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Recent decades have witnessed a rising interest in the measurement of inequality from a multidimensional perspective. This literature has however remained largely theoretical. This chapter presents an empirical application of a recent methodology and in doing so offers practical insights on how multidimensional inequality can be measured over two attributes (wealth and health) in the developing country context. Following Abul Naga and Geoffard (2006), a methodological framework allowing the decomposition of multidimensional inequality into two univariate Atkinson–Kolm–Sen equality indices and a third term measuring the association between the attributes is implemented. The methodology is then illustrated using data from the World Health Surveys 2002–2003. Specifically, this study presents the first comparative analysis on multidimensional inequality for a set of Middle East and North African (MENA) countries. Results reveal that the multidimensional (in-)equality indices tend to mimic the (in-)equality ordering of the wealth distributions as the latter are always less equally distributed than health. An empirical conclusion that emerges is that reducing the correlation between the attributes may help to reduce overall welfare inequality, specifically when socioeconomic inequality in health is pro-poor. The finding that the correlation between attributes has a significant contribution in the quantification of inequality has important policy implications since it reveals that it is not only wealth and health inequalities per se that matter in the measurement of welfare inequality but also the associations between them.