Measuring global health inequalities: the Gini, Theil and Slope inequality index for 291 diseases and injuries and 76 risk factors

Article type
Authors
von Philipsborn P1, Steinbeis F2, Gotham D3, Bender ME4, Matthiessen C5, Sauter C6, Tinnemann P7
1Technische Universät München and Universities Allied for Essential Medicines (UAEM), Germany
2Charité Universitätsmedizin Berlin and Universities Allied for Essential Medicines (UAEM), Germany
3Imperial College London, and Universities Allied for Essential Medicines (UAEM), United Kingdom
4Charité Universitätsmedizin Berlin, and Universities Allied for Essential Medicines (UAEM), Germany
5University of Copenhagen, and Universities Allied for Essential Medicines (UAEM), Denmark
6Universität Bonn, Germany
7Charité Universitätsmedizin Berlin, Germany
Abstract
Background: Numerous health care initiatives, including Cochrane, aim to reduce global health inequalities. Knowledge about the contribution of different diseases and risk factors and existing disparities in health status can contribute to evidence-based, equity-sensitive priority setting in research and policy-making.
Objectives: To calculate concise, comprehensive inequality measures to synthesize the vast amount of information on health inequalities provided by the Global Burden of Disease Study 2010.
Methods: We use the population-weighted Gini and Theil index to measure relative health inequalities, and the population-weighted Slope Inequality Index (SII) to measure absolute inequality, applying them to country-level disease burden data, measured in disability-adjusted life years (DALYs). The Gini index and the SSI are derived from the Lorenz Curve and the Pen's Parade, respectively (see Graphs 1 and 2), which can also be used to visualize results. All three indices have been used widely in analysis of inequality in the distribution of health outcomes.
Results: Overall relative and absolute global health inequalities increased between 1990 and 2000, but have decreased after 2000. Between 2000 and 2010, absolute inequality fell below 1990 levels, while relative inequality did not (see Graph 3). Cause groups that drove the rise in global inequality between 1990 and 2000 were HIV, interpersonal violence, and road traffic injuries. Overall, communicable, maternal, neonatal and nutritional disorders (Gini = 0.583), as well as injuries (Gin i= 0.302) contribute more to existing inequalities than non-communicable diseases (Gini = 0.172) (see Graph 4), with considerable variance within these groups. In 2010, relative global health inequalities among women (Gini = 0.318) were considerably larger than among men (Gini = 0.285).
Conclusions: While global health inequality has decreased since 2000, overall levels remain high, with a marked variance amongst different health conditions and risk factors. Increased attention for those conditions and risk factors that contribute most to existing global health inequalities may be warranted.