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Prevalence and Patterns of Multimorbidity Among Rural Elderly: Findings of the AHSETS Study

Introduction: In India, the proportion of older population is projected to increase from 8% in 2015 to 19% in 2050 and a third of the country's population will be older adults by end of the century. Multimorbidity is common among the elderly and the prevalence increases with age. Chronic condit...

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Autores principales: Kshatri, Jaya Singh, Palo, Subrata Kumar, Bhoi, Trilochan, Barik, Shakti Ranjan, Pati, Sanghamitra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7676903/
https://www.ncbi.nlm.nih.gov/pubmed/33251177
http://dx.doi.org/10.3389/fpubh.2020.582663
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author Kshatri, Jaya Singh
Palo, Subrata Kumar
Bhoi, Trilochan
Barik, Shakti Ranjan
Pati, Sanghamitra
author_facet Kshatri, Jaya Singh
Palo, Subrata Kumar
Bhoi, Trilochan
Barik, Shakti Ranjan
Pati, Sanghamitra
author_sort Kshatri, Jaya Singh
collection PubMed
description Introduction: In India, the proportion of older population is projected to increase from 8% in 2015 to 19% in 2050 and a third of the country's population will be older adults by end of the century. Multimorbidity is common among the elderly and the prevalence increases with age. Chronic conditions are most often present as clusters and it's critical to explore the prevalent pattern of clustering for better public health strategies. Method: A cross-sectional study was conducted among 725 rural older adults (>60 years) in Tigiria block of Odisha, India. Multimorbidity status was assessed using the prior validated MAQ-PC tool. Survey was conducted using android tablets installed with open data kit software. While Euclidean distances using K-means clustering algorithm were used to estimate the similarity or dissimilarity of observations. The optimum numbers of clusters were determined using silhouette method. Data were analyzed using multiple open source packages of R statistical programming software ver-3.6.3. Result: The overall prevalence of multimorbidity was 48.8% of which dyads (25%) were the most common form, followed by triads (15.2%). The prevalence of multimorbidity was higher in females (50.4%) than males (47.4%). The optimal number of clusters was found to be 3. While arthritis alone was a separate cluster, hypertension and acid peptic disease were in another cluster and all the rest conditions were included in the third cluster. Conclusion: The cluster analysis to measure of proximity suggested arthritis, hypertension, and acid peptic disease are the diseases that occur mostly in isolation with the other chronic conditions in the rural elderly.
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spelling pubmed-76769032020-11-27 Prevalence and Patterns of Multimorbidity Among Rural Elderly: Findings of the AHSETS Study Kshatri, Jaya Singh Palo, Subrata Kumar Bhoi, Trilochan Barik, Shakti Ranjan Pati, Sanghamitra Front Public Health Public Health Introduction: In India, the proportion of older population is projected to increase from 8% in 2015 to 19% in 2050 and a third of the country's population will be older adults by end of the century. Multimorbidity is common among the elderly and the prevalence increases with age. Chronic conditions are most often present as clusters and it's critical to explore the prevalent pattern of clustering for better public health strategies. Method: A cross-sectional study was conducted among 725 rural older adults (>60 years) in Tigiria block of Odisha, India. Multimorbidity status was assessed using the prior validated MAQ-PC tool. Survey was conducted using android tablets installed with open data kit software. While Euclidean distances using K-means clustering algorithm were used to estimate the similarity or dissimilarity of observations. The optimum numbers of clusters were determined using silhouette method. Data were analyzed using multiple open source packages of R statistical programming software ver-3.6.3. Result: The overall prevalence of multimorbidity was 48.8% of which dyads (25%) were the most common form, followed by triads (15.2%). The prevalence of multimorbidity was higher in females (50.4%) than males (47.4%). The optimal number of clusters was found to be 3. While arthritis alone was a separate cluster, hypertension and acid peptic disease were in another cluster and all the rest conditions were included in the third cluster. Conclusion: The cluster analysis to measure of proximity suggested arthritis, hypertension, and acid peptic disease are the diseases that occur mostly in isolation with the other chronic conditions in the rural elderly. Frontiers Media S.A. 2020-11-05 /pmc/articles/PMC7676903/ /pubmed/33251177 http://dx.doi.org/10.3389/fpubh.2020.582663 Text en Copyright © 2020 Kshatri, Palo, Bhoi, Barik and Pati. http://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
Kshatri, Jaya Singh
Palo, Subrata Kumar
Bhoi, Trilochan
Barik, Shakti Ranjan
Pati, Sanghamitra
Prevalence and Patterns of Multimorbidity Among Rural Elderly: Findings of the AHSETS Study
title Prevalence and Patterns of Multimorbidity Among Rural Elderly: Findings of the AHSETS Study
title_full Prevalence and Patterns of Multimorbidity Among Rural Elderly: Findings of the AHSETS Study
title_fullStr Prevalence and Patterns of Multimorbidity Among Rural Elderly: Findings of the AHSETS Study
title_full_unstemmed Prevalence and Patterns of Multimorbidity Among Rural Elderly: Findings of the AHSETS Study
title_short Prevalence and Patterns of Multimorbidity Among Rural Elderly: Findings of the AHSETS Study
title_sort prevalence and patterns of multimorbidity among rural elderly: findings of the ahsets study
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7676903/
https://www.ncbi.nlm.nih.gov/pubmed/33251177
http://dx.doi.org/10.3389/fpubh.2020.582663
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