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

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.