Fine particulate air pollution and its components in association with cause-specific emergency admissions

Isoleucilactucin Ameliorates Coal Fly Ash-Induced Inflammation through the NF-κB and MAPK Pathways in MH-S Cells

We investigated whether isoleucilactucin, an active constituent of Ixeridium dentatum, reduces inflammation caused by coal fly ash (CFA) in alveolar macrophages (MH-S). The anti-inflammatory effects of isoleucilactucin were assessed by measuring the concentration of nitric oxide (NO) and the expression of pro-inflammatory mediators in MH-S cells exposed to CFA-induced inflammation. We found that isoleucilactucin reduced CFA-induced NO generation dose-dependently in MH-S cells. Moreover, isoleucilactucin suppressed CFA-activated proinflammatory mediators, including cyclooxygenase-2 (COX2) and inducible NO synthase (iNOS), and the proinflammatory cytokines such as interleukin-(IL)-1β, IL-6, and tumor necrosis factor (TNF-α). The inhibiting properties of isoleucilactucin on the nuclear translocation of phosphorylated nuclear factor-kappa B (p-NF-κB) were observed. The effects of isoleucilactucin on the NF-κB and mitogen-activated protein kinase (MAPK) pathways were also measured in CFA-stimulated MH-S cells. These results indicate that isoleucilactucin suppressed CFA-stimulated inflammation in MH-S cells by inhibiting the NF-κB and MAPK pathways, which suggest it might exert anti-inflammatory properties in the lung.

Coal beneficiation technology to reduce hazardous heavy metals in fly ash

Fly ash emitted from the coal-fired power plant is the major contributor of the outdoor airborne particulate matters (PMs). Coal beneficiation, an industrial process to improve the quality of raw coal by removing ash-bearing components, can be a cost-effective sustainable and clean technology to reduce the emission of hazardous trace metals. As the removal efficiency of mineral matters and heavy metals within the coal is depend highly on the raw coal and the employed beneficiation process, a wide range of case studies at laboratory- and industrial-scale, published in the last 20 years, are reviewed in this study. Our review indicates that the coal beneficiation processes can effectively reduce content of heavy metals of fly ash, encouraging the use of clean coal to reduce pollutants emission.

PM2.5 Exacerbates Oxidative Stress and Inflammatory Response through the Nrf2/NF-κB Signaling Pathway in OVA-Induced Allergic Rhinitis Mouse Model

Air pollution-related particulate matter (PM) exposure reportedly enhances allergic airway inflammation. Some studies have shown an association between PM exposure and a risk for allergic rhinitis (AR). However, the effect of PM for AR is not fully understood. An AR mouse model was developed by intranasal administration of 100 μg/mouse PM with a less than or equal to 2.5 μm in aerodynamic diameter (PM_2.5) solution, and then by intraperitoneal injection of ovalbumin (OVA) with alum and intranasal challenging with 10 mg/mL OVA. The effects of PM_2.5 on oxidative stress and inflammatory response via the Nrf2/NF-κB signaling pathway in mice with or without AR indicating by histological, serum, and protein analyses were examined. PM_2.5 administration enhanced allergic inflammatory cell expression in the nasal mucosa through increasing the expression of inflammatory cytokine and reducing the release of Treg cytokine in OVA-induced AR mice, although PM_2.5 exposure itself induced neither allergic responses nor damage to nasal and lung tissues. Notably, repeated OVA-immunization markedly impaired the nasal mucosa in the septum region. Moreover, AR with PM_2.5 exposure reinforced this impairment in OVA-induced AR mice. Long-term PM_2.5 exposure strengthened allergic reactions by inducing the oxidative through malondialdehyde production. The present study also provided evidence, for the first time, that activity of the Nrf2 signaling pathway is inhibited in PM_2.5 exposed AR mice. Furthermore, PM_2.5 exposure increased the histopathological changes of nasal and lung tissues and related the inflammatory cytokine, and clearly enhanced PM_2.5 phagocytosis by alveolar macrophages via activating the NF-κB signaling pathway. These obtained results suggest that AR patients may experience exacerbation of allergic responses in areas with prolonged PM_2.5 exposure.

Respiratory Emergency Department Visits Associations with Exposures to PM2.5 Mass, Constituents, and Sources in Dhaka, Bangladesh Air Pollution

RATIONALE

To date, there is no published local epidemiological evidence documenting the respiratory health effects of source specific air pollution in South Asia, where PM2.5 composition is different from past studies. Differences include more biomass and residue crop-burning emissions, which may have differing health implications.

OBJECTIVES

We assessed PM2.5 associations with respiratory emergency department (ED) visits in a biomass-burning dominated high pollution region, and evaluated their variability by pollution source and composition.

METHODS

Time-series regression modeling was applied to daily ED visits from January 2014 through December 2017. Air pollutant effect sizes were estimated after addressing long-term trends and seasonality, day-of-week, holidays, relative humidity, ambient temperature, and the effect modification by season, age, and sex.

RESULTS

PM2.5 yielded a significant association with increased respiratory ED visits [0.84% (95% CI: 0.33%, 1.35%)] per 10 μg/m3 increase. The PM2.5 health effect size varied with season, the highest being during monsoon season, when fossil-fuel combustion sources dominated exposures. Results from a source-specific health effect analysis was also consistent with fossil-fuel PM2.5 having a larger effect size per 10 μg/m3 than PM2.5 from other sources [fossil-fuel PM2.5: 2.79% (0.33% to 5.31%), biomass-burning PM2.5: 1.27% (0% to 2.54%), and other-PM2.5: 0.95% (0.06% to 1.85%)]. Age-specific associations varied, with children and older adults being disproportionately affected by the air pollution, especially by the combustion-related particles.

CONCLUSIONS

This study provided novel and important evidence that respiratory health in Dhaka is significantly affected by particle air pollution, with a greater health impact by fossil-fuel combustion derived PM2.5.

Estimating the Acute Health Impacts of Fire-Originated PM2.5 Exposure During the 2017 California Wildfires: Sensitivity to Choices of Inputs

Exposure to wildfire smoke increases the risk of respiratory and cardiovascular hospital admissions. Health impact assessments, used to inform decision-making processes, characterize the health impacts of environmental exposures by combining preexisting epidemiological concentration-response functions (CRFs) with estimates of exposure. These two key inputs influence the magnitude and uncertainty of the health impacts estimated, but for wildfire-related impact assessments the extent of their impact is largely unknown. We first estimated the number of respiratory, cardiovascular, and asthma hospital admissions attributable to fire-originated PM2.5 exposure in central California during the October 2017 wildfires, using Monte Carlo simulations to quantify uncertainty with respect to the exposure and epidemiological inputs. We next conducted sensitivity analyses, comparing four estimates of fire-originated PM2.5 and two CRFs, wildfire and nonwildfire specific, to understand their impact on the estimation of excess admissions and sources of uncertainty. We estimate the fires accounted for an excess 240 (95% CI: 114, 404) respiratory, 68 (95% CI: -10, 159) cardiovascular, and 45 (95% CI: 18, 81) asthma hospital admissions, with 56% of admissions occurring in the Bay Area. Although differences between impact assessment methods are not statistically significant, the admissions estimates' magnitude is particularly sensitive to the CRF specified while the uncertainty is most sensitive to estimates of fire-originated PM2.5. Not accounting for the exposure surface's uncertainty leads to an underestimation of the uncertainty of the health impacts estimated. Employing context-specific CRFs and using accurate exposure estimates that combine multiple data sets generates more certain estimates of the acute health impacts of wildfires.

Sources of indoor PM2.5 gross α and β activities measured in 340 homes

Particle radioactivity (PR) exposure has been linked to adverse health effects. PR refers to the presence of α- and β-emitting radioisotopes attached to fine particulate matter (PM_2.5). This study investigated sources contributing to indoor PM_2.5 gross α- and β-radioactivity levels. We measured activity from long-lived radon progeny radionuclides from archived PM_2.5 samples collected in 340 homes in Massachusetts during the period 2006-2010. We analyzed the data using linear mixed effects models and positive matrix factorization (PMF) analysis. Indoor PM_2.5 gross α-activity levels were correlated with sulfur (S), iron (Fe), bromine (Br), vanadium (V), sodium (Na), lead (Pb), potassium (K), calcium (Ca), silicon (Si), zinc (Zn), arsenic (As), titanium (Ti), radon (²²²Rn) and black carbon (BC) concentrations (p <0.05). Indoor PM_2.5 β-activity was correlated with S, As, antimony (Sb), Pb, Br and BC. We identified four indoor PM_2.5 sources: outdoor air pollution (62%), salt aerosol source (14%), fireworks and environmental tobacco smoke (7%) and indoor mixed dust (17%). Outdoor air pollution was the most significant contributor to indoor PM_2.5 α- and β-activity levels. The contributions of this source were during the summer months and when windows were open. Indoor mixed dust was also found to contribute to PM_2.5 α-activity. PM_2.5 α-activity was further associated with radon during winter months, showing radon's important role as an indoor source of ionizing radiation.

Illuminating a time-response mechanism in mice liver after PM2.5 exposure using metabolomics analysis

PM_2.5 is recognized as an atmospheric pollutant that seriously jeopardizes human health. Emerging evidence indicates that PM_2.5 exposure is associated with metabolic disorders. Existing epidemiology and toxicology studies on the health effects of PM_2.5 usually focused on its different components and doses, the effects on susceptible populations, or the effects of indoor and outdoor pollution. The underlying mechanisms of exposure time are poorly understood. Liver, as the central organ involved in various metabolisms, has special signaling pathways non-existed in lung and cardiovascular systems. Exacerbation in liver by the prolonged exposure of PM_2.5 leads to hepatic function disorder. It is therefore essential to elucidate the mechanism underlying hepatotoxicity after PM_2.5 exposure from the perspective of time-response relationship. In this study, targeted metabolomics was utilized to explore the hepatic injury in mice after PM_2.5 exposure. Our results showed that prolonged exposure of PM_2.5 would aggravate liver metabolic disorders. The metabolic process was divided into three phases. In phase I, it was found that PM_2.5 exposure disturbed the hepatic urea synthesis. In phase II, oxidative damages and inflammations obviously occurred in liver, which would further cause neurobehavioral disorders and fat deposits. In phase III, the changes of metabolites and metabolic pathways indicated that the liver has been severely damaged, with the accelerated biosynthesis and fat metabolism. Finally, using ROC analysis coupled with their biological functions, 4 potential biomarkers were screened out, with which we established a method to classify and diagnose the progress of liver damage in mice after PM_2.5 exposure. In this paper, we not only established the time-response relationship of PM_2.5, but also provided new insights for the classification and prediction of the toxic injury stages in mice liver, which provides a ground work for the future drug intervention to prevent oxidative damage of PM_2.5.

Therapeutic effects and mechanisms study of Hanchuan Zupa Granule in a Guinea pig model of cough variant asthma

ETHNOPHARMACOLOGICAL RELEVANCE

Hanchuan Zupa Granule (HCZP), a traditional Chinese ethnodrug, has the functions of supressing a cough, resolving phlegm, warming the lungs, and relieving asthma. In clinical practice employing traditional Chinese medicine (TCM), HCZP is commonly used to treat acute colds, cough and abnormal mucous asthma caused by a cold, or "Nai-Zi-Lai" in the Uygur language. Studies have confirmed the use of HCZP to treat cough variant asthma (CVA) and other respiratory diseases. However, the pharmacological mechanisms of HCZP remain unrevealed.

AIM OF THE STUDY

To investigate the anti-tussive and anti-asthmatic effects and the possible pharmacological mechanisms of HCZP in the treatment of CVA.

MATERIALS AND METHODS

A guinea pig CVA animal model was established by intraperitoneal injection of ovalbumin (OVA) combined with intraperitoneal injection of aluminium hydroxide adjuvant and atomized OVA. Meanwhile, guinea pigs with CVA received oral HCZP (at dosages of 0.571, 0.285 and 0.143 g/kg bodyweight). The number of coughs induced by aerosol capsaicin was recorded, and the airway hyperresponsiveness (AHR) of CVA guinea pigs was detected with the FinePointe series RC system. H&E staining of lung tissues was performed to observe pathological changes. ELISA was used to detect inflammatory cytokines. qRT-PCR and western blotting analyses were used to detect the expression of Th1-specific transcription factor (T-bet), Th2-specific transcription factor (GATA3), and Toll-like receptor 4 (TLR4) signal transduction elements. These methods were performed to assess the protective effects and the potential mechanisms of HCZP on CVA.

RESULTS

Great changes were found in the CVA guinea pig model after HCZP treatment. The number of coughs induced by capsaicin in guinea pigs decreased, the body weights of guinea pigs increased, and inflammation of the eosinophilic airway and AHR were reduced simultaneously. These results indicate that HCZP has a significant protective effect on CVA. A pharmacological study of HCZP showed that the levels of interleukin-4 (IL-4) and IL-5 and tumour necrosis factor-α (TNF-α) in serum decreased. The amount of interferon-γ (IFN-γ) increased, mRNA and protein expression of TLR4 and GATA3 weakened, and mRNA and protein expression of T-bet increased.

CONCLUSIONS

HCZP ameliorated the symptoms of guinea pigs with CVA induced by OVA by regulating the Th1/Th2 imbalance and TLR4 receptors.

Associations between PM2.5 metal components and QT interval length in the Normative Aging Study

BACKGROUND

Several studies have found associations between increases in QT interval length, a marker of cardiac electrical instability, and short-term fine particulate matter (PM2.5) exposures. To our knowledge, this is the first study to examine the association between specific PM2.5 metal components and QT interval length.

METHODS

We measured heart-rate corrected QT interval (QTc) duration among 630 participants in the Normative Aging Study (NAS) based in Eastern Massachusetts between 2000 and 2011. We utilized time-varying linear mixed-effects regressions with a random intercept for each participant to analyze associations between QTc interval and moving averages (0-7 day moving averages) of 24-h mean concentrations of PM2.5 metal components (vanadium, nickel, copper, zinc and lead) measured at the Harvard Supersite monitoring station. Models were adjusted for daily PM2.5 mass estimated at a 1 km × 1 km grid cell from a previously validated prediction model and other covariates. Bayesian kernel machine regression (BKMR) was utilized to assess the overall joint effect of the PM2.5 metal components.

RESULTS

We found consistent results with higher lead (Pb) associated with significant higher QTc intervals for both the multi-pollutant and the two pollutant (PM2.5 mass and a PM2.5 component) models across the moving averages. The greatest effect of lead on QTc interval was detected for the 4-day moving average lead exposure. In the multi-pollutant model, each 2.72 ng/m3 increase in daily lead levels for a 4-day moving average was associated with a 7.91 ms (95% CI: 3.63, 12.18) increase in QTc interval. In the two-pollutant models with PM2.5 mass and lead, each 2.72 ng/m3 increase in daily lead levels for a 4-day moving average was associated with an 8.50 ms (95% CI: 4.59, 12.41) increase in QTc interval. We found that 4-day moving average of copper has a negative association with QTc interval when compared to the other PM2.5 metal components. In the multi-pollutant model, each 1.81 ng/m3 increase in daily copper levels for a 4-day moving average was associated with an -3.89 ms (95% CI: -6.98, -0.79) increase in QTc interval. Copper's essential function inside the human body could mediate its cardiotoxicity on cardiac conductivity and explain why we found that copper in comparison to the other metals was less harmful for QTc interval.

CONCLUSIONS

Exposure to metals contained in PM2.5 are associated with acute changes in ventricular repolarization as indicated by QT interval characteristics.

Associations between short term exposure to ambient particulate matter from dust storm and anthropogenic sources and inflammatory biomarkers in healthy young adults

This study examined the association between particulate matter from anthropogenic and natural sources and inflammatory biomarkers, including hs-CRP, IL-6, sTNF-RII, and WBCs, in two groups of healthy young subjects. We followed up subjects of two panels (16 to 22 years old), including 22 subjects selected from the urban area (Tehran city) with high-level pollution background and 22 subjects selected from the rural area (Ahmadabad) with low-level pollution background. In each group, we collected 4 times blood samples in various air pollution conditions, In the subjects of the urban group, there was a substantial difference (p < 0.05) between inversion days and cold season control days, and between dust storm days and warm season control days for concentrations of hs-CRP, IL-6, and WBCs biomarkers. In the subjects of the rural group, a significant difference could be detected in the concentration of hs-CRP, IL-6, and WBCs biomarkers (p < 0.05) between inversion days and cold season control days, and between dust storm and warm control days. We found that the difference in concentrations of hs-CRP, IL-6, and WBCs biomarkers between dust storm days and warm control conditions in the rural group were higher than the difference in inversion and cold control conditions, which can be attributed to low background air pollution in the rural area. In the urban area, the health effect of anthropogenic sources of PM is higher than the dust storm condition, which can be attributed to the stronger effect of anthropogenic pollution effect.

Source-specific contributions of particulate matter to asthma-related pediatric emergency department utilization

Ambient particulate matter smaller than 2.5 μm (PM_2.5) is associated with different chronic diseases. It is crucial to identify the sources of ambient particulate matter to reduce the impact on health. Still, only a few studies have been linked with specific ambient particulate matter sources. In this study, we estimated the contributions of sources of PM_2.5 and examined their association with daily asthma hospital utilization in Cincinnati, Ohio, USA. We used a model-based clustering method to group days with similar source-specific contributions into six distinct clusters. Specifically, elevated PM_2.5 concentrations occurring on days characterized by low coal combustion contributions showed a significantly reduced risk of hospital utilization for asthma (rate ratio: 0.86, 95% CI: [0.77, 0.95]) compared to other clusters. Reducing coal combustion contribution to PM_2.5 levels could be an effective intervention for lowering asthma-related hospital utilization.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13755-021-00141-z.

Evaluation of adverse effects of particulate matter on human life

Particulate matter (PM_2.5) has a severe impact on human health. The concentration of PM_2.5, related to air-quality changes, may be associated with perceptible effects on people's health. In this study, computer intelligence was used to assess the negative effects of PM_2.5. The input data, used for the evaluation, were grid definitions (shape-file), PM_2.5, air-quality data, incidence/prevalence rates, a population dataset, and the (Krewski) health-impact function. This paper presents a local (Pakistan) health-impact assessment of PM_2.5 in order to estimate the long-term effects on mortality. A rollback-to-a-standard scenario was based on the PM_2.5 concentration of 15 μg m^-3. Health benefits for a population of about 73 million people were calculated. The results showed that the estimated avoidable mortality, linked to ischemic heart disease and lung cancer, was 2,773 for every 100,000 people, which accounts for 2,024,290 preventable deaths of the total population. The total cost, related to the above mortality, was estimated to be US $ 1,000 million. Therefore, a policy for a PM_2.5-standard up to 15 μg m^-3 is suggested.

The PI3K/Akt/mTORC signaling axis in head and neck squamous cell carcinoma: Possibilities for therapeutic interventions either as single agents or in combination with conventional therapies

The latest advances in the sequencing methods in head and neck squamous cell carcinoma (HNSCC) tissues have revolutionized our understanding of the disease by taking off the veil from the most frequent genetic alterations in the components of the oncogenic pathways. Among all the identified alterations, aberrancies in the genes attributed to the phosphoinositide 3-kinases (PI3K) axis have attracted special attention as they were altered in more than 90% of the tissues isolated from HNSCC patients. In fact, the association between these aberrancies and the increased risk of cancer metastasis suggested this axis as an "Achilles Heel" of HNSCC, which may be therapeutically targeted. The results of the clinical trials investigating the therapeutic potential of the inhibitors targeting the components of the PI3K axis in the treatment of HNSCC patients, either alone or in a combined-modal strategy, opened a new chapter in the treatment strategy of this malignancy. The present study aimed to review the importance of the PI3K axis in the pathogenesis of HNSCC and also provide a piece of information about the breakthroughs and challenges of PI3K inhibitors in the therapeutic strategies of the disease.

Association of change in air quality with hospital admission for acute exacerbation of chronic obstructive pulmonary disease in Guangdong, China: A province-wide ecological study

AIMS

To assess possible effect of air quality improvements, we investigated the temporal change in hospital admissions for acute exacerbations of chronic obstructive pulmonary disease (AECOPD) associated with pollutant concentrations.

METHODS

We collected daily concentrations of particulate matter (i.e., PM_2.5, PM₁₀ and PM_coarse), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), ozone (O₃), and admissions for AECOPD for 21 cities in Guangdong from 2013 to 2017. We examined the association of air pollution with AECOPD admissions using two-stage time-series analysis, and estimated the annual attributable fractions, numbers, and direct hospitalization costs of AECOPD admissions with principal component analysis.

RESULTS

From 2013-2017, mean daily concentrations of SO₂, PM₁₀ and PM_2.5 declined by nearly 40%, 30%, and 26% respectively. As the average daily 8 h O₃ concentration increased considerably, the number of days exceeding WHO target (i.e.,100 μg/m³) increased from 103 in 2015-152 in 2017. For each interquartile range increase in pollutant concentration, the relative risks of AECOPD admission at lag 0-3 were 1.093 (95% CI 1.06-1.13) for PM_2.5, 1.092 (95% CI 1.08-1.11) for O₃, and 1.092 (95% CI 1.05-1.14) for SO₂. Attributable fractions of AECOPD admission advanced by air pollution declined from 9.5% in 2013 to 4.9% in 2016, then increased to 6.0% in 2017. A similar declining trend was observed for direct AECOPD hospitalization costs.

CONCLUSION

Declined attributable hospital admissions for AECOPD may be associated with the reduction in concentrations of PM_2.5, PM₁₀ and SO₂ in Guangdong, while O₃ has emerged as an important risk factor. Summarizes the main finding of the work： Reduction in PM may result in declined attributable hospitalizations for AECOPD, while O₃ has emerged as an important risk factor following an intervention.

Fine Particulate Matter (PM2.5) and Chronic Kidney Disease

The impact of ambient particulate matter (PM) on public health has become a great global concern, which is especially prominent in developing countries. For health purposes, PM is typically defined by size, with the smaller particles having more health impacts. Particles with a diameter <2.5 μm are called PM_2.5. Initial research studies have focused on the impact of PM_2.5 on respiratory and cardiovascular diseases; nevertheless, an increasing number of data suggested that PM_2.5 may affect every organ system in the human body, and the kidney is of no exception. The kidney is vulnerable to particulate matter because most environmental toxins are concentrated by the kidney during filtration. According to the high morbidity and mortality related to chronic kidney disease, it is necessary to determine the effect of PM_2.5 on kidney disease and its mechanism that needs to be identified. To understand the current status of PM_2.5 in the atmosphere and their potential harmful kidney effects in different regions of the world this review article was prepared based on peer-reviewed scientific papers, scientific reports, and database from government organizations published after the year 1998. In this review, we focus on the worldwide epidemiological evidence linking PM_2.5 with chronic kidney disease and the effect of PM_2.5 on the chronic kidney disease (CKD) progression. At the same time, we also discuss the possible mechanisms of PM_2.5 exposure leading to kidney damage, in order to emphasize the contribution of PM_2.5 to kidney damage. A global database on PM_2.5 and kidney disease should be developed to provide new ideas for the prevention and treatment of kidney disease.

Ambient Particle Components and Newborn Blood Pressure in Project Viva

Background

Both elemental metals and particulate air pollution have been reported to influence adult blood pressure (BP). The aim of this study is to examine which elemental components of particle mass with diameter ≤2.5 μm (PM_2.5) are responsible for previously reported associations between PM_2.5 and neonatal BP.

Methods and Results

We studied 1131 mother‐infant pairs in Project Viva, a Boston‐area prebirth cohort. We measured systolic BP (SBP) and diastolic BP (DBP) at a mean age of 30 hours. We calculated average exposures during the 2 to 7 days before birth for the PM_2.5 components—aluminum, arsenic, bromine, sulfur, copper, iron, zinc, nickel, vanadium, titanium, magnesium, potassium, silicon, sodium, chlorine, calcium, and lead—measured at the Harvard supersite. Adjusting for covariates and PM_2.5, we applied regression models to examine associations between PM_2.5 components and median SBP and DBP, and used variable selection methods to select which components were more strongly associated with each BP outcome. We found consistent results with higher nickel associated with significantly higher SBP and DBP, and higher zinc associated with lower SBP and DBP. For an interquartile range increase in the log Z score (1.4) of nickel, we found a 1.78 mm Hg (95% CI, 0.72–2.84) increase in SBP and a 1.30 (95% CI, 0.54–2.06) increase in DBP. Increased zinc (interquartile range log Z score 1.2) was associated with decreased SBP (−1.29 mm Hg; 95% CI, −2.09 to −0.50) and DBP (−0.85 mm Hg; 95% CI: −1.42 to −0.29).

Conclusions

Our findings suggest that prenatal exposures to particulate matter components, and particularly nickel, may increase newborn BP.

Diesel Exhaust Particulates Induce Neutrophilic Lung Inflammation by Modulating Endoplasmic Reticulum Stress-Mediated CXCL1/KC Expression in Alveolar Macrophages

Diesel exhaust particulates (DEP) have adverse effects on the respiratory system. Endoplasmic reticulum (ER) abnormalities contribute to lung inflammation. However, the relationship between DEP exposure and ER stress in the respiratory immune system and especially the alveolar macrophages (AM) is poorly understood. Here, we examined ER stress and inflammatory responses using both in vivo and in vitro study. For in vivo study, mice were intratracheally instilled with 25, 50, and 100 μg DEP and in vitro AM were stimulated with DEP at 1, 2, and 3 mg/mL. DEP increased lung weight and the number of inflammatory cells, especially neutrophils, and inflammatory cytokines in bronchoalveolar lavage fluid of mice. DEP also increased the number of DEP-pigmented AM and ER stress markers including bound immunoglobulin protein (BiP) and CCAAT/enhancer binding protein-homologous protein (CHOP) were upregulated in the lungs of DEP-treated mice. In an in vitro study, DEP caused cell damage, increased intracellular reactive oxygen species, and upregulated inflammatory genes and ER stress-related BiP, CHOP, splicing X-box binding protein 1, and activating transcription factor 4 expressions in AM. Furthermore, DEP released the C-X-C Motif Chemokine Ligand 1 (CXCL1/KC) in AM. In conclusion, DEP may contribute to neutrophilic lung inflammation pathogenesis by modulating ER stress-mediated CXCL1/KC expression in AM.

A machine learning-based model to estimate PM2.5 concentration levels in Delhi's atmosphere

During the last many years, the air quality of the capital city of India, Delhi had been hazardous. A large number of people have been diagnosed with Asthma and other breathing-related problems. The basic reason behind this has been the high concentration of life-threatening PM2.5 particles dissolved in its atmosphere. A good model, to forecast the concentration level of these dissolved particles, may help to prepare the residents with better prevention and safety strategies in order to save them from many health-related diseases. This work aims to forecast the PM2.5 concentration levels in various regions of Delhi on an hourly basis, by applying time series analysis and regression, based on various atmospheric and surface factors such as wind speed, atmospheric temperature, pressure, etc. The data for the analysis is obtained from various weather monitoring sites, set-up in the city, by the Indian Meteorological Department (IMD). A regression model is proposed, which uses Extra-Trees regression and AdaBoost, for further boosting. Experimentation for comparative study with the recent works is done and results indicate the efficacy of the proposed model.

Short-term effects of particulate matter on cardiovascular morbidity in Italy: a national analysis

AIMS

We aimed at investigating the relationship between particulate matter (PM) and daily admissions for cardiovascular diseases (CVDs) at national level in Italy.

METHODS AND RESULTS

Daily numbers of cardiovascular hospitalizations were collected for all 8084 municipalities of Italy, in the period 2013-2015. A satellite-based spatiotemporal model was used to estimate daily PM10 (inhalable particles) and PM2.5 (fine particles) concentrations at 1-km2 resolution. Multivariate Poisson regression models were fit to estimate the association between daily PM and cardiovascular admissions. Flexible functions were estimated to explore the shape of the associations at low PM concentrations, also in non-urban areas. We analysed 2 154 810 acute hospitalizations for CVDs (25% stroke, 24% ischaemic heart diseases, 22% heart failure, and 5% atrial fibrillation). Relative increases of total cardiovascular admissions, per 10 µg/m3 variation in PM10 and PM2.5 at lag 0-5 (average of last 6 days since admission), were 0.55% (95% confidence intervals: 0.32%, 0.77%) and 0.97% (0.67%, 1.27%), respectively. The corresponding estimates for heart failure were 1.70% (1.28%, 2.13%) and 2.66% (2.09%, 3.23%). We estimated significant effects of PM10 and PM2.5 also on ischaemic heart diseases, myocardial infarction, atrial fibrillation, and ischaemic stroke. Associations were similar between less and more urbanized areas, and persisted even at low concentrations, e.g. below WHO guidelines.

CONCLUSION

PM was robustly associated with peaks in daily cardiovascular admissions, especially for heart failure, both in large cities and in less urbanized areas of Italy. Current WHO Air Quality Guidelines for PM10 and PM2.5 are not sufficient to protect public health.

Temporal variations of short-term effects of particulate matter on hospital admissions in the most densely populated city in Thailand

Short-term effects of ambient particulate matter (PM) on daily hospital admissions have been comprehensively elucidated, but very few studies evaluated the temporal variations of ambient PM associated with hospital admissions, especially in developing countries. This study aimed to explore the temporal changes of the short-term effects of PM₁₀ on hospital admissions in Bangkok, Thailand from 2006 to 2014. The overdispersed Poisson regression model was applied to related daily PM₁₀ concentrations to daily cardiovascular and respiratory hospital admissions by adjusting for temperature, humidity, long-term trend and seasonality, day of the week, public holiday, and population dynamics. The temporal variations of the effects of PM₁₀ on hospital admissions were assessed by adding an interaction term between PM₁₀ concentration and predefined time periods into the model. The relative risks per 10 μg/m³ increase in PM₁₀ were 1.0092 (95% CI: 1.0046, 1.0138) for cardiovascular admissions at lag 0-3 day and 1.0209 (95% CI: 1.0145, 1.0273) for respiratory admissions at lag 0-7 day over the entire study period. Despite non-homogenous decreasing trends in annual PM₁₀ concentrations during the study period, the effects of PM₁₀ on cardiovascular and respiratory admissions remained significant and even showed an increasing trend for cardiovascular admissions. Specifically, the relative risks of cardiovascular admission per 10 μg/m³ increase in PM₁₀ were 1.0050 (95% CI: 0.9965, 1.0135), 1.0086 (95% CI: 1.0000, 1.0174), and 1.0103 (95% CI: 1.0041, 1.0165) for the period of 2006-2008, 2009-2011, and 2012-2014, respectively (p-value for interaction <0.01). This finding indicated that estimated effects of PM₁₀ on cardiovascular admissions significantly changed over time, speculating that the composition of PM₁₀ might have changed and introduced the alterations of overall toxicity of PM₁₀. Therefore, the efforts on air pollution control need to be continued to reduce health effects of PM₁₀ in the future.

Review: Strategies for using satellite-based products in modeling PM2.5 and short-term pollution episodes

Short-term air pollution episodes motivate improved understanding of the association between air pollution and acute morbidity and mortality episodes, and triggers required mitigation plans. A variety of methods have been employed to estimate exposure to air pollution episodes, including GIS-based dispersion models, interpolation between sparse monitoring sites, land-use regression models, optimization models, line- or area-dispersion plume models, and models using information from imaging satellites, often including land-use and meteorological variables. There has been increasing use of satellite-borne aerosol products for assessing short-term air quality events. They provide better spatial coverage, but currently at the price of low temporal coverage and rather crude spatial resolution. This is a brief review on using satellite data for modeling short-term air quality and pollution events. The review can be pursued as a practical guide for modeling air quality with satellite-based products, as it includes important questions that should be considered in both the study design as well as the model development stages. Progress in this field is detailed and includes published models and their use in environmental and health studies. Both current and future satellite-borne capabilities are covered. It also provides links to access and download relevant datasets and some example R code for data processing and modeling.

County-level variation in the long-term association between PM2.5 and lung cancer mortality in China

INTRODUCTION

The relative risk (RR) of long-term exposure to PM_2.5 in lung cancer mortality (LCM) may vary spatially in China. However, previous studies applying global regression have been unable to capture such variation. We aimed to employ a geographically weighted Poisson regression (GWPR) to estimate the RRs of LCM among the elderly (≥65 years) related to long-term exposure to PM_2.5 and the LCM attributable to PM_2.5 at the county level in China.

METHODS

We obtained annual LCM in the elderly between 2013 and 2015 from the National Death Surveillance. We linked annual mean concentrations of PM_2.5 between 2000 and 2004 with LCM using GWPR model at 148 counties across mainland China, adjusting for smoking and socioeconomic covariates. We used county-specific GWPR models to estimate annual average LCM in the elderly between 2013 and 2015 attributable to PM_2.5 exposure between 2000 and 2004.

RESULTS

The magnitude of the association between long-term exposure to PM_2.5 and LCM varied with county. The median of county-specific RRs of LCM among elderly men and women was 1.52 (range: 0.90, 2.40) and 1.49 (range: 0.88, 2.56) for each 10 μg/m³ increment in PM_2.5, respectively. The RRs were positively significant (P < 0.05) at 95% (140/148) of counties among both elderly men and women. Higher RRs of PM_2.5 among elderly men were located at Southwest and South China, and higher RRs among elderly women were located at Northwest, Southwest, and South China. There were 99,967 and 54,457 lung cancer deaths among elderly men and women that could be attributed to PM_2.5, with the attributable fractions of 31.4% and 33.8%, respectively.

CONCLUSIONS

The relative importance of long-term exposure to PM_2.5 in LCM differed by county. The results could help the government design tailored and efficient interventions. More stringent PM_2.5 control is urgently needed to reduce LCM in China.

Quantification of toxic metals using machine learning techniques and spark emission spectroscopy

The United States Environmental Protection Agency (US EPA) list of hazardous air pollutants (HAPs) includes toxic metal suspected or associated with development of cancer. Traditional techniques for detecting and quantifying toxic metals in the atmosphere are either not real time, hindering identification of sources, or limited by instrument costs. Spark emission spectroscopy is a promising and cost-effective technique that can be used for analyzing toxic metals in real time. Here, we have developed a cost-effective spark emission spectroscopy system to quantify the concentration of toxic metals targeted by the US EPA. Specifically, Cr, Cu, Ni, and Pb solutions were diluted and deposited on the ground electrode of the spark emission system. The least absolute shrinkage and selection operator (LASSO) was optimized and employed to detect useful features from the spark-generated plasma emissions. The optimized model was able to detect atomic emission lines along with other features to build a regression model that predicts the concentration of toxic metals from the observed spectra. The limits of detections (LODs) were estimated using the detected features and compared to the traditional single-feature approach. LASSO is capable of detecting highly sensitive features in the input spectrum; however, for some toxic metals the single-feature LOD marginally outperforms LASSO LOD. The combination of low-cost instruments with advanced machine learning techniques for data analysis could pave the path forward for data-driven solutions to costly measurements.

Health and economic impacts of air pollution induced by weather extremes over the continental U.S

Extreme weather events may enhance ozone (O₃) and fine particulate matter (PM_2.5) pollution, causing additional adverse health effects. This work aims to evaluate the health and associated economic impacts of changes in air quality induced by heat wave, stagnation, and compound extremes under the Representative Concentration Pathways (RCP) 4.5 and 8.5 climate scenarios. The Environmental Benefits Mapping and Analysis Program-Community Edition is applied to estimate health and related economic impacts of changes in surface O₃ and PM_2.5 levels due to heat wave, stagnation, and compound extremes over the continental U.S. during past (i.e., 2001-2010) and future (i.e., 2046-2055) decades under the two RCP scenarios. Under the past and future decades, the weather extremes-induced concentration increases may lead to several tens to hundreds O₃-related deaths and several hundreds to over ten thousands PM_2.5-related deaths annually. High mortalities and morbidities are estimated for populated urban areas with strong spatial heterogeneities. The estimated annual costs for these O₃ and PM_2.5 related health outcomes are $5.5-12.5 and $48.6-140.7 billion U.S. dollar for mortalities, and $8.9-97.8 and $19.5-112.5 million for morbidities, respectively. Of the extreme events, the estimated O₃- and PM_2.5-related mortality and morbidity attributed to stagnation are the highest, followed by heat wave or compound extremes. Large increases in heat wave and compound extreme events in the future decade dominate changes in mortality during these two extreme events, whereas population growth dominates changes in mortality during stagnation that is projected to occur less frequently. Projected reductions of anthropogenic emissions under bothRCP scenarios compensate for the increased mortality due to increasedoccurrence for heat wave and compound extremes in the future. These results suggest a need to further reduce air pollutant emissions during weather extremes to minimize the adverse impacts of weather extremes on air quality and human health.

Lung function of primary cooks using LPG or biomass and the effect of particulate matter on airway epithelial barrier integrity

BACKGROUND

Cooks exposed to biomass fuel experience increased risk of respiratory disease and mortality. We sought to characterize lung function and environmental exposures of primary cooking women using two fuel-types in southeastern India, as well as to investigate the effect of particulate matter (PM) from kitchens on human airway epithelial (HAE) cells in vitro.

METHODS

We assessed pre- and post-bronchodilator lung function on 25 primary female cooks using wood biomass or liquified petroleum gas (LPG), and quantified exposures from 34 kitchens (PM_2.5, PM < 40 μm, black carbon, endotoxin, and PM metal and bacterial content). We then challenged HAE cells with PM, assessing its cytotoxicity to small-airway cells (A549) and its effect on: transepithelial conductance and macromolecule permeability (NuLi cells), and antimicrobial activity (using airway surface liquid, ASL, from primary HAE cells).

RESULTS

Lung function was impaired in cooks using both fuel-types. 60% of participants in both fuel-types had respiratory restriction (post bronchodilator FEV₁/FVC>90). The remaining 40% in the LPG group had normal spirometry (post FEV₁/FVC = 80-90), while only 10% of participants in the biomass group had normal spirometry, and the remaining biomass cooks (30%) had respiratory obstruction (post FEV₁/FVC<80). Significant differences were found in environmental parameters, with biomass kitchens containing greater PM_2.5, black carbon, zirconium, arsenic, iron, vanadium, and endotoxin concentrations. LPG kitchens tended to have more bacteria (p = 0.14), and LPG kitchen PM had greater sulphur concentrations (p = 0.02). In vitro, PM induced cytotoxicity in HAE A549 cells in a dose-dependent manner, however the effect was minimal and there were no differences between fuel-types. PM from homes of participants with a restrictive physiology increased electrical conductance of NuLi HAE cells (p = 0.06) and decreased macromolar permeability (p ≤ 0.05), while PM from homes of those with respiratory obstruction tended to increase electrical conductance (p = 0.20) and permeability (p = 0.07). PM from homes of participants with normal spirometry did not affect conductance or permeability. PM from all homes tended to inhibit antimicrobial activity of primary HAE cell airway surface liquid (p = 0.06).

CONCLUSIONS

Biomass cooks had airway obstruction, and significantly greater concentrations of kitchen environmental contaminants than LPG kitchens. PM from homes of participants with respiratory restriction and obstruction altered airway cell barrier function, elucidating mechanisms potentially responsible for respiratory phenotypes observed in biomass cooks.

Air Pollution, Stress, and Allostatic Load: Linking Systemic and Central Nervous System Impacts

 Air pollution is a risk factor for cardiovascular and respiratory morbidity and mortality. A growing literature also links exposure to diverse air pollutants (e.g., nanoparticles, particulate matter, ozone, traffic-related air pollution) with brain health, including increased incidence of neurological and psychiatric disorders such as cognitive decline, dementia (including Alzheimer’s disease), anxiety, depression, and suicide. A critical gap in our understanding of adverse impacts of pollutants on the central nervous system (CNS) is the early initiating events triggered by pollutant inhalation that contribute to disease progression. Recent experimental evidence has shown that particulate matter and ozone, two common pollutants with differing characteristics and reactivity, can activate the hypothalamic-pituitary-adrenal (HPA) axis and release glucocorticoid stress hormones (cortisol in humans, corticosterone in rodents) as part of a neuroendocrine stress response. The brain is highly sensitive to stress: stress hormones affect cognition and mental health, and chronic stress can produce profound biochemical and structural changes in the brain. Chronic activation and/or dysfunction of the HPA axis also increases the burden on physiological stress response systems, conceptualized as allostatic load, and is a common pathway implicated in many diseases. The present paper provides an overview of how systemic stress-dependent biological responses common to particulate matter and ozone may provide insight into early CNS effects of pollutants, including links with oxidative, inflammatory, and metabolic processes. Evidence of pollutant effect modification by non-chemical stressors (e.g., socioeconomic position, psychosocial, noise), age (prenatal to elderly), and sex will also be reviewed in the context of susceptibility across the lifespan.

Chemical identity and cardiovascular toxicity of hydrophobic organic components in PM2.5

Numerous experimental and epidemiological studies have demonstrated that exposure to PM_2.5 may result in pathogenesis of several major cardiovascular diseases (CVDs), which can be attributed to the combined adverse effects induced by the complicated components of PM_2.5. Organic materials, which are major components of PM_2.5, contain thousands of chemicals, and most of them are environmental hazards. However, the contamination profile and contribution to overall toxicity of PM_2.5-bound organic components (OCs) have not been thoroughly evaluated yet. Herein, we aim to provide an overview of the literature on PM_2.5-bound hydrophobic OCs, with an emphasis on the chemical identity and reported impairments on the cardiovascular system, including the potential exposure routes and mechanisms. We first provide an update on the worldwide mass concentration and composition data of PM_2.5, and then, review the contamination profile of PM_2.5-bound hydrophobic OCs, including constitution, concentration, distribution, formation, source, and identification. In particular, the link between exposure to PM_2.5-bound hydrophobic OCs and CVDs and its possible underlying mechanisms are discussed to evaluate the possible risks of PM_2.5-bound hydrophobic OCs on the cardiovascular system and to provide suggestions for future studies.

Fine particular matter and its constituents in air pollution and gestational diabetes mellitus

BACKGROUND

Ambient air pollution has been linked to the development of gestational diabetes mellitus (GDM). However, previous studies provided inconsistent findings and no study has examined the effects of complex chemical constituents of the particular matter on GDM, especially in developing countries. Therefore, we aim to investigate the associations of exposure to PM_2.5 (particular matter ≤ 2.5 μm) and its constituents with GDM, and to identify susceptible exposure window in a large survey in China.

METHODS

The China Labor and Delivery Survey was a cross-sectional investigation conducted in 24 provinces in China between 2015 and 2016. A random sample of all deliveries in each participating hospital was selected and detailed obstetric and newborn information was extracted from medical records. Average concentrations of PM_2.5 and six constituents (organic matter, black carbon, sulfate, nitrate, ammonium and soil dust) were estimated (1 km × 1 km) using a combined geoscience-statistical model. GDM was diagnosed based on an oral glucose tolerance test (OGTT) between 24 to 28 weeks of gestation and according to IADPSG criteria. Generalized linear mixed models were used to adjust for potential confounders.

RESULTS

A total of 54,517 subjects from 55 hospitals were included. The incidence of GDM was 10.8%. An interquartile range (IQR) increase in PM_2.5 exposure in the 2nd trimester of pregnancy was associated with an increased GDM risk in the single pollutant model, [adjusted odds ratio (aOR) = 1.11 and 95% confidence interval (CI): 1.01-1.22]. Exposure to organic matter (aOR = 1.14; 95%CI: 1.05-1.23), black carbon (aOR = 1.15; 95%CI: 1.07-1.25) and nitrate (aOR = 1.13; 95%CI: 1.02-1.24) during 2nd trimester were associated with increased risks of GDM. Associations between constituents and GDM were robust after controlling for total PM_2.5 mass and accounting for multi-collinearity.

CONCLUSIONS

Exposure to PM_2.5 in 2^nd trimester of pregnancy was associated with an increased risk of GDM. Organic matter, black carbon and nitrate may be the main culprits for the association.

Effects of Ultrafine Particles in Ambient Air on Primary Health Care Consultations for Diabetes in Children and Elderly Population in Ljubljana, Slovenia: A 5-Year Time-Trend Study

Epidemiological studies indicate that exposure to ultrafine particles (UFP) in ambient air represents an important environmental public health issue. The aim of this study was to determine the association between UFP in ambient air and the daily number of consultations in the primary health care unit due to diabetes mellitus in children and elderly population of the Municipality of Ljubljana. A 5-year time-trend ecological study was carried out for the period between 1 January 2013 and 31 December 2017. The daily number of primary health care consultations due to diabetes mellitus among children and elderly population was observed as the health outcome. Daily mean UFP concentrations (different size from 10 to 100 nm) were measured and calculated. Poisson regression analysis was used to investigate the association between the observed outcome and the daily UFP, particulate matter fine fraction (PM_2.5), and particulate matter coarse fraction (PM₁₀) concentrations, adjusted to other covariates. The results show that the daily number of consultations due to diabetes mellitus were highly significantly associated with the daily concentrations of UFP (10 to 20 nm; p ≤ 0.001 and 20 to 30 nm; p ≤ 0.001) in all age groups and in the elderly population. In observed the population of children, we did not confirm the association. Findings indicate that specified environmental challenges should be addressed by comprehensive public health strategies leading to the coordinated cross-sectoral measures for the reduction of UFP in ambient air and the mitigation of adverse health effects.

The potential impact of bushfire smoke on brain health

Smoke from bushfires (also known as wildfires or forest fires) has blanketed large regions of Australia during the southern hemisphere summer of 2019/2020, potentially endangering residents who breathe the polluted air. While such air pollution is known to cause respiratory irritation and damage, its effect on the brain is not well described. In this review, we aim to outline the potentially damaging effects of bushfire smoke on brain health. We also describe the composition of air pollution, including ambient particulate matter (PM) and bushfire PM, before covering the general health effects of each. The investigated entry routes for ambient PM and postulated entry routes for bushfire PM are discussed, along with epidemiological and experimental evidence of the effect of both PMs in the brain. It appears that bushfire PM may be more toxic than ambient PM, and that it may enter the brain through extrapulmonary or olfactory routes to cause inflammation and oxidative stress. Ultimately, this review highlights the desperate requirement of greater research into the effects of bushfire PM on brain health.

Organ-on-a-Chip: Opportunities for Assessing the Toxicity of Particulate Matter

Recent developments in epidemiology have confirmed that airborne particulates are directly associated with respiratory pathology and mortality. Although clinical studies have yielded evidence of the effects of many types of fine particulates on human health, it still does not have a complete understanding of how physiological reactions are caused nor to the changes and damages associated with cellular and molecular mechanisms. Currently, most health assessment studies of particulate matter (PM) are conducted through cell culture or animal experiments. The results of such experiments often do not correlate with clinical findings or actual human reactions, and they also cause difficulty when investigating the causes of air pollution and associated human health hazards, the analysis of biomarkers, and the development of future pollution control strategies. Microfluidic-based cell culture technology has considerable potential to expand the capabilities of conventional cell culture by providing high-precision measurement, considerably increasing the potential for the parallelization of cellular assays, ensuring inexpensive automation, and improving the response of the overall cell culture in a more physiologically relevant context. This review paper focuses on integrating the important respiratory health problems caused by air pollution today, as well as the development and application of biomimetic organ-on-a-chip technology. This more precise experimental model is expected to accelerate studies elucidating the effect of PM on the human body and to reveal new opportunities for breakthroughs in disease research and drug development.

Relationship between air pollution and hospitalizations for congestive heart failure in elderly people in the city of São Paulo

To evaluate the effects of air pollutants on hospitalizations of elderly people for congestive heart failure (CHF) in the city of São Paulo, stratified by sex, exploring lag structures, from 2000 to 2013. Ecological time series study using information on hospitalization of elderly patients for CHF (ICD-10th: I50) obtained from DATASUS for the city of São Paulo. Information on O₃, PM₁₀, NO₂, SO₂, CO, temperature and humidity was obtained from CETESB. Descriptive analyses, Pearson correlation, and generalized linear Poisson regression model were applied to estimate the effects of pollutants. The interquartile variations of O₃ (52.45 μg/m³), PM₁₀ (24.28 μg/m³), NO₂ (7.63 μg/m³), SO₂ (50.22 μg/m³), and CO (1.28 ppm) were associated with increased hospitalizations for CHF. Air pollutants continue to be a factor that contributes to the increase in the number of hospitalizations due to CHF.

Chemical content and source apportionment of 36 heavy metal analysis and health risk assessment in aerosol of Beijing

The concentration levels of 36 airborne heavy metals and atmospheric radioactivity in total suspended particulate (TSP) samples were measured to investigate the chemical characteristics, potential sources of aerosols, and health risk in Beijing, China, from September 2016 to September 2017. The TSP concentrations varied from 6.93 to 469.18 μg/m³, with a median of 133.97 μg/m³. The order for the mean concentrations of heavy metals, known as hazardous air pollutants (HAPs), was as follows: Mn > Pb > As > Cr > Ni > Se > Cd > Co > Sb > Hg > Be; Non-Designated HAPs Metals: Ca > Fe > Mg > Al > K > Na > Zn > P > Ba > Ti > Cu > Sr > B > Sn > I > V > Rb > Ce > Mo > Cs > Th > Ag > U > Pt. The median concentration of As was higher than China air quality standard (6 ng/m³). The gross α and β concentration levels in aerosols were (1.84 ± 1.59) mBg/m³ and (1.15 ± 0.85) mBg/m³, respectively. The enrichment factor values of Cu, Ba, B, Ce, Tl, Cs, Pb, As, Cd, Sb, Hg, Fe, Zn, Sn, I, Mo, and Ag were higher than 10, which indicated enriched results from anthropogenic sources. Pb, As, and Cd are considered to originate from multiple sources; fireworks released Ba during China spring festival; Fe, Ce, and Cs may come from stable emissions such as industrial gases. The health risks from anthropogenic metals via inhalation, ingestion, and dermal pathway were estimated on the basis of health quotient as well as the results indicated that children faced the higher risk than adults during the research period. For adults, the health risk posed by heavy metals in atmospheric particles was below the acceptable level.

Associations of annual ambient PM2.5 components with DNAm PhenoAge acceleration in elderly men: The Normative Aging Study

Current studies indicate that long-term exposure to ambient fine particulate matter (PM_2.5) is related with global mortality, yet no studies have explored relationships of PM_2.5 and its species with DNAm PhenoAge acceleration (DNAmPhenoAccel), a new epigenetic biomarker of phenotypic age. We identified which PM_2.5 species had association with DNAmPhenoAccel in a one-year exposure window in a longitudinal cohort. We collected whole blood samples from 683 elderly men in the Normative Aging Study between 1999 and 2013 (n = 1254 visits). DNAm PhenoAge was calculated using 513 CpGs retrieved from the Illumina Infinium HumanMethylation450 BeadChip. Daily concentrations of PM_2.5 species were measured at a fixed air-quality monitoring site and one-year moving averages were computed. Linear mixed-effect (LME) regression and Bayesian kernel machine (BKM) regression were used to estimate the associations. The covariates included chronological age, body mass index (BMI), cigarette pack years, smoking status, estimated cell types, batch effects etc. Benjamini-Hochberg false discovery rate at a 5% false positive threshold was used to adjust for multiple comparison. During the study period, the mean DNAm PhenoAge and chronological age in our subjects were 68 and 73 years old, respectively. Using LME model, only lead and calcium were significantly associated with DNAmPhenoAccel. For example, an interquartile range (IQR, 0.0011 μg/m³) increase in lead was associated with a 1.29-year [95% confidence interval (CI): 0.47, 2.11] increase in DNAmPhenoAccel. Using BKM model, we selected PM_2.5, lead, and silicon to be predictors for DNAmPhenoAccel. A subsequent LME model showed that only lead had significant effect on DNAmPhenoAccel: 1.45-year (95% CI: 0.46, 2.46) increase in DNAmPhenoAccel following an IQR increase in one-year lead. This is the first study that investigates long-term effects of PM_2.5 components on DNAmPhenoAccel. The results demonstrate that lead and calcium contained in PM_2.5 was robustly associated with DNAmPhenoAccel.

National secular trends in ambient air volatile organic compound levels and biomarkers of exposure in the United States

BACKGROUND

Exposure to air pollution is a leading cause of global mortality. Volatile organic compounds (VOCs) are constituents of ambient air that could exert adverse health effects.

OBJECTIVE

To examine the relationship between VOC levels in ambient air and individual-level exposure to VOCs, as assessed by urinary VOC metabolites.

METHODS

Secular trends in 11 ambient air VOCs (2005-2013) and individual-level metabolites of 14 VOCs (2005-2014) were assessed using National Monitoring Programs (NMP) and National Health and Nutrition Examination Survey (NHANES) data, respectively. To isolate environmental exposure, individuals reporting exposure to tobacco smoke were excluded. Quantile regression models were used to assess secular trends in VOC exposure, and survey-weighted regression models were built to identify factors associated with VOC exposure.

RESULTS

All annual levels of ambient VOCs decreased from 2005 to 2013 (Range: 12.5%-77.2%). However, 11 of the corresponding VOC metabolites increased during the same time (Range: 0.3%-53.6%). There was a proportional change in patterns of VOC exposure across NHANES waves, with the middle quantiles of exposure showing the largest increase. VOC exposures were significantly associated with age, sex, race, education, and physical inactivity, but not with secular VOC trends.

DISCUSSION

In the United States, individual-level exposure to several VOCs increased between 2005 and 2014 despite a decline in ambient air VOC levels. This inverse relationship suggests that ambient VOCs are not the primary source of VOC exposure, therefore, decreasing ambient VOCs alone may not be sufficient to protect against the adverse health effects associated with VOC exposure.

Inverse probability weighted distributed lag effects of short-term exposure to PM2.5 and ozone on CVD hospitalizations in New England Medicare participants - Exploring the causal effects

BACKGROUND

Although many studies have established significant associations between short-term air pollution and the risk of getting cardiovascular diseases, there is a lack of evidence based on causal distributed lag modeling.

METHODS

Inverse probability weighting (ipw) propensity score models along with conditional logistic outcome regression models based on a case-crossover study design were applied to get the causal unconstrained distributed (lag0-lag5) as well as cumulative lag effect of short-term exposure to PM2.5/Ozone on hospital admissions of acute myocardial infarction (AMI), congestive heart failure (CHF) and ischemic stroke (IS) among New England Medicare participants during 2000-2012. Effect modification by gender, race, secondary diagnosis of Chronic Obstructive Pulmonary Diseases (COPD) and Diabetes (DM) was explored.

RESULTS

Each 10 μg/m3 increase in lag0-lag5 cumulative PM2.5 exposure was associated with an increase of 4.3% (95% confidence interval: 2.2%, 6.4%, percentage change) in AMI hospital admission rate, an increase of 3.9% (2.4%, 5.5%) in CHF rate and an increase of 2.6% (0.4%, 4.7%) in IS rate. A weakened lagging effect of PM2.5 from lag0 to lag5 could be observed. No cumulative short-term effect of ozone on CVD was found. People with secondary diagnosis of COPD, diabetes, female gender and black race are sensitive population.

CONCLUSIONS

Based on our causal distributed lag modeling, we found that short-term exposure to an increased ambient PM2.5 level had the potential to induce higher risk of CVD hospitalization in a causal way. More attention should be paid to population of COPD, diabetes, female gender and black race.

Short-term Effect of Air Pollution on Tuberculosis Based on Kriged Data: A Time-series Analysis

Tuberculosis (TB) has a very high mortality rate worldwide. However, only a few studies have examined the associations between short-term exposure to air pollution and TB incidence. Our objectives were to estimate associations between short-term exposure to air pollutants and TB incidence in Wuhan city, China, during the 2015–2016 period. We applied a generalized additive model to access the short-term association of air pollution with TB. Daily exposure to each air pollutant in Wuhan was determined using ordinary kriging. The air pollutants included in the analysis were particulate matter (PM) with an aerodynamic diameter less than or equal to 2.5 micrometers (PM_2.5), PM with an aerodynamic diameter less than or equal to 10 micrometers (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and ground-level ozone (O₃). Daily incident cases of TB were obtained from the Hubei Provincial Center for Disease Control and Prevention (Hubei CDC). Both single- and multiple-pollutant models were used to examine the associations between air pollution and TB. Seasonal variation was assessed by splitting the all-year data into warm (May–October) and cold (November–April) seasons. In the single-pollutant model, for a 10 μg/m³ increase in PM_2.5, PM₁₀, and O₃ at lag 7, the associated TB risk increased by 17.03% (95% CI: 6.39, 28.74), 11.08% (95% CI: 6.39, 28.74), and 16.15% (95% CI: 1.88, 32.42), respectively. In the multi-pollutant model, the effect of PM_2.5 on TB remained statistically significant, while the effects of other pollutants were attenuated. The seasonal analysis showed that there was not much difference regarding the impact of air pollution on TB between the warm season and the cold season. Our study reveals that the mechanism linking air pollution and TB is still complex. Further research is warranted to explore the interaction of air pollution and TB.

The association between high particulate matter pollution and daily cause-specific hospital admissions: a time-series study in Yichang, China

Particulate matter (PM) air pollution is one of the major causes of morbidity and mortality in China. In this study, we estimated the short-term effects of PM on cause-specific hospitalization in Yichang, China. Daily data for PM level, meteorological factors, and hospital admissions (total hospitalization counts = 391,960) in Yichang between 2015 and 2017 were collected. We conducted a time-series study and applied a generalized additive model to evaluate the association between every 10 μg/m³ increment of PM and percent increase of hospitalization. We found positive and statistically significant associations between PM and hospital admissions for multiple outcomes, including all-cause, total respiratory, total cardiovascular diseases, and disease subcategories (hypertensive disease, coronary heart disease, stroke and the stroke subtype, chronic obstructive pulmonary disease, and lower respiratory infection). Each 10 μg/m³ increase in PM_2.5 at Lag01 (a moving average of Lag0 to Lag1), was significantly associated with an increase of 1.31% (95% CI: 0.79%, 1.83%), 1.12% (95% CI: 0.40%, 1.84%), and 1.14% (95% CI: 0.53%, 1.75%) in hospitalizations for all-cause, CVD, and respiratory, respectively. The association for PM₁₀ with all-cause, CVD, and respiratory admissions was similar but weaker than PM_2.5. The effect on admissions persisted for up to 7 days, and peaked at Lag01. The associations between PM and all-cause hospitalizations were stronger among older individuals and in cold seasons. It is therefore important to continue implementation of emission abatement and other effective measures in Yichang and other cities in China.

Short-term association between ambient air pollution and lung cancer mortality

RATIONALE

Long-term exposure to air pollution has been associated with increased lung cancer incidence and mortality. However, the short-term association between air pollution and lung cancer mortality (LCM) remains largely unknown.

METHODS

We collected daily data on particulate matter with diameter <2.5 μm (PM_2.5), particulate matter with diameter < 10 μm (PM₁₀), sulfur dioxide (SO₂), and ozone (O₃), and LCM in three of the biggest cities in China, i.e. Beijing, Chongqing, and Guangzhou, from 2013 to 2015. We first estimated city-specific relationships between air pollutants and LCM using time-series generalized linear models, adjusting for potential confounders. A classification and regression tree (CART) model was used to stratify LCM risk based on combinations of air pollutants and meteorological factors in each city. Then we pooled the city-specific associations using random-effects meta-analysis. Meta regression was used to explore if city-specific characteristics modified the air pollution-LCM association. Finally, we stratified the analyses by season, age, and sex.

RESULTS

Over the entire period, the current-day concentrations of PM_2.5 and PM₁₀ in Chongqing and PM_2.5, PM₁₀, and SO₂ in Guangzhou were positively associated with LCM (Excess risk ranged from 0.72% (95% CI 0.27%-1.17%) to 6.06% (95% CI 0.76%-11.64%) with each 10 μg/m³ increment in different pollutants), but the association between current-day air pollution and LCM in Beijing was not significant (P > 0.05). When considering the environmental and weather factors simultaneously, current-day PM_2.5, relative humidity, and PM₁₀ were the most important factors associated with LCM in Beijing, Chongqing, and Guangzhou, respectively. LCM risk related with daily PM_2.5, PM₁₀, and SO₂ significantly increased with the increasing annual mean temperature and humidity of the city, while LCM risk related with daily O₃ significantly increased with the increases of latitude, annual mean O₃ concentration, and socioeconomic level. After stratification, the current-day PM_2.5, PM₁₀, and O₃ during the warm season in Beijing and PM_2.5, PM₁₀, and SO₂ during the cool season in Chongqing and Guangzhou were positively associated with LCM (Excess risk ranged from 0.93% (95% CI 0.42%-1.45%) to 7.16% (95% CI 0.64%-14.09%) with each 10 μg/m³ increment in different pollutants). Male and the elderly lung cancer patients were more sensitive to the short-term effect of air pollution.

CONCLUSIONS

Lung cancer patients should enhance protection measures against air pollution. More attentions should be paid for the high PM_2.5, PM₁₀, and O₃ during the warm season in Beijing, and high PM_2.5, PM₁₀, and SO₂ during the cool season in Chongqing and Guangzhou.

Short term exposure to fine particulate matter and hospital admission risks and costs in the Medicare population: time stratified, case crossover study

OBJECTIVE

To assess risks and costs of hospital admission associated with short term exposure to fine particulate matter with diameter less than 2.5 µm (PM2.5) for 214 mutually exclusive disease groups.

DESIGN

Time stratified, case crossover analyses with conditional logistic regressions adjusted for non-linear confounding effects of meteorological variables.

SETTING

Medicare inpatient hospital claims in the United States, 2000-12 (n=95 277 169).

PARTICIPANTS

All Medicare fee-for-service beneficiaries aged 65 or older admitted to hospital.

MAIN OUTCOME MEASURES

Risk of hospital admission, number of admissions, days in hospital, inpatient and post-acute care costs, and value of statistical life (that is, the economic value used to measure the cost of avoiding a death) due to the lives lost at discharge for 214 disease groups.

RESULTS

Positive associations between short term exposure to PM2.5 and risk of hospital admission were found for several prevalent but rarely studied diseases, such as septicemia, fluid and electrolyte disorders, and acute and unspecified renal failure. Positive associations were also found between risk of hospital admission and cardiovascular and respiratory diseases, Parkinson's disease, diabetes, phlebitis, thrombophlebitis, and thromboembolism, confirming previously published results. These associations remained consistent when restricted to days with a daily PM2.5 concentration below the WHO air quality guideline for the 24 hour average exposure to PM2.5. For the rarely studied diseases, each 1 µg/m3 increase in short term PM2.5 was associated with an annual increase of 2050 hospital admissions (95% confidence interval 1914 to 2187 admissions), 12 216 days in hospital (11 358 to 13 075), US$31m (£24m, €28m; $29m to $34m) in inpatient and post-acute care costs, and $2.5bn ($2.0bn to $2.9bn) in value of statistical life. For diseases with a previously known association, each 1 µg/m3 increase in short term exposure to PM2.5 was associated with an annual increase of 3642 hospital admissions (3434 to 3851), 20 098 days in hospital (18 950 to 21 247), $69m ($65m to $73m) in inpatient and post-acute care costs, and $4.1bn ($3.5bn to $4.7bn) in value of statistical life.

CONCLUSIONS

New causes and previously identified causes of hospital admission associated with short term exposure to PM2.5 were found. These associations remained even at a daily PM2.5 concentration below the WHO 24 hour guideline. Substantial economic costs were linked to a small increase in short term PM2.5.

A Study on the Design Method of Indoor Fine Particulate Matter (PM2.5) Pollution Control in China

Airborne fine particulate matter (PM2.5) is an important factor affecting indoor air quality and is significantly related to human health. A lot of research has been done on PM2.5 pollution control in buildings, but there is lack of systematic indoor PM2.5 pollution control for engineering applications. In this study, first, we propose an outdoor calculated concentration of PM2.5 in 74 cities, in China, using the "not guaranteed for five days" method, which is based on outdoor PM2.5 concentration monitoring data from 2016 to 2018. Then, different levels of indoor calculated concentrations of PM2.5 (25 μg/m³, 35 μg/m³, and 75 μg/m³) are put forward. Secondly, methods for selecting air purification equipment in centralized, semi-centralized, and decentralized air conditioning systems are proposed. Finally, PM2.5 pollution control measures and system energy-saving operation strategies in buildings are put forward. This study stipulates the calculation of PM2.5 concentration, unifies design methods, proposes control measures, and standardizes operations management. The aim of this study is to provide technical guidance for engineering design, construction and operation, and therefore to reduce the risk of indoor diseases caused by exposure to PM2.5.

Biochanin A protects against PM2.5-induced acute pulmonary cell injury by interacting with the target protein MEK5

Epidemiological studies have shown that exposure to ambient fine particulate matter (PM_2.5) is associated with an increased risk for cardiopulmonary diseases. The MEK5/ERK5 and NF-κB signaling pathways are closely related to the regulation of acute pulmonary cell injury (APCI) and may play an important role in the underlying pathophysiological mechanisms. Related studies have shown that Biochanin A (BCA) effectively interferes with APCI, but the underlying mechanism through which this occurs is not fully understood. Previously, based on proteomic and bioinformatic research, we found the indispensable role of MEK5 in mediating remission effects of BCA against PM_2.5-induced lung toxicity. Therefore, using A549 adenocarcinoma human alveolar basal epithelial cells (A549 cells), we combined western blot and qRT-PCR to study the protective signaling pathways induced by BCA, indicating that MEK5/ERK5 and NF-κB are both involved in mediating APCI in response to PM_2.5, and MEK5/ERK5 positively activated NF-κB and its downstream cellular regulatory factors. BCA significantly suppressed PM_2.5-induced upregulation of MEK5/ERK5 expression and phosphorylation and activation of NF-κB. Furthermore, due to the specificity of the MEK5/ERK5 protein structure, the binding sites and binding patterns of BCA and MEK5 were analyzed using molecular docking correlation techniques, which showed that there are stable hydrogen bonds between BCA and the PB1 domain of MEK5 as well as its kinase domain. BCA forms a stable complex with MEK5, which has potential effects on MEKK2/3-MEK5-ERK5 ternary interactions, p62/αPKC-mediated NF-κB regulation, and inhibition of MEK5 target protein phosphorylation. Therefore, our study suggests that MEK5 is an important regulator of intracellular signaling of APCI in response to PM_2.5 exposure. BCA may exert anti-APCI activity by targeting MEK5 to inhibit activation of the MEK5/ERK5/NF-κB signaling pathway.

Effect of O3, PM10 and PM2.5 on cardiovascular and respiratory diseases in cities of France, Iran and Italy

At present, both tropospheric ozone (O₃) and particulate matters (PM) are among the most threatening air pollutants for human health in cities. The air pollution effects over public health include increased risk of hospital admissions and mortality for respiratory and cardiovascular diseases even when air pollutant concentrations are below European and international standards. The aim of this study was to (i) estimate the burden of mortality and morbidity for cardiovascular and respiratory diseases attributed to PM_2.5, PM₁₀ and O₃ in nine selected cities in France, Iran and Italy in 2015 and 2016 and to (ii) compare estimated burdens at current O₃ and PM levels with pre-industrial levels. The selected Mediterranean cities are among the most affected by the air pollution in Europe, in particular by rising O₃ while the selected Iranian cities rank as the most polluted by PM in the world. The software AirQ+ was used to estimate the short-term health effects, in terms of mortality and morbidity by using in situ air quality data, city-specific relative risk values and baseline incidence. Compared to pre-industrial levels, long-term exposures to ambient PM_2.5, PM₁₀ and O₃ have substantially contributed to mortality and hospital admissions in selected cities: about 8200 deaths for non-accidental causes, 2400 deaths for cardiovascular diseases, 540 deaths for respiratory diseases, 220 deaths for chronic obstructive pulmonary diseases as well as 18,800 hospital admissions for cardiovascular diseases and 3400 for respiratory diseases were reported in 2015. The study supports the need of city-specific epidemiological data and urgent strategies to mitigate the health burden of air pollution.

Health impacts and cost-benefit analyses of surface O3 and PM2.5 over the U.S. under future climate and emission scenarios

Health impacts of surface ozone (O₃) and fine particulate matter (PM_2.5) are of major concern worldwide. In this work, the Environmental Benefits Mapping and Analysis Program tool is applied to estimate the health and economic impacts of projected changes in O₃ and PM_2.5 in the U.S. in future (2046-2055) decade relative to current (2001-2010) decade under the Representative Concentration Pathway (RCP) 4.5 and 8.5 climate scenarios. Future annual-mean O₃ reductions under RCP 4.5 prevent ~1,800 all-cause mortality, 761 respiratory hospital admissions (HA), and ~1.2 million school loss days annually, and result in economic benefits of ~16 billion, 29 million, and 132 million U.S. dollars (USD), respectively. By contrast, the projected future annual-mean O₃ increases under RCP8.5 cause ~2,400 mortality, 941 respiratory HA, and ~1.6 million school loss days annually and result in economic disbenefits of ~21 billion, 36 million, and 175 million USD, respectively. Health benefits of reduced O₃ double under RCP4.5 and health dis-benefits of increased O₃ increase by 1.5 times under RCP8.5 in future with 2050 population and baseline incidence rate. Because of the reduction in projected future PM_2.5 over CONUS under both scenarios, the annual avoided all-cause deaths, cardiovascular HA, respiratory HA, and work loss days are ~63,000 and ~83,000, ~5,300 and ~7,000, ~12,000 and ~15,000, and ~7.8 million and ~10 million, respectively, leading to economic benefits of ~560 and ~740 billion, ~240 and ~320 million, ~450 and ~590 million, and ~1,400 and ~1,900 million USD for RCP4.5 and 8.5, respectively. Health benefits of reduced PM_2.5 for future almost double under both scenarios with the largest benefits in urban areas. RCP8.5 projects larger health and economic benefits due to a greater reduction in PM_2.5 but with a warmer atmosphere and higher O₃ pollution than RCP4.5. RCP4.5 leads to multiple-benefit goals including reduced O₃ and PM_2.5, reduced mortality and morbidity, and saved costs. Greater reduction in future PM_2.5 under RCP4.5 should be considered to achieve larger multi-benefits.

Climate impact on ambient PM2.5 elemental concentration in the United States: A trend analysis over the last 30 years

Weather impacts on the chemical composition of PM_2.5 varies significantly over space and time given the diversity of particle components and the complex mechanisms governing particle formation and removal. In this study, we employed generalized additive models (GAMs) to estimate weather-associated changes in PM_2.5 composition in the US during 1988-2017. We considered seven components of ambient PM_2.5, which included elemental carbon (EC), organic carbon (OC), nitrate, sulfate, sodium, ammonium, and silicon. The impact of long-term weather changes on each PM_2.5 component was defined in our study as "weather penalty". During our study period, temperature increased in four regions, including the Industrial Midwest and Northeast during the warm and cold season; and Upper Midwest and West in the cold season. Wind speed decreased in the both seasons. Relative humidity increased in the warm season and decreased in the cold season. The weather changes between 1988 and 2017 were associated with most PM_2.5 components during both warm and cold seasons. The direction and the magnitude of the weather penalty varied considerably over the space and season. In the warm season, our findings suggest a nationwide weather penalty for EC, OC, nitrate, sulfate, sodium, ammonium, and silicon of 0.04, 0.21, 0.04, 0.35, -0.01, 0.05, and 0.01 μg/m³, respectively. In the cold season, the estimated total penalty was 0.04, 0.21, 0.06, 0.04, -0.01, -0.02, and 0.02 μg/m³, respectively.

Improving and Expanding Estimates of the Global Burden of Disease Due to Environmental Health Risk Factors

BACKGROUND

The Global Burden of Disease (GBD) study, coordinated by the Institute for Health Metrics and Evaluation (IHME), produces influential, data-driven estimates of the burden of disease and premature death due to major risk factors. Expanded quantification of disease due to environmental health (EH) risk factors, including climate change, will enhance accuracy of GBD estimates, which will contribute to developing cost-effective policies that promote prevention and achieving Sustainable Development Goals.

OBJECTIVES

We review key aspects of the GBD for the EH community and introduce the Global Burden of Disease-Pollution and Health Initiative (GBD-PHI), which aims to work with IHME and the GBD study to improve estimates of disease burden attributable to EH risk factors and to develop an innovative approach to estimating climate-related disease burden-both current and projected.

METHODS

We discuss strategies for improving GBD quantification of specific EH risk factors, including air pollution, lead, and climate change. We highlight key methodological challenges, including new EH risk factors, notably evidence rating and global exposure assessment.

DISCUSSION

A number of issues present challenges to the scope and accuracy of current GBD estimates for EH risk factors. For air pollution, minimal data exist on the exposure-risk relationships associated with high levels of pollution; epidemiological studies in high pollution regions should be a research priority. For lead, the GBD's current methods do not fully account for lead's impact on neurodevelopment; innovative methods to account for subclinical effects are needed. Decisions on inclusion of additional EH risk-outcome pairs need to be guided by findings of systematic reviews, the size of exposed populations, feasibility of global exposure estimates, and predicted trends in exposures and diseases. Neurotoxicants, endocrine-disrupting chemicals, and climate-related factors should be high priorities for incorporation into upcoming iterations of the GBD study. Enhancing the scope and methods will improve the GBD's estimates and better guide prevention policy. https://doi.org/10.1289/EHP5496.

A fast divide-and-conquer sparse Cox regression

We propose a computationally and statistically efficient divide-and-conquer (DAC) algorithm to fit sparse Cox regression to massive datasets where the sample size $n_0$ is exceedingly large and the covariate dimension $p$ is not small but $n_0\gg p$. The proposed algorithm achieves computational efficiency through a one-step linear approximation followed by a least square approximation to the partial likelihood (PL). These sequences of linearization enable us to maximize the PL with only a small subset and perform penalized estimation via a fast approximation to the PL. The algorithm is applicable for the analysis of both time-independent and time-dependent survival data. Simulations suggest that the proposed DAC algorithm substantially outperforms the full sample-based estimators and the existing DAC algorithm with respect to the computational speed, while it achieves similar statistical efficiency as the full sample-based estimators. The proposed algorithm was applied to extraordinarily large survival datasets for the prediction of heart failure-specific readmission within 30 days among Medicare heart failure patients.