Search results

Most politicians and ethical observers are not interested in pure health inequalities, as they want to distinguish between different causes of health differences. Measures of “unfair” inequality – direct unfairness and the fairness gap, but also the popular standardized concentration index (CI) – therefore neutralize the effects of what are considered to be “legitimate” causes of inequality. This neutralization is performed by putting a subset of the explanatory variables at reference values, for example, their means. We analyze how the inequality ranking of different policies depends on the specific choice of reference values. We show with mortality data from the Netherlands that the problem is empirically relevant and we suggest a statistical method for fixing the reference values.

What change in the distribution of a population’s health preserves the level of inequality? The answer to this analogous question in the context of income inequality lies somewhere between a uniform and a proportional change. These polar positions represent the absolute and relative inequality equivalence criterion (IEC), respectively. A bounded health variable may be presented in terms of both health attainments and shortfalls. As a distributional change cannot simultaneously be proportional to attainments and to shortfalls, relative inequality measures may rank populations differently from the two perspectives. In contrast to the literature that stresses the importance of measuring inequality in attainments and shortfalls consistently using an absolute IEC, this chapter formalizes a new compromise concept for a bounded variable by explicitly considering the two relative IECs, defined with respect to attainments and shortfalls, to represent the polar cases of defensible positions.

We use a surplus-sharing approach to provide new insights on commonly used inequality indices by evaluating the underpinning IECs in terms of how infinitesimal surpluses of health must be successively distributed to preserve the level of inequality. We derive a one-parameter IEC that, unlike those implicit in commonly used indices, assigns constant weights to the polar cases independent of the health distribution.

In this chapter we explore different ways to obtain decompositions of rank-dependent indices of socioeconomic inequality of health, such as the Concentration Index. Our focus is on the regression-based type of decomposition. Depending on whether the regression explains the health variable, or the socioeconomic variable, or both, a different decomposition formula is generated. We illustrate the differences using data from the Ethiopia 2011 Demographic and Health Survey (DHS).

The purpose of this paper is to assess the trends of socioeconomic-related inequalities in maternal healthcare utilization in Ghana between 2003 and 2014 and examine the causes of inequalities in maternal healthcare utilization in Ghana.

Data are drawn from three rounds of the Ghana Demographic and Health Survey collected in 2003, 2008 and 2014, respectively. The authors employ two alternative measures of socioeconomic inequalities in health – the Wagstaff and Erreygers indices – to examine the trends of socioeconomic inequalities in maternal healthcare utilization. The authors proceed to decompose the causes of inequalities in maternal healthcare by applying a recently developed generalized decomposition technique based on recentered influence function regressions.

The study finds substantial pro-rich inequalities in maternal healthcare utilization in Ghana. The degree of inequalities has been decreasing since 2003. The elimination of user fees for maternal healthcare has contributed to achieving equity and inclusion in utilization. The decomposition analysis reveals significant contributions of individual, household and locational characteristics to inequalities in maternal healthcare. The authors find that educational attainment, urban residence and challenges with physical access to healthcare facilities increase the socioeconomic gap in maternal healthcare utilization.

There is a need to target vulnerable women who are unlikely to utilize maternal healthcare services. In addition to the elimination of user fees, there is a need to reduce inequalities in the distribution and quality of maternal health services to achieve universal coverage in Ghana.