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Related Concept Videos

Life Tables01:22

Life Tables

A life table is a statistical tool that summarizes the mortality and survival patterns of a population, providing detailed insights into the likelihood of survival or death across different age intervals within a cohort. By organizing data on survival probabilities and mortality rates, life tables offer a clear snapshot of population dynamics over time. They are extensively used in demography, public health, actuarial science, and ecology to analyze life expectancy, design health interventions,...
Kaplan-Meier Approach01:24

Kaplan-Meier Approach

The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
Censoring Survival Data01:09

Censoring Survival Data

Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different reasons...

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Related Experiment Video

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Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults
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Mortality experience in the elderly in the Impairment Study Capture System.

Thomas Ashley1, Clifton P Titcomb, Anna Hart

  • 1Gen Re LifeHealth, 695 E Main St, Stamford, CT 06901, USA. tashley@genre.com

Journal of Insurance Medicine (New York, N.Y.)
|January 6, 2009
PubMed
Summary

This study on life insurance policies for individuals aged 70+ found higher mortality ratios for smokers. Underwriting effectiveness was confirmed, with mortality varying by duration post-issue, aligning with the 2001 VBT select period.

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Area of Science:

  • Actuarial science
  • Mortality studies
  • Insurance underwriting

Background:

  • Analyzing mortality experience in older policyholders is crucial for accurate risk assessment.
  • Understanding underwriting impacts on mortality provides insights into insurance product viability.

Purpose of the Study:

  • To evaluate mortality experience and underwriting effectiveness for life insurance policies issued at ages 70 and above.
  • To examine mortality ratios based on smoking status, underwriting type, and policy duration.

Main Methods:

  • Utilized the Impairment Study Capture System dataset.
  • Analyzed policy data from 1990-1998 with 5-12 years of observation.
  • Calculated mortality ratios, differentiating by smoking status and underwriting class.

Main Results:

  • Observed a significantly higher mortality ratio for smokers compared to nonsmokers, despite adjusted expected mortality.
  • Confirmed the intended effects of underwriting through analysis of different underwriting types and risk classes.
  • Mortality ratio variations by duration post-issue were consistent with the 2001 VBT select period slope.

Conclusions:

  • Smokers aged 70+ exhibit elevated mortality risk in life insurance.
  • Underwriting practices effectively differentiate risk classes and influence mortality outcomes.
  • The study validates established mortality tables for older policyholders.