1. Biodemography of Mortality and Longevity
CONTEMPORARY METHODS OF MORTALITY ANALYSIS
CONTEMPORARY METHODS OF MORTALITY ANALYSIS
Biodemography of Mortality and Longevity
Lecture 1
Leonid Gavrilov
Natalia Gavrilova
Center on Aging
NORC and the University of Chicago
Chicago, Illinois, USA

3. Empirical Laws of Mortality

4. The Gompertz-Makeham Law
Death rate is a sum of age-independent component (Makeham term) and age-dependent component (Gompertz function), which increases exponentially with age.
μ(x) = A + R e αx
A – Makeham term or background mortality
R e αx – age-dependent mortality; x - age
risk of death

5. Gompertz Law of Mortality in Fruit Flies
Based on the life table for females of Drosophila melanogaster published by Hall (1969).
Source: Gavrilov, Gavrilova, “The Biology of Life Span” 1991

6. Gompertz-Makeham Law of Mortality in Flour Beetles
Based on the life table for 400 female flour beetles (Tribolium confusum Duval). published by Pearl and Miner (1941).
Source: Gavrilov, Gavrilova, “The Biology of Life Span” 1991

7. Gompertz-Makeham Law of Mortality in Italian Women
Based on the official Italian period life table for
Source: Gavrilov, Gavrilova, “The Biology of Life Span” 1991

8. How can the Gompertz-Makeham law be used?
By studying the historical dynamics of the mortality components in this law:
μ(x) = A + R e αx
Makeham component
Gompertz component

9. The Strehler-Mildvan Correlation: Inverse correlation between the Gompertz parameters
Limitation: Does not take into account the Makeham parameter that leads to spurious correlation

10. Modeling mortality at different levels of Makeham parameter but constant Gompertz parameters
1 – A=0.01 year-1
2 – A=0.004 year-1
3 – A=0 year-1

11. Coincidence of the spurious inverse correlation between the Gompertz parameters and the Strehler-Mildvan correlation
Dotted line – spurious inverse correlation between the Gompertz parameters
Data points for the Strehler-Mildvan correlation were obtained from the data published by Strehler-Mildvan (Science, 1960)

12. Compensation Law of Mortality (late-life mortality convergence)
Relative differences in death rates are decreasing with age, because the lower initial death rates are compensated by higher slope (actuarial aging rate)

13. Compensation Law of Mortality Convergence of Mortality Rates with Age
1 – India, , males
2 – Turkey, , males
3 – Kenya, 1969, males
4 - Northern Ireland, , males
5 - England and Wales, , females
6 - Austria, , females
7 - Norway, , females
Source: Gavrilov, Gavrilova,
“The Biology of Life Span” 1991

14. Compensation Law of Mortality (Parental Longevity Effects) Mortality Kinetics for Progeny Born to Long-Lived (80+) vs Short-Lived Parents
Sons
Daughters

15. Compensation Law of Mortality in Laboratory Drosophila
1 – drosophila of the Old Falmouth, New Falmouth, Sepia and Eagle Point strains (1,000 virgin females)
2 – drosophila of the Canton-S strain (1,200 males)
3 – drosophila of the Canton-S strain (1,200 females)
4 - drosophila of the Canton-S strain (2,400 virgin females)
Mortality force was calculated for 6-day age intervals.
Source: Gavrilov, Gavrilova,
“The Biology of Life Span” 1991

16. Implications
Be prepared to a paradox that higher actuarial aging rates may be associated with higher life expectancy in compared populations (e.g., males vs females)
Be prepared to violation of the proportionality assumption used in hazard models (Cox proportional hazard models)
Relative effects of risk factors are age- dependent and tend to decrease with age

17. The Late-Life Mortality Deceleration (Mortality Leveling-off, Mortality Plateaus)
The late-life mortality deceleration law states that death rates stop to increase exponentially at advanced ages and level-off to the late-life mortality plateau.

18. Mortality deceleration at advanced ages.
After age 95, the observed risk of death [red line] deviates from the value predicted by an early model, the Gompertz law [black line].
Mortality of Swedish women for the period of from the Kannisto-Thatcher Database on Old Age Mortality
Source: Gavrilov, Gavrilova, “Why we fall apart. Engineering’s reliability theory explains human aging”. IEEE Spectrum

19. Mortality Leveling-Off in House Fly Musca domestica
Based on life table of 4,650 male house flies published by Rockstein & Lieberman, 1959

20. Non-Aging Mortality Kinetics in Later Life
Source: A. Economos. A non-Gompertzian paradigm for mortality kinetics of metazoan animals and failure kinetics of manufactured products. AGE, 1979, 2:

21. Non-Aging Failure Kinetics of Industrial Materials in ‘Later Life’ (steel, relays, heat insulators)
Source:
A. Economos.
A non-Gompertzian paradigm for mortality kinetics of metazoan animals and failure kinetics of manufactured products. AGE, 1979, 2:

22. Mortality Deceleration in Animal Species
Mammals:
Mice (Lindop, 1961; Sacher, 1966; Economos, 1979)
Rats (Sacher, 1966)
Horse, Sheep, Guinea pig (Economos, 1979; 1980)
However no mortality deceleration is reported for
Rodents (Austad, 2001)
Baboons (Bronikowski et al., 2002)
Invertebrates:
Nematodes, shrimps, bdelloid rotifers, degenerate medusae (Economos, 1979)
Drosophila melanogaster (Economos, 1979; Curtsinger et al., 1992)
Housefly, blowfly (Gavrilov, 1980)
Medfly (Carey et al., 1992)
Bruchid beetle (Tatar et al., 1993)
Fruit flies, parasitoid wasp (Vaupel et al., 1998)

23. Existing Explanations of Mortality Deceleration
Population Heterogeneity (Beard, 1959; Sacher, 1966). “… sub-populations with the higher injury levels die out more rapidly, resulting in progressive selection for vigour in the surviving populations” (Sacher, 1966)
Exhaustion of organism’s redundancy (reserves) at extremely old ages so that every random hit results in death (Gavrilov, Gavrilova, 1991; 2001)
Lower risks of death for older people due to less risky behavior (Greenwood, Irwin, 1939)
Evolutionary explanations (Mueller, Rose, 1996; Charlesworth, 2001)

24. Testing the “Limit-to-Lifespan” Hypothesis
Source: Gavrilov L.A., Gavrilova N.S The Biology of Life Span

25. Implications
There is no fixed upper limit to human longevity - there is no special fixed number, which separates possible and impossible values of lifespan.
This conclusion is important, because it challenges the common belief in existence of a fixed maximal human life span.

26. Latest Developments Was the mortality deceleration law overblown?
A Study of the Extinct Birth Cohorts in the United States

27. More recent birth cohort mortality
Nelson-Aalen monthly estimates of hazard rates using Stata 11

28. What about other mammals?
Mortality data for mice:
Data from the NIH Interventions Testing Program, courtesy of Richard Miller (U of Michigan)
Argonne National Laboratory data, courtesy of Bruce Carnes (U of Oklahoma)

29. Mortality of mice (log scale) Miller data
males
females
Actuarial estimate of hazard rate with 10-day age intervals

30. What are the explanations of mortality laws?
Mortality and aging theories

31. What Should the Aging Theory Explain
Why do most biological species including humans deteriorate with age?
The Gompertz law of mortality
Mortality deceleration and leveling-off at advanced ages
Compensation law of mortality

32. Additional Empirical Observation: Many age changes can be explained by cumulative effects of cell loss over time
Atherosclerotic inflammation - exhaustion of progenitor cells responsible for arterial repair (Goldschmidt-Clermont, 2003; Libby, 2003; Rauscher et al., 2003).
Decline in cardiac function - failure of cardiac stem cells to replace dying myocytes (Capogrossi, 2004).
Incontinence - loss of striated muscle cells in rhabdosphincter (Strasser et al., 2000).

33. Like humans, nematode C. elegans experience muscle loss
Herndon et al Stochastic and genetic factors influence tissue- specific decline in ageing C. elegans. Nature 419,
“…many additional cell types (such as hypodermis and intestine) … exhibit age- related deterioration.”
Body wall muscle sarcomeres
Left - age 4 days. Right - age 18 days

34. What Is Reliability Theory?
Reliability theory is a general theory of systems failure developed by mathematicians:

35. Aging is a Very General Phenomenon!

36. Stages of Life in Machines and Humans
Bathtub curve for human mortality as seen in the U.S. population in has the same shape as the curve for failure rates of many machines.
The so-called bathtub curve for technical systems

37. Gavrilov, L. , Gavrilova, N. Reliability theory of aging and longevity
Gavrilov, L., Gavrilova, N. Reliability theory of aging and longevity. In: Handbook of the Biology of Aging. Academic Press, 6th edition, 2006, pp.3-42.

38. The Concept of System’s Failure
In reliability theory failure is defined as the event when a required function is terminated.

39. Definition of aging and non-aging systems in reliability theory
Aging: increasing risk of failure with the passage of time (age).
No aging: 'old is as good as new' (risk of failure is not increasing with age)
Increase in the calendar age of a system is irrelevant.

40. Aging and non-aging systems
Progressively failing clocks are aging (although their 'biomarkers' of age at the clock face may stop at 'forever young' date)
Perfect clocks having an ideal marker of their increasing age (time readings) are not aging

41. Mortality in Aging and Non-aging Systems
Example: radioactive decay

42. According to Reliability Theory: Aging is NOT just growing old Instead Aging is a degradation to failure: becoming sick, frail and dead
'Healthy aging' is an oxymoron like a healthy dying or a healthy disease
More accurate terms instead of 'healthy aging' would be a delayed aging, postponed aging, slow aging, or negligible aging (senescence)

43. The Concept of Reliability Structure
The arrangement of components that are important for system reliability is called reliability structure and is graphically represented by a schema of logical connectivity

44. Two major types of system’s logical connectivity
Components connected in series
Components connected in parallel
Fails when the first component fails
Ps = p1 p2 p3 … pn = pn
Fails when all components fail
Qs = q1 q2 q3 … qn = qn
Combination of two types – Series-parallel system

45. Series-parallel Structure of Human Body
Vital organs are connected in series
Cells in vital organs are connected in parallel

46. Redundancy Creates Both Damage Tolerance and Damage Accumulation (Aging)
System without redundancy dies after the first random damage (no aging)
System with redundancy accumulates damage (aging)

47. Reliability Model of a Simple Parallel System
Failure rate of the system:
Elements fail randomly and independently with a constant failure rate, k
n – initial number of elements
 nknxn-1 early-life period approximation, when 1-e-kx  kx
 k late-life period approximation, when 1-e-kx  1

48. Failure of elements is random
Failure Rate as a Function of Age in Systems with Different Redundancy Levels
Failure of elements is random

49. Standard Reliability Models Explain
Mortality deceleration and leveling-off at advanced ages
Compensation law of mortality

50. Standard Reliability Models Do Not Explain
The Gompertz law of mortality observed in biological systems
Instead they produce Weibull (power) law of mortality growth with age

51. An Insight Came To Us While Working With Dilapidated Mainframe Computer
The complex unpredictable behavior of this computer could only be described by resorting to such 'human' concepts as character, personality, and change of mood.

52. Reliability structure of (a) technical devices and (b) biological systems
Low redundancy
Low damage load
High redundancy
High damage load
X - defect

53. Models of systems with distributed redundancy
Organism can be presented as a system constructed of m series-connected blocks with binomially distributed elements within block (Gavrilov, Gavrilova, 1991, 2001)

54. Model of organism with initial damage load
Failure rate of a system with binomially distributed redundancy (approximation for initial period of life):
Binomial law of mortality
- the initial virtual age of the system
where
The initial virtual age of a system defines the law of system’s mortality:
x0 = 0 - ideal system, Weibull law of mortality
x0 >> 0 - highly damaged system, Gompertz law of mortality

55. People age more like machines built with lots of faulty parts than like ones built with pristine parts.
As the number of bad components, the initial damage load, increases [bottom to top], machine failure rates begin to mimic human death rates.

56. Statement of the HIDL hypothesis: (Idea of High Initial Damage Load )
"Adult organisms already have an exceptionally high load of initial damage, which is comparable with the amount of subsequent aging-related deterioration, accumulated during the rest of the entire adult life."
Source: Gavrilov, L.A. & Gavrilova, N.S The Biology of Life Span:
A Quantitative Approach. Harwood Academic Publisher, New York.

57. Why should we expect high initial damage load in biological systems?
General argument: --  biological systems are formed by self-assembly without helpful external quality control.
Specific arguments:
Most cell divisions responsible for  DNA copy-errors occur in early development leading to clonal expansion of mutations
Loss of telomeres is also particularly high in early-life
Cell cycle checkpoints are disabled in early development

58. Practical implications from the HIDL hypothesis:
"Even a small progress in optimizing the early-developmental processes can potentially result in a remarkable prevention of many diseases in later life, postponement of aging-related morbidity and mortality, and significant extension of healthy lifespan."
Source: Gavrilov, L.A. & Gavrilova, N.S The Biology of Life Span:
A Quantitative Approach. Harwood Academic Publisher, New York.

59. Life Expectancy and Month of Birth
Data source: Social Security Death Master File

61. Evolution of Species Reliability
Reliability theory of aging is perfectly compatible with the idea of biological evolution.
Moreover, reliability theory helps evolutionary theories to explain how the age of onset of diseases caused by deleterious mutations could be postponed to later ages during the evolution.

62. Evolution in the Direction of Low Mortality at Young Ages
This could be easily achieved by simple increase in the initial redundancy levels (e.g., initial cell numbers).
Log risk of death
Age

63. Evolution of species reliability
Fruit flies from the very beginning of their lives have very unreliable design compared to humans.
High late-life mortality of fruit flies compared to humans suggests that fruit flies are made of less reliable components (presumably cells), which have higher failure rates compared to human cells.

64. Reliability of Birds vs Mammals
Birds should be very prudent in redundancy of their body structures (because it comes with a heavy cost of additional weight).
Result: high mortality at younger ages.
Flight adaptation should force birds to evolve in a direction of high reliability of their components (cells).
Result: low rate of elements’ (cells’) damage resulting in low mortality at older ages

65. Effect of extrinsic mortality on the evolution of senescence in guppies. Reznick et al Nature 431,
Reliability-theory perspective:
Predators ensure selection for better performance and lower initial damage load.
Hence life span would increase in high predator localities.
Solid line – high predator locality
Dotted line –low predator locality

66. Conclusions (I)
Redundancy is a key notion for understanding aging and the systemic nature of aging in particular. Systems, which are redundant in numbers of irreplaceable elements, do deteriorate (i.e., age) over time, even if they are built of non-aging elements.
An apparent aging rate or expression of aging (measured as age differences in failure rates, including death rates) is higher for systems with higher redundancy levels.

67. Conclusions (II)
Redundancy exhaustion over the life course explains the observed ‘compensation law of mortality’ (mortality convergence at later life) as well as the observed late-life mortality deceleration, leveling-off, and mortality plateaus.
Living organisms seem to be formed with a high load of initial damage, and therefore their lifespans and aging patterns may be sensitive to early-life conditions that determine this initial damage load during early development. The idea of early-life programming of aging and longevity may have important practical implications for developing early-life interventions promoting health and longevity.

68. Testing Biological Theories of Aging with Demographic and Genealogical Data

69. What are the data and the predictions of the evolutionary theory on
Links between human longevity and fertility
Lifespan heritability in humans
Quality of offspring conceived to older parents

70. Founding Fathers
Beeton, M., Yule, G.U., Pearson, K Data for the problem of evolution in man. V. On the correlation between duration of life and the number of offspring. Proc. R. Soc. London, 67:
Data used: English Quaker records and Whitney Family of Connectucut records for females and American Whitney family and Burke’s ‘Landed Gentry’ for males.

71. Findings and Conclusions by Beeton et al., 1900
They tested predictions of the Darwinian evolutionary theory that the fittest individuals should leave more offspring.
Findings: Slightly positive relationship between postreproductive lifespan (50+) of both mothers and fathers and the number of offspring.
Conclusion: “fertility is correlated with longevity even after the fecund period is passed” and “selective mortality reduces the numbers of the offspring of the less fit relatively to the fitter.”

72. Other Studies, Which Found Positive Correlation Between Reproduction and Postreproductive Longevity
Telephone inventor Alexander Graham Bell (1918):
“The longer lived parents were the most fertile.”
Bettie Freeman (1935): Weak positive correlations between the duration of postreproductive life in women and the number of offspring borne. Human Biology, 7:
Bideau A. (1986): Duration of life in women after age 45 was longer for those women who borne 12 or more children. Population 41:

73. Henry L. 1956. Travaux et Documents.
Studies that Found no Relationship Between Postreproductive Longevity and Reproduction
Henry L Travaux et Documents.
Gauter, E. and Henry L Travaux et Documents, 26.
Knodel, J Demographic Behavior in the Past.
Le Bourg et al., Experimental Gerontology, 28:

74. Study that Found a Trade-Off Between Reproductive Success and Postreproductive Longevity
Westendorp RGJ, Kirkwood TBL Human longevity at the cost of reproductive success. Nature 396:
Extensive media coverage including BBC and over 100 citations in scientific literature as an established scientific fact. Previous studies were not quoted and discussed in this article.

75. Point estimates of progeny number for married aristocratic women from different birth cohorts as a function of age at death. The estimates of progeny number are adjusted for trends over calendar time using multiple regression.
Source: Westendorp, Kirkwood, Human longevity at the cost of reproductive success. Nature, 1998, 396, pp

76. “… it is not a matter of reduced fertility, but a case of 'to have or have not'.“
Source: Toon Ligtenberg & Henk Brand. Longevity — does family size matter? Nature, 1998, 396, pp

77. Number of progeny and age at first childbirth dependent on the age at death of married aristocratic women
Source: Westendorp, R. G. J., Kirkwood, T. B. L. Human longevity at the cost of reproductive success. Nature, 1998, 396, pp

78. Source: Westendorp, R. G. J. , Kirkwood, T. B. L
Source: Westendorp, R. G. J., Kirkwood, T. B. L. Human longevity at the cost of reproductive success. Nature, 1998, 396, pp

79. Do longevous women have impaired fertility
Do longevous women have impaired fertility ? Why is this question so important and interesting? Scientific Significance
This is a testable prediction of some evolutionary theories of aging - disposable soma theory of aging (Kirkwood)
"The disposable soma theory on the evolution of ageing states that longevity requires investments in somatic maintenance that reduce the resources available for reproduction“ (Westendorp, Kirkwood, Nature, 1998).

80. Do longevous women have impaired fertility ?
Practical Importance.
Do we really wish to live a long life at the cost of infertility?:
“the next generations of Homo sapiens will have even longer life spans but at the cost of impaired fertility”
Rudi Westendorp “Are we becoming less disposable? EMBO Reports, 2004, 5: 2-6.
"... increasing longevity through genetic manipulation of the mechanisms of aging raises deep biological and moral questions. These questions should give us pause before we embark on the enterprise of extending our lives“
Walter Glennon "Extending the Human Life Span", Journal of Medicine and Philosophy, 2002, Vol. 27, No. 3, pp

81. Educational Significance
Do we teach our students right?
Impaired fertility of longevous women is often presented in scientific literature and mass media as already established fact (Brandt et al., 2005; Fessler et al., 2005; Schrempf et al., 2005; Tavecchia et al., 2005; Kirkwood, 2002; Westendorp, 2002, 2004; Glennon, 2002; Perls et al., 2002, etc.).
This "fact" is now included in teaching curriculums in biology, ecology and anthropology world-wide (USA, UK, Denmark).
Is it a fact or artifact ?

82. General Methodological Principle:
Before making strong conclusions, consider all other possible explanations, including potential flaws in data quality and analysis
Previous analysis by Westendorp and Kirkwood was made on the assumption of data completeness: Number of children born = Number of children recorded
Potential concerns: data incompleteness, under- reporting of short-lived children, women (because of patrilineal structure of genealogical records), persons who did not marry or did not have children. Number of children born   >> Number of children recorded

83. Test for Data Completeness
Direct Test: Cross-checking of the initial dataset with other data sources
We examined 335 claims of childlessness in the dataset used by Westendorp and Kirkwood. When we cross-checked these claims with other professional sources of data, we  found that at least 107 allegedly childless women (32%) did have children!
At least 32% of childlessness claims proved to be wrong ("false negative claims") !
Some illustrative examples:
Henrietta Kerr (1653­1741) was apparently childless in the dataset used by Westendorp and Kirkwood and lived 88 years. Our cross-checking revealed that she did have at least one child, Sir William Scott (2nd Baronet of Thirlstane, died on October 8, 1725).
 Charlotte Primrose (1776­1864) was also considered childless in the initial dataset and lived 88 years. Our cross-checking of the data revealed that in fact she had as many as five children: Charlotte (1803­1886), Henry (1806­1889), Charles (1807­1882), Arabella ( ), and William (1815­1881).
Wilhelmina Louise von Anhalt-Bernburg (1799­1882), apparently childless, lived 83 years. In reality, however, she had at least two children, Alexander (1820­1896) and Georg (1826­1902).

84. Point estimates of progeny number for married aristocratic women from different birth cohorts as a function of age at death. The estimates of progeny number are adjusted for trends over calendar time using multiple regression.
Source: Westendorp, R. G. J., Kirkwood, T. B. L. Human longevity at the cost of reproductive success. Nature, 1998, 396, pp

85. Antoinette de Bourbon (1493-1583)
Lived almost 90 years
She was claimed to have only one child in the dataset used by Westendorp and Kirkwood: Marie ( ), who became a mother of famous Queen of Scotland, Mary Stuart.
Our data cross-checking revealed that in fact Antoinette had 12 children!
Marie
Francois Ier
Louise
Renee
Charles
Claude
Louis
Philippe
Pierre 1529
Antoinette
Francois
Rene

86. Characteristics of Our Data Sample for ‘Reproduction-Longevity’ Studies
3,723 married women born in and belonging to the upper European nobility.
Women with two or more marriages (5%) were excluded from the analysis in order to facilitate the interpretation of results (continuity of exposure to childbearing).
Every case of childlessness has been checked using at least two different genealogical sources.

87. Typical Mistakes in Biological Studies of Human Longevity
Using lifespan data for non-extinct birth cohorts (“cemetery effect”)
Failure to control for birth cohort – spurious correlations may be found if variables have temporal dynamics
Failure to take into account social events and factors – e.g., failure to control for age at marriage in longevity-reproduction studies

88. Lifespan is not affected by physiological load of multiple pregnancies
Childlessness is better outcome than number of children for testing evolutionary theories of aging on human data
Applicable even for population practicing birth control (few couple are voluntarily childless)
Lifespan is not affected by physiological load of multiple pregnancies
Lifespan is not affected by economic hardship experienced by large families

90. Source:
Gavrilova et al. Does exceptional human longevity come with high cost of infertility? Testing the evolutionary theories of aging. Annals of the New York Academy of Sciences, 2004, 1019:

91. Source:
Gavrilova, Gavrilov. Human longevity and reproduction: An evolutionary perspective. In: Grandmotherhood - The Evolutionary Significance of the Second Half of Female Life. Rutgers University Press, 2005,

92. Short Conclusion:
Exceptional human longevity is NOT associated with infertility or childlessness

93. More Detailed Conclusions
We have found that previously reported high rate of childlessness among long-lived women is an artifact of data incompleteness, caused by under-reporting of children. After data cleaning, cross-checking and supplementation the association between exceptional longevity and childlessness has disappeared.
Thus, it is important now to revise a highly publicized scientific concept of heavy reproductive costs for human longevity. and to make corrections in related teaching curriculums for students.

94. More Detailed Conclusions (2)
It is also important to disavow the doubts and concerns over further extension of human lifespan, that were recently cast in biomedical ethics because of gullible acceptance of the idea of harmful side effects of lifespan extension, including infertility (Glannon, 2002).
There is little doubt that the number of children can affect human longevity through complications of pregnancies and childbearing, as well as through changes in socioeconomic status,  etc.  However,  the concept of heavy infertility cost of human longevity is not supported by data, when these data are carefully reanalyzed.

95. Heritability of Longevity

96. Mutation Accumulation Theory of Aging (Medawar, 1946)
From the evolutionary perspective, aging is an inevitable result of the declining force of natural selection with age.
So, over successive generations, late-acting deleterious mutations will accumulate, leading to an increase in mortality rates late in life.

97. Predictions of the Mutation Accumulation Theory of Aging
Mutation accumulation theory predicts that those deleterious mutations that are expressed in later life should have higher frequencies (because mutation-selection balance is shifted to higher equilibrium frequencies due to smaller selection pressure).
Therefore, ‘expressed’ genetic variability should increase with age (Charlesworth, Evolution in Age-structured Populations).
This should result in higher heritability estimates for lifespan of offspring born to longer-lived parents.

98. Linearity Principle of Inheritance in Quantitative Genetics
Dependence between parental traits and offspring traits is linear

99. The Best Possible Source on Familial Longevity Genealogies of European Royal and Noble Families
Charles IX d’Anguleme ( )
Marie-Antoinette von Habsburg-Lothringen ( )
Henry VIII Tudor ( )

100. Characteristic of our Dataset
Over 16,000 persons belonging to the European aristocracy
extinct birth cohorts
Adult persons aged 30+
Data extracted from the professional genealogical data sources including Genealogisches Handbook des Adels, Almanac de Gotha, Burke Peerage and Baronetage.

101. Daughter's Lifespan (Mean Deviation from Cohort Life Expectancy) as a Function of Paternal Lifespan
Offspring data for adult lifespan (30+ years) are smoothed by year running average.
Extinct birth cohorts (born in )
European aristocratic families ,443 cases

102. “… long life runs in families”
Paradox of low heritability of lifespan vs high familial clustering of longevity
“The Heritability of Life-Spans Is Small” C.E. Finch, R.E. Tanzi, Science, 1997, p.407
“… long life runs in families”
A. Cournil, T.B.L. Kirkwood, Trends in Genetics, 2001, p.233

103. Heritability Estimates of Human Lifespan
Author(s)
Heritability estimate
Population
McGue et al., 1993
0.22
Danish twins
Ljungquist et al., 1998
<0.33
Swedish twins
Bocquet-Appel, Jacobi, 1990
French village
Mayer, 1991
New England families
Cournil et al., 2000
0.27
Mitchell et al., 2001
0.25
Old Order Amish

104. Compensation Law of Mortality Convergence of Mortality Rates with Age
1 – India, , males
2 – Turkey, , males
3 – Kenya, 1969, males
4 - Northern Ireland, , males
5 - England and Wales, , females
6 - Austria, , females
7 - Norway, , females
Source: Gavrilov, Gavrilova,
“The Biology of Life Span” 1991

105. Compensation Law of Mortality (Parental Longevity Effects) Mortality Kinetics for Progeny Born to Long-Lived (80+) vs Short-Lived Parents
Sons
Daughters

106. Acknowledgments This study was made possible thanks to:
generous support from the
National Institute on Aging (R01 AG028620)
Stimulating working environment at the Center on Aging, NORC/University of Chicago

107. And Please Post Your Comments at our Scientific Discussion Blog:
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108. Spontaneous mutant frequencies with age in heart and small intestine
Source: Presentation of Jan Vijg at the IABG Congress, Cambridge, 2003