141st APHA Annual Meeting and Exposition

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Recorded Annual Meeting Presentations (RAMP) are now available for purchase.
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Online Program

286185
Geographic information systems and weighted cumulative impact scoring: A model for quantifying potential health impacts


Wednesday, November 6, 2013 : 11:10 a.m. - 11:30 a.m.

John Prochaska, DrPH, MPH, Department of Preventive Medicine & Community Health, University of Texas Medical Branch, Galveston, TX
Alexandra Nolen, PhD, MPH, Center to Eliminate Health Disparities, University of Texas Medical Branch, Galveston, TX
Rob Buschmann, MPP, University of Texas Medical Branch, Galveston, TX
Elizabeth Fuller, DrPH, Georgia Health Policy Center, Georgia State University, Atlanta, GA
Erin Ruel, PhD, Department of Sociology, Georgia State University, Atlanta, GA
Holly Avey, PhD, MPH, Georgia Health Policy Center, Georgia State University, Atlanta, GA
Deirdre Oakley, PhD, Department of Sociology, Georgia State University, Atlanta
James E. Dills, MUP, MPH, Georgia Health Policy Center, Georgia State University, Atlanta, GA
Michelle Rushing, MPH, Andrew Young School of Policy Studies, Georgia State University, Georgia Health Policy Center, Atlanta, GA
     
Background Health impact assessments are gaining increased attention in the U.S.; however, quantification of health impacts is relatively rare. This new model applies geographic information systems (GIS) and a weighting system to assess, quantatively, potential neighborhood-level health impacts, and was applied to screen census blocks for the future siting of public housing across Galveston, Texas, following Hurricane Ike.

Methods With input from community stakeholders, literature review, and content experts, researchers developed a list of 16 neighborhood-level indicators to inform an assessment of health impacts specifically to future public housing residents. Data were entered into a geographic information system (GIS). Densities, distances, and binary outcomes were calculated, depending on the nature of a specific indicator. Data were z-score standardized, then weighted based on strength of the evidence and potential impact to health. Cumulative scores for each census block were calculated for blocks with current or potential use for residential development. Census blocks were categorized based on quintile.

Results Nearly 68% of census blocks in Galveston were included in the final analysis. A choropleth map of census blocks was produced to identify the census blocks with scores in the fourth and fifth quintiles. The highlighted blocks generally followed other assessments of neighborhood quality in the city. Further, by modifying the values of selected indicators, potential impacts of mitigation strategies can be modeled.

Discussion The results from this analysis will be used to refine the pool of potential parcels for development of scattered-site public housing and to assess the potential impacts of proposed mitigation strategies. The results were developed using a data-driven approach that provide a robust assessment of potential health impacts. This method can be applied in other settings seeking to assess potential health impacts to populations across a relatively broad geographic area.

Learning Areas:

Assessment of individual and community needs for health education
Environmental health sciences
Public health or related public policy

Learning Objectives:
Describe current approaches to health impact assessment in the U.S. Identify potential sources of positive and negative health impacts to public housing residents Discuss the application of this methodology to the screening of potential public housing sites

Keyword(s): Geographic Information Systems, Public Housing

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I served as the project manager at the project site for the conduct of this Health Impact Assessment and was involved with all aspects of the project.
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.

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