Abstract
This study examines spatial patterns of healthcare expenditure, discrimination, aging-related vulnerability, and socio-economic disadvantage among older adults in India, with focus on Northeast. Using 21 indicators from different datasets, Global Moran's I and LISA assessed spatial clustering. All-India results show significant positive spatial autocorrelation for healthcare expenditure and vulnerability indicators, while Northeast India shows no significant global autocorrelation, though LISA reveals recurring High-Low discrimination clusters. Northeast India exhibits lower healthcare expenditure, greater variability, and heightened poverty, aging, and discrimination related vulnerabilities. Findings highlight geographic and socio-economic disparities, informing targeted gerontological social work, pension linkage, anti-ageist advocacy, and equitable aging policy.