Literature DB >> 33269598

Predicting Body Composition From Anthropometrics.

Kong Y Chen1.   

Abstract

Body weight, height, and other simple, noninvasive anthropometric measures are the cornerstones of epidemiological research. Body composition determinants such as fat and lean tissue masses and their distributions are better associated with metabolic conditions, such as diabetes, than anthropometrics alone. However, body composition is generally more challenging to measure. This analysis article comments on the manuscript by Cichosz et al that appeared in this issue of the Journal of Diabetes Science and Technology, where a machine-learning approach was developed to predict body composition using measured anthropometric parameters for potentially easier estimations of risk factors of metabolic diseases in the future.

Entities:  

Keywords:  fat distribution; fat mass; lean body mass; machine learning; metabolic risks

Mesh:

Year:  2020        PMID: 33269598      PMCID: PMC8655275          DOI: 10.1177/1932296820976584

Source DB:  PubMed          Journal:  J Diabetes Sci Technol        ISSN: 1932-2968


  7 in total

1.  Comparison of effective dose to children and adults from dual X-ray absorptiometry examinations.

Authors:  Glen M Blake; Marium Naeem; Maria Boutros
Journal:  Bone       Date:  2005-12-22       Impact factor: 4.398

2.  Skeletal muscle attenuation determined by computed tomography is associated with skeletal muscle lipid content.

Authors:  B H Goodpaster; D E Kelley; F L Thaete; J He; R Ross
Journal:  J Appl Physiol (1985)       Date:  2000-07

3.  Impact of abdominal visceral and subcutaneous adipose tissue on cardiometabolic risk factors: the Jackson Heart Study.

Authors:  Jiankang Liu; Caroline S Fox; DeMarc A Hickson; Warren D May; Kristen G Hairston; J Jeffery Carr; Herman A Taylor
Journal:  J Clin Endocrinol Metab       Date:  2010-09-15       Impact factor: 5.958

4.  Development and validation of anthropometric prediction equations for lean body mass, fat mass and percent fat in adults using the National Health and Nutrition Examination Survey (NHANES) 1999-2006.

Authors:  Dong Hoon Lee; NaNa Keum; Frank B Hu; E John Orav; Eric B Rimm; Qi Sun; Walter C Willett; Edward L Giovannucci
Journal:  Br J Nutr       Date:  2017-11-07       Impact factor: 3.718

5.  Visceral fat: a key mediator of steatohepatitis in metabolic liver disease.

Authors:  David van der Poorten; Kerry-Lee Milner; Jason Hui; Alexander Hodge; Michael I Trenell; James G Kench; Roslyn London; Tony Peduto; Donald J Chisholm; Jacob George
Journal:  Hepatology       Date:  2008-08       Impact factor: 17.425

6.  Precise Prediction of Total Body Lean and Fat Mass From Anthropometric and Demographic Data: Development and Validation of Neural Network Models.

Authors:  Simon Lebech Cichosz; Nicklas Højgaard Rasmussen; Peter Vestergaard; Ole Hejlesen
Journal:  J Diabetes Sci Technol       Date:  2020-11-16

Review 7.  Advanced body composition assessment: from body mass index to body composition profiling.

Authors:  Magnus Borga; Janne West; Jimmy D Bell; Nicholas C Harvey; Thobias Romu; Steven B Heymsfield; Olof Dahlqvist Leinhard
Journal:  J Investig Med       Date:  2018-03-25       Impact factor: 2.895

  7 in total

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