Mortality Implications of Mortality Plateaus

Missov, Trifon I.; Vaupel, James W.

doi:10.1137/130912992

Cited by 29 publications

(38 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In fact, later age mortality rates are accelerating faster, because the basal mortality level ("minimum mortality") from which the Gompertz exponential arises has been lowered, thereby delaying, but not reducing senescence at later ages (11)(12)(13). The mortality rate plateau that was once thought to be reached by the age of 90 y has been remapped to ages of 110-114 y (14), and thus does not pertain to the experience of the vast majority of aging humans (12,13).…”

Section: Molecular Aging Morbidity and Mortalitymentioning

confidence: 99%

Constant molecular aging rates vs. the exponential acceleration of mortality

Finch

Crimmins

2016

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

Section: Molecular Aging Morbidity and Mortalitymentioning

confidence: 99%

Constant molecular aging rates vs. the exponential acceleration of mortality

Finch

Crimmins

2016

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

“…As a result they can only be slightly distorted even if the age at censoring is low, that is, when the proportion of censored individuals is high. To illustrate that this effect is not restricted to the ΓGM model, that is, to the model that describes best adult human mortality (Missov and Vaupel, 2015), we consider an additional example with experimental non-human data (rats), where the mortality pattern is well captured by a Gompertz model.…”

Section: γGm Model-based Mortality Measuresmentioning

confidence: 99%

“…The ΓGM frailty model is widely used in human mortality research as it captures well the S-shaped pattern of mortality at adult ages. For detailed discussion on the semantics and mathematics behind the ΓGM we redirect our readers to Vaupel et al (1979), Missov andFinkelstein (2011), Vaupel andMissov (2014) and Missov and Vaupel (2015). We use maximum likelihood for fitting the ΓGM model, that is, we maximize a Poisson log-likelihood…”

mentioning

confidence: 99%

How much can we trust life tables? Sensitivity of mortality measures to right-censoring treatment

2016

View full text Add to dashboard Cite

International organizations, research institutions, insurance companies, pension funds and health policymakers calculate human mortality measures from life tables. Life-table data, though, are usually right-censored; that is, the last open-end age group does not contain information about the exact ages at death of individuals there, and mortality measures are sensitive to the way censoring is addressed. The standard way of "closing" the life table assumes a constant hazard of death for the last age group. This might lead to erroneous conclusions about mortality measures, especially when the open-end age interval contains a large proportion of the study population. In this article, we propose, instead, fitting a parametric model that well describes human mortality patterns, the gamma-GompertzMakeham, accounting for censoring, and constructing model-based equivalents of five mortality measures: life expectancy, the modal age at death, life disparity, entropy and the Gini coefficient. We show that, in comparison to conventional life-table measures, modelbased measures are less sensitive to the age at censoring or, equivalently, to the proportion of censored individuals, and can be only slightly distorted even if the age at censoring is low. This study also compares life-table and model-based mortality measures for a non-human population with an underlying Gompertz mortality schedule in which a fixed proportion of the population is censored. Using model-based mortality measures is essential when studying the mortality of populations subjected to substantial censoring; for instance, many life tables for developing countries contain an open-end interval that contains more than 10% of the population. In this study, we show that life expectancy at birth for Brazilian females in 2007, calculated by standard life-table algebra, exceeds by almost 3 years the gamma-GompertzMakeham model-based life expectancy. This article might serve as a basis for recalculation of mortality measures for all populations subjected to substantial censoring.

show abstract

“…It is not for instance, compatible with the accelerated-life models (Finkelstein and Esaulova, 2006) or with the assumption that frailty is log-normally distributed (Missov and Finkelstein, 2011). If a mortality plateau really exists, the only meaningful way of describing human mortality seems to be the Gamma-Gompertz model where the individual rate of ageing is constant, the hazards evolve exponentially (à la Gompertz) and frailty is Gamma distributed (Missov and Vaupel, 2015).…”

Section: Introductionmentioning

confidence: 99%

Earlier and more rapid ageing: Does nutrition contribute?

Salinari¹,

Santis²

2015

IJPS

View full text Add to dashboard Cite

This paper estimated three parameters related to demographic ageing, i.e., the acceleration in mortality rates as people get older. These parameters are: (i) the age when the process begins (onset), (ii) the rate of ageing in a (simple) Gompertz model and (iii) the rate of ageing in a (more elaborate) Gamma-Gompertz model. These three indicators were estimated on the basis of female cohorts born in seven European countries between 1890 and 1919. Our results indicated a progressively earlier onset and a steeper rise in the rate of ageing in recent cohorts, i.e., ageing seems to have accelerated over time. The reasons for these shifts are still unknown, but due to their similarity with the results of a vast body of experiments of calorie restriction on lab animals, we suggested here that the changed dietary regime of humans since the end of the 19th century may have played a part in the evolution of their mortality schedule.

show abstract

Mortality Implications of Mortality Plateaus

Cited by 29 publications

References 36 publications

Constant molecular aging rates vs. the exponential acceleration of mortality

Constant molecular aging rates vs. the exponential acceleration of mortality

How much can we trust life tables? Sensitivity of mortality measures to right-censoring treatment

Earlier and more rapid ageing: Does nutrition contribute?

Contact Info

Product

Resources

About