BACKGROUND: Socio-economic inequalities in health within countries are a key public health issue. It is important that we can effectively make international comparisons of the level of inequalities and assess trends over time. We investigate how the results of such comparisons can differ depending on whether inequality is quantified using the rate ratio or rate difference. METHODS: We examine levels and trends in inequality in under-five mortality using data from 22 low/lower-middle income countries [Africa (11), Latin America/Caribbean (5), Asia (6)], each with two Demographic and Health Surveys between 1991 and 2001. Within-country inequalities are quantified using the rate ratio and rate difference. RESULTS: Ranking countries by their level of inequality at one point in time differed, sometimes substantially, according to whether the rate ratio or difference was used (Spearman's rank correlation = 0.49). Similarly, ranking countries according to the magnitude and direction of change in inequality over time depended on the measure used. Importantly from a policy perspective, in five countries the direction of change was in the opposite direction (increase vs decline in inequality) when using the ratio compared with the difference measure. CONCLUSIONS: The results of comparisons of the magnitude of health inequalities between countries and over time depend upon whether the rate ratio or rate difference is used. When statements are made comparing the size of inequalities it should be made completely clear whether these are measured on an absolute or relative scale. If the substantive conclusions differ according to the measure used this should be clearly stated. In this situation emphasis should only be given to results based on one summary measure if this can be clearly and explicitly justified in the context.

Original publication

DOI

10.1093/ije/dym176

Type

Journal article

Journal

Int J Epidemiol

Publication Date

12/2007

Volume

36

Pages

1285 - 1291

Keywords

Child, Preschool, Cross-Sectional Studies, Data Interpretation, Statistical, Demography, Global Health, Health Status, Health Status Indicators, Health Surveys, Humans, Infant, Infant, Newborn, Mortality, Socioeconomic Factors