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1.
Obesity (Silver Spring) ; 24(2): 469-75, 2016 Feb.
Article in English | MEDLINE | ID: mdl-26748774

ABSTRACT

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.


Subject(s)
Body Mass Index , Health Surveys/statistics & numerical data , Life Expectancy , Aged , Aged, 80 and over , Female , Humans , Male , Middle Aged , Overweight/mortality , Predictive Value of Tests , Proportional Hazards Models , Reference Values , Risk Factors
2.
J Cogn Neurosci ; 21(1): 119-27, 2009 Jan.
Article in English | MEDLINE | ID: mdl-18476762

ABSTRACT

Functional neuroimaging has been used to study a wide array of psychological traits, including aspects of personality and intelligence. Progress in identifying the neural correlates of individual differences in such traits, for the sake of basic science, has moved us closer to the applied science goal of measuring them and thereby raised ethical concerns about privacy. How realistic are such concerns given the current state of the art? In this article, we describe the statistical basis of the measurement of psychological traits using functional neuroimaging and examine the degree to which current functional neuroimaging protocols could be used for this purpose. By analyzing the published data from 16 studies, we demonstrate that the use of imaging to gather information about an individual's psychological traits is already possible, but to an extremely limited extent.


Subject(s)
Brain Mapping/methods , Ethics, Medical , Neuropsychology/ethics , Personality/physiology , Privacy , Brain/physiology , Data Interpretation, Statistical , Electrophysiology/ethics , Humans , Magnetic Resonance Imaging/ethics
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