title: Related risk factors for injury severity of e-bike and bicycle crashes in Hefei.
abstract: OBJECTIVE
  To explore the related risk factors of injuries caused by e-bike and bicycle crashes in Hefei, Anhui.
  
  
  METHODS
  Between June 2009 and June 2011, the records of injuries were triggered by e-bike and bicycle crashes in Hefei maintained by 105th Hospital of PLA. A form was designed to document patient age, gender, road user category (driver, passenger, pedestrian), safety factors (safety devices present, speed, traffic violations), environmental factors (time of trauma, light conditions, road surface), crash mode, impact type, and vehicle type.
  
  
  RESULTS
  Of the 205 cases, 108 were female and 97 were male. One hundred forty-six patients suffered injuries due to e-bike accidents and 59 due to bicycle accident. The chi-squared test compared distribution of categorical variables suggested that age (P =.0250), road user category (P =.0278), traffic rule violations (P =.0132), crash mode (P =.0027), impact type (P =.0019), and vehicle type (P =.0219) are related to the severity of injuries caused by e-bike/bicycle crashes in Hefei. The multiple-factor nonconditional logistic regression analysis showed that injury severity is the most commonly sustained within the vehicle type (odds ratio [OR] = 14.418; 95% confidence interval [CI], 4.680-44.418), followed by crash mode (OR = 11.556; 95% CI, 4.430-30.142), traffic rule violations (OR = 4.735; 95% CI, 1.934-11.594), and age (OR = 2.910; 95% CI, 1.213-6.979).
  
  
  CONCLUSIONS
  With the study of e-bike/bicycle crashes in Hefei, primary identification of the risk factors for the traffic injuries is obtained. These findings are important in decision making regarding preventive measures.
authors.affiliation: a PLA Clinical College Affiliated with Anhui Medical University , Hefei, Anhui , China.
authors.forename: Feng
authors.initials: F
authors.lastname: Hu
authors.forename: Donglai
authors.initials: D
authors.lastname: Lv
authors.forename: Jie
authors.initials: J
authors.lastname: Zhu
authors.forename: Jian
authors.initials: J
authors.lastname: Fang
mesh_terms: D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001642:Bicycling / Q000293:injuries*; D002648:Child; D002675:Child, Preschool; D002681:China; D005260:Female; D006801:Humans; D015601:Injury Severity Score; D008297:Male; D008875:Middle Aged; D012044:Regression Analysis; D012307:Risk Factors; D055815:Young Adult