A Simulation Study of Health Disparity Indexes: How Do They Depend on Prevalence?

• Activity Number: 315
• Type: Contributed
• Date/Time: Tuesday, August 4, 2009 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Stuart Gansky*+ and Nancy F. Cheng and Gloria Mejia
• Companies: University of California, San Francisco and University of California, San Francisco and University of California, San Francisco
• Keywords: inequality ; Gini index ; Theil's index ; probit ; health concentration index ; Taylor series linearization

Abstract

The National Center for Health Statistics recommends using health disparities indices (HDIs). Some authors claim all HDIs are prevalence dependent. In a recent simulation we showed only some HDIs depend on prevalence (Cheng et al. 2008). That simulation varied prevalence conditional on odds ratio (i.e. logit model). This more in-depth investigation studied how HDIs are affected by underlying factors conditional on prevalence difference (i.e. probit model). HDIs were estimated for the California Oral Health Needs Assessment 2004, a complex survey, to assess associations with untreated caries. Absolute measure, slope index of inequality, relative index of inequality (RII-mean), and absolute concentration index (ACI) were prevalence invariant with constant prevalence difference in a probit simulation model; relative measures depended on prevalence. Support: USDHHS NIH/NIDCR R03DE018116.