Particulate Matter Air Pollution Research Articles

Causal relationship between particulate matter and COVID-19 risk: A mendelian randomization study

BackgroundObservational studies have linked exposure to fine (PM2.5) and coarse (PM10) particulate matter air pollution with adverse COVID-19 outcomes, including higher incidence and mortality. However, some studies questioned the effect of air pollution on COVID-19 susceptibility, raising questions about the causal nature of these associations. To address this, a less biased method like Mendelian randomization (MR) is utilized, which employs genetic variants as instrumental variables to infer causal relationships in observational data. MethodWe performed two-sample MR analysis using public genome-wide association studies data. Instrumental variables correlated with PM2.5 concentration, PM2.5 absorbance, PM2.5-10 concentration and PM10 concentration were identified. The inverse variance weighted (IVW), robust adjusted profile score (RAPS) and generalized summary data-based Mendelian randomization (GSMR) methods were used for analysis. ResultsIVW MR analysis showed PM2.5 concentration [odd ratio (OR) = 3.29, 95% confidence interval (CI) 1.48–7.35, P-value = 0.0036], PM2.5 absorbance (OR = 5.62, 95%CI 1.98–15.94, P-value = 0.0012), and PM10 concentration (OR = 3.74, 95%CI 1.52–9.20, P-value = 0.0041) increased the risk of COVID-19 severity after Bonferroni correction. Further validation confirmed PM2.5 absorbance was associated with heightened COVID-19 severity (OR = 6.05, 95%CI 1.99–18.38, P-value = 0.0015 for RAPS method; OR = 4.91, 95%CI 1.65–14.59, P-value = 0.0042 for GSMR method) and hospitalization (OR = 3.15, 95%CI 1.54–6.47, P-value = 0.0018 for RAPS method). No causal links were observed between particulate matter exposure and COVID-19 susceptibility. ConclusionsOur study established a causal relationship between smaller particle pollution, specifically PM2.5, and increased risk of COVID-19 severity and hospitalization. These findings highlight the importance of improving air quality to mitigate respiratory disease progression.

TEMPORAL ANALYSIS AND PREDICTIVE MODELING OF AMBIENT AIR QUALITY IN HULU LANGAT DISTRICT, SELANGOR, MALAYSIA: A CHEMOMETRIC APPROACH

One of the most important environmental problems facing the globe today is air pollution. The centre area for the local populace is the Hulu Langat district, which borders Kuala Lumpur, the capital. The purpose of this study is to look at how the ambient air quality varies in Hulu Langat, Selangor. The Air Quality Division of the Malaysian Department of Environment provided five years' worth of secondary data on the air quality at Hulu Langat. The database included five primary air pollutant characteristics sulphur dioxide (SO2), carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), and particulate matter with a diameter of 10 microns or less (PM10), in addition to data from the Air Pollutant Index (API). Chemometric analysis was used to examine the results. According to the results, SO2, NO2 and PM10 had the greatest correlations with API readings. A statistical process known as statistical control (SPC) showed that certain PM10 values were over national recommendations and control limits. The artificial neural network method's air quality prediction model demonstrated good accuracy with real data (R2 = 0.9). The results of this investigation indicated a strong correlation between the Hulu Langat air quality data. In order to achieve sustainable environmental practices in the future, it is imperative to engage in extensive collaboration across environmental departments and relevant authorities and engage in continuous monitoring of air quality.

Leading determinants of incident dementia among individuals with and without the apolipoprotein E ε4 genotype: a retrospective cohort study

BackgroundLittle is known regarding the leading risk factors for dementia/Alzheimer’s disease (AD) in individuals with and without APOE4. The identification of key risk factors for dementia/Alzheimer’s disease (AD) in individuals with and without the APOE4 gene is of significant importance in global health.MethodsOur analysis included 110,354 APOE4 carriers and 220,708 age- and sex-matched controls aged 40–73 years at baseline (between 2006–2010) from UK Biobank. Incident dementia was ascertained using hospital inpatient, or death records until January 2021. Individuals of non-European ancestry were excluded. Furthermore, individuals without medical record linkage were excluded from the analysis. Moderation analysis was tested for 134 individual factors.ResultsDuring a median follow-up of 11.9 years, 4,764 cases of incident all-cause dementia and 2065 incident AD cases were documented. Hazard ratios (95% CIs) for all-cause dementia and AD associated with APOE4 were 2.70(2.55–2.85) and 3.72(3.40–4.07), respectively. In APOE4 carriers, the leading risk factors for all-cause dementia included low self-rated overall health, low household income, high multimorbidity risk score, long-term illness, high neutrophil percentage, and high nitrogen dioxide air pollution. In non-APOE4 carriers, the leading risk factors included high multimorbidity risk score, low overall self-rated health, low household income, long-term illness, high microalbumin in urine, high neutrophil count, and low greenspace percentage. Population attributable risk for these individual risk factors combined was 65.1%, and 85.8% in APOE4 and non-APOE4 carriers, respectively. For 20 risk factors including multimorbidity risk score, unhealthy lifestyle habits, and particulate matter air pollutants, their associations with incident dementia were stronger in non-APOE4 carriers. For only 2 risk factors (mother’s history of dementia, low C-reactive protein), their associations with incident all-cause dementia were stronger in APOE4 carriers.ConclusionsOur findings provide evidence for personalized preventative approaches to dementia/AD in APOE4 and non-APOE4 carriers. A mother’s history of dementia and low levels of C-reactive protein were more important risk factors of dementia in APOE4 carriers whereas leading risk factors including unhealthy lifestyle habits, multimorbidity risk score, inflammation and immune-related markers were more predictive of dementia in non-APOE4 carriers.

Ambient particulate matter and surrounding greenness in relation to sleep quality among pregnant women: A nationwide cohort study

BackgroundParticulate air pollution and residential greenness are associated with sleep quality in the general population; however, their influence on maternal sleep quality during pregnancy has not been assessed. ObjectiveThis cross-sectional study investigated the individual and interactive effects of exposure to particulate matter (PM) air pollution and residential greenness on sleep quality in pregnant women. MethodsPregnant women (n = 4933) enrolled in the Korean Children's Environmental Health Study with sleep quality information and residential address were included. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). The average concentrations of PM (PM2.5 and PM10) during pregnancy were estimated through land use regression, and residential greenness in a 1000 m buffer area around participants' residences was estimated using the Normalized Difference Vegetation Index (NDVI1000-m). Modified Poisson regression models were used to estimate the associations between PM and NDVI and poor sleep quality (PSQI >5) after controlling for a range of covariates. A four-way mediation analysis was conducted to examine the mediating effects of PM. ResultsAfter adjusting for confounders, each 10 μg/m3 increase in PM2.5 and PM10 exposure was associated with a higher risk of poor sleep quality (relative risk [RR]: 1.06; 95% confidence interval [CI]: 1.01, 1.11; and RR: 1.09; 95% CI: 1.06, 1.13, respectively), and each 0.1-unit increase in NDVI1000-m was associated with a lower risk of poor sleep quality (RR: 0.97; 95% CI: 0.95, 0.99). Mediation analysis showed that PM mediated approximately 37%–56% of the association between residential greenness and poor sleep quality. ConclusionsThis study identified a positive association between residential greenness and sleep quality. Furthermore, these associations are mediated by a reduction in exposure to particulate air pollution and highlight the link between green areas, air pollution control, and human health.

Time-stratified case-crossover studies for aggregated data in environmental epidemiology: a tutorial.

The case-crossover design is widely used in environmental epidemiology as an effective alternative to the conventional time-series regression design to estimate short-term associations of environmental exposures with a range of acute events. This tutorial illustrates the implementation of the time-stratified case-crossover design to study aggregated health outcomes and environmental exposures, such as particulate matter air pollution, focusing on adjusting covariates and investigating effect modification using conditional Poisson regression. Time-varying confounders can be adjusted directly in the conditional regression model accounting for the adequate lagged exposure-response function. Time-invariant covariates at the subpopulation level require reshaping the typical time-series data set into a long format and conditioning out the covariate in the expanded stratum set. When environmental exposure data are available at geographical units, the stratum set should combine time and spatial dimensions. Moreover, it is possible to examine effect modification using interaction models. The time-stratified case-crossover design offers a flexible framework to properly account for a wide range of covariates in environmental epidemiology studies.

Global Burden of Lung Cancer Attributable to Household Fine Particulate Matter Pollution in 204 Countries and Territories, 1990 to 2019

IntroductionHousehold particulate matter (PM) air pollution is substantially associated with lung cancer. Nevertheless, the global burden of lung cancer attributable to household PM2.5 is still uncertain. MethodsIn this study, data from the Global Burden and Disease Study 2019 are used to thoroughly assess the burden of lung cancer associated with household PM2.5. ResultsThe number of deaths and disability-adjusted life-years (DALYs) attributable to household PM2.5 was found to be 0.08 million and 1.94 million, respectively in 2019. Nevertheless, the burden of lung cancer attributable to household PM2.5 decreased from 1990 to 2019. At the sociodemographic index (SDI) district level, the middle SDI region had the most number of lung cancer deaths and DALYs attributable to household PM2.5. Moreover, the burden of lung cancer was mainly distributed in low-SDI regions, such as Sub-Saharan Africa. Conversely, in high-SDI regions, the age-standardized mortality rate and age-standardized DALY rate of lung cancer attributable to household PM2.5 exhibit the most rapid declines. The burden of lung cancer attributable to household PM2.5 is heavier for men than for women. The sex difference is more obvious in the elderly. ConclusionsThe prevalence of lung cancer attributable to household PM2.5 has exhibited a declining trend from 1990 to 2019 owing to a concurrent decline in household PM2.5 exposure.

Microglial TLR4 Mediates White Matter Injury in a Combined Model of Diesel Exhaust Exposure and Cerebral Hypoperfusion.

Air pollution particulate matter exposure and chronic cerebral hypoperfusion (CCH) contribute to white matter toxicity through shared mechanisms of neuroinflammation, oxidative stress, and myelin breakdown. Prior studies showed that exposure of mice to joint particulate matter and CCH caused supra-additive injury to corpus callosum white matter. This study examines the role of TLR4 (toll-like receptor 4) signaling in mediating neurotoxicity and myelin damage observed in joint particulate matter and CCH exposures. Experiments utilized a novel murine model of inducible monocyte/microglia-specific TLR4 knockout (i-mTLR4-ko). Bilateral carotid artery stenosis (BCAS) was induced surgically to model CCH. TLR4-intact (control) and i-mTLR4-ko mice were exposed to 8 weeks of either aerosolized diesel exhaust particulate (DEP) or filtered air (FA) in 8 experimental groups: (1) control/FA (n=10), (2) control/DEP (n=10), (3) control/FA+BCAS (n=9), (4) control/DEP+BCAS (n=10), (5) i-mTLR4-ko/FA (n=9), (6) i-mTLR4-ko/DEP (n=8), (7) i-mTLR4-ko/FA+BCAS (n=8), and (8) i-mTLR4-ko/DEP+BCAS (n=10). Corpus callosum levels of 4-hydroxynonenal, 8-Oxo-2'-deoxyguanosine, Iba-1 (ionized calcium-binding adapter molecule 1), and dMBP (degraded myelin basic protein) were assayed via immunofluorescence to measure oxidative stress, neuroinflammation, and myelin breakdown, respectively. Compared with control/FA mice, control/DEP+BCAS mice exhibited increased dMBP (41%; P<0.01), Iba-1 (51%; P<0.0001), 4-hydroxynonenal (100%; P<0.0001), and 8-Oxo-2'-deoxyguanosine (65%; P<0.05). I-mTLR4 knockout attenuated responses to DEP/BCAS for all markers. i-mTLR4-ko markedly reduced neuroinflammation and oxidative stress and attenuated white matter degradation following DEP and CCH exposures. This suggests a potential role for targeting TLR4 signaling in individuals with vascular cognitive impairment, particularly those exposed to substantial ambient air pollution.

Penalized distributed lag interaction model: Air pollution, birth weight, and neighborhood vulnerability

AbstractMaternal exposure to air pollution during pregnancy has a substantial public health impact. Epidemiological evidence supports an association between maternal exposure to air pollution and low birth weight. A popular method to estimate this association while identifying windows of susceptibility is a distributed lag model (DLM), which regresses an outcome onto exposure history observed at multiple time points. However, the standard DLM framework does not allow for modification of the association between repeated measures of exposure and the outcome. We propose a distributed lag interaction model that allows modification of the exposure‐time‐response associations across individuals by including an interaction between a continuous modifying variable and the exposure history. Our model framework is an extension of a standard DLM that uses a cross‐basis, or bi‐dimensional function space, to simultaneously describe both the modification of the exposure‐response relationship and the temporal structure of the exposure data. Through simulations, we showed that our model with penalization out‐performs a standard DLM when the true exposure‐time‐response associations vary by a continuous variable. Using a Colorado, USA birth cohort, we estimated the association between birth weight and ambient fine particulate matter air pollution modified by an area‐level metric of health and social adversities from Colorado EnviroScreen.

Particulate Matter Emission and Air Pollution Reduction by Applying Variable Systems in Tribologically Optimized Diesel Engines for Vehicles in Road Traffic

Regardless of the increasingly intensive application of vehicles with electric drives, internal combustion engines are still dominant as power units of mobile systems in various sectors of the economy. In order to reduce the emission of exhaust gases and satisfy legal regulations, as a temporary solution, hybrid drives with optimized internal combustion engines and their associated systems are increasingly being used. Application of the variable compression ratio and diesel fuel injection timing, as well as the tribological optimization of parts, contribute to the reduction in fuel consumption, partly due to the reduction in mechanical losses, which, according to test results, also results in the reduction in emissions. This manuscript presents the results of diesel engine testing on a test bench in laboratory conditions at different operating modes (compression ratio, fuel injection timing, engine speed, and load), which were processed using a zero-dimensional model of the combustion process. The test results should contribute to the optimization of the combustion process from the aspect of minimal particulate matter emission. As a special contribution, the results of tribological tests of materials for strengthening the sliding surface of the aluminum alloy piston and cylinder of the internal combustion engine and air compressors, which were obtained using a tribometer, are presented. In this way, tribological optimization should also contribute to the reduction in particulate matter emissions due to the reduction in fuel consumption, and thus emissions due to the reduction in friction, as well as the recorded reduction in the wear of materials that are in sliding contact. In this way, it contributes to the reduction in harmful gases in the air.

Reductions in premature deaths from heat and particulate matter air pollution in South Asia, China, and the United States under decarbonization

Following a sustainable development pathway designed to keep warming below 2 °C will benefit human health. We quantify premature deaths attributable to fine particulate matter (PM2.5) air pollution and heat exposures for China, South Asia, and the United States using projections from multiple climate models under high- and low-emission scenarios. Projected changes in premature deaths are typically dominated by population aging, primarily reflecting increased longevity leading to greater sensitivity to environmental risks. Changes in PM2.5 exposure typically have small impacts on premature deaths under a high-emission scenario but provide substantial benefits under a low-emission scenario. PM2.5-attributable deaths increase in South Asia throughout the century under both scenarios but shift to decreases by late century in China, and US values decrease throughout the century. In contrast, heat exposure increases under both scenarios and combines with population aging to drive projected increases in deaths in all countries. Despite population aging, combined PM2.5- and heat-related deaths decrease under the low-emission scenario by ~2.4 million per year by midcentury and ~2.9 million by century's end, with ~3% and ~21% of these reductions from heat, respectively. Intermodel variations in exposure projections generally lead to uncertainties of <40% except for US and China heat impacts. Health benefits of low emissions are larger from reduced heat exposure than improved air quality by the late 2090s in the United States. In contrast, in South and East Asia, the PM2.5-related benefits are largest throughout the century, and their valuation exceeds the cost of decarbonization, especially in China, over the next 30 y.

Analyzing COVID-19 and Air Pollution Effects on Pediatric Asthma Emergency Room Visits in Taiwan.

(1) Background: An asthma exacerbation that is not relieved with medication typically requires an emergency room visit (ERV). The coronavirus disease 2019 (COVID-19) pandemic began in Taiwan in January of 2020. The influence of the COVID-19 pandemic on pediatric ERVs in Taiwan was limited. Our aim was to survey pediatric asthma ERVs in the COVID-19 era; (2) Methods: Data were collected from the health quality database of the Taiwanese National Health Insurance Administration from 2019 to 2021. Air pollution and climatic factors in Taipei were used to evaluate these relationships. Changes in the rates of pediatric asthma ERVs were assessed using logistic regression analysis. Poisson regression was used to evaluate the impact of air pollution and climate change; (3) Results: The rate of pediatric asthma ERVs declined in different areas and at different hospital levels including medical centers, regional and local hospitals. Some air pollutants (particulate matter ≤ 2.5 µm, particulate matter ≤ 10 µm, nitrogen dioxide, and carbon monoxide) reduced during the COVID-19 lockdown. Ozone increased the relative risk (RR) of pediatric asthma ERVs during the COVID-19 period by 1.094 (95% CI: 1.095-1.12) per 1 ppb increase; (4) Conclusions: The rate of pediatric asthma ERVs declined during the COVID-19 pandemic and ozone has harmful effects. Based on these results, the government could reduce the number of pediatric asthma ERVs through healthcare programs, thereby promoting children's health.

Air Pollution: A Challenge to Public Health and Healthcare Systems

Air Pollution: A Challenge to Public Health and Healthcare Systems

Light-Duty Vehicle Brake Emission Factors

Particulate Matter (PM) air pollution has been linked to major adverse health effects. Road transport still contributes significantly to ambient PM concentrations, but mainly due to the non-exhaust emissions from vehicles. For the first time worldwide, limits for non-exhaust emissions have been proposed by the European Union for the upcoming Euro 7 step. For these reasons, interest in brake emissions has increased in the past few years. Realistic emission factors are necessary to accurately calculate the contribution of brake emissions to air pollution but also to estimate the emissions reduction potential of new or existing technologies and improved brake formulations. This paper reviews emission factors from light-duty vehicles reported in the literature, with a focus on those that followed the recently introduced Global Technical Regulation (GTR 24) methodology on brakes in light-duty vehicles. Reduction efficiencies of non-asbestos organic (NAO) pads, brake dust filters, ceramic discs, coated discs, and regenerative braking are also discussed. Finally, the emission factors are compared with roadside measurements of brake emissions and emission inventories worldwide. The findings of this study can be used as an input in emission inventories to estimate the contribution of brakes to air pollution.

Emerging Stroke Risk Factors: A Focus on Infectious and Environmental Determinants.

This review focuses on emerging risk factors for stroke, including air pollution and climate change, gut microbiota, high altitude, and systemic infection. Up to 14% of all stroke-associated mortality is attributed to air pollution and is more pronounced in developing countries. Fine particulate matter and other air pollutants contribute to an increased stroke risk, and this risk appears to increase with higher levels and duration of exposure. Short term air pollution exposure has also been reported to increase the stroke risk. The gut microbiota is a complex ecosystem of bacteria and other microorganisms that reside in the digestive system and affect multiple body systems. Disruptions in the gut microbiota may contribute to stroke development, possibly by promoting inflammation and atherosclerosis. High altitudes have been associated with erythrocytosis and cerebrovascular sinus thrombosis, but several studies have reported an increased risk of thrombosis and ischemic stroke at high altitudes, typically above 3000 m. Systemic infection, particularly infections caused by viruses and bacteria, can also increase the risk of stroke. The risk seems to be greatest in the days to weeks following the infection, and the pathophysiology is complex. All these emerging risk factors are modifiable, and interventions to address them could potentially reduce stroke incidence.

Multipollutant reciprocal neurological hazard from smoke particulate matter and heavy metals cadmium and lead in brain nerve terminals

Heavy metals, Cd2+ and Pb2+, and carbonaceous air pollution particulate matter are hazardous neurotoxicants. Here, a capability of water-suspended smoke particulate matter preparations obtained from poplar wood (WPs) and polypropylene fibers (medical facemasks) (MPs) to influence Cd2+/Pb2+-induced neurotoxicity, and vice versa, was monitored using biological system, i.e. isolated presynaptic rat cortex nerve terminals. Combined application of Pb2+ and WPs/MPs to nerve terminals in an acute manner revealed that smoke preparations did not change a Pb2+-induced increase in the extracellular levels of excitatory neurotransmitter L-[14C]glutamate and inhibitory one [3H]GABA, thereby demonstrating additive result and no interference of neurotoxic effects of Pb2+ and particulate matter. Whereas, both smoke preparations decreased a Cd2+-induced increase in the extracellular level of L-[14C]glutamate and [3H]GABA in nerve terminals. In fluorimetric measurements, the metals and smoke preparations demonstrated additive effects on the membrane potential of nerve terminals causing membrane depolarisation. WPs/MPs-induced reduction of spontaneous ROS generation was mitigated by Cd2+ and Pb2+. Therefore, a potential variety of multipollutant heavy metal-/airborne particulate-induced effects on key presynaptic processes was revealed. Multipollutant reciprocal neurological hazard through disturbance of the excitation-inhibition balance, membrane potential and ROS generation was evidenced. This multipollutant approach and data contribute to up-to-date environmental quality/health risk estimation.

Boosted income, busted environment: a tradeoff in the wider economic impacts of transport corridor investments?

AbstractThe literature on the impacts of transport corridors points to a tradeoff between income and environmental quality. We estimate the impacts of India's Golden Quadrilateral and North-South-East-West highways on income and environmental quality to test this tradeoff hypothesis. Applying the difference-in-difference method to district level data, we find that the highways increased both local income and particulate matter air pollution. The estimated increase in air pollution is robust to using an instrumental variables approach, while that in income is not. Examining heterogeneity in these impacts, we find that the income–environment tradeoff was less steep in districts with initially higher educational attainment rates because they experienced a smaller increase in air pollution due to the highways.

The Impact of PM2.5 on Radiation-induced Pneumonitis in Patients With Breast Cancer.

Exposure to particulate matter (PM) air pollution is known to adversely affect respiratory disease, but no study has examined its effect on radiation-induced pneumonitis (RIP) in patients with breast cancer. We conducted a retrospective review of 2,736 patients with breast cancer who received postoperative radiation therapy (RT) between 2017 and 2020 in a single institution. The distance between the PM measurement station and our institution was only 3.43 km. PM data, including PM2.5 and PM10, were retrieved from the open dataset in the official government database. Overall incidence rate of RIP was 1.74%. After adjusting for age, RT technique, regional irradiation, fractionation and boost, the average value of PM2.5 was significantly associated with a higher risk of RIP (p=0.047) when patients received ≥20 fractions of RT. Specifically, PM2.5 ≥35 (μg/m3) showed a significantly higher risk of RIP (p=0.019) in patients with ≥20 fractions of RT. This is the first study to reveal the association between PM2.5 and RIP in patients with breast cancer who received 20 fractions or more of postoperative RT. We demonstrated that high PM2.5 levels around the RT institution were associated with RIP, suggesting that reducing PM air pollution may be a modifiable risk factor.

Real-World Effectiveness of Portable Air Cleaners in Reducing Home Particulate Matter Concentrations.

Portable air cleaners (PACs) equipped with HEPA filters are gaining attention as cost-effective means of decreasing indoor particulate matter (PM) air pollutants and airborne viruses. However, the performance of PACs in naturalistic settings and spaces beyond the room containing the PAC is not well characterized. We conducted a single-blinded randomized cross-over interventional study between November 2020 and May 2021 in the homes of adults who tested positive for COVID-19. The intervention was air filtration with PAC operated with the HEPA filter set installed ("filter" condition) versus removed ("sham" condition, i.e., control). Sampling was performed in 29 homes for two consecutive 24-hour periods in the primary room (containing the PAC) and a secondary room. PAC effectiveness, calculated as reductions in overall mean PM2.5 and PM10 concentrations during the filter condition, were for the primary rooms 78.8% and 63.9% (n = 23), respectively, and for the secondary rooms 57.9% and 60.4% (n = 22), respectively. When a central air handler (CAH) was reported to be in use, filter-associated reductions of PM were statistically significant during the day (06:00-22:00) and night (22:01-05:59) in the primary rooms but only during the day in the secondary rooms. Our study adds to the literature evaluating the real-world effects of PACs on a secondary room and considering the impact of central air systems on PAC performance.

The effects of ambient particulate matter air pollution on platelets and hemostasis.

Elevated ambient pollution exposure is potentially linked to thromboembolism. However, the mechanisms by which particulate matter (PM) interferes with the balance of hemostatic system remain unclear. This study investigates PM-mediated hemostatic changes in individuals across unique seasonal variations of ambient pollution. This prospective study was conducted between February and July 2020 during alterations in ambient pollution in Chiang Mai, Thailand. Blood tests from 30 healthy subjects were assessed at four-week intervals, four times in total. Various coagulation tests, including prothrombin time (PT), activated partial thromboplastin time (aPTT), von Willebrand factor (vWF), platelet count, and platelet functions, were evaluated. A mixed-effects model was used to analyze the impact of high PM2.5 and PM10 on hemostatic parameters. Thirty male subjects with mean age of 38.9 ± 8.2 years, were included. High levels of PM2.5 and PM10 were significantly associated with PT shortening, with no such effect observed in aPTT. PM2.5 and PM10 values also positively correlated with vWF function, while vWF antigen levels remained unchanged. Soluble P-selectin showed a strong positive association with PM2.5 and PM10 levels. Platelet function analysis revealed no correlation with PM values. Short-term exposure to elevated PM2.5 and PM10 concentrations was linked to shortened PT and enhanced vWF function in healthy individuals. Exploring the impact of these changes on clinically relevant thrombosis is crucial. Additional studies on the pathogenesis of pollution-related thrombosis are warranted for maintaining good health.

A causal relationship between particulate matter 2.5 and obesity and its related indicators: a Mendelian randomization study of European ancestry.

In recent years, the prevalence of obesity has continued to increase as a global health concern. Numerous epidemiological studies have confirmed the long-term effects of exposure to ambient air pollutant particulate matter 2.5 (PM2.5) on obesity, but their relationship remains ambiguous. Utilizing large-scale publicly available genome-wide association studies (GWAS), we conducted univariate and multivariate Mendelian randomization (MR) analyses to assess the causal effect of PM2.5 exposure on obesity and its related indicators. The primary outcome given for both univariate MR (UVMR) and multivariate MR (MVMR) is the estimation utilizing the inverse variance weighted (IVW) method. The weighted median, MR-Egger, and maximum likelihood techniques were employed for UVMR, while the MVMR-Lasso method was applied for MVMR in the supplementary analyses. In addition, we conducted a series of thorough sensitivity studies to determine the accuracy of our MR findings. The UVMR analysis demonstrated a significant association between PM2.5 exposure and an increased risk of obesity, as indicated by the IVW model (odds ratio [OR]: 6.427; 95% confidence interval [CI]: 1.881-21.968; P FDR = 0.005). Additionally, PM2.5 concentrations were positively associated with fat distribution metrics, including visceral adipose tissue (VAT) (OR: 1.861; 95% CI: 1.244-2.776; P FDR = 0.004), particularly pancreatic fat (OR: 3.499; 95% CI: 2.092-5.855; PFDR =1.28E-05), and abdominal subcutaneous adipose tissue (ASAT) volume (OR: 1.773; 95% CI: 1.106-2.841; P FDR = 0.019). Furthermore, PM2.5 exposure correlated positively with markers of glucose and lipid metabolism, specifically triglycerides (TG) (OR: 19.959; 95% CI: 1.269-3.022; P FDR = 0.004) and glycated hemoglobin (HbA1c) (OR: 2.462; 95% CI: 1.34-4.649; P FDR = 0.007). Finally, a significant negative association was observed between PM2.5 concentrations and levels of the novel obesity-related biomarker fibroblast growth factor 21 (FGF-21) (OR: 0.148; 95% CI: 0.025-0.89; P FDR = 0.037). After adjusting for confounding factors, including external smoke exposure, physical activity, educational attainment (EA), participation in sports clubs or gym leisure activities, and Townsend deprivation index at recruitment (TDI), the MVMR analysis revealed that PM2.5 levels maintained significant associations with pancreatic fat, HbA1c, and FGF-21. Our MR study demonstrates conclusively that higher PM2.5 concentrations are associated with an increased risk of obesity-related indicators such as pancreatic fat content, HbA1c, and FGF-21. The potential mechanisms require additional investigation.