Literature DB >> 12908715

On the relationship between human all-cause mortality and age.

H Kesteloot1, X Huang.   

Abstract

Many equations can be used to study the relationship between mortality rates and age: Gompertz, Weibull, logistic, polynomial and age-period-cohort equations a.o. All these equations result in highly significant correlations between ln mortality rates and age in the age range 35-84 years. This applies to all developed countries and is independent of the differences in causes of death between populations. The best fit is obtained by a second-degree polynomial equation (R2 > 0.99), closely followed by the Gompertz equation. This equation is preferred in view of its extreme simplicity. A highly significant correlation exists between the intercept and the slope of the Gompertz equations, pointing to a crossing-over age. Beyond that age, around 85 years, populations with high mortality rates have a lower mortality, due to selective survival of the strongest individuals. The polynomial age 2 term may be positive or negative, an expression of the acceleration or de-acceleration of mortality at higher ages and is significantly more often positive in women. The equations used are very useful for the study of the aging process and for examining the relationship between possible causal factors and mortality rates in populations.

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Year:  2003        PMID: 12908715     DOI: 10.1023/a:1024641614659

Source DB:  PubMed          Journal:  Eur J Epidemiol        ISSN: 0393-2990            Impact factor:   8.082


  7 in total

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Journal:  Eur J Epidemiol       Date:  2003       Impact factor: 8.082

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3.  Differential evolution of mortality between Denmark and Scotland, period 1970 to 1999. A comparison with mortality data from the European Union.

Authors:  H Kesteloot
Journal:  Eur J Epidemiol       Date:  2006       Impact factor: 8.082

4.  Onset of mortality increase with age and age trajectories of mortality from all diseases in the four Nordic countries.

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5.  The interaction between individualism and wellbeing in predicting mortality: Survey of Health Ageing and Retirement in Europe.

Authors:  Judith A Okely; Alexander Weiss; Catharine R Gale
Journal:  J Behav Med       Date:  2017-07-15

6.  The interaction between stress and positive affect in predicting mortality.

Authors:  Judith A Okely; Alexander Weiss; Catharine R Gale
Journal:  J Psychosom Res       Date:  2017-07-08       Impact factor: 3.006

7.  Senescence and Longevity of Sea Urchins.

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Journal:  Genes (Basel)       Date:  2020-05-20       Impact factor: 4.096

  7 in total

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