Title: Biodemography and perspectives of human lifespan extension
1Biodemography and perspectives of human lifespan
extension
- Leonid A. Gavrilov, Ph.D.
- Natalia S. Gavrilova, Ph.D.
-
- Center on Aging
- NORC and The University of Chicago
- Chicago, USA
2Statement 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.
3Why should we expect high initial damage load in
biological systems?
- General argument-- biological systems are
formed by self-assembly without helpful external
quality control. - Specific arguments
- Most cell divisions responsible for DNA
copy-errors occur in early development leading to
clonal expansion of mutations - Loss of telomeres is also particularly high in
early-life - Cell cycle checkpoints are disabled in early
development
4Spontaneous mutant frequencies with age in heart
and small intestine
Source Presentation of Jan Vijg at the IABG
Congress, Cambridge, 2003
5Practical 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.
6Life 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.
7Approach
- To study success stories in long-term avoidance
of fatal diseases (survival to 100 years) and
factors correlated with this remarkable survival
success
8Centenarians 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)
9Revolution in Information TechnologyWhat does
it mean for longevity studies?
- Millions of official census, birth, marriage,
death and other records are available online now!
10Predictors of Exceptional Longevity
11Study 1
- How centenarians are different from their
shorter-lived sibling?
12Within-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
13Design of the Study
14A typical image of centenarian family in 1900
census
15First-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
16Birth Order and Odds to Become a Centenarian
17Can 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)
18First-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
19Are 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
20Birth 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
21Are 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
22Maternal Age at Persons Birth and Odds to Become
a Centenarian
23Birth 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
24Even 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
25Being 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.
26Possible 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.
27Study 2
- How centenarians are different from their
shorter-lived peers when compared at young adult
age?
28Physical 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
29Height What to Expect
- Height seems to be a good indicator of
nutritional status and infectious disease history
in the past. - Historical studies showed a negative correlation
between height and mortality. - Hence we may expect that centenarians were taller
than average
30Build What to Expect
- Slender build may suggest a poor nutrition during
childhood. We may expect that centenarians were
less likely to be slender when young. - On the other hand, biological studies suggest
that rapid growth may be harmful and somewhat
delayed maturation may be beneficial for
longevity.
31Small Dogs Live Longer
Miller RA. Kleemeier Award Lecture Are there
genes for aging? J Gerontol Biol Sci
54AB297B307, 1999.
32Small Mice Live Longer
Source Miller et al., 2000. The Journals of
Gerontology Series A Biological Sciences and
Medical Sciences 55B455-B461
33Design of the Study
34Data Sources
- Social Security Administration Death Master File
- WWI civil draft registration cards (completed for
almost 100 percent men born between 1873 and
1900)
35WWI 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.
36WWI 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.
37Registration Day Parade
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39Information 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
40Draft Registration CardAn Example
41Study 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
240 selected men, 15 were not eligible for draft.
The linkage success for remaining records was
77.5 (174 records) - Controls men matched on birth year, race and
county of WWI civil draft registration
42SAMPLE 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
43Height and Survival to 100
44Body Build and Survival to 100
45Multivariate 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
46Results 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
47Results 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
48Other 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
49Having 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
50Conclusion
- 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
51Conclusion
- 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
52Other 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.
53The Ongoing Project
- Data for 15,031 female centenarians and 5,383
male centenarians born in 1891-1895 with known
genealogies were identified for further
validation. -
- These centenarians will be compared to their
peers born in the same birth year window and
survived to only 70 years.
54Acknowledgments
- This study was made possible thanks to
- generous support from the National Institute on
Aging and the Society of Actuaries -
55For 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/
56Multivariate AnalysisConditional logistic
regression
- For 11 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.
57Final Conclusion
- The shortest conclusion was suggested in the
title of the New York Times article about this
study
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