title: Prediction of percentage body fat in rural thai population using simple anthropometric measurements.
abstract: OBJECTIVE
  To develop and validate sex-specific equations for predicting percentage body fat (%BF) in rural Thai population, based on BMI and anthropometric measurements.
  
  
  METHODS
  %BF (DXA; GE Lunar Corp., Madison, WI) was measured in 181 men and 255 women who were healthy and between 20 and 84 years old. Anthropometric measures such as weight (kilograms), height (centimeters), BMI (kilograms per meter squared), waist circumference (centimeters), hip circumference (centimeters), thickness at triceps skinfold (millimeters), biceps skinfold (millimeters), subscapular skinfold (millimeters), and suprailiac skinfold (millimeters) were also measured. The sample was randomly divided into a development group (98 men and 125 women) and a validation group (83 men and 130 women). Regression equations of %BF derived from the development group were then evaluated for accuracy in the validation group.
  
  
  RESULTS
  The equation for estimating %BF in men was: %BF(men) = 0.42 x subscapular skinfold + 0.62 x BMI - 0.28 x biceps skinfold + 0.17 x waist circumference - 18.47, and in women: %BF(women) = 0.42 x hip circumference + 0.17 x suprailiac skinfold + 0.46 x BMI - 23.75. The coefficient of determination (R2) for both equations was 0.68. Without anthropometric variables, the predictive equation using BMI, age, and sex was: %BF = 1.65 x BMI + 0.06 x age - 15.3 x sex - 10.67 (where sex = 1 for men and sex = 0 for women), with R2 = 0.83. When these equations were applied to the validation sample, the difference between measured and predicted %BF ranged between +/-9%, and the positive predictive values were above 0.9.
  
  
  CONCLUSIONS
  These results suggest that simple, noninvasive, and inexpensive anthropometric variables may provide an accurate estimate of %BF and could potentially aid the diagnosis of obesity in rural Thais.
authors.affiliation: Division of Endocrinology and Metabolism, Department of Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, 40002 Thailand. pchatl@kku.ac.th
authors.forename: Chatlert
authors.initials: C
authors.lastname: Pongchaiyakul
authors.forename: Vongsvat
authors.initials: V
authors.lastname: Kosulwat
authors.forename: Nipa
authors.initials: N
authors.lastname: Rojroongwasinkul
authors.forename: Somsri
authors.initials: S
authors.lastname: Charoenkiatkul
authors.forename: Kaewjai
authors.initials: K
authors.lastname: Thepsuthammarat
authors.forename: Malinee
authors.initials: M
authors.lastname: Laopaiboon
authors.forename: Tuan V
authors.initials: TV
authors.lastname: Nguyen
authors.forename: Rajata
authors.initials: R
authors.lastname: Rajatanavin
mesh_terms: D000005:Abdomen; D000273:Adipose Tissue; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging; D000886:Anthropometry / Q000379:methods*; D001823:Body Composition; D015992:Body Mass Index; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000453:epidemiology; D012424:Rural Population; D012680:Sensitivity and Specificity; D012727:Sex Characteristics; D012885:Skinfold Thickness; D013785:Thailand / Q000453:epidemiology; D014944:World Health Organization