Background: Surveys of chronic health conditions provide information about prevalence but not about the incidence and the process of change within the population.
Objective: We show how the “age dynamics” of chronic conditions -- the probabilities of contracting the conditions at different ages, of moving from one chronic conditions state to another, and of dying -- can be inferred from prevalence data for those conditions that can be viewed as irreversible.
Methods: Transition probability matrices are constructed for five-year age groups, representing the age dynamics of health conditions for a stationary population. We illustrate the application of the matrices by simulating the age/health path of an initially healthy cohort.
Results and conclusion: Surveys of chronic conditions provide valuable information about prevalence rates; we show that such surveys can be made even more valuable by allowing the calculation of the transition probabilities that define the chronic conditions age dynamic process. We report the results of simulations based on transition probabilities that we have derived, and note the general applicability of the methods.