title: The influence of age on the morbidity and mortality of pedestrian victims.
abstract: OBJECTIVE
  The present study examined the influence of age on the morbidity and mortality of pedestrian victims while controlling for confounding factors.
  
  
  METHODS
  The Pedestrian Crash Data Study (PCDS) database was used for a cross-sectional study to compare the outcome of senior (age >or=60 years) and adult (age 19 to 50 years) pedestrian victims. The outcome measures were the Injury Severity Score (ISS), Maximum Abbreviated Injury Score (MAIS), Abbreviated Injury Scale (AIS), and Mortality. Logistic regression models were used to estimate age-associated risks while controlling for confounders such as vehicle type, impact speed, and pedestrian height, weight, and gender.
  
  
  RESULTS
  Compared to the adult victims, the seniors had a higher average ISS (23 vs. 16, p = 0.018) and higher mortality (30 percent vs. 11 percent, p <or= 0.001). The seniors were also more likely to have an ISS >or=9 (odds ratio = 2.72; 95 percent CI: 1.31-5.68) and to die (odds ratio = 6.68; 95 percent CI: 2.37-19.88). The seniors were approximately twice as likely to have higher AIS scores to almost every body region.
  
  
  CONCLUSIONS
  The adjusted age-dependent risks indicated by the current study should be considered when calculating or projecting pedestrian morbidity and mortality. Adjustment in statistical models is essential to achieve precise risk estimates and in turn to appropriately allocate public health rescores.
authors.affiliation: Center for Applied Biomechanics, University of Virginia, Charlottesville, Virginia, USA. byh6p@virginia.edu
authors.forename: Basem Y
authors.initials: BY
authors.lastname: Henary
authors.forename: Johan
authors.initials: J
authors.lastname: Ivarsson
authors.forename: Jeff R
authors.initials: JR
authors.lastname: Crandall
mesh_terms: D000063:Accidents, Traffic / Q000401:mortality / Q000706:statistics & numerical data*; D000328:Adult; D000367:Age Factors; D003430:Cross-Sectional Studies; D019992:Databases as Topic; D005260:Female; D006801:Humans; D015601:Injury Severity Score; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D018986:Motor Vehicles; D012307:Risk Factors; D014947:Wounds and Injuries / Q000453:epidemiology* / Q000401:mortality