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Inequities in curative health-care utilization among the adult population (20–59 years) in India: A comparative analysis of NSS 71(st) (2014) and 75(th) (2017–18) rounds
OBJECTIVE: The study attempts (a) to compute the degree of socio-economic inequity in health care utilization and (b) to decompose and analyze the drivers of socio-economic inequity in health care utilization among adults (20–59 years) in India during the periods 2014 and 2017–18. DATA SOURCE: The a...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7688179/ https://www.ncbi.nlm.nih.gov/pubmed/33237937 http://dx.doi.org/10.1371/journal.pone.0241994 |
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author | Banerjee, Shreya Roy Chowdhury, Indrani |
author_facet | Banerjee, Shreya Roy Chowdhury, Indrani |
author_sort | Banerjee, Shreya |
collection | PubMed |
description | OBJECTIVE: The study attempts (a) to compute the degree of socio-economic inequity in health care utilization and (b) to decompose and analyze the drivers of socio-economic inequity in health care utilization among adults (20–59 years) in India during the periods 2014 and 2017–18. DATA SOURCE: The analysis has been done by using the unit level data of Social Consumption: Health (Schedule number 25.0), of National sample Survey (NSS), corresponding to the 71st and 75(th) rounds. METHODS: Odds ratios were computed through logistic regression analysis to examine the effect of the socio-economic status on the health seeking behaviour of the ailing adult population in India. Concentration Indices (CIs) were calculated to quantify the magnitude of socio-economic inequity in health care utilization. Further, the CIs were decomposed to find out the share of the major contributory factors in the overall inequity. RESULTS: The regression results revealed that socio-economic status continues to show a strong association with treatment seeking behavior among the adults in India. The positive estimates of CIs across both the rounds of NSS suggested that health care utilization among the adults continues to be concentrated within the higher socio-economic status, although the magnitude of inequity in health care utilization has shrunk from 0.0336 in 2014 to 0.0230 in 2017–18. However, the relative contribution of poor economic status to the overall explained inequities in health care utilisation observed a rise in its share from 31% in 2014 to 45% in 2017–18. CONCLUSION: To reduce inequities in health care utilization, policies should address issues related to both supply and demand sides. Revamping the public health infrastructure is the foremost necessary condition from the supply side to ensure equitable health care access to the poor. Therefore, it is warranted that India ramps up investments and raises the budgetary allocation in the health care infrastructure and human resources, much beyond the current spending of 1.28% of its GDP as public expenditure on health. Further, to reduce the existing socio-economic inequities from the demand side, there is an urgent need to strengthen the redistributive mechanisms by tightening the various social security networks through efficient targeting and broadening the outreach capacity to the vulnerable and marginalized sections of the population. |
format | Online Article Text |
id | pubmed-7688179 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-76881792020-12-05 Inequities in curative health-care utilization among the adult population (20–59 years) in India: A comparative analysis of NSS 71(st) (2014) and 75(th) (2017–18) rounds Banerjee, Shreya Roy Chowdhury, Indrani PLoS One Research Article OBJECTIVE: The study attempts (a) to compute the degree of socio-economic inequity in health care utilization and (b) to decompose and analyze the drivers of socio-economic inequity in health care utilization among adults (20–59 years) in India during the periods 2014 and 2017–18. DATA SOURCE: The analysis has been done by using the unit level data of Social Consumption: Health (Schedule number 25.0), of National sample Survey (NSS), corresponding to the 71st and 75(th) rounds. METHODS: Odds ratios were computed through logistic regression analysis to examine the effect of the socio-economic status on the health seeking behaviour of the ailing adult population in India. Concentration Indices (CIs) were calculated to quantify the magnitude of socio-economic inequity in health care utilization. Further, the CIs were decomposed to find out the share of the major contributory factors in the overall inequity. RESULTS: The regression results revealed that socio-economic status continues to show a strong association with treatment seeking behavior among the adults in India. The positive estimates of CIs across both the rounds of NSS suggested that health care utilization among the adults continues to be concentrated within the higher socio-economic status, although the magnitude of inequity in health care utilization has shrunk from 0.0336 in 2014 to 0.0230 in 2017–18. However, the relative contribution of poor economic status to the overall explained inequities in health care utilisation observed a rise in its share from 31% in 2014 to 45% in 2017–18. CONCLUSION: To reduce inequities in health care utilization, policies should address issues related to both supply and demand sides. Revamping the public health infrastructure is the foremost necessary condition from the supply side to ensure equitable health care access to the poor. Therefore, it is warranted that India ramps up investments and raises the budgetary allocation in the health care infrastructure and human resources, much beyond the current spending of 1.28% of its GDP as public expenditure on health. Further, to reduce the existing socio-economic inequities from the demand side, there is an urgent need to strengthen the redistributive mechanisms by tightening the various social security networks through efficient targeting and broadening the outreach capacity to the vulnerable and marginalized sections of the population. Public Library of Science 2020-11-25 /pmc/articles/PMC7688179/ /pubmed/33237937 http://dx.doi.org/10.1371/journal.pone.0241994 Text en © 2020 Banerjee, Roy Chowdhury http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Banerjee, Shreya Roy Chowdhury, Indrani Inequities in curative health-care utilization among the adult population (20–59 years) in India: A comparative analysis of NSS 71(st) (2014) and 75(th) (2017–18) rounds |
title | Inequities in curative health-care utilization among the adult population (20–59 years) in India: A comparative analysis of NSS 71(st) (2014) and 75(th) (2017–18) rounds |
title_full | Inequities in curative health-care utilization among the adult population (20–59 years) in India: A comparative analysis of NSS 71(st) (2014) and 75(th) (2017–18) rounds |
title_fullStr | Inequities in curative health-care utilization among the adult population (20–59 years) in India: A comparative analysis of NSS 71(st) (2014) and 75(th) (2017–18) rounds |
title_full_unstemmed | Inequities in curative health-care utilization among the adult population (20–59 years) in India: A comparative analysis of NSS 71(st) (2014) and 75(th) (2017–18) rounds |
title_short | Inequities in curative health-care utilization among the adult population (20–59 years) in India: A comparative analysis of NSS 71(st) (2014) and 75(th) (2017–18) rounds |
title_sort | inequities in curative health-care utilization among the adult population (20–59 years) in india: a comparative analysis of nss 71(st) (2014) and 75(th) (2017–18) rounds |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7688179/ https://www.ncbi.nlm.nih.gov/pubmed/33237937 http://dx.doi.org/10.1371/journal.pone.0241994 |
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