Abstract
Approaches to measuring health inequalities are often problematic because they use methods that are inappropriate for categorical data. In this paper we focus on “pure” or univariate health inequality (rather than income-related or bivariate health inequality) and use a concept of individual status that allows a consistent treatment of such data. We take alternative versions of the status concept and apply methods for treating categorical data to examine self-assessed health inequality for the countries included in the World Health Survey. We also use regression analysis on the apparent determinants of these health inequality estimates. We show that the status concept that is used will affect health-inequality rankings across countries and the way health inequality is related to countries’ median health, income, demographics and governance.
Highlights
Measuring health inequality presents challenges that are distinct from the standard problem of measuring income or wealth inequality
Does the concept of status matter empirically when comparing self-assessed health (SAH)-inequality across countries? We address this question in three ways: a graphical approach, correlations of country ranks and regression analysis. 4.1 A graphical approach It is well known that, if the underlying Lorenz curves for two distributions A and B intersect, computing the Generalised Entropy (GE) index (4) for different values of the sensitivity parameter α can lead to different conclusions about whether A is more unequal than B
A similar effect appears in Fig. 1 which shows the geographical pattern of SAH-inequality using Iα(s), the inequality index for categorical data in the case of downward-looking status
Summary
Measuring health inequality presents challenges that are distinct from the standard problem of measuring income or wealth inequality. The challenges principally lie in the measurement of health itself: health cannot be assumed to be directly and unambiguously observable and it may not make sense to treat it as though it were a cardinal variable. As a consequence one has to use indirect methods that may involve elicitation of a person’s self-assessed health (SAH) status, or explicit modelling using observables that are thought to be related to health. The purpose of this paper is to examine approaches to inequality measurement in the health context and the ways different assumptions about health status affect inequality comparisons
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