1. Biodemography of Exceptional Longevity Leonid A. Gavrilov Natalia S. Gavrilova Center on Aging NORC and The University of Chicago Chicago, USA

2. 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)

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

4. Winnie ain’t quitting now. Smith G D Int. J. Epidemiol. 2011;40:537-562 Published by Oxford University Press on behalf of the International Epidemiological Association © The Author 2011; all rights reserved. An example of incredible resilience

5. Exceptional longevity in a family of Iowa farmers Father: Mike Ackerman, Farmer, 1865-1939 lived 74 years Mother: Mary Hassebroek 1870-1961 lived 91 years 1. Engelke "Edward" M. Ackerman b: 28 APR 1892 in Iowa 101 2. Fred Ackerman b: 19 JUL 1893 in Iowa 103 3. Harmina "Minnie" Ackerman b: 18 SEP 1895 in Iowa 100 4. Lena Ackerman b: 21 APR 1897 in Iowa 105 5. Peter M. Ackerman b: 26 MAY 1899 in Iowa 86 6. Martha Ackerman b: 27 APR 1901 in IA 95 7. Grace Ackerman b: 2 OCT 1904 in IA 104 8. Anna Ackerman b: 29 JAN 1907 in IA 101 9. Mitchell Johannes Ackerman b: 25 FEB 1909 in IA 85

6. Meeting with 104-years-old Japanese centenarian (New Orleans, 2010)

7. 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

8. There are two factors of longevity 1. Modifiable factors – lifestyle, nutrition, early-life events and conditions, etc. 2. Non-modifiable factors – sex, race, ethnicity, genotype We are more interested in modifiable type of factors

9. The role of early-life conditions in shaping late-life mortality is now well recognized

10. 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.

11. 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.

12. 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.

13. Studies of centenarians require careful design and serious work on age validation The main problem is to find an appropriate control group

14. The most common approach: To use population control Limitation: If centenarians and controls are sampled differently then the results of the longevity study may be biased by the factors unrelated to differential survival (for example, genetic composition of centenarians and controls may be affected by migration)

15. Within-Family Approach: How centenarians are different from their shorter-lived sibling? Allows researchers to eliminate between-family variation including the differences in genetic background and childhood living conditions

16. Design of the Study

17. 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

18. 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)

19. A typical image of ‘centenarian’ family in 1900 census

20. Maternal age and chances to live to 100 for siblings survived to age 50 Conditional (fixed-effects) logistic regression N=5,778. Controlled for month of birth, paternal age and gender. Paternal and maternal lifespan >50 years Maternal ageOdds ratio95% CIP-value <201.731.05-2.880.033 20-241.631.11-2.400.012 25-291.531.10-2.120.011 30-341.160.85-1.600.355 35-391.060.77-1.460.720 40+1.00Reference

21. People Born to Young Mothers Have Twice Higher Chances to Live to 100 Within-family study of 2,153 centenarians and their siblings survived to age 50. Family size <9 children. p=0.020 p=0.013 p=0.043

22. 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.

23. 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.

24. 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

25. Siblings Born in September-November Have Higher Chances to Live to 100 Within-family study of 9,724 centenarians born in 1880-1895 and their siblings survived to age 50

26. 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.

27. Limitation of within-family approach Relatively small number of explanatory variables

28. Another approach: Centenarians and their shorter-lived peers How centenarians are different from their shorter-lived peers when compared at young adult age? Compare population-based sample of male centenarians born in 1887 to their shorter-lived peers from the same county participated in WWI civil draft registration (1917)

29. 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

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

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

32. Study Design Cases: male 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

33. 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)

34. 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.

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

36. Registration Day Parade

38. 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

39. Draft Registration Card: An Example

40. Height and survival to age 100

41. Body build and survival to age 100

42. 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

43. Results of multivariate study VariableOdds Ratio P-value Medium height vs short and tall height 1.350.260 Slender and medium build vs stout build 2.63*0.025 Farming2.20*0.016 Married vs unmarried0.680.268 Native born vs foreign b. 1.130.682

44. Having children by age 30 and survival to age 100 Conditional (fixed-effects) logistic regression N=171. Reference level: no children VariableOdds ratio95% CIP-value 1-3 children1.620.89-2.950.127 4+ children2.710.99-7.390.051

45. 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

46. 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.

47. One More Approach Compare centenarians and shorter- lived controls, which are randomly sampled from the same data universe: computerized genealogies Advantage: Possibility to control for familial longevity

48. Design of the study Compare centenarians with their peers born in the same year but died at age 65 years It is assumed that the majority of deaths at age 65 occur due to chronic diseases related to aging rather than injuries or infectious diseases (confirmed by analysis of available death certificates)

49. Case-control study of longevity Cases - 765 centenarians survived to age 100 and born in USA in 1890-91 Controls – 783 their shorter-lived peers born in USA in 1890-91 and died at age 65 years Method: Multivariate logistic regression Genealogical records were linked to 1900 and 1930 US censuses providing a rich set of variables

50. Age validation Death dates of centenarians were validated using the U.S. Social Security Administration Death Master File (DMF) Birth dates were validated through linkage of centenarian records to early U.S. censuses (when centenarians were children)

51. Variables Early-life conditions. 1900 census provided information on type of parental household (farm or non-farm, own or rented), parental literacy, parental immigration status, paternal occupation, number of children born/survived by mother, size of parental household in 1900, places of birth for household members. Midlife conditions. 1930 census provided type of person’s household, availability of radio in household, person’s age at first marriage, person’s occupation (husband’s occupation in the case of women), industry of occupation, number of children in household, veteran status. Family characteristics. Information on paternal and maternal lifespan, paternal and maternal age at person’s birth, number of spouses and siblings was provided by family histories.

52. Example of images from 1930 census (controls)

53. Parental longevity, early-life and midlife conditions and survival to age 100. Men Multivariate logistic regression, N=723 Variable Odds ratio 95% CIP-value Father lived 80+1.841.35-2.51<0.001 Mother lived 80+1.701.25-2.320.001 Farmer in 19301.671.21-2.310.002 Born in North-East2.081.27-3.400.004 Born in the second half of year 1.361.00-1.840.050 Radio in household, 19300.870.63-1.190.374

54. Parental longevity, early-life and midlife conditions and survival to age 100 Women Multivariate logistic regression, N=815 Variable Odds ratio 95% CIP-value Father lived 80+2.191.61-2.98<0.001 Mother lived 80+2.231.66-2.99<0.001 Husband farmer in 19301.150.84-1.560.383 Radio in household, 19301.611.18-2.200.003 Born in the second half of year 1.180.89-1.580.256 Born in the North-East region1.040.62-1.670.857

55. Variables found to be non-significant in multivariate analyses Parental literacy and immigration status, farm childhood, size of household in 1900, percentage of survived children (for mother) – a proxy for child mortality, sibship size, father-farmer in 1900 Marital status, veteran status, childlessness, age at first marriage Paternal and maternal age at birth, loss of parent before 1910

56. Conclusions Both midlife and early-life conditions affect survival to age 100 Parental longevity turned out to be the strongest predictor of survival to age 100 Men are likely to be more sensitive to the effects of early-life conditions.

57. Mortality patterns of men and women suggest that women may have more reserves (redundancy) compared to men in terms of reliability theory of aging U.S. population, 1999

58. Failure Rate as a Function of Age in Systems with Different Redundancy Levels Failure of elements is random

59. Possible explanation from the reliability theory of aging point of view Men are likely to have less reserves (lower redundancy) compared to women Organisms with lower redundancy may be more vulnerable to external shocks early in life, which deplete further their low reserves Hence men are more sensitive to the effects of early-life conditions.

60. References Gavrilov L.A., Gavrilova N.S. Predictors of Exceptional Longevity: Effects of Early-Life Childhood Conditions, Mid- Life Environment and Parental Characteristics. In: 2014 Living to 100 Monograph [published online – August, 2014, http://livingto100.soa.org/]. The Society of Actuaries, 2014, 18 pages Gavrilov L.A., Gavrilova N.S. Determinants of exceptional human longevity: new ideas and findings. Vienna Yearbook of Population Research, 2013, 11: 291-323 Gavrilov L.A., Gavrilova N.S. Biodemography of exceptional longevity: Early-life and mid-life predictors of human longevity. Biodemography and Social Biology, 2012, 58(1):14-39, DOI: 10.1080/19485565.2012.666121

61. 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

62. 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/

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