Development and validation of anthropometric equations to estimate appendicular muscle mass in elderly women

Abstract

ObjectiveThis study aimed to examine the cross validity of two anthropometric equations commonly used and propose simple anthropometric equations to estimate appendicular muscle mass (AMM) in elderly women.MethodsAmong 234 physically active and functionally independent elderly women, 101 (60 to 89 years) were selected through simple drawing to compose the study sample. The paired t test and the Pearson correlation coefficient were used to perform cross-validation and concordance was verified by intraclass correction coefficient (ICC) and by the Bland and Altman technique. To propose predictive models, multiple linear regression analysis, anthropometric measures of body mass (BM), height, girth, skinfolds, body mass index (BMI) were used, and muscle perimeters were included in the analysis as independent variables. Dual-Energy X-ray Absorptiometry (AMMDXA) was used as criterion measurement. The sample power calculations were carried out by Post Hoc Compute Achieved Power. Sample power values from 0.88 to 0.91 were observed.ResultsWhen compared, the two equations tested differed significantly from the AMMDXA (p <0.001 and p = 0.001). Ten population / specific anthropometric equations were developed to estimate AMM, among them, three equations achieved all validation criteria used: AMM (E2) = 4.150 +0.251 [bodymass (BM)] - 0.411 [bodymass index (BMI)] + 0.011 [Right forearm perimeter (PANTd) 2]; AMM (E3) = 4.087 + 0.255 (BM) - 0.371 (BMI) + 0.011 (PANTd) 2 - 0.035 [thigh skinfold (DCCO)]; MMA (E6) = 2.855 + 0.298 (BM) + 0.019 (Age) - 0,082 [hip circumference (PQUAD)] + 0.400 (PANTd) - 0.332 (BMI). The equations estimated the criterion method (p = 0.056 p = 0.158), and explained from 0.69% to 0.74% of variations observed in AMMDXA with low standard errors of the estimate (1.36 to 1.55 kg) and high concordance (ICC between 0,90 and 0.91 and concordance limits from -2,93 to 2,33 kg).ConclusionThe equations tested were not valid for use in physically active and functionally independent elderly women. The simple anthropometric equations developed in this study showed good practical applicability and high validity to estimate AMM in elderly women.

Estimation of appendicular skeletal muscle: Development and validation of anthropometric prediction equations in Chinese patients with knee osteoarthritis

“…The use of this method in populations with different ethnicities, health conditions or illnesses is reported to have a high R 2 and small SEE. However, almost all authors have suggested that the equation applies only to the population that developed it, and validation in other populations leads to clinically unacceptable bias . Currently, we have not found equations specifically developed for Chinese patients with knee osteoarthritis.…”

“…As an old method, anthropometry has been extensively applied since it was first reported in 1998 by Baumgartner et al, who developed equations for estimating ASM and screening sarcopenia . The use of this method in populations with different ethnicities, health conditions or illnesses is reported to have a high R 2 and small SEE.…”

“…As an old method, anthropometry has been extensively applied since it was first reported in 1998 by Baumgartner et al, 3 who developed equations for estimating ASM and screening sarcopenia. [15][16][17][18][19][20]22,26,27 The use of this method in populations with different ethnicities, health conditions or illnesses is reported to have a high R 2 and small SEE. However, almost all authors have suggested that the equation applies only to the population that developed it, and validation in other populations leads to clinically unacceptable bias.…”

“…Meanwhile, bioelectrical impedance analysis is portable but requires the purchase of equipment, and its measurement accuracy is questionable . As an old body composition analysis method, anthropometry has been validated in different races and disease groups with good accuracy . Its advantages include simplicity, low cost, portability and non‐invasiveness.…”

“…14 As an old body composition analysis method, anthropometry has been validated in different races and disease groups with good accuracy. [15][16][17][18][19][20][21][22] Its advantages include simplicity, low cost, portability and non-invasiveness. However, these anthropometric models may only be applied to the population who developed it [15][16][17][18] ; it may not be appropriate to use these models in other races and groups due to the dissimilar morphology and skeletal muscle mass of different ethnic groups and disease groups.…”