Socio-Ecological Assessment of Elderly Primary Healthcare Accessibility in China Using the Vegetation Nighttime Condition Index and the Enhanced 2SFCA

China’s rapidly aging population poses a significant challenge to the equitable allocation of primary healthcare resources. Conventional accessibility assessments often rely solely on economic indicators, overlooking the ecological constraints that shape human settlement and service provision. To address this problem, this study proposes a socio-ecological framework integrating remote sensing data with spatial accessibility modeling. This study employs the Vegetation Nighttime Condition Index (VNCI)—a fusion of VIIRS nighttime lights and MODIS NDVI—as a proxy for human activity intensity under ecological constraints. The spatial accessibility of primary healthcare for the elderly (aged 65+) is evaluated across 31 provinces in mainland China using the Enhanced Two-Step Floating Catchment Area (2SFCA) method. Furthermore, a coupling coordination model and the Relative Development Index (RDI) are applied to examine the relative alignment between healthcare accessibility and the socio-ecological development context represented by VNCI. Empirical results reveal a distinct East–West gradient. Eastern coastal regions exhibit high accessibility; however, the coupling analysis identifies that healthcare accessibility lags behind high socio-ecological development intensity (low RDI). Conversely, western and rural regions generally suffer from a “low-level trap,” characterized by both low accessibility and weak socio-ecological coordination. The findings demonstrate that satellite-derived indices like VNCI effectively capture fine-scale human-environment interactions, offering a basis for spatially differentiated healthcare planning.