1. Predictors of Exceptional Longevity: Effects of early-life childhood conditions, mid-life environment and parental characteristics 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. An example of the most simple 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. 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) Our earlier study: centenarians were found in computerized family histories and compared to 5% sample of the U.S. 1900 census (IPUMS dataset)

16. How centenarians are different from their shorter-lived sibling?

17. 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

18. Design of the Study

19. 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

20. 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)

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

22. 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

23. 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

24. 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.

25. 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.

26. 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

27. 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

28. 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.

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

30. 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)

31. 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

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

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

34. 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

35. 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)

36. 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.

37. 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.

38. Registration Day Parade

40. 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

41. Draft Registration Card: An Example

42. Height and survival to age 100

43. Body build and survival to age 100

44. 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

45. 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

46. 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

47. 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

48. 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.

49. One more approach Compare centenarians with their peers born in the same year but died at age 65 years Both centenarians and shorter-lived controls are randomly sampled from the same data universe: computerized genealogies 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

50. 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

51. Age validation is a key moment in human longevity studies Death dates of centenarians were validated using the U.S. Social Security Death Index Birth dates were validated through linkage of centenarian records to early U.S. censuses (when centenarians were children)

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

53. Early-life characteristics Type of parental household (farm or non- farm, own or rented), Parental literacy, Parental immigration status Paternal (or head of household) occupation Number of children born/survived by mother Size of parental household in 1900 Region of birth

54. Midlife Characteristics from 1930 census 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, Marital status

55. Family Characteristics from genealogy Information on paternal and maternal lifespan Paternal and maternal age at person’s birth, Number of spouses and siblings Birth order Season of birth

56. Example of images from 1930 census (controls)

57. Parental longevity, early-life and midlife conditions and survival to age 100. Males Multivariate logistic regression, N=714 Variable Odds ratio 95% CIP-value Father lived 80+1.821.33-2.50<0.001 Mother lived 80+1.971.44-2.70<0.001 Farmer in 19301.801.30-2.49<0.001 Age at first marriage1.010.99-1.030.204 Born in North-East1.891.16-3.100.011 Born in the second half of year 1.431.05-1.960.022 Radio in household, 19300.920.67-1.280.620

58. Parental longevity, early-life and midlife conditions and survival to age 100 Women Multivariate logistic regression, N=750 Variable Odds ratio 95% CIP-value Father lived 80+2.041.48-2.81<0.001 Mother lived 80+2.331.71-3.17<0.001 Husband farmer in 19301.230.89-1.700.210 Age at first marriage1.021.001-1.040.013 Radio in hh, 19301.601.16-2.230.005 Born in the second half of year 0.990.69-1.430.966 Born in North-East1.020.62-1.650.950

59. 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), sibship size, father-farmer in 1900 Marital status, veteran status, childlessness Paternal and maternal age at birth, loss of parent before 1910

60. Season of birth and survival to 100 Birth in the first half and the second half of the year among centenarians and controls died at age 65 Significant difference P=0.008 Significant difference: p=0.008

61. 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

62. 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

63. 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.

64. 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 Information about such an important predictor as parental longevity should be collected in contemporary longitudinal studies

65. Study of biological and non- biological relatives of centenarians Numerous studies showed that biological relatives of centenarians have substantial survival advantage compared to biological relatives of shorter-lived individuals

66. Who lives longer in centenarian families? Siblings > Spouses > Siblings-in-law Relatives: MenWomen NLS50*N Parents 159076.2155777.2 Spouses 87775.428381.4 Siblings 532477.6487782.4 Siblings in law 236375.1241079.5 1900 US birth cohort 73.379.4 *Mean lifespan conditional on survival to age 50 Relatives of 1,711 centenarians born in 1880-1895

67. Little is known about effects of centenarian’s sex on longevity of relatives In this study effects of centenarian’s sex were used to explore genetic and environmental effects on longevity

68. Dataset We have developed and analyzed a new computerized database on 1,711 validated centenarians born in 1880-1895 in the the United States, their parents and 13,185 shorter-lived siblings.

69. Having centenarian brother is ‘better’ than centenarian sister (for males only) Siblings of cente- narians Male centenarians Female centenarians P-value NLE50N Brothers 126829.25405627.09<0.001 Sisters 107132.06380632.450.328 Life expectancy of siblings at age 50 depending on the sex of centenarian

70. Survival of male siblings of centenarians, by sex of centenarian

71. Male centenarians Female centenarians P-value NLE50N Fathers 37427.22121625.930.023 Mothers 36227.97119527.030.176 Life expectancy of parents at age 50 depending on the sex of centenarian Having centenarian son is ‘better’ than centenarian daughter (for fathers only)

72. Using siblings-in-law as a control group Siblings-in-law do not share genetic background and living conditions with centenarians On the other hand, they usually come from a similar socio-economic background, so may be a good control group

73. Sex of centenarian is important for siblings but not for siblings-in-law Married relatives: Male centenarians Females centenarians P-value NLE50N Brothers 78429.53243727.12<0.001 Sisters 65031.36237832.400.045 Brothers in law 49224.95185725.060.846 Sisters in law 61129.22179629.550.539 Life expectancy of relatives at age 50 depending on the sex of centenarian

74. Only women benefit from having centenarian spouse Centenarian spouses Sibling spouses P-value Sex of spouse NLE50N Men 87525.40234925.040.411 Men (married to 103+ centenarians) 21425.36234925.04NS Women 28331.40240729.460.007 Life expectancy of spouses at age 50 depending on the sex of centenarian

75. Conclusion Familial factors in human longevity are likely to be sex-specific. Exploring complex environmental and genetic effects in longevity could be facilitated by further analysis of sex-specific effects

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

78. 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

79. 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/

80. Population surveys Provide more detailed information on specific topics compared to censuses Cover relatively small proportion of population (usually several thousand) Population-based survey – random sample of the total population; represents existing groups of population

81. New trends in health surveys Harmonization of surveys at world scale Biomarker collection

82. Large-scale study of health and retirement of older Americans Survey of more that 22000 Americans older than 55 years every 2 years. Started in 1992

83. HRS-harmonizing studies UK English Longitudinal Study of Ageing (ELSA) Study on Health, Ageing and Retirement in Europe (SHARE) WHO Study on global AGEing and adult health (SAGE) including Russia Other studies in Mexico, China, India, Japan, Korea, Ireland

84. Introduction to:

85. http://www.icpsr.umich.edu/NACDA/ Public Dataset

86. NSHAP Collaborators Co-Investigators Linda Waite, PI Ed Laumann Wendy Levinson Martha McClintock Stacy Tessler Lindau Colm O’Muircheartaigh Phil Schumm NORC Team Stephen Smith and many others Collaborators David Friedman Thomas Hummel Jeanne Jordan Johan Lundstrom Thomas McDade Ethics Consultant John Lantos Outstanding Research Associates and Staff

87. Study Timeline Funding: NIH / October, 2003 Pretest: September – December, 2004 Wave I Field Period: June 2005 – March 2006 Wave I Analysis: Began October, 2006

88. Interview 3,005 community-residing adults ages 57-85 Population-based sample, minority over-sampling 75.5% weighted response rate 120-minute in-home interview Questionnaire Biomarker collection Leave-behind questionnaire NSHAP Design Overview

89. Medical Physical Health Medications, vitamins, nutritional supplements Mental Health Caregiving HIV Women’s Health Ob/gyn history, care Hysterectomy, oophorectomy Vaginitis, STDs Incontinence Demographics Basic Background Information Marriage Employment and Finances Religion Social Networks Social Support Activities, Engagement Intimate relationships, sexual partnerships Physical Contact Domains of Inquiry

90. NSHAP Biomeasures Blood: hgb, HgbA1c, CRP, EBV Saliva: estradiol, testosterone, progesterone, DHEA, cotinine Vaginal Swabs: BV, yeast, HPV, cytology Anthropometrics: ht, wt, waist Physiological: BP, HR and regularity Sensory: olfaction, taste, vision, touch Physical: gait, balance

91. NSHAP Biomeasures Cooperation

92. Principles of Minimal Invasiveness Compelling rationale: high value to individual health, population health or scientific discovery In-home collection is feasible Cognitively simple Can be self-administered or implemented by single data collector during a single visit Affordable Low risk to participant and data collector Low physical and psychological burden Minimal interference with participant’s daily routine Logistically simple process for transport from home to laboratory Validity with acceptable reliability, precision and accuracy Lindau ST and McDade TW. 2006. Minimally-Invasive and Innovative Methods for Biomeasure Collection in Population-Based Research. National Academies and Committee on Population Workshop. Under Review.

93. McClintock Laboratory (Cytology) Jordan Clinical Lab Magee Women’s Hospital (Bacterial, HPV Analysis) McDade Lab Northwestern (Blood Spot Analysis) Salimetrics (Saliva Analysis) “Laboratory Without Walls” UC Cytopathology (Cytology) NSHAP Biomeasures

94. Sex hormone assays Salivary Biomeasures Estradiol Progesterone DHEA Testosterone Cotinine

95. Salivary Sex Hormones (preliminary analysis) log(progesterone) Frequency log(estradiol) Frequency log(testosterone) Frequency Units: pg/ml

96. Nicotine metabolite Objective marker of tobacco exposure, including second-hand Non-invasive collection method (vs. serum cotinine) Salivary Cotinine

97. 10 ng15 ng34 ng 10% M 103 ng 30% M 344 ng M Nonsmoker Passive Occasional Regular 0.05.1.15.2 Fraction -50510 log(Cotinine) M = mean cotinine among female who report current smoking Bar on left corresponds to cotinine below level of detection Cut-points based on distribution among smokers Classification of Smoking Status by Cotinine Level in Females Distribution of Salivary Cotinine

98. C-Reactive Protein (CRP) Epstein-Barr Virus (EBV) Antibody Titers Dried Blood Spots Thanks, Thom and McDade Lab Staff!

99. Chicago Core on Biomarkers in Population-Based Aging Research An information and educational resource on biomarkers Biomeasures conferences at a regular basis Monthly electronic CCBAR Newsletter CCBAR website

100. More detailed information can be found at the site: http://biomarkers.uchicago.edu/

101. Publication on sexuality Lindau, Gavrilova, British Medical Journal, 2010, 340, c810

102. Prevalence of Sexual Activity by Age and Gender (MIDUS 1) Men and women having intimate partner

103. Life expectancy and sexually active life expectancy (SALE) Based on the MIDUS study

104. Sexually active life expectancy and self-rated health Based on the MIDUS study