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
dilution method.
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.
