Predictors of human death per Road Traffic Injury in Bahir Bar City, North- Western Ethiopia

Abstract

Background: Road traffic injuries are a major public health problem in developing countries, affecting the health conditions as well as economic activities in Africa. The objective of current study was assessing the predictors of the number of human death per road traffic injury in Bahir Dar city, North-western part of Ethiopia. Materials and Methods: Data collected by traffic police at Bahir Dar city from july2015-june2017 was included under current investigation. A random sample of 172 samples was selected out of 907 registered injuries in the study area. In this study, Zero inflated Quasi- Poisson Regression Model was used for data analysis. Zero Inflated Quasi-Poisson regression models provided more appropriate fit to the number of human death per road traffic injury data included in current investigation. Results: Among the potential predictors, Age of vehicles, sex of driver, age of driver, driving after alcohol drinking, driving under fatigue, not give priority, days of weeks, regular services/maintenance of vehicles, yearly technical checking of vehicles, road condition, overloading, over speeding and type of crush were found to be statistically significant predictors for the number of human death per road traffic injury. Conclusion: Important factors are identified for the cause of the number of human death per road traffic injury. Awareness should be created for those drivers who are driving after drinking alcohol, for those drivers driving on wet road, for those drivers who are driving over speed, overload and for those drivers driving under fatigue. Awareness should be also given for drivers in order to respect the traffic rules.