M Frost1, T L Nielsen, K Brixen, M Andersen. 1. Department of Endocrinology, Odense University Hospital Odense, DK-5000, Odense C, Denmark, frostnielsen@yahoo.com.
Abstract
SUMMARY: The prevalence of sarcopenia increases with age. The diagnosis of sarcopenia relies in part on normative data on muscle mass, but these data are lacking. This study provides population-based reference data on muscle mass in young men, and these results may be used clinically for the diagnosis of sarcopenia in men. INTRODUCTION: The ageing population increases the prevalence of sarcopenia. Estimation of normative data on muscle mass in young men during the peak of anabolic hormones is necessary for the diagnosis of sarcopenia in ageing males. The purposes of this study were to provide population-based reference data on lean body mass (LBM) in young men during the time of peak levels of GH/IGF-1 and testosterone and further to apply the reference data on a population-based sample of men aged 60-74 years to estimate the prevalence of sarcopenia. METHODS: This is a cross-sectional, population-based single-centre study. Our participants are from random selection of 783 men, aged 20-29 years, and 600 men, aged 60-74 years. LBM was assessed by dual-energy X-ray absorptiometry (DXA). LBM T-scores were calculated on the basis of LBM in the young participants. Muscle function in the lower extremities was measured using a leg extension power (LEP) rig in the ageing participants. RESULTS: Total lean body mass (TLB) was (mean (SD)) 64.7 kg (6.8) in the young and 60.4 kg (6.4) in the ageing men (p<0.001). Lower extremity lean mass (LELB) was 22.0 kg (2.6) in the young and 19.2 kg (2.4) in the ageing men (p<0.001). In the ageing men, TLB and LELB T-scores were -0.64 (0.94) and -1.09 (0.94). A total of 4.8 and 8.5% had a TLB or LELB T-score of less than -2 and a LEP in the lowest quartile. CONCLUSIONS: This study provides population-based reference data on LBM in men, and these data may be used clinically for the diagnosis of sarcopenia.
SUMMARY: The prevalence of sarcopenia increases with age. The diagnosis of sarcopenia relies in part on normative data on muscle mass, but these data are lacking. This study provides population-based reference data on muscle mass in young men, and these results may be used clinically for the diagnosis of sarcopenia in men. INTRODUCTION: The ageing population increases the prevalence of sarcopenia. Estimation of normative data on muscle mass in young men during the peak of anabolic hormones is necessary for the diagnosis of sarcopenia in ageing males. The purposes of this study were to provide population-based reference data on lean body mass (LBM) in young men during the time of peak levels of GH/IGF-1 and testosterone and further to apply the reference data on a population-based sample of men aged 60-74 years to estimate the prevalence of sarcopenia. METHODS: This is a cross-sectional, population-based single-centre study. Our participants are from random selection of 783 men, aged 20-29 years, and 600 men, aged 60-74 years. LBM was assessed by dual-energy X-ray absorptiometry (DXA). LBM T-scores were calculated on the basis of LBM in the young participants. Muscle function in the lower extremities was measured using a leg extension power (LEP) rig in the ageing participants. RESULTS: Total lean body mass (TLB) was (mean (SD)) 64.7 kg (6.8) in the young and 60.4 kg (6.4) in the ageing men (p<0.001). Lower extremity lean mass (LELB) was 22.0 kg (2.6) in the young and 19.2 kg (2.4) in the ageing men (p<0.001). In the ageing men, TLB and LELB T-scores were -0.64 (0.94) and -1.09 (0.94). A total of 4.8 and 8.5% had a TLB or LELB T-score of less than -2 and a LEP in the lowest quartile. CONCLUSIONS: This study provides population-based reference data on LBM in men, and these data may be used clinically for the diagnosis of sarcopenia.
Authors: A Y Bijlsma; C G M Meskers; N van den Eshof; R G Westendorp; S Sipilä; L Stenroth; E Sillanpää; J S McPhee; D A Jones; M V Narici; H Gapeyeva; M Pääsuke; T Voit; Y Barnouin; J Y Hogrel; G Butler-Browne; A B Maier Journal: Age (Dordr) Date: 2013-07-02
Authors: Bret H Goodpaster; Seok Won Park; Tamara B Harris; Steven B Kritchevsky; Michael Nevitt; Ann V Schwartz; Eleanor M Simonsick; Frances A Tylavsky; Marjolein Visser; Anne B Newman Journal: J Gerontol A Biol Sci Med Sci Date: 2006-10 Impact factor: 6.053
Authors: Alfonso J Cruz-Jentoft; Jean Pierre Baeyens; Jürgen M Bauer; Yves Boirie; Tommy Cederholm; Francesco Landi; Finbarr C Martin; Jean-Pierre Michel; Yves Rolland; Stéphane M Schneider; Eva Topinková; Maurits Vandewoude; Mauro Zamboni Journal: Age Ageing Date: 2010-04-13 Impact factor: 10.668
Authors: Harnish P Patel; Holly Emma Syddall; Karen Jameson; Sian Robinson; Hayley Denison; Helen C Roberts; Mark Edwards; Elaine Dennison; Cyrus Cooper; Avan Aihie Sayer Journal: Age Ageing Date: 2013-02-05 Impact factor: 10.668
Authors: F Landi; R Calvani; E Ortolani; S Salini; A M Martone; L Santoro; A Santoliquido; A Sisto; A Picca; E Marzetti Journal: Osteoporos Int Date: 2017-02-02 Impact factor: 4.507
Authors: Jean-Yves Reginster; Cyrus Cooper; René Rizzoli; John A Kanis; Geoff Appelboom; Ivan Bautmans; Heike A Bischoff-Ferrari; Maarten Boers; Maria Luisa Brandi; Olivier Bruyère; Antonio Cherubini; Bruno Flamion; Roger A Fielding; Andrea Ildiko Gasparik; Luc Van Loon; Eugene McCloskey; Bruce H Mitlak; Alberto Pilotto; Suzanne Reiter-Niesert; Yves Rolland; Yannis Tsouderos; Marjolein Visser; Alfonso J Cruz-Jentoft Journal: Aging Clin Exp Res Date: 2015-12-30 Impact factor: 3.636
Authors: Thibault Sutter; Hechmi Toumi; Antoine Valery; Rawad El Hage; Antonio Pinti; Eric Lespessailles Journal: PLoS One Date: 2019-03-08 Impact factor: 3.240
Authors: Todd C Shoepe; Joseph W LaBrie; Grant T Mello; Allison G Leggett; Hawley C Almstedt Journal: BMC Musculoskelet Disord Date: 2020-11-10 Impact factor: 2.362