4041.0: Tuesday, November 14, 2000 - 8:45 AM

Abstract #15965

Geomapping Pedestrian and Bicycle Injury: Linking Crime, Planning, and Injury Data

Mary D. Gunnels, MS, RN, Christopher Bangs, MS(c), Annette L Adams, MPH(c), and Jonathan Jui, MD, MPH. Emergency Medicine, School of Medicine, Oregon Health Sciences University, 3181 SW Sam Jackson Park Road, CR114, Portland, OR 97201, (503)494-1614, gunnelsm@ohsu.edu

Introduction: Linking crime, planning, and trauma system data provide opportunity to expand our understanding of the epidemiology of injury; Geographic Information Systems [GIS] elucidate human and environmental risk factors. This study evaluates the relationship between crime incidence and population density among injured pedestrians and bicyclists.

Methods: This retrospective cohort analysis examined cases from April 1,1995 through June 30, 1998. Data sources were: the Metropolitan Regional Planning Agency [METRO RLIS], Portland police neighborhood crime [CRIME], and Tri-county Trauma Communications [TCC] databases. Analysis steps: 1) Geocoding cases - injured pedestrians and bicyclists entered into the Oregon trauma system in a largely urban tri-county region, 2) Selection of attributes, such as; age, gender, type of injury incident, time of day, street type and classification, 3) Superimposition of METRO RLIS and CRIME maps.

Results: Study n=1189 injured pedestrians and bicyclists (out of 6765 traumas). Mean age=30 years (SD 19.33), 832 (70%) male. Address match rate >=95%. GIS analysis illustrates notable unequal distributions between four primary quadrants (NW, NE, SW, SE). In comparing TCC, METRO RLIS planning & CRIME (the highest incidence of traffic violation, protective custody, warrant, and fugitive activity) data, there was + correlation between injury patterns;arrays to population density and crime incidence (NE, SW).

Conclusions: This study suggests that there is a relationship between injury risk, crime incidence,and population density among pedestrians and bicyclists in urban neighborhoods. GIS analysis is promising method for linking databases to create a community portrait of injury.

Learning Objectives: 1. Understand the relationship between crime incidence and population density among injured pedestrians and bicyclists. 2. Describe steps in linking databases using GIS. 3. Identify three potential methods for using GIS to create a community injury profile

Keywords: Geographic Information Systems, Injury Risk

Presenting author's disclosure statement:
Organization/institution whose products or services will be discussed: Oregon Health Sciences University The Oregon Trauma System Geographic Information Systems (ArcView Spatial and Network Analyst)
I do not have any significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.

The 128th Annual Meeting of APHA