Identification of determinant factors for crash severity levels occurred in Addis Ababa City, Ethiopia, from 2017 to 2020: using ordinal logistic regression model approach
Abstract Background Road traffic Injuries (RTI) are multifaceted occurrences determined by the combination of multiple factors. Also, severity levels of injuries from road traffic accidents are determined by the interaction of the composite factors. Even though most accidents are severe to fatal in...
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| Format: | Article |
| Language: | English |
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BMC
2023-09-01
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| Series: | BMC Public Health |
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| Online Access: | https://doi.org/10.1186/s12889-023-16785-3 |
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| author | Tariku Bekelcho Ararso Baru Olani Asfawosen Woldemeskel Micheal Alemayehu Geleta Guta |
| author_facet | Tariku Bekelcho Ararso Baru Olani Asfawosen Woldemeskel Micheal Alemayehu Geleta Guta |
| author_sort | Tariku Bekelcho |
| collection | DOAJ |
| description | Abstract Background Road traffic Injuries (RTI) are multifaceted occurrences determined by the combination of multiple factors. Also, severity levels of injuries from road traffic accidents are determined by the interaction of the composite factors. Even though most accidents are severe to fatal in developing countries, there is still a lack of extensive researches on crash severity levels and factors associated with these accidents. Hence, this study was intended to identify severity levels of road traffic injuries and determinant factors in Addis Ababa City, Ethiopia. Methods The study was conducted in Addis Ababa, the capital city of Ethiopia, using secondary data obtained from the Addis Ababa Police Commission office. The ordinal logistic regression model was used to investigate road traffic injury severity levels and factors worsening injury severity levels using the recorded dataset from October 2017 to July 2020. Results A total of 8458 car accidents were considered in the study, of which 15.1% were fatal, 46.7% severe, and 38.3% were slight injuries. The results of the ordinal logistic regression analysis estimation showed that being a commercial truck, college and above level educated driver, rollover crash, motorbike passengers, the crash day on Friday, and darkness were significantly associated factors with crash injury severity levels in the study area. On the contrary, driving experience (> 10 years), passenger of the vehicle, two-lane roads, and afternoon crashes were found to decrease the severity of road traffic injuries. Conclusions Road traffic injury reduction measures should include strict law enforcement in order to maintain road traffic rules especially among commercial truckers, motorcyclists, and government vehicle drivers. Also, it is better to train drivers to be more alert and conscious in their travels, especially on turning and handling their vehicles while driving. |
| first_indexed | 2024-03-09T14:50:18Z |
| format | Article |
| id | doaj.art-570bb03c6daa41fa80783f848c281f92 |
| institution | Directory Open Access Journal |
| issn | 1471-2458 |
| language | English |
| last_indexed | 2024-03-09T14:50:18Z |
| publishDate | 2023-09-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Public Health |
| spelling | doaj.art-570bb03c6daa41fa80783f848c281f922023-11-26T14:29:30ZengBMCBMC Public Health1471-24582023-09-0123111510.1186/s12889-023-16785-3Identification of determinant factors for crash severity levels occurred in Addis Ababa City, Ethiopia, from 2017 to 2020: using ordinal logistic regression model approachTariku Bekelcho0Ararso Baru Olani1Asfawosen Woldemeskel2Micheal Alemayehu3Geleta Guta4Department of Emergency Medicine and Critical Care, Arba Minch UniversityDepartment of Emergency Medicine and Critical Care, Arba Minch UniversityDepartment of Medicine, Ethiopian Police UniversityDepartment of Emergency and Critical Care, Tirunesh Beijing General HospitalDepartment of Water Resources and Irrigation Engineering, Arba Minch UniversityAbstract Background Road traffic Injuries (RTI) are multifaceted occurrences determined by the combination of multiple factors. Also, severity levels of injuries from road traffic accidents are determined by the interaction of the composite factors. Even though most accidents are severe to fatal in developing countries, there is still a lack of extensive researches on crash severity levels and factors associated with these accidents. Hence, this study was intended to identify severity levels of road traffic injuries and determinant factors in Addis Ababa City, Ethiopia. Methods The study was conducted in Addis Ababa, the capital city of Ethiopia, using secondary data obtained from the Addis Ababa Police Commission office. The ordinal logistic regression model was used to investigate road traffic injury severity levels and factors worsening injury severity levels using the recorded dataset from October 2017 to July 2020. Results A total of 8458 car accidents were considered in the study, of which 15.1% were fatal, 46.7% severe, and 38.3% were slight injuries. The results of the ordinal logistic regression analysis estimation showed that being a commercial truck, college and above level educated driver, rollover crash, motorbike passengers, the crash day on Friday, and darkness were significantly associated factors with crash injury severity levels in the study area. On the contrary, driving experience (> 10 years), passenger of the vehicle, two-lane roads, and afternoon crashes were found to decrease the severity of road traffic injuries. Conclusions Road traffic injury reduction measures should include strict law enforcement in order to maintain road traffic rules especially among commercial truckers, motorcyclists, and government vehicle drivers. Also, it is better to train drivers to be more alert and conscious in their travels, especially on turning and handling their vehicles while driving.https://doi.org/10.1186/s12889-023-16785-3Road traffic injuriesOrdinal logistic regressionInjury severity levelAddis AbabaEthiopia |
| spellingShingle | Tariku Bekelcho Ararso Baru Olani Asfawosen Woldemeskel Micheal Alemayehu Geleta Guta Identification of determinant factors for crash severity levels occurred in Addis Ababa City, Ethiopia, from 2017 to 2020: using ordinal logistic regression model approach BMC Public Health Road traffic injuries Ordinal logistic regression Injury severity level Addis Ababa Ethiopia |
| title | Identification of determinant factors for crash severity levels occurred in Addis Ababa City, Ethiopia, from 2017 to 2020: using ordinal logistic regression model approach |
| title_full | Identification of determinant factors for crash severity levels occurred in Addis Ababa City, Ethiopia, from 2017 to 2020: using ordinal logistic regression model approach |
| title_fullStr | Identification of determinant factors for crash severity levels occurred in Addis Ababa City, Ethiopia, from 2017 to 2020: using ordinal logistic regression model approach |
| title_full_unstemmed | Identification of determinant factors for crash severity levels occurred in Addis Ababa City, Ethiopia, from 2017 to 2020: using ordinal logistic regression model approach |
| title_short | Identification of determinant factors for crash severity levels occurred in Addis Ababa City, Ethiopia, from 2017 to 2020: using ordinal logistic regression model approach |
| title_sort | identification of determinant factors for crash severity levels occurred in addis ababa city ethiopia from 2017 to 2020 using ordinal logistic regression model approach |
| topic | Road traffic injuries Ordinal logistic regression Injury severity level Addis Ababa Ethiopia |
| url | https://doi.org/10.1186/s12889-023-16785-3 |
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