Patterns of injuries and injury severity among hospitalized road traffic injury (RTI) patients in Bangladesh

Abstract

Background: Road traffic injuries (RTIs) are one of the key public health issues worldwide causing 1.3 million deaths every year. This study aimed to determine the patterns of injuries due to road traffic accidents (RTAs), the severity of injuries, and factors associated with injury severity. Methodology: A cross-sectional study was conducted among RTA victims, who attended two large tertiary care hospitals located inside the Dhaka metropolitan area, through structured interview between 28 January and 22 March 2020. Results: Among 375 RTI patients, a total of 1390 injuries were recorded among interviewed patients, yielding a mean of 3.7 injuries per patient. The most frequently injured systems were external (n ¼ 351), lower limb (n ¼ 235), head and neck (n ¼ 151), and face (n ¼ 150). The mean ISS were 20.96 AE 12.027 with a maximum of 65 and a minimum of 4. Among patients, 87 (23.20%) had a severe injury, and 37 (9.87%) patients were critically injured. A statistically significant variation in ISS was observed in ANOVA among various categories of age, education, occupation, and purpose of going outside, vehicle type and fitness, accident type, road type, times required in hospitalization, and death history (p < 0.05). Conclusions: Our study has revealed several important findings which will help stakeholders and policymakers devise better policies to reduce RTA and RTA related injuries in Bangladesh.

Socioeconomic status and severity of traffic accident injuries: a cross-sectional study

“…Similar to our study, family income and employment were significantly associated with the severity of the injury of traffic accidents (15). Hasselberg et al showed that young drivers from worker families have an 80% higher risk of accidents than young drivers from employed families (16).…”

Association of Air Pollution and Weather Factors with Traffic Injury Severity: A Study in Taiwan

“…Low light levels result in delayed reaction times [ 63 ]. A cross-sectional study in Bangladesh indicated that patients who sustained from RTAs that occurred after midnight tended to have higher ISSs [ 64 ].…”

A knowledge elicitation approach to traffic accident analysis in open data: comparing periods before and after the Covid-19 outbreak

“…The literature identifies the growing importance of traffic accidents as the main cause of injuries and fatalities ( Olowosegun et al, 2022 ; Roy et al, 2021 ; Valent, 2022 ; Ratanavaraha and Suangka, 2014 ; Xin et al, 2020 ). Various determinants have been considered and examined in association with traffic accidents and models have been developed to explain these determinants.…”

“…There are a variety of reasons for the serious problem of a high volume of traffic accidents, and some possible solutions with respect to policies and strategies, such as helmet and drink-driving laws, have been proposed and implemented ( Vorel et al, 2014 ; George et al, 2017 ; Alcaniz et al, 2021 ). Prediction models that can be used to disclose causes of traffic accidents in historical data are proposed by researchers to aid in developing such strategies to reduce traffic accidents ( Li and Zhao, 2022 ; Roy et al, 2021 ; Valent, 2022 ; Sangkharat et al, 2021 ; Olowosegun et al, 2022 ; Antona-Makoshi et al, 2018 ).…”

“…The models that have been proposed to predict accidents have adopted various data sources and analysis techniques ( Chand et al, 2021 ; Li and Zhao, 2022 ; Olowosegun et al, 2021; Roy et al, 2021 ). For example, classification-oriented models (decision trees) were proposed to discover decision rules to detect traffic accidents ( de Oña et al, 2014 ; da Cruz da Cruz Figueira et al, 2017 ).…”