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RESEARCH PRODUCT
Validation of bioelectrical impedance analysis for estimating limb lean mass in free-living Caucasian elderly people
Egle PerissinottoS. CarraroFrancesco BolzettaEnzo ManzatoEnzo ManzatoNicola VeroneseCaterina TrevisanGiulia BanoLinda BertonAlessandra CoinGiuseppe SergiS. PizzatoMarina De Ruisubject
MaleSarcopeniamedicine.medical_specialtyUrology030209 endocrinology & metabolismCritical Care and Intensive Care MedicineBody weightWhite PeopleNOBody Mass Index03 medical and health sciences0302 clinical medicineAbsorptiometry PhotonmedicineElectric ImpedanceElderly peopleHumans030212 general & internal medicineMuscle SkeletalSarcopenia Body composition Prediction equation Limb lean mass Older adultsAgedMultiple regression equationAged 80 and overNutrition and Dieteticsbusiness.industryBody WeightReproducibility of ResultsHealthy elderlyLimb lean massMiddle Agedmedicine.diseaseResistive indexPrediction equationCross-Sectional StudiesOlder adultsSarcopeniaLean body massPhysical therapyBody CompositionBody composition; Limb lean mass; Older adults; Prediction equation; Sarcopenia; Critical Care and Intensive Care Medicine; Nutrition and DieteticsFemalebusinessBioelectrical impedance analysisdescription
Background & aims Aging is characterized by a loss of limb lean mass (LLM) that can lead to physical disability and death. Regional bioelectrical impedance analysis (BIA) may be a reliable method for estimating LLM, but no prediction equations are available for elderly Caucasian subjects. The aim of this study was to develop and validate a BIA-based equation for predicting LLM in healthy elderly Caucasians, taking dual X-ray absorptiometry (DXA) as the reference method. Methods Using a cross-sectional design, 244 free-living healthy Caucasian subjects (117 men, 179 women) over 60 years of age were enrolled. LLM was measured with DXA (LLMDXA), and the resistance (Rz) and reactance (Xc) of each limb were measured with a regional bioelectrical impedance analyzer. A resistive index (RI) was calculated from stature in meters divided by Rz of each arm. A BIA-based multiple regression equation for predicting the lean mass (LM) of dominant and non-dominant limbs was developed using a double cross-validation technique. Results Using the sample as a whole, cross-validation resulted in an equation specific for each limb, as follows, where sex equals 1 for males, and 0 for females: LM (kg) = −0.081 + (0.061*RI) + (0.010*body weight) + (0.299*sex) for the dominant arm; LM (kg) = −0.026 + (0.014*RI) + (0.009*body weight) + (0.352*sex) for the non-dominant arm; LM (kg) = −0.462 + (0.027*RI) + (0.047*body weight) + (0.639*sex) + (0.026*Xc) for the dominant leg; and for the non-dominant leg, LM (kg) = −0.522 + (0.029*RI) + (0.045*body weight) + (0.569*sex) + (0.025*Xc). The DXA-measured and BIA-predicted LLM for each limb did not differ significantly. Conclusion Our newly-developed BIA equations seem to provide a valid estimation of LLM in older Caucasian adults. © 2016 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism
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2017-01-01 |