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Big data on the prevalence of injury deaths among 187 488 elderly Chinese in the past 20 years (2000–2020): a systematic review and meta-analysis
BACKGROUND: This study systematically reviewed injury death and causes in the elderly population in China from 2000 to 2020, to prevent or reduce the occurrence of injuries and death. METHODS: The CNKI, VIP, Wan Fang, MEDLINE, Embase, SinoMed, and Web of Science databases were searched to collect ep...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10233884/ https://www.ncbi.nlm.nih.gov/pubmed/37259039 http://dx.doi.org/10.1186/s12877-023-04056-0 |
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author | Yang, Shan-lan Zhang, Lang-lang Zhu, Xiang Tu, Jia-xin Huang, He-lang Yu, Chao Wu, Lei |
author_facet | Yang, Shan-lan Zhang, Lang-lang Zhu, Xiang Tu, Jia-xin Huang, He-lang Yu, Chao Wu, Lei |
author_sort | Yang, Shan-lan |
collection | PubMed |
description | BACKGROUND: This study systematically reviewed injury death and causes in the elderly population in China from 2000 to 2020, to prevent or reduce the occurrence of injuries and death. METHODS: The CNKI, VIP, Wan Fang, MEDLINE, Embase, SinoMed, and Web of Science databases were searched to collect epidemiological characteristics of injury death among elderly over 60 years old in China from January 2000 to December 2020. Random effects meta-analysis was performed to pool injury mortality rate and identify publication bias, with study quality assessed using the AHRQ risk of bias tool. RESULTS: (1) A total of 41 studies with 187 488 subjects were included, covering 125 million elderly. The pooled injury mortality rate was 135.58/10(5) [95%CI: (113.36 to 162.14)/10(5)], ranking second in the total death cause of the elderly. (2)Subgroup analysis showed that male injury death (146.00/10(5)) was significantly higher than that of females (127.90/10(5)), and overall injury mortality increased exponentially with age (R(2) = 0.957), especially in those over 80 years old; the spatial distribution shows that the injury death rate in the central region is higher than that in the east and west and that in the countryside is higher than that in the city; the distribution of death time shows that after entering an aging society (2000–2020) is significantly higher than before (1990–2000). (3) There are more than 12 types of injury death, and the top three are falling, traffic accidents, and suicide. CONCLUSIONS: China's elderly injury death rate is at a high level in the world, with more males than females, especially after the age of 80. There are regional differences. The main types of injury death are falling, traffic, and suicide. During the 14th Five-Year Plan period, for accidental injuries and death, a rectification list for aging and barrier-free environments was issued. PROSPERO REGISTRATION: The systematic review was registered in PROSPERO under protocol number CRD42022359992. |
format | Online Article Text |
id | pubmed-10233884 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-102338842023-06-02 Big data on the prevalence of injury deaths among 187 488 elderly Chinese in the past 20 years (2000–2020): a systematic review and meta-analysis Yang, Shan-lan Zhang, Lang-lang Zhu, Xiang Tu, Jia-xin Huang, He-lang Yu, Chao Wu, Lei BMC Geriatr Research BACKGROUND: This study systematically reviewed injury death and causes in the elderly population in China from 2000 to 2020, to prevent or reduce the occurrence of injuries and death. METHODS: The CNKI, VIP, Wan Fang, MEDLINE, Embase, SinoMed, and Web of Science databases were searched to collect epidemiological characteristics of injury death among elderly over 60 years old in China from January 2000 to December 2020. Random effects meta-analysis was performed to pool injury mortality rate and identify publication bias, with study quality assessed using the AHRQ risk of bias tool. RESULTS: (1) A total of 41 studies with 187 488 subjects were included, covering 125 million elderly. The pooled injury mortality rate was 135.58/10(5) [95%CI: (113.36 to 162.14)/10(5)], ranking second in the total death cause of the elderly. (2)Subgroup analysis showed that male injury death (146.00/10(5)) was significantly higher than that of females (127.90/10(5)), and overall injury mortality increased exponentially with age (R(2) = 0.957), especially in those over 80 years old; the spatial distribution shows that the injury death rate in the central region is higher than that in the east and west and that in the countryside is higher than that in the city; the distribution of death time shows that after entering an aging society (2000–2020) is significantly higher than before (1990–2000). (3) There are more than 12 types of injury death, and the top three are falling, traffic accidents, and suicide. CONCLUSIONS: China's elderly injury death rate is at a high level in the world, with more males than females, especially after the age of 80. There are regional differences. The main types of injury death are falling, traffic, and suicide. During the 14th Five-Year Plan period, for accidental injuries and death, a rectification list for aging and barrier-free environments was issued. PROSPERO REGISTRATION: The systematic review was registered in PROSPERO under protocol number CRD42022359992. BioMed Central 2023-05-31 /pmc/articles/PMC10233884/ /pubmed/37259039 http://dx.doi.org/10.1186/s12877-023-04056-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Yang, Shan-lan Zhang, Lang-lang Zhu, Xiang Tu, Jia-xin Huang, He-lang Yu, Chao Wu, Lei Big data on the prevalence of injury deaths among 187 488 elderly Chinese in the past 20 years (2000–2020): a systematic review and meta-analysis |
title | Big data on the prevalence of injury deaths among 187 488 elderly Chinese in the past 20 years (2000–2020): a systematic review and meta-analysis |
title_full | Big data on the prevalence of injury deaths among 187 488 elderly Chinese in the past 20 years (2000–2020): a systematic review and meta-analysis |
title_fullStr | Big data on the prevalence of injury deaths among 187 488 elderly Chinese in the past 20 years (2000–2020): a systematic review and meta-analysis |
title_full_unstemmed | Big data on the prevalence of injury deaths among 187 488 elderly Chinese in the past 20 years (2000–2020): a systematic review and meta-analysis |
title_short | Big data on the prevalence of injury deaths among 187 488 elderly Chinese in the past 20 years (2000–2020): a systematic review and meta-analysis |
title_sort | big data on the prevalence of injury deaths among 187 488 elderly chinese in the past 20 years (2000–2020): a systematic review and meta-analysis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10233884/ https://www.ncbi.nlm.nih.gov/pubmed/37259039 http://dx.doi.org/10.1186/s12877-023-04056-0 |
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