Background
China is home to 56 ethnic groups, the predominant one being Han, with the remaining 55 constituting various ethnic minority groups [
1]. Globally, health resources for ethnic minority populations are often limited [
2‐
4], a trend that is also observable in western China [
5‐
7]. This limited accessibility to health resources often results in poorer health outcomes for minority populations as compared to their non-minority counterparts [
8‐
12]. To address these disparities, the Chinese Government has implemented several measures, including preferential policies for ethnic minority regions. These measures encompass tax reductions and exemptions, as well as support for health infrastructure development [
13‐
15]. A key aim of the medical reform initiated in 2009 was to enhance health resources in ethnic minority regions [
16]. However, it remains unclear whether these preferential policies have successfully improved the equitable allocation of health resources between ethnic minority and non-minority regions.
The foundation for delivering high-quality healthcare services is the availability of beds, doctors, and nursing staff within healthcare institutions [
17‐
19]. Factors such as governmental policies, regional economic development, and geographical conditions significantly influence the distribution of these health resources [
11,
20,
21]. Ethnic minority populations predominantly reside in remote, high-altitude areas characterized by limited economic development, while the Han population typically inhabits regions with lower altitudes and more robust economies. Consequently, the interplay of policy, geography, and economic factors contributes to disparities in health resource allocation. The impact of preferential policies and the influence of adverse geographical and economic factors on the provision of beds, doctors, and nurses in ethnic minority regions following the 2009 medical reform remain to be fully understood.
Sichuan Province, located in southwest China, is home to all 56 ethnic groups found within the country. The majority of the 55 ethnic minority populations reside in 67 of the 181 counties in the province. These 67 ethnic autonomous counties account for 62.1% of Sichuan's total area, with an average altitude exceeding 2400 m above sea level (a.s.l.) and a per capita gross domestic product (GDP) lower than that of non-minority regions. The unique combination of natural and social characteristics makes Sichuan an ideal location for investigating the effects of policies, geographical environment, and economic development on the temporal variations and disparities of health resources among distinct ethnic groups.
In response to the scarcity of healthcare resources in ethnic minority counties, the Sichuan Province Government implemented the "Ten-year Action Plan for Health Development in Ethnic Minority Counties of Sichuan Province" from 2011 to 2020 [
22]. The execution of this action plan resulted in an investment exceeding 2 billion RMB to increase the number of healthcare facilities and practitioners in these minority regions. We hypothesize that the growth rate of healthcare resources (beds, doctors, and nurses) in ethnic minority counties has surpassed that of non-minority counties since 2009. However, the per capita resources in ethnic minority counties likely remain inferior to those in non-minority counties due to the significantly low baseline values in the former. Furthermore, we propose that the equitable distribution of healthcare resources improved between 2009 and 2019. We also speculate that policy measures and economic development primarily drive variations in healthcare facilities, while income, economic development, and geographical factors significantly influence the allocation of healthcare practitioners. Specifically, we aim to investigate the changes and disparities in health resource allocation among ethnic minority, poverty-stricken, and non-minority regions in Sichuan Province from 2009 to 2019, and to identify the key factors influencing these changes.
Discussion
Our findings confirm that health resources (Bed
p1000, Doc
p1000 and Nur
p1000) are less distributed in ethnic minority counties. Despite lower Bed
p1000 values in all ethnic minority counties compared to Non-minority counties, our results demonstrate that preferential policies have effectively enhanced health facilities (beds), rather than healthcare workers, in ethnic minority regions. This is evidenced by the higher ratio of Bed
p1000 than Doc
p1000 and Nur
p1000 between ethnic minority and Non-minority counties in 2019. Additionally, the reduced Theil Index (TI) for beds from 2009 to 2019 (Fig.
4A) also shows the roles of policies in increasing beds in the ethnic minority counties. This is further supported by the decrease in doctors in many Yi and Zang counties (Fig.
2E). Indeed, it is easier to build hospitals in underserved areas than it is to staff them.
Our findings do not support a higher growth rate of health resources in all ethnic minority counties compared to Non-minority counties (Fig.
2), highlighting the inadequacy of current policies in augmenting the doctor population in these ethnic minority regions. This is firstly evidenced by the negative growth of doctors in approximately 33% of Yi and 50% of Zang counties. The deficiency is further supported by the low DNpB in the Yi group and DN/HP values for both Yi and Zang counties (Fig.
3). The higher DNpB in Zang counties relative to the Sichuan Province average between 2017 and 2019 does not imply adequate health practitioner and facilities. Rather, it demonstrates insufficiency in both areas as the number of doctors, nurses and beds in the Zang counties only accounted for 70%, 61% and 79% of the Sichuan Province average during the three years, respectively. In addition, the rising inter-category TI for doctors (Fig.
4) suggests the widening disparities in doctor distribution between different ethnic regions. Wang & Pan similarly reported difficulties in accessing doctors for ethnic minority groups due to shortages in these regions [
26]. As health practitioners play a critical role in determining health system performance and outcomes [
24,
27], this shortage may have adverse consequences. For example, maternal mortality ratios in Zang and Yi ethnic minority counties exceeded those in non-minority counties, as reported in the Sichuan Health Statistical Yearbook from 2009 to 2019.
Our analysis partially corroborates a decline in the equity of health resource allocation in Sichuan Province between 2009 and 2019. This is evident as the Theil Index (TI) for beds and nurses decreased, while the TI for doctors displayed a contrasting trajectory (Fig.
4). The observed decrease in TI for beds and nurses represents different forms of equity. For instance, the Bed
p1000 across all five categories exceeded that in Guangdong Province in 2019 (4.73), which has the highest GDP in China. This underscores a high level of equality in bed allocation. Conversely, all ethnic minority and PSC counties demonstrated a significantly lower Nur
p1000 compared to the average in western China in 2019 (3.26), generally considered the least developed region in China. Hence, the distribution of nurses among the five categories exemplifies a low level of equality. The declining equity in doctor allocation suggests that the existing preferential policies have not effectively bolstered the numbers of doctors in ethnic minority counties. It's plausible that other factors contribute to this diminished equity in doctor allocation.
Economic development considerably influenced the increase in beds between 2009 and 2019. Approximately 42% of the variation in Bed
p1000 was accounted for by GDP per capita (Fig.
5). GDP per capita, a key economic development indicator, is widely recognized as a significant influence on health resources, as evidenced by numerous previous studies [
25,
28‐
31]. Although non-minority counties generally have higher GDP per capita than ethnic minority counties, the more substantial growth rate of Bed
p1000 in Yi and other ethnic minority counties compared to non-minority counties attests to the effectiveness of preferential policies in increasing bed availability in these ethnic minority counties (Fig.
2). Thus, we conclude that preferential policies and economic development over the past decade have been crucial in enhancing bed availability in ethnic minority regions, thereby promoting health facility equity in Sichuan Province.
The significantly lower health practitioner growth rates (Nur
p1000 and Doc
p1000) in Zang and Yi counties compared to other ethnic minority counties cannot be solely ascribed to economic indicators (Fig.
5). Other ethnic minority counties exhibited only slightly higher GDP per capita than Zang counties, as per the Sichuan Statistical Yearbook. Considering the higher average altitudes of Yi (2139 m a.s.l.) and Zang (3656 m a.s.l.) counties compared to other ethnic minority counties (1592 m a.s.l.), challenging geographical environments could be an additional factor hindering the growth of doctors and nurses in Yi and Zang counties. This is further supported by the finding that correlations between health practitioner metrics (Nur
p1000 and Doc
p1000) and average county altitude became significant in 2019, having been insignificant in 2009 (Fig.
5). Consequently, the relatively low economic development levels and harsh geographical environments in Yi and Zang counties contribute to the lower growth rate of doctors in these regions compared to the other three regions, ultimately leading to decreased equity in doctor availability across Sichuan Province (Fig.
4). Given the complexities associated with swiftly altering geographical circumstances and improving the economic status of the Zang and Yi counties, we propose two potential strategies to address the shortage of healthcare practitioners in these areas. Firstly, we recommend offering additional financial incentives for physicians and nursing staff working in these regions. Secondly, we suggest promoting internet-enabled diagnostic and therapeutic services to mitigate the current shortage of medical professionals in the remote Zang and Yi counties.
Our study has several limitations. Language barriers and a relatively low level of primary education may influence residents' health-seeking behavior and medical graduates' willingness to serve in ethnic minority regions. Owing to data accessibility challenges, we did not analyze the impact of these two factors on the trend in Nurp1000 and Docp1000. Additionally, a questionnaire survey is crucial to elucidate the reasons for the shortage of health practitioners in ethnic minority regions, particularly in the Yi and Zang regions. Furthermore, as the primary goal of this study was to highlight disparities between ethnic minority and non-minority counties, counties defined by government documents as both ethnic minority and poverty-stricken were classified as ethnic minority counties in this study. However, this mutually exclusive categorization is unlikely to significantly affect the results, as both types of counties received similar preferential policies from 2010 to 2019.
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