Over the last two decades social vulnerability has emerged as a major area of study, with increasing attention to the study of vulnerable populations. Generally, the elderly are among the most vulnerable members of any society, and widespread population aging has led to greater focus on elderly vulnerability. However, the absence of a valid and practical measure constrains the ability of policy-makers to address this issue in a comprehensive way. This study developed a composite indicator, The Elderly Social Vulnerability Index (ESVI), and used it to undertake a comparative analysis of the availability of support for elderly Jamaicans based on their access to human, material and social resources. The results of the ESVI indicated that while the elderly are more vulnerable overall, certain segments of the population appear to be at greater risk. Females had consistently lower scores than males, and the oldest-old had the highest scores of all groups of older persons. Vulnerability scores also varied according to place of residence, with more rural parishes having higher scores than their urban counterparts. These findings support the political economy framework which locates disadvantage in old age within political and ideological structures. The findings also point to the pervasiveness and persistence of gender inequality as argued by feminist theories of aging. Based on the results of the study it is clear that there is a need for policies that target specific population segments, in addition to universal policies that could make the experience of old age less challenging for the majority of older persons. Overall, the ESVI has displayed usefulness as a tool for theoretical analysis and demonstrated its potential as a policy instrument to assist decision-makers in determining where to target their efforts as they seek to address the issue of social vulnerability in old age. Data for this study came from the 2001 population and housing census of Jamaica, with multiple imputation for missing data. The index was derived from the linear aggregation of three equally weighted domains, comprised of eleven unweighted indicators which were normalized using z-scores. Indicators were selected based on theoretical relevance and data availability.