The new trends in survival improvement require a revision of traditional gerontological concepts

Decomposing changes in life expectancy: Compression versus shifting mortality

“…After this period, changes in life expectancy became gradually dependent on the shift in the senescent modal age at death. These results are consistent with the findings of other studies looking at changes in the modal age at death and at different variability measures (Wilmoth and Horiuchi 1999;Robine 2001;Yashin et al 2001;Canudas-Romo 2008). The results also confirm the increasing importance of the modal age at death as a key indicator of lifespan.…”

“…This generated changes in the mechanisms behind the increase in life expectancy (Wilmoth and Horiuchi 1999;Edwards and Tuljapurkar 2005;Smits and Monden 2009). The new mechanism behind improvement in life expectancy is best illustrated by a shift in the distribution of death toward older ages with a shape remaining nearly constant (Yashin et al 2001;Bongaarts 2005;Cheung et al 2005;Cheung and Robine 2007;Canudas-Romo 2008). Vaupel (1986), Vaupel and Gowan (1986) and Bongaarts (2005) were among the first to articulate the idea of shifting mortality.…”

Shaping human mortality patterns through intrinsic and extrinsic vitality processes

“…Indeed, Yashin et al (2001a) noted "a revision of traditional gerontological concepts" is necessary. Of the current suite of models the dominant class, the Gompertz-Makeham type, express one mortality rate process as age-dependent and the other process as ageindependent (Gompertz 1825;Heligman et al 1980;Makeham 1860;Siler 1979;Strehler et al 1960;Vaupel et al 1979;Yashin et al 2001a).…”

“…Of the current suite of models the dominant class, the Gompertz-Makeham type, express one mortality rate process as age-dependent and the other process as ageindependent (Gompertz 1825;Heligman et al 1980;Makeham 1860;Siler 1979;Strehler et al 1960;Vaupel et al 1979;Yashin et al 2001a). A second "point-of-view", class of models explicitly describes intrinsic mortality through the passage of a hidden Markov process, i.e., vitality, to an absorbing boundary representing death (Aalen et al 2001;Anderson 2000;Li et al 2009;Weitz et al 2001), or in terms of a loss of homeostasis (Yashin et al 2000).…”

How Genes Influence Life Span: The Biodemography of Human Survival

“…The model explained a striking regularity detected in comparisons of the Gompertz mortality rates across different populations: The parameters R 0 and a of this curve were not changing independently from one population to the next, as one might expect, but showed a strong negative correlation, later called the Strehler-Mildvan (SM) correlation. This model has been applied to explaining differences in mortality rates among different populations 19,23,24 and to differences in mortality rates in the same country at different time periods, or in subsequent subcohorts, [24][25][26] as well as in cause-specific mortality rates. The SM model represents the age-specific Gompertz mortality function l(x) = R 0 exp(ax) (which typically gives a good fit to population patterns of human mortality rates between ages 30 and 85 years) in terms of two sets of parameters: One describes the age-dependent decline in vitality and the second characterizes external stresses.…”