Abstract:
Background: Body composition indicators provide a better guidance for growth and nutritional status of the
infants. This study was designed to (1) measure the body composition of the Sri Lankan infants using a reference
method, the 18O dilution method; (2) calculate the body fat content of the infants using published skinfold prediction
equations; and (3) evaluate the applicability of the skinfold equations to predict body fat among Sri Lankan infants
against the 18O dilutionmethod.
Methods: Twenty five healthy, exclusively breast-fed infants were randomly recruited at well-baby clinics, for this
cross-sectional study. Body composition was measured using 18O dilution. Infant body weight, length, skinfold
thicknesses and mid upper-arm circumference were measured using standard procedures. The Bland and Atlman
pair-wise comparison method was used to evaluate the agreement of body fat generated using the anthropometric
prediction equations against the 18O dilution values as the reference.
Results: Mean (SD) body weight and length of the infants were 6.5 kg (0.9) and 64.7 cm (2.8) respectively. Mean total
body water, fat free mass, fat mass and % fat mass as measured by 18O dilution method were 58.8% (5.0), 4.6 kg (0.8),
1.9 (0.5) and 29.5% (6.1). Total body water and fat free mass were significantly higher in boys when compared to girls.
With the exception of three prediction equations (Bandana et al., Goran et al. and Durnin and Wormsley), most of the
other commonly used anthropometry-based prediction equations yielded a bias which was not constant but a function
of the % fat mass.
Conclusions: Body composition of Sri Lankan infants is comparable to the normative data available from the
industrialized countries. Most of the commonly used anthropometric prediction equations generated a bias which
varies with the size of the body fat. Only three prediction equations (Bandana, Goran, Durnin & Wormsley) yield a
constant bias. The Durnin & Wormsely equation showed the smallest bias when compared to the 18O dilution values
with the narrowest limits of agreement. Accuracy of some of the prediction equations is a function of gender.