Mortality Measurement at Advanced Ages: A Study of the Social Administration Death Master File

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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, Ph.D.
• Center on Aging
• NORC and The University of Chicago
• Chicago, Illinois, USA

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What Do We Know About Mortality of Centenarians?
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A Study That Answered This Question
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M. Greenwood, J. O. Irwin. BIOSTATISTICS OF
SENILITY
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Mortality at Advanced Ages

• Source Gavrilov L.A., Gavrilova N.S. The
  Biology of Life Span
• A Quantitative Approach, NY Harwood Academic
  Publisher, 1991

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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)

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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.

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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 organisms 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)

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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

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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

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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

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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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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
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Mortality when all data are used
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Mortality for data with presumably different
quality
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Mortality when all data are used
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Mortality for data with presumably different
quality
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Mortality for data with presumably different
quality
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Mortality at Advanced Ages by Sex
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Mortality at Advanced Ages by Sex
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Mortality at Advanced Ages by Sex
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Mortality at Advanced Ages by Sex
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Mortality at Advanced Ages by Sex
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Mortality at Advanced Ages by Sex
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Crude Indicator of Mortality Plateau (1)

• Linearity of survival curves in semi-log
  coordinates (log survival age)

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Logarithm of Survival at Advanced Ages
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Crude Indicator of Mortality Plateau (2)

• Coefficient of variation for life expectancy
  is close to, or higher than 100
• CV s/µ
• where s is a standard deviation and µ is
  mean

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Coefficient of variation for life expectancy as a
function of age
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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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Month-of-Birth effects disappear at age 100
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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

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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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Life expectancy at age 90
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Median lifespan at age 90
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Life expectancy at age 100
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Male life expectancy at age 90
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Female life expectancy at age 90