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Urban–Rural Differences in Patterns and Associated Factors of Multimorbidity Among Older Adults in China: A Cross-Sectional Study Based on Apriori Algorithm and Multinomial Logistic Regression

Introduction: Multimorbidity has become one of the key issues in the public health sector. This study aimed to explore the urban–rural differences in patterns and associated factors of multimorbidity in China and to provide scientific reference for the development of health management strategies to...

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Autores principales: Zhang, Chichen, Xiao, Shujuan, Shi, Lei, Xue, Yaqing, Zheng, Xiao, Dong, Fang, Zhang, Jiachi, Xue, Benli, Lin, Huang, Ouyang, Ping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8437131/
https://www.ncbi.nlm.nih.gov/pubmed/34527650
http://dx.doi.org/10.3389/fpubh.2021.707062
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author Zhang, Chichen
Xiao, Shujuan
Shi, Lei
Xue, Yaqing
Zheng, Xiao
Dong, Fang
Zhang, Jiachi
Xue, Benli
Lin, Huang
Ouyang, Ping
author_facet Zhang, Chichen
Xiao, Shujuan
Shi, Lei
Xue, Yaqing
Zheng, Xiao
Dong, Fang
Zhang, Jiachi
Xue, Benli
Lin, Huang
Ouyang, Ping
author_sort Zhang, Chichen
collection PubMed
description Introduction: Multimorbidity has become one of the key issues in the public health sector. This study aimed to explore the urban–rural differences in patterns and associated factors of multimorbidity in China and to provide scientific reference for the development of health management strategies to reduce health inequality between urban and rural areas. Methods: A cross-sectional study, which used a multi-stage random sampling method, was conducted effectively among 3,250 participants in the Shanxi province of China. The chi-square test was used to compare the prevalence of chronic diseases among older adults with different demographic characteristics. The Apriori algorithm and multinomial logistic regression were used to explore the patterns and associated factors of multimorbidity among older adults, respectively. Results: The findings showed that 30.3% of older adults reported multimorbidity, with significantly higher proportions in rural areas. Among urban older adults, 10 binary chronic disease combinations with strong association strength were obtained. In addition, 11 binary chronic disease combinations and three ternary chronic disease combinations with strong association strength were obtained among rural older adults. In rural and urban areas, there is a large gap in patterns and factors associated with multimorbidity. Conclusions: Multimorbidity was prevalent among older adults, which patterns mainly consisted of two or three chronic diseases. The patterns and associated factors of multimorbidity varied from urban to rural regions. Expanding the study of urban–rural differences in multimorbidity will help the country formulate more reasonable public health policies to maximize the benefits of medical services for all.
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spelling pubmed-84371312021-09-14 Urban–Rural Differences in Patterns and Associated Factors of Multimorbidity Among Older Adults in China: A Cross-Sectional Study Based on Apriori Algorithm and Multinomial Logistic Regression Zhang, Chichen Xiao, Shujuan Shi, Lei Xue, Yaqing Zheng, Xiao Dong, Fang Zhang, Jiachi Xue, Benli Lin, Huang Ouyang, Ping Front Public Health Public Health Introduction: Multimorbidity has become one of the key issues in the public health sector. This study aimed to explore the urban–rural differences in patterns and associated factors of multimorbidity in China and to provide scientific reference for the development of health management strategies to reduce health inequality between urban and rural areas. Methods: A cross-sectional study, which used a multi-stage random sampling method, was conducted effectively among 3,250 participants in the Shanxi province of China. The chi-square test was used to compare the prevalence of chronic diseases among older adults with different demographic characteristics. The Apriori algorithm and multinomial logistic regression were used to explore the patterns and associated factors of multimorbidity among older adults, respectively. Results: The findings showed that 30.3% of older adults reported multimorbidity, with significantly higher proportions in rural areas. Among urban older adults, 10 binary chronic disease combinations with strong association strength were obtained. In addition, 11 binary chronic disease combinations and three ternary chronic disease combinations with strong association strength were obtained among rural older adults. In rural and urban areas, there is a large gap in patterns and factors associated with multimorbidity. Conclusions: Multimorbidity was prevalent among older adults, which patterns mainly consisted of two or three chronic diseases. The patterns and associated factors of multimorbidity varied from urban to rural regions. Expanding the study of urban–rural differences in multimorbidity will help the country formulate more reasonable public health policies to maximize the benefits of medical services for all. Frontiers Media S.A. 2021-08-30 /pmc/articles/PMC8437131/ /pubmed/34527650 http://dx.doi.org/10.3389/fpubh.2021.707062 Text en Copyright © 2021 Zhang, Xiao, Shi, Xue, Zheng, Dong, Zhang, Xue, Lin and Ouyang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Zhang, Chichen
Xiao, Shujuan
Shi, Lei
Xue, Yaqing
Zheng, Xiao
Dong, Fang
Zhang, Jiachi
Xue, Benli
Lin, Huang
Ouyang, Ping
Urban–Rural Differences in Patterns and Associated Factors of Multimorbidity Among Older Adults in China: A Cross-Sectional Study Based on Apriori Algorithm and Multinomial Logistic Regression
title Urban–Rural Differences in Patterns and Associated Factors of Multimorbidity Among Older Adults in China: A Cross-Sectional Study Based on Apriori Algorithm and Multinomial Logistic Regression
title_full Urban–Rural Differences in Patterns and Associated Factors of Multimorbidity Among Older Adults in China: A Cross-Sectional Study Based on Apriori Algorithm and Multinomial Logistic Regression
title_fullStr Urban–Rural Differences in Patterns and Associated Factors of Multimorbidity Among Older Adults in China: A Cross-Sectional Study Based on Apriori Algorithm and Multinomial Logistic Regression
title_full_unstemmed Urban–Rural Differences in Patterns and Associated Factors of Multimorbidity Among Older Adults in China: A Cross-Sectional Study Based on Apriori Algorithm and Multinomial Logistic Regression
title_short Urban–Rural Differences in Patterns and Associated Factors of Multimorbidity Among Older Adults in China: A Cross-Sectional Study Based on Apriori Algorithm and Multinomial Logistic Regression
title_sort urban–rural differences in patterns and associated factors of multimorbidity among older adults in china: a cross-sectional study based on apriori algorithm and multinomial logistic regression
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8437131/
https://www.ncbi.nlm.nih.gov/pubmed/34527650
http://dx.doi.org/10.3389/fpubh.2021.707062
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