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Predictors of health insurance enrolment and wealth-related inequality in Nepal: evidence from Multiple Indicator Cluster Survey (MICS) 2019

OBJECTIVES: We analysed predictors of health insurance enrolment in Nepal, measured wealth-related inequality and decomposed inequality into its contributing factors. DESIGN: Cross-sectional study. SETTING: We used nationally representative data based on Nepal Multiple Indicator Cluster Survey 2019....

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Autores principales: Bhusal, Umesh Prasad, Sapkota, Vishnu Prasad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628343/
https://www.ncbi.nlm.nih.gov/pubmed/34836898
http://dx.doi.org/10.1136/bmjopen-2021-050922
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author Bhusal, Umesh Prasad
Sapkota, Vishnu Prasad
author_facet Bhusal, Umesh Prasad
Sapkota, Vishnu Prasad
author_sort Bhusal, Umesh Prasad
collection PubMed
description OBJECTIVES: We analysed predictors of health insurance enrolment in Nepal, measured wealth-related inequality and decomposed inequality into its contributing factors. DESIGN: Cross-sectional study. SETTING: We used nationally representative data based on Nepal Multiple Indicator Cluster Survey 2019. Out of 10 958 households included in this study, 6.95% households were enroled in at least one health insurance scheme. PRIMARY OUTCOME: measures health insurance (of any type) enrolment. RESULTS: Households were more likely to have health insurance membership when household head have higher secondary education or above compared with households without formal education (adjusted OR 1.87; 95% CI: 1.32 to 2.64)). Households with mass media exposure were nearly three times more likely to get enroled into the schemes compared with their counterparts (adjusted OR 2.96; 95% CI 2.03 to 4.31). Hindus had greater odds of being enroled (adjusted OR 1.82; 95% CI 1.20 to 2.77) compared with non-Hindus. Dalits were less likely to get enroled compared with Brahmin, Chhetri and Madhesi (adjusted OR 0.66; 95% CI 0.47 to 0.94). Households from province 2, Bagmati and Sudurpaschim were less likely to have membership compared with households from province 1. Households from Richer and Richest wealth quintiles were more than two times more likely to have health insurance membership compared with households from the poorest wealth quintile. A positive concentration index 0.25 (95% CI 0.21 to 0.30; p<0.001) indicated disproportionately higher health insurance enrolment among wealthy households. CONCLUSIONS: Education of household head, exposure to mass media, religious and ethnic background, geographical location (province) and wealth status were key predictors of health insurance enrolment in Nepal. There was a significant wealth-related inequality in health insurance affiliation. The study recommends regular monitoring of inequality in health insurance enrolment across demographic and socioeconomic groups to ensure progress towards Universal Health Coverage.
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spelling pubmed-86283432021-12-17 Predictors of health insurance enrolment and wealth-related inequality in Nepal: evidence from Multiple Indicator Cluster Survey (MICS) 2019 Bhusal, Umesh Prasad Sapkota, Vishnu Prasad BMJ Open Health Economics OBJECTIVES: We analysed predictors of health insurance enrolment in Nepal, measured wealth-related inequality and decomposed inequality into its contributing factors. DESIGN: Cross-sectional study. SETTING: We used nationally representative data based on Nepal Multiple Indicator Cluster Survey 2019. Out of 10 958 households included in this study, 6.95% households were enroled in at least one health insurance scheme. PRIMARY OUTCOME: measures health insurance (of any type) enrolment. RESULTS: Households were more likely to have health insurance membership when household head have higher secondary education or above compared with households without formal education (adjusted OR 1.87; 95% CI: 1.32 to 2.64)). Households with mass media exposure were nearly three times more likely to get enroled into the schemes compared with their counterparts (adjusted OR 2.96; 95% CI 2.03 to 4.31). Hindus had greater odds of being enroled (adjusted OR 1.82; 95% CI 1.20 to 2.77) compared with non-Hindus. Dalits were less likely to get enroled compared with Brahmin, Chhetri and Madhesi (adjusted OR 0.66; 95% CI 0.47 to 0.94). Households from province 2, Bagmati and Sudurpaschim were less likely to have membership compared with households from province 1. Households from Richer and Richest wealth quintiles were more than two times more likely to have health insurance membership compared with households from the poorest wealth quintile. A positive concentration index 0.25 (95% CI 0.21 to 0.30; p<0.001) indicated disproportionately higher health insurance enrolment among wealthy households. CONCLUSIONS: Education of household head, exposure to mass media, religious and ethnic background, geographical location (province) and wealth status were key predictors of health insurance enrolment in Nepal. There was a significant wealth-related inequality in health insurance affiliation. The study recommends regular monitoring of inequality in health insurance enrolment across demographic and socioeconomic groups to ensure progress towards Universal Health Coverage. BMJ Publishing Group 2021-11-26 /pmc/articles/PMC8628343/ /pubmed/34836898 http://dx.doi.org/10.1136/bmjopen-2021-050922 Text en © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Health Economics
Bhusal, Umesh Prasad
Sapkota, Vishnu Prasad
Predictors of health insurance enrolment and wealth-related inequality in Nepal: evidence from Multiple Indicator Cluster Survey (MICS) 2019
title Predictors of health insurance enrolment and wealth-related inequality in Nepal: evidence from Multiple Indicator Cluster Survey (MICS) 2019
title_full Predictors of health insurance enrolment and wealth-related inequality in Nepal: evidence from Multiple Indicator Cluster Survey (MICS) 2019
title_fullStr Predictors of health insurance enrolment and wealth-related inequality in Nepal: evidence from Multiple Indicator Cluster Survey (MICS) 2019
title_full_unstemmed Predictors of health insurance enrolment and wealth-related inequality in Nepal: evidence from Multiple Indicator Cluster Survey (MICS) 2019
title_short Predictors of health insurance enrolment and wealth-related inequality in Nepal: evidence from Multiple Indicator Cluster Survey (MICS) 2019
title_sort predictors of health insurance enrolment and wealth-related inequality in nepal: evidence from multiple indicator cluster survey (mics) 2019
topic Health Economics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628343/
https://www.ncbi.nlm.nih.gov/pubmed/34836898
http://dx.doi.org/10.1136/bmjopen-2021-050922
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