Search for mechanisms of exceptional human

longevity

Dr. Natalia S. Gavrilova, Ph.D.Dr. Leonid A. Gavrilov, Ph.D.

Center on Aging

NORC and The University of Chicago Chicago, USA

Approach

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

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)

Revolution in Information Technology

What does it mean for longevity studies?

Millions of official census, birth, marriage, death and other records are available online now!

Predictors of Exceptional Longevity

Study 1

How centenarians are different from their shorter-

lived sibling?

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

Design of the Study

A typical image of ‘centenarian’ family in 1900

census

First-born siblings are more likely to become centenarians

(odds = 1.8)

Conditional (fixed-effects) logistic regressionN=950, Prob > chi2=0.0000

VariableOdds ratio

95% CIP-

value

First-born status

1.771.18-2.66

0.006

Male sex 0.400.28-0.58

<0.001

Birth Order and Odds to Become a Centenarian

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)

First-born adult siblings (20+years) are more likely

to become centenarians (odds = 1.95)

Conditional (fixed-effects) logistic regressionN=797, Prob > chi2=0.0000

VariableOdds ratio

95% CIP-

value

First-born status

1.951.26-3.01

0.003

Male sex 0.460.32-0.66

<0.001

Are young fathers responsible for birth order effect?

Conditional (fixed-effects) logistic regressionN=950, Prob > chi2=0.0000

VariableOdds ratio

95% CIP-

value

Born to young father

1.860.99-3.50

0.056

Male sex 0.420.29-0.59

<0.001

Birth order is more important than paternal age for chances

to become a centenarianConditional (fixed-effects) logistic regressionN=950, Prob > chi2=0.0000

VariableOdds ratio

95% CIP-

value

First-born status

1.641.03-2.61

0.039

Born to young father

1.290.63-2.67

0.484

Male sex 0.410.29-0.58

<0.001

Are young mothers responsible for the birth order

effect?

Conditional (fixed-effects) logistic regressionN=950, Prob > chi2=0.0000

VariableOdds ratio

95% CIP-

value

Born to young mother

2.031.33-3.11

0.001

Male sex 0.410.29-0.59

<0.001

Maternal Age at Person’s Birth and Odds to Become a

Centenarian

Birth order effect explained:Being born to young mother!

Conditional (fixed-effects) logistic regressionN=950, Prob > chi2=0.0000

VariableOdds ratio

95% CIP-

value

First-born status

1.360.86-2.15

0.189

Born to young mother

1.761.09-2.85

0.021

Male sex 0.410.29-0.58

<0.001

Even at age 75 it still helps to be born to young mother (age

<25)(odds = 1.9)

Conditional (fixed-effects) logistic regressionN=557, Prob > chi2=0.0000

VariableOdds ratio

95% CIP-

value

Born to young mother

1.861.15-3.05

0.012

Male sex 0.460.31-0.69

<0.001

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.

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.

Study 2

How centenarians are different from their shorter-lived peers

when compared at young adult age?

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

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

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.

Small Dogs Live Longer

Miller RA. Kleemeier Award Lecture: Are there genes for aging? J Gerontol Biol Sci 54A:B297–B307, 1999.

Small Mice Live Longer

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

Design of the Study

De athw in d o w fo r

ce n te n arian s

Birthyear

Death window for controls

Controls: M ales m atched on birth year, race andcounty of registration

M ale Centenarians born in 1887(from the Social Security Adm inistration Death M aster F ile)

1887 1917-18 1987

W W I draftregistration

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)

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.

WWI Draft RegistrationRegistration 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 7:00 or 7:30 opening of registration, while businesses, schools, and saloons closed to accommodate the event.

Registration Day Parade

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

Draft Registration Card:An Example

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

Height and Survival to 100

0

10

20

30

40

50

60

70

cases controls

short

medium

tall

Body Build and Survival to 100

0

10

20

30

40

50

60

70

80

cases controls

slender

medium

stout

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

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

Results of multivariate study

Significant 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

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

Having children by age 30 and survival to age 100

Conditional (fixed-effects) logistic regressionN=171. Reference level: no children

VariableOdds ratio

95% CIP-

value

1-3 children 1.620.89-2.95

0.127

4+ children 2.710.99-7.39

0.051

Conclusion

The study of height and build among men born in 1887 suggests that rapid growth and overweight at young adult age (30 years) might be harmful for attaining longevity

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

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.

AcknowledgmentsThis study was made possible thanks to:

generous support from the National Institute on Aging and

the Society of Actuaries

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/

Multivariate Analysis:Conditional logistic

regression

For 1:1 matched study, the conditional likelihood is given by:

Where xi1 and xi0 are vectors representing the prognostic factors for the case and control, respectively, of the ith matched set.

101 ))(exp(1( i

ii xx

Final Conclusion

The shortest conclusion was suggested in the title of the New York Times article about this study

New Striking Findings: Invitation for discussion

and brain-storming!

The favorable "Young Mother Effect" is particularly strong when parents have particularly large differences in their lifespan

Odds Ratio to live to 100 years if born to young mother

as a function of maternal and paternal lifespans (tertiles)

MOTHER

FATHERShorter-lived

Medium-lived

Longer-lived

Shorter-lived

0.93 1.29 4.04*

Medium-lived

3.49* 3.01 1.50

Longer-lived

11.62* 1.21 0.36

* p<0.05

Month of Birth and the Likelihood to Become a Centenarian

among WWI draft participants

Method:

Conditional logistic regression for odds to become a centenarian. Controls – men matched on birth year, race and county of draft registration.

Adjusted for occupation, height and build.

76 observations

Month of Birth and the Likelihood to Become a Centenarian

for Adult Siblings

Method:

Conditional logistic regression for odds to become a centenarian, using siblings as within-family control.

787 observations

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.

Results In smaller families (less than 9 children) the

effect of young mother is even larger:Odds ratio = 2.23, P=0.004; 95%CI = 1.30 -

3.98 Compare to larger families (more than 9

children):Odds ratio = 1.72, P=0.11; 95%CI = 0.88 - 3.34

Conclusion:"Young mother effect" is not confined to

extremely large family size