Abstract  Epidemiological studies have observed between city heterogeneity in PM2.5-mortality risk estimates. These differences could potentially be due to the use of central-site monitors as a surrogate for exposure which do not account for an individual's activities or ambient pollutant infiltration to the indoor environment. Therefore, relying solely on central-site monitoring data introduces exposure error in the epidemiological analysis. The amount of exposure error produced by using the central-site monitoring data may differ by city. The objective of this analysis was to cluster cities with similar exposure distributions based on residential infiltration and in-vehicle commuting characteristics. Factors related to residential infiltration and commuting were developed from the American Housing Survey (AHS) from 2001 to 2005 for 94 Core-Based Statistical Areas (CBSAs). We conducted two separate cluster analyses using a k-means clustering algorithm to cluster CBSAs based on these factors. The first only included residential infiltration factors (i.e. percent of homes with central air conditioning (AC) mean year home was built, and mean home size) while the second incorporated both infiltration and commuting (i.e. mean in-vehicle commuting time and mean in-vehicle commuting distance) factors. Clustering on residential infiltration factors resulted in 5 clusters, with two having distinct exposure distributions. Cluster 1 consisted of cities with older, smaller homes with less central AC while homes in Cluster 2 cities were newer, larger, and more likely to have central AC. Including commuting factors resulted in 10 clusters. Clusters with shorter in-vehicle commuting times had shorter in-vehicle commuting distances. Cities with newer homes also tended to have longer commuting times and distances. This is the first study to employ cluster analysis to group cities based on exposure factors. Identifying cities with similar exposure distributions may help explain city-to-city heterogeneity in PM2.5 mortality risk estimates.

Abstract  RATIONALE: Several studies have linked long-term exposure to particulate air pollution with increased cardiopulmonary mortality; only two have also examined incident circulatory disease. OBJECTIVES: To examine associations of individualized long-term exposures to particulate and gaseous air pollution with incident myocardial infarction (MI) and stroke, as well as all-cause and cause-specific mortality. METHODS: We estimated long-term residential air pollution exposure for over 100,000 participants in the California Teachers Study, a prospective cohort of female public school professionals. We linked geocoded residential addresses with inverse distance-weighted monthly pollutant surfaces for two measures of particulate matter and for several gaseous pollutants. We examined associations between exposure to these pollutants and risks of incident MI and stroke, and of all-cause and cause-specific mortality, using Cox proportional hazards models. MEASUREMENTS AND MAIN RESULTS: We found elevated hazard ratios linking long-term exposure to fine particulate matter (PM2.5, scaled to an increment of 10 µg/m3) with mortality from ischemic heart disease (IHD) (1.20, 95% C.I. 1.02-1.41) and, particularly among post-menopausal women, incident stroke (1.19, 95% C.I. 1.02-1.38). Long-term exposure to particulate matter less than 10 µm aerodynamic diameter (PM10) was associated with elevated risks for IHD mortality (1.06, 95% C.I. 0.99-1.14) and incident stroke 1.06 (95% CI: 1.00-1.13), while nitrogen oxides were associated with elevated risks for cardiovascular as well as IHD mortality. CONCLUSIONS: Long-term exposures to PM2.5 and PM10 were associated with increased risks of incident stroke and death from IHD; exposures to nitrogen oxides were associated with all cardiovascular as well as IHD mortality.

Abstract  #Using the photographs and optical measurements taken during a summer field program (REVEAL) designed to examine the chemical and physical characteristics of visibility impairment in the Fraser Valley, southwestern British Columbia, a protocol for gauging public perception of visibility in this region was devised and tested in a pilot survey. This paper details the protocol (which is based on previous studies conducted in the United States of America) and analysis techniques for survey responses. A preliminary assessment of the results of the pilot study is also presented. A public perception survey conducted in Denver (Ely et al., 1991), resolved a visibility standard for Denver of bext (total light extinction) = 0.076 Î 10-3 m-1. Assuming a homogeneous atmosphere, this level of bext is approximately equal to a visual range of 50 km. Using a similar protocol, responses from this pilot study were used to extrapolate visibility standards for two suburban locations in the Fraser Valley of b(ext) (approx) 0.09 Î 10-3-0.105 Î 10-3 m-1 (bsp (particle light scattering) (approx) 0.051 Î 10-3-0.063 Î 10-3 m-1) and b(sp) (approx) 0.39 Î 10-3 m-1. These levels of light extinction (bsp is the largest component of b(ext)) relate to approximate visual range of between 40 and 60 km in a homogeneous atmosphere. Possible reasons for the apparent discrepancies between locations are discussed and the effect of survey group are addressed.

Abstract  Background and Methods Atrial fibrillation is associated with an increased risk of ischemic stroke. Data on individual patients were pooled from five recently completed randomized trials comparing warfarin (all studies) or aspirin (the Atrial Fibrillation, Aspirin, Anticoagulation Study and the Stroke Prevention in Atrial Fibrillation Study) with control in patients with atrial fibrillation. The purpose of the analysis was to (1) identify patient features predictive of a high or low risk of stroke, (2) assess the efficacy of antithrombotic therapy in major patient subgroups (eg, women), and (3) obtain the most precise estimate of the efficacy and risks of antithrombotic therapy in atrial fibrillation. For the warfarin-control comparison there were 1889 patient-years receiving warfarin and 1802 in the control group. For the aspirin-placebo comparison there were 1132 patient-years receiving aspirin and 1133 receiving placebo. The daily dose of aspirin was 75 mg in the Atrial Fibrillation, Aspirin, Anticoagulation Study and 325 mg in the Stroke Prevention in Atrial Fibrillation Study. To monitor warfarin dosage, three studies used prothrombin time ratios and two used international normalized ratios. The lowest target intensity was a prothrombin time ratio of 1.2 to 1.5 and the highest target intensity was an international normalized ratio of 2.8 to 4.2. The primary end points were ischemic stroke and major hemorrhage, as assessed by each study. Results At the time of randomization the mean age was 69 years and the mean blood pressure was 142/82 mm Hg. Forty-six percent of the patients had a history of hypertension, 6% had a previous transient ischemic attack or stroke, and 14% had diabetes. Risk factors that predicted stroke on multivariate analyses in control patients were increasing age, history of hypertension, previous transient ischemic attack or stroke, and diabetes. Patients younger than 65 years who had none of the other predictive factors (15% of all patients) had an annual rate of stroke of 1.0%, 95% confidence interval (CI) 0.3% to 3.0%. The annual rate of stroke was 4.5% for the control group and 1.4% for the warfarin group (risk reduction, 68%; 95% CI, 50% to 79%). The efficacy of warfarin was consistent across all studies and subgroups of patients. In women, warfarin decreased the risk of stroke by 84% (95% CI, 55% to 95%) compared with 60% (95% CI, 35% to 76%) in men. The efficacy of aspirin was not as consistent. The risk reduction with 75 mg of aspirin in the Atrial Fibrillation, Aspirin, Anticoagulation Study was 18% (95% CI, 60% to 58%), and with 325 mg of aspirin in the Stroke Prevention in Atrial Fibrillation Study the risk reduction was 44% (95% CI, 7% to 66%). When both studies were combined the risk reduction was 36% (95% CI, 4% to 57%). The annual rate of major hemorrhage (intracranial bleeding or a bleed requiring hospitalization or 2 units of blood) was 1.0% for the control group, 1.0% for the aspirin group, and 1.3% for the warfarin group. Conclusion In these five randomized trials warfarin consistently decreased the risk of stroke in patients with atrial fibrillation (a 68% reduction in risk) with virtually no increase in the frequency of major bleeding. Patients with atrial fibrillation younger than 65 years without a history of hypertension, previous stroke or transient ischemic attack, or diabetes were at very low risk of stroke even when not treated. The efficacy of aspirin was less consistent. Further studies are needed to clarify the role of aspirin in atrial fibrillation.

Abstract  OBJECTIVES: Develop statistical methods for survival models to indirectly adjust hazard ratios of environmental exposures for missing risk factors.

METHODS: A partitioned regression approach for linear models is applied to time to event survival analyses of cohort study data. Information on the correlation between observed and missing risk factors is obtained from ancillary data sources such as national health surveys. The relationship between the missing risk factors and survival is obtained from previously published studies. We first evaluated the methodology using simulations, by considering the Weibull survival distribution for a proportional hazards regression model with varied baseline functions, correlations between an adjusted variable and an adjustment variable as well as selected censoring rates. Then we illustrate the method in a large, representative Canadian cohort of the association between concentrations of ambient fine particulate matter and mortality from ischemic heart disease.

RESULTS: Indirect adjustment for cigarette smoking habits and obesity increased the fine particulate matter-ischemic heart disease association by 3%-123%, depending on the number of variables considered in the adjustment model due to the negative correlation between these two risk factors and ambient air pollution concentrations in Canada. The simulations suggested that the method yielded small relative bias (<40%) for most cohort designs encountered in environmental epidemiology.

CONCLUSIONS: This method can accommodate adjustment for multiple missing risk factors simultaneously while accounting for the associations between observed and missing risk factors and between missing risk factors and health endpoints.

Abstract  The U.S. Environmental Protection Agency (EPA) is conducting a review of the existing air quality criteria for particulate matter (PM) and of the primary (health-based) and secondary (welfare-based) national ambient air quality standards (NAAQS) for PM. This review will provide an integrative assessment of relevant scientific information on PM and will focus on the basic elements of the PM NAAQS: the indicator, averaging time, form, and level. These elements, which together serve to define each NAAQS, are considered collectively in evaluating the protection to public health and public welfare afforded by the standards. The purpose of this Integrated Review Plan (IRP) is to communicate the plan for reviewing the air quality criteria and the primary and secondary NAAQS for PM.

Abstract  BACKGROUND: Many studies have identified an inequitable distribution of exposure to PM2.5 (particulate matter less than 2.5 microns) by race. We investigated the association of PM2.5 and cardiovascular mortality considering both the decedents' race and neighborhood racial composition as potential modifiers.

METHODS: We obtained geocoded cardiovascular mortality records of all black and white decedents from urban block-groups in Massachusetts between 2001 and 2011 (n = 130,863). We examined the association between PM2.5 and cardiovascular mortality, and assessed effect modification by three types of racial modifiers: decedents' race, census block-group percent black and white, and two novel measures of racial segregation. The Racial Residential Segregation (RRS) quantifies the concentration of non-Hispanic blacks and whites in each block-group. The Index of Racial Dissimilarity measures dissimilarity in non-Hispanic black and white racial distribution between the smaller census block-group and larger tract.

RESULTS: We found a 2.35%(95%CI: 0.92%;3.79%) increase in mortality for each 10μg/m3 increase in two-day average exposure to PM2.5. The effect was modified by the block-group racial composition, with higher risks in block-groups with the highest percentage of black residents (interaction p-value = 0.04), and in block-groups with the lowest RRS (i.e. higher black to white resident ratio, interaction p-value = 0.072). Racial dissimilarity did not modify the associations.

CONCLUSION: Current levels of PM2.5 are associated with increased cardiovascular deaths in Massachusetts, with different risks between areas with different racial composition and segregation. This suggests that pollution reductions in neighborhoods with the highest percentage of non-Hispanic blacks would be most beneficial in reducing cardiovascular mortality and disparities.

Abstract  The Integrated Science Assessment (ISA) for Oxides of Nitrogen, Oxides of Sulfur and Particulate Matter Ecological Criteria is a comprehensive evaluation and synthesis of the most policy relevant science aimed at characterizing the ecological effects caused by oxides of nitrogen, oxides of sulfur, and particulate matter. The ISA provides the scientific foundation necessary for the review of ecological effects associated with the secondary (welfare based) National Ambient Air Quality Standards (NAAQS) for these three criteria pollutants under the Clean Air Act. Welfare effects according to the Clean Air Act include, but are not limited to, effects on soils, water, crops, vegetation, animals, wildlife and climate. Oxides of nitrogen, oxides of sulfur, and particulate matter are three of six criteria pollutants for which EPA has established NAAQS. Periodically, EPA reviews the scientific basis for these standards by preparing an ISA (formerly called an Air Quality Criteria Document). The intent of the ISA, as described in the Clean Air Act (CAA), is to 'accurately reflect the latest scientific knowledge expected from the presence of [a] pollutant in ambient air.' It includes scientific research from atmospheric sciences, exposure and deposition, biogeochemistry, hydrology, soil science, marine science, plant physiology, animal physiology, and ecology conducted at multiple scales (e.g., population, community, ecosystem, landscape levels). Key information and judgments formerly found in the Air Quality Criteria Documents for oxides of sulfur, oxides of nitrogen and particulate matter for ecological effects are included; appendices provide additional details supporting the ISA. Together, the ISA and appendices serve to update and revise the 2008 Integrated Science Assessment for Oxides of Nitrogen and Oxides of Sulfur - Ecological Criteria and the ecological portion of the last particulate matter ISA which was published in 2009. Additionally, the Clean Air Scientific Advisory Committee (CASAC) is an independent science advisory committee whose review and advisory functions are mandated by Section 109(d)(2) of the Clean Air Act, and charged (among other things) with performing an independent scientific review of all the EPA’s air quality criteria.

Abstract  BACKGROUND: Air pollution has been associated with increased mortality. However, updated evidence from cohort studies with detailed information on various risk factors is needed, especially in regions with low air pollution levels. We investigated the associations between long-term exposure to air pollution and mortality in a prospective cohort.

METHODS: We studied 88,615 participants aged ≥30 years from an ongoing cohort study in Ontario, Canada from 2009 to 2017. Exposure to ambient fine particulate matter (PM2.5) and nitrogen dioxide (NO2) was estimated at participants' residence. Cox proportional hazard models were used to investigate the associations between air pollution and non-accidental, cardiovascular, and respiratory mortality, adjusted for a wide array of individual-level and contextual covariates. Potential effect modification by socio-demographic and behavioral factors was also examined in exploratory stratified analyses.

RESULTS: The fully adjusted hazard ratios (HRs) per 1 µg/m3 increment in PM2.5 were 1.037 [95% confidence interval (CI): 1.018, 1.057]¸ 1.083 (95% CI: 1.040, 1.128) and 1.109 (95% CI: 1.035, 1.187) for non-accidental, cardiovascular, and respiratory mortality, respectively. Positive associations were also found for NO2; the corresponding HRs per 1 ppb increment were 1.027 (95% CI: 1.021, 1.034), 1.032 (95% CI: 1.019, 1.046) and 1.044 (95% CI: 1.020, 1.068). We found suggestive evidence of stronger associations in physically active participants, smokers, and those with lower household income.

CONCLUSIONS: Long-term exposure to PM2.5 and NO2 was associated with increased risks for non-accidental, cardiovascular, and respiratory mortality, suggesting potential benefits of further improvement in air quality even in low-exposure environments.

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

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

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

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

Abstract  BACKGROUND: Estimating the causal effect of pollution on human health is integral for evaluating returns to pollution regulation, yet separating out confounding factors remains a perennial challenge.

METHODS: We use a quasi-experimental design to investigate the causal relationship between regulation of particulate matter smaller than 2.5 micrograms per cubic meter (PM2.5) and mortality among those 65 years of age and older. We exploit regulatory changes in the Clean Air Act Amendments (CAAA). Regulation in 2005 impacted areas of the United States differentially based on pre-regulation air quality levels for PM2.5. We use county-level mortality data, extracted from claims data managed by the Centers for Medicare & Medicaid Services, merged to county-level average PM2.5 readings and attainment status as classified by the Environmental Protection Agency.

RESULTS: Based on estimates from log-linear difference-in-differences models, our results indicate after the CAAA designation for PM2.5 in 2005, PM2.5 levels decreased 1.59 micrograms per cubic meter (95% CI = 1.39, 1.80) and mortality rates among those 65 and older decreased by 0.93% (95% CI = 0.10%, 1.77%) in nonattainment counties, relative to attainment ones. Results are robust to a series of alternate models, including nearest-neighbor matching based on propensity score estimates.

CONCLUSION: This analysis suggests large health returns to the 2005 PM2.5 designations, and provides evidence of a causal association between pollution and mortality among the Medicare population.

Abstract  Various approaches have been proposed to model PM2.5 in the recent decade, with satellite-derived aerosol optical depth, land-use variables, chemical transport model predictions, and several meteorological variables as major predictor variables. Our study used an ensemble model that integrated multiple machine learning algorithms and predictor variables to estimate daily PM2.5 at a resolution of 1 km × 1 km across the contiguous United States. We used a generalized additive model that accounted for geographic difference to combine PM2.5 estimates from neural network, random forest, and gradient boosting. The three machine learning algorithms were based on multiple predictor variables, including satellite data, meteorological variables, land-use variables, elevation, chemical transport model predictions, several reanalysis datasets, and others. The model training results from 2000 to 2015 indicated good model performance with a 10-fold cross-validated R2 of 0.86 for daily PM2.5 predictions. For annual PM2.5 estimates, the cross-validated R2 was 0.89. Our model demonstrated good performance up to 60 μg/m3. Using trained PM2.5 model and predictor variables, we predicted daily PM2.5 from 2000 to 2015 at every 1 km × 1 km grid cell in the contiguous United States. We also used localized land-use variables within 1 km × 1 km grids to downscale PM2.5 predictions to 100 m × 100 m grid cells. To characterize uncertainty, we used meteorological variables, land-use variables, and elevation to model the monthly standard deviation of the difference between daily monitored and predicted PM2.5 for every 1 km × 1 km grid cell. This PM2.5 prediction dataset, including the downscaled and uncertainty predictions, allows epidemiologists to accurately estimate the adverse health effect of PM2.5. Compared with model performance of individual base learners, an ensemble model would achieve a better overall estimation. It is worth exploring other ensemble model formats to synthesize estimations from different models or from different groups to improve overall performance.

Abstract  Background: Long-term exposure to particulate matter <2.5 µm in diameter (PM2.5) and ozone has been associated with the development and progression of cardiovascular disease and, in the case of PM2.5, higher cardiovascular mortality. Whether exposure to PM2.5 and ozone is associated with patients' health status and quality of life is unknown. We used data from 2 prospective myocardial infarction (MI) registries to assess the relationship between long-term PM2.5 and ozone exposure with health status outcomes 1 year after an MI. Methods and Results: TRIUMPH (Translational Research Investigating Underlying Disparities in Acute Myocardial Infarction) and PREMIER (Prospective Registry Evaluating Myocardial Infarction: Events and Recovery) enrolled patients presenting with MI at 31 US hospitals between 2003 and 2008. One year later, patients were assessed with the disease-specific Seattle Angina Questionnaire, and 5-year mortality was assessed with the Centers for Disease Control's National Death Index. Individual patients' exposures to PM2.5 and ozone over the year after their MI were estimated from the Environment Protection Agency's Fused Air Quality Surface Using Downscaling tool that integrates monitoring station data and atmospheric models to predict daily air pollution exposure at the census tract level. We assessed the association of exposure to ozone and PM2.5 with 1-year health status and mortality over 5 years using regression models adjusting for age, sex, race, socioeconomic status, date of enrollment, and comorbidities. In completely adjusted models, higher PM2.5 and ozone exposure were independently associated with poorer Seattle Angina Questionnaire summary scores at 1-year (β estimate per +1 SD increase =-0.8 [95% CI, -1.4 to -0.3; P=0.002] for PM2.5 and -0.9 [95% CI, -1.3 to -0.4; P<0.001] for ozone). Moreover, higher PM2.5 exposure, but not ozone, was independently associated with greater mortality risk (hazard ratio =1.13 per +1 SD [95% CI, 1.07-1.20; P<0.001]). Conclusions: In our study, greater exposure to PM2.5 and ozone was associated with poorer 1-year health status following an MI, and PM2.5 was associated with increased risk of 5-year death.

Abstract  INTRODUCTION: Effects of more than one-year exposure to air pollution on atherosclerosis is seldom studied. This paper aims to examine the association between five-year exposure to particulate matter ≤2.5 μm (PM2.5), ozone (O3) and atherosclerosis observed about seven years later in late midlife women.

MATERIAL AND METHODS: This study was conducted among 1188 women of the Study of Women's Health Across the Nation (SWAN) from five sites, Detroit, MI; Oakland, CA; Pittsburgh, PA; Chicago, IL; and Newark, NJ, with available data on both air pollutant exposure and carotid ultrasound scans. Five-year mean annualized exposure levels of two air pollutants, PM2.5 and ozone (O3), were collected during 5 SWAN visits (1999-2005) from monitors 20 km within the participant's residential address. Linear regression models were used to estimate the association of prior five-year mean annualized exposure to PM2.5 and O3 with common carotid intima-media thickness (cIMT) and inter-adventitial diameter (IAD) examined approximately seven years later (2009-2013). Logistic and multinomial logistic regressions were applied to assess the associations of air pollutants with plaque presence and plaque index, respectively.

RESULTS: At time of carotid ultrasound scan, women were on average 59.6 (±2.7) years old and a majority was postmenopausal (88.4%). The women were White (48.4%), Black (31.2%), Chinese (13.3%) and Hispanic (7.1%). A 1 μg/m3 higher 5-year mean annualized exposure to PM2.5 was associated with an 8.0 μm (95% CI: 1.0-15.1) greater maximum cIMT at a later mid-life, adjusting for cardiovascular disease risk factors; but was only related to IAD after adjusting for site. No association was found between either pollutant and plaque presence or plaque index.

CONCLUSIONS: Long-term exposure to PM2.5 may contribute to elevated risk of atherosclerosis in the post-menopausal period.

Abstract  BACKGROUND: Although growing evidence links air pollution to stroke incidence, less is known about the effect of air pollution on atrial fibrillation (AF), an important risk factor for stroke. OBJECTIVES: We assessed the associations between air pollution and incidence of AF and stroke. We also sought to characterize the shape of pollutant–disease relationships. METHODS: The population-based cohort comprised 5,071,956 Ontario residents, age 35–85 y and without the diagnoses of both outcomes on 1 April 2001 and was followed up until 31 March 2015. AF and stroke cases were ascertained using health administrative databases with validated algorithms. Based on annual residential postal codes, we assigned 5-y running average concentrations of fine particulate matter (PM2:5), nitrogen dioxide (NO2), and ozone (O3) from satellite-derived data, a land-use regression model, and a fusion-based method, respectively, as well as redox-weighted averages of NO2 and O3 (Ox) for each year. Using Cox proportional hazards models, we estimated the hazard ratios (HRs) and 95% confidence intervals (95% CIs) of AF and stroke with each of these pollutants, adjusting for individual- and neighborhood-level variables. We used newly developed nonlinear risk models to characterize the shape of pollutant–disease relationships. RESULTS: Between 2001 and 2015, we identified 313,157 incident cases of AF and 122,545 cases of stroke. Interquartile range increments of PM2:5, NO2, O3, and Ox were associated with increases in the incidence of AF [HRs (95% CIs): 1.03 (1.01, 1.04), 1.02 (1.01, 1.03), 1.01 (1.00, 1.02), and 1.01 (1.01, 1.02), respectively] and the incidence of stroke [HRs (95% CIs): 1.05 (1.03, 1.07), 1.04 (1.01, 1.06), 1.05 (1.03, 1.06), and 1.05 (1.04, 1.06), respectively]. Associations of similar magnitude were found in various sensitivity analyses. Furthermore, we found a near-linear association for stroke with PM2:5, whereas Ox-stroke, PM2:5-, and Ox-AF relationships exhibited sublinear shapes. CONCLUSIONS: Air pollution was associated with stroke and AF onset, even at very low concentrations. https://doi.org/10.1289/EHP4883

Abstract  Rationale: Growing evidence suggests that long-term exposure to fine particulate matter (PM2.5) air pollution contributes to risk of cardiovascular disease (CVD) morbidity and mortality. There is uncertainty regarding who are most susceptible. Individuals with underlying cardiometabolic disorders, including hypertension, diabetes, and obesity, may be at greater risk. PM2.5 pollution may also contribute to cardiometabolic disorders, augmenting CVD risk. Objective: This analysis evaluates relationships between long-term PM2.5 exposure and cardiometabolic disease on risk of death from CVD and cardiometabolic conditions. Methods and Results: Data on 669,046 participants from the American Cancer Society, Cancer Prevention Study II cohort were linked to modeled PM2.5 concentrations at geocoded home addresses. Cox proportional hazards regression models were used to estimate adjusted hazards ratios (HR) for death from CVD and cardiometabolic diseases based on death-certificate information. Effect modification by pre-existing cardiometabolic risk factors on the PM2.5-CVD mortality association was examined. PM2.5 exposure was associated with CVD mortality, with the HR (95% CI) per 10 µg/m(3) increase in PM2.5 equal to 1.12 (1.10-1.15). Deaths linked to hypertension and/or diabetes (mentioned on death certificate as either primary or contributing cause of death) were also associated with PM2.5. There was no consistent evidence of effect modification by cardiometabolic disease risk factors on the PM2.5-CVD mortality association. Conclusions: Pollution-induced CVD mortality risk is observed for those with and without existing cardiometabolic disorders. Long-term exposure may also contribute to the development or exacerbation of cardiometabolic disorders, increasing risk of CVD and cardiometabolic disease mortality.

Abstract  We used a geographically weighted regression (GWR) statistical model to represent bias of fine particulate matter concentrations (PM2.5) derived from a 1 km optimal estimate (OE) aerosol optical depth (AOD) satellite retrieval that used AOD-to-PM2.5 relationships from a chemical transport model (CTM) for 2004-2008 over North America. This hybrid approach combined the geophysical understanding and global applicability intrinsic to the CTM relationships with the knowledge provided by observational constraints. Adjusting the OE PM2.5 estimates according to the GWR-predicted bias yielded significant improvement compared with unadjusted long-term mean values (R(2) = 0.82 versus R(2) = 0.62), even when a large fraction (70%) of sites were withheld for cross-validation (R(2) = 0.78) and developed seasonal skill (R(2) = 0.62-0.89). The effect of individual GWR predictors on OE PM2.5 estimates additionally provided insight into the sources of uncertainty for global satellite-derived PM2.5 estimates. These predictor-driven effects imply that local variability in surface elevation and urban emissions are important sources of uncertainty in geophysical calculations of the AOD-to-PM2.5 relationship used in satellite-derived PM2.5 estimates over North America, and potentially worldwide.

Abstract  OBJECTIVE: Long-term exposure to traffic and particulate matter air pollution is associated with a higher risk of cardiovascular disease, potentially via atherosclerosis promotion. Prior research on associations of traffic and particulate matter with coronary artery calcium Agatston score (CAC), an atherosclerosis correlate, has yielded inconsistent findings. Given this background, we assessed whether residential proximity to major roadway or fine particulate matter were associated with CAC in a Northeastern US study.

APPROACH AND RESULTS: We measured CAC ≤2 times from 2002 to 2005 and 2008 to 2011 among Framingham Offspring or Third-Generation Cohort participants. We assessed associations of residential distance to major roadway and residential fine particulate matter (2003 average; spatiotemporal model) with detectable CAC, using generalized estimating equation regression. We used linear mixed effects models to assess associations with loge(CAC). We also assessed associations with CAC progression. Models were adjusted for demographic variables, socioeconomic position markers, and time. Among 3399 participants, 51% had CAC measured twice. CAC was detectable in 47% of observations. At first scan, mean age was 52.2 years (standard deviation 11.7); 51% male. There were no consistent associations with detectable CAC, continuous CAC, or CAC progression. We observed heterogeneous associations of distance to major roadway with odds of detectable CAC by hypertensive status; interpretation of these findings is questionable.

CONCLUSIONS: Our findings add to prior work and support evidence against strong associations of traffic or fine particulate matter with the presence, extent, or progression of CAC in a region with relatively low levels of and little variation in fine particulate matter.

Abstract  Epidemiologic studies on acute effects of air pollution have generally been limited to larger cities, leaving questions about rural populations behind. Recently, we had developed a spatiotemporal model to predict daily PM2.5 level at a 1 km(2) using satellite aerosol optical depth (AOD) data. Based on the results from the model, we applied a case-crossover study to evaluate the acute effect of PM2.5 on mortality in North Carolina, South Carolina, and Georgia between 2007 and 2011. Mortality data were acquired from the Departments of Public Health in the States and modeled PM2.5 exposures were assigned to the zip code of residence of each decedent. We performed various stratified analyses by age, sex, race, education, cause of death, residence, and environmental protection agency (EPA) standards. We also compared results of analyses using our modeled PM2.5 levels and those imputed daily from the nearest monitoring station. 848,270 non-accidental death records were analyzed and we found each 10 μg/m(3) increase in PM2.5 (mean lag 0 and lag 1) was associated with a 1.56% (1.19 and 1.94) increase in daily deaths. Cardiovascular disease (2.32%, 1.57-3.07) showed the highest effect estimate. Blacks (2.19%, 1.43-2.96) and persons with education ≤8 year (3.13%, 2.08-4.19) were the most vulnerable populations. The effect of PM2.5 on mortality still exists in zip code areas that meet the PM2.5 EPA annual standard (2.06%, 1.97-2.15). The effect of PM2.5 below both EPA daily and annual standards was 2.08% (95% confidence interval=1.99-2.17). Our results showed more power and suggested that the PM2.5 effects on rural populations have been underestimated due to selection bias and information bias. We have demonstrated that our AOD-based exposure models can be successfully applied to epidemiologic studies. This will add new study populations in rural areas, and will confer more generalizability to conclusions from such studies.Journal of Exposure Science and Environmental Epidemiology advance online publication, 26 August 2015; doi:10.1038/jes.2015.47.

Abstract  Visible Multifilter Rotating Shadowband Radiometer (vis-MFRSR) data were collected at Storm Peak Laboratory (SPL), a mountain-top facility in northwest Colorado, from 1999 to 2011 and in 2013. From 2011 to 2014, in situ measurements of aerosol light scattering were also obtained. Using these data sets together, the seasonal impact of dust and biomass burning is considered for the western USA. Analysis indicates that the median contributions to spring and summer aerosol optical depth (AOD) from dust and biomass-burning aerosols across the data set are comparable. The mean AOD is slightly greater in the summer, with significantly more frequent and short-duration high AOD measurements due to biomass-burning episodes than in the spring. The angstrom ngstrom exponent showed a significant increase in the summer for both the in situ and vis-MFRSR data, suggesting an increase in combustion aerosols. Spring dust events are less distinguishable in the in situ data than the column measurement, suggesting that a significant amount of dust may be found above the elevation of SPL, 3220 ma.s.l. Twenty-two known case studies of intercontinental dust, regional dust, and biomass-burning events were investigated. These events were found to follow a similar pattern, in both aerosol loading and angstrom ngstrom exponent, as the seasonal mean signal in both the vis-MFRSR and ground-based nephelometer. This data set highlights the wide-scale implications of a warmer, drier climate on visibility in the western USA.

Abstract  Mounting evidence over the past several decades has demonstrated inequitable distribution of pollutants of ambient origin between sociodemographic groups in the United States. Most environmental inequality studies to date are cross-sectional and used proximity-based methods rather than modeled air pollution concentrations, limiting the ability to examine trends over time or the factors that drive exposure inequalities. In this paper, we use 1km2 modeled PM2.5 and NO2 concentrations in Massachusetts over an 8-year period and Census demographic data to quantify inequality between sociodemographic groups and to develop a more nuanced understanding of the drivers and trends in longitudinal air pollution inequality. Annual-average population-weighted PM2.5 and NO2 concentrations were highest for urban non-Hispanic black populations (11.8µg/m3 in 2003 and 8.4µg/m3 in 2010, vs. 11.3µg/m3 and 8.1µg/m3 for urban non-Hispanic whites) and urban Hispanic populations (15.9 ppb in 2005 and 13.0 ppb in 2010, vs. 13.0 ppb and 10.2 ppb for urban non-Hispanic whites), respectively. While population groups experienced similar absolute decreases in exposure over time, disparities in population-weighted concentrations increased over time when quantified by the Atkinson Index, a relative inequality measure. Exposure inequalities were approximately one order of magnitude greater for NO2 compared to PM2.5, were more pronounced in urban compared to rural geographies, and between racial/ethnic groups compared to income and educational attainment groups. Our results also revealed similar longitudinal PM2.5 and NO2 inequality trends using Census 2000 and Census 2010 data, indicating that spatio-temporal shifts in air pollution may best explain observed trends in inequality. These findings enhance our understanding of factors that contribute to persistent inequalities and underscore the importance of targeted exposure reduction strategies aimed at vulnerable populations and neighborhoods.

Abstract  The impact of chronic exposure to fine particulate matter (PM2.5) on respiratory disease and lung cancer mortality is poorly understood. In a cohort of 18.9 million Medicare beneficiaries (4.2 million deaths) living across the conterminous United States between 2000 to 2008, we examined the association of chronic PM2.5 exposure and cause-specific mortality, and evaluated confounding through adjustment of neighborhood behavioral covariates and decomposition of PM2.5 into two spatiotemporal scales. We found significantly positive associations of 12-month moving average PM2.5 exposures (per 10 ug/m3 increase) with respiratory, chronic obstructive pulmonary disease and pneumonia mortality, with risk ratios ranging from 1.10 to 1.24. We also found significant PM2.5-associated elevated risks for cardiovascular-related and lung cancer mortality. Risk ratios generally increased with longer moving averages; e.g., elevation in 60-month moving averaged PM2.5 exposures was linked to 1.33 times the lung cancer mortality risk (95% confidence interval: 1.24, 1.40), as compared to 1.13 (95% confidence interval: 1.11, 1.15) for 12-month moving averaged exposures. Observed associations were robust in multivariable models, although evidence of unmeasured confounding remained. In our large cohort of American elderly, we provide important new evidence that long-term PM2.5 exposure is significantly related to increased respiratory-, lung cancer and cardiovascular-related mortality.

Abstract  BACKGROUND: The effect of air pollution exposure on atherosclerosis severity or incident clinical events in patients with coronary artery disease is not known.

METHODS AND RESULTS: We conducted a prospective longitudinal cohort study of 6575 Ohio residents undergoing elective diagnostic coronary angiography. Multinomial regression and Cox proportional hazards models were used to assess the relationship between exposure to fine particulate matter <2.5 μm in diameter (PM2.5) and nitrogen dioxide on coronary artery disease severity at baseline and risk of myocardial infarction, stroke, or all-cause mortality over 3 years of follow-up. Among participants with coronary artery disease, exposure to PM2.5 levels was associated with increased likelihood of having coronary atherosclerosis that was mild (odds ratio 1.43, 95% CI 1.11-1.83, P=0.005) and severe (odds ratio 1.63, 95% CI 1.26-2.11, P<0.0001), with the effect on severe coronary artery disease being significantly increased compared with mild disease (Ptrend=0.03). Exposure to higher PM2.5 levels was also significantly associated with increased risk of incident myocardial infarction (hazard ratio 1.33, 95% CI 1.02-1.73, P=0.03) but not stroke or all-cause mortality. The association of PM2.5 with incident myocardial infarction was not affected after adjustment for Framingham Adult Treatment Panel III (ATP III) risk score or statin therapy. In comparison, there were no significant associations between nitrogen dioxide levels and all-cause mortality or risk of stroke after adjustment for Framingham ATP III risk score.

CONCLUSIONS: Exposure to PM2.5 increased the likelihood of having severe coronary artery disease and the risk of incident myocardial infarction among patients undergoing elective cardiac evaluation. These results suggest that ambient air pollution exposure may be a modifiable risk factor for risk of myocardial infarction in a highly susceptible patient population.