Identification of determinant factors for crash severity levels occurred in Addis Ababa City, Ethiopia, from 2017 to 2020: using ordinal logistic regression model approach

Bekelcho, Tariku; Olani, Ararso Baru; Woldemeskel, Asfawosen; Alemayehu, Micheal; Guta, Geleta · 2023 · Crossref

DOI: 10.1186/s12889-023-16785-3

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Summary

This study investigates the determinant factors influencing road traffic injury severity levels in Addis Ababa, Ethiopia, addressing a critical gap in research within developing nations where road traffic injuries (RTIs) are disproportionately severe and fatal. Motivated by the high burden of RTIs in low-income countries and the lack of extensive research on crash severity determinants in Ethiopia, the authors aimed to identify specific factors associated with injury outcomes to inform targeted road safety policies. The research utilized secondary data from the Addis Ababa Police Commission covering 8,458 recorded accidents between October 2017 and July 2020. The study employed an ordinal logistic regression model to analyze the relationship between various explanatory variables and the ordinal outcome of injury severity, categorized as slight, severe, or fatal. This statistical approach was selected to preserve the ordinal nature of the data without collapsing categories, thereby maintaining statistical power. Variables included driver demographics (age, gender, education, experience), vehicle characteristics (type, ownership), crash circumstances (time, day, light conditions, road type), and victim roles. The proportional odds assumption was tested and confirmed, validating the use of the ordinal model. The results indicated that 15.1% of accidents were fatal, 46.7% severe, and 38.3% slight. The regression analysis identified several factors significantly associated with increased injury severity. Crashes involving commercial trucks, drivers with college-level education or higher, rollover incidents, motorbike passengers, accidents occurring on Fridays, and crashes in darkness were linked to higher odds of severe or fatal injuries. Conversely, factors associated with decreased injury severity included drivers with more than ten years of experience, vehicle passengers (as opposed to drivers or pedestrians), crashes on two-lane roads, and accidents occurring in the afternoon. Pedestrians constituted the majority of victims (71.4%), highlighting their vulnerability. The findings underscore the need for targeted interventions in Addis Ababa. The authors conclude that road safety measures should prioritize strict law enforcement, particularly for commercial truckers, motorcyclists, and government vehicle drivers. Additionally, they recommend training drivers to enhance alertness and vehicle handling skills, especially during turns and in low-light conditions. By identifying specific risk factors, this study provides evidence-based insights for designing predictive models and implementing effective strategies to reduce the frequency and severity of road traffic injuries in Ethiopia.

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Topics

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• demographic disparities
• fatality injury trends
• incidence prevalence
• pre crash contributing factors

Information type

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• Empirical Findings: crash risk outcomes