Related Experiment Video
Updated: Mar 27, 2026

Author Spotlight: Advancements in 3D Optical Imaging for Comprehensive Body Composition Assessment in Modern Research
Published on: June 7, 2024
How well does the standard body mass index or variations with a different exponent predict human lifespan?
Dean Foster1,2, Howard Karloff, Kenneth E Shirley
1Department of Statistics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Objective:
The objective was twofold: (1) to estimate for each individual the body mass index (BMI) which is associated with the lowest risk of death, and (2) to study variants of the BMI formula to determine which gives the best predictions of death.
Methods:
Treating BMI = mass/height(2) as a continuous variable and estimating its interaction effects with several other variables, this study analyzed the NIH-AARP study data set of approximately 566,000 individuals and fit Cox proportional hazards models to the survival times.
Results:
For each individual, a "personalized optimal BMI," the BMI for that individual which, according to the model, is associated with the lowest risk of death, is estimated. The average personalized optimal BMI is approximately 26, which is in the current "overweight" category. In fact, mass/height is a better predictor of death on the data set than BMI itself.
Conclusions:
The model suggests that an individual's "optimal" BMI depends on his or her features; "one-size-fits-all" recommendations may be not best.
Related Concept Videos
Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Obesity
Life Tables
Metabolic Rate
The Basal Metabolic Rate (BMR) measures the energy expended at rest.
Several factors influence...
Introduction to Exponential Functions
Exponential Equations for Modeling Growth

