title: Prediction of body fat by anthropometry in older Chinese people.
abstract: OBJECTIVE
  To derive regression equations for fat percentage by using simple anthropometric measurements applicable in normal and immobile (cannot stand or walk) older people.
  
  
  METHODS
  The study population comprised 352 females and 261 males, apparently well and community-dwelling, aged 69 to 82 years. Fifty-one females and 27 males were recruited for external validation. Body weight, standing height, arm span, triceps and biceps skinfold thicknesses (SFTs), and midarm circumference were measured. The reference method of total body fat percentage was dual-energy X-ray densitometry. Predictive equations for fat percentages were derived by stepwise multiple linear regression on anthropometric indices and gender.
  
  
  RESULTS
  Upper-limb SFTs, body mass index, and gender yielded the more predictive equation. The SEE was 4.1% weight. There was a significant trend of underestimation in overweight subjects, especially in females. The equation using SFTs and midarm circumference was less reliable but more applicable to older immobile people and those with significant kyphoscoliosis.
  
  
  CONCLUSIONS
  The combination of body mass index and upper-limb SFTs gives reliable prediction of fat percentages in older Chinese people, except in the obese.
authors.affiliation: Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin. tkwok@cuhk.edu.hk
authors.forename: T
authors.initials: T
authors.lastname: Kwok
authors.forename: J
authors.initials: J
authors.lastname: Woo
authors.forename: E
authors.initials: E
authors.lastname: Lau
mesh_terms: D015502:Absorptiometry, Photon; D000273:Adipose Tissue / Q000033:anatomy & histology*; D000368:Aged; D000369:Aged, 80 and over; D044466:Asian People; D001823:Body Composition; D015992:Body Mass Index; D006233:Persons with Disabilities; D005260:Female; D006801:Humans; D008019:Life Style; D016014:Linear Models; D008297:Male; D011237:Predictive Value of Tests; D012044:Regression Analysis; D012885:Skinfold Thickness