Estimating processes of counts from cross-sectional aggregate data, with an application to multistate life tables and health expectancies

This paper discusses the estimation of time-dependent probabilities of a finite state-space discrete-time process using aggregate cross-sectional data. A large-sample version of multistate logistic regression is described and shown to be useful for analysing multistate life tables. The technique is applied to the estimation of disability-free, severely disabled and other disabled survival curves and health expectancies in Australia, based on data from national health surveys in 1988, 1993 and 1998. A conclusion is that there has been a general upward trend in the future time expected to be spent in a state of disability, the picture being more pessimistic for males than females. For example, during 1988-1998 the estimated increase in male life expectancy at birth of 2.7 years is decomposed as a decrease of 1.2 years in disability-free health (life) expectancy and increases of 1.3 and 2.6 years, respectively, in states of severe disability and other disability.