Maternal Age, Fertility, and Longevity Leonid A. Gavrilov Natalia S. Gavrilova Center on Aging NORC...

Maternal Age, Fertility, and Longevity

Leonid A. GavrilovNatalia 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 ageNegative 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 between-family 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

50Conditional (fixed-effects) logistic regressionN=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 1.731.05-2.88

0.033

20-24 1.631.11-2.40

0.012

25-29 1.531.10-2.12

0.011

30-34 1.160.85-1.60

0.355

35-39 1.060.77-1.46

0.720

40+ 1.00Referenc

e

People Born to Young Mothers Have Twice Higher Chances to Live to 100Within-family study of 2,153 centenarians and their siblings survived to age 50. Family size

<9 children.

0.8

1

1.2

1.4

1.6

1.8

2

2.2

2.4

2.6

<20 20-24 25-29 30-34 35-39 40+

Odds

rati

o

Maternal Age at Birth

p=0.020

p=0.013

p=0.043

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 100Within-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.

Month of Birth

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

life

exp

ecta

ncy

at

age

80, y

ears

7.6

7.7

7.8

7.9

1885 Birth Cohort1891 Birth Cohort

Life Expectancy and Month of BirthData 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.

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

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.

Telephone inventor Alexander Graham Bell (1918):

“The longer lived parents were the most fertile.”

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: 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.

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

“… 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 Number of children

(years) 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, 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

Test for Data CompletenessDirect 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 (1653 1741) 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 (1776 1864) 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 (1803 1886), Henry (1806 1889), Charles (1807 1882), Arabella (1809-1884), and William (1815 1881).

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 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

Tim e

Fertility

Longevity

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 Womenas a Function of Their Lifespan

Data for European Aristocratic Women

Women's Lifespan

<20 20-29 30-39 40-49 50-59 60-69 70-79 80-89 90+

Pe

rce

nt

of

Ch

ild

les

s W

om

en

0

10

20

30

40

50

60

70

Data published by Westendorp and Kirkwood (1998)

Our corrected data

Antoinette de Bourbon(1493-1583)

Lived almost 90 yearsShe 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 Estimatesas a Function of Wife's Age at Marriage

Multivariate logistic regression analysis of3,723 European aristocratic families

Wife's Age at Marriage

<20 20-25 25-30 30-35 35-40 40+

Ch

ild

les

sn

es

s O

dd

s R

ati

o (

Ne

t E

ffe

ct)

0

5

10

15

20

25

Net effects, adjusted for wife's calendar year of birth, wife's lifespan, husband's lifespan and husband's age at marriage

55

1,107

Childlessness Odds Ratio Estimatesas a Function of Husband's Age at Marriage

Multivariate logistic regression analysis of3,723 European aristocratic families

Husband's Age at Marriage

<20 20-25 25-30 30-35 35-40 40-45 45+

Ch

ild

les

sn

es

s O

dd

s R

ati

o (

Ne

t E

ffe

ct)

0

1

2

3

4

5

Net effects, adjusted for wife's calendar year of birth, wife's lifespan, husband's lifespan and wife's age at marriage

268

150

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.

Childlessness Odds Ratio Estimatesas a Function of Wife's Lifespan

Multivariate logistic regression analysis of3,723 European aristocratic families

Wife's Lifespan

<20 20-29 30-39 40-49 50-59 60-69 70-79 80-89 90+

Ch

ild

les

sn

es

s O

dd

s R

ati

o (

Ne

t E

ffe

ct)

0

2

4

6

8

10

Childlessness and lifespan in aristocratic women

31 case

Our results were based on carefully checked data

(genealogies for European aristocratic families)

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 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.

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 shorter-lived 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 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

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

DISTRIBUTION OF AGE AT MENARCHE IN THE MIDUS

SAMPLE0

.1.2

.3D

en

sity

8 10 12 14 16 18age of menarche

DISTRIBUTION OF AGE AT MENOPAUSE IN THE MIDUS

SAMPLE0

.02

.04

.06

.08

Den

sity

20 30 40 50 60 70age of menopause

DISTRIBUTION OF AGE AT DEATH, SWEDISH FEMALES, 1995

0.0

1.0

2.0

3.0

4D

en

sity

0 50 100age

Data source: Human Mortality Database

Variation for characteristics of human aging and

developmentCharacterist

icMean 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

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 yearsCountry 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 (X-axis) 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