Assessment of injury severity and recovery trajectories in urban motorcycle crashes: An analysis of hospital data from Dhaka, Bangladesh

Motorcycle crashes, one of the major contributors to worldwide road traffic crashes (RTCs), remain a critical public health issue often in several low- and middle-income countries, where data limitations hinder comprehensive safety assessments. Existing studies have largely relied on police-reported data, which often underrepresents crash severity and lacks detail on post-crash recovery. To address the gap, this study aims to utilize hospital-based data for examining the distribution of patients across demographic, vehicular, situational and crash dynamics related factors; and to provide a severity-based assessment across several variables, such as patient’s age, impact speed, collision type, and impacted body region. Furthermore, it aims to evaluate severity-based post-crash outcomes, focusing on patient’s 30-day recovery status. The study used a questionnaire-based interview to collect data from 509 motorcycle crash victims admitted in two major hospitals, over a nine-month period in Dhaka, Bangladesh. The Abbreviated Injury Scale (AIS) was employed to provide a standardized assessment of injury severity, while the data summarization and visualization was achieved using R software package. Findings reveal a high frequency of motorcycle crashes among males in the 11–40 age bracket, middle-income individuals, and students or service-holders, with most incidents occurring at moderate speeds and head-on collisions on single-lane roads. Severity-based analysis highlights that injuries in AIS 2 (moderate) and 3 (serious) are predominant, with a trend of increasing proportion of injuries with severity of AIS 3 or above correlated with older age groups, high-speed crashes, and specific collision types like rear-end and head-on. Lower extremity, specially the legs, are the most susceptible body part to injuries across all severity categories. Moreover, recovery rates (proportion of injured patients who fully or partially recover from their injuries after 30-days) decrease with higher injury severity, with permanent disabilities being more common among severely injured patients. The data distribution reveals how crash frequency, and severity varies across several key factors while also divulging how injury severity impacts recovery trajectories. The results are expected to provide a foundation for future research and policy development toward reducing motorcycle crash risks and improving post-crash recoveries in similar urban settings.