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Injury severity level and associated factors among road traffic accident victims attending emergency department of Tirunesh Beijing Hospital, Addis Ababa, Ethiopia: A cross sectional hospital-based study

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  • Rediet Fikru Gebresenbet
  • Anteneh Dirar Aliyu

Abstract

Background: Road Traffic Accidents have become an enormous global public health problem killing approximately 1.25 million people and injuring 20 to 50 million others yearly. It is the 10th leading cause of death universally and the number one cause of mortality of the young population between the ages of 5 and 29. Only few studies have been conducted on the severity of road traffic injuries in Ethiopia hence the need for the study. Objective: To assess injury severity level and associated factors among road traffic accident victims. Methods: A cross-sectional study of patients involved in road traffic accident and attended Tirunesh Beijing hospital, Addis Ababa, Ethiopia. Victims were consecutively recruited until sample size (164) attained during the study period. Data collectors administered a structured questionnaire. The collected data was then entered and cleaned using Epi info and exported to IBM SPSS for statistical analysis. Independent factors associated with injury severity were assessed using bivariate and multivariate logistic regression. Results: A total of 164 road traffic injury victims were included to the study. Prevalence of severe injury accounted for 36.6% of cases. “can read and write” educational status OR 35.194(95% CI; 3.325–372.539), sustaining multiple injury OR 18.400(95% CI; 5.402–62.671), sustaining multiple injury type OR 6.955(95% CI; 1.716–28.185) and being transported by ambulance from the scene of accident OR 13.800(95% CI; 1.481–128.635) were the explanatory variables found to have a statistically significant association with severe injury. Conclusion: This study showed road traffic accident is predominantly affecting the economically active, male young population. Not a single victim received pre-hospital care, majority were extracted by bystanders and most used commercial vehicle to be transported to a health institution reflecting the need for improvements in pre-hospital emergency services and socio-economic related infrastructures.

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  • Rediet Fikru Gebresenbet & Anteneh Dirar Aliyu, 2019. "Injury severity level and associated factors among road traffic accident victims attending emergency department of Tirunesh Beijing Hospital, Addis Ababa, Ethiopia: A cross sectional hospital-based st," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-16, September.
    • Handle: RePEc:plo:pone00:0222793
    DOI: 10.1371/journal.pone.0222793
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    References listed on IDEAS

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    1. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
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    1. Yookyung Boo & Youngjin Choi, 2021. "Comparison of Prediction Models for Mortality Related to Injuries from Road Traffic Accidents after Correcting for Undersampling," IJERPH, MDPI, vol. 18(11), pages 1-14, May.
    2. Vorapot Sapsirisavat & Wiriya Mahikul, 2021. "Drinking and Night-Time Driving May Increase the Risk of Severe Health Outcomes: A 5-Year Retrospective Study of Traffic Injuries among International Travelers at a University Hospital Emergency Cente," IJERPH, MDPI, vol. 18(18), pages 1-9, September.

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