China’s rapid population aging presents profound challenges for equitable institutional elderly care. Traditional spatial accessibility metrics typically neglect affordability constraints, leading to systematic overestimation of effective access for low-income older adults. We developed a national, 1-km resolution accessibility dataset for mainland China using an affordability-constrained Gaussian two-step floating catchment area (AC-Ga2SFCA) method that couples travel-time impedance with price–income affordability weighting. Household payment capacity is represented by a high-resolution per capita disposable income surface downscaled from county statistics, and facility contributions are down-weighted according to fees. Across multiple travel-time catchments, the dataset provides three complementary raster layers—baseline accessibility (spatial reachability), affordability-constrained accessibility (effective access), and the accessibility gap (affordability-driven exclusion)—for both total beds and nursing-care beds, alongside administrative summaries and inequality metrics. Technical validation shows strong performance of the income downscaling model (R2 = 0.889) and near-proportional agreement between OSRM travel times and three commercial routing services. The dataset supports reproducible assessment of spatial equity, identification of service–demand mismatches, and scenario-based planning for long-term care provision.
Wang et al. (Sat,) studied this question.