Faculty Bibliography

BACKGROUND: Quantification of the disease burden caused by different risks informs prevention by providing an account of health loss different to that provided by a disease-by-disease analysis. No complete revision of global disease burden caused by risk factors has been done since a comparative risk assessment in 2000, and no previous analysis has assessed changes in burden attributable to risk factors over time. METHODS: We estimated deaths and disability-adjusted life years (DALYs; sum of years lived with disability [YLD] and years of life lost [YLL]) attributable to the independent effects of 67 risk factors and clusters of risk factors for 21 regions in 1990 and 2010. We estimated exposure distributions for each year, region, sex, and age group, and relative risks per unit of exposure by systematically reviewing and synthesising published and unpublished data. We used these estimates, together with estimates of cause-specific deaths and DALYs from the Global Burden of Disease Study 2010, to calculate the burden attributable to each risk factor exposure compared with the theoretical-minimum-risk exposure. We incorporated uncertainty in disease burden, relative risks, and exposures into our estimates of attributable burden. FINDINGS: In 2010, the three leading risk factors for global disease burden were high blood pressure (7.0% [95% uncertainty interval 6.2-7.7] of global DALYs), tobacco smoking including second-hand smoke (6.3% [5.5-7.0]), and alcohol use (5.5% [5.0-5.9]). In 1990, the leading risks were childhood underweight (7.9% [6.8-9.4]), household air pollution from solid fuels (HAP; 7.0% [5.6-8.3]), and tobacco smoking including second-hand smoke (6.1% [5.4-6.8]). Dietary risk factors and physical inactivity collectively accounted for 10.0% (95% UI 9.2-10.8) of global DALYs in 2010, with the most prominent dietary risks being diets low in fruits and those high in sodium. Several risks that primarily affect childhood communicable diseases, including unimproved water and sanitation and childhood micronutrient deficiencies, fell in rank between 1990 and 2010, with unimproved water and sanitation accounting for 0.9% (0.4-1.6) of global DALYs in 2010. However, in most of sub-Saharan Africa childhood underweight, HAP, and non-exclusive and discontinued breastfeeding were the leading risks in 2010, while HAP was the leading risk in south Asia. The leading risk factor in Eastern Europe, most of Latin America, and southern sub-Saharan Africa in 2010 was alcohol use; in most of Asia, North Africa and Middle East, and central Europe it was high blood pressure. Despite declines, tobacco smoking including second-hand smoke remained the leading risk in high-income north America and western Europe. High body-mass index has increased globally and it is the leading risk in Australasia and southern Latin America, and also ranks high in other high-income regions, North Africa and Middle East, and Oceania. INTERPRETATION: Worldwide, the contribution of different risk factors to disease burden has changed substantially, with a shift away from risks for communicable diseases in children towards those for non-communicable diseases in adults. These changes are related to the ageing population, decreased mortality among children younger than 5 years, changes in cause-of-death composition, and changes in risk factor exposures. New evidence has led to changes in the magnitude of key risks including unimproved water and sanitation, vitamin A and zinc deficiencies, and ambient particulate matter pollution. The extent to which the epidemiological shift has occurred and what the leading risks currently are varies greatly across regions. In much of sub-Saharan Africa, the leading risks are still those associated with poverty and those that affect children. FUNDING: Bill & Melinda Gates Foundation.

Background: Asthma is a growing epidemic in the United States. Associations of acute air pollution with asthma hospital admissions have been shown to be modified by co-morbid conditions. However, no known previous study has investigated the modifying effects of concurrent respiratory infections, specifically bronchitis and upper respiratory infection (URI), on these associations. Methods: Data for 105,914 unscheduled hospital admissions in New York City with a primary diagnosis of asthma were obtained for years 2003-2006. A Poisson generalized linear model was applied to determine the association of inter-quartile increases in daily ambient air pollution (i.e., PM2.5, NO2, SO2, and O3) exposures with asthma hospital admissions, after controlling for meteorological and temporal variables. Stratified analyses were conducted for admissions with secondary diagnoses of bronchitis and URI, respectively. Results: Air pollution associations of asthma admissions with a secondary diagnosis of bronchitis were significantly higher vs. admissions without a secondary diagnosis of bronchitis (e.g., PM2.5 risk ratios are 1.19 (95% CI = 1.07-1.30) with bronchitis vs. 1.05 (95% CI = 1.02-1.07) without bronchitis). However, secondary diagnoses of URI did not modify the associations of air pollutants with asthma hospital admissions. These results were observed across multiple pollutants and age groups. Discussion: There is an increased risk of air pollution related asthma hospital admission among individuals with bronchitis, but not with URI. The identification of differential risks based on infection of the bronchioles, but not the upper respiratory tract, provides an opportunity for further investigation into the mechanisms by which air pollution affects respiratory function

Background: Multi-city time-series and long-term cohort studies have reported associations between PM2.5 and both mortality and hospitalizations. However, the specific PM components most responsible for the observed associations have not been established. Objective: To identify PM2.5 sources responsible for both short- and long-term health effects. Methods: We examined both acute and long-term epidemiological associations across the U.S. Using Poisson modeling, daily mortality (years 2001-2006), and elderly hospitalizations (years 2000-2008) were associated with PM2.5 and its chemical components using EPA's CSN data in 150 U.S. cities, and separately for a 64 cities sub-set where PM2.5, its chemical constituents, and gaseous pollutant data were all available. Using the nationwide American Cancer Society CPS-II Cohort, we similarly investigated U.S. mortality associations with components of long-term PM2.5 exposures.. Results: Nationwide factor analyses identified seven major sources: Traffic, Soil, Coal combustion, Salt, Metals, Biogenic Burning, and Residual Oil combustion. The Traffic factor showed most consistent associations with daily all-cause mortality, and with CVD and respiratory hospitalizations. Our extended ACS cohort follow-up analyses (through 2004) indicated that Coal Combustion PM2.5 was most consistently associated with increased risk of IHD mortality. Soil or Wood burning sources were consistently not associated with any causes of mortality. Conclusions: Associations of components of PM2.5 and health varied by outcome (hospitalization vs. mortality), by cause (cardiac vs. respiratory), and between acute and long-term exposures. In general, acute morbidity and mortality associations were most related to traffic-related components, while chronic mortality was most strongly associated with long-term exposure to Coal Combustion PM2.5

Background. Particulate matter (PM) is a complex mixture of chemical constituents affecting health risks. However, current health-based PM standards are limited to mass concentrations. Objective. To conduct an integrated series of toxicology and epidemiology studies to determine which PM components are most influential. Methods. Using EPA's CSN data enabled us to study the influence of PM2.5 components on: 1) shortterm human morbidity and mortality in 150 US cities; and 2) annual mortality rates in 100 US cities. We also conducted: 3) a series of 6-month subchronic inhalation studies (6 h/d, 5 d/wk) of concentrated (10X) ambient air PM2.5 (CAPs) in ApoE-/- mice in five U.S. airsheds; and 4) we administered aliquots of PM10-2.5, PM2.5-0.2, and PM<0.2 samples from the same 5 airsheds to cells in vitro, and to mouse lungs in vivo by aspiration to determine their comparative acute effects. Results. Across all four substudies, fossil-fuel combustion sources were most consistently associated with both short- and long-term cardiovascular disease (CVD) effects. Daily human CVD mortality and hospital admissions, and cardiac function in the mice, were most closely associated with constituents from residual oil combustion and traffic, while annual human CVD mortality and aortic plaque progression in the mice were more closely associated with coal combustion effluents. Conclusions. 1) PM toxicity is driven by a complex interaction of particle size, study site, and season; 2) the most influential constituents vary with endpoint. These results can: 1) guide future research; selection of emission controls; and 3) optimization of the public health benefits

Background: Which components of ambient air particulate matter (PM) are most associated with adverse health effects is less well known. In addition, current Chemical Speciation Network (CSN) data, with every 3rd/6th day sampling schedule, do not allow an examination of multi-day effects of chemical components. Objectives: To determine the associations between daily PM2.5 (PM < 2.5 mum in aerodynamic diameter) components and hospitalizations in Seattle and Detroit using time-series analyses. Methods: We obtained daily PM2.5 Teflon filters for the years of 2002-2004 and analyzed trace elements using X-ray fluorescence, and black carbon (BC) using light reflectance as a surrogate measure of elemental carbon (EC). We used Poisson regression and distributed-lag models to estimate cumulative effects (lags of 0 through 2 days) for cardiovascular and respiratory diseases, with adjustments for time-varying covariates. We computed the excess risks for interquartile range (IQR) increases of each pollutant component for both warm and cold seasons. Results: The PM2.5 components and gaseous pollutants most closely associated with cardiovascular and respiratory hospitalization in Detroit were secondary aerosols, traffic markers, and biomass combustion; while in Seattle, those for cold season traffic emissions and residual oil burning. Conclusions: The effects of PM2.5 on daily hospitalizations vary with source, season, and locale, consistent with the hypothesis that PM2.5 composition has an appreciable influence on the health effects attributable to PM2.5. The multi-day risk estimates were generally bigger than individual day effects, suggesting that risk assessments using a single day lag model are likely to underestimate the health impacts

Ambient air pollution is associated with numerous adverse health impacts. Previous assessments of global attributable disease burden have been limited to urban areas or by coarse spatial resolution of concentration estimates. Recent developments in remote sensing, global chemical-transport models, and improvements in coverage of surface measurements facilitate virtually complete spatially resolved global air pollutant concentration estimates. We combined these data to generate global estimates of long-term average ambient concentrations of fine particles (PM(2.5)) and ozone at 0.1 degrees x 0.1 degrees spatial resolution for 1990 and 2005. In 2005, 89% of the world's population lived in areas where the World Health Organization Air Quality Guideline of 10 mug/m(3) PM(2.5) (annual average) was exceeded. Globally, 32% of the population lived in areas exceeding the WHO Level 1 Interim Target of 35 mug/m(3), driven by high proportions in East (76%) and South (26%) Asia. The highest seasonal ozone levels were found in North and Latin America, Europe, South and East Asia, and parts of Africa. Between 1990 and 2005 a 6% increase in global population-weighted PM(2.5) and a 1% decrease in global population-weighted ozone concentrations was apparent, highlighted by increased concentrations in East, South, and Southeast Asia and decreases in North America and Europe. Combined with spatially resolved population distributions, these estimates expand the evaluation of the global health burden associated with outdoor air pollution.

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