Department of Social Security, School of Labor and Human Resources, Renmin University of China, Haidian District, Beijing, China.
Division of Global Health Equity, Brigham & Women's Hospital, Boston, MA, USA.
Int J Equity Health. 2018 May 10;17(1):57. doi: 10.1186/s12939-018-0769-1.
Ensuring equal access to care and providing financial risk protection are at the center of the global health agenda. While Rwanda has made impressive progress in improving health outcomes, inequalities in medical care utilization and household catastrophic health spending (HCHS) between the impoverished and non-impoverished populations persist. Decomposing inequalities will help us understand the factors contributing to inequalities and design effective policy instruments in reducing inequalities. This study aims to decompose the inequalities in medical care utilization among those reporting illnesses and HCHS between the poverty and non-poverty groups in Rwanda.
Using the 2005 and 2010 nationally representative Integrated Living Conditions Surveys, our analysis focuses on measuring contributions to inequalities from poverty status and other sources. We conducted multivariate logistic regression analysis to obtain poverty's contribution to inequalities by controlling for all observed covariates. We used multivariate nonlinear decomposition method with logistic regression models to partition the relative and absolute contributions from other sources to inequalities due to compositional or response effects.
Poverty status accounted for the majority of inequalities in medical care utilization (absolute contribution 0.093 in 2005 and 0.093 in 2010) and HCHS (absolute contribution 0.070 in 2005 and 0.032 in 2010). Health insurance status (absolute contribution 0.0076 in 2005 and 0.0246 in 2010) and travel time to health centers (absolute contribution 0.0025 in 2005 and 0.0014 in 2010) were significant contributors to inequality in medical care utilization. Health insurance status (absolute contribution 0.0021 in 2005 and 0.0011 in 2010), having under-five children (absolute contribution 0.0012 in 2005 and 0.0011 in 2010), and having disabled family members (absolute contribution 0.0002 in 2005 and 0.0001 in 2010) were significant contributors to inequality in HCHS. Between 2005 and 2010, the main sources of the inequalities remained unchanged.
Expanding insurance coverage and reducing travel time to health facilities for those living in poverty could be used as policy instruments to mitigate inequalities in medical care utilization and HCHS between the poverty and non-poverty groups.
确保平等获得医疗保健和提供财务风险保护是全球卫生议程的核心。尽管卢旺达在改善健康结果方面取得了令人瞩目的进展，但贫困和非贫困人口在医疗服务利用和家庭灾难性卫生支出（HCHS）方面仍然存在不平等。分解不平等有助于我们了解导致不平等的因素，并设计有效政策手段来减少不平等。本研究旨在分解卢旺达报告患病和 HCHS 的贫困和非贫困人群之间的医疗服务利用不平等。
使用 2005 年和 2010 年全国代表性综合生活条件调查，我们的分析侧重于衡量贫困状况和其他来源对不平等的贡献。我们通过控制所有观察到的协变量进行多变量逻辑回归分析，以获得贫困对不平等的贡献。我们使用多变量非线性分解方法和逻辑回归模型，将其他来源对因构成或反应效应引起的不平等的相对和绝对贡献进行划分。
贫困状况导致医疗服务利用（2005 年的绝对贡献为 0.093，2010 年为 0.093）和 HCHS（2005 年的绝对贡献为 0.070，2010 年为 0.032）的大部分不平等。健康保险状况（2005 年的绝对贡献为 0.0076，2010 年为 0.0246）和前往卫生中心的旅行时间（2005 年的绝对贡献为 0.0025，2010 年为 0.0014）是医疗服务利用不平等的重要贡献者。健康保险状况（2005 年的绝对贡献为 0.0021，2010 年为 0.0011）、五岁以下儿童（2005 年的绝对贡献为 0.0012，2010 年为 0.0011）和残疾家庭成员（2005 年的绝对贡献为 0.0002，2010 年为 0.0001）是 HCHS 不平等的重要贡献者。2005 年至 2010 年间，不平等的主要来源保持不变。
扩大保险覆盖范围并减少贫困人群前往卫生设施的旅行时间，可以作为政策手段，减轻贫困和非贫困人口在医疗服务利用和 HCHS 方面的不平等。
