title: Revisiting exposure: fatal and non-fatal traffic injury risk across different populations of travelers in Wisconsin, 2001-2009.
abstract: Comparing the injury risk of different travel modes requires using a travel-based measure of exposure. In this study we quantify injury risk by travel mode, age, race/ethnicity, sex, and injury severity using three different travel-based exposure measures (person-trips, person-minutes of travel, and person-miles of travel) to learn how these metrics affect the characterization of risk across populations. We used a linked database of hospital and police records to identify non-fatal injuries (2001-2009), the Fatality Analysis Reporting System for fatalities (2001-2009), and the 2001 Wisconsin Add-On to the National Household Travel Survey for exposure measures. In Wisconsin, bicyclists and pedestrians have a moderately higher injury risk compared to motor vehicle occupants (adjusting for demographic factors), but the risk is much higher when exposure is measured in distance. Although the analysis did not control for socio-economic status (a likely confounder) it showed that American Indian and Black travelers in Wisconsin face higher transportation injury risk than White travelers (adjusting for sex and travel mode), across all three measures of exposure. Working with multiple metrics to form comprehensive injury risk profiles such as this one can inform decision making about how to prioritize investments in transportation injury prevention.
authors.affiliation: Department of Planning and Design, University of Colorado Denver, 1250 14(th) Street, Suite 300, Denver, CO 80209, United States. Electronic address: carolyn.mcandrews@ucdenver.edu.
authors.forename: Carolyn
authors.initials: C
authors.lastname: McAndrews
authors.forename: Kirsten
authors.initials: K
authors.lastname: Beyer
authors.forename: Clare E
authors.initials: CE
authors.lastname: Guse
authors.forename: Peter
authors.initials: P
authors.lastname: Layde
mesh_terms: D000063:Accidents, Traffic / Q000401:mortality / Q000517:prevention & control / Q000706:statistics & numerical data*; D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D001642:Bicycling / Q000293:injuries* / Q000706:statistics & numerical data; D002648:Child; D002675:Child, Preschool; D016208:Databases, Factual; D005006:Ethnicity; D005260:Female; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D015601:Injury Severity Score; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D018986:Motor Vehicles / Q000706:statistics & numerical data*; D009049:Motorcycles; D044469:Racial Groups; D018570:Risk Assessment; D012307:Risk Factors; D012449:Safety; D012737:Sex Factors; D013997:Time Factors; D014195:Travel / Q000706:statistics & numerical data*; D016138:Walking / Q000293:injuries* / Q000706:statistics & numerical data; D014922:Wisconsin / Q000453:epidemiology; D014947:Wounds and Injuries / Q000453:epidemiology / Q000209:etiology* / Q000401:mortality; D055815:Young Adult
keywords: Accident; Exposure; Injury prevention; Traffic safety; Victim characteristics