Multiple inequity in health care: An example from Brazil.

Abstract The paper develops and illustrates a new multivariate approach to analysing inequity in health care. We measure multiple inequity in health care relating to multiple equity-relevant variables – including income, gender, ethnicity, rurality, insurance status and others – and decompose the contribution of each variable to multiple inequity. Our approach encompasses the standard bivariate approach as a special case in which there is only one equity-relevant variable, such as income. We illustrate through an application to physician visits in Brazil, using data from the Health and Health Care Supplement of the Brazilian National Household Sample Survey, comprising 391,868 individuals in the year 2008. We find that health insurance coverage and urban location both contribute more to multiple inequity than income. We hope this approach will help researchers and analysts shed light on the comparative size and importance of the many different inequities in health care of interest to decision makers, rather than focus narrowly on income-related inequity. Highlights • We developed methods for measuring multiple inequity in health care. • Multiple inequity relates to multiple equity-relevant variables, not just income. • We analysed multiple inequity in physician visits in Brazil using survey data. • Insurance coverage and geography contributed more to multiple inequity than income. [ABSTRACT FROM AUTHOR]