High-Resolution dataset on elderly care facility accessibility and inequality in 21 Chinese cities (2020)

Area of Science:

• Urban Planning
• Public Health
• Geospatial Analysis

Background:

• China's rapidly aging population necessitates equitable elderly care access.
• Significant data gaps exist in quantifying and comparing elderly care accessibility across cities.

Purpose of the Study:

• To create a comprehensive dataset on spatial accessibility and inequality of elderly care facilities in 21 major Chinese cities.
• To address the data gap and support research in urban planning and public health.

Main Methods:

• Utilized the Gaussian Two-Step Floating Catchment Area (Ga2SFCA) method.
• Integrated facility capacity, population demand, and distance decay.
• Generated high-resolution raster files for accessibility (100m) and spatial inequality (1km Gini coefficient).

Main Results:

• Developed a dataset covering spatial accessibility and inequality for 21 major Chinese cities circa 2020.
• Validated model accuracy against commercial map services (R² > 0.94).
• Publicly released raster and tabular data for research use.

Conclusions:

• The dataset provides a crucial resource for understanding and addressing disparities in elderly care access.
• Facilitates research in urban planning, public health, transportation geography, and socioeconomics.
• Supports evidence-based policy and planning for aging populations.