In This Issue

Abstract

By measuring health-related differences among subgroups within populations, we can identify areas where improvement is needed and possible. But the measures we select sometimes reflect values in ways that are not recognized by researchers or policymakers, and they may incorporate normative judgments that affect how they are interpreted and used. This is the central message of the first article in this issue, “Implicit Value Judgments in the Measurement of Health Inequalities,” by Sam Harper, Nicholas King, Stephen Meersman, Marsha Reichman, Nancy Breen, and John Lynch. Researchers can characterize health-related differences or disparities (the terms have different connotations) in a variety of ways: over time or by gender, region, race, ethnicity, or socioeconomic status within populations. Harper and his colleagues present five cases to show that the measures used or the way they are calculated can have a major effect on the nature and magnitude of differences that are found. The choices may involve measuring relative or absolute inequality or using weighted or unweighted data, to cite two of their examples. Their point is not that certain summary measures are necessarily preferable to other measures, because those used may depend on the purpose of the analysis or the characteristics of the data set. Instead, their point is that unrecognized value judgments can be built into measures of inequality. Harper and his colleagues urge researchers to be aware of the implicit value judgments involved in the choice of measures, not to use a particular measure uncritically just because it is widely accepted, and to consider carefully the implicit normative judgments that may be embedded in any particular measure. They also urge researchers to strive for transparency and to be explicit about the judgments used in choosing the measure. The authors also advise policymakers and other users of information about health-related inequalities to consider carefully the measures used and to use more than one whenever possible.