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The Impact of Multimorbidities on Catastrophic Health Expenditures among Patients Suffering from Hypertension in China: An Analysis of Nationwide Representative Data

Author

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  • Yu Fu

    (School of Health Policy & Management, Nanjing Medical University, Nanjing 211166, China)

  • Mingsheng Chen

    (School of Health Policy & Management, Nanjing Medical University, Nanjing 211166, China
    Creative Health Policy Research Group, Nanjing Medical University, Nanjing 211166, China
    Center for Global Health, Nanjing Medical University, Nanjing 211166, China)

Abstract

Background: Patients with hypertension are sensitive to multimorbidities (i.e., the existence of ≥2 chronic diseases), and the related treatment can create enormous economic burdens. We sought to examine the distribution of multimorbidities, the prevalence and factors of catastrophic health expenditure (CHE), the impact of multimorbidities on CHE, and the variation in this relationship across age groups, work status, and combinations of socioeconomic status and health insurance types. Methods: Socioeconomic-related inequality associated with CHE was estimated by concentration curve and concentration index. We examined the determinants of CHE and the impact of age groups, work status, and combinations of socioeconomic groups and health insurance schemes against the relationship with multimorbidities and CHE using logistic regression. Results: 5693 (83.3%) participants had multimorbidities. In total, 49.8% of families had experienced CHE, and the concentration index was −0.026 (95% confidence interval [CI], −0.032 to −0.020). Multimorbidities were related to the increased odds of CHE (odds ratio [OR], 1.21; 95% CI, 1.18–1.25). The relationship between multimorbidities and CHE persisted across age groups, work status, and combinations of socioeconomic status and health insurance schemes. Conclusions: More than 80% of patients with hypertension had multimorbidities. The protection of health insurance schemes against financial risks is very limited.

Suggested Citation

  • Yu Fu & Mingsheng Chen, 2022. "The Impact of Multimorbidities on Catastrophic Health Expenditures among Patients Suffering from Hypertension in China: An Analysis of Nationwide Representative Data," Sustainability, MDPI, vol. 14(13), pages 1-15, June.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:13:p:7555-:d:843927
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    References listed on IDEAS

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    1. Ye Li & Qunhong Wu & Chaojie Liu & Zheng Kang & Xin Xie & Hui Yin & Mingli Jiao & Guoxiang Liu & Yanhua Hao & Ning Ning, 2014. "Catastrophic Health Expenditure and Rural Household Impoverishment in China: What Role Does the New Cooperative Health Insurance Scheme Play?," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-9, April.
    2. Robinson Oyando & Martin Njoroge & Peter Nguhiu & Fredrick Kirui & Jane Mbui & Antipa Sigilai & Zipporah Bukania & Andrew Obala & Kenneth Munge & Anthony Etyang & Edwine Barasa, 2019. "Patient costs of hypertension care in public health care facilities in Kenya," International Journal of Health Planning and Management, Wiley Blackwell, vol. 34(2), pages 1166-1178, April.
    3. Cylus, Jonathan & Thomson, Sarah & Evetovits, Tamás, 2018. "Catastrophic health spending in Europe: equity and policy implications of different calculation methods," LSE Research Online Documents on Economics 89062, London School of Economics and Political Science, LSE Library.
    4. Owen O’Donnell & Stephen O’Neill & Tom Van Ourti & Brendan Walsh, 2016. "conindex: Estimation of concentration indices," Stata Journal, StataCorp LP, vol. 16(1), pages 112-138, March.
    5. John Tayu Lee & Fozia Hamid & Sanghamitra Pati & Rifat Atun & Christopher Millett, 2015. "Impact of Noncommunicable Disease Multimorbidity on Healthcare Utilisation and Out-Of-Pocket Expenditures in Middle-Income Countries: Cross Sectional Analysis," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-18, July.
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    1. Chen, Mingsheng & Xu, Lizheng & Si, Lei & Wang, Zhonghua & Jan, Stephen, 2023. "Examining the level and distribution of catastrophic health expenditure from 2013 to 2018: A province-level study in China," Economic Modelling, Elsevier, vol. 121(C).

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