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Mortality Measurement at Advanced Ages: A Study of the Social Administration Death Master File Dr. Leonid A. Gavrilov, Ph.D. Dr. Natalia S. Gavrilova,

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Presentation on theme: "Mortality Measurement at Advanced Ages: A Study of the Social Administration Death Master File Dr. Leonid A. Gavrilov, Ph.D. Dr. Natalia S. Gavrilova,"— Presentation transcript:

1 Mortality Measurement at Advanced Ages: A Study of the Social Administration Death Master File 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 Challenges in Hazard Rate Estimation At Extremely Old Ages Mortality deceleration 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 Relax 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 1937-2007 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 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.

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14 Quality Control Study of mortality in states with better age reporting: Records for persons applied to SSN in the Southern states, Hawaii and Puerto Rico were eliminated

15 Mortality when all data are used

16 Mortality for data with presumably different quality

17 Mortality when all data are used

18 Mortality for data with presumably different quality

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21 Mortality at Advanced Ages by Sex

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28 Crude Indicator of Mortality Plateau (1) Linearity of survival curves in semi-log coordinates (log survival – age)

29 Logarithm of Survival at Advanced Ages

30 Crude Indicator of Mortality Plateau (2) Coefficient of variation for life expectancy is close to, or higher than 100% CV = σ/μ where σ is a standard deviation and μ is mean

31 Coefficient of variation for life expectancy as a function of age

32 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

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35 Month-of-Birth effects disappear at age 100+

36 Conclusions Late-life mortality deceleration appears to be not that strong - cohort mortality at advanced ages continues to grow up to age 105 years Late-life mortality plateau is likely not to be an artifact and is expressed earlier in males than females Month of birth effects on mortality exist at age 80 but then fade and disappear by age 100+

37 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

38 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/

39 Life expectancy at age 90

40 Median lifespan at age 90

41 Life expectancy at age 100

42 Male life expectancy at age 90

43 Female life expectancy at age 90


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