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

Association of residential greenness, air pollution with adverse birth outcomes: Results from 61,762 mother‑neonatal pairs in project ELEFANT (2011-2021)

BACKGROUND

Emerging evidence has demonstrated the benefits of greenness exposure on human health, while conflicts remain unsolved in issue of adverse birth outcomes.

METHODS

Utilizing data from project ELEFANT spanning the years 2011 to 2021, we assessed residential greenness using the NDVI from MODIS data and residential PM2.5 exposure level from CHAP data. Our primary concerns were PTD, LBW, LGA, and SGA. Cox proportional hazard regression model was used to examine the association of residential greenness and air pollution exposure with risk of adverse birth outcomes. We performed mediation and modification effect analyses between greenness and air pollutant.

RESULTS

We identified 61,762 mother‑neonatal pairs in final analysis. For per 10 μg/m3 increase in PM2.5 concentration during entire pregnancy was associated with 19.8 % and 20.7 % increased risk of PTD and LGA. In contrast, we identified that an 0.1 unit increment in NDVI were associated with 24 %, 43 %, 26.5 %, and 39.5 % lower risk for PTD, LBW, LGA, and SGA, respectively. According to mediation analysis, NDVI mediated 7.70 % and 7.89 % of the associations between PM2.5 and PTD and LGA. Residential greenness could reduce the risk of PTD among mothers under 35 years old, living in rural areas, primigravidae and primiparity..

CONCLUSIONS

In summary, our results highlighted the potential of residential greenness to mitigate the risk of adverse birth outcomes, while also pointing to the adverse impact of PM2.5 on increased risk of multiple adverse birth outcomes (PTD and LGA). The significant mediation effect of NDVI emphasizes its potential as an important protective factor of PM2.5 exposure. Additionally, the identification of susceptible subgroups can inform targeted interventions to reduce adverse birth outcomes related to air pollution and lack of green spaces. Further research and understanding of these associations can contribute to better public health strategies aimed at promoting healthier pregnancies and birth outcomes.

Associations between air pollution, residential greenness, and glycated hemoglobin (HbA1c) in three prospective cohorts of U.S. adults

BACKGROUND

While studies suggest impacts of individual environmental exposures on type 2 diabetes (T2D) risk, mechanisms remain poorly characterized. Glycated hemoglobin (HbA1c) is a biomarker of glycemia and diagnostic criterion for prediabetes and T2D. We explored associations between multiple environmental exposures and HbA1c in non-diabetic adults.

METHODS

HbA1c was assessed once in 12,315 women and men in three U.S.-based prospective cohorts: the Nurses' Health Study (NHS), Nurses' Health Study II (NHSII), and Health Professionals Follow-up Study (HPFS). Residential greenness within 270 m and 1,230 m (normalized difference vegetation index, NDVI) was obtained from Landsat. Fine particulate matter (PM2.5) and nitrogen dioxide (NO2) were estimated from nationwide spatiotemporal models. Three-month and one-year averages prior to blood draw were assigned to participants' addresses. We assessed associations between single exposure, multi-exposure, and component scores from Principal Components Analysis (PCA) and HbA1c. Fully-adjusted models built on basic models of age and year at blood draw, BMI, alcohol use, and neighborhood socioeconomic status (nSES) to include diet quality, race, family history, smoking status, postmenopausal hormone use, population density, and season. We assessed interactions between environmental exposures, and effect modification by population density, nSES, and sex.

RESULTS

Based on HbA1c, 19% of participants had prediabetes. In single exposure fully-adjusted models, an IQR (0.14) higher 1-year 1,230 m NDVI was associated with a 0.27% (95% CI: 0.05%, 0.49%) lower HbA1c. In basic component score models, a SD increase in Component 1 (high loadings for 1-year NDVI) was associated with a 0.19% (95% CI: 0.04%, 0.34%) lower HbA1c. CI's crossed the null in multi-exposure and fully-adjusted component score models. There was little evidence of associations between air pollution and HbA1c, and no evidence of effect modification.

CONCLUSIONS

Among non-diabetic adults, environmental exposures were not consistently associated with HbA1c. More work is needed to elucidate biological pathways between the environment and prediabetes.

Ambient particulate matter, maternal thyroid function, and birth weight: A mediation analysis

BACKGROUND

Birth weight (BW) is an indicator of fetal growth and development. Previous studies showed inconsistent results on the association of ambient particulate matter (PM) exposure with BW, and the role of maternal thyroid function has not been clarified.

METHODS

We recruited 1711 gravidas between 2017 and 2019 in Henan, China. All participants were followed up until delivery. Daily concentrations of PM, including PM2.5 and PM10, were evaluated by using the spatial-temporal model. Maternal thyroid hormone (TH) levels were quantified by electrochemiluminescent microparticle immunoassay. Linear regression models were employed to examine the association among PM, BW, and maternal TH. Mediating effects of maternal TH interrelated with PM exposure on BW were investigated by causal mediation analyses.

RESULTS

A total of 1049 gravidas were identified. We found that per 10 µg/m3 increase in PM2.5 and PM10 were associated with a decreased BW of 9.941 g, and 7.758 g (PM2.5: 95 %CI: -18.184, -1.698; PM10: 95 %CI: -14.436, -1.080). An inverse correlation of maternal FT4 levels with BW was found, with the pooled β of -319.983 g (95 %CI: -483.216, -156.750). We found a prominent positive correlation between gestational FT4 and PM exposure (PM2.5: β = 0.004, 95 %CI: 0.001, 0.007; PM10: β = 0.003, 95 %CI: 0.000, 0.006). Mediation analysis found that FT4 levels mediated the relationship between maternal PM exposure and BW, ranging from 5.55 % to 15.86 %.

CONCLUSIONS

Maternal PM exposure may induce a reduction in newborn BW by affecting the maternal TH concentrations.

"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.

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.