An econometric analysis in identifying behavioral and demographic factors associated with road crash severity in Bangladesh: Evidence from the Dhaka metropolitan city - Nazmul Islam; Nasif Ahmed Chowdhury; Md. Ahnaf Zaman; Armana Sabiha Huq; Sk Fateh Md Rasel (PLoS ONE, 2026)
This study explores the demographic and behavioral determinants of road traffic accident (RTA) severity in the context of the Dhaka metropolitan area, Bangladesh. Road crash data recorded by the Dhaka Metropolitan Police (DMP) were analyzed through ordered logistic regression and generalized ordered logistic regression. The results were interpreted using log odds ratios, odds ratios, predicted probabilities, and marginal effects. The findings reveal that young and middle-aged drivers exhibit significantly higher odds of severe crashes compared to underage drivers. Young-aged drivers are 14 percentage points more likely to cause fatal crashes when compared to old aged drivers in our ordered logit model. In addition, male drivers show higher odds of severe crashes than females. Factors such as overloading of vehicles, alcohol consumption while driving, and over-speeding were identified as the major contributors to increasing crash severity. Alcohol consumption had an odds ratio of 1.223 in the ordered logit model, and it had odds ratios of 2.418, 1.722, and 1.086 for the thresholds of motor collision, simple injury, and grievous injury, respectively, in the generalized ordered logit model. In contrast, the use of seatbelts, vehicle fitness maintenance, and drivers’ licensing shows mitigating effects on crash severity, with significant odds ratios < 1 in both the ordered logit and generalized ordered logit models. From the ordered logit model, we found that seat belt use, fitness certificate, and license decrease the likelihood of fatal crash by 10.7 percentage points, 8.2 percentage points, and 28.2 percentage points, respectively, whereas overspeed increases the likelihood of fatal crash by 13.5 percentage points. The results were reflected in the generalized ordered logit model, too. This research provides valuable insights for policymakers to design and implement effective policies and transport planning, including demographic driving regulations and behavioral control mechanisms to reduce road crash severity.