Abstract
ABSTRACT Introduction: Body composition assessment (BCA) using anthropometric measurements (AM) is used to monitor the nutritional and health status of the elderly. As predictor variables, MAs must be valid, practical, and quick, as they favor adherence and avoid possible resistance and embarrassment on the part of those being assessed and being minimally invasive. Objective: To develop and validate equations using accessible and minimally invasive anthropometric measurements for BCA in elderly women. Methods: 100 women (68.1±6.15 years) were randomly assigned to two groups: validation (n=40; 68.1±6.15 years); and estimation (n=60; 68.4±6.70 years). DXA was selected as the criterion measure, and MAs (body mass, height, skinfolds, circumferences) were selected as predictor variables. Means were compared using the paired Student's t-test; correlations were verified using Pearson's r-test; equations using Multiple Linear Regression. The level of agreement between the groups’ results was checked using the Bland-Altman technique. Results: Two equations developed and tested (E3 and E4) met the validation criteria as they showed adequate correlation coefficients (E3: r=0.73; E4: r=0.70), low constant errors (E3: EC= −0.56; E4: EC=-0.90), total error (E3: ET=3.22; E4: ET=3.06) lower than the Standard Error of Estimate (E3: EPE=3.24; E4: EPE=3.21), indicating no statistically significant difference between the two BCA techniques observed (p>0.05). The Bland-Altman technique showed good agreement between the results of the two techniques. Conclusion: Two were validated: E3 (%Gdxa= −41.556 + 4.041(BMI) + 0.165(DcCox) − 0.440(CircCox) + 0.269(CircQuad) − 0.053(BMI)²); and E4 (%GdxaE4= 15.329 + 1.044(BMI) −1.055(CircAbra) + 0.282(CircQuad) + 0.164(DcCox) − 0.262(CircCox)). Notably, the small number of measurements were located in areas of the body that are easily accessible and have little body exposure, which minimizes possible embarrassment and favors adherence by the elderly. Level of Evidence IV; Correlational study to build a predictive equation.
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