Global Association of Air Pollution and Cardiorespiratory Diseases: A Systematic Review, Meta-Analysis, and Investigation of Modifier Variables

Respiratory Effects of Exposure to Traffic-Related Air Pollutants During Exercise

Traffic-related air pollution (TRAP) is increasing worldwide. Habitual physical activity is known to prevent cardiorespiratory diseases and mortality, but whether exposure to TRAP during exercise affects respiratory health is still uncertain. Exercise causes inflammatory changes in the airways, and its interaction with the effects of TRAP or ozone might be detrimental, for both athletes exercising outdoor and urban active commuters. In this Mini-Review, we summarize the literature on the effects of exposure to TRAP and/or ozone during exercise on lung function, respiratory symptoms, performance, and biomarkers. Ozone negatively affected pulmonary function after exercise, especially after combined exposure to ozone and diesel exhaust (DE). Spirometric changes after exercise during exposure to particulate matter and ultrafine particles suggest a decrease in lung function, especially in patients with chronic obstructive pulmonary disease. Ozone frequently caused respiratory symptoms during exercise. Women showed decreased exercise performance and higher symptom prevalence than men during TRAP exposure. However, performance was analyzed in few studies. To date, research has not identified reliable biomarkers of TRAP-related lung damage useful for monitoring athletes' health, except in scarce studies on airway cells obtained by induced sputum or bronchoalveolar lavage. In conclusion, despite partly counteracted by the positive effects of habitual exercise, the negative effects of TRAP exposure to pollutants during exercise are hard to assess: outdoor exercise is a complex model, for multiple and variable exposures to air pollutants and pollutant concentrations. Further studies are needed to identify pollutant and/or time thresholds for performing safe outdoor exercise in cities.

Assessment of PM2.5-bound nitrogen-containing organic compounds (NOCs) during winter at urban sites in China and Korea

In this study, ambient fine particles (PM_2.5) were collected in two urban cities in China and Korea (Beijing and Gwangju, respectively) simultaneously in January 2018. Analysis of the nonpolar and semipolar organic matter (OM) using atmospheric pressure photoionization (APPI) Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) revealed that compounds containing only C, H, and O (CHO) and those containing C, H, O, and N (CHON) accounted for more than 90% of the total intensity of the OM peaks. Higher proportions of CHON compounds were observed during days with abnormally high PM_2.5 concentrations at both sites than on regular or non-event days. The proportion of CHON species at the Beijing site was not correlated with secondary ionic species (i.e., NO₃^-, SO₄^2-, and NH₄⁺) or gaseous components (i.e., O₃, NO₂, and SO₂). In contrast, the proportion of CHON species at the Gwangju site was positively correlated with the concentrations of particulate nitrate and ammonium ions, assuming that ambient ammonium nitrate plays a role in the atmospheric formation of nitrogen-containing organic compounds (NOCs) at the Gwangju site and that Gwangju is more strongly influenced by secondary aerosols than Beijing is. In particular, a significant proportion of the compounds observed at the Beijing site contained only C, H and N (CHN), while negligible amounts of CHN were detected at the Gwangju site. The CHN species in Beijing were identified as quinoline compounds and the corresponding -CH₂ homologous series using complementary GC × GC-TOF MS analysis. These results suggest that NOCs and their -CH₂ homologous series from primary emissions may be significant contributors to nonpolar and semipolar OM during winter in Beijing, while NOCs with high oxidation states, likely formed via ambient-phase nitrate-mediated reactions, may be the dominant OM constituents in Gwangju.

The contribution of PM2.5 to cardiovascular disease in China

China is experiencing rapid urbanization and industrialization with correspondingly high levels of air pollution. Although the harm of PM2.5 has been long reported, it is only quite recently that there is increasing concern in China for its possible adverse health effects on cardiovascular disease. We reviewed the epidemiologic evidence of potential health effects of PM2.5 on cardiovascular disease reported from recent studies in China (2013 onwards). There is clear evidence for the contribution of PM2.5 to cardiovascular outcomes, including mortality, ischemic heart disease, and stroke from studies based in various regions in China. This evidence adds to the global evidence that PM2.5 contributes to adverse cardiovascular health risk and highlights the need for improved air quality in China.

An Ensemble Learning Approach for Estimating High Spatiotemporal Resolution of Ground-Level Ozone in the Contiguous United States

In this paper, we integrated multiple types of predictor variables and three types of machine learners (neural network, random forest, and gradient boosting) into a geographically weighted ensemble model to estimate the daily maximum 8 h O₃ with high resolution over both space (at 1 km × 1 km grid cells covering the contiguous United States) and time (daily estimates between 2000 and 2016). We further quantify monthly model uncertainty for our 1 km × 1 km gridded domain. The results demonstrate high overall model performance with an average cross-validated R² (coefficient of determination) against observations of 0.90 and 0.86 for annual averages. Overall, the model performance of the three machine learning algorithms was quite similar. The overall model performance from the ensemble model outperformed those from any single algorithm. The East North Central region of the United States had the highest R², 0.93, and performance was weakest for the western mountainous regions (R² of 0.86) and New England (R² of 0.87). For the cross validation by season, our model had the best performance during summer with an R² of 0.88. This study can be useful for the environmental health community to more accurately estimate the health impacts of O₃ over space and time, especially in health studies at an intra-urban scale.

An Ensemble Learning Approach for Estimating High Spatiotemporal Resolution of Ground-Level Ozone in the Contiguous United States

In this paper, we integrated multiple types of predictor variables and three types of machine learners (neural network, random forest, and gradient boosting) into a geographically weighted ensemble model to estimate the daily maximum 8 h O₃ with high resolution over both space (at 1 km × 1 km grid cells covering the contiguous United States) and time (daily estimates between 2000 and 2016). We further quantify monthly model uncertainty for our 1 km × 1 km gridded domain. The results demonstrate high overall model performance with an average cross-validated R² (coefficient of determination) against observations of 0.90 and 0.86 for annual averages. Overall, the model performance of the three machine learning algorithms was quite similar. The overall model performance from the ensemble model outperformed those from any single algorithm. The East North Central region of the United States had the highest R², 0.93, and performance was weakest for the western mountainous regions (R² of 0.86) and New England (R² of 0.87). For the cross validation by season, our model had the best performance during summer with an R² of 0.88. This study can be useful for the environmental health community to more accurately estimate the health impacts of O₃ over space and time, especially in health studies at an intra-urban scale.

Health and economic impacts of particulate matter pollution on hospital admissions for mental disorders in Chengdu, Southwestern China

The evidence for adverse effects of ambient particulate matter (PM) pollution on mental disorders (MDs) is limited, especially in developing countries. This study aimed to quantify both PM related health impacts and corresponding economic loses for overall and specific MDs in southwestern China. Data regarding 134,292 hospital admissions for MDs were collected from local Compulsory Medical Insurance Database in 2013-2017. A generalized additive model (GAM) was applied to estimate the exposure-response effects of PM pollution on hospital admissions for MDs. And the cost of illness method (COI) was adopted to further assess corresponding hospitalization costs and productivity loses. It was showed that PM pollution was significantly related to hospital admissions for overall and specific MDs. Each 10 μg/m³ increase in concentrations of PM₁₀ (particles with an aerodynamic diameters ≤10 μm), PM_2.5 (≤ 2.5 μm) and PMc (2.5 μm < c < 10 μm) at the cumulative lag03 day would be responsible for 3.25% (95%CI: 2.34-4.16%), 6.38% (95%CI: 4.79-7.97%), and 3.81% (95%CI: 2.13-5.50%) increments in daily hospital admissions for MDs, respectively. Stronger associations were observed in males, cool season and people over 45 years. During the study period, PM pollution brought 1453.18 million Yuan economic losses for overall MDs, accounting for 0.026% of local GDP. This study suggested that short-term exposure to PM pollution, especially to PM_2.5, was associated with increased hospital admissions for MDs in southwestern China. In addition, potential benefits of lowering PM concentrations are considerable.

Role of functional groups in reaction kinetics of dithiothreitol with secondary organic aerosols

The toxicity of organic aerosols has been largely ascribed to the generation of reactive oxygen species, which could subsequently induce oxidative stress in biological systems. The reaction of DTT with redox-active species in PM has been generally assumed to be pseudo-first order, with the oxidative potential of PM being represented by the DTT consumption per minute of reaction time per μg of PM. Although catalytic reactive species such as transition metals and quinones are long believed to be the main contributors of DTT responses, the role of non-catalytic DTT reactive species such as organic hydroperoxides (ROOH) and electron-deficient alkenes (e.g., conjugated carbonyls) in DTT consumption has been recently highlighted. Thus, understanding the reaction kinetics and mechanisms of DTT consumption by various PM components is required to interpret the oxidative potential measured by DTT assays more accurately. In this study, we measured the DTT consumptions over time and characterized the reaction products using model compounds and secondary organic aerosols (SOA) with varying initial concentrations. We observed that the DTT consumption rates linearly increased with both initial DTT and sample concentrations. The overall reaction order of DTT with non-catalytic reactive species and SOA in this study is second order. The reactions of DTT with different functional groups have significantly different rate constants. The reaction rate constant of isoprene SOA with DTT is mainly determined by the concentration of ROOH. For toluene SOA, both ROOH and electron-deficient alkenes may dominate its DTT reaction rates. These results provide some insights into the interpretation of DTT-based aerosol oxidative potential and highlight the need to study the toxicity mechanism of ROOH and electron-deficient alkenes in PM for future work.

Ambient particulate matter and biomass burning: an ecological time series study of respiratory and cardiovascular hospital visits in northern Thailand

BACKGROUND

Exposure to particulate matter (PM) emitted from biomass burning is an increasing concern, particularly in Southeast Asia. It is not yet clear how the source of PM influences the risk of an adverse health outcome. The objective of this study was to quantify and compare health risks of PM from biomass burning and non-biomass burning sources in northern Thailand.

METHODS

We collected ambient air pollutant data (PM with a diameter of < 10 μm [PM10], PM2.5, Carbon Monoxide [CO], Ozone [O3], and Nitrogen Dioxide [NO2]) from ground-based monitors and daily outpatient hospital visits in Thailand during 2014-2017. Outpatient data included chronic lower respiratory disease (CLRD), ischaemic heart disease (IHD), and cerebrovascular disease (CBVD). We performed an ecological time series analysis to evaluate the association between daily air pollutants and outpatient visits. We used the 90th and 95th percentiles of PM10 concentrations to determine days of exposure to PM predominantly from biomass burning.

RESULTS

There was significant intra annual variation in PM10 levels, with the highest concentrations occurring during March, coinciding with peak biomass burning. Incidence Rate Ratios (IRRs) between daily PM10 and outpatient visits were elevated most on the same day as exposure for CLRD = 1.020 (95% CI: 1.012 to 1.028) and CBVD = 1.020 (95% CI: 1.004 to 1.035), with no association with IHD = 0.994 (95% CI: 0.974 to 1.014). Adjusting for CO tended to increase effect estimates. We did not find evidence of an exposure response relationship with levels of PM10 on days of biomass burning.

CONCLUSIONS

We found same-day exposures of PM10 to be associated with certain respiratory and cardiovascular outpatient visits. We advise implementing measures to reduce population exposures to PM wherever possible, and to improve understanding of health effects associated with burning specific types of biomass in areas where such large-scale activities occur.

Time-series analysis of ambient PM2.5 and cardiorespiratory emergency room visits in Lima, Peru during 2010-2016

INTRODUCTION

There have been no time-series studies of air pollution in Peru. Here we evaluate the effect of ambient PM_2.5 on emergency room (ER) visits in Lima.

METHODS

We estimated daily PM_2.5 levels at a 1 km² resolution during 2010-2016 using ground measurements, satellite data, and chemical transport model simulations. Population-weighted average daily PM_2.5 levels were calculated for each district in Lima (n = 40), and assigned to patients based on residence. ER visits for respiratory and circulatory diseases were gathered from nine large public hospitals. Poisson regression was used to estimate the rate ratio for daily ER visits with change in daily PM_2.5, controlling for meteorology, time trends, and district.

RESULTS

For each interquartile range (IQR) increase in PM_2.5, respiratory disease ER visits increased 4% (95% CI: 0-5%), stroke visits 10% (3-18%), and ischemic heart disease visits (adults, 18-64 years) 11% (-1, 24%). Districts with higher poverty showed significantly stronger associations of PM_2.5 and respiratory disease ER visits than districts with lower poverty. Effects were diminished 24-42% using Lima-wide instead of district-specific PM_2.5 levels.

CONCLUSIONS

Short-term exposure to ambient PM_2.5 is associated with increases in ER visits in Lima for respiratory diseases and stroke, and among middle-aged adults, ischemic heart disease.

How to choose healthier urban biking routes: CO as a proxy of traffic pollution

According to the World Health Organization (WHO) air pollution in urban areas, mainly associated with inhalation of gaseous pollutants and particulate matter emitted from motor vehicles, is responsible for one million deaths per year. Carbon monoxide (CO) from the incomplete combustion of fuel is known to bind with hemoglobin, decreasing the blood oxygen-delivery and inducing tissues hypoxia; being more pronounced under conditions of stress like physical activity. The present study demonstrates the usefulness of a compact CO sensor (Alphasense CO-B4) mounted on a bicycle to evaluate atmospheric levels of CO associated with urban microenvironments within a growing Australian city (Brisbane). Urban bike pathways show pronounced and significant variations in air quality according to the surrounding microenvironment and the time of day. The inhaled dose in real time and the CO total dose over each trip were valuable for estimating the air quality of the route, and identifed how the health benefits of riding a bicycle could be partially offset by poor air quality depending on where and when a cycle route is taken in the inner-city. Finally, environmental conditions, such as wind speed, were found to significantly affected atmospheric CO concentrations, at least during the study period. The present work provides information regarding commuters' exposure to atmospheric pollutants, necessary for modifying the population's (including cyclists) perception of pollution in the urban environment, providing people with the opportunity to choose a healthier route.

Quantifying the Public Health Benefits of Reducing Air Pollution: Critically Assessing the Features and Capabilities of WHO's AirQ+ and U.S. EPA's Environmental Benefits Mapping and Analysis Program - Community Edition (BenMAP - CE)

Scientific evidence spanning experimental and epidemiologic studies has shown that air pollution exposures can lead to a range of health effects. Quantitative approaches that allow for the estimation of the adverse health impacts attributed to air pollution enable researchers and policy analysts to convey the public health impact of poor air quality. Multiple tools are currently available to conduct such analyses, which includes software packages designed by the World Health Organization (WHO): AirQ+, and the U.S. Environmental Protection Agency (U.S. EPA): Environmental Benefits Mapping and Analysis Program - Community Edition (BenMAP - CE), to quantify the number and economic value of air pollution-attributable premature deaths and illnesses. WHO's AirQ+ and U.S. EPA's BenMAP - CE are among the most popular tools to quantify these effects as reflected by the hundreds of peer-reviewed publications and technical reports over the past two decades that have employed these tools spanning many countries and multiple continents. Within this paper we conduct an analysis using common input parameters to compare AirQ+ and BenMAP - CE and show that the two software packages well align in the calculation of health impacts. Additionally, we detail the research questions best addressed by each tool.

Relationship of chronic kidney disease with major air pollutants - A systematic review and meta-analysis of observational studies

BACKGROUND

Articles concerning the correlation of the risk of chronic kidney disease (CKD) with air contaminant exposure present inconsistent findings and the magnitude of the link is still unclear. Therefore, we planned to systematically and quantitatively investigate the overall strength of proofs in this field.

METHODS

Relevant articles on Cochrane, EMBASE, Medline, Web of Science, and CINHAL were searched as per relevant strategies. Only observational studies that disclosed the link of CKD risk with major air pollutants were enrolled, including PM10 and PM2.5, which were particulate matter less than 10 um and less than 2.5 um in erodynamic diameter respectively. Pooled relative risk (RR) and 95 % confidence interval (CI) were determined using random--effects models, regardless of the heterogeneity quantified by I² statistic.

RESULTS

Finally, 7 studies involving 5,812,381 participants were included. The incidence of CKD was increased by long-term exposure to PM10 (including solely estimated exposure to PM10 from studies using PM2.5) (RR 1.08, 95 %CI 1.04-1.11) with considerable heterogeneity (I² = 79 %), and the risk of CKD was raised by 8% when the long-time exposure to PM10 increased by 10 ug/m³. The pooled RR (95 %CI) with a 10 μg/m³ increase in PM2.5 for risk of CKD was 1.09 (1.03-1.17). Stratified analysis also verified the general negative effects.

CONCLUSIONS

Chronic subjection to major air contaminants (PM10 and PM2.5) is more likely to cause CKD. Thus, developing global approaches of air pollution elimination to prevent CKD is urgent.

The contribution of improved air quality to reduced cardiovascular mortality: Declines in socioeconomic differences over time

Major improvements in air quality since 1990, observed through reductions in fine particulate matter (PM2.5), have been associated with reduced cardiovascular mortality rates (CMR). However, it is not well understood whether the health benefit attributed to PM2.5 reductions has been similar across strata of socioeconomic deprivation (SED). Using mixed effect regression models, we estimated the PM2.5-related change in the CMR across 2,132 US counties in five SED strata between 1990 and 2010. The analysis included annual county CMR (deaths/100,000 person-year), annual county PM2.5 (μg/m3), and an index of county SED based on socioeconomic factors from the 1990 US Census. The contribution of PM2.5 reductions to decreased CMR varied by SED strata and over time. Yearly differences resulted from varying rates of PM2.5 reduction and because of the non-linear relationship between CMR and PM2.5 concentration. In early years, PM2.5-related CMR reductions were smallest in the most deprived counties compared to all other counties (range: 0.4-0.6 vs 0.7-1.6 fewer deaths/100,000 person-year), due to slower rates of PM2.5 reduction in these counties. However, in later years, PM2.5-related CMR reductions were highest counties with moderate to high deprivation, compared to counties with the least deprivation (range: 1.0-2.2 vs 0.5-0.9 fewer deaths/100,000 person-year) due to larger CMR reductions per decrease in PM2.5. We identified that CMR reductions related to air quality improvements have become more similar over time between socioeconomic strata.

Short-Term Impact of Traffic-Related Particulate Matter and Noise Exposure on Cardiac Function

Exposure to traffic-related air pollution and noise exposure contributes to detrimental effects on cardiac function, but the underlying short-term effects related to their simultaneous personal exposure remain uncertain. The aim is to assess the impact of total inhaled dose of particulate matter and total noise exposure on the variations of electrocardiogram (ECG) parameters between pre-cycling and post-cycling periods. Mid-June 2019, we collected four participants' personal exposure data related to traffic-related noise and particulate matter (PM_2.5 and PM₁₀) as well as ECG parameters. Several Bayesian linear models were built to examine a potential association between air pollutants and noise exposure and ECG parameters: heart rate (HR), standard deviation of the normal-to-normal intervals (SDNN), percentage of successive RR intervals that differ by more than 50 ms (pNN50), root mean square of successive RR interval differences (rMSSD), low-frequency power (LF), high-frequency power (HF), and ratio of low- to high-frequency power (LF/HF). We analyzed in total 255 5-min segments of RR intervals. We observed that per 1 µg increase in cumulative inhaled dose of PM_2.5 was associated with 0.48 (95% CI: 0.22; 15.61) increase in variation of the heart rate, while one percent of total noise dose was associated with 0.49 (95% CI: 0.17; 0.83) increase in variation of heart rate between corresponding periods. Personal noise exposure was no longer significant once the PM_2.5 was introduced in the whole model, whilst coefficients of the latter that were significant previously remained unchanged. Short-term exposure to traffic-related air and noise pollution did not, however, have an impact on heart rate variability.

Association of PM2.5 concentration with health center outpatient visits for respiratory diseases of children under 5 years old in Lima, Peru

BACKGROUND

Lima is one of the more polluted cities in Latin America. High levels of PM_2.5 have been shown to increase health center outpatient visits of respiratory diseases.

METHODS

Health center outpatient visits for children < 5 years for childhood respiratory disease (acute lower respiratory infections (ALRI), pneumonia and acute bronchiolitis/asthma) from 498 public clinics in Lima were available on a weekly basis from 2011 to 2015 from Peru's Ministry of Health (MINSA). The association between the average weekly concentrations of PM_2.5 was evaluated in relation to the number of weekly health center outpatient visits for children. Weekly PM_2.5 values were estimated using a recently developed model that combined data observed from ground monitors, with data from space satellite and meteorology. Ground monitoring data came from 10 fixed stations of the Peruvian National Service of Meteorology and Hydrology (SENAMHI) and from 6 mobile stations located in San Juan de Miraflores by Johns Hopkins University. We conducted a time-series analysis using a negative binomial model.

RESULTS

We found a significant association between exposure to PM_2.5 and all three types of respiratory diseases, across all age groups. For an interquartile increase in PM_2.5, we found an increase of 6% for acute lower respiratory infections, an increase of 16-19% for pneumonia, and an increase of 10% for acute bronchiolitis / asthma.

CONCLUSIONS

Higher emissions of environmental pollutants such as PM_2,5 could be a trigger for the increase of health center outpatients visits for respiratory diseases (ALRI, pneumonia and asthma), which are themselves risk factors for mortality for children in Lima province, Peru.

A Methodology for Data-Driven Decision-Making in the Monitoring of Particulate Matter Environmental Contamination in Santiago of Chile

Atmospheric pollution derives mainly from anthropogenic activities that use combustion and may lead to adverse effects in exposed populations. It is generally accepted that air contamination causes cardiovascular and pulmonary morbidity in addition to increased mortality after exposure, but other epidemiological associations have also been described, including cancer as well as reproductive and immunological toxicity. Thus the concentration of chemicals in the air must be controlled. We propose that monitoring of air quality may be achieved by employing data analytics to generate information within the context of data-driven decision making to prevent and/or adequately alert the population about possible critical episodes of air contamination. In this paper, we propose a methodology for monitoring particulate matter pollution in Santiago of Chile which is based on bivariate control charts with heavy-tailed asymmetric distributions. This methodology is useful for monitoring environmental risk when the particulate matter concentrations follow bivariate Birnbaum-Saunders or Birnbaum-Saunders-t-Student distributions. A case study with real particulate matter pollution from Santiago is provided, which shows that the methodology is suitable to alert early episodes of extreme air pollution. The results are in agreement with the critical episodes reported with the current model used by the Chilean health authority.

Implicit Definition of Flow Patterns in Street Canyons—Recirculation Zone—Using Exploratory Quantitative and Qualitative Methods

Air pollution is a major health hazard for the population that increasingly lives in cities. Street-scale Air Quality Models (AQMs) are a cheap and efficient way to study air pollution and possibly provide solutions. Having to include all the complex phenomena of wind flow between buildings, AQMs employ several parameterisations, one of which is the recirculation zone. Goal of this study is to derive an implicit or explicit definition for the recirculation zone from the flow in street canyons using computational fluid dynamics (CFD). Therefore, a CFD-Large Eddy Simulation model was employed to investigate street canyons with height to width ratio from 1 to 0.20 under perpendicular wind direction. The developed dataset was analyzed with traditional methods (vortex visualization criteria and pollutant dispersion fields), as well as clustering methods (machine learning). Combining the above analyses, it was possible to extract qualitative features that agree well with literature but most importantly to develop quantitative expressions that describe their topology. The extracted features’ topology depends strongly on the street canyon dimensions and not surprisingly is independent of the wind velocity. The developed expressions describe areas with common flow characteristics inside the canyon and thus they can be characterised as an implicit definition for the recirculation zone. Furthermore, the presented methodology can be further applied to cover more parameters such us oblique wind direction and heated-facades and more methods for data analysis.

The nexus between air pollution, green infrastructure and human health

Cities are constantly evolving and so are the living conditions within and between them. Rapid urbanization and the ever-growing need for housing have turned large areas of many cities into concrete landscapes that lack greenery. Green infrastructure can support human health, provide socio-economic and environmental benefits, and bring color to an otherwise grey urban landscape. Sometimes, benefits come with downsides in relation to its impact on air quality and human health, requiring suitable data and guidelines to implement effective greening strategies. Air pollution and human health, as well as green infrastructure and human health, are often studied together. Linking green infrastructure with air quality and human health together is a unique aspect of this article. A holistic understanding of these links is key to enabling policymakers and urban planners to make informed decisions. By critically evaluating the link between green infrastructure and human health via air pollution mitigation, we also discuss if our existing understanding of such interventions is sufficient to inform their uptake in practice. Natural science and epidemiology approach the topic of green infrastructure and human health very differently. The pathways linking health benefits to pollution reduction by urban vegetation remain unclear and the mode of green infrastructure deployment is critical to avoid unintended consequences. Strategic deployment of green infrastructure may reduce downwind pollution exposure. However, the development of bespoke design guidelines is vital to promote and optimize greening benefits, and measuring green infrastructure's socio-economic and health benefits are key for their uptake. Greening cities to mitigate pollution effects is on the rise and these need to be matched by scientific evidence and appropriate guidelines. We conclude that urban vegetation can facilitate broad health benefits, but there is little empirical evidence linking these benefits to air pollution reduction by urban vegetation, and appreciable efforts are needed to establish the underlying policies, design and engineering guidelines governing its deployment.

A Case-Crossover Study to Investigate the Effects of Atmospheric Particulate Matter Concentrations, Season, and Air Temperature on Accident and Emergency Presentations for Cardiovascular Events in Northern Italy

Atmospheric particulate matter (PM) has multiple adverse effects on human health, high temperatures are also associated with adverse health outcomes, and the frequency of cardiovascular events (CVEs) varies with season. We investigated a hypothesized increase in PM-related accident and emergency (A&E) presentations for CVE with high temperature, warm season, days of high influenza incidence, and in people with a cancer diagnosis, using a time-stratified case-crossover study design. Outcomes were associations of A&E presentation for CVE with atmospheric PM ≤ 10 μm (PM₁₀), season, and air temperature. PM₁₀ levels in the municipality of residence (exposure variable) were estimated by modeling data from local monitoring stations. Conditional logistic regression models estimated odds ratios (OR) with 95% confidence intervals (CI) for presentations in relation to supposed influencers, adjusting for confounders. Study participants were all who presented at the A&E of a large hospital near Milan, Italy, for a CVE (ICD-9: 390–459) from 1st January 2014 to 31st December 2015. There were 1349 A&E presentations for CVE in 2014–2015 and 5390 control days. Risk of A&E presentation was significantly increased on hot days with OR 1.34 (95%CI 1.05–1.71) per 10 μg/m³ PM₁₀ increment (as mean PM₁₀ on day of presentation, and 1 and 2 days before (lags 0–2)), and (for lag 0) in autumn (OR 1.23, 95%CI 1.09–1.37) and winter (OR 1.18, 95%CI 1.01–1.38). Risks were also significantly increased when PM₁₀ was on lag 1, in people with a cancer diagnosis in the spring and summer months (1.88, 95%CI 1.05–3.37), and on days (lags 0–2) of high influenza incidence (OR 2.34, 95%CI 1.01–5.43). PM₁₀ levels exceeded the 50 μg/m³ “safe” threshold recommended by the WHO and Italian legislation for only 3.8% of days during the warm periods of 2014–2015. Greater risk of A&E presentation for CVE in periods of high PM₁₀ and high temperature suggests that “safe” thresholds for PM₁₀ should be temperature-dependent and that the adverse effects of PM₁₀ will increase as temperatures increase due to climate change.

Short-term PM2.5 forecasting based on CEEMD-RF in five cities of China

The development of industrial civilization has greatly enriched the material and spiritual life of human beings, but it is accompanied by the intensification of the consumption of earth resources and environmental pollution. The smog that has emerged in various parts of China in recent years is a typical problem, which not only endangers human health but also affects normal human work and life. It is difficult to control smog in a short time productively, so people need to understand the rule of smog formation gradually, and effectively predict the PM2.5 index to help people continuously analyze relevant mechanisms and timely protect-related hazards. This paper proposes a hybrid model that uses the Complementary Ensemble Empirical Modal Decomposition algorithm to mine the information in the original PM2.5 sequence and then predicts the pertinent random forests. The trend of PM2.5 concentration during the decomposition process is effectively reflected, and the decomposition sequence is modeled by the high tolerance of the random forest to the noise data and the good fitting ability. In the modeling process, the parameters are optimized according to the evaluation function of the model on the verification set, and eventually, the prediction sequences are superimposed to obtain the final predicted PM2.5 concentration value. The validity of the model is verified by the data of several Chinese cities with different geographical features in the past 5 years. The results show that the recommendation model is higher than other comparison models in terms of model stability and prediction accuracy.

Estimating cardiovascular hospitalizations and associated expenses attributable to ambient carbon monoxide in Lanzhou, China: Scientific evidence for policy making

OBJECTIVES

Air pollution is an important trigger of cardiovascular disease worldwide, but few studies have determined the cardiovascular disease, health, and economic burdens attributable to ambient carbon monoxide (CO). This study aimed to examine the association between CO and CVD hospitalizations, and quantified the attributable CVD hospitalizations, associated hospital stays and hospitalization costs for CO in Lanzhou, one of the most air-polluted Chinese cities historically.

METHODS

Daily data on CVD hospitalizations, air pollutants, and weather records from 2013 to 2017 were obtained for Lanzhou, China. Generalized additive model with a quasi-Poisson link was used to model the association between CO and CVD hospitalizations, after controlling for other air pollutants, weather conditions, day of week, long-term trend, influenza and pneumonia incidence. The effects of CO on hospital stays and hospitalization expenses from CVD were also quantified.

RESULTS

CO concentrations below the current Chinese ambient air quality standard had a significant impact on CVD hospitalizations. Each 1 mg/m³ increase in CO concentration on the present day and previous 4 days (lag 0-4) was associated with an 11% (95% confidence interval: 3%-20%) increase in total CVD hospitalizations. During the study period, CO was responsible for 11.74% of total CVD hospitalizations, equating to 62,792 inpatient days and 149 million RMB. Each adult patient on average spent approximately 5% of annual salary on medicine from CO-related CVD treatment during hospitalization. Maintaining the historical CO concentration within 1 to 3 mg/m³ could avert hundreds of total CVD hospitalizations and save millions of RMB annually in Lanzhou, China.

CONCLUSIONS

Exposure to low-level ambient CO concentration increased the risk of CVD hospitalizations and resulted in substantial health and economic burdens in Lanzhou, China. Our findings can be used for evidence-based practice and policy making to assess the cost-effectiveness of prevention measures.

Personal Fine Particulate Matter Constituents, Increased Systemic Inflammation, and the Role of DNA Hypomethylation

Limited evidence is available on the effects of various fine particulate matter (PM_2.5) components on inflammatory cytokines and DNA methylation. We examined whether 16 PM_2.5 components are associated with changes in four blood biomarkers, that is, tumor necrosis factor-α (TNF-α), soluble cluster of differentiation 40 ligand (sCD40L), soluble intercellular adhesion molecule-1 (sICAM-1), and fibrinogen, as well as their corresponding DNA methylation levels in a panel of 36 healthy college students in Shanghai, China. We used linear mixed-effect models to evaluate the associations, with controls of potential confounders. We further conducted mediation analysis to evaluate the potential mediation effects of components on inflammatory markers through change in DNA methylation. We observed that several components were consistently associated with TNF-α and fibrinogen as well as their DNA hypomethylation. For example, an interquartile range increase in personal exposure to PM_2.5-lead (Pb) was associated with 65.20% (95% CI: 37.07, 99.10) increase in TNF-α and 2.66 (95% CI: 37.07, 99.10) decrease in TNF-α methylation, 30.51% (95% CI: 0.72, 69.11) increase in fibrinogen and 1.25 (95% CI: 0.67, 1.83) decrease in F3 methylation. PM_2.5 components were significantly associated with sICAM-1 methylation but not with sICAM-1 protein. DNA methylation mediated 19.89%-41.75% of the elevation in TNF-α expression by various PM_2.5 constituents. Our findings provide clues that personal PM_2.5 constituents exposure may contribute to increased systemic inflammation through DNA hypomethylation.

Association of Long-Term Exposure to Fine Particulate Matter and Cardio-Metabolic Diseases in Low- and Middle-Income Countries: A Systematic Review

: Background: Numerous epidemiological studies indicated high levels of particulate matter less than2.5 μm diameter (PM2.5) as a major cardiovascular risk factor. Most of the studies have been conducted in high-income countries (HICs), where average levels of PM2.5 are far less compared to low- and middle- income countries (LMICs), and their socio-economic profile, disease burden, and PM speciation/composition are very different. We systematically reviewed the association of long-term exposure to PM2.5 and cardio-metabolic diseases (CMDs) in LMICs.

METHODS

Multiple databases were searched for English articles with date limits until March 2018. We included studies investigating the association of long-term exposure to PM2.5 (defined as an annual average/average measure for 3 more days of PM2.5 exposure) and CMDs, such as hospital admissions, prevalence, and deaths due to CMDs, conducted in LMICs as defined by World Bank. We excluded studies which employed exposure proxy measures, studies among specific occupational groups, and specific episodes of air pollution.

RESULTS

A total of 5567 unique articles were identified, of which only 17 articles were included for final review, and these studies were from Brazil, Bulgaria, China, India, and Mexico. Outcome assessed were hypertension, type 2 diabetes mellitus and insulin resistance, and cardiovascular disease (CVD)-related emergency room visits/admissions, death, and mortality. Largely a positive association between exposure to PM2.5 and CMDs was found, and CVD mortality with effect estimates ranging from 0.24% to 6.11% increased per 10 μg/m3 in PM2.5. CVD-related hospitalizations and emergency room visits increased by 0.3% to 19.6%. Risk factors like hypertension had an odds ratio of 1.14, and type 2 diabetes mellitus had an odds ratio ranging from 1.14-1.32. Diversity of exposure assessment and health outcomes limited the ability to perform a meta-analysis.

CONCLUSION

Limited evidence on the association of long-term exposure to PM2.5 and CMDs in the LMICs context warrants cohort studies to establish the association.

Toward an Improved Air Pollution Warning System in Quebec

The nature of pollutants involved in smog episodes can vary significantly in various cities and contexts and will impact local populations differently due to actual exposure and pre-existing sensitivities for cardiovascular or respiratory diseases. While regulated standards and guidance remain important, it is relevant for cities to have local warning systems related to air pollution. The present paper proposes indicators and thresholds for an air pollution warning system in the metropolitan areas of Montreal and Quebec City (Canada). It takes into account past and current local health impacts to launch its public health warnings for short-term episodes. This warning system considers fine particulate matter (PM_2.5) as well as the combined oxidant capacity of ozone and nitrogen dioxide (O_x) as environmental exposures. The methodology used to determine indicators and thresholds consists in identifying extreme excess mortality episodes in the data and then choosing the indicators and thresholds to optimize the detection of these episodes. The thresholds found for the summer were 31 μg/m³ for PM_2.5 and 43 ppb for O_x in Montreal, and 32 μg/m³ and 23 ppb in Quebec City. In winter, thresholds found were 25 μg/m³ and 26 ppb in Montreal, and 33 μg/m³ and 21 ppb in Quebec City. These results are in line with different guidelines existing concerning air quality, but more adapted to the cities examined. In addition, a sensitivity analysis is conducted which suggests that O_x is more determinant than PM_2.5 in detecting excess mortality episodes.

Assessment of Spatial Variability across Multiple Pollutants in Auckland, New Zealand

Spatial saturation studies using source-specific chemical tracers are commonly used to examine intra-urban variation in exposures and source impacts, for epidemiology and policy purposes. Most such studies, however, has been performed in North America and Europe, with substantial regional combustion-source contributions. In contrast, Auckland, New Zealand, a large western city, is relatively isolated in the south Pacific, with minimal impact from long-range combustion sources. However, fluctuating wind patterns, complex terrain, and an adjacent major port complicate pollution patterns within the central business district (CBD). We monitored multiple pollutants (fine particulate matter (PM_2.5), black carbon (BC), elemental composition, organic diesel tracers (polycyclic aromatic hydrocarbons (PAHs), hopanes, steranes), and nitrogen dioxide (NO₂)) at 12 sites across the ~5 km² CBD during autumn 2014, to capture spatial variation in traffic, diesel, and proximity to the port. PM_2.5 concentrations varied 2.5-fold and NO₂ concentrations 2.9-fold across the CBD, though constituents varied more dramatically. The highest-concentration constituent was sodium (Na), a distinct non-combustion-related tracer for sea salt (µ = 197.8 ng/m³ (SD = 163.1 ng/m³)). BC, often used as a diesel-emissions tracer, varied more than five-fold across sites. Vanadium (V), higher near the ports, varied more than 40-fold across sites. Concentrations of most combustion-related constituents were higher near heavy traffic, truck, or bus activity, and near the port. Wind speed modified absolute concentrations, and wind direction modified spatial patterns in concentrations (i.e., ports impacts were more notable with winds from the northeast).

Effects of economic crisis on air quality in Ioannina, Greece

The aim of this study was to investigate the regime of air pollution in Ioannina, NW Greece during the years of Greek financial crisis. Annual, weekly and daily patterns for PM₁₀, PM_2.5, NO₂, O₃ and Benzene were defined in order to reveal the sources of air pollutants in Ioannina and the time periods of probable episodes. The quality of air was characterized according to the European Environment Agency's European Air Quality Index, separately for winter and summer, while it was examined if and in what extend the thresholds of European Directives for each pollutant have been exceeded. The air quality in Ioannina was found to be "Good" as far as NO₂ and O₃ were concerned. In contrast, there were many cases with "Poor" and "Very Poor" conditions related to PM₁₀ and PM_2.5 levels, mainly during winter and autumn, caused by wood burning for residential heating. The mean annual concentrations of all pollutants did not exceed EU's standards, but from 2011 onwards, the number of cases with PM₁₀ mean daily concentration above threshold surpassed the number of permitted exceedences of EU directives.

Air pollution and hospital admissions for cardiovascular diseases in Ahvaz, Iran

Cardiovascular disease is one of the main causes of death in Iran. The aim of this study was to determine the relation between air pollution and cardiovascular hospital admissions in Ahwaz, Iran. Daily information about cardiovascular hospital admissions (based on the ICD-10) and data on air pollutants during 2008-2018 were inquired. A quasi-Poisson regression combined with linear distributed lag models; adjusted for trend, seasonality, temperature, relative humidity, weekdays and holidays was used to assess the relation between hospital admission for cardiovascular diseases and the average daily air pollution. The results of this study showed a significant increase in cardiovascular hospital admissions in the total population and women's population in relation to O₃. There was a significant increase in hospital admissions for cardiovascular diseases in the whole population as well as gender and age groups associated with NO₂ and NO. A significant increase was found in hospital admissions for cardiovascular diseases in relation to CO in the 65-74-year-old population. Finally, the results of this study showed that there was a significant increase in hospital admissions for cardiovascular disease associated with SO₂. The main results of the present study confirm the deleterious short term impact of air pollution on cardiovascular morbidity in Ahvaz city. This evidence empasizes the need to implement policies for reducing air pollution.

Estimating Ground-Level Concentrations of Multiple Air Pollutants and Their Health Impacts in the Huaihe River Basin in China

Air pollutants existing in the environment may have negative impacts on human health depending on their toxicity and concentrations. Remote sensing data enable researchers to map concentrations of various air pollutants over vast areas. By combining ground-level concentrations with population data, the spatial distribution of health impacts attributed to air pollutants can be acquired. This study took five highly populated and severely polluted provinces along the Huaihe River, China, as the research area. The ground-level concentrations of four major air pollutants including nitrogen dioxide (NO₂), sulfate dioxide (SO₂), particulate matters with diameter equal or less than 10 (PM₁₀) or 2.5 micron (PM_2.5) were estimated based on relevant remote sensing data using the geographically weighted regression (GWR) model. The health impacts of these pollutants were then assessed with the aid of co-located gridded population data. The results show that the annual average concentrations of ground-level NO₂, SO₂, PM₁₀, and PM_2.5 in 2016 were 31 µg/m³, 26 µg/m³, 100 µg/m³, and 59 µg/m³, respectively. In terms of the health impacts attributable to NO₂, SO₂, PM₁₀, and PM_2.5, there were 546, 1788, 10,595, and 8364 respiratory deaths, and 1221, 9666, 46,954, and 39,524 cardiovascular deaths, respectively. Northern Henan, west-central Shandong, southern Jiangsu, and Wuhan City in Hubei are prone to large health risks. Meanwhile, air pollutants have an overall greater impact on cardiovascular disease than respiratory disease, which is primarily attributable to the inhalable particle matters. Our findings provide a good reference to local decision makers for the implementation of further emission control strategies and possible health impacts assessment.

Ambient air pollution exposure and obesity-related traits in Korean adults

PURPOSE

Although some studies have tried to determine the impact of long-term air pollution exposure on obesity, they have mainly focused on body mass index (BMI) and the results are inconsistent. Therefore, we investigated the association of annual ambient air pollution exposure with various obesity traits, including computed tomography-measured abdominal fatness, in a large Korean adult population.

PATIENTS AND METHODS

A total of 5,114 participants who underwent routine health check-ups at Seoul National University Hospital were included in the analysis. We calculated the annual average concentrations of ambient air pollutants, such as particulate matter ≤10 μm in diameter (PM₁₀) and nitrogen dioxide (NO₂), using the individual's zip code. Obesity-related indicators included the BMI, waist circumference (WC), percent body fat (PBF), total adipose tissue (TAT), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT).

RESULTS

The mean age of the population was 53.5 and 70.9% were men. The mean annual concentrations of PM₁₀ and NO₂ were 49.4 μg/m³ and 30.3 ppb, respectively. In the full covariates model, adjusted for demographic and clinical variables, interquartile range increase in annual average concentration of PM₁₀ and NO₂ was not associated with any obesity-related phenotypes including BMI, WC, PBF, TAT, VAT, and SAT (all P>0.05). Likewise, no significant association between air pollutants and obesity-related traits was observed in any subgroups, stratified by sex and age (all P>0.05).

CONCLUSION

Annual exposure to ambient air pollution is not associated with any obesity-related traits in Korean adults.

Pure ultra-fine carbon particles do not exert pro-coagulation and inflammatory effects on microvascular endothelial cells

Pro-thrombotic and inflammatory changes play an important role in cardiovascular morbidity and mortality, resulting from short-term exposure to fine particulate air-pollution. Part of those effects has been attributed to the ultra-fine particles (UFPs) that pass through the lung and directly contact blood-exposed and circulating cells. Despite UFP-induced platelet activation, it is unclear whether the penetrated particles exert any direct effect on endothelial cells. While exposure levels are boosting as a result of world-wide increases in economic development and desertification, which create more air-polluted regions, as well as increase in demands for synthetic UFPs in medicine and various industries, further studies on the health effects of these particles are required. In this study, human pulmonary and cardiac microvascular endothelial cells (MECs) have been exposed to 0.1, 1, 10, and 100 μg/ml suspensions of either a natural (carbon black) or a synthetic (multi-walled carbon nano-tubes) type of UFPs, in vitro. As a result, no changes in the levels of coagulation factor VIII, Von Willebrand factor, Interleukin 8, and P-selectin measured in the cells' supernatant were observed prior to and 6, 12, and 24 h after exposure. In parallel, the spatio-temporal effect of UFPs on cardiac MECs was evaluated by Transmission Electron Microscopy. Despite phagocytic uptake of pure UFPs observed on cellular sections of the treated cells, Weibel-Palade bodies remained intact in shape and similar in number when compared with the untreated cells. Our work shows that carbon itself is a non-toxic carrier for endothelial cells.

Proliferation of low-cost sensors. What prospects for air pollution epidemiologic research in Sub-Saharan Africa?

Addressing the worsening urban air quality situation in Sub-Saharan Africa (SSA) is proving increasingly difficult owing to paucity of data on air pollution levels and also, lack of local evidence on the magnitude of the associated health effects. There is therefore the urgent need to expand air quality monitoring (AQM) networks in SSA to enable the conduct of high quality epidemiologic studies to help inform policies aimed at addressing air pollution and the associated health effects. In this commentary, I explore the prospects that the proliferation of low-cost sensors in recent times holds for air pollution epidemiologic research in SSA. This commentary is timely because most SSA governments do not see investments in air pollution control that requires assembling a network of sophisticated and prohibitively expensive instrumentation for AQM as necessary for improving and protecting public health. I conclude that, in a region that is bereft of air pollution data, the growing influx of low-cost sensors represents an excellent opportunity for bridging the data gap to inform air pollution control policies and regulations for public health protection. However, it is essential that only the most promising sensor technologies that performs creditably well in the harsh environmental conditions of the region are promoted.

Association of short-term exposure to ambient carbon monoxide with hospital admissions in China

Evidence on the acute effects of ambient carbon monoxide (CO) pollution on morbidity risk in developing countries is scarce and inconsistent. We conducted a multicity case-crossover study in 26 largest cities in China from January, 2014 to December, 2015 to examine the association between short-term exposure to CO and daily hospital admission. We fitted conditional logistic regression to obtain effect estimates of the associations. We also performed subset analyses to explore the health effects of CO at low levels. During the study period, a total of 14,569,622, 2,008,786 and 916,388 all-cause, cardiovascular and respiratory admissions were identified, respectively. A 1 mg/m³ increase in the CO concentrations corresponded to a 3.75% (95% CI, 3.63–3.87%), 4.39% (95% CI, 4.07–4.70%), and 4.44% (95% CI, 3.97–4.92%) increase in all-cause, cardiovascular, and respiratory admissions on the same day, respectively. The associations were robust to controlling for criteria co-pollutants. In subset analyses, negative effects of short-term CO exposure on hospital admission were observed at lower concentrations (<1 mg/m³), while positive effects were observed at higher concentrations (>2 mg/m³). In conclusion, current CO levels in China were significantly associated with increased daily hospital admissions.

Acute effects of ambient air pollution on outpatient children with respiratory diseases in Shijiazhuang, China

Background

Associations between ambient air pollution and child health outcomes have been well documented in developed countries such as the United States; however, only a limited number of studies have been conducted in developing countries. This study aimed to explore the acute effects of five ambient air pollutants (inhalable particles [PM₁₀], fine particles [PM_2.5], sulfur dioxide [SO₂], nitrogen dioxide [NO₂] and 0zone [O₃]) on children hospital outpatients with respiratory diseases in Shijiazhuang, China.

Methods

Three years (2013–2015) of daily data, including cause-specific respiratory outpatient records and the concentrations of five air pollutants, were collected to examine the short-term association between air pollution and children’s respiratory diseases; using a quasi-Poisson regression generalized additive model. Stratified analyses by season and age were also performed.

Results

From 2013 to 2015, a total of 551,678 hospital outpatient records for children with respiratory diseases were collected in Shijiazhuang, China. A 10 μg/m³ increase in a two-day average concentration (lag01) of NO₂, PM_2.5, and SO₂ corresponded to an increase of 0.66% (95% confidence interval [CI]: 0.30–1.03%), 0.13% (95% CI: 0.02–0.24%), and 0.33% (95% CI: 0.10–0.56%) in daily hospital outpatient visits for children with respiratory diseases, respectively. The effects were stronger in the transition season (April, May, September and October) than in other seasons (the hot season [June to August] and the cool season [November to March]). Furthermore, results indicated a generally stronger association in older (7–14 years of age) than younger children (< 7 years of age).

Conclusions

This research found a significant association between ambient NO₂, PM_2.5, and SO₂ levels and hospital outpatient visits in child with respiratory diseases in Shijiazhuang, China.

Early life stress, air pollution, inflammation, and disease: An integrative review and immunologic model of social-environmental adversity and lifespan health

Socially disadvantaged individuals are at greater risk for simultaneously being exposed to adverse social and environmental conditions. Although the mechanisms underlying joint effects remain unclear, one hypothesis is that toxic social and environmental exposures have synergistic effects on inflammatory processes that underlie the development of chronic diseases, including cardiovascular disease, diabetes, depression, and certain types of cancer. In the present review, we examine how exposure to two risk factors that commonly occur with social disadvantage-early life stress and air pollution-affect health. Specifically, we identify neuroimmunologic pathways that could link early life stress, inflammation, air pollution, and poor health, and use this information to propose an integrated, multi-level model that describes how these factors may interact and cause health disparity across individuals based on social disadvantage. This model highlights the importance of interdisciplinary research considering multiple exposures across domains and the potential for synergistic, cross-domain effects on health, and may help identify factors that could potentially be targeted to reduce disease risk and improve lifespan health.

Cardiorespiratory health effects of gaseous ambient air pollution exposure in low and middle income countries: a systematic review and meta-analysis

BACKGROUND

Lack of research on the effects of gaseous pollutants (nitrogen oxides [NO_x], sulfur dioxide [SO₂], carbon monoxide [CO] and ozone [O₃]) in the ambient environment on health outcomes from within low and middle income countries (LMICs) is leading to reliance on results from studies performed within high income countries (HICs). This systematic review and meta-analysis examines the cardiorespiratory health effects of gaseous pollutants in LMICs exclusively.

METHODS

Systematic searching was carried out and estimates pooled by pollutant, lag and outcome, and presented as excess relative risk per 10 μg/m³ (NO_x, SO₂, O₃) or 1 ppm (CO) increase pollutant. Sub-group analysis was performed examining estimates by specific outcomes, city and co-pollutant adjustment.

RESULTS

Sixty studies met the inclusion criteria, most (44) from the East Asia and Pacific region. A 10 μg/m³ increase in same day NOx was associated with 0.92% (95% CI: 0.44, 1.39), and 0.70% (0.01, 1.40) increases in cardiovascular and respiratory mortality respectively, same day NO_x was not associated with morbidity. Same day sulfur dioxide was associated with 0.73% (0.04, 1.42) and 0.50% (0.01, 1.00) increases in respiratory morbidity and in cardiovascular mortality respectively.

CONCLUSIONS

Acute exposure to gaseous ambient air pollution (AAP) is associated with increases in morbidity and mortality in LMICs, with greatest associations observed for cardiorespiratory mortality.