Post on 28-Dec-2015
Factors of Exceptional Longevity
Dr. Natalia S. Gavrilova, Ph.D.Dr. Leonid A. Gavrilov, Ph.D.
Center on Aging
NORC and The University of Chicago Chicago, Illinois, USA
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
Sarah Knauss (1880-1999)Pennsylvania, USA
Revolution in Information Technology
What does it mean for longevity studies?
Over 75 millions of computerized genealogical records are available online now!
Computerized genealogies is a promising source of information about potential predictors of exceptional longevity: life-course events, early-life conditions and family history of longevity
Computerized Genealogies as a Resource for Longevity
Studies
Pros: provide important information about family and life-course events, which otherwise is difficult to collect (including information about lifespan of parents and other relatives)
Cons: Uncertain data quality Uncertain validity and generalizability
For longevity studies the genealogies with detailed birth dates and death
dates for long-lived individuals (centenarians) and their relatives are of
particular interest
In this study 1,001 genealogy records for centenarians born in 1875-1899 were collected and used for further age validation
Internet Resources Used in Centenarian Age Verification
Social Security Administration Death Master File is publicly available at the Rootsweb website: http://ssdi.rootsweb.com/cgi-bin/ssdi.cgi
Head of household indexes and census page images for 1900, 1920 and 1910 federal censuses are provided by Genealogy.com
Individual indexes of enumerated persons by 1900, 1920 and 1930 federal censuses and census page images are provided by Ancestry.com
Steps of Centenarian Age Verification
1. Internal consistency checks of dates
2. Verification of death dates – linkage to the Social Security Administration Death Master File (DMF)
3. Verification of birth dates – linkage to early Federal censuses (1900, 1910, 1920, 1930)
A typical image of ‘centenarian’ family in 1900
census
Results of Centenarian Age Verification
1001 records consistency checks
990 records used for further verification
990 records were linked to the SSA Death Master File
Linkage success rate 77% (80% for centenarians born after 1890) In 3% of cases centenarian status was not confirmed
548 records found in DMF for persons born in 1890-1899 were then linked to early US censuses
Linkage success rate 80% when using Genealogy.com and 91% after supplementation with Ancestry.com. In 8% of cases a 1-year disagreement between genealogy and census record was observed
Conclusions of the Age Verification Study
Death dates of centenarians recorded in genealogies always require verification because of strong outliers (1.3%, misprints)
Birth dates of centenarians recorded in genealogies are sufficiently accurate - 92% are correct; for the remaining 8% only one-year disagreements
Quality of genealogical data is good enough if these data are pre-selected for high data quality
Birth Order and Chances to Become a Centenarian
Cases - 436 centenarians born in the United States between 1890 and 1899
Controls – their siblings born in the same time window (1,119 controls)
Model:
log(longevity odds ratio) = ax + bx2 + cz + dwhere x – birth order; z – family size; a,b,c,d – parameters of polynomial regression model
Birth Order and Survival to 100
Source:
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.
Birth order
1 2 3 4 5 6 7 8 9 10
Od
ds
to b
eco
me
a ce
nte
nar
ian
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
FemalesMales
New Developments
Can birth order effect be confirmed by more rigorous approach – a strictly within-family analysis?
Method of conditional logistic regression allows us to compare centenarians with their siblings within the same family. This eliminates confounding caused by between-family variation.
First-born siblings are more likely to become centenarians
(odds = 1.8) Conditional (fixed-effects) logistic regression Number of obs = 950 LR chi2(2) = 33.75 Prob > chi2 = 0.0000Log likelihood = -282.22348 Pseudo R2 = 0.0564
---------------------------------------------------------------------- Variable Odds Ratio P>|z| [95% Conf. Interval]-------------+--------------------------------------------------------
First-born status 1.772 0.006 1.180 2.663
Male sex .404 0.000 .284 .576---------------------------------------------------------------------------------
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 regression Number of obs = 797 LR chi2(2) = 27.54 Prob > chi2 = 0.0000Log likelihood = -247.93753 Pseudo R2 = 0.0526
---------------------------------------------------------------------------------- Variable | Odds Ratio P>|z| [95% Conf. Interval]-------------+--------------------------------------------------------------------
First-born status | 1.949 0.003 1.261 3.010
Male sex | .458 0.000 .318 .658
----------------------------------------------------------------------------------
Even at age 75 it still helps to be a first-born child
(odds = 1.7) Conditional (fixed-effects) logistic regression Number of obs = 557 LR chi2(2) = 19.03 Prob > chi2 = 0.0001Log likelihood = -186.22869 Pseudo R2 = 0.0486
---------------------------------------------------------------- Variable Odds Ratio P>|z| [95% Conf. Interval]-------------+--------------------------------------------------
First-born status 1.659 0.040 1.022 2.693
Male sex .459 0.000 .306 .687
----------------------------------------------------------------
Are young fathers responsible for birth order effect?
Conditional (fixed-effects) logistic regression Number of obs = 950 LR chi2(2) = 30.11 Prob > chi2 = 0.0000Log likelihood = -284.04284 Pseudo R2 = 0.0503
--------------------------------------------------------------------------- Variable Odds Ratio P>|z| [95% Conf. Interval]-------------+-------------------------------------------------------------
Born to young father 1.856 0.056 .985 3.496
Male sex .415 0.000 .291 .590
---------------------------------------------------------------------------
Birth order is more important than paternal age for chances
to become a centenarianConditional (fixed-effects) logistic regression Number of obs = 950 LR chi2(3) = 34.24 Prob > chi2 = 0.0000Log likelihood = -281.97993 Pseudo R2 = 0.0572
---------------------------------------------------------------- Variable Odds Ratio P>|z| [95% Conf. Interval]-------------+--------------------------------------------------
First-born status 1.635 0.039 1.025 2.607
Born to young father 1.294 0.484 .628 2.668
Male sex .407 0.000 .285 .580
--------------------------------------------------------------------------------------
Are young mothers responsible for the birth order
effect?Conditional (fixed-effects) logistic regression Number of obs = 950 LR chi2(2) = 37.35 Prob > chi2 = 0.0000Log likelihood = -280.42473 Pseudo R2 = 0.0624
------------------------------------------------------------------------------------- Variable Odds Ratio P>|z| [95% Conf. Interval]-------------+-----------------------------------------------------------------------
Born to young mother 2.031 0.001 1.326 3.110
Male sex .412 0.000 .289 .586
-------------------------------------------------------------------------------------
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 regression Number of obs = 950 LR chi2(3) = 39.05 Prob > chi2 = 0.0000Log likelihood = -279.57165 Pseudo R2 = 0.0653
------------------------------------------------------------------------------------- Variable Odds Ratio P>|z| [95% Conf. Interval]-------------+-----------------------------------------------------------------------
First-born status 1.360 0.189 .859 2.153
Born to young mother 1.760 0.021 1.089 2.846
Male sex .407 0.000 .285 .580
--------------------------------------------------------------------------------------
Even at age 75 it still helps to be born to young mother (age
<25)(odds = 1.9)
Conditional (fixed-effects) logistic regression Number of obs = 557 LR chi2(2) = 21.31 Prob > chi2 = 0.0000Log likelihood = -185.08639 Pseudo R2 = 0.0544
---------------------------------------------------------------------------------- Variable Odds Ratio P>|z| [95% Conf. Interval]-------------+--------------------------------------------------------------------
Born to young mother 1.869 0.012 1.145 3.051
Male sex .461 0.000 .307 .690
----------------------------------------------------------------------------------
Younger Moms' Kids Get Longevity Edge
Children of women under 25 twice as likely to live to 100, study finds
HealthDayMonday, April 17, 2006
MONDAY, April 17 (HealthDay News) -- Society's oldest members are most likely to be born to its youngest mothers, new research suggests.
The odds of living to 100 and beyond double when a person is born to a woman under 25 years of age, compared to those people born to older mothers, according to one of the most rigorous studies on the subject yet conducted.
The finding may also help clear up a statistical mystery -- three years ago, the same husband-and-wife team of researchers found that being the first-born child in a family also boosted longevity, although no one knew why.
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.
Back to a broader comparison of
‘centenarian’ and ‘non-centenarian’ families
Case-Control Study of Early-Life Conditions and Exceptional
LongevityCases - 382 households where centenarians (born in 1890-1899) were raised (from centenarian records linked to 1900 census)
Controls – 1% random sample of households with children below age 10 enumerated by 1900 census (from Integrated Public Use Microdata Sample, IPUMS: http://www.ipums.umn.edu/usa/index.html)
Childhood Residence and Survival to Age 100
Odds for household to be in a ‘centenarian’ group
A – New England and Middle Atlantic (reference group)
B – Mountain West and Pacific West
C – Southeast and Southwest
D – North Central0
0.5
1
1.5
2
2.5
3
3.5
A B C D
MalesFemales
Household Property Status During Childhood and Survival to Age 100
Odds for household to be in a ‘centenarian’ group
A – Rented House
B – Owned House
C – Rented Farm
D – Owned farm(reference group)
00.10.20.30.40.50.60.70.80.9
1
A B C D
MalesFemales
Paternal Immigration Status and Survival to Age 100
Odds for household to be in a ‘centenarian’ group
A – Father immigrated
B – Father native-born
(reference group)
00.10.20.30.4
0.50.60.70.80.9
1
A B
MalesFemales
No Association was Found (so far) Between Chances to
Become a Centenarian and
Paternal literacy
Child mortality of siblings
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
Month of Birth Predicts the US Life Expectancy at Age 80
Computed using the Social Security Administration data
Source:
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.
Seasonality (month-of-birth effects) for US life expectancy
Within-Family Study of Month-of-Birth Effects on Exceptional
Longevity
Cases - Centenarians born in 1890-1893
Controls – Their own siblings
Method: Conditional logistic regression
Advantage: Allows researchers to eliminate confounding effects of between-family variation
Month of Birth and the Likelihood to Become a Centenarian
Method:
Conditional logistic regression for odds to become a centenarian, using siblings as within-family control.
921 observations
Month of Birth and the Likelihood to Become a Centenarian
for Adult Siblings (20+ years)
Method:
Conditional logistic regression for odds to become a centenarian, using siblings as within-family control.
787 observations
Conclusions
The shortest conclusion was suggested in the title of the New York Times article about our previous related study
Conclusions
The chances of exceptional longevity are strongly modulated by such characteristics of person's childhood as:
Mother's age at person's birth Month of birth Place of birth and some other characteristics
of parental family
Most important, these findings indicate that a larger research project on early-life determinants of exceptional human longevity is likely to produce more new results, very important for future longevity studies
AcknowledgmentsThis study was made possible thanks to:
generous support from the National Institute on Aging and
the Society of Actuaries
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