Association of long-term exposure to PM2.5 constituents with glucose metabolism in Chinese rural population

Disturbed glucose homeostasis and its increased allostatic load in response to individual, joint and fluctuating air pollutants exposure: Evidence from a longitudinal study in prediabetes

We investigated the effect of individual, joint and fluctuating exposure to air pollution (PM2.5, BC, NO3-, NH4+, OM, SO42-, PM10, NO2, SO2, O3) on glucose metabolisms among prediabetes, and simultaneously explored the modifying effect of lifestyle. We conducted a longitudinal study among prediabetes during 2018-2022. Exposure windows within 60-days moving averages and their variabilities were calculated. FBG, insulin, HOMA-IR, HOMA-B, triglyceride glucose index (TyG), glucose insulin ratio (GI) and allostatic load of glucose homeostasis system (AL-GHS) was included. Linear mixed-effects model and BKMR were adopted to investigate the individual and overall effects, respectively. We also explored the preventive role of lifestyle. Individual air pollutant was associated with increased FBG, insulin, HOMA-IR, HOMA-B, TyG, and decreased GI. People with FBG ≥6.1 mmol/L were more susceptible. Air pollutants mixture were only associated with increased HOMA-B, and constituents have the highest group-PIP. Air pollutants variation also exert harmful effect. We observed similar diabetic effect on AL-GHS. Finally, the diabetic effect of air pollutants disappeared if participants adopt a favorable lifestyle. Our findings highlighted the importance of comprehensively assessing multiple air pollutants and their variations, focusing on metabolic health status in the early prevention of T2D, and adopting healthy lifestyle to mitigate such harmful effect.

Long-term effect of fine particulate matter constituents on reproductive hormones homeostasis in women attending assisted reproductive technologies: A population-based longitudinal study

Fine particulate matter (PM2.5) may disrupt women's reproductive hormones, posing potential reproductive risks. However, the exact compositions of PM2.5 responsible for these effects remain unclear. Our investigation explored the long-term impacts of PM2.5 constituents on reproductive hormones, based on a large longitudinal assisted reproductive cohort study in Anhui, China. We included 24,396 reproductive hormone samples from 19,845 women attending assisted reproductive technologies (ART) between 2014 and 2020. Using high-resolution gridded data (1-km resolution), we calculated the residence-specified PM2.5 constituents during the year before the month of hormone testing. Relationships between PM2.5 constituents [organic matter (OM), chloride (Cl-), sulfate (SO42-), ammonium (NH4+), black carbon, and nitrate] and reproductive hormones were investigated using the linear mixed model with subject-specific intercepts. The constituent-proportion model and the constituent-residual model were also constructed. Additionally, cubic spline analysis was used to examine the potential non-linear exposure-response relationship. We found that per interquartile range (IQR) increment in OM was associated with a 5.31 % (3.74 %, 6.89 %) increase in estradiol, and per IQR increment in Cl- and NH4+ were associated with 13.56 % (7.63 %, 19.82 %) and 9.07 % (4.35 %, 14.01 %) increases in luteinizing hormone. Conversely, per IQR increment in OM and Cl- were associated with -7.27 % (-9.34 %, -5.16 %) and -8.52 % (-10.99 %, -5.98 %) decreases in progesterone, and per IQR increment in SO42- was associated with a -9.15 % (-10.31 %, -7.98 %) decrease in testosterone. These associations were held in both proportional and residual models. Moreover, exposure-response curves for estradiol and progesterone with PM2.5 constituents exhibited approximately U-shaped. These results suggested that specific PM2.5 constituents might disrupt reproductive hormone homeostasis in women attending ART, providing new evidence for formulating PM2.5 pollution reduction strategies that could benefit women's reproductive health.

Exposure to 6-PPD quinone disrupts glucose metabolism associated with lifespan reduction by affecting insulin and AMPK signals in Caenorhabditis elegans

Glucose metabolism plays an important role for formation of normal physiological state of organisms. However, association between altered glucose metabolism and toxicity of 6-PPD quinone (6-PPDQ) remains largely unknown. In 1-100 μg/L 6-PPDQ exposed Caenorhabditis elegans, we observed increased glucose content. After 6-PPDQ exposure (1-100 μg/L), expressions of F47B8.10 and fbp-1 governing gluconeogenesis were increased, and expressions of hxk-1, hxk-3, pfk-1.1, pyk-1, and pyk-2 governing glycolysis were decreased. Under 6-PPDQ exposure condition, glucose content could be changed by RNAi of F47B8.10, hxk-1, and hxk-3, key genes for gluconeogenesis and glycolysis. In 6-PPDQ exposed nematodes, RNAi of daf-16 and aak-2 elevated glucose content, increased expressions of F47B8.10 and/or fbp-1, and decreased expressions of hxk-1, hxk-3, and/or pfk-1.1. Additionally, lifespan and locomotion during aging were increased by RNAi of F47B8.10 and decreased by RNAi of hxk-1 and hxk-3 in 6-PPDQ exposed nematodes. Moreover, after 6-PPDQ exposure, RNAi of F47B8.10 decreased expressions of insulin peptide genes (ins-7 and daf-28) and insulin receptor gene daf-2 and increased expressions of daf-16 and aak-2. In 6-PPDQ exposed nematodes, RNAi of hxk-1 and hxk-3 further increased expressions of ins-7, daf-28, and daf-2 and decreased expressions of daf-16 and aak-2. Our results demonstrated important association between altered glucose metabolism and toxicity of 6-PPDQ in inducing lifespan reduction in organisms.

Association between long-term exposure to PM2.5 chemical components and metabolic syndrome in middle-aged and older adults

Background

Previous studies indicated that exposure to ambient fine particulate matter (PM2.5) could increase the risk of metabolic syndrome (MetS). However, the specific impact of PM2.5 chemical components remains uncertain.

Methods

A national cross-sectional study of 12,846 Chinese middle-aged and older adults was conducted. Satellite-based spatiotemporal models were employed to determine the 3-year average PM2.5 components exposure, including sulfates (SO4 2-), nitrates (NO3 -), ammonia (NH4 +), black carbon (BC), and organic matter (OM). Generalized linear models were used to investigate the associations of PM2.5 components with MetS and the components of MetS, and restricted cubic splines curves were used to establish the exposure-response relationships between PM2.5 components with MetS, as well as the components of MetS.

Results

MetS risk increased by 35.1, 33.5, 33.6, 31.2, 32.4, and 31.4% for every inter-quartile range rise in PM2.5, SO4 2-, NO3 -, NH4 +, OM and BC, respectively. For MetS components, PM2.5 chemical components were associated with evaluated risks of central obesity, high blood pressure (high-BP), high fasting glucose (high-FBG), and low high-density lipoprotein cholesterol (low-HDL).

Conclusion

This study indicated that exposure to PM2.5 components is related to increased risk of MetS and its components, including central obesity, high-BP, high-FBG, and low-HDL. Moreover, we found that the adverse effect of PM2.5 chemical components on MetS was more sensitive to people who were single, divorced, or widowed than married people.

Associations of incident female breast cancer with long-term exposure to PM2.5 and its constituents: Findings from a prospective cohort study in Beijing, China

This study aimed to investigate the association between long-term exposure to fine particulate matter (PM2.5) and its constituents (black carbon (BC), ammonium (NH4+), nitrate (NO3-), organic matter (OM), inorganic sulfate (SO42-)) and incident female breast cancer in Beijing, China. Data from a prospective cohort comprising 85,504 women enrolled in the National Urban Cancer Screening Program in Beijing (2013-2019) and the Tracking Air Pollution in China dataset are used. Monthly exposures were aggregated to calculate 5-year average concentrations to indicate long-term exposure. Cox models and mixture exposure models (weighted quantile sum, quantile-based g-computation, and explanatory machine learning model) were employed to analyze the associations. Findings indicated increased levels of PM2.5 and its constituents were associated with higher breast cancer risk, with hazard ratios per 1-μg/m3 increase of 1.02 (95% confidence interval (CI): 1.01, 1.03), 1.39 (95% CI: 1.16, 1.65), 1.28 (95% CI: 1.12, 1.46), 1.15 (95% CI: 1.05, 1.24), 1.05 (95% CI: 1.02, 1.08), and 1.15 (95% CI: 1.07, 1.23) for PM2.5, BC, NH4+, NO3-, OM, and SO42-, respectively. Exposure-response curves demonstrated a monotonic risk increase without an evident threshold. Mixture exposure models highlighted BC and SO42- as key factors, underscoring the importance of reducing emissions of these pollutants.

Accelerated biological aging mediated associations of ammonium, sulfate in fine particulate matter with liver cirrhosis

BACKGROUND

Although both air pollution and aging are related to the development of liver cirrhosis, the role of biological aging in association of the mixture of fine particulate matter (PM2.5) and its constituents with liver cirrhosis was unknown.

METHODS

This case-control retrospective study included 100 liver cirrhosis patients and 100 control subjects matched by age and sex. The concentrations of PM2.5 and its constituents were estimated for patients using machine-learning methods. The clinical biomarkers were used to calculate biological age using the Klemera-Doubalmethod (KDM) algorithms. Individual associations of PM2.5 and its constituents or biological age with liver cirrhosis were analyzed by generalized linear models. WQS and BKMR were applied to analyze association of mixture of PM2.5 and its constituents with liver cirrhosis. The mediation effect of biological age on associations of PM2.5 and its constituents with liver cirrhosis was further explored.

RESULTS

we found that each 1-unit increment in NH4+, NO3-, SO42- and biological age were related to 3.618-fold (95%CI: 1.896, 6.904), 1.880-fold (95%CI: 1.319, 2.680), 2.955-fold (95%CI: 1.656, 5.272) and 1.244-fold (95%CI: 1.093, 1.414) increased liver cirrhosis. Both WQS and BKMR models showed that the mixture of PM2.5 and its constituents was related to increased liver cirrhosis. Furthermore, the mediated proportion of biological age on associations of NH4+ and SO42- with liver cirrhosis were 14.7 % and 14.6 %, respectively.

CONCLUSIONS

Biological aging may partly explain the exposure to PM2.5 and its constituents in association with increased risk for liver cirrhosis, implying that delaying the aging process may be a key step for preventing PM2.5-related liver cirrhosis risk.

PM2.5, component cause of severe metabolically abnormal obesity: An in silico, observational and analytical study

Obesity is currently one of the most alarming pathological conditions due to the progressive increase in its prevalence. In the last decade, it has been associated with fine particulate matter suspended in the air (PM2.5). The purpose of this study was to explore the mechanistic interaction of PM2.5 with a high-fat diet (HFD) through the differential regulation of transcriptional signatures, aiming to identify the association of these particles with metabolically abnormal obesity. The research design was observational, using bioinformatic methods and an explanatory approach based on Rothman's causal model. We propose three new transcriptional signatures in murine adipose tissue. The sum of transcriptional differences between the group exposed to an HFD and PM2.5, compared to the control group, were 0.851, 0.265, and -0.047 (p > 0.05). The HFD group increased body mass by 20% with two positive biomarkers of metabolic impact. The group exposed to PM2.5 maintained a similar weight to the control group but exhibited three positive biomarkers. Enriched biological pathways (p < 0.05) included PPAR signaling, small molecule transport, adipogenesis genes, cytokine-cytokine receptor interaction, and HIF-1 signaling. Transcriptional regulation predictions revealed CpG islands and common transcription factors. We propose three new transcriptional signatures: FAT-PM2.5-CEJUS, FAT-PM2.5-UP, and FAT-PM2.5-DN, whose transcriptional regulation profile in adipocytes was statistically similar by dietary intake and HFD and exposure to PM2.5 in mice; suggesting a mechanistic interaction between both factors. However, HFD-exposed murines developed moderate metabolically abnormal obesity, and PM2.5-exposed murines developed severe abnormal metabolism without obesity. Therefore, in Rothman's terms, it is concluded that HFD is a sufficient cause of the development of obesity, and PM2.5 is a component cause of severe abnormal metabolism of obesity. These signatures would be integrated into a systemic biological process that would induce transcriptional regulation in trans, activating obesogenic biological pathways, restricting lipid mobilization pathways, decreasing adaptive thermogenesis and angiogenesis, and altering vascular tone thus inducing a severe metabolically abnormal obesity.

Long-term exposure to fine particulate matter constituents in relation to chronic kidney disease: evidence from a large population-based study in China

The effects of long-term exposure to fine particulate matter (PM2.5) constituents on chronic kidney disease (CKD) are not fully known. This study sought to examine the association between long-term exposure to major PM2.5 constituents and CKD and look for potential constituents contributing substantially to CKD. This study included 81,137 adults from the 2018 to 2019 baseline survey of China Multi-Ethnic Cohort. CKD was defined by the estimated glomerular filtration rate. Exposure concentration data of 7 major PM2.5 constituents were assessed by satellite remote sensing. Logistic regression models were used to estimate the effect of each PM2.5 constituent exposure on CKD. The weighted quantile sum regression was used to estimate the effect of mixed exposure to all constituents. PM2.5 constituents had positive correlations with CKD (per standard deviation increase), with ORs (95% CIs) of 1.20 (1.02-1.41) for black carbon, 1.27 (1.07-1.51) for ammonium, 1.29 (1.08-1.55) for nitrate, 1.20 (1.01-1.43) for organic matter, 1.25 (1.06-1.46) for sulfate, 1.30 (1.11-1.54) for soil particles, and 1.63 (1.39-1.91) for sea salt. Mixed exposure to all constituents was positively associated with CKD (1.68, 1.32-2.11). Sea salt was the constituent with the largest weight (0.36), which suggested its importance in the PM2.5-CKD association, followed by nitrate (0.32), organic matter (0.18), soil particles (0.10), ammonium (0.03), BC (0.01). Sulfate had the least weight (< 0.01). Long-term exposure to PM2.5 sea salt and nitrate may contribute more than other constituents in increasing CKD risk, providing new evidence and insights for PM2.5-CKD mechanism research and air pollution control strategy.

Green space and its types can attenuate the associations of PM2.5 and its components with prediabetes and diabetes-- a multicenter cross-sectional study from eastern China

BACKGROUND

The effect of fine particulate matter (PM2.5) components on prediabetes and diabetes is of concern, but the evidence is limited and the specific role of different green space types remains unclear. This study aims to investigate the relationship of PM2.5 and its components with prediabetes and diabetes as well as the potential health benefits of different types and combinations of green spaces.

METHODS

A multicenter cross-sectional study was conducted in eastern China by using a multi-stage random sampling method. Health screening and questionnaires for 98,091 participants were performed during 2017-2020. PM2.5 and its five components were estimated by the inverse distance weighted method, and green space was reflected by the Normalized Difference Vegetation Index (NDVI), percentages of tree or grass cover. Multivariate logistic regression and quantile g-computing were used to explore the associations of PM2.5 and five components with prediabetes and diabetes and to elucidate the potential moderating role of green space and corresponding type combinations in these associations.

RESULTS

Each interquartile range (IQR) increment of PM2.5 was associated with both prediabetes (odds ratio [OR]: 1.15, 95%CI [confidence interval]: 1.10-1.20) and diabetes (OR: 1.18, 95% CI: 1.11-1.25), respectively. All five components of PM2.5 were related to prediabetes and diabetes. The ORs of PM2.5 on diabetes were 1.49 (1.35-1.63) in the low tree group and 0.90 (0.82-0.98) in the high tree group, respectively. In the high tree-high grass group, the harmful impacts of PM2.5 and five components were significantly lower than in the other groups.

CONCLUSION

Our study suggested that PM2.5 and its components were associated with the increased risk of prediabetes and diabetes, which could be diminished by green space. Furthermore, the coexistence of high levels of tree and grass cover provided greater benefits. These findings had critical implications for diabetes prevention and green space-based planning for healthy city.

Associations of Long-Term Exposure to PM2.5 and Its Constituents with Erythrocytosis and Thrombocytosis in Rural Populations

Evidence on the effect of long-term exposure to fine particulate matter (PM2.5) on erythrocytosis and thrombocytosis prevalence was limited. We aimed to investigate the association of PM2.5 and its constituents with the risks of erythrocytosis and thrombocytosis. The present study included a total of 33,585 participants from the Henan Rural Cohort at baseline between 2015 and 2017. A hybrid satellite-based model was employed to estimate the concentrations of PM2.5 mass and its constituents (including black carbon [BC], nitrate [NO3-], ammonium [NH4+], inorganic sulfate [SO42-], organic matter [OM], and soil particles [SOIL]). The logistic regression model was used to assess the associations of single exposure to PM2.5 and its constituents with the risks of erythrocytosis and thrombocytosis, and the quantile G-computation method was applied to evaluate their joint exposure risk. For the independent association, the odds ratios for erythrocytosis/thrombocytosis with 1 μg/m3 increase was 1.049/1.043 for PM2.5 mass, 1.596/1.610 for BC, 1.410/1.231 for NH4+, 1.205/1.139 for NO3-, 1.221/1.359 for OM, 1.300/1.143 for SO42-, and 1.197/1.313 for SOIL. Joint exposure to PM2.5 and its components was also positively associated with erythrocytosis and thrombocytosis. The estimated weight of NH4+ was found to be the largest for erythrocytosis, while OM had the largest weight for thrombocytosis. PM2.5 mass and its constituents were positively linked to prevalent erythrocytosis and thrombocytosis, both in single-exposure and joint-exposure models. Additionally, NH4+/OM was identified as a potentially responsible component for the association between PM2.5 and erythrocytosis/thrombocytosis.

Residential greenness and cardiac conduction abnormalities: epidemiological evidence and an explainable machine learning modeling study

BACKGROUND

Previous studies indicated the beneficial influence of residential greenness on cardiovascular disease (CVD), however, the association of residential greenness with cardiac conduction performance remains unclear. This study aims to examine the epidemiological associations between residential greenness and cardiac conduction abnormalities in rural residents, simultaneously exploring the role of residential greenness for cardiac health in an explainable machine learning modeling study.

METHODS

A total of 27,294 participants were derived from the Henan Rural Cohort. Two satellite-based indices, the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI), were used to estimate residential greenness. Independent and combined associations of residential greenness indices and physical activities with electrocardiogram (ECG) parameter abnormalities were evaluated using the logistic regression model and generalized linear model. The Gradient Boosting Machine (GBM) and the SHapely Additive exPlanations (SHAP) were employed in the modeling study.

RESULTS

The odds ratios (OR) and 95% confidence interval (CI) for QRS interval, heart rate (HR), QTc interval, and PR interval abnormalities with per interquartile range in NDVI were 0.896 (0.873-0.920), 0.955 (0.926-0.986), 1.015 (0.984-1.047), and 0.986 (0.929-1.045), respectively. Furthermore, the participants with higher physical activities plus residential greenness (assessed by EVI) were related to a 1.049-fold (1.017-1.081) and 1.298-fold (1.245-1.354) decreased risk for abnormal QRS interval and HR. Similar results were also observed in the sensitivity analysis. The NDVI ranked fifth (SHAP mean value 0.116) in the analysis for QRS interval abnormality risk in the modeling study.

CONCLUSION

A higher level of residential greenness was significantly associated with cardiac conduction abnormalities. This effect might be strengthened in residents with more physical activities. This study indicated the cruciality of environmental greenness to cardiac functions and also contributed to refining preventive medicine and greenness design strategies.

Association of Fine Particulate Matter Constituents with the Predicted 10-Year Atherosclerotic Cardiovascular Disease Risk: Evidence from a Large-Scale Cross-Sectional Study

Little is known concerning the associations of fine particulate matter (PM2.5) and its constituents with atherosclerotic cardiovascular disease (ASCVD). A total of 31,162 participants enrolled from the Henan Rural Cohort were used to specify associations of PM2.5 and its constituents with ASCVD. Hybrid machine learning was utilized to estimate the 3-year average concentration of PM2.5 and its constituents (black carbon [BC], nitrate [NO3-], ammonium [NH4+], inorganic sulfate [SO42-], organic matter [OM], and soil particles [SOIL]). Constituent concentration, proportion, and residual models were utilized to examine the associations of PM2.5 constituents with 10-year ASCVD risk and to identify the most hazardous constituent. The isochronous substitution model (ISM) was employed to analyze the substitution effect between PM2.5 constituents. We found that each 1 μg/m3 increase in PM2.5, BC, NH4+, NO3-, OM, SO42-, and SOIL was associated with a 3.5%, 49.3%, 19.4%, 10.5%, 21.4%, 14%, and 28.5% higher 10-year ASCVD risk, respectively (all p < 0.05). Comparable results were observed in proportion and residual models. The ISM found that replacing BC with other constituents will generate the greatest health benefits. The results indicated that long-term exposure to PM2.5 and its constituents were associated with increased risks of ASCVD, with BC being the most attributable constituent.

Independent risk evaluation associated with short-term black carbon exposure on mortality in two megacities of Yangtze River Delta, China

The adverse health effects of PM_2.5 have been well demonstrated by many studies. However, as a component of PM_2.5, evidence on the mortality risk of black carbon (BC) is still limited. In this study, based on the data of daily mean PM_2.5 concentration, BC concentration, meteorological factors, total non-accidental (all-cause) and cardiovascular mortality in Shanghai and Nanjing during 2015-2016, a semi-parameter generalized additive model (GAM) in the time series and the constituent residual approach were employed to explore the exposure-response relationship between BC and human mortality in these two megacities of Yangtze River Delta, China. The main objective was to separate the health effects of BC from total PM_2.5, and compare the difference of mortality ER related to BC original concentration and adjusted concentration after controlling PM_2.5. Results showed that there were all significantly associated with daily mortality for PM_2.5 and BC. The percentage excess risk (ER) increases in all-cause and cardiovascular categories were 1.68 % (95 % s 1.28, 2.08) and 2.16 % (95 % CI: 1.54, 2.79) with 1 μg/m³ increment in original BC concentration in Shanghai. And the ER in Nanjing was smaller than that in Shanghai. After eliminating PM_2.5 confounding effects by a constituent residual approach, the BC residual concentration still had a strong significant ER. The ER for BC residual in Shanghai got an obvious increase, and ER of the cardiovascular mortality for all, females and males increased by 0.55 %, 1.46 % and 0.62 %, respectively, while the ER in Nanjing decreased slightly. It also revealed that females were more sensitive to the health risk associated with short-term BC exposure than males. Our findings provide additional important evidence and ER for mortality related to independent BC exposure. Therefore, BC emission reduction should be paid more attention in air pollution control strategies to reduce BC-related health burdens.