Estimating health expectancies from two cross-sectional surveys

Michel Guillot, University of Wisconsin at Madison
Yan Yu, University of Wisconsin at Madison

Health expectancy is a key indicator for monitoring the health of populations, as well as for informing debates about compression or expansion of morbidity. However, current methodologies are not entirely satisfactory. They are either of limited applicability because of high data requirements (the multistate method) or not methologically sound (the Sullivan method). This paper proposes a new method which relies on the multistate framework but uses widely available data. The idea is to use age-specific proportions healthy at two successive (but independent) cross-sectional health surveys, and, together with information on general mortality, to solve for the set of transition probabilities that produces the observed sequence of proportions healthy. The system is solved by making realistic parametric assumptions about the age patterns of transition probabilities. Using data from the Medicare Current Beneficiary Survey, the method is tested against both the Sullivan method and the goldstandard multistate method.