/m3 increase. Random effect models were applied to calculate combined effect size and 95% confidence intervals (CIs) were computed. A total of 8 articles were included for meta-analysis. The pooled effect size (ES) for per 10 μg/m3 BC intake was 1.67 (95% CI: 1.25, 2.22), P = 0.449. For every 10 μg/m3 rise in NO2 concentration, ES was 1.03 (95% CI: 1.01, 1.05), P = 0.319. Meanwhile, there was a boundary association between NOx and adult brain tumors (ES and 95% CI: 1.01; 1.00, 1.01/10 μg/m3; P = 0.716). While there was no conjunction between PM2.5, PM10, O3 (PM2.5: ES and 95% CI: 1.04; 0.99, 1.08/10 μg/m3; P = 0.834; PM10: ES and 95% CI: 1.01; 0.97, 1.04/10 μg/m3; P = 0.627; O3: ES and 95% CI: 0.97; 0.94, 1.00/10 μg/m3; P = 0.253). This research shows testimony of a significant link between air pollutants and brain tumors in adults, especially when exposed to BC, NO2, and NOx. This evidence emphasizes the importance of improving air quality as part of a comprehensive approach to prevent the occurrence and deterioration of brain tumors.

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.

Maternal particulate matter exposure and gestational diabetes mellitus: a population-based cohort study

BACKGROUND

Gestational diabetes mellitus prevalence is steadily increasing worldwide, posing a significant threat to the short-term and long-term health of both mother and offspring. Because particulate matter air pollution has been reported to affect glucose metabolism, it was suggested that maternal particulate matter exposure may be associated with the development of gestational diabetes mellitus; however, the evidence is limited and inconsistent.

OBJECTIVE

This study aimed to determine the association between maternal exposure to particulate matter of diameter ≤2.5 µm and of diameter of ≤10 µm and the risk of gestational diabetes mellitus, to identify critical windows of susceptibility and to evaluate effect modification by ethnicity.

STUDY DESIGN

A retrospective cohort study was conducted including pregnancies of women who delivered at a large tertiary medical center in Israel between 2003 and 2015. Residential particulate matter levels were estimated by a hybrid spatiotemporally resolved satellite-based model at 1 km spatial resolution. Multivariable logistic analyses were applied to study the association between maternal particulate matter exposure in different pregnancy periods and gestational diabetes mellitus risk, while adjusting for background, obstetrical, and pregnancy characteristics. Analyses were also stratified by ethnicity (Jewish and Bedouin).

RESULTS

The study included 89,150 pregnancies, of which 3245 (3.6%) were diagnosed with gestational diabetes mellitus. First trimester exposure to both particulate matter of diameter ≤2.5 µm (adjusted odds ratio per 5 μg/m3, 1.09; 95% confidence interval, 1.02-1.17) and particulate matter of diameter of ≤10 µm (adjusted odds ratio per 10 μg/m3, 1.11; 95% confidence interval, 1.06-1.17) was significantly associated with increased risk for gestational diabetes mellitus. In the stratified analyses, the association with first trimester particulate matter of diameter of ≤10 µm exposure was consistent among pregnancies of both Jewish and Bedouin women, whereas the association with first trimester particulate matter of diameter ≤2.5 µm exposure was significant among pregnancies of Jewish women only (adjusted odds ratio per 5 μg/m3, 1.09; 95% confidence interval, 1.00-1.19), as well as association with preconception particulate matter of diameter of ≤10 µm exposure (adjusted odds ratio per 10 μg/m3, 1.07; 95% confidence interval, 1.01-1.14). No association was found between second trimester particulate matter exposure and gestational diabetes mellitus risk.

CONCLUSION

Maternal exposure to both particulate matter of diameter ≤2.5 µm and diameter of 10 µm or less during the first trimester of pregnancy is associated with gestational diabetes mellitus, suggesting that the first trimester is a particular window of susceptibility to the effect of particulate matter exposure on gestational diabetes mellitus risk. The effects found in this study differed by ethnic group, emphasizing the importance of addressing ethnic disparities when assessing environmental impacts on health.

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.

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

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

Methods

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

Results

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

Discussion

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

Short-term exposure to air pollution and outpatient visits for conjunctivitis: a time-series analysis in Urumqi, China

Conjunctivitis is an inflammatory disease of the conjunctival tissue caused by a variety of causes; despite the conjunctiva being directly exposed to the external atmospheric environment, the important role of air pollution is not fully evaluated, especially in areas with poor air quality undergoing rapid economic and industrial development. Information on 59,731 outpatient conjunctivitis visits from 1 January 2013 to 31 December 2020 was obtained from the Ophthalmology Department of the First Affiliated Hospital of Xinjiang Medical University (Urumqi, Xinjiang, China), and data on six air pollutants including particulate matter with a median aerometric diameter of less than 10 and 2.5 mm (PM₁₀ and PM_2.5, respectively), carbon monoxide (CO), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and ozone (O₃) from eleven standard urban background fixed air quality monitors were also recorded. A time-series analysis design and a quasi-Poisson generalized linear regression model combined with a distributed lagged nonlinear model (DLNM) were used to fit the effect of exposure to air pollutants on the risk of conjunctivitis outpatient visits. Further subgroup analyses were conducted for gender, age, and season, as well as the type of conjunctivitis. Single and multi-pollutant models showed that exposure to PM_2.5, PM₁₀, NO₂, CO, and O₃ was associated with increased risk of outpatient conjunctivitis visits on the lag 0 day and various other lag days. Variations in the effect estimates on direction and magnitude were found in different subgroup analyses. We conducted the first time-series analysis with the longest duration as well as the largest sample size in Northwest China, which provides evidence that outpatient conjunctivitis visits is significantly associated with air pollution in Urumqi, China. Meanwhile, our results demonstrate the effectiveness of SO₂ reduction in reducing the risk of outpatient conjunctivitis visits in the Urumqi region and reaffirm the need to implement special air pollution control measures.

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.

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

Background

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

Methods

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

Results

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

Conclusion

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

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.

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.

A global view of hypertensive disorders and diabetes mellitus during pregnancy

Two important maternal cardiometabolic disorders (CMDs), hypertensive disorders in pregnancy (HDP) (including pre-eclampsia) and gestational diabetes mellitus (GDM), result in a large disease burden for pregnant individuals worldwide. A global consensus has not been reached about the diagnostic criteria for HDP and GDM, making it challenging to assess differences in their disease burden between countries and areas. However, both diseases show an unevenly distributed disease burden for regions with a low income or middle income, or low-income and middle-income countries (LMICs), or regions with lower sociodemographic and human development indexes. In addition to many common clinical, demographic and behavioural risk factors, the development and clinical consequences of maternal CMDs are substantially influenced by the social determinants of health, such as systemic marginalization. Although progress has been occurring in the early screening and management of HDP and GDM, the accuracy and long-term effects of such screening and management programmes are still under investigation. In addition to pharmacological therapies and lifestyle modifications at the individual level, a multilevel approach in conjunction with multisector partnership should be adopted to tackle the public health issues and health inequity resulting from maternal CMDs. The current COVID-19 pandemic has disrupted health service delivery, with women with maternal CMDs being particularly vulnerable to this public health crisis.

Association of ambient fine particulate matter exposure with gestational diabetes mellitus and blood glucose levels during pregnancy

BACKGROUND

Previous studies have examined the associations between ambient fine particulate matter (PM_2.5) exposure and gestational diabetes mellitus (GDM). However, limited studies explored the relationships between PM_2.5 exposure and blood glucose levels during pregnancy, especially in highly polluted areas.

OBJECTIVES

To examine the associations of prenatal ambient PM_2.5 exposure with GDM and blood glucose levels, and to identify the sensitive exposure windows in a highly air-polluted area.

METHODS

From July 2016 to October 2017, a birth cohort study was conducted in Beijing, China. Participants were interviewed in each trimester regarding demographics, lifestyle, living and working environment, and medical conditions. Participant's daily ambient PM_2.5 levels from 3 m before last menstrual period (LMP) to the third trimester was estimated by a hybrid spatiotemporal model. Indoor air quality index was calculated based on environmental tobacco smoke, ventilation, cooking, painting, pesticide, and herbicide use. Distributed lag non-linear model was applied to explore the sensitive weeks of PM_2.5 exposure.

RESULTS

Of 165 pregnant women, 23 (13.94%) developed GDM. After adjusting for potential confounders, PM_2.5 exposure during the 1^st trimester was associated with higher odds of GDM (10 μg/m³ increase: OR = 1.89, 95% CI: 1.04-3.49). Each 10 μg/m³ increase in PM_2.5 during the 2^nd trimester was associated with 17.70% (2.21-33.20), 15.99% (2.96-29.01), 18.82% (4.11-33.52), and 17.10% (3.28-30.92) increase in 1-h, 2-h, Δ1h-fasting (1-h minus fasting), and Δ2h-fasting (2-h minus fasting) blood glucose levels, respectively. PM_2.5 exposure at 24^th-27^th weeks after LMP was associated with increased GDM risk. We identified sensitive exposure windows of 21^st-24^th weeks for higher 1-h and 2-h blood glucose levels and of 20^th-22^nd weeks for increased Δ1h-fasting and Δ2h-fasting.

CONCLUSIONS

Ambient PM_2.5 exposure during the second trimester was associated with higher odds of GDM and higher blood glucose levels. Avoiding exposure to high air pollution levels during the sensitive windows might prevent women from developing GDM.

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

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

Gestational exposure to ambient particulate matter and preterm birth: An updated systematic review and meta-analysis

Previous studies on gestational particulate matter (PM) exposure and preterm birth (PTB) showed inconsistent results, and no study systematically examined the short-term effect of PM exposure on PTB subtypes. To investigate both long- and short-term effects of the evidence to date in general population, we searched for epidemiological studies on PM exposure and PTB that published in PubMed, Web of Science, Embase and Cochrane Library up to March 31, 2022. The protocol for this review was registered with PROSPERO (CRD42021265202). Heterogeneity was assessed by Cochran's Q test and I² statistic. Publication bias was evaluated using funnel plots and Egger's tests. Subgroup analysis, meta-regression and sensitivity analysis were performed. Of 16,801 records, 84 eligible studies were finally included. The meta-analysis of long-term effect showed that per 10 μg/m³ increase in PM_2.5 and PM₁₀ during entire pregnancy were associated with PTB, the pooled odds ratios (ORs) were 1.084 (95% CI: 1.055-1.113) and 1.034 (95% CI: 1.018-1.049). Positive associations were found between PM_2.5 in second trimester and PTB subtypes. For the short-term exposure, we observed that PTB was positively associated with a 10 μg/m³ increment in PM_2.5 on lag day 2 and 3, the pooled ORs and 95% CIs were 1.003 (1.001-1.004) and 1.003 (1.001-1.005), with I² of 65.30% and 76.60%. PM₁₀ exposure on ave day 1 increased the risk of PTB, the pooled OR was 1.001 (95% CI: 1.000, 1.001). We also found that PM₁₀ exposure in 2 weeks prior to birth increased PTB risk. Our results support the hypothesis of both long- and short-term PM_2.5 exposure increase the risk of PTB. Further well-designed longitudinal studies and investigations into potential biological mechanisms are warranted.

Spatiotemporal Distribution of Continuous Air Pollution and Its Relationship with Socioeconomic and Natural Factors in China

Continuous air pollution (CAP) incidents last even longer and generate greater health hazards relative to conventional air pollution episodes. However, few studies have focused on the spatiotemporal distribution characteristics and driving factors of CAP in China. Drawing on the daily reported ground monitoring data on the ambient air quality in 2019 in China, this paper identifies the spatiotemporal distribution characteristics of CAP across 337 Chinese cities above the prefecture level using descriptive statistics and spatial statistical analysis methods, and further examines the spatial heterogeneity effects of both socioeconomic factors and natural factors on CAP with a Multiscale Geographically Weighted Regression (MGWR) model. The results show that the average proportion of CAP days in 2019 reached 11.50% of the whole year across Chinese cities, a figure equaling to about 65 days, while the average frequency, the maximum amount of days and the average amount of days of CAP were 8.02 times, 7.85 days and 4.20 days, respectively. Furthermore, there was a distinct spatiotemporal distribution disparity in CAP in China. Spatially, the areas with high proportions of CAP days were concentrated in the North China Plain and the Southwestern Xinjiang Autonomous Region in terms of the spatial pattern, while the proportion of CAP days showed a monthly W-shaped change in terms of the temporal pattern. In addition, the types of regions containing major pollutants during the CAP period could be divided into four types, including “Composite pollution”, “O₃ + NO₂ pollution”, “PM₁₀ + PM_2.5 pollution” and “O₃ + PM_2.5 pollution”, while the region type “PM₁₀ + PM_2.5 pollution” covered the highest number of cities. The MGWR model, characterized by multiple spatial scale impacts among the driving factors, outperformed the traditional OLS and GWR model, and both socioeconomic factors and natural factors were found to have a spatial non-stationary relationship with CAP in China. Our findings provide new policy insights for understanding the spatiotemporal distribution characteristics of CAP in urban China and can help the Chinese government make prevention and control measures of CAP incidents.

New Insights for Tracking Global and Local Trends in Exposure to Air Pollutants

Over six million people die prematurely each year from exposure to air pollution. Current air quality metrics insufficiently monitor exposure to air pollutants. This gap hinders the ability of decisionmakers to address the public health impacts of air pollution. To spur new emissions control policies and ensure implemented solutions realize meaningful gains in environmental health, we develop a framework of public-health-focused air quality indicators that quantifies over 200 countries' trends in exposure to particulate matter, ozone, nitrogen oxides, sulfur dioxide, carbon monoxide, and volatile organic compounds. We couple population density to ground-level pollutant concentrations to derive population-weighted exposure metrics that quantify the pollutant levels experienced by the average resident in each country. Our analyses demonstrate that most residents in 171 countries experience pollutant levels exceeding international health guidelines. In addition, we find a negative correlation between temporal trends in ozone and nitrogen oxide concentrations, which─when qualitatively interpreted with a simple atmospheric chemistry box model─can help describe the apparent tradeoff between the mitigation of these two pollutants on local scales. These novel indicators and their applications enable regulators to identify their most critical pollutant exposure trends and allow countries to track the performance of their emission control policies over time.

A Critical Review on the Complex Interplay between Social Determinants of Health and Maternal and Infant Mortality

Background: U.S. maternal and infant mortality rates constitute an important public health problem, because these rates surpass those in developed countries and are characterized by stark disparities for racial/ethnic minorities, rural residents, and individuals with less privileged socioeconomic status due to social determinants of health (SDoH). Methods: A critical review of the maternal and infant mortality literature was performed to determine multilevel SDoH factors leading to mortality disparities with a life course lens. Results: Black mothers and infants fared the worst in terms of mortality rates, likely due to the accumulation of SDoH experienced as a result of structural racism across the life course. Upstream SDoH are important contributors to disparities in maternal and infant mortality. More research is needed on the effectiveness of continuous quality improvement initiatives for the maternal–infant dyad, and expanding programs such as paid maternity leave, quality, stable and affordable housing, and social safety-nets (Medicaid, CHIP, WIC), in reducing maternal and infant mortality. Finally, it is important to address research gaps in individual, interpersonal, community, and societal factors, because they affect maternal and infant mortality and related disparities. Conclusion: Key SDoH at multiple levels affect maternal and infant health. These SDoH shape and perpetuate disparities across the lifespan and are implicated in maternal and infant mortality disparities.

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.

Vitamin D intake modifies the association of household air pollution exposure with maternal disorders of pregnancy

To date, only three studies have investigated the association of household air pollution (HAP) exposure with pregnancy disorders. The ameliorating role of diet and nutrition in the association has never been explored. We conducted a cross-sectional study among 799 mothers who had recently given singleton birth in the Cape Coast Metropolis, Ghana. Structured questionnaire and semi-quantitative food frequency questionnaire were used to assess HAP exposure (from use of biomass fuels for cooking and garbage burning at home) and vitamin D (vitD) intake, respectively. Multivariable binary logistic regression was used to investigate the association between HAP exposure and pregnancy disorders. HAP exposure due to cooking with biomass fuels and garbage burning at home was associated with two fold (AOR = 2.15; 95% confidence interval [CI]: 1.05, 4.43) and six fold (AOR = 6.35; 95% CI: 2.43, 16.58) increased odds of hypertensive disorders of pregnancy (HDP). For gestational diabetes (GDM), the increased odds were two folds for both exposures but the 95% CI included the null value. Stove stacking was also associated with two folds increased odds of GDM (AOR = 1.83; 95% CI: 0.91, 3.68). In stratified analysis, the odds of HDP and GDM associated with biomass fuels use decreased with increasing vitD intake. All the interaction p values were, however, greater than 0.05. We provide the first evidence on the ameliorating role of vitD intake on the effect of HAP exposure on pregnancy disorders. In LMICs where solid fuel use and garbage burning at home is widespread, health workers should advise mothers during antenatal care visits to increase intake of vitamin D rich foods.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

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.

Silica nanoparticles inhibiting the differentiation of round spermatid and chromatin remodeling of haploid period via MIWI in mice

Researches have shown that silica nanoparticles (SiNPs) could reduce both the quantity and quality of sperm. However, the mechanism of toxicity induced by SiNPs in the male reproductive system is still unclear. In this study, male mice were randomly divided into a control group, and SiNPs treated group (20 mg/kg dose; n = 30 per group). Half of the mice per group were sacrificed on 35 days and the remaining on 50 days of the SiNPs exposure. SiNPs were found to decrease sperm count and mobility, increase the sperm abnormality rate, and damage the testes' structure. Furthermore, SiNPs decreased the protein levels of Protamine 1(PRM1) and elevated the histones' levels and suppressed the chromatin condensation of sperm. There was a significant reduction of the ubiquitinated H2A (ubH2A)/H2B (ubH2B) and RING finger protein 8 (RNF8) levels in the spermatid nucleus, while the RNF8 level in the spermatid cytoplasm increased evidently. The protein expression levels of PIWI-like protein 1(MIWI) in the late spermatids significantly increased on day 35 of SiNPs exposure. After 15 days of the withdrawal, the sperm parameters and protamine levels, and histones in the epididymal sperm were unrecovered; however, the changes in testis induced by SiNPs were recovered. Our results suggested that SiNPs could decrease the RNF8 level in the nucleus of spermatid either by upregulating of the expression of MIWI or by inhibiting its degradation. This resulted in the detention of RNF8 in the cytoplasm that maybe inhibited the RNF8-mediated ubiquitination of ubH2A and ubH2B. These events culminated in creating obstacles during the H2A and H2B removal and chromatin condensation, thereby suppressing the differentiation of round spermatids and chromatin remodeling, which compromised the sperm quality and quantity.

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.

The pregnancy-related anxiety characteristics in women with gestational diabetes mellitus: why should we care?

Background

Gestational diabetes mellitus (GDM) is very commonly-seen in clinical settings, and GDM patients may have higher levels of anxiety. It’s necessary to evaluate the anxiety level and potentially influencing factors in patients with GDM, to provide insights for the management of anxiety of GDM patients.

Methods

Patients with GDM treated in our hospital from May, 2018 to May, 2020 were included. We evaluated the characteristics of patients and the scores of pregnancy-related anxiety scale for anxiety level, vulnerable personality style questionnaire (VPSQ) for personality, general self-efficacy scale (GSES) for self-efficacy, social support rating scale (SSRS) for social support level. Logistic regression analyses were conducted to identify the potential influencing factors of anxiety in GDM patients.

Results

A total of 386 GDM patients were included, the incidence of anxiety in patients with GDM was 59.07%. Anxiety was positively correlated with the susceptible personality (r = 0.604, p = 0.023), and it was negatively correlated with self-efficacy and social support (r = -0.586 and -0.598 respectively, all p < 0.05). The education level, monthly income, abnormal pregnancy (miscarriage, premature rupture of membranes) and cesarean section history and first pregnancy were the independent influencing factors for the anxiety in the patients with GDM (all p < 0.05).

Conclusions

The anxiety of GDM patients is very common, early care and interventions are warranted for those patients with abnormal pregnancy and cesarean section history, first pregnancy, lower education level, and less monthly income.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

Ambient air pollution exposure and risk of chronic kidney disease: A systematic review of the literature and meta-analysis

Ambient air pollution has been identified as one of the leading causes of global burden of disease. The relationship between ambient air pollution exposure and risk of chronic kidney disease (CKD) has stimulated increasing scientific interest in the past few years. However, evidence from human epidemiological studies is still limited and inconsistent. We performed an updated systematic review and meta-analysis to clarify the potential association comprehensively. Selected electronic databases were searched for related English language studies until March 1, 2020 with a final follow-up in December 31, 2020. Risk of bias assessment for individual studies were assessed using the OHAT (Office of Health Assessment and Translation) risk-of-bias rating tool. Confidence rating and level-of-evidence conclusions were developed for bodies of evidence for a given ambient air pollutant. Summary effect estimates were calculated using random-effects meta-analyses when three or more studies are identified for the same air pollutant-CKD combination. A total of 13 studies were finally identified in our study. The meta-analytic estimates (ORs) for risk of CKD were 1.15 (95% CI: 1.07, 1.24) for each 10 μg/m³ increase in PM_2.5, 1.25 (95% CI: 1.11, 1.40) for each 10 μg/m³ increase in PM₁₀, 1.10 (95% CI: 1.03, 1.17) for each 10 ppb increase in NO₂, 1.06 (95% CI: 0.98, 1.15) for each 1 ppb increase in SO₂ and 1.04 (95% CI: 1.00, 1.08) for each 0.1 ppm increase in CO, respectively. The level of evidence was appraised as moderate for four of the five tested air pollutant-CKD combinations using an adaptation of the GRADE (Grading of Recommendations Assessment, Development and Evaluation) tool. In conclusion, this study suggests that certain ambient air pollutant exposure was significantly associated with an increased risk of CKD. Given the limitations, the results of this study should be interpreted with caution, and further well-designed epidemiological studies are needed to draw a definite evidence of a causal relationship.

Association between short-term exposure to ambient nitrogen dioxide and the risk of conjunctivitis in Hefei, China: A time-series analysis

BACKGROUND

Conjunctivitis, one of the most common ocular surface diseases, can be caused by many contributors. However, the important role of air pollution has been inadequately evaluated, particularly in countries with poor air quality. This study aims to explore the possible association of short-term ambient nitrogen dioxide (NO₂) exposure with the risk of outpatient visits for conjunctivitis.

METHODS

A total of 43,462 conjunctivitis patients from January 1, 2014 to December 31, 2018 were identified from the Department of Ophthalmology of The Second Affiliated Hospital of Anhui Medical University, Hefei, China. Such data were linked to the daily mean concentration of NO₂ at ten fixed air quality monitoring stations. A distributed lag nonlinear model (DLNM) combined with a quasi-Poisson generalized linear regression model was employed to assess the association between NO₂ exposure and the risk of outpatient visits for conjunctivitis. Stratified analyses were also performed on the basis of gender, age group and season.

RESULTS

The association of NO₂ exposure with the risk of outpatient visits for conjunctivitis was statistically significant. In the single-day lags (lag 0 to lag 11) analysis, the largest effect estimates were observed at lag 0. In the moving average exposure lags (lag 0-1 to lag 0-11) analysis, the cumulative effects were stronger than the single-day lag effects. The stratified analyses suggested that the effect of NO₂ exposure was more pronounced in females and patients aged 19-65 years and in the cold season.

CONCLUSIONS

This study confirms the evidence that short-term NO₂ exposure is associated with an increased risk of conjunctivitis outpatient visits. Our research encourages individuals to avoid outdoor activities on severe air pollution days and the government is obliged to adopt more stringent environmental policies to alleviate the effects of air pollution on human health, particularly for individuals at risk of developing conjunctivitis.

Social capital and sleep disorders in Tibet, China

Objective

Sleep plays an important role in the health and well-being of middle aged and elderly people, and social capital may be one of the important factors for sleep disorders. This study aimed to understand the relationship between social capital and sleep disorders in a unique region of China –Tibet that generally has the disadvantaged economic status compared to other parts of China.

Methods

The study was based on Tibetan data from The China Multi-Ethnic Cohort (CMEC) and was conducted from May 2018 to September 2019. A total of 3194 Tibetans aged > 50 were selected from the community population by multi-stage stratified cluster sampling. Social capital was measured using two validated health-related social capital scales, family/community and society.. Sleep disorders were measured as the presence of disorders of initiating and maintaining sleep, early morning awakening, or daytime dysfunction. Logistic regression models were applied to examine the association between social capital and sleep disorders.

Results

39.9% (1271/3194) of the participants had sleep disorders. In addition, after controlling for all potential variables, family social capital was significantly negatively associated with sleep disorders (OR = 0.95, P < 0.05), while community and society social capital was not associated with sleep disorders. Then, when we did all the sex-stratified analyses, the significant association between social capital and sleep disorders was found only in women (OR = 0.94, P < 0.05), while no association was found in males; neither males nor females showed any association with community and society social capital.

Conclusion

Our study would help to better understand the extent of health inequality in China, and guide future interventions, strategies and policies to promote sleep quality in low-income areas, taking into account both the role of Tibetan specific cultural traditions, lifestyles and religious beliefs in social capital and the gender differences in social capital.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-10626-x.

Ambient air pollution exposure during pregnancy and gestational diabetes mellitus in Shenyang, China: a prospective cohort study

The prevalence of gestational diabetes mellitus (GDM) is increasing worldwide. Reports of the association between air pollution exposure and GDM have been inconsistent in previous studies. We conducted a cohort study to investigate the associations between air pollution exposure and GDM in the city of Shenyang in Northeast China for the first time. We studied interactions with different air pollutant exposures and conducted a stratified analysis according to folic acid intake, age, body mass index (BMI), primiparity, and sleep quality. We found significant associations between prenatal exposure to NO_x and SO₂ and the development of GDM during the second trimester: the largest effect on GDM was exposure to SO₂ (odds ratio (OR): 1.77, 95% confidence interval (CI): 1.23-2.56) in the largest quartile compared with the lowest quartile. Significant interactions between age, BMI, parity, sleep quality, and air pollution exposures were observed; stratified analysis showed stronger associations between GDM and high air pollutant exposure in pregnant women with older age, larger BMI, poorer sleep quality, and more parity. We found that air pollution exposure during the second trimester was significantly associated with GDM in a prospective birth cohort study in Northeast China. SO₂, oxynitride (NOX, NO₂, NO), CO, and O₃ all showed a linear trend effect on GDM. Interactions between prenatal air pollution exposure and other factors, such as age at pregnancy, BMI before pregnancy, primiparity, folic acid intake, and sleep quality, during the second trimester might exist.

Dietary patterns and associations between air pollution and gestational diabetes mellitus

The prevalence of gestational diabetes mellitus (GDM) has been increasing worldwide. Dietary patterns and air pollution are closely related to the occurrence of GDM. No previous study has explored the interaction effect of air pollution exposure and dietary patterns on GDM. We explored the interaction effect between main dietary patterns and pre-pregnancy exposure to air pollution on the development of GDM based on a prospective birth cohort in Northeast China. A total of 2244 participants were included in this study. Factor analysis was used to identify dietary patterns. We found that long-term exposure to nitrogen dioxide (NO₂) and carbon monoxide (CO) before pregnancy was significantly associated with an increased risk of GDM; the animal foods pattern significantly modified these associations. The sub-group analysis showed that compared with a lower intake in the animal foods pattern (NO₂, odds ratio [OR] = 1.07, 95% confidence interval [CI]: 0.84, 1.35; CO, OR = 1.05, 95% CI: 0.81, 1.34), higher intake in the animal foods pattern (NO₂, OR = 1.41, 95% CI: 1.09, 1.83; CO, OR = 1.36, 95% CI: 1.05, 1.76) before pregnancy increased the hazardous effects of NO₂ and CO on GDM development. The intake of animal blood, animal organs, preserved eggs, and processed meat products in animal food pattern could all aggravate the effect of exposure to air pollution due to NO₂ and CO on GDM. Our study demonstrated that there was a significant interaction effect between animal foods pattern and exposure to air pollution on GDM. These results provide further scientific evidence of the associations among air pollution, dietary intake, and GDM, and may help as well as the prevention of GDM.

Ambient air pollution exposure associated with glucose homeostasis during pregnancy and gestational diabetes mellitus

BACKGROUND

To investigate the effects of air pollution exposure during pregnancy on the indicators of glucose homeostasis and gestational diabetes mellitus (GDM).

METHODS

We conducted a birth cohort study in Foshan, China during 2015-2019. Oral glucose tolerance test (OGTT) was administered to each participant during pregnancy. GDM was defined according to the International Association of Diabetes and Pregnancy Study Groups criteria (IADPSG). Air pollutant (fine particulate matter (PM_2.5), particulate matter with an aerodynamic diameter of 10 μm or less (PM₁₀), sulfate dioxide (SO₂), nitrogen dioxide (NO₂) and ozone (O₃)) concentrations from the air monitoring stations in Foshan were used to estimate individual air pollutant exposure during the first two trimesters. Linear and logistic regression models were employed to estimate the associations between air pollution exposure during the first two trimesters and OGTT glucose levels and GDM.

RESULTS

Of 12,842 pregnant women, 3055 (23.8%) had GDM. A 10 μg/m³ increase in PM_2.5, PM₁₀ and SO₂ during trimester 1, trimester 2 and two trimesters were associated with 0.07 mmol/L to 0.29 mmol/L increment in OGTT-fasting glucose levels in single-pollutant model. A 10 μg/m³ increase in NO₂ and O₃ during two trimesters were associated with 0.15 mmol/L and 0.12 mmol/L decrease in OGTT-fasting glucose in single-pollutant model. However, no significant or weaker effects of O₃ during two trimesters on OGTT-fasting glucose were observed in two-pollutant models. Moreover, exposure to PM_2.5, PM₁₀ and SO₂ were associated with increased risk of GDM in both single- and two-pollutant models.

CONCLUSIONS

Our study suggests PM_2.5, PM₁₀ and SO₂ exposure during the first two trimesters might increase the risk of GDM.

The mediation effect of maternal glucose on the association between ambient air pollution and birth weight in Foshan, China

Maternal blood glucose level is associated with fetal growth, therefore, its role in the associations between air pollution and birth weight deserves investigation. We examined the mediation effect of maternal blood glucose on the associations between maternal air pollution exposure and birth weight. A total of 10,904 pregnant women in Foshan, China during 2015-2019 were recruited. Oral glucose tolerance test (OGTT) was administered to each participant after late trimester 2. Air pollution data at the monitoring stations in residential districts was used to estimate exposures of each participant during trimester 1 and trimester 2. Mixed-effects linear models were used to estimate the associations between air pollution and birth weight. After controlling for ten covariates, the direct effect of PM_2.5 and SO₂ (each 10 μg/m³ increment) on birth weight was -15.7 g (95% CI: -29.4, -4.8 g) and -83.6 g (95% CI: -134.8, -33.0 g) during trimester 1. The indirect effect of PM_2.5 and SO₂ (each 10 μg/m³ increment) on birth weight by increasing maternal fasting glucose level was 6.6 g (95% CI: 4.6, 9.1 g) and 22.0 g (95% CI: 4.1, 44.0 g) during trimester 1. Our findings suggest that air pollution might affect the birth weight through direct and indirect pathway, and the indirect effect might be mediated by maternal blood glucose.

Particle air pollution and gestational diabetes mellitus in Houston, Texas

BACKGROUND

There is mixed evidence implicating prenatal exposure to particulate matter <2.5 μm in aerodynamic diameter (PM_2.5) in the risk of gestational diabetes mellitus (GDM) and only one study has examined exposure to PM_2.5 constituents, which vary with location because of different emission sources.

METHODS

We conducted a retrospective cohort study of singleton live births in Harris County, Texas from 2008 to 2013. With data from the Texas Commission on Environmental Quality (TCEQ), we spatially interpolated maternal exposures to total and speciated PM_2.5, nitrogen dioxide (NO₂) and ozone (O₃) over the 12-week preconception period and trimesters 1 and 2. We estimated odds ratios (OR) and 95% confidence intervals (CI) for the association between pre-conception and pregnancy exposures to total and speciated PM_2.5 and odds of GDM, adjusted for temperature and maternal covariates. We also evaluated confounding from NO₂ and O₃ exposures in multi-pollutant models.

RESULTS

An interquartile range (IQR) increase in total PM_2.5 exposure was associated with elevated odds for developing GDM over the preconception (adjusted OR = 1.09, 95% CI: 1.06, 1.12), first trimester (OR = 1.13, 95% CI: 1.10, 1.17) and second trimester (OR = 1.13, 95% CI: 1.09, 1.17) periods. Effect estimates increased with adjustment for NO₂ and O₃. We observed modest increases in odds of GDM for IQR increases in first trimester ammonium ion PM_2.5 (OR = 1.03, 95% CI: 1.00, 1.05) and sulfate PM_2.5 (OR = 1.03, 95% CI: 1.00, 1.05) exposures, as well as preconception Cr PM_2.5 exposures (OR = 1.05, 95% CI: 1.02, 1.07).

CONCLUSION

Exposures to PM_2.5, before and during pregnancy were associated with elevated odds of GDM. Mitigating air pollution exposures may reduce the risk of GDM and its long-term implications for maternal and child health.

Real-world assessment of vehicle air pollutant emissions subset by vehicle type, fuel and EURO class: New findings from the recent UK EDAR field campaigns, and implications for emissions restricted zones

This paper reports upon and analyses vehicle emissions measured by the Emissions Detecting and Reporting (EDAR) system, a Vehicle Emissions Remote Sensing System (VERSS) type device, used in five UK based field campaigns in 2016 and 2017. In total 94,940 measurements were made of 75,622 individual vehicles during the five campaigns. The measurements are subset into vehicle type (bus, car, HGV, minibus, motorcycle, other, plant, taxi, van, and unknown), fuel type for car (petrol and diesel), and EURO class, and particulate matter (PM), nitric oxide (NO) and nitrogen dioxide (NO₂) are reported. In terms of recent EURO class emission trends, NO and NO_x emissions decrease from EURO 5 to EURO 6 for nearly all vehicle categories. Interestingly, taxis show a marked increase in NO₂ emissions from EURO 5 to EURO 6. Perhaps most concerningly is a marked increase in PM emissions from EURO 5 to EURO 6 for HGVs. Another noteworthy observation was that vans, buses and HGVs of unknown EURO class were often the dirtiest vehicles in their classes, suggesting that where counts of such vehicles are high, they will likely make a significant contribution to local emissions. Using Vehicle Specific Power (VSP) weighting we provide an indication of the magnitude of the on-site VERSS bias and also a closer estimate of the regulatory test/on-road emissions differences. Finally, a new 'EURO Updating Potential' (EUP) factor is introduced, to assess the effect of a range of air pollutant emissions restricted zones either currently in use or marked for future introduction. In particular, the effects of the London based Low Emission Zone (LEZ) and Ultra-Low Emissions Zone (ULEZ), and the proposed Birmingham based Clean Air Zone (CAZ) are estimated. With the current vehicle fleet, the impacts of the ULEZ and CAZ will be far more significant than the LEZ, which was introduced in 2008.

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.

Associations of exposure to fine particulate matter during pregnancy with maternal blood glucose levels and gestational diabetes mellitus: Potential effect modification by ABO blood group

BACKGROUND

Previous studies have examined the relationships between prenatal fine particulate matter (PM_2.5) exposure and gestational diabetes mellitus (GDM), but the results were inconsistent. Furthermore, the possible effect modification by ABO blood group has not been explored.

OBJECTIVES

To assess the associations of PM_2.5 exposures during pregnancy with maternal glucose levels as well as GDM, and further to evaluate the potential effect modification by ABO blood group.

METHODS

Between January 2013 and January 2015, 4783 pregnant women were enrolled in our study based on a birth cohort in Wuhan. Daily PM_2.5 exposure levels for each woman during pregnancy were estimated using a spatial-temporal land-use regression model. Linear regressions with general estimating equations (GEE) were performed to assess the associations between trimester-specific PM_2.5 exposures and maternal glucose levels. Modified Poisson regressions with GEE analyses were used to evaluate the impacts of PM_2.5 exposures during each trimester on the risk of GDM. The associations of PM_2.5 exposure during the whole study period with glucose levels and GDM were estimated using multiple linear regression model and modified Poisson regression model, respectively. We conducted a stratified analysis to explore the potential effect modification by ABO blood group.

RESULTS

Among all the 4783 participants, 394 (8.24%) had GDM. Exposure to PM_2.5 was found to be positively associated with elevated fasting glucose level during the whole study period [0.382 mg/dL, 95% confidence interval (CI): 0.179-0.586, per 10 μg/m³ increase in PM_2.5], the first trimester (0.154 mg/dL ,95% CI: 0.017-0.291) and the second trimester (0.541 mg/dL, 95% CI: 0.390-0.692). No statistically significant results were observed between PM_2.5 and 1-h and 2-h glucose levels during any study period. Increased risks of GDM for each 10 μg/m³ increase in PM_2.5 levels were observed during the whole study period [relative risk (RR): 1.120, 95% CI: 1.021-1.228] and the first trimester (RR: 1.074, 95% CI: 1.012-1.141), but not the second trimester (RR: 1.035, 95% CI: 0.969-1.106). Stratified analysis indicated that the associations of PM_2.5 exposures with GDM were more pronounced among pregnant women with blood group A, but no significant effect modifications were observed.

CONCLUSION

Our study enriched epidemiological evidence linking PM_2.5 exposures during pregnancy to elevated maternal glucose levels and increased risk of GDM. More importantly, we first highlighted that the impact of PM_2.5 on GDM might be greater among pregnant women with blood group A.

Assessment of Maternal Glycemia and Newborn Size Among Pregnant Women Who Use Wood Stoves in Northern New England

This cohort study uses data from the New Hampshire Birth Cohort Study to assess maternal glycemia and newborn size among pregnant women who use wood-burning stoves in their New England homes.

Maternal Exposure to Ambient Air Pollution and Pregnancy Complications in Victoria, Australia

The relationship between maternal exposure to ambient air pollution and pregnancy complications is not well characterized. We aimed to explore the relationship between maternal exposure to ambient nitrogen dioxide (NO₂) and fine particulate matter (PM_2.5) and hypertensive disorders of pregnancy, gestational diabetes mellitus (GDM) and placental abruption. Using administrative data, we defined a state-wide cohort of singleton pregnancies born between 1 March 2012 and 31 December 2015 in Victoria, Australia. Annual average NO₂ and PM_2.5 was assigned to maternal residence at the time of birth. 285,594 singleton pregnancies were included. An IQR increase in NO₂ (3.9 ppb) was associated with reduced likelihood of hypertensive disorders of pregnancy (RR 0.89; 95%CI 0.86, 0.91), GDM (RR 0.92; 95%CI 0.90, 0.94) and placental abruption (RR 0.81; 95%CI 0.69, 0.95). Mixed observations and smaller effect sizes were observed for IQR increases in PM_2.5 (1.3 µg/m³) and pregnancy complications; reduced likelihood of hypertensive disorders of pregnancy (RR 0.95; 95%CI 0.93, 0.97), increased likelihood of GDM (RR 1.02; 95%CI 1.00, 1.03) and no relationship for placental abruption. In this exploratory study using an annual metric of exposure, findings were largely inconsistent with a priori expectations and further research involving temporally resolved exposure estimates are required.

Sensor-as-a-Service: Convergence of Sensor Analytic Point Solutions (SNAPS) and Pay-A-Penny-Per-Use (PAPPU) Paradigm as a Catalyst for Democratization of Healthcare in Underserved Communities

In this manuscript, we discuss relevant socioeconomic factors for developing and implementing sensor analytic point solutions (SNAPS) as point-of-care tools to serve impoverished communities. The distinct economic, environmental, cultural, and ethical paradigms that affect economically disadvantaged users add complexity to the process of technology development and deployment beyond the science and engineering issues. We begin by contextualizing the environmental burden of disease in select low-income regions around the world, including environmental hazards at work, home, and the broader community environment, where SNAPS may be helpful in the prevention and mitigation of human exposure to harmful biological vectors and chemical agents. We offer examples of SNAPS designed for economically disadvantaged users, specifically for supporting decision-making in cases of tuberculosis (TB) infection and mercury exposure. We follow-up by discussing the economic challenges that are involved in the phased implementation of diagnostic tools in low-income markets and describe a micropayment-based systems-as-a-service approach (pay-a-penny-per-use—PAPPU), which may be catalytic for the adoption of low-end, low-margin, low-research, and the development SNAPS. Finally, we provide some insights into the social and ethical considerations for the assimilation of SNAPS to improve health outcomes in marginalized communities.