A number of multidimensional poverty measures have recently been proposed, within counting approach framework, respecting the ordinal nature of dimensions. Besides ensuring a reduction in poverty, however, it is important to monitor distributional changes to ensure that poverty reduction has been inclusive in reaching the poorest. Distributional issues are typically captured by adjusting a poverty measure to be sensitive to inequality among the poor. This approach however has certain practical and conceptual limitations. It conflicts, for example, with some policy-relevant measurement features, such as the ability to decompose a measure into dimensions post-identification, and does not create an appropriate framework for assessing disparity in poverty across population subgroups. In this paper, we propose and justify the use of a separate decomposable inequality measurea positive multiple of 'variance' -to capture the distribution of deprivations among the poor and to assess disparity in poverty across population subgroups. We demonstrate the applicability of our approach through two contrasting inter-temporal illustrations using Demographic Health Survey (DHS) datasets for Haiti and India.