A 1-km resolution dataset of affordability-constrained accessibility to elderly care facilities in China

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.