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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Tehran University of Medical Sciences
2023
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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 |
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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 |
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