1. Predictors of Exceptional Longevity Dr. Leonid A. Gavrilov, Ph.D. Dr. Natalia S. Gavrilova, Ph.D. Center on Aging NORC and The University of Chicago Chicago, Illinois, USA

2. What Do We Know About Mortality of Centenarians?

3. A Study That Answered This Question

4. M. Greenwood, J. O. Irwin. BIOSTATISTICS OF SENILITY

5. Mortality at Advanced Ages Source: Gavrilov L.A., Gavrilova N.S. The Biology of Life Span: A Quantitative Approach, NY: Harwood Academic Publisher, 1991

6. Mortality Deceleration in Other Species Invertebrates: Nematodes, shrimps, bdelloid rotifers, degenerate medusae (Economos, 1979) Drosophila melanogaster (Economos, 1979; Curtsinger et al., 1992) Medfly (Carey et al., 1992) Housefly, blowfly (Gavrilov, 1980) Fruit flies, parasitoid wasp (Vaupel et al., 1998) Bruchid beetle (Tatar et al., 1993) Mammals: Mice (Lindop, 1961; Sacher, 1966; Economos, 1979) Rats (Sacher, 1966) Horse, Sheep, Guinea pig (Economos, 1979; 1980) However no mortality deceleration is reported for Rodents (Austad, 2001) Baboons (Bronikowski et al., 2002)

7. Mortality Leveling-Off in House Fly Musca domestica Our analysis of the life table for 4,650 male house flies published by Rockstein & Lieberman, 1959. Source: Gavrilov & Gavrilova. Handbook of the Biology of Aging, Academic Press, 2006, pp.3-42.

8. Existing Explanations of Mortality Deceleration Population Heterogeneity (Beard, 1959; Sacher, 1966). “… sub-populations with the higher injury levels die out more rapidly, resulting in progressive selection for vigour in the surviving populations” (Sacher, 1966) Exhaustion of organism’s redundancy (reserves) at extremely old ages so that every random hit results in death (Gavrilov, Gavrilova, 1991; 2001) Lower risks of death for older people due to less risky behavior (Greenwood, Irwin, 1939) Evolutionary explanations (Mueller, Rose, 1996; Charlesworth, 2001)

9. Problems in Hazard Rate Estimation At Extremely Old Ages Mortality deceleration in humans may be an artifact of mixing different birth cohorts with different mortality (heterogeneity effect) Standard assumptions of hazard rate estimates may be invalid when risk of death is extremely high Ages of very old people may be highly exaggerated

10. Social Security Administration Death Master File Helps to Alleviate the First Two Problems Allows to study mortality in large, more homogeneous single-year or even single-month birth cohorts Allows to study mortality in one-month age intervals narrowing interval of hazard rates estimation

11. What Is SSA DMF ? SSA DMF is a publicly available data resource (available at Rootsweb.com) Covers 93-96 percent deaths of persons 65+ occurred in the United States in the period 1937-2009 Some birth cohorts covered by DMF could be studied by method of extinct generations Considered superior in data quality compared to vital statistics records by some researchers

12. Social Security Administration Death Master File (DMF) Was Used in This Study: (1) Study of cohort mortality at advanced ages: Estimation of hazard rates for each month of age for single-year extinct birth cohorts. (2) Month-of-birth and mortality after age 80: Estimation of life expectancy in real birth cohort according to month of birth.

14. Hypothesis Mortality deceleration at advanced ages should be less expressed for data of higher quality

15. Quality Control (1) Study of mortality in states with different quality of age reporting: Records for persons applied to SSN in the Southern states, Hawaii and Puerto Rico were suggested to have lower quality (Rosenwaike, Stone, 2003)

16. Mortality when all data are used

17. Mortality for data with presumably different quality

18. Quality Control (2) Study of mortality for earlier and later single-year extinct birth cohorts: Records for later born persons were suggested to have higher quality due to more accurate age reporting.

19. Mortality for data with presumably different quality

21. Mortality at Advanced Ages by Sex

27. Mortality at advanced ages: Actuarial 1900 cohort life table and SSDI 1887 cohort Source for actuarial life table: Bell, F.C., Miller, M.L. Life Tables for the United States Social Security Area 1900-2100 Actuarial Study No. 116

28. Mortality at advanced ages: Actuarial cohort life table and SSDI 1887 cohort Estimating Gompertz slope parameter 1900 cohort, age interval 50-100 alpha (95% CI): 0.092 (0.092,0.093) 1887 cohort, age interval 85-103 alpha (95% CI): 0.094 (0.093,0.095) 1887 cohort, age interval 85-100 alpha (95% CI): 0.117 (0.116,0.118)

29. SSDI Data Quality Evaluation

30. Month-of-Birth and Mortality at Advanced Ages SSA Death Master File allows researchers to study mortality in real birth cohorts by month-of-birth Provides more accurate and unbiased estimates of life expectancy by month of birth compared to usage of cross- sectional death certificates

33. Month-of-Birth effects disappear at age 100+

34. Conclusions Late-life mortality deceleration appears to be not that strong - cohort mortality at advanced ages continues to grow up to age 105 years Month of birth effects on mortality exist at age 80 but then fade and disappear by age 100+

35. Predictors of Exceptional Longevity

36. 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)

37. Design of the Study

38. 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.

39. 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.

40. Registration Day Parade

42. 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

43. Draft Registration Card: An Example

44. 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 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

45. SAMPLE CHARACTERISTICS (%) CentenariansControls Foreign born20.522.2 Married68.463.7 Had children52.642.1 Farmers31.623.4 African Am.5.3

46. 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

47. 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

48. 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.

49. Small Dogs Live Longer

50. Small Mice Live Longer

51. 171 pairs of men born in 1887 Centenarians Controls Body Height short 6.4 8.8 medium 65.5 56.7 tall 28.1 34.5 Body Build slender 25.2 medium 67.8 60.2 stout 7.0 14.6 BODY HEIGHT AND BODY BUILD DISTRIBUTIONS (%)

52. Height Distribution Among Centenarians and Controls

53. Body Build Distribution Among Centenarians and Controls

54. Results of multivariate study VariableORP-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

55. Results of multivariate study Significant predictors only VariableOdds Ratio P-value ‘Slender’ body build reference: stout build 2.540.040 ‘Medium’ body build reference: stout build 2.640.017 Farming1.990.025

56. Household Property Status During Childhood (1900 census) and Survival to Age 100 Odds for household to be in a ‘centenarian’ group A – Rented House (reference group) B – Owned House C – Rented Farm D – Owned farm Source: Gavrilova, Gavrilov, NAAJ, 2007

57. Other physical characteristics VariableOdds Ratio P-value Blue eye color1.620.069 ‘Short’ body height reference: tall height 1.020.967 ‘Medium’ body height reference: tall height 1.430.212 Other variables include body build and farming

58. 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

59. 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

60. 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.

61. Acknowledgments This study was made possible thanks to: generous support from the National Institute on Aging The Society of Actuaries grant Stimulating working environment at the Center on Aging, NORC/University of Chicago

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