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Final Report: Ambient Particle Health Effects: Exposure, Susceptibility, and Mechanisms
EPA Grant Number: R827353Center: EPA Harvard Center for Ambient Particle Health Effects
Center Director: Koutrakis, Petros
Title: Ambient Particle Health Effects: Exposure, Susceptibility, and Mechanisms
Investigators: Koutrakis, Petros , Adamkiewicz, Gary , Bateson, T. , Brown, Kathleen Ward , Christiani, David , Coull, Brent , Demokritou, Phil , Dockery, Douglas W. , Dubowsky, S. , Evans, John S. , Fox, L. , Godleski, John J. , Gold, Diane R. , Gonzalez-Flecha, Beatriz , Kobzik, Lester , Laden, Francine , Lawrence, Joy , Levy, Jonathan , Luttmann-Gibson, Heike , Mark, Teresa , O’Neill, M. , Park, S. , Ruiz, Pablo , Sarnat, Jeremy , Schwartz, Joel , Smythe, Alice , Speizer, Frank E. , Spengler, John D. , Stevens, G. , Stone, Peter , Suh, Helen H. , Tsuda, Akira , Vallarino, Jose , Verrier, Richard , Wellenius, Gregory , Wheeler, A. , Wilson, A. , Wolfson, Jack M. , Zanobetti, Antonella
Institution: Harvard University
EPA Project Officer: Stacey Katz/Gail Robarge,
Project Period: June 1, 1999 through May 31, 2005 (Extended to May 31, 2006)
Project Amount: $7,747,040
RFA: Airborne Particulate Matter (PM) Centers (1999)
Research Category: Particulate Matter
Description:
Objective:Overview
The U.S. Environmental Protection Agency (EPA) Center for Ambient Particle Health Effects at Harvard worked to address key scientific issues regarding the health effects of ambient particles. The overall strategy of this Center was to build upon both our previous and ongoing research on particle health effects. The aims of the Center reflected the National Research Council’s (NRC’s) ten highest research priorities for ambient particle research (NRC, 1998). To meet these objectives, the Center focused on the three research themes: Exposure, Susceptibility and Biological Mechanisms/Dosimetry. We also made significant methodological advances to improve our abilities to conduct exposure and health effects studies. Over the five years the EPA Center supported a large interdisciplinary research group that collaborated intensively to investigate the health effects of ambient particulate matter (PM), in accordance with the NRC’s research priorities for ambient particle research. Collectively, our projects addressed eight out of the ten research priorities included in the NRC report.
Exposure Relationships. A large data set on personal exposures and indoor and outdoor concentrations was collected for panels of susceptible individuals across the US (Sarnat, et al., 2000; Sarnat, et al., 2001; Sarnat, et al., 2002). These investigations suggest that personal exposures to particulate matter less than 2.5 μm (PM2.5) of ambient origin are highly correlated with outdoor concentrations. However, the regression slopes of personal exposures on outdoor concentrations, which are usually less than one, vary substantially depending on house characteristics, season and city climatic conditions. The strong correlations between personal and ambient concentrations were unique to PM2.5, as personal exposures to ozone (O3), sulfur dioxide (SO2) and nitrogen dioxide (NO2) were substantially lower than, and weakly correlated with, corresponding outdoor concentrations (Sarnat, et al., 2005).
Susceptible Populations. Our epidemiological studies have provided strong evidence that individuals with congestive heart failure, chronic obstructive pulmonary disease (COPD), and diabetes are at higher risk than healthy individuals (Braga, et al., 2000; Dockery, 2001; Hong, et al., 2002; Schwartz, et al., 2003; Schwartz and Bateson, 2004; Zanobetti and Schwartz, 2002; Zanobetti, et al., 2003). In an effort to understand why individuals with certain diseases are at greater risk than others, Center researchers exposed animals with cardiopulmonary diseases such as COPD and myocardial infarction to concentrated ambient particles (CAPs) (Batalha, et al., 2002; Clarke, et al., 2000). The findings of these toxicological studies support those of the epidemiological studies and provide insight about possible mechanisms responsible for the observed PM effects.
Toxic Components. Many of our CAPs animal toxicology and human panel studies have linked pulmonary and cardiovascular health outcomes to different PM components such as trace metals, elemental carbon (EC), sulfates and silicon (Batalha, et al., 2002; Clarke, et al., 2000; Saldiva, et al., 2002). Reanalysis of the Harvard Six Cities study provided strong evidence of increased toxicity associated with combustion-related PM from traffic and power plants compared to soil dust (Laden, et al., 2000).
Biological Mechanisms. We have conducted exposure studies designed to elucidate the biological mechanisms whereby PM can induce adverse health effects. Results from a series of human and animal studies showed that exposures were linked to changes in heart rate variability (HRV), arrhythmias, pulmonary inflammation and vascular dysfunction (Adamkiewicz, et al., 2004; Clancy, et al., 2002; Clarke, et al., 2000; Goodman, et al., 2004; Peters, et al., 2001).
Methodological Issues. New statistical and epidemiological methods were developed to provide the necessary tools to address challenging PM issues such as: harvesting (Schwartz, 2001; Zanobetti, et al., 2000c; Zanobetti, et al., 2003); confounding (Schwartz and Coull, 2003); dose-exposure relationships (Schwartz, 2000a; Schwartz and Zanobetti, 2000; Schwartz, 2001; Schwartz, et al., 2002); gaseous co-pollutants; and weather confounding (Braga, et al., 2000; Braga, et al., 2001; Goodman, et al., 2004; O’Neill, et al., 2003a; O’Neill, et al., 2003b; O’Neill, et al., 2003c; O’Neill, et al., 2004). Many new exposure and monitoring particle technologies were also developed under the aegis of our Center and are currently used worldwide. These include the ultrafine particle concentrator, the toxicological samplers, the miniature multi-pollutant sampler, the personal cascade impactor and the membrane diffusion denuder (Demokritou, et al., 2002b; Demokritou, et al., 2002a; Demokritou, et al., 2003; Demokritou, et al., 2002c; Demokritou, et al., 2001a; Demokritou, et al., 2002d; Demokritou, et al., 2001b; Demokritou, et al., 2004a; Demokritou, et al., 2004b).
Summary of Findings:
Introduction
The U.S. EPA Center for Ambient Particle Health Effects at Harvard worked to address key scientific issues regarding the health effects of ambient particles. The aims of the Center reflected the NRC’s ten highest research priorities for ambient particle research (NRC, 1998). To meet these objectives, the Center focused on the following three research themes: Exposure, Susceptibility, and Biological Mechanisms/Dosimetry. Theme I (Exposure) investigated human exposures to particles and gaseous co-pollutants in order to differentiate the health effects of particles from outdoor and indoor sources. This theme also quantified the effect of exposure error for fine particles and their co-pollutants on risk estimates from epidemiological studies. Theme II (Susceptibility) used innovative methods to identify individuals who are sensitive to the effects of air pollution, assessed whether these individuals are “harvested” by air pollution episodes, and measured the effect of chronic air pollution exposure on the development of chronic diseases. Through studies of animal and human subjects, Theme III (Biological Mechanisms/Dosimetry) identified the particulate components, or characteristics, and gaseous air pollutants that trigger adverse health effects, as well as differentiated biological mechanisms that may lead to fatal outcomes. Collectively, our projects addressed eight out of the ten research priorities included in the NRC report.
By building the Center around the three defined research themes, we maintained both a common focus and an integrated approach, which enabled us to address key issues relating to the health effects of ambient particles. These three themes included projects that spanned several disciplines in which our investigators have expertise. Our investigative group has been collaborating on particle health effects research for more than fifteen years.
The overall strategy of this Center was to build upon both our previous and ongoing research on particle health effects. This enabled us to maximize the use of data and resources in order to obtain the most useful scientific information to meet our objectives. We used data from previous epidemiological studies, as well as personal exposure measurements from more recent investigations as the basis for certain projects. The mechanistic and dosimetric studies were conducted in conjunction with our inhalation studies. As a result, the ambitious research portfolio outlined in this proposal was both timely and cost-effective.
Over the five years the EPA Center supported a large interdisciplinary research group that collaborated intensively to investigate the health effects of ambient PM, in accordance with the NRC’s research priorities for ambient particle research. Center research produced more than 100 peer-reviewed publications (see separate full publications list). While there were a large number of individual projects conducted under the EPA Center program, this report highlights several projects in each study theme.
THEME I: ASSESSING PARTICLE EXPOSURES FOR HEALTH EFFECTS STUDIES
A large data set on personal exposures and indoor and outdoor concentrations was collected for panels of susceptible individuals across the US (Sarnat, et al., 2000; Sarnat, et al., 2001; Sarnat, et al., 2002; Koutrakis, et al., 2005). These investigations suggest that personal exposures to PM2.5 of ambient origin are highly correlated with outdoor concentrations. However, the regression slopes of personal exposures on outdoor concentrations, which are usually less than one, vary substantially depending on house characteristics, season, and city climatic conditions. The strong correlations between personal and ambient concentrations were unique to PM2.5, as personal exposures to O3, SO2 and NO2 were substantially lower than, and weakly correlated with, corresponding outdoor concentrations (Sarnat, et al., 2005).
The primary focus of Theme I was to assess human exposures to particles and gaseous co-pollutants in order to better understand their heath effects. As such, research conducted as part of Theme I contained five main objectives:
- to characterize the inter- and intra- variability in personal particulate and gaseous exposures;
- to identify factors affecting the relationship between personal exposures and outdoor levels;
- to determine the contribution of outdoor and indoor particles to personal particulate exposures;
- to quantify the effect of measurement error for fine particles and their co-pollutants (coarse mass and the criteria gases) on risk estimates from epidemiological studies; and
- to differentiate the health effects of particles from outdoor and indoor sources.
These objectives were addressed by three inter-related research projects, which made use of our database of personal, indoor, and outdoor particulate and gaseous exposures.
Assessing Human Exposures to Particulate and Gaseous Air Pollutants (R827353C001)
Investigators: Petros Koutrakis, Helen, Suh, Jeremy Sarnat, Kathleen Ward Brown
Objective(s) of the Research Project: A central research objective of this group of projects was the examination of relationships between ambient particles and gases and corresponding personal exposures. The primary objectives of this work were to characterize exposures to PM2.5 and its major components and to assess the relative importance of several error sources to our ability to estimate exposures from ambient fine particle concentrations. These objectives were addressed using measurements of personal particulate exposures and corresponding indoor, outdoor, and ambient concentrations that were made for several cohorts of sensitive individuals. These data were specifically used to examine the impact of geographic location on the relationships between personal particulate and gaseous exposures; to evaluate the ability of ambient, home outdoor and home indoor pollutant concentrations to serve as proxies of personal exposure; and to determine how housing characteristics and activity patterns affect the relationships between personal exposures and ambient concentrations. The current findings indicate that geographical differences, ventilation of the home, time spent outdoors and local traffic sources may affect the ability of ambient concentrations to serve as proxies for personal exposures.
Summary of Findings: Pooling results from the Boston and Baltimore panel studies, we assessed whether the contribution of ambient particles on personal exposures varied by city, season and cohort. No cohort effect was found on the attenuation factors, which suggests that subjects from each cohort (i.e., seniors, children, chronic obstructive pulmonary disease [COPD] patients) were exposed to the same fraction of ambient PM2.5, given the same concentrations of ambient PM2.5. A report detailing these findings was published in 2005 (Koutrakis, et al., 2005). In one paper, we analyzed data from a Baltimore multiple pollutant exposure assessment to examine the role of ambient pollutant concentrations in PM2.5 epidemiologic models (Sarnat, et al., 2001). Since the Baltimore analysis was the first to examine relationships between personal exposures and ambient concentrations for PM2.5 and gaseous pollutants, it was important to conduct a similar analysis for other cities. We conducted an analysis including personal exposure and ambient concentration multi-pollutant data from the Boston panel study. Results from the Boston analysis, which includes both data from Baltimore and Boston, provide further evidence that the ambient gaseous pollutant concentrations are better surrogates of personal PM2.5 exposures, especially personal exposures to PM2.5 of ambient origin, than their respective personal exposures. These findings suggest that using ambient gas concentrations in multiple-pollutant health effects models along with PM2.5 may not be appropriate, since both the ambient gaseous and PM2.5 concentrations are serving as surrogates for PM2.5 exposures. In addition, the robustness of these findings was demonstrated by using various analytical methods and model structures. A paper entitled, “Relationships among Personal Exposures and Ambient Concentrations of Particulate and Gaseous Pollutants and their Implications for Particle Health Effects Studies,” was published in April 2005 in Epidemiology.
An additional panel study conducted in Boston found ambient particulate sulfate (SO42-) to be strongly correlated with corresponding personal exposures and home indoor concentrations for individuals not using humidifiers, a source of indoor SO42-. Correlations between ambient SO42- and personal exposures, however, varied by subject and by season. Associations with outdoor SO42- concentrations were similar to those for ambient concentrations. Ambient EC and PM2.5 concentrations were more weakly associated with corresponding personal and indoor levels, as compared to SO42-, likely due to the contributions of indoor and other local EC and PM2.5 sources.
In addition, this study found infiltration of outdoor pollutants into the home to be a key factor determining the contribution of ambient pollution to personal exposures, due to the large proportion of time individuals spend in their residences. High indoor-outdoor SO42- correlations indicated that home indoor and home outdoor levels correlated consistently regardless of the differences in the absolute levels in the two microenvironments. The significantly weaker associations for EC and PM2.5 compared to SO42- indicate that personal and household activities likely play an important role in determining personal exposures and can weaken associations with outdoor or ambient concentrations.
For EC, substantial spatial variation in outdoor concentrations was found, with this spatial variation lessening the ability of ambient concentrations to act as proxies of personal EC exposures. These results suggest that placement of outdoor EC monitors closer to participants’ homes may reduce exposure error in epidemiological studies of EC and other traffic-related particles. Infiltration was also shown to impact the ability of ambient concentrations to reflect exposures, as a strong seasonal difference in infiltration was found, where greater ventilation during the summer may have resulted in significantly higher personal exposures to particles originating from ambient sources. In contrast in the winter, lower infiltration can result in a greater contribution of indoor sources to personal exposures to EC and PM2.5.
A number of exposure and source factors were also found to affect personal exposures, particularly ventilation, time spent outdoors, time spent in transit and proximity to a major roadway. As indicated in previous panel studies, ventilation was a significant exposure modifier primarily during summer with open windows in the home approximately doubling the personal-ambient slopes for all pollutants, except NO2. While ventilation increased exposures to pollutants generated outdoors, there was evidence in this study of large impacts from indoor sources particularly at low ventilation rates. Subjects that spent more than an hour outdoors during summer had significantly increased personal exposures compared to individuals that spent less than that time outdoors, but the overall effect on personal exposures differed by pollutant with the greatest difference seen for EC. Living close to a major road was associated with higher traffic-related pollutants—EC, PM2.5 and NO2. This study also associated humidifiers using tap water with the highest personal and indoor SO42- and PM2.5 levels measured in the study. Other residence-specific location factors, including traffic density, population density, and percentage urban land use, were not significant modifiers of the personal-ambient association for any of the pollutants.
This analysis also indicated that open window status provided more consistent model results than air exchange rate (AER) in this study. The inconsistent results for AER may be due to the fact that many of the homes measured were apartments. As a result, the AER method could not differentiate between make-up air from outdoors or from neighboring apartments. Imprecision in the AER method also cannot be ruled out as contributing to this finding. As a result, future studies that include personal or indoor exposure measures may consider open windows as a better indicator of air exchange with outdoors in apartments or multi-unit buildings over a 24-hour period.
The results also indicated that infiltration into homes during the one-week monitoring period was remarkably consistent, given the various housing types measured. While the inter-home variability in infiltration ratios was substantial, infiltration ratios for a given home varied little over the week. Minimal intra-home variation in infiltration ratios is important given the complexity and difficulty of conducting large-scale personal exposure studies. A better understanding of how some housing, activity and source factors affect personal-ambient relationships may allow us to better estimate personal exposures in future health assessment studies.
Conclusions
Determining how well ambient monitors estimate personal exposures is especially important, given the recent generation of combined health and exposure studies on small panels of individuals. For these studies, more accurate estimates of exposures are needed to provide sufficient power to examine PM-associated impacts on intermediate health outcomes, such as heart rate variability and blood inflammation markers (Dubowsky, et al., 2006). In addition to assessing ambient concentrations, an assessment of ventilation conditions in the homes will likely provide a good indicator of the amount of outdoor pollution contributing to exposures in these studies.
Quantifying Exposure Error and its Effect on Epidemiological Studies (R827353C002)
Investigators: H. Suh, J. Sarnat, J. Schwartz, A. Zanobetti
Objective(s) of the Research Project: The main objective of this project was to quantify exposure error and to investigate its effect on the observed associations between exposure and health outcome.
Summary of Findings: As mentioned above, the preliminary findings of Project Ia (R827353C001) suggest that home characteristics, particularly home ventilation, are the primary determinant of the fraction of outdoor particles that penetrate indoor environments and thus are an important determinant of personal exposures to particles of outdoor origin as well. Through its impact on exposures to particles of outdoor origin, it is possible that home ventilation may also affect the association between outdoor particle concentrations and health risk. To test this hypothesis, we used data from 14 cities located across the US to examine the relationship between air conditioning prevalence and the coefficient for the relationship between ambient PM10 concentrations and cause-specific hospital admissions (Janssen, et al., 2002). In addition, we examined whether observed variability in the risk coefficients was specifically related to PM10 emissions from mobile, combustion, and other sources.
Our research examined the impact of exposure-related factors on risk estimates from time-series studies of PM10 and hospital admissions. In a paper published in 2002, we used data from 14 cities located across the US to examine the relationship between air conditioning prevalence and the coefficient for the relationship between ambient PM10 concentrations and cause-specific hospital admissions (Janssen, et al., 2002). In addition, we examined whether observed variability in the risk coefficients was specifically related to PM10 emissions from mobile, combustion, and other sources. Results from this study indicate that air conditioning use explains a substantial amount of the variability in the risk coefficients from the different cities. Furthermore, PM10 emissions from mobile and diesel sources were also found to be important determinants of the variability in the risk coefficients, particularly for cardiovascular disease (CVD)-related hospital admissions. To validate these findings, we used the same data to examine whether ventilation and source emission profiles explain season-specific risks of PM10 on hospital admissions in each of these 14 cities. This analysis is nearly complete, but a paper has not been submitted for review.
As part of our work to assess exposure error, we developed new methods to correct for measurement error in hierarchical models (Schwartz and Coull, 2003). We showed that existing standard two-stage estimators will be biased in the presence of exposure measurement error and that this bias can be away from the null hypothesis of no effect. We proposed two alternative methods for estimating the independent effects of two predictors in a hierarchical model. We applied the new methodology to show that the estimated effect of fine particles on daily deaths, independent of coarse particles, was downwardly biased by measurement error in an original analysis that did not correct for measurement error. We also used the methods to estimate the effect of gaseous air pollutants on daily deaths. The resulting effect size estimates were very small and the confidence intervals included zero. We applied this approach to a reanalysis of the National Morbidity, Mortality, and Air Pollution Study (NMMAPS) mortality study conducted by Johns Hopkins University researchers, which was published as a report to the Health Effects Institute (HEI, 2003). Also, using data from multi-pollutant exposure studies in Boston and Baltimore, simulations were conducted to assess the feasibility of health risks attributed to gases and particles. Results provided evidence that the gaseous pollutants are unlikely confounders of PM health risk estimates for these locations. These results were presented in a meeting abstract (Schwartz and Sarnat, 2002), and a manuscript has been submitted to the Journal of Exposure Science and Environmental Epidemiology.
We have also been working on the development and application of near-source and long-range atmospheric dispersion models to better quantify the relationship between emissions and concentrations of primary and secondary PM. This analysis will allow for improved spatially resolved exposure estimates and reduced exposure misclassification. A paper is under preparation, but it has not been finalized for submission.
Spatial-Temporal Modeling of Exposure
We developed spatial-temporal models of spatially varying exposures, such as traffic pollution, in the Boston area. Given a good model for exposure, this approach yields more accurate measures of spatially heterogeneous exposures than central site monitoring, and allows for examination of longer averaging times than the limited personal exposures. This approach can decrease the amount of measurement error associated with the central-site measurements and in turn yield more powerful tests of health effects. This manuscript was published. A revised manuscript describing the methodology and results of this analysis has been accepted by the Journal of the Royal Statistical Society (Gryparis, et al., 2007).
Quantifying Model Uncertainty in Epidemiological Analyses
A criticism of existing PM epidemiologic analyses is the multiple sources of uncertainty involved in obtaining health effect estimates. One key uncertainty is the shape of the concentration-response relation. Another is estimating how long one would have to wait after lowering pollution before the health improvements arrive. That is, are the associations with twenty-year average exposures, which will change slowly, or are they with recent exposures? We examined the use of Bayesian model averaging as a way of addressing these two forms of model uncertainty in a reanalysis of the Harvard Six Cities study. This approach avoids relying on an effect estimates from a single “final” model, which ignores uncertainty associated with model choice and thus can underestimate the variability associated with these effect estimates. Rather this method takes a weighted average of estimates from a range of plausible models. We implemented this approach to average over plausible models for the dose-response relationship of PM as well as the lag structure in the model. Preliminary results suggest that the dose-response curve is approximately linear and the strongest lagged effects occur during the current year (i.e. lag 0) and the immediately preceding year (i.e. lag 1). A paper describing the analysis has been submitted and is currently under review.
Conclusions
Results from our work indicate that air conditioning use explains a substantial amount of the variability in the relationship between ambient PM10 concentrations and cause-specific hospital admissions from 14 different cities studied. Additional results provided evidence that gaseous pollutants are unlikely confounders of PM health risk estimates. Finally, our results suggest that the dose-response curve for PM health effects is approximately linear, and the strongest lagged effects occur during the current year (i.e. lag 0) and the immediately preceding year (i.e. lag 1).
The St. Louis, Steubenville, and Atlanta Bus Studies (R827353C003)
Investigators: D. Gold, H. Suh, G. Adamkiewicz, S. Dubowsky, S. Sarnat, B. Coull, D. Dockery, H. Luttmann-Gibson, J. Schwartz, P. Stone, A. Wheeler, A. Zanobetti
The St. Louis Bus Study
H. Suh, G. Adamkiewicz, S. Dubowsky, D. Gold, S. Sarnat
Objective(s) of the Research Project: As part of Theme 1, we conducted a particle exposure and health effects study that specifically focused on the health effects of traffic-related pollutant exposures. This study examined the effects of ambient and traffic related pollution on intermediate cardiovascular and inflammatory health markers, including heart rate variability (HRV), systemic inflammation and pulmonary inflammation. The field study was conducted in St. Louis, MO during Spring 2002. We monitored the cardiovascular health of 44 individuals living in retirement facilities in metropolitan St. Louis, MO as they traveled on field trips aboard a diesel-powered bus. Markers of altered cardiovascular function including heart rate variability, heart rate, inflammatory indicators in the blood, and oxygen saturation of the blood were measured for participants during four separate 24-hr periods as the individuals traveled between the health testing room, a moving shuttle bus, indoor locations within the city, and his or her senior residence facility. Micro-environmental PM2.5, black carbon (BC) and fine particle count (PC0.3-1.0) exposures were assessed continuously for the study participants using two portable monitoring carts that traveled with the study participants throughout the day. The EPA-funded St. Louis Super Site served as the stationary ambient monitoring (SAM) site for measuring ambient concentrations.
Summary of Findings:
Particle Exposures
As shown in Figure 1, personal exposures to PM2.5, BC and PC0.3-1.0 were significantly higher when participants were aboard the diesel-powered shuttle bus as compared to when they were in their residence facilities (p<0.001). Exposures were the most elevated for BC. It can be assumed that elevated exposures during bus trips were attributed to emissions from surrounding vehicles and the shuttle bus, since mean concentrations at the SAM site during the bus and facility periods were comparable.
![Figure 1. Hourly Micro-Environmental and Ambient PM[2.5] and BC Concentrations.](https://webarchive.library.unt.edu/eot2008/20081105180008im_/http://es.epa.gov/ncer/progress/images/R827353_F_001.gif)
![Figure 1. Hourly Micro-Environmental and Ambient PM[2.5] and BC Concentrations.](https://webarchive.library.unt.edu/eot2008/20081105180008im_/http://es.epa.gov/ncer/progress/images/R827353_F_002.gif)
Figure 1. Hourly Micro-Environmental and Ambient PM2.5 and BC Concentrations. Microenvironmental PM2.5 (left) and BC (right) exposures were measured as participants traveled on a field trip via two bus rides and spent time in their residence facility. Micro-environmental exposures are shown in black; ambient concentrations are shown in grey. Exposures and concentrations were averaged by hour.
Heart Rate Variability
Exposure to airborne particles may increase cardiac risk by altering autonomic balance. As these risks may be particularly great for traffic-related particles, we examined associations between particles and heart rate variability for 44 subjects who participated in four repeated trips aboard a diesel bus. Twenty-four hour electrocardiograms were correlated with continuous particle concentrations using generalized additive models controlled for subject, weekday, time, apparent temperature, trip type, activity, medications, and autoregressive terms. Associations were assessed for short and medium-term mean concentrations.
Heart rate variability was significantly and negatively associated with fine particulate matter. Significant positive associations were demonstrated with heart rate and the low to high frequency power ratio. Associations were strongest with 24-hour mean concentrations although strong and significant short-term associations also were found during bus periods, independent of daily exposures. Overall, associations were largest for high frequency power with 16 (95% confidence interval [CI]: -17, –15), 19 (95% CI: -22, –17), and 14 (95% CI: -16, –13) percent decreases per inter-quartile changes in the 24-hour PM2.5 (4.6 μg/m3), black carbon (458 ng/m3), and fine particle count (39 pt/cm3) concentrations, respectively. Eleven percent (95% CI: -13.6, –7.8) decreases in high frequency power were predicted per inter-quartile change in the 5-minute PM2.5 (10 μg/m3) aboard the bus. This investigation indicates that fine particles are negatively associated with heart rate variability, with an overall trend towards reduced parasympathetic tone. While daily associations were evident for all particles, short-term associations were predominantly limited to bus periods and possibly fresh traffic-related particles. These findings were published in Epidemiology (Adar, et al., 2007b).
Systemic Inflammation
Inflammation may represent a pathway through which airborne particles lead to increased cardiac risk. Therefore, we investigated associations between ambient particles and acute systemic inflammation among repeated measures of 44 seniors and examined susceptibility by conditions linked to chronic inflammation. Mixed models were used to identify associations between fine particle concentrations (PM2.5) averaged over 1 to 7 days and measures of C-reactive protein (CRP), interleukin-6 (IL-6), and white blood cell counts (WBC). Effect modification was investigated for diabetes, obesity, hypertension, and elevated mean inflammatory markers.
Positive associations were consistently found between ambient PM2.5 and WBC across all participants, with an 11% (95% CI: 0.19 to 22%) increase per 10 μg/m3 increase in PM2.5 averaged over the previous week. PM2.5 and CRP also exhibited positive associations among all individuals for averaging periods longer than 1 day with the strongest associations for persons with diabetes, obesity, and hypertension. For example, a 10 μg/m3 increase in the 5 day mean PM2.5 was associated with a 24% increase in CRP (95% CI: -8.8 to 67%) for all individuals and a 170% (95% CI: 36 to 420%) increase for persons with diabetes, obesity, and hypertension. Persons with diabetes, obesity, and hypertension also exhibited positive associations between PM2.5 and IL-6. Individuals with elevated mean inflammatory markers exhibited enhanced responsiveness for CRP, IL-6, and WBC. This investigation demonstrates that air pollution is positively associated with acute systemic inflammation and indicates enhanced sensitivity for individuals with diabetes, obesity, hypertension, and elevated mean inflammatory markers. These findings were published in Environmental Health Perspectives (Dubowsky, et al., 2006).
Pulmonary Inflammation
Airborne particles have been linked to pulmonary oxidative stress and inflammation. As these effects may be particularly great for traffic-related particles, we examined associations between particle exposures and exhaled nitric oxide (eNO), a marker of pulmonary inflammation. Samples of eNO collected before and after the trips were correlated with micro-environmental and ambient particle concentrations using mixed models controlled for subject, day, trip, vitamins, collection device, mold, pollen, room air nitric oxide, apparent temperature, and time to analysis. While ambient concentrations were collected at a fixed location, continuous group-level personal samples characterized micro-environmental exposures throughout facility and trip periods. Findings from this analysis have been published in Environmental Health Perspectives (Adar, et al., 2007a).
Briefly, we found eNO concentrations collected prior to participation in a bus trip to be significantly associated with PM2.5 and PC0.3-1.0 averaged over the previous 24-hrs. For example, an inter-quartile increase in the 24-hr mean ambient PM2.5 of 10 μg/m3 resulted in a 15% (95% CI: 6–26%) increase in eNO using linear models adjusted for day of week, ambient apparent temperature, past nitrate consumption, recent meal, time between sample collection and analysis, study room nitric oxide (NO) concentrations, and a random subject effect. A similar increase for personal PM2.5 (as measured by the portable monitoring carts inside the facility) corresponded to a 20% (95% CI: 1–43%) increase in eNO, while an inter-quartile range (IQR) change in PC0.3-1.0 of about 70 pt/cc resulted in 30% increase in eNO (95% CI: 1–43%). Changes in BC, carbon monoxide (CO), NO, and NO2 were not significantly associated with deviations in eNO at the 95% confidence level.
On the day following the bus trip, we found similar effect estimates for measures of micro-environmental PM2.5 (20%, CI: 6–35%) and PC0.3-1.0 (23%, CI: 8–40%) when identical models were used. While ambient PM2.5 was predictive of eNO when participants were at their living facilities for the previous 24-hr, ambient PM2.5 was not predictive of eNO when the same individuals took part in a field trip that included two hours on the highway. While the gases remained non-predictive of post-trip eNO, BC became a significant predictor of eNO (20%, CI: 2–40%) for samples collected on the days after the bus trips. Data suggest that elevated exposures to traffic-related particles result in increased pulmonary inflammation as measured by eNO. Future findings will refine our analyses of the effects of motor vehicle exposures on eNO and determine whether autonomic effects such as HRV, ST-segment depression, and arrhythmias are also associated with motor vehicle exposures, as this was shown in a previous Center publication (Gold, et al., 2005).
Conclusions
These results suggest that air pollution exposures are associated with systemic inflammation among seniors having at least one symptom of metabolic syndrome, suggesting pollution impacts for a large proportion of the elderly in the U.S. (approximately 33% with obesity and 50% with hypertension). Inflammation associated with air pollution appears to occur acutely, with most effects within the first day of exposure.
This investigation also indicates that fine particles are negatively associated with heart rate variability with an overall trend towards reduced parasympathetic tone. While daily associations were evident for all particles, short-term associations were predominantly limited to traffic-related particles.
Steubenville
Investigators: D. Gold, H. Suh, B. Coull, D. Dockery, H. Luttmann-Gibson, S. Sarnat, J. Schwartz, P. Stone
Objective(s) of the Research Project: We conducted a particle exposure and health effects study in Steubenville, OH (Sarnat, et al., 2006). This field study included weekly measurement of thirty-two non-smoking older adults for 24 weeks during summer and fall 2000. Continuous electrocardiogram (ECG) measurements were made for each subject using a standardized 30 minute protocol. A central ambient monitoring station provided daily concentrations of PM2.5, sulfate, elemental carbon, and gases.
Analysis of these results focused on: (1) the potential effects of particulate matter and gases on autonomic nervous system dysfunction and inflammation, potential pathways by which particles affect cardiac rate and rhythm; and (2) the potential effects of these pollutants on the parasympathetic and sympathetic nervous systems. For the first area of research, published by Sarnat, et al. (2006), the two primary health outcomes were supraventricular ectopy (SVE), defined as extra cardiac depolarizations within the atria, and ventricular ectopy (VE) or extra depolarizations in the ventricles. For the second area of research (Luttmann-Gibson, et al., 2006), the effects of the pollutants on various measures of HRV were assessed. These HRV measures included: (1) the standard deviation of normal R-R intervals in the ECG (SDNN); (2) the mean square of differences between adjacent RR intervals in the ECG (r-RMSSD); (3) high frequency (HF) power; and (4) low frequency (LF) power.
In addition, we measured the fraction of exhaled nitric oxide (FENO) in the study subjects’ breath to evaluate the potential association with air pollution levels, as this metric is a non-invasive measure of airway inflammation (Adamkiewicz, et al., 2004).
Summary of Findings: Participant specific mean counts of arrhythmia over the protocol varied between 0.1–363 for SVE and 0–350 for VE. The authors observed odds ratios for having SVE over the length of the protocol of 1.42 (95% CI 0.99 to 2.04), 1.70 (95% CI 1.12 to 2.57), and 1.78 (95% CI 0.95 to 3.35) for 10.0 μg/m3, 4.2 μg/m3, and 14.9 ppb increases in five day moving average PM2.5, sulfate and ozone concentrations, respectively. The other pollutants, including elemental carbon, showed no effect on arrhythmia. Participants reporting cardiovascular conditions (for example, previous myocardial infarction (MI) or hypertension) were the most susceptible to pollution induced SVE. The authors found no association of pollution with VE.
In a community with significant industrial sources for air pollution, our study demonstrated an association of particle pollution with increased odds of supraventricular arrhythmia in a cohort of older adults, with findings of 42%, 70%, and 78% increases in odds of SVE associated with IQR increases in five day moving average PM2.5, sulfate and ozone, respectively. Air pollution effects were greatest for participants with a history of clinically significant cardiac disease. Since two pollutant models demonstrated stability in the effects of both particles and ozone, collectively our results may provide evidence of the combined effect of the secondary pollutant mix in Steubenville on cardiac arrhythmia. Specifically, the strong effects found with sulfate are interesting as Steubenville is located in an industrial area of the Ohio River Valley, with little traffic but with a number of coal-fired power plants, which are the major source of SO2, a sulfate precursor. It is important to note that ambient sulfate concentrations were measured with higher overall precision, and further, that ambient sulfate concentrations were better proxies of corresponding personal exposures as compared to EC. Both factors may have resulted in sufficient power to detect associations between arrhythmia and ambient concentrations of sulfate. A previous study conducted in Boston, reporting on patients with implantable cardioverter defibrillators, found that traffic related pollutants, particularly NO2, showed the greatest odds of arrhythmia (Peters, et al., 2000). Our data suggest that pollution in an industrial location may also contribute to the risk of arrhythmia, and they indicate the potential for varying impacts of air pollution by geographical location and source contributions.
The second paper found significant reductions in HRV measures associated with increased PM2.5 and sulfate, but no significant reductions in HRV associated with EC, NO2, SO2 or O3 levels. An IQR increase in sulfate of approximately 5 μg/m3 resulted in decreases of 3.3% for SDNN, 5.6% for RMSSD and 10.3% for HF with similar results for PM2.5.
In addition, an increase in the 24 hour average PM2.5 concentration of 17.7 μg/m3 was associated with an increase in FENO of 1.45 ppb (95% CI 0.33 to 2.57) in models adjusted for subject, week of study, day of the week, hour of the day, ambient barometric pressure, temperature, and relative humidity. This represents a change of approximately 15% compared with the mean FENO in the cohort (9.9 ppb). The associations between FENO and PM2.5 were significantly higher in subjects with a doctor’s diagnosis of COPD (p value for interaction = 0.03).
Conclusions
Our results suggest that increased levels of ambient air pollution, particularly for regional pollutants, including sulfate and ozone, may increase the risk of supraventricular arrhythmia in the elderly. The highest and most significant effects were found for greater than five day moving average concentrations before the health assessment, which may suggest that a long acting mechanism promoted the ectopic beats in our population. Furthermore, the results suggest that individuals with a history of clinically significant cardiac disease may be at particular risk of air pollution health effects. Additional analysis found that increased levels of sulfate and PM2.5 may adversely affect autonomic nervous system function, resulting in significant cardiac effects. Ambient pollution may also lead to airway inflammation as measured by FENO. These subclinical inflammatory changes may be an important step in the pathogenesis of the cardiopulmonary effects induced by exposure to air pollution.
Atlanta
Investigators: D. Gold, H. Suh, J. Schwartz, P. Stone, A. Wheeler, A. Zanobetti
Objective(s) of the Research Project: Associations between concentrations of PM2.5 and HRV have differed by study population. Results from previous studies suggested that compromised autonomic control of the heart may play a role in the acute cardiovascular toxicity of particles but that this role may differ with the underlying health status of the individual. The impact of health status on the relationship between HRV and ambient PM had not been examined directly, with previous panel studies including participants of only one susceptible disease group. To examine this issue more directly, we conducted a study to evaluate associations between ambient PM2.5 and HRV for sensitive individuals (Wheeler, et al., 2006). We then examined whether these associations differed for individuals with preexisting pulmonary disease compared to those with cardiovascular disease.
We examined the effects of ambient pollution on HRV for 18 individuals with COPD and 12 individuals with recent MI living in Atlanta, Georgia. HRV, baseline pulmonary function and medication data were collected for each participant during 7 days in fall 1999 and/or spring 2000. Hourly ambient pollution concentrations were obtained from monitoring sites in Atlanta. The association between ambient pollution and HRV was examined using linear mixed-effect models. The primary time domain HRV measures presented here include: (1) the standard deviation of normal R-R intervals in the ECG (SDNN), and (2) the square root of the mean of the sum of squares of differences between adjacent NN intervals in the ECG (RMSSD).
Summary of Findings: Ambient pollution had opposing effects on HRV in our COPD and MI participants, resulting in no significant effect of ambient pollution on HRV in the entire population for 1-, 4-, or 24-hr moving averages. Findings from our study provide direct evidence of heterogeneity in the autonomic response to ambient pollution that is dependent on the underlying health status of the study population. Changes in HRV were significantly and positively associated with ambient PM2.5 concentrations for individuals with COPD. Although not statistically significant, observed associations were consistently negative for individuals with recent MI. Further support that the HRV response to ambient PM2.5 differs for individuals with MI and COPD was provided by the fact that we found comparable effect estimates, with significant differences between disease groups, using models that included an interaction term between pollution and disease status. Associations with ambient PM2.5 were strongest for the 4-hr moving average and for SDNN an overall measure of HRV, although consistent trends with disease status were observed for other moving averages and other HRV measures. We also observed strong and significant associations with SDNN by disease group with ambient NO2, and to a lesser extent with ambient EC. Because ambient NO2 and EC originate primarily from motor vehicles, our findings suggest that motor vehicle-related pollution may be partly responsible for the observed effects of ambient particles on HRV.
The effect of medication use, respiratory rate, baseline pulmonary function (based on FEV1), air conditioning use, exercise during HRV measurement, body mass index, age, and heart rate on the association between 4-hr ambient pollution and overall SDNN was examined to determine whether these factors was responsible for the differences in response between the disease groups. Of these, medication use and baseline FEV1 were found to be significant effect modifiers for 4-hr PM2.5 and NO2 concentrations, with results comparable for the two pollutants. Similar effect modification by medication use and baseline pulmonary function was also found for EC but with smaller effect sizes.
Conclusions
Findings from our study provide direct evidence of heterogeneity in the autonomic response to ambient pollution that is dependent on the underlying health status of the study population. Changes in HRV were significantly and positively associated with ambient PM2.5 concentrations for individuals with COPD. Although not statistically significant, observed associations were consistently negative for individuals with recent MI.
Modeling Relationships Between Mobile Source Particle Emissions and Population Exposures (R827353C012)
Investigators: J. Spengler, J. Evans, S. Greco, J. Levy, G. Stevens, A. Wilson
Objective(s) of the Research Project: This project entailed extending our intake fraction (iF) methodology (Levy, et al., 2003; Levy, et al., 2002) to address motor vehicle emissions, as a way of informing PM control decisions and future analyses. Our specific objectives were to:
- Evaluate geographic patterns in primary and secondary particulate matter iFs for mobile sources, using a national-scale source-receptor (S-R) matrix;
- Determine the relative contributions of near-source and long-range populations to particulate matter iFs for mobile sources in different geographic locations;
- Develop predictive regression equations for iFs to explain geographic patterns as a function of population density and meteorological covariates
Summary of Findings: Results from this analysis were recently published (Greco, et al., 2007b). For primary fine particulate matter emitted from mobile sources, the intake fractions varied across source counties from 0.14 to 23 per million (median of 1.2 per million). These values were highly correlated with near-source population density; the population in the source county explained 43% of the variability in the above estimates, and a multivariate regression model with population at various radii from the source explained 86% of the variability. Spatial analyses of residuals indicated generally strong model performance, with greater errors along the coasts, where wind fields are more difficult to characterize and downwind populations may be less significant.
For secondary ammonium sulfate formed from SO2 emissions, the median intake fraction (0.43 per million) was somewhat lower than for primary PM. The variability was similar to that for primary PM, but with more regional variability rather than small-scale spatial variability. In spite of the regional influence on atmospheric chemistry, multivariate regressions with only population terms had an R2 of 0.78, indicating the significance of population patterns even in this context. However, there was relatively greater statistical significance for population beyond 200 km from the source, relative to primary PM, and relatively lower statistical significance for population within 200 km, reflecting expected concentration patterns.
Secondary ammonium nitrate formed from NOx emissions had an even lower median intake fraction (0.072 per million), with spatial variability driven somewhat by population patterns (R2 of 0.63 in multivariate regression model) but also by relative ambient concentrations of sulfate, nitrate and ammonium. Higher values tended to be found in the Midwest, where there is adequate ammonia to neutralize nitrate (and lower ambient sulfate), versus higher levels in the Ohio River Valley and Northeast for secondary sulfate and primary PM.
We also quantified the extent to which SO2 controls might free up ammonia to react with nitrate, thereby increasing ammonium nitrate concentrations. We determined that the public health benefits of SO2 emission controls (due to sulfate reductions) would be offset by ammonium nitrate increases by an average of 9%, ranging from 1% to 29% across U.S. counties.
As mentioned above, one of our primary objectives was to determine the relative importance of near-source and long-range populations. The median distances within which half of the total intake fraction was realized was about 150 km for primary PM, 450 km for secondary sulfate, and 390 km for secondary nitrate. However, these values varied substantially by setting (i.e., range for primary PM from 0 km, indicating that more than 50% of the iF was realized in the source county, to 1800 km). In dense urban areas, often a majority of the intake fraction was realized within the source county, indicating that more geographically resolved dispersion modeling may be warranted.
Comparing our results with the published literature, the magnitude of our estimates appear reasonable, and this analysis remains the first attempt to characterize spatial variability in mobile source intake fractions and to derive conclusions about the model scope and resolution needed to accurately estimate public health benefits of pollution control from mobile sources. Specifically, we concluded that a national-scale county-resolution dispersion model is likely sufficient for secondary particulate matter or primary particulate matter in rural areas with substantial downwind populations, but that more resolved models should be explored in dense urban areas or less-populated areas without significant downwind populations.
Based on the findings from Greco, et al. (2007b) we proceeded with follow-up work addressing potential within-county heterogeneity in primary PM mobile source intake fractions, as well as the questions of the spatial extent of the iF for sources within urban areas and the potential biases in estimates based on county-level resolution. We used the CAL3QHCR dispersion model (in the CALINE family of models) to simulate the influence of line-source emissions on concentrations on 23,000 road segments in the Boston area. A year’s worth of hourly intake fractions were determined for each road segment using actual meteorological conditions and residential population patterns. The annual average values for the road segments range from 0.8 to 53 per million, with a mean of 12 per million. On average, 46% of the total exposure is realized within 200 m of the road segment, though this varies from 0–93% across road segments, largely due to variable population patterns. Our findings indicate the likelihood of substantial intra-urban variability in mobile source primary PM2.5 iF, especially as taking into account population dynamics, localized meteorological conditions, and street-canyon configurations might all increase the variability in iF. These results were published as part of a doctoral thesis, and a manuscript has been submitted to Environmental Science & Technology (Greco, et al., 2007a).
Conclusions
Specifically, we concluded that a national-scale county-resolution dispersion model is likely sufficient for secondary particulate matter or primary particulate matter in rural areas with substantial downwind populations. Our findings also indicate the likelihood of substantial intra-urban variability in mobile source primary PM2.5 iF, especially as taking into account population dynamics, localized meteorological conditions, and street-canyon configurations might all increase the variability in iF. As a result, more resolved models should be explored in dense urban areas or less-populated areas without significant downwind populations.
THEME II: IDENTIFYING POPULATIONS SUSCEPTIBLE TO THE HEALTH EFFECTS OF PARTICULATE AIR POLLUTION
Examining Conditions That Predispose Towards Acute Adverse Effects of Particulate Exposures (R827353C004)
Investigators: J. Schwartz, M. O’Neill, G. Wellenius, A. Zanobetti
Objective(s) of the Research Project: Identification of populations that are especially susceptible to PM health effects can further our understanding of biologic mechanisms of heart and lung disease attributable to PM. This area of our work has focused on testing the hypothesis that patients with pre-existing respiratory, cardiovascular or diabetic conditions have an enhanced mortality response to particle exposures.
Summary of Findings: As part of this research effort, we previously reported that socio-economic factors were not modifiers of the risk of PM associated mortality (Zanobetti and Schwartz, 2000), although there was some increased risk in females. The same pattern held true for hospital admissions for heart and lung disease (Zanobetti, et al., 2000a). In contrast, we found that respiratory illness modified the risk of cardiovascular hospital admissions associated with PM (Zanobetti, et al., 2000b) and that heart failure modified the risk of PM-associated COPD admissions.
Additional work by our group has shown that individuals with diabetes are at higher risk from exposure to PM. We have published several papers addressing this issue. We published two studies suggesting that diabetes is an effect modifier (Zanobetti and Schwartz, 2001; 2002). One paper examined effect modification by concurrent diagnosis of diabetes overall and by age group in four U.S. cities (Zanobetti and Schwartz, 2002), concluding that individuals with diabetes have twice the risk of a PM10-associated cardiovascular admission compared to those without the disease.
To further examine susceptibility by diabetes observed in these population studies, we obtained clinical information to gain insights on potential biological mechanisms. With researchers at the Joslin Diabetes Center and Beth Israel/Deaconess Hospital, we analyzed the relationship between air pollution and both inflammation and vascular reactivity in over 200 greater-Boston residents participating in clinical trials. We used particle data (PM2.5, particle number [PN], BC and SO42-) measured at the Harvard School of Public Health (HSPH) site established by the PM Center. Both BC and SO42- particles appeared to have effects on vascular reactivity and endothelial function, especially among people with diabetes. (O’Neill, et al., 2005b) Additional analyses have shown associations between increased particle levels and blood markers of inflammation, including ICAM-1, VCAM-1, and von Willibrand’s factor, and a manuscript has been accepted for publication in Occupational and Environmental Medicine (O’Neill, et al., 2007).
We continued to explore factors influencing vulnerability to temperature-related mortality. Data on air pollution compiled for PM center projects have been used to control for confounding. In a study of seven US cities, lower educational attainment, black race, and dying outside a hospital were markers of vulnerability to death on extreme temperature days, controlling for PM10 exposure (O’Neill, et al., 2003c). In a follow-up analysis, we found that air conditioning prevalence explained some of the observed racial disparities in heat-related mortality in four of these cities (O’Neill, et al., 2005c). An additional analysis found that air pollution and epidemics were important confounders of temperature and mortality associations and suggested inclusion of PM10, O3, and epidemic periods in future analyses that can be used in forecasting health impacts of climate change. (O’Neill, et al., 2005a).
Furthermore, we conducted mortality follow-ups of subjects whose potentially predisposing conditions were identified for use in hospital admissions data. These analyses used the case-crossover approach. We completed a methodological paper examining the potential for bias and confounding in that approach and developed new statistical methods to address these problems (Bateson and Schwartz, 2001). The newly developed methods estimate and subtract biases from health risk estimates. We also conducted simulations showing our method has correct coverage probabilities, but a paper has not been submitted for review (Bateson and Schwartz, in preparation).
Mixed models are another group of analysis methods that represent an important tool for determining whether persons with certain characteristics are more susceptible to the effects of airborne particles. However, classic mixed regression programs are linear models, whereas we know that season and weather effects on health are often nonlinear. These have often been addressed using nonparametric smoothing. To enhance our ability to assess sensitivity while maintaining good covariate control, we developed an additive mixed model, which combines the attributes of both approaches (Coull, et al., 2001).
The case-crossover approach was also used to examine the PM10-associated risk of emergenc
Journal Articles: 148 Displayed | Download in RIS Format
| Other center views: | All 149 publications | 149 publications in selected types | All 148 journal articles |
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Adamkiewicz G, Ebelt S, Syring M, Slater J, Speizer FE, Schwartz J, Suh H, Gold DR. Association between air pollution exposure and exhaled nitric oxide in an elderly population. Thorax 2004;59(3):204-209. |
R827353 (Final) R827353C003 (Final) R826780 (Final) |
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Adar SD, Adamkiewicz G, Gold DR, Schwartz J, Coull B A, Suh H. Ambient and microenvironmental particles and exhaled nitric oxide before and after a group bus trip. Environmental Health Perspectives 2007;115(4):507-512. |
R827353 (Final) R827353C003 (Final) |
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Adar SD, Gold DR, Coull BA, Schwartz J, Stone PH, Suh H. Focused exposures to airborne traffic particles and heart rate variability in the elderly. Epidemiology 2007;18(1):95-103. |
R827353 (Final) R827353C003 (Final) |
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Alexeeff SE, Litonjua AA, Suh H, Sparrow D, Vokonas PS, Schwartz J. Ozone exposure and lung function: effect modified by obesity and airways hyperresponsiveness in the VA Normative Aging Study. Chest 2007;132(6):1890-1897. |
R827353 (Final) R832416 (2006) |
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Alexeeff SE, Litonjua AA, Sparrow D, Vokonas PS, Schwartz J. Statin use reduces decline in lung function: VA Normative Aging Study. American Journal of Respiratory and Critical Care Medicine 2007;176(8):742-747. |
R827353 (Final) R832416 (2006) |
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Baccarelli A, Zanobetti A, Martinelli I, Grillo P, Hou L, Lanzani G, Mannucci PM, Bertazzi PA, Schwartz J. Air pollution, smoking, and plasma homocysteine. Environmental Health Perspectives 2007;115(2):176-181. |
R827353 (Final) |
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Baccarelli A, Zanobetti A, Martinelli I, Grillo P, Hou L, Giacomini S, Bonzini M, Lazani G, Mannuci PM, Bertazzi PA, Schwartz J. Effects of exposure to air pollution on blood coagulation. Journal of Thrombosis and Haemostasis 2006;5(2):252-260. |
R827353 (Final) R827353C010 (Final) |
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Baccarelli A, Martinelli I, Zanobetti A, Grillo P, Hou LF, Bertazzi PA, Mannucci PM, Schwartz J. Exposure to particulate air pollution and risk of deep vein thrombosis. Archives of Internal Medicine 2008;168(9):920-927. |
R827353 (Final) R832416 (2006) |
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Baccarelli A, Cassano PA, Litonjua A, Park SK, Suh H, Sparrow D, Vokonas P, Schwartz J. Cardiac autonomic dysfunction: effects from particulate air pollution and protection by dietary methyl nutrients and metabolic polymorphisms. Circulation 2008;117(14):1802-1809. |
R827353 (Final) R832416 (2006) |
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Batalha JRF, Saldiva PHN, Clarke RW, Coull BA, Stearns RC, Lawrence J, Krishna Murthy GG, Koutrakis P, Godleski JJ. Concentrated ambient air particles induce vasoconstriction of small pulmonary arteries in rats. Environmental Health Perspectives 2002;110(12):1191-1197. |
R827353 (Final) R827353C014 (Final) |
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Bateson TF, Schwartz J. Selection bias and confounding in case-crossover analyses of environmental time-series data. Epidemiology 2001;12(6):654-661. |
R827353 (Final) R827353C004 (2002) R827353C004 (2003) R827353C004 (2004) R827353C004 (Final) R827353C005 (2001) R827353C005 (2002) R827353C005 (2003) R827353C005 (Final) |
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Bateson TF, Schwartz J. Who is sensitive to the effects of particulate air pollution on mortality? A case-crossover analysis of effect modifiers. Epidemiology 2004;15(2):143-149. |
R827353 (Final) R827353C005 (Final) |
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Braga ALF, Zanobetti A, Schwartz J. Do respiratory epidemics confound the association between air pollution and daily deaths? European Respiratory Journal 2000;16(4):723-728. |
R827353 (Final) R827353C005 (2000) R827353C005 (2002) R827353C005 (2003) R827353C005 (Final) |
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Braga ALF, Zanobetti A, Schwartz J. The effect of weather on respiratory and cardiovascular deaths in 12 U.S. cities. Environmental Health Perspectives 2002;110(9):859-863. |
R827353 (Final) R827353C004 (2002) R827353C004 (2003) R827353C004 (Final) |
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Braga ALF, Zanobetti A, Schwartz J. The lag structure between particulate air pollution and respiratory and cardiovascular deaths in 10 US cities. Journal of Occupational and Environmental Medicine 2001;43(11):927-933. |
R827353 (Final) R827353C005 (2001) R827353C005 (2002) R827353C005 (2003) R827353C005 (Final) |
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Braga ALF, Zanobetti A, Schwartz J. The time course of weather-related deaths. Epidemiology 2001;12(6):662-667. |
R827353 (Final) R827353C004 (2002) R827353C004 (2003) R827353C004 (2004) R827353C004 (Final) |
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Carrothers TJ, Evans JS. Assessing the impact of differential measurement error on estimates of fine particle mortality. Journal of the Air & Waste Management Association 2000;50(1):65-74. |
R827353 (Final) R827353C015 (Final) |
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Chahine T, Baccarelli A, Litonjua AA, Wright RO, Suh H, Gold DR, Sparrow D, Vokonas PS, Schwartz J. Particulate air pollution, oxidative stress genes, and heart rate variability in an elderly cohort. Environmental Health Perspectives 2007;115(11):1617-1622. |
R827353 (Final) R832416 (2006) |
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Chen JC, Schwartz J. Metabolic syndrome and inflammatory responses to long-term particulate air pollutants. Environmental Health Perspectives 2008;116(5):612-617. |
R827353 (Final) R832416 (2006) |
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Clancy L, Goodman P, Sinclair H, Dockery DW. Effect of air-pollution control on death rates in Dublin, Ireland: an intervention study. Lancet 2002;360(9341):1210-1214. |
R827353 (Final) R827353C006 (2001) R827353C006 (2002) R827353C006 (2003) R827353C006 (Final) |
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Clarke RW, Coull B, Reinisch U, Catalano P, Killingsworth CR, Koutrakis P, Kavouras I, Krishna Murthy GG, Lawrence J, Lovett E, Wolfson JM, Verrier RL, Godleski JJ. Inhaled concentrated ambient particles are associated with hematologic and bronchoalveolar lavage changes in canines. Environmental Health Perspectives 2000;108(12):1179-1187. |
R827353 (Final) R827353C014 (Final) |
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Coull BA, Schwartz J, Wand MP. Respiratory health and air pollution: additive mixed model analyses. Biostatistics 2001;2(3):337-349. |
R827353 (Final) R827353C004 (2000) R827353C004 (2001) R827353C004 (Final) |
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Demokritou P, Kavouras I, Harrison D, Koutrakis P. Development and evaluation of an impactor for a PM2.5 speciation sampler. Journal of the Air & Waste Management Association 2001;51(4):514-523. |
R827353 (Final) R827353C017 (Final) |
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Demokritou P, Kavouras IG, Ferguson ST, Koutrakis P. Development and laboratory performance evaluation of a personal multipollutant sampler for simultaneous measurements of particulate and gaseous pollutants. Aerosol Science and Technology 2001;35(3):741-752. |
R827353 (Final) R827353C017 (Final) |
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Demokritou P, Gupta T, Koutrakis P. A high volume apparatus for the condensational growth of ultrafine particles for inhalation toxicological studies. Aerosol Science and Technology 2002;36(11):1061-1072. |
R827353 (Final) R827353C017 (Final) |
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Demokritou P, Gupta T, Ferguson S, Koutrakis P. Development and laboratory characterization of a prototype coarse particle concentrator for inhalation toxicological studies. Journal of Aerosol Science 2002;33(8):1111-1123. |
R827353 (Final) R827353C017 (Final) R825270 (2000) R825270 (Final) |
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Demokritou P, Gupta T, Ferguson S, Koutrakis P. Development and laboratory performance evaluation of a personal cascade impactor. Journal of the Air & Waste Management Association 2002;52(10):1230-1237. |
R827353 (Final) R827353C017 (Final) |
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Demokritou P, Kavouras IG, Ferguson ST, Koutrakis P. Development of a high volume cascade impactor for toxicological and chemical characterization studies. Aerosol Science and Technology 2002;36(9):925-933. |
R827353 (Final) R827353C017 (Final) R825270 (2000) R825270 (Final) |
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Demokritou P, Gupta T, Ferguson S, Koutrakis P. Development of a high-volume concentrated ambient particles system (CAPS) for human and animal inhalation toxicological studies. Inhalation Toxicology 2003;15(2):111-129. |
R827353 (Final) R827353C017 (Final) |
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Demokritou P, Lee SJ, Ferguson ST, Koutrakis P. A compact multistage (cascade) impactor for the characterization of atmospheric aerosols. Journal of Aerosol Science 2004;35(3):281-299. |
R827353 (Final) R827353C017 (Final) |
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Demokritou P, Lee SJ, Koutrakis P. Development and evaluation of a high loading PM2.5 speciation sampler. Aerosol Science and Technology 2004;38(2):111-119. |
R827353 (Final) R827353C017 (Final) |
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Ding Y, Koutrakis P. Development of a dichotomous slit nozzle virtual impactor. Journal of Aerosol Science 2000;31(12):1421-1431. |
R827353 (Final) R827353C017 (Final) |
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Dockery DW. Epidemiologic evidence of cardiovascular effects of particulate air pollution. Environmental Health Perspectives 2001;109(Suppl. 4):483-486. |
R827353 (Final) R827353C005 (2002) R827353C005 (2003) R827353C005 (Final) |
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Dockery DW, Luttmann-Gibson H, Rich DQ, Link MS, Mittleman MA, Gold DR, Koutrakis P, Schwartz JD, Verrier RL. Association of air pollution with increased incidence of ventricular tachyarrhythmias recorded by implanted cardioverter defibrillators. Environmental Health Perspectives 2005;113(6):670-674. |
R827353 (Final) R827353C004 (Final) |
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Dubowsky SD, Suh H, Schwartz J, Coull BA, Gold DR. Diabetes, obesity, and hypertension may enhance associations between air pollution and markers of system ic inflammation. Environmental Health Perspectives 2006;114(7):992-998. |
R827353 (Final) R827353C003 (Final) |
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Evans JS, Wolff SK, Phonboon K, Levy JI, Smith KR. Exposure efficiency: an idea whose time has come? Chemosphere 2002;49(9):1075-1091. |
R827353 (Final) R827353C015 (Final) |
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Franco Suglia S, Gryparis A, Wright RO, Schwartz J, Wright RJ. Association of black carbon with cognition among children in a prospective birth cohort study. American Journal of Epidemiology 2008;167(3):280-286. |
R827353 (Final) R832416 (2006) |
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Franklin M, Zeka A, Schwartz J. Association between PM2.5 and all-cause and specific-cause mortality in 27 US communities. Journal of Exposure Science & Environmental Epidemiology 2007;17(3):279-287. |
R827353 (Final) R827353C017 (Final) |
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Ghelfi E, Rhoden CR, Wellenius GA, Lawrence J, Gonzalez-Flecha B. Cardiac oxidative stress and electrophysiological changes in rats exposed to concentrated air particles are mediated by TRP-dependent pulmonary reflexes. Toxicological Sciences 2008;102(2):328-336. |
R827353 (Final) |
not available |
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Gold DR, Litonjua AA, Zanobetti A, Coull BA, Schwartz J, MacCallum G, Verrier RL, Nearing BD, Canner MJ, Suh H, Stone PH. Air pollution and ST-segment depression in elderly subjects. Environmental Health Perspectives 2005;113(7):883-887. |
R827353 (Final) R827353C003 (Final) |
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Goodman PG, Dockery DW, Clancy L. Cause-specific mortality and the extended effects of particulate pollution and temperature exposure. Environmental Health Perspectives 2004;112(2):179-185. |
R827353 (Final) R827353C005 (2003) R827353C005 (Final) R827353C006 (Final) |
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Greco SL, Wilson AM, Spengler JD, Levy JI. Spatial patterns of mobile source particulate matter emissions-to-exposure relationships across the United States. Atmospheric Environment 2007;41(5):1011-1025. |
R827353 (Final) R827353C012 (Final) |
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Gryparis A, Coull BA, Schwartz J, Suh HH. Semiparametric latent variable regression models for spatiotemporal modeling of mobile source particles in the greater Boston area. Journal of the Royal Statistical Society: Series C (Applied Statistics) 2007;56(2):183-209. |
R827353 (Final) |
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Gupta T, Demokritou P, Koutrakis P. Development and performance evaluation of a high-volume ultrafine particle concentrator for inhalation toxicological studies. Inhalation Toxicology 2004;16(13):851-862. |
R827353 (Final) R827353C017 (Final) |
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Haber S, Yitzhak D, Tsuda A. Gravitational deposition in a rhythmically expanding and contracting alveolus. Journal of Applied Physiology 2003;95(2):657-671. |
R827353 (Final) R827353C009 (2002) R827353C009 (Final) |
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Hamada K, Goldsmith C-A, Suzaki Y, Goldman A, Kobzik L. Airway hyperresponsiveness caused by aerosol exposure to residual oil fly ash leachate in mice. Journal of Toxicology and Environmental Health-Part A 2002;65(18):1351-1365. |
R827353 (Final) R827353C014 (Final) R826779 (Final) |
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Hatzis C, Godleski JJ, Gonzalez-Flecha B, Wolfson JM, Koutrakis P. Ambient particulate matter exhibits direct inhibitory effects on oxidative stress enzymes. Environmental Science & Technology 2006;40(8):2805-2811. |
R827353 (Final) R827353C011 (2004) R827353C011 (Final) |
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Henry FS, Butler JP, Tsuda A. Kinematically irreversible acinar flow: a departure from classical dispersive aerosol transport theories. Journal of Applied Physiology 2002;92(2):835-845. |
R827353 (Final) R827353C009 (2002) R827353C009 (Final) |
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Hopke PK, Ito K, Mar T, Christiansen WF, Eatough DJ, Henry RC, Kim E, Laden F, Lall R, Larson TV, Liu H, Neas L, Pinto J, Stölzel M, Suh H, Paatero P, Thurston GD. PM source apportionment and health effects: 1. Intercomparison of source apportionment results. Journal of Exposure Science & Environmental Epidemiology 2006;16(3):275-286. |
R827353 (Final) R827353C017 (Final) R827354 (Final) R827354C001 (Final) R827355 (Final) R827355C008 (Final) |
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Ito K, Christiansen WF, Eatough DJ, Henry RC, Kim E, Laden F, Lall R, Larson TV, Neas L, Hopke PK, Thurston GD. PM source apportionment and health effects: 2. An investigation of intermethod variability in associations between source-apportioned fine particle mass and daily mortality in Washington, DC. Journal of Exposure Science & Environmental Epidemiology 2006;16(4):300-310. |
R827353 (Final) R827353C015 (Final) R827351 (Final) R827351C001 (Final) R827354 (Final) R827354C001 (Final) R827355 (Final) R827355C008 (Final) R827997 (Final) |
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Janssen NAH, Schwartz J, Zanobetti A, Suh HH. Air conditioning and source-specific particles as modifiers of the effect of PM10 on hospital admissions for heart and lung disease. Environmental Health Perspectives 2002;110(1):43-49. |
R827353 (Final) R827353C002 (2000) R827353C002 (2001) R827353C002 (2002) R827353C002 (2003) R827353C002 (Final) |
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Laden F, Schwartz J, Speizer FE, Dockery DW. Reduction in fine particulate air pollution and mortality: extended follow-up of the Harvard Six Cities Study. American Journal of Respiratory and Critical Care Medicine 2006;173(6):667-672. |
R827353 (Final) R827353C006 (2004) R827353C006 (Final) |
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Lee SJ, Demokritou P, Koutrakis P. Performance evaluation of commonly used impaction substrates under various loading conditions. Journal of Aerosol Science 2005;36(7):881-895. |
R827353 (Final) R827353C017 (Final) |
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Lee SJ, Demokritou P, Koutrakis P, Delgado-Saborit JM. Development and evaluation of personal respirable particulate Sampler (PRPS). Atmospheric Environment 2006;40(2):212-224. |
R827353 (Final) R827353C017 (Final) |
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Levy JI, Wolff SK, Evans JS. A regression-based approach for estimating primary and secondary particulate matter intake fractions. Risk Analysis 2002;22(5):895-904. |
R827353 (Final) R827353C012 (Final) R827353C015 (Final) |
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Levy JI, Wilson AM, Evans JS, Spengler JD. Estimation of primary and secondary particulate matter intake fractions for power plants in Georgia. Environmental Science & Technology 2003;37(24):5528-5536. |
R827353 (Final) R827353C012 (Final) R827353C015 (Final) |
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Lippmann M, Frampton M, Schwartz J, Dockery D, Schlesinger R, Koutrakis P, Froines J, Nel A, Finkelstein J, Godleski J, Kaufman J, Koenig J, Larson T, Luchtel D, Liu L-J S, Oberdorster G, Peters A, Sarnat J, Sioutas C, Suh H, Sullivan J, Utell M, Wichmann E, Zelikoff J. The U.S. Environmental Protection Agency Particulate Matter Health Effects Research Centers Program: a midcourse report of status, progress, and plans. Environmental Health Perspectives 2003;111(8):1074-1092. |
R827353 (Final) R827353C006 (Final) R827353C015 (Final) R827351 (2002) R827351 (Final) R827352 (Final) R827352C002 (Final) R827352C014 (Final) R827354 (Final) R827355 (Final) |
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Liu Y, Sarnat JA, Coull BA, Koutrakis P, Jacob DJ. Validation of Multiangle Imaging Spectroradiometer (MISR) aerosol optical thickness measurements using Aerosol Robotic Network (AERONET) observations over the contiguous United States. Journal of Geophysical Research–Atmospheres 2004;109(D6):D06205, doi:10.1029/2003JD003981. |
R827353 (Final) R827353C017 (Final) |
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Liu Y, Sarnat JA, Kilaru V, Jacob DJ, Koutrakis P. Estimating ground-level PM2.5 in the Eastern United States using satellite remote sensing. Environmental Science & Technology 2005;39(9):3269-3278. |
R827353 (Final) R827353C017 (Final) |
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Liu Y, Koutrakis P, Kahn R. Estimating fine particulate matter component concentrations and size distributions using satellite-retrieved fractional aerosol optical depth:Part 1-method development. Journal of the Air & Waste Management Association 2007;57(11):1351-1359. |
R827353 (Final) R832416 (2006) |
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Liu Y, Koutrakis P, Kahn R, Turquety S, Yantosca RM. Estimating fine particulate matter component concentrations and size distributions using satellite-retrieved fractional aerosol optical depth: Part 2--a case study. Journal of the Air & Waste Management Association 2007;57(11):1360-1369. |
R827353 (Final) R832416 (2006) |
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Liu Y, Franklin M, Kahn R, Koutrakis P. Using aerosol optical thickness to predict ground-level PM2.5 concentrations in the St. Louis area: a comparison between MISR and MODIS. Remote Sensing of Environment 2007;107(1-2):33-44. |
R827353 (Final) R827353C017 (Final) |
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Liu Y, Park RJ, Jacob DJ, Li Q, Kilaru V, Sarnat JA. Mapping annual mean ground-level PM2.5 concentrations using Multiangle Imaging Spectroradiometer aerosol optical thickness over the contiguous United States. Journal of Geophysical Research–Atmospheres 2004;109(D22):D22206, doi:10.1029/2004JD005025. |
R827353 (Final) R827353C017 (Final) |
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Luttmann-Gibson H, Suh HH, Coull BA, Dockery DW, Sarnat SE, Schwartz J, Stone PH, Gold DR. Short-term effects of air pollution on heart rate variability in senior adults in Steubenville, Ohio. Journal of Occupational and Environmental Medicine 2006;48(8):780-788. |
R827353 (Final) R827353C003 (Final) |
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Magari SR, Hauser R, Schwartz J, Williams PL, Smith TJ, Christiani DC. Association of heart rate variability with occupational and environmental exposure to particulate air pollution. Circulation 2001;104(9):986-991. |
R827353 (Final) R828678C002 (2001) R828678C002 (2003) R828678C002 (2004) R828678C002 (2005) R828678C002 (2006) |
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Mar TF, Ito K, Koenig JQ, Larson TV, Eatough DJ, Henry RC, Kim E, Laden F, Lall R, Neas L, Stolzel M, Paatero P, Hopke PK, Thurston GD. PM source apportionment and health effects. 3. Investigation of inter-method variations in associations between estimated source contributions of PM2.5 and daily mortality in Phoenix, AZ. Journal of Exposure Science & Environmental Epidemiology 2006;16(4):311-320. |
R827353 (Final) R827353C015 (Final) R827351 (Final) R827354 (Final) R827354C001 (Final) R827355 (Final) R827355C002 (Final) R827355C008 (Final) |
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Maynard D, Coull BA, Gryparis A, Schwartz J. Mortality risk associated with short-term exposure to traffic particles and sulfates. Environmental Health Perspectives 2007;115(5):751-755. |
R827353 (Final) |
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McCracken JP, Smith KR, Diaz A, Mittleman MA, Schwartz J. Chimney stove intervention to reduce long-term wood smoke exposure lowers blood pressure among Guatemalan women. Environmental Health Perspectives 2007;115(7):996-1001. |
R827353 (Final) |
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Medina-Ramon M, Zanobetti A, Cavanagh DP, Schwartz J. Extreme temperatures and mortality: assessing effect modification by personal characteristics and specific cause of death in a multi-city case-only analysis. Environmental Health Perspectives 2006;114(9):1331-1336. |
R827353 (Final) R827353C004 (Final) |
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Medina-Ramon M, Zanobetti A, Schwartz J. The effect of ozone and PM10 on hospital admissions for pneumonia and chronic obstructive pulmonary disease: a national multicity study. American Journal of Epidemiology 2006;163(6):579-588. |
R827353 (Final) R827353C005 (Final) |
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Medina-Ramon M, Schwartz J. Temperature, temperature extremes, and mortality: a study of acclimatisation and effect modification in 50 US cities. Occupational and Environmental Medicine 2007;64(12):827-833. |
R827353 (Final) |
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Montoya L, Lawrence J, Krishna Murthy G, Sarnat J, Godleski J, Koutrakis P. Continuous measurements of ambient particle deposition in human subjects. Aerosol Science and Technology 2004;38(10):980-990. |
R827353 (Final) R827353C009 (Final) |
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Nikolov MC, Coull BA, Catalano PJ, Godleski JJ. An informative Bayesian structural equation model to assess source-specific health effects of air pollution. Biostatistics 2007;8(3):609-624. |
R827353 (Final) R827353C005 (Final) |
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Nishioka Y, Levy JI, Norris GA, Wilson A, Hofstetter P, Spengler JD. Integrating risk assessment and life cycle assessment: a case study of insulation. Risk Analysis 2002;22(5):1003-1017. |
R827353 (Final) R827353C015 (Final) |
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O’Neill MS. Air conditioning and heat-related health effects. Applied Environmental Science and Public Health 2003;1(1):9-12. |
R827353 (Final) R827353C004 (2002) R827353C004 (2003) R827353C004 (Final) |
not available |
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O’Neill MS, Jerrett M, Kawachi I, Levy JI, Cohen AJ, Gouveia N, Wilkinson P, Fletcher T, Cifuentes L, Schwartz J. Health, wealth, and air pollution: advancing theory and methods. Environmental Health Perspectives 2003;111(16):1861-1870. |
R827353 (Final) R827353C004 (2003) R827353C004 (Final) |
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O’Neill MS, Zanobetti A, Schwartz J. Modifiers of the temperature and mortality association in seven US cities. American Journal of Epidemiology 2003;157(12):1074-1082. |
R827353 (Final) R827353C004 (2003) R827353C004 (Final) |
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O’Neill MS, Loomis D, Borja Aburto VH, Gold D, Hertz-Picciotto I, Castillejos M. Do associations between airborne particles and daily mortality in Mexico City differ by measurement method, region, or modeling strategy? Journal of Exposure Analysis and Environmental Epidemiology 2004;14(6):429-439. |
R827353 (Final) R827353C005 (2003) R827353C005 (Final) |
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O’Neill MS, Veves A, Zanobetti A, Sarnat JA, Gold DR, Economides PA, Horton ES, Schwartz J. Diabetes enhances vulnerability to particulate air pollution-associated impairment in vascular reactivity and endothelial function. Circulation 2005;111(22):2913-2920. |
R827353 (Final) R827353C004 (2003) R827353C004 (2004) R827353C004 (Final) |
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O’Neill MS, Zanobetti A, Schwartz J. Disparites by race in heat-related mortality in four US cities: the role of air conditioning prevalence. Journal of Urban Health 2005;82(2):191-197. |
R827353 (Final) R827353C004 (Final) |
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O’Neill MS, Hajat S, Zanobetti A, Ramirez-Aguilar M, Schwartz J. Impact of control for air pollution and respiratory epidemics on the estimated associations of temperature and daily mortality. International Journal of Biometeorology 2005;50(2):121-129. |
R827353 (Final) R827353C004 (2003) R827353C004 (2004) R827353C004 (Final) |
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O’Neill MS, Veves A, Sarnat JA, Zanobetti A, Gold DR, Economides PA, Horton ES, Schwartz J. Air pollution and inflammation in type 2 diabetes: a mechanism for susceptibility. Occupational and Environmental Medicine 2007;64(6):373-379. |
R827353 (Final) R827353C004 (Final) |
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Park SK, O’Neill MS, Vokonas PS, Sparrow D, Schwartz J. Effects of air pollution on heart rate variability: the VA Normative Aging Study. Environmental Health Perspectives 2005;113(3):304-309. |
R827353 (Final) R827353C010 (Final) |
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Park SK, O’Neill MS, Wright RO, Hu H, Vokonas PS, Sparrow D, Suh H, Schwartz J. HFE genotype, particulate air pollution, and heart rate variability: a gene-environment interaction. Circulation 2006;114(25):2798-2805. |
R827353 (Final) R827353C010 (Final) |
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Park SK, Schwartz J, Weisskopf M, Sparrow D, Vokonas PS, Wright RO, Coull B, Nie H, Hu H. Low-level lead exposure, metabolic syndrome, and heart rate variability: the VA Normative Aging Study. Environmental Health Perspectives 2006;114(11):1718-1724. |
R827353 (Final) |
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Park SK, O’Neill MS, Stunder BJB, Vokonas PS, Sparrow D, Koutrakis P, Schwartz J. Source location of air pollution and cardiac autonomic function: trajectory cluster analysis for exposure assessment. Journal of Exposure Science & Environmental Epidemiology 2007;17(15):488-497. |
R827353 (Final) R827353C010 (Final) |
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Park SK, O’Neill MS, Vokonas PS, Sparrow D, Wright RO, Coull B, Nie H, Hu H, Schwartz J. Air pollution and heart rate variability: effect modification by chronic lead exposure. Epidemiology 2008;19(1):111-120. |
R827353 (Final) R832416 (2006) |
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Park SK, O’Neill MS, Vokonas PS, Sparrow D, Spiro A III, Tucker KL, Suh H, Hu H, Schwartz J. Traffic-related particles are associated with elevated homocysteine: the VA Normative Aging Study. American Journal of Respiratory and Critical Care Medicine 2008;178(3):283-289. |
R827353 (Final) R832416 (2006) |
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Peters A, Dockery DW, Muller JE, Mittleman MA. Increased particulate air pollution and the triggering of myocardial infarction. Circulation 2001;103(23):2810-2815. |
R827353 (Final) R827353C004 (2002) R827353C004 (2003) R827353C004 (Final) |
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Rhoden CR, Lawrence J, Godleski JJ, Gonzalez-Flecha B. N-Acetylcysteine prevents lung inflammation after short-term inhalation exposure to concentrated ambient particles. Toxicological Sciences 2004;79(2):296-303. |
R827353 (Final) R827353C011 (2003) R827353C011 (Final) |
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Rhoden CR, Wellenius GA, Ghelfi E, Lawrence J, Gonzalez-Flecha B. PM-induced cardiac oxidative stress and dysfunction are mediated by autonomic stimulation. Biochimica et Biophysica Acta 2005;1725(3):305-313. |
R827353 (Final) R827353C011 (2004) R827353C011 (Final) |
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Rich DQ, Schwartz J, Mittleman MA, Link M, Luttmann-Gibson H, Catalano PJ, Speizer FE, Dockery DW. Association of short-term ambient air pollution concentrations and ventricular arrhythmias. American Journal of Epidemiology 2005;161(12):1123-1132. |
R827353 (Final) R827353C004 (Final) |
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Rich DQ, Mittleman MA, Link MS, Schwartz J, Luttmann-Gibson H, Catalano PJ, Speizer FE, Gold DR, Dockery DW. Increased risk of paroxysmal atrial fibrillation episodes associated with acute increases in ambient air pollution. Environmental Health Perspectives 2006;114(1):120-123. |
R827353 (Final) R827353C004 (Final) |
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Ruiz PA, Lawrence JE, Ferguson ST, Wolfson JM, Koutrakis P. A counter-current parallel-plate membrane denuder for the non-specific removal of trace gases. Environmental Science & Technology 2006;40(16):5058-5063. |
R827353 (Final) R827353C013 (Final) |
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Ruiz PA, Lawrence JE, Wolfson JM, Ferguson ST, Gupta T, Kang CM, Koutrakis P. Development and evaluation of a photochemical chamber to examine the toxicity of coal-fired power plant emissions. Inhalation Toxicology 2007;19(8):597-606. |
R827353 (Final) |
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Ruiz PA, Gupta T, Kang CM, Lawrence JE, Ferguson ST, Wolfson JM, Rohr AC, Koutrakis P. Development of an exposure system for the toxicological evaluation of particles derived from coal-fired power plants. Inhalation Toxicology 2007;19(8):607-619. |
R827353 (Final) |
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Saldiva PHN, Clarke RW, Coull BA, Stearns RC, Lawrence J, Krishna Murthy GG, Diaz E, Koutrakis P, Suh H, Tsuda A, Godleski JJ. Lung inflammation induced by concentrated ambient air particles is related to particle composition. American Journal of Respiratory and Critical Care Medicine 2002;165(12):1610-1617. |
R827353 (Final) R827353C014 (Final) |
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Sarnat JA, Koutrakis P, Suh HH. Assessing the relationship between personal particulate and gaseous exposures of senior citizens living in Baltimore, MD. Journal of the Air & Waste Management Association 2000;50(7):1184-1198. |
R827353 (Final) R827353C001 (2000) R827353C001 (2001) R827353C001 (2002) R827353C001 (2003) R827353C001 (2004) R827353C001 (Final) |
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Sarnat JA, Schwartz J, Catalano PJ, Suh HH. Gaseous pollutants in particulate matter epidemiology: confounders or surrogates? Environmental Health Perspectives 2001;109(10):1053-1061. |
R827353 (Final) R827353C001 (2001) R827353C001 (2002) R827353C001 (Final) |
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Sarnat JA, Long CM, Koutrakis P, Coull BA, Schwartz J, Suh HH. Using sulfur as a tracer of outdoor fine particulate matter. Environmental Science & Technology 2002;36(24):5305-5314. |
R827353 (Final) R827353C001 (2001) R827353C001 (Final) |
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Sarnat JA, Brown KW, Schwartz J, Coull BA, Koutrakis P. Ambient gas concentrations and personal particulate matter exposures: implications for studying the health effects of particles. Epidemiology 2005;16(3):385-395. |
R827353 (Final) R827353C001 (2003) R827353C001 (2004) R827353C001 (Final) |
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Sarnat SE, Suh HH, Coull BA, Schwartz J, Stone PH, Gold DR. Ambient particulate air pollution and cardiac arrhythmia in a panel of older adults in Steubenville, Ohio. Occupational and Environmental Medicine 2006;63(10):700-706. |
R827353 (Final) R827353C003 (Final) |
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Sarnat SE, Coull BA, Schwartz J, Gold DR, Suh HH. Factors affecting the association between ambient concentrations and personal exposures to particles and gases. Environmental Health Perspectives 2006;114(5):649-654. |
R827353 (Final) R827353C001 (Final) |
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Sarnat SE, Coull BA, Ruiz PA, Koutrakis P, Suh HH. The influences of ambient particle composition and size on particle infiltration in Los Angeles, CA residences. Journal of the Air & Waste Management Association 2006;56(2):186-196. |
R827353 (Final) R827353C001 (Final) |
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Savage ST, Lawrence J, Katz T, Stearns RC, Coull BA, Godleski JJ. Does the Harvard/U.S. Environmental Protection Agency ambient particle concentrator change the toxic potential of particles? Journal of the Air & Waste Management Association 2003;53(9):1088-1097. |
R827353 (Final) R827353C014 (Final) R827353C017 (Final) |
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Schwartz J. Assessing confounding, effect modification, and thresholds in the association between ambient particles and daily deaths. Environmental Health Perspectives 2000;108(6):563-568. |
R827353 (Final) R827353C004 (2003) R827353C004 (Final) |
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Schwartz J. Daily deaths are associated with combustion particles rather than SO2 in Philadelphia. Occupational and Environmental Medicine 2000;57(10):692-697. |
R827353 (Final) R827353C005 (2000) R827353C005 (2001) R827353C005 (Final) |
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Schwartz J. Harvesting and long term exposure effects in the relation between air pollution and mortality. American Journal of Epidemiology 2000;151(5):440-448. |
R827353 (Final) R827353C005 (2000) R827353C005 (Final) |
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Schwartz J, Zanobetti A. Using meta-smoothing to estimate dose-response trends across multiple studies, with application to air pollution and daily death. Epidemiology 2000;11(6):666-672. |
R827353 (Final) R827353C005 (2000) R827353C005 (2002) R827353C005 (2003) R827353C005 (Final) |
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Schwartz J. Is there harvesting in the association of airborne particles with daily deaths and hospital admissions? Epidemiology 2001;12(1):55-61. |
R827353 (Final) R827353C005 (Final) |
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Schwartz J, Ballester F, Saez M, Perez-Hoyos S, Bellido J, Cambra K, Arribas F, Canada A, Perez-Boillos MJ, Sunyer J. The concentration-response relation between air pollution and daily deaths. Environmental Health Perspectives 2001;109(10):1001-1006. |
R827353 (Final) R827353C005 (2000) R827353C005 (2002) R827353C005 (2003) R827353C005 (Final) |
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Schwartz J, Laden F, Zanobetti A. The concentration-response relation between PM2.5 and daily deaths. Environmental Health Perspectives 2002;110(10):1025-1029. |
R827353 (Final) R827353C005 (Final) |
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Schwartz J. The use of epidemiology in environmental risk assessment. Human and Ecological Risk Assessment 2002;8(6):1253-1265. |
R827353 (Final) R827353C015 (Final) |
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Schwartz J, Coull BA. Control for confounding in the presence of measurement error in hierarchical models. Biostatistics 2003;4(4):539-553. |
R827353 (Final) R827353C002 (Final) R827353C005 (Final) |
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Schwartz J. Is the association of airborne particles with daily deaths confounded by gaseous air pollutants? An approach to control by matching. Environmental Health Perspectives 2004;112(5):557-561. |
R827353 (Final) R827353C002 (Final) |
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Schwartz J. The effects of particulate air pollution on daily deaths: a multi-city case crossover analysis. Occupational and Environmental Medicine 2004;61(12):956-961. |
R827353 (Final) R827353C005 (Final) |
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Schwartz J, Park SK, O’Neill MS, Vokonas PS, Sparrow D, Weiss S, Kelsey K. Glutathione-S-transferase M1, obesity, statins, and autonomic effects of particles: gene-by-drug-by-environment interaction. American Journal of Respiratory and Critical Care Medicine 2005;172(12):1529-1533. |
R827353 (Final) R827353C010 (Final) |
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Schwartz J. How sensitive is the association between ozone and daily deaths to control for temperature? American Journal of Respiratory and Critical Care Medicine 2005;171(6):627-631. |
R827353 (Final) R827353C005 (Final) |
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Schwartz J. Who is sensitive to extremes of temperature? A case-only analysis. Epidemiology 2005;16(1):67-72. |
R827353 (Final) R827353C004 (2004) R827353C004 (Final) |
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Schwartz J. Comments on "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. |
R827353 (Final) |
not available |
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Sunyer J, Atkinson R, Ballester F, Le Tertre A, Ayres JG, Forastiere F, Forsberg B, Vonk JM, Bisanti L, Anderson RH, Schwartz J, Katsouyanni K. Respiratory effects of sulphur dioxide: a hierarchical multicity analysis in the APHEA 2 study. Occupational and Environmental Medicine 2003;60(8):e2. |
R827353 (Final) R827353C005 (Final) |
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Thurston GD, Ito K, Mar T, Christensen WF, Eatough DJ, Henry RC, Kim E, Laden F, Lall R, Larson TV, Liu H, Neas L, Pinto J, Stotzel M, Suh H, Hopke PK. Workgroup report: workshop on source apportionment of particulate matter health effects--Inter-Comparison of results and implications. Environmental Health Perspectives 2005;113(12):1768-1774. |
R827353 (Final) R827353C015 (Final) R827351 (Final) R827351C001 (Final) R827354 (Final) R827354C001 (Final) R827355 (Final) R827355C008 (Final) |
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Tsuda A, Rogers RA, Hydon PE, Butler JP. Chaotic mixing deep in the lung. Proceedings of the National Academy of Sciences of the United States of America 2002;99(15):10173-10178. |
R827353 (Final) R827353C009 (Final) |
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Wellenius GA, Saldiva PHN, Batalha JRF, Krishna Murthy GG, Coull BA, Verrier RL, Godleski JJ. Electrocardiographic changes during exposure to residual oil fly ash (ROFA) particles in a rat model of myocardial infarction. Toxicological Sciences 2002;66(2):327-335. |
R827353 (Final) R827353C008 (2001) R827353C008 (2002) R827353C008 (2003) R827353C008 (Final) |
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Wellenius GA, Coull BA, Godleski JJ, Koutrakis P, Okabe K, Savage ST, Lawrence JE, Krishna Murthy GG, Verrier RL. Inhalation of concentrated ambient air particles exacerbates myocardial ischemia in conscious dogs. Environmental Health Perspectives 2003;111(4):402-408. |
R827353 (Final) R827353C008 (2001) R827353C008 (2002) R827353C008 (2003) R827353C008 (Final) |
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Wellenius GA, Batalha JRF, Diaz EA, Lawrence J, Coull BA, Katz T, Verrier RL, Godleski JJ. Cardiac effects of carbon monoxide and ambient particles in a rat model of myocardial infarction. Toxicological Sciences 2004;80(2):367-376. |
R827353 (Final) R827353C008 (Final) |
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Wellenius GA, Schwartz J, Mittleman MA. Air pollution and hospital admissions for ischemic and hemorrhagic stroke among Medicare beneficiaries. Stroke 2005;36(12):2549-2553. |
R827353 (Final) R827353C004 (2004) R827353C004 (Final) |
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Wellenius GA, Bateson TF, Mittleman MA, Schwartz J. Particulate air pollution and the rate of hospitalization for congestive heart failure among Medicare beneficiaries in Pittsburgh, Pennsylvania. American Journal of Epidemiology 2005;161(11):1030-1036. |
R827353 (Final) R827353C004 (2004) R827353C004 (Final) |
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Wellenius GA, Coull BA, Batalha JRF, Diaz EA, Lawrence J, Godleski JJ. Effects of ambient particles and carbon monoxide on supraventricular arrhythmias in a rat model of myocardial infarction. Inhalation Toxicology 2006;18(14):1077-1082. |
R827353 (Final) R827353C008 (Final) |
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Wellenius GA, Schwartz J, Mittleman MA. Particulate air pollution and hospital admissions for congestive heart failure in seven United States cities. The American Journal of Cardiology 2006;97(3):404-408. |
R827353 (Final) R827353C004 (2004) R827353C004 (Final) |
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Wellenius GA, Yeh GY, Coull BA, Suh HH, Phillips RS, Mittleman MA. Effects of ambient air pollution on functional status in patients with chronic congestive heart failure: a repeated-measures study. Environmental Health 2007;6:26. |
R827353 (Final) R832416 (2006) |
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Wellenius GA, Mittleman MA. Disparities in myocardial infarction case fatality rates among the elderly: the 20-year Medicare experience. American Heart Journal 2008;156(3):483-490. |
R827353 (Final) |
not available |
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Wheeler A, Zanobetti A, Gold DR, Schwartz J, Stone P, Suh HH. The relationship between ambient air pollution and heart rate variability differs for individuals with heart and pulmonary disease. Environmental Health Perspectives 2006;114(4):560-566. |
R827353 (Final) R827353C003 (Final) |
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Zanobetti A, Schwartz J, Dockery D. Airborne particles are a risk factor for hospital admissions for heart and lung disease. Environmental Health Perspectives 2000;108(11):1071-1077. |
R827353 (Final) R827353C004 (2000) R827353C004 (Final) |
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Zanobetti A, Schwartz J, Gold D. Are there sensitive subgroups for the health effects of airborne particles? Environmental Health Perspectives 2000;108(9):841-845. |
R827353 (Final) R827353C004 (2000) R827353C004 (Final) |
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Zanobetti A, Wand MP, Schwartz J, Ryan LM. Generalized additive distributed lag models: quantifying mortality displacement. Biostatistics 2000;1(3):279-292. |
R827353 (Final) R827353C004 (2000) R827353C004 (2002) R827353C004 (2003) R827353C004 (Final) |
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Zanobetti A, Schwartz J. Race, gender, and social status as modifiers of the effects of PM10 on mortality. Journal of Occupational and Environmental Medicine 2000;42(5):469-474. |
R827353 (Final) R827353C004 (Final) |
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Zanobetti A, Schwartz J. Are diabetics more susceptible to the health effects of airborne particles? American Journal of Respiratory and Critical Care Medicine 2001;164(5):831-833. |
R827353 (Final) R827353C004 (2001) R827353C004 (Final) |
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Zanobetti A, Schwartz J, Samoli E, Gryparis A, Touloumi G, Atkinson R, Le Tertre A , Bobros J, Celko M, Goren A, Forsberg B, Michelozzi P, Rabczenko D, Aranguez Ruiz E, Katsouyanni K. The temporal pattern of mortality responses to air pollution: a multicity assessment of mortality displacement. Epidemiology 2002;13(1):87-93. |
R827353 (Final) R827353C004 (2002) R827353C004 (2003) R827353C004 (Final) |
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Zanobetti A, Schwartz J. Cardiovascular damage by airborne particles: Are diabetics more susceptible? Epidemiology 2002;13(5):588-592. |
R827353 (Final) R827353C004 (2001) R827353C004 (2002) R827353C004 (2003) R827353C004 (Final) R827353C005 (2003) R827353C005 (Final) |
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Zanobetti A, Schwartz J, Samoli E, Gryparis A, Touloumi G, Peacock J, Anderson RH, Le Tertre A , Bobros J, Celko M, Goren A, Forsberg B, Michelozzi P, Rabczenko D, Hoyos SP, Wichmann HE, Katsouyanni K. The temporal pattern of respiratory and heart disease mortality in response to air pollution. Environmental Health Perspectives 2003;111(9):1188-1193. |
R827353 (Final) R827353C004 (2002) R827353C004 (2003) R827353C004 (Final) |
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Zanobetti A, Schwartz J. The effect of particulate air pollution on emergency admissions for myocardial infarction: a multicity case-crossover analysis. Environmental Health Perspectives 2005;113(8):978-982. |
R827353 (Final) R827353C004 (2004) R827353C004 (Final) |
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Zanobetti A, Schwartz J. Air pollution and emergency admissions in Boston, MA. Journal of Epidemiology and Community Health 2006;60(10):890-895. |
R827353 (Final) R827353C004 (Final) R827353C005 (Final) |
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Zanobetti A, Schwartz J. Particulate air pollution, progression, and survival after myocardial infarction. Environmental Health Perspectives 2007;115(5):769-775. |
R827353 (Final) |
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Zeka A, Schwartz J. Estimating the independent effects of multiple pollutants in the presence of measurement error:an application of a measurement-error-resistant technique. Environmental Health Perspectives 2004;112(17):1686-1690. |
R827353 (Final) |
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Zeka A, Zanobetti A, Schwartz J. Short term effects of particulate matter on cause specific mortality: effects of lags and modification by city characteristics. Occupational and Environmental Medicine 2005;62(10):718-725. |
R827353 (Final) R827353C005 (Final) |
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Zeka A, Zanobetti A, Schwartz J. Individual-level modifiers of the effects of particulate matter on daily mortality. American Journal of Epidemiology 2006;163(9):849-859. |
R827353 (Final) R827353C004 (Final) |
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Zeka A, Sullivan JR, Vokonas PS, Sparrow D, Schwartz J. Inflammatory markers and particulate air pollution: characterizing the pathway to disease. International Journal of Epidemiology 2006;35(5):1347-1354. |
R827353 (Final) R827353C004 (Final) R827353C010 (Final) |
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Air, Geographic Area, Scientific Discipline, Health, RFA, Susceptibility/Sensitive Population/Genetic Susceptibility, Molecular Biology/Genetics, Toxicology, Biology, indoor air, Risk Assessments, genetic susceptability, Epidemiology, air toxics, Children's Health, Environmental Engineering, Environmental Microbiology, particulate matter, Environmental Chemistry, Environmental Monitoring, State, tropospheric ozone, ambient measurement methods, cardiopulmonary, risk assessment, California (CA), Maryland (MD), exposure and effects, ambient air quality, cardiovascular disease, health effects, indoor air quality, inhalation, developmental effects, epidemelogy, animal inhalation study, respiratory disease, inhalation toxicology, air quality, ambient air, cardiopulmonary response, indoor exposure, lead, molecular epidemiology, assessment of exposure, cardiopulmonary responses, human health risk, interindividual variability, monitoring, susceptibility, genetic susceptibility, particle exposure, epidemeology, air pollutants, human health effects, particulates, respiratory, sensitive populations, measurement methods , biological response, ambient particle health effects, air pollution, ambient monitoring, children, metals, microbiology, stratospheric ozone, ambient air monitoring, chemical exposure, dosimetry, exposure, inhaled particles, pulmonary, human health, human susceptibility, environmental health hazard, biological mechanism , health risks, human exposure, Human Health Risk Assessment, PM, pulmonary disease, Massachusetts (MA), Georgia (GA)
Relevant Websites:
http://www.hsph.harvard.edu/epacenter/epa_center_99-05/index.html
Progress and Final Reports:
Original Abstract
Subprojects under this Center:
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
R827353C001 Assessing Human Exposures to Particulate and Gaseous Air Pollutants
R827353C002 Quantifying Exposure Error and its Effect on Epidemiological
Studies
R827353C003 St. Louis Bus, Steubenville and Atlanta Studies
R827353C004 Examining Conditions That Predispose Towards
Acute Adverse Effects of Particulate Exposures
R827353C005 Assessing Life-Shortening Associated with Exposure to
Particulate Matter
R827353C006 Investigating Chronic Effects of Exposure to Particulate
Matter
R827353C007 Determining the Effects of Particle Characteristics on Respiratory Health of Children
R827353C008 Differentiating the Roles of Particle Size, Particle Composition,
and Gaseous Co-Pollutants on Cardiac Ischemia
R827353C009 Assessing Deposition of Ambient Particles in the Lung
R827353C010 Relating Changes in Blood Viscosity, Other Clotting Parameters,
Heart Rate, and Heart Rate Variability to Particulate and Criteria Gas Exposures
R827353C011 Studies of Oxidant Mechanisms
R827353C012 Modeling Relationships Between Mobile Source Particle Emissions and Population Exposures
R827353C013 Toxicological Evaluation of Realistic Emissions of Source Aerosols (TERESA) Study
R827353C014 Identifying the Physical and Chemical Properties of Particulate Matter Responsible for the Observed Adverse Health Effects
R827353C015 Research Coordination Core
R827353C016 Analytical and Facilities Core
R827353C017 Technology Development and Transfer Core