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Journal Article

Citation

Sedain B, Gurung YB. Inj. Prev. 2022; 28(Suppl 2): A56.

Copyright

(Copyright © 2022, BMJ Publishing Group)

DOI

10.1136/injuryprev-2022-safety2022.167

PMID

unavailable

Abstract

Proceedings of the 14th World Conference on Injury Prevention and Safety Promotion (Safety 2022)

Background As in many countries, Nepal is also experiencing death and disability in population from Road Traffic Injuries (RTIs).

Aims This study aims to describe the status and risk factors of RTIs in Nepal.

Methods Details recorded by Nepal Police for FY 2017/18 were extracted, and a descriptive analysis was carried out to describe road traffic injuries and deaths. Logistic regression and Random Forest algorithm were used, and feature importance was calculated to identify factors associated with road traffic deaths.

Results A total of 25,511 people were exposed to Road Traffic Crashes (RTCs) in the study period, of which 8.5% were deaths. The mean age of victims was 30.89 years, and the majority were male (75.5%). Most of the RTCs occurred between 14:00 and 20:00 hours; however, deaths were higher during 16:00-20:00 hours. Motorized two-wheelers were involved in 40% of RTIs, followed by pedestrians (23.2%). Non-fatal injuries were highest for young adults, whereas children and seniors (60+ years) were at higher risk of death. Random Forest and logistic regression analysis predicted that tractor crashes posed a higher death probability. Similarly, RTCs with pedestrians in Bagmati Province on Friday were more likely to result in death.

Conclusion Numerous two-wheelers, tractor users, and pedestrians were dying and disabled from preventable deaths. Hence, comprehensive road safety measures need to be implemented to prevent untimely deaths.

Learning outcomes Feature importance obtained from the Random Forest model and logistic regression and descriptive analysis can be used to better understand the risk factors of road crashes.


Language: en

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