Evidence map›Paper›PMID 38894823›Full record

ArticleIranian journal of public health2024

Road Traffic Safety in Developing Countries: Taking China as an Example.

Shuwei Zhang

Abstract read
In one paragraph

Article in Iranian journal of public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Shuwei ZhangSchool of Transportation Engineering, East China Jiaotong University, Nanchang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Road traffic accidents are still serious, especially in developing countries. This paper takes China as a typical example of a developing country with rich characteristics related to road traffic safety for analysis. Methods: Temporal, spatial, road traffic accidents and economic information were gathered from the China Statistical Yearbook. Principal components analysis (PCA) was employed to establish a comprehensive indicator to represent road traffic safety based on different types of road traffic accidents information. Pearson correlation analysis and Eta coefficient test were performed to analyze whether time and space characteristics would affect the established indicator. Then the established indicator was introduced as dependent variable while year and regions as independent variables in the mixed linear model (MLM). At last, single-element regression model was built to study the impact of GDP per capita on road traffic safety. Results: In PCA, the variance explained by the established indicator was 93.993%. The results of Pearson correlation analysis and Eta coefficient test suggested that time and region were both related to the established indicator. MLM showed that the year, the regions and the interaction between them influenced road traffic safety in China significantly. The single-variable regression analysis indicated that, with the increase in GDP per capita, road traffic safety initially decreased and then increased. Conclusion: Road traffic safety in China was grim and changed greatly between different regions and years. This might be attributed to the yearly economic development and disparities among regions. .

Indexed as

ChinaDeveloping countriesRoad traffic safety

Identifiers

PMID38894823
PMCPMC11182461

What OpenQuestion holds

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Registered trials

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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.