Summary Measures of Disparity for Domains with Ordered Categories

Reviews
Shared by: Emily Emric
Stats
views:
17
rating:
not rated
reviews:
0
posted:
6/7/2009
language:
English
pages:
0
Summary Measures of Disparity for Domains with Ordered Categories National Center for Health Statistics Centers for Disease Control and Prevention Elsie Pamuk Measurement of disparity allows comparisons:    Across health indicators Between or across populations Over time Focus of attention?  Individual groups • Comparing single groups to a reference point  A domain • Summarizing disparity across all groups constituting a conceptual domain Definition of “domain” A domain consists of the entire set of population groups that are based on one or more characteristics of persons in a population Why focus on the domain, rather than the groups?  The groups are not inherently meaningful  The groups are inherently meaningful, but so is the defining aspect of the domain Distinction between ordered and unordered domains – for inherently ordered domains, the primary focus is usually on the domain itself, rather than the component groups. Whenever the focus is on the domain, it is appropriate to combine information from the component groups and create a summary measure of disparity. Domains with ordered categories  Socioeconomic status (SES) • Income • Education • Wealth • Occupational status  Other • Urbanization Asthma rates for children <18 years of age, NHIS 1998-2003 10 9 8 7 6 5 4 3 2 1 0 <100% 100200%- 400%+ <200% <400% <100% 100200%- 400%+ <200% <400% White Black 9.1 7.5 6.5 7.2 7.1 5.3 5.2 4.9 White % of population .10 .18 .36 .36 Black % of population .35 .26 .27 .13 % with asthma episode 9.1 7.5 6.5 7.2 1.9 1.26 Income <100% 100<200% 200<400% 400%+ % with asthma episode 7.1 5.3 5.2 4.9 2.2 1.45 Lowest - Highest = = Lowest / Highest Common characteristics of summary measures of health disparities related to SES    Use information from all of the component groups Preserve the inherent ordering of the groups Incorporate the size of the groups Regression-based measures 10 9 8 7 6 5 4 3 2 1 0 0 Percent of White Children with Asthma by Income (as a percent of poverty) <100% 100 < 200% 200 - <400% 400%+ 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Cumulative proportion of population 10 9 8 7 6 5 4 3 2 1 0 0 Percent of White Children with Asthma by Income (as a percent of poverty) <100% 100 < 200% 200 - <400% 400%+ 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Cumulative proportion of population 10 9 8 7 6 5 4 3 2 1 0 0 Percent of White Children with Asthma by Income (as a percent of poverty) <100% 100 < 200% 200 - <400% 400%+ 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Cumulative proportion of population Percent of White Children with Asthma by Income (as a percent of poverty) 10 9 8 7 6 5 4 3 2 1 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 100 < 200% <100% Slope Index of Inequality SII = b = -1.7 200 - <400% 400%+ Cumulative proportion of population Percent of White Children with Asthma by Income (as a percent of poverty) 10 9 8 7 6 5 4 3 2 1 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 100 < 200% <100% Slope Index of Inequality SII = b = -1.7 = (6.1-4.5) 200 - <400% 400%+ Cumulative proportion of population Regression based measures of disparity SII = b = (y at x=1) – (y at x=0) RII (mean) = SII/mean of y mean of y = population value of y Or RII (ratio) = (y at x=1) / (y at x=0) Percent of White Children with Asthma by Income (as a percent of poverty) 10 9 8 7 6 5 4 3 2 1 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 100 < 200% <100% Mean of y = 5.3 RII (mean) = -.32 = (-1.7/5.3) RII (ratio) = 1.4 = (6.1/4.5) 200 - <400% 400%+ Cumulative proportion of population Percent of Black Children with Asthma by Income (as a percent of poverty) 10 9 8 7 6 5 4 3 2 1 0 0 SII = -3.4 RII (mean) = -.44 RII (ratio) = 1.6 <100% 100 - < 200% 200 - < 400% 400%+ 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Cumulative proportion of population White % of population .10 .18 .36 .36 -1.7 -.32 1.4 Black % of population .35 .26 .27 .13 -3.4 -.44 1.6 % with asthma episode 9.1 7.5 6.5 7.2 Income <100% 100<200% 200<400% 400%+ % with asthma episode 7.1 5.3 5.2 4.9 SII RII (mean) RII (ratio) Concentration Indices CONCENTRATION INDEX 1 0.9 0.8 0.7 Cumulative proportion of Black children with asthma C = -.07 0.6 0.5 0.4 0.3 0.2 0.1 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Cumulative proportion of Black children by family income level <100% 100-<200% 200-<400% 400%+ CONCENTRATION INDEX 1 0.9 0.8 0.7 Cumulative proportion of White children with asthma C = -.05 0.6 0.5 0.4 0.3 0.2 0.1 0 0 <100% 100<200% 200-<400% 400%+ 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Cumulative proportion of White children by family income level White % of population .10 .18 .36 .36 -1.7 -.32 1.4 Black % of population .35 .26 .27 .13 -3.4 -.44 1.6 % with asthma episode 9.1 7.5 6.5 7.2 Income <100% 100<200% 200<400% 400%+ % with asthma episode 7.1 5.3 5.2 4.9 SII RII (mean) RII (ratio) C -.05 -.07 Conversion between C and RII C = 2 cov(x,y)/m SII = cov(x,y)/var(x) and, RII = SII/m = [cov(x,y)/var(x)]/m so, C = 2 var(x)(RII) Practical considerations when choosing methods to summarize SES disparities in health  Graphical presentation Ease of computation / statistics  Percent of children with no health care visit in the past year, NHIS 1990 and 2003 1990 Income <100% 100-<200% 200%+ Lowest - Highest Lowest / Highest % of population .17 .26 .57 % with no MD visit 23.2 22.0 14.9 8.3 1.56 2003 % of population .16 .22 .62 % with no MD visit 12.2 13.0 8.1 4.1 1.51 Percent of children with no health care visit in the past year, NHIS 1990 and 2003 1990 Income <100% 2003 % with no MD visit 23.2 % of population .17 % of population .16 % with no MD visit 12.2 100<200% 200%+ SII RII (mean) RII (ratio) C .26 .57 22.0 14.9 -14.46 -.80 2.3 -.105 .22 .62 13.0 8.1 -8.9 -.91 2.7 -.110 Making decisions on how to measure disparity  Who is the audience?  What is the purpose and scope of the exercise? Argument for weighting summary measures of disparity for SES domains:  The essentially arbitrary nature of the categories  Categories differ by amount, rather than type Distributions can be influenced by policy 

Related docs
premium docs
Other docs by Emily Emric