Early-Life Predictors of Exceptional Early-Life Predictors of Exceptional Longevity in the United States:Longevity in the United States:
Why Centenarians are Different From Their Why Centenarians are Different From Their
Shorter-Lived SiblingsShorter-Lived Siblings
Leonid A. Gavrilov, Ph.D.Natalia S. Gavrilova, Ph.D.
Center on Aging
NORC and The University of Chicago Chicago, USA
Some results from our Some results from our previous studies of previous studies of
exceptional longevityexceptional longevity
Parental longevity is an Parental longevity is an important predictor of the important predictor of the
offspring longevityoffspring longevity
Daughter's LifespanDaughter's Lifespan(Mean Deviation from the Birth Cohort Life Expectancy)(Mean Deviation from the Birth Cohort Life Expectancy)
as a Function of Paternal Lifespanas a Function of Paternal Lifespan
Paternal Lifespan, years40 50 60 70 80 90 100
Dau
ghte
r's L
ifesp
an (d
evia
tion)
, yea
rs
-2
2
4
6
0
Offspring data for adult lifespan (30+ years) are smoothed by 5-year running average.
Extinct birth cohorts (born in 1800-1880)
European aristocratic families. 6,443 cases
Source: Gavrilova, Gavrilov, JAAM, 2001
Study of the U.S. centenarians Study of the U.S. centenarians based on computerized family based on computerized family histories linked to early U.S. histories linked to early U.S.
censusescensuses
Household Property Status During Childhood Household Property Status During Childhood and Survival to Age 100and Survival to Age 100
Odds for household to be in a ‘centenarian’ groupOdds for household to be in a ‘centenarian’ group
00.10.20.30.40.50.60.70.80.9
1
A B C D
MalesFemales
A – Rented House
B – Owned House
C – Rented Farm
D – Owned farm(reference group)
Childhood Residence Childhood Residence and Survival to Age 100and Survival to Age 100
Odds for household to be in a ‘centenarian’ groupOdds for household to be in a ‘centenarian’ group
00.5
11.5
22.5
33.5
A B C D
MalesFemales
A – New England and Middle Atlantic (reference group)
B – Mountain West and Pacific West
C – Southeast and Southwest
D – North Central
Study of the U.S. male Study of the U.S. male centenarians linked to the WWI centenarians linked to the WWI
draft registration cards:draft registration cards:
Socio-demographic and physical Socio-demographic and physical characteristics at age 30 and characteristics at age 30 and
survival to age 100survival to age 100
Body Build and Survival to 100Body Build and Survival to 100
Results of multivariate studyResults of multivariate studyVariable Odds
RatioP-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 0.268Native born vs foreign b.
1.13 0.682
Having children by age 30 and survival Having children by age 30 and survival to age 100to age 100
Conditional (fixed-effects) logistic regressionN=171. 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
Study based on individual Study based on individual records from the Social records from the Social Security Death Index Security Death Index
Month of BirthJan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
life
expe
ctan
cy a
t age
80,
yea
rs
7.6
7.7
7.8
7.9
1885 Birth Cohort1891 Birth Cohort
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.
The role of early-life conditions The role of early-life conditions in shaping late-life mortality is in shaping late-life mortality is
now well recognizednow well recognized
New Vision of Aging-Related DiseasesNew Vision of Aging-Related Diseases
How centenarians are How centenarians are different from their different from their
shorter-lived sibling?shorter-lived sibling?
Within-Family ApproachWithin-Family ApproachAllows researchers to eliminate
between-family variation including the differences in
genetic background and childhood living conditions
Computerized genealogies is a Computerized genealogies is a promising source of information promising source of information about potential predictors of about potential predictors of exceptional longevity: life-exceptional longevity: life-course events, early-life course events, early-life conditions and family history of conditions and family history of longevity longevity
Internet Resources Used for Internet Resources Used for Centenarian Data Collection and Centenarian Data Collection and
VerificationVerificationComputerized genealogies available at the
Rootsweb website
Social Security Administration Death Master File is publicly available at the Rootsweb website
Individual indexes of enumerated persons by 1900, 1910, 1920 and 1930 federal censuses and census page images are provided by Ancestry.com
Steps of the studySteps of the study
23,127 records of centenarians born in 1880-1895 with known information about parents were identified using the Rootsweb genealogical website
2,834 centenarians having detailed information on their 21,893 siblings were selected
1,711 centenarians had their death dates verified using the Social Security Death Index
Finally 1,081 centenarians born in a more narrow window of 1880-1889 were used for further analyses
Within-Family Study Within-Family Study of Exceptional Longevityof Exceptional Longevity
Cases - 1,081 centenarians born in the U.S. in 1880-1889 with known information about parental lifespan
Controls – 6,413 their own shorter-lived siblings (5,778 survived to age 50)
Method: Conditional logistic regression
Advantage: Allows researchers to eliminate confounding effects of between-family variation
Design of the StudyDesign of the Study
Multivariate Analysis:Multivariate Analysis:Conditional logistic regressionConditional logistic regression
For 1:n matched study, the likelihood for N matched sets is given by:
Where ui is the covariate vector for the case and vi1, vi2 , …, vin(i) are covariate vectors for the ni controls, respectively, of the ith matched set.
N
in
jij
ii
v
u1
1
)exp(
)exp(
Maternal age and odds to live to 100 for Maternal age and odds to live to 100 for siblings survived to age 50siblings survived to age 50
Conditional (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 1.73 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
Does maternal age effect Does maternal age effect depend on the gender of depend on the gender of
siblings?siblings?Data were split by the gender of
siblings (‘daughters only’ and ‘sons only’ analyses)
Maternal age and odds to live to 100, by Maternal age and odds to live to 100, by gender. Odds ratios (p-value)gender. Odds ratios (p-value)
Conditional (fixed-effects) logistic regressionControlled for month of birth and paternal. Paternal and maternal lifespan >50 years
Maternal age
Daughters n=4732
Sons N=1681
<20 1.43 (0.121) 1.72 (0.162)
20-24 1.37 (0.067) 1.77 (0.042)
25-29 1.57 (0.006) 1.24 (0.435)
30-34 1.07 (0.708) 1.29 (0.360)
35-39 1.10 (0.0552) 0.92 (0.769)
40+ Reference Reference
QuestionQuestion
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.
ResultsResults
In smaller families (less than 9 children) the effect of young mother is even larger (for siblings survived to age 50 and maternal age 20-24 years vs 40+ years):
Odds ratio = 2.23, P=0.013; 95%CI = 1.18 – 4.21 Compare to larger families (more than 9 children):Odds ratio = 1.39, P=0.188; 95%CI = 0.85 – 2.27Conclusion:"Young mother effect" is not confined to extremely large
family size
People Born to Young Mothers Have Twice People Born to Young Mothers Have Twice Higher Chances to Live to 100Higher Chances to Live to 100
Within-family study of 2,153 centenarians and their siblings survived to age 50. Family size <9 children.Within-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
ratio
Maternal Age at Birth
p=0.020
p=0.013
p=0.043
Being born to Young Mother Helps Being born to Young Mother Helps Laboratory Mice to Live LongerLaboratory Mice to Live Longer
Source:
Tarin et al., Delayed Motherhood Decreases Life Expectancy of Mouse Offspring.
Biology of Reproduction 2005 72: 1336-1343.
Possible explanationPossible explanationThese 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.
Siblings Born in November Have Twice Higher Siblings Born in November Have Twice Higher Chances to Live to 100Chances to Live to 100
Within-family study of 5,698 centenarians and their siblings survived to age 50Within-family study of 5,698 centenarians and their siblings survived to age 50
AcknowledgmentsAcknowledgmentsThis study was made possible
thanks to:
generous support from the National Institute on Aging grant #R01AG028620
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Final ConclusionFinal Conclusion
The shortest conclusion was suggested in the title of the New York Times article about this study
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