She maintains that the same ten-year female advantage in life expectancy could be observed if males lived for only ten years and that the same 50 percent male deficit could be observed if they lived for sixty years.
This problem is evident even in Asada's “single population” case, in which the respective life expectancies of ten and twenty years for men and women generate a ten-year absolute and a 50 percent relative difference for men.
The point of our article was that difficulties arise not when trying to determine whether inequalities exist(in a cross-sectional comparison), but whether some are worse than others (comparing across different populations or over time). Although this point is technically correct, it misses the larger issue. She argues that one must distinguish between “single population” and “multiple population” cases when measuring inequality, observing that in the single population cases, both absolute and relative measures “assess only inequality,” since neither provides any information about underlying levels of health. In contrast, Asada chooses a less compelling example to illustrate her argument. We certainly agree on the complexity of this issue, which is why our examples address complex cases in which absolute and relative measures disagree on the direction and magnitude of inequality trends. 2010, 22).Īsada contends that the relationship between population health and inequality is “more complex than suggested by analysis” (617). As we state in our conclusion, “Because inequality is a complex, multidimensional concept, we do not believe that there is a single, one-size-fits-all strategy for determining how best to measure and interpret health inequalities” ( Harper et al. Our point is that choosing among inequality measures always requires a normative judgment, so one cannot identify a single “best metric” without first determining what “best” means in a given situation. The seven words that Asada quotes from our article are from a rhetorical question that we used to illustrate exactly the opposite: that there are no inherently “best” metrics for assessing inequality.
#Morpheus red pill how to
2010, 22)Īsada has misread our description of the implicit value judgments embedded in some measures as a prescription for how to use those measures.Īsada also has misread the general purpose of our article, when she states that our “effort to explore the ‘best metric for assessing trends in inequality’ is commendable” (617). We thus urge researchers to avoid uncritically using a single measure (such as a rate ratio) simply because it is widely accepted practice to do so, and to consider the implicit normative judgments embedded in many measures of inequality. Researchers should recognize that relying exclusively on a single measure of health inequality may implicitly endorse normative judgments and that this endorsement is an unavoidable byproduct of the structure of those measures…. Actually, we recommend nothing of the sort. Although we appreciate her comments, we believe that they are based on a fundamental misreading of our article.Īsada claims that we recommend “that analysts use relative inequality measures when concerned only about health inequality … but use absolute inequality measures when concerned also about other issues, such as the population's overall level of health and each group's level of health” (617). We are grateful to Yukiko Asada for her commentary ( Asada 2010), as it gives us an opportunity to reiterate and clarify several points from our original article.
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