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Published:
Apr 11, 2022DOI:
10.4314/mejs.v13i2.3Keywords:
Article Details
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Main Article Content
Identification of Determinant Factors for Car Accident Levels Occurred in Mekelle City, Tigray, Ethiopia: Ordered Logistic Regression Model Approach
Abstract
The car accident injury level is known to be a result of a complex interaction of factors to drivers’ behavior, vehicle characteristics, and environmental condition. Therefore, it is obvious that identifying the contribution of the factors to the accident injury is very critical. The objective of the study was to perform a descriptive analysis to see the characteristics of car accidents, and to assess the prevalence and determinants of road safety practices in Mekelle City, Tigray, Ethiopia. A random sample of data was extracted from the traffic police office from September 2014 to July 2017. An ordered logistic regression model was used to examine factors that worsen the car accident level. A total sample of 385 car accidents was considered in the study of which 56.7% were fatal, 28.6% serious, and 14.7% slight injury. The model estimation result showed that being experienced drivers (Coef. = 0.686; p-value< = 0.050) were found to increase the level of injury. On the other hand, being private vehicle (Coef. = -1.160; p-value <= 0.010), the type of accident of vehicle with pedestrian (Coef. = -2.852; p-value <= 0.010), being heavy truck (Coef. = -0.656; p-value <= 0.050), being a cross country bus (Coef. = -0.889; p-value <= 0.050) and being owner of vehicle is the driver himself (Coef. = -.690, p-value <= 0.050) were found to decrease the level of car accident injury severity. In conclusion, it is better to create continued awareness for those who are experienced drivers, who carelessly follow the traffic rules. Special attention is required for government-owned vehicle drivers, as they were found to increase the level of car accident injury through different short-term training.
