Predicting body composition from anthropometry and bioimpedance in marginally undernourished adolescents and young adults

Abstract

Body-composition prediction equations were developed using data from a sample of 201 female and male Guatemalan ladinos (ie, people of Amerindian-European descent) aged 11-25 y. Fat-free mass (FFM) values were estimated from body density by using the two-component model and age- and sex-specific values for the density of FFM. The root-mean-square error (RMSE) of the best model predicting FFM from a set of simple anthropometric variables was 1.59 kg for females and 1.90 kg for males. The addition of more extensive anthropometry to the set of candidate predictors reduced the RMSE to 1.42 kg for females and 1.88 kg for males. The subsequent addition of a bioelectrical impedance measure (Ht2/R) further reduced the RMSE to 1.32 kg for females and 1.82 kg for males. These results suggest that for a marginally undernourished population with relatively little body fat, simple anthropometrics are as useful as more sophisticated measures for the prediction of body composition.

Fatness and body mass index from birth to young adulthood in a rural Guatemalan population

“…Percentage body fat was calculated as a function of weight and fat-free mass. Fatfree mass was calculated with sex-specific prediction equations based on anthropometry developed through a densitometric study of Guatemalans matched to the subjects on age, anthropometric measurements, and ethnic origin (34). Waist-to-hip ratio (ϫ100) was used as an indicator of abdominal fatness.…”

Validity of published prediction equations for body composition in high altitude Bolivian Aymara as evaluated by doubly labeled water

“…Estimated values and errors for TBW, FFM, and fat% varied greatly with prediction equation. Among the prediction equations tested, however, three, Mellits and Cheek (1970; M&C), Durnin and Womersley (1974; D&W) and Conlisk et al (1992; CNL), had a smaller bias and higher precision than others. Compared to the DLW method, the prediction errors of these equations for FFM and fat% as evaluated by the mean bias and the 95% limits of agreement were −0.7 ± 4.5 kg and 1.5 ± 10% (M&C), 0.9 ± 3.6 kg and −2.1 ± 8.5% (D&W), and 1.1 ± 3.6 kg and −2.7 ± 9.3% (CNL).…”

“…Taking into consideration the use of the multicomponent approach to body composition, their curvilinear equations use the triceps and subscapular skinfolds and account for the chemical immaturity of children. The equations of Conlisk et al (1992) estimate FFM based on a sample of 9-25 year old Guatemalan Ladinos (people of Amerindian-European descent). The equations are based on densitometry and designed to estimate body composition of marginally undernourished populations in Latin America.…”

“…Other ethnic groups, such as the natives of the Latin American countries, who generally have smaller frame size and lighter weight, have been less studied. Several recent reports have developed empirical prediction equations for body composition on rural Guatemalan farmers, urban Guatemalan Ladinos, and urban Colombian women (Diaz et al, 1991;Conlisk et al, 1992;Spurr et al, 1994). The usefulness of these published prediction equations when applied to other samples remains unknown.…”

Predição da massa corporal magra de adultos brasileiros através da área muscular do braço

“…A validade e a confiabilidade da BIA foram determinadas através de estudos que a confrontaram com a pesagem hidrostática. Os métodos apresentaram boa associação, com elevados coeficientes de correlação para a estimativa da MCM (r= 0,84 a 0,98), e reduzidos erros padrões da estimativa (EPE= 1,31 a 5,8 kg) [7][8][9][10][11][12][13] . A última técnica, no entanto, não prescinde de examinadores qualificados e de uma longa fase de preparação a ser criteriosamente seguida pelo avaliado 14 .…”