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Major improvements in air quality since 1990, observed through reductions in fine particulate matter (PM 2.5 ), have been associated with reduced cardiovascular mortality rates (CMR). However, it is not well understood whether the health benefit attributed to PM 2.5 reductions has been similar across strata of socioeconomic deprivation (SED). Using mixed effect regression models, we estimated the PM 2.5 -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 PM 2.5 (μg/m 3 ), and an index of county SED based on socioeconomic factors from the 1990 US Census. The contribution of PM 2.5 reductions to decreased CMR varied by SED strata and over time. Yearly differences resulted from varying rates of PM 2.5 reduction and because of the non-linear relationship between CMR and PM 2.5 concentration. In early years, PM 2.5 -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 PM 2.5 reduction in these counties. However, in later years, PM 2.5 -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 PM 2.5 . We identified that CMR reductions related to air quality improvements have become more similar over time between socioeconomic strata., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Reductions in ambient concentrations of fine particulate matter ( PM 2.5 ) have contributed to reductions in cardiovascular (CV) mortality., Objectives: We examined changes in CV mortality attributed to reductions in emissions from mobile, point, areal, and nonroad sources through changes in concentrations of PM 2.5 and its major components [nitrates, sulfates, elemental carbon (EC), and organic carbon (OC)] in 2,132 U.S. counties between 1990 and 2010., Methods: Using Community Multiscale Air Quality model estimated PM 2.5 total and component concentrations, we calculated population-weighted annual averages for each county. We estimated PM 2.5 total- and component-related CV mortality, adjusted for county-level population characteristics and baseline PM 2.5 concentrations. Using the index of Emission Mitigation Efficiency for primary emission-to-particle pathways, we expressed changes in particle-related mortality in terms of precursor emissions by each sector., Results: PM 2.5 reductions represented 5.7% of the overall decline in CV mortality. Large point source emissions of sulfur dioxide accounted for 6.685 [95% confidence interval (CI): 5.703, 7.667] fewer sulfate-related CV deaths per 100,000 people. Mobile source emissions of primary EC and nitrous oxides accounted for 3.396 (95% CI: 2.772, 4.020) and 3.984 (95% CI: 2.472, 5.496) fewer CV deaths per 100,000 people respectively. Increased EC and OC emissions from areal sources increased carbon-related CV mortality by 0.788 (95% CI: - 0.540 , 2.116) and 0.245 (95% CI: - 0.697 , 1.187) CV deaths per 100,000 people., Discussion: In a nationwide epidemiological study of emission sector contribution to PM 2.5 -related mortality, we found that reductions in sulfur-dioxide emissions from large point sources and nitrates and EC emissions from mobile sources contributed the largest reduction in particle-related mortality rates respectively. https://doi.org/10.1289/EHP5692.

Background: Air pollution-induced changes in cardiac electrophysiological properties could be a pathway linking air pollution and cardiovascular events. The evidence of air pollution effects on the cardiac conduction system is incomplete yet. We investigated short-term effects of particulate matter ≤ 2.5 μm in aerodynamic diameter (PM 2.5 ) and ozone (O 3 ) on cardiac electrical impulse propagation and repolarization as recorded in surface electrocardiograms (ECG)., Methods: We analyzed repeated 12-lead ECG measurements performed on 5,332 patients between 2001 and 2012. The participants came from the Duke CATHGEN Study who underwent cardiac catheterization and resided in North Carolina, United States (NC, U.S.). Daily concentrations of PM 2.5 and O 3 at each participant's home address were predicted with a hybrid air quality exposure model. We used generalized additive mixed models to investigate the associations of PM 2.5 and O 3 with the PR interval, QRS interval, heart rate-corrected QT interval (QTc), and heart rate (HR). The temporal lag structures of the associations were examined using distributed-lag models., Results: Elevated PM 2.5 and O 3 were associated with four-day lagged lengthening of the PR and QRS intervals, and with one-day lagged increases in HR. We observed immediate effects on the lengthening of the QTc interval for both PM 2.5 and O 3 , as well as delayed effects for PM 2.5 (lagged by 3 - 4 days). The associations of PM 2.5 and O 3 with the PR interval and the association of O 3 with the QRS interval persisted until up to seven days after exposure., Conclusions: In patients undergoing cardiac catheterization, short-term exposure to air pollution was associated with increased HR and delays in atrioventricular conduction, ventricular depolarization and repolarization.

Background: In 1997 the U.S. Environmental Protection Agency set the first annual National Ambient Air Quality Standard (NAAQS) for fine particulate matter (PM 2.5 ). Although the weight of scientific evidence has determined that a causal relationship exists between PM 2.5 exposures and cardiovascular effects, few studies have concluded whether NAAQS-related reductions in PM 2.5 led to improvements in public health., Methods: We examined the change in cardiovascular (CV) mortality rate and the association between change in PM 2.5 and change in CV-mortality rate before (2000-2004) and after implementation of the 1997 annual PM 2.5 NAAQS (2005-2010) among U.S. counties. We further examined how the association varied with respect to two factors related to NAAQS compliance: attainment status and design values (DV). We used difference-in-differences and linear regression models, adjusted for sociodemographic confounders., Findings: Across 619 counties, there were 1.10 (95% CI: 0.37, 1.82) fewer CV-deaths per year per 100,000 people for each 1µg/m 3 decrease in PM 2.5 . Nonattainment counties had a twofold larger reduction in mean annual PM 2.5 , 2.1µg/m 3 , compared to attainment counties, 0.97µg/m 3 . CV-mortality rate decreased by 0.59 (95% CI: -0.54, 1.71) in nonattainment and 1.96 (95% CI: 0.77, 3.15) deaths per 100,000 people for each 1µg/m 3 decrease in PM 2.5 in attainment counties. When stratifying counties by DV, results were similar: counties with DV greater than 15µg/m 3 experienced the greatest decrease in mean annual PM 2.5 (2.29µg/m 3 ) but the smallest decrease in CV-mortality rate per unit decrease in PM 2.5 , 0.73 (95% CI: -0.57, 2.02)., Interpretation: We report a significant association between the change in PM 2.5 and the change in CV-mortality rate before and after the implementation of NAAQS and note that the health benefits per 1µg/m 3 decrease in PM 2.5 persist at levels below the current national standard., Funding: US EPA intermural research., (Published by Elsevier Inc.)

Background: Adverse cardiovascular events have been linked with PM 2.5 exposure obtained primarily from air quality monitors, which rarely co-locate with participant residences. Modeled PM 2.5 predictions at finer resolution may more accurately predict residential exposure; however few studies have compared results across different exposure assessment methods., Methods: We utilized a cohort of 5679 patients who had undergone a cardiac catheterization between 2002-2009 and resided in NC. Exposure to PM 2.5 for the year prior to catheterization was estimated using data from air quality monitors (AQS), Community Multiscale Air Quality (CMAQ) fused models at the census tract and 12km spatial resolutions, and satellite-based models at 10km and 1km resolutions. Case status was either a coronary artery disease (CAD) index >23 or a recent myocardial infarction (MI). Logistic regression was used to model odds of having CAD or an MI with each 1-unit (μg/m3) increase in PM 2.5 , adjusting for sex, race, smoking status, socioeconomic status, and urban/rural status., Results: We found that the elevated odds for CAD>23 and MI were nearly equivalent for all exposure assessment methods. One difference was that data from AQS and the census tract CMAQ showed a rural/urban difference in relative risk, which was not apparent with the satellite or 12km-CMAQ models., Conclusions: Long-term air pollution exposure was associated with coronary artery disease for both modeled and monitored data., (Published by Elsevier Inc.)

Rationale: Exposure to ambient particulate matter (PM) and ozone has been associated with cardiovascular disease (CVD). However, the mechanisms linking PM and ozone exposure to CVD remain poorly understood., Objective: This study explored associations between short-term exposures to PM with a diameter <2.5μm (PM 2.5 ) and ozone with plasma metabolite concentrations., Methods and Results: We used cross-sectional data from a cardiac catheterization cohort at Duke University, North Carolina (NC), USA, accumulated between 2001 and 2007. Amino acids, acylcarnitines, ketones and total non-esterified fatty acid plasma concentrations were determined in fasting samples. Daily concentrations of PM 2.5 and ozone were obtained from a Bayesian space-time hierarchical model, matched to each patient's residential address. Ten metabolites were selected for the analysis based on quality criteria and cluster analysis. Associations between metabolites and PM 2.5 or ozone were analyzed using linear regression models adjusting for long-term trend and seasonality, calendar effects, meteorological parameters, and participant characteristics. We found delayed associations between PM 2.5 or ozone and changes in metabolite levels of the glycine-ornithine-arginine metabolic axis and incomplete fatty acid oxidation associated with mitochondrial dysfunction. The strongest association was seen for an increase of 8.1μg/m 3 in PM 2.5 with a lag of one day and decreased mean glycine concentrations (-2.5% [95% confidence interval: -3.8%; -1.2%])., Conclusions: Short-term exposures to ambient PM 2.5 and ozone is associated with changes in plasma concentrations of metabolites in a cohort of cardiac catheterization patients. Our findings might help to understand the link between air pollution and cardiovascular disease., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Background: The relationship between traffic-related air pollution (TRAP) and risk factors for cardiovascular disease needs to be better understood in order to address the adverse impact of air pollution on human health., Objective: We examined associations between roadway proximity and traffic exposure zones, as markers of TRAP exposure, and metabolic biomarkers for cardiovascular disease risk in a cohort of patients undergoing cardiac catheterization., Methods: We performed a cross-sectional study of 2,124 individuals residing in North Carolina (USA). Roadway proximity was assessed via distance to primary and secondary roadways, and we used residence in traffic exposure zones (TEZs) as a proxy for TRAP. Two categories of metabolic outcomes were studied: measures associated with glucose control, and measures associated with lipid metabolism. Statistical models were adjusted for race, sex, smoking, body mass index, and socioeconomic status (SES)., Results: An interquartile-range (990 m) decrease in distance to roadways was associated with higher fasting plasma glucose (β = 2.17 mg/dL; 95% CI: -0.24, 4.59), and the association appeared to be limited to women (β = 5.16 mg/dL; 95% CI: 1.48, 8.84 compared with β = 0.14 mg/dL; 95% CI: -3.04, 3.33 in men). Residence in TEZ 5 (high-speed traffic) and TEZ 6 (stop-and-go traffic), the two traffic zones assumed to have the highest levels of TRAP, was positively associated with high-density lipoprotein cholesterol (HDL-C; β = 8.36; 95% CI: -0.15, 16.9 and β = 5.98; 95% CI: -3.96, 15.9, for TEZ 5 and 6, respectively)., Conclusion: Proxy measures of TRAP exposure were associated with intermediate metabolic traits associated with cardiovascular disease, including fasting plasma glucose and possibly HDL-C.

With the advent of multicity studies, uniform statistical approaches have been developed to examine air pollution-mortality associations across cities. To assess the sensitivity of the air pollution-mortality association to different model specifications in a single and multipollutant context, the authors applied various regression models developed in previous multicity time-series studies of air pollution and mortality to data from Philadelphia, Pennsylvania (May 1992-September 1995). Single-pollutant analyses used daily cardiovascular mortality, fine particulate matter (particles with an aerodynamic diameter ≤2.5 µm; PM(2.5)), speciated PM(2.5), and gaseous pollutant data, while multipollutant analyses used source factors identified through principal component analysis. In single-pollutant analyses, risk estimates were relatively consistent across models for most PM(2.5) components and gaseous pollutants. However, risk estimates were inconsistent for ozone in all-year and warm-season analyses. Principal component analysis yielded factors with species associated with traffic, crustal material, residual oil, and coal. Risk estimates for these factors exhibited less sensitivity to alternative regression models compared with single-pollutant models. Factors associated with traffic and crustal material showed consistently positive associations in the warm season, while the coal combustion factor showed consistently positive associations in the cold season. Overall, mortality risk estimates examined using a source-oriented approach yielded more stable and precise risk estimates, compared with single-pollutant analyses.

Background: In June 2008, burning peat deposits produced haze and air pollution far in excess of National Ambient Air Quality Standards, encroaching on rural communities of eastern North Carolina. Although the association of mortality and morbidity with exposure to urban air pollution is well established, the health effects associated with exposure to wildfire emissions are less well understood., Objective: We investigated the effects of exposure on cardiorespiratory outcomes in the population affected by the fire., Methods: We performed a population-based study using emergency department (ED) visits reported through the syndromic surveillance program NC DETECT (North Carolina Disease Event Tracking and Epidemiologic Collection Tool). We used aerosol optical depth measured by a satellite to determine a high-exposure window and distinguish counties most impacted by the dense smoke plume from surrounding referent counties. Poisson log-linear regression with a 5-day distributed lag was used to estimate changes in the cumulative relative risk (RR)., Results: In the exposed counties, significant increases in cumulative RR for asthma [1.65 (95% confidence interval, 1.25-2.1)], chronic obstructive pulmonary disease [1.73 (1.06-2.83)], and pneumonia and acute bronchitis [1.59 (1.07-2.34)] were observed. ED visits associated with cardiopulmonary symptoms [1.23 (1.06-1.43)] and heart failure [1.37 (1.01-1.85)] were also significantly increased., Conclusions: Satellite data and syndromic surveillance were combined to assess the health impacts of wildfire smoke in rural counties with sparse air-quality monitoring. This is the first study to demonstrate both respiratory and cardiac effects after brief exposure to peat wildfire smoke.

Studies have linked increased levels of particulate air pollution to decreased autonomic control, as measured by heart rate variability (HRV), particularly in susceptible populations such as the elderly. In this study, we use data obtained from the 1998 USEPA epidemiology-exposure longitudinal panel study of elderly adults in a Baltimore retirement home to examine the relationship between HRV and PM₂.₅ personal exposure. We consider PM₂.₅ personal exposure in the aggregate and personal exposure to the components of PM₂.₅ as estimated in two ways using receptor models. We develop a Bayesian hierarchical model for HRV as a function of personal exposure to PM₂.₅, which integrates HRV measurements and data obtained from personal, indoor and outdoor PM₂.₅ monitoring and meteorological data. We found a strong relationship between decreased HRV (HF, LF, r-MSSD and SDNN) and total personal exposure to PM₂.₅ at a lag of 1 day. Using personal exposure monitoring (PEM) apportionment results, we examined the relative importance of ambient and non-ambient personal PM₂.₅ exposure to HRV and found the effect of internal non-ambient sources of PM₂.₅ on HRV to be minimal. Using the PEM apportionment data, a consistent effect of soil at short time scales (lag 0) was found across all five HRV measures, and an effect of sulfate on HRV was seen for HF and r-MSSD at the moving average of lags 0 and 1 days. Modeling of ambient site apportionment data indicated effects of nitrate on HRV at lags of 1 day, and moving averages of days 0 and 1 and days 0-2 for all but the ratio LF/HF. Sulfate had an effect on HRV at a lag of 1 day for four HRV measures (HF, LF, r-MSSD, SDNN) and for LF/HF at a moving average of days 0-2.

Background and Objective: Exposure to fine airborne particles (PM2.5) has been shown to be responsible for cardiovascular and hematological effects, especially in older people with cardiovascular disease. Some epidemiological studies suggest that individuals with diabetes may be a particularly susceptible population. This study examined effects of short-term exposures to ambient PM2.5 on markers of systemic inflammation, coagulation, autonomic control of heart rate, and repolarization in 22 adults (mean age: 61 years) with type 2 diabetes., Methods: Each individual was studied for four consecutive days with daily assessments of plasma levels of blood markers. Cardiac rhythm and electrocardiographic parameters were examined at rest and with 24-hour ambulatory ECG monitors. PM2.5 and meteorological data were measured daily on the rooftop of the patient exam site. Data were analyzed with models adjusting for season, weekday, meteorology, and a random intercept. To identify susceptible subgroups, effect modification was analyzed by clinical characteristics associated with insulin resistance as well as with oxidative stress and by medication intake., Results: Interleukin (IL)-6 and tumor necrosis factor alpha showed a significant increase with a lag of two days (percent change of mean level: 20.2% with 95%-confidence interval [6.4; 34.1] and 13.1% [1.9; 24.4], respectively) in association with an increase of 10 mug/m3 in PM2.5. Obese participants as well as individuals with elevated glycosylated hemoglobin, lower adiponectin, higher ferritin or with glutathione S-transferase M1 null genotype showed higher IL-6 effects. Changes in repolarization were found immediately as well as up to four days after exposure in individuals without treatment with a beta-adrenergic receptor blocker., Conclusions: Exposure to elevated levels of PM2.5 alters ventricular repolarization and thus may increase myocardial vulnerability to arrhythmias. Exposure to PM2.5 also increases systemic inflammation. Characteristics associated with insulin resistance or with oxidative stress were shown to enhance the association.

Passive ambient air sampling for nitrogen dioxide (NO(2)) and volatile organic compounds (VOCs) was conducted at 25 school and two compliance sites in Detroit and Dearborn, Michigan, USA during the summer of 2005. Geographic Information System (GIS) data were calculated at each of 116 schools. The 25 selected schools were monitored to assess and model intra-urban gradients of air pollutants to evaluate impact of traffic and urban emissions on pollutant levels. Schools were chosen to be statistically representative of urban land use variables such as distance to major roadways, traffic intensity around the schools, distance to nearest point sources, population density, and distance to nearest border crossing. Two approaches were used to investigate spatial variability. First, Kruskal-Wallis analyses and pairwise comparisons on data from the schools examined coarse spatial differences based on city section and distance from heavily trafficked roads. Secondly, spatial variation on a finer scale and as a response to multiple factors was evaluated through land use regression (LUR) models via multiple linear regression. For weeklong exposures, VOCs did not exhibit spatial variability by city section or distance from major roads; NO(2) was significantly elevated in a section dominated by traffic and industrial influence versus a residential section. Somewhat in contrast to coarse spatial analyses, LUR results revealed spatial gradients in NO(2) and selected VOCs across the area. The process used to select spatially representative sites for air sampling and the results of coarse and fine spatial variability of air pollutants provide insights that may guide future air quality studies in assessing intra-urban gradients.

This study evaluates performance of nitrogen dioxide (NO2) and volatile organic compound (VOC) passive samplers with corresponding reference monitors at two sites in the Detroit, Michigan area during the summer of 2005. Ogawa passive NO2 samplers and custom-made, re-useable Perkin-Elmer (PE) tubes with Carbopack X sorbent for VOCs were deployed under week-long sampling periods for six weeks. Precise results (5% relative standard deviation, RSD) were found for NO2 measurements from collocated Ogawa samplers. Reproducibility was also good for duplicate PE tubes for benzene, toluene, ethylbenzene, and xylene isomers (BTEX species, all < or = 6% RSD). As seen in previous studies, comparison of Ogawa NO2 samplers with reference chemiluminescence measurements suggested good agreement. Generally good agreement was also found between the PE tubes and reference methods for BTEX species.

Preterm delivery can lead to serious infant health outcomes, including death and lifelong disability. Small increases in preterm delivery risk in relation to spatial gradients of air pollution have been reported, but previous studies may have controlled inadequately for individual factors. Using a time-series analysis, which eliminates potential confounding by individual risk factors that do not change over short periods of time, we investigated the effect of ambient outdoor particulate matter with diameter < or = 10 microm (PM10) and sulfur dioxide on risk for preterm delivery. Daily counts of preterm births were obtained from birth records in four Pennsylvania counties from 1997 through 2001. We observed increased risk for preterm delivery with exposure to average PM10 and SO2 in the 6 weeks before birth [respectively, relative risk (RR) = 1.07; 95% confidence interval (CI), 0.98-1.18 per 50 microg/m3 increase; RR = 1.15; 95% CI, 1.00-1. 32 per 15 ppb increase], adjusting for long-term preterm delivery trends, co-pollutants, and offsetting by the number of gestations at risk. We also examined lags up to 7 days before the birth and found an acute effect of exposure to PM10 2 days and 5 days before birth (respectively, RR = 1.10; 95% CI, 1.00-1.21; RR = 1.07; 95% CI, 0.98-1.18) and SO2 3 days before birth (RR = 1.07; 95% CI, 0.99-1.15), adjusting for covariates, including temperature, dew point temperature, and day of the week. The results from this time-series analysis, which provides evidence of an increase in preterm birth risk with exposure to PM10 and SO2, are consistent with prior investigations of spatial contrasts.

The relationship between continuous measurements of volatile organic compounds sources and particle number was evaluated at a Photochemical Assessment Monitoring Station Network (PAMS) site located near the U.S.-Mexico Border in central El Paso, TX. Sources of volatile organic compounds (VOCs) were investigated using the multivariate receptor model UNMIX and the effective variance least squares receptor model known as Chemical Mass Balance (CMB, Version 8.0). As expected from PAMS measurements, overall findings from data screening as well as both receptor models confirmed that mobile sources were the major source of VOCs. Comparison of hourly source contribution estimates (SCEs) from the two receptor models revealed significant differences in motor vehicle exhaust and evaporative gasoline contributions. However, the motor vehicle exhaust contributions were highly correlated with each other. Motor vehicle exhaust was also correlated with the ultrafine and accumulation mode particle count, which suggests that motor vehicle exhaust is a source of these particles at the measurement site. Wind sector analyses were performed using the SCE and pollutant data to assess source location of VOCs, particle count, and criteria pollutants. Results from this study have application to source apportionment studies and mobile source emission control strategies that are ongoing in this air shed.

This study evaluates the performance of Model 3300 Ogawa Passive Nitrogen Dioxide (NO2) Samplers and 3M 3520 Organic Vapor Monitors (OVMs) by comparing integrated passive sampling concentrations to averaged hourly NO2 and volatile organic compound (VOC) measurements at two sites in El Paso, TX. Sampling periods were three time intervals (3-day weekend, 4-day weekday, and 7-day weekly) for three consecutive weeks. OVM concentrations were corrected for ambient pressure to account for higher elevation. Precise results (< 5% relative standard deviation, RSD) were found for NO2 measurements from collocated Ogawa samplers. Reproducibility was lower from duplicate OVMs for BTEX (benzene, toluene, ethylbenzene, and xylene isomers) VOCs (> or = 77% RSD for 2-day samples) with better precision for longer sampling periods. Comparison of Ogawa NO2 samplers with chemiluminescence measurements averaged over the same time period suggested potential calibration problems with the chemiluminescence analyzer. For BTEX species, generally good agreement was obtained between OVMs and automated-gas chromatograph (auto-GC) measurements. The OVMs successfully tracked increasing levels of VOCs recorded by the auto-GCs. However, except for toluene, OVM BTEX measurements generally exceeded their continuous counterparts with a mean bias of 5-10%. Although interpretation of the study results was limited due to small sample sizes, diffusion barrier influences caused by shelters that housed OVMs and differences in sampling heights between OVMs and auto-GC inlet may explain the overestimation.

The association between airborne particles and daily mortality has been reported in many locations, but mainly in western countries. There is a need to investigate the association in locations where the emission sources, weather, and other environmental conditions differ from those in western countries. In this study, the acute effects of PM10 and visibility on daily mortality in Bangkok, Thailand, from 1992 to 1997, were examined. A Poisson regression model was developed to estimate the excess daily mortality associated with PM10 and visibility, while controlling for long-term trends, season, and variations in weather. It was found that increasing PM10 and decreasing visibility levels were independently associated with increasing daily mortality from all non-external causes, cardiovascular, respiratory, and other diseases. The observed associations were stronger for respiratory diseases than for cardiovascular and other diseases and were stronger for persons aged > or = 65 years than for those in the younger age group. The results of the PM10/mortality and visibility/mortality models were consistent, suggesting that visibility may be considered as a surrogate marker for the assessment of the adverse health effects of fine particulate matter when data from direct gravimetric measurements are not available.