2005 Progress Report: Relating Cardiovascular Disease Risk to Ambient Air Pollutants Using Geographic Information Systems Technology and Bayesian Neural Networks: The AHSMOG Study

EPA Grant Number: R830547
Title: Relating Cardiovascular Disease Risk to Ambient Air Pollutants Using Geographic Information Systems Technology and Bayesian Neural Networks: The AHSMOG Study
Investigators: Knutsen, Synnove F. , Beeson, Larry , Ghamsary, Mark , Soret, Samuel
Institution: Loma Linda University
EPA Project Officer: Chung, Serena
Project Period: February 1, 2003 through December 31, 2006 (Extended to January 31, 2009)
Project Period Covered by this Report: February 1, 2005 through December 31, 2006
Project Amount: $964,436
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: Health Effects , Particulate Matter , Air

Objective:

The primary objective of this project is to determine the association between cardiovascular disease and long-term particulate ambient pollutants in 6,338 nonsmoking California Seventh-day Adventists.  The outcomes include both fatal and nonfatal coronary heart disease (CHD) as well as other cardiovascular disease during 22 years of followup.  Further, the objectives are to assess the same effects in sensitive subgroups (e.g., prevalent cardiovascular disease [CVD], hypertensives, diabetics, elderly).

Further, this study aims to assess whether other pollutants (specifically gaseous pollutants) modify the association between particulate pollution and CVD.

Approach

  1. Utilize data from the existing Adventist Health and Smog (AHSMOG) Study, which has been updated through March 2000 through the current U.S. Environmental Protection Agency (EPA) Science To Achieve Results (STAR) Grant (R827998).  These data include monthly indices of air pollutants to ZIP code centroids, monthly residence and work location histories, outcome assessment (CHD, fatal and nonfatal) and assessment of relevant confounders (smoking, environmental tobacco smoke, diet, exercise, etc.).
  2. Develop new indices of ambient air pollutants for the individual subjects in the AHSMOG Study using geographic information systems (GIS) technology and stochastic models that include error estimates of the indices.
  3. Develop nonlinear statistical models using Bayesian neural networks to develop alternative analytical strategies for modeling the relationship between different ambient air pollutants and risk of CHD where several pollutants and latent (unobserved) and missing values can be incorporated.
  4. Compare new methods developed under approaches 2 and 3 to the classic or conventional methods previously used in the AHSMOG Study.

Progress Summary:

Air Pollution Estimates

The AHSMOG Study already had monthly air pollution estimates for each subject since the start of the study in 1973 and for some pollutants (PM2.5) back to 1966. These were developed using a deterministic method with interpolation to the centroid of each ZIP code. The AHSMOG Study had used information from all relevant monitoring stations in California to develop their ambient air pollution estimates. However, in meetings between the STAR grantees and EPA, it was decided to use a common air pollution database from EPA. This will allow a comparison of estimated ambient air pollution values by the four studies. For AHSMOG, this also will allow a comparison with our previous, comprehensive methods for estimation of ambient air pollution. However, this decision also has delayed the progress of the study in obtaining air pollution estimates using geostatistical methods.

To date, we have developed individual mean estimates of the different air pollutants for 1977 to 1999 (or date of death) based on monthly residence history and monthly workplace ZIP code, which have been geocoded. In collaboration with the research team at Environmental Systems Research Institute (ESRI), we have developed a software program that can combine the geocoded residence and workplace information with the EPA air pollution database to assess subject-specific ambient air pollution estimates using geostatistical data analysis. Thus, we have subject-specific ambient air pollutant values for the entire AHSMOG cohort.

In addition, we have done analyses for risk assessment of fatal CHD and total mortality using alternate statistical methods, including Bayesian neural networks and Bayesian Cox (using BUGS software program).

Assessment of Outcome

Incident CHD. From 1977-1982, we have information on and verification of incident myocardial infarctions (MI). For the period 1983-1999, we have self-reported incidence of acute MI with additional information on name and address of the hospital in which these were diagnosed. Validity of this information was planned through obtainment of medical records from the individual hospitals. However, this has proved impossible as hospitals do not keep medical records in-house for usually more than 5 years. After that, they are put in remote storage and, if records are older than 10 years, they often are destroyed. Thus, we have not been able to obtain more than 56 percent of the records or a total of 318 of 568.

To compensate for a lack of data for incident CHD, we have requested permission from EPA to modify this part of the study and instead assess incident CHD in a new cohort, the Adventist Health Study 2 cohort. This cohort of 100,000 subjects has recently been assembled through funding from the National Cancer Institute (NCI) to study the effect of lifestyle, especially diet, on cancer outcomes. We propose to use the information from bi-annual hospitalization forms to study the association between particulate air pollution and incident CHD in the six western U.S. states using this population and a nested case-control design. We have a total of 417 self-reported incidents of CHD among 47,775 subjects. After verifying their self-reported coronary event, we will select four controls for each case. We are currently in the process of obtaining Institutional Review Board approval for this study.

Cardiovascular Disease Mortality. All death certificates have been coded by a certified nosologist, and all mortality outcomes have thus been updated. A total of 2,462 deaths have occurred in the cohort since 1977. Of these, 2,393 are natural cause deaths (ICD-9 < 800), and 644 are a result of ischemic heart disease (ICD-9: 410-414).

Analyses and Results

Coronary Heart Disease Mortality. A paper has been published (Chen, et al., 2005) assessing the effect of fine particles on the risk of CHD in males and females and finding a stronger effect in females than in males.

Outcomes in Sensitive Subgroups. The following sensitive subgroups have been identified:

  • Older age (> 64 years and > 74 years).
  • Prevalent CHD.
  • Prevalent CHD, stroke, diabetes, or hypertension.
  • Past smokers.
  • Prevalent chronic obstructive pulmonary disease (COPD).

Preliminary analyses of sensitive subgroups using previously estimated ambient air pollution do not indicate any increased risk associated with particulate matter air pollution in sensitive subgroups, except for persons with COPD where the risk of fatal CHD seems to be elevated, especially in males. However, further analyses using ambient air pollution estimates using GIS methodology will be done in accordance with the objectives of this grant.

Cancer Outcomes. A paper on the risk of non-Hodgkin’s Lymphoma associated with coarse particulate matter (PM10) currently is being reviewed for publication. We also are in the process of writing a paper on the risk of lung cancer in relation to PM10.

Progress

As mentioned earlier, the aim of assessing the relationship between ambient air pollution and incident CHD cannot be fulfilled. Therefore, we are moving forward to assess this in a newly established NCI-funded cohort of Adventists, the Adventist Health Study 2 cohort. We will use the six western U.S. states and have identified 417 subjects who report having had a CHD event recently. Using these as our cases, we will select four controls for each case and use a nested case-control study design. We will obtain medical records for all cases after obtaining their approval using a Health Insurance Portability and Accountability Act of 1996 (HIPAA)-appropriate consent form.

The development of GIS-based individual ambient air pollution estimates has been completed for PM10, PM2.5, NO2, SO2, and ozone. We have worked in close collaboration with ESRI and have developed an automated program that can estimate individual and time-specific measures based on GIS krieging of the air pollutant and the subject’s residence and work location.

Likewise, the development of statistical models using neural networks and Bayesian neural networks is progressing. The first paper on this work was presented at the Hawaii International Conference on Statistics in Honolulu in June 2004. Three students pursuing a Master of Science in Public Health (MSPH) degree have worked on one paper each, one developing a model using survival neural network analysis based on a method developed by Dr. Dipley of University of Oxford, United Kingdom. The second MSPH student has been developing a model using Bayesian Neural Network using an approach described by Dr. Rad Neill of the University of Ontario, Canada. The third student is working on a new model for dealing with missing values.

We also have been able to use the BUGS statistical software to do Bayesian Cox analyses. Dr. Ghamsary has worked closely with the developers of this software to make it run with large datasets such as ours. Comparing the risk estimates using BUGS with estimates using traditional COX analysis was reassuring, as they gave virtually the same estimates.

Two abstracts were presented at the International Society for Environmental Epidemiology (ISEE) meeting in New York in August 2004, using previous air pollution estimates.

One paper has been published on particulate matter and fatal CHD. Another paper on risk of non-Hodgkin’s lymphoma and particulate matter was rejected but has been submitted to another journal.

Two other papers are in their final stages before submission: (1) the effect of particulate matter on risk of all-cause, cardiopulmonary, and noncancer respiratory mortality; and (2) the effect of particulate matter on risk of fatal CHD in sensitive subgroups. In addition, Dr. Knutsen and David Shavlik are working on a paper on lung cancer incidence and mortality and particulate air pollution, and Dr. Beeson is working on a paper on hospitalizations for cardiovascular disease and respiratory disease in relation to air pollution.

Dr. Soret is working on two manuscripts describing the development of estimates using GIS-based krieging versus a deterministic model. He also is looking at the errors introduced, if any, by using ZIP code centroids versus actual street address of residence to estimate individual measures of air pollution.

Future Activities:

Because of the problems with assessment of incident CHD and moving to a new cohort, we will request a no-cost extension.  During this extension year, we will request permission to obtain the subject’s medical records and then contact the relevant hospital for these records.  We will use similar criteria for incident CHD as was used by the Artherosclerosis Risk in Communities (ARIC) study.

We hope to have obtained and coded all medical records by March 2007, and then be ready for analyses in spring and summer of 2007.

In addition to the change of cohort for assessment of incident CHD, we expect to continue our work of publishing our other findings: 

  • Air pollution and all-cause mortality.
  • Air pollution and risk of death in sensitive subgroups.
  • Air pollution and risk of lung cancer.
  • Air pollution and risk of being hospitalized for CHD and respiratory diseases.
  • Comparisons of risk using traditional individual estimates and GIS-based krieging estimates.
  • Comparison of deterministic and krieging methods for assessment of air pollution levels.
  • Disease risk estimates using Bayesian neural network versus traditional COX.


Journal Articles on this Report : 1 Displayed | Download in RIS Format

Other project views: All 25 publications 4 publications in selected types All 4 journal articles
Type Citation Project Document Sources
Journal Article Chen LH, Knutsen SF, Shavlik D, Beeson WL, Petersen F, Ghamsary M, Abbey D. The association between fatal coronary heart disease and ambient particulate air pollution:are females at greater risk? Environmental Health Perspectives 2005;113(12):1723-1729. R830547 (2005)
R830547 (2006)
R830547 (2007)
R830547 (Final)
R827998 (Final)
  • Full-text from PubMed
  • Abstract from PubMed
  • Associated PubMed link
  • Full-text: EHP-Full Text HTML
  • Other: EHP-Full Text PDF
  • Supplemental Keywords:

    ambient air, ozone, particulate matter, exposure, risk, risk assessment, health effects, human health, sensitive populations, population, elderly, cumulative effects, susceptibility, epidemiology, modeling, monitoring, analytical, Bayesian neural networks, GIS, southwest, California, CA,, RFA, Economic, Social, & Behavioral Science Research Program, Health, Scientific Discipline, Air, ENVIRONMENTAL MANAGEMENT, particulate matter, Health Risk Assessment, Risk Assessments, Susceptibility/Sensitive Population/Genetic Susceptibility, Disease & Cumulative Effects, Biochemistry, Environmental Statistics, genetic susceptability, Biology, Risk Assessment, ambient air quality, elderly adults, health effects, sensitive populations, health risk analysis, air pollutants, long term exposure, acute lung injury, Bayesian approach, cardiovascular vulnerability, Bayesian neural networks, Bayesian method, exposure, air pollution, chronic health effects, particulate exposure, susceptibility, statistical models, human exposure, sensitive subjects, Acute health effects, elderly, GIS, sensitive subgroups, mortality, cardiotoxicity, tobacco smoke, age dependent response, cumulative effects, cardiopulmonery responses, respiratory, exposure assessment, environmental hazard exposures, toxics, human health risk, cardiovascular disease

    Relevant Websites:

    http://www.llu.edu/llu/health/ahsmog.htm Exit

    Progress and Final Reports:

    Original Abstract
  • 2003 Progress Report
  • 2004 Progress Report
  • 2006 Progress Report
  • 2007 Progress Report
  • Final Report