Estimation of Health Status Inequalities from Prevalence Data: A Risky Business

Alberto Palloni, University of Wisconsin at Madison
Jason R. Thomas, University of Wisconsin at Madison

Assessing the impact that socioeconomic determinants have on the prevalence of certain chronic conditions reported by respondents in population surveys must confront two problems. The first is that the self-reports could be in error (false positive and false negatives). The second is that those reporting are a selected sample of those who ever experience the problem, the selection being heavily influenced by excess mortality due to the condition being reported. In this paper we use a combination of empirical data and microsimulation to (a) assess the magnitude of the biases due to the reporting and selection problems and (b) suggests adjustment procedures that correct for the biases.