Effects of PM2.5 on Chronic Airway Diseases: A Review of Research Progress

Ambient PM2.5 and cardiopulmonary mortality in the oldest-old people in China: A national time-stratified case-crossover study

BACKGROUND

Evidence on the associations of fine particulate matter (PM2.5) with cardiopulmonary mortality in the oldest-old (aged 80+ years) people remains limited.

METHODS

We conducted a time-stratified case-crossover study of 1,475,459 deaths from cardiopulmonary diseases in China to estimate the associations between short-term exposure to ambient PM2.5 and cardiopulmonary mortality among the oldest-old people.

FINDINGS

Each 10 μg/m3 increase in PM2.5 concentration (6-day moving average [lag05]) was associated with higher mortality from cardiopulmonary diseases (excess risks [ERs] = 1.69%, 95% confidence interval [CI]: 1.54%, 1.84%), cardiovascular diseases (ER = 1.72%, 95% CI: 1.54%, 1.90%), and respiratory diseases (ER = 1.62%, 95% CI: 1.33%, 1.91%). Compared to the other groups, females (ER = 1.94%, 95% CI: 1.73%, 2.15%) (p for difference test = 0.043) and those aged 95-99 years (ER = 2.31%, 95% CI: 1.61%, 3.02%) (aged 80-85 years old was the reference, p for difference test = 0.770) presented greater mortality risks. We found 14 specific cardiopulmonary causes associated with PM2.5, out of which emphysema (ER = 3.20%, 95% CI: 1.57%, 4.86%) had the largest association. Out of the total deaths, 6.27% (attributable fraction [AF], 95% CI: 5.72%, 6.82%) were ascribed to short-term PM2.5 exposure.

CONCLUSIONS

This study provides evidence of PM2.5-induced cardiopulmonary mortality and calls for targeted prevention actions for the oldest-old people.

FUNDING

This work was supported by the National Key Research and Development Program of China, the National Natural Science Foundation of China, the Foreign Expert Program of the Ministry of Science and Technology, the Natural Science Foundation of Guangdong, China, and the Science and Technology Program of Guangzhou.

Particulate Matter Air Pollution is a Significant Risk Factor for Cardiovascular Disease

Air pollution is responsible worldwide for 9-12 million deaths annually. The major contributor to air pollution is particulate matter ≤2.5 µg per cubic meter of air (PM2.5) from vehicles, industrial emissions, and wildfire smoke. United States ambient air standards recommend annual average PM2.5 concentrations of ≤12 μg/m³ while European standards allow an average annual PM2.5 concentration of ≤20 μg/m3. However, significant PM2.5 cardiovascular and pulmonary health risks exist below these concentrations. Chronic PM2.5 exposure significantly increases major cardiovascular and pulmonary event risks in Americans by 8 to more than 20% for each 10-μg/m3 increase in PM2.5. PM2.5-induced increases in lipid peroxidation, induction of vascular inflammation and endothelial cell injury initiate and propagate respiratory diseases, coronary and carotid atherosclerosis. PM2.5 can cause atherosclerotic vascular plaque rupture and myocardial infarction and stroke by activating metalloproteinases. This article discusses PM2.5 effects on the cardiovascular and pulmonary systems, specific PM2.5 pathophysiologic mechanisms contributing to cardiopulmonary disease, and preventive measures to limit the cardiovascular and pulmonary effects of PM2.5.

Climate change and mortality rates of COPD and asthma: A global analysis from 2000 to 2018

BACKGROUND

Climate change plays a significant role in global health threats, particularly with respiratory diseases such as chronic obstructive pulmonary disease (COPD) and asthma, but the long-term global-scale impact of climate change on these diseases' mortality remains unclear.

OBJECTIVE

This study aims to investigate the impact of climate change on the age-standardized mortality rates (ASMR) of COPD and asthma at national levels.

METHODS

We used Global Burden of Disease (GBD) data of ASMR of COPD and asthma from 2000 to 2018. The climate change index was represented as the deviance percentage of temperature (DPT) and relative humidity (DPRH), calculated based on 19-year temperature and humidity averages. Annual temperature, RH, and fine particulate matter (PM2.5) levels in 185 countries/regions were obtained from ERA5 and the OECD's environmental statistics database. General linear mixed-effect regression models were used to examine the associations between climate change with the log of ASMR (LASMR) of COPD and asthma.

RESULTS

After adjusting for annual PM2.5, SDI level, smoking prevalence, and geographical regions, a 0.26% increase in DPT was associated with decreases of 0.016, 0.017, and 0.014 per 100,000 people in LASMR of COPD and 0.042, 0.046, and 0.040 per 100,000 people in LASMR of asthma for both genders, males, and females. A 2.68% increase in DPRH was associated with increases of 0.009 and 0.011 per 100,000 people in LASMR of COPD. We observed a negative association of DPT with LASMR for COPD in countries/regions with temperatures ranging from 3.8 to 29.9 °C and with LASMR for asthma ranging from -5.3-29.9 °C. However, we observed a positive association of DPRH with LASMR for both COPD and asthma in the RH range of 41.2-67.2%.

CONCLUSION

Climate change adaptation and mitigation could be crucial in reducing the associated COPD and asthma mortality rates, particularly in regions most vulnerable to temperature and humidity fluctuations.

Electrospun Cyclodextrin/Poly(L-lactic acid) Nanofibers for Efficient Air Filter: Their PM and VOC Removal Efficiency and Triboelectric Outputs

In this work, PLLA and CD/PLLA nanofibers were fabricated using electrospinning and utilized as a particulate matter (PM) and volatile organic compounds (VOCs) filter. The electrospun PLLA and CD/PLLA were characterized with various techniques, including SEM, BET, FTIR, XRD, XPS, WCA, DSC, tensile strength testing, PM and VOCs removal efficiency, and triboelectric performance. The results demonstrated that the best air filter was 2.5 wt%CD/PLLA, which performed the highest filtration efficiencies of 96.84 ± 1.51% and 99.38 ± 0.43% for capturing PM_2.5 and PM₁₀, respectively. Its PM_2.5 removal efficiency was 16% higher than that of pure PLLA, which were contributed by their higher surface area and porosity. These 2.5 wt%CD/PLLA nanofibers also exhibited the highest and the fastest VOC entrapment. For triboelectric outputs, the 2.5 wt%CD/PLLA-based triboelectric nanogenerator provided the highest electrical outputs as 245 V and 84.70 μA. These give rise to a three-fold enhancement of electrical outputs. These results indicated that the 2.5 wt%CD/PLLA can improve surface charge density that could capture more PM via electrostatic interaction under surrounding vibration. Therefore, this study suggested that 2.5 wt%CD/PLLA is a good candidate for a multifunction nanofibrous air filter that offers efficient PM and VOC removal.

Grounding (earthing) as related to electromagnetic hygiene: An integrative review

There are a growing number of studies investigating how grounding (earthing) the body may benefit biological performance and aid the treatment of non-communicable diseases. Research also indicates how biological grounding initiatives can sometimes be compromised, or inappropriate, and the need to take additional factors into account as potential contributory factors, or confounders, to expected results. It is proposed that expanding electromagnetic hygiene measures beyond biological grounding alone may help reduce spread of communicable diseases, incidence of respiratory conditions, neurodegenerative disease and all-cause mortality. Identifying potential synergies that exist could enable multilevel interventions to further increase the efficacy of measures. It is hoped that this review will help act as a catalyst to inspire and inform multi-disciplinary research within these topic areas, best practices and policies to help drive medical innovation, reduce health burdens, improve bioelectromagnetic-based therapies, and influence the general design of the built environment and next-generation technologies.

Effects of antibiotics and metals on lung and intestinal microbiome dysbiosis after sub-chronic lower-level exposure of air pollution in ageing rats

We investigated the effects of antibiotics, drugs, and metals on lung and intestinal microbiomes after sub-chronic exposure of low-level air pollution in ageing rats. Male 1.5-year-old Fischer 344 ageing rats were exposed to low-level traffic-related air pollution via whole-body exposure system for 3 months with/without high-efficiency particulate air (HEPA) filtration (gaseous vs. particulate matter with aerodynamic diameter of ≤2.5 µm (PM_2.5) pollution). Lung functions, antibiotics, drugs, and metals in lungs were examined and linked to lung and fecal microbiome analyses by high-throughput sequencing analysis of 16 s ribosomal (r)DNA. Rats were exposed to 8.7 μg/m³ PM_2.5, 10.1 ppb NO₂, 1.6 ppb SO₂, and 23.9 ppb O₃ in average during the study period. Air pollution exposure decreased forced vital capacity (FVC), peak expiratory flow (PEF), forced expiratory volume in 20 ms (FEV₂₀), and FEF at 25∼75% of FVC (FEF_25-75). Air pollution exposure increased antibiotics and drugs (benzotriazole, methamphetamine, methyl-1 H-benzotriazole, ketamine, ampicillin, ciprofloxacin, pentoxifylline, erythromycin, clarithromycin, ceftriaxone, penicillin G, and penicillin V) and altered metals (V, Cr, Cu, Zn, and Ba) levels in lungs. Fusobacteria and Verrucomicrobia at phylum level were increased in lung microbiome by air pollution, whereas increased alpha diversity, Bacteroidetes and Proteobacteria and decreased Firmicutes at phylum level were occurred in intestinal microbiome. Lung function decline was correlated with increasing antibiotics, drugs, and metals in lungs as well as lung and intestinal microbiome dysbiosis. The antibiotics, drugs, and Cr, Co, Ca, and Cu levels in lung were correlated with lung and intestinal microbiome dysbiosis. The lung microbiome was correlated with intestinal microbiome at several phylum and family levels after air pollution exposure. Our results revealed that antibiotics, drugs, and metals in the lung caused lung and intestinal microbiome dysbiosis in ageing rats exposed to air pollution, which may lead to lung function decline.

Lactobacillus casei HY2782 and Pueraria lobata Root Extract Complex Ameliorates Particulate Matter-Induced Airway Inflammation in Mice by Inhibiting Th2 and Th17 Immune Responses

This study aimed to investigate the effects of Lactobacillus casei HY2782 and Pueraria lobata root extract complex (HY2782 complex) in mitigating airway inflammation resulting from exposure to particulate matter ≤2.5 μm in diameter (PM2.5) in an animal model. Chronic inflammatory airway disease is associated with Th2-related cytokines interleukin (IL)-4, IL-5, and IL-13 and Th17-related cytokine IL-17A, which are the major contributors to allergy and asthma. Results indicated that PM2.5 elevates allergen-related airway inflammation and respiratory hyperresponsiveness in C57BL/6 mice. The HY2782 complex significantly reduced Th2/Th17-derived cytokines IL-4, IL5, IL-13, and IL-17A; immunoglobulin E; and leukotriene C₄ in bronchoalveolar lavage fluid (BALF) and serum. Furthermore, the HY2782 complex was associated with the modulation of oxidative stress-related genes. Administration of the HY2782 complex resulted in a markedly reduced number of neutrophils and eosinophil infiltration in BALF. Histopathological observation of lung tissue also showed reduced inflammatory cell infiltration into airways and surrounding tissue. The HY2782 complex may be a promising candidate for the preventive therapy of allergic diseases and airway inflammation caused by PM2.5 inhalation.

Unorganized Machines to Estimate the Number of Hospital Admissions Due to Respiratory Diseases Caused by PM10 Concentration

The particulate matter PM10 concentrations have been impacting hospital admissions due to respiratory diseases. The air pollution studies seek to understand how this pollutant affects the health system. Since prediction involves several variables, any disparity causes a disturbance in the overall system, increasing the difficulty of the models’ development. Due to the complex nonlinear behavior of the problem and their influencing factors, Artificial Neural Networks are attractive approaches for solving estimations problems. This paper explores two neural network architectures denoted unorganized machines: the echo state networks and the extreme learning machines. Beyond the standard forms, models variations are also proposed: the regularization parameter (RP) to increase the generalization capability, and the Volterra filter to explore nonlinear patterns of the hidden layers. To evaluate the proposed models’ performance for the hospital admissions estimation by respiratory diseases, three cities of São Paulo state, Brazil: Cubatão, Campinas and São Paulo, are investigated. Numerical results show the standard models’ superior performance for most scenarios. Nevertheless, considering divergent intensity in hospital admissions, the RP models present the best results in terms of data dispersion. Finally, an overall analysis highlights the models’ efficiency to assist the hospital admissions management during high air pollution episodes.