Background
Achieving health equity is at the center of global health agenda. The Sustainable Development Goals (SDGs) prioritizes improving equity over the next 15 years [
1,
2]. Previous studies have identified significant inequalities in medical care utilization and catastrophic health spending between income groups in low- and middle-income countries such as Armenia, Burkina Faso, Indonesia, Vietnam, Chile, Turkey, China, India, Ghana, Tanzania, and Rwanda, with the poor less likely to use medical care and more likely to incur catastrophic health spending than those outside of poverty [
3‐
13]. However, other than poverty status itself, other sources of inequalities between the income groups, and their exact contributions to such inequalities, remain unknown. To design effective interventions against inequalities between income groups and monitor progress in reducing inequalities, it is important to identify sources of inequalities between income levels and quantify their contributions to inequality. Drawing upon such evidence, policy makers and other stakeholders will be able to construct related short-term and long-term policy measures to effectively reach their targets.
Rwanda is a low-income agricultural country in central east Africa, with a gross domestic product per capita of US$690 in 2015 [
14]. The country had a population of 11.3 million in 2014, with 83% of its population living in rural areas and 39.1% living below the national poverty line [
15]. Since 2000, Rwanda has made impressive progress in improving health outcomes. Its under-five child mortality rate fell drastically, from 196 per 1000 live births in 2000 to 50 per 1000 live births in 2015 [
16], making Rwanda one of only a few sub-Saharan countries that met the MDG target on reducing child mortality [
17]. Previous studies have observed a significant increase in medical care utilization when in need and a significant reduction in households with catastrophic health spending (HCHS) in Rwanda [
18‐
20]. However, inequalities in medical care utilization and HCHS between those living under poverty (poverty groups) and those living above poverty (non-poverty groups) have persisted over time (Liu K, Cook B, Lu C. Health inequality and community-based health insurance: a case study of rural Rwanda with repeated cross-sectional data, forthcoming).
Like many other developing countries, ensuring access to health care with financial risk protection for the poorest is part of the government’s policy agenda in Rwanda. Rwanda established Mutuelles at the national level in 2005 to promote health equity. In 2010, about 67% of individuals in Rwanda enrolled in the program (Liu K, Cook B, Lu C. Health inequality and community-based health insurance: a case study of rural Rwanda with repeated cross-sectional data, forthcoming). In both 2005 and 2010, the percentage of individuals enrolled in Mutuelles in the non-poverty group was significantly higher than in the poverty group, and the Mutuelles program did not play significant role in reducing inequalities in medical care utilization and HCHS between the two income groups in 2005 and 2010 (Liu K, Cook B, Lu C. Health inequality and community-based health insurance: a case study of rural Rwanda with repeated cross-sectional data, forthcoming).
In this study, we used the nationally-representative and publicly accessible Integrated Living Conditions Surveys (EICV) in 2005 and 2010 and decomposed the inequalities in medical care utilization among those reporting illnesses and HCHS between the poverty and non-poverty groups. We extended previous work by identifying the main sources of inequalities in addition to poverty status and quantifying their contributions in both compositional effect and response effect. We also tracked changes over time in the magnitude of their contributions.
Discussion
Using the nationally representative EICV surveys in Rwanda in 2005 and 2010, this study has two salient findings. First, while poverty status was the largest contributor, other sources also made significant positive contributions to inequalities in medical care utilization (e.g., health insurance, travel time taken to health centers) and HCHS (e.g., health insurance, health needs) between the poverty and non-poverty groups. Second, the main sources of inequality in medical care utilization and HCHS remained unchanged between 2005 and 2010.
These findings study are consistent with previous studies about determinants of medical care utilization and HCHS in Rwanda. Evidence has shown that members of the poverty group were less likely to use medical care and more likely to incur HCHS [
6,
18‐
20]. Enrolling in the
Mutuelles, a community-based health insurance for rural residents and those in the informal economy in Rwanda, promoted medical care utilization and reduced catastrophic health spending in both 2005 and 2010 [
6,
18]. Travel time taken to health centers was found to be inversely associated with medical care utilization, and health care needs were positively associated with medical care utilization and HCHS [
6,
18]. In addition, previous studies found that health inequalities are associated with
Mutuelles enrollment and benefit package design [
20]. Differing from these studies, our study adds evidence about the exact contributions of other risk factors and poverty status itself to inequalities in medical care utilization and HCHS between income groups.
The positive coefficients of compositional effect for health insurance indicate that the reducing gaps in
Mutuelles enrollment may potentially mitigate the inequalities in either medical care utilization or HCHS between the two income groups. In addition,
the Mutuelles may not have provided the same protective function of promoting medical care utilization in the poverty group as it does in the non-poverty group in 2005 and 2010, as shown by the negative coefficient of response effect for health insurance. Both positive coefficient of compositional effect and negative coefficient of response effect for having health insurance suggest that, to mitigate inequalities between the two groups, policies for increasing
Mutuelles enrollment among the poverty group and providing more protective effects to the poverty group (such as more service coverage) could be effective instruments. Since 2011, the Government of Rwanda has proposed providing a full subsidy for premiums and copayments
of the Mutuelles for the poorest population in Rwanda (about 25%) [
31], which could be expected to enlarge the coverage of
the Mutuelles among the poorest and provide further financial risk protection to improve their access to care.
Between 2005 and 2010, accessibility of health services was substantially improved, with more health centers established during this time period (from 353 in 2005 to 436 in 2010). Numbers of physicians and nurses also increased, from 5,298 in 2005 to 8,806 in 2010 [
18]. This improvement in service accessibility may explain the reduction of proportion of inequality in medical care utilization resulting from time travelling to health centers between 2005 and 2010.
Our study is subject to some potential limitations. First, factors (such as preferences, medical service availability, or satisfaction of services) that might contribute to observed inequalities in medical care utilization and HCHS between the two income groups were not included in the analysis due to unavailable data. As shown in this study and previous studies, the unknown factors could account for a sizable proportion of observed income-related inequality in medical care utilization [
32]. Second, data were self-reported and may be subject to measurement errors, such as recall bias [
33,
34]. Third, our construction of poverty indicators could potentially lead to under-estimation of inequality in 2005 and 2010, where 3% of non-poverty households were misallocated to the poverty group in 2005 and 5% of poverty households were misallocated to the non-poverty group in 2010.
Conclusions
Findings from this study add to the knowledge of inequalities in medical care utilization and HCHS between the poverty and non-poverty groups in Rwanda. For the first time, the sources of inequalities were identified and their contributions were quantified in 2005 and 2010. Decomposing inequalities provided evidence for policy makers in designing interventions for reducing inequalities. In the long-term, eliminating poverty is a key solution to health care inequality and requires sustained economic growth and strong commitment from governments. In the short-term, as health insurance and travel time to health centers accounted for a considerable share of inequality between the poverty and non-poverty groups in medical care utilization and HCHS, expanding health insurance coverage and improving geographic access to health facilities for those living in poverty could be used as policy instruments for mitigating inequalities.
Future studies should focus on (1) evaluating the impact of policy instruments, such as eliminating premium and user fees of Mutuelles for those living in poverty, on reducing the inequalities between the poverty and non-poverty groups; and (2) identifying data sources in Rwanda that would allow us to analyze the confounding factors that were not included in this study and elucidate how they contributed to the observed inequalities in medical care utilization and HCHS.