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Measuring global health inequity.

Reidpath DD, Allotey P - Int J Equity Health (2007)

Bottom Line: 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.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Centre for Public Health Research, Brunel University, Uxbridge, UK. daniel.reidpath@brunel.ac.uk.

ABSTRACT

Background: 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.

Method: 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).

Results: 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.

Conclusion: 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.

No MeSH data available.


Related in: MedlinePlus

The Lorenz curve of the global distribution of health (DALYs) by WHO mortality sub-region.
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Figure 1: The Lorenz curve of the global distribution of health (DALYs) by WHO mortality sub-region.

Mentions: The magnitude of the is demonstrable in a number of ways, with the Lorenz curve being one of the better known illustrations (Figure 1). The curve is fitted directly to the data points and hence the lack of deviation. Having ordered the WHO sub-regions according to their DALYs per capita burden, the Lorenz curve shows the proportion of global DALYs that are accounted for, by any given proportion of the world's population. Under conditions of equality (i.e., DALYs per capita are equal for each mortality sub-region), one would observe 10% of the DALYs accounted for by 10% of the world's population, 20% of the DALYs accounted for by 20% of the world's population, and so on. This line of equality appears as the straight (dotted) line. The degree to which the actual data (the solid line) deviate from the line of equality illustrates the degree to which poor heath is unequally distributed across the mortality sub-regions.


Measuring global health inequity.

Reidpath DD, Allotey P - Int J Equity Health (2007)

The Lorenz curve of the global distribution of health (DALYs) by WHO mortality sub-region.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2147004&req=5

Figure 1: The Lorenz curve of the global distribution of health (DALYs) by WHO mortality sub-region.
Mentions: The magnitude of the is demonstrable in a number of ways, with the Lorenz curve being one of the better known illustrations (Figure 1). The curve is fitted directly to the data points and hence the lack of deviation. Having ordered the WHO sub-regions according to their DALYs per capita burden, the Lorenz curve shows the proportion of global DALYs that are accounted for, by any given proportion of the world's population. Under conditions of equality (i.e., DALYs per capita are equal for each mortality sub-region), one would observe 10% of the DALYs accounted for by 10% of the world's population, 20% of the DALYs accounted for by 20% of the world's population, and so on. This line of equality appears as the straight (dotted) line. The degree to which the actual data (the solid line) deviate from the line of equality illustrates the degree to which poor heath is unequally distributed across the mortality sub-regions.

Bottom Line: 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.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Centre for Public Health Research, Brunel University, Uxbridge, UK. daniel.reidpath@brunel.ac.uk.

ABSTRACT

Background: 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.

Method: 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).

Results: 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.

Conclusion: 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.

No MeSH data available.


Related in: MedlinePlus