Evidence map›Paper›PMID 42694541›Full record

ArticleJournal of public health research2026

Pattern of road traffic accidents in Nepal: A cross-sectional record review.

Minani Gurung, Olita Shilpakar, Lisasha Poudel, Bipsana Shrestha, Aakriti Poudel, Tai Anjuk Lama, Niranjan Panta, Bibek Giri

Abstract read
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Article in Journal of public health research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors.

Minani GurungDepartment of Public Health, Kathmandu University School of Medical Sciences, Dhulikhel, Nepal.ORCID https://orcid.org/0000-0002-0330-0848
Olita ShilpakarDepartment of Emergency Medicine, Maharajgunj Medical Campus, Institute of Medicine, Tribhuvan University Teaching Hospital, Kathmandu, Nepal.
Lisasha PoudelInstitute of Medicine, Tribhuvan University, Kathmandu, Nepal.
Bipsana ShresthaInstitute of Medicine, Tribhuvan University, Kathmandu, Nepal.
Aakriti PoudelSchool of Public Health, Patan Academy of Health Sciences, Lalitpur, Nepal.
Tai Anjuk LamaEmergency Department, Patan Academy of Health Sciences, Lalitpur, Nepal.
Niranjan PantaWestern Regional Hospital, Pokhara Academy of Health Sciences, Pokhara, Nepal.
Bibek GiriGraduate School of Venture, Hoseo University, Seoul, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Road traffic accidents (RTAs) are a leading cause of mortality and disability in Nepal. Despite the scale of the problem, comprehensive province-level analyses covering recent years remain limited. This study describes the pattern of RTAs across all seven provinces of Nepal over four fiscal years. Design and methods: A cross-sectional record review was conducted using RTA records obtained from Nepal Traffic Police departments across all provinces. Records spanning fiscal years 2020/21-2023/24 AD were analysed. Variables extracted included province and year of incident, urban/rural classification, driver age group, and vehicle type. Descriptive statistics were computed using SPSS version 20. Data for 2023/24 cover only the first five months of the fiscal year and should be interpreted with caution. Results: A total of 74,929 RTAs were recorded over the study period. Annual totals increased from 20,640 in 2020/21 to a peak of 24,537 in 2021/22, before declining modestly to 23,597 in 2022/23. The Kathmandu Valley consistently recorded the highest accident burden (10,733 in 2021/22; 10,675 in 2022/23). Drivers aged 25-40 years accounted for the largest proportion of recorded driver involvements with known age (58,614; 50.2%), followed by those aged 16-25 years (34,886; 29.9%). Motorcycles and scooters were the most commonly involved vehicle type. Urban areas accounted for 30,401 accidents (59.0% of accidents with known location), though rural predominance was observed in Madhesh and Koshi provinces. Conclusions: RTAs in Nepal are concentrated among young and middle-aged adult drivers, predominantly involve two-wheeled vehicles, and exhibit marked urban-rural variation across provinces. These findings support age-targeted safety interventions, strengthened motorcycle helmet enforcement, and geographically differentiated road safety strategies.

Indexed as

cross-sectional studyepidemiologyNepalroad traffic accidentroad traffic injurytraffic police records

Identifiers

PMID42694541
PMCPMC13539021

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.