 In the field of multidimensional inequality or poverty measurement, a key divide has separated the measures that evaluate the distribution in every dimension (such as income, health, asset deprivation...) before they aggregate over the dimensions, from the measures that first evaluate individual situations, all dimensions included, before aggregating over individuals. The latter has been praised (Decancq and Lugo 2013) for being closer to the standard individualistic approach in welfare economics, and for making it possible to have measures that are sensitive to the correlation between disadvantages (e.g., the positive correlation between income and health), and therefore more accurately record the multidimensional suffering of the worst off. An interesting feature of such measures is that a positive correlation among attributes of advantage or disadvantage worsens inequalities only if the elasticity of substitution between attributes, in the measure of individual multidimensional advantage, is greater than the inequality aversion in the social index. To illustrate, consider two canonical distributions, with two individuals and two attributes: