Aldo Scafoglieri1, Jan Pieter Clarys2, Jürgen M Bauer3, Sjors Verlaan4, Lien Van Malderen5, Stijn Vantieghem6, Tommy Cederholm7, Cornel C Sieber8, Tony Mets9, Ivan Bautmans10. 1. Frailty in Ageing Research Group (FRIA), Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090, Brussels, Belgium. Electronic address: aldo.scafoglieri@vub.ac.be. 2. Radiology Department, University Hospital Brussels, Laarbeeklaan 101, 1090, Brussels, Belgium. Electronic address: jclarys@vub.ac.be. 3. Department of Geriatric Medicine, Carl Von Ossietzky University, Oldenburg, Germany. Electronic address: juergenmbauer@me.com. 4. Nutricia Research, Nutricia Advanced Medical Nutrition, Utrecht, The Netherlands; Department of Internal Medicine, Section of Gerontology and Geriatrics, VU University Medical Center, Amsterdam, The Netherlands. Electronic address: sjors.verlaan@nutricia.com. 5. Frailty in Ageing Research Group (FRIA), Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090, Brussels, Belgium. Electronic address: lien.van.malderen@vub.ac.be. 6. Frailty in Ageing Research Group (FRIA), Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090, Brussels, Belgium. Electronic address: stijn.vantieghem@vub.ac.be. 7. Department of Public Health and Caring Sciences/Clinical Nutrition and Metabolism, Department of Geriatric Medicine, Uppsala University Hospital, Uppsala, Sweden. Electronic address: tommy.cederholm@pubcare.uu.se. 8. Institute for Biomedicine on Ageing, Friedrich-Alexander-University Erlangen-Nürnberg, Nürnberg, Germany. Electronic address: cornel.sieber@iba.fau.de. 9. Frailty in Ageing Research Group (FRIA), Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090, Brussels, Belgium. Electronic address: tony.mets@vub.ac.be. 10. Frailty in Ageing Research Group (FRIA), Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090, Brussels, Belgium. Electronic address: ivan.bautmans@vub.ac.be.
Abstract
BACKGROUND & AIMS: No generalizable formulas exist that are derived from bioelectrical impedance analysis (BIA) for predicting appendicular lean mass (ALM) and fat mass (AFM) in sarcopenic older adults. Since precision of regional body composition (BC) data in multicentre trials is essential, this study aimed to: 1) develop and cross-validate soft tissue BIA equations with GE Lunar and Hologic DXA systems as their reference 2) to compare our new ALM equation to two previously published models and 3) to assess the agreement between BIA- and DXA-derived soft tissue ratios as indicators of limb tissue quality. METHODS: Two-hundred and ninety-one participants with functional limitations (SPPB-score 4-9; sarcopenia class I or II, measured by BIA) were recruited from 18 study centres in six European countries. BIA equations, using DXA-derived ALM and AFM as the dependent variable, and age, gender, weight, impedance index and reactance as independent variables, were developed using a stepwise multiple linear regression approach. RESULTS: Cross-validation gave rise to 4 equations using the whole sample: ALMLUNAR (kg) = 1.821 + (0.168*height2/resistance) + (0.132*weight) + (0.017*reactance) - (1.931*sex) [R2 = 0.86 and SEE = 1.37 kg] AFMLUNAR (kg) = -6.553 - (0.093* height2/resistance) + (0.272*weight) + (4.295*sex) [R2 = 0.70 and SEE = 1.53 kg] ALMHOLOGIC (kg) = 4.957 + (0.196* height2/resistance) + (0.060*weight) - (2.554*sex) [R2 = 0.90 and SEE = 1.28 kg] AFMHOLOGIC (kg) = -4.716 - (0.142* height2/resistance) + (0.316*weight) + (4.453*sex) - (0.040*reactance) [R2 = 0.73 and SEE = 1.54 kg] Both previously published models significantly overestimated ALM in our sample with biases of -0.36 kg to -1.05 kg. For the ratio of ALM to AFM, a strong correlation (r = 0.82, P < 0.0001) was found between the mean estimate from BIA and the DXA models without significant difference (estimated bias of 0.02 and 95% LOA -0.62, 0.65). CONCLUSION: We propose new BIA equations allowing the estimation of appendicular lean and fat mass. Our equations allow to accurately estimate the appendicular lean/fat ratio which might provide information regarding limb tissue quality, in clinical settings. Furthermore, these BIA equations can be applied to characterize sarcopenia with Hologic and Lunar reference values for BC. Previously published BIA-based models tend to overestimate ALM in sarcopenic older adults. Users of both GE Lunar and Hologic may now benefit from these equations in field research.
BACKGROUND & AIMS: No generalizable formulas exist that are derived from bioelectrical impedance analysis (BIA) for predicting appendicular lean mass (ALM) and fat mass (AFM) in sarcopenic older adults. Since precision of regional body composition (BC) data in multicentre trials is essential, this study aimed to: 1) develop and cross-validate soft tissue BIA equations with GE Lunar and Hologic DXA systems as their reference 2) to compare our new ALM equation to two previously published models and 3) to assess the agreement between BIA- and DXA-derived soft tissue ratios as indicators of limb tissue quality. METHODS: Two-hundred and ninety-one participants with functional limitations (SPPB-score 4-9; sarcopenia class I or II, measured by BIA) were recruited from 18 study centres in six European countries. BIA equations, using DXA-derived ALM and AFM as the dependent variable, and age, gender, weight, impedance index and reactance as independent variables, were developed using a stepwise multiple linear regression approach. RESULTS: Cross-validation gave rise to 4 equations using the whole sample: ALMLUNAR (kg) = 1.821 + (0.168*height2/resistance) + (0.132*weight) + (0.017*reactance) - (1.931*sex) [R2 = 0.86 and SEE = 1.37 kg] AFMLUNAR (kg) = -6.553 - (0.093* height2/resistance) + (0.272*weight) + (4.295*sex) [R2 = 0.70 and SEE = 1.53 kg] ALMHOLOGIC (kg) = 4.957 + (0.196* height2/resistance) + (0.060*weight) - (2.554*sex) [R2 = 0.90 and SEE = 1.28 kg] AFMHOLOGIC (kg) = -4.716 - (0.142* height2/resistance) + (0.316*weight) + (4.453*sex) - (0.040*reactance) [R2 = 0.73 and SEE = 1.54 kg] Both previously published models significantly overestimated ALM in our sample with biases of -0.36 kg to -1.05 kg. For the ratio of ALM to AFM, a strong correlation (r = 0.82, P < 0.0001) was found between the mean estimate from BIA and the DXA models without significant difference (estimated bias of 0.02 and 95% LOA -0.62, 0.65). CONCLUSION: We propose new BIA equations allowing the estimation of appendicular lean and fat mass. Our equations allow to accurately estimate the appendicular lean/fat ratio which might provide information regarding limb tissue quality, in clinical settings. Furthermore, these BIA equations can be applied to characterize sarcopenia with Hologic and Lunar reference values for BC. Previously published BIA-based models tend to overestimate ALM in sarcopenic older adults. Users of both GE Lunar and Hologic may now benefit from these equations in field research.
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