Modelling the risk factors for injury severity in motorcycle users in Ghana

• Published in: Journal of public health Vol. 28; no. 2; pp. 199 - 209
• Main Authors: Aidoo, Eric Nimako, Amoh-Gyimah, Richard
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2020; Springer Nature B.V
• Subjects: Crashes; Data processing; Epidemiology; Health Promotion and Disease Prevention; Industrial research; Logit models; Medicine; Medicine & Public Health; Motorcycles; Occupant injuries; Original Article; Passengers; Public Health; Risk analysis; Risk factors; Roads & highways; Traffic accidents; Traffic accidents & safety; Traffic control; Weather; Ghana; Pillion passenger; Generalized ordered logit; Motorcycle; Traffic crashes; Injury severity; Rider
• ISSN: 2198-1833; 1613-2238
• DOI: 10.1007/s10389-019-01047-7

Aim This study aims to determine risk factors associated with the injury severity of motorcycle users in Ghana. Subject and methods Data on all reported crashes involving motorcycle users in Ghana were analyzed. The data were extracted from the National Road Traffic Accident Database at the Building and Road Research Institute (BRRI) of the Council for Scientific and Industrial Research (CSIR). Generalized ordered logit models were specified separately for riders and pillion passengers to determine the relationship between injury severity, as an ordered categorical outcome, and a set of possible explanatory variables. Results The results from the model showed that the injury severity of both riders and pillion passengers was significantly influenced by the day of the week when the crash occurred, weather conditions, road geometry, location type, and traffic control. In addition, the injury severity of riders was also influenced by their age, presence of passenger, and light conditions, whilst the injury severity of pillion passengers was influenced by the time of the crash. Conclusion The findings from this study provide useful information to improve the understanding of risk factors associated with motorcycle user injury severity. Such data are also important to support the development of appropriate countermeasures to help prevent motorcycle crashes.