Faculty Bibliography

Population-based personal exposures to particulate matter (PM) and personal-ambient relationships of PM and component concentrations for outpatients with COPD and/or asthma were investigated in New York City (NYC) and Seattle for thoracic PM (PM(10)) and fine PM (PM(2.5)). Measurements of outdoor, indoor, and personal PM(10) and PM(2.5) concentrations were made concurrently for 12-consecutive days at 24 patients' residences. Filters were analyzed for elemental components, using XRF and black carbon (BC), by reflectance. Daily morning and evening measurements of heart rate (HR) and blood oxygen saturation (SpO(2)) by pulse oximeter, and forced expiratory volume in 1 s (FEV(1)) and peak expiratory flowrate (PEF) by spirometry were also measured, and symptom data were collected. Central monitoring site, outdoor, indoor, and personal concentration-response relationships of PM(2.5), PM(10-2.5), and their components were examined using mixed-effect models. The relatively small sample size of the study limited the interpretation of results, but of the PM chemical components examined, only nickel concentrations showed consistent associations, and only with HR in the NYC COPD patients.

Using daily fine particulate matter (PM2.5) composition data from the 2000-2005 U.S. EPA Chemical Speciation Network (CSN) for over 200 sites, we applied multivariate methods to identify and quantify the major fine particulate matter (PM2.5) source components in the U.S. Novel aspects of this work were: (1) the application of factor analysis (FA) to multi-city daily data, drawing upon both spatial and temporal variations of chemical species; and, (2) the exclusion of secondary components (sulfates, nitrates and organic carbon) from the source identification FA to more clearly discern and apportion the PM2.5 mass to primary emission source categories. For the quantification of source-related mass, we considered two approaches based upon the FA results: 1) using single key tracers for sources identified by FA in a mass regression; and, 2) applying Absolute Principal Component Analysis (APCA). In each case, we followed a two-stage mass regression approach, in which secondary components were first apportioned among the identified sources, and then mass was apportioned to the sources and to other secondary mass not explained by the individual sources. The major U.S. PM2.5 source categories identified via FA (and their key elements) were: Metals Industry (Pb, Zn); Crustal/Soil Particles (Ca, Si); Motor Vehicle Traffic (EC, NO2); Steel Industry (Fe, Mn); Coal Combustion (As, Se); Oil Combustion (V, Ni); Salt Particles (Na, Cl) and Biomass Burning (K). Nationwide spatial plots of the source-related PM2.5 impacts were confirmatory of the factor interpretations: ubiquitous sources, such as Traffic and Soil, were found to be spread across the nation, more unique sources (such as Steel and Metals Processing) being highest in select industrialized cities, Biomass Burning was highest in the U.S. Northwest, while Residual Oil combustion was highest in cities in the Northeastern U.S. and in cities with major seaports. The sum of these source contributions and the secondary PM2.5 components agreed well with the U.S. PM2.5 observed during the study period (mean=14.3 ug/m3; R2= 0.91). Apportionment regression analyses using single-element tracers for each source category gave results consistent with the APCA estimates. Comparisons of nearby sites indicated that the PM2.5 mass and the secondary aerosols were most homogenous spatially, while traffic PM2.5 and its tracer, EC, were among the most spatially representative of the source-related components. Comparison of apportionment results to a previous analysis of the 1979-1982 IP Network revealed similar and correlated major U.S. source category factors, albeit at lower levels than in the earlier period, suggesting a consistency in the U.S. spatial patterns of these source-related exposures over time, as well. These results indicate that applying source apportionment methods to the nationwide CSN can be an informative avenue for identifying and quantifying source components for the subsequent estimation of source-specific health effects, potentially contributing to more efficient regulation of PM2.5.

Background: Past time-series studies of the health effects of fine particulate matter [aerodynamic diameter </= 2.5 microm (PM2.5)] have used chemically nonspecific PM2.5 mass. However, PM2.5 is known to vary in chemical composition with source, and health impacts may vary accordingly.Objective: We tested the association between source-specific daily PM2.5 mass and hospital admissions in a time-series investigation that considered both single-lag and distributed-lag models.Methods: Daily PM2.5 speciation measurements collected in midtown Manhattan were analyzed via positive matrix factorization source apportionment. Daily and distributed-lag generalized linear models of Medicare respiratory and cardiovascular hospital admissions during 2001-2002 considered PM2.5 mass and PM2.5 from five sources: transported sulfate, residual oil, traffic, steel metal works, and soil.Results: Source-related PM2.5 (specifically steel and traffic) was significantly associated with hospital admissions but not with total PM2.5 mass. Steel metal works-related PM2.5 was associated with respiratory admissions for multiple-lag days, especially during the cleanup efforts at the World Trade Center. Traffic-related PM2.5 was consistently associated with same-day cardiovascular admissions across disease-specific subcategories. PM2.5 constituents associated with each source (e.g., elemental carbon with traffic) were likewise associated with admissions in a consistent manner. Mean effects of distributed-lag models were significantly greater than were maximum single-day effect models for both steel- and traffic-related PM2.5.Conclusions: Past analyses that have considered only PM2.5 mass or only maximum single-day lag effects have likely underestimated PM2.5 health effects by not considering source-specific and distributed-lag effects. Differing lag structures and disease specificity observed for steel-related versus traffic-related PM2.5 raise the possibility of distinct mechanistic pathways of health effects for particles of differing chemical composition

BACKGROUND: Recent toxicological and epidemiological studies have shown associations between particulate matter (PM) and adverse health effects, but which PM components are most influential is less well known. OBJECTIVES: In this study, we used time-series analyses to determine the associations between daily fine PM [PM </= 2.5 microm in aerodynamic diameter (PM2.5)] concentrations and daily mortality in two U.S. cities-Seattle, Washington, and Detroit, Michigan. METHODS: We obtained daily PM2.5 filters for the years of 2002-2004 and analyzed trace elements using X-ray fluorescence and black carbon using light reflectance as a surrogate measure of elemental carbon. We used Poisson regression and distributed lag models to estimate excess deaths for all causes and for cardiovascular and respiratory diseases adjusting for time-varying covariates. We computed the excess risks for interquartile range increases of each pollutant at lags of 0 through 3 days for both warm and cold seasons. RESULTS: The cardiovascular and respiratory mortality series exhibited different source and seasonal patterns in each city. The PM2.5 components and gaseous pollutants associated with mortality in Detroit were most associated with warm season secondary aerosols and traffic markers. In Seattle, the component species most closely associated with mortality included those for cold season traffic and other combustion sources, such as residual oil and wood burning. CONCLUSIONS: The effects of PM2.5 on daily mortality vary with source, season, and locale, consistent with the hypothesis that PM composition has an appreciable influence on the health effects attributable to PM

Background: Recent time-series studies have indicated that both cardiovascular disease (CVD)mortality and hospitalizations are associated with particulate matter (PM). However, seasonal patterns of PM associations with these outcomes are not consistent, and PM components responsible for these associations have not been determined. We investigated this issue in New York City (NYC), where PM originates from regional and local combustion sources.Objective: In this study, we examined the role of particulate matter with aerodynamic diameter </= 2.5 microm (PM2.5) and its key chemical components on both CVD hospitalizations and on mortality in NYC.Methods: We analyzed daily deaths and emergency hospitalizations for CVDs among persons >/= 40 years of age for associations with PM2.5, its chemical components, nitrogen dioxide (NO2), carbon monoxide, and sulfur dioxide for the years 2000-2006 using a Poisson time-series model adjusting for temporal and seasonal trends, temperature effects, and day of the week. We estimated excess risks per interquartile-range increases at lags 0 through 3 days for warm (April through September) and cold (October through March) seasons.Results: The CVD mortality series exhibit strong seasonal trends, whereas the CVD hospitalization series show a strong day-of-week pattern. These outcome series were not correlated with each other but were individually associated with a number of PM2.5 chemical components from regional and local sources, each with different seasonal patterns and lags. Coal-combustion-related components (e.g., selenium) were associated with CVD mortality in summer and CVD hospitalizations in winter, whereas elemental carbon and NO2 showed associations with these outcomes in both seasons.Conclusion: Local combustion sources, including traffic and residual oil burning, may play a year-round role in the associations between air pollution and CVD outcomes, but transported aerosols may explain the seasonal variation in associations shown by PM2.5 mass

BACKGROUND: Prospective syndromic surveillance of emergency department visits has been used for near-real time tracking of communicable diseases to detect outbreaks or other unexpected disease clusters. The utility of syndromic surveillance for tracking cardiovascular events, which may be influenced by environmental factors and influenza, has not been evaluated. We developed and evaluated a method for tracking cardiovascular events using emergency department free-text chief complaints. METHODOLOGY/PRINCIPAL FINDINGS: There were three phases to our analysis. First we applied text processing algorithms based on sensitivity, specificity, and positive predictive value to chief complaint data reported by 11 New York City emergency departments for which ICD-9 discharge diagnosis codes were available. Second, the same algorithms were applied to data reported by a larger sample of 50 New York City emergency departments for which discharge diagnosis was unavailable. From this more complete data, we evaluated the consistency of temporal variation of cardiovascular syndromic events and hospitalizations from 76 New York City hospitals. Finally, we examined associations between particulate matter </=2.5 microm (PM(2.5)), syndromic events, and hospitalizations. Sensitivity and positive predictive value were low for syndromic events, while specificity was high. Utilizing the larger sample of emergency departments, a strong day of week pattern and weak seasonal trend were observed for syndromic events and hospitalizations. These time-series were highly correlated after removing the day-of-week, holiday, and seasonal trends. The estimated percent excess risks in the cold season (October to March) were 1.9% (95% confidence interval (CI): 0.6, 3.2), 2.1% (95% CI: 0.9, 3.3), and 1.8% (95%CI: 0.5, 3.0) per same-day 10 microg/m(3) increase in PM(2.5) for cardiac-only syndromic data, cardiovascular syndromic data, and hospitalizations, respectively. CONCLUSIONS/SIGNIFICANCE: Near real-time emergency department chief complaint data may be useful for timely surveillance of cardiovascular morbidity related to ambient air pollution and other environmental events

Cardiovascular morbidity has been associated with particulate matter (PM) air pollution, although the relation between pollutants and sudden death from cardiac arrest has not been established. This study examined associations between out-of-hospital cardiac arrests and fine PM (of aerodynamic diameter </=2.5 mum, or PM(2.5)), ozone, nitrogen dioxide, sulfur dioxide, and carbon monoxide in New York City. The authors analyzed 8,216 out-of-hospital cardiac arrests of primary cardiac etiology during the years 2002-2006. Time-series and case-crossover analyses were conducted, controlling for season, day-of-week, same-day, and delayed/apparent temperature. An increased risk of cardiac arrest in time-series (relative risk (RR) = 1.06, 95% confidence interval (CI): 1.02, 1.10) and case-crossover (RR = 1.04, 95% CI: 0.99, 1.08) analysis for a PM(2.5) increase of 10 mug/m(3) in the average of 0- and 1-day lags was found. The association was significant in the warm season (RR = 1.09, 95% CI: 1.03, 1.15) but not the cold season (RR = 1.01, 95% CI: 0.95, 1.07). Associations of cardiac arrest with other pollutants were weaker. These findings, consistent with studies implicating acute cardiovascular effects of PM, support a link between PM(2.5) and out-of-hospital cardiac arrests. Since few individuals survive an arrest, air pollution control may help prevent future cardiovascular mortality

BACKGROUND: Ambient fine particles (particular matter <2.5 microm diameter [PM(2.5)]) and ozone exacerbate respiratory conditions including asthma. There is little documentation determining whether children are more vulnerable to the effects of ambient pollution than adults, or whether pollution causes life-threatening episodes requiring intensive care unit (ICU) admission. OBJECTIVE: We investigate the relationship between severe asthma morbidity and PM(2.5) and ozone in the warm season, and determine whether there is an age-related susceptibility to pollution. METHODS: Daily time-series analysis of 6008 asthma ICU admissions and 69,375 general (non-ICU) asthma admissions in 4 age groups (<6, 6-18, 19-49, and 50+ years) in 74 New York City hospitals for the months April to August from 1999 to 2006. The regression model adjusted for temporal trends, weather, and day of the week. Risks were estimated for interquartile range increases in the a priori exposure time window of the average of 0-day and 1-day lagged pollutants. RESULTS: Age was a significant effect modifier for hospitalizations, and children age 6 to 18 years consistently had the highest risk. Among children age 6 to 18 years, there was a 26% (95% CI, 10% to 44%) increased rate of ICU admissions and a 19% increased rate of general hospitalizations (95% CI, 12% to 27%) for each 12-microg/m(3) increase in PM(2.5). For each 22-ppb increase in ozone, there was a 19% (95% CI, 1% to 40%) increased risk for ICU admissions and a 20% (95% CI, 11% to 29%) increased risk for general hospitalizations. CONCLUSION: Warm weather patterns of ozone and PM(2.5) disproportionately affect children with asthma and appear responsible for severe attacks that could have been avoided