Air pollution, land use, and complications of pregnancy

Ambient air pollution and hypertensive disorders of pregnancy in Rome

BACKGROUND

Ambient air pollution has been associated with hypertensive disorders of pregnancy (HDP), but few studies rely on assessment of fine-scale variation in air quality, specific subtypes and multi-pollutant exposures.

AIM

To study the impact of long-term exposure to individual and mixture of air pollutants on all and specific subtypes of HDP.

METHODS

We obtained data from 130,470 liveborn singleton pregnacies in Rome during 2014-2019. Spatiotemporal land-use random-forest models at 1 km spatial resolution assigned to the maternal residential addresses were used to estimate the exposure to particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), and ozone (O3).

RESULTS

For PM2.5, PM10 and NO2, there was suggestive evidence of increased risk of preeclampsia (PE, n = 442), but no evidence of increased risk for all subtypes of HDP (n = 2297) and gestational hypertension (GH, n = 1901). For instance, an interquartile range of 7.0 μg/m3 increase in PM2.5 exposure during the first trimester of pregnancy was associated with an odds ratio (OR) of 1.06 (95% confidence interval: 0.81, 1.39) and 1.04 (0.92, 1.17) after adjustment for NO2 and the corresponding results for a 15.7 μg/m3 increase in NO2 after adjustment for PM2.5 were 1.11 (0.92, 1.34) for PE and 0.83 (0.76, 0.90) for HDP. Increased risks for HDP and GH were suggested for O3 in single-pollutant models and for PM after adjustment for NO2, but all other associations were stable or attenuated in two-pollutant models.

CONCLUSIONS

The results of our study suggest that PM2.5, PM10 and NO2 increases the risk of PE and that these effects are robust to adjustment for O3 while the increased risks for GH and HDP suggested for O3 attenuated after adjustment for PM or NO2. Additional studies are needed to evaluate the effects of source-specific component of PM on subtypes as well as all types of HDP which would help to target preventive actions.

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.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Co-exposure to phthalates and polycyclic aromatic hydrocarbons and the risk of gestational hypertension in Chinese women

Phthalates (PAEs) and polycyclic aromatic hydrocarbons (PAHs) are frequently detected in females of reproductive age. Many studies have found that environmental PAE and PAH levels are independent risk factors for gestational hypertension. However, exposure to both components is a more realistic scenario. To better assess the health effects of PAEs and PAHs in pregnant women, we explored the associations of exposure to both individual and combined PAEs and PAHs with gestational hypertension. This nested case-control study was a component of a prospective cohort study conducted in Beijing, China. We included 206 women with gestational hypertension and 214 pregnant controls. We used gas chromatography/tandem mass spectrometry (GC-MS/MS) to detect 8 PAEs and 13 PAHs in > 80 % of all collected hair samples. Multiple linear regression models were employed to test the individual associations between each component and gestational hypertension. A quantile-based g-computation (qgcomp) model and a weighted quantile sum (WQS) regression model were used to estimate whether exposure to both PAEs and PAHs increased the risk of gestational hypertension. The individual exposure analyses revealed that diethyl phthalate (DEP), diisobutyl phthalate (DIBP) (both PAEs), benzo(k)fluoranthene (BKF), anthracene, (ANT), and benzo(a)pyrene (BAP) (all PAHs) were positively associated with increased risk of gestational hypertension. In mixed-effect analyses, the qgcomp model indicated that co-exposure to PAEs and PAHs increased the risk of gestational hypertension (odds ratio = 2.01; 95 % confidence interval: 1.02, 3.94); this finding was verified by the WQS regression model. Our findings support earlier evidence that both PAEs and PAHs increase the risk of gestational hypertension, both individually and in combination. This suggests that reductions in exposure to endocrine system-disrupting chemicals such as PAEs and PAHs might reduce the risk of gestational hypertension.

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.

Exposure to ambient black carbon and particulate matter during pregnancy in associations with risk of pre-eclampsia: A meta-analysis based on population-based studies

Air pollution control protocols and policies formulated for PM2.5 and PM10 (particulate matter [PM] with an aerodynamic diameter of ≤2.5 and 10 μm), however, such protocols and policies have not been available for black carbon (BC). A growing number of studies have evaluated the association between long-term exposure to ambient air pollution with BC and PM and pre-eclampsia. We applied a meta-analysis to estimate pooled odds ratios (ORs) and 95 % confidence intervals (CIs) based on four exposure windows (first/second/third trimester and entire pregnancy). 24 studies meeting our selection criteria (8 for BC, 21 and 15 for PM2.5 and PM10) were finally included after screening studies published up to June 22, 2023. An increase of 1 μg/m3 BC during the second trimester and entire pregnancy were associated with a 16 % (OR: 1.16, 95 % CI: [1.02, 1.32]) and a 15 % (OR: 1.15, 95 % CI: [1.03, 1.29]) increased risk of pre-eclampsia, respectively. A 10 μg/m3 increase in second-trimester exposure to PM2.5 and PM10 was associated with a 1 % (OR: 1.01, 95 % CI: [1.00, 1.03]) and a 5 % (OR: 1.05, 95 % CI: [1.01, 1.10]) increased risk of pre-eclampsia. An 11 % (OR: 1.11, 95 % CI: [1.03, 1.21]) increased risk of pre-eclampsia was found to be associated with a 10 μg/m3 increase in PM10 exposure during the entire pregnancy. The results support the potential effect of exposure to ambient particulate pollutants on risk of pre-eclampsia and emphasize the necessity of strategies and protocols for controlling BC. Greater efforts in controlling ambient particulate pollution and especially BC are needed in order to prevent pregnant women from developing pre-eclampsia.

Residential mobility in pregnancy and potential exposure misclassification of air pollution, temperature, and greenness

Introduction

Epidemiological studies commonly use residential addresses at birth to estimate exposures throughout pregnancy, ignoring residential mobility. Lack of consideration for residential mobility during pregnancy might lead to exposure misclassification that should be addressed in environmental epidemiology.

Methods

We investigated potential exposure misclassification from estimating exposure during pregnancy by residence at delivery utilizing a prospective cohort of pregnant women in New York, United States (n = 1899; 2016-2019). We calculated exposure during pregnancy corresponding to each address for fine particles (PM2.5), temperature, and greenness (Enhanced Vegetation Index [EVI]).

Results

Twenty-two percent of participants moved at least once during pregnancy; 82.3% of movers changed residences during the second or third trimesters. Participants with better health, lower parity, and higher socioeconomic status were more likely to move. Exposures based on address at delivery rather than residential history overestimated exposure for PM2.5 (exposure error: range -5.7 to 4.6 µg/m3, average -0.6 µg/m3) and EVI (range -0.305 to 0.307, average -0.013), but not temperature. Overestimations were significantly larger for mothers with higher socioeconomic status. Our findings indicate that the error for prenatal exposure can occur when residential mobility is not considered and is disproportional by maternal characteristics.

Conclusions

Epidemiological studies should consider residential mobility in exposure assessments based on geolocation when possible, and results based on mother's residence at birth should be interpreted with understanding of potential differential exposure misclassification.

Ambient air pollution and maternal cardiovascular health in pregnancy

In this review, we summarise the current epidemiological and experimental evidence on the association of ambient (outdoor) air pollution exposure and maternal cardiovascular health during pregnancy. This topic is of utmost clinical and public health importance as pregnant women represent a potentially susceptible group due to the delicate balance of the feto-placental circulation, rapid fetal development and tremendous physiological adaptations to the maternal cardiorespiratory system during pregnancy.Several meta-analyses including up to 4 245 170 participants provide robust evidence that air pollutants, including particulate matter, nitrogen oxides and others, have adverse effects on the development of hypertensive disorders of pregnancy, gestational diabetes mellitus and cardiovascular events during labour. Potential underlying biological mechanisms include oxidative stress with subsequent endothelial dysfunction and vascular inflammation, β-cell dysfunction and epigenetic changes. Endothelial dysfunction can lead to hypertension by impairing vasodilatation and promoting vasoconstriction. Air pollution and the consequent oxidative stress can additionally accelerate β-cell dysfunction, which in turn triggers insulin resistance leading to gestational diabetes mellitus. Epigenetic changes in placental and mitochondrial DNA following air pollution exposures can lead to altered gene expression and contribute to placental dysfunction and induction of hypertensive disorders of pregnancy.The maternal and fetal consequences of such cardiovascular and cardiometabolic disease during pregnancy can be serious and long lasting, including preterm birth, increased risk of type 2 diabetes mellitus or cardiovascular disease later in life. Acceleration of efforts to reduce air pollution is therefore urgently needed to realise the full health benefits for pregnant mothers and their children.

Preconceptional and prenatal exposure to air pollutants and risk of gestational diabetes in the MADRES prospective pregnancy cohort study

Background

Air pollution has been associated with gestational diabetes mellitus (GDM). We aim to investigate susceptible windows of air pollution exposure and factors determining population vulnerability.

Methods

We ascertained GDM status in the prospective Maternal and Developmental Risks from Environmental and Social Stressors (MADRES) pregnancy cohort from Los Angeles, California, USA. We calculated the relative risk of GDM by exposure to ambient particulate matter (PM10; PM2.5), nitrogen dioxide (NO2), and ozone (O3) in each week from 12 weeks before to 24 weeks after conception, adjusting for potential confounders, with distributed lag models to identify susceptible exposure windows. We examined effect modification by prenatal depression, median-split pre-pregnancy BMI (ppBMI) and age.

Findings

Sixty (9.7%) participants were diagnosed with GDM among 617 participants (mean age: 28.2 years, SD: 5.9; 78.6% Hispanic, 11.8% non-Hispanic Black). GDM risk increased with exposure to PM2.5, PM10, and NO2 in a periconceptional window ranging from 5 weeks before to 5 weeks after conception: interquartile-range increases in PM2.5, PM10, and NO2 during this window were associated with increased GDM risk by 5.7% (95% CI: 4.6-6.8), 8.9% (8.1-9.6), and 15.0% (13.9-16.2), respectively. These sensitive windows generally widened, with greater effects, among those with prenatal depression, with age ≥28 years, or with ppBMI ≥27.5 kg/m2, than their counterparts.

Interpretation

Preconception and early-pregnancy are susceptible windows of air pollutants exposure that increased GDM risk. Prenatal depression, higher age, or higher ppBMI may increase one's vulnerability to air pollution-associated GDM risk.

Funding

National Institutes of Health, Environmental Protection Agency.

Women's Employment in Industries and Risk of Preeclampsia and Gestational Diabetes: A National Population Study of Republic of Korea

Background

Some working conditions may pose a higher physical or psychological demand to pregnant women leading to increased risks of pregnancy complications.

Objectives

We assessed the association of woman's employment status and the industrial classification with obstetric complications.

Methods

We conducted a national population study using the National Health Information Service database of Republic of Korea. Our analysis encompassed 1,316,310 women who experienced first-order live births in 2010-2019. We collected data on the employment status and the industrial classification of women, as well as their diagnoses of preeclampsia (PE) and gestational diabetes mellitus (GDM) classified as A1 (well controlled by diet) or A2 (requiring medication). We calculated odds ratios (aORs) of complications per employment, and each industrial classification was adjusted for individual risk factors.

Results

Most (64.7%) were in employment during pregnancy. Manufacturing (16.4%) and the health and social (16.2%) work represented the most prevalent industries. The health and social work exhibited a higher risk of PE (aOR = 1.11, 95% confidence interval [CI]: 1.03-1.21), while the manufacturing industry demonstrated a higher risk of class A2 GDM (1.20, 95% CI: 1.03-1.41) than financial intermediation. When analyzing both classes of GDM, women who worked in public administration and defense/social security showed higher risk of class A1 GDM (1.04, 95% CI: 1.01, 1.07). When comparing high-risk industries with nonemployment, the health and social work showed a comparable risk of PE (1.02, 95% CI: 0.97, 1.07).

Conclusion

Employment was associated with overall lower risks of obstetric complications. Health and social service work can counteract the healthy worker effect in relation to PE. This highlights the importance of further elucidating specific occupational risk factors within the high-risk industries.

Effects of Air Pollution Exposure during Preconception and Pregnancy on Gestational Diabetes Mellitus

This study aimed to investigate the association between air pollution and gestational diabetes mellitus (GDM) in small- and medium-sized cities, identify sensitive periods and major pollutants, and explore the effects of air pollution on different populations. A total of 9820 women who delivered in Handan Maternal and Child Health Hospital in the Hebei Province from February 2018 to July 2020 were included in the study. Logistic regression and principal component logistic regression models were used to assess the effects of air pollution exposure during preconception and pregnancy on GDM risk and the differences in the effects across populations. The results suggested that each 20 μg/m3 increase in PM2.5 and PM10 exposure during preconception and pregnancy significantly increased the risk of GDM, and a 10 μg/m3 increase in NO2 exposure during pregnancy was also associated with the risk of GDM. In a subgroup analysis, pregnant women aged 30-35 years, nulliparous women, and those with less than a bachelor's education were the most sensitive groups. This study provides evidence for an association between air pollution and the prevalence of GDM, with PM2.5, PM10, and NO2 as risk factors for GDM.

Advances in epigenetic research of adolescent idiopathic scoliosis and congenital scoliosis

Scoliosis is a three-dimensional structural deformity of the spine; more than 80% of scoliosis has no specific pathogenesis but is understood to be closely related to genetic, hormonal, and environmental factors. In recent years, the epigenetic alterations observed in scoliosis have been analyzed in numerous studies to determine the pathogenesis and progression of this condition, however, there is currently no comprehensive review of the epigenetic factors to date. We searched PubMed, Embase, and Web of Science databases for relative studies without language and date restrictions in March 2023. Twenty-five studies were included in this review and analyzed from the four main aspects of epigenetic alteration: DNA methylation, non-coding RNAs, histone modifications, and chromatin remodeling. The relationship between DNA methylation, non-coding RNAs, and scoliosis was considerably reported in the literature, and the corresponding related signaling pathways and novel biomarkers observed in scoliosis provide insights into innovative prevention and treatment strategies. However, the role of histone modifications is rarely reported in scoliosis, and few studies have investigated the relationship between scoliosis and chromatin remodeling. Therefore, these related fields need to be further explored to elucidate the overall effects of epigenetics in scoliosis.

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.

"Residential greenness, gestational diabetes mellitus (GDM) and microbiome diversity during pregnancy"

BACKGROUND

Gestational diabetes mellitus (GDM) is associated with reduced gut microbiota richness that was also reported to differ significantly between those living in rural compared to urban environments. Therefore, our aim was to examine the associations between greenness and maternal blood glucose levels and GDM, with microbiome diversity as a possible mediator in these associations.

METHODS

Pregnant women were recruited between January 2016 and October 2017. Residential greenness was evaluated as mean Normalized Difference Vegetation Index (NDVI) within 100, 300 and 500 m buffers surrounding each maternal residential address. Maternal glucose levels were measured at 24-28 weeks of gestation and GDM was diagnosed. We estimated the associations between greenness and glucose levels and GDM using generalized linear models, adjusting for socioeconomic status and season at last menstrual period. Using causal mediation analysis, the mediation effects of four different indices of microbiome alpha diversity in first trimester stool and saliva samples were assessed.

RESULTS

Of 269 pregnant women, 27 participants (10.04%) were diagnosed with GDM. Although not statistically significant, adjusted exposure to medium tertile levels of mean NDVI at 300 m buffer had lower odds of GDM (OR = 0.45, 95% CI: 0.16, 1.26, p = 0.13) and decreased change in mean glucose levels (β = -6.28, 95% CI: 14.91, 2.24, p = 0.15) compared to the lowest tertile levels of mean NDVI. Mixed results were observed at 100 and 500 m buffers, and when comparing highest tertile levels to lowest. No mediation effect of first trimester microbiome on the association between residential greenness and GDM was observed, and a small, possibly incidental, mediation effect on glucose levels was observed.

CONCLUSION

Our study suggests possible associations between residential greenness and glucose intolerance and risk of GDM, though without sufficient evidence. Microbiome in the first trimester, while involved in GDM etiology, is not a mediator in these associations. Future studies in larger populations should further examine these associations.

Environmental Exposure: Effect on Maternal Morbidity and Mortality and Neonatal Health

Environmental factors are important causes that impair global pregnancy outcomes and are, importantly, responsible for maternal morbidity and mortality. However, apart from the direct reasons for maternal deaths, mainly obstetric and neonatal complications, such factors are ignored or given less importance. The recent surge in research on the impact of various environmental factors on pregnancy outcomes suggests the need for immediate attention to such factors and device-specific policies to counter the situation. Moreover, the recent coronavirus disease of 2019 (COVID-19) pandemic, global warming, and climate change showed a lack of preparedness to counter the impact of such events on maternal survival and safe and successful pregnancy outcomes. In the present review, we have emphasized the specific factors responsible for increased maternal and neonatal deaths and their association with specific environmental factors. Increased attention on maternal healthcare, preparedness to counter sudden environmental challenges and improvement of the conventional requirement for better maternal healthcare access and nutrition at a global level may improve the scenario.

Women with preeclampsia exposed to air pollution during pregnancy: Relationship between oxidative stress and neonatal disease - Pilot study

Oxidative imbalance as a pathophysiological mechanism has been reported as an adverse outcome in pregnant women who develop preeclampsia and in their newborns. Furthermore, emerging evidence suggests the same mechanism by which air pollutants may exert their toxic effects. Therefore, the objective of the study was to evaluate the biomarkers of oxidative stress and their relationship with neonatal disease in premature newborns from mothers with preeclampsia exposed to air pollution during pregnancy. The data of air pollutants (PM_2.5, PM₁₀ and ozone) were collected at fixed monitoring stations. Oxidative and antioxidant status markers were obtained through special techniques in women with preeclampsia and in umbilical cord blood of their premature newborns. The oxidative stress markers were significantly higher in women with preeclampsia and their newborns who were exposed to higher levels of ambient air pollutants in the first and second trimester of pregnancy. Neonatal diseases are associated with preeclampsia in pregnancies, specifically intrauterine growth restriction (IUGR) and necrotizing enterocolitis (NEC). A significant correlation was identified in the levels of prooxidant agents and antioxidant enzyme activity in the presence of neonatal diseases associated with preeclampsia. There is increased oxidative damage in both the maternal and fetal circulation in women who develop preeclampsia exposed to air pollution during pregnancy. Therefore, these pregnancies complicated by preeclampsia have a greater adverse outcome as neonatal disease in the preterm infant.

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.

Causal Associations of PM2.5 and GDM: A Two-Sample Mendelian Randomization Study

Epidemiological studies have linked particulate matter (PM2.5) to gestational diabetes mellitus (GDM). However, the causality of this association has not been established; Mendelian randomization was carried out using summary data from genome-wide association studies (GWAS). For the analysis of the causal relationship between PM2.5 and GDM, the inverse variance weighted (IVW) method was used. The exposure data came from a GWAS dataset of IEU analysis of the United Kingdom Biobank phenotypes consisting of 423,796 European participants. The FinnGen consortium provided the GDM data, which included 6033 cases and 123,000 controls. We also performed multivariate MR (MVMR), adjusting for body mass index (BMI) and smoking. As a result, we found that each standard deviation increase in PM2.5 is associated with a 73.6% increase in the risk of GDM (OR: 1.736; 95%CI: 1.226-2.457). Multivariable MR analysis showed that the effect of PM2.5 on GDM remained after accounting for BMI and smoking. Our results demonstrate a causal relationship between PM2.5 and GDM.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Breastfeeding, socioeconomic status, and long-term postpartum weight retention

BACKGROUND

Almost half of all pregnant women in the United States gain weight above Institute of Medicine gestational weight gain guidelines. Breastfeeding has been shown to reduce weight retention in the first year postpartum; however, women with lower socioeconomic status (SES) tend to initiate breastfeeding less often than women with higher SES. We investigated associations between duration of breastfeeding with mother's long-term postpartum weight status at 4-10 years and evaluated whether the associations varied by SES.

METHODS

Maternal and infant dyads (N = 2144 dyads) are from the Geographic Research on Wellbeing survey (GROW), 2012-2013, a long-term, cross-sectional follow-up of the Maternal and Infant Health Assessment (MIHA) based in California, USA. Pre-pregnancy body mass index (BMI) was obtained from self-report of height and weight during MIHA, while breastfeeding history and self-report of current body weight was collected at the 4-10 year GROW postpartum visit. SES score was derived from a composite score of percent federal poverty level and education and was dichotomized into High and Low SES groups at a score of three. Multivariable linear regression was used to examine association between breastfeeding and maternal weight status, and to examine for effect modification by SES.

RESULTS

Average long-term weight retention 4-10 years postpartum was 4.0 kg. Fewer lower SES vs. higher SES women breast fed at least six months (51% versus 70%, p < .001) or ever breastfed (74% versus 89%, P < .001). Women who breastfed at least six months had lower long-term postpartum weight retention compared to those who did not (b = -1.06 kg, (-1.93, 0.25); p = 0.01); however, these association did not vary by SES.

CONCLUSION

Six months of breastfeeding is associated with lower BMI at 4-10 years and lower body weight, and effects do not vary by SES. Future policies and guidelines should consider building an infrastructure that is supportive of longer breastfeeding duration. Moreover, further research is needed to identify the impact of additional behavioral and environmental factors on long-term maternal weight status. Understanding the drivers of excessive weight retention pospartum can help us not only improve the pregnant person's health but the health of their children.

Green space, air pollution and gestational diabetes mellitus: A retrospective cohort study in central China

Emerging evidence suggests residential surrounding green space is beneficial for human health. The association between green space and GDM showed inconsistent results, and potential effect modification of green space with air pollution is still unclear. This study aims to evaluate the association between green space and GDM, and further explore potential interaction and medication effects. Participants were recruited from a retrospective cohort study between 2015 and 2020 in Henan, China. Residential green space based on normalized difference vegetation index (NDVI) and air pollution exposure were estimated using spatial-statistical models. Multivariate logistic regression was applied to evaluate the association between per 0.1 unit increase in NDVI with 4 buffer sizes (250 m, 500 m, 1000 m, 2000 m) and GDM. We examined potential interaction of green space and air pollutants on GDM. Mediating effects of air pollution associated with green space exposure on GDM were also investigated by causal mediation analyses. A total of 46,665 eligible pregnant women were identified. There were 4092 (8.8 %) women diagnosed with GDM according to the IADPSG criteria. We found that per 0.1-unit increment in NDVI250 m, NDVI500 m, NDVI1000 m and NDVI2000 m in second trimester were associated with the decreased risk of GDM, with adjusted OR of 0.921(95 %CI: 0.890-0.953), 0.922 (95 %CI: 0.891-0.953), 0.921 (95 %CI: 0.892-0.952) and 0.921 (95 %CI: 0.892-0.951), respectively. We identified significant interactions between second trimester PM2.5 and O3 exposure and NDVI for GDM (Pinteraction < 0.001). The causal mediation analysis showed that PM2.5 mediated approximately 2.5-5.5 % of the association between green space and GDM, while the estimated mediating effect of O3 was approximately 30.1-38.5 %. In conclusion, our study indicates that residential green space was associated with a reduced risk of GDM, particularly second trimester. Green space may benefit to GDM partly mediated by a reduction in PM2.5 and O3.

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

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

A study on exposure to greenspace during pregnancy and lipid profile in cord blood samples

Although evidence reporting the beneficial associations of prenatal greenspace exposure with pregnancy outcomes is increasing, there is still a lack of evidence on the potential association of such exposure to greenspace on fetal lipid profile. We aimed to first-time investigate the associations between prenatal exposure to greenspace and lipid levels in the cord blood. The present study was based on data from 150 expectant mothers, residents of Sabzevar city in Iran (2018). For each participant, we identified exposure to greenspace in residential surroundings, residential accessibility to green space, use of green spaces, and the number of plant pots inside the home. Measures of levels of triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and TC/HDL-C and TG/HDL-C ratios in samples of cord blood were applied to identify the lipid profile. We developed adjusted linear regression models to estimate the associations of each indicator of greenspace exposure with each cord blood lipid. We found increased greenspace in residential surroundings across a 100 m buffer, higher residential accessibility to green space, and more use of green spaces were associated with decreased cord blood lipid levels. The remainder findings regarding the greenspace in residential surroundings across 300 m and 500 m buffers and the number of plant pots were null. Some suggestions were observed for a potential mediatory role of air pollution. This study suggests that greenspace exposure during pregnancy may influence positively fetal lipid levels in the cord blood.

Temporal-spatial change of China's coastal ecosystems health and driving factors analysis

Understanding the spatial distribution pattern change and driving factors behind ecosystem health is essential to ecosystem management and restoration. However, in the research of regional ecosystem health, there is little research on ecosystem health in coastal regions, and there is little exploration of its temporal and spatial pattern change and its driving factors. In this study, we use the Vigor-Organization-Resilience-Services (VORS) model and marine ecosystem health index to diagnose the ecosystem health of the whole coastal area of China over the last 20 years, and find the main contributing factors affecting ecosystem health with the help of geographic detectors and geographic weighted regression analysis. Our results show that: (1) the ecosystem health level in the south of the coastal region is higher than that in the north, mainly with 30° north latitude as the main dividing line. (2) The regions with high change rate are mainly concentrated in Bohai Bay, the Yangtze River Estuary, Hangzhou Bay and the Pearl River Estuary, and the change is mainly negative. (3) Both natural and human factors have an impact on ecosystem health, and the influencing factors are different on different scales. The interaction between different factors is greater than the impact of a single factor on ecosystem health. The study puts forward a new evaluation framework for the study of ecosystem health in coastal areas, which can be applied to other coastal areas with similar conditions, and can help the sustainable and healthy development of coastal areas.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

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

Environmental health influences in pregnancy and risk of gestational diabetes mellitus: a systematic review

Background

Gestational diabetes mellitus (GDM) is one of the most common pregnancy complications globally. Environmental risk factors may lead to increased glucose levels and GDM, which in turn may affect not only the health of the mother but assuming hypotheses of "fetal programming", also the health of the offspring. In addition to traditional GDM risk factors, the evidence is growing that environmental influences might affect the development of GDM. We conducted a systematic review analyzing the association between several environmental health risk factors in pregnancy, including climate factors, chemicals and metals, and GDM.

Methods

We performed a systematic literature search in Medline (PubMed), EMBASE, CINAHL, Cochrane Library and Web of Science Core Collection databases for research articles published until March 2021. Epidemiological human and animal model studies that examined GDM as an outcome and / or glycemic outcomes and at least one environmental risk factor for GDM were included.

Results

Of n = 91 studies, we classified n = 28 air pollution, n = 18 persistent organic pollutants (POP), n = 11 arsenic, n = 9 phthalate n = 8 bisphenol A (BPA), n = 8 seasonality, n = 6 cadmium and n = 5 ambient temperature studies. In total, we identified two animal model studies. Whilst we found clear evidence for an association between GDM and air pollution, ambient temperature, season, cadmium, arsenic, POPs and phthalates, the findings regarding phenols were rather inconsistent. There were clear associations between adverse glycemic outcomes and air pollution, ambient temperature, season, POPs, phenols, and phthalates. Findings regarding cadmium and arsenic were heterogeneous (n = 2 publications in each case).

Conclusions

Environmental risk factors are important to consider in the management and prevention of GDM. In view of mechanisms of fetal programming, the environmental risk factors investigated may impair the health of mother and offspring in the short and long term. Further research is needed.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13965-5.

Prenatal Exposure to PM2.5 and Its Specific Components and Risk of Hypertensive Disorders in Pregnancy: A Nationwide Cohort Study in China

Hypertensive disorders in pregnancy (HDP) are a leading cause of maternal mortality and adverse birth outcomes. Fine particulate matter (PM_2.5) has been linked to HDP risk; however, limited studies have explored the relationships between specific chemical constituents of PM_2.5 and HDP risk. Based on maternal data from the China Labor and Delivery Survey (CLDS), this study included a total of 67,659 participants from 95 participant hospitals in 25 provinces of China between March 1, 2015, and December 31, 2016. Maternal exposure to total PM_2.5 mass and six main components during pregestation and pregnancy were estimated using the Combined Geoscience-Statistical Method. Multilevel logistic regression models were applied to quantify the associations, controlling for sociodemographic characteristics. We found that an interquartile range (IQR) increase in PM_2.5 exposure during the second trimester was associated with a 14% increase in HDP risk (95% CI: 2%, 29%). We observed that black carbon (BC) and SO₄^2- had larger or comparable estimates of the effect than total PM_2.5 mass. The association estimates were greater in the gestational hypertension group than in the group of pre-eclampsia and eclampsia. Our findings suggest that PM_2.5 exposure and specific chemical components (particularly BC and SO₄^2-) were associated with an increased HDP risk in China.

An exposure-response meta-analysis of ambient PM2.5 during pregnancy and preeclampsia

Relationships between PM_2.5 exposure and preeclampsia have been the focus of four recent systematic reviews and meta-analyses. We expand on knowledge gaps in these reviews by characterizing the shape of the exposure-outcome relationship, and by assessing the heterogeneity in these associations by study characteristics. Studies of PM_2.5 and preeclampsia were identified from reviews, and confounder-adjusted estimates were extracted. Estimates were derived using a random-effects model. Potential non-linearity was evaluated using a one-stage dose-response meta-analysis. Contrary to previous meta-analyses reporting stronger relationships, the overall adjusted relative risk (RR) for a 10 μg/m³ average increase in PM_2.5 during pregnancy and preeclampsia was modest and not statistically significant (RR: 1.07, 95% CI: 0.99-1.15). This was mainly attributable to inclusion/exclusion decisions for studies made during this review. In addition, there was no evidence of non-linearity, and no important sub-group differences by characteristics such as region, exposure assessment, participant exclusions, and early versus late-onset preeclampsia. Overall, our analysis suggests a modest relationship between ambient PM_2.5 and preeclampsia. We provide details on inclusion and exclusion decisions that were lacking in previous studies, and report novel investigations of non-linearity and heterogeneity.

Built and Social Environments, Environmental Justice, and Maternal Pregnancy Complications

Purpose of Review

The Environmental Justice Movement centers on addressing inequitable distribution of environmental harms in marginalized communities. It has been commonly understood as the disproportionate concentration of environmental pollutants or hazards. As such, much of the work on environmental harms and maternal pregnancy complications have focused on environmental toxins. This scoping review surveyed the literature exploring the built and social environment factors and maternal pregnancy complications among racially marginalized women and highlights how an environmental justice framework can inform policy interventions for maternal health inequities caused by structural racism in built and social environments.

Recent Findings

The literature examining the association between neighborhood level built and social environment factors and maternal pregnancy complications in the last five years is sparse. When excluding environmental toxins, we identified 16 studies that fit our criteria of neighborhood-level environmental exposure, with the majority focused on built environment factors, specifically proximity to greenspace and food environment.

Summary

We identified a few important gaps and opportunities for future research in this area. First is a need to explore additional built environment elements. Secondly, extensive research is needed on the social environment. Third is a critical understanding to incorporate structural racism and cultural perspectives to better understand these relationships in minoritized populations and highlight the intersection between environmental hazards concentration and their structural causes. Finally, an environmental justice framework is critically needed in the interpretation and translation of this literature to inform policy solutions that can counteract the harms in racially marginalized communities and improve health.

Association between greenspace and blood pressure: A systematic review and meta-analysis

Many studies have investigated the association between greenspaces and blood pressure (BP), but the results remain mixed. We conducted a systematic review and meta-analysis to comprehensively evaluate the evidence concerning greenspaces with BP levels and prevalent hypertension. Systematic literature searches were performed in Web of Science, PubMed, and Embase up to 25 April 2021. Combined effect estimates were calculated using random-effect models for each greenspace exposure assessment method that had been examined in ≥3 studies. Sensitivity analysis, subgroup analysis, and publication bias were also conducted. Of 38 articles (including 52 analyses, 5.2 million participants in total) examining the effects of normalized difference vegetation index (NDVI) (n = 23), proportion of greenspace (n = 11), distance to greenspace (n = 9), and others (n = 9) were identified. Most studies (65%) reported beneficial associations between greenspaces and BP levels/hypertension. Our results of meta-analyses showed that higher NDVI_500m was significantly associated with lower levels of systolic blood pressure (SBP = -0.77 mmHg, 95%CI: -1.23 to -0.32) and diastolic blood pressure (DBP = -0.32 mmHg, 95%CI: -0.57 to -0.07). We also found that NDVI in different buffers and the proportion of greenspaces were significantly associated with lower odds (1-9%) of hypertension. However, no significant effect was found for distance to greenspaces. In summary, our results indicate the beneficial effects of greenspace exposure on BP and hypertension. However, future better-designed studies, preferably longitudinal, are needed to confirm and better quantify the observed benefits in BP and/or hypertension.

Exploring the Spatiotemporal Evolution and Socioeconomic Determinants of PM2.5 Distribution and Its Hierarchical Management Policies in 366 Chinese Cities

From 2013 to 2017, progress has been made by implementing the Air Pollution Prevention and Control Action Plan. Under the background of the 3 Year Action Plan to Fight Air Pollution (2018–2020), the pollution status of PM2.5, a typical air pollutant, has been the focus of continuous attention. The spatiotemporal specificity of PM2.5 pollution in the Chinese urban atmospheric environment from 2018 to 2020 can be summarized to help conclude and evaluate the phased results of the battle against air pollution, and further, contemplate the governance measures during the period of the 14th Five-Year Plan (2021–2025). Based on PM2.5 data from 2018 to 2020 and taking 366 cities across China as research objects, this study found that PM2.5 pollution has improved year by year from 2018 to 2020, and that the heavily polluted areas were southwest Xinjiang and North China. The number of cities with a PM2.5 concentration in the range of 25–35 μg/m³ increased from 34 in 2018 to 86 in 2019 and 99 in 2020. Moreover, the spatial variation of the PM2.5 gravity center was not significant. Concretely, PM2.5 pollution in 2018 was more serious in the first and fourth quarters, and the shift of the pollution's gravity center from the first quarter to the fourth quarter was small. Global autocorrelation indicated that the space was positively correlated and had strong spatial aggregation. Local Moran's I and Local Geti's G were applied to identify hotspots with a high degree of aggregation. Integrating national population density, hotspots were classified into four areas: the Beijing–Tianjin–Hebei region, the Fenwei Plain, the Yangtze River Delta, and the surrounding areas were selected as the key hotspots for further geographic weighted regression analysis in 2018. The influence degree of each factor on the average annual PM2.5 concentration declined in the following order: (1) the proportion of secondary industry in the GDP, (2) the ownership of civilian vehicles, (3) the annual grain planting area, (4) the annual average population, (5) the urban construction land area, (6) the green space area, and (7) the per capita GDP. Finally, combined with the spatiotemporal distribution of PM2.5, specific suggestions were provided for the classified key hotspots (Areas A, B, and C), to provide preliminary ideas and countermeasures for PM2.5 control in deep-water areas in the 14th Five-Year Plan.

Greenness alleviates the effects of ambient particulate matter on the risks of high blood pressure in children and adolescents

Both ambient particulate matter (PM) and decrease of greenness have been suggested as risk factors for high blood pressure (HBP) in children and adolescents. But most evidence were from cross-sectional studies with limited data from prospective cohorts. In this cohort study, we included 588,004 children and adolescents aged 7 to 18 years without HBP from 2005 to 2018 in Beijing (240,081) and Zhongshan (347,923) city of China. The cumulative incidence of HBP was 32.04%, and incidence rate was 14.86 per 100 person-year. After adjustment for confounders, the ten-unit increase in PM₁, PM_2.5, and PM₁₀ exposure was significantly associated with 43%, 70%, and 43%- higher risks of HBP, respectively, but the 0.1-unit increase in NDVI exposure was significantly associated with a 25% lower risk of HBP. The HRs of PM₁ on the HBP risk were 1.486 and 1.150 in the low and the high-level of greenness, and they were 2.635 and 2.507 for PM_2.5, and for PM₁₀ 1.367 and 1.702 in the two groups. The attributable fraction (AFs) of PM₁, PM_2.5, and PM₁₀ on HBP incidents were 13.74%, 40.08%, and 15.47% in the low-level of greenness, which simultaneously was higher than those in the high-level of greenness (AF = 4.62%, 17.28%, and 9.96%). The exposure to higher ambient PM air pollution and lower greenness around schools were associated with a higher risk of HBP in children and adolescents, but higher greenness alleviated the adverse effects of ambient PM₁ and PM_2.5 on the HBP risks. Our findings highlighted a synergic strategy in preventing childhood HBP by decreasing air pollution reduction and improving greenness concurrently.

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.

Association between high-risk pregnancy and environmental contaminants in the Metropolitan Region of Baixada Santista, Brazil

The Metropolitan Region of Baixada Santista (MRBS) is a highly contaminated area. High-risk pregnancy is one factor that leads to a higher chance of both morbidity and mortality of the mother-fetus binomial. The purpose of this study is to analyze the association between exposure to environmental contaminants and high-risk pregnancy. Case-control study, using a probabilistic and random sample composed of 201 high-risk pregnant women (cases) and 201 no high-risk pregnant women (control) followed up during prenatal care at a Public Hospital. The instrument used was a self-administered questionnaire. Contaminated areas data were obtained from the Environmental Company of the São Paulo State. The participants were georeferenced by their place of residence. Descriptive analysis, Chi-square test, and univariate and multiple logistic regression analysis were performed. The multiple logistic regression model demonstrated that living in a contaminated area (OR = 1.565; 95%CI: 1.033; 2.370), preterm delivery in the current pregnancy (OR = 1.989; 95%CI: 1.239; 3.194), and more than 35 years old (OR = 2.822; 95%CI: 1.692; 4.706) are factors jointly related to high-risk pregnancy. Environmental contaminants play an important role in high-risk pregnancy, and mitigating measures are needed to improve the environment and reduce high-risk pregnancy.

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.

Hyperlocalized Measures of Air Pollution and Preeclampsia in Oakland, California

Exposure to nitrogen dioxide (NO₂), black carbon (BC), and ultrafine particles (UFPs) during pregnancy may increase the risk of preeclampsia, but previous studies have not assessed hyperlocalized differences in pollutant levels, which may cause exposure misclassification. We used data from Google Street View cars with mobile air monitors that repeatedly sampled NO₂, BC, and UFPs every 30 m in Downtown and West Oakland neighborhoods during 2015-2017. Data were linked to electronic health records of pregnant women in the 2014-2016 Sutter Health population, who resided within 120 m of monitoring data (N = 1095), to identify preeclampsia cases. We used G-computation with log-binomial regression to estimate risk differences (RDs) associated with a hypothetical intervention reducing pollutant levels to the 25th percentile observed in our sample on preeclampsia risk, overall and stratified by race/ethnicity. Prevalence of preeclampsia was 6.8%. Median (interquartile range) levels of NO₂, BC, and UFPs were 10.8 ppb (9.0, 13.0), 0.34 μg/m³ (0.27, 0.42), and 29.2 # × 10³/cm³ (26.6, 32.6), respectively. Changes in the risk of preeclampsia achievable by limiting each pollutant to the 25th percentile were NO₂ RD = -1.5 per 100 women (95% confidence interval (CI): -2.5, -0.5); BC RD = -1.0 (95% CI: -2.2, 0.02); and UFP RD = -0.5 (95% CI: -1.8, 0.7). Estimated effects were the largest for non-Latina Black mothers: NO₂ RD = -2.8 (95% CI: -5.2, -0.3) and BC RD = -3.0 (95% CI: -6.4, 0.4).

Particulate matter and hypertensive disorders in pregnancy: systematic review and meta-analysis

OBJECTIVES

We aimed to quantitatively synthesize the association between maternal exposure to particulate matter (PM; including PM <2.5 μm and PM <10 μm) and hypertensive disorders in pregnancy (HDP; including gestational hypertension [GH] and pre-eclampsia) and to explore the influence of certain factors on the outcome.

STUDY DESIGN

Meta-analysis was used to quantitatively synthesize the results of similar independent studies.

METHODS

Original documents were identified by searching six electronic bibliographic databases from their inceptions to August 17, 2021. Then we performed meta-analysis to combine the effect estimates if at least three estimates reported the same exposure and outcome and used stratified analysis to evaluate the impact of exposure assessment method, data source, and study area on heterogeneity. In addition, we used the 95% prediction interval to evaluate the potential effects of exposure in random effects meta-analysis.

RESULTS

The overall meta-analysis showed that the risk of HDP was significantly associated with per 5 μg/m³ increase in PM_2.5 exposure during T1 and PM₁₀ exposure during T, with odds ratios [ORs] 1.06 (95% confidence interval [CI]: 1.01-1.12) and 1.04 (95% CI: 1.02-1.07), respectively. The results also showed that PM_2.5 exposure during T1 and T2 and PM₁₀ exposure during T1 increased the incidence of GH; the summary ORs were 1.11 (95% CI: 1.01-1.23), 1.16 (95% CI: 1.05-1.29), and 1.04 (95% CI: 1.02-1.07), respectively. Subgroup analyses showed that the pooled effects were generally significant or more apparent in studies using models to assess exposure, studies whose data derived from birth registers, and studies in Europe.

CONCLUSIONS

This meta-analysis showed that PM exposure was associated with increased HDP risks, and the association varied by study area, data source, and exposure assessment method. With the continuous improvement of research design and exposure assessment, future research may find higher risks.

The relationship between the neighborhood built and social environment and hypertensive disorders of pregnancy: A scoping review

BACKGROUND

Theory and limited empirical research suggest that the neighborhood environment influences maternal health outcomes. The goal of this scoping review is to summarize extant research considering the impact of the built and social environment of resident neighborhood on hypertensive disorders of pregnancy (HDP) globally.

METHODS

We performed a systematic search of the literature using four databases, PubMed, Web of Science, CINAHL, and Embase on July 15, 2020. We excluded articles not in English, that did not consider one or more HDP as a primary or secondary outcome, and that did not include an element of the neighborhood built or social environment as an exposure. We applied a modified version of the Effective Public Health Practice Project Quality Assessment Tool for Quantitative Studies to evaluate quality of included studies.

RESULTS

Our search identified 11,385 unique abstracts for screening. Following exclusions, we included 64 articles in the final review. The majority of articles measured an element of the built environment (70.3% (44)), most commonly traffic-related air pollution (42.2% (27)). A third of articles (31.3% (20)) considered an element of the neighborhood social environment, most commonly neighborhood deprivation (10.9% (7)). Global quality ratings were mostly moderate (29.7% (19)) or weak (68.8% (44)), primarily due to inattention to neighborhood-level confounding.

CONCLUSION

Critical gaps remain in understanding how the resident neighborhood may impact HDP. Future research should focus on designing high-quality studies incorporating elements of both the built and social environment to holistically understand how context may impact maternal health.

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.

Land use and semen quality: A fertility center cohort study

This study explored the association between built environment and semen parameters among men who sought fertility evaluation. We used a data of 5,886 men living in the Seoul capital area whose semen was tested at a single fertility center during 2016–2018. Distance to fresh water, the coast, major roadways, and neighborhood greenness measured by Normalized Difference Vegetation Index (NDVI) were evaluated. Outcome indicators were semen volume, sperm concentration, percentage of progressive motility, vitality, normal morphology, and total motile sperm count. Linear regression models were fitted to standardized values of six semen indicators. Majority of men were white-collar, clerical, and service workers. Linear associations between built environment features and semen quality indicators were not evident except for NDVI within 500 m and sperm vitality (β = 0.05; 95% confidence interval (CI): 0.01, 0.09). The 2^nd quartile of distance to fresh water was associated with lower progressive motility compared to the 1^st quartile (β = −0.10; 95% CI: −0.17, −0.03). Proportion of vitality was higher among men in the 2^nd quartile of distance to roadways than those in the 1^st quartile (0.08; 95% CI: 0.01, 0.15). Men in the 2^nd quartile of NDVI had higher total motile sperm count (0.09; 95% CI: 0.01, 0.17). In the multi-exposure model, the positive association between NDVI and vitality remained (0.03; 95% CI: 0.00, 0.06). We observed potential evidence regarding the impact of built environment on male fertility, specifically a positive association between residential greenness and sperm vitality among men with a history of infertility.

Assessing the effects of non-optimal temperature on risk of gestational diabetes mellitus in a cohort of pregnant women in Guangzhou, China

Previous observational studies have shown that exposure to ambient temperature and air pollution were associated with the incidence of gestational diabetes mellitus (GDM). However, the susceptible time window of non-optimal temperature on GDM is still unknown, and the interaction with air pollution has not been examined. We conducted a prospective cohort study in Guangzhou, China to investigate the windows of susceptibility of temperature extremes and variability on the risk of GDM and to explore any interaction effect with air pollution. Daily maximum (T_max), minimum temperature (T_min) and diurnal temperature range (DTR) were obtained from Guangdong Meteorological Service. Distributed lag non-linear models with a logistic regression were applied to assess the effect of temperature extremes and DTR in different weeks of gestation on GDM. To examine the interaction effect, relative excess risk due to interaction index, attributable proportion and synergy index were calculated. There were 5,165 pregnant women enrolled, of which 604 were diagnosed with GDM (11.7%). Compared with a reference temperature (50th percentile of T_max), we found that extreme high temperature (99th percentile of T_max) exposure during 21st and 22nd gestational weeks was associated with an increased risk of GDM. Extreme low temperature (1st percentile of T_max) exposure during 14th to 17th weeks increased the risk of GDM. We observed that per 1 °C increment of DTR during 21st to 24th weeks was associated with an elevated GDM risk. No interaction effect of temperature extremes or variability with air pollution on GDM were observed. Our results suggested that non-optimal temperature is an independent risk factor of GDM. The time window of susceptibility for extreme temperatures and DTR exposure on the risk of GDM generally occurred in second trimester of pregnancy. In the context of climate change, our study has important implications for reproductive health and justifies more research in different climate zones.

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.

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

BACKGROUND

Fasting blood glucose may capture the adverse effects of air pollution on pregnant women better than the incidence of gestational diabetes mellitus (GDM), but evidence on the association between air pollution and maternal glucose concentrations is limited.

OBJECTIVE

To investigate the associations between air pollutants, GDM and fasting blood glucose during pregnancy.

METHODS

We recruited 2326 pregnant women from two birth cohorts located in Guangzhou and Heshan, the Pearl River Delta region (PRD), China. PM₁₀, PM_2.5 and black carbon (BC) exposure concentrations in the first and second trimesters of pregnancy were collected at fixed-site monitoring stations for each cohort. Multiple logistic regressions were employed to estimate the associations between particle pollution and GDM. Mixed-effects models were used to evaluate the associations of air pollutants with blood glucose levels. Restricted cubic spline functions were fitted to visualize the concentration-response relationships. Distributed lag non-linear models were used to estimate week-specific lag effects of particle pollution exposure on GDM and blood glucose. Unconstrained distributed lag models with lags of 0-3 weeks were used to examine potential cumulative effects.

RESULTS

We observed positive and significant associations of PM₁₀, PM_2.5 and BC exposure with fasting glucose, particularly in the second trimester. PM₁₀, PM_2.5 and BC were strongly correlated and displayed similar cumulative (lag 0-3 weeks) associations with fasting blood glucose. Exposure to particle pollution was not associated with 1-h or 2-h blood glucose. Models estimating the association between air pollutants and GDM were consistent with statistical insignificance.

CONCLUSIONS

Based on the results of the present study, exposure to air pollution during pregnancy exerts cumulative, adverse effects on fasting glucose levels. This study provides preliminary support for the use of blood glucose levels to explore the potential health impact of air pollution on pregnant women.

Association between residential greenness and glycosylated hemoglobin in pregnant women: Findings from the baseline data of Yuexiu birth cohort

BACKGROUND

Previous studies have indicated that residential greenness can affect human health, but limited studies have examined the association between residential greenness and glucose homeostasis during pregnancy. We aimed to investigate the associations of residential greenness with plasma glucose, glycosylated hemoglobin (HbA1c) and gestational diabetes mellitus (GDM).

METHODS

We recruited a total of 587 pregnant women aged 20-45 years in Guangzhou, China. We extracted normalized difference vegetation index with different buffers (NDVI-250m, 500m and 1000m) from remote satellite data based on maternal residential addresses. We measured plasma glucose levels and HbA1c during 20-28 weeks' gestation, and GDM was diagnosed with a 75-g oral glucose tolerance test. We collected the information of relevant covariates by face-to-face interviews and questionnaires. We used generalized linear regression to examine the associations of residential greenness with quantitative and categorized outcomes.

RESULTS

In the final analyses, 123 (21.0%) of the pregnant women were diagnosed as GDM at 20-28 weeks gestation. With a 0.1 unit increase in NDVI-250m, the percent of HbA1c changed by -0.05% [95% confidence interval (CI): -0.08, -0.02]. The results of HbA1c were consistent when using different resolution of NDVI [NDVI-500m: 0.03, 95%CI: -0.05, -0.01; NDVI-1000m: 0.05, 95%CI: -0.08, -0.02]. We observed non-significant associations of glucose levels and the risk of GDM in relation to NDVI with different resolutions when adjusted for confounding. The results remained robust in sensitivity analyses.

CONCLUSION

The present study in Guangzhou, China was the first to identify negative association of NDVI with HbA1c in pregnant women, but we did not observe its association with plasma glucose levels or the risk of GDM. The results support that building sufficient green infrastructure could be considered in urban design and planning to promote maternal health.

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.

Air pollution and pre-eclampsia; associations and potential mechanisms

INTRODUCTION

Air pollution has significant negative health impacts, particularly on the cardiovascular system. The aims of this narrative review were to identify whether there is an association between air pollution and the incidence of pre-eclampsia, and the potential mechanisms by which any effects may be mediated.

METHODS

We undertook a literature search using Google Scholar, PubMed, the Cochrane Library and NICE Evidence. The primary eligibility criterion was articles correlating exposure to air pollution with incidence of pre-eclampsia.

RESULTS

Meta-analyses currently show a positive association between pre-eclampsia and exposure to both particulate matter PM_2.5 and nitrogen dioxide, but no significant associations with ambient ozone or carbon monoxide exposure. No meta-analysis has been performed for exposure to sulfur dioxide. Variability in terms of quantification of exposure, the exposure period and co-founders among the studies makes comparisons complex. Adverse effects on trophoblast invasion and placental vascularisation, and increases in oxidative stress and anti-angiogenic factors, such as sFlt-1, in response to air pollution provide pathways by which exposure may contribute to the pathophysiology of pre-eclampsia. So far, studies have not discriminated between the early- and late-onset forms of the syndrome.

DISCUSSION

Future prospective studies using personal air pollution monitors and blood biomarkers of pre-eclampsia would strengthen the associations. Interactions between pollutants are poorly documented, and at present there is minimal informed advice available to women on the need to avoid exposure to air pollutants during pregnancy.

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

BACKGROUND

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

METHODS

Two-hundred and fifty healthy pregnant women with singleton pregnancies and 24-26 weeks of gestations participated in our study. Land use regression (LUR) models were applied to estimate the annual mean of PM1, PM2.5 and PM10 at the residential address. Traffic indicators, including proximity of women to major roads as well as total streets length in 100, 300 and 500 m buffers around the home were calculated using the street map of Sabzevar. The oral glucose tolerance test (OGTT) was used to assess glucose tolerance during pregnancy. Multiple linear regression adjusted for relevant covariates was used to estimate the association of fasting blood glucose (FBG), 1-h and 2-h post-load glucose with PMs and traffic indicators.

RESULTS

Exposure to PM1, PM2.5 and PM10 was significantly associated with higher FBG concentration. Higher total streets length in a 100 m buffer was associated with higher FBG and 1-h glucose concentrations. An interquartile range (IQR) increase in proximity to major roads was associated with a decrease of - 3.29 mg/dL (95% confidence interval (CI): - 4.35, - 2.23, P-value < 0.01) in FBG level and - 3.65 mg/dL (95% CI, - 7.01, - 0.28, P-value = 0.03) decrease in 1-h post-load glucose.

CONCLUSION

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

Climate factors and gestational diabetes mellitus risk - a systematic review

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

The Associations of Ambient Fine Particulate Matter Exposure During Pregnancy With Blood Glucose Levels and Gestational Diabetes Mellitus Risk: A Prospective Cohort Study in Wuhan, China

Investigators in previous studies have drawn inconsistent conclusions regarding the relationship between relatively low exposure to fine particulate matter (particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5)) and risk of gestational diabetes mellitus (GDM), while the association between high PM2.5 exposure and GDM risk has not been well studied. We investigated the association of high PM2.5 exposure during pregnancy with blood glucose levels and GDM risk in Chinese women. The present study was conducted from August 2013 to May 2016 among 3,967 pregnant women in the Tongji Maternal and Child Health Cohort in Wuhan, China. PM2.5 exposure during pregnancy for each participant was estimated by means of land-use regression models. An interquartile-range increase in PM2.5 exposure (33.84 μg/m3 for trimester 1 and 33.23 μg/m3 for trimester 2) was associated with 36% (95% confidence interval (CI): 1.15, 1.61) and 23% (95% CI: 1.01, 1.50) increased odds of GDM during trimester 1 and trimester 2, respectively. An interquartile-range increment of PM2.5 exposure during trimester 1 increased 1-hour and 2-hour blood glucose levels by 1.40% (95% CI: 0.42, 2.37) and 1.82% (95% CI: 0.98, 2.66), respectively. The same increment of PM2.5 exposure during trimester 2 increased fasting glucose level by 0.85% (95% CI: 0.41, 1.29). Our findings suggest that high PM2.5 exposure during pregnancy increases blood glucose levels and GDM risk in Chinese women.