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Analysis of multimorbidity networks associated with different factors in Northeast China: a cross-sectional analysis
OBJECTIVES: This study aimed to identify and study the associations and co-occurrence of multimorbidity, and assessed the associations of diseases with sex, age and hospitalisation duration. DESIGN: Cross-sectional. SETTING: 15 general hospitals in Jilin Province, China. PARTICIPANTS: A total of 431...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8572406/ https://www.ncbi.nlm.nih.gov/pubmed/34732482 http://dx.doi.org/10.1136/bmjopen-2021-051050 |
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author | Yu, Jianxing Li, Yingying Zheng, Zhou Jia, Huanhuan Cao, Peng Qiangba, Yuzhen Yu, Xihe |
author_facet | Yu, Jianxing Li, Yingying Zheng, Zhou Jia, Huanhuan Cao, Peng Qiangba, Yuzhen Yu, Xihe |
author_sort | Yu, Jianxing |
collection | PubMed |
description | OBJECTIVES: This study aimed to identify and study the associations and co-occurrence of multimorbidity, and assessed the associations of diseases with sex, age and hospitalisation duration. DESIGN: Cross-sectional. SETTING: 15 general hospitals in Jilin Province, China. PARTICIPANTS: A total of 431 295 inpatients were enrolled through a cross-sectional study in Jilin Province, China. PRIMARY OUTCOME MEASURES: The complex relationships of multimorbidity were presented as weighted networks. RESULTS: The distributions of the numbers of diseases differed significantly by sex, age and hospitalisation duration (p<0.001). Cerebrovascular diseases (CD), hypertensive diseases (HyD), ischaemic heart diseases (IHD) and other forms of heart disease (OFHD) showed the highest weights in the multimorbidity networks. The connections between different sexes or hospitalisation duration and diseases were similar, while those between different age groups and diseases were different. CONCLUSIONS: CD, HyD, IHD and OFHD were the central points of disease clusters and directly or indirectly related to other diseases or factors. Thus, effective interventions for these diseases should be adopted. Furthermore, different intervention strategies should be developed according to multimorbidity patterns in different age groups. |
format | Online Article Text |
id | pubmed-8572406 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-85724062021-11-17 Analysis of multimorbidity networks associated with different factors in Northeast China: a cross-sectional analysis Yu, Jianxing Li, Yingying Zheng, Zhou Jia, Huanhuan Cao, Peng Qiangba, Yuzhen Yu, Xihe BMJ Open Public Health OBJECTIVES: This study aimed to identify and study the associations and co-occurrence of multimorbidity, and assessed the associations of diseases with sex, age and hospitalisation duration. DESIGN: Cross-sectional. SETTING: 15 general hospitals in Jilin Province, China. PARTICIPANTS: A total of 431 295 inpatients were enrolled through a cross-sectional study in Jilin Province, China. PRIMARY OUTCOME MEASURES: The complex relationships of multimorbidity were presented as weighted networks. RESULTS: The distributions of the numbers of diseases differed significantly by sex, age and hospitalisation duration (p<0.001). Cerebrovascular diseases (CD), hypertensive diseases (HyD), ischaemic heart diseases (IHD) and other forms of heart disease (OFHD) showed the highest weights in the multimorbidity networks. The connections between different sexes or hospitalisation duration and diseases were similar, while those between different age groups and diseases were different. CONCLUSIONS: CD, HyD, IHD and OFHD were the central points of disease clusters and directly or indirectly related to other diseases or factors. Thus, effective interventions for these diseases should be adopted. Furthermore, different intervention strategies should be developed according to multimorbidity patterns in different age groups. BMJ Publishing Group 2021-11-03 /pmc/articles/PMC8572406/ /pubmed/34732482 http://dx.doi.org/10.1136/bmjopen-2021-051050 Text en © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Public Health Yu, Jianxing Li, Yingying Zheng, Zhou Jia, Huanhuan Cao, Peng Qiangba, Yuzhen Yu, Xihe Analysis of multimorbidity networks associated with different factors in Northeast China: a cross-sectional analysis |
title | Analysis of multimorbidity networks associated with different factors in Northeast China: a cross-sectional analysis |
title_full | Analysis of multimorbidity networks associated with different factors in Northeast China: a cross-sectional analysis |
title_fullStr | Analysis of multimorbidity networks associated with different factors in Northeast China: a cross-sectional analysis |
title_full_unstemmed | Analysis of multimorbidity networks associated with different factors in Northeast China: a cross-sectional analysis |
title_short | Analysis of multimorbidity networks associated with different factors in Northeast China: a cross-sectional analysis |
title_sort | analysis of multimorbidity networks associated with different factors in northeast china: a cross-sectional analysis |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8572406/ https://www.ncbi.nlm.nih.gov/pubmed/34732482 http://dx.doi.org/10.1136/bmjopen-2021-051050 |
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