2009 Progress Report: Johns Hopkins Particulate Matter Research Center

EPA Grant Number: R832417
Center: Johns Hopkins Particulate Matter Research Center
Center Director: Samet, Jonathan M.
Title: Johns Hopkins Particulate Matter Research Center
Investigators: Samet, Jonathan M. , Breysse, Patrick N. , Chillrud, Steven , Dominici, Francesca , Garcia, Joe , Ondov, John M.
Institution: The Johns Hopkins University , University of Chicago , University of Maryland , Yale University
Current Institution: The Johns Hopkins University , Columbia University (Lamont Doherty Earth Observatory) (JHPMRC) , University of Chicago , University of Maryland , Yale University
EPA Project Officer: Chung, Serena
Project Period: October 1, 2005 through September 30, 2010
Project Period Covered by this Report: October 1, 2008 through September 30,2009
Project Amount: $7,993,275
RFA: Particulate Matter Research Centers (2004) RFA Text |  Recipients Lists
Research Category: Health Effects , Air

Objective:

The Johns Hopkins Center for Particulate Matter (PM) Research has an agenda targeted towards identifying those characteristics of particles that determine the risk of PM to health.  This topic was highlighted as a key area of research need by the National Research Council’s Committee on Research Priorities for Airborne Particulate Matter.  More complete understanding of this topic is needed, if there is to be a shift away from mass-based standards for PM towards approaches that target the most toxic particles and the sources of these particles. 

The Center’s approach is inherently multidisciplinary, interweaving epidemiology, exposure assessment and atmospheric monitoring, and toxicology.  We use the epidemiological evidence on risks to health as the focal point for the Center’s work.  Underlying our approach is the hypothesis that differences in particle characteristics contribute to the variation of the health risks of PM across the United States.  In the Center’s work, we first characterized this heterogeneity of the risks to health of PM across the country and then used it as the basis for establishing a sampling frame for selecting locations for both detailed PM characterization and for collection of bulk samples of PM, both PM2.5 and PM10-2.5.  The PM samples will be evaluated for toxicity in murine models of two human diseases, asthma and congestive heart failure, associated with susceptibility to PM.  In these models, we anticipate finding similar indications of toxicity across the samples, as found in the epidemiological analyses.  Together, the detailed PM characterization and the bioassay results should lead to more focused hypotheses with regard to particular components that can be tested in further studies.

To accomplish this research agenda, the Johns Hopkins Center includes three component projects.  The first (Project 1) involves analyses of data bases of national scope on PM exposure and risk for hospitalization and mortality and on geographic and seasonal variation in the components of PM, as monitored by the EPA’s Speciation Trends  Network (STN).  Project 2 investigators have developed the suite of monitoring equipment to be brought to locations identified in Project 1 and a cyclone device for collecting a substantial mass of particles for analysis and use in bioassays.  Project 3 involves the development of bioassays for assessing the particles collected in Project 2.  In a later phase of its research, the Center investigators will test more focused hypotheses using epidemiological and toxicological approaches, as well as carrying out exposure assessment studies directed at specific PM components. 

Progress Summary:

Together, the three project teams have set the foundation for meeting the overall Center goal.  Project 1 has previously characterized the variation in the PM-associated risk for hospitalization and mortality across the country and also analyzed the available data from the STN for the years 2000-2005.  These analyses were critical to the selection of locations for PM collection and monitoring Project 2.  The variability of PM mass across the 203 counties covered was largely accounted for by seven components, suggesting that the 52 components assessed by the STN, some tightly co-varying spatially and temporally, share sources.  The seven were sulfate, nitrate, silicon, elemental carbon (EC), organic carbon matter (OCM), sodium ion, and ammonium ion. These seven components, in aggregate, constituted 83% of the total PM2.5 mass, whereas all other components individually contributed less than one percent. Ambient levels of EC and OCM, which are generated primarily from vehicle emissions, diesel, and wood burning, were associated with the largest risks of emergency hospitalization across the major chemical constituents of PM2.5. for Bayesian model averaging using clustered data; during the past year Project 1 focused on a number of methodological issues. These include accounting for Exposure Measurement Error in estimating acute health effects or coarse particulate matter; imputing missing PM data; and proposing a new study design and a statistical model, which uses spatio-temporal information to estimate the long-term effects of air pollution exposure on  life expectancy.

Project 1 estimated the relative risk of death in a U.S. population of elderly associated with long-term exposure to PM2.5 by region and age-groups, for the period 2000-2005. Chronic exposure to PM2.5 was associated with mortality in the eastern and central regions, but not in the western U.S.

The Environmental Protection Agency has considered regulation for one size-specific component of PM, PM10-2.5—so-called “coarse” PM.  Evidence on the risks of PM10-2.5 has been limited and consequently we used the Medicare data set to explore risk for hospitalization associated with PM10-2.5, finding weak evidence as to whether PM10-2.5 has an independent association with risk, after taking account of PM2.5 concentration.

There was substantial variation in the makeup of the PM, both spatially and temporally.  Using the Medicare data base for cardiovascular and respiratory admissions, the Project 1 investigators also found geographic variation in risks for hospitalization for these diseases; distributions of risk were defined within five broad geographical regions of the country and from the locations, counties were selected that were at the high and low ends.  This analysis confirmed overall significant variation in risks across the country and provided the sampling frame for selecting the monitoring sites to be visited by Project 2.   The nine monitoring sites were:  1) King WA, 2) Sacramento CA, 3) Maricopa AZ, 4) Hennepin MN, 5) Harris TX, 6) Allegheny PA, 6) Jefferson KY, 8) Kings KY, 9) Pinellas FL.

To refine understanding of how PM characteristics determine risk, we need to be able to have a substantial mass of particles for chemical and physical characterization and for testing in biological assays that give insights into comparative toxicity of different samples and opportunities to explore the mechanistic basis of the effects of PM.  The collection of PM is complicated by the potential to alter the PM as a consequence of the action of the collecting device, by the difficulty of collecting the small particles, termed “ultrafine” or PM0.1 and by the unavoidable loss of volatile and semi-volatile components.  Our approach, which utilizes a custom-made sequential cyclone operating at a high collection volume, recognizes these difficulties and provides the compromise of collection of several  grams of PM over a one-month period; we have a known loss of PM0.1 and cannot avoid the volatilization of components over the month-long collection period.  On the other hand, the samples are collected in a standardized fashion, along with detailed monitoring, in all locations.  The protocol for field monitoring and collection has been tested and sampling and collection have not been carried out at seven locations.

During the last year Project 2 completed monitoring and bulk sample collection in Hennepin/Anoka County, MN); Harris County, TX; Pinellas County, FL; and Jefferson County, KY.  Analysis of all coarse and fine bulk PM and PM10 and PM2.5 samples from all locations visited to date have been analyzed for anions, 24 metals, and elemental carbon (PM2.5 only). All bulk and filter PM samples have been analyzed for platinum group elements. All bulk fine PM has been analyzed by XANES/EXFAS at the National Synchontron Light Source for oxidation states of manganese, iron, and chromium.

Finally, Bulk fine PM from all locations visited to date has been delivered to Project 3.

For control of the health effects of PM, regulators need to know if all particles, regardless of source have similar or differing profiles of toxicity.  In Project 3, the investigators have developed a set of bioassays for this purpose.  Initially, they carried out in vitro (cell system) assays with human lung epithelial and endothelial cells and already collected samples of PM from Baltimore.  These experiments pointed to the diverse mechanisms by which PM may trigger biological responses.  Two in vivo (mouse) models of human disease will be used to compare the toxicity of PM samples collected in the various locations identified in Project 1, and sampled by Project 2: one is a long-used mouse model of asthma that uses the asthma-susceptible AJ mouse strain and involves the induction of asthma by ovalbumin; and the second is a mouse model of cardiomyopathy that leads to congestive heart failure, a prevalent human disease that conveys susceptibility to PM.  In the initial phase of development of the bioassays, the existing Baltimore PM samples were used.  The models were characterized as to their responsiveness to PM and the nature of dose-response relationships with the instilled PM.  Work in progress is pursuing molecular signatures of the effects of PM using genomic approaches. 

Using bulk Pm collected by Project 2 in Baltimore, Project 3 has demonstrated a dose-dependent effect of Baltimore PM on airway hyperresponsiveness (AHR), BAL protein, and BAL inflammatory leukocytes infiltration in both asthmatic and naïve animals. Interestingly, fine-PM from Maricopa county, compared to Sacramento, induced a significantly higher level of AHR, and infiltration of white blood cell count, including neutrophils and  eosinophils into the alveolar space; however, no difference in BAL protein (protein leak) between PM collected from the two the two locations was observed. We also demonstrated a differential effect of fine-PM from Maricopa and Sacramento on regulation of gene expression in the murine model of Asthma.

With respect to the mouse model of cardiomyopathy, our studies demonstrate that fine-PM exaggerates cardiac arrhythmias and respiratory dysynchrony in mice with heart failure via heightened carotid body sensitivity.

A number of papers have been prepared as part of this project.  These are desribed below.

  1. Estimating the Acute Health Effects of Coarse Particulate Matter Accounting for Exposure Measurement Error

    In Chang et al (2009) (submitted), we develop a modeling approach for estimating the short-term effects of air pollution in time series analysis when the ambient concentrations vary spatially within the study region. Among Medicare enrollees from 59 U.S. counties between the period 1999 to 2005, we find a consistent positive association between coarse PM and same-day admission for cardiovascular diseases.

    Ref: Chang H, Peng R, Dominici F A Model Approach for Estimating the Acute Health Effects of Coarse Particulate Matter Accounting for Exposure Measurement Error.

  2. Mortality in the Medicare Population and Chronic Exposure to Fine Particulate Air Pollution in Urban Centers (2000-2005)

    In Zeger et al (2009), we estimate the relative risk of death in a U.S. population of elderly associated with long-term exposure to PM2.5  by region and age-groups, for the period 2000-2005. By linking fine particulate matter (PM2.5) monitoring data to the Medicare billing claims  by zip code of residence of the enrollees, we have developed a new retrospective cohort study, the Medicare Cohort Air Pollution Cohort Study. The study population comprises 13.2 million participants living in 4,568 zip codes having centroids within 6 miles of a PM2.5 monitor. In the East and Central regions, a 10 µg/m3 increase in six year average of PM2.5 is associated with a 6.8% (95% CI: 4.9 to 8.7%) and 13.2% (95% CI: 9.5 to 16.9) increases in mortality, respectively. We did not find evidence of an association in the West and for persons above 85 years of age.  We established a cohort of Medicare participants for investigating air pollution and mortality on longer-term time frames.  Chronic exposure to PM2.5 was associated with mortality in the eastern and central regions, but not in the western U.S.

    Ref: Zeger SL,  Dominici F, McDermott A, Samet JM  (2008) Mortality in the Medicare Population and Chronic Exposure to Fine Particulate Matter,  Environmental Health Perspectives 116,1614–1619 .

  3. Bayesian Model Averaging for Clustered data: Imputing Missing PM Data

    In Chang et al (2009) (submitted) we have developed an innovative statistical methodology for imputing missing PM2.5 data when PM10 data from the co-located monitor is available (and vice versa). We assume that the two daily time series of PM10 and PM2.5 from the pair of collocated monitors form a data cluster.  The goal is to best predict the missing PM data at the co-located monitor pair in presence of multiple competing prediction models. In the presence of multiple competing models, Bayesian model averaging (BMA) offers a powerful tool to account for model uncertainty and improve prediction. However, the typical application of BMA to clustered data determines model weights (posterior probabilities of the competing models) by comparing how data from all clusters fit each model.  In Chang et al 2009 we develop a BMA approach for clustered data that accounts for differences in the best-fitting models among clusters. This is accomplished by allowing the weights of competing regression models to vary between clusters while borrowing information across clusters in estimating model parameters. The work is motivated by the problem of imputing missing observations in clustered data when the performance of different prediction models varies across clusters. Through simulation and cross-validation studies, we demonstrate that our approach outperforms the standard BMA. Finally, we apply the proposed method to a national dataset of daily ambient particulate matter concentrations between 2003 and 2005. We then estimate the posterior probability of coarse PM nonattainment status for 95 US counties based on the Environmental Protection Agency’s proposed 24-hour standard. .

    Ref:   Chang H, Peng R, Dominici F, Bayesian Model Averaging For Clustered Data (Student Paper Award Winner, 2009 Eastern North American Region/International Biometric Society, Student Paper Award Winner, 2009 American Statistical Association Health Policy & Statistics Section’s).

  4. Spatio-Temporal Approach for Estimating Chronic  Effects of Air Pollution

    Estimating the health risks associated with air pollution exposure is of great importance in public health. In air pollution epidemiology, two study designs have been used mainly. Time series studies estimate acute risk associated with short- term exposure. They compare day-to- day variation of pollution concentrations and mortality rates, and have been criticized for potential confounding by time- varying covariates. Cohort studies estimate chronic effects associated with long- term exposure. They compare long-term average pollution concentrations and time-to-death across cities, and have been criticized for potential confounding by individual risk factors or city-level characteristics.

    In Greven et al, we propose a new study design and a statistical model, which use spatio-temporal information to estimate the long-term effects of air pollution exposure on  life expectancy. Our approach avoids confounding by time-varying covariates and individual or city- level risk factors. By estimating the increase in life expectancy due to decreases in long-term air pollution concentrations, it provides easily interpretable values for public policy purposes. We develop a suitable backfitting algorithm that permits efficient fitting of our model to large spatio-temporal data sets. We evaluate spatio-temporal correlation in the data and obtain appropriate standard errors. We apply our methods to the Medicare Cohort Air Pollution Study, including data on fine particulate matter (PM2.5) and mortality for 18.2 million Medicare enrollees from 814 locations in the U.S. during an average of 65 months in 2000-2006.

    Ref: Greven S, Dominici F, Zeger SL A Spatio-Temporal Approach for Estimating the Chronic Effects of Air Pollution.

Future Activities:

The Johns Hopkins PM Center has a unifying goal and draws on a multidisciplinary group of investigators to address this goal.  In its first four years, it has completed a comprehensive set of analyses of variation in the components of PM across the STN and in variation in the risks of hospitalization associated with PM—PM2.5, PM10-2.5, and components of PM.  Overall, the results support the hypothesis that PM risks vary with characteristics, thereby supporting the rationale for our overall approach.  We have also developed the PM monitoring and collection methods and are in the process of monitoring the selected sites across the country.  Furthermore, we have demonstrated important differences in PM-toxicity for PM collected at two of the monitoring sites.

Within the remaining time, we anticipate completing the PM monitoring and collection and having much of the bioassay work done.  At that point, we will have an understanding of whether there are differing particle characteristics at places where differing risks to health have been observed epidemiologically.  If they do, the animal models could prove to be quite useful for assessing mechanisms of toxicity. 

In the last phase of the Center’s work, we anticipate the development and testing of more refined hypotheses for future research.  We will continue to use multidisciplinary approaches. 


Journal Articles: 64 Displayed | Download in RIS Format

Other center views: All 89 publications 66 publications in selected types All 64 journal articles
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Journal Article Anderson BG, Bell ML. Weather-related mortality: how heat, cold, and heat waves affect mortality in the United States. Epidemiology 2009;20(2):205-213. R832417 (Final)
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  • Journal Article Anderson GB, Bell ML. Heat waves in the United States: mortality risk during heat waves and effect modification by heat wave characteristics in 43 U.S. communities.Environmental Health Perspectives 2011;119(2):210-218. R832417 (Final)
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  • Journal Article Anderson GB, Bell ML. Lights out: impact of the August 2003 power outage on mortality in New York, NY. Epidemiology 2012;23(2):189-193. R832417 (Final)
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  • Journal Article Barr CD, Dominici F. Comment on article by Craigmile et al. Bayesian Analysis 2009;4(1):37-40. R832417C001 (2009)
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  • Journal Article Barr CD, Dominici F. Cap and trade legislation for greenhouse gas emissions: public health benefits from air pollution mitigation. JAMA-Journal of the American Medical Association 2010;303(1):69-70. R832417 (Final)
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  • Journal Article Barr CD, Diez DM, Wang Y, Dominici F, Samet JM. Comprehensive smoking bans and acute myocardial infarction among Medicare enrollees in 387 US counties:1999–2008. American Journal of Epidemiology 2012;176(7):642-648. R832417 (Final)
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  • Journal Article Bell ML, Peng RD, Dominici F. The exposure-response curve for ozone and risk of mortality and the adequacy of current ozone regulations. Environmental Health Perspectives 2006;114(4):532-536. R832417 (Final)
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  • Journal Article Bell ML, Dominici F, Ebisu K, Zeger SL, Samet JM. Spatial and temporal variation in PM2.5 chemical composition in the United States for health effects studies. Environmental Health Perspectives 2007;115(7):989-995. R832417 (Final)
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  • Journal Article Bell ML, Kim JY, Dominici F. Potential confounding of particulate matter on the short-term association between ozone and mortality in multisite time-series studies. Environmental Health Perspectives 2007;115(11):1591-1595. R832417 (Final)
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  • Journal Article Bell ML, Dominici F. Effect modification by community characteristics on the short-term effects of ozone exposure and mortality in 98 US communities. American Journal of Epidemiology 2008;167(8):986-997. R832417 (Final)
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  • Journal Article Bell ML, Ebisu K, Peng RD, Walker J, Samet JM, Zeger SL, Dominici F. Seasonal and regional short-term effects of fine particles on hospital admissions in 202 US counties, 1999-2005. American Journal of Epidemiology 2008;168(11):1301-1310. R832417 (2008)
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  • Journal Article Bell ML, Ebisu K, Peng RD, Samet JM, Dominici F. Hospital admissions and chemical composition of fine particle air pollution. American Journal of Respiratory and Critical Care Medicine 2009;179(12):1115-1120. R832417 (Final)
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  • Journal Article Bell ML, Peng RD, Dominici F, Samet JM. Emergency hospital admissions for cardiovascular diseases and ambient levels of carbon monoxide: results for 126 United States urban counties, 1999-2005. Circulation 2009;120(11):949-955. R832417 (Final)
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  • Journal Article Bell ML, Ebisu K, Peng RD, Dominici F. Adverse health effects of particulate air pollution: modification by air conditioning. Epidemiology 2009;20(5):682-686. R832417 (Final)
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  • Journal Article Bell ML, Belanger K, Ebisu K, Gent JF, Lee HJ, Koutrakis P, Leaderer BP. Prenatal exposure to fine particulate matter and birth weight: variations by particulate constituents and sources. Epidemiology 2010;21(6):884-891. R832417 (Final)
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  • Journal Article Bell ML, Ebisu K, Peng RD. Community-level spatial heterogeneity of chemical constituent levels of fine particulates and implications for epidemiological research. Journal of Exposure Science & Environmental Epidemiology 2011;21(4):372-384. R832417 (Final)
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  • Journal Article Bell ML, Belanger K, Ebisu K, Gent JF, Leaderer BP. Relationship between birth weight and exposure to airborne fine particulate potassium and titanium during gestation. Environmental Research 2012;117:83-89. R832417 (Final)
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  • Journal Article Bobb JF, Dominici F, Peng RD. A Bayesian model averaging approach for estimating the relative risk of mortality associated with heat waves in 105 U.S. cities. Biometrics 2011;67(4):1605-1616. R832417 (Final)
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  • Journal Article Chang HH, Peng RD, Dominici F. Estimating the acute health effects of coarse particulate matter accounting for exposure measurement error. Biostatistics 2011;12(4):637-652. R832417 (Final)
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  • Journal Article Crainiceanu CM, Dominici F, Parmigiani G. Adjustment uncertainty in effect estimation. Biometrika 2008;95(3):635-651. R832417 (Final)
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  • Journal Article Datta S, Rule AM, Mihalic JN, Chillrud SN, Bostick BC, Ramos-Bonilla JP, Han I, Polyak LM, Geyh AS, Breysse PN. Use of X-ray absorption spectroscopy to speciate manganese in airborne particulate matter from five counties across the United States. Environmental Science & Technology 2012;46(6):3101-3109. R832417 (Final)
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  • Journal Article Dominici F, Peng RD, Bell ML, Pham L, McDermott A, Zeger SL, Samet JM. Fine particulate air pollution and hospital admission for cardiovascular and respiratory diseases. JAMA-Journal of the American Medical Association 2006;295(10):1127-1134. R832417 (Final)
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  • Journal Article Dominici F, Peng RD, Ebisu K, Zeger SL, Samet JM, Bell ML. Does the effect of PM10 on mortality depend on PM nickel and vanadium content? A reanalysis of the NMMAPS data. Environmental Health Perspectives 2007;115(12):1701-1703. R832417 (Final)
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  • Journal Article Dominici F, Peng RD, Zeger SL, White RH, Samet JM. Dominici et al. respond to "Heterogeneity of particulate matter health risks." American Journal of Epidemiology 2007;166(8):892-893. R832417 (2008)
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  • Journal Article Dominici F, Peng RD, Zeger SL, White RH, Samet JM. Particulate air pollution and mortality in the United States: did the risks change from 1987 to 2000? American Journal of Epidemiology 2007;166(8):880-888. R832417 (Final)
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  • Journal Article Dominici F, Wang C, Crainiceanu C, Parmigiani G. Model selection and health effect estimation in environmental epidemiology. Epidemiology 2008;19(4):558-560. R832417 (2008)
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  • Journal Article Dominici F, Peng RD, Barr CD, Bell ML. Protecting human health from air pollution: shifting from a single-pollutant to a multipollutant approach. Epidemiology 2010;21(2):187-194. R832417 (Final)
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  • Journal Article Eftim SE, Samet JM, Janes H, McDermott A, Dominici F. Fine particulate matter and mortality: a comparison of the six cities and American Cancer Society cohorts with a Medicare cohort. Epidemiology 2008;19(2):209-216. R832417 (2008)
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  • Journal Article Greven S, Dominici F, Zeger S. An approach to the estimation of chronic air pollution effects using spatio-temporal information. Journal of the American Statistical Association 2011;106(494):396-406. R832417 (Final)
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  • Journal Article Han I, Ramos-Bonilla JP, Rule AM, Mihalic JN, Polyak LM, Breysse PN, Geyh AS. Comparison of spatial and temporal variations in p-PAH, BC, and p-PAH/BC ratio in six US counties. Atmospheric Environment 2011;45(40):7644-7652. R832417 (Final)
    R832417C002 (Final)
  • Full-text: ScienceDirect-Full Text HTML
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  • Journal Article Han I, Mihalic JN, Ramos-Bonilla JP, Rule AM, Polyak LM, Peng RD, Geyh AS, Breysse PN. Assessment of heterogeneity of metal composition of fine particulate matter collected from eight U.S. counties using principal component analysis. Journal of the Air & Waste Management Association 2012;62(7):773-782. R832417 (Final)
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  • Full-text: Taylor&Francis-Full Text HTML
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  • Journal Article Heaton MJ, Peng RD. Flexible distributed lag models using random functions with application to estimating mortality displacement from heat-related deaths. Journal of Agricultural Biological and Environmental Statistics 2012;17(3):313-331. R832417 (Final)
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  • Journal Article Janes H, Dominici F, Zeger S. Partitioning evidence of association between air pollution and mortality. Epidemiology 2007;18(4):427-428. R832417 (2008)
    R832417 (Final)
    R832417C001 (2008)
    R832417C001 (2009)
    R832417C001 (Final)
    R833622 (2008)
    R833622 (2009)
    R833622 (Final)
  • Full-text: Epidemiology-Full Text HTML
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  • Journal Article Janes H, Dominici F, Zeger SL. Trends in air pollution and mortality: an approach to the assessment of unmeasured confounding. Epidemiology 2007;18(4):416-423. R832417 (Final)
    R832417C001 (2006)
    R832417C001 (2007)
    R832417C001 (2008)
    R832417C001 (2009)
    R832417C001 (Final)
    R830548 (Final)
    R833622 (Final)
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  • Abstract: Epidemiology-Abstract
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  • Journal Article Janes H, Dominici F, Zeger S. On quantifying the magnitude of confounding. Biostatistics 2010;11(3):572-582. R832417 (Final)
    R832417C001 (Final)
    R833622 (Final)
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  • Full-text: Biostatistics-Full Text HTML
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  • Abstract: Biostatistics-Abstract
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  • Journal Article Krall JR, Anderson GB, Dominici F, Bell ML, Peng RD. Short-term exposure to particulate matter constituents and mortality in a national study of U.S. urban communities. Environmental Health Perspectives 2013;121(10):1148-1153. R832417 (Final)
    R834798 (2013)
    R834798 (2014)
    R834798 (Final)
    R834798C005 (Final)
    R834894 (Final)
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  • Journal Article Levy JI, Diez D, Dou Y, Barr CD, Dominici F. A meta-analysis and multisite time-series analysis of the differential toxicity of major fine particulate matter constituents. American Journal of Epidemiology 2012;175(11):1091-1099. R832417 (Final)
    R832416C001 (Final)
    R834798 (2012)
    R834798 (2013)
    R834798 (2014)
    R834798 (2015)
    R834798 (Final)
    R834798C001 (2014)
    R834798C005 (2012)
    R834798C005 (Final)
    R834894 (2012)
    R834894 (2013)
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  • Full-text: AJE-Full Text HTML
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  • Journal Article Mauderly JL, Samet JM. Is there evidence for synergy among air pollutants in causing health effects? Environmental Health Perspectives 2009;117(1):1-6. R832417 (Final)
    CR831455 (Final)
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  • Journal Article Peng RD, Dominici F, Louis TA. Model choice in time series studies of air pollution and mortality. Journal of the Royal Statistical Society Series A-Statistics in Society 2006;169(2):179-203. R832417 (Final)
    R832417C001 (2006)
    R832417C001 (2007)
    R832417C001 (2008)
    R830548 (Final)
  • Full-text: Wiley-Full Text HTML
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  • Journal Article Peng RD, Dominici F, Zeger SL. Reproducible epidemiological research. American Journal of Epidemiology 2006;163(9):783-789. R832417 (Final)
    R832417C001 (2006)
    R832417C001 (2007)
    R832417C001 (2008)
    R832417C001 (2009)
    R832417C001 (Final)
    R830548 (Final)
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  • Journal Article Peng RD, Chang HH, Bell ML, McDermott A, Zeger SL, Samet JM, Dominici F. Coarse particulate matter air pollution and hospital admissions for cardiovascular and respiratory diseases among Medicare patients. JAMA-Journal of the American Medical Association 2008;299(18):2172-2179. R832417 (2008)
    R832417 (Final)
    R832417C001 (2008)
    R832417C001 (2009)
    R832417C001 (Final)
    R833622 (2008)
    R833622 (2009)
    R833622 (Final)
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  • Journal Article Peng RD. A Method for Visualizing Multivariate Time Series Data. Journal of Statistical Software 2008;25(Code Snippet 1):1-17 R832417 (2008)
    not available
    Journal Article Peng RD, Dominici F, Welty LJ. A Bayesian hierarchical distributed lag model for estimating the time course of risk of hospitalization associated with particulate matter air pollution. Journal of the Royal Statistical Society Series C--Applied Statistics 2009;58(1):3-24. R832417 (2008)
    R832417 (Final)
    R832417C001 (2009)
    R832417C001 (Final)
    R833622 (Final)
  • Full-text: JohnsHopkins-Prepublication Full Text PDF
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  • Abstract: Wiley-Abstract
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  • Journal Article Peng RD, Bell ML, Geyh AS, McDermott A, Zeger SL, Samet JM, Dominici F. Emergency admissions for cardiovascular and respiratory diseases and the chemical composition of fine particle air pollution. Environmental Health Perspectives 2009;117(6):957-963. R832417 (Final)
    R832417C001 (2009)
    R832417C001 (Final)
    R833622 (Final)
    R833863 (2009)
    R833863 (Final)
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  • Journal Article Peng RD, Bell ML. Spatial misalignment in time series studies of air pollution and health data. Biostatistics 2010;11(4):720-740. R832417 (Final)
    R832417C001 (Final)
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  • Journal Article Peng RD, Bobb JF, Tebaldi C, McDaniel L, Bell ML, Dominici F. Toward a quantitative estimate of future heat wave mortality under global climate change. Environmental Health Perspectives 2011;119(5):701-706. R832417 (Final)
    R833622 (Final)
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  • Journal Article Ramos-Bonilla JP, Breysse PN, Dominici F, Geyh A, Tankersley CG. Ambient air pollution alters heart rate regulation in aged mice. Inhalation Toxicology 2010;22(4):330-339. R832417 (Final)
    R832417C002 (Final)
  • Abstract from PubMed
  • Abstract: Taylor and Francis-Abstract
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  • Journal Article Rava M, White RH, Dominici F. Does attainment status for the PM10 National Air Ambient Quality Standard change the trend in ambient levels of particulate matter? Air Quality, Atmosphere & Health 2011;4(2):133-143. R832417 (Final)
    R832417C001 (Final)
    R833622 (2009)
    R833622 (Final)
  • Abstract: Springer-Abstract
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  • Journal Article Rule AM, Geyh AS, Ramos-Bonilla JP, Mihalic JN, Margulies JD, Polyak LM, Kesavan J, Breysse PN. Design and characterization of a sequential cyclone system for the collection of bulk particulate matter. Journal of Environmental Monitoring 2010;12(10):1807-1814. R832417 (Final)
    R832139 (Final)
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  • Journal Article Samet JM. Air pollution risk estimates: Determinants of heterogeneity. Journal of Toxicology and Environmental Health-Part A-Current Issues 2008;71(9-10):578-582 R832417 (2008)
    not available
    Journal Article Symons JM, Wang L, Guallar E, Howell E, Dominici F, Schwab M, Ange BA, Samet J, Ondov J, Harrison D, Geyh A. A case-crossover study of fine particulate matter air pollution and onset of congestive heart failure symptom exacerbation leading to hospitalization. American Journal of Epidemiology 2006;164(5):421-433. R832417 (Final)
    R832417C001 (2006)
    R832417C001 (2007)
    R832417C001 (2008)
    R832417C001 (2009)
    R832417C001 (Final)
    R830548 (Final)
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  • Journal Article Thomas DC, Jerrett M, Kuenzli N, Louis TA, Dominici F, Zeger S, Schwartz J, Burnett RT, Krewski D, Bates D. Bayesian model averaging in time-series studies of air pollution and mortality. Journal of Toxicology and Environmental Health-Part A 2007;70(3-4):311-315. R832417 (Final)
    R832417C001 (2007)
    R832417C001 (2008)
    R832417C001 (2009)
    R832417C001 (Final)
    R830548 (Final)
    R831861 (2005)
  • Abstract from PubMed
  • Abstract: Taylor&Francis-Abstract
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  • Journal Article Venturini S, Dominici F, Parmigiani G. Gamma shape mixtures for heavy-tailed distributions. The Annals of Applied Statistics 2008;2(2):756-776. R832417 (2007)
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  • Journal Article Wang C, Parmigiani G, Dominici F. Bayesian effect estimation accounting for adjustment uncertainty. Biometrics 2012;68(3):661-671. R832417 (Final)
    R832416 (Final)
    R833622 (Final)
    R834798 (2012)
    R834798 (2013)
    R834798 (2014)
    R834798 (Final)
    R834798C005 (2012)
    R834798C005 (2013)
    R834798C005 (Final)
    R834894 (2012)
    R834894 (2013)
  • Abstract from PubMed
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  • Journal Article Wang T, Moreno-Vinasco L, Huang Y, Lang GD, Linares JD, Goonewardena SN, Grabavoy A, Samet JM, Geyh AS, Breysse PN, Lussier YA, Natarajan V, Garcia JGN. Murine lung responses to ambient particulate matter: genomic analysis and influence on airway hyperresponsiveness. Environmental Health Perspectives 2008;116(11):1500-1508. R832417 (2008)
    R832417 (Final)
    R832417C003 (2008)
    R832417C003 (2009)
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  • Journal Article Wang T, Chiang ET, Moreno-Vinasco L, Lang GD, Pendyala S, Samet JM, Geyh AS, Breysse PN, Chillrud SN, Natarajan V, Garcia JGN. Particulate matter disrupts human lung endothelial barrier integrity via ROS-and p38 MAPK-dependent pathways. American Journal of Respiratory Cell and Molecular Biology 2010;42(4):442-449. R832417 (Final)
    R832417C003 (2009)
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  • Journal Article Wang T, Lang GD, Moreno-Vinasco L, Huang Y, Goonewardena SN, Peng YJ, Svensson EC, Natarajan V, Lang RM, Linares JD, Breysse PN, Geyh AS, Samet JM, Lussier YA, Dudley S, Prabhakarz NR, Garcia JGN. Particulate matter induces cardiac arrhythmias via dysregulation of carotid body sensitivity and cardiac sodium channels. American Journal of Respiratory Cell and Molecular Biology 2012;46(4):524-531. R832417 (Final)
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  • Journal Article Wang T, Wang L, Moreno-Vinasco L, Lang GD, Siegler JH, Mathew B, Usatyuk PV, Samet JM, Geyh AS, Breysse PN, Natarajan V, Garcia JGN. Particulate matter air pollution disrupts endothelial cell barrier via calpain-mediated tight junction protein degradation. Particle and Fibre Toxicology 2012;9:35 (12 pp.). R832417 (Final)
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  • Journal Article Wang T, Wang L, Zaidi SR, Sammani S, Siegler J, Moreno-Vinasco L, Mathew B, Natarajan V, Garcia JG. Hydrogen sulfide attenuates particulate matter-induced human lung endothelial barrier disruption via combined reactive oxygen species scavenging and Akt activation. American Journal of Respiratory Cell and Molecular Biology 2012;47(4):491-496. R832417 (Final)
    R832417C003 (Final)
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  • Journal Article Welty LJ, Peng RD, Zeger SL, Dominici F. Bayesian distributed lag models: estimating effects of particulate matter air pollution on daily mortality. Biometrics 2009;65(1):282-291. R832417 (2008)
    R832417 (Final)
    R832417C001 (2009)
    R832417C001 (Final)
    R833622 (Final)
  • Abstract from PubMed
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  • Journal Article Zeger SL, Dominici F, McDermott A, Samet JM. Mortality in the Medicare population and chronic exposure to fine particulate air pollution in urban centers (2000–2005). Environmental Health Perspectives 2008;116(12):1614-1619. R832417 (2008)
    R832417 (2009)
    R832417 (Final)
    R832417C001 (2009)
    R832417C001 (Final)
    R833622 (2008)
    R833622 (2009)
    R833622 (Final)
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  • Journal Article Zhao Y, Usatyuk PV, Gorshkova IA, He D, Wang T, Moreno-Vinasco L, Geyh AS, Breysse PN, Samet JM, Spannhake EW, Garcia JGN, Natarajan V. Regulation of COX-2 expression and IL-6 release by particulate matter in airway epithelial cells. American Journal of Respiratory Cell and Molecular Biology 2009;40(1):19-30. R832417 (2008)
    R832417 (Final)
    R832417C003 (2008)
    R832417C003 (2009)
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  • Journal Article Zhou Y, Dominici F, Louis TA. Racial disparities in risks of mortality in a sample of the US Medicare population. Journal of the Royal Statistical Society: Series C (Applied Statistics) 2010;59(2):319-339. R832417 (2007)
  • Abstract: Wiley Online-Abstract
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  • Journal Article Zigler CM, Dominici F, Wang Y. Estimating causal effects of air quality regulations using principal stratification for spatially correlated multivariate intermediate outcomes. Biostatistics 2012;13(2):289-302. R832417 (Final)
    R833622 (Final)
    R834798 (2012)
    R834798 (2013)
    R834798 (2014)
    R834798C005 (2012)
    R834798C005 (2013)
    R834894 (2012)
    R834894 (2013)
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  • Supplemental Keywords:

    RFA, Health, Scientific Discipline, Air, particulate matter, Environmental Chemistry, Health Risk Assessment, Risk Assessments, atmospheric particulate matter, cardiopulmonary responses, chemical characteristics, epidemiology, human health effects, toxicology, lung epithelial cells, cardiovascular vulnerability, exposure, airborne particulate matter, pulmonary toxicity, particle exposure, biological mechanisms, endothelial function, pariculate matter, cardiopulmonary mechanisms, human exposure, particulate exposure, ambient particle health effects, ultrafine particulate matter, respiratory impact, PM, cardiotoxicity, particulate matter components, cardiovascular disease, human health risk

    Progress and Final Reports:

    Original Abstract
  • 2006 Progress Report
  • 2007 Progress Report
  • 2008 Progress Report
  • Final Report
  • Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
    R832417C001 Estimation of the Risks to Human Health of PM and PM Components
    R832417C002 PM Characterization and Exposure Assessment (Project 2)
    R832417C003 Biological Assessment of the Toxicity of PM and PM Components