As discussed in many places, the pattern whereby the rarer an outcome the greater tends to be the relative difference in experiencing it and the smaller tends to be the relative difference in avoiding it can be illustrated with virtually any data set that allows one to examine various points on a continuum of factors associated with experiencing an outcome.The pattern (and related patterns discussed in the Scanlan’s Rule page are illustrated with hypothetical test score data in Table 1 of the BSPS 2006 presentation (and the tables and figures of many other presentations found here), with NHANES data on blood pressure and folate level in the figure ofICHPS 2008 presentation and the table on the NHANES Illustrations sub-page of the Scanlan’s Rule page (SR), life table information in the tables of the Life Tables Illustrations sub-page of SR, and information from the Framingham Studies on the Framingham Illustrations sub-page of SR.One of the most readily available types of data illustrating these patterns is published income data showing proportions of different demographic groups falling below various percentages of the population, and hence demonstrating how lowering poverty will tend to increase relative differences in rates of avoiding poverty and reduce relative differences in rates of avoiding poverty, while increasing poverty will tend to have the opposite effects.
In addition to underlying some of the earliest illustrations of these patterns (e.g., The “feminization of poverty” is misunderstood (Plain Dealer 1987), The perils of provocative statistics (Public Interest 1991), such data underlie the table and figures in Can we actually measure health disparities? (Chance 2006).The table from article is reproduced below.The figures, which do not reproduce well on this page, can be viewed in the article.As with all of the other illustrations of patterns of correlations between the overall prevalence of an outcome and measures of differences between rates of experiencing or avoiding the outcome, one must keep in mind that observed patterns are function of both the prevalence of an outcome and the differences between the underlying distributions (as well as irregularities in the distributions.