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Decomposing urban-rural differences in multimorbidity among older adults in India: a study based on LASI data

BACKGROUND: Multimorbidity is defined as the co-occurrence of two or more than two diseases in the same person. With rising longevity, multimorbidity has become a prominent concern among the older population. Evidence from both developed and developing countries shows that older people are at much h...

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Autores principales: Chauhan, Shekhar, Srivastava, Shobhit, Kumar, Pradeep, Patel, Ratna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8922782/
https://www.ncbi.nlm.nih.gov/pubmed/35291975
http://dx.doi.org/10.1186/s12889-022-12878-7
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author Chauhan, Shekhar
Srivastava, Shobhit
Kumar, Pradeep
Patel, Ratna
author_facet Chauhan, Shekhar
Srivastava, Shobhit
Kumar, Pradeep
Patel, Ratna
author_sort Chauhan, Shekhar
collection PubMed
description BACKGROUND: Multimorbidity is defined as the co-occurrence of two or more than two diseases in the same person. With rising longevity, multimorbidity has become a prominent concern among the older population. Evidence from both developed and developing countries shows that older people are at much higher risk of multimorbidity; however, urban-rural differential remained scarce. Therefore, this study examines urban-rural differential in multimorbidity among older adults by decomposing the risk factors of multimorbidity and identifying the covariates that contributed to the change in multimorbidity. METHODS: The study utilized information from 31,464 older adults (rural-20,725 and urban-10,739) aged 60 years and above from the recent release cross-sectional data of the Longitudinal Ageing Study in India (LASI). Descriptive, bivariate, and multivariate decomposition analysis techniques were used. RESULTS: Overall, significant urban-rural differences were found in the prevalence of multimorbidity among older adults (difference: 16.3; p < 0.001). The multivariate decomposition analysis revealed that about 51% of the overall differences (urban-rural) in the prevalence of multimorbidity among older adults was due to compositional characteristics (endowments). In contrast, the remaining 49% was due to the difference in the effect of characteristics (Coefficient). Moreover, obese/overweight and high-risk waist circumference were found to narrow the difference in the prevalence of multimorbidity among older adults between urban and rural areas by 8% and 9.1%, respectively. Work status and education were found to reduce the urban-rural gap in the prevalence of multimorbidity among older adults by 8% and 6%, respectively. CONCLUSIONS: There is a need to substantially increase the public sector investment in healthcare to address the multimorbidity among older adults, more so in urban areas, without compromising the needs of older adults in rural areas.
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spelling pubmed-89227822022-03-22 Decomposing urban-rural differences in multimorbidity among older adults in India: a study based on LASI data Chauhan, Shekhar Srivastava, Shobhit Kumar, Pradeep Patel, Ratna BMC Public Health Research BACKGROUND: Multimorbidity is defined as the co-occurrence of two or more than two diseases in the same person. With rising longevity, multimorbidity has become a prominent concern among the older population. Evidence from both developed and developing countries shows that older people are at much higher risk of multimorbidity; however, urban-rural differential remained scarce. Therefore, this study examines urban-rural differential in multimorbidity among older adults by decomposing the risk factors of multimorbidity and identifying the covariates that contributed to the change in multimorbidity. METHODS: The study utilized information from 31,464 older adults (rural-20,725 and urban-10,739) aged 60 years and above from the recent release cross-sectional data of the Longitudinal Ageing Study in India (LASI). Descriptive, bivariate, and multivariate decomposition analysis techniques were used. RESULTS: Overall, significant urban-rural differences were found in the prevalence of multimorbidity among older adults (difference: 16.3; p < 0.001). The multivariate decomposition analysis revealed that about 51% of the overall differences (urban-rural) in the prevalence of multimorbidity among older adults was due to compositional characteristics (endowments). In contrast, the remaining 49% was due to the difference in the effect of characteristics (Coefficient). Moreover, obese/overweight and high-risk waist circumference were found to narrow the difference in the prevalence of multimorbidity among older adults between urban and rural areas by 8% and 9.1%, respectively. Work status and education were found to reduce the urban-rural gap in the prevalence of multimorbidity among older adults by 8% and 6%, respectively. CONCLUSIONS: There is a need to substantially increase the public sector investment in healthcare to address the multimorbidity among older adults, more so in urban areas, without compromising the needs of older adults in rural areas. BioMed Central 2022-03-15 /pmc/articles/PMC8922782/ /pubmed/35291975 http://dx.doi.org/10.1186/s12889-022-12878-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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
Chauhan, Shekhar
Srivastava, Shobhit
Kumar, Pradeep
Patel, Ratna
Decomposing urban-rural differences in multimorbidity among older adults in India: a study based on LASI data
title Decomposing urban-rural differences in multimorbidity among older adults in India: a study based on LASI data
title_full Decomposing urban-rural differences in multimorbidity among older adults in India: a study based on LASI data
title_fullStr Decomposing urban-rural differences in multimorbidity among older adults in India: a study based on LASI data
title_full_unstemmed Decomposing urban-rural differences in multimorbidity among older adults in India: a study based on LASI data
title_short Decomposing urban-rural differences in multimorbidity among older adults in India: a study based on LASI data
title_sort decomposing urban-rural differences in multimorbidity among older adults in india: a study based on lasi data
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8922782/
https://www.ncbi.nlm.nih.gov/pubmed/35291975
http://dx.doi.org/10.1186/s12889-022-12878-7
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