Maternal Age, Fertility, and
Longevity
Leonid A. Gavrilov
Natalia S. Gavrilova
Center on Aging
NORC and The University of Chicago
Chicago, USA
New Vision of Aging-Related Diseases
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.
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.
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
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
Design of the Study
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 betweenfamily variation
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)
A typical image of ‘centenarian’
family in 1900 census
Maternal age and chances to live to
100 for siblings survived to age 50
Conditional (fixed-effects) logistic regression
N=5,778. Controlled for month of birth, paternal age
and gender. Paternal and maternal lifespan >50 years
Maternal age Odds ratio
95% CI
P-value
<20
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
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 <9 children.
2.6
p=0.020
2.4
p=0.013
Odds ratio
2.2
2
p=0.043
1.8
1.6
1.4
1.2
1
0.8
<20
20-24
25-29
30-34
Maternal Age at Birth
35-39
40+
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.
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
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
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
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.
Life Expectancy and Month of Birth
7.9
life expectancy at age 80, years
1885 Birth Cohort
1891 Birth Cohort
Data source:
Social Security
Death Master File
7.8
Published in:
7.7
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.
7.6
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month of Birth
Fertility and Longevity
How are they related?
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 Burke’s
‘Landed Gentry’ for males.
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.”
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.
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.
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: 743746.
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.
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 743746
“… it is not a matter of reduced fertility, but a
case of 'to have or have not'.“
Table 1 Relationship between age at death and number of children for married aristocratic
women
Age at death
Proportion childless
(years)
Number of children
mean for all women
mean for women having children
<20
0.66
0.45
1.32
21-30
0.39
1.35
2.21
31-40
0.26
2.05
2.77
41-50
0.31
2.01
2.91
51-60
0.28
2.4
3.33
61-70
0.33
2.36
3.52
71-80
0.31
2.64
3.83
81-90
0.45
2.08
3.78
>90
0.49
1.80
3.53
Source: Toon Ligtenberg & Henk Brand. Longevity — does family
size matter? Nature, 1998, 396, pp 743-746
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
Source: Westendorp, R. G. J., Kirkwood, T. B. L.
Human longevity at the cost of reproductive
success. Nature, 1998, 396, pp 743-746
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).
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.
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 ?
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, underreporting 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
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).
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
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.
Typical Mistakes in Biological
Studies of Human Longevity



Using lifespan data for nonextinct 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 longevityreproduction studies
Fertility
Longevity
Time
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
Proportion of Childless Women
as a Function of Their Lifespan
Data for European Aristocratic Women
70
Percent of Childless Women
60
Data published by Westendorp
and Kirkwood (1998)
50
40
30
20
Our corrected data
10
0
<20
20-29 30-39 40-49 50-59 60-69 70-79 80-89 90+
Women's Lifespan
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
Childlessness Odds Ratio Estimates
as a Function of Wife's Age at Marriage
Multivariate logistic regression analysis of
3,723 European aristocratic families
Childlessness Odds Ratio (Net Effect)
25
Net effects, adjusted for wife's calendar year of birth,
wife's lifespan, husband's lifespan
and husband's age at marriage
55
20
15
10
5
1,107
0
<20
20-25
25-30
30-35
35-40
Wife's Age at Marriage
40+
Childlessness Odds Ratio Estimates
as a Function of Husband's Age at Marriage
Multivariate logistic regression analysis of
3,723 European aristocratic families
Childlessness Odds Ratio (Net Effect)
5
Net effects, adjusted for wife's calendar year of birth,
wife's lifespan, husband's lifespan
and wife's age at marriage
268
4
3
2
150
1
0
<20
20-25 25-30 30-35 35-40 40-45
Husband's Age at Marriage
45+
Childlessness and lifespan in aristocratic women
Childlessness Odds Ratio Estimates
as a Function of Wife's Lifespan
Multivariate logistic regression analysis of
3,723 European aristocratic families
Our results were based on
carefully checked data
(genealogies for European
aristocratic families)
Childlessness Odds Ratio (Net Effect)
10
Source:
8
6
4
31 case
2
0
<20
20-29 30-39 40-49 50-59 60-69 70-79 80-89
Wife's Lifespan
90+
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.
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.
Short Conclusion:
Exceptional human longevity
is NOT associated with
infertility or childlessness
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 underreporting of children. After data cleaning, crosschecking 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.
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.
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 shorterlived controls
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
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/
Testing Predictions of the
Programmed and Stochastic
Theories of Aging:
Comparison of Variation in
Age at Death, Menopause,
and Sexual Maturation
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.
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

Age at natural menopause as a
marker of reproductive aging
Mean age (SD) at natural
menopause
Population
South Korean women
Mean age (SD)
at menopause,
years
46.9 (4.9)
Source
Hong et al., MATURITAS,
2007
Viennese women aged 47 49.2 (3.6)
to 68
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
49.5 (4.7)
48.9 (4.2)
Walker et al., International
Journal of Obstetrics &
Gynaecology, 2005
Black women in South
Africa: rural
urban
Our results using
the MIDUS study

National survey conducted in 1994/95

Americans aged 25-74


core national sample (N=3,485)
city oversamples (N=957)

Additional samples: twins, siblings

Subsample used in this study: women having
natural menopause (no surgeries affecting the
age at menopause) aged 60-74
0
.1
Density
.2
.3
DISTRIBUTION OF AGE AT
MENARCHE IN THE MIDUS
SAMPLE
8
10
12
14
age of menarche
16
18
.04
0
.02
Density
.06
.08
DISTRIBUTION OF AGE AT
MENOPAUSE IN THE MIDUS
SAMPLE
20
30
40
50
age of menopause
60
70
.02
0
.01
Density
.03
.04
DISTRIBUTION OF AGE AT
DEATH, SWEDISH FEMALES,
1995
0
50
100
age
Data source: Human Mortality Database
Variation for characteristics of
human aging and development
Characteristic
Mean age Coefficient
(SD) years
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
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
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
Standard Deviations (Y-axis) and Mean Values (Xaxis) for Human Life Cycle Characteristics
Mean ages at menarche (1), menopause (2), and death (3)
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