Bioelectrical impedance analysis and dual x-ray absorptiometry agreement for skeletal muscle mass index evaluation in sarcopenia diagnosis.

Background: All definitions for diagnosing sarcopenia include the estimation of muscle mass. This can be made using bioelectrical impedance analysis (BIA) or dual x-ray absorptiometry (DXA). BIA is a portable and inexpensive method suitable for clinical settings, while DXA is cumbersome, more expensive and less available.

Objectives: To evaluate the interchangeability of both techniques for skeletal muscle mass index (SMI) estimation, and assess whether the two methods are comparable for the diagnosis of sarcopenia.

Approach: Prospective, cross-sectional study.

Setting: Faculty for Health Sciences, Universidad de Caldas, Colombia.

Participants: Seventy-two subjects aged 65-80 years were recruited.

Measurements: BIA and DXA for SMI estimation and sarcopenia diagnoses using the definition of the European Working Group on Sarcopenia in Older People (EWGSOP). Of the 72 patients, 28 were diagnosed with sarcopenia by BIA and corroborated by DXA were included in the study. To establish the agreement between techniques, the intraclass correlation coefficient and the concordance correlation coefficient were calculated. A Bland-Altman plot evaluated the agreement. To evaluate agreement on the diagnosis of sarcopenia, a Cohen's kappa test was performed.

Main Results: Agreement between SMI by BIA and DXA was good according to the intraclass correlation coefficient (ICC 0.7 95% CI 0.5 to 0.8) but poor when the concordance correlation coefficient was used (CCC 0.4 was calculated 95% CI 0.3 to 0.5). The Bland-Altman analysis showed a clinically unacceptable discrepancy between the methods; the confidence intervals were too wide; the difference between methods tends to get larger as the average increases and the scatter around the bias line get larger as the average gets higher. Cohen's kappa test was 0.2 (SEE: 0.1).

Significance: The agreement between BIA and DXA was weak. We concluded that, in this studied population, the methods were not interchangeable. Results may improve if a specific formula in a greater sample size is used.