Slums are examples of localized communities within third-world urban systems representing a range of vulnerabilities and adaptive capacities. This study examines vulnerability in relation to flooding, environmental degradation, social status, demographics, and health in the slums of Accra, Ghana, by utilizing a place-based approach informed by fieldwork, remote sensing, census data, and geographically weighted regression (GWR). The study objectives are threefold: (1) to move slums from a dichotomous into a continuous classification and examine the spatial patterns of the gradient, (2) to develop measures of vulnerability for a developing world city and model the relationship between slums and vulnerability, and (3) to assess if the most vulnerable individuals live in the worst slums. A previously developed slum index is utilized, and four new measures of vulnerability are developed through principal components analysis (PCA), including a novel component of health vulnerability based on child mortality. Visualizations of the vulnerability measures assess spatial patterns of vulnerability in Accra. Ordinary least squares (OLS), spatial, and GWR model the ability of the slum index to predict the four vulnerability measures. The slum index performs well for three of the four vulnerability measures, but is least able to predict health vulnerability, underscoring the complex relationship between slums and child mortality in Accra. Finally, quintile analysis demonstrates the elevated prevalence of high vulnerability in places with high slum index scores.