Tripathy, Sheila
(2017)
Hybrid land use regression modeling of fine particulate matter and metal components for application in two Pittsburgh cohorts.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
While numerous studies have linked exposure to ambient fine particulate matter (PM2.5) to adverse health outcomes (e.g., asthma, cardiovascular disease), less is known about which specific components of PM2.5 drive these associations. Because PM2.5 composition varies spatially with sources, characterizing fine-scale variation in constituents is critical to improving epidemiological studies on health effects of source-specific PM2.5. One approach for improving this characterization may be hybrid models wherein source-specific dispersion covariates are integrated into land use regression models (LURs).
The objective of this dissertation was to develop hybrid dispersion-LUR models for PM2.5, black carbon (BC), and steel-related PM2.5 constituents [lead (Pb), manganese (Mn), iron (Fe), and zinc (Zn)], by combining concentrations data from spatial saturation monitoring with daily Environmental Protection Agency (EPA) regulatory data. These models were used to assign residence-based exposure estimates for time windows of interest for two Pittsburgh-area epidemiological cohorts.
The first epidemiologic study examined associations between one-year pollutant exposures and levels of both circulating and lipopolysaccharide (LPS)-stimulated inflammatory mediators in the Adult Health and Behavior II (AHAB II) cohort. We found that exposures to PM2.5 and BC were associated with higher LPS-stimulated IL-1β, IL-6, and TNF-α. Pb was associated with increased stimulated TNF-α (p = 0.02) and IL-1β (p = 0.02), but were insignificant after adjusting for multiple comparisons (Bonferroni correction). No pollutant exposures were associated with circulating IL-6 or CRP. The second epidemiological study explored associations between pollutant exposures and brain morphology indicators (i.e., total and cortical gray matter volumes, cortical white matter volume, total white matter surface area, mean cortical thickness) from magnetic resonance images of participants in the AHAB II and Pittsburgh Imaging Project Cohorts, finding no significant associations.
These results suggest that, although pollutants were not associated with circulating inflammatory mediators or brain morphology in these samples of healthy midlife adults, some chronic air pollution exposures may influence immune responsiveness, influencing risk for future inflammatory conditions. Taken together, these results indicate the public health importance of better understanding relationships between long-term source-specific PM2.5 and component exposures with functional indicators of immune responsiveness and other processes shaping risk for future health effects.
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Details
| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
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| Date: |
29 June 2017 |
| Date Type: |
Publication |
| Defense Date: |
14 April 2017 |
| Approval Date: |
29 June 2017 |
| Submission Date: |
21 April 2017 |
| Access Restriction: |
1 year -- Restrict access to University of Pittsburgh for a period of 1 year. |
| Number of Pages: |
124 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
School of Public Health > Environmental and Occupational Health |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
land use regression, PM2.5, metal constituents, stimulated cytokines, IL-6, CRP, brain morphology |
| Date Deposited: |
29 Jun 2017 23:49 |
| Last Modified: |
01 May 2018 05:15 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/31536 |
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