Evaluation of health insurance policy impact on maternal and child health outcomes in coastal areas

Saman Saman

doi:10.61099/jakespol.v1i3.404

Authors

Saman Saman Poltekkes Kemenkes Palu, Central Sulawesi, Indonesia https://orcid.org/0000-0001-7054-970X

DOI:

https://doi.org/10.61099/jakespol.v1i3.404

Keywords:

Child Health Services, Coastal Population, Health Insurance, Maternal Health, Universal Health Coverage

Abstract

Introduction: Maternal and child healthcare inequities remain a major challenge in coastal communities despite the implementation of national health insurance programs. This study aimed to evaluate the impact of health insurance policy implementation on maternal and child health outcomes in coastal areas.

Methods: A quantitative cross-sectional analytical study was conducted in several coastal districts in Eastern Indonesia between January and April 2026. A total of 348 mothers with children under five years old were selected using multistage cluster sampling. Data were collected through structured questionnaires and analyzed using descriptive statistics, chi-square tests, and multivariate logistic regression with a significance level of α = 0.05.

Results: Active health insurance participation was significantly associated with improved maternal and child healthcare access. Multivariate analysis showed that distance to healthcare facilities was the strongest predictor of limited healthcare access (AOR = 3.46; 95% CI: 2.01–5.95; p < 0.001). Non-insured respondents were more likely to experience healthcare access barriers (AOR = 2.84; 95% CI: 1.63–4.95; p < 0.001). Transportation limitations (AOR = 2.17; 95% CI: 1.28–3.69; p = 0.004) and low household income (AOR = 1.88; 95% CI: 1.09–3.23; p = 0.021) also significantly influenced healthcare accessibility.

Conclusion: Health insurance policies improved healthcare utilization; however, structural barriers continued to limit equitable maternal and child healthcare access in coastal communities. Strengthening geographically responsive healthcare systems is necessary to optimize universal health coverage implementation.

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References

[1] F. Abate et al., “UNITY: A low-field magnetic resonance neuroimaging initiative to characterize neurodevelopment in low and middle-income settings,” Dev. Cogn. Neurosci., vol. 69, p. 101397, Oct. 2024, doi: https://dx.doi.org/10.1016/j.dcn.2024.101397.

[2] N. Ahmed, E. Chu, F. Mustafa, R. Javanmard, J. Jui, and J. Lee, “Understanding inequalities in spatial accessibility to multi-tier healthcare for older adults in rapidly aging Bangladesh,” J. Transp. Heal., vol. 44, p. 102121, 2025, doi: https://doi.org/10.1016/j.jth.2025.102121.

[3] A. Assa’ad, A. Y. Hershko, C. Irani, M. Mahdavinia, D. A. Khan, and J. A. Bernstein, “Health disparities in the Middle East: Representative analysis of the region,” J. Allergy Clin. Immunol. Glob., vol. 4, no. 1, p. 100350, 2025, doi: https://doi.org/10.1016/j.jacig.2024.100350.

[4] S. Baird et al., “A call to action: the second Lancet Commission on adolescent health and wellbeing,” Lancet, vol. 405, no. 10493, pp. 1945–2022, May 2025, doi: https://doi.org/10.1016/S0140-6736(25)00503-3.

[5] S. Barbado, A. Credo, D. Espiritu, N. M. Gubat, O. Llagas, and E. Onsay, “The impact of conditional cash transfer (CCT) on health and education in a coastal community: A randomized control trial (RCT) and regression discontinuity design (RDD),” Dev. Sustain. Econ. Financ., vol. 2–4, p. 100026, 2024, doi: https://doi.org/10.1016/j.dsef.2024.100026.

[6] T. Bu, D. Tang, Z. Zhang, and C. Jiang, “Rural road improvement and individual health in China,” J. Asian Econ., vol. 98, p. 101908, 2025, doi: https://doi.org/10.1016/j.asieco.2025.101908.

[7] K. N. Cajachagua-Torres, H. G. Quezada-Pinedo, W. C. Guzman-Vilca, C. Tarazona-Meza, R. M. Carrillo-Larco, and L. Huicho, “Vulnerable newborn phenotypes in Peru: a population-based study of 3,841,531 births at national and subnational levels from 2012 to 2021,” Lancet Reg. Heal. - Am., vol. 31, p. 100695, 2024, doi: https://doi.org/10.1016/j.lana.2024.100695.

[8] S. L. Cutter, “The origin and diffusion of the social vulnerability index (SoVI),” Int. J. Disaster Risk Reduct., vol. 109, p. 104576, 2024, doi: https://doi.org/10.1016/j.ijdrr.2024.104576.

[9] C. Field et al., “Community-level social determinants of health and pregestational and gestational diabetes,” Am. J. Obstet. Gynecol. MFM, vol. 6, no. 2, p. 101249, 2024, doi: https://doi.org/10.1016/j.ajogmf.2023.101249.

[10] C. A. Herrera et al., “No time to wait: resilience as a cornerstone for primary health care across Latin America and the Caribbean, a World Bank-PAHO Lancet Regional Health Americas Commission,” Lancet Reg. Heal. - Am., vol. 50, p. 101240, Oct. 2025, doi: https://doi.org/10.1016/j.lana.2025.101240.

[11] G. E. Kasse et al., “Food insecurity and health behaviors in a disaster-affected population: A case study of Tacloban, Philippines,” Hum. Nutr. Metab., vol. 41, p. 200327, 2025, doi: https://doi.org/10.1016/j.hnm.2025.200327.

[12] Z. Lan, X. Wu, X. Xing, and Y. Qian, “Factors influencing the fertility intentions among women of childbearing age in China,” Acta Psychol. (Amst)., vol. 260, p. 105640, 2025, doi: https://doi.org/10.1016/j.actpsy.2025.105640.

[13] S. Li, N. Mohamed Nor, and S. R. Kaliappan, “Do maternal socioeconomic status influence child overweight?,” Heliyon, vol. 10, no. 2, p. e24630, 2024, doi: https://doi.org/10.1016/j.heliyon.2024.e24630.

[14] P. Monisha Mary, A. M. Jacob, J. Jithin Daniel, and A. K. Shetty, “Estimation of out-of-pocket expenditures on health in a coastal rural community in Karnataka, India,” Soc. Sci. Humanit. Open, vol. 11, p. 101553, 2025, doi: https://doi.org/10.1016/j.ssaho.2025.101553.

[15] R. J. Nathanael, L. N. Adyanis, and K. Oginawati, “The last decade epidemiologic concern of drinking water contaminants of emerging concern (CECs) in Asian Countries: A scoping review,” Heliyon, vol. 10, no. 20, p. e39236, 2024, doi: https://doi.org/10.1016/j.heliyon.2024.e39236.

[16] K. O’Sharkey et al., “Prenatal exposure to criteria air pollution and traffic-related air toxics and risk of autism spectrum disorder: A population-based cohort study of California births (1990–2018),” Environ. Int., vol. 201, p. 109562, 2025, doi: https://doi.org/10.1016/j.envint.2025.109562.

[17] A. A. Shah et al., “Health and livelihood impacts of flood hazards on internally displaced persons in Pakistan,” Int. J. Disaster Risk Reduct., vol. 119, p. 105295, 2025, doi: https://doi.org/10.1016/j.ijdrr.2025.105295.

[18] Suprapto, “Digital Transformation and Collaborative Innovation Public Health Services in Indonesia: A Qualitative,” J. Interdiscip. Heal., vol. 2, no. 2, pp. 72–82, Mar. 2026, doi: https://doi.org/10.61099/jih.v2i2.253.

[19] S. Suprapto and Nawir Rahman, “Transformational Leadership, Knowledge Sharing, and Health Policy: A Qualitative Study in Organizational Contexts,” J. Edukasi Ilm. Kesehat., vol. 4, no. 1, pp. 9–18, Mar. 2026, doi: https://dx.doi.org/10.61099/junedik.v4i1.216.

[20] I. Syarif, W. Langelo, J. Jukarnain, A. Nursiah, and N. Masita, “Family Health Tasks and Childhood Stunting in Primary Care: A Cross-Sectional Study in Indonesia,” J. Ilm. Kesehat. Sandi Husada, vol. 15, no. 1 SE-Articles, pp. 49–59, Apr. 2026, doi: https://doi.org/10.35816/jiksh.v15i1.206.

[21] S. E. Ulrich, M. M. Sugg, M. R. Desjardins, and J. D. Runkle, “Disparities in spatiotemporal clustering of maternal mental health conditions before and during the COVID-19 pandemic,” Health Place, vol. 89, p. 103307, 2024, doi: https://doi.org/10.1016/j.healthplace.2024.103307.

[22] S. E. Ulrich, M. M. Sugg, D. Guignet, and J. D. Runkle, “Mental health disparities among maternal populations following heatwave exposure in North Carolina (2011–2019): a matched analysis,” Lancet Reg. Heal. - Am., vol. 42, p. 100998, 2025, doi: https://doi.org/10.1016/j.lana.2025.100998.

[23] Y. Wu and X. Zhang, “State-led regional development strategy and multidimensional health poverty of the residents: Evidence from the China’s great western development program,” Econ. Hum. Biol., vol. 57, p. 101494, 2025, doi: https://doi.org/10.1016/j.ehb.2025.101494.

[24] Y. Yan et al., “Provincial Maternal and Child Information System in Inner Mongolia, China: Descriptive Implementation Study,” JMIR Pediatr. Parent., vol. 7, 2024, doi: https://doi.org/10.2196/46813.

[25] C. Yu, W. Shen, and Z. Zhang, “Assessing progress toward sustainable development in China and its impact on human well-being,” Environ. Impact Assess. Rev., vol. 110, p. 107729, 2025, doi: https://doi.org/10.1016/j.eiar.2024.107729.

[26] S. Yu, Q. Guo, and Y. Liang, “The power of education: The intergenerational impact of children’s education on the poverty of Chinese older adults,” Int. J. Educ. Dev., vol. 116, p. 103297, 2025, doi: https://doi.org/10.1016/j.ijedudev.2025.103297.

[27] T. A. Bin Zaman, T. Haque, H. Sen Gupta, M. Sameer, and O. Nofal, “Computational review of disaster resilience research in Bangladesh,” Prog. Disaster Sci., vol. 28, p. 100486, 2025, doi: https://doi.org/10.1016/j.pdisas.2025.100486.

[28] Y. Zhao, H. Fan, Y. Luo, R. Zhang, and X. Zheng, “Gender Inequalities in Employment of Parents Caring for Children With Autism Spectrum Disorder in China: Cross-Sectional Study,” JMIR Pediatr. Parent., vol. 7, 2024, doi: https://doi.org/10.2196/59696.