(1) Background: Population aging has been accelerating in China since the 1990s, and the number of people over 65 reached 190 million in 2020. However, the spatial distribution of the aged is not homogeneous; in rural areas, the aged population accounted for 17.72% of the total population, whereas in urban areas, it accounted for 11.11%, which is 6.61 p.p. less. Therefore, this study aims to examine the spatial heterogeneity and influencing factors of population aging in rural China from 2000 to 2020. (2) Methods: First, Getis–Ord Gi* was used to analyze the spatial clustering of the aged population in rural China. Then, standard deviational ellipse was used to characterize the temporal trend of the spatial clustering of population aging in rural China. Finally, potential influencing factors that could have contributed to the spatial–temporal patterns were analyzed using a novel spatial statistical package “Geographical Detector”. (3) Results: (a). Aging in rural populations increased and occurred throughout China from 2000 to 2020. (b). The spatial patterns of aging in China are roughly divided by the Hu Line, which is the population density boundary of China. (c). The mean center of the aged population tended to orient around a northeast-to-southwest major axis over the past 20 years, contrary to the internal migration pattern that flows from north to south. (d). The population age structure, longevity rate, and fertility rate were the predominant factors of aging in rural areas. (4) Conclusions: As the aged population is rapidly increasing in rural areas in China in a spatially heterogeneous fashion, governments and private sectors need to collaborate to alleviate the problem.

Optimizing the allocation of basic medical services and ensuring their equity are necessary to improve the ability to respond to public health emergencies and promote health equity in the context of COVID-19. This study aims to analyze the equity of Guangzhou’s basic medical service and identify areas where health resources are relatively scarce. The spatial distribution and patterns of basic medical services were analyzed using kernel density analysis and standard deviation ellipse. The equity was analyzed using the Gini coefficient and Lorenz curve in terms of population and geographical area, respectively. Considering the medical demand and supply sides, the Gaussian two-step floating catchment area method was used to analyze the accessibility to different levels of medical institutions. The kernel density analysis and standard deviation ellipse showed that the spatial distribution of medical and health resources in Guangzhou is unevenly distributed, and high-level hospitals and medical resources are mainly concentrated in the centrum. From the perspective of population, Guangzhou’s medical equity is generally reasonable. The accessibility of medical institutions differs with different levels, and the tertiary medical institutions have the best accessibility, while the unclassified, primary, and secondary medical institutions generally have lower accessibility. The accessibility of districts in Guangzhou varies greatly. Areas in the center are most accessible to basic medical services, while accessibility in outskirt areas has gradually decreased. Conclusion: The quantity of per capita medical and health resources in Guangzhou, as evidenced by basic medical services, is sufficient, but the spatial distribution is unequal. The developed city center enjoys more adequate healthcare resources than the distant suburbs. Primary healthcare should be built, especially in distant suburbs, to strengthen basic medical service equity in Guangzhou.