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Multidimensional health heterogeneity of Chinese older adults and its determinants

BACKGROUND: Nowadays, the “Healthy China” and “Actively Addressing Population Aging” are two important national strategies in China. Promoting high-quality development of demand-driven older adults health services is an important way to achieve these strategies. From the perspective of active ageing...

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Autores principales: Hu, Yi, Wang, Zhenyu, Wu, Liqun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10661850/
https://www.ncbi.nlm.nih.gov/pubmed/38021459
http://dx.doi.org/10.1016/j.ssmph.2023.101547
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author Hu, Yi
Wang, Zhenyu
Wu, Liqun
author_facet Hu, Yi
Wang, Zhenyu
Wu, Liqun
author_sort Hu, Yi
collection PubMed
description BACKGROUND: Nowadays, the “Healthy China” and “Actively Addressing Population Aging” are two important national strategies in China. Promoting high-quality development of demand-driven older adults health services is an important way to achieve these strategies. From the perspective of active ageing, assessing the health status of older adults from multiple dimensions becomes crucial as it helps identify their specific health service needs, intervention measures, and health policies tailored to this population. METHODS: Data were derived from the China Health and Retirement Longitudinal Study (CHARLS) wave 4 (2018). A total of 4190 older adults (aged ≥60 years) were included as the analysis sample. Latent class analysis was performed to categorize older adults based on 6 health indicators, including Activities of Daily Living (ADLs), Instrumental Activities of Daily Living (IADLs), doctor diagnosed chronic diseases, depressive symptoms, cognitive function, and social participation. Multinomial logistic model was used to explore determinants associated with the various patterns of multidimensional health of older adults. RESULTS: The multidimensional health of older people was classified into three latent classes: Relatively Healthy (Class 1, n = 2806, 66.97%), Highly Depressed and Relatively Health Risk (Class 2, n = 1189, 28.38%), and Functional Impairment (Class 3, n = 195, 4.65%). Gender, age, education, marital status, number of children, alcohol consumption, physical activity, savings, residence, air quality satisfaction, and medical service satisfaction had significant effects on the attribution of all multidimensional health latent classes. CONCLUSION: Heterogeneous and multidimensional health classes exist in China's older population, and these classes are influenced by a variety of factors and to varying degrees. Policymakers and healthcare providers can use these evidence to further address the diverse needs of older adults and improve older-care health services, ultimately achieving the goal of Active Ageing and Healthy China.
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spelling pubmed-106618502023-11-04 Multidimensional health heterogeneity of Chinese older adults and its determinants Hu, Yi Wang, Zhenyu Wu, Liqun SSM Popul Health Regular Article BACKGROUND: Nowadays, the “Healthy China” and “Actively Addressing Population Aging” are two important national strategies in China. Promoting high-quality development of demand-driven older adults health services is an important way to achieve these strategies. From the perspective of active ageing, assessing the health status of older adults from multiple dimensions becomes crucial as it helps identify their specific health service needs, intervention measures, and health policies tailored to this population. METHODS: Data were derived from the China Health and Retirement Longitudinal Study (CHARLS) wave 4 (2018). A total of 4190 older adults (aged ≥60 years) were included as the analysis sample. Latent class analysis was performed to categorize older adults based on 6 health indicators, including Activities of Daily Living (ADLs), Instrumental Activities of Daily Living (IADLs), doctor diagnosed chronic diseases, depressive symptoms, cognitive function, and social participation. Multinomial logistic model was used to explore determinants associated with the various patterns of multidimensional health of older adults. RESULTS: The multidimensional health of older people was classified into three latent classes: Relatively Healthy (Class 1, n = 2806, 66.97%), Highly Depressed and Relatively Health Risk (Class 2, n = 1189, 28.38%), and Functional Impairment (Class 3, n = 195, 4.65%). Gender, age, education, marital status, number of children, alcohol consumption, physical activity, savings, residence, air quality satisfaction, and medical service satisfaction had significant effects on the attribution of all multidimensional health latent classes. CONCLUSION: Heterogeneous and multidimensional health classes exist in China's older population, and these classes are influenced by a variety of factors and to varying degrees. Policymakers and healthcare providers can use these evidence to further address the diverse needs of older adults and improve older-care health services, ultimately achieving the goal of Active Ageing and Healthy China. Elsevier 2023-11-04 /pmc/articles/PMC10661850/ /pubmed/38021459 http://dx.doi.org/10.1016/j.ssmph.2023.101547 Text en © 2023 The Authors. Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Regular Article
Hu, Yi
Wang, Zhenyu
Wu, Liqun
Multidimensional health heterogeneity of Chinese older adults and its determinants
title Multidimensional health heterogeneity of Chinese older adults and its determinants
title_full Multidimensional health heterogeneity of Chinese older adults and its determinants
title_fullStr Multidimensional health heterogeneity of Chinese older adults and its determinants
title_full_unstemmed Multidimensional health heterogeneity of Chinese older adults and its determinants
title_short Multidimensional health heterogeneity of Chinese older adults and its determinants
title_sort multidimensional health heterogeneity of chinese older adults and its determinants
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10661850/
https://www.ncbi.nlm.nih.gov/pubmed/38021459
http://dx.doi.org/10.1016/j.ssmph.2023.101547
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