Dynamic paradigms for human mortality and aging

Hazard models are often applied to mortality data of humans and other speci es so that the parameter estimates made for those models can be used to mak e inferences about the biology, and comparative biology, of aging processes . Enough longitudinal data on physiological and functional changes in human s now exist to know that the age trajectory of the physiological state of i ndividuals is multidimensional, stochastic, and plastic. Thus, to fully ass ess the biological significance of existing longitudinal data on human agin g and mortality processes, multivariate stochastic process models must be d eveloped that are biologically detailed and valid. This requires assessing genetic mechanisms controlling human longevity and rates of aging, developi ng models of how those traits may have evolved, and developing statistical methods for identifying gene environment interactions. This article examine s the theoretical basis for such models and the biological rationale of the ir parametric structure. Several examples are given.