ORIGINAL RESEARCH article
Front. Public Health
Sec. Aging and Public Health
This article is part of the Research TopicPublic Health Outcomes: The Role of Social Security Systems in Improving Residents' Health Welfare, Volume IIView all 28 articles
Health Opportunity Inequality in Middle-aged and Elderly Cardiovascular and Cerebrovascular Patients
Provisionally accepted
- Yanshan University, Qinhuangdao, China
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Objective: To measure and decompose health opportunity inequality among middle-aged and elderly patients with cardiovascular and cerebrovascular diseases, providing scientific evidence for the development of targeted health policies, particularly those aimed at ensuring health equity for middle-aged and elderly individuals with cardiovascular and cerebrovascular diseases. Methods: Based on inpatient medical record data from H Province, China, we employed a pre-parameter method, combining linear regression, conditional inference trees, and random forests to measure health opportunity inequality among middle-aged and elderly patients aged 45 and above with cardiovascular and cerebrovascular diseases. The relative contributions of various environmental factors to health opportunity inequality were quantified. Additionally, unconditional quantile regression models were used to further examine the contributions of environmental factors to health opportunity inequality at different quantiles. Results: The indices of opportunity inequality for major health and overall health ranged between 7.25%–12.72% and 7.13%–12.54%, respectively. Key influencing factors included surgical level, the number of doctors per 1,000 people, and the number of hospital beds per 1,000 people. Furthermore, the contribution of the variance in medical expenses to opportunity inequality significantly increased with quantile values, with contributions at higher quantiles only second to the aforementioned core environmental factors. Conclusion: To promote global health equity, this study proposes several policy directions: establishing a disease–resource alignment mechanism to optimise the allocation of advanced medical resources, strengthening primary healthcare and human resource systems, reforming healthcare financing towards equitable protection, and advancing prevention-oriented, data-driven health governance.
Keywords: Health opportunity inequality, Shapley value decomposition, Conditional inference trees, Random forests, Healthcare Disparities
Received: 17 Aug 2025; Accepted: 24 Nov 2025.
Copyright: © 2025 Hu, Zhao and Yu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Zi Yu
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