Crash Characteristics And Injury Patterns Among Commercial Motorcycle Users Attending Kitale County Referral Hospital, Kenya 2013

Abstract

Globally road traffic injuries contribute significantly to the burden of disease and mortality. Road traffic injuries are ranked 9th among the leading causes of Disability adjusted life years lost and predicted to be 7th by the year 2030. Each year more than 1.25 million people are killed and as many as 50 million are injured. Most vulnerable group that account for half of traffic deaths globally are motorcyclists, passengers and pedestrians. Number of deaths in Kenya from motorcycle injury has been increasing in the past 10 years from as low as 44 in 2005 to 391 deaths in 2014. This descriptive cross sectional study sought to determine crash characteristics and injury patterns among motorcycle users attending Kitale county referral hospital, Kenya. Three hundred and seventy-one commercial motorcycle crash victims were recruited into the study. Data collection was done using a semi structured, interviewer administered questionnaire. The mean age of the motorcycle crash victims was 30.7 years (range 3-80years). Males were 269 (70.1%) and females 115 (29.9%). Motorcycle traffic injuries accounted for 39.4% of all traffic crashes. The most common mechanism of motorcycle crash injury involved motorcycle versus vehicle 175 (45.6%). Majority of the injured patients 240 (69.9%) were assessed as having Glasgow coma scale (GCS) of 9-12, 26% Glasgow coma scale of 13-15 and 7% Glasgow coma scale of 3-8. Pattern of injuries sustained by victims included; head and neck injury 147 (39.9%), lower extremity injury 147 (39.9%) and chest injury 30 (8.2%). Higher proportions of motorcycle riders had severe injuries as compared to passengers ( 2 =127.649, P<0.01). Similarly a statistical relationship existed between age group (25-30 years) and severity of motorcycle crash injuries ( 2 =17.678, P<0.007). Majority of motorcycle riders 167 (45.1%) and passengers 149 (38.9%) who did not have a helmet during the crash injury sustained head injuries. This was statistically significant ( 2 =106.944, P<0.001). Among the motorcycle riders 62.3% had no formal training and this was statistically significant ( 2 =5.72, p<0.001). Head injuries and lower extremity injuries accounted for the major proportion of injuries sustained by xviii motorcycle users. Non helmet use was associated with increased risk of head injuries. Morbidity can be mitigated by encouraging use of protective gear like helmets and wearing of reflective clothing.