Evidence map›Paper›PMID 37484713›Full record

ArticleIranian journal of public health2023

Disease Burden Evaluation of Injury and Poisoning in China from 2009 to 2019.

Xiuli Hu, Miao Qi, Ping Yuan, Guojia Qi, Xiahong Li, Yanna Zhou, Xiuquan Shi

Abstract read
In one paragraph

Article in Iranian journal of public health, 2023. 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
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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

7 authors.

Xiuli HuDepartment of Epidemiology and Health Statistics, School of Public Health, Zunyi Medical University, Zunyi, Guizhou, China.
Miao QiDepartment of Epidemiology and Health Statistics, School of Public Health, Zunyi Medical University, Zunyi, Guizhou, China.
Ping YuanDepartment of Epidemiology and Health Statistics, School of Public Health, Zunyi Medical University, Zunyi, Guizhou, China.
Guojia QiDepartment of Epidemiology and Health Statistics, School of Public Health, Zunyi Medical University, Zunyi, Guizhou, China.
Xiahong LiDepartment of Epidemiology and Health Statistics, School of Public Health, Zunyi Medical University, Zunyi, Guizhou, China.
Yanna ZhouDepartment of Epidemiology and Health Statistics, School of Public Health, Zunyi Medical University, Zunyi, Guizhou, China.
Xiuquan ShiDepartment of Epidemiology and Health Statistics, School of Public Health, Zunyi Medical University, Zunyi, Guizhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: We aimed to analyze the differences and changing trends of mortality of Injury and Poisoning (IP) between urban and rural areas and gender in China to find out the influencing factors and to propose improvement measures. Methods: IP mortality, population, economy, medical and health information data came from the official web-site of the National Bureau of Statistics, and basic data on education level came from the Chinese Ministry of Education. Then the differences of the mortality of IP were compared between different areas and gender in China from 2009 to 2019, and the relationships between the mortality changes of IP and education level, GDP per capita, the numbers of practicing physicians, health institutions and urbanization rate were also explored by establishing a ridge regression model. Results: The mortality of IP in rural areas was significantly higher than that of urban areas, and in male was higher than that of female (both Conclusion: As the difference of working nature, economic development imbalance, psychological and gender, the mortality of IP was significantly different, so the state should take more effective measures to develop the urban and rural areas balanced, and reduce the IP risk in some particular occupations.

Indexed as

Gender differenceInjury and poisoningMortalityUrban and rural areas

Identifiers

PMID37484713
PMCPMC10362209

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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.