Mortality risk associated with short-term exposure to traffic particles and sulfates

Heterogeneity in the health effects of PM2.5 sources across the major metropolitan cities, South Korea: Significance of region-specific management

Ambient PM2.5, well-known for its adverse impacts on human health, is a very heterogeneous pollutant. Its chemical composition and attributable sources vary by region, influenced by meteorological and geographical conditions as well as emission sources. However, administrative policies are currently focused on mass concentrations. However, not all PM2.5 sources provide equally toxic particles. Thus, those sources that should be the focus of controls has not been the priority. In the present study, we conducted source apportionment utilizing positive matrix factorization (PMF) and investigated the association of PM2.5 source contributions with emergency department visits (EDVs) in major megacities in South Korea. Overall, an interquartile range (IQR) increment in source contribution increased the number of emergency room visits. Industry and coal combustion sources, marked by heavy metals, were principally associated with the adverse health impacts. However, the sources showing significant associations with EDVs differed across the study area. In addition, we found that region-specific relationships between PM2.5 sources and morbidity were plausible, considering the existence of relevant sources such as industrial complexes and coal-fired power plants. The analysis of source contributions according to wind conditions also supported the source-morbidity relationships. These findings suggest that administrative policies for PM2.5 control should be established and implemented considering region-specific characteristics of the links between PM2.5 sources and health impacts to maximize the control's public health effects. Furthermore, the results of the present study indicate that PMF was an effective method for linking acute exposure to PM2.5 source types with health outcomes to prioritize its sources.

Predicting latent source-specific PM2.5 pollution from regional sources at unmonitored sites by Bayesian spatial multivariate receptor modeling

Fine particulate matter (PM_2.5) has been a pollutant of main interest globally for more than two decades, owing to its well-known adverse health effects. For developing effective management strategies for PM_2.5, it is vital to identify its major sources and quantify how much they contribute to ambient PM_2.5 concentrations. With the expanded monitoring efforts established during recent decades in Korea, speciated PM_2.5 data needed for source apportionment of PM_2.5 are now available for multiple sites (cities). However, many cities in Korea still do not have any speciated PM_2.5 monitoring station, although quantification of source contributions for those cities is in great need. While there have been many PM_2.5 source apportionment studies throughout the world for several decades based on monitoring data collected from receptor site(s), none of those receptor-oriented studies could predict unobserved source contributions at unmonitored sites. This study predicts source contributions of PM_2.5 at unmonitored locations using a recently developed novel spatial multivariate receptor modeling (BSMRM) approach, which incorporates spatial correlation in data into modeling and estimation for spatial prediction of latent source contributions. The validity of BSMRM results is also assessed based on the data from a test site (city), not used in model development and estimation.

Commuter's personal exposure to air pollutants after the implementation of a cable car for public transport: Results of the natural experiment TrUST

Commuters in urban settlements are frequently exposed to high concentrations of air pollutants due to their proximity to mobile sources, making exposure to traffic-related air pollutants an important public health issue. Recent trends in urban transport towards zero- and low-tailpipe emission alternatives will likely result in decreased exposure to air pollutants. The TrUST (Urban transformations and health) study offers a unique opportunity to understand the impacts of a new cable car (TransMiCable) in underserved communities within Bogotá, Colombia. The aims of this study are to assess the personal exposure to fine particulate matter (PM_2.5), equivalent Black Carbon (eBC), and Carbon Monoxide (CO) in transport micro-environments and to estimate the inhaled dose per trip during mandatory multimodal trips before and after the implementation of the TransMiCable. We collected personal exposure data for Bus-Rapid-Transit (BRT) feeder buses, regular buses, informal transport, pedestrians, and TransMiCable. TransMiCable showed lower exposure concentration compared to BRT feeder and regular buses (PM_2.5: 23.6 vs. 87.0 μg m^-3 (P ≤ 0.001) and eBC: 5.2 vs. 28.2 μg m^-3 (P ≤ 0.001), respectively). The mean concentration of PM_2.5 and eBC inside the TransMiCable cabins were 62 % and 82 % lower than the mean concentrations in buses. Furthermore, using a Monte Carlo simulation model, we found that including the TransMiCable as a feeder is related to a 54.4 μg/trip reduction in PM_2.5 inhaled dose and 35.8 μg/trip in eBC per trip. Those changes represent a 27 % and 34 % reduction in an inhaled dose per trip, respectively. Our results show that PM_2.5, eBC, and CO inhaled dose for TransMiCable users is reduced due to lower exposure concentration inside its cabins and shorter travel time. The implementation of a cable car in Bogotá is likely to reduce air pollution exposure in transport micro-environments used by vulnerable populations living in semi-informal settlements.

Evaluating the influence of constant source profile presumption on PMF analysis of PM2.5 by comparing long- and short-term hourly observation-based modeling

Hourly PM_2.5 speciation data have been widely used as an input of positive matrix factorization (PMF) model to apportion PM_2.5 components to specific source-related factors. However, the influence of constant source profile presumption during the observation period is less investigated. In the current work, hourly concentrations of PM_2.5 water-soluble inorganic ions, bulk organic and elemental carbon, and elements were obtained at an urban site in Nanjing, China from 2017 to 2020. PMF analysis based on observation data during specific pollution (firework combustion, sandstorm, and winter haze) and emission-reduction (COVID-19 pandemic) periods was compared with that using the whole 4-year data set (PMF_whole). Due to the lack of data variability, event-based PMF solutions did not separate secondary sulfate and nitrate. But they showed better performance in simulating average concentrations and temporal variations of input species, particularly for primary source markers, than the PMF_whole solution. After removing event data, PMF modeling was conducted for individual months (PMF_month) and the 4-year period (PMF_4-year), respectively. PMF_month solutions reflected varied source profiles and contributions and reproduced monthly variations of input species better than the PMF_4-year solution, but failed to capture seasonal patterns of secondary salts. Additionally, four winter pollution days were selected for hour-by-hour PMF simulations, and three sample sizes (500, 1000, and 2000) were tested using a moving window method. The results showed that using short-term observation data performed better in reflecting immediate changes in primary sources, which will benefit future air quality control when primary PM emissions begin to increase.

The air quality of Palangka Raya, Central Kalimantan, Indonesia: The impacts of forest fires on visibility

Airborne particles in urban Palangka Raya, Kalimantan from Oct 2011 until Oct 2020 have been collected and analyzed for PM_2.5, PM₁₀, and Black Carbon (BC) concentrations. Palangka Raya is a city that serves the capital of the Central Kalimantan province on the island of Borneo. Kalimantan is affected by peat fires that occur periodically. There were identified increases in PM_2.5 and PM₁₀ concentrations during El Niño periods. During the forest fire episode in September - October 2015, PM_2.5 and PM₁₀ concentrations increased significantly, to nearly 400 µg/m³ and 800 µg/m³, respectively, and visibility in the city was reduced to < 0.2 miles. The highest BC concentrations were observed during this massive forest fires episode. The regression analyses for PM_2.5, PM₁₀ and visibility in Palangka Raya during the period of 2011-2020, showed a non-linear correlation with reduction in visibility due to increased PM_2.5 and PM₁₀. There was no correlation for BC with visibility. Air quality in Palangka Raya was at a relatively good level with concentrations below the national ambient air quality standard when there were no forest fires event. Emissions from forest fires caused a substantial reduction in air quality reaching concentrations well above ambient air quality standards and are likely to have caused adverse health effects on the people living in the area.Implications: Indonesia has repeatedly experienced forest fires, especially on Kalimantan and Sumatera Islands, which burned large areas of peatland. The forest fires leading to increasing PM concentrations especially in the PM_2.5 size range which influence visibility. The seasonal variations of BC in Palangka Raya and the relationships of fine particulates with visibility were assessed. The results of regression analyses for PM_2.5 and PM₁₀ to visibility during the period of 2011-2020 showed non-linear relationships. An increasing of PM_2.5 and PM₁₀ concentrations during El Nino periods were detected well above the ambient air quality standard. To ensure effective and continued handling and prevention of forest and peatland fires, the government set up a special task force and review on several rules, including laws and government regulations as well as governor regulations that permit the burning of forest and peatland areas. These results are expected to be used to formulate more effective mitigations in reducing forest fires events in Indonesia.

Potential toxicity of inorganic ions in particulate matter: Ion permeation in lung and disruption of cell metabolism

Exposure to ambient particulate matter (PM) is associated with adverse health effects. Yet, due to the complexity of its chemical composition, the molecular effects of PM exposure and the mechanism of PM-mediated toxicity remain largely unknown. Here, we show that water-soluble inorganics such as nitrate and sulfate ions, rather than PM itself, rapidly penetrate the lung surfactant barrier to the alveolar region and perturb gene expression in the lungs. Through high-throughput sequencing of lung adenocarcinoma cells, we find that exposure to nitrate and sulfate ions activates the cholesterol biosynthetic metabolism and induces the expression of genes related to tumorigenesis. Transcriptome analysis of mouse lungs exposed to nitrate/sulfate aerosols reveals interferon gamma-associated immune response. Interestingly, we find that exposure to a nitrate/sulfate mixture leads to a unique gene expression pattern that is not observed when nitrate or sulfate is treated alone. Our work suggests that the water-soluble ions are a potential source of PM-mediated toxicity and provides a roadmap to unveil the molecular mechanism of health hazards from PM exposure.

Is short-term and long-term exposure to black carbon associated with cardiovascular and respiratory diseases? A systematic review and meta-analysis based on evidence reliability

OBJECTIVE

Adverse health effects of fine particles (particulate matter_2.5) have been well documented by a series of studies. However, evidences on the impacts of black carbon (BC) or elemental carbon (EC) on health are limited. The objectives were (1) to explored the effects of BC and EC on cardiovascular and respiratory morbidity and mortality, and (2) to verified the reliability of the meta-analysis by drawing p value plots.

DESIGN

The systematic review and meta-analysis using adapted Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach and p value plots approach.

DATA SOURCES

PubMed, Embase and Web of Science were searched from inception to 19 July 2021.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Time series, case cross-over and cohort studies that evaluated the associations between BC/EC on cardiovascular or respiratory morbidity or mortality were included.

DATA EXTRACTION AND SYNTHESIS

Two reviewers independently selected studies, extracted data and assessed risk of bias. Outcomes were analysed via a random effects model and reported as relative risk (RR) with 95% CI. The certainty of evidences was assessed by adapted GRADE. The reliabilities of meta-analyses were analysed by p value plots.

RESULTS

Seventy studies met our inclusion criteria. (1) Short-term exposure to BC/EC was associated with 1.6% (95% CI 0.4% to 2.8%) increase in cardiovascular diseases per 1 µg/m³ in the elderly; (2) Long-term exposure to BC/EC was associated with 6.8% (95% CI 0.4% to 13.5%) increase in cardiovascular diseases and (3) The p value plot indicated that the association between BC/EC and respiratory diseases was consistent with randomness.

CONCLUSIONS

Both short-term and long-term exposures to BC/EC were related with cardiovascular diseases. However, the impact of BC/EC on respiratory diseases did not present consistent evidence and further investigations are required.

PROSPERO REGISTRATION NUMBER

CRD42020186244.

Exposure to Primary Air Pollutants Generated by Highway Traffic and Daily Mortality Risk in Near-Road Communities: A Case-Crossover Study

Most epidemiologic studies fail to capture the impact of spatiotemporal fluctuations in traffic on exposure to traffic-related air pollutants in the near-road population. Using a case-crossover design and the Research LINE source (R-LINE) dispersion model with spatiotemporally resolved highway traffic data, we quantified associations between primary pollutants generated by highway traffic-particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM2.5), oxides of nitrogen (NOx), and black carbon (BC)-and daily nonaccidental, respiratory, cardiovascular, and cerebrovascular mortality among persons who had resided within 1 km (0.6 mile) of major highways in the Puget Sound area of Washington State between 2009 and 2013. We estimated these associations using conditional logistic regression, adjusting for time-varying covariates. Although highly resolved modeled concentrations of PM2.5, NOx, and BC from highway traffic in the hours before death were used, we found no evidence of an association between mortality and the preceding 24-hour average PM2.5 exposure (odds ratio = 0.99, 95% confidence interval: 0.96, 1.02) or exposure during shorter averaging periods. This work did not support the hypothesis that mortality risk was meaningfully higher with greater exposures to PM2.5, NOx, and BC from highways in near-road populations, though we did incorporate a novel approach to estimate exposure to traffic-generated air pollution based on detailed traffic congestion data.

Characterising professional drivers' exposure to traffic-related air pollution: Evidence for reduction strategies from in-vehicle personal exposure monitoring

Professional drivers working in congested urban areas are required to work near harmful traffic related pollutants for extended periods, representing a significant, but understudied occupational risk. This study collected personal black carbon (BC) exposures for 141 drivers across seven sectors in London. The aim of the study was to assess the magnitude and the primary determinants of their exposure, leading to the formulation of targeted exposure reduction strategies for the occupation. Each participant's personal BC exposures were continuously measured using real-time monitors for 96 h, incorporating four shifts per participant. 'At work' BC exposures (3.1 ± 3.5 µg/m³) were 2.6 times higher compared to when 'not at work' (1.2 ± 0.7 µg/m³). Workers spent 19% of their time 'at work driving', however this activity contributed 36% of total BC exposure, highlighting the disproportionate effect driving had on their daily exposure. Taxi drivers experienced the highest BC exposures due to the time they spent working in congested central London, while emergency services had the lowest. Spikes in exposure were observed while driving and were at times greater than 100 µg/m³. The most significant determinants of drivers' exposures were driving in tunnels, congestion, location, day of week and time of shift. Driving with closed windows significantly reduced exposures and is a simple behaviour change drivers could implement. Our results highlight strategies by which employers and local policy makers can reduce professional drivers' exposure to traffic-related air pollution.

Relationship between ambient black carbon and daily mortality in Tehran, Iran: a distributed lag nonlinear time series analysis

PURPOSE

The aim of the present study was to investigate the effect of short-term exposure to ambient black carbon (BC) on daily cause-specific mortality, including mortality due to respiratory, cardiovascular, ischemic heart and cerebrovascular diseases in Tehran, Iran.

MATERIALS AND METHODS

Daily non-accidental death counts, meteorological data and hourly concentrations of air pollutants from 2014 to 2017 were collected in Tehran. A distributed lag non-linear model was used to assess the association between exposure to BC and daily mortality.

RESULTS

The mean daily BC concentration during the study period was 3.96 ± 1.19 µg/m³. The results indicated that BC was significantly associated with cardiovascular, ischemic heart disease, and cerebrovascular mortality, but not with respiratory mortality. In first model, each 10 µg/m³ increase in at lag 3, lag 4 and lag 5 were associated with cardiovascular mortality in 16-65 year age group with the relative risks (RRs) of 1.17 (95 % CI: 1.02-1.33), 1.17 (95 % CI: 1.04-1.31) and 1.12 (95 % CI: 1.02-1.24), respectively. The highest mortality rate per 10 µg/m³ increase in exposure was found for ischemic heart diseases with RR of 3.98 (95 % CI: 1.04-1.81, lag 01) for 16-65 age group. Cerebrovascular mortality was associated with 10 µg/m³ increases in non-cumulative exposure with RR of 1.17 (95 % 1.009-1.35, lag 5) in the age group ≥ 65 years. In the second model for a 10 µg/m³ increase in BC, cardiovascular mortality at specific lag days (5 and 6 days) in the age group ≤ 16 years were associated with RR of 1.34 (95 % CI 1.08-1.66) and 1.35(95 % CI 1.02-1.77), respectively.

CONCLUSIONS

This study in Tehran found significant effects of BC exposure on daily mortality for cardiovascular, ischemic heart disease, cerebrovascular disease.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s40201-021-00659-0.

Autophagy changes in lung tissues of mice at 30 days after carbon black-metal ion co-exposure

OBJECTIVES

Accumulating studies have investigated the PM2.5-induced pulmonary toxicity, while gaps still remain in understanding its toxic mechanism. Due to its high specific surface area and adsorption capacity similar to nanoparticles, PM2.5 acts as a significant carrier of metals in air and then leads to altered toxic effects. In this study, we aimed to use CBs and Ni as model materials to investigate the autophagy changes and pulmonary toxic effects at 30 days following intratracheal instillation of CBs-Ni mixture.

MATERIALS AND METHODS

Groups of mice were instilled with 100 µL normal saline (NS), 20 µg CBs, and 4 µg Ni or CBs-Ni mixture, respectively. At 7 and 30 days post-instillation, all the mice were weighed and then sacrificed. The evaluation system was composed of the following: (a) autophagy and lysosomal function assessment, (b) trace element biodistribution observation in lungs, (c) pulmonary lavage biomedical analysis, (d) lung histopathological evaluation, (e) coefficient analysis of major organs and (f) CBs-Ni interaction and cell proliferation assessment.

RESULTS

We found that after CBs-Ni co-exposure, no obvious autophagy and lysosomal dysfunction or pulmonary toxicity was detected, along with complete clearance of Ni from lung tissues as well as recovery of biochemical indexes to normal range.

CONCLUSIONS

We conclude that the damaged autophagy and lysosomal function, as well as physiological function, was repaired at 30 days after exposure of CBs-Ni. Our findings provide a new idea for scientific assessment of the impact of fine particles on environment and human health, and useful information for the comprehensive treatment of air pollution.

Development of a land use regression model for black carbon using mobile monitoring data and its application to pollution-avoiding routing

Black carbon is often used as an indicator for combustion-related air pollution. In urban environments, on-road black carbon concentrations have a large spatial variability, suggesting that the personal exposure of a cyclist to black carbon can heavily depend on the route that is chosen to reach a destination. In this paper, we describe the development of a cyclist routing procedure that minimizes personal exposure to black carbon. Firstly, a land use regression model for predicting black carbon concentrations in an urban environment is developed using mobile monitoring data, collected by cyclists. The optimal model is selected and validated using a spatially stratified cross-validation scheme. The resulting model is integrated in a dedicated routing procedure that minimizes personal exposure to black carbon during cycling. The best model obtains a coefficient of multiple correlation of R=0.520. Simulations with the black carbon exposure minimizing routing procedure indicate that the inhaled amount of black carbon is reduced by 1.58% on average as compared to the shortest-path route, with extreme cases where a reduction of up to 13.35% is obtained. Moreover, we observed that the average exposure to black carbon and the exposure to local peak concentrations on a route are competing objectives, and propose a parametrized cost function for the routing problem that allows for a gradual transition from routes that minimize average exposure to routes that minimize peak exposure.

Human Health Risk Assessment associated with contaminants in the finest fraction of sidewalk dust collected in proximity to trafficked roads

The objective of the study was to determine concentration of metals in sidewalk dust collected in close vicinity to heavily congested roads in Poland in order to assess non-carcinogenic and carcinogenic health risk for both children and adults associated with the ingestion, dermal contact and inhalation of sidewalk dust. Results revealed that sidewalk dust from Warsaw, Krakow, Wroclaw and Opole is heavily contaminated especially with Sb, Se, Cd, Cu, Zn, Pb, considered as indicators of traffic emission. Hazardous indices determined for different exposure pathways indicated that the greatest health risk for both children and adults is associated with the ingestion of sidewalk dust. Carcinogenic risk associated with the ingestion of sidewalk dust by children, calculated for As, Cd, Ni and Pb exceeded safe level of 1 × 10^-4 in all cities except for Warsaw. Non-carcinogenic risk of ingestion for children was two orders of magnitude higher than dermal risk and four to five orders of magnitude higher than risk of inhalation. Non-carcinogenic risk associated with the ingestion of sidewalk dust by adults is comparable with dermal contact risk and five orders of magnitude higher when inhalation risk.

Inflammation and acute traffic-related air pollution exposures among a cohort of youth with type 1 diabetes

BACKGROUND

Evidence remains equivocal regarding the association of inflammation, a precursor to cardiovascular disease, and acute exposures to ambient air pollution from traffic-related particulate matter. Though youth with type 1 diabetes are at higher risk for cardiovascular disease, the relationship of inflammation and ambient air pollution exposures in this population has received little attention.

OBJECTIVES

Using five geographically diverse US sites from the racially- and ethnically-diverse SEARCH for Diabetes in Youth Cohort, we examined the relationship of acute exposures to PM2.5 mass, Atmospheric Dispersion Modeling System (ADMS)-Roads traffic-related PM concentrations near roadways, and elemental carbon (EC) with biomarkers of inflammation including interleukin-6 (IL-6), c-reactive protein (hs-CRP) and fibrinogen.

METHODS

Baseline questionnaires and blood were obtained at a study visit. Using a spatio-temporal modeling approach, pollutant exposures for 7 days prior to blood draw were assigned to residential addresses. Linear mixed models for each outcome and exposure were adjusted for demographic and lifestyle factors identified a priori.

RESULTS

Among the 2566 participants with complete data, fully-adjusted models showed positive associations of EC average week exposures with IL-6 and hs-CRP, and PM2.5 mass exposures on lag day 3 with IL-6 levels. Comparing the 25th and 75th percentiles of average week EC exposures resulted in 8.3% higher IL-6 (95%CI: 2.7%,14.3%) and 9.8% higher hs-CRP (95%CI: 2.4%,17.7%). We observed some evidence of effect modification for the relationships of PM2.5 mass exposures with hs-CRP by gender and with IL-6 by race/ethnicity.

CONCLUSIONS

Indicators of inflammation were associated with estimated traffic-related air pollutant exposures in this study population of youth with type 1 diabetes. Thus youth with type 1 diabetes may be at increased risk of air pollution-related inflammation. These findings and the racial/ethnic and gender differences observed deserve further exploration.

Synthesis of Harvard Environmental Protection Agency (EPA) Center studies on traffic-related particulate pollution and cardiovascular outcomes in the Greater Boston Area

The association between particulate pollution and cardiovascular morbidity and mortality is well established. While the cardiovascular effects of nationally regulated criteria pollutants (e.g., fine particulate matter [PM_2.5] and nitrogen dioxide) have been well documented, there are fewer studies on particulate pollutants that are more specific for traffic, such as black carbon (BC) and particle number (PN). In this paper, we synthesized studies conducted in the Greater Boston Area on cardiovascular health effects of traffic exposure, specifically defined by BC or PN exposure or proximity to major roadways. Large cohort studies demonstrate that exposure to traffic-related particles adversely affect cardiac autonomic function, increase systemic cytokine-mediated inflammation and pro-thrombotic activity, and elevate the risk of hypertension and ischemic stroke. Key patterns emerged when directly comparing studies with overlapping exposure metrics and population cohorts. Most notably, cardiovascular risk estimates of PN and BC exposures were larger in magnitude or more often statistically significant compared to those of PM_2.5 exposures. Across multiple exposure metrics (e.g., short-term vs. long-term; observed vs. modeled) and different population cohorts (e.g., elderly, individuals with co-morbidities, young healthy individuals), there is compelling evidence that BC and PN represent traffic-related particles that are especially harmful to cardiovascular health. Further research is needed to validate these findings in other geographic locations, characterize exposure errors associated with using monitored and modeled traffic pollutant levels, and elucidate pathophysiological mechanisms underlying the cardiovascular effects of traffic-related particulate pollutants. Implications: Traffic emissions are an important source of particles harmful to cardiovascular health. Traffic-related particles, specifically BC and PN, adversely affect cardiac autonomic function, increase systemic inflammation and thrombotic activity, elevate BP, and increase the risk of ischemic stroke. There is evidence that BC and PN are associated with greater cardiovascular risk compared to PM_2.5. Further research is needed to elucidate other health effects of traffic-related particles and assess the feasibility of regulating BC and PN or their regional and local sources.

Transboundary and traffic influences on air pollution across two Caribbean islands

Exposure to ambient air pollution has been linked to adverse health outcomes ranging from asthma to premature mortality. However, little to no information exists on the exposure of residents and visitors in the Caribbean islands. While a few previous studies have quantified levels of PM₁₀ (particulate matter <10 μm) from Sahara dust in Trinidad, our study focussed on a local source of air pollution, traffic emissions. Mass concentrations of black carbon (BC) and PM_2.5 (PM <2.5 μm) were measured at ten locations across the islands of Trinidad and Tobago over a three-week period. PM_2.5 concentrations were observed to be heavily influenced by air masses showing origins from the Sahara Desert (31%), North America (26%) and Atlantic Ocean (42%), which resulted in similar average concentrations between the two islands. Average concentrations of BC were five times higher in Trinidad than Tobago (2.0 vs 0.43 μg/m³). In addition, BC in Trinidad was three times higher near than away from major roads (2.21 vs. 0.72 μg/m³), with concentrations reaching levels comparable to those near highways in large Metropolitan cities. The elevated BC concentrations observed in this study suggests that significant exposure to diesel exhaust is occurring in Trinidad, with significant contributions from traffic.

Stroke prevalence among the Turkish population in a rural area of Istanbul: A community-based study

Background

The population-based information on the prevalence of stroke from rural areas of Middle East countries including Turkey is unknown. Our aim is to evaluate the prevalence of stroke in those ⩾18 years in the Turkish population in a rural area of Istanbul.

Methods

A cross-sectional door-to-door study was conducted in a rural area of Istanbul between 1 March and 30 March 2013. A research protocol recommended by World Health Organization for developing countries was used. Each screening teams consisted of one neurologist, one local nurse, and five surveyors. Teams were trained about the survey and questionnaire. The patients, who claimed to have suffered a stroke, were examined, and the diagnosis was confirmed by a neurologist on site. The findings and medical records were documented.

Results

In total, 2906 people ⩾18 years were screened. 50 stroke cases were detected. 80% of those were found to have had an ischemic stroke, 14% of those were hemorrhagic cases, and 6% of those had an unclassified stroke type. The overall prevalence rate in those ⩾ 18 years was 1.7%. The male/female ratio was 0.92. Young (<45) stroke prevalence was found to be 0.6%.

Conclusion

This study was the first of its kind to show the stroke prevalence among Turkish population ⩾ 18 years in a rural area of Istanbul. When compared to other studies which investigate people ⩾45 years from Turkey, the result (in the same age group) was moderate high. The male/female ratio was low compared to many other studies.

Fine Particle Sources and Cognitive Function in An Older Puerto Rican Cohort in Greater Boston

Supplemental Digital Content is available in the text.

Background:

Puerto Ricans living in the mainland US have substantially higher rates of impairment to cognitive performance as compared to non-Hispanic Whites, with air pollutant exposures a potential risk factor. We investigated whether exposures to specific air pollution sources were associated with performance across several cognitive domains in a cohort of Puerto Rican older adults.

Objectives:

To investigate the association between sources of fine particulate matter (PM_2.5) and cognitive performance in each of five cognitive domains.

Methods:

We obtained demographic, health, and cognitive function data for 1500 elderly participants of the Boston Puerto Rican Health Study. Cognitive function was assessed in each of two waves for five domains: verbal memory, recognition, mental processing, and executive and visuospatial function. To these data, we linked concentrations of PM_2.5 and its components, black carbon (BC), nickel, sulfur, and silicon, as tracers for PM_2.5 from traffic, oil combustion, coal combustion, and resuspended dust, respectively. Associations between each PM_2.5 component and cognitive domain were examined using linear mixed models.

Results:

One year moving average exposures to BC were significantly associated with decreased verbal memory (−0.38; 95% confidence interval [CI] = −0.46, −0.30), recognition (−0.35; 95% CI = −0.46, −0.25), mental processing (−1.14; 95% CI = −1.55, −0.74), and executive function (−0.94; 95% CI = −1.31, −0.56). Similar associations were found for nickel. Associations for sulfur, and silicon, and PM_2.5 were generally null, although sulfur (−0.51; 95% CI = −0.75, −0.28), silicon (−0.25; 95% CI = −0.36, −0.13), and PM_2.5 (−0.35; 95% CI = −0.57, −0.12) were associated with decreased recognition.

Conclusion:

Long-term exposures to BC and nickel, tracers of traffic and oil combustion, respectively, were associated with decreased cognitive function across all domains, except visuospatial function.

Assessing the associations of daily respiratory symptoms and lung function in schoolchildren using an Air Quality Index for ozone: Results from the RESPOZE panel study in Athens, Greece

BACKGROUND

Air Quality indicators or indices (AQIs) are mainly used for communicating the air pollution levels and risk to the general population. However, very few epidemiological studies have used AQIs for characterizing exposure.

OBJECTIVE

In the framework of the RESPOZE panel study we evaluated the association of daily ozone AQI levels with the daily occurrence of respiratory symptoms and Peak Expiratory Flow (PEF) and compared the effects with those estimated using measurements from fixed outdoor monitoring sites, in the city of Athens, Greece.

MATERIALS AND METHODS

A panel of 97 children, aged 10-11years, was followed intensively for 35days (5weeks) during the academic year 2013-14. PEF and symptoms were recorded daily by each child. Two ozone AQIs classifying the air quality into 7 categories of increasing severity, were calculated; one characterizing the whole Athens area and one the local area around the child's residence and school. Measurements from fixed sites were also used. Mixed effects models for repeated measurements were applied, adjusting for several confounders.

RESULTS

Increasing ozone levels were associated with increased incidence of symptoms, but the strongest and most statistically significant associations were found with the local air quality characterization with the AQI. Specifically, an increase in AQI-local by one category was associated with 34% (95% CI: 9%, 64%) increased odds of stuffy nose. When the AQI categories were "Bad" and "Severe", an increase in the incidence of cough was observed (OR 3.05 (95% CI: 1.29, 7.22) and 6.42 (95% CI: 1.47, 28.03) respectively). We did not observe a statistically significant association between AQI and PEF.

CONCLUSION

Our results show that the use of an AQI based on local conditions may be advantageous over the use of only measurements when investigating the effects of air pollution on health outcomes for improving communication of risk to the public.

Stroke Prevalence in a Coastal Town on the Black Sea Coast in Turkey: Community Based Study

BACKGROUND

This study aims to determine the stroke prevalence in Akçakoca which is a rural area in Turkey.

METHODS

The study was designed as a cross-sectional, door-to-door survey. The stroke questionnaire was completed by a trained team in the presence of the participants according to their answers. Based on the screenings, patients who had been diagnosed with stroke previously were reexamined by a neurologist and determined the prevalence values, risk factors, and stroke types.

RESULTS

A total of 3750 people over 44 years old were reached in the screenings. It was determined that 83 people had previously suffered a stroke. The prevalence rate of stroke in those above 44 years was found to be 2.2 (98% confidence level and ± 2% margin of error). 70 (84.3%) patients had suffered an ischemic stroke while 12 (14.5%) had suffered a hemorrhagic stroke. Male/female ratio was 1.1.

CONCLUSION

The results of this study give the prevalence rate of stroke among the Turkish population living in a rural area. Due to a lack of other similar studies, it is impossible to make any data comparison. However, the results of this study help shed light on the stroke prevalence rate.

Effect of Particulate Matter Air Pollution on Cardiovascular Oxidative Stress Pathways

SIGNIFICANCE

Particulate matter (PM) air pollution is a leading cause of global cardiovascular morbidity and mortality. Understanding the biological action of PM is of particular importance in improvement of public health. Recent Advances: Both fine (PM <2.5 μM) and ultrafine particles (<0.1 μM) are widely believed to mediate their effects through redox regulated pathways. A rather simplistic graded ramp model of redox stress has been replaced by a more sophisticated understanding of the role of oxidative stress in signaling, and the realization that many of the observed effects may involve disruption and/or enhancement of normal endogenous redox signaling and induction of a potent immune-mediated response, through entrainment of multiple reactive oxygen species (ROS).

CRITICAL ISSUES

The molecular events by which pulmonary oxidative stress in response to inhalational exposure to air pollution triggers inflammation, major ROS (e.g., superoxide, hydroxyl radical, nitric oxide, and peroxynitrite) generated in air pollution exposure, types of oxidative tissue damage in target organs, contributions of nonimmune and immune cells in inflammation, and the role of protective proteins (e.g., surfactant, proteins, and antioxidants) are highly complex and may differ depending on models and concomitant disease states.

FUTURE DIRECTIONS

While the role of oxidative stress in the lung has been well demonstrated, the role of oxidative stress in mediating systemic effects especially in inflammation and injury processes needs further work. The role of antioxidant defenses with chronic exposure will also need further exploration. Antioxid. Redox Signal. 28, 797-818.

Development of a modeling approach to estimate indoor-to-outdoor sulfur ratios and predict indoor PM2.5 and black carbon concentrations for Eastern Massachusetts households

The effects of indoor air pollution on human health have drawn increasing attention among the scientific community as individuals spend most of their time indoors. However, indoor air sampling is labor-intensive and costly, which limits the ability to study the adverse health effects related to indoor air pollutants. To overcome this challenge, many researchers have attempted to predict indoor exposures based on outdoor pollutant concentrations, home characteristics, and weather parameters. Typically, these models require knowledge of the infiltration factor, which indicates the fraction of ambient particles that penetrates indoors. For estimating indoor fine particulate matter (PM_2.5) exposure, a common approach is to use the indoor-to-outdoor sulfur ratio (S_indoor/S_outdoor) as a proxy of the infiltration factor. The objective of this study was to develop a robust model that estimates S_indoor/S_outdoor for individual households that can be incorporated into models to predict indoor PM_2.5 and black carbon (BC) concentrations. Overall, our model adequately estimated S_indoor/S_outdoor with an out-of-sample by home-season R² of 0.89. Estimated S_indoor/S_outdoor reflected behaviors that influence particle infiltration, including window opening, use of forced air heating, and air purifier. Sulfur ratio-adjusted models predicted indoor PM_2.5 and BC with high precision, with out-of-sample R² values of 0.79 and 0.76, respectively.

Stroke epidemiology in Karabük city Turkey: Community based study

Introduction

Stroke has been projected to increase in developing countries like Turkey. Information about the prevalence of stroke may uncover the etiology of stroke and overcome its impact burden. However, data is limited due to a lack of studies based in Turkey and neighboring regions. We aimed to investigate the prevalence and risk factors of stroke in the Turkish city of Karabük and to pave the way for future epidemiological studies in Turkey.

Methods

The study was designed as a cross-sectional, door-to-door survey. The questionnaire was completed by a trained team in the presence of the participants according to their answers. Patients who had been diagnosed with stroke prior to the survey were re-examined by a neurologist.

Results

3131 persons who were above 44 years old were screened. 129 of them were found to have had a stroke previously. The prevalence rate of stroke above 44 years was found to be 4.12% (98% confidence level and ± 2% margin of error). 72.1% of stroke patients had hypertension. Male/female ratio was 0.72.

Conclusion

This study showed a high prevalence rate of stroke in Karabük Turkey with a low male/female ratio when compared to other studies.

Can dispersion modeling of air pollution be improved by land-use regression? An example from Stockholm, Sweden

Both dispersion modeling (DM) and land-use regression modeling (LUR) are often used for assessment of long-term air pollution exposure in epidemiological studies, but seldom in combination. We developed a hybrid DM-LUR model using 93 biweekly observations of NO_x at 31 sites in greater Stockholm (Sweden). The DM was based on spatially resolved topographic, physiographic and emission data, and hourly meteorological data from a diagnostic wind model. Other data were from land use, meteorology and routine monitoring of NO_x. We built a linear regression model for NO_x, using a stepwise forward selection of covariates. The resulting model predicted observed NO_x (R²=0.89) better than the DM without covariates (R²=0.68, P-interaction <0.001) and with minimal apparent bias. The model included (in descending order of importance) DM, traffic intensity on the nearest street, population (number of inhabitants) within 100 m radius, global radiation (direct sunlight plus diffuse or scattered light) and urban contribution to NO_x levels (routine urban NO_x, less routine rural NO_x). Our results indicate that there is a potential for improving estimates of air pollutant concentrations based on DM, by incorporating further spatial characteristics of the immediate surroundings, possibly accounting for imperfections in the emission data.

A spatio-temporal prediction model based on support vector machine regression: Ambient Black Carbon in three New England States

Fine ambient particulate matter has been widely associated with multiple health effects. Mitigation hinges on understanding which sources are contributing to its toxicity. Black Carbon (BC), an indicator of particles generated from traffic sources, has been associated with a number of health effects however due to its high spatial variability, its concentration is difficult to estimate. We previously fit a model estimating BC concentrations in the greater Boston area; however this model was built using limited monitoring data and could not capture the complex spatio-temporal patterns of ambient BC. In order to improve our predictive ability, we obtained more data for a total of 24,301 measurements from 368 monitors over a 12 year period in Massachusetts, Rhode Island and New Hampshire. We also used Nu-Support Vector Regression (nu-SVR) - a machine learning technique which incorporates nonlinear terms and higher order interactions, with appropriate regularization of parameter estimates. We then used a generalized additive model to refit the residuals from the nu-SVR and added the residual predictions to our earlier estimates. Both spatial and temporal predictors were included in the model which allowed us to capture the change in spatial patterns of BC over time. The 10 fold cross validated (CV) R² of the model was good in both cold (10-fold CV R² = 0.87) and warm seasons (CV R² = 0.79). We have successfully built a model that can be used to estimate short and long-term exposures to BC and will be useful for studies looking at various health outcomes in MA, RI and Southern NH.

Air Pollution and Public Health: A PRISMA-Compliant Systematic Review

(1) Background: Particulate matter increases the risk of respiratory, allergic and oncological diseases in both exposed workers and the general population due to its toxic compounds (e.g., PAHs, gases, heavy metals, microorganisms). The aim of this review is to show the results obtained by our department regarding air pollution’s contributions to health damage in both occupationally and non-occupationally exposed people. (2) Methods: This review was performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, searching articles on PubMed, using eligibility criteria, extracting data independently from reports to reduce bias and considering the accuracy of the statistical analyses. (3) Results: Of fifteen papers, only three respected the abovementioned criteria. A total of 453 cases (174 occupationally exposed and 279 non-occupationally exposed individuals) were included in the review. Qualitative analysis showed that among workers, occupational exposure to air pollution increased the risk of allergic and pulmonary diseases, whereas environmental exposure to PM increased heavy metal intake, the last of which was characterized by well-known carcinogenic effects. 4) Conclusion: The use of personal protective equipment, a meticulous health surveillance program and specific environmental protection policies are needed to protect public health from damages due to air pollution.

Modeling indoor particulate exposures in inner-city school classrooms

Outdoor air pollution penetrates buildings and contributes to total indoor exposures. We investigated the relationship of indoor to outdoor particulate matter in inner-city school classrooms. The School Inner City Asthma Study investigates the effect of classroom-based environmental exposures on students with asthma in the northeast United States. Mixed effects linear models were used to determine the relationships between indoor PM2.5 (particulate matter) and black carbon (BC), and their corresponding outdoor concentrations, and to develop a model for predicting exposures to these pollutants. The indoor-outdoor sulfur ratio was used as an infiltration factor of outdoor fine particles. Weeklong concentrations of PM2.5 and BC in 199 samples from 136 classrooms (30 school buildings) were compared with those measured at a central monitoring site averaged over the same timeframe. Mixed effects regression models found significant random intercept and slope effects, which indicate that: (1) there are important PM2.5 sources in classrooms; (2) the penetration of outdoor PM2.5 particles varies by school and (3) the site-specific outside PM2.5 levels (inferred by the models) differ from those observed at the central monitor site. Similar results were found for BC except for lack of indoor sources. The fitted predictions from the sulfur-adjusted models were moderately predictive of observed indoor pollutant levels (out of sample correlations: PM2.5: r2=0.68, BC; r2=0.61). Our results suggest that PM2.5 has important classroom sources, which vary by school. Furthermore, using these mixed effects models, classroom exposures can be accurately predicted for dates when central site measures are available but indoor measures are not available.

Spatial Multiresolution Analysis of the Effect of PM2.5 on Birth Weights

Fine particulate matter (PM_2.5) measured at a given location is a mix of pollution generated locally and pollution traveling long distances in the atmosphere. Therefore, the identification of spatial scales associated with health effects can inform on pollution sources responsible for these effects, resulting in more targeted regulatory policy. Recently, prediction methods that yield high-resolution spatial estimates of PM_2.5 exposures allow one to evaluate such scale-specific associations. We propose a two-dimensional wavelet decomposition that alleviates restrictive assumptions required for standard wavelet decompositions. Using this method we decompose daily surfaces of PM_2.5 to identify which scales of pollution are most associated with adverse health outcomes. A key feature of the approach is that it can remove the purely temporal component of variability in PM_2.5 levels and calculate effect estimates derived solely from spatial contrasts. This eliminates the potential for unmeasured confounding of the exposure - outcome associations by temporal factors, such as season. We apply our method to a study of birth weights in Massachusetts, U.S.A from 2003-2008 and find that both local and urban sources of pollution are strongly negatively associated with birth weight. Results also suggest that failure to eliminate temporal confounding in previous analyses attenuated the overall effect estimate towards zero, with the effect estimate growing in magnitude once this source of variability is removed.

Relation of ST-Segment Elevation Myocardial Infarction to Daily Ambient Temperature and Air Pollutant Levels in a Japanese Nationwide Percutaneous Coronary Intervention Registry

Effects of daily fluctuation of ambient temperature and concentrations of air pollutants on acute cardiovascular events have not been well studied. From January 2011 to December 2012, a total of 56,863 consecutive ST-segment elevation myocardial infarction (STEMI) patients who underwent primary percutaneous coronary intervention were registered from 929 institutes with median interinstitutional distance of 2.6 km. We constructed generalized linear mixed models in which the presence or absence of patients with STEMI per day per institute was included as a binomial response variable, with daily meteorologic and environmental data obtained from their respective observatories nearest to the institutes (median distance of 9.7 and 5.6 km) as the explanatory variables. Both lower mean temperature and increase in maximum temperature from the previous day were independently associated with the STEMI occurrence throughout the year (odds ratio [OR] 0.925, 95% confidence interval [CI] 0.915 to 0.935, per 10°C, p <0.001; and OR 1.012, 95% CI 1.009 to 1.015, per °C, p <0.001, respectively). Decrement in minimum temperature from -4 days to -3 days before the event date was marginally associated with the STEMI occurrence, only during the wintertime (OR 0.991, 95% CI 0.982 to 0.999, per °C, p = 0.03). As for the air pollutants, nitrogen oxides and suspended particle matter were not correlated with the occurrence of STEMI after adjusting for the meteorologic and livelihood variables. Both the absolute value and relative change in the ambient temperature were associated with the occurrence of STEMI; the associations with the air pollutant levels were less clear after adjustment for these meteorologic variables in Japan.

Highly Acidic Ambient Particles, Soluble Metals, and Oxidative Potential: A Link between Sulfate and Aerosol Toxicity

Soluble transition metals in particulate matter (PM) can generate reactive oxygen species in vivo by redox cycling, leading to oxidative stress and adverse health effects. Most metals, such as those from roadway traffic, are emitted in an insoluble form, but must be soluble for redox cycling. Here we present the mechanism of metals dissolution by highly acidic sulfate aerosol and the effect on particle oxidative potential (OP) through analysis of size distributions. Size-segregated ambient PM were collected from a road-side and representative urban site in Atlanta, GA. Elemental and organic carbon, ions, total and water-soluble metals, and water-soluble OP were measured. Particle pH was determined with a thermodynamic model using measured ionic species. Sulfate was spatially uniform and found mainly in the fine mode, whereas total metals and mineral dust cations were highest at the road-side site and in the coarse mode, resulting in a fine mode pH < 2 and near neutral coarse mode. Soluble metals and OP peaked at the intersection of these modes demonstrating that sulfate plays a key role in producing highly acidic fine aerosols capable of dissolving primary transition metals that contribute to aerosol OP. Sulfate-driven metals dissolution may account for sulfate-health associations reported in past studies.

Estimating Causal Effects of Local Air Pollution on Daily Deaths: Effect of Low Levels

BACKGROUND

Although many time-series studies have established associations of daily pollution variations with daily deaths, there are fewer at low concentrations, or focused on locally generated pollution, which is becoming more important as regulations reduce regional transport. Causal modeling approaches are also lacking.

OBJECTIVE

We used causal modeling to estimate the impact of local air pollution on mortality at low concentrations.

METHODS

Using an instrumental variable approach, we developed an instrument for variations in local pollution concentrations that is unlikely to be correlated with other causes of death, and examined its association with daily deaths in the Boston, Massachusetts, area. We combined height of the planetary boundary layer and wind speed, which affect concentrations of local emissions, to develop the instrument for particulate matter ≤ 2.5 μm (PM2.5), black carbon (BC), or nitrogen dioxide (NO2) variations that were independent of year, month, and temperature. We also used Granger causality to assess whether omitted variable confounding existed.

RESULTS

We estimated that an interquartile range increase in the instrument for local PM2.5 was associated with a 0.90% increase in daily deaths (95% CI: 0.25, 1.56). A similar result was found for BC, and a weaker association with NO2. The Granger test found no evidence of omitted variable confounding for the instrument. A separate test confirmed the instrument was not associated with mortality independent of pollution. Furthermore, the association remained when all days with PM2.5 concentrations > 30 μg/m3 were excluded from the analysis (0.84% increase in daily deaths; 95% CI: 0.19, 1.50).

CONCLUSIONS

We conclude that there is a causal association of local air pollution with daily deaths at concentrations below U.S. EPA standards. The estimated attributable risk in Boston exceeded 1,800 deaths during the study period, indicating that important public health benefits can follow from further control efforts. Citation: Schwartz J, Bind MA, Koutrakis P. 2017. Estimating causal effects of local air pollution on daily deaths: effect of low levels. Environ Health Perspect 125:23-29; http://dx.doi.org/10.1289/EHP232.

Spatio-temporal ozone variation in a case-crossover analysis of childhood asthma hospital visits in New York City

BACKGROUND

Childhood asthma morbidity has been associated with short-term air pollution exposure. To date, most investigations have used time-series models, and it is not well understood how exposure misclassification arising from unmeasured spatial variation may impact epidemiological effect estimates. Here, we develop case-crossover models integrating temporal and spatial individual-level exposure information, toward reducing exposure misclassification in estimating associations between air pollution and child asthma exacerbations in New York City (NYC).

METHODS

Air pollution data included: (a) highly spatially-resolved intra-urban concentration surfaces for ozone and co-pollutants (nitrogen dioxide and fine particulate matter) from the New York City Community Air Survey (NYCCAS), and (b) daily regulatory monitoring data. Case data included citywide hospital records for years 2005-2011 warm-season (June-August) asthma hospitalizations (n=2353) and Emergency Department (ED) visits (n=11,719) among children aged 5-17 years. Case residential locations were geocoded using a multi-step process to maximize positional accuracy and precision in near-residence exposure estimates. We used conditional logistic regression to model associations between ozone and child asthma exacerbations for lag days 0-6, adjusting for co-pollutant and temperature exposures. To evaluate the effect of increased exposure specificity through spatial air pollution information, we sequentially incorporated spatial variation into daily exposure estimates for ozone, temperature, and co-pollutants.

RESULTS

Percent excess risk per 10ppb ozone exposure in spatio-temporal models were significant on lag days 1 through 5, ranging from 6.5 (95% CI: 0.2-13.1) to 13.0 (6.0-20.6) for inpatient hospitalizations, and from 2.9 (95% CI: 0.1-5.7) to 9.4 (6.3-12.7) for ED visits, with strongest associations consistently observed on lag day 2. Spatio-temporal excess risk estimates were consistently but not statistically significantly higher than temporal-only estimates on lag days 0-3.

CONCLUSION

Incorporating case-level spatial exposure variation produced small, non-significant increases in excess risk estimates. Our modeling approach enables a refined understanding of potential measurement error in temporal-only versus spatio-temporal air pollution exposure assessments. As ozone generally varies over much larger spatial scales than that observed within NYC, further work is necessary to evaluate potential reductions in exposure misclassification for populations spanning wider geographic areas, and for other pollutants.

Design and characterization of human exposure to generated sulfate and soot particles in a pilot chamber study

A number of literatures have documented adverse health effects of exposure to fine particulate matter (PM2.5), and secondary sulfate aerosol and black carbon may contribute to health impacts of PM2.5 exposure. We designed an exposure system to generate sulfate and traffic soot particles, and assessed the feasibility of using it for human exposure assessment in a pilot human exposure study. In the designed exposure system, average mass concentrations of generated sulfate and soot particles were 74.19 μg/m3 and 11.54 μg/m3 in the chamber and did not vary significantly during two-hour human exposure sessions. The size ranges of generated sulfate were largely between 20 to 200 nm, whereas those of generated soot particles were in the size ranges of 50 to 200 nm. Following two-hour exposure to generated sulfate and soot particles, we observed significant increases in fractional exhaled NO (FeNO) in young and health subjects. Building on established human exposure system and health response follow-up methods, future full-scale studies focusing on the effects of mixed particulates and individual PM2.5 components would provide data in understanding the underpinning cardio-respiratory outcomes in relation to air pollution mixture exposure.

IMPLICATIONS

Controlled exposure is a useful design to measure the biological responses repeatedly following particulate exposures of target components and set exposure at target levels of health concerns. Our study provides rational and establishes method for future full-scale studies to focus on examining the effects of mixed particulates and individual PM2.5 components.

Short-term exposure to traffic-related air pollution and daily mortality in London, UK

Epidemiological studies have linked daily concentrations of urban air pollution to mortality, but few have investigated specific traffic sources that can inform abatement policies. We assembled a database of >100 daily, measured and modelled pollutant concentrations characterizing air pollution in London between 2011 and 2012. Based on the analyses of temporal patterns and correlations between the metrics, knowledge of local emission sources and reference to the existing literature, we selected, a priori, markers of traffic pollution: oxides of nitrogen (general traffic); elemental and black carbon (EC/BC) (diesel exhaust); carbon monoxide (petrol exhaust); copper (tyre), zinc (brake) and aluminium (mineral dust). Poisson regression accounting for seasonality and meteorology was used to estimate the percentage change in risk of death associated with an interquartile increment of each pollutant. Associations were generally small with confidence intervals that spanned 0% and tended to be negative for cardiovascular mortality and positive for respiratory mortality. The strongest positive associations were for EC and BC adjusted for particle mass and respiratory mortality, 2.66% (95% confidence interval: 0.11, 5.28) and 2.72% (0.09, 5.42) per 0.8 and 1.0 μg/m(3), respectively. These associations were robust to adjustment for other traffic metrics and regional pollutants, suggesting a degree of specificity with respiratory mortality and diesel exhaust containing EC/BC.

Short-term exposure to traffic-related air pollution and daily mortality in London, UK

Epidemiological studies have linked daily concentrations of urban air pollution to mortality, but few have investigated specific traffic sources that can inform abatement policies. We assembled a database of >100 daily, measured and modelled pollutant concentrations characterizing air pollution in London between 2011 and 2012. Based on the analyses of temporal patterns and correlations between the metrics, knowledge of local emission sources and reference to the existing literature, we selected, a priori, markers of traffic pollution: oxides of nitrogen (general traffic); elemental and black carbon (EC/BC) (diesel exhaust); carbon monoxide (petrol exhaust); copper (tyre), zinc (brake) and aluminium (mineral dust). Poisson regression accounting for seasonality and meteorology was used to estimate the percentage change in risk of death associated with an interquartile increment of each pollutant. Associations were generally small with confidence intervals that spanned 0% and tended to be negative for cardiovascular mortality and positive for respiratory mortality. The strongest positive associations were for EC and BC adjusted for particle mass and respiratory mortality, 2.66% (95% confidence interval: 0.11, 5.28) and 2.72% (0.09, 5.42) per 0.8 and 1.0 μg/m(3), respectively. These associations were robust to adjustment for other traffic metrics and regional pollutants, suggesting a degree of specificity with respiratory mortality and diesel exhaust containing EC/BC.

Approaches to prevent the patients with chronic airway diseases from exacerbation in the haze weather

Haze weather is becoming one of the biggest problems in many big cities in China. It triggers both public anxiety and official concerns. Particulate matter (PM) plays the most important role in causing the adverse health effects. Chemical composition of PM2.5 includes primary particles and secondary particles. The toxicological mechanisms of PM2.5 to the human body include the oxidative stress, inflammation and carcinogenesis. Short or long-term exposure to PM (especially PM2.5) can cause a series of symptoms including respiratory symptoms such as cough, wheezing and dyspnea as well as other symptoms. There are positive associations between PM2.5 and mortality due to a number of causes. PM2.5 is considered to contribute to the onset of asthma, the exacerbation of chronic obstructive pulmonary disease (COPD) in haze weather. Some approaches including outdoor health care, indoor health care and preventive medications can prevent the patients with chronic airway diseases from exacerbations.

National Spatiotemporal Exposure Surface for NO2: Monthly Scaling of a Satellite-Derived Land-Use Regression, 2000-2010

Land-use regression (LUR) is widely used for estimating within-urban variability in air pollution. While LUR has recently been extended to national and continental scales, these models are typically for long-term averages. Here we present NO2 surfaces for the continental United States with excellent spatial resolution (∼100 m) and monthly average concentrations for one decade. We investigate multiple potential data sources (e.g., satellite column and surface estimates, high- and standard-resolution satellite data, and a mechanistic model [WRF-Chem]), approaches to model building (e.g., one model for the whole country versus having separate models for urban and rural areas, monthly LURs versus temporal scaling of a spatial LUR), and spatial interpolation methods for temporal scaling factors (e.g., kriging versus inverse distance weighted). Our core approach uses NO2 measurements from U.S. EPA monitors (2000-2010) to build a spatial LUR and to calculate spatially varying temporal scaling factors. The model captures 82% of the spatial and 76% of the temporal variability (population-weighted average) of monthly mean NO2 concentrations from U.S. EPA monitors with low average bias (21%) and error (2.4 ppb). Model performance in absolute terms is similar near versus far from monitors, and in urban, suburban, and rural locations (mean absolute error 2-3 ppb); since low-density locations generally experience lower concentrations, model performance in relative terms is better near monitors than far from monitors (mean bias 3% versus 40%) and is better for urban and suburban locations (1-6%) than for rural locations (78%, reflecting the relatively clean conditions in many rural areas). During 2000-2010, population-weighted mean NO2 exposure decreased 42% (1.0 ppb [∼5.2%] per year), from 23.2 ppb (year 2000) to 13.5 ppb (year 2010). We apply our approach to all U.S. Census blocks in the contiguous United States to provide 132 months of publicly available, high-resolution NO2 concentration estimates.

Estimating Causal Associations of Fine Particles With Daily Deaths in Boston

Many studies have reported associations between daily particles less than 2.5 µm in aerodynamic diameter (PM2.5) and deaths, but they have been associational studies that did not use formal causal modeling approaches. On the basis of a potential outcome approach, we used 2 causal modeling methods with different assumptions and strengths to address whether there was a causal association between daily PM2.5 and deaths in Boston, Massachusetts (2004-2009). We used an instrumental variable approach, including back trajectories as instruments for variations in PM2.5 uncorrelated with other predictors of death. We also used propensity score as an alternative causal modeling analysis. The former protects against confounding by measured and unmeasured confounders and is based on the assumption of a valid instrument. The latter protects against confounding by all measured covariates, provides valid estimates in the case of effect modification, and is based on the assumption of no unmeasured confounders. We found a causal association of PM2.5 with mortality, with a 0.53% (95% confidence interval: 0.09, 0.97) and a 0.50% (95% confidence interval: 0.20, 0.80) increase in daily deaths using the instrumental variable and the propensity score, respectively. We failed to reject the null association with exposure after the deaths (P =0.93). Given these results, prior studies, and extensive toxicological support, the association between PM2.5 and deaths is almost certainly causal.

Is there a Hispanic Health Paradox in Sensitivity to Air Pollution? Hospital Admissions for Asthma, Chronic Obstructive Pulmonary Disease and Congestive Heart Failure Associated with NO2 and PM2.5 in El Paso, TX, 2005-2010

STUDY OBJECTIVE

Linkages between pollution and morbidity have been observed in numerous studies. But race/ethnicity has been underemphasized as a modifier of that association, and few studies have tested for a Hispanic Health Paradox in sensitivity to air pollution.

METHODS

Daily asthma, chronic obstructive pulmonary disease (COPD) and congestive heart failure (CHF) hospital admissions in El Paso, Texas were studied in age groups and insurance groups. Daily PM2.5 and NO2 were calculated from pollution monitors and all models adjusted for apparent temperature and wind speed. Conditional logistic regression for the case-crossover design was used for a between-group comparison and for a within-group comparison for Hispanics.

RESULTS

Hispanics were at lower risk than non-Hispanic whites and non-Hispanics of other races for NO2-associated admissions, but at greater risk for PM2.5-associated admissions. While Hispanics were generally protected with regards to NO2, Hispanic children (vs. elderly) faced increased risk for asthma and uninsured Hispanics (vs. Private) faced increased risk for COPD admissions. While Hispanics were at increased risk of PM2.5-associated admissions, certain characteristics heightened their risks: being a Hispanic child (vs. Elderly) for asthma; being a Hispanic with Medicare (vs. Private) for asthma; and being a Hispanic with private insurance (vs. all other insurance types) for CHF. The main effect of pollution on admissions was more significant for asthma and CHF than for COPD, which had the fewest cases.

CONCLUSIONS

There was heterogeneity in sensitivity to air pollution based on social characteristics and moderate evidence for a Hispanic Health Paradox in sensitivity to NO2.

Traffic-related air pollution and sleep in the Boston Area Community Health Survey

Little is known about environmental determinants of sleep. We investigated the association between black carbon (BC), a marker of traffic-related air pollution, and sleep measures among participants of the Boston Area Community Health Survey. We also sought to assess the impact of sociodemographic factors, health conditions, and season on associations. Residential 24-h BC was estimated from a validated land-use regression model for 3821 participants and averaged over 1-6 months and 1 year. Sleep measures included questionnaire-assessed sleep duration, sleep latency, and sleep apnea. Linear and logistic regression models controlling for confounders estimated the association between sleep measures and BC. Effect modification was tested with interaction terms. Main effects were not observed between BC and sleep measures. However, in stratified models, males experienced 0.23 h less sleep (95% CI: -0.42, -0.03) and those with low SES 0.25 h less sleep (95% CI: -0.48, -0.01) per IQR increase in annual BC (0.21 μg/m(3)). In blacks, sleep duration increased with annual BC (β=0.34 per IQR; 95% CI: 0.12, 0.57). Similar findings were observed for short sleep (≤5 h). BC was not associated with sleep apnea or sleep latency, however, long-term exposure may be associated with shorter sleep duration, particularly in men and those with low SES, and longer sleep duration in blacks.

Epidemiology of air pollution and diabetes

Air pollution affects a large proportion of the global population. Air pollutants are hypothesized to exert their effects via impaired endothelial function, elevated systemic inflammation, mitochondrial dysfunction, and oxidative stress, all of which are hallmarks of type 2 diabetes (T2D). Here we review epidemiological studies aimed at answering whether diabetes patients are more vulnerable to ambient (outdoor) air pollution exposure and whether air pollution is associated with diabetes development or other predisposing conditions for T2D. Current evidence suggests an association between air pollution exposure and T2D, but more critical analysis is warranted. Understanding the associations between air pollution exposure and the development of T2D is critical in our efforts to control sources of air pollution and their impact on the disease.

Transferability and generalizability of regression models of ultrafine particles in urban neighborhoods in the Boston area

Land use regression (LUR) models have been used to assess air pollutant exposure, but limited evidence exists on whether location-specific LUR models are applicable to other locations (transferability) or general models are applicable to smaller areas (generalizability). We tested transferability and generalizability of spatial-temporal LUR models of hourly particle number concentration (PNC) for Boston-area (MA, U.S.A.) urban neighborhoods near Interstate 93. Four neighborhood-specific regression models and one Boston-area model were developed from mobile monitoring measurements (34-46 days/neighborhood over one year each). Transferability was tested by applying each neighborhood-specific model to the other neighborhoods; generalizability was tested by applying the Boston-area model to each neighborhood. Both the transferability and generalizability of models were tested with and without neighborhood-specific calibration. Important PNC predictors (adjusted-R(2) = 0.24-0.43) included wind speed and direction, temperature, highway traffic volume, and distance from the highway edge. Direct model transferability was poor (R(2) < 0.17). Locally-calibrated transferred models (R(2) = 0.19-0.40) and the Boston-area model (adjusted-R(2) = 0.26, range: 0.13-0.30) performed similarly to neighborhood-specific models; however, some coefficients of locally calibrated transferred models were uninterpretable. Our results show that transferability of neighborhood-specific LUR models of hourly PNC was limited, but that a general model performed acceptably in multiple areas when calibrated with local data.

Physical Activity- and Alcohol-dependent Association Between Air Pollution Exposure and Elevated Liver Enzyme Levels: An Elderly Panel Study

OBJECTIVES

The deleterious effects of air pollution on various health outcomes have been demonstrated. However, few studies have examined the effects of air pollution on liver enzyme levels.

METHODS

Blood samples were drawn up to three times between 2008 and 2010 from 545 elderly individuals who regularly visited a community welfare center in Seoul, Korea. Data regarding ambient air pollutants (particulate matter ≤2.5 μm [PM2.5], nitrogen dioxide [NO2], ozone [O3], carbon monoxide, and sulfur dioxide) from monitoring stations were used to estimate air pollution exposure. The effects of the air pollutants on the concentrations of three liver enzymes (aspartate aminotransferase [AST], alanine aminotransferase [ALT], and γ-glutamyltranspeptidase [γ-GTP)]) were evaluated using generalized additive and linear mixed models.

RESULTS

Interquartile range increases in the concentrations of the pollutants showed significant associations of PM2.5 with AST (3.0% increase, p=0.0052), ALT (3.2% increase, p=0.0313), and γ-GTP (5.0% increase, p=0.0051) levels; NO2 with AST (3.5% increase, p=0.0060) and ALT (3.8% increase, p=0.0179) levels; and O3 with γ-GTP (5.3% increase, p=0.0324) levels. Significant modification of these effects by exercise and alcohol consumption was found (p for interaction <0.05). The effects of air pollutants were greater in non-exercisers and heavy drinkers.

CONCLUSIONS

Short-term exposure to air pollutants such as PM2.5, NO2, and O3 is associated with increased liver enzyme levels in the elderly. These adverse effects can be reduced by exercising regularly and abstinence from alcohol.

Reprint of: Perinatal and early childhood environmental factors influencing allergic asthma immunopathogenesis

BACKGROUND

The prevalence of asthma has increased dramatically over the past several decades. While hereditary factors are highly important, the rapid rise outstrips the pace of genomic variation. Great emphasis has been placed on potential modifiable early life exposures leading to childhood asthma.

METHODS

We reviewed the recent medical literature for important studies discussing the role of the perinatal and early childhood exposures and the inception of childhood asthma.

RESULTS AND DISCUSSION

Early life exposure to allergens (house dust mite (HDM), furred pets, cockroach, rodent and mold), air pollution (nitrogen dioxide (NO2), ozone (O3), volatile organic compounds (VOCs), and particulate matter (PM)) and viral respiratory tract infections (Respiratory syncytial virus (RSV) and human rhinovirus (hRV)) has been implicated in the development of asthma in high risk children. Conversely, exposure to microbial diversity in the perinatal period may diminish the development of atopy and asthma symptoms.

Health effects of multi-pollutant profiles

BACKGROUND

The association between exposure to particle mass and mortality is well established; however, there are still uncertainties as to whether certain chemical components are more harmful than others. Moreover, understanding the health effects associated with exposure to pollutant mixtures may lead to new regulatory strategies.

OBJECTIVES

Recently we have introduced a new approach that uses cluster analysis to identify distinct air pollutant mixtures by classifying days into groups based on their pollutant concentration profiles. In Boston during the years 1999-2009, we examined whether the effect of PM2.5 on total mortality differed by distinct pollution mixtures.

METHODS

We applied a time series analysis to examine the association of PM2.5 with daily deaths. Subsequently, we included an interaction term between PM2.5 and the pollution mixture clusters.

RESULTS

We found a 1.1% increase (95% CI: 0.0, 2.2) and 2.3% increase (95% CI: 0.9-3.7) in total mortality for a 10 μg/m(3) increase in the same day and the two-day average of PM2.5 respectively. The association is larger in a cluster characterized by high concentrations of the elements related to primary traffic pollution and oil combustion emissions with a 3.7% increase (95% CI: 0.4, 7.1) in total mortality, per 10 μg/m(3) increase in the same day average of PM2.5.

CONCLUSIONS

Our study shows a higher association of PM2.5 on total mortality during days with a strong contribution of traffic emissions, and fuel oil combustion. Our proposed method to create multi-pollutant profiles is robust, and provides a promising tool to identify multi-pollutant mixtures which can be linked to the health effects.

Long-term exposure to ambient air pollution and incidence of cerebrovascular events: results from 11 European cohorts within the ESCAPE project

BACKGROUND

Few studies have investigated effects of air pollution on the incidence of cerebrovascular events.

OBJECTIVES

We assessed the association between long-term exposure to multiple air pollutants and the incidence of stroke in European cohorts.

METHODS

Data from 11 cohorts were collected, and occurrence of a first stroke was evaluated. Individual air pollution exposures were predicted from land-use regression models developed within the European Study of Cohorts for Air Pollution Effects (ESCAPE). The exposures were: PM2.5 [particulate matter (PM) ≤ 2.5 μm in diameter], coarse PM (PM between 2.5 and 10 μm), PM10 (PM ≤ 10 μm), PM2.5 absorbance, nitrogen oxides, and two traffic indicators. Cohort-specific analyses were conducted using Cox proportional hazards models. Random-effects meta-analysis was used for pooled effect estimation.

RESULTS

A total of 99,446 study participants were included, 3,086 of whom developed stroke. A 5-μg/m3 increase in annual PM2.5 exposure was associated with 19% increased risk of incident stroke [hazard ratio (HR) = 1.19, 95% CI: 0.88, 1.62]. Similar findings were obtained for PM10. The results were robust to adjustment for an extensive list of cardiovascular risk factors and noise coexposure. The association with PM2.5 was apparent among those ≥ 60 years of age (HR = 1.40, 95% CI: 1.05, 1.87), among never-smokers (HR = 1.74, 95% CI: 1.06, 2.88), and among participants with PM2.5 exposure < 25 μg/m3 (HR = 1.33, 95% CI: 1.01, 1.77).

CONCLUSIONS

We found suggestive evidence of an association between fine particles and incidence of cerebrovascular events in Europe, even at lower concentrations than set by the current air quality limit value.

Perinatal and early childhood environmental factors influencing allergic asthma immunopathogenesis

BACKGROUND

The prevalence of asthma has increased dramatically over the past several decades. While hereditary factors are highly important, the rapid rise outstrips the pace of genomic variation. Great emphasis has been placed on potential modifiable early life exposures leading to childhood asthma.

METHODS

We reviewed the recent medical literature for important studies discussing the role of the perinatal and early childhood exposures and the inception of childhood asthma.

RESULTS AND DISCUSSION

Early life exposure to allergens (house dust mite (HDM), furred pets, cockroach, rodent and mold), air pollution (nitrogen dioxide (NO(2)), ozone (O(3)), volatile organic compounds (VOCs), and particulate matter (PM)) and viral respiratory tract infections (Respiratory syncytial virus (RSV) and human rhinovirus (hRV)) has been implicated in the development of asthma in high risk children. Conversely, exposure to microbial diversity in the perinatal period may diminish the development of atopy and asthma symptoms.