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1.
Diabetes Nutr Metab ; 14(4): 181-8, 2001 Aug.
Article in English | MEDLINE | ID: mdl-11716286

ABSTRACT

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.


Subject(s)
Diet , Energy Intake , Obesity/diet therapy , Absorptiometry, Photon , Adipose Tissue , Adult , Basal Metabolism , Blood Glucose/analysis , Body Composition , Body Mass Index , Cholesterol, HDL/blood , Cholesterol, LDL/blood , Diet, Reducing , Female , Fibrinogen/analysis , Glucose Tolerance Test , Humans , Insulin/blood , Italy , Mediterranean Region , Nutrition Policy , Obesity/metabolism , Prospective Studies , Quality Control , Triglycerides/blood , Uric Acid/blood
2.
Appl Radiat Isot ; 49(5-6): 739-41, 1998.
Article in English | MEDLINE | ID: mdl-9569597

ABSTRACT

Body composition (BC) assessment is a useful tool for a careful evaluation of nutrition status. Bioelectrical impedance analysis (BIA) is a safe, low-cost and reliable method for BC assessment. For epidemiological and clinical research in children, paediatric-age specific formula for fat-free mass (FFM) prediction from BIA is needed. Thus, in 35 children (age 7.7-13.0 years) with different levels of body fatness (relative weight for age 70.6-133.8%), FFM was calculated from dual-energy X-ray absorptiometry (DXA). A regression equation from BIA and DXA data was elaborated. The impedance index (ZI = height2/bioelectrical impedance) was the strongest predictor of FFM, explaining 89% of its variance. However, the variance increased to 96% when body weight was added with ZI in the regression model. No variable, including sex and age, contributed to the prediction of FFM in the presence of ZI and body weight. The regression formula [FFM = 2.330 + 0.588 ZI (cm2/omega) + 0.211 Weight (kg) (r = 0.96, SEE = 1.0 kg)], allows a reliable prediction of FFM in children from body impedance values.


Subject(s)
Absorptiometry, Photon/methods , Body Composition , Electric Impedance , Adipose Tissue , Adolescent , Anthropometry/methods , Body Height , Body Weight , Child , Female , Humans , Male , Nutritional Status , Regression Analysis , Reproducibility of Results , Skinfold Thickness
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