A generalized ordered logit analysis of risk factors associated with driver injury severity

Eric Nimako Aidoo*, Williams Ackaah

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


Aim: Road traffic crashes remain a major public health issue and have been the subject of debate in many studies due to their effect on society. This study contributes to the discussion by investigating the risk factors that significantly contribute to driver injury severity sustained in traffic crashes. Subject and methods: Using the crash data from the Greater Accra region of Ghana, spanning a 3-year period (2014–2016), a generalized ordered logit (GOL) model was estimated to determine the effect of a wide range of variables on driver injury severity outcome. Results: The results suggest that, in the event of a crash, more severe driver injury was influenced by multiple factors including driver’s gender, driver’s action (e.g., turning, overtaking, going ahead), number of vehicles involved, day of week of the crash, vehicle size, and road width. Conclusion: The findings of this study highlight the need to further study risk factors significantly influencing driver injury severity.

Original languageEnglish
Pages (from-to)471-477
Number of pages7
JournalJournal of Public Health
Issue number2
Early online date19 Oct 2019
Publication statusPublished - Apr 2021


  • Accra
  • Driver injury severity
  • Generalized ordered logit model
  • Ordered response

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health


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