Tropical Geography ›› 2023, Vol. 43 ›› Issue (9): 1777-1786.doi: 10.13284/j.cnki.rddl.003739

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Spatiotemporal Evolution of the Matching Relationship between the Elderly Population and Facilities for the Elderly: A Case Study of Guangzhou

Liuqing Zhou1(), Tingting Zhou1(), Li Wang2, Bo Wang2,3,4   

  1. 1.Guangzhou Tujian Urban Planning Survey and Design Co. Ltd, Guangzhou 511399, China
    2.School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China
    3.Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519000, China
    4.Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, Guangzhou 510275, China
  • Received:2022-10-31 Revised:2023-01-05 Online:2023-09-05 Published:2023-09-11
  • Contact: Tingting Zhou E-mail:45134405@qq.com;99171844@qq.com

Abstract:

As places providing professional living care, facilities for the elderly (hereafter abbreviated as "facilities") are playing an increasingly important role in China's old-age service system. Evidence suggests that older adults who receive living care from nearby facilities enjoy better health outcomes than those who move to facilities over long distances. Therefore, a higher level of matching between the elderly population and facilities is crucial for improving service efficiency and facility support. Taking Guangzhou as a case study, this study collected data on the population census and facilities from 2000 to 2020. The data were used to analyze the spatiotemporal evolution of the elderly population, facilities, and their matching relationships, focusing on microscale units (i.e., sub-districts and towns). The results show that the uneven spatial distribution of both the elderly population and facilities is becoming more evident. Specifically, there is a stable "high-low-middle" sphere structure of the elderly population distribution. While the central areas are already home to an aged society, suburban areas have a relatively low level of population aging owing to the concentration of the modern service industry and strategic emerging industries that attract the working-age population. Accordingly, the level of population aging in outskirts is between those of the central and suburban areas. Compared to the consistent sphere structure of the elderly population distribution, the number of facilities has evolved from an even distribution to a polarized distribution that decreases stepwise from the inside to the outside. Although populations in both areas have aged rapidly, the number of facilities have increased considerably in the central areas, whereas limited growth has occurred in the outskirts. Second, from a global perspective, although the matching relationship between the elderly population and facilities has improved, the level remains low. Specifically, the Gini coefficient of the elderly population and facilities decreased from 0.62 in 2000 to 0.54 in 2020. However, even by 2020, 30% of the elderly population was able to enjoy living care from nearly 60% of facilities; instead, approximately 10% of the elderly population was not well covered by facilities. Third, from a local perspective, improvement in the matching relationship between the elderly population and facilities did not occur equally across Guangzhou. Specifically, although most sub-districts and towns have witnessed an improvement from a low level of "mismatch" to a medium level of "match," these sub-districts and towns are mainly distributed in Tianhe and Huangpu. Generally, even by 2020, few sub-districts and towns reached a high level of "match" relationship between the elderly population and facilities. The percentage of these subdistricts and towns, which are mainly concentrated in the central areas and are located near Baiyun and Panyu, has slowly increased from 25.4% in 2000 to 32.4% in 2020. Finally, some policy measures regarding the spatial planning of facilities have been independently proposed for the central areas, suburban areas, and outskirts based on the specific spatiotemporal evolution characteristics of the matching relationship between the elderly population and facilities during the last two decades.

Key words: elderly population, facilities for the elderly, matching relationship, spatiotemporal evolution, Guangzhou

CLC Number: 

  • D669.6