Compare methods

	Oaxaca-Blinder Health Decomposition	Theil Index for Health Inequality
Field	Social Epidemiology	Social Epidemiology
Family	Regression model	Process / pipeline
Year of origin	1973	2008
Originator	Ronald Oaxaca; Alan Blinder (health extension popularized by Fairlie and others)	Henri Theil (entropy index); Sam Harper & John Lynch; Luisa Borrell & Makram Talih (health-disparity applications)
Type	Regression-based decomposition of a between-group mean gap in a health outcome	Entropy-based decomposable index of inequality applied to health disparities
Seminal source	Oaxaca, R. (1973). Male-Female Wage Differentials in Urban Labor Markets. International Economic Review, 14(3), 693-709.	Harper, S., Lynch, J., Meersman, S. C., Breen, N., Davis, W. W., & Reichman, M. E. (2008). An Overview of Methods for Monitoring Social Disparities in Cancer with an Example Using Trends in Lung Cancer Incidence by Area-Socioeconomic Position and Race-Ethnicity, 1992-2004. American Journal of Epidemiology, 167(8), 889-899.
Aliases	Blinder-Oaxaca Decomposition for Health Inequalities, Threefold Decomposition of Health Disparities, Detailed Decomposition of Health Gaps, Nonlinear Oaxaca-Blinder for Binary Health Outcomes	Theil Index, Theil's T, Theil Entropy Index of Health Disparity, Symmetrized Theil Index
Related	4	4
Summary	The Oaxaca-Blinder decomposition partitions the mean difference in a health outcome between two groups into a portion explained by differences in their measured characteristics and a residual, unexplained portion attributed to differences in how those characteristics translate into health. Developed independently by Ronald Oaxaca (1973) and Alan Blinder (1973) to study labor-market wage gaps, the method was imported into social epidemiology to quantify, for example, how much of a Black-White, urban-rural, or rich-poor gap in self-rated health, BMI, hypertension, or mortality is accounted for by differences in socioeconomic exposures versus differences in returns to those exposures. Group-specific regressions are estimated, the gap in fitted means is written as a function of mean covariates and coefficients, and that gap is algebraically split into an explained (composition) component and an unexplained (coefficient) component, each of which can be further decomposed variable by variable.	The Theil index is an entropy-based measure of inequality, adapted from information theory, that quantifies how disproportionately a quantity is distributed across groups - and in social epidemiology it measures how unequally ill health (or its burden) is shared across population subgroups defined by race-ethnicity, area socioeconomic position, or other categories. Its defining advantage over simpler disparity measures is additive decomposability: total inequality splits cleanly into a between-group component and a within-group component, so analysts can ask how much overall health disparity is due to differences among, say, racial groups versus differences among areas inside those groups. Harper, Lynch, and colleagues' 2008 American Journal of Epidemiology overview placed the Theil index among the recommended summary measures for monitoring social disparities in health, illustrating it with trends in U.S. lung-cancer incidence. Borrell and Talih's 2011 Statistics in Medicine paper introduced a symmetrized version that removes the standard index's dependence on which group is treated as the reference and derived its variance for complex survey data. Because it is reference-free, decomposable, and population-weighted, the Theil index is well suited to multi-group, nested disparity analysis where ordered-rank measures like the concentration index do not apply.