Multistate method

The multistate life table method has been proposed by Rogers and colleagues in order to take into account the recovery of lost functions and return to a state of good health. Data comes from longitudinal surveys which provide requested probabilities over a couple of years:
- onset of disability or other health problems
- recovery from disability or other heath problems
- probability of dying for people who had initially disability and for people who were initially healthy.

Based on this set of probabilities, multistate life tables can be computed by simulating from age to age the risks of entering disability, recovering and dying and deriving from it the person-years with and without disability.

The advantage of this method - based on transitions between states of health - is that it gives a period indicator that takes into account the reversibility of disability. The specific drawback of the multistate life table method arises from the scarceness of adequate data. Data requirements for multistate methods are considerable and there are very few countries where national data are available or likely to be available for some time. Biases are introduced when the gaps between successive waves of longitudinal studies are too long, thus failing to capture a part of the flows between health states during the inter-survey.

  • Rogers A, Rogers RG, Branch LG. A multistate analysis of active life expectancy. Public Health Rep 1989;104:222-225.

On this webpage you can find documents and links toward different methods to compute multistate life tables:

  • The Interpolated Markov Chain method "IMaCh":
    Lièvre A., Brouard N. and Heathcote Ch. Estimating health expectancies from cross-longitudinal surveys. Mathematical Population Studies 2003;10(4):211-248
  • The Gibbs Sampler for Multistate Life Tables Software-GSMLT: Brown S, Lynch S.
  • The SPACE program:
    Cai L., Hayward M., Saito Y., Lubitz J., Hagedorn A., Crimmins E.M. Estimation of multi-state life table functions and their variability from complex survey data using the SPACE Program. Demographic Res. 2010;22(6):129-158.