Insights into mortality patterns and causes of death through a process point of view model

Abstract

Process point of view models of mortality, such as the Strehler-Mildvan and stochastic vitality models, represent death in terms of the loss of survival capacity through challenges and dissipation. Drawing on hallmarks of aging, we link these concepts to candidate biological mechanisms through a framework that defines death as challenges to vitality where distal factors defined the age-evolution of vitality and proximal factors define the probability distribution of challenges. To illustrate the process point of view, we hypothesize that the immune system is a mortality nexus, characterized by two vitality streams: increasing vitality representing immune system development and immunosenescence representing vitality dissipation. Proximal challenges define three mortality partitions: juvenile and adult extrinsic mortalities and intrinsic adult mortality. Model parameters, generated from Swedish mortality data (1751-2010), exhibit biologically meaningful correspondences to economic, health and cause-of-death patterns. The model characterizes the 20th century epidemiological transition mainly as a reduction in extrinsic mortality resulting from a shift from high magnitude disease challenges on individuals at all vitality levels to low magnitude stress challenges on low vitality individuals. Of secondary importance, intrinsic mortality was described by a gradual reduction in the rate of loss of vitality presumably resulting from reduction in the rate of immunosenescence. Extensions and limitations of a distal/proximal framework for characterizing more explicit causes of death, e.g. the young adult mortality hump or cancer in old age are discussed.

The relationship of survivorship and body mass modeled by metabolic and vitality theories

“…where x W is a noise process with zero mean value and unit variance, ρ is the mean rate of loss of vitality and σ scales the level of stochastic variability in the rate (Anderson 2000;Anderson et al 2017;Li and Anderson 2013). Equation (2) characterizes an ensemble of random vitality trajectories that begin at 0 1 v = and drift towards a zero boundary where they are absorbed ( Fig.…”

“…(4) . As an aside, a juvenile extrinsic mortality rate, involving challenges to a developing juvenile immune system can be expressed in a similar manner (Anderson et al 2017). This paper does not consider juvenile extrinsic mortality.…”

“…With this assumption, the effect of challenges on extrinsic survival is characterized by their frequency λ only. However, when considering the effects of challenge magnitude on survivorship patterns across time, temporal changes in challenge magnitude can be important (Anderson et al 2017).…”

“…The goal of this paper is to develop a mathematical model linking body size to longevity through cellular level processes. The framework combines metabolic theory (Brown et al 2004;West et al 1997), processes of cell aging (López-Otín et al 2013) and vitality theory (Anderson 2000;Anderson et al 2017;Li and Anderson 2013).…”

The relationship of mammal survivorship and body mass modeled by metabolic and vitality theories

“…The framework combines metabolic theory (West et al 1997; Brown et al 2004), processes of cell aging (López-Otín et al 2013) and vitality theory (Anderson 2000; Li and Anderson 2013; Anderson et al 2017). …”