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Maternal%20Age,%20Fertility,%20and%20Longevity

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Title: Maternal%20Age,%20Fertility,%20and%20Longevity


1
Maternal Age, Fertility, and Longevity
  • Leonid A. Gavrilov
  • Natalia S. Gavrilova
  • Center on Aging
  • NORC and The University of Chicago
  • Chicago, USA

2
New Vision of Aging-Related Diseases
3
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. 1991.
The Biology of Life Span A Quantitative
Approach. Harwood Academic Publisher, New York.
4
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. 1991.
The Biology of Life Span A Quantitative
Approach. Harwood Academic Publisher, New York.
5
Hypothesis
  • Ovarian aging (decline in egg quality) may have
    long-term effects on offspring quality, health
    and longevity. Down syndrome is just a tip of the
    iceberg of numerous less visible defects.
  • Testable prediction
  • Odds of longevity decrease with maternal age
  • Negative impact of maternal aging on offspring
    longevity

6
Within-Family Approach How centenarians are
different from their shorter-lived siblings?
  • Allows researchers to eliminate between-family
    variation including the differences in genetic
    background and childhood living conditions

7
Design of the Study
8
Within-family study of longevity
Cases - 1,081 centenarians survived to age 100
and born in USA in 1880-1889 Controls 6,413
their shorter-lived brothers and sisters (5,778
survived to age 50) Method Conditional logistic
regression Advantage Allows to eliminate
between-family variation
9
Age validation is a key moment in human longevity
studies
  • Death date was validated using the U.S. Social
    Security Death Index
  • Birth date was validated through linkage of
    centenarian records to early U.S. censuses (when
    centenarians were children)

10
A typical image of centenarian family in 1900
census
11
Maternal age and chances to live to 100 for
siblings survived to age 50
Conditional (fixed-effects) logistic regression N5,778. Controlled for month of birth, paternal age and gender. Paternal and maternal lifespan gt50 years Conditional (fixed-effects) logistic regression N5,778. Controlled for month of birth, paternal age and gender. Paternal and maternal lifespan gt50 years Conditional (fixed-effects) logistic regression N5,778. Controlled for month of birth, paternal age and gender. Paternal and maternal lifespan gt50 years Conditional (fixed-effects) logistic regression N5,778. Controlled for month of birth, paternal age and gender. Paternal and maternal lifespan gt50 years
Maternal age Odds ratio 95 CI P-value
lt20 1.73 1.05-2.88 0.033
20-24 1.63 1.11-2.40 0.012
25-29 1.53 1.10-2.12 0.011
30-34 1.16 0.85-1.60 0.355
35-39 1.06 0.77-1.46 0.720
40 1.00 Reference
12
People Born to Young Mothers Have Twice Higher
Chances to Live to 100 Within-family study of
2,153 centenarians and their siblings survived to
age 50. Family size lt9 children.
p0.020
p0.013
p0.043
13
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.

14
Hypothesis
  • Egg Quality could be modulated by living
    conditions (e.g. diet), which may have seasonal
    variation
  • Testable prediction
  • Odds of longevity should depend on month of birth

15
Within-Family Study of Season of Birth and
Exceptional Longevity
Month of birth is a useful proxy characteristic
for environmental effects acting during in-utero
and early infancy development
16
Siblings Born in September-November Have Higher
Chances to Live to 100 Within-family study of
9,724 centenarians born in 1880-1895 and their
siblings survived to age 50
17
Possible explanations
  • These are several explanations of season-of birth
    effects on longevity pointing to the effects of
    early-life events and conditions
  • seasonal exposure to infections,
  • nutritional deficiencies,
  • environmental temperature and sun exposure.
  • All these factors were shown to play role in
    later-life health and longevity.

18
Life Expectancy and Month of Birth
Data source Social Security Death Master
File Published in Gavrilova, N.S., Gavrilov,
L.A. Search for Predictors of Exceptional Human
Longevity. In Living to 100 and Beyond
Monograph. The Society of Actuaries, Schaumburg,
Illinois, USA, 2005, pp. 1-49.
19
Fertility and Longevity
  • How are they related?

20
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.

21
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
    post-reproductive 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.

22
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.

23
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.

24
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 the scientific literature as an
    established scientific fact. Previous studies
    were not quoted and discussed in this article.

25
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

26
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
27
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

28
  • Source Westendorp, R. G. J., Kirkwood, T. B. L.
    Human longevity at the cost of reproductive
    success. Nature, 1998, 396, pp 743-746

29
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).
30
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.
31
  • Educational Significance
  • Do we teach our students right?
  • Impaired fertility of longevous women is
    often presented in the 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 ?

32
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 Numbe
    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

33
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
    (1809-1884), and William (18151881).

34
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

35
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.

36
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

37
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

38
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39
Data published by Westendorp and Kirkwood (1998)
Our corrected data
40
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

41
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43
Childlessness and lifespan in aristocratic women
Our results were based on carefully checked data
(genealogies for European aristocratic families)
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.
31 case
44
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.
45
Short Conclusion
  • Exceptional human longevity is NOT associated
    with infertility or childlessness

46
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.

47
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.

48
Current state of research
  • Some studies found support for disposable soma
    theory Lycett, Dunbar et al. 2000 Doblhammer and
    Oeppen 2003 Tabatabaie, Atzmon et al. 2011)
  • Other studies found no relation between longevity
    and reproduction (Gavrilova, Gavrilov et al.
    2004 Chereji, Gatz et al. 2013) or even higher
    fertility among long-lived individuals (Goegele,
    Pattaro et al. 2011).
  • Conclusion This issue is still not resolved
  • We plan to revisit this issue using data on
    validated American centenarians and their
    shorter-lived controls

49
Acknowledgment
  • This study was made possible thanks to
  • generous support from the National Institute on
    Aging grant R01AG028620
  • stimulating working environment at the Center
    on Aging, NORC/University of Chicago

50
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/

51
Testing Predictions of the Programmed and
Stochastic Theories of Aging Comparison of
Variation in Age at Death, Menopause, and Sexual
Maturation
52
One of the arguments used by the opponents of
programmed aging is a too high variation in
individual lifespans compared to the observed
variation of programmed events (such as the age
of sexual maturation).
  • The main goal of this study was to test the
    validity of this argument.

53
Measures of variability
  • Absolute measure standard deviation
  • For distribution of lifespan, demographers often
    calculate standard deviation at age 10 SD10
    (Edwards Tuljapurkar 2005).
  • Relative measure coefficient of variation.
    Equals the standard deviation divided by the mean

54
Age at natural menopause as a marker of
reproductive aging
55
Mean age (SD) at natural menopause
Population Mean age (SD) at menopause, years Source
South Korean women 46.9 (4.9) Hong et al., MATURITAS, 2007
Viennese women aged 47 to 68 49.2 (3.6) Kirchengast et al., International Journal of Anthropology , 1999
Mexico Puebla Mexico city 46.7 (4.77) 46.5 (5.00) Sievert, Hautaniemi, Human Biology, 2003
Black women in South Africa rural urban 49.5 (4.7) 48.9 (4.2) Walker et al., International Journal of Obstetrics Gynaecology, 2005
56
Our results using the MIDUS study
57
  • National survey conducted in 1994/95
  • Americans aged 25-74
  • core national sample (N3,485)
  • city oversamples (N957)
  • Additional samples twins, siblings
  • Subsample used in this study women having
    natural menopause (no surgeries affecting the age
    at menopause) aged 60-74

58
DISTRIBUTION OF AGE AT MENARCHE IN THE MIDUS
SAMPLE
59
DISTRIBUTION OF AGE AT MENOPAUSE IN THE MIDUS
SAMPLE
60
DISTRIBUTION OF AGE AT DEATH, SWEDISH FEMALES,
1995
Data source Human Mortality Database
61
Variation for characteristics of human aging and
development
Characteristic Mean age (SD) years Coefficient of variation Source
Age at onset of menarche 12.9 (1.6) 12.4 MIDUS data
Age at onset of menopause 49.7 (5.2) 10.5 MIDUS data
Age at death 78.7 (16.1) 20.5 USA, women, 1995. Human mortality database
62
Variation of age at onset of menarche and age at
death (in 2005)
Country Mean age (SD) for onset of menarche CV Mean age (SD) at death CV
France 12.84 (1.40) 10.9 83.3 (13.8) 16.6
Italy 12.54 (1.46) 11.6 83.3 (13.1) 15.7
Sweden 13.59 (1.41) 10.4 82.3 (12.9) 15.7
UK 12.89 (1.54) 12.0 80.2 (14.0) 17.5
USA 12.9 (1.60) 12.4 78.7 (16.1) 20.5
63
Variation of age at onset of menarche and age at
death (in 2005) after 10 years
Country Mean age (SD) for onset of menarche CV Mean age (SD10) at death after 10 CV10
France 12.84 (1.40) 10.9 83.7 (12.7) 15.2
Italy 12.54 (1.46) 11.6 83.7 (11.9) 14.2
Sweden 13.59 (1.41) 10.4 82.5 (12.0) 14.5
UK 12.89 (1.54) 12.0 81.2 (12.6) 15.5
USA 12.9 (1.60) 12.4 79.4 (14.3) 18.0
64
Standard Deviations (Y-axis) and Mean Values
(X-axis) for Human Life Cycle Characteristics
Mean ages at menarche (1), menopause (2), and
death (3)
65
Conclusions
  • Standard deviations for age at onset of menarche
    are about 10 times lower than standard deviations
    for ages at death
  • Coefficients of variation for ages at onset of
    menarche and ages at death for contemporary
    populations are of the same order of magnitude
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