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Late-life mortality is underestimated because of data errors.

Leonid A Gavrilov1, Natalia S Gavrilova1

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Longevity records for individuals aged 105 and older are frequently inaccurate, potentially skewing aging research. New, rigorous data validation methods are crucial for reliable mortality trajectory analysis in extreme old age.

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Area of Science:

  • Gerontology
  • Demography
  • Biostatistics

Background:

  • Accurate mortality data is vital for testing aging theories.
  • Existing demographic data for extreme old age (105+) is often unreliable.

Purpose of the Study:

  • To highlight the unreliability of longevity records above 105 years.
  • To emphasize the need for improved data quality control in gerontology.

Main Methods:

  • Review of existing studies on age validation and data quality.
  • Analysis of simulation and direct age validation findings.

Main Results:

  • Longevity records for ages 105+ are frequently incorrect.
  • Inaccurate data can lead to false conclusions about mortality deceleration and plateaus.
  • Current data cleaning methods are insufficient for extreme ages.

Conclusions:

  • Mortality estimates for ages above 105 years require extreme caution.
  • Development and testing of stricter data quality control methodologies are necessary.
  • Extraordinary longevity claims need extraordinary evidence.