Utility and limitations of measures of health inequities: a theoretical perspective

box What is already known on this subject? Various measures have been used in quantifying health inequities among populations in recent times; most of these measures were derived to capture the socioeconomic inequalities in health. These different measures do not always lend themselves to common interpretation by policy makers and health managers because they each reflect limited aspects of the concept of health inequities. What does this study add? To inform a more appropriate application of the different measures currently used in quantifying health inequities, this article explicates common theories underlying the definition of health inequities and uses this understanding to show the utility and limitations of these different measures. It also suggests some key features of an ideal indicator based on the conceptual understanding, with the hope of influencing future efforts in developing more robust measures of health inequities. The article also provides a conceptual 'product label' for the common measures of health inequities to guide users and 'consumers' in making more robust inferences and conclusions. This paper examines common approaches for quantifying health inequities and assesses the extent to which they incorporate key theories necessary for explicating the definition of health inequity. The first theoretical analysis examined the distinction between inter-individual and inter-group health inequalities as measures of health inequities. The second analysis considered the notion of fairness in health inequalities from different philosophical perspectives. To understand the extent to which different measures of health inequities incorporate these theoretical explanations, four criteria were used to assess each measure: 1) Does the indicator demonstrate inter-group or inter-individual health inequalities or both; 2) Does it reflect health inequalities in relation to socioeconomic position; 3) Is it sensitive to the absolute transfer of health (outcomes, services, or both) or income/wealth between groups; 4) Could it be used to capture inequalities in relation to other population groupings (other than socioeconomic status)? The measures assessed include: before and after measures within only the disadvantaged population, range, Gini coefficient, Pseudo-Gini coefficient, index of dissimilarity, concentration index, slope and relative indices of inequality, and regression techniques. None of these measures satisfied all the four criteria, except the range. Whereas each measure quantifies a different perspective in health inequities, using a measure within only the disadvantaged population does not measure health inequities in a meaningful way, even using before and after changes. For a more complete assessment of how programs affect health inequities, it may be useful to use more than one measure.