Cargando…

Burden, patterns, and impact of multimorbidity in North India: findings from a rural population-based study

AIM: To estimate the prevalence, socio-demographic determinants, common disease combinations, and health impact of multimorbidity among a young rural population. METHODS: We conducted a cross-sectional survey among participants aged ≥30 years in rural Punjab, North India, from Jan 2019 to April 2019...

Descripción completa

Detalles Bibliográficos
Autores principales: Gupta, Priti, Patel, Shivani A., Sharma, Hanspria, Jarhyan, Prashant, Sharma, Rakshit, Prabhakaran, Dorairaj, Tandon, Nikhil, Mohan, Sailesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9159928/
https://www.ncbi.nlm.nih.gov/pubmed/35655207
http://dx.doi.org/10.1186/s12889-022-13495-0
_version_ 1784719164419604480
author Gupta, Priti
Patel, Shivani A.
Sharma, Hanspria
Jarhyan, Prashant
Sharma, Rakshit
Prabhakaran, Dorairaj
Tandon, Nikhil
Mohan, Sailesh
author_facet Gupta, Priti
Patel, Shivani A.
Sharma, Hanspria
Jarhyan, Prashant
Sharma, Rakshit
Prabhakaran, Dorairaj
Tandon, Nikhil
Mohan, Sailesh
author_sort Gupta, Priti
collection PubMed
description AIM: To estimate the prevalence, socio-demographic determinants, common disease combinations, and health impact of multimorbidity among a young rural population. METHODS: We conducted a cross-sectional survey among participants aged ≥30 years in rural Punjab, North India, from Jan 2019 to April 2019. Multimorbidity was defined as the coexistence of ≥two conditions using a 14-condition tool validated in India. We also calculated a multimorbidity-weighted index (MWI), which provides a weight to each disease based on its impact on physical functioning. Logistic regression was conducted to evaluate the association with sociodemographic variables, mental health (PHQ-9), physical functioning (ADL scale), and self-rated health (SRH). RESULTS: We analyzed data from 3213 adults [Mean age 51.5 (±13), 54% women]. Prevalence of single chronic condition, multimorbidity, and MWI was 28.6, 18% and − 1.9 respectively. Age, higher wealth index and ever use alcohol were significantly associated with multimorbidity. Overall, 2.8% of respondents had limited physical functioning, 2.1% had depression, and 61.5% reported low SRH. Poorer health outcomes were more prevalent among the elderly, women, less educated, and those having lower wealth index and multimorbidity, were found to be significantly associated with poor health outcomes. CONCLUSIONS: The burden of multimorbidity was high in this young rural population, which portends significant adverse effects on their health and quality of life. The Indian health system should be reconfigured to address this emerging health priority holistically, by adopting a more integrated and sustainable model of care. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-022-13495-0.
format Online
Article
Text
id pubmed-9159928
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-91599282022-06-02 Burden, patterns, and impact of multimorbidity in North India: findings from a rural population-based study Gupta, Priti Patel, Shivani A. Sharma, Hanspria Jarhyan, Prashant Sharma, Rakshit Prabhakaran, Dorairaj Tandon, Nikhil Mohan, Sailesh BMC Public Health Research AIM: To estimate the prevalence, socio-demographic determinants, common disease combinations, and health impact of multimorbidity among a young rural population. METHODS: We conducted a cross-sectional survey among participants aged ≥30 years in rural Punjab, North India, from Jan 2019 to April 2019. Multimorbidity was defined as the coexistence of ≥two conditions using a 14-condition tool validated in India. We also calculated a multimorbidity-weighted index (MWI), which provides a weight to each disease based on its impact on physical functioning. Logistic regression was conducted to evaluate the association with sociodemographic variables, mental health (PHQ-9), physical functioning (ADL scale), and self-rated health (SRH). RESULTS: We analyzed data from 3213 adults [Mean age 51.5 (±13), 54% women]. Prevalence of single chronic condition, multimorbidity, and MWI was 28.6, 18% and − 1.9 respectively. Age, higher wealth index and ever use alcohol were significantly associated with multimorbidity. Overall, 2.8% of respondents had limited physical functioning, 2.1% had depression, and 61.5% reported low SRH. Poorer health outcomes were more prevalent among the elderly, women, less educated, and those having lower wealth index and multimorbidity, were found to be significantly associated with poor health outcomes. CONCLUSIONS: The burden of multimorbidity was high in this young rural population, which portends significant adverse effects on their health and quality of life. The Indian health system should be reconfigured to address this emerging health priority holistically, by adopting a more integrated and sustainable model of care. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-022-13495-0. BioMed Central 2022-06-02 /pmc/articles/PMC9159928/ /pubmed/35655207 http://dx.doi.org/10.1186/s12889-022-13495-0 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
Gupta, Priti
Patel, Shivani A.
Sharma, Hanspria
Jarhyan, Prashant
Sharma, Rakshit
Prabhakaran, Dorairaj
Tandon, Nikhil
Mohan, Sailesh
Burden, patterns, and impact of multimorbidity in North India: findings from a rural population-based study
title Burden, patterns, and impact of multimorbidity in North India: findings from a rural population-based study
title_full Burden, patterns, and impact of multimorbidity in North India: findings from a rural population-based study
title_fullStr Burden, patterns, and impact of multimorbidity in North India: findings from a rural population-based study
title_full_unstemmed Burden, patterns, and impact of multimorbidity in North India: findings from a rural population-based study
title_short Burden, patterns, and impact of multimorbidity in North India: findings from a rural population-based study
title_sort burden, patterns, and impact of multimorbidity in north india: findings from a rural population-based study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9159928/
https://www.ncbi.nlm.nih.gov/pubmed/35655207
http://dx.doi.org/10.1186/s12889-022-13495-0
work_keys_str_mv AT guptapriti burdenpatternsandimpactofmultimorbidityinnorthindiafindingsfromaruralpopulationbasedstudy
AT patelshivania burdenpatternsandimpactofmultimorbidityinnorthindiafindingsfromaruralpopulationbasedstudy
AT sharmahanspria burdenpatternsandimpactofmultimorbidityinnorthindiafindingsfromaruralpopulationbasedstudy
AT jarhyanprashant burdenpatternsandimpactofmultimorbidityinnorthindiafindingsfromaruralpopulationbasedstudy
AT sharmarakshit burdenpatternsandimpactofmultimorbidityinnorthindiafindingsfromaruralpopulationbasedstudy
AT prabhakarandorairaj burdenpatternsandimpactofmultimorbidityinnorthindiafindingsfromaruralpopulationbasedstudy
AT tandonnikhil burdenpatternsandimpactofmultimorbidityinnorthindiafindingsfromaruralpopulationbasedstudy
AT mohansailesh burdenpatternsandimpactofmultimorbidityinnorthindiafindingsfromaruralpopulationbasedstudy