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Body fat in Singaporean infants: development of body fat prediction equations in Asian newborns

Body fat in Singaporean infants: development of body fat prediction equations in Asian newborns
Body fat in Singaporean infants: development of body fat prediction equations in Asian newborns
BACKGROUND/OBJECTIVES: Prediction equations are commonly used to estimate body fat from anthropometric measurements, but are population specific. We aimed to establish and validate a body composition prediction formula for Asian newborns, and compared the performance of this formula with that of a published equation.

SUBJECTS/METHODS: Among 262 neonates (174 from day 0, 88 from days 1-3 post delivery) from a prospective cohort study, body composition was measured using air-displacement plethysmography (PEA POD), with standard anthropometric measurements, including triceps and subscapular skinfolds. Using fat mass measurement by PEA POD as a reference, stepwise linear regression was utilized to develop a prediction equation in a randomly selected subgroup of 62 infants measured on days 1-3, which was then validated in another subgroup of 200 infants measured on days 0-3.

RESULTS: Regression analyses revealed subscapular skinfolds, weight, gender and gestational age were significant predictors of neonatal fat mass, explaining 81.1% of the variance, but not triceps skinfold or ethnicity. By Bland-Altman analyses, our prediction equation revealed a non-significant bias with limits of agreement (LOA) similar to those of a published equation for infants measured on days 1-3 (95% LOA: (-0.25, 0.26)?kg vs (-0.23, 0.21)?kg) and on day 0 (95% LOA: (-0.19, 0.17)?kg vs (-0.17, 0.18)?kg). The published equation, however, exhibited a systematic bias in our sample.

CONCLUSIONS: Our equation requires only one skinfold site measurement, which can significantly reduce time and effort. It does not require the input of ethnicity and, thus, aid its application to other Asian neonatal populations.
0954-3007
922-927
Aris, I.M.
ee15a46e-ead3-4b4a-a208-d39038a85480
Soh, S.E.
00a5ad13-4c5b-4fad-aaa9-d080d9aa63e8
Tint, M.T.
02d6a006-3b94-4328-b3c3-147a618d66c3
Liang, S.
2d62fcbf-c433-4fb3-9c20-c4aabef8d3f1
Chinnadurai, A.
c218e5f8-7ba5-428e-a2f5-e8f894305403
Saw, S.M.
0684517e-f27e-49f0-98c3-7630e8fd1bbd
Kwek, K.
1a9b6c6e-a5e9-40a2-9bfe-44c2cea62a98
Godfrey, K.M.
0931701e-fe2c-44b5-8f0d-ec5c7477a6fd
Gluckman, P.D.
492295c0-ef71-4871-ad5a-771c98e1059a
Chong, Y.S.
b50c99c9-4d83-46c5-a1c7-23f9a553ab8a
Yap, F.K.
693a7952-b778-4ce3-ae75-a9aede0000bd
Lee, Y.S.
829a41bb-945c-49cd-ad12-0f3d9c2782c6
Aris, I.M.
ee15a46e-ead3-4b4a-a208-d39038a85480
Soh, S.E.
00a5ad13-4c5b-4fad-aaa9-d080d9aa63e8
Tint, M.T.
02d6a006-3b94-4328-b3c3-147a618d66c3
Liang, S.
2d62fcbf-c433-4fb3-9c20-c4aabef8d3f1
Chinnadurai, A.
c218e5f8-7ba5-428e-a2f5-e8f894305403
Saw, S.M.
0684517e-f27e-49f0-98c3-7630e8fd1bbd
Kwek, K.
1a9b6c6e-a5e9-40a2-9bfe-44c2cea62a98
Godfrey, K.M.
0931701e-fe2c-44b5-8f0d-ec5c7477a6fd
Gluckman, P.D.
492295c0-ef71-4871-ad5a-771c98e1059a
Chong, Y.S.
b50c99c9-4d83-46c5-a1c7-23f9a553ab8a
Yap, F.K.
693a7952-b778-4ce3-ae75-a9aede0000bd
Lee, Y.S.
829a41bb-945c-49cd-ad12-0f3d9c2782c6

Aris, I.M., Soh, S.E., Tint, M.T., Liang, S., Chinnadurai, A., Saw, S.M., Kwek, K., Godfrey, K.M., Gluckman, P.D., Chong, Y.S., Yap, F.K. and Lee, Y.S. (2013) Body fat in Singaporean infants: development of body fat prediction equations in Asian newborns. European Journal of Clinical Nutrition, 67 (9), 922-927. (doi:10.1038/ejcn.2013.69). (PMID:23549200)

Record type: Article

Abstract

BACKGROUND/OBJECTIVES: Prediction equations are commonly used to estimate body fat from anthropometric measurements, but are population specific. We aimed to establish and validate a body composition prediction formula for Asian newborns, and compared the performance of this formula with that of a published equation.

SUBJECTS/METHODS: Among 262 neonates (174 from day 0, 88 from days 1-3 post delivery) from a prospective cohort study, body composition was measured using air-displacement plethysmography (PEA POD), with standard anthropometric measurements, including triceps and subscapular skinfolds. Using fat mass measurement by PEA POD as a reference, stepwise linear regression was utilized to develop a prediction equation in a randomly selected subgroup of 62 infants measured on days 1-3, which was then validated in another subgroup of 200 infants measured on days 0-3.

RESULTS: Regression analyses revealed subscapular skinfolds, weight, gender and gestational age were significant predictors of neonatal fat mass, explaining 81.1% of the variance, but not triceps skinfold or ethnicity. By Bland-Altman analyses, our prediction equation revealed a non-significant bias with limits of agreement (LOA) similar to those of a published equation for infants measured on days 1-3 (95% LOA: (-0.25, 0.26)?kg vs (-0.23, 0.21)?kg) and on day 0 (95% LOA: (-0.19, 0.17)?kg vs (-0.17, 0.18)?kg). The published equation, however, exhibited a systematic bias in our sample.

CONCLUSIONS: Our equation requires only one skinfold site measurement, which can significantly reduce time and effort. It does not require the input of ethnicity and, thus, aid its application to other Asian neonatal populations.

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More information

Published date: 3 April 2013
Organisations: Faculty of Medicine

Identifiers

Local EPrints ID: 359271
URI: https://eprints.soton.ac.uk/id/eprint/359271
ISSN: 0954-3007
PURE UUID: f3421731-d174-4363-9e0a-f97b38c838a4
ORCID for K.M. Godfrey: ORCID iD orcid.org/0000-0002-4643-0618

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Date deposited: 25 Oct 2013 12:09
Last modified: 20 Jul 2019 01:22

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Contributors

Author: I.M. Aris
Author: S.E. Soh
Author: M.T. Tint
Author: S. Liang
Author: A. Chinnadurai
Author: S.M. Saw
Author: K. Kwek
Author: K.M. Godfrey ORCID iD
Author: P.D. Gluckman
Author: Y.S. Chong
Author: F.K. Yap
Author: Y.S. Lee

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