Spatial-temporal distribution and evolution of medical and health talents in China.

BACKGROUND

In the context of public health emergencies, the presence of medical and health talents (MHT) is critically important for support in any country or region. This study aims to analyze the spatial and temporal distributions and evolution of MHT in China and propose strategies and recommendations for promoting a balanced distribution.

METHODS

This research used data from 31 provinces in China to construct a multidimensional index system for measuring the agglomeration level of MHT. The indices include talent agglomeration density (TAD), talent agglomeration scale (TAS), talent agglomeration intensity (TAI), and talent agglomeration equilibrium (TAE). Using provincial data from the years 1982, 1990, 2000, 2010, and 2020, a spatiotemporal analysis of the MHT agglomeration levels was conducted. Furthermore, the regional dynamic distribution of MHT was analyzed using kernel density estimation diagrams. The spatial autocorrelation of MHT was assessed through global and local Moran's I, and the spatial gap and decomposition of MHT were analyzed using the Dagum Gini coefficient.

RESULTS

From the temporal level, the TAD and TAI of MHT showed an increasing trend over the studied period, whereas TAS decreased and TAE first increased and then decreased from 1982 to 2020. At the spatial level, the TAD, TAS, TAI, and TAE of MHT exhibited varied patterns among the eastern, central, and western regions of China, showing significant geographical disparities, generally demarcated by the Hu Huanyong Line. The regional dynamic distribution level of MHT in the country and the three regions were expanding. Spatial autocorrelation analysis using global and local Moran's I for TAD, TAS, TAI, and TAE demonstrated significant regional differences. The Dagum Gini coefficient of TAD, TAS, TAI, and TAE revealed divergent trends in regional disparities, with overall declines in disparities for TAD and TAI, a slight increase for TAS, and fluctuating patterns for TAE.

CONCLUSIONS

From a temporal perspective, the overall number of MHT in China has been increasing annually at the national and provincial levels. From the spatial perspective, TAD, TAS, TAI, and TAE exhibit significant differences among the three regions. Kernel analysis reveals that the distribution differences are gradually expanding in national level and varying in regional level. Moreover, the global and local Moran's I indices reveal varying spatial autocorrelation for TAD, TAS, TAI, and TAE. The Dagum Gini coefficients of TAD, TAS, TAI, and TAE show different patterns of decomposition.