With rapid economic and social development in China, the population is rapidly aging and will continue in the coming decades, which creates challenges for providing care for the older population. As an important component of public services, elderly care services are fundamental for improving the quality of life of older people. The older population has been rapidly increasing since the 1990s, and the Beijing Municipal Government put forward the “Special Plan for Residential Care Facilities in Beijing” in 2010 and set a goal to achieve a capacity of “9064” in 2020 (Municipal Civil Affairs Bureau, 2015), which proposed to provide community care services and residential care services for 6% and 4% of the older population respectively. By the end of 2020, the population aged 60 and over in Beijing had increased to 4.29 million, accounting for 19.6% of the total population, which is a significant increase compared to the proportion of 12.5% in 2010 (Committee, 2021). In recent years, an urgent issue has emerged in addressing whether the development of RCFs matches the rapid growth of the older population. It is important to understand the spatiotemporal changes in the distribution of the older population and RCFs for future planning and development in the residential care industry.

Current research on elderly care services includes the choice of places for aging and spatial allocation of elderly care facilities. Studies have analyzed factors that affect facility selection and found that demands for residential care services are differentiated and diversified with dynamic changes (Klein et al., 1997; Sales et al., 2005). Furthermore, these characteristics should be considered when planning the types and scales of RCFs (Gao et al., 2012). The demand for RCFs is rapidly growing in China, and the shortage of RCF beds is particularly serious (Beijing Municipal Commission, 2017). Internationally, research has paid attention to care giving (Keefe et al., 2022), living environments in RCFs (Nordin et al., 2017), adaptations of elderly people in RCFs (O'Neill et al., 2022), and psychological transitions by using qualitative methods (Ellis, 2010). The relationship between the environment of RCFs and the sense of home and belonging among the elderly has also been explored (Johansson et al., 2022), as well as the role of nursing staff (Coe and Werner, 2022; Matarese et al., 2021).

Geographical research on residential care services mainly includes three aspects. First, there has been a focus on the spatial distribution of the aging population from the perspective of the demands for residential care services (Li et al., 2011; Zhou, 2014) and on the spatial distribution, regional migration, and suburbanization of the elderly population at national and regional levels during the process of population aging (Golant, 1990; Moore and Pacey, 2004; Natera-Rivas et al., 2022). The results show that there are significant differences in the spatial distribution of the elderly population in Beijing, and there is an obvious trend of central agglomeration and suburbanization.

Second, studies have focused on the geographical distribution of RCFs. Klein and Salaske (1996) analyzed the regional differences in the supply of RCFs in Germany at the national scale, and Dai et al. (2011) analyzed the construction layout of RCFs in Beijing. Some scholars have further analyzed spatial equity of residential care resources based on the spatial distribution characteristics (Zhou et al., 2013). Ford and Smith (2008) studied the spatial and structural changes in elderly care service resources in England between 1993 and 2001. Hamnett and Mullings (1992) analyzed the spatiotemporal development of RCFs and the differences in England and Wales. Xi and Cheng (2015) analyzed the spatiotemporal changes of RCF layout in Beijing. From the perspective of the supply of residential care services, these studies focused on the dynamic development and spatial pattern of RCFs.

Third, a considerable amount of research has taken into account both demand and supply of RCFs and the matching relationship between the two in space. Frochen et al. (2021) utilized hotspot analysis and per capita bed number index to analyze the spatial distribution of RCFs in California and their matching relationship with elderly women. Kang (2016) found that there was a structural contradiction between the supply and demand of RCFs in Beijing based on a regression correlation analysis. Tao et al. (2014, 2015) evaluated the spatial accessibility of RCFs in Beijing based on the distribution of supply and demand and road network data, identified areas with limited facility resources, and optimized the layout of RCFs based on future demand forecast. Zhang et al. (2023) studied the accessibility and supply-demand relationship of RCFs based on traffic data. In addition to the cross-sectional analysis, some scholars have comprehensively analyzed the spatiotemporal distribution of the elderly population and RCFs in California from a dynamic perspective, but only summarized the changes in the number of facilities per capita considering supply and demand over time (Frochen et al., 2021).

The above studies discussed the spatial allocation of RCFs from the perspective of temporal and spatial changes in the supply and demand of RCFs and the cross-sectional accessibility evaluation of comprehensive supply and demand. However, their explanation for whether the development of RCFs can dynamically meet the changes in the elderly population is limited. Moreover, studies on Beijing have shown that there is a spatial mismatch between the supply and demand of RCFs. Therefore, this study will evaluate the spatiotemporal distribution of accessibility to RCFs from a dynamic perspective from 2010 to 2020, and further explore the changes in the spatial equity of accessibility.

Accessibility can be measured considering the population demands and the RCFs supply, and the spatial matching between the demands and supply are significant for analysis. As the time goes by, the changes in population will affect the demands for resources and the changes in residential care resources will also affect the supply, resulting the spatial matching pattern. The current characteristics of residential care supply and future demand are crucial for planning, taking into account the spatial-temporal changing pattern of RCFs and elderly population. The theoretical framework is created in Fig. 1.