a PLA Clinical College Affiliated with Anhui Medical University , Hefei, Anhui , China.
Traffic Inj Prev. 2014;15(3):319-23. doi: 10.1080/15389588.2013.817669.
To explore the related risk factors of injuries caused by e-bike and bicycle crashes in Hefei, Anhui.
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.
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).
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.
探索合肥市电动自行车和自行车事故致伤的相关危险因素。
2009 年 6 月至 2011 年 6 月,由解放军第 105 医院保存的合肥市电动自行车和自行车事故致伤记录,设计了一份表格,记录患者年龄、性别、道路使用者类别(驾驶员、乘客、行人)、安全因素(安全装置、速度、交通违法行为)、环境因素(创伤时间、光照条件、路面)、碰撞模式、碰撞类型和车辆类型。
205 例中,女性 108 例,男性 97 例。146 例患者因电动自行车事故受伤,59 例因自行车事故受伤。卡方检验比较分类变量的分布表明,年龄(P=.0250)、道路使用者类别(P=.0278)、交通违法(P=.0132)、碰撞模式(P=.0027)、碰撞类型(P=.0019)和车辆类型(P=.0219)与合肥市电动自行车/自行车事故致伤严重程度有关。多因素非条件 logistic 回归分析显示,损伤严重程度最常见于车辆类型(比值比[OR] = 14.418;95%置信区间[CI],4.680-44.418),其次是碰撞模式(OR = 11.556;95% CI,4.430-30.142)、交通违法(OR = 4.735;95% CI,1.934-11.594)和年龄(OR = 2.910;95% CI,1.213-6.979)。
通过对合肥市电动自行车/自行车事故的研究,初步确定了交通伤害的危险因素。这些发现对制定预防措施的决策具有重要意义。