142nd APHA Annual Meeting and Exposition

Home Events & Meetings Annual Meeting Schedule & Program

Online Program

Annual Meeting Recordings are now available for purchase

313201
Satellite-Derived Air Quality Estimates in Health Studies: A Critical Evaluation

142nd APHA Annual Meeting and Exposition (November 15 - November 19, 2014): http://www.apha.org/events-and-meetings/annual
Tuesday, November 18, 2014 : 11:15 AM - 11:30 AM

Howard Chang, PhD , Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA
Stefanie Sarnat , Emory University, Atlanta
Lance Waller, PhD , Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA
Yang Liu, PhD , Department of Environmental Health, Emory University, Atlanta, GA
Audio (mp3) recording Recorded Presentation (mp4)
With their broad spatial coverage, satellite images have the potential to increase the spatial-temporal availability of air quality data beyond ground-level monitoring measurements. To improve exposure assessment for epidemiologic studies, there is a growing interest to utilize remotely sensed aerosol optical depth (AOD) for estimating concentrations of fine particulate matter less than 2.5 μm in aerodynamic diameter (PM2.5).

In this presentation, we evaluate the use of satellite-derived PM2.5 estimates for two health outcomes with exposure metrics defined on different spatial and temporal scales.  We utilize a unique AOD product at 1 km spatial resolution to derive PM2.5 estimates via a Bayesian hierarchical statistical model that also incorporates land use and meteorological variables. 

Using both ground measurements and satellite-derived PM2.5, we examine association between PM2.5 and daily emergency department visits, as well as associations between gestational PM2.5 exposure and birth weight within the Atlanta metropolitan area during 2001-2010.  Through simulation studies, we evaluate how monitor placement, monitor number, and magnitude of prediction error may impact the utility of satellite-derived PM2.5 estimates in health studies.

Learning Areas:

Communication and informatics
Environmental health sciences
Public health or related research

Learning Objectives:
Describe spatial-temporal statistical models for predicting ambient air pollution concentrations and models Describe statistical models for estimating associations between environmental exposures and health outcomes.

Keyword(s): Geographic Information Systems (GIS), Public Health Research

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am a biostatistician trained in spatial-temporal statistics and environmental epidemiology. I have experience in the use of satellite data for exposure assessment in environmental health studies.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.

Back to: 4142.0: International Innovations in Geoscience and Healthography