Evidence map›Paper›PMID 32680705›Full record

ReviewChinese journal of traumatology = Zhonghua chuang shang za zhi2020

Global road traffic injury statistics: Challenges, mechanisms and solutions.

Fang-Rong Chang, He-Lai Huang, David C Schwebel, Alan H S Chan, Guo-Qing Hu

Abstract readReview
In one paragraph

Review in Chinese journal of traumatology = Zhonghua chuang shang za zhi, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
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

22 citing papers in PubMed.

  1. Article
  2. Article
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  4. Glycemic variability improves risk prediction and reveals a mortality threshold in orthopedic trauma patients with sepsis.Journal of orthopaedics and traumatology : official journal of the Italian Society of Orthopaedics and Traumatology · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. New motivation for injury prevention in the face of dramatic demographic changes in China.Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention · 2025
    Article
  9. Article
  10. Observational
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
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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

5 authors.

Fang-Rong ChangSchool of Traffic &Transportation Engineering, Central South University, Changsha, China; Department of System Engineering and Engineering Management, The City University of Hong Kong, Hong Kong, China.
He-Lai HuangSchool of Traffic &Transportation Engineering, Central South University, Changsha, China.
David C SchwebelDepartment of Psychology, College of Arts and Sciences, University of Alabama at Birmingham, Birmingham, AL, USA.
Alan H S ChanDepartment of System Engineering and Engineering Management, The City University of Hong Kong, Hong Kong, China.
Guo-Qing HuDepartment of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, 410078, China. Electronic address: huguoqing009@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-quality data are the foundation to monitor the progress and evaluate the effects of road traffic injury prevention measures. Unfortunately, official road traffic injury statistics delivered by governments worldwide, are often believed somewhat unreliable and invalid. We summarized the reported problems concerning the road traffic injury statistics through systematically searching and reviewing the literature. The problems include absence of regular data, under-reporting, low specificity, distorted cause spectrum of road traffic injury, inconsistency, inaccessibility, and delay of data release. We also explored the mechanisms behind the problematic data and proposed the solutions to the addressed challenges for road traffic statistics.

Indexed as

Global HealthAccidental InjuriesAccidents, TrafficHumansMechanisms behind the dataReported problemsTraffic injury data

Identifiers

PMID32680705
PMCPMC7451583

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.