title: Assessing the relative risk of severe injury in automotive crashes for older female occupants.
abstract: A logistic regression model was used in the prediction of injury severity for individuals who are involved in a vehicular crash. The model identified females and older occupants (segmented by age 55-74, and 75 and older) as having a significantly higher risk of severe injuries in a crash. Further, interactions of older females with other factors, such as occupant seat position, crash type, and environmental factors were also shown to significantly impact the relative risk of a severe injury. This study revealed that females 75 years and older had the lowest odds of injury among all female occupants studied (OR=1.16) while females between 55 and 74 years old have higher risk of severe injuries (OR=1.74). All older females (55 and older) were at greater risk for head-on, side-impact and rear-end collisions. Seatbelt use reduced severe injuries for females in this age group, but not to the same extent as the rest of the population studied. Additionally, crashes in severe weather, which were less likely to result in severe injuries for the general population, increased the risk of severe injuries to females that were 55 and older. Among occupants of light trucks, sport utility vehicles and vans, older females were less likely than others to be severely injured. In this case, older females appear better off in vehicles which are larger and protect better in severe crashes. This research demonstrates that circumstances surrounding a crash greatly impact the severity of injuries sustained by older female occupants.
authors.affiliation: Department of Mechanical and Industrial Engineering, and Public Policy Center, The University of Iowa, 3131 Seamans Center, Iowa City, IA 52242, USA.
authors.forename: John D
authors.initials: JD
authors.lastname: Hill
authors.forename: Linda Ng
authors.initials: LN
authors.lastname: Boyle
mesh_terms: D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D017677:Age Distribution; D000367:Age Factors; D000368:Aged; D016022:Case-Control Studies; D005260:Female; D006801:Humans; D015994:Incidence; D016015:Logistic Models; D008875:Middle Aged; D012042:Registries / Q000706:statistics & numerical data; D012306:Risk; D015599:Trauma Severity Indices; D014481:United States / Q000453:epidemiology; D014947:Wounds and Injuries / Q000453:epidemiology*