Method for calculating healthy life expectancy by including dynamic changes of both mortality and health

This thesis incorporates the self-reported health status information from the National Health Interview Survey in the United States into a cohort life table to estimate and forecast healthy life expectancy, which is the average of years lived in good health. First, thethesis defines the Health Status Index (HSI) representing the proportion of the population of people who are in bad health. Applying the HSI, the main contribution of this thesis ismodeling the dynamic changes of both the mortality and health processes by using the Lee-Carter model and constructing their stochastic projections. Based on goodness-of-fit tests wefind that the Lee-Carter model fits the data quite well. Healthy life expectancy (HLE) is estimated and projected using Sullivan’s method by including the stochastic projectuon of the HSI into cohort life tables. The results show increasing trends of both life expectancy (LE)and healthy life expectancy (HLE), whereas the latter increases faster than the former. Another novelty of this thesis is the inclusion of uncertainty intervals by means of simulationmethod for expected simulated LE and HLE.We found that HLE have larger uncertainty than LE. Moreover, males’s LE and HLE are lower than females’ but increase faster with larger confidence intervals. The thesis also provides a comparison between models using level andlogit HSI formats, and shows that healthy life expectancies derived from the models with logit HSI are slightly lower, and increase slower with narrower confidence intervals than from the level format models, and a logit transformation is superior to the level format by construction.