Evidence map›Paper›PMID 38123988›Full record

ArticleInjury prevention : journal of the International Society for Child and Adolescent Injury Prevention2024

Overview of road traffic injuries among migrant workers in Guangzhou, China, from 2017 to 2021.

Tengfei Yang, Jiangwei Kong, Xinzhe Chen, Haotian Zeng, Nian Zhou, Xingan Yang, Qifeng Miao, Xinbiao Liao, Fu Zhang, Fengchong Lan and 2 more

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 33% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 1 country.

Tengfei YangDepartment of Forensic Evidence Science, School of Forensic Medicine, Southern Medical University, Guangzhou, China.
Jiangwei KongDepartment of Forensic Evidence Science, School of Forensic Medicine, Southern Medical University, Guangzhou, China.
Xinzhe ChenSouth China University of Technology School of Mechanical and Automotive Engineering, Guangzhou, China.
Haotian ZengGuangzhou Public Security Bureau, Guangzhou, China.
Nian ZhouDepartment of Forensic Evidence Science, School of Forensic Medicine, Southern Medical University, Guangzhou, China.
Xingan YangDepartment of Forensic Evidence Science, School of Forensic Medicine, Southern Medical University, Guangzhou, China.
Qifeng MiaoGuangdong Province Research Center of Traffic Accident Identification Engineering Technology, Guangzhou, China.
Xinbiao LiaoDepartment of Guangdong Public Security, Forensic Pathology Lab, Guangzhou, China.
Fu ZhangDepartment of Guangdong Public Security, Forensic Pathology Lab, Guangzhou, China.
Fengchong LanSouth China University of Technology School of Mechanical and Automotive Engineering, Guangzhou, China.
Huijun WangDepartment of Forensic Evidence Science, School of Forensic Medicine, Southern Medical University, Guangzhou, China.
Dongri LiDepartment of Forensic Evidence Science, School of Forensic Medicine, Southern Medical University, Guangzhou, China lidongri@smu.edu.cn.ORCID 0000-0002-2714-2741
Southern Medical University · CNSouth China University of Technology · CNShanghai Public Security Bureau · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThere are many migrant workers in China's first-tier cities, but little is known about road safety. This paper systematically analysed road traffic injuries and risk factors among migrant workers in Guangzhou, China.

methodsRoad traffic crash data from 2017 to 2021 were obtained from the Guangzhou Public Security Traffic Management Integrated System. We plotted the crash network of road users in road traffic crashes and used logistic regression to analyse the risk factors for migrant workers of motorcycle and four-wheeled vehicle crashes. Moreover, the roles of migrant workers and control individuals as perpetrators in road traffic crashes were also analysed.

resultsBetween 2017 and 2021, 76% of road traffic injuries were migrant workers in Guangzhou. Migrant workers who were motorcyclist drivers most commonly experienced road traffic injuries. Crashes between motorcyclists and car occupants were the most common. The illegal behaviours of migrant worker motorcyclists were closely related to casualties, with driving without a licence only and driving without a licence and drunk driving accounting for the greatest number. Migrant workers were responsible for many injuries of other road users. Motorcycle drivers have a higher proportion of drunk driving. DISCUSSION: Migrant workers play an important role in road traffic safety. They were both the leading source of road traffic injuries and the main perpetrators of road traffic crashes. Measures such as strict requirements for migrant workers to drive motorcycles with licences, prohibit drunk driving, greater publicity of road safety regulations, and combining compulsory education with punishment for illegal behaviours.

Indexed as

Accidents, TrafficMotorcyclesTransients and MigrantsAdultAutomobile DrivingChinaDriving Under the InfluenceFemaleHumansMaleMiddle AgedRisk FactorsWounds and Injuriescohort studymigrant workersmotorcyclerisk factor researchviolence

Identifiers

PMID38123988
PMCPMC11137450
OpenAlexW4389977543

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.