OBJECTIVE: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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.
OBJECTIVE: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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.
Entities:
Keywords:
Iran; alcohol; crashes; human factors; public health
Authors: Edrisa Sanyang; Corinne Peek-Asa; Paul Bass; Tracy L Young; Babanding Daffeh; Laurence J Fuortes Journal: J Environ Public Health Date: 2017-04-23