Paul Deurenberg

In 1229 subjects, 521 males and 708 females, with a wide range in body mass index (BMI; 13.9-40.9 kg/m2), and an age range of 7-83 years, body composition was determined by densitometry and anthropometry. The relationship between densitometrically-determined body fat percentage (BF%) and BMI, taking age and sex (males = 1, females = 0) into account, was analysed. For children aged 15 years and younger, the relationship differed from that in adults, due to the height-related increase in BMI in children. In children the BF% could be predicted by the formula BF% = 1.51 x BMI-0.70 x age - 3.6 x sex + 1.4 (R2 0.38, SE of estimate (SEE) 4.4% BF%). In adults the prediction formula was: BF% = 1.20 x BMI + 0.23 x age - 10.8 x sex - 5.4 (R2 0.79, SEE = 4.1% BF%). Internal and external cross-validation of the prediction formulas showed that they gave valid estimates of body fat in males and females at all ages. In obese subjects however, the prediction formulas slightly overestimated the BF%. The prediction error is comparable to the prediction error obtained with other methods of estimating BF%, such as skinfold thickness measurements or bioelectrical impedance.

The objective was to study the relationship between body mass index (BMI) and body fat per cent (BF%) in different population groups of Asians. The study design was a literature overview with special attention to recent Asian data. Specific information is provided on Indonesians (Malays and Chinese ancestry), Singaporean Chinese, Malays and Indians, and Hong Kong Chinese. The BMI was calculated from weight and height and the BF% was determined by deuterium oxide dilution, a chemical-for-compartment model, or dual-energy X-ray absorptiometry. All Asian populations studied had a higher BF% at a lower BMI compared to Caucasians. Generally, for the same BMI their BF% was 3-5% points higher compared to Caucasians. For the same BF% their BMI was 3-4 units lower compared to Caucasians. The high BF% at low BMI can be partly explained by differences in body build, i.e. differences in trunk-to-leg-length ratio and differences in slenderness. Differences in muscularity may also contribute to the different BF%/BMI relationship. Hence, the relationship between BF% and BMI is ethnic-specific. For comparisons of obesity prevalence between ethnic groups, universal BMI cut-off points are not appropriate.

Urinary excretion of caffeine in two populations (men and women) of cyclotourists was measured, at rest and during exercise, after oral administration of 350 mg of caffeine in aqueous solution. The so-called “total metabolites”, as measured by the EMIT test, were also determined, as well as urinary creatinine. At rest, elimination in relation to body weight was identical in men and women. During exercise a fivefold decrease in the female and twofold decrease in the male populations were observed. After exercise, caffeine elimination was greater than during the physical trial but remained lower for women than for men. “Total metabolites” excretion showed evidence for a slowing of caffeine catabolism during exercise and a restart of it after exercise. The caffeine content of beverages varies considerably from one country to another, depending on local customs, so that caffeine intake may be highly variable. Our results lead us to query the validity of the upper authorized official limit for urinary caffeine (12 μg·ml−1) in doping controls. The nature of the sporting event, sex, weight, and sampling delay after exercise are all factors that argue against the utilization of a unique standard.