Feng Hu1, Donglai Lv, Jie Zhu, Jian Fang. 1. a PLA Clinical College Affiliated with Anhui Medical University , Hefei, Anhui , China.
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.
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: Till Berk; Sascha Halvachizadeh; Johannnes Backup; Yannik Kalbas; Thomas Rauer; Ralph Zettl; Hans-Christoph Pape; Florian Hess; Jo Ellen Welter Journal: Patient Saf Surg Date: 2022-03-05
Authors: Susana García-Herrero; Juan Diego Febres; Wafa Boulagouas; José Manuel Gutiérrez; Miguel Ángel Mariscal Saldaña Journal: Int J Environ Res Public Health Date: 2021-07-04 Impact factor: 3.390