Prediction of percentage body fat in rural thai population using simple anthropometric measurements.

OBJECTIVE: To develop and validate sex-specific equations for predicting percentage body fat (%BF) in rural Thai population, based on BMI and anthropometric measurements. RESEARCH METHODS AND PROCEDURES: %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. DISCUSSION: 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.

RCT Entities:   Population Interventions Outcomes