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Although concentrations of ambient air pollution continue to decline in high-income regions, epidemiological studies document adverse health effects at levels below current standards in many countries. The Health Effects Institute (HEI) recently completed a comprehensive research initiative to investigate the health effects of long-term exposure to low levels of air pollution in the United States (U.S.), Canada, and Europe. We provide an overview and synthesis of the results of this initiative along with other key research, the strengths and limitations of the research, and remaining research needs. The three studies funded through the HEI initiative estimated the effects of long-term ambient exposure to fine particulate matter (PM 2.5 ), nitrogen dioxide, ozone, and other pollutants on a broad range of health outcomes, including cause-specific mortality and cardiovascular and respiratory morbidity. To ensure high quality research and comparability across studies, HEI worked actively with the study teams and engaged independent expert panels for project oversight and review. All three studies documented positive associations between mortality and exposure to PM 2.5 below the U.S. National Ambient Air Quality Standards and current and proposed European Union limit values. Furthermore, the studies observed nonthreshold linear (U.S.), or supra-linear (Canada and Europe) exposure-response functions for PM 2.5 and mortality. Heterogeneity was found in both the magnitude and shape of this association within and across studies. Strengths of the studies included the large populations (7-69 million), state-of-the-art exposure assessment methods, and thorough statistical analyses that applied novel methods. Future work is needed to better understand potential sources of heterogeneity in the findings across studies and regions. Other areas of future work include the changing and evolving nature of PM components and sources, including wildfires, and the role of indoor environments. This research initiative provided important new evidence of the adverse effects of long-term exposures to low levels of air pollution at and below current standards, suggesting that further reductions could yield larger benefits than previously anticipated.

Background/aim: Industrial-scale animal feeding operations (AFOs) have adverse impacts on regional air quality. Air emissions include endotoxins and other pro-inflammatory components, and exposure may cause airway inflammation and respiratory effects in susceptible individuals residing nearby. We aimed to develop and validate metrics for estimating time-varying exposure to AFO air pollution in surrounding communities and, secondly, to determine whether exposure is associated with health effects in children with asthma., Methods: We conducted a longitudinal panel study of N = 58 children with asthma in an agricultural region of Washington State with a high density of dairy AFOs. Children were followed for up to 26 months with repeated measures of respiratory health (N = 2023 interviews; N = 3853 lung function measurements); urine was collected in a subcohort (N = 16) at six-day intervals over three months and analyzed for leukotriene E4 (LTE4), a biomarker of systemic inflammation (N = 138 measurements). We developed an approach to estimate daily exposure to AFO airborne emissions based on distance to AFOs, AFO size, and daily wind speed and direction, and validated the estimates against direct measurements of ammonia, a chemical marker of AFO emissions, measured biweekly at 18 sites across the region for 14 months. Short-term relationships between AFO pollutant exposure and outcomes were assessed using regression models accounting for within-participant correlation and several potential confounders., Results: Estimates of daily AFO air pollution correlated moderately well with outdoor ammonia measurements (N = 842; r = 0.62). Forced expiratory volume in 1 s (FEV 1 ) as percent of predicted was 2.0% (95% CI: 0.5, 3.5) lower with each interquartile increase in previous day exposure, but no associations with asthma symptoms were observed. There was suggestive evidence that LTE4 concentrations were higher following days of elevated exposure to AFO emissions (p = 0.06)., Conclusions: A simple metric of time-varying exposure to AFO emissions was correlated with daily outdoor ammonia levels. Children with asthma may be adversely affected by exposure to AFO emissions., (Copyright © 2019 Elsevier GmbH. All rights reserved.)

Background: Long-term ozone ([Formula: see text]) exposure is associated with cardiovascular mortality, but little is known about the associations between [Formula: see text] and subclinical arterial disease., Objectives: We studied the longitudinal association of exposure to [Formula: see text] and progression of key subclinical arterial markers in adults: intima-media thickness of common carotid artery ([Formula: see text]), carotid plaque (CP) burden, and coronary artery calcification (CAC)., Methods: CAC was measured one to four times at baseline and at follow-up exams (1999–2012) by computed tomography (CT) in 6,619 healthy adults, recruited at age 45-84 y without cardiovascular disease (CVD), over a mean of 6.5 y (standard deviation: 3.5 y). [Formula: see text] and CP burden were quantified in 3,392 participants using carotid artery ultrasound imaging acquired over a mean of 9 y (1.7 y). Over 91% and 89% participants had at least one follow-up [Formula: see text] and CAC measurement, respectively. Residence-specific [Formula: see text] concentrations were estimated by a validated spatiotemporal model spanning from 1999 to 2012. This model relied on comprehensive monitoring data and geographical variables to predict individualized long-term average concentrations since baseline. Linear mixed models and logistic regression model were used to evaluate relationships of long-term average exposure to [Formula: see text] with longitudinal change in [Formula: see text], CAC, and CP formation, respectively., Results: Mean progression rates of [Formula: see text] and CAC were [Formula: see text] and [Formula: see text]. CP formation was identified in 55% of the subjects. A [Formula: see text] increase in long-term average [Formula: see text] exposure was associated with a [Formula: see text] [95% confidence interval (CI): 1.4, 9.7] greater increase in [Formula: see text] over 10 y. A [Formula: see text] increase in [Formula: see text] was also associated with new CP formation [odds ratio (OR): 1.2 (95% CI: 1.1, 1.4)] but not CAC progression [[Formula: see text] (95% CI: [Formula: see text], 2)]. Associations were robust in the analysis with extended covariate adjustment, including copollutants, i.e., nitrogen oxides ([Formula: see text]) and particulate matter with diameter [Formula: see text] ([Formula: see text])., Conclusion: Over almost a decade of follow-up, outdoor [Formula: see text] concentrations were associated with increased rate of carotid wall thickness progression and risk of new plaque formation, suggesting arterial injury in this cohort. https://doi.org/10.1289/EHP3325.

Background: Autonomic nervous system effects have been hypothesized as a mechanism of air pollutant health effects, though scant prior epidemiologic research has examined the association between air pollutants and catecholamines., Objectives: To examine the association of long-term air pollutants with three urinary catecholamines: dopamine (DA), epinephrine (EPI), and norepinephrine (NE). As a secondary aim, we also examined the association between short-term (or acute) exposure to fine particulate matter [particulate matter with aerodynamic diameter [Formula: see text] ([Formula: see text])] and those catecholamines., Methods: We used data from the Multi-Ethnic Study of Atherosclerosis (MESA) and two of its ancillary studies, the MESA Air Pollution Study and the MESA Stress Study, to provide exposure and outcome data. DA, EPI, and NE from urine samples were collected from 2004 to 2006 from 1,002 participants in the New York, New York, and Los Angeles, California, study sites. Spatiotemporal models incorporated cohort-specific monitoring and estimated annual average pollutant concentrations ([Formula: see text], [Formula: see text], [Formula: see text] and black carbon) at participants' homes the year prior to urine collection. Secondarily, short-term [Formula: see text] was evaluated (day of, day prior, and 2- to 5-d lags prior to urine collection). Several covariates were considered confounders (age, race, sex, site, socioeconomic status, cardiovascular disease risk factors, psychosocial stressors, and medication use) in linear regression models., Results: A [Formula: see text] higher annual [Formula: see text] concentration was associated with 6.3% higher mean EPI level [95% confidence interval (CI): 0.3%, 12.6%]. A 2-[Formula: see text] higher annual ambient [Formula: see text] concentration was associated with 9.1% higher mean EPI (95% CI: 3.2%, 15.3%) and 4.4% higher DA level (95% CI: 1%, 7.9%). [Formula: see text], black carbon, and short-term [Formula: see text] exposures were not significantly associated with any of the catecholamines., Conclusions: We found an association between EPI and long-term concentrations of [Formula: see text] and [Formula: see text] and an association between DA and long-term ambient [Formula: see text]. These novel findings provide modest support for the hypothesis that air pollutant exposures are related to sympathetic nervous system activation. https://doi.org/10.1289/EHP3286.

Objectives: We aim to characterize the qualities of estimation approaches for individual exposure to ambient-origin fine particulate matter (PM 2.5 ), for use in epidemiological studies., Methods: The analysis incorporates personal, home indoor, and home outdoor air monitoring data and spatio-temporal model predictions for 60 participants from the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). We compared measurement-based personal PM 2.5 exposure with several measured or predicted estimates of outdoor, indoor, and personal exposures., Results: The mean personal 2-week exposure was 7.6 (standard deviation 3.7) µg/m 3 . Outdoor model predictions performed far better than outdoor concentrations estimated using a nearest-monitor approach (R = 0.63 versus R = 0.43). Incorporating infiltration indoors of ambient-derived PM 2.5 provided better estimates of the measurement-based personal exposures than outdoor concentration predictions (R = 0.81 versus R = 0.63) and better scaling of estimated exposure (mean difference 0.4 versus 5.4 µg/m 3 higher than measurements), suggesting there is value to collecting data regarding home infiltration. Incorporating individual-level time-location information into exposure predictions did not increase correlations with measurement-based personal exposures (R = 0.80) in our sample consisting primarily of retired persons., Conclusions: This analysis demonstrates the importance of incorporating infiltration when estimating individual exposure to ambient air pollution. Spatio-temporal models provide substantial improvement in exposure estimation over a nearest monitor approach.

No cohort studies in China on the health effects of long-term air pollution exposure have employed exposure estimates at the fine spatial scales desirable for cohort studies with individual-level health outcome data. Here we assess an array of modern air pollution exposure estimation approaches for assigning within-city exposure estimates in Beijing for individual pollutants and pollutant sources to individual members of a cohort. Issues considered in selecting specific monitoring data or new monitoring campaigns include: needed spatial resolution, exposure measurement error and its impact on health effect estimates, spatial alignment and compatibility with the cohort, and feasibility and expense. Sources of existing data largely include administrative monitoring data, predictions from air dispersion or chemical transport models and remote sensing (specifically satellite) data. New air monitoring campaigns include additional fixed site monitoring, snapshot monitoring, passive badge or micro-sensor saturation monitoring and mobile monitoring, as well as combinations of these. Each of these has relative advantages and disadvantages. It is concluded that a campaign in Beijing that at least includes a mobile monitoring component, when coupled with currently available spatio-temporal modeling methods, should be strongly considered. Such a campaign is economical and capable of providing the desired fine-scale spatial resolution for pollutants and sources., Competing Interests: The authors declare no conflicts of interest.

We studied whether ambient air pollution is associated with interstitial lung abnormalities (ILAs) and high attenuation areas (HAAs), which are qualitative and quantitative measurements of subclinical interstitial lung disease (ILD) on computed tomography (CT).We performed analyses of community-based dwellers enrolled in the Multi-Ethnic Study of Atherosclerosis (MESA) study. We used cohort-specific spatio-temporal models to estimate ambient pollution (fine particulate matter (PM 2.5 ), nitrogen oxides (NO x ), nitrogen dioxide (NO 2 ) and ozone (O 3 )) at each home. A total of 5495 participants underwent serial assessment of HAAs by cardiac CT; 2671 participants were assessed for ILAs using full lung CT at the 10-year follow-up. We used multivariable logistic regression and linear mixed models adjusted for age, sex, ethnicity, education, tobacco use, scanner technology and study site.The odds of ILAs increased 1.77-fold per 40 ppb increment in NO x (95% CI 1.06 to 2.95, p = 0.03). There was an overall trend towards an association between higher exposure to NO x and greater progression of HAAs (0.45% annual increase in HAAs per 40 ppb increment in NO x ; 95% CI -0.02 to 0.92, p = 0.06). Associations of ambient fine particulate matter (PM 2.5 ), NO x and NO 2 concentrations with progression of HAAs varied by race/ethnicity (p = 0.002, 0.007, 0.04, respectively, for interaction) and were strongest among non-Hispanic white people.We conclude that ambient air pollution exposures were associated with subclinical ILD., Competing Interests: Conflict of interest: Disclosures can be found alongside this article at erj.ersjournals.com, (The content of this work is not subject to copyright. Design and branding are copyright ©ERS 2017.)

Tools to assess time-location patterns related to environmental exposures have expanded from reliance on time-location diaries (TLDs) and questionnaires to use of geospatial location devices such as data-logging Global Positioning System (GPS) equipment. The Multi-Ethnic Study of Atherosclerosis and Air Pollution obtained typical time-location patterns via questionnaire for 6424 adults in six US cities. At a later time (mean 4.6 years after questionnaire), a subset (n=128) participated in high-resolution data collection for specific 2-week periods resulting in concurrent GPS and detailed TLD data, which were aggregated to estimate time spent in various microenvironments. During these 2-week periods, participants were observed to spend the most time at home indoors (mean of 78%) and a small proportion of time in-vehicle (mean of 4%). Similar overall patterns were reported by these participants on the prior questionnaire (mean home indoors: 75%; mean in-vehicle: 4%). However, individual micro-environmental time estimates measured over specific 2-week periods were not highly correlated with an individual's questionnaire report of typical behavior (Spearman's ρ of 0.43 for home indoors and 0.39 for in-vehicle). Although questionnaire data about typical time-location patterns can inform interpretation of long-term epidemiological analyses and risk assessment, they may not reliably represent an individual's short-term experience.

Background: Long-term exposure to ambient particulate matter (PM) has been previously linked with higher risk of cardiovascular events. This association may be mediated, at least partly, by increasing the risk of incident hypertension, a key determinant of cardiovascular risk. However, whether long-term exposure to PM is associated with incident hypertension remains unclear., Methods: Using national geostatistical models incorporating geographic covariates and spatial smoothing, we estimated annual average concentrations of residential fine (PM 2.5 ), respirable (PM 10 ), and course (PM 10-2.5 ) fractions of particulate matter among 44,255 post-menopausal women free of hypertension enrolled in the Women's Health Initiative (WHI) clinical trials. We used time-varying Cox proportional hazards models to evaluate the association between long-term average residential pollutant concentrations and incident hypertension, adjusting for potential confounding by sociodemographic factors, medical history, neighborhood socioeconomic measures, WHI study clinical site, clinical trial, and randomization arm., Results: During 298,383 person-years of follow-up, 14,511 participants developed incident hypertension. The adjusted hazard ratios per interquartile range (IQR) increase in PM 2.5 , PM 10 , and PM 10-2.5 were 1.13 (95% CI: 1.08, 1.17), 1.06 (1.03, 1.10), and 1.01 (95% CI: 0.97, 1.04), respectively. Statistically significant concentration-response relationships were identified for PM 2.5 and PM 10 fractions. The association between PM 2.5 and hypertension was more pronounced among non-white participants and those residing in the Northeastern United States., Conclusions: In this cohort of post-menopausal women, ambient fine and respirable particulate matter exposures were associated with higher incidence rates of hypertension. These results suggest that particulate matter may be an important modifiable risk factor for hypertension., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Background: Long-term fine particulate matter (PM2.5) exposure is linked with cardiovascular disease, and disadvantaged status may increase susceptibility to air pollution-related health effects. In addition, there are concerns that this association may be partially explained by confounding by socioeconomic status (SES)., Objectives: We examined the roles that individual- and neighborhood-level SES (NSES) play in the association between PM2.5 exposure and cardiovascular disease., Methods: The study population comprised 51,754 postmenopausal women from the Women's Health Initiative Observational Study. PM2.5 concentrations were predicted at participant residences using fine-scale regionalized universal kriging models. We assessed individual-level SES and NSES (Census-tract level) across several SES domains including education, occupation, and income/wealth, as well as through an NSES score, which captures several important dimensions of SES. Cox proportional-hazards regression adjusted for SES factors and other covariates to determine the risk of a first cardiovascular event., Results: A 5 μg/m3 higher exposure to PM2.5 was associated with a 13% increased risk of cardiovascular event [hazard ratio (HR) 1.13; 95% confidence interval (CI): 1.02, 1.26]. Adjustment for SES factors did not meaningfully affect the risk estimate. Higher risk estimates were observed among participants living in low-SES neighborhoods. The most and least disadvantaged quartiles of the NSES score had HRs of 1.39 (95% CI: 1.21, 1.61) and 0.90 (95% CI: 0.72, 1.07), respectively., Conclusions: Women with lower NSES may be more susceptible to air pollution-related health effects. The association between air pollution and cardiovascular disease was not explained by confounding from individual-level SES or NSES. Citation: Chi GC, Hajat A, Bird CE, Cullen MR, Griffin BA, Miller KA, Shih RA, Stefanick ML, Vedal S, Whitsel EA, Kaufman JD. 2016. Individual and neighborhood socioeconomic status and the association between air pollution and cardiovascular disease. Environ Health Perspect 124:1840-1847; http://dx.doi.org/10.1289/EHP199., Competing Interests: The contents of this publication are solely the responsibility of the grantee and do not necessarily represent the official views of the U.S. EPA or the NIH. Further, the U.S. EPA does not endorse the purchase of any commercial products or services mentioned in the publication. The authors declare they have no actual or potential competing financial interests.

Although cohort studies of the health effects of PM2.5 have developed exposure prediction models to represent spatial variability across participant residences, few models exist for PM2.5 components. We aimed to develop a city-specific spatio-temporal prediction approach to estimate long-term average concentrations of four PM2.5 components including sulfur, silicon, and elemental and organic carbon for the Multi-Ethnic Study of Atherosclerosis cohort, and to compare predictions to those from a national spatial model. Using 2-week average measurements from a cohort-focused monitoring campaign, the spatio-temporal model employed selected geographic covariates in a universal kriging framework with the data-driven temporal trend. Relying on long-term means of daily measurements from regulatory monitoring networks, the national spatial model employed dimension-reduced predictors using universal kriging. For the spatio-temporal model, the cross-validated and temporally-adjusted R(2) was relatively higher for EC and OC, and in the Los Angeles and Baltimore areas. The cross-validated R(2)s for both models across the six areas were reasonably high for all components except silicon. Predicted long-term concentrations at participant homes from the two models were generally highly correlated across cities but poorly correlated within cities. The spatio-temporal model may be preferred for city-specific health analyses, whereas both models could be used for multi-city studies., Competing Interests: The authors declare no conflict of interest.

Background: Large-scale animal feeding operations compromise regional air quality in the rural US through emission of pollutants, such as ammonia gas. Exposure to airborne pollution from animal feeding operations may cause pediatric asthma exacerbations in surrounding communities., Objectives: To describe spatial and temporal patterns in ambient ammonia concentrations in an agricultural region, and to investigate associations between short-term fluctuations in ammonia and subsequent changes in respiratory health in children with asthma., Methods: For 13 months in the Yakima Valley of Washington State, 14 monitors sampled ammonia in outdoor air for 24-hour periods every 6 days. School-age children with asthma (n = 51) were followed for two health outcomes: biweekly reports of asthma symptoms and quick relief medication usage, and daily measurements of forced expiratory volume in 1 second. We assessed associations between each outcome and ammonia using generalized estimating equations., Results: Twenty-four-hour ammonia concentrations varied from 0.2 to 238.1 μg/m during the study period and displayed a strong correlation with proximity to animal feeding operations. The percentage of forced expiratory volume in 1 second was 3.8% lower (95% confidence interval = 0.2, 7.3) per interquartile increase in 1-day lagged ammonia concentration and 3.0% lower (95% confidence interval = 0.5, 5.8) for 2-day lagged concentration. We observed no associations between self-reported asthma symptoms or medication usage and estimated ammonia exposure., Conclusions: Ammonia concentrations were elevated in this community and strongly predicted by proximity to animal feeding operations. Ammonia's association with acute lung function decrements in children with asthma in the surrounding community may be causal or, alternatively, ammonia may be a marker for other pollutants from animal feeding operations associated with respiratory effects.

Background: Regulatory monitoring data have been the exposure data resource most commonly applied to studies of the association between long-term PM2.5 components and health. However, data collected for regulatory purposes may not be compatible with epidemiological studies., Objectives: We studied three important features of the PM2.5 component monitoring data to determine whether it would be appropriate to combine all available data from multiple sources for developing spatiotemporal prediction models in the National Particle Component and Toxicity (NPACT) study., Methods: The NPACT monitoring data were collected in an extensive monitoring campaign targeting cohort participant residences. The regulatory monitoring data were obtained from the Chemical Speciation Network (CSN) and the Interagency Monitoring of Protected Visual Environments (IMPROVE). We performed exploratory analyses to examine features that could affect our approach to combining data: comprehensiveness of spatial coverage, comparability of analysis methods, and consistency in sampling protocols. In addition, we considered the viability of developing spatiotemporal prediction models given a) all available data, b) NPACT data only, and c) NPACT data with temporal trends estimated from other pollutants., Results: The number of CSN/IMPROVE monitors was limited in all study areas. The different laboratory analysis methods and sampling protocols resulted in incompatible measurements between networks. Given these features we determined that it was preferable to develop our spatiotemporal models using only the NPACT data and under simplifying assumptions., Conclusions: Investigators conducting epidemiological studies of long-term PM2.5 components need to be mindful of the features of the monitoring data and incorporate this understanding into the design of their monitoring campaigns and the development of their exposure prediction models.

Background: Associations of short-term exposure to fine particulate matter (PM2.5) with daily mortality may be due to specific PM2.5 chemical components. Daily concentrations of PM2.5 components were measured over five years in Denver to investigate whether specific PM2.5 components are associated with daily mortality., Methods: Daily counts of total and cause-specific deaths were obtained for the 5-county Denver metropolitan region from 2003 through 2007. Daily 24-hour concentrations of PM2.5, elemental carbon (EC), organic carbon (OC), sulfate and nitrate were measured at a central residential monitoring site. Using generalized additive models, we estimated relative risks (RRs) of daily death counts for daily PM2.5 and four PM2.5 component concentrations at single and distributed lags between the current and three previous days, while controlling for longer-term time trend and meteorology., Results: RR of total non-accidental mortality for an inter-quartile increase of 4.55 μg/m(3) in PM2.5 distributed over 4 days was 1.012 (95 % confidence interval: 0.999, 1.025); RRs for EC and OC were larger (1.024 [1.005, 1.043] and 1.020 [1.000, 1.040] for 0.33 and 1.67 μg/m(3) increases, respectively) than those for sulfate and nitrate. We generally did not observe associations with cardiovascular and respiratory mortality except for associations with ischemic heart disease mortality at lags 3 and 0-3 depending on the component. In addition, there were associations with cancer mortality, particularly for EC and OC, possibly reflecting advanced deaths of a frail population., Conclusions: PM2.5 components possibly from combustion-related sources are more strongly associated with daily mortality than are secondary inorganic aerosols.

Rationale: Limited prior data suggest an association between traffic-related air pollution and incident asthma in adults. No published studies assess the effect of long-term exposures to particulate matter less than 2.5 μm in diameter (PM2.5) on adult incident asthma., Objectives: To estimate the association between ambient air pollution exposures (PM2.5 and nitrogen dioxide, NO2) and development of asthma and incident respiratory symptoms., Methods: The Sister Study is a U.S. cohort study of risk factors for breast cancer and other health outcomes (n = 50,884) in sisters of women with breast cancer (enrollment, 2003-2009). Annual average (2006) ambient PM2.5 and NO2 concentrations were estimated at participants' addresses, using a national land-use/kriging model incorporating roadway information. Outcomes at follow-up (2008-2012) included incident self-reported wheeze, chronic cough, and doctor-diagnosed asthma in women without baseline symptoms., Measurements and Main Results: Adjusted analyses included 254 incident cases of asthma, 1,023 of wheeze, and 1,559 of chronic cough. For an interquartile range (IQR) difference (3.6 μg/m(3)) in estimated PM2.5 exposure, the adjusted odds ratio (aOR) was 1.20 (95% confidence interval [CI] = 0.99-1.46, P = 0.063) for incident asthma and 1.14 (95% CI = 1.04-1.26, P = 0.008) for incident wheeze. For NO2, there was evidence for an association with incident wheeze (aOR = 1.08, 95% CI = 1.00-1.17, P = 0.048 per IQR of 5.8 ppb). Neither pollutant was significantly associated with incident cough (PM2.5: aOR = 0.95, 95% CI = 0.88-1.03, P = 0.194; NO2: aOR = 1.00, 95% CI = 0.93-1.07, P = 0.939)., Conclusions: Results suggest that PM2.5 exposure increases the risk of developing asthma and that PM2.5 and NO2 increase the risk of developing wheeze, the cardinal symptom of asthma, in adult women.

Long-term exposure to outdoor particulate matter with an aerodynamic diameter less than or equal to 2.5 µm (PM2.5) has been associated with cardiovascular morbidity and mortality. The chemical composition of PM2.5 that may be most responsible for producing these associations has not been identified. We assessed cross-sectional associations between long-term concentrations of PM2.5 and 4 of its chemical components (sulfur, silicon, elemental carbon, and organic carbon (OC)) and subclinical atherosclerosis, measured as carotid intima-media thickness (CIMT) and coronary artery calcium, between 2000 and 2002 among 5,488 Multi-Ethnic Study of Atherosclerosis participants residing in 6 US metropolitan areas. Long-term concentrations of PM2.5 components at participants' homes were predicted using both city-specific spatiotemporal models and a national spatial model. The estimated differences in CIMT associated with interquartile-range increases in sulfur, silicon, and OC predictions from the spatiotemporal model were 0.022 mm (95% confidence interval (CI): 0.014, 0.031), 0.006 mm (95% CI: 0.000, 0.012), and 0.026 mm (95% CI: 0.019, 0.034), respectively. Findings were generally similar using the national spatial model predictions but were often sensitive to adjustment for city. We did not find strong evidence of associations with coronary artery calcium. Long-term concentrations of sulfur and OC, and possibly silicon, were associated with CIMT using 2 distinct exposure prediction modeling approaches., (© The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Studies estimating health effects of long-term air pollution exposure often use a two-stage approach: building exposure models to assign individual-level exposures, which are then used in regression analyses. This requires accurate exposure modeling and careful treatment of exposure measurement error., Objective: To illustrate the importance of accounting for exposure model characteristics in two-stage air pollution studies, we considered a case study based on data from the Multi-Ethnic Study of Atherosclerosis (MESA)., Methods: We built national spatial exposure models that used partial least squares and universal kriging to estimate annual average concentrations of four PM2.5 components: elemental carbon (EC), organic carbon (OC), silicon (Si), and sulfur (S). We predicted PM2.5 component exposures for the MESA cohort and estimated cross-sectional associations with carotid intima-media thickness (CIMT), adjusting for subject-specific covariates. We corrected for measurement error using recently developed methods that account for the spatial structure of predicted exposures., Results: Our models performed well, with cross-validated R2 values ranging from 0.62 to 0.95. Naïve analyses that did not account for measurement error indicated statistically significant associations between CIMT and exposure to OC, Si, and S. EC and OC exhibited little spatial correlation, and the corrected inference was unchanged from the naïve analysis. The Si and S exposure surfaces displayed notable spatial correlation, resulting in corrected confidence intervals (CIs) that were 50% wider than the naïve CIs, but that were still statistically significant., Conclusion: The impact of correcting for measurement error on health effect inference is concordant with the degree of spatial correlation in the exposure surfaces. Exposure model characteristics must be considered when performing two-stage air pollution epidemiologic analyses because naïve health effect inference may be inappropriate.

Background: Fine particulate matter (PM2.5) has been linked to cardiovascular disease, possibly via accelerated atherosclerosis. We examined associations between the progression of the intima-medial thickness (IMT) of the common carotid artery, as an indicator of atherosclerosis, and long-term PM2.5 concentrations in participants from the Multi-Ethnic Study of Atherosclerosis (MESA)., Methods and Results: MESA, a prospective cohort study, enrolled 6,814 participants at the baseline exam (2000-2002), with 5,660 (83%) of those participants completing two ultrasound examinations between 2000 and 2005 (mean follow-up: 2.5 years). PM2.5 was estimated over the year preceding baseline and between ultrasounds using a spatio-temporal model. Cross-sectional and longitudinal associations were examined using mixed models adjusted for confounders including age, sex, race/ethnicity, smoking, and socio-economic indicators. Among 5,362 participants (5% of participants had missing data) with a mean annual progression of 14 µm/y, 2.5 µg/m(3) higher levels of residential PM2.5 during the follow-up period were associated with 5.0 µm/y (95% CI 2.6 to 7.4 µm/y) greater IMT progressions among persons in the same metropolitan area. Although significant associations were not found with IMT progression without adjustment for metropolitan area (0.4 µm/y [95% CI -0.4 to 1.2 µm/y] per 2.5 µg/m(3)), all of the six areas showed positive associations. Greater reductions in PM2.5 over follow-up for a fixed baseline PM2.5 were also associated with slowed IMT progression (-2.8 µm/y [95% CI -1.6 to -3.9 µm/y] per 1 µg/m(3) reduction). Study limitations include the use of a surrogate measure of atherosclerosis, some loss to follow-up, and the lack of estimates for air pollution concentrations prior to 1999., Conclusions: This early analysis from MESA suggests that higher long-term PM2.5 concentrations are associated with increased IMT progression and that greater reductions in PM2.5 are related to slower IMT progression. These findings, even over a relatively short follow-up period, add to the limited literature on air pollution and the progression of atherosclerotic processes in humans. If confirmed by future analyses of the full 10 years of follow-up in this cohort, these findings will help to explain associations between long-term PM2.5 concentrations and clinical cardiovascular events.

Various methods have been developed recently to estimate personal exposures to ambient particulate matter less than 2.5 microm in diameter (PM2.5) using fixed outdoor monitors as well as personal exposure monitors. One class of estimators involves extrapolating values using ambient-source components of PM2.5, such as sulfate and iron. A key step in extrapolating these values is to correct for differences in infiltration characteristics of the component used in extrapolation (such as sulfate within PM2.5) and PM2.5. When this is not done, resulting health effect estimates will be biased. Another class of approaches involves factor analysis methods such as positive matrix factorization (PMF). Using either an extrapolation or a factor analysis method in conjunction with regression calibration allows one to estimate the direct effects of ambient PM2.5 on health, eliminating bias caused by using fixed outdoor monitors and estimated personal ambient PM2.5 concentrations. Several forms of the extrapolation method are defined, including some new ones. Health effect estimates that result from the use of these methods are compared with those from an expanded PMF analysis using data collected from a health study of asthmatic children conducted in Denver, Colorado. Examining differences in health effect estimates among the various methods using a measure of lung function (forced expiratory volume in 1 s) as the health indicator demonstrated the importance of the correction factor(s) in the extrapolation methods and that PMF yielded results comparable with the extrapolation methods that incorporated correction factors.

The number of studies conducted on the health effects of air pollution has increased exponentially. Important methodological advances include the application of novel observational study designs, in particular the multi-city design, and the development and application of airborne particle concentrators for use in experimental human exposure studies and toxicological studies. Experimental data are validating and providing insight into some surprising observational findings.

To examine hypotheses regarding air pollution health effects, we conducted an exploratory study to evaluate relationships between personal and ambient concentrations of particles with measures of cardiopulmonary health in a sample of patients with chronic obstructive pulmonary disease (COPD). Sixteen currently non-smoking COPD patients (mean age=74) residing in Vancouver were equipped with a particle (PM(2.5)) monitor for seven 24-h periods. Subjects underwent ambulatory heart monitoring, had their lung function and blood pressure (BP) measured, and recorded symptoms and medication use. Ambient PM(2.5), PM(10), sulfate, and gaseous pollutant concentrations were monitored at five sites within the study area. Although no associations between air pollution and lung function were statistically significant, an estimated effect of 3% and 1% declines in daily FEV(1) change (DeltaFEV(1)) for each 10 microg/m(3) increase in ambient PM(10) and PM(2.5), respectively, was observed. Increases of 1 microg/m(3) in personal or ambient sulfate were associated with 1.0% and 0.3% declines in DeltaFEV(1), respectively. Weak associations were observed between particle concentrations and increased supraventricular ectopic heartbeats and with decreased systolic BP. No consistent associations were observed between any particle metric and diastolic BP, heart rate, or heart rate variability (r-MSSD or SDNN), symptom severity, or bronchodilator use. Of the pollutants measured, ambient PM(10) was most consistently associated with health parameters; the use of personal exposures did not improve the strength of any associations or lead to increased effect estimates.

Linear, no-threshold relationships are typically reported for time series studies of air pollution and mortality. Since regulatory standards and economic valuations typically assume some threshold level, we evaluated the fundamental question of the impact of exposure misclassification on the persistence of underlying personal-level thresholds when personal data are aggregated to the population level in the assessment of exposure-response relationships. As an example, we measured personal exposures to two particle metrics, PM2.5 and sulfate (SO2-4), for a sample of lung disease patients and compared these with exposures estimated from ambient measurements. Previous work has shown that ambient:personal correlations for PM2.5 are much lower than for SO2-4, suggesting that ambient PM2.5 measurements misclassify exposures to PM2.5. We then developed a method by which the measured:estimated exposure relationships for these patients were used to simulate personal exposures for a larger population and then to estimate individual-level mortality risks under different threshold assumptions. These individual risks were combined to obtain the population risk of death, thereby exhibiting the prominence (and the value) of the threshold in the relationship between risk and estimated exposure. Our results indicated that for poorly classified exposures (PM2.5 in this example) population-level thresholds were apparent at lower ambient concentrations than specified common personal thresholds, while for well-classified exposures (e.g., SO2-4), the apparent thresholds were similar to these underlying personal thresholds. These results demonstrate that surrogate metrics that are not highly correlated with personal exposures obscure the presence of thresholds in epidemiological studies of larger populations, while exposure indicators that are highly correlated with... [ABSTRACT FROM AUTHOR]