This study was based on panel data from Chinese cities spanning from 2001 to 2020. By employing different models, we have demonstrated that the long-term convergence rate of the geographic distribution of healthcare resources in China was higher than the short-term convergence rate. Furthermore, the convergence rate of doctor density surpassed that of hospital bed density. Additionally, we have discovered that economic growth, measured by per capita GDP, significantly influenced the convergence rate of healthcare resources, and this effect was nonlinear. Lastly, the heterogeneity among provinces had an undeniable impact on the convergence of healthcare resources.

The investment in healthcare resources, such as doctors and hospital bed, requires a lengthy process. For instance, doctors typically have higher educational levels compared to other professions [54], and their training period is often prolonged [55]. Therefore, the long-term convergence rate of investment in healthcare resources is higher than the short-term convergence rate. Figures 2, 3, 4, 5, 6 and 7 present the physician density and hospital bed density across Chinese cities in 2001, 2005, and 2019, respectively. From 2001 to 2005, there was no significant change in the distribution of healthcare resources among cities nationwide. However, from 2005 to 2019, there was a notable shift in the distribution of healthcare resources, indicating that the long-term convergence rate exceeds the short-term rate. Moreover, as time progressed, there was an increase in healthcare resource density, suggesting a positive correlation between per capita income and healthcare resource density. This finding aligns with the international trend where high-income countries generally possess more healthcare resources compared to low-income countries. Furthermore, between 2001 and 2019, there were dynamic changes in the distribution of healthcare resources, ultimately trending towards fairness.

The physician density across Chinese cities in 2001

The hospital bed density across Chinese cities in 2001

The physician density across Chinese cities in 2005

The hospital bed density across Chinese cities in 2005

The physician density across Chinese cities in 2019

The hospital bed density across Chinese cities in 2019

The majority of doctors are usually employed in hospitals and primary healthcare institutions, with statistics showing that 92.3% of healthcare personnel in China work in hospitals and primary healthcare institutions [56]. Consequently, an increase in hospital beds leads to an increase in doctor density. In comparison to fixed capital investment, the adjustment speed of variable capital investment is faster and yields returns earlier. As hospital beds represent fixed capital, their convergence rate is lower than that of variable capital investment, i.e., doctors.

The influence of income growth on healthcare resources highlights the important role played by market mechanisms in guiding resource allocation. However, this process may not be linear. The findings provide evidence supporting the credibility of the Kuznets curve theory in elucidating the distribution patterns of healthcare resources in China. As per this theory, the occurrence of healthcare resource inequality among cities follows a pattern where it initially increases and subsequently decreases as per capita income experiences an upsurge. The Kuznets curve theory reflects the relationship between income inequality and economic development [57], and has subsequently been widely applied in other areas, such as healthcare and environmental quality [58, 59]. In the immediate term, economic growth in China engenders heightened disparities across various social dimensions, including healthcare. However, over the long haul, these disparities may diminish as healthcare resources converge among regions, consequently mitigating the unequal distribution of such resources. The inequality observed in the intercity allocation of healthcare resources manifests an inverted “U” trajectory, initially escalating in the short term before subsiding in the long term. It is worth noting that the outcomes presented in Table 3 indicate that sustained economic growth will reinforce the dynamic convergence pattern for the distribution of doctors. Nonetheless, given the sluggish adjustment pace of fixed capital, the distribution of hospital beds is still approaching a critical turning point, which will eventually reverse as per capita income continues to rise. In summary, our empirical research findings support the soundness of the Kuznets curve theory in expounding upon the healthcare resource distribution in China, wherein disparities initially augment across regions but subsequently decline as per capita income increases.

After incorporating the effects of provincial heterogeneity, the overall convergence rate is lower than the results without controlling for provincial heterogeneity. The convergence cycle of hospital bed density has been extended by 2 years (from k ≥ 4 to k ≥ 6). In comparison to per capita GDP, population size, and government expenditure, a substantial portion of the errors can be attributed to unobserved disparities in provincial characteristics. Nonetheless, these differences do not influence the overall rate of convergence. Decomposition of the estimates from the fixed model indicates substantial inter-provincial variations. Regional disparities in healthcare resources often result in patient mobility, which is a common phenomenon reflecting the status of healthcare reforms, legislative changes, and healthcare system development in a country or region [60]. Therefore, healthcare resources not only radiate within provinces but also have an impact on neighboring provinces. However, government regulations on the healthcare sector may hinder the transmission of market signals to the healthcare industry, thereby narrowing the supply-demand gap in healthcare resources and causing temporary surpluses or shortages of healthcare resources [61], which in turn reduces the cross-regional convergence of healthcare resources. Therefore, the empirical research outcomes we have obtained also indicate that a more lenient approach to policies within healthcare sector could potentially foster the seamless integration of healthcare resources throughout various regions, consequently aiding in the alleviation of healthcare disparities.

For a considerable period of time, economic development has exacerbated the inequitable distribution of healthcare resources. Without proactive measures, transitioning to the next stage may prove challenging. The poorest individuals among the poor suffer from a disproportionately high incidence of disease and premature death. A social gradient is observed across all countries: the lower the socioeconomic status, the poorer the health outcomes [62]. In other words, unequal economic status predicts unequal health outcomes. In the case of China, in addition to the widening disparities in health achievements among provinces with differing levels of prosperity as mentioned above, the differences in health outcomes resulting from wealth disparity are also pronounced. Although the under-5 mortality rate substantially decreased between 1996 and 2004, the rural areas still exhibited significantly higher rates than urban areas, with the mortality gap between rich and poor widening in rural areas. When categorizing rural areas according to their socioeconomic environments, the under-5 mortality rate in affluent rural areas decreased by approximately 50%, while the rate in relatively impoverished rural areas decreased by around 16% [63]. Before 2004, there was a significant disparity in the hospital delivery rates between urban and rural areas in China. However, the findings of this study demonstrate the credibility of the Kuznets curve theory in explaining the distribution patterns of healthcare resources in China. The economic development-induced wealth inequality is not a persistent trend; instead, it reaches a peak and subsequently begins to decrease. China has already experienced this turning point. The narrowing of economic inequality heralds the convergence of urban health resources, leading to a more equitable health outcome. For example, from 2000 to 2010, the life expectancy in Beijing and Shanghai increased by 4.08 and 2.12 years, respectively, from 76.10 and 78.14 years to 80.18 and 80.26 years. In Gansu Province, life expectancy increased by 4.76 years, from 67.47 to 72.23 years, surpassing the growth rate of the two wealthiest regions in China [64]. Furthermore, following China’s proposal for deepening healthcare reform in 2009, urban healthcare resources have been gradually converging, resulting in a diminishing urban-rural divide and a reduction in health outcome disparities attributable to economic disparities [12]. For instance, after 2009, the in-hospital delivery rates in both urban and rural China remained at relatively high levels with little differentiation, reaching 99.9% in 2019 [64]. These data indicate that, as the economic level advances, disparities in healthcare resources between urban areas initially increase before subsequently decreasing.

Governments and institutions in China, as well as across all nations globally, should actively take steps to address health inequities. Indeed, China is making efforts in this regard. In 2013, China launched the targeted poverty alleviation program with the goal of eradicating extreme poverty by 2020. In 2016, China issued Healthy China 2030 plan, aiming to achieve high-quality universal health coverage by 2030. In 2019, Healthy China Action (2019–2030) was released. These robust economic and health policies have yielded results in the healthcare sector, including the promotion of inter-regional medical insurance policies and strong support for the construction of national regional medical centers [65, 66]. For instance, as of July 2023, China has identified 125 projects for the construction of national regional medical centers in five batches, covering provinces with weak healthcare resources [67]. We are confident that in the future, the unequal distribution of healthcare resources in China will gradually decrease. The Russian government has also taken proactive steps and made efforts. Although Russia experienced a severe economic downturn after the dissolution of the Soviet Union in 1991 [68], and had very low healthcare expenditure, improvement began rapidly in 2000. The government increased spending on healthcare and on vulnerable populations, alleviating the vulnerability of rural and low-income groups to catastrophic healthcare expenses [69]. Moreover, early insurance coverage heavily depended on geographical location and employment status, with higher coverage among the affluent population. However, this trend gradually evolved into a more equal distribution, with almost 97.4% of the Russian population having medical insurance by 2011 [70]. India lags behind most neighboring countries in life expectancy, maternal mortality rate, and infant mortality rate, and many people struggle to access adequate and affordable care [71]. In light of this disadvantage, India has also been actively exploring new healthcare models to promote health equity. In 2007, India launched the Rashtriya Swasthya Bima Yojana (RSBY), a program that provides free medical services to impoverished families, although the program has faced many shortcomings. In 2010, India proposed detailed reform plans to expand RSBY. In 2017, based on RSBY, India announced a healthcare program called “Ayushman Bharath,” consisting of two parts: strengthening existing primary healthcare and providing inpatient treatment for identified low-income families. India has committed to achieving universal health coverage, although progress has not been effectively improved at present and faces significant challenges [71]. The health disparities between countries have also been alleviated, in addition to within each country. Some forecasts indicate that the competitiveness of the BRICS countries (Brazil, Russia, India, China) has been continuously strengthened compared to the major markets of the Organization for Economic Cooperation and Development (OECD) [72]. From 1995 to 2012, the share of global health expenditure accounted for by the OECD declined significantly in nominal and purchasing power parity terms [72], indicating a certain improvement in the unfair distribution of health resources between high-income and middle-to-low-income countries.

Therefore, we advocate that all countries around the world should actively implement corresponding measures, which includes improving the birth environment and healthcare standards in impoverished areas and among vulnerable populations, addressing inequalities in rights, finances, and resource allocation, establishing a system for monitoring health equity, conducting internal assessments of health inequality, investing in training for decision-makers and healthcare professionals, and emphasizing social determinants of health in public health research. Despite facing numerous challenges, China’s experience provides important insights. Since 2013, the Chinese government has proposed and implemented the “Belt and Road” cooperation initiative, aiming to connect the Asia-Pacific economic area with the European economic area through the establishment of the “Silk Road Economic Belt” and the “21st Century Maritime Silk Road,” thereby creating a significant practice of building a community with a shared future for mankind. This initiative provides a platform for strengthening global health strategies.

Addressing the inequitable distribution of healthcare resources between different cities is a complex issue that requires collaborative efforts from the government, healthcare institutions, and society as a whole. In response to this, we propose several possible approaches: 1) Establishing equitable resource allocation standards: Develop scientifically-based healthcare resource allocation standards that take into account factors such as population density, regional development level, and disease burden, ensuring fair distribution of healthcare resources. 2) Increasing investment in primary healthcare services: Enhance investment in primary healthcare facilities in rural and remote areas, improving their service capabilities to bridge the healthcare resource gap between urban and rural areas. 3) Improving the mobility of healthcare services: Encourage healthcare professionals, including doctors and nurses, to move between different regions, particularly to disadvantaged and densely populated areas, to balance the supply of medical resources across different regions. 4) Enhancing healthcare insurance policies: Strengthen healthcare insurance coverage for low-income groups, alleviating the burden of medical expenses and enhancing their access to healthcare services. 5) Strengthening regulation and assessment: Establish sound regulatory systems to supervise and evaluate the allocation of healthcare resources, promptly identifying and rectifying any unfair practices. 6) Enhancing transparency in healthcare resource information: Establish a comprehensive system for publicly disclosing healthcare resource information, including the actual situation of healthcare resources, distribution criteria, and utilization, ensuring that the public and regulatory authorities have a clear understanding of the allocation of healthcare resources. 7) Promoting integrated utilization of healthcare resources: Facilitate the integration and utilization of healthcare resources between different cities, by establishing platforms for sharing healthcare resources, ensuring their more efficient and effective utilization. 8) Encouraging tilt of medical technology and resources towards underdeveloped areas: The government can incentivize the tilt of medical technology and resources towards underdeveloped areas through policies such as establishing dedicated medical aid funds to support the healthcare resource development and technological upgrades in these regions. Furthermore, as described in the background, apart from uneven economic development, other factors such as natural geographic environment, transportation convenience, and population distribution may also be important reasons affecting the distribution of healthcare resources. Therefore, it is necessary to work together from various perspectives and approaches to promote fair distribution of healthcare resources. In summary, improving the inequitable distribution of healthcare resources between different cities requires comprehensive strategies, including the formulation of reasonable policies, strengthened regulation, promotion of resource sharing and integrated utilization, to achieve equitable distribution and maximized utilization of healthcare resources.

Our study has several limitations. Firstly, we focused only on the density of healthcare resources, while the distribution of healthcare resource quality is equally important to investigate. Secondly, the underlying mechanisms through which GDP influences healthcare resources remain unclear, such as the preference of physicians and hospitals for location selection. Thirdly, our study employed physician density and bed density as proxies for healthcare resources, which cannot differentiate whether the allocation of specialized physicians and other resources is fair. In fact, the distribution of different specialized physician groups can vary significantly. Future research can explore the quality of healthcare resources and examine different specialized physicians, which may have important policy implications for ensuring equitable access to high-quality healthcare services for both urban and rural populations.