Dear Editor

Studies of changing inequalities in receipt of procedures like that carried out with respect to revascularization by Hetemaa et al.[1] need to be undertaken with an appreciation of the statistical tendency whereby the rarer an outcome the greater the relative difference in rates of experiencing it and the smaller the relative difference in rates of avoiding it.[2-6]

Most research into inequality in the health arena examines morbidity and mortality. Typically these are examined in terms of relative differences in experiencing adverse outcomes. In recent decades most, though not all, adverse health outcomes have been declining and relative differences in experiencing them have been increasing. Generally these increases have been regarded as reflecting meaningful worsening of the relative situation of disadvantaged groups, but without recognition of the extent to which such increases may be solely the consequences declining prevalence of the outcomes or recognition that relative differences in experiencing the opposite outcome may be declining. Whether the observed patterns of changing relative differences are more than or less than those that would be expected to flow solely from declines in the prevalence of the outcome has gone unexamined, though it is not clear that there are effective tools to answer such questions.[2,6]

Research into inequalities in the receipt of beneficial procedures, on the other hand, has generally examined rates of experiencing the favorable outcome (i.e., receipt, rather than denial, of the procedure). Because rates of receiving these procedures usually have been increasing, relative differences in rates of receiving them have been declining, though relative rates of failing to receive them have been increasing. A greater increase in rates of receiving the procedure experienced by groups with lower baseline rates of receiving the procedures (relative to proxy for need), such as that found in the study by Hetemaa et al., is a corollary to this pattern, as is a smaller decrease in rates of failing to receive the procedure. Table 1 in the study provides many illustrations of the pattern. For example, the overall female rate of receiving revascularization procedures increased 71 percent more than the male rate (a 317% increase for women compared with a 186% increase for men), but the female rate of failing to receive the procedure declined by 22 percent less than the male rate (a 20% decline for women compare with 26% decline for men). Correspondingly the relative difference in rates of receiving the procedure decreased while the relative difference in rates of failing to receive the procedure increased.

The authors note an expectation of declining inequality based on what has been observed in other situations where there occurred an increased supply of coronary revascularization procedures. Yet, the pattern of declining relative differences in receipt of procedures, not only for revascularization but for all procedures that are increasing, is generally to expected to occur solely as a result of the increase in supply, as is an increase in the relative difference in failing to receive the outcome. Whether either change reflects a meaningful change in inequalities – i.e., one that is not solely a consequence of the increasing availability of the procedure – requires a closer examination. Again, however, it is not clear that there exist effective tools for doing so.

The above-described tendency is pertinent not only to comparisons of changes over time, but to all comparisons of relative differences in settings with differing overall frequencies of an outcome. The authors note smaller relative differences in procedures in districts where the procedures are more common and larger relative differences among persons over 70 (where procedure are rarer). This pattern is to be expected simply because of the differing frequencies of the procedures in the different settings. And one would likely find the reverse pattern if one examined rates of failing to receive the procedure.

That is not to say that these patterns will be observed with respect to every comparison of the size of relative differences in varying temporal, demographic, or geographic settings. For factors other than the referenced statistical tendency are at work as well. Nevertheless, one cannot evaluate those factors without appreciation of the purely statistical aspects of the observed patterns.

In the United States, citing the receipt or non-receipt of mammography as an example, the National Center for Health Statistics (NCHS) recently recognized that the size and the patterns of change in health inequalities may turn on whether one examines the favorable or the adverse outcome.[7] It recommended that all relative differences between groups be measured in terms of adverse outcomes. If the recommendation is followed, in many situations where relative differences were perceived to be declining – as, for example, in the case of male-female revascularization rates in Finland – the differences would instead be perceived to be increasing. But NCHS has yet to acknowledge that relative differences in rates of experiencing favorable and adverse outcomes tend to change systematically in opposite directions as the prevalence of each outcome changes or to suggest a means of identifying changes in inequality that are not solely the consequence of changes in prevalence.

One might think that the NCHS focus on adverse outcomes would be especially inappropriate for something like revascularization, since, even among those hospitalized for cardiac heart disease, revascularization is not appropriate for everyone. The point, however, is that the value of health inequality studies lies in identifying changes that are not solely the result of changes in prevalence. Neither changes in relative differences in receipt of procedures nor changes in relative differences in denial of procedures – nor changes in absolute differences (which here favored men)[2,6] – seem to serve that purpose.

James P. Scanlan

References

1. Hetemaa T, Keskimäki I, Manderbacka, et al. How did the recent increase in the supply or coronary operations in Finland affect socioeconomic and gender equity in their use? J Epidemiol Community Health 2003;57:178-185.

2. Scanlan JP. Can we actually measure health disparities? Chance 2006:19(2):47-51: http://www.jpscanlan.com/images/Can_We_Actually_Measure_Health_Disparities.pdf.

3. Scanlan JP. Measuring health disparities. J Public Health Manag Pract 2006;12(3):294 [Lttr]: http://www.nursingcenter.com/library/JournalArticle.asp?Article_ID=641470.

4. Scanlan JP. Race and Mortality. Society. 2000;37(2):19-35: http://www.jpscanlan.com/images/Race_and_Mortality.pdf.

5. Scanlan JP. Divining difference. Chance. 1994;7(4):38-9,48: http://jpscanlan.com/images/Divining_Difference.pdf.

6. Scanlan JP. The misinterpretation of health inequalities in the United Kingdom. Paper presented at: British Society for Population Studies Annual Conference 2006, Southampton, England, Sept. 18-20, 2006: http://www.jpscanlan.com/images/BSPS_2006_Complete_Paper.pdf.

7. Keppel K., Pamuk E., Lynch J., et al. Methodological issues in measuring health disparities. Vital Health Stat 2005;2 (141): http://www.cdc.gov/nchs/data/series/sr_02/sr02_141.pdf.