Measurements of body fat in Indonesian adults: Comparison between a three-compartment model and widely used methods

Body composition was assessed in Indonesian male (n = 18) and female (n = 23) students using densitometry (underwater weighing), deuterium oxide dilution, skinfold thickness measurements, bioelectrical impedance analysis (BIA) and a prediction equation based on the body mass index. From body density...

Full description

Saved in:
Bibliographic Details
Published inAsia Pacific journal of clinical nutrition Vol. 7; no. 1; pp. 49 - 54
Main Authors Küpper, J, Bartz, M, Schultink, J W, Lukito, W, Deurenberg, P
Format Journal Article
LanguageEnglish
Published Australia 01.03.1998
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Body composition was assessed in Indonesian male (n = 18) and female (n = 23) students using densitometry (underwater weighing), deuterium oxide dilution, skinfold thickness measurements, bioelectrical impedance analysis (BIA) and a prediction equation based on the body mass index. From body density and total body water percentage body fat (BF%) was calculated using a three-compartment body composition model. Percentage body fat obtained by this three-compartment model was regarded as the reference value and BF% obtained by the single methods were compared with this value. Mean differences (± SD) in BF% from the threecompartment model minus the single methods were -1.1 ± 2.1 for densitometry, +1.1 ± 1.6 for deuterium oxide dilution, +1.3 ± 2.8 for skinfold thickness measurement, +2.8 ± 4.3 for BIA and +3.4 ± 4.8 for body mass index in males. In females these values were +0.1 ± 1.7, +0.2 ± 1.4, +3.6 ± 3.3, +3.6 ± 2.4 and +8.7 ± 2.0 BF%, respectively. Correlation coefficients between different methods were high and significant (P < 0.05 in males, P < 0.001 in females). This study shows that the single predictive methods have considerable mean and individual biases compared with the three-compartment model and all predictive methods underestimated body fat in the studied subjects. It is concluded that the development of population-specific prediction formulas may be necessary.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0964-7058
1440-6047