title: Induced exposure estimates of rollover risk for different types of passenger vehicles.
abstract: OBJECTIVE
  This study aimed to model rollover risk of New Zealand and Australian passenger vehicles to identify which driver and vehicle factors were associated with the highest risk of rollover. A further objective was to test the feasibility and reliability of the quasi-induced risk estimation approach for studying rollover risk.
  
  
  METHODS
  The most appropriate comparison crash type, whose counts formed the exposure measures for the induced exposure risk estimates, had been identified in a previous study to be multi-vehicle crashes in which the vehicle in question had been damaged in the rear. Statistical models were fitted to data from four Australasian jurisdictions from 1993 to 2004 for vehicles involved in rollover crashes and vehicles involved in the comparison crash type.
  
  
  RESULTS
  Higher rollover risk was found for those vehicle types with a relatively high center of gravity compared to the width of the wheel track, namely sport utility vehicles (SUVs) and people movers. A particularly high risk of rollover was found when teenagers drove SUVs. Within vehicle market groups, there was evidence of improving rollover safety for newer model vehicles relative to older vehicles and evidence of generally reducing rollover risk over the period studied.
  
  
  CONCLUSIONS
  The quasi-induced exposure method produced very consistent estimates of rollover risk despite large differences in the crash recording systems and crash type definitions used in the four jurisdictions studied. This provides evidence of the reliability of this approach to crash risk estimation and of the generalizability of the findings of this study.
authors.affiliation: Wellington School of Medicine and Health Sciences, Otago University, Wellington, New Zealand. Michael.keall@otago.ac.nz
authors.forename: Michael
authors.initials: M
authors.lastname: Keall
authors.forename: Stuart
authors.initials: S
authors.lastname: Newstead
mesh_terms: D000063:Accidents, Traffic / Q000145:classification* / Q000706:statistics & numerical data*; D000328:Adult; D000367:Age Factors; D001315:Australia; D001336:Automobiles / Q000145:classification* / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009520:New Zealand; D018570:Risk Assessment; D012307:Risk Factors; D012737:Sex Factors