出版社：The International Institute for Science, Technology and Education (IISTE)
摘要：Road traffic accidents are a major public health concern. In developing countries road traffic accidents are among the leading cause of death and injury. Ethiopia experiences the highest rate of such accidents in Sub-Saharan Africa. Out of all the accidents registered in Ethiopia, Addis Ababa accounts for 60% on average especially in Wolaita zone more 25% on average. The objective of this study is to identify factors that contribute to the occurrence of road traffic accidents leading to human injuries and death. For study purpose we employed ordinal logistic regression models to identify factors influencing traffic fatalities and injuries. Stratified sampling with proportional allocation and simple random sampling technique are used to select samples from recorded frame. The result of ordinal logistic regression analyses shows that drivers aged 18-30 years caused the largest number of accidents. Low educational background of drivers, absence and poor lighting along roads, wet surface and asphalt surface, morning and evening hours, places like offices, residential and commercial neighborhoods, automobiles and small taxis/Bajaj’s were found to be associated with fatalities and serious injuries. We conclude that for effective and safe traffic management, the concerned transportation authorities can consider the above mentioned predictors as potential causes of accidents in their order of importance in order to take preventive measures.
其他摘要：Road traffic accidents are a major public health concern. In developing countries road traffic accidents are among the leading cause of death and injury. Ethiopia experiences the highest rate of such accidents in Sub-Saharan Africa. Out of all the accidents registered in Ethiopia, Addis Ababa accounts for 60% on average especially in Wolaita zone more 25% on average. The objective of this study is to identify factors that contribute to the occurrence of road traffic accidents leading to human injuries and death. For study purpose we employed ordinal logistic regression models to identify factors influencing traffic fatalities and injuries. Stratified sampling with proportional allocation and simple random sampling technique are used to select samples from recorded frame. The result of ordinal logistic regression analyses shows that drivers aged 18-30 years caused the largest number of accidents. Low educational background of drivers, absence and poor lighting along roads, wet surface and asphalt surface, morning and evening hours, places like offices, residential and commercial neighborhoods, automobiles and small taxis/Bajaj’s were found to be associated with fatalities and serious injuries. We conclude that for effective and safe traffic management, the concerned transportation authorities can consider the above mentioned predictors as potential causes of accidents in their order of importance in order to take preventive measures. Keywords: Fatalities, injuries, odds ratio, ordinal logistic regression, traffic accident. Wolaita zone, Ethiopia
