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Journal of Mathematical Biology

, Volume 34, Issue 1, pp 1–16 | Cite as

The effects of health histories on stochastic process models of aging and mortality

  • Anatoli I. Yashin
  • Kenneth G. Manton
  • Max A. Woodbury
  • Eric Stallard
Article

Abstract

A model of human health history and aging, based on a multivariate stochastic process with both continuous diffusion and discrete jump components, is presented. Discrete changes generate non-Gaussian diffusion with time varying continuous state distributions. An approach to calculating transition rates in dynamically heterogeneous populations, which generalizes the conditional averaging of hazard rates done in “fixed frailty” population models, is presented to describe health processes with multiple jumps. Conditional semi-invariants are used to approximate the conditional p.d.f. of the unobserved health history components. This is useful in analyzing the age dependence of mortality and health changes at advanced age (e.g., 95 +) where homeostatic controls weaken, and physiological dynamics and survival manifest nonlinear behavior.

Key words

Gaussian processes Semi-invariants Aging and mortality Physiological dynamics, mortality 

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Copyright information

© Springer-Verlag 1995

Authors and Affiliations

  • Anatoli I. Yashin
    • 1
  • Kenneth G. Manton
    • 2
  • Max A. Woodbury
    • 2
  • Eric Stallard
    • 2
  1. 1.Institute of Community HealthOdense UniversityDenmark
  2. 2.Center for Demographic StudiesDuke UniversityDurhamUSA

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