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Measuring global health inequity

Overview of attention for article published in International Journal for Equity in Health, October 2007
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Title
Measuring global health inequity
Published in
International Journal for Equity in Health, October 2007
DOI 10.1186/1475-9276-6-16
Pubmed ID
Authors

Daniel D Reidpath, Pascale Allotey

Abstract

Notions of equity are fundamental to, and drive much of the current thinking about global health. Health inequity, however, is usually measured using health inequality as a proxy - implicitly conflating equity and equality. Unfortunately measures of global health inequality do not take account of the health inequity associated with the additional, and unfair, encumbrances that poor health status confers on economically deprived populations. Using global health data from the World Health Organization's 14 mortality sub-regions, a measure of global health inequality (based on a decomposition of the Pietra Ratio) is contrasted with a new measure of global health inequity. The inequity measure weights the inequality data by regional economic capacity (GNP per capita). The least healthy global sub-region is shown to be around four times worse off under a health inequity analysis than would be revealed under a straight health inequality analysis. In contrast the healthiest sub-region is shown to be about four times better off. The inequity of poor health experienced by poorer regions around the world is significantly worse than a simple analysis of health inequality reveals. By measuring the inequity and not simply the inequality, the magnitude of the disparity can be factored into future economic and health policy decision making.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 132 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Serbia 1 <1%
South Africa 1 <1%
Unknown 130 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 18%
Student > Master 19 14%
Student > Ph. D. Student 17 13%
Student > Postgraduate 9 7%
Professor 9 7%
Other 32 24%
Unknown 22 17%
Readers by discipline Count As %
Medicine and Dentistry 33 25%
Social Sciences 29 22%
Economics, Econometrics and Finance 8 6%
Nursing and Health Professions 6 5%
Psychology 6 5%
Other 18 14%
Unknown 32 24%