ArticleBMC public health2023
Predictors of national health insurance membership among the poor with different education levels in Indonesia.
Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed, 35 citations in OpenAlex.
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- Financial protection failure among urban poor populations in Karachi, Pakistan: a cross-sectional household survey of catastrophic health expenditure prevalence, determinants and insurance effectiveness.BMJ public health · 2026Article
- Who remains uncovered? Assessing inequalities and determinants of national health insurance enrolment among informal sector workers in Kenya.Global health research and policy · 2025Article
- Payment compliance of informal sector workers in Indonesia National Health Insurance: a study on ability and willingness to pay.Health economics review · 2025Article
- Health insurance coverage, healthcare use, and financial protection amongst people with disabilities in Indonesia: analysis of the 2021 National Socioeconomic Survey.The Lancet regional health. Southeast Asia · 2025Article
- Social determinants of health as risk factors for keratoconus in the All of Us database.The British journal of ophthalmology · 2025Article
- Refugees' Human and Social Capital and Health Insurance Coverage.Journal of immigrant and minority health · 2025Article
- National health insurance membership in Indonesia: Do socio-economic elements matter?PloS one · 2025Article
- Health-Related Quality of Life in Patients End-Stage Kidney Disease with Hypertension: Hemodialysis Vs Continuous Ambulatory Peritoneal Dialysis Using EQ-5D-5L at a Tertiary Center in Indonesia.International journal of nephrology and renovascular disease · 2025Article
- Knowledge, attitudes, and practices regarding keratopathy among diabetic patients.BMC public health · 2024Article
- Role of Socioeconomic Status in National Health Insurance Ownership in Indonesia's Rural Areas.Journal of research in health sciences · 2024Article
- Appraisal of universal health insurance and maternal health services utilization: pre- and post-context of the Jaminan Kesehatan Nasional implementation in Indonesia.Frontiers in public health · 2024Article
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Authors and funding
3 authors at 3 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundIndonesia has made significant progress in expanding universal health coverage (UHC) through its National Health Insurance (NHI) mechanism. However, in the context of NHI implementation in Indonesia, socioeconomic disparities caused its subpopulations to have different literacy of NHI concepts and procedures, increasing the risk of healthcare access inequities. Hence, the study aimed to analyse the predictors of NHI membership among the poor with different education levels in Indonesia.
methodsThis study used the secondary dataset of the nationwide survey "Abilities and Willingness to Pay, Fee, and Participant Satisfaction in implementing National Health Insurance in Indonesia in 2019" by The Ministry of Health of the Republic of Indonesia. The study population was the poor population in Indonesia and included a weighted sample of 18,514 poor people. The study used NHI membership as a dependent variable. Meanwhile, the study analysed seven independent variables: wealth, residence, age, gender, education, employment, and marital status. In the final step of the analysis, the study used binary logistic regression.
resultsThe results show that the NHI membership among the poor population tends to be higher among those who have higher education, live in urban areas, are older than 17 years old, are married and are wealthier. The poor population with higher education levels is more likely to become NHI members than those with lower education. Their residence, age, gender, employment, marital status, and wealth also predicted their NHI membership. Poor people with primary education are 1.454 times more likely to be NHI members than those without education (AOR 1.454; 95% CI 1.331-1.588). Meanwhile, those with secondary education are 1.478 times more likely to be NHI members than those with no education (AOR 1.478; 95% CI 1.309-1.668). Moreover, higher education is 1.724 times more likely to result in being an NHI member than no education (AOR 1.724; 95% CI 1.356-2.192).
conclusionEducation level, residence, age, gender, employment, marital status, and wealth predict NHI membership among the poor population. Since significant differences exist in all of those predictors among the poor population with different education levels, our findings highlighted the importance of government investment in NHI, which must be supported with investment in the poor population's education.
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