S Vermeiren1, D Beckwée2, R Vella-Azzopardi3, I Beyer3, V Knoop1, B Jansen4, A Delaere1, A Antoine5, I Bautmans6, A Scafoglieri7. 1. Gerontology Department and Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, B-1090, Brussels, Belgium; Frailty in Ageing (FRIA) Research Department, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, B-1090, Brussels, Belgium. 2. Gerontology Department and Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, B-1090, Brussels, Belgium; Frailty in Ageing (FRIA) Research Department, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, B-1090, Brussels, Belgium; Rehabilitation Sciences Research Department (RERE), Vrije Universiteit Brussel, Laarbeeklaan 103, B-1090, Brussels, Belgium. 3. Gerontology Department and Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, B-1090, Brussels, Belgium; Frailty in Ageing (FRIA) Research Department, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, B-1090, Brussels, Belgium; Geriatrics Department, Universitair Ziekenhuis Brussel (UZ Brussel), Laarbeeklaan 101, B-1090 Brussels, Belgium. 4. Department of Electronics and Informatics ETRO, Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Elsene, Belgium; IMEC Brussel, Vrije Universiteit Brussel (VUB), Pleinlaan 9, 1050 Elsene, Belgium. 5. Gerontology Department and Frailty in Ageing (FRIA) Research Department, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, B-1090 Brussels, Belgium. 6. Gerontology Department and Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, B-1090, Brussels, Belgium; Frailty in Ageing (FRIA) Research Department, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, B-1090, Brussels, Belgium; Geriatrics Department, Universitair Ziekenhuis Brussel (UZ Brussel), Laarbeeklaan 101, B-1090 Brussels, Belgium. Electronic address: ivan.bautmans@vub.be. 7. Frailty in Ageing (FRIA) Research Department, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, B-1090, Brussels, Belgium; Experimental Anatomy (EXAN), Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, B-1090 Brussels, Belgium.
Abstract
BACKGROUND: To date, the accuracy of bio-impedance (BIA) to assess body composition & sarcopenia in persons aged 80 and over remains unclear. OBJECTIVE: We aimed to evaluate the agreement between dual energy X-ray absorptiometry (DXA) and BIA equations to determine lean mass, as well as their suitability to identify sarcopenia. DESIGN: 174 community dwelling well-functioning persons (83 women, 91 men) aged 80 and over were included. Appendicular lean mass (ALM) was predicted using BIA-based equations available in literature, and compared to DXA outcomes. Through cross-validation and stepwise multiple linear regression, a new ALM-formula was generated suitable for this population. RESULTS: Literature-based BIA equations systematically overestimated ALM. The new prediction formula that we propose for the 80+ is: ALM = 0,827+(0,19*Impedance Index)+(2,101*Sex)+(0,079*Weight); R2 = 0,888; SEE = 1,450 kg. Sarcopenia classification based on our new BIA equation for ALM showed better agreement with DXA (k ≥ 0,454) compared to literature-based BIA equations (k < 0,368). CONCLUSIONS: Despite the high correlation between both methods, literature-based BIA equations consistently overestimate ALM compared to DXA in persons aged 80 and over. We proposed a new equation for ALM, reaching higher agreement with DXA and thus improving the accuracy of BIA for this specific age group.
BACKGROUND: To date, the accuracy of bio-impedance (BIA) to assess body composition & sarcopenia in persons aged 80 and over remains unclear. OBJECTIVE: We aimed to evaluate the agreement between dual energy X-ray absorptiometry (DXA) and BIA equations to determine lean mass, as well as their suitability to identify sarcopenia. DESIGN: 174 community dwelling well-functioning persons (83 women, 91 men) aged 80 and over were included. Appendicular lean mass (ALM) was predicted using BIA-based equations available in literature, and compared to DXA outcomes. Through cross-validation and stepwise multiple linear regression, a new ALM-formula was generated suitable for this population. RESULTS: Literature-based BIA equations systematically overestimated ALM. The new prediction formula that we propose for the 80+ is: ALM = 0,827+(0,19*Impedance Index)+(2,101*Sex)+(0,079*Weight); R2 = 0,888; SEE = 1,450 kg. Sarcopenia classification based on our new BIA equation for ALM showed better agreement with DXA (k ≥ 0,454) compared to literature-based BIA equations (k < 0,368). CONCLUSIONS: Despite the high correlation between both methods, literature-based BIA equations consistently overestimate ALM compared to DXA in persons aged 80 and over. We proposed a new equation for ALM, reaching higher agreement with DXA and thus improving the accuracy of BIA for this specific age group.
Authors: Jantine van den Helder; Amely M Verreijen; Carliene van Dronkelaar; Robert G Memelink; Mariëlle F Engberink; Raoul H H Engelbert; Peter J M Weijs; Michael Tieland Journal: Front Nutr Date: 2022-06-02
Authors: Kwon Chan Jeon; So-Young Kim; Fang Lin Jiang; Sochung Chung; Jatin P Ambegaonkar; Jae-Hyeon Park; Young-Joo Kim; Chul-Hyun Kim Journal: Int J Environ Res Public Health Date: 2020-08-12 Impact factor: 3.390