Optimized predictions of absolute and relative amounts of body fat from weight, height, other anthropometric predictors, and age 1.
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.


OBJECTIVE
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.


METHODS
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.


CONCLUSIONS
Our data suggest that W/H may be a more optimal weight-for-height index than is BMI, particularly at high body weights.
Larsson
Ingrid
I
Sahlgrenska Academy at Göteborg University, Department of Body Composition and Metabolism, Göteborg, Sweden. lars.sjostrom@medfak.gu.se
Henning
Björn
B
Lindroos
Anna Karin
AK
Näslund
Ingmar
I
Sjöström
Carl David
CD
Sjöström
Lars
L
D015502:Absorptiometry, Photon / Q000379:methods; D000273:Adipose Tissue / Q000033:anatomy & histology; D000328:Adult; D000367:Age Factors; D000886:Anthropometry / Q000379:methods*; D001823:Body Composition / Q000502:physiology; D001827:Body Height / Q000502:physiology*; D015992:Body Mass Index; D001835:Body Weight / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009765:Obesity / Q000145:classification / Q000175:diagnosis*; D011237:Predictive Value of Tests; D012044:Regression Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012737:Sex Factors