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

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          Abstract

          Introduction

          There 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.

          Methods

          Road 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.

          Results

          Between 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.

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          Most cited references36

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          Depression and associated factors in internal migrant workers in China.

          Xiao Ma, Jin Li, Peiyuan Qiu … (2011)
          Internal migrant workers are a large population in China. Current health related studies among this population mainly focused on infectious disease, maternal health and occupational diseases and injuries. However, very limited studies were paid attention to mental health of migrant workers though it is an important public health issue. The current study aims to understand prevalence of depression symptoms and factors associated with depression among Chinese migrant workers using novel methods to develop a comprehensive sample. Respondent-driven sampling (RDS) was employed to recruit the target population, who are required 1) not to hold a hukou indicative of living in central areas or near suburbs of Chengdu city; 2) to be 16 years or older; 3) not to be a student. The Center for Epidemiologic Depression Scale (CES-D) was used to measure depression symptoms of migrant workers. And then Structural Equation Model (SEM) was applied to explore factors associated with depression among Chinese migrant workers. Among 1180 migrant workers, 23.7% of them had clinically relevant depression symptoms (CES-D score >= 16), and 12.8% were consistent with a clinical diagnosis of depression (CES-D score >= 21). Self-rated economic status, city adaptation status, and self-rated health had negative effects on depression. Social economic status (SES) affected depression, and was mediated by self-rated economic status and self-rated health. City adaptation status was affected by length of residence in the city, satisfaction with one's job, and the social support that one could obtain while living in the city. The findings indicated a higher prevalence of depression symptoms among migrant workers comparing to general population reported by previous studies, identified possible factors associated with depression symptoms, and also explored relationships between these factors. Our study provides a model to understand mental health of Chinese internal migrant workers and to generate important research questions for the future. Copyright © 2011 Elsevier B.V. All rights reserved.
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            The subjective wellbeing of migrants in Guangzhou, China: The impacts of the social and physical environment

            Fulong Wu, Yuqi Liu, Fangzhu Zhang … (2017)
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              Global impact of COVID-19 pandemic on road traffic collisions

              Yasin Yasin, Michal Grivna, Fikri M Abu-Zidan (2021)
              Background Various strategies to reduce the spread of COVID-19 including lockdown and stay-at-home order are expected to reduce road traffic characteristics and consequently road traffic collisions (RTCs). We aimed to review the effects of the COVID-19 pandemic on the incidence, patterns, and severity of the injury, management, and outcomes of RTCs and give recommendations on improving road safety during this pandemic. Methods We conducted a narrative review on the effects of COVID-19 pandemic on RTCs published in English language using PubMed, Scopus, and Google Scholar with no date restriction. Google search engine and websites were also used to retrieve relevant published literature, including discussion papers, reports, and media news. Papers were critically read and data were summarized and combined. Results Traffic volume dropped sharply during the COVID-19 pandemic which was associated with significant drop in RTCs globally and a reduction of road deaths in 32 out of 36 countries in April 2020 compared with April 2019, with a decrease of 50% or more in 12 countries, 25 to 49% in 14 countries, and by less than 25% in six countries. Similarly, there was a decrease in annual road death in 33 out of 42 countries in 2020 compared with 2019, with a reduction of 25% or more in 5 countries, 15–24% in 13 countries, and by less than 15% in 15 countries. In contrast, the opposite occurred in four and nine countries during the periods, respectively. There was also a drop in the number of admitted patients in trauma centers related to RTCs during both periods. This has been attributed to an increase in speeding, emptier traffic lanes, reduced law enforcement, not wearing seat belts, and alcohol and drug abuse. Conclusions The COVID-19 pandemic has generally reduced the overall absolute numbers of RTCs, and their deaths and injuries despite the relative increase of severity of injury and death. The most important factors that affected the RTCs are decreased mobility with empty lines, reduced crowding, and increased speeding. Our findings serve as a baseline for injury prevention in the current and future pandemics.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Inj Prev
                Journal ID (iso-abbrev): Inj Prev
                Journal ID (hwp): injuryprev
                Journal ID (publisher-id): ip
                Title: Injury Prevention
                Publisher: BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                ISSN (Print): 1353-8047
                ISSN (Electronic): 1475-5785
                Publication date (Print): June 2024
                Publication date (Electronic): 19 December 2023
                Volume: 30
                Issue: 3
                Pages: 224-232
                Affiliations
                [1 ] departmentDepartment of Forensic Evidence Science, School of Forensic Medicine , Ringgold_70570Southern Medical University , Guangzhou, China
                [2 ] Ringgold_506754South China University of Technology School of Mechanical and Automotive Engineering , Guangzhou, China
                [3 ] Guangzhou Public Security Bureau , Guangzhou, China
                [4 ] Guangdong Province Research Center of Traffic Accident Identification Engineering Technology , Guangzhou, China
                [5 ] departmentDepartment of Guangdong Public Security , Forensic Pathology Lab , Guangzhou, China
                Author notes
                [Correspondence to ] Professor Dongri Li, Department of Forensic Evidence Science, School of Forensic Medicine, Southern Medical University, Guangzhou, Guangdong, China; lidongri@ 123456smu.edu.cn
                Author information
                http://orcid.org/0000-0002-2714-2741
                Article
                Publisher ID: ip-2023-044986
                DOI: 10.1136/ip-2023-044986
                PMC ID: 11137450
                PubMed ID: 38123988
                SO-VID: 088f596d-3a6e-4856-bbf0-14f9e21ccfa9
                Copyright © © Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
                License:

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

                History
                Date received : 25 May 2023
                Date accepted : 18 November 2023
                Funding
                Funded by: the Foundation of the Opening of Key Laboratory of the Ministry of Public Security;
                Award ID: GABFYBL202201
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 81971802
                Categories
                Subject: Original Research
                Subject: 1506
                Custom metadata
                special-feature unlocked

                ScienceOpen disciplines: Medicine
                Keywords: motorcycle,migrant workers,violence,cohort study,risk factor research
                Data availability:
                ScienceOpen disciplines: Medicine
                Keywords: motorcycle, migrant workers, violence, cohort study, risk factor research

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