Analysis of pedestrian-vehicle crash injury severity factors in Colorado 2006–2016

• Published in: Accident analysis and prevention 2020-12, Vol.148, p.105782-105782, Article 105782
• Main Authors: Batouli, Ghazal, Guo, Manze, Janson, Bruce, Marshall, Wesley
• Format: Article
• Language: English
• Subjects: Accidents, Traffic - mortality; Colorado - epidemiology; Humans; Lives potentially saved; Logistic Models; Logistic regression; Outcome severity; Pedestrian safety; Pedestrians; Risk Factors; Wounds and Injuries - epidemiology
• ISSN: 0001-4575; 1879-2057
• DOI: 10.1016/j.aap.2020.105782

•13,856 reported pedestrian-vehicle crashes in Colorado from 2006 to 2016 were analyzed.•14,391 pedestrians were involved in these crashes causing 612 pedestrian fatalities and 11,576 pedestrian injuries.•Significant factors were intersection proximity, lighting, vehicle type and speed, ped age and impairment, and driver impairment.•Lives potentially saved by having better factor levels present are estimated using risk ratios from logistic regression.•Lives saved estimates reflect relative magnitudes of benefits that might be achieved by potential countermeasures. This paper investigates factors associated with the severity of pedestrian outcomes from motor vehicle crashes by analyzing a database of all 13,856 reported pedestrian crashes in Colorado over an 11-year period from 2006 to 2016. A total of 14,391 pedestrians were involved in these crashes, resulting in 612 (4.3%) pedestrian fatalities, 11,576 (80.4%) pedestrian injuries, and 2203 (15.3%) property damage only outcomes. The objective is to analyze crash records, as similarly compiled by other states, to show how lives potentially saved by improved factor levels can be estimated as needed for benefit-cost comparisons of alternative countermeasures. Odds ratios of fatal versus non-fatal pedestrian outcomes are computed both independently (unadjusted) and from logistic regression (adjusted) for each factor level accounting for possible correlations between factors. Also computed are odds ratios for fatal plus incapacitating injuries and odds ratios for just 2011−2016 versus all years. This study found that intersection proximity, lighting condition, vehicle type and speed, pedestrian age, pedestrian impairment, and driver impairment by drugs or alcohol were all significant factors associated with the severity of pedestrian outcomes from motor vehicle crashes. Risk ratios from these odds ratios are used to estimate lives potentially saved by having better factor levels present at the time of these crashes. These estimates reflect the relative magnitudes of benefits that might be achieved by potential countermeasures taking into account the number of cases affected.