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How well does the standard body mass index or variations with a different exponent predict human lifespan?
Author(s) -
Foster Dean,
Karloff Howard,
Shirley Kenneth E.
Publication year - 2016
Publication title -
obesity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.438
H-Index - 199
eISSN - 1930-739X
pISSN - 1930-7381
DOI - 10.1002/oby.21318
Subject(s) - body mass index , overweight , proportional hazards model , medicine , statistics , demography , index (typography) , data set , exponent , mathematics , computer science , sociology , world wide web , linguistics , philosophy
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.