title: Analysis of risk factors affecting the severity of intersection crashes by logistic regression.
abstract: OBJECTIVE
  The objective of this research was to study the risk factors that significantly influence the severity of intersection crashes for vehicle occupants, as well as for pedestrians and other vulnerable road users.
  
  
  METHODS
  Logistic regression was applied as the method in this study to analyze a data set of intersection crashes involving casualties in Victoria, Australia, for the period January 2000 to December 2009.
  
  
  RESULTS
  Seven risk factors obtained were found to be significantly associated with the severity of intersection crashes, including driver age and gender, speed zone, traffic control type, time of day, crash type, and seat belt usage.
  
  
  CONCLUSIONS
  This study found that male drivers as well as older drivers (age 65 and above) had higher odds of being involved in fatal intersection crashes. Intersection crashes occurring between midnight and early morning (12:00 a.m. to 5:59 a.m.), in 100 km/h speed zones, or with no traffic control had a higher odds of a fatal outcome than their counterpart categories. Furthermore, intersection crashes involving pedestrians or a non-seat belt-wearing driver were more likely to lead to a fatal outcome. In general, identification of risk factors and the discussion of the odds ratio between levels on the impact of the intersection crash severity would be beneficial for road safety stakeholders to develop initiatives to reduce the severity of intersection crashes.
authors.affiliation: State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, Hunan, China.
authors.forename: Huiqin
authors.initials: H
authors.lastname: Chen
authors.forename: Libo
authors.initials: L
authors.lastname: Cao
authors.forename: David B
authors.initials: DB
authors.lastname: Logan
mesh_terms: D000063:Accidents, Traffic / Q000401:mortality* / Q000706:statistics & numerical data*; D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000367:Age Factors; D000368:Aged; D004779:Environment Design / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D012307:Risk Factors; D012622:Seat Belts / Q000706:statistics & numerical data; D017678:Sex Distribution; D012737:Sex Factors; D013997:Time Factors; D014739:Victoria / Q000453:epidemiology; D016138:Walking / Q000293:injuries*; D055815:Young Adult