Evaluation of PM2.5 air pollution sources and cardiovascular health

A case-crossover study of ST-elevation myocardial infarction and organic carbon and source-specific PM2.5 concentrations in Monroe County, New York

Background

Previous work reported increased rates of cardiovascular hospitalizations associated with increased source-specific PM2.5 concentrations in New York State, despite decreased PM2.5 concentrations. We also found increased rates of ST elevation myocardial infarction (STEMI) associated with short-term increases in concentrations of ultrafine particles and other traffic-related pollutants in the 2014-2016 period, but not during 2017-2019 in Rochester. Changes in PM2.5 composition and sources resulting from air quality policies (e.g., Tier 3 light-duty vehicles) may explain the differences. Thus, this study aimed to estimate whether rates of STEMI were associated with organic carbon and source-specific PM2.5 concentrations.

Methods

Using STEMI patients treated at the University of Rochester Medical Center, compositional and source-apportioned PM2.5 concentrations measured in Rochester, a time-stratified case-crossover design, and conditional logistic regression models, we estimated the rate of STEMI associated with increases in mean primary organic carbon (POC), secondary organic carbon (SOC), and source-specific PM2.5 concentrations on lag days 0, 0-3, and 0-6 during 2014-2019.

Results

The associations of an increased rate of STEMI with interquartile range (IQR) increases in spark-ignition emissions (GAS) and diesel (DIE) concentrations in the previous few days were not found from 2014 to 2019. However, IQR increases in GAS concentrations were associated with an increased rate of STEMI on the same day in the 2014-2016 period (Rate ratio [RR] = 1.69; 95% CI = 0.98, 2.94; 1.73 μg/m3). In addition, each IQR increase in mean SOC concentration in the previous 6 days was associated with an increased rate of STEMI, despite imprecision (RR = 1.14; 95% CI = 0.89, 1.45; 0.42 μg/m3).

Conclusion

Increased SOC concentrations may be associated with increased rates of STEMI, while there seems to be a declining trend in adverse effects of GAS on triggering of STEMI. These changes could be attributed to changes in PM2.5 composition and sources following the Tier 3 vehicle introduction.

Hemolytic Properties of Fine Particulate Matter (PM2.5) in In Vitro Systems

Epidemiological studies have suggested that inhalation exposure to particulate matter (PM) air pollution, especially fine particles (i.e., PM2.5 (PM with an aerodynamic diameter of 2.5 microns or less)), is causally associated with cardiovascular health risks. To explore the toxicological mechanisms behind the observed adverse health effects, the hemolytic activity of PM2.5 samples collected during different pollution levels in Beijing was evaluated. The results demonstrated that the hemolysis of PM2.5 ranged from 1.98% to 7.75% and demonstrated a clear dose-response relationship. The exposure toxicity index (TI) is proposed to represent the toxicity potential of PM2.5, which is calculated by the hemolysis percentage of erythrocytes (red blood cells, RBC) multiplied by the mass concentration of PM2.5. In a pollution episode, as the mass concentration increases, TI first increases and then decreases, that is, TI (low pollution levels) < TI (heavy pollution levels) < TI (medium pollution levels). In order to verify the feasibility of the hemolysis method for PM toxicity detection, the hemolytic properties of PM2.5 were compared with the plasmid scission assay (PSA). The hemolysis results had a significant positive correlation with the DNA damage percentages, indicating that the hemolysis assay is feasible for the detection of PM2.5 toxicity, thus providing more corroborating information regarding the risk to human cardiovascular health.

A Narrative Review on the Impact of Air Pollution on Heart Failure Risk and Exacerbation

Air pollution is a risk factor for many cardiovascular diseases, including heart failure (HF). Although the links between air pollution and HF have been explored, the results are scattered and difficult to piece together into a cohesive story. Therefore, we undertook a narrative review of all aspects of the relationship between HF and air pollution exposure, including risks of developing HF when exposed to air pollution, the exacerbation of HF symptoms by air pollution exposure, and the increased susceptibility that individuals with HF have for air pollution-related health risks. We also examined the literature on environmental justice as well as air pollution interventions for HF. We found substantial evidence linking air pollution exposure to HF incidence. There were a limited number of studies that examined air pollution exposure in clearly defined populations with HF to explore exacerbation of HF or the susceptibility of individuals with HF to air pollution health risks. However, there is substantial evidence that HF-related hospitalisations are increased under air pollution exposure and that the air pollution associated increase in HF-related hospitalisations is greater than hospitalisations for other chronic diseases, supporting links between air pollution and both exacerbation of HF and susceptibility of individuals with HF. There is emerging evidence for interventions that can decrease air pollution health risks for individuals with HF, and more studies are needed, particularly randomised controlled trials. Thus, although the air pollution-related health risks for HF incidence and hospitalisations are clear, further studies specifically targeted at identified data gaps will greatly improve our knowledge of the susceptibility of individuals with HF and interventions to reduce risks.

Associations between source-apportioned PM2.5 and 30-day readmissions in heart failure patients

BACKGROUND

Air pollution exposure is a significant risk factor for morbidity and mortality, especially for those with pre-existing chronic disease. Previous studies highlighted the risks that long-term particulate matter exposure has for readmissions. However, few studies have evaluated source and component specific associations particularly among vulnerable patient populations.

OBJECTIVES

Use electronic health records from 5556 heart failure (HF) patients diagnosed between July 5, 2004 and December 31, 2010 that were part of the EPA CARES resource in conjunction with modeled source-specific fine particulate matter (PM2.5) to estimate the association between exposure to source and component apportioned PM2.5 at the time of HF diagnosis and 30-day readmissions.

METHODS

We used zero-inflated mixed effects Poisson models with a random intercept for zip code to model associations while adjusting for age at diagnosis, year of diagnosis, race, sex, smoking status, and neighborhood socioeconomic status. We undertook several sensitivity analyses to explore the impact of geocoding precision and other factors on associations and expressed associations per interquartile range increase in exposures.

RESULTS

We observed associations between 30-day readmissions and an interquartile range increase in gasoline- (16.9% increase; 95% confidence interval = 4.8%, 30.4%) and diesel-derived PM2.5 (9.9% increase; 95% confidence interval = 1.7%, 18.7%), and the secondary organic carbon component of PM2.5 (SOC; 20.4% increase; 95% confidence interval = 8.3%, 33.9%). Associations were stable in sensitivity analyses, and most consistently observed among Black study participants, those in lower income areas, and those diagnosed with HF at an earlier age. Concentration-response curves indicated a linear association for diesel and SOC. While there was some non-linearity in the gasoline concentration-response curve, only the linear component was associated with 30-day readmissions.

DISCUSSION

There appear to be source specific associations between PM2.5 and 30-day readmissions particularly for traffic-related sources, potentially indicating unique toxicity of some sources for readmission risks that should be further explored.

Effects of urban particulate matter on the quality of erythrocytes

With the acceleration of industrialisation and urbanisation, air pollution has become a serious global concern as a hazard to human health, with urban particulate matter (UPM) accounting for the largest share. UPM can rapidly pass into and persist within systemic circulation. However, few studies exist on whether UPM may have any impact on blood components. In this study, UPM standards (SRM1648a) were used to assess the influence of UPM on erythrocyte quality in terms of oxidative and metabolic damage as well as phagocytosis by macrophages in vitro and clearance in vivo. Our results showed that UPM had weak haemolytic properties. It can oxidise haemoglobin and influence the oxygen-carrying function, redox balance, and metabolism of erythrocytes. UPM increases the content of reactive oxygen species (ROS) and decreases antioxidant function according to the data of malonaldehyde (MDA), glutathione (GSH), and glucose 6 phosphate dehydrogenase (G6PDH). UPM can adhere to or be internalised by erythrocytes at higher concentrations, which can alter their morphology. Superoxide radicals produced in the co-incubation system further disrupted the structure of red blood cell membranes, thereby lowering the resistance to the hypotonic solution, as reflected by the osmotic fragility test. Moreover, UPM leads to an increase in phosphatidylserine exposure in erythrocytes and subsequent clearance by the mononuclear phagocytic system in vivo. Altogether, this study suggests that the primary function of erythrocytes may be affected by UPM, providing a warning for erythrocyte quality in severely polluted areas. For critically ill patients, transfusion of erythrocytes with lesions in morphology and function will have serious clinical consequences, suggesting that potential risks should be considered during blood donation screening. The current work expands the scope of blood safety studies.

Modern Concepts of the Role of Fine Particles (PM 2.5) in the Genesis of Atherosclerosis and Myocardial Damage: Clinical and Epidemiological Data, the Main Pathophysiological Mechanisms

Due to the fact that atherosclerotic cardiovascular diseases (CVDs) dominate in the structure of morbidity, disability and mortality of the population, the study of the risk factors for the development of atherosclerotic CVDs, as well as the study of the underlying pathogenetic mechanisms thereof, is the most important area of scientific research in modern medicine. Understanding these aspects will allow improving the set of treatment and preventive measures and activities. One of the important risk factors for the development of atherosclerosis, which has been actively studied recently, is air pollution with fine particulate matter (PM 2.5). According to clinical and epidemiological data, the level of air pollution with PM 2.5 exceeds the normative indicators in most regions of the world and is associated with subclinical markers of atherosclerosis and mortality from atherosclerotic CVDs. The aim of this article is to systematize and discuss in detail the role of PM 2.5 in the development of atherosclerosis and myocardial damage with the consideration of epidemiological and pathogenetic aspects. Materials and Methods: This narrative review is based on the analysis of publications in the Medline, PubMed, and Embase databases. The terms "fine particles" and "PM 2.5" in combination with "pathophysiological mechanisms," "cardiovascular diseases", "atherosclerosis", "cardiac troponins", "myocardial damage" and "myocardial injury" were used to search publications. Conclusion: According to the conducted narrative review, PM 2.5 should be regarded as the significant risk factor for the development of atherosclerotic CVDs. The pro-atherogenic effect of fine particulate matter is based on several fundamental and closely interrelated pathophysiological mechanisms: endothelial dysfunction, impaired lipid metabolism, increased oxidative stress and inflammatory reactions, impaired functioning of the vegetative nervous system and increased activity of the hemostatic system. In addition, PM 2.5 causes subclinical damage to cardiac muscle cells by several mechanisms: apoptosis, oxidative stress, decreased oxygen delivery due to coronary atherosclerosis and ischemic damage of cardiomyocytes. Highly sensitive cardiac troponins are promising markers for detecting subclinical myocardial damage in people living in polluted regions.

The Role of Fine Particles (PM 2.5) in the Genesis of Atherosclerosis and Myocardial Damage: Emphasis on Clinical and Epidemiological Data, and Pathophysiological Mechanisms

Due to the fact that atherosclerotic cardiovascular diseases (CVDs) dominate in the structure of morbidity, disability and mortality of the population, the study of the risk factors for the development of atherosclerotic CVDs, as well as the study of the underlying pathogenetic mechanisms thereof, is the most important area of scientific research in modern medicine. Understanding these aspects will allow to improve the set of treatment and preventive measures and activities. One of the important risk factors for the development of atherosclerosis, which has been actively studied recently, is air pollution with fine particulate matter (PM 2.5). According to clinical and epidemiological data, the level of air pollution with PM 2.5 exceeds the normative indicators in most regions of the world and is associated with subclinical markers of atherosclerosis and mortality from atherosclerotic CVDs. The aim of this article is to systematize and discuss in detail the role of PM 2.5 in the development of atherosclerosis and myocardial damage.

A new combination model using decomposition ensemble framework and error correction technique for forecasting hourly PM2.5 concentration

PM_2.5 pollutants are seriously harmful to human health, which is of great significance for the forecasting of PM_2.5 concentration. To accurately forecast hourly PM_2.5 concentration, a new combination model based on agreement index variational mode decomposition (AIVMD), radial basis function neural network (RBF), induced ordered weighted averaging (IOWA) operator, long short-term memory neural network (LSTM) and error correction (EC), named AIVMD-RBF-IOWA-LSTM-EC, is proposed, which uses decomposition ensemble framework and error correction technique. Taking the reduction of reconstruction error in the process of VMD as the goal, an adaptive method to determine the mode number of VMD by agreement index (AI), named AIVMD, is proposed. Firstly, PM_2.5 concentration data are decomposed into simple intrinsic mode function components (IMFs) by AIVMD to reduce the complexity of the data. Secondly, LSTM and RBF models are established for each IMF component, and the prediction results of each model are combined separately. Thirdly, an error correction model based on RBF is established to correct the prediction results. The predicted values of error are not only used to correct the prediction results, but also can be used as the induced value of IOWA operators to solve the weight allocation problem. Finally, the IOWA operator is used to weight the error correction prediction results, and the final result is obtained. To solve the problem that the forecasting accuracy of the combination model based on IOWA operators is low when the complementarity between single models is poor, a combination forecasting method with complementary disadvantage based on IOWA operators is proposed, which effectively improves the robustness of the model. A formula for calculating the proportion of complementary points is given. By solving the formula, the complementarity of the models can be judged, and the method of calculating the weight of the combined model can be selected accordingly. The proposed model is used to forecast PM_2.5 concentration in Xi'an, and compared with the predicted results of contrast models. The results show that the proposed model has a great advantage in short-term forecasting of PM_2.5 concentration.

The links of fine airborne particulate matter exposure to occurrence of cardiovascular and metabolic diseases in Michigan, USA

Air pollutants, particularly airborne particulate matter with aerodynamic diameter < 2.5μm (PM2.5), have been linked to the increase in mortality and morbidity associated with cardiovascular and metabolic diseases. In this study, we investigated the dose-risk relationships between PM2.5 concentrations and occurrences of cardiovascular and metabolic diseases as well as the confounding socioeconomic factors in Michigan, USA, where PM2.5 levels are generally considered acceptable. Multivariate linear regression analyses were performed to investigate the relationship between health outcome and annual ground-level PM2.5 concentrations of 82 counties in Michigan. The analyses revelated significant linear dose-response associations between PM2.5 concentrations and cardiovascular disease (CVD) hospitalization. A 10 μg/m3 increase in PM2.5 exposure was found to be associated with a 3.0% increase in total CVD, 0.45% increase in Stroke, and a 0.3% increase in Hypertension hospitalization rates in Medicare beneficiaries. While the hospitalization rates of Total Stroke, Hemorrhagic Stroke, and Hypertension in urbanized counties were significantly higher than those of rural counties, the death rates of coronary heart disease and ischemic stroke in urbanized counties were significantly lower than those of rural counties. These results were correlated with the facts that PM2.5 levels in urbanized counties were significantly higher than that in rural counties and that the percentage of the population with health insurance and the median household income in rural counties were significantly lower. While obesity prevalence showed evidence of a weak positive correlation (ρ = 0.20, p-value = 0.078) with PM2.5 levels, there was no significant dose-response association between county diabetes prevalence rates and PM2.5 exposure in Michigan. In summary, this study revealed strong dose-response associations between PM2.5 concentrations and CVD incidence in Michigan, USA. The socioeconomic factors, such as access to healthcare resources and median household income, represent important confounding factors that could override the impact of PM2.5 exposure on CVD mortality.

Application of an Improved Gas-constrained Source Apportionment Method Using Data Fused Fields: a Case Study in North Carolina, USA

A number of studies have found differing associations of disease outcomes with PM_2.5 components (or species) and sources (e.g., biomass burning, diesel vehicles and gasoline vehicles). Here, a unique method of fusing daily chemical transport model (Community Multiscale Air Quality Modeling) results with observations has been utilized to generate spatiotemporal fields of the concentrations of major gaseous pollutants (CO, NO₂, NO_x, O₃, and SO₂), total PM_2.5 mass, and speciated PM_2.5 (including crustal elements) over North Carolina for 2002-2010. The fused results are then used in chemical mass balance source apportionment model, CMBGC-Iteration, which uses both gas constraint and particulate matter concentrations to quantify source impacts. The method, as applied to North Carolina, quantifies the impacts of ten source categories and provides estimates of source contributions to PM_2.5 concentrations. The ten source categories include both primary sources (diesel vehicles, gasoline vehicles, dust, biomass burning, coal-fired power plants and sea salt) and secondary components (ammonium sulfate, ammonium bisulfate, ammonium nitrate and secondary organic carbon). The results show a steady decrease in anthropogenic source impacts, especially from diesel vehicles and coal-fired power plants. Secondary pollutant components accounted for approximately 70% of PM_2.5 mass. This study demonstrates an ability to provide spatiotemporal fields of both PM components and source impacts using a chemical transport model fused with observation data, linked to a receptor-based source apportionment method, to develop spatiotemporal fields of multiple pollutants.

The Role of Fossil Fuel Combustion Metals in PM2.5 Air Pollution Health Associations

In this review, we elucidate the central role played by fossil fuel combustion in the health-related effects that have been associated with inhalation of ambient fine particulate matter (PM2.5). We especially focus on individual properties and concentrations of metals commonly found in PM air pollution, as well as their sources and their adverse health effects, based on both epidemiologic and toxicological evidence. It is known that transition metals, such as Ni, V, Fe, and Cu, are highly capable of participating in redox reactions that produce oxidative stress. Therefore, particles that are enriched, per unit mass, in these metals, such as those from fossil fuel combustion, can have greater potential to produce health effects than other ambient particulate matter. Moreover, fossil fuel combustion particles also contain varying amounts of sulfur, and the acidic nature of the resulting sulfur compounds in particulate matter (e.g., as ammonium sulfate, ammonium bisulfate, or sulfuric acid) makes transition metals in particles more bioavailable, greatly enhancing the potential of fossil fuel combustion PM2.5 to cause oxidative stress and systemic health effects in the human body. In general, there is a need to further recognize particulate matter air pollution mass as a complex source-driven mixture, in order to more effectively quantify and regulate particle air pollution exposure health risks.