Bakhtiyari Mahmood, Delpisheh Ali, Monfared Ayad Bahadori, Kazemi-Galougahi Mohammad Hassan, Mehmandar Mohammad Reza, Riahi Mohammad, Salehi Masoud, Mansournia Mohammad Ali
a Safety Promotion and Injury Prevention Research Centre , Shahid Beheshti University of Medical Sciences , Tehran , Iran.
Traffic Inj Prev. 2015;16(1):36-41. doi: 10.1080/15389588.2014.898182. Epub 2014 Sep 26.
Traffic crashes are multifactorial events caused by human factors, technical issues, and environmental conditions. The present study aimed to determine the role of human factors in traffic crashes in Iran using the proportional odds regression model.
The database of all traffic crashes in Iran in 2010 (n = 592, 168) registered through the "COM.114" police forms was investigated. Human risk factors leading to traffic crashes were determined and the odds ratio (OR) of each risk factor was estimated using an ordinal regression model and adjusted for potential confounding factors such as age, gender, and lighting status within and outside of cities.
The drivers' mean age ± standard deviation was 34.1 ± 14.0 years. The most prevalent risk factors leading to death within cities were disregarding traffic rules and regulations (45%), driver rushing (31%), and alcohol consumption (12.3%). Using the proportional odds regression model, alcohol consumption was the most significant human risk factor in traffic crashes within cities (OR = 6.5, 95% confidence interval [CI], 4.88-8.65) and outside of cities (OR = 1.73, 95% CI, 1.22-3.29).
Public health strategies and preventive policies should be focused on more common human risk factors such as disregarding traffic rules and regulations, drivers' rushing, and alcohol consumption due to their greater population attributable fraction and more intuitive impacts on society.
交通事故是由人为因素、技术问题和环境条件引起的多因素事件。本研究旨在使用比例优势回归模型确定人为因素在伊朗交通事故中的作用。
对通过“COM.114”警察表格登记的2010年伊朗所有交通事故数据库(n = 592,168)进行调查。确定导致交通事故的人为风险因素,并使用有序回归模型估计每个风险因素的优势比(OR),并针对年龄、性别和城市内外照明状况等潜在混杂因素进行调整。
驾驶员的平均年龄±标准差为34.1±14.0岁。导致城市内死亡的最常见风险因素是无视交通规则和法规(45%)、驾驶员超速(31%)和饮酒(12.3%)。使用比例优势回归模型,饮酒是城市内(OR = 6.5,95%置信区间[CI],4.88 - 8.65)和城市外(OR = 1.73,95% CI,1.22 - 3.29)交通事故中最显著的人为风险因素。
公共卫生策略和预防政策应侧重于更常见的人为风险因素,如无视交通规则和法规、驾驶员超速和饮酒,因为它们的人群归因分数更高,对社会的影响更直观。