BACKGROUND: Lean body mass (LBM) is not easy to measure directly in the field or clinical setting. Equations to predict LBM from simple anthropometric measures, which account for the differing contributions of fat and lean to body weight at different ages and levels of adiposity, would be useful to both human biologists and clinicians. AIM: To develop and validate equations to predict LBM in children and adolescents across the entire range of the adiposity spectrum. SUBJECTS AND METHODS: Dual energy X-ray absorptiometry was used to measure LBM in 836 healthy children (437 females) and linear regression was used to develop sex-specific equations to estimate LBM from height, weight, age, body mass index (BMI) for age z-score and population ancestry. Equations were validated using bootstrapping methods and in a local independent sample of 332 children and in national data collected by NHANES. RESULTS: The mean difference between measured and predicted LBM was - 0.12% (95% limits of agreement - 11.3% to 8.5%) for males and - 0.14% ( - 11.9% to 10.9%) for females. Equations performed equally well across the entire adiposity spectrum, as estimated by BMI z-score. Validation indicated no over-fitting. LBM was predicted within 5% of measured LBM in the validation sample. CONCLUSION: The equations estimate LBM accurately from simple anthropometric measures.
BACKGROUND: Lean body mass (LBM) is not easy to measure directly in the field or clinical setting. Equations to predict LBM from simple anthropometric measures, which account for the differing contributions of fat and lean to body weight at different ages and levels of adiposity, would be useful to both human biologists and clinicians. AIM: To develop and validate equations to predict LBM in children and adolescents across the entire range of the adiposity spectrum. SUBJECTS AND METHODS: Dual energy X-ray absorptiometry was used to measure LBM in 836 healthy children (437 females) and linear regression was used to develop sex-specific equations to estimate LBM from height, weight, age, body mass index (BMI) for age z-score and population ancestry. Equations were validated using bootstrapping methods and in a local independent sample of 332 children and in national data collected by NHANES. RESULTS: The mean difference between measured and predicted LBM was - 0.12% (95% limits of agreement - 11.3% to 8.5%) for males and - 0.14% ( - 11.9% to 10.9%) for females. Equations performed equally well across the entire adiposity spectrum, as estimated by BMI z-score. Validation indicated no over-fitting. LBM was predicted within 5% of measured LBM in the validation sample. CONCLUSION: The equations estimate LBM accurately from simple anthropometric measures.
Authors: Rebecca L Ruebner; Derek Ng; Mark Mitsnefes; Bethany J Foster; Kevin Meyers; Bradley Warady; Susan L Furth Journal: Clin J Am Soc Nephrol Date: 2016-09-14 Impact factor: 8.237
Authors: Kelly A Dougherty; Chiara Bertolaso; Joan I Schall; Kim Smith-Whitley; Virginia A Stallings Journal: J Pediatr Hematol Oncol Date: 2018-07 Impact factor: 1.289
Authors: Anne van Rongen; Janelle D Vaughns; Ganesh S Moorthy; Jeffrey S Barrett; Catherijne A J Knibbe; Johannes N van den Anker Journal: Br J Clin Pharmacol Date: 2015-09-10 Impact factor: 4.335
Authors: Emma L Ross; Jennifer Jorgensen; Peter E DeWitt; Carol Okada; Renee Porter; Matthew Haemer; Pamela D Reiter Journal: J Pediatr Pharmacol Ther Date: 2014-04
Authors: Jennifer Le; Edmund V Capparelli; Uzra Wahid; Yi Shuan S Wu; Gale L Romanowski; Tri M Tran; Austin Nguyen; John S Bradley Journal: Clin Ther Date: 2015-05-29 Impact factor: 3.393
Authors: David C Turner; Fariba Navid; Najat C Daw; Shenghua Mao; Jianrong Wu; Victor M Santana; Michael Neel; Bhaskar Rao; Jennifer Reikes Willert; David M Loeb; K Elaine Harstead; Stacy L Throm; Burgess B Freeman; Clinton F Stewart Journal: Clin Cancer Res Date: 2014-03-17 Impact factor: 12.531
Authors: Kelly A Dougherty; Joan I Schall; Chiara Bertolaso; Kim Smith-Whitley; Virginia A Stallings Journal: J Pediatr Health Care Date: 2020-06-05 Impact factor: 1.812