Cargando…

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

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 info...

Descripción completa

Detalles Bibliográficos
Autores principales: Hu, Xiuli, Qi, Miao, Yuan, Ping, Qi, Guojia, Li, Xiahong, Zhou, Yanna, Shi, Xiuquan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Tehran University of Medical Sciences 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10362209/
https://www.ncbi.nlm.nih.gov/pubmed/37484713
http://dx.doi.org/10.18502/ijph.v52i5.12717
_version_ 1785076375011459072
author Hu, Xiuli
Qi, Miao
Yuan, Ping
Qi, Guojia
Li, Xiahong
Zhou, Yanna
Shi, Xiuquan
author_facet Hu, Xiuli
Qi, Miao
Yuan, Ping
Qi, Guojia
Li, Xiahong
Zhou, Yanna
Shi, Xiuquan
author_sort Hu, Xiuli
collection PubMed
description 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 P<0.001). Primary school graduates, GDP per capita, the number of practicing physicians, health institutions and urbanization rate had strong correlations (r(min)=−0.622) with the mortality of IP. Ridge regression model showed that there was a quantitative relationship between primary school graduates, GDP per capita, the number of practising physicians, health institutions, urbanization rate and the mortality of IP in China. 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.
format Online
Article
Text
id pubmed-10362209
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Tehran University of Medical Sciences
record_format MEDLINE/PubMed
spelling pubmed-103622092023-07-23 Disease Burden Evaluation of Injury and Poisoning in China from 2009 to 2019 Hu, Xiuli Qi, Miao Yuan, Ping Qi, Guojia Li, Xiahong Zhou, Yanna Shi, Xiuquan Iran J Public Health Original Article 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 P<0.001). Primary school graduates, GDP per capita, the number of practicing physicians, health institutions and urbanization rate had strong correlations (r(min)=−0.622) with the mortality of IP. Ridge regression model showed that there was a quantitative relationship between primary school graduates, GDP per capita, the number of practising physicians, health institutions, urbanization rate and the mortality of IP in China. 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. Tehran University of Medical Sciences 2023-05 /pmc/articles/PMC10362209/ /pubmed/37484713 http://dx.doi.org/10.18502/ijph.v52i5.12717 Text en Copyright © 2023 Hu et al. Published by Tehran University of Medical Sciences https://creativecommons.org/licenses/by-nc/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International license (https://creativecommons.org/licenses/by-nc/4.0/). Non-commercial uses of the work are permitted, provided the original work is properly cited.
spellingShingle Original Article
Hu, Xiuli
Qi, Miao
Yuan, Ping
Qi, Guojia
Li, Xiahong
Zhou, Yanna
Shi, Xiuquan
Disease Burden Evaluation of Injury and Poisoning in China from 2009 to 2019
title Disease Burden Evaluation of Injury and Poisoning in China from 2009 to 2019
title_full Disease Burden Evaluation of Injury and Poisoning in China from 2009 to 2019
title_fullStr Disease Burden Evaluation of Injury and Poisoning in China from 2009 to 2019
title_full_unstemmed Disease Burden Evaluation of Injury and Poisoning in China from 2009 to 2019
title_short Disease Burden Evaluation of Injury and Poisoning in China from 2009 to 2019
title_sort disease burden evaluation of injury and poisoning in china from 2009 to 2019
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10362209/
https://www.ncbi.nlm.nih.gov/pubmed/37484713
http://dx.doi.org/10.18502/ijph.v52i5.12717
work_keys_str_mv AT huxiuli diseaseburdenevaluationofinjuryandpoisoninginchinafrom2009to2019
AT qimiao diseaseburdenevaluationofinjuryandpoisoninginchinafrom2009to2019
AT yuanping diseaseburdenevaluationofinjuryandpoisoninginchinafrom2009to2019
AT qiguojia diseaseburdenevaluationofinjuryandpoisoninginchinafrom2009to2019
AT lixiahong diseaseburdenevaluationofinjuryandpoisoninginchinafrom2009to2019
AT zhouyanna diseaseburdenevaluationofinjuryandpoisoninginchinafrom2009to2019
AT shixiuquan diseaseburdenevaluationofinjuryandpoisoninginchinafrom2009to2019