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Gender inequalities in prevalence, pattern and predictors of multimorbidity among geriatric population in rural West Bengal

CONTEXT: Multimorbidity is considered as a priority for global health research. It is defined as the coexistence of two or more chronic health conditions in an individual. It is increasingly being recognized as a major concern for primary care physicians due to its huge impact on individual, family,...

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Autores principales: Sembiah, Sembagamuthu, Dasgupta, Aparajita, Taklikar, Chandrashekhar S., Paul, Bobby, Bandyopadhyay, Lina, Burman, Jayeeta, Pawar, Neeraj, Subbakrishna, N
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9638597/
https://www.ncbi.nlm.nih.gov/pubmed/36352948
http://dx.doi.org/10.4103/jfmpc.jfmpc_565_21
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author Sembiah, Sembagamuthu
Dasgupta, Aparajita
Taklikar, Chandrashekhar S.
Paul, Bobby
Bandyopadhyay, Lina
Burman, Jayeeta
Pawar, Neeraj
Subbakrishna, N
author_facet Sembiah, Sembagamuthu
Dasgupta, Aparajita
Taklikar, Chandrashekhar S.
Paul, Bobby
Bandyopadhyay, Lina
Burman, Jayeeta
Pawar, Neeraj
Subbakrishna, N
author_sort Sembiah, Sembagamuthu
collection PubMed
description CONTEXT: Multimorbidity is considered as a priority for global health research. It is defined as the coexistence of two or more chronic health conditions in an individual. It is increasingly being recognized as a major concern for primary care physicians due to its huge impact on individual, family, and societal level. AIM: The aim of this study was to find the quantum of gender-related inequalities and determinants of multimorbidity among the elderly people in a rural part of West Bengal. MATERIALS AND METHODS: This is a cross-sectional study carried out among 246 elderly people (60 years and above) in a community setting from Oct 2017 to Sep 2018. Logistic regression analysis was done to find out the predictors of multimorbidity. Data were analyzed using the SPSS software (version 16.0. Chicago, SPSS Inc.). RESULTS: Approximately 82% of the study subjects were suffering from multi-morbidity with a significant difference between males (80.9%) and females (88.5%). In binary logistics, people of both the genders aged >70 years, who had less than primary level education, had more than three children, whose source of income was from their children (sons/daughters), were dependent on others for daily routine were at high risk of being multimorbid; whereas depression was a significant predictor of multimorbidity in females and not in males. In multivariable analysis, age remained the only significant predictor for both the gender and for females; depression remained significant after adjusting with significant variables in binary logistics. CONCLUSION: Morbidity screening at each visit, individual as well as family counseling and lifestyle modifications help to cope with the rising burden of multimorbidity at the primary care level. More insight into the epidemiology of multi-morbidity is necessary to take steps to prevent it, lower its burden and align health-care services as per needs.
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spelling pubmed-96385972022-11-08 Gender inequalities in prevalence, pattern and predictors of multimorbidity among geriatric population in rural West Bengal Sembiah, Sembagamuthu Dasgupta, Aparajita Taklikar, Chandrashekhar S. Paul, Bobby Bandyopadhyay, Lina Burman, Jayeeta Pawar, Neeraj Subbakrishna, N J Family Med Prim Care Original Article CONTEXT: Multimorbidity is considered as a priority for global health research. It is defined as the coexistence of two or more chronic health conditions in an individual. It is increasingly being recognized as a major concern for primary care physicians due to its huge impact on individual, family, and societal level. AIM: The aim of this study was to find the quantum of gender-related inequalities and determinants of multimorbidity among the elderly people in a rural part of West Bengal. MATERIALS AND METHODS: This is a cross-sectional study carried out among 246 elderly people (60 years and above) in a community setting from Oct 2017 to Sep 2018. Logistic regression analysis was done to find out the predictors of multimorbidity. Data were analyzed using the SPSS software (version 16.0. Chicago, SPSS Inc.). RESULTS: Approximately 82% of the study subjects were suffering from multi-morbidity with a significant difference between males (80.9%) and females (88.5%). In binary logistics, people of both the genders aged >70 years, who had less than primary level education, had more than three children, whose source of income was from their children (sons/daughters), were dependent on others for daily routine were at high risk of being multimorbid; whereas depression was a significant predictor of multimorbidity in females and not in males. In multivariable analysis, age remained the only significant predictor for both the gender and for females; depression remained significant after adjusting with significant variables in binary logistics. CONCLUSION: Morbidity screening at each visit, individual as well as family counseling and lifestyle modifications help to cope with the rising burden of multimorbidity at the primary care level. More insight into the epidemiology of multi-morbidity is necessary to take steps to prevent it, lower its burden and align health-care services as per needs. Wolters Kluwer - Medknow 2022-08 2022-08-30 /pmc/articles/PMC9638597/ /pubmed/36352948 http://dx.doi.org/10.4103/jfmpc.jfmpc_565_21 Text en Copyright: © 2022 Journal of Family Medicine and Primary Care https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Original Article
Sembiah, Sembagamuthu
Dasgupta, Aparajita
Taklikar, Chandrashekhar S.
Paul, Bobby
Bandyopadhyay, Lina
Burman, Jayeeta
Pawar, Neeraj
Subbakrishna, N
Gender inequalities in prevalence, pattern and predictors of multimorbidity among geriatric population in rural West Bengal
title Gender inequalities in prevalence, pattern and predictors of multimorbidity among geriatric population in rural West Bengal
title_full Gender inequalities in prevalence, pattern and predictors of multimorbidity among geriatric population in rural West Bengal
title_fullStr Gender inequalities in prevalence, pattern and predictors of multimorbidity among geriatric population in rural West Bengal
title_full_unstemmed Gender inequalities in prevalence, pattern and predictors of multimorbidity among geriatric population in rural West Bengal
title_short Gender inequalities in prevalence, pattern and predictors of multimorbidity among geriatric population in rural West Bengal
title_sort gender inequalities in prevalence, pattern and predictors of multimorbidity among geriatric population in rural west bengal
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9638597/
https://www.ncbi.nlm.nih.gov/pubmed/36352948
http://dx.doi.org/10.4103/jfmpc.jfmpc_565_21
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