Despite the Millennium Developing Goals (MDGs) did not directly target reducing inequalities in health, this goal is as important as increasing coverage of health services. This paper presents an important assessment of trends in equity of reproductive and maternal health interventions.
However, the assessment of trends in inequality will be incomplete if one does not take into account both changes in absolute and relative inequalities. Conceptually, relative inequality gives an idea of how unfair the differences are, and absolute inequality indicates how much effort is needed to minimize differences or close the gap. On the other hand, mathematically speaking, it may be easier to reduce relative inequalities than absolute inequalities when intervention coverage is increasing. For example, if rich and poor groups present coverages of 40% and 20%, respectively, and coverage doubles for both groups over study time, the coverages will be 80% and 40% at endpoint. The relative inequality did not change, but absolute inequality doubled. Therefore, findings on inequality trends based solely on relative (or absolute) inequalities do not present the whole scenario.
The assessment of inequality should take into account both absolute and relative inequalities, and Barros & Victora present a framework for that (1). Apparent inconsistency of results (when relative inequality decreases while absolute inequality increases) are explained, and a graph approach is proposed in order to make sense of both values at the same time.
A clear example of the problem of having discordant measures is seen in this paper, figure 9(B): the relative inequality presented a decreasing pattern over time, but the absolute inequality is clearly increasing.
The authors briefly mentioned this issue and argued that they presented basically relative measures of inequality due to lack of space. However, using the quadrant graph (figure 5 in Barros & Victora, 2013), which plots differences on both relative and absolute inequalities across time, solves this issue in a very concise way. Additionally, using both measures is likely to change some of the conclusions of this paper.

Reference
1. Barros, A. J. D., & Victora, C. G. (2013). Measuring Coverage in MNCH: Determining and Interpreting Inequalities in Coverage of Maternal, Newborn, and Child Health Interventions. PLoS Medicine, 10(5), e1001390. http://doi.org/10.1371/jo...


Authors: Fernanda Ewerling, Fernando C Wehrmeister, Inácio C M da Silva, Aluísio J D Barros