Multimorbidity Among Urban Poor in India: Findings From LASI, Wave-1

BackgroundMultimorbidity has become a norm in low-and middle-income countries such as India requiring notable health system improvements to combat. Urban population is a heterogeneous group where poor are at a risk of facing inequity in accessing healthcare services which can jeopardize our efforts...

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Main Authors: Abhinav Sinha, Sushmita Kerketta, Shishirendu Ghosal, Srikanta Kanungo, Sanghamitra Pati
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-06-01
Series:Frontiers in Public Health
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fpubh.2022.881967/full
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author Abhinav Sinha
Sushmita Kerketta
Shishirendu Ghosal
Srikanta Kanungo
Sanghamitra Pati
author_facet Abhinav Sinha
Sushmita Kerketta
Shishirendu Ghosal
Srikanta Kanungo
Sanghamitra Pati
author_sort Abhinav Sinha
collection DOAJ
description BackgroundMultimorbidity has become a norm in low-and middle-income countries such as India requiring notable health system improvements to combat. Urban population is a heterogeneous group where poor are at a risk of facing inequity in accessing healthcare services which can jeopardize our efforts to attain universal health coverage (UHC). We aimed to estimate the prevalence, assess correlates and patterns of multimorbidity among urban poor. Further, we assessed the outcomes of multimorbidity such as healthcare utilization, expenditure and self-rated health.MethodsLongitudinal Aging Study in India (LASI), wave-1 is a nationally representative survey conducted amongst participants aged ≥45 years in 2017–18. We included 9,327 participants residing in urban areas, categorized as poor based on monthly per capita expenditure. Descriptive statistics computed prevalence with 95% uncertainty interval. Multivariable logistic regression was executed to assess the association between multimorbidity and various correlates, expressed as adjusted odds ratio. An ordinal regression model was run between self-rated health and number of chronic conditions.ResultsThe prevalence of multimorbidity was 45.26% among the urban poor. Hypertension and oral morbidities were the most commonly observed dyad. Respondents who were poorer [AOR: 1.27 (1.06–1.51)] had higher chances of having multimorbidity than the poorest. Respondents with a health insurance [AOR: 1.40 (1.14–1.70)] had a higher risk of having multimorbidity. In-patient admission was significantly higher among participants having multimorbidity. Out of pocket expenditure increased while self-rated health deteriorated with each additional morbid condition.ConclusionMultimorbidity is found to be increasingly prevalent among urban poor and individuals having health insurance which demonstrates the need to expand healthcare insurance schemes such as Ayushman Bharat for urban poor to achieve UHC.
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spelling doaj.art-3b8790fee595432ca9185e671550c3762022-12-22T02:26:53ZengFrontiers Media S.A.Frontiers in Public Health2296-25652022-06-011010.3389/fpubh.2022.881967881967Multimorbidity Among Urban Poor in India: Findings From LASI, Wave-1Abhinav SinhaSushmita KerkettaShishirendu GhosalSrikanta KanungoSanghamitra PatiBackgroundMultimorbidity has become a norm in low-and middle-income countries such as India requiring notable health system improvements to combat. Urban population is a heterogeneous group where poor are at a risk of facing inequity in accessing healthcare services which can jeopardize our efforts to attain universal health coverage (UHC). We aimed to estimate the prevalence, assess correlates and patterns of multimorbidity among urban poor. Further, we assessed the outcomes of multimorbidity such as healthcare utilization, expenditure and self-rated health.MethodsLongitudinal Aging Study in India (LASI), wave-1 is a nationally representative survey conducted amongst participants aged ≥45 years in 2017–18. We included 9,327 participants residing in urban areas, categorized as poor based on monthly per capita expenditure. Descriptive statistics computed prevalence with 95% uncertainty interval. Multivariable logistic regression was executed to assess the association between multimorbidity and various correlates, expressed as adjusted odds ratio. An ordinal regression model was run between self-rated health and number of chronic conditions.ResultsThe prevalence of multimorbidity was 45.26% among the urban poor. Hypertension and oral morbidities were the most commonly observed dyad. Respondents who were poorer [AOR: 1.27 (1.06–1.51)] had higher chances of having multimorbidity than the poorest. Respondents with a health insurance [AOR: 1.40 (1.14–1.70)] had a higher risk of having multimorbidity. In-patient admission was significantly higher among participants having multimorbidity. Out of pocket expenditure increased while self-rated health deteriorated with each additional morbid condition.ConclusionMultimorbidity is found to be increasingly prevalent among urban poor and individuals having health insurance which demonstrates the need to expand healthcare insurance schemes such as Ayushman Bharat for urban poor to achieve UHC.https://www.frontiersin.org/articles/10.3389/fpubh.2022.881967/fullmultimorbidityLASIIndiainequityurban poorUHC
spellingShingle Abhinav Sinha
Sushmita Kerketta
Shishirendu Ghosal
Srikanta Kanungo
Sanghamitra Pati
Multimorbidity Among Urban Poor in India: Findings From LASI, Wave-1
Frontiers in Public Health
multimorbidity
LASI
India
inequity
urban poor
UHC
title Multimorbidity Among Urban Poor in India: Findings From LASI, Wave-1
title_full Multimorbidity Among Urban Poor in India: Findings From LASI, Wave-1
title_fullStr Multimorbidity Among Urban Poor in India: Findings From LASI, Wave-1
title_full_unstemmed Multimorbidity Among Urban Poor in India: Findings From LASI, Wave-1
title_short Multimorbidity Among Urban Poor in India: Findings From LASI, Wave-1
title_sort multimorbidity among urban poor in india findings from lasi wave 1
topic multimorbidity
LASI
India
inequity
urban poor
UHC
url https://www.frontiersin.org/articles/10.3389/fpubh.2022.881967/full
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AT sushmitakerketta multimorbidityamongurbanpoorinindiafindingsfromlasiwave1
AT shishirendughosal multimorbidityamongurbanpoorinindiafindingsfromlasiwave1
AT srikantakanungo multimorbidityamongurbanpoorinindiafindingsfromlasiwave1
AT sanghamitrapati multimorbidityamongurbanpoorinindiafindingsfromlasiwave1