Three important results concerning the shape and the trends of the human mortality rate were discussed recently in demographic and epidemiological literature. These are the deceleration of the mortality rate at old ages, the tendency to rectangularization of the survival curve, and the decline of the old age mortality observed in the second part of the 20th century. In this paper we show that all these results can be explained by using a model with a new type of heterogeneity associated with individual differences in adaptive capacity. We first illustrate the idea of such a model by considering survival in a mixture of two subpopulations of individuals (called "labile" and "stable"). These subpopulations are characterized by different Gompertz mortality patterns, such that their mortality rates cross over. The survival chances of individuals in these subpopulations have different sensitivities to changes in environmental conditions. Then we develop a more comprehensive model in which the mortality rate is related to the adaptive capacity of an organism. We show that the trends in survival patterns experienced by a mixture of such individuals resemble those obtained in an analysis of empirical data on survival in developed countries. Lastly, we present evidence of the existence of subpopulations of phenotypes in both humans and experimental organisms, which were used as prototypes in our models. The existence of such phenotypes provides the possibility that at least part of today's centenarians originated from an initially frail part of the cohort.

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Americans aged 65-69 years manifest a significant improvement in health over the 1980s-1990s but the dynamics differs in gender and race groups. Possible reasons for these differences are discussed.

We consider a scheme of aging with two possible mechanisms of senescence processes: aging with apoptosis and necrosis for differentiated cells and a multistage process of malignant transformation. Our model describes the multistage phenomena of aging and carcinogenesis by a set of stochastic equations using multivariate and diffusion processes. This model fits experimental data on the acceleration of aging processes from postnatal exposure to 5-bromodeoxyuridine (BrdU), and the induction of genome instability. The methods of stochastic modeling and computer simulation of the processes of aging and carcinogenesis have been used for the verification of the biological suggestions.