2006 Progress Report: Chronic Exposure to Particulate Matter and Cardiopulmonary Disease

EPA Grant Number: R830545
Title: Chronic Exposure to Particulate Matter and Cardiopulmonary Disease
Investigators: Laden, Francine , Camargo, Carlos , Neas, Lucas M. , Schwartz, Joel , Speizer, Frank E. , Suh, Helen H.
Current Investigators: Laden, Francine , Camargo, Carlos , Puett, Robin C. , Schwartz, Joel , Speizer, Frank E. , Suh, Helen H. , Yanosky, Jeff D.
Institution: Brigham and Women’s Hospital , U. S. Environmental Protection Agency
Current Institution: Brigham and Women's Hospital, Inc.
EPA Project Officer: Chung, Serena
Project Period: January 20, 2003 through January 19, 2006 (Extended to January 19, 2008)
Project Period Covered by this Report: January 20, 2006 through January 19,2007
Project Amount: $933,602
RFA: Epidemiologic Research on Health Effects of Long-Term Exposure to Ambient Particulate Matter and Other Air Pollutants (2002) RFA Text |  Recipients Lists
Research Category: Air Quality and Air Toxics , Health Effects , Particulate Matter , Air

Objective:

We proposed:  (1) to develop a model estimating long-term exposure to air pollution in the continental United States using existing databases, including the U.S. Environmental Protection Agency (EPA) Air Quality System (AQS); and (2) to evaluate the association of chronic exposure to air pollution with incident coronary and respiratory disease and total mortality in the Nurses’ Health Study (NHS), an ongoing prospective cohort study of 121,700 women residing throughout the United States.  We hypothesize that the incidence of these diseases and total mortality are positively associated with air pollution and that exposure to air pollution exacerbates existing disease.  We also hypothesize that the association with coronary heart disease will be greater among diabetics than nondiabetics and that consumption of antioxidants will modify the association.

Approach:

The basic approach is threefold: (1) to use existing data sources to create a model for exposure to air pollution throughout the U.S.; (2) to link the yearly average exposure to the residential addresses of the study participants; and (3) to evaluate the relative risk of the outcomes in the high compared with the low exposure areas. We will model long-term exposure to air pollution for the years 1986 through 2000 using data from the EPA's Aerometric Information Retrieval System (AIRS), the National Emissions Trends database, National Oceanic and Atmospheric Association, and commercially available traffic count data. Existing ambient monitoring data from specific sites will be used to supplement this information. Residential addresses are updated every two years and will be mapped using geographic information system (GIS) software and linked to the exposure model. Incident cases of cardiovascular disease and of chronic obstructive pulmonary disease, asthma, and lung cancer, diagnosed during the study period, are identified routinely on the NHS biennial self-administered questionnaire. Cases are confirmed by supplemental questionnaire and review of medical records. Mortality is reported by next-of-kin and also obtained by regular searches of the National Death Index. We will estimate the relative risks of these outcomes associated with air pollution using the proportional hazards model, including adjustment for smoking, and other confounders. We will also assess interactions with comorbid diabetes and consumption of antioxidants.

Progress Summary:

We have developed a predictive model of particulate matter less than 10 microns in diameter (PM10) for the northeastern United States for the years 1988 through 2002.  Finalization of a similar model for PM2.5 is currently underway.  These models quantify chronic ambient exposure to air pollution in survival analyses of mortality and chronic disease outcomes in the Nurses’ Health Study.  Follow-up questionnaires are mailed to participants every 2 years, thereby providing a complete residential address history.  The 1988 through 2002 addresses have been geocoded and will provide a link to the prediction models.

Air Pollution Modeling
 
Our PM10 prediction model is a generalized, additive-mixed model that includes monthly smooth spatial terms and smooth regression terms of GIS-derived and meteorological covariates and incorporated PM10 data from monitoring sites in EPA’s Air Quality System (AQS), the Interagency Monitoring of Protected Visual Environments (IMPROVE) network, and Harvard research studies.  This model structure allows for highly spatially and temporally resolved predictions of chronic PM exposures, even for individuals living in areas with no nearby monitors (albeit with greater uncertainty for locations with distant monitors).  GIS-derived model covariates included block group and county-level population density; distance to nearest road by Census Feature Class Code road class; elevation from the U.S. Geological Survey (USGS) National Elevation Dataset; land use/land cover from the USGS National Land Cover Dataset; primary PM10 emissions information from the EPA National Emissions Inventory (NEI); and meteorological variables, including wind speed and precipitation, from the National Climatic Data Center (NCDC).
 
PM2.5 monitoring data are not available on a national level until 1999.  Therefore, to predict PM2.5 levels for earlier time periods, we are using observations of horizontal visual range made at Weather Bureau/Army/Navy (WBAN) stations (about 430 nationwide), after correcting for the truncated nature of the observations, as a predictor for PM2.5.  Our models use the above-mentioned corrected visibility observations, PM10 predictions, and the PM2.5 monitoring data collected from 1999 to 2002 to estimate monthly average PM2.5 levels back in time to 1988.
 
Epidemiologic Analyses
 
We have used Cox proportional hazards models to examine the associations of PM10 with nonfatal myocardial infarction, fatal coronary heart disease, strokes, and all causes of mortality for various time periods of exposure.  We have explored potential confounders and effect modifiers, including:  smoking, physical activity, body mass index (BMI), physician-diagnosed hypertension and diabetes, hormone use, menopausal status, median family income of census tract of residence, and median household value of census tract of residence.  We are currently finalizing our geographic sensitivity analyses and our assessment of effect modification and confounding for all cause mortality and cardiovascular outcomes.  We will similarly analyze the associations between chronic air pollution exposure and respiratory disease outcomes.

Expected Results:

Although there is a substantial body of literature demonstrating the adverse health effects associated with air pollution, to date there have only been two large cohort studies of mortality. This proposed study will not only evaluate mortality but it will be the first study to prospectively evaluate cause-specific incident disease on a nationwide basis. Further, it will provide information on the extent of life shortening associated with the exposure by measuring survival and severity of disease after the first event.

Future Activities:

In the coming funding year, we will expand the PM10 model to the entire nation, and we will refine and expand the PM2.5 exposure model.  In addition, we will refine our Cox proportional hazards models of the associations of chronic PM10 exposure with lung cancer, asthma, and chronic obstructive pulmonary disease.  We will also use Cox proportional hazards models to examine the associations of chronic PM2.5 exposure with mortality and chronic health outcomes.  Through this modeling process, we will examine potential confounders and effect modifiers, such as:  smoking, physical activity, BMI, physician-diagnosed hypertension, and diabetes.

Journal Articles:

No journal articles submitted with this report: View all 12 publications for this project

Supplemental Keywords:

epidemiology, health effects, ambient air, particulates,  environmental monitoring, PM2.5, PM10, air pollutants, cardiovascular disease, chronic effects, chronic exposure, human exposure, mortality, exposure modeling, GIS, geocoding, asthma, chronic obstructive pulmonary disease, myocardial infarction, antioxidants, lung cancer, diabetes, smoking, physical activity, epidemiology, health effects, ambient air, particulates, susceptibility, diet,, RFA, Health, Scientific Discipline, PHYSICAL ASPECTS, Air, Ecosystem Protection/Environmental Exposure & Risk, HUMAN HEALTH, particulate matter, Bioavailability, Health Risk Assessment, air toxics, Exposure, Epidemiology, Monitoring/Modeling, Risk Assessments, Disease & Cumulative Effects, Environmental Monitoring, Physical Processes, tropospheric ozone, particulates, health effects, ambient air quality, sensitive populations, urban air, atmospheric measurements, EMPACT, chronic exposure, monitoring, PM 2.5, air pollutants, effects assessment, particulate, stratospheric ozone, acute cardiovascular effects, airway disease, pulmonary disease, ozone, continuous monitoring, ambient air, air pollution, children, carbon black, particles, human exposue, clinical studies, human exposure, chronic effects, sensitive subgroups, ecological risk, ambient particulates, Acute health effects, PM2.5, allergic response, cardiotoxicity, mortality, measurement methods , atmospheric chemistry, long-term exposure, cardiopulmonery responses, cardiovascular disease

Progress and Final Reports:

Original Abstract
  • 2003 Progress Report
  • 2004 Progress Report
  • 2005 Progress Report
  • Final Report