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Modeling Personal Exposures to Ultrafine Particles and Effects on Cardiovascular HealthEPA Grant Number: FP917349
Title: Modeling Personal Exposures to Ultrafine Particles and Effects on Cardiovascular Health
Investigators: Lane, Kevin J
Institution: Boston University
EPA Project Officer: Cobbs-Green, Gladys M.
Project Period: September 1, 2011 through August 31, 2014
Project Amount: $126,000
RFA: STAR Graduate Fellowships (2011) RFA Text | Recipients Lists
Research Category: Fellowship - Human Health: Public Health Sciences , Academic Fellowships
There exists a dearth of research on particulate matter (PM) nanoparticles, or ultrafine particles (1-100 nm in aerodynamic diameter, UFP), and associated health outcomes. UFPs constitute a developing area of exposure and epidemiological research that requires novel modeling approaches to deal with bias stemming from the high spatial and temporal variability of this pollutant. This research proposal seeks to aid in filling this PM research gap through an examination of the association between UFP and cardiovascular health in populations residing in close proximity to an interstate highway in the greater Boston, Massachusetts area. Due to the high spatial-temporal variability of UFP, specific times of day, such as during rush hour traffic, create significantly elevated exposure windows. Actual exposures during these windows of time depend on where people are physically located and will require a more refined exposure assessment model to minimize misclassification so that the exposuredisease relationships can be observed.
This research study will design and evaluate an exposure assessment model that incorporates time-activity data as a way to deal with error from exposure misclassification before implementing the personal UFP exposure model in an epidemiological analysis. First, an analysis of the use of questionnaire derived time-activity data in designing a personal exposure assessment model will be conducted through a validation study using GPS units. The questionnaire data will be used to develop an exposure assessment model that includes time-activity data, and compare this with a model that does not adjust for time-activity to examine the errors and direction of bias in a health outcomes study. After the model has been developed and tested, it will be used in the health outcomes study to examine the association between exposure to UFP and cardiovascular health, measured as biomarkers of systemic inflammation with high sensitivity C-reactive protein (CRP), fibrinogen, plasma interleukin-6 (IL-6) and tumor necrosis factor-α receptor (TNFα), adjusting for other exposure and personal variables.
Current research into time-activity and movement patterns of populations indicate that people are highly mobile but relatively predictable in their daily routines and can result in misclassification of exposure in studies that focus on pollutants with high spatial and temporal variability using a residential location as the basis for the exposure model. The relative predictability of movement patterns would suggest that only limited data are needed on a person’s daily activities to determine where they routinely may be found at a specific time of day. This indicates that time-activity data collected through questionnaires could be used to develop a more accurate exposure assessment model. Incorporation of time activity data into an exposure assessment model of UFP will allow for a comparison of associated cardiovascular health outcome risk between the unadjusted (residential only exposure) and time activity adjusted models. If the unadjusted model is biasing results towards the null, then it is expected that the time-activity adjusted model will yield a stronger association and smaller standard error for the ß-estimates. Exposure parameters such as occupational and ambient UFP intrusion into the indoor environment will be analyzed at this time and included in the final exposure assessment model that will be used in the full epidemiology analysis. Integration of time-activity data into the exposure assessment model should reduce exposure misclassification that can occur in a study of a pollutant like UFP with such high spatial and temporal variability, allowing for a more representative health effects association to be observed.
Potential to Further Environmental / Human Health Protection
Vehicle emissions are the primary source by which people are exposed to UFP, and approximately 11 percent of U.S. households reside within 100 m of highways. There is a limited amount of epidemiological data available on the health effects of UFP, no national network to monitor UFPs and no standards to regulate emissions of UFP. This research will contribute to a new and growing body of analyses that can inform future policy discussions about whether to regulate UFP exposure and, if so, at what level. New policy solutions and monitoring strategies may need to be developed if UFP concentrations are found to be associated with adverse health effects in epidemiology studies.