Grantee Research Project Results
Final Report: Statistics and Data Core
EPA Grant Number: R827355C009Subproject: this is subproject number 009 , established and managed by the Center Director under grant R827355
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
Center: Center for Air, Climate, and Energy Solutions
Center Director: Robinson, Allen
Title: Statistics and Data Core
Investigators: Sheppard, Lianne (Elizabeth) A. , Wakefield, Jon , Sampson, Paul , Lumley, Thomas
Institution: University of Washington
EPA Project Officer: Chung, Serena
Project Period: June 1, 1999 through May 31, 2004 (Extended to May 31, 2005)
RFA: Airborne Particulate Matter (PM) Centers (1999) RFA Text | Recipients Lists
Research Category: Air Quality and Air Toxics , Particulate Matter , Air
Objective:
The overall objective of the statistics effort of this research project was to develop and clarify statistical methodology in the air pollution field. The specific objectives were to: (1) use source apportioned exposure data in health effects analyses, (2) interpret exposure effects in chronic effect studies, (3) review case-crossover methods used in analyzing air pollution exposure data, (4) develop a strategy for spatio-temporal modeling of PM, (5) review methods in air pollution panel studies, and (6) integrate statistical methods into biomarker research (methodological issues associated with below the limit of detection data).
The objectives of the data core are to: (1) compile and manage data to support PM Center research; (2) utilize existing data for analyses of health effects; (3) ensure quality statistical design and analysis for PM Center research; and (4) identify statistical methodology research needs for PM Center research and seek resources to perform such research.
Summary/Accomplishments (Outputs/Outcomes):
Statistics
- Source Apportioned Exposure Data and Estimation of Health Effects
This research investigated the effects of using positive matrix factorization (PMF) imputed source contributions as exposure variables in health effects models. We reviewed the use of PMF for the identification of sources of PM and studied the properties of health effects estimated using source exposures imputed by PMF. We used a simulation study to demonstrate that directly substituting PMF results into a health effects model produces biased health effects estimates. Our results indicated that the uncertainty in PM source estimates imputed by PMF, although small enough to allow identification of sources and characterization of their contributions to overall particulate burden, has the potential to cause serious bias in estimated health effects.
We are preparing a paper to discuss the range of issues that affect the design of epidemiologic studies of the health effects of air pollution from PM sources, in particular using speciated data. This paper uses the framework of three models, a disease model, an exposure model, and a measurement model. These are integrated into a discussion of different study designs to clarify the opportunities and challenges associated with conducting health studies using speciated data with the intent of estimating the health effects of sources.
- Interpretation of Exposure Effects in Chronic Effect Studies
This research considered how one interprets the exposure effect parameter from a cohort study. The standard Cox model used in air pollution cohort study analyses assumes the exposure is fixed at baseline and the effect is propagated at the constant level throughout follow-up. We looked at sensitivity to this structure by establishing a framework for the effect of exposure on the disease outcome by considering the time resolution of the data, the exposure history, and the association history (i.e., how is risk at time t affected by exposure at an earlier time s?). Data were simulated from an individual-level model and then analyzed in the more typical aggregate framework where exposure is aggregated over time. We performed an “insensitivity” analysis to shed light on the underlying model parameter that would generate identical results from the standard analysis using mean exposure as the predictor. A paper describing this research is in preparation.
- Case-Crossover Methods in Air Pollution
In revising our case-crossover review paper, “Referent Selection Strategies in Case-Crossover Analyses of Air Pollution Exposure Data: Implications for Bias,” we conducted research in several new areas. First, we carried out an exhaustive review of air pollution case-crossover studies to date, and summarized their referent selection strategies. We also compared the statistical efficiency of the various referent selection strategies. We have proposed new terminology for case-crossover referent strategies, and have worked to clarify the issue of overlap bias, which is encountered when a referent strategy is improperly paired with an analysis method. We clarified the so-called “rare event” assumption in the case-crossover design, and have pointed out why this assumption is necessary. We also have made a point to distinguish between two types of models that have been used to describe case-crossover data, and have indicated which model is most appropriate for air pollution exposure data. Finally, we have researched the properties of various referent selection strategies for cases when individuals do not all share the same exposure series.
- Spatio-Temporal Modeling of PM
We developed a strategy for spatial modeling and estimation of PM concentrations that combines data from monitoring sites operating at different temporal scales, recording integrated average concentrations at either daily, 3-day, or 2-week intervals. The modeling builds on the spatial-deformation modeling strategy for nonstationary spatial covariance structure introduced by Drs. Sampson and Guttorp and further developed in a Bayesian framework in collaboration with one of their students. We have combined this modeling strategy with a new flexible, but parsimonious approach to modeling the spatio-temporal trend in such monitoring data. This approach represents seasonal structure that varies in space and from year to year. It is based on a modified (smoothed) singular value decomposition of the (typically incomplete) space x time matrix of observed concentrations. This approach (for a monitoring at a single time scale) has been explained and illustrated with an application to ozone monitoring data in a recently submitted chapter. Separate empirical analyses of PM, NOx, and NO2 data for southern California at daily and 2-week average scales have been carried out to confirm the applicability of the model structure prior to the implementation of the strategy for integration of monitoring data at different time scales.
- Review of Methods in Air Pollution Panel Studies
We currently are working on writing a paper that is aimed at clarifying the statistical issues that arise in the design and analysis of air pollution panel studies. We portray the appropriate types of exposures and outcomes, contrast the various modeling approaches, discuss methods for controlling for confounding, and describe appropriate exploratory data analysis techniques. We illustrate the concepts throughout using data from the Seattle Panel Study.
- Methodological Issues Associated With Below the Limit of Detection Data
We investigated the relative bias and efficiency of regression models for environmental data when some observations lie below the limit of detection and others are missing at random. We investigated the performance of linear regression models and parametric survival models for left censored data when only complete cases are included and after using multiple imputation to account for random missingness in the data. Our simulated data were based on the distribution of measurements of methoxyphenol compounds in ambient air collected at Panel Study outdoor and central sites.
Data Core
The following activities were completed by the Data Core:
- Support of the agricultural burning study data analyses.
- Support of management and analysis of project size-distributed data, including data management, data validation, data analyses, and development of new software and methods.
- Support of epidemiology studies activities, particularly with respect to the Women’s Health Initiative (WHI) study, Multi-Ethnic Study of Atherosclerosis (MESA) Air Pollution Study, cystic fibrosis analysis, Myocardial Infarction Triage and Intervention (MITI) study analysis, and bronchiolitis study.
- Support of the Panel Study Health Effects project, particularly health effects analyses (heart rate variability, bloods, lung).
- Support of biomarker research.
- Support of the Diesel Facility Project, including data forms development, data organization, database management, data validation, technical systems review (TSR) support, and statistical collaboration/support.
- General support of data analyses and data sharing, including preparation of a final PM Center data release.
- Implementation and support of statistical analysis plans (SAPs).
Journal Articles on this Report : 20 Displayed | Download in RIS Format
Other subproject views: | All 44 publications | 30 publications in selected types | All 29 journal articles |
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Other center views: | All 209 publications | 113 publications in selected types | All 109 journal articles |
Type | Citation | ||
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Allen R, Wallace L, Larson T, Sheppard L, Liu L-JS. Estimated hourly personal exposures to ambient and nonambient particulate matter among sensitive populations in Seattle, Washington. Journal of the Air & Waste Management Association 2004;54(9):1197-1211. |
R827355 (2004) R827355 (Final) R827355C003 (2003) R827355C003 (2004) R827355C003 (Final) R827355C008 (Final) R827355C009 (Final) |
Exit Exit Exit |
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Haneuse S, Wakefield J, Sheppard L. The interpretation of exposure effect estimates in chronic air pollution studies. Statistics in Medicine 2007;26(16):3172-3187. |
R827355 (Final) R827355C009 (Final) |
Exit |
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Janes H, Sheppard L, Lumley T. Overlap bias in the case-crossover design, with application to air pollution exposures. Statistics in Medicine 2005;24(2):285-300. |
R827355 (2004) R827355 (Final) R827355C009 (2003) R827355C009 (Final) |
Exit Exit |
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Janes H, Sheppard L, Lumley T. Case-crossover analyses of air pollution exposure data:referent selection strategies and their implication for bias. Epidemiology 2005;16(6):717-726. |
R827355 (Final) R827355C009 (Final) |
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Koenig JQ, Mar TF, Allen RW, Jansen K, Lumley T, Sullivan JH, Trenga CA, Larson TV, Liu L-JS. Pulmonary effects of indoor-and outdoor-generated particles in children with asthma. Environmental Health Perspectives 2005;113(4):499-503. |
R827355 (2004) R827355 (Final) R827355C002 (2003) R827355C002 (2004) R827355C002 (Final) R827355C003 (2004) R827355C003 (Final) R827355C009 (Final) |
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Larson TV, Covert DS, Kim E, Elleman R, Schreuder AB, Lumley T. Combining size distribution and chemical species measurements into a multivariate receptor model of PM2.5. Journal of Geophysical Research-Atmospheres 2006;111(D10):D10S09 (10 pp.). |
R827355 (Final) R827355C004 (Final) R827355C008 (Final) R827355C009 (Final) |
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Lumley T, Sheppard L. Assessing seasonal confounding and model selection bias in air pollution epidemiology using positive and negative control analyses. Environmetrics 2000;11(6):705-717. |
R827355 (2001) R827355 (Final) R827355C001 (2000) R827355C001 (2001) R827355C009 (Final) R825173 (1999) |
Exit Exit |
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Lumley T, Levy D. Bias in the case-crossover design: implications for studies of air pollution. Environmetrics 2000;11(6):689-704. |
R827355 (2001) R827355 (Final) R827355C009 (Final) R825173 (1999) |
Exit Exit |
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Moolgavkar SH, Hazelton W, Leubeck G, Levy D, Sheppard L. Air pollution, pollens, and admissions for chronic respiratory disease in King County, Washington. Inhalation Toxicology 2000;12(Suppl 1):157-171. |
R827355 (2001) R827355 (Final) R827355C009 (Final) R825266 (Final) |
Exit |
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Sheppard L, Kaufman J. Sorting out the role of air pollutants in asthma initiation. Epidemiology 2000;11(2):100-101. |
R827355 (2004) R827355 (Final) R827355C001 (1999) R827355C001 (2001) R827355C009 (Final) |
Exit |
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Sheppard L, Damian D. Estimating short-term PM effects accounting for surrogate exposure measurements from ambient monitors. Environmetrics 2000;11(6):675-687. |
R827355 (2001) R827355 (Final) R827355C009 (Final) |
Exit Exit |
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Sheppard L, Levy D, Checkoway H. Correcting for the effects of location and atmospheric conditions on air pollution exposures in a case-crossover study. Journal of Exposure Analysis and Environmental Epidemiology 2001;11(2):86-96. |
R827355 (2004) R827355 (Final) R827355C001 (2001) R827355C009 (Final) R825173 (1999) R825173 (2000) |
Exit Exit |
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Sheppard L. Insights on bias and information in group-level studies. Biostatistics 2003;4(2):265-278. |
R827355 (2004) R827355 (Final) R827355C009 (Final) |
Exit Exit |
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Sheppard L, Wakefield JC. Comment: "Statistical issues in studies of the long-term effects of air pollution: the Southern California Children's Health Study" by Berhane K, Gauderman WF, Stram DO, Thomas DC. Statistical Science 2004;19(3):438-441. |
R827355 (2004) R827355 (Final) R827355C009 (Final) |
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Sheppard L. Acute air pollution effects:consequences of exposure distribution and measurements. Journal of Toxicology and Environmental Health-Part A-Current Issues 2005;68(13-14):1127-1135. |
R827355 (2004) R827355 (Final) R827355C009 (2003) R827355C009 (Final) |
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Sheppard L, Slaughter JC, Schildcrout J, Liu L-JS, Lumley T. Exposure and measurement contributions to estimates of acute air pollution effects. Journal of Exposure Analysis and Environmental Epidemiology 2005;15(4):366-376. |
R827355 (2004) R827355 (Final) R827355C009 (2003) R827355C009 (Final) |
Exit Exit |
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Slaughter JC, Kim E, Sheppard L, Sullivan JH, Larson TV, Claiborn C. Association between particulate matter and emergency room visits, hospital admissions and mortality in Spokane, Washington. Journal of Exposure Analysis and Environmental Epidemiology 2005;15(2):153-159. |
R827355 (Final) R827355C008 (Final) R827355C009 (2002) R827355C009 (2003) R827355C009 (Final) R828678C010 (2003) R828678C010 (2004) R828678C010 (2005) R828678C010 (2006) R828678C010 (2007) R828678C010 (Final) |
Exit Exit Exit |
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Sullivan JH, Schreuder AB, Trenga CA, Liu SL, Larson TV, Koenig JQ, Kaufman JD. Association between short term exposure to fine particulate matter and heart rate variability in older subjects with and without heart disease. Thorax 2005;60(6):462-466. |
R827355 (Final) R827355C001 (Final) R827355C009 (2003) R827355C009 (Final) |
Exit Exit Exit |
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Sullivan J, Sheppard L, Schreuder A, Ishikawa N, Siscovick D, Kaufman J. Relation between short-term fine-particulate matter exposure and onset of myocardial infarction. Epidemiology 2005;16(1):41-48. |
R827355 (Final) R827355C001 (2003) R827355C001 (Final) R827355C009 (2003) R827355C009 (Final) |
Exit Exit Exit |
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Trenga CA, Sullivan JH, Schildcrout JS, Shepherd KP, Shapiro GG, Liu LJ, Kaufman JD, Koenig JQ. Effect of particulate air pollution on lung function in adult and pediatric subjects in a Seattle panel study. Chest 2006;129(6):1614-1622. |
R827355 (Final) R827355C002 (Final) R827355C009 (Final) |
Exit Exit Exit |
Supplemental Keywords:
ambient particles, fine particles, combustion, health, exposure, biostatistics, susceptibility, human susceptibility, sensitive populations, air toxics, genetic susceptibility, indoor air, indoor air quality, indoor environment, tropospheric ozone, California, CA, polyaromatic hydrocarbons, PAHs, hydrocarbons, acute cardiovascular effects, aerosols, air pollutants, air pollution, air quality, airborne pollutants, airway disease, airway inflammation, allergen, ambient aerosol, ambient aerosol particles, ambient air, ambient air quality, ambient particle health effects, animal model, assessment of exposure, asthma, atmospheric aerosols, atmospheric chemistry, biological markers, biological response, cardiopulmonary response, cardiovascular disease, children, children’s vulnerability, combustion, combustion contaminants, combustion emissions, epidemiology, exposure, exposure and effects, exposure assessment, harmful environmental agents, hazardous air pollutants, health effects, health risks, human exposure, human health effects, human health risk, incineration, inhalation, lead, morbidity, mortality, mortality studies, particle exposure, particle transport, particulates, particulate matter, risk assessment,, RFA, Health, Scientific Discipline, PHYSICAL ASPECTS, Air, ENVIRONMENTAL MANAGEMENT, Geographic Area, particulate matter, air toxics, Environmental Chemistry, Health Risk Assessment, Air Pollutants, State, Epidemiology, Air Pollution Effects, Northwest, Risk Assessments, Susceptibility/Sensitive Population/Genetic Susceptibility, Biochemistry, Physical Processes, genetic susceptability, Atmospheric Sciences, Risk Assessment, biostatistics, health effects, ambient aerosol, particulates, sensitive populations, ambient air quality, morbidity, cardiopulmonary responses, human health effects, toxicology, exposure and effects, health risks, acute cardiovascular effects, hazardous air pollutants, exposure, epidemelogy, dose-response, air pollution, particle exposure, Human Health Risk Assessment, atmospheric aerosols, ambient particle health effects, mortality studies, cardiopulmonary response, inhalation, human exposure, air pollutant, human susceptibility, PM, mortality, California (CA), biomarker based exposure inference, air quality, particle transport, cardiovascular disease, human health risk, aerosols, atmospheric chemistry, exposure assessment, environmental hazard exposures, toxicsRelevant Websites:
http://depts.washington.edu/pmcenter/ Exit
Progress and Final Reports:
Original AbstractMain Center Abstract and Reports:
R827355 Center for Air, Climate, and Energy Solutions Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
R827355C001 Epidemiologic Study of Particulate Matter and Cardiopulmonary
Mortality
R827355C002 Health Effects
R827355C003 Personal PM Exposure Assessment
R827355C004 Characterization of Fine Particulate Matter
R827355C005 Mechanisms of Toxicity of Particulate Matter Using Transgenic Mouse Strains
R827355C006 Toxicology Project -- Controlled Exposure Facility
R827355C007 Health Effects Research Core
R827355C008 Exposure Core
R827355C009 Statistics and Data Core
R827355C010 Biomarker Core
R827355C011 Oxidation Stress Makers
The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.
Project Research Results
29 journal articles for this subproject
Main Center: R827355
209 publications for this center
109 journal articles for this center