Contemporary%20methods%20of%20mortality%20analysis:%20Determinants%20of%20Exceptional%20Longevity

1
Contemporary methods of mortality
analysisDeterminants of Exceptional Longevity

• Dr. Leonid A. Gavrilov, Ph.D.
• Dr. Natalia S. Gavrilova, Ph.D.
• Center on Aging
• NORC and The University of Chicago
• Chicago, Illinois, USA

2
Approach

• To study success stories in long-term avoidance
  of fatal diseases (survival to 100 years) and
  factors correlated with this remarkable survival
  success

3
Centenarians represent the fastest growing age
group in the industrialized countries

• Yet, factors predicting exceptional longevity and
  its time trends remain to be fully understood
• In this study we explored the new opportunities
  provided by the ongoing revolution in information
  technology, computer science and Internet
  expansion to explore early-childhood predictors
  of exceptional longevity

Jeanne Calment (1875-1997)
4
Revolution in Information TechnologyWhat does
it mean for longevity studies?

• Over 75 millions of computerized genealogical
  records are available online now!

5
Computerized genealogies is a promising source of
information about potential predictors of
exceptional longevity life-course events,
early-life conditions and family history of
longevity
6
Computerized Genealogies as a Resource for
Longevity Studies

• Pros provide important information about family
  and life-course events, which otherwise is
  difficult to collect (including information about
  lifespan of parents and other relatives)
• Cons Uncertain data quality
  Uncertain validity and generalizability
  

7
For longevity studies the genealogies with
detailed birth dates and death dates for
long-lived individuals (centenarians) and their
relatives are of particular interest

• In this study 1,001 genealogy records for
  centenarians born in 1875-1899 were collected and
  used for further age validation

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Steps of Centenarian Age Verification

1. Internal consistency checks of dates
2. Verification of death dates linkage to the
   Social Security Administration Death Master File
   (DMF)
3. Verification of birth dates linkage to early
   Federal censuses (1900, 1910, 1920, 1930)

10
Results of Centenarian Age Verification
1001 records consistency checks 990 records used for further verification
990 records were linked to the SSA Death Master File Linkage success rate 77 (80 for centenarians born after 1890) In 3 of cases centenarian status was not confirmed
548 records found in DMF for persons born in 1890-1899 were then linked to early US censuses Linkage success rate 80 when using Genealogy.com and 91 after supplementation with Ancestry.com. In 8 of cases a 1-year disagreement between genealogy and census record was observed
11
Conclusions of the Age Verification Study

• Death dates of centenarians recorded in
  genealogies always require verification because
  of strong outliers (1.3, misprints)
• Birth dates of centenarians recorded in
  genealogies are sufficiently accurate - 92 are
  correct for the remaining 8 only one-year
  disagreements
• Quality of genealogical data is good enough if
  these data are pre-selected for high data quality

12
Predictors of Exceptional Longevity
13
Study 1Compare centenarians with their
siblings (within-family study)
14
Within-Family Study of Exceptional Longevity
Cases - 198 Centenarians born in U.S. in
1890-1893 Controls Their own siblings Method
Conditional logistic regression Advantage
Allows researchers to eliminate confounding
effects of between-family variation
15
Design of the Study
16
A typical image of centenarian family in 1900
census
17
First-born siblings are more likely to become
centenarians (odds 1.8)
Conditional (fixed-effects) logistic regression N950, Prob gt chi20.0000 Conditional (fixed-effects) logistic regression N950, Prob gt chi20.0000 Conditional (fixed-effects) logistic regression N950, Prob gt chi20.0000 Conditional (fixed-effects) logistic regression N950, Prob gt chi20.0000
Variable Odds ratio 95 CI P-value
First-born status 1.77 1.18-2.66 0.006
Male sex 0.40 0.28-0.58 lt0.001
18
Birth Order and Odds to Become a Centenarian
19
Can the birth-order effect be a result of
selective child mortality, thus not applicable to
adults?

• Approach
• To compare centenarians with those siblings only
  who survived to adulthood (age 20)

20
First-born adult siblings (20years) are more
likely to become centenarians (odds
1.95)
Conditional (fixed-effects) logistic regression N797, Prob gt chi20.0000 Conditional (fixed-effects) logistic regression N797, Prob gt chi20.0000 Conditional (fixed-effects) logistic regression N797, Prob gt chi20.0000 Conditional (fixed-effects) logistic regression N797, Prob gt chi20.0000
Variable Odds ratio 95 CI P-value
First-born status 1.95 1.26-3.01 0.003
Male sex 0.46 0.32-0.66 lt0.001
21
Are young fathers responsible for birth order
effect?
Conditional (fixed-effects) logistic regression N950, Prob gt chi20.0000 Conditional (fixed-effects) logistic regression N950, Prob gt chi20.0000 Conditional (fixed-effects) logistic regression N950, Prob gt chi20.0000 Conditional (fixed-effects) logistic regression N950, Prob gt chi20.0000
Variable Odds ratio 95 CI P-value
Born to young father 1.86 0.99-3.50 0.056
Male sex 0.42 0.29-0.59 lt0.001
22
Birth order is more important than paternal age
for chances to become a centenarian
Conditional (fixed-effects) logistic regression N950, Prob gt chi20.0000 Conditional (fixed-effects) logistic regression N950, Prob gt chi20.0000 Conditional (fixed-effects) logistic regression N950, Prob gt chi20.0000 Conditional (fixed-effects) logistic regression N950, Prob gt chi20.0000
Variable Odds ratio 95 CI P-value
First-born status 1.64 1.03-2.61 0.039
Born to young father 1.29 0.63-2.67 0.484
Male sex 0.41 0.29-0.58 lt0.001
23
Are young mothers responsible for the birth order
effect?
Conditional (fixed-effects) logistic regression N950, Prob gt chi20.0000 Conditional (fixed-effects) logistic regression N950, Prob gt chi20.0000 Conditional (fixed-effects) logistic regression N950, Prob gt chi20.0000 Conditional (fixed-effects) logistic regression N950, Prob gt chi20.0000
Variable Odds ratio 95 CI P-value
Born to young mother 2.03 1.33-3.11 0.001
Male sex 0.41 0.29-0.59 lt0.001
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Maternal Age at Persons Birth and Odds to Become
a Centenarian
25
Birth order effect explainedBeing born to young
mother!
Conditional (fixed-effects) logistic regression N950, Prob gt chi20.0000 Conditional (fixed-effects) logistic regression N950, Prob gt chi20.0000 Conditional (fixed-effects) logistic regression N950, Prob gt chi20.0000 Conditional (fixed-effects) logistic regression N950, Prob gt chi20.0000
Variable Odds ratio 95 CI P-value
First-born status 1.36 0.86-2.15 0.189
Born to young mother 1.76 1.09-2.85 0.021
Male sex 0.41 0.29-0.58 lt0.001
26
Even at age 75 it still helps to be born to young
mother (age lt25)(odds 1.9)
Conditional (fixed-effects) logistic regression N557, Prob gt chi20.0000 Conditional (fixed-effects) logistic regression N557, Prob gt chi20.0000 Conditional (fixed-effects) logistic regression N557, Prob gt chi20.0000 Conditional (fixed-effects) logistic regression N557, Prob gt chi20.0000
Variable Odds ratio 95 CI P-value
Born to young mother 1.86 1.15-3.05 0.012
Male sex 0.46 0.31-0.69 lt0.001
27
Question

• Families were quite large in the past,
  particularly those covered by genealogical
  records (large family size bias).
• Is the "young mother effect" robust to the family
  size, and is it observed in smaller families too?
• Or is it confined to extremely large families
  only?
• Approach
• To split data in two equal parts by median family
  size (9 children) and re-analyze the data in each
  group separately.

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Results

• In smaller families (less than 9 children) the
  effect of young mother is even larger
• Odds ratio 2.23, P0.004 95CI 1.30 - 3.98
• Compare to larger families (more than 9
  children)
• Odds ratio 1.72, P0.11 95CI 0.88 - 3.34
• Conclusion
• "Young mother effect" is not confined to
  extremely large family size

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Being born to Young Mother Helps Laboratory Mice
to Live Longer

• Source
• Tarin et al., Delayed Motherhood
  Decreases Life Expectancy of Mouse Offspring.
• Biology of Reproduction 2005 72 1336-1343.

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Possible explanation

• These findings are consistent with the 'best eggs
  are used first' hypothesis suggesting that
  earlier formed oocytes are of better quality, and
  go to fertilization cycles earlier in maternal
  life.

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Study 2Compare centenarians when they were
young adults to their peersusing WWI Civil
Draft Registration Cards
32
Physical Characteristics at Young Age and
Survival to 100
A study of height and build of centenarians when
they were young using WWI civil draft
registration cards
33
Height What to Expect

1. Height seems to be a good indicator of
   nutritional status and infectious disease history
   in the past.
2. Historical studies showed a negative correlation
   between height and mortality.
3. Hence we may expect that centenarians were taller
   than average

34
Build What to Expect

1. Slender build may suggest a poor nutrition during
   childhood. We may expect that centenarians were
   less likely to be slender when young.
2. On the other hand, biological studies suggest
   that rapid growth may be harmful and somewhat
   delayed maturation may be beneficial for
   longevity.

35
Small Dogs Live Longer

Miller RA. Kleemeier Award Lecture Are there
genes for aging? J Gerontol Biol Sci
54AB297B307, 1999.
36
Small Mice Live Longer

Source Miller et al., 2000. The Journals of
Gerontology Series A Biological Sciences and
Medical Sciences 55B455-B461
37
Data Sources

1. Social Security Administration Death Master File
2. WWI civil draft registration cards (completed for
   almost 100 percent men born between 1873 and
   1900)

38
Study Design

• Cases men centenarians born in 1887 (randomly
  selected from the SSA Death Master File) and
  linked to the WWI civil draft records. Out of
  120 selected men, 19 were not eligible for draft.
  The linkage success for remaining 101 records was
  75 (76 records)
• Controls men matched on birth year, race and
  county of WWI civil draft registration

39
Design of the Study
40
WWI Civilian Draft Registration

• In 1917 and 1918, approximately 24 million
  men born between 1873 and 1900 completed draft
  registration cards. President Wilson proposed the
  American draft and characterized it as necessary
  to make "shirkers" play their part in the war.
  This argument won over key swing votes in
  Congress.

41
WWI Draft Registration
Registration was done in three parts, each
designed to form a pool of men for three
different military draft lotteries. During each
registration, church bells, horns, or other noise
makers sounded to signal the 700 or 730 opening
of registration, while businesses, schools, and
saloons closed to accommodate the event.
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Registration Day Parade

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Information Available in the Draft Registration
Card

• age, date of birth, race, citizenship
• permanent home address
• occupation, employer's name
• height (3 categories), build (3 categories), eye
  color, hair color, disability

45

46
SAMPLE CHARACTERISTICS ()
Centenarians Controls
Foreign born 20.5 22.2
Married 68.4 63.7
Had children 52.6 42.1
Farmers 31.6 23.4
African Am. 5.3 5.3
47
BODY HEIGHT AND BODY BUILD DISTRIBUTIONS ()
171 pairs of men born in 1887 Centenarians Controls 171 pairs of men born in 1887 Centenarians Controls 171 pairs of men born in 1887 Centenarians Controls
Body Height Body Height
short 6.4 8.8 6.4 8.8
medium 65.5 56.7 65.5 56.7
tall 28.1 34.5 28.1 34.5
Body Build
slender 25.2 25.2 25.2 25.2
medium 67.8 60.2 67.8 60.2
stout 7.0 14.6 7.0 14.6
48
Height Distribution Among Centenarians and
Controls
49
Body Build Distribution Among Centenarians and
Controls
50
Multivariate Analysis

• Conditional multiple logistic regression model
  for matched case-control studies to investigate
  the relationship between an outcome of being a
  case (extreme longevity) and a set of prognostic
  factors (height, build, occupation, marital
  status, number of children, immigration status)
• Statistical package Stata-10, command clogit

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Results of multivariate study
Variable Odds Ratio P-value
Medium height vs short and tall height 1.35 0.260
Slender and medium build vs stout build 2.63 0.025
Farming 2.20 0.016
Married vs unmarried 0.68 0.268
Native born vs foreign b. 1.13 0.682
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Results of multivariate studySignificant
predictors only
Variable Odds Ratio P-value
Slender body build reference stout build 2.54 0.040
Medium body build reference stout build 2.64 0.017
Farming 1.99 0.025
53
Other physical characteristics
Variable Odds Ratio P-value
Blue eye color 1.62 0.069
Short body height reference tall height 1.02 0.967
Medium body height reference tall height 1.43 0.212
Other variables include body build and farming
54
Having children by age 30 and survival to age 100
Conditional (fixed-effects) logistic regression N171. Reference level no children Conditional (fixed-effects) logistic regression N171. Reference level no children Conditional (fixed-effects) logistic regression N171. Reference level no children Conditional (fixed-effects) logistic regression N171. Reference level no children
Variable Odds ratio 95 CI P-value
1-3 children 1.62 0.89-2.95 0.127
4 children 2.71 0.99-7.39 0.051
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Conclusion

• The study of height and body build among men born
  in 1887 suggests that obesity at young adult age
  (30 years) has strong long-lasting effect in
  preventing longevity

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Other Conclusions

• Both farming and having large number of
  children (4) at age 30 significantly increased
  the chances of exceptional longevity by 100-200.
• The effects of immigration status, marital
  status, and body height on longevity were less
  important, and they were statistically
  insignificant in the studied data set.

57
Study 3Compare centenarians found in
computerized genealogies with general population
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Case-Control Study of Early-Life Conditions and
Exceptional Longevity
Cases - 382 white households where
centenarians (born in 1890-1899) were raised
(from centenarian records linked to 1900
census) Controls 1 random sample of white
households with children below age 10 enumerated
by 1900 census (from Integrated Public Use
Microdata Sample, IPUMS http//www.ipums.umn.edu/
usa/index.html)
59
Statistical Approach

• Logistic regression
• Dependent variable Households with child-future
  centenarian (y1) vs control households (y0)
• Predictor variables childhood residence,
  household property status, paternal immigration
  status, etc.

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Childhood Residence and Survival to Age 100Odds
for household to be in a centenarian group

• A New England and Middle Atlantic (reference
  group)
• B Mountain West and Pacific West
• C Southeast and Southwest
• D North Central

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Household Property Status During Childhood and
Survival to Age 100 Odds for household to be in
a centenarian group

• A Rented House
• B Owned House
• C Rented Farm
• D Owned farm
• (reference group)

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Paternal Immigration Status and Survival to Age
100 Odds for household to be in a centenarian
group

• A Father immigrated
• B Father native-born
• (reference group)

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No Association was Found (so far) Between Chances
to Become a Centenarian and

• Paternal literacy
• Child mortality of siblings

64
Limitations

• Reporting bias in genealogies
• People mentioned in genealogies may be not
  representative to the whole population
• more fertile, longer-living (?), wealthier (?),
  more educated (?)

65
General Conclusionof Centenarian Studies

• The shortest conclusion was suggested in the
  title of the New York Times article about our
  previous related study

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For More Information and Updates Please Visit Our
Scientific and Educational Website on Human
Longevity

• http//longevity-science.org

And Please Post Your Comments at our Scientific
Discussion Blog

• http//longevity-science.blogspot.com/

68
What are the Links Between Human Longevity and
Fertility?
Testing the evolutionary theory of aging
69
Founding Fathers

• Beeton, M., Yule, G.U., Pearson, K. 1900. 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
  159-179.
• Data used English Quaker records and Whitney
  Family of Connectucut records for females and
  American Whitney family and Burkes Landed
  Gentry for males.

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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.

71
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, 7 392-418.
• Bideau A. (1986) Duration of life in women after
  age 45 was longer for those women who borne 12 or
  more children. Population 41 59-72.

72
Studies that Found no Relationship Between
Postreproductive Longevity and Reproduction

• Henry L. 1956. Travaux et Documents.
• Gauter, E. and Henry L. 1958. Travaux et
  Documents, 26.
• Knodel, J. 1988. Demographic Behavior in the
  Past.
• Le Bourg et al., 1993. Experimental Gerontology,
  28 217-232.

73
Study that Found a Trade-Off Between
Reproductive Success and Postreproductive
Longevity

• Westendorp RGJ, Kirkwood TBL. 1998. Human
  longevity at the cost of reproductive success.
  Nature 396 743-746.
• 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.

74
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 743-746

75
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
743-746
76
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 743-746

77

• Source Westendorp, R. G. J., Kirkwood, T. B. L.
  Human longevity at the cost of reproductive
  success. Nature, 1998, 396, pp 743-746

78
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).
79
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. 339-354.
80

• 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 ?

81
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 completenessNumbe
  r 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   gtgt
  Number of children recorded

82
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 examplesHenrietta 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
  (1809-1884), 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).

83
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 743-746

84
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
  (1515-1560), who became a mother of famous Queen
  of Scotland, Mary Stuart.
• Our data cross-checking revealed that in fact
  Antoinette had 12 children!
• Marie 1515-1560
• Francois Ier 1519-1563
• Louise 1521-1542
• Renee 1522-1602
• Charles 1524-1574
• Claude 1526-1573
• Louis 1527-1579
• Philippe 1529-1529
• Pierre 1529
• Antoinette 1531-1561
• Francois 1534-1563
• Rene 1536-1566

85
Characteristics of Our Data Sample for
Reproduction-Longevity Studies

• 3,723 married women born in 1500-1875 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.

86
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

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88
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 513-517.
89
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, 59-80.
90
Short Conclusion

• Exceptional human longevity is NOT associated
  with infertility or childlessness

91
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.

92
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.

93
Parental-Age Effects in Humans (accumulation of
mutation load in parental germ cells)

• What are the Data and the Predictions of
  Evolutionary Theory on the Quality of Offspring
  Conceived to Older Parents?
• Does progeny conceived to older parents live
  shorter lives?

94
Evolutionary Justification for Parental-Age
Effects

• "The evolutionary explanation of senescence
  proposes that selection against alleles with
  deleterious effects manifested only late in life
  is weak because most individuals die earlier for
  extrinsic reasons.
• This argument also applies to alleles whose
  deleterious effects are nongenetically
  transmitted from mother to progeny, that is, that
  affect the performance of progeny produced at
  late ages rather than of the aging individuals
  themselves.
• a decline of offspring quality with parental
  age should receive more attention in the context
  of the evolution of aging.
• Stearns et al. "Decline in offspring
  viability as a manifestation of aging in
  Drosophila melianogaster." Evolution, 2001, Vol.
  55, No. 9, pp. 18221831.

95
Genetic Justification for Paternal Age Effects

• Advanced paternal age at child conception is the
  main source of new mutations in human
  populations.
• James F. Crow, geneticist

Professor Crow (University of Wisconsin-Madison)
is recognized as a leader and statesman of
science. He is a member of the National Academy
of Sciences, the National Academy of Medicine,
The American Philosophical Society, the American
Academy of Arts and Sciences, the World Academy
of Art and Science.
96
Paternal Age and Risk of Schizophrenia

• Estimated cumulative incidence and percentage of
  offspring estimated to have an onset of
  schizophrenia by age 34 years, for categories of
  paternal age. The numbers above the bars show the
  proportion of offspring who were estimated to
  have an onset of schizophrenia by 34 years of
  age.
• Source Malaspina et al., Arch Gen
  Psychiatry.2001.

97
Paternal Age as a Risk Factor for Alzheimer
Disease

• MGAD - major gene for Alzheimer Disease
• Source L. Bertram et al. Neurogenetics, 1998, 1
  277-280.

98
Daughters' Lifespan (30) as a Functionof
Paternal Age at Daughter's Birth6,032 daughters
from European aristocratic families born in
1800-1880

• Life expectancy of adult women
  (30) as a function of father's age when these
  women were born (expressed as a difference from
  the reference level for those born to fathers of
  40-44 years).
• The data are point estimates (with standard
  errors) of the differential intercept
  coefficients adjusted for other explanatory
  variables using multiple regression with nominal
  variables.
• Daughters of parents who survived to 50
  years.

99
Contour plot for daughters lifespan (deviation
from cohort mean) as a function of paternal
lifespan (X axis) and paternal age at daughters
birth (Y axis)
7984 cases 1800-1880 birth cohorts European
aristocratic families Distance weighted least
squares smooth
100
Daughters Lifespan as a Function of
Paternal Age at Daughters Birth Data are
adjusted for other predictor variables
Daughters of shorter-lived fathers (lt80), 6727
cases
Daughters of longer-lived fathers (80), 1349
cases
101
Conclusions

• Being conceived to old fathers is a risk factor,
  but it is moderated by paternal longevity
• It is OK to be conceived to old father if he
  lives more than 80 years
• Methodological implications Paternal lifespan
  should be taken into account in the studies of
  paternal-age effects

102
Heritability of Longevity
103
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.

104
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, 1994. Evolution
  in Age-structured Populations).
• This should result in higher heritability
  estimates for lifespan of offspring born to
  longer-lived parents.

105
Linearity Principle of Inheritance in
Quantitative Genetics

• Dependence between parental traits and offspring
  traits is linear

106
The Best Possible Source on Familial Longevity
Genealogies of European Royal and Noble Families
Charles IX dAnguleme (1550-1574)
Marie-Antoinette von Habsburg-Lothringen
(1765-1793)
Henry VIII Tudor (1491-1547)
107
Characteristic of our Dataset

• Over 16,000 persons belonging to the European
  aristocracy
• 1800-1880 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.

108
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 5-year running average.
• Extinct birth cohorts (born in 1800-1880)
• European aristocratic families. 6,443
  cases

109
The Heritability of Life-Spans Is SmallC.E.
Finch, R.E. Tanzi, Science, 1997, p.407
Paradox of low heritability of lifespan vs high
familial clustering of longevity
long life runs in families A. Cournil, T.B.L.
Kirkwood, Trends in Genetics, 2001, p.233
110
Heritability Estimates of Human Lifespan
Author(s) Heritability estimate Population
McGue et al., 1993 0.22 Danish twins
Ljungquist et al., 1998 lt0.33 Swedish twins
Bocquet-Appel, Jacobi, 1990 0.10-0.30 French village
Mayer, 1991 0.10-0.33 New England families
Cournil et al., 2000 0.27 French village
Mitchell et al., 2001 0.25 Old Order Amish
111
Is the effect of non-linear inheritance remain
valid after controlling for other explanatory
variables?

• Lifespan of other parent
• Parental ages at childs conception
• Ethnicity
• Month of birth

112
Offspring Lifespan at Age 30 as a Function
of Paternal LifespanData are adjusted for
other predictor variables
Daughters, 8,284 cases
Sons, 8,322 cases
113
Offspring Lifespan at Age 30 as a Function
of Maternal LifespanData are adjusted for
other predictor variables
Daughters, 8,284 cases
Sons, 8,322 cases
114
Is the effect of non-linear inheritance observed
for non-biological relatives?

• We need to test an alternative hypothesis that
  positive effects of long-lived parents on the
  offspring survival may be non-biological and
  caused by common environment and life style
• What about lifespan of spouses?

115
Persons Lifespan as a Function of Spouse
LifespanData are adjusted for other predictor
variables
Married Women, 4,530 cases
Married Men, 5,102 cases
116
Acknowledgments

• This study was made possible thanks to
• generous support from the National Institute on
  Aging and the Society of Actuaries

117
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