# Spatial distribution and the imbalance between supply and demand: an analysis of the geographical characteristics and regional differences of elderly care institutions in China

## TL;DR

This study analyzes the uneven distribution of elderly care institutions in China and identifies key factors influencing their spatial patterns.

## Contribution

The novel use of ArcGIS and OPGD methods reveals new insights into the spatial imbalance and drivers of elderly care resource allocation in China.

## Key findings

- ECIs show a 'dense southeast–sparse northwest' pattern aligned with the Hu Huanyong Line.
- Population size and hospital beds are the main factors influencing ECI distribution.
- Medical-care integration and government investment significantly affect resource allocation.

## Abstract

Against the backdrop of China’s continuously intensifying population aging, the spatially balanced distribution of elderly care institutions (ECIs) has emerged as a critical issue for alleviating elderly care pressure and advancing social equity. Utilizing nationally registered ECI data, this study integrates ArcGIS spatial analysis with an Optimal-Parameter Geographical Detector (OPGD) approach to systematically investigate the spatial heterogeneity, supply-demand imbalance patterns, and underlying formation mechanisms of ECIs in China at the provincial level. A key finding is the pronounced spatial and structural imbalance between supply and demand. Kernel density estimation reveals a multi-level clustering structure centered on Shanghai and Chongqing, while the consistency coefficient identifies distinct mismatch patterns: regions such as Xinjiang and Northeast China experience “supply exceeding demand,” whereas economically dynamic areas like the Pearl River Delta face “supply falling behind demand.” Spatially, ECIs overall follow a “dense southeast–sparse northwest” pattern closely aligned with the “Hu Huanyong Line,” with six provinces including Henan and Sichuan accounting for 34.1% of institutions, compared to only 1.6% in four western provinces/regions and Hainan. Furthermore, OPGD analysis identifies the permanent population size and number of hospital beds as the dominant factors influencing the spatial layout of ECIs. Their interaction with public transportation accessibility and fiscal expenditure significantly enhances explanatory power, highlighting the crucial role of medical-care integration and government investment in resource allocation. This study provides a scientific basis for optimizing the spatial allocation of elderly care resources and promoting coordinated regional development in China.