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

Effect of fine particulate matter exposure on gestational diabetes mellitus risk: a retrospective cohort study

BACKGROUND

The literature on the association between fine particulate matter (PM2.5) exposure and gestational diabetes mellitus (GDM) risk has focused mainly on exposure during the first and second trimesters, and the research results are inconsistent. Therefore, this study aimed to investigate the associations between PM2.5 exposure during preconception, the first trimester and second trimester and GDM risk in pregnant women in Guangzhou.

METHODS

A retrospective cohort study of 26 354 pregnant women was conducted, estimating PM2.5, particulate matter with a diameter >10 µm (PM10), sulphur dioxide (SO2), carbon monoxide (CO) and ozone (O3) exposure during preconception and the first and second trimesters. Analyses were performed using Cox proportional hazards models and nonlinear distributed lag models.

RESULTS

The study found that exposure to PM2.5 or a combination of two pollutants (PM2.5+PM10, PM2.5+SO2, PM2.5+CO and PM2.5+O3) was found to be significantly associated with GDM risk (P < 0.05). In the second trimester, with significant interactions found for occupation and anaemia between PM2.5 and GDM. When the PM2.5 concentrations were ≥19.56, ≥25.69 and ≥23.87 μg/m3 during preconception and the first and second trimesters, respectively, the hazard ratio for GDM started to increase. The critical window for PM2.5 exposure was identified to be from 9 to 11 weeks before conception.

CONCLUSIONS

Our study results suggest that PM2.5 exposure during preconception and the first and second trimesters increases the risk of GDM, with the preconception period appearing to be the critical window for PM2.5 exposure.

Association between ambient air pollutants and short-term mortality risks during 2015-2019 in Guangzhou, China

With the development of technology and industry, the problem of global air pollution has become difficult to ignore. We investigated the association between air pollutant concentrations and daily all-cause mortality and stratified the analysis by sex, age, and season. Data for six air pollutants [fine particulate matter (PM2.5), inhalable particles (PM10), nitric dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO)] and daily mortality rates were collected from 2015 to 2019 in Guangzhou, China. A time-series study using a quasi-Poisson generalized additive model was used to examine the relationships between environmental pollutant concentrations and mortality. Mortality data for 296,939 individuals were included in the analysis. The results showed that an increase of 10 μg/m3 in the concentrations of PM2.5, PM10, SO2, O3, NO2, and CO corresponded to 0.84% [95% confidence interval (CI): 0.47, 1.21%], 0.70% (0.44, 0.96%), 3.59% (1.77, 5.43%), 0.21% (0.05, 0.36%), 1.06% (0.70, 1.41%), and 0.05% (0.02, 0.09%), respectively. The effects of the six air pollutants were more significant for male individuals than female individuals, the cool season than the warm season, and people 75 years or older than those younger than 75 years. PM2.5, PM10, SO2, and NO2 were all associated with neoplasms and circulatory and respiratory diseases. The two-pollutant models found that PM2.5, PM10, and NO2 may independently affect the risk of mortality. The results showed that exposure to PM2.5, PM10 and NO2 may increase the risk of daily all-cause excessive mortality in Guangzhou.

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

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

Does PM1 exposure during pregnancy impact the gut microbiota of mothers and neonates?

BACKGROUND

Ambient air pollutant exposure can change the composition of gut microbiota at 6-months of age, but there is no epidemiological evidence on the impacts of exposure to particulate matter with an aerodynamic diameter ≤1 μm (PM1) during pregnancy on gut microbiota in mothers and neonates. We aimed to determine if gestational PM1 exposure is associated with the gut microbiota of mothers and neonates.

METHODS

Leveraging a mother-infant cohort from the central region of China, we estimated the exposure concentrations of PM1 during pregnancy based on residential address records. The gut microbiota of mothers and neonates was analyzed using 16 S rRNA V3-V4 gene sequences. Functional pathway analyses of 16 S rRNA V3-V4 bacterial communities were conducted using Tax4fun. The impact of PM1 exposure on α-diversity, composition, and function of gut microbiota in mothers and neonates was evaluated using multiple linear regression, controlling for nitrogen dioxide (NO2) and ozone (O3). Permutation multivariate analysis of variance (PERMANOVA) was used to analyze the interpretation degree of PM1 on the sample differences at the OTU level using the Bray-Curtis distance algorithm.

RESULTS

Gestational PM1 exposure was positively associated with the α-diversity of gut microbiota in neonates and explained 14.8% (adj. P = 0.026) of the differences in community composition among neonatal samples. In contrast, gestational PM1 exposure had no impact on the α- and β-diversity of gut microbiota in mothers. Gestational PM1 exposure was positively associated with phylum Actinobacteria of gut microbiota in mothers, and genera Clostridium_sensu_stricto_1, Streptococcus, Faecalibacterium of gut microbiota in neonates. At Kyoto Encyclopedia of Genes and Genomes pathway level 3, the functional analysis results showed that gestational PM1 exposure significantly down-regulated Nitrogen metabolism in mothers, as well as Two-component system and Pyruvate metabolism in neonates. While Purine metabolism, Aminoacyl-tRNA biosynthesis, Pyrimidine metabolism, and Ribosome in neonates were significantly up-regulated.

CONCLUSIONS

Our study provides the first evidence that exposure to PM1 has a significant impact on the gut microbiota of mothers and neonates, especially on the diversity, composition, and function of neonatal meconium microbiota, which may have important significance for maternal health management in the future.

Independent and interactive effects of ozone and thermal inversion exposure on the risk of gestational diabetes mellitus in Wuhan, China

The adverse effects of exposure to thermal inversion (TI) and ozone (O3) on human health have been reported; however, there are few studies have explored the independent and potential interactive effects of them on gestational diabetes mellitus (GDM). A total of 31,262 pregnant women from the Wuhan Children's Hospital covering the period from 2017 to 2021 were included in this study. The logistic regression adjusted for the covariates was applied to explore the independent effect of exposure to O3 and TI on GDM. The relative excess risk due to the interaction (RERI) analysis was applied to assess the possible interactive effect. Per 10 μg/m3 increased in O3 (OR = 1.069, 95% CI: 1.049, 1.089) during the first trimester and per 10 days increased in TI (OR = 1.041, 95% CI: 1.005, 1.080) in the second trimester were significantly associated with the risk of GDM. The synergistic effect of exposure to TI and O3 was larger than their sum effect (RERI = 0.330, 95% CI: 0.170, 0.476). This study added further support for public health-related policy to improve maternal health by curbing TI and O3.

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.

Association of exposure to air pollutants with gestational diabetes mellitus in Chiayi City, Taiwan

INTRODUCTION

We investigated the associations of exposure to particulate matter with an aerodynamic diameter less than 2.5 μm (PM_2.5) and several gaseous pollutants with risk of gestational diabetes mellitus (GDM) in Taiwan.

METHODS

We retrospectively identified pregnant women who underwent a two-step approach to screen for GDM between 2006 and 2014. Information on concentrations of air pollutants (including PM_2.5, sulfur dioxide [SO₂], nitrogen oxides [NO_x], and ozone [O₃]) were collected from a single fixed-site monitoring station. We conducted logistic regression analyses to determine the associations between exposure to air pollutants and risk of GDM.

RESULTS

A total of 11210 women were analyzed, and 705 were diagnosed with GDM. Exposure to PM_2.5 during the second trimester was associated with a nearly 50% higher risk of GDM (odds ratio [OR] 1.47, 95% CI 0.96 to 2.24, p=0.077). The associations were consistent in the two-pollutant model (PM_2.5 + SO₂ [OR 1.73, p=0.038], PM_2.5 + NO_x [OR 1.52, p=0.064], PM_2.5 + O₃ [OR 1.96, p=0.015]), and were more prominent in women with age <30 years and body mass index <25 kg/m² (interaction p values <0.01).

DISCUSSION

Exposure to PM_2.5 was associated with risk of GDM, especially in women who were younger or had a normal body mass index.