BACKGROUND:Body mass index (BMI) is the dominating weight-for-height index, but its validity as a body fat (BF) index has not been properly examined. OBJECTIVES: Our aims were to establish and validate optimal weight-for-height indexes for predicting absolute and relative (percentage) amounts of BF, to examine whether other commonly available anthropometric variables or age could add to the predictive power, and to explore the upper limit for percentage BF. DESIGN:One thousand one hundred twelve randomly selected subjects, and an additional 149 obese subjects, were included in the study. The subjects were randomly allocated to either a primary study group or a validation group. BF was measured with dual-energy X-ray absorptiometry. The relations between weight/heightx (W/Hx) and BF (absolute or percentage) were examined for values of the exponent x that ranged from 0.0 to 3.0. The predictive power of equations that were based on optimal weight-for-height indexes was compared with equations based on weight, height, other anthropometric variables, and age. RESULTS:Absolute BF was optimally and linearly predicted by W/H1, whereas the percentage BF was optimally and nonlinearly predicted by W/H2. The percentage BF asymptotically approached 52% in women and 56% in men. The percentage BF increased only marginally from BMI (in kg/m2) values of >35 in women and >60 in men. Predictions of absolute BF were associated with smaller errors (8.5% for men and 5.7% for women) than were predictions of percentage BF (8.7% for men and 7.9% for women). The addition of other anthropometric measurements for both men and women, and the addition of age for women only, in the regression analyses moderately reduced these errors. CONCLUSION: Our data suggest that W/H may be a more optimal weight-for-height index than is BMI, particularly at high body weights.
RCT Entities:
BACKGROUND: Body mass index (BMI) is the dominating weight-for-height index, but its validity as a body fat (BF) index has not been properly examined. OBJECTIVES: Our aims were to establish and validate optimal weight-for-height indexes for predicting absolute and relative (percentage) amounts of BF, to examine whether other commonly available anthropometric variables or age could add to the predictive power, and to explore the upper limit for percentage BF. DESIGN: One thousand one hundred twelve randomly selected subjects, and an additional 149 obese subjects, were included in the study. The subjects were randomly allocated to either a primary study group or a validation group. BF was measured with dual-energy X-ray absorptiometry. The relations between weight/heightx (W/Hx) and BF (absolute or percentage) were examined for values of the exponent x that ranged from 0.0 to 3.0. The predictive power of equations that were based on optimal weight-for-height indexes was compared with equations based on weight, height, other anthropometric variables, and age. RESULTS: Absolute BF was optimally and linearly predicted by W/H1, whereas the percentage BF was optimally and nonlinearly predicted by W/H2. The percentage BF asymptotically approached 52% in women and 56% in men. The percentage BF increased only marginally from BMI (in kg/m2) values of >35 in women and >60 in men. Predictions of absolute BF were associated with smaller errors (8.5% for men and 5.7% for women) than were predictions of percentage BF (8.7% for men and 7.9% for women). The addition of other anthropometric measurements for both men and women, and the addition of age for women only, in the regression analyses moderately reduced these errors. CONCLUSION: Our data suggest that W/H may be a more optimal weight-for-height index than is BMI, particularly at high body weights.
Authors: John M Schuna; Courtney M Peterson; Diana M Thomas; Moonseong Heo; Sangmo Hong; Woong Choi; Steven B Heymsfield Journal: Am J Hum Biol Date: 2014-11-08 Impact factor: 1.937
Authors: David S Freedman; Heidi M Blanck; William H Dietz; Pronabesh DasMahapatra; Sathanur R Srinivasan; Gerald S Berenson Journal: Br J Nutr Date: 2012-04-13 Impact factor: 3.718
Authors: Steven B Heymsfield; Courtney M Peterson; Diana M Thomas; Moonseong Heo; John M Schuna; Sangmo Hong; Woong Choi Journal: Am J Clin Nutr Date: 2014-10-08 Impact factor: 7.045
Authors: George A Bray; Claude Bouchard; Timothy S Church; William T Cefalu; Frank L Greenway; Alok K Gupta; Lee M Kaplan; Eric Ravussin; Steven R Smith; Donna H Ryan Journal: Obesity (Silver Spring) Date: 2009-04 Impact factor: 5.002