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Estimation of fat-free mass in Asian neonates using bioelectrical impedance analysis

  • Mya-Thway Tint (a1) (a2), Leigh C. Ward (a3), Shu E. Soh (a4), Izzuddin M. Aris (a4), Amutha Chinnadurai (a5), Seang Mei Saw (a6), Peter D. Gluckman (a4) (a7), Keith M. Godfrey (a8), Yap-Seng Chong (a1) (a4), Michael S. Kramer (a9), Fabian Yap (a10) (a11), Barbara Lingwood (a12) and Yung Seng Lee (a2) (a4) (a13)...

Abstract

The aims of this study were to develop and validate a prediction equation of fat-free mass (FFM) based on bioelectrical impedance analysis (BIA) and anthropometry using air-displacement plethysmography (ADP) as a reference in Asian neonates and to test the applicability of the prediction equations in an independent Western cohort. A total of 173 neonates at birth and 140 at two weeks of age were included. Multiple linear regression analysis was performed to develop the prediction equations in a two-third randomly selected subset and validated on the remaining one-third subset at each time point and in an independent Queensland cohort. FFM measured by ADP was the dependent variable, and anthropometric measures, sex and impedance quotient (L2/R50) were independent variables in the model. Accuracy of prediction equations was assessed using intra-class correlation and Bland–Altman analyses. L2/R50 was the significant predictor of FFM at week two but not at birth. Compared with the model using weight, sex and length, including L2/R50 slightly improved the prediction with a bias of 0·01 kg with 2 sd limits of agreement (LOA) (0·18, −0·20). Prediction explained 88·9 % of variation but not beyond that of anthropometry. Applying these equations to the Queensland cohort provided similar performance at the appropriate age. However, when the Queensland equations were applied to our cohort, the bias increased slightly but with similar LOA. BIA appears to have limited use in predicting FFM in the first few weeks of life compared with simple anthropometry in Asian populations. There is a need for population- and age-appropriate FFM prediction equations.

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Corresponding author

* Corresponding author: Associate Professor Y. S. Lee, fax +65 67 797 486, email yung_seng_lee@nuhs.edu.sg

References

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