A dynamical network model for age-related health deficits and mortality

Abstract

How long people live depends on their health, and how it changes with age. Individual health can be tracked by the accumulation of age-related health deficits. The fraction of age-related deficits is a simple quantitative measure of human aging. This quantitative frailty index (F) is as good as chronological age in predicting mortality. In this paper, we use a dynamical network model of deficits to explore the effects of interactions between deficits, deficit damage and repair processes, and the connection between the F and mortality. With our model, we qualitatively reproduce Gompertz's law of increasing human mortality with age, the broadening of the F distribution with age, the characteristic non-linear increase of the F with age, and the increased mortality of high-frailty individuals. No explicit time-dependence in damage or repair rates is needed in our model. Instead, implicit time-dependence arises through deficit interactions -- so that the average deficit damage rates increases, and deficit repair rates decreases, with age . We use a simple mortality criterion, where mortality occurs when the most connected node is damaged.

12 pages, 38 figures

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• Parameter Space Compression Underlies Emergent Theories and Predictive Models
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