Evidence map›Paper›PMID 37885752›Full record

ArticleSSM - population health2023

The temporal trend of road traffic mortality in China from 2004 to 2020.

Kehao Ren, Lipeng Miao, Juncheng Lyu

Abstract read
In one paragraph

Article in SSM - population health, 2023. 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
–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

1 citing paper in PubMed.

  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

3 authors.

Kehao RenWeifang Medical University, School of Public Health, China.
Lipeng MiaoWeifang Medical University, School of Public Health, China.
Juncheng LyuWeifang Medical University, School of Public Health, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Road traffic accidents are one of the critical disasters that cause massive negative influences to the social economy and people's property, health and life safety. The purpose of this study is to analyze the temporal trend of road traffic mortality in China from 2004 to 2020, and further analyze the key factors that the influencing changes in China's road traffic mortality and provides information for the development of targeted interventions to reduce the number of preventable deaths. Methods: The data were retrieved from the Chinese Death Cause Monitoring Data Set from 2004 to 2020. The road traffic mortality rates were standardized by the Sixth National Population Census (6th NPC) data. Joinpoint regression method was manipulated to analyze temporal trends of standardized road traffic mortality. The study used annual percentage change (APC) and average annual percentage change (AAPC) calculated by the Joinpoint regression model to describe trends in road traffic mortality rates. Results: The overall age-adjusted road traffic mortality in China showed a declining trend from 2004 to 2020 (AAPC Conclusions: From 2004 to 2020, the road traffic mortality rates in China generally declined. At the same time, there was a slow reduction or even an upward trend in road traffic mortality rates among the elderly and in western regions. Rural males are a priority group for road traffic injury prevention.

Indexed as

ChinaJoinpoint regressionMortalityRoad traffic injuryTrends

Identifiers

PMID37885752
PMCPMC10597791

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.