title: Body fat in Singaporean infants: development of body fat prediction equations in Asian newborns.
abstract: OBJECTIVE
  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.
  
  
  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.
authors.affiliation: Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
authors.forename: I M
authors.initials: IM
authors.lastname: Aris
authors.forename: S E
authors.initials: SE
authors.lastname: Soh
authors.forename: M T
authors.initials: MT
authors.lastname: Tint
authors.forename: S
authors.initials: S
authors.lastname: Liang
authors.forename: A
authors.initials: A
authors.lastname: Chinnadurai
authors.forename: S M
authors.initials: SM
authors.lastname: Saw
authors.forename: K
authors.initials: K
authors.lastname: Kwek
authors.forename: K M
authors.initials: KM
authors.lastname: Godfrey
authors.forename: P D
authors.initials: PD
authors.lastname: Gluckman
authors.forename: Y S
authors.initials: YS
authors.lastname: Chong
authors.forename: F K P
authors.initials: FK
authors.lastname: Yap
authors.forename: Y S
authors.initials: YS
authors.lastname: Lee
mesh_terms: D000273:Adipose Tissue / Q000502:physiology*; D044466:Asian People; D001499:Bayes Theorem; D001823:Body Composition; D001835:Body Weight; D005260:Female; D005865:Gestational Age; D006801:Humans; D007231:Infant, Newborn; D008297:Male; D018482:Muscle, Skeletal; D010991:Plethysmography; D011446:Prospective Studies; D012044:Regression Analysis; D012846:Singapore; D012885:Skinfold Thickness