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Prevalence, factors and inequalities in chronic disease multimorbidity among older adults in India: analysis of cross-sectional data from the nationally representative Longitudinal Aging Study in India (LASI)

OBJECTIVE: This study examines the prevalence, patterns and factors of chronic disease-related multimorbidity. Also, this study examines the inequality in the prevalence of multimorbidity among older adults in India. DESIGN: Cross-sectional study; large nationally representative survey data. SETTING...

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Autores principales: Chauhan, Shekhar, Patel, Ratna, Kumar, Shubham
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8961109/
https://www.ncbi.nlm.nih.gov/pubmed/35351706
http://dx.doi.org/10.1136/bmjopen-2021-053953
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author Chauhan, Shekhar
Patel, Ratna
Kumar, Shubham
author_facet Chauhan, Shekhar
Patel, Ratna
Kumar, Shubham
author_sort Chauhan, Shekhar
collection PubMed
description OBJECTIVE: This study examines the prevalence, patterns and factors of chronic disease-related multimorbidity. Also, this study examines the inequality in the prevalence of multimorbidity among older adults in India. DESIGN: Cross-sectional study; large nationally representative survey data. SETTING AND PARTICIPANTS: We have used the first wave of a Longitudinal Ageing Study in India conducted in 2017–2018 across all the 35 states (excluded Sikkim) and union territories in India. This study used information from 31 373 older people aged 60+years in India. PRIMARY AND SECONDARY OUTCOME MEASURES: The outcome variable for this study is multimorbidity. The study used multinomial logistic regression to examine the risk factors for multimorbidity among older adults. To measure the inequality in multimorbidity, the slope of index inequality and relative index of inequality have been used to understand the ranked-based inequality. RESULTS: Almost one-fourth (24.1%) reported multimorbidity. The relative risk ratio (RRR) of multimorbidity (RRR=2.12; 95% CI=1.49 to 3.04) was higher among higher educated older adults than uneducated older adults. Furthermore, the RRR of multimorbidity (RRR=2.35; 95% CI=2.02 to 2.74) was higher among urban older adults than their rural counterparts. Older adults in the richest wealth quintile were more likely to report multimorbidities (RRR=2.86; 95% CI=2.29 to 3.55) than the poorest older adults. Good self-rated health and no activities of daily living disability were associated with a lower risk of multimorbidities. CONCLUSIONS: This study contributes to the comprehensive knowledge of the prevalence, factors and inequality of the chronic disease-related multimorbidity among older adults in India. Considering India’s ageing population and high prevalence of multimorbidity, the older adults must be preferred in disease prevention and health programmes, however, without compromising other subpopulations in the country. There is a need to develop geriatric healthcare services in India. Additionally, there is a need to disseminate awareness and management of multimorbidity among urban and highly educated older adults.
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spelling pubmed-89611092022-04-11 Prevalence, factors and inequalities in chronic disease multimorbidity among older adults in India: analysis of cross-sectional data from the nationally representative Longitudinal Aging Study in India (LASI) Chauhan, Shekhar Patel, Ratna Kumar, Shubham BMJ Open Public Health OBJECTIVE: This study examines the prevalence, patterns and factors of chronic disease-related multimorbidity. Also, this study examines the inequality in the prevalence of multimorbidity among older adults in India. DESIGN: Cross-sectional study; large nationally representative survey data. SETTING AND PARTICIPANTS: We have used the first wave of a Longitudinal Ageing Study in India conducted in 2017–2018 across all the 35 states (excluded Sikkim) and union territories in India. This study used information from 31 373 older people aged 60+years in India. PRIMARY AND SECONDARY OUTCOME MEASURES: The outcome variable for this study is multimorbidity. The study used multinomial logistic regression to examine the risk factors for multimorbidity among older adults. To measure the inequality in multimorbidity, the slope of index inequality and relative index of inequality have been used to understand the ranked-based inequality. RESULTS: Almost one-fourth (24.1%) reported multimorbidity. The relative risk ratio (RRR) of multimorbidity (RRR=2.12; 95% CI=1.49 to 3.04) was higher among higher educated older adults than uneducated older adults. Furthermore, the RRR of multimorbidity (RRR=2.35; 95% CI=2.02 to 2.74) was higher among urban older adults than their rural counterparts. Older adults in the richest wealth quintile were more likely to report multimorbidities (RRR=2.86; 95% CI=2.29 to 3.55) than the poorest older adults. Good self-rated health and no activities of daily living disability were associated with a lower risk of multimorbidities. CONCLUSIONS: This study contributes to the comprehensive knowledge of the prevalence, factors and inequality of the chronic disease-related multimorbidity among older adults in India. Considering India’s ageing population and high prevalence of multimorbidity, the older adults must be preferred in disease prevention and health programmes, however, without compromising other subpopulations in the country. There is a need to develop geriatric healthcare services in India. Additionally, there is a need to disseminate awareness and management of multimorbidity among urban and highly educated older adults. BMJ Publishing Group 2022-03-28 /pmc/articles/PMC8961109/ /pubmed/35351706 http://dx.doi.org/10.1136/bmjopen-2021-053953 Text en © Author(s) (or their employer(s)) 2022. 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
Chauhan, Shekhar
Patel, Ratna
Kumar, Shubham
Prevalence, factors and inequalities in chronic disease multimorbidity among older adults in India: analysis of cross-sectional data from the nationally representative Longitudinal Aging Study in India (LASI)
title Prevalence, factors and inequalities in chronic disease multimorbidity among older adults in India: analysis of cross-sectional data from the nationally representative Longitudinal Aging Study in India (LASI)
title_full Prevalence, factors and inequalities in chronic disease multimorbidity among older adults in India: analysis of cross-sectional data from the nationally representative Longitudinal Aging Study in India (LASI)
title_fullStr Prevalence, factors and inequalities in chronic disease multimorbidity among older adults in India: analysis of cross-sectional data from the nationally representative Longitudinal Aging Study in India (LASI)
title_full_unstemmed Prevalence, factors and inequalities in chronic disease multimorbidity among older adults in India: analysis of cross-sectional data from the nationally representative Longitudinal Aging Study in India (LASI)
title_short Prevalence, factors and inequalities in chronic disease multimorbidity among older adults in India: analysis of cross-sectional data from the nationally representative Longitudinal Aging Study in India (LASI)
title_sort prevalence, factors and inequalities in chronic disease multimorbidity among older adults in india: analysis of cross-sectional data from the nationally representative longitudinal aging study in india (lasi)
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8961109/
https://www.ncbi.nlm.nih.gov/pubmed/35351706
http://dx.doi.org/10.1136/bmjopen-2021-053953
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