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  5. Evaluation of a suggested novel method to adjust BMI calculated from self‐reported weight and height for measurement error

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Article
en
2021

Evaluation of a suggested novel method to adjust BMI calculated from self‐reported weight and height for measurement error

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en
2021
Vol 29 (10)
Vol. 29
DOI: 10.1002/oby.23239

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John P A Ioannidis
John P A Ioannidis

Stanford University

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Katherine M. Flegal
Barry I. Graubard
John P A Ioannidis

Abstract

Abstract Objective In 2019, Ward et al. proposed a method to adjust BMI calculated from self‐reported weight and height for bias relative to measured data. They did not evaluate the adjusted values relative to measured BMI values for the same individuals. Methods A large data set ( n = 37,439) with both measured and self‐reported weight and height was randomly divided into two groups. The proposed method was used to adjust the BMI values in one group to the measured data from the other group. The adjusted values were then compared with the measured values for the same individuals. Results Before adjustment, 24.9% were incorrectly classified relative to measured BMI categories, including 7.9% in too high a category; after adjustment, 24.3% were incorrectly classified, with 12.8% in too high a category. The variance of the difference was unchanged. The adjustments reduced some errors and introduced new errors. At an individual level, results were unpredictable. Conclusions The suggested method has little effect on misclassification, can introduce new errors, and could magnify errors associated with factors, such as age, race, educational level, or other characteristics. State‐level estimates and projections of obesity prevalence from values adjusted by this method may be incorrect.

How to cite this publication

Katherine M. Flegal, Barry I. Graubard, John P A Ioannidis (2021). Evaluation of a suggested novel method to adjust BMI calculated from self‐reported weight and height for measurement error. , 29(10), DOI: https://doi.org/10.1002/oby.23239.

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Publication Details

Type

Article

Year

2021

Authors

3

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1002/oby.23239

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