The biology of life span: A quantitative approach

Gavrilov, Leonid A.; Gavrilova, Natalia S.

doi:10.1016/0891-5849(92)90121-v

Cited by 190 publications

(302 citation statements)

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“…U.S. Americans, Australians, and Swedes; Rockwood and Mitnitski, 2007). The stylized fact that women start out unhealthier and age slower than men has a microfoundation in biology, based on reliability and redundancy of body cells (Gavrilov and Gavrilova, 1991;Fries, 1980). Combined with the gender-gap in longevity, the law of health deficit accumulation implies that, on average, women at the time of death have accumulated more health deficits than men.…”

Section: Introductionmentioning

confidence: 99%

The gender gap in mortality: How much is explained by behavior?

Schünemann

Strulik

Trimborn

2017

Journal of Health Economics

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract. In developed countries, women are expected to live about 4-5 years longer than men. In this paper we develop a novel approach in order to gauge to what extent gender differences in longevity can be attributed to gender-specific preferences and health behavior. For that purpose we set up a physiologically founded model of health deficit accumulation and calibrate it using recent insights from gerontology. Terms of use: Documents inFrom fitting life cycle health expenditure and life expectancy we obtain estimates of the gender-specific preference parameters. We then perform the counterfactual experiment of endowing women with the preferences of men. In our benchmark scenario this reduces the gender gap in life expectancy from 4.6 to 1.4 years. When we add gender-specific preferences for unhealthy consumption, the model can motivate up to 88 percent of the gender gap. Our theory offers also an economic explanation for why the gender gap declines with rising income.

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Section: Introductionmentioning

confidence: 99%

The gender gap in mortality: How much is explained by behavior?

Schünemann

Strulik

Trimborn

2017

Journal of Health Economics

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“…To the best of our knowledge, however, there exists no research in economics on human life span. 1 With contrast to life expectancy, which is population specific and situation specific, life span is usually conceptualized as a species-specific characteristic (Arking 2006;Gavrilov and Gavrilova 1991). Life expectancy of a population of mice, for example, depends on the specific environment in the wild or in the laboratory.…”

Section: Introductionmentioning

confidence: 99%

Long-run trends of human aging and longevity

Strulik

Vollmer

2013

J Popul Econ

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Over the last 200 years, humans experienced a huge increase of life expectancy. These advances were largely driven by extrinsic improvements of their environment (for example, the available diet, disease prevalence, vaccination, and the state of hygiene and sanitation). In this paper, we ask whether future improvements of life expectancy will be bounded from above by human life span. Life span, in contrast to life expectancy, is conceptualized as a biological measure of longevity driven by the intrinsic rate of bodily deterioration. In order to pursue our question, we first present a modern theory of aging developed by bio-gerontologists and show that immutable life span would put an upper limit on life expectancy. We then show for a sample of developed countries that human life span thus defined was indeed constant until the mid-twentieth century but increased since then in sync with life expectancy. In other words, we find evidence for manufactured life span.

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“…This law, observed by Gompertz (1825), was proved to be valid for the populations of most industrialised countries, describing the age dynamics of human mortality rather accurately in the age window from about 30 to 80 years of age (Thatcher, 1999). The Gompertz law of exponential increase in mortality rates with age is observed in many biological species (Strehler, 1978;Finch, 1990), including humans, rats, mice, fruit flies, flour beetles, and human lice (Gavrilov and Gavrilova, 1991). Let S(α) be the probability of surviving from birth to age α, which can be obtained by the cumulative distribution of the stable age distribution.…”

Section: Introductionmentioning

confidence: 97%

Evolution of the rate of biological aging using a phenotype based computational model

Kittas

2010

Journal of Theoretical Biology

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.Evolution of the rate of biological aging using a phenotype based computational model Aristotelis KittasTo cite this version: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.Evolution of the rate of biological aging using a phenotype based computational model Aristotelis KittasDepartment of Physics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece AbstractIn this work I introduce a simple model to study how natural selection acts upon aging, which focuses on the viability of each individual. It is able to reproduce the Gompertz law of mortality and can make predictions about the relation between the level of mutation rates (beneficial/deleterious/neutral), age at reproductive maturity and the degree of biological aging. With no mutations, a population with low age at reproductive maturity R stabilizes at higher density values, while with mutations it reaches its maximum density, because even for large pre-reproductive periods each individual evolves to survive to maturity. Species with very short pre-reproductive periods can only tolerate a small number of detrimental mutations. The probabilities of detrimental (P d ) or beneficial (P b ) mutations are demonstrated to greatly affect the process. High absolute values produce peaks in the viability of the population over time. Mutations combined with low selection pressure move the system towards weaker phenotypes. For low values in the ratio P d /P b , the speed at which aging occurs is almost independent of R, while higher values favor significantly species with high R. The value of R is critical to whether the population survives or dies out. The aging rate is controlled by P d and P b and the amount the viability of each individual is modified, with neutral mutations allowing the system more "room" to evolve. The process of aging in this simple model is revealed to be fairly complex, yielding a rich variety of results.

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The biology of life span: A quantitative approach

Cited by 190 publications

References 2 publications

The gender gap in mortality: How much is explained by behavior?

The gender gap in mortality: How much is explained by behavior?

Long-run trends of human aging and longevity

Evolution of the rate of biological aging using a phenotype based computational model

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