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

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.