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Identification of status quo and association rules for chronic comorbidity among Chinese middle-aged and older adults rural residents

BACKGROUND: Chronic comorbidity has become a major challenge in chronic disease prevention and control. This issue is particularly pronounced in rural areas of developing countries, where the prevalence of chronic disease comorbidity is high, especially among middle-aged and older adults populations...

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Autores principales: Yu, Zijing, Chen, Yuquan, Xia, Qianhang, Qu, Qingru, Dai, Tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10267321/
https://www.ncbi.nlm.nih.gov/pubmed/37325337
http://dx.doi.org/10.3389/fpubh.2023.1186248
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author Yu, Zijing
Chen, Yuquan
Xia, Qianhang
Qu, Qingru
Dai, Tao
author_facet Yu, Zijing
Chen, Yuquan
Xia, Qianhang
Qu, Qingru
Dai, Tao
author_sort Yu, Zijing
collection PubMed
description BACKGROUND: Chronic comorbidity has become a major challenge in chronic disease prevention and control. This issue is particularly pronounced in rural areas of developing countries, where the prevalence of chronic disease comorbidity is high, especially among middle-aged and older adults populations. However, the health status of middle-aged and older adults individuals in rural areas of China has received inadequate attention. Therefore, it is crucial to investigate the correlation among chronic diseases to establish a reference basis for adjusting health policies aimed at promoting the prevention and management of chronic diseases among middle-aged and older adults individuals. METHODS: This study selected 2,262 middle-aged and older adults residents aged 50 years or older in Shangang Village, Jiangsu Province, China, as the study population. To analyze the chronic comorbidity of middle-aged and older adults residents with different characteristics, we used the χ(2) test with SPSS statistical software. Data analysis was conducted using the Apriori algorithm of Python software, set to mine the strong association rules of positive correlation between chronic disease comorbidities of middle-aged and older adults residents. RESULTS: The prevalence of chronic comorbidity was 56.6%. The chronic disease comorbidity group with the highest prevalence rate was the lumbar osteopenia + hypertension group. There were significant differences in the prevalence of chronic disease comorbidity among middle-aged and older adults residents in terms of gender, BMI, and chronic disease management. The Apriori algorithm was used to screen 15 association rules for the whole population, 11 for genders, and 15 for age groups. According to the order of support, the most common association rules of comorbidity of three chronic diseases were: {lumbar osteopenia} → {hypertension} (support: 29.22%, confidence: 58.44%), {dyslipidemia} → {hypertension} (support: 19.14%, confidence: 65.91%) and {fatty liver} → {hypertension} (support: 17.82%, confidence: 64.17%). CONCLUSION: The prevalence of chronic comorbidity among middle-aged and older adults rural residents in China is relatively high. We identified many association rules among chronic diseases, dyslipidemia is mostly the antecedent, and hypertension is primarily the result. In particular, the majority of comorbidity aggregation patterns consisted of hypertension and dyslipidemia. By implementing scientifically-proven prevention and control strategies, the development of healthy aging can be promoted.
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spelling pubmed-102673212023-06-15 Identification of status quo and association rules for chronic comorbidity among Chinese middle-aged and older adults rural residents Yu, Zijing Chen, Yuquan Xia, Qianhang Qu, Qingru Dai, Tao Front Public Health Public Health BACKGROUND: Chronic comorbidity has become a major challenge in chronic disease prevention and control. This issue is particularly pronounced in rural areas of developing countries, where the prevalence of chronic disease comorbidity is high, especially among middle-aged and older adults populations. However, the health status of middle-aged and older adults individuals in rural areas of China has received inadequate attention. Therefore, it is crucial to investigate the correlation among chronic diseases to establish a reference basis for adjusting health policies aimed at promoting the prevention and management of chronic diseases among middle-aged and older adults individuals. METHODS: This study selected 2,262 middle-aged and older adults residents aged 50 years or older in Shangang Village, Jiangsu Province, China, as the study population. To analyze the chronic comorbidity of middle-aged and older adults residents with different characteristics, we used the χ(2) test with SPSS statistical software. Data analysis was conducted using the Apriori algorithm of Python software, set to mine the strong association rules of positive correlation between chronic disease comorbidities of middle-aged and older adults residents. RESULTS: The prevalence of chronic comorbidity was 56.6%. The chronic disease comorbidity group with the highest prevalence rate was the lumbar osteopenia + hypertension group. There were significant differences in the prevalence of chronic disease comorbidity among middle-aged and older adults residents in terms of gender, BMI, and chronic disease management. The Apriori algorithm was used to screen 15 association rules for the whole population, 11 for genders, and 15 for age groups. According to the order of support, the most common association rules of comorbidity of three chronic diseases were: {lumbar osteopenia} → {hypertension} (support: 29.22%, confidence: 58.44%), {dyslipidemia} → {hypertension} (support: 19.14%, confidence: 65.91%) and {fatty liver} → {hypertension} (support: 17.82%, confidence: 64.17%). CONCLUSION: The prevalence of chronic comorbidity among middle-aged and older adults rural residents in China is relatively high. We identified many association rules among chronic diseases, dyslipidemia is mostly the antecedent, and hypertension is primarily the result. In particular, the majority of comorbidity aggregation patterns consisted of hypertension and dyslipidemia. By implementing scientifically-proven prevention and control strategies, the development of healthy aging can be promoted. Frontiers Media S.A. 2023-06-01 /pmc/articles/PMC10267321/ /pubmed/37325337 http://dx.doi.org/10.3389/fpubh.2023.1186248 Text en Copyright © 2023 Yu, Chen, Xia, Qu and Dai. 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
Yu, Zijing
Chen, Yuquan
Xia, Qianhang
Qu, Qingru
Dai, Tao
Identification of status quo and association rules for chronic comorbidity among Chinese middle-aged and older adults rural residents
title Identification of status quo and association rules for chronic comorbidity among Chinese middle-aged and older adults rural residents
title_full Identification of status quo and association rules for chronic comorbidity among Chinese middle-aged and older adults rural residents
title_fullStr Identification of status quo and association rules for chronic comorbidity among Chinese middle-aged and older adults rural residents
title_full_unstemmed Identification of status quo and association rules for chronic comorbidity among Chinese middle-aged and older adults rural residents
title_short Identification of status quo and association rules for chronic comorbidity among Chinese middle-aged and older adults rural residents
title_sort identification of status quo and association rules for chronic comorbidity among chinese middle-aged and older adults rural residents
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10267321/
https://www.ncbi.nlm.nih.gov/pubmed/37325337
http://dx.doi.org/10.3389/fpubh.2023.1186248
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