Development and validation of an equation to estimate body fat in elderly women

• Autor(a) principal: Damasceno, Vinicius de Oliveira
• Data de Publicação: 2020
• Outros Autores: Barros, Tercio Araújo do Rego, Gomes, Willemax dos Santos, Santos, Jhonnatan Vasconcelos Pereira, Ferreira, Daniela Karina da Silva, Campos, Eduardo Zapaterra, Costa, André dos Santos
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista Brasileira de Cineantropometria & Desempenho Humano (Online)
• Texto Completo: https://periodicos.ufsc.br/index.php/rbcdh/article/view/73625

The purpose of this present study was to develop and validate a prediction equation for body composition assessment using anthropometric measures of elderly women. This is cross-sectional correlational study with 243 older women ± 64.5 years old and body mass index (BMI) ± 28.70 kg/m². For the development of the equation it was utilized the method of hold-out sample validation. The participants were randomly divided into equation development group (96 elderly women) and a group for validation (147 elderly women). Total body mass, height, waist and hip circumferences, ratio waist-hip ratio and BMI were measured. The whole-body dual-energy X-ray absorptiometry (DXA) assessed body composition (percentage of body fat, fat mass, and fat-free mass). The equations were developed using multiple linear regression, with validation by the stepwise method; the comparison of the equations was analyzed by the paired Student's t test and the analysis of residual scores by the method of Blant and Altman. The New Equation presents a strong correlation (R = 0.83) and (R² = 0.69), and a standard error of estimation equals to 3.21% for percentage body fat prediction. The mean difference between the estimations of percentage body fat from DXA and the New Equation was 0.11% (t(0,180);  P = 0.850). Therefore, the New Equation had an accuracy of 93.5% and a total error of 1.8%. The body fat estimation in older women using this New Equation based on BMI and age is valid and accurate.