Use of foot-to-foot bioelectrical impedance analysis in children.

The aim of this study was to compare two methods of measuring body composition in children aged 6-10 years: with a traditional bioelectrical impedance analyser and a foot-to-foot impedance device. In 117 subjects (55 girls, 62 boys), bioelectrical impedance was measured using a Xitron 4000 device and a foot-to-foot impedance instrument (Rowenta); body fat mass and fat-free mass were then calculated and comparisons between means were performed using appropriate statistical tests.

Use of quality control indices in moderately hypocaloric Mediterranean diet for treatment of obesity.

A large number of studies have been published on very-low calorie diets and markedly hypocaloric dietary regimens for treatment of obesity. However, scanty data are available on moderately hypocaloric diets based on the Mediterranean diet model. We evaluated the efficacy and safety of a moderately hypocaloric Mediterranean diet (MHMD) by assessing changes in body composition and in metabolic profile in 19 obese women, aged 32+/-4 years, body weight 84.7+/-9.6 kg, body mass index (BMI) 33.67+/-2.61 kg/m2. The energy content of the diet (mean 6.5 MJ/day) matched the resting metabolic rate and its content in macronutrients (55% carbohydrate, 25% fat, 20% protein, 30 g fibre) was based on the Italian Recommended Dietary Allowances (LARN). Based on the Mediterranean diet model, available nutritional indices like the animal/vegetable protein ratio, the Cholesterol/Saturated Fat Index, the Glycaemic Index, the Atherogenic Index, the Thrombogenic Index and the Mediterranean Adequacy Index were taken into account in elaborating diets. At baseline and after 2 months, body composition by dual energy X-ray absorptiometry, metabolic profile, uric acid, fibrinogen and oral glucose tolerance test (OGTT) were assessed. Following MHMD, body weight decreased to 78.1+/-10.5 kg and BMI to 31.18+/-2.74 kg/m2. Total (-4.9+/-0.9 kg) and segmental fat mass decreased, no significant loss of total and segmental lean body mass was observed. No decrease of fasting blood glucose (5.05+/-0.45 vs 4.98+/-0.43 mmol/l, NS), of the area under the curve (AUC) for glucose (29.50+/-6.24 vs 28.07+/-5.29, NS) as well as of HDL-cholesterol (1.30+/-0.30 vs 1.33+/-0.33 mmol/l, NS) and of triglycerides (1.70+/-1.00 vs 1.46+/-0.66 mmol/l, NS) was observed. However, a significant decrease of basal insulin (11.48+/-6.77 vs 8.07+/-4.17 mU/ml, p<0.01) as well as of the AUC for insulin (263+/-118 vs 208+/-82,p<0.005), of total (5.40+/-1.04 vs 4.97+/-0.92 mmol/l,p<0.05) and LDL-cholesterol (3.36+/-1.07 vs 2.90+/-0.74 mmol/l,p<0.005), of uric acid (0.30+/-0.06 vs 0.28+/-0.05 mmol/l,p<0.01) and fibrinogen (359+/-78 vs 324+/-87 mg/100 ml, p<0.0001) was observed. In conclusion, MHMD prevents loss of fat-free mass and improves metabolic parameters in obese people. We advocate a wider use of nutritional indices and body composition assessment as tools for quality control of hypocaloric diets.

A new predictive equation to calculate resting metabolic rate in athletes.

BACKGROUND: The purposes of the present study were: 1) to examine the accuracy and precision of seven published equations for predicting resting metabolic rate (RMR) in male athletes and 2) to develop a population-specific equation. SETTING: The study occurred during a non-intensive training period. The measurements were performed at the Human Physiology laboratory. PARTICIPANTS: Fifty-one male athletes (22 waterpolo, 12 judo, 17 karate) who exercised regularly at least three hours per day. MEASURES: RMR was measured (mRMR) using indirect calorimetry (ventilated hood system). Besides, mRMR was compared with values predicted (pRMR) using equations of FAO/WHO/UNU, Harris and Benedict, Mifflin et al., Owen et al., Cunningham, Robertson and Reid, Fleisch. Statistical analyses. mRMR was compared with pRMR by means of Student's paired "t" tests, linear regression analysis and the Bland-Altman test. Relationships between mRMR and the different predictive variables were evaluated by Pearson correlation coefficients. The best subset was used to develop the predictive equation for RMR. RESULTS: mRMR was significantly underestimated by six of the seven equations in this sample of athletes. Only the Cunningham equation overestimated (+59 kcal/d) the actual RMR. Bland-Altman 95% limits of agreement were wide (+/- 200-300 kcal/d) for all equations. RMR correlated best with body surface area (r = 0.88), body weight (r = 0.84) and height (r = 0.81). The best-fit equation for the entire data included both weight and height and it was given by: RMR (kcal/d) = -857 + 9.0 (Wt in kg) + 11.7 (Ht in cm) (R2 = 0.78; SEE = 91 kcal/d; 95% IC: -226, 228). CONCLUSIONS: For an individual resting metabolic rate evaluation, the use of indirect calorimetry is recommended. In conditions where this technique cannot be used, our developed equation can predict the RMR of athletes better than any of the currently available prediction equations.