Related Experiment Video
Updated: Dec 22, 2025
06:55
Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
15.0K
Activity Level as a Mortality Predictor in a Population Sample after Typical Underwriting Exclusions and Laboratory
Journal of Insurance Medicine (New York, N.Y.)
|May 1, 2020
Summary
Physical activity significantly impacts mortality rates in healthy adults. Higher sedentary time increases mortality risk, while increased daily activity lowers it, independent of other health factors.
Area of Science:
- Epidemiology
- Public Health
- Biostatistics
Background:
- Sedentary lifestyles are linked to adverse health outcomes and increased mortality.
- Activity monitors are increasingly considered for life insurance underwriting.
- Quantifying physical activity's independent effect on mortality is crucial.
Purpose of the Study:
- To quantify the impact of physical activity on mortality in healthy individuals.
- To assess physical activity's predictive power for mortality, controlling for other risk factors.
- To determine if activity levels and laboratory risk scores independently predict mortality.
Main Methods:
- Utilized National Health and Nutrition Examination Survey (NHANES) data (1999-2014).
- Employed a proprietary algorithm (CRL SmartScore) for laboratory-based mortality risk scoring.
- Analyzed self-reported activity and pedometer data, excluding individuals with pre-existing health conditions.
Main Results:
- Lower physical activity levels (MET*hours/day) were associated with increased hazard ratios for mortality.
- Increased sedentary time, measured by pedometers, correlated with higher mortality risk.
- Both activity levels and laboratory risk scores remained significant independent predictors of mortality.
Conclusions:
- High proportions of sedentary time are clearly associated with increased mortality.
- Physical activity and laboratory risk scores represent distinct influences on mortality risk.
- Findings support the independent value of physical activity data in mortality risk assessment.
Related Concept Videos
01:20Actuarial Approach
240
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
240
01:22Life Tables
422
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,...
422
01:24Kaplan-Meier Approach
486
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,...
486
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
330
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
330
01:20Comparing the Survival Analysis of Two or More Groups
488
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
488
01:15Assumptions of Survival Analysis
321
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
321