Daily time series for cardiovascular hospital admissions and previous day's air pollution in London, UK

The impact of short-term exposure to meteorological factors on the risk of death from hypertension and its major complications: a time series analysis based on Hefei, China

OBJECTIVES

This study aimed to reveal the short-term impact of meteorological factors on the mortality risk in hypertensive patients, providing a scientific foundation for formulating pertinent prevention and control policies.

METHODS

In this research, meteorological factor data and daily death data of hypertensive patients in Hefei City from 2015 to 2018 were integrated. Time series analysis was performed using distributed lag nonlinear model (DLNM) and generalized additive model (GAM). Furthermore, we conducted stratified analysis based on gender and age. Relative risk (RR) combined with 95% confidence interval (95% CI) was used to represent the mortality risk of single day and cumulative day in hypertensive patients.

RESULTS

Single-day lag results indicated that high daily mean temperature (T mean) (75th percentile, 24.9 °C) and low diurnal temperature range (DTR) (25th percentile, 4.20 °C) levels were identified as risk factors for death in hypertensive patients (maximum effective RR values were 1.144 and 1.122, respectively). Extremely high levels of relative humidity (RH) (95th percentile, 94.29%) reduced the risk of death (RR value was 0.893). The stratified results showed that the elderly and female populations are more susceptible to low DTR levels, whereas extremely high levels of RH have a more significant protective effect on both populations.

CONCLUSION

Overall, we found that exposure to low DTR and high T mean environments increases the risk of death for hypertensive patients, while exposure to extremely high RH environments significantly reduces the risk of death for hypertensive patients. These findings contribute valuable insights for shaping targeted prevention and control strategies.

Disentangling impacts of multiple pollutants on acute cardiovascular events in New York city: A case-crossover analysis

BACKGROUND

Ambient air pollution contributes to an estimated 6.67 million deaths annually, and has been linked to cardiovascular disease (CVD), the leading cause of death. Short-term increases in air pollution have been associated with increased risk of CVD event, though relatively few studies have directly compared effects of multiple pollutants using fine-scale spatio-temporal data, thoroughly adjusting for co-pollutants and temperature, in an exhaustive citywide hospitals dataset, towards identifying key pollution sources within the urban environment to most reduce, and reduce disparities in, the leading cause of death worldwide.

OBJECTIVES

We aimed to examine multiple pollutants against multiple CVD diagnoses, across lag days, in models adjusted for co-pollutants and meteorology, and inherently adjusted by design for non-time-varying individual and aggregate-level covariates, using fine-scale space-time exposure estimates, in an exhaustive dataset of emergency department visits and hospitalizations across an entire city, thereby capturing the full population-at-risk.

METHODS

We used conditional logistic regression in a case-crossover design - inherently controlling for all confounders not varying within case month - to examine associations between spatio-temporal nitrogen dioxide (NO2), fine particulate matter (PM2.5), sulfur dioxide (SO2), and ozone (O3) in New York City, 2005-2011, on individual risk of acute CVD event (n = 837,523), by sub-diagnosis [ischemic heart disease (IHD), heart failure (HF), stroke, ischemic stroke, acute myocardial infarction].

RESULTS

We found significant same-day associations between NO2 and risk of overall CVD, IHD, and HF - and between PM2.5 and overall CVD or HF event risk - robust to all adjustments and multiple comparisons. Results were comparable by sex and race - though median age at CVD was 10 years younger for Black New Yorkers than White New Yorkers. Associations for NO2 were comparable for adults younger or older than 69 years, though PM2.5 associations were stronger among older adults.

DISCUSSION

Our results indicate immediate, robust effects of combustion-related pollution on CVD risk, by sub-diagnosis. Though acute impacts differed minimally by age, sex, or race, the much younger age-at-event for Black New Yorkers calls attention to cumulative social susceptibility.

The impact of air quality on cardiovascular health: A state of the art review

Air pollution is a global health challenge, increasing the risk of cardiovascular diseases such as heart disease, stroke, and arrhythmias. Particulate matter (PM), particularly PM2.5 and ultrafine particles (UFP), is a key contributor to the adverse effects of air pollution on cardiovascular health. PM exposure can lead to oxidative stress, inflammation, atherosclerosis, vascular dysfunction, cardiac arrhythmias, and myocardial injury. Reactive oxygen species (ROS) play a key role in mediating these effects. PM exposure can also lead to hypertension, a significant risk factor for cardiovascular disease. The COVID-19 pandemic resulted in a significant reduction of air pollutants, leading to a decline in the incidence of heart attacks and premature deaths caused by cardiovascular diseases. This review highlights the relationship between environmental air quality and cardiovascular health, elucidating the pathways through which air pollutants affect the cardiovascular system. It also emphasizes the need for increased awareness, collective efforts to mitigate the adverse effects of air pollution, and strategic policies for long-term air quality improvement to prevent the devastating effects of air pollution on global cardiovascular health.

Uncertainties in source allocation of carbonaceous aerosols in a Mediterranean region

Understanding the atmospheric processes involving carbonaceous aerosols (CAs) is crucial for assessing air pollution impacts on human health and climate. The sources and formation mechanisms of CAs are not well understood, making it challenging to quantify impacts in models. Studies suggest residential wood combustion (RWC) and traffic significantly contribute to CAs in Europe's urban and rural areas. Here, we used an atmospheric chemistry model (MONARCH) and three different emission inventories (two versions of the European-scale emission inventory CAMS-REG_v4 and the HERMESv3 detailed national inventory for Spain) to assess the uncertainties in CAs simulation and source allocation (from traffic, RWC, shipping, fires and others) in Northeast Spain. For this, black carbon (BC) and organic aerosol (OA) measurements performed at three supersites representing different environments (urban, regional and remote) were used. Our findings show the importance of model resolution and detailed emission input data in accurately reproducing BC/OA observations. Even though emissions of total particulate matter are rather consistent between inventories in Spain, we found discrepancies between them mainly related to the spatiotemporal disaggregation (particularly relevant for traffic and RWC) and the treatment of the condensable fraction of CAs in RWC (changes in the speciation of elemental/organic carbon). The main source contribution to BC concentrations in the urban site is traffic, accounting for 71.1%/65.2% (January/July) in close agreement with the fossil contribution derived from observations (78.8%/84.2%), followed by RWC (12.8%/3%) and shipping emissions (5.4%/13.8%). An over-representation of RWC (winter) and shipping (summer) is obtained with CAMS-REG_v4. Noteworthy uncertainties arise in OA results due to condensables in emissions and a limited secondary aerosol production in the model. These findings offer insights into MONARCH's effectiveness in simulating CAs concentrations and source contribution in Northeast Spain. The study highlights the benefits of combining new datasets and modeling techniques to refine emission inventories and better understand and mitigate air pollution impacts.

Analyzing and Forecasting Pediatric Fever Clinic Visits in High Frequency Using Ensemble Time-Series Methods After the COVID-19 Pandemic in Hangzhou, China: Retrospective Study

BACKGROUND

The COVID-19 pandemic has significantly altered the global health and medical landscape. In response to the outbreak, Chinese hospitals have established 24-hour fever clinics to serve patients with COVID-19. The emergence of these clinics and the impact of successive epidemics have led to a surge in visits, placing pressure on hospital resource allocation and scheduling. Therefore, accurate prediction of outpatient visits is essential for informed decision-making in hospital management.

OBJECTIVE

Hourly visits to fever clinics can be characterized as a long-sequence time series in high frequency, which also exhibits distinct patterns due to the particularity of pediatric treatment behavior in an epidemic context. This study aimed to build models to forecast fever clinic visit with outstanding prediction accuracy and robust generalization in forecast horizons. In addition, this study hopes to provide a research paradigm for time-series forecasting problems, which involves an exploratory analysis revealing data patterns before model development.

METHODS

An exploratory analysis, including graphical analysis, autocorrelation analysis, and seasonal-trend decomposition, was conducted to reveal the seasonality and structural patterns of the retrospective fever clinic visit data. The data were found to exhibit multiseasonality and nonlinearity. On the basis of these results, an ensemble of time-series analysis methods, including individual models and their combinations, was validated on the data set. Root mean square error and mean absolute error were used as accuracy metrics, with the cross-validation of rolling forecasting origin conducted across different forecast horizons.

RESULTS

Hybrid models generally outperformed individual models across most forecast horizons. A novel model combination, the hybrid neural network autoregressive (NNAR)-seasonal and trend decomposition using Loess forecasting (STLF), was identified as the optimal model for our forecasting task, with the best performance in all accuracy metrics (root mean square error=20.1, mean absolute error=14.3) for the 15-days-ahead forecasts and an overall advantage for forecast horizons that were 1 to 30 days ahead.

CONCLUSIONS

Although forecast accuracy tends to decline with an increasing forecast horizon, the hybrid NNAR-STLF model is applicable for short-, medium-, and long-term forecasts owing to its ability to fit multiseasonality (captured by the STLF component) and nonlinearity (captured by the NNAR component). The model identified in this study is also applicable to hospitals in other regions with similar epidemic outpatient configurations or forecasting tasks whose data conform to long-sequence time series in high frequency exhibiting multiseasonal and nonlinear patterns. However, as external variables and disruptive events were not accounted for, the model performance declined slightly following changes in the COVID-19 containment policy in China. Future work may seek to improve accuracy by incorporating external variables that characterize moving events or other factors as well as by adding data from different organizations to enhance algorithm generalization.

Effect of Air Pollution on Heart Failure: Systematic Review and Meta-Analysis

BACKGROUND

Heart failure (HF) poses a significant global disease burden. The current evidence on the impact of air pollution on HF remains inconsistent.

OBJECTIVES

We aimed to conduct a systematic review of the literature and meta-analysis to provide a more comprehensive and multiperspective assessment of the associations between short- and long-term air pollution exposure and HF from epidemiological evidences.

METHODS

Three databases were searched up to 31 August 2022 for studies investigating the association between air pollutants (PM 2.5 , PM 10 , NO 2 , SO 2 , CO, O 3 ) and HF hospitalization, incidence, or mortality. A random effects model was used to derive the risk estimations. Subgroup analysis was conducted by geographical location, age of participants, outcome, study design, covered area, the methods of exposure assessment, and the length of exposure window. Sensitivity analysis and adjustment for publication bias were performed to test the robustness of the results.

RESULTS

Of 100 studies covering 20 countries worldwide, 81 were for short-term and 19 were for long-term exposure. Almost all air pollutants were adversely associated with the risk of HF in both short- and long-term exposure studies. For short-term exposures, we found the risk of HF increased by 1.8% [relative risk ( RR ) = 1.018 , 95% confidence interval (CI): 1.011, 1.025] and 1.6% (RR = 1.016 , 95% CI: 1.011, 1.020) per 10 - μ g / m 3 increment of PM 2.5 and PM 10 , respectively. HF was also significantly associated with NO 2 , SO 2 , and CO, but not O 3 . Positive associations were stronger when exposure was considered over the previous 2 d (lag 0-1) rather than on the day of exposure only (lag 0). For long-term exposures, there were significant associations between several air pollutants and HF with RR (95% CI) of 1.748 (1.112, 2.747) per 10 - μ g / m 3 increment in PM 2.5 , 1.212 (1.010, 1.454) per 10 - μ g / m 3 increment in PM 10 , and 1.204 (1.069, 1.356) per 10 -ppb increment in NO 2 , respectively. The adverse associations of most pollutants with HF were greater in low- and middle-income countries than in high-income countries. Sensitivity analysis demonstrated the robustness of our results.

DISCUSSION

Available evidence highlighted adverse associations between air pollution and HF regardless of short- and long-term exposure. Air pollution is still a prevalent public health issue globally and sustained policies and actions are called for to reduce the burden of HF. https://doi.org/10.1289/EHP11506.

A method for calibrating measurement data of a micro air quality monitor based on MLR-BRT-ARIMA combined model

A micro air quality monitor can realize grid monitoring and real-time monitoring of air pollutants. Its development can effectively help human beings to control air pollution and improve air quality. However, affected by many factors, the measurement accuracy of micro air quality monitors needs to be improved. In this paper, a combined calibration model of Multiple Linear Regression, Boosted Regression Tree and AutoRegressive Integrated Moving Average model (MLR-BRT-ARIMA) is proposed to calibrate the measurement data of the micro air quality monitor. First, the very widely used and easily interpretable multiple linear regression model is used to find the linear relationship between various pollutant concentrations and the measurement data of the micro air quality monitor to obtain the fitted values of various pollutant concentrations. Second, we take the measurement data of the micro air quality monitor and the fitted value of the multiple regression model as the input, and use the boosted regression tree to find the nonlinear relationship between the concentrations of various pollutants and the input variables. Finally, the autoregressive integrated moving average model is used to extract the information hidden in the residual sequence, and finally the establishment of the MLR-BRT-ARIMA model is completed. Root mean square error, mean absolute error and relative mean absolute percent error are used to compare the calibration effect of the MLR-BRT-ARIMA model and other commonly used models such as multilayer perceptron neural network, support vector regression machine and nonlinear autoregressive models with exogenous input. The results show that no matter what kind of pollutant, the MLR-BRT-ARIMA combined model proposed in this paper has the best performance of the three indicators. Using this model to calibrate the measurement value of the micro air quality monitor can improve the accuracy by 82.4-95.4%.

Impact of the COVID-19 lockdown on typical ambient air pollutants: Cyclical response to anthropogenic emission reduction

Preliminary studies have confirmed that ambient air pollutant concentrations are significantly influenced by the COVID-19 lockdown measures, but little attention focus on the long term impacts of human countermeasures in cities all over the world during the period. Still, fewer have addressed their other essential properties, especially the cyclical response to concentration reduction. This paper aims to fill the gaps with combined methods of abrupt change test and wavelet analysis, research areas were made of five cities, Wuhan, Changchun, Shanghai, Shenzhen and Chengdu, in China. Abrupt changes in contaminant concentrations commonly occurred in the year prior to the outbreak. The lockdown has almost no effect on the short cycle below 30 d (days) for both pollutants, and a negligible impact on the cycle above 30 d. PM_2.5 (fine particulate matter) has a stable short-cycle nature, which is greatly influenced by anthropogenic emissions. The analysis revealed that the sensitivity of PM_2.5 to climate is increased along with the concentrations of PM_2.5 were decreasing by the times when above the threshold (30-50 μg m^-3), and which could lead to PM_2.5 advancement relative to the ozone phase over a period of 60 d after the epidemic. These results suggest that the epidemic may have had an impact earlier than when it was known. And significant reductions in anthropogenic emissions have little impact on the cyclic nature of pollutants, but may alter the inter-pollutant phase differences during the study period.

A systematic review and meta-analysis of air pollution and angina pectoris attacks: identification of hazardous pollutant, short-term effect, and vulnerable population

We conducted a systematic review and meta-analysis of global epidemiological studies of air pollution and angina pectoris, aiming to explore the deleterious air pollutant(s) and vulnerable sub-populations. PubMed and Web of Science databases were searched for eligible articles published between database inception and October 2021. Meta-analysis weighted by inverse-variance was utilized to pool effect estimates based on the type of air pollutant, including particulate matters (PM_2.5 and PM₁₀: particulate matter with an aerodynamic diameter ≤ 2.5 µm and ≤ 10 µm), gaseous pollutants (NO₂: nitrogen dioxide; CO: carbon monoxide; SO₂: sulfur dioxide, and O₃: ozone). Study-specific effect estimates were standardized and calculated with percentage change of angina pectoris for each 10 µg/m³ increase in air pollutant concentration. Twelve studies involving 663,276 angina events from Asia, America, Oceania, and Europe were finally included. Meta-analysis showed that each 10 µg/m³ increase in PM_2.5 and PM₁₀ concentration was associated with an increase of 0.66% (95%CI: 0.58%, 0.73%; p < 0.001) and 0.57% (95%CI: 0.20%, 0.94%; p = 0.003) in the risk of angina pectoris on the second day of exposure. Adverse effects were also observed for NO₂ (0.67%, 95%CI: 0.33%, 1.02%; p < v0.001) on the second day, CO (0.010%, 95%CI: 0.006%, 0.014%; p < 0.001). The elderly and patients with coronary artery disease (CAD) appeared to be at higher risk of angina pectoris. Our findings suggest that short-term exposure to PM_2.5, PM₁₀, NO₂, and CO was associated with an increased risk of angina pectoris, which may have implications for cardiologists and patients to prevent negative cardiovascular outcomes.

Circulatory health risks from additive multi-pollutant models: short-term exposure to three common air pollutants in Canada

Numerous studies have reported adverse health effects of ambient air pollution on circulatory health outcomes mainly based on single-pollutant models. However, limited studies have focused on adjusted effect of multi-pollutant exposures on public health. This study aimed to examine short-term effects of three common air pollutants-ground-level ozone (ozone), nitrogen dioxide (NO2), and fine particulate matter (PM2.5)-through multi-pollutant models for mixed effect of adjustment. Daily data (circulatory hospitalization and mortality) and hourly data (air pollutants and temperature) were collected for 24 Canadian cities for 2001-2012. We applied generalized additive over-dispersion Poisson regression models with 1, 2, or 3 pollutants for city-specific risks, and Bayesian hierarchical models for national risks. This study found little mixed effect of adjustment through multi-pollutant models (ozone and/or NO2 and/or PM2.5) for circulatory hospitalization or mortality in Canada for 2001-2012, indicating that the 1-pollutant model did not result in considerable under- or over-estimates. It seemed weak-to-moderate correlations among air pollutants did not change the significant effect of one air pollutant after accounting for others. Inconsistent findings between other previous studies and this study indicate the need of comparable study design for multi-pollutant effect analysis.

Association between short-term exposure to ambient air pollution and heart failure: An updated systematic review and meta-analysis of more than 7 million participants

Introduction

Exposure to air pollution has been linked to the mortality of heart failure. In this study, we sought to update the existing systematic review and meta-analysis, published in 2013, to further assess the association between air pollution and acute decompensated heart failure, including hospitalization and heart failure mortality.

Methods

PubMed, Web of Science, EMBASE, and OVID databases were systematically searched till April 2022. We enrolled the studies regarding air pollution exposure and heart failure and extracted the original data to combine and obtain an overall risk estimate for each pollutant.

Results

We analyzed 51 studies and 7,555,442 patients. Our results indicated that heart failure hospitalization or death was associated with increases in carbon monoxide (3.46% per 1 part per million; 95% CI 1.0233-1.046, P < 0.001), sulfur dioxide (2.20% per 10 parts per billion; 95% CI 1.0106-1.0335, P < 0.001), nitrogen dioxide (2.07% per 10 parts per billion; 95% CI 1.0106-1.0335, P < 0.001), and ozone (0.95% per 10 parts per billion; 95% CI 1.0024-1.0166, P < 0.001) concentrations. Increases in particulate matter concentration were related to heart failure hospitalization or death (PM_2.5 1.29% per 10 μg/m³, 95% CI 1.0093-1.0165, P < 0.001; PM₁₀ 1.30% per 10 μg/m³, 95% CI 1.0102-1.0157, P < 0.001).

Conclusion

The increase in the concentration of all pollutants, including gases (carbon monoxide, sulfur dioxide, nitrogen dioxide, ozone) and particulate matter [(PM_2.5), (PM₁₀)], is positively correlated with hospitalization rates and mortality of heart failure.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42021256241.

Geographic Medical Overview of Noncommunicable Diseases (Cardiovascular Diseases and Diabetes) in the Territory of the AP Vojvodina (Northern Serbia)

The objective of this study was a geographic medical analysis of noncommunicable diseases (cardiovascular diseases from 2010 to 2020 and diabetes from 2010 to 2019) in the AP Vojvodina (northern Serbia) in order to identify the most and least burdened counties as well as to present trends in the mentioned diseases. The Mann-Kendall trend test, a cluster analysis, and Getis-Ord Gi* method for hot spot analysis were applied in this analysis. Regarding acute coronary syndrome and myocardial infarction, the North Backa County had a lower mortality rate although the number of newly reported cases was above average. The largest number of new cases of unstable angina pectoris was in the North Backa, North Banat, and Middle Banat Counties, while the West Backa County was identified as a county with a higher mortality rate. The cluster analysis showed that the number of death cases from diabetes in the Srem County is significantly higher than that in the other counties. Likewise, the West Backa County had a high number of new diabetes patients, but also a much lower mortality rate. Chronic noncommunicable diseases are predominant in newly diagnosed incidences and death cases in the AP Vojvodina. Studies of this kind promote public health and healthcare systems in the researched area and in the Republic of Serbia, as well as in other countries.

Health and economic impacts of ambient air pollution on hospital admissions for overall and specific cardiovascular diseases in Panzhihua, Southwestern China

Background

The associations of ambient air pollution with hospital admissions (HAs) for overall and specific causes of cardiovascular diseases (CVDs), as well as related morbidity and economic burdens remain understudied, especially in low-pollution areas of low- and middle-income countries (LMICs). We evaluated the short-term effects of exposure to PM_2.5 (particles with an aerodynamic diameter ≤2.5 μm), PM₁₀ (particles with an aerodynamic diameter ≤10 μm), and SO₂ (sulfur dioxide) on HAs for CVDs in Panzhihua, China, during 2016-2020, and calculated corresponding attributable risks and economic burden.

Methods

We used a generalized additive model (GAM) while controlling for time trends, meteorological conditions, holidays, and days of the week to estimate the associations. The cost of illness (COI) method was adopted to further assess corresponding hospitalization costs and productivity losses.

Results

A total of 27 660 HAs for CVDs were included in this study. PM₁₀ and SO₂ were significantly associated with elevated risks of CVDs hospitalizations. Each 10 μg/m³ increase in PM₁₀ and SO₂ at lag06 corresponded to an increase of 2.48% (95% confidence interval (CI) = 0.92%-4.06%), and 5.50% (95% CI = 3.09%-7.97%) in risk of HAs for CVDs, respectively. The risk estimates of PM₁₀ and SO₂ on CVD hospitalizations were generally robust after adjustment for other pollutants in two-pollutant models. We found stronger associations between air pollution (PM₁₀ and SO₂) and CVDs in cool seasons than in warm seasons. For specific causes of CVDs, significant associations of PM₁₀ and SO₂ exposure with cerebrovascular disease and ischaemic heart disease were observed. Using 0 μg/m³ as the reference concentrations, 11.91% (95%CI = 4.64%-18.56%) and 15.71% (95%CI = 9.30%-21.60%) of HAs for CVDs could be attributable to PM₁₀ and SO₂, respectively. During the study period, PM₁₀ and SO₂ brought 144.34 million Yuan economic losses for overall CVDs, accounting for 0.028% of local GDP.

Conclusions

Our results suggest that PM₁₀ and SO₂ exposure might be an important trigger of HAs for CVDs and accounted for substantial morbidity and economic burden.

Calibration of miniature air quality detector monitoring data with PCA-RVM-NAR combination model

The development of miniature air quality detectors makes it possible for humans to monitor air quality in real time and grid. However, the accuracy of measuring pollutants by miniature air quality detectors needs to be improved. In this paper, the PCA-RVM-NAR combined model is proposed to calibrate the measurement accuracy of the miniature air quality detector. First, correlation analysis is used to find out the main factors affecting pollutant concentrations. Second, principal component analysis is used to reduce the dimensionality of these main factors and extract their main information. Thirdly, taking the extracted principal components as independent variables and the observed values of pollutant concentrations as dependent variables, a PCA-RVM model is established by the relevance vector machine. Finally, the nonlinear autoregressive neural network is used to correct the error and finally complete the establishment of the PCA-RVM-NAR model. Root mean square error, goodness of fit, mean absolute error and relative mean absolute percent error are used to compare the calibration effect of PCA-RVM-NAR model and other commonly used models such as multiple linear regression model, support vector machine, multilayer perceptron neural network and nonlinear autoregressive models with exogenous input. The results show that, no matter which pollutant, the PCA-RVM-NAR model achieves better calibration results than other models in the four indicators. Using this model to correct the data of the miniature air quality detector can improve its accuracy by 77.8-93.9%.

A data calibration method for micro air quality detectors based on a LASSO regression and NARX neural network combined model

Studies have shown that there is a certain correlation between air pollution and various human diseases, especially lung diseases, so it is very meaningful to monitor the concentration of pollutants in the air. Compared with the national air quality monitoring station (national control point), the micro air quality detector has the advantage that it can monitor the concentration of pollutants in real time and grid, but its measurement accuracy needs to be improved. This paper proposes a model combining the least absolute selection and shrinkage operator (LASSO) regression and nonlinear autoregressive models with exogenous inputs (NARX) to calibrate the data measured by the micro air quality detector. Before establishing the LASSO-NARX model, correlation analysis is used to test whether the correlation between the concentration of air pollutants and its influencing factors is significant, and to find out the main factors that affect the concentration of pollutants. Due to the multicollinearity between various influencing factors, LASSO regression is used to further screen the influencing factors and give the quantitative relationship between the pollutant concentration and various influencing factors. In order to improve the prediction accuracy of pollutant concentration, the predicted value of each pollutant concentration in the LASSO regression model and the measurement data of the micro air quality detector are used as input variables, and the LASSO-NARX model is constructed using the NARX neural network. Several indicators such as goodness of fit, root mean square error, mean absolute error and relative mean absolute percent error are used to compare various air quality models. The results show that the prediction results of the LASSO-NARX model are not only better than the LASSO model alone and the NARX model alone, but also better than the commonly used multilayer perceptron and radial basis function neural network. Using this model to calibrate the measurement data of the micro air quality detector can increase the accuracy by 61.3-91.7%.

Inhalation of particulate matter containing free radicals leads to decreased vascular responsiveness associated with an altered pulmonary function

Airborne particulate matter (PM) is associated with an increased risk for cardiovascular diseases. Although the goal of thermal remediation is to eliminate organic wastes through combustion, when incomplete combustion occurs, organics chemisorb to transition metals to generate PM-containing environmentally persistent free radicals (EPFRs). Similar EPFR species have been detected in PM found in diesel and gasoline exhaust, woodsmoke, and urban air. Prior in vivo studies demonstrated that EPFRs reduce cardiac function secondary to elevations in pulmonary arterial pressures. In vitro studies showed that EPFRs increase ROS and cytokines in pulmonary epithelial cells. We thus hypothesized that EPFR inhalation would promote lung inflammation and oxidative stress, leading to systemic inflammation, vascular endothelial injury, and a decline in vascular function. Mice were exposed to EPFRs for either 4 h or for 4 h/day for 10 days and lung and vascular function were assessed. After a 4-h exposure, plasma nitric oxide (NO) was reduced while endothelin-1 (ET-1) was increased, however lung function was not altered. After 10 day, plasma NO and ET-1 levels were again altered and lung tidal volume was reduced. These time course studies suggested the vasculature may be an early target of injury. To test this hypothesis, an intermediate time point of 3 days was selected. Though the mice exhibited no marked inflammation in either the lung or the blood, we did note significantly reduced endothelial function concurrent with a reduction in lung tidal volume and an elevation in annexin V protein levels in the lung. Although vascular dysfunction was not dependent upon inflammation, it may be associated with an injury at the air-blood interface. Gene expression analysis suggested roles for oxidative stress and aryl hydrocarbon receptor (Ahr) signaling. Studies probing the relationship between pulmonary oxidative stress and AhR signaling at the air-blood interface with vascular dysfunction seem warranted.NEW & NOTEWORTHY Particulate matter (PM) resulting from the combustion of organic matter is known to contribute to cardiopulmonary disease. Despite hypotheses that cardiovascular dysfunction occurring after PM exposures is secondary to lung or systemic inflammation, these studies investigating exposures to PM-containing environmentally persistent free radicals (EPFRs) demonstrate that cardiovascular dysfunction precedes pulmonary inflammation. The cardiopulmonary health consequences of EPFRs have yet to be thoroughly evaluated, especially in healthy, adult mice. Our data suggest the vasculature as a direct target of PM exposure, and our studies aimed to elucidate the mechanisms contributing to EPFR-induced vascular dysfunction.

Estimation of PM10 pollutant and its effect on total mortality (TM), hospitalizations due to cardiovascular diseases (HACD), and respiratory disease (HARD) outcome

Dust storms not only affect the quality of life but also pose a serious health and social problem. The main source dust events include central and west Asia, the Taklimakan desert, and Middle East, carrying out high volume of particulate matter, which increased the level of PM₁₀ as representative of dust storm. The purpose of this study was to investigate the number of mortality (TM), hospitalizations due to cardiovascular diseases (HACD) and respiratory diseases (HARD) among the people of Bishkek and Ahvaz. Data validation was performed using the WHO criteria. The average time PM₁₀ in outdoor air was calculated, and its health effects were obtained by entering its annual data and population at risk, baseline incidence (BI), and relative risk index (RR) for IHD outcomes. In our study, AirQ software was used. The number of excess cases in Bishkek and Ahvaz for total mortality and cardiovascular mortality was 63 and 758 and 35 and 478 persons while for HARD and HACD was 84 and 2054 and 33 and 560 persons, respectively. The survey requires the need to enact and enforce permissible PM₁₀ levels/standards due to dust storms to reduce the health effect on humans by relevant environmental authorities both at federal and state levels.

Joint exposure to various ambient air pollutants and incident heart failure: a prospective analysis in UK Biobank

AIMS

Little is known about the relation between the long-term joint exposure to various ambient air pollutants and the incidence of heart failure (HF). We aimed to assess the joint association of various air pollutants with HF risk and examine the modification effect of the genetic susceptibility.

METHODS AND RESULTS

This study included 432 530 participants free of HF, atrial fibrillation, or coronary heart disease in the UK Biobank study. All participants were enrolled from 2006 to 2010 and followed up to 2018. The information on particulate matter (PM) with diameters ≤2.5 µm (PM2.5), ≤10 µm (PM10), and between 2.5 and 10 µm (PM2.5-10) as well as nitrogen oxides (NO2 and NOx) was collected. We newly proposed an air pollution score to assess the joint exposure to the five air pollutants through summing each pollutant concentration weighted by the regression coefficients with HF from single-pollutant models. We also calculated the weighted genetic risk score of HF. During a median of 10.1 years (4 346 642 person-years) of follow-up, we documented 4201 incident HF. The hazard ratios (HRs) [95% confidence interval (CI)] of HF for a 10 µg/m3 increase in PM2.5, PM10, PM2.5-10, NO2, and NOx were 1.85 (1.34-2.55), 1.61 (1.30-2.00), 1.13 (0.80-1.59), 1.10 (1.04-1.15), and 1.04 (1.02-1.06), respectively. We found that the air pollution score was associated with an increased risk of incident HF in a dose-response fashion. The HRs (95% CI) of HF were 1.16 (1.05-1.28), 1.19 (1.08-1.32), 1.21 (1.09-1.35), and 1.31 (1.17-1.48) in higher quintile groups compared with the lowest quintile of the air pollution score (P trend <0.001). In addition, we observed that the elevated risk of HF associated with a higher air pollution score was strengthened by the genetic susceptibility to HF.

CONCLUSION

Our results indicate that the long-term joint exposure to various air pollutants including PM2.5, PM10, PM2.5-10, NO2, and NOx is associated with an elevated risk of incident HF in an additive manner. Our findings highlight the importance to comprehensively assess various air pollutants in relation to the HF risk.

Analysis and prediction of air quality in Nanjing from autumn 2018 to summer 2019 using PCR-SVR-ARMA combined model

In order to correct the monitoring data of the miniature air quality detector, an air quality prediction model fusing Principal Component Regression (PCR), Support Vector Regression (SVR) machine, and Autoregressive Moving Average (ARMA) model was proposed to improve the prediction accuracy of the six types of pollutants in the air. First, the main information of factors affecting air quality is extracted by principal component analysis, and then principal component regression is used to give the predicted values of six types of pollutants. Second, the support vector regression machine is used to regress the predicted value of principal component regression and various influencing factors. Finally, the autoregressive moving average model is used to correct the residual items, and finally the predicted values of six types of pollutants are obtained. The experimental results showed that the proposed combination prediction model of PCR–SVR–ARMA had a better prediction effect than the artificial neural network, the standard support vector regression machine, the principal component regression, and PCR–SVR method. The Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and relative Mean Absolute Percent Error (MAPE) are used as evaluation indicators to evaluate the PCR–SVR–ARMA model. This model can increase the accuracy of self-built points by 72.6% to 93.2%, and the model has excellent prediction effects in the training set and detection set, indicating that the model has good generalization ability. This model can play an active role scientific arrangement and promotion of miniature air quality detectors and grid-based monitoring of the concentration of various pollutants.

Short-term exposure to carbon monoxide and myocardial infarction: A systematic review and meta-analysis

BACKGROUND

Previous studies suggest an association between short-term exposure to carbon monoxide and myocardial infarction. We performed a systematic review and meta-analysis to assess current evidence on this association to support the update of the World Health Organization (WHO) Global Air Quality Guidelines.

METHODS

We searched Medline, Embase and Cochrane Central Register of Controlled Trials to update the evidence published in a previous systematic review up to 30th September 2018 for studies investigating the association between short-term exposure to ambient carbon monoxide (up to lag of seven days) and emergency department visits or hospital admissions and mortality due to myocardial infarction. Two reviewers assessed potentially eligible studies and performed data extraction independently. Random-effects meta-analysis was used to derive the pooled risk estimate per 1 mg/m³ increase in ambient carbon monoxide concentration. Risk of bias in individual studies was assessed using a domain-based assessment tool. The overall certainty of the body of evidence was evaluated using an adapted certainty of evidence assessment framework.

RESULTS

We evaluated 1,038 articles from the previous review and our updated literature search, of which, 26 satisfied our inclusion criteria. Overall, myocardial infarction was associated with exposure to ambient carbon monoxide concentration (risk ratio of 1.052, 95% confidence interval 1.017-1.089 per 1 mg/m³ increase). A third of studies were assessed to be at high risk of bias (RoB) due to inadequate adjustment for confounding. Using an adaptation of the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework, the overall evidence was assessed to be of moderate certainty.

CONCLUSIONS

This review demonstrated that the pooled risk ratio for myocardial infarction was 1.052 (95% CI 1.017-1.089) per 1 mg/m³ increase in ambient carbon monoxide concentration. However, very few studies originated from low- and middle-income countries.

A case-crossover study on the effect of short-term exposure to moderate levels of air pollution on the risk of heart failure

Aims

Exposure to high levels of air pollution in industrialized urban areas is associated with an increased risk of heart failure (HF). On most days, the majority of European cities are only moderately affected by air pollution. The aim of this study was to evaluate the association between short‐term exposure to moderate levels of air pollution with the risk of HF in a city with good air quality.

Methods and results

We recruited 576 patients (median age 82 years; 58.2% men) admitted to a large university hospital in Central Germany for HF to participate in a hospital‐based, bidirectional, case‐crossover study. Diagnosis of HF and symptom onset were verified individually. The effect of short‐term exposure to nitrogen dioxide (NO₂), particulate matter (PM₁₀), and ozone (O₃) on the risk of HF was estimated using linear and non‐linear (categorized) multivariate analyses for three different lag times (1, 2, and 3 days before HF onset). Air pollution variables were adjusted to the date of HF symptom onset. During the study period, the average daily concentration of air pollutants was only moderate and reflects the average European background air pollution. In particular, the concentration of air pollutants ranged from 2 to 63.39 μg/m³ (median = 17.46 μg/m³) for NO₂, from 2 to 125.88 μg/m³ (median = 44.61 μg/m³) for O₃, and from 2.21 to 166.79 μg/m³ (median = 18.67 μg/m³) for PM₁₀. We did not find a linear or non‐linear association between short‐term exposure to NO₂, O₃, or PM₁₀ and risk for HF at all lag times in the overall population and subgroups.

Conclusions

In an area with only moderate air pollution, short‐term exposure to major air pollutants does not increase the risk for HF. Future studies should focus on a potential threshold effect of air pollution on HF risk as a basis for evidence‐based development of statutory limits in highly polluted areas.

Time series analysis of meteorological factors and air pollutants and their association with hospital admissions for acute myocardial infarction in Korea

BACKGROUND

We assessed the association between multiple meteorological factors and air pollutants and the number of acute myocardial infarction (AMI) cases using a multi-step process.

METHODS

Daily AMI hospitalizations matched with 16 meteorological factors and air pollutants in 7 metropolitan provinces of the Republic of Korea from 2002 to 2017 were analyzed. We chose the best fit model after conducting the Granger causality (GC) test and examined the daily lag time effect on the orthogonalized impulse response functions. To define dose-response relationships, we performed a time series analysis using multiple generalized additive lag models based on seasons.

RESULTS

A total of 196,762 cases of AMI in patients older than 20 years admitted for hospitalization were identified. The distribution of meteorological factors and air pollutants showed characteristics of a temperate climate. The GC test revealed a complex interaction between meteorological factors, including air pollutants, and AMI. The final selected factors were NO₂ and temperature; these increased the incidence of AMI on lag day 4 during summer (NO₂: population-attributable fraction [PAF], 3.9%; 95% confidence interval [CI], 3.6-4.0; mean temperature: PAF, 3.3%; 95% CI, 2.7-3.9).

CONCLUSIONS

This multi-step time series analysis found that average temperature and NO₂ are the most important factors impacting AMI hospitalizations, specifically during summer. Based on the model, we were able to visualize the effect-time association of meteorological factors and air pollutants and AMI.

Systematic review and meta-analysis of case-crossover and time-series studies of short term outdoor nitrogen dioxide exposure and ischemic heart disease morbidity

BACKGROUND

Nitrogen dioxide (NO₂) is a pervasive urban pollutant originating primarily from vehicle emissions. Ischemic heart disease (IHD) is associated with a considerable public health burden worldwide, but whether NO₂ exposure is causally related to IHD morbidity remains in question. Our objective was to determine whether short term exposure to outdoor NO₂ is causally associated with IHD-related morbidity based on a synthesis of findings from case-crossover and time-series studies.

METHODS

MEDLINE, Embase, CENTRAL, Global Health and Toxline databases were searched using terms developed by a librarian. Screening, data extraction and risk of bias assessment were completed independently by two reviewers. Conflicts between reviewers were resolved through consensus and/or involvement of a third reviewer. Pooling of results across studies was conducted using random effects models, heterogeneity among included studies was assessed using Cochran's Q and I² measures, and sources of heterogeneity were evaluated using meta-regression. Sensitivity of pooled estimates to individual studies was examined using Leave One Out analysis and publication bias was evaluated using Funnel plots, Begg's and Egger's tests, and trim and fill.

RESULTS

Thirty-eight case-crossover studies and 48 time-series studies were included in our analysis. NO₂ was significantly associated with IHD morbidity (pooled odds ratio from case-crossover studies: 1.074 95% CI 1.052-1.097; pooled relative risk from time-series studies: 1.022 95% CI 1.016-1.029 per 10 ppb). Pooled estimates for case-crossover studies from Europe and North America were significantly lower than for studies conducted elsewhere. The high degree of heterogeneity among studies was only partially accounted for in meta-regression. There was evidence of publication bias, particularly for case-crossover studies. For both case-crossover and time-series studies, pooled estimates based on multi-pollutant models were smaller than those from single pollutant models, and those based on older populations were larger than those based on younger populations, but these differences were not statistically significant.

CONCLUSIONS

We concluded that there is a likely causal relationship between short term NO₂ exposure and IHD-related morbidity, but important uncertainties remain, particularly related to the contribution of co-pollutants or other concomitant exposures, and the lack of supporting evidence from toxicological and controlled human studies.

Acute effects of fine particulate matter (PM2.5) on hospital admissions for cardiovascular disease in Beijing, China: a time-series study

BACKGROUND

Air pollution and cardiovascular disease are increasing problems in China. However, the short-term association between fine particulate matter (PM_2.5) and cardiovascular disease (CVD) is not well documented. The purpose of this study is to estimate the short-term effects of PM_2.5 on CVD admissions in Beijing, China.

METHODS

In total, 460,938 electronic hospitalization summary reports for CVD between 2013 and 2017 were obtained. A generalized additive model using a quasi-Poisson distribution was used to investigate the association between exposure to PM_2.5 and hospitalizations for total and cause-specific CVD, including coronary heart disease (CHD), atrial fibrillation (AF), and heart failure (HF) after controlling for the season, the day of the week, public holidays, and weather conditions. A stratified analysis was also conducted for age (18-64 and ≥ 65 years), sex and season.

RESULTS

For every 10 μg/m³ increase in the PM_2.5 concentration from the previous day to the current (lag 0-1) there was a significant increase in total CVD admissions (0.30, 95% CI: 0.20, 0.39%), with a strong association for older adults (aged ≥65 years), CHD (0.34, 95% CI: 0.22 to 0.45%) and AF (0.29, 95% CI, 0.03 to 0.55%). However, the observed increased risk was not statistically significant for HF hospitalizations. The associations in the single-pollutant models were robust to the inclusion of other pollutants in a two-pollutant model. No differences were found after stratification by sex and season.

CONCLUSIONS

Exposure to PM_2.5 increased the risk of hospitalizations from CVD, especially for CHD, and appeared to have more influence in the elderly. Precautions and protective measures and efforts to reduce exposure to PM_2.5 should be strengthened, especially for the elderly.

Ambient air quality and spatio-temporal patterns of cardiovascular emergency department visits

BACKGROUND

Air pollutants have been associated with various adverse health effects, including increased rates of hospital admissions and emergency room visits. Although numerous time-series studies and case-crossover studies have estimated associations between day-to-day variation in pollutant levels and mortality/morbidity records, studies on geographic variations in emergency department use and the spatial effects in their associations with air pollution exposure are rare.

METHODS

We focused on the elderly who visited emergency room for cardiovascular related disease (CVD) in 2011. Using spatially and temporally resolved multi-pollutant exposures, we investigated the effect of short-term exposures to ambient air pollution on emergency department utilization. We developed two statistical models with and without spatial random effects within a hierarchical Bayesian framework to capture the spatial heterogeneity and spatial autocorrelation remaining in emergency department utilization.

RESULTS

Although the cardiovascular effect of spatially homogeneous pollutants, such as PM2.5 and ozone, was unchanged, we found the cardiovascular effect of NO[Formula: see text] was pronounced after accounting for the spatially correlated structure in emergency department utilization. We also identified areas with high ED utilization for CVD among the elderly and assessed the uncertainty associated with risk estimates.

CONCLUSIONS

We assessed the short-term effect of multi-pollutants on cardiovascular risk of the elderly and demonstrated the use of community multiscale air quality model-derived spatially and temporally resolved multi-pollutant exposures to an epidemiological study. Our results indicate that NO[Formula: see text] was significantly associated with the elevated ED utilization for CVD among the elderly.

Chronic obstructive pulmonary diseases related to outdoor PM10, O3, SO2, and NO2 in a heavily polluted megacity of Iran

This study was conducted to quantify, by an approach proposed by the World Health Organization (WHO), the daily hospital admissions for chronic obstructive pulmonary disease (COPD) related to exposure to particulate matter (PM₁₀) and oxidants such as ozone (O₃), sulfur dioxide (SO₂), and nitrogen dioxide (NO₂) in a heavily polluted city in Iran. For the health impact assessment, in terms of COPD, the current published relative risk (RR) and baseline incidence (BI) values, suggested by the WHO, and the 1-h O₃ concentrations and daily PM₁₀, NO₂, and SO₂ concentrations were compiled. The results showed that 5.9, 4.1, 1.2, and 1.9% of the COPD daily hospitalizations in 2011 and 6.6, 1.9, 2.3, and 2.1% in 2012 were attributed to PM₁₀, O₃, SO₂, and NO₂ concentrations exceeding 10 μg/m³, respectively. This study indicates that air quality and the high air pollutant levels have an effect on COPD morbidity. Air pollution is associated with visits to emergency services and hospital admissions. A lower relative risk can be achieved if some stringent control strategies for reducing air pollutants or emission precursors are implemented.

Is smog innocuous? Air pollution and cardiovascular disease

Air pollution is a significant environmental and health hazard. Earlier studies had examined the adverse health effects associated with short- and long-term exposure to particulate matter on respiratory disease. However, later studies demonstrated that was actually cardiovascular disease that accounted for majority of mortality. Furthermore, it was not gaseous pollutants like oxides of nitrate, sulfur, carbon mono-oxide or ozone but the particulate matter or PM, of fine or coarse size (PM_2.5 and PM₁₀) which was linearly associated with mortality; PM_2.5 with long term and PM₁₀ with short term. Several cardiovascular diseases are associated with pollution; acute myocardial infarction, heart failure, cardiac arrhythmias, atherosclerosis and cardiac arrest. The ideal way to address this problem is by adhering to stringent environmental standards of pollutants but some individual steps like choosing to stay indoors (on high pollution days), reducing outdoor air permeation to inside, purifying indoor air using air filters, and also limiting outdoor physical activity near source of air pollution can help. Nutritional anti-oxidants like statins or Mediterranean diet, and aspirin have not been associated with reduced risk but specific nutritional agents like broccoli, cabbage, cauliflower or brussels sprouts, fish oil supplement may help. Use of face-mask has been controversial but may be useful if particulate matter load is higher.

The mechanisms of air pollution and particulate matter in cardiovascular diseases

Clinical and epidemiological studies demonstrate that short- and long-term exposure to air pollution increases mortality due to respiratory and cardiovascular diseases. Given the increased industrialization and the increased sources of pollutants (i.e., cars exhaust emissions, cigarette smoke, industry emissions, burning of fossil fuels, incineration of garbage), air pollution has become a key public health issue to solve. Among pollutants, the particulate matter (PM) is a mixture of solid and liquid particles which differently affects human health depending on their size (i.e., PM₁₀ with a diameter <10 μm reach the lung and PM_2.5 with a diameter <2.5 μm penetrate deeper into the lung). In particular, the acute exposure to PM₁₀ and PM_2.5 increases the rate of cardiovascular deaths. Thus, appropriate interventions to reduce air pollution may promote great benefits to public health by reducing the risk of cardiovascular diseases. Several biological mechanisms have been identified to date which could be responsible for PM-dependent adverse cardiovascular outcomes. Indeed, the exposure to PM₁₀ and PM_2.5 induces sustained oxidative stress and inflammation. PM_2.5 is also able to increase autonomic nervous system activation. Some potential therapeutic approaches have been tested both in pre-clinical and clinical studies, based on the intake of antioxidants from dietary or by pharmacological administration. Studies are still in progress to increase the knowledge of PM activation of intracellular pathways and propose new strategies of intervention.

Air pollution and admissions due to ST elevation myocardial infarction-a time-series study from northwest of Iran

We investigated the association between the levels of air pollutants and the number of daily admissions due to ST segment elevation myocardial infarction (STEMI) in a metropolitan in the northwest of Iran. Daily concentrations of common air pollutants were obtained for the greater city of Tabriz for a period of 2 years. These reports included sulfur dioxide (SO2), nitrogen dioxide (NO2), nitric oxide (NO), nitrogen byproducts (NOx), carbon monoxide (CO), ozone (O3), and particulate matters < 10 μm (PM10). The census of admissions for STEMI was retrieved for the same period from hospital registries. The association of daily variations in air pollutant levels and the daily number of STEMI admissions were investigated in a time-series analysis. In the multi-pollutant model adjusting for long-term trend, seasonality, and temperature, a significant association was found for 1-h [NO2] and 24-h [CO]. A marginally significant association was observed for 24-h [NO2] and 8-h [CO]. The 24-h [CO] had the strongest association with the number of admissions with STEMI. Maximum 1-h concentrations of NO2 on the same day and on the prior day as well as 24-h concentrations of CO on the prior day were independently associated with increased number of STEMI admissions. However, daily concentrations of SO2, NO, O3, and PM10 were not associated with the frequency of hospital admissions for STEMI.

Short-term effects of ambient air pollution on emergency room admissions due to cardiovascular causes in Beijing, China

Ambient air pollution has been a major global public health issue. A number of studies have shown various adverse effects of ambient air pollution on cardiovascular diseases. In the current study, we investigated the short-term effects of ambient air pollution on emergency room (ER) admissions due to cardiovascular causes in Beijing from 2009 to 2012 using a time-series analysis. A total of 82430 ER cardiovascular admissions were recorded. Different gender (male and female) and age groups (15yrs ≤ age <65 yrs and age ≥ 65 yrs) were also examined by single model and multiple-pollutant model. Three major pollutants (SO₂, NO₂ and PM₁₀) had lag effects of 0-2 days on cardiovascular ER admissions. The relative risks (95% CI) of per 10 μg/m³ increase in PM₁₀, SO₂ and NO₂ were 1.008 (0.997-1.020), 1.008(0.999-1.018) and 1.014(1.003-1.024), respectively. The effect was more pronounced in age ≥65 and males in Beijing. We also found the stronger acute effects on the elderly and females at lag 0 than on the younger people and males at lag 2.

Health benefits of PM10 reduction in Iran

Air pollution contains a complex mixture of poisonous compounds including particulate matter (PM) which has wide spectrum of adverse health effects. The main purpose of this study was to estimate the potential health impacts or benefits due to any changes in annual PM₁₀ level in four major megacities of Iran. The required data of PM₁₀ for AirQ software was collected from air quality monitoring stations in four megacities of Iran. The preprocessing was carried out using macro coding in excel environment. The relationship between different presumptive scenarios and health impacts was determined. We also assessed the health benefits of reducing PM₁₀ to WHO Air Quality Guidelines (WHO-AQGs) and National Ambient Air Quality Standards (NAAQSs) levels with regard to the rate of mortality and morbidity in studied cities. We found that the 10 μg/m³ increase in annual PM₁₀ concentration is responsible for seven (95% CI 6-8) cases increase in total number of deaths per 2 × 10⁵ person. We also found that 10.7, 7.2, 5.7, and 5.3% of total death is attributable to short-term exposure to air pollution for Ahvaz, Isfahan, Shiraz, and Tehran, respectively. We found that by attaining the WHO's proposed value for PM₁₀, the potential health benefits of 89, 84, 79, and 78% were obtained in Ahvaz, Isfahan, Shiraz, and Tehran, respectively. The results also indicated that 27, 10, 3, and 1% of health impacts were attributed to dust storm days for Ahvaz, Isfahan, Shiraz, and Tehran, respectively.

Hospital admissions in Iran for cardiovascular and respiratory diseases attributed to the Middle Eastern Dust storms

The main objective of this study was to assess the possible effects of airborne particulate matter less than 10 μm in diameter (PM₁₀) from the Middle Eastern Dust (MED) events on human health in Khorramabad (Iran) in terms of estimated hospital admissions (morbidity) for cardiovascular diseases (HACD) and for respiratory diseases (HARD) during the period of 2015 to 2016. The AirQ program developed by the World Health Organization (WHO) was used to estimate the potential health impacts to daily PM₁₀ exposures. The numbers of excess cases for cardiovascular/respiratory morbidity were 20/51, 72/185, and 20/53 on normal, dusty, and MED event days, respectively. The highest number of hospital admissions was estimated for PM₁₀ concentrations in the range of 40 to 49 μg/m³, i.e, lower than the daily (50 μg/m³) limit value established by WHO. The results also showed that 4.7% (95% CI 3.2-6.7%) and 4.2% (95% CI 2.6-5.8%) of HARD and HACD, respectively, were attributed to PM₁₀ concentrations above 10 μg/m³. The study demonstrates a significant impact of air pollution on people, which is manifested primarily as respiratory and cardiovascular problems. To reduce these effects, several immediate actions should be taken by the local authorities to control the impacts of dust storms on residents' health, e.g., developing a green beltway along the Iran-Iraq border and management of water such as irrigation of dry areas that would be effective as mitigation strategies.

Acute myocardial infarction and COPD attributed to ambient SO2 in Iran

Acute myocardial infarction (MI) and chronic obstructive pulmonary disease (COPD) are important diseases worldwide. Inhalation is the major route of short-term exposure to air sulfur dioxide (SO₂) that negatively affect human health. The objective of this study was to estimate the health effects of short-term exposure to SO₂ in Khorramabad, Iran using the AirQ software developed by the World Health Organization (WHO). Daily mean SO₂ concentrations were used as the estimates of human short-term exposure and allow calculation of the attributable excess relative risk of an acute MI and hospital admissions due to COPD (HACOPD). The annual mean SO₂ concentration in Khorramabad was 51.33µg/m³. Based on the relative risk (RR) and baseline incidence (BI) approach of WHO, an increased risk of 2.7% (95% CI: 1.1-4.2%) of acute MI and 2.0% (95% CI: 0-4.6%) of HACOPD, respectively, were attributed to a 10µg/m³ SO₂ increase. Since the geographic, demographic, and climatic characteristics are different from the areas in which the risk relationships were developed and not evaluated here, further investigations will be needed to fully quantify other health impacts of SO₂. A decreased risk for MIs and COPD attributable to SO₂ could be achieved if mitigation strategies and measures are implemented to reduce the exposure.

Seasonal Periodicity of Ischemic Heart Disease and Heart Failure

Seasonal variation for ischemic heart disease and heart failure is known. The interplay of environmental, biological, and physiologic changes is fascinating. This article highlights the seasonal periodicity of ischemic heart disease and heart failure and examines some of the potential reasons for these unique observations.

Short-term effects of ozone air pollution on hospital admissions for myocardial infarction: A time-stratified case-crossover study in Taipei

This study was undertaken to determine whether there was a correlation between ambient ozone (O₃) levels and number of hospital admissions for myocardial infarction (MI) in Taipei, Taiwan. Hospital admissions for MI and ambient air pollution data for Taipei were obtained for the period from 2006 to 2010. The relative risk (RR) of hospital admissions for MI was estimated using a time-stratified case-crossover approach, controlling for weather variables, day of the week, seasonality, and long-term time trends. For the single-pollutant model (without adjustment for other pollutants), increased RR for a number of MI admissions was significantly associated with higher O₃ levels both on warm days (>23°C) and on cool days (<23°C). This observation was accompanied by an interquartile range elevation correlated with a 7% (95% CI = 2%-12%) and 17% (95% CI = 11%-25%) rise in number of MI admissions, respectively. In the two-pollutant models, no significant associations between ambient O₃ concentrations and number of MI admissions were observed on warm days. However, on cool days, correlation between ambient O₃ after inclusion of each of the other five pollutants, particulate matter (PM₁₀ or PM_2.5), sulfur dioxide (SO₂), nitrogen dioxide (NO₂) or carbon monoxide (CO), and number of MI admissions remained significant. This study provides evidence that higher levels of ambient O₃ increase the RR of number of hospital admissions for MI.

The short-term associations of weather and air pollution with emergency ambulance calls for paroxysmal atrial fibrillation

A circadian variation in the cardiovascular parameters has been detected. It is plausible that the influence of the environment varies during different periods of the day. We investigated the association between daily emergency ambulance calls (EC) for paroxysmal atrial fibrillation (AF) that occurred during the time intervals of 8:00-13:59, 14:00-21:59, and 22:00-7:59, and weather conditions and exposure to CO and PM₁₀. We used Poisson regression to explore the association between the risk of EC for AF and environmental variables, adjusting for seasonal variation. Before noon, the risk was associated with an IQR (0.333 mg/m³) increase in CO at lag 2-6 days above the median (RR = 1.15, P = 0.002); a protective impact of CO on previous day was observed (RR = 0.91, P = 0.018). During 14:00-21:59, a negative effect of air temperature below 1.9 °C (lag 2-3 days) was detected (per 10 °C decrease: RR = 1.17, P = 0.044). At night, the elevated risk was associated with wind speed above the median (lag 2-4 days) (per 1-kt increase: RR = 1.07, P = 0.001) and with PM₁₀ at lag 2-5 days below the median (per IQR (7.31 μg/m³) increase: RR = 1.21, P = 0.002). Individuals over 65 years of age were more sensitive to air pollution, especially at night (CO lag 2-3 days < median, per IQR (0.12 mg/m³) increase: RR = 1.14, P = 0.045; PM₁₀ lag 2-5 days < median, per IQR increase: RR = 1.32, P = 0.001). The associations of air pollution and other environmental variables with acute events may be analyzed depending on the time of the event.

Health risk assessment of exposure to the Middle-Eastern Dust storms in the Iranian megacity of Kermanshah

OBJECTIVE

This study assessed the effects of particulate matter (PM), equal or less than 10 μm in aerodynamic diameter (PM₁₀), from the Middle-Eastern Dust events on public health in the megacity of Kermanshah (Iran).

STUDY DESIGN

This study used epidemiological modeling and monitored ambient air quality data to estimate the potential PM₁₀ impacts on public health.

METHODS

The AirQ2.2.3 model was used to calculate mortality and morbidity attributed to PM₁₀ as representative of dust events. Using Visual Basic for Applications, the programming language of Excel software, hourly PM₁₀ concentrations obtained from the local agency were processed to prepare input files for the AirQ2.2.3 model.

RESULTS

Using baseline incidence, defined by the World Health Organization, the number of estimated excess cases for respiratory mortality, hospital admissions for chronic obstructive pulmonary disease, for respiratory diseases, and for cardiovascular diseases were 37, 39, 476, and 184 persons, respectively, from 21st March, 2014 to 20th March, 2015. Furthermore, 92% of mortality and morbidity cases occurred in days with PM₁₀ concentrations lower than 150 μg/m³. The highest percentage of person-days occurred for daily concentrations range of 100-109 μg/m³, causing the maximum health end-points among the citizens of Kermanshah.

CONCLUSIONS

Calculating the number of cumulative excess cases for mortality or morbidity attributed to PM₁₀ provides a good tool for decision and policy-makers in the field of health care to compensate their shortcomings particularly at hospital and healthcare centers for combating dust storms. To diminish these effects, several immediate actions should be managed in the governmental scale to control dust such as spreading mulch and planting new species that are compatible to arid area.

Air pollution and the incidence of ischaemic and haemorrhagic stroke in the South London Stroke Register: a case-cross-over analysis

Background

Few European studies investigating associations between short-term exposure to air pollution and incident stroke have considered stroke subtypes. Using information from the South London Stroke Register for 2005–2012, we investigated associations between daily concentrations of gaseous and particulate air pollutants and incident stroke subtypes in an ethnically diverse area of London, UK.

Methods

Modelled daily pollutant concentrations based on a combination of measurements and dispersion modelling were linked at postcode level to incident stroke events stratified by haemorrhagic and ischaemic subtypes. The data were analysed using a time-stratified case–cross-over approach. Conditional logistic regression models included natural cubic splines for daily mean temperature and daily mean relative humidity, a binary term for public holidays and a sine–cosine annual cycle. Of primary interest were same day mean concentrations of particulate matter <2.5 and <10 µm in diameter (PM_2.5, PM₁₀), ozone (O₃), nitrogen dioxide (NO₂) and NO₂+nitrogen oxide (NO_X).

Results

Our analysis was based on 1758 incident strokes (1311 were ischaemic and 256 were haemorrhagic). We found no evidence of an association between all stroke or ischaemic stroke and same day exposure to PM_2.5, PM₁₀, O₃, NO₂ or NO_X. For haemorrhagic stroke, we found a negative association with PM₁₀ suggestive of a 14.6% (95% CI 0.7% to 26.5%) fall in risk per 10 µg/m³ increase in pollutant.

Conclusions

Using data from the South London Stroke Register, we found no evidence of a positive association between outdoor air pollution and incident stroke or its subtypes. These results, though in contrast to recent meta-analyses, are not inconsistent with the mixed findings of other UK studies.

Review of the health effects of wildland fire smoke on wildland firefighters and the public

Each year, the general public and wildland firefighters in the US are exposed to smoke from wildland fires. As part of an effort to characterize health risks of breathing this smoke, a review of the literature was conducted using five major databases, including PubMed and MEDLINE Web of Knowledge, to identify smoke components that present the highest hazard potential, the mechanisms of toxicity, review epidemiological studies for health effects and identify the current gap in knowledge on the health impacts of wildland fire smoke exposure. Respiratory events measured in time series studies as incidences of disease-caused mortality, hospital admissions, emergency room visits and symptoms in asthma and chronic obstructive pulmonary disease patients are the health effects that are most commonly associated with community level exposure to wildland fire smoke. A few recent studies have also determined associations between acute wildland fire smoke exposure and cardiovascular health end-points. These cardiopulmonary effects were mostly observed in association with ambient air concentrations of fine particulate matter (PM2.5). However, research on the health effects of this mixture is currently limited. The health effects of acute exposures beyond susceptible populations and the effects of chronic exposures experienced by the wildland firefighter are largely unknown. Longitudinal studies of wildland firefighters during and/or after the firefighting career could help elucidate some of the unknown health impacts of cumulative exposure to wildland fire smoke, establish occupational exposure limits and help determine the types of exposure controls that may be applicable to the occupation.

Major air pollutants and risk of COPD exacerbations: a systematic review and meta-analysis

Background

Short-term exposure to major air pollutants (O₃, CO, NO₂, SO₂, PM₁₀, and PM_2.5) has been associated with respiratory risk. However, evidence on the risk of chronic obstructive pulmonary disease (COPD) exacerbations is still limited. The present study aimed at evaluating the associations between short-term exposure to major air pollutants and the risk of COPD exacerbations.

Methods

After a systematic search up until March 30, 2016, in both English and Chinese electronic databases such as PubMed, EMBASE, and CNKI, the pooled relative risks and 95% confidence intervals were estimated by using the random-effects model. In addition, the population-attributable fractions (PAFs) were also calculated, and a subgroup analysis was conducted. Heterogeneity was assessed by I².

Results

In total, 59 studies were included. In the single-pollutant model, the risks of COPD were calculated by each 10 μg/m³ increase in pollutant concentrations, with the exception of CO (100 μg/m³). There was a significant association between short-term exposure and COPD exacerbation risk for all the gaseous and particulate pollutants. The associations were strongest at lag0 and lag3 for gaseous and particulate air pollutants, respectively. The subgroup analysis not only further confirmed the overall adverse effects but also reduced the heterogeneities obviously. When 100% exposure was assumed, PAFs ranged from 0.60% to 4.31%, depending on the pollutants. The adverse health effects of SO₂ and NO₂ exposure were more significant in low-/middle-income countries than in high-income countries: SO₂, relative risk: 1.012 (95% confidence interval: 1.001, 1.023); and NO₂, relative risk: 1.019 (95% confidence interval: 1.014, 1.024).

Conclusion

Short-term exposure to air pollutants increases the burden of risk of COPD acute exacerbations significantly. Controlling ambient air pollution would provide benefits to COPD patients.

The hidden economic burden of air pollution-related morbidity: evidence from the Aphekom project

Public decision-makers commonly use health impact assessments (HIA) to quantify the impacts of various regulation policies. However, standard HIAs do not consider that chronic diseases (CDs) can be both caused and exacerbated by a common factor, and generally focus on exacerbations. As an illustration, exposure to near road traffic-related pollution (NRTP) may affect the onset of CDs, and general ambient or urban background air pollution (BP) may exacerbate these CDs. We propose a comprehensive HIA that explicitly accounts for both the acute effects and the long-term effects, making it possible to compute the overall burden of disease attributable to air pollution. A case study applies the two HIA methods to two CDs-asthma in children and coronary heart disease (CHD) in adults over 65-for ten European cities, totaling 1.89 million 0-17-year-old children and 1.85 million adults aged 65 and over. We compare the current health effects with those that might, hypothetically, be obtained if exposure to NRTP was equally low for those living close to busy roads as it is for those living farther away, and if annual mean concentrations of both PM₁₀ and NO₂-taken as markers of general urban air pollution-were no higher than 20 μg/m³. Returning an assessment of € 0.55 million (95 % CI 0-0.95), the HIA based on acute effects alone accounts for only about 6.2 % of the annual hospitalization burden computed with the comprehensive method [€ 8.81 million (95 % CI 3-14.4)], and for about 0.15 % of the overall economic burden of air pollution-related CDs [€ 370 million (95 % CI 106-592)]. Morbidity effects thus impact the health system more directly and strongly than previously believed. These findings may clarify the full extent of benefits from any public health or environmental policy involving CDs due to and exacerbated by a common factor.

Short-Term Exposure to Air Pollution and Cardiac Arrhythmia: A Meta-Analysis and Systematic Review

The objective was to assess the transient association between air pollution and cardiac arrhythmia. Five databases were searched for studies investigating the association between daily increases in air pollutants (PM2.5, PM10, carbon monoxide, nitrogen dioxide, sulfur dioxide and ozone) and arrhythmia hospitalization or arrhythmia mortality. Two reviewers independently selected studies, extracted data, and assessed risk of bias. Outcomes were analyzed via a random-effects model and reported as relative risk and 95% confidence interval. 25 studies satisfied our inclusion criteria and 23 contributed to the meta-analysis. Arrhythmia hospitalization or mortality were associated with increases in PM2.5 (RR = 1.015 per 10 μg/m³, 95% CI: 1.006-1.024), PM10 (RR = 1.009 per 10 μg/m³, 95% CI: 1.004-1.014), carbon monoxide (RR = 1.041 per 1 ppm, 95% CI: 1.017-1.065), nitrogen dioxide (RR = 1.036 per 10 ppb, 95% CI: 1.020-1.053), and sulfur dioxide (RR = 1.021 per 10 ppb, 95% CI: 1.003-1.039), but not ozone (RR = 1.012 per 10 ppb, 95% CI: 0.997-1.027). Both particulate and gaseous components, with the exception of ozone, have a temporal association with arrhythmia hospitalization or mortality. Compared with Europe and North America, a stronger association was noted in Asia.

Air particulate matter and cardiovascular disease: the epidemiological, biomedical and clinical evidence

Air pollution is now becoming an independent risk factor for cardiovascular morbidity and mortality. Numerous epidemiological, biomedical and clinical studies indicate that ambient particulate matter (PM) in air pollution is strongly associated with increased cardiovascular disease such as myocardial infarction (MI), cardiac arrhythmias, ischemic stroke, vascular dysfunction, hypertension and atherosclerosis. The molecular mechanisms for PM-caused cardiovascular disease include directly toxicity to cardiovascular system or indirectly injury by inducing systemic inflammation and oxidative stress in peripheral circulation. Here, we review the linking between PM exposure and the occurrence of cardiovascular disease and discussed the possible underlying mechanisms for the observed PM induced increases in cardiovascular morbidity and mortality.

Air Pollution and Acute Myocardial Infarction Hospital Admission in Alberta, Canada: A Three-Step Procedure Case-Crossover Study

Adverse associations between air pollution and myocardial infarction (MI) are widely reported in medical literature. However, inconsistency and sensitivity of the findings are still big concerns. An exploratory investigation was undertaken to examine associations between air pollutants and risk of acute MI (AMI) hospitalization in Alberta, Canada. A time stratified case-crossover design was used to assess the transient effect of five air pollutants (carbon monoxide (CO), nitrogen dioxide (NO₂), nitric oxide (NO), ozone (O₃) and particulate matter with an aerodynamic diameter ≤2.5 (PM_2.5)) on the risk of AMI hospitalization over the period 1999–2009. Subgroups were predefined to see if any susceptible group of individuals existed. A three-step procedure, including univariate analysis, multivariate analysis, and bootstrap model averaging, was used. The multivariate analysis was used in an effort to address adjustment uncertainty; whereas the bootstrap technique was used as a way to account for regression model uncertainty. There were 25,894 AMI hospital admissions during the 11-year period. Estimating health effects that are properly adjusted for all possible confounding factors and accounting for model uncertainty are important for making interpretations of air pollution–health effect associations. The most robust findings included: (1) only 1-day lag NO₂ concentrations (6-, 12- or 24-hour average), but not those of CO, NO, O₃ or PM_2.5, were associated with an elevated risk of AMI hospitalization; (2) evidence was suggested for an effect of elevated risk of hospitalization for NSTEMI (Non-ST Segment Elevation Myocardial Infarction), but not for STEMI (ST segment elevation myocardial infarction); and (3) susceptible subgroups included elders (age ≥65) and elders with hypertension. As this was only an exploratory study there is a need to replicate these findings with other methodologies and datasets.

Weight-of-evidence evaluation of short-term ozone exposure and cardiovascular effects

There is a relatively large body of research on the potential cardiovascular (CV) effects associated with short-term ozone exposure (defined by EPA as less than 30 days in duration). We conducted a weight-of-evidence (WoE) analysis to assess whether it supports a causal relationship using a novel WoE framework adapted from the US EPA's National Ambient Air Quality Standards causality framework. Specifically, we synthesized and critically evaluated the relevant epidemiology, controlled human exposure, and experimental animal data and made a causal determination using the same categories proposed by the Institute of Medicine report Improving the Presumptive Disability Decision-making Process for Veterans ( IOM 2008). We found that the totality of the data indicates that the results for CV effects are largely null across human and experimental animal studies. The few statistically significant associations reported in epidemiology studies of CV morbidity and mortality are very small in magnitude and likely attributable to confounding, bias, or chance. In experimental animal studies, the reported statistically significant effects at high exposures are not observed at lower exposures and thus not likely relevant to current ambient ozone exposures in humans. The available data also do not support a biologically plausible mechanism for CV effects of ozone. Overall, the current WoE provides no convincing case for a causal relationship between short-term exposure to ambient ozone and adverse effects on the CV system in humans, but the limitations of the available studies preclude definitive conclusions regarding a lack of causation. Thus, we categorize the strength of evidence for a causal relationship between short-term exposure to ozone and CV effects as "below equipoise."