Body Composition Prediction—BOMP: A New Tool for Assessing Fat and Lean Body Mass
Authors' conclusion
The results indicate that it is possible to develop a "white-box" model with high precision.The proof of concept webapp is available as open source under the MIT license.
Study context
- Population
- NHANES participantsNHANES
- Participants
- 18,430 participants
- Outcome
- Model performance for lean body mass and fat mass
Methodological detailsstepwise linear regression with linear, interaction and quadratic terms, webapp frontend (HTML and Javascript), Proof-of-concept webapp available as open source under the MIT license
- Stepwise linear regression with linear, interaction and quadratic terms
- Webapp frontend (HTML and Javascript)
- Proof-of-concept webapp available as open source under the MIT license
Main finding
As reported in the abstract
Correlation coefficient R
0.99-0.98
P < .001
Standard error of estimate (SEE)
2.07-2.05
Original publication
Body Composition Prediction—BOMP: A New Tool for Assessing Fat and Lean Body Mass. J Diabetes Sci Technol. Published 9 February 2022. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →