In view of the impact of extreme temperatures on physical and psychological health, particularly in urban areas, several studies have focused on assessing social vulnerability using quantitative indexing approaches with the aim of creating a heat vulnerability index (HVI). In this context, this study employs three statistical methodologies frequently used to construct HVIs on the territory of the Toulouse Métropole, France, at the census block (IRIS) scale to assess the efficiency of this type of approach for evaluating social vulnerability in urban environments considering the current theoretical conceptualization. The three HVIs show the same general trends, with a spatial configuration in which high levels of vulnerability are concentrated in the downtown and suburbs of the Toulouse municipality. Vulnerability gradually decreases away from the urban core, becoming moderate in the inner suburbs and low on the outskirts. However, a spatial analysis of the clusters reveals variability in the boundaries of the vulnerability hotspots. Value class matching indicates that a significant number of census blocks are classified differently according to the method considered. These results raise questions concerning the ability of HVIs to provide reliable vulnerability assessments, given their geostatistical and conceptual limitations. Indexing approaches therefore appear to contradict current theoretical conceptualizations promoting the concept of vulnerability as being complex and multifactorial.