@article {Anderson067967, author = {James J. Anderson and Ting Li and David J. Sharrow}, title = {Insights into mortality patterns and causes of death through a process point of view model}, elocation-id = {067967}, year = {2016}, doi = {10.1101/067967}, publisher = {Cold Spring Harbor Laboratory}, 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.}, URL = {https://www.biorxiv.org/content/early/2016/11/15/067967}, eprint = {https://www.biorxiv.org/content/early/2016/11/15/067967.full.pdf}, journal = {bioRxiv} }