The sympathetic nervous system is recognized to play a role in the etiology of animal and possibly human obesity through its impact on energy expenditure and/or food intake. We, therefore, measured fasting muscle sympathetic nerve activity (MSNA) in the peroneal nerve and its relationship with energy expenditure and body composition in 25 relatively lean Pima Indian males (means±SD; 26±6 yr, 82±19 kg, 28±10% body fat) and 19 Caucasian males (29±5 yr, 81±13 kg, 24±9% body fat). 24-h energy expenditure, sleeping metabolic rate, and resting metabolic rate were measured in a respiratory chamber, whereas body composition was estimated by hydrodensitometry.Pima Indians had lower MSNA than Caucasians (23±6 vs 33±10 bursts/min, P = 0.0007). MSNA was significantly related to percent body fat in Caucasians (r = 0.55, P = 0.01) but not in Pimas. MSNA also correlated with energy expenditure adjusted for fat-free mass, fat mass, and age in Caucasians (r = 0.51, P = 0.03; r = 0.54, P = 0.02; and r = 0.53, P = 0.02 for adjusted 24-h energy expenditure, sleeping metabolic rate, and resting metabolic rate, respectively) but not in Pima Indians.In conclusion, the activity of the sympathetic nervous system is a determinant of energy expenditure in Caucasians. Individuals with low resting MSNA may be at risk for body weight gain resulting from a lower metabolic rate. A low resting MSNA and the lack of impact of MSNA on metabolic rate might play a role in the etiology of obesity in Pima Indians. (J.

The aim of the present study was to determine whether any benefit might occur from lowering the glycaemic index of diet in the medium term in diabetic patients. Eighteen well-controlled diabetic patients (12 Type 1 and 6 Type 2 non-insulin-treated), were assigned to either a high mean glycaemic index or low mean glycaemic index diet for 5 weeks each in a random order using a cross-over design. The two diets were equivalent in terms of nutrient content and total and soluble fibre content. The glycaemic indices were 64 +/- 2 (mean +/- SD) % and 38 +/- 5% for the two diets. The high glycaemic index diet was enriched in bread and potato and the low glycaemic index diet in pasta, rice, and legumes. At the end of the study periods, the following variables were improved on the low compared to the high glycaemic index diet: fructosamine (3.9 +/- 0.9 vs 3.4 +/- 0.4 mmol l-1, p less than 0.05); fasting blood glucose (10.8 +/- 2.8 vs 9.6 +/- 2.7 mmol l-1, p less than 0.02); 2-h postprandial blood glucose (11.6 +/- 2.9 vs 10.3 +/- 2.5 mmol l-1, p less than 0.02); mean daily blood glucose (12.0 +/- 2.5 vs 10.4 +/- 2.7 mmol l-1, p less than 0.02); serum triglycerides (1.5 +/- 0.9 vs 1.2 +/- 0.6 mmol l-1, p less than 0.05). No significant differences were found in body weight, HbA1C, insulin binding to erythrocytes, insulin and drug requirements, and other circulating lipids (cholesterol, HDL-cholesterol, phospholipids, Apolipoprotein A1, Apolipoprotein B). Thus the inclusion of low glycaemic index foods in the diet of diabetic patients may be an additional measure which slightly but favourably influences carbohydrate and lipid metabolism, requires only small changes in nutritional habits and has no known deleterious effects.

Since females have a greater prevalence of obesity compared with males, the question arises whether females have lower metabolic rate than males after adjusting for differences in body weight and composition. 24-h energy expenditure (24EE), basal metabolic rate (BMR), and sleeping metabolic rate (SMR) were measured in a respiratory chamber in 235 healthy, nondiabetic Caucasian subjects (114 males, 121 females). Body composition was determined by hydrodensitometry. 24EE was 124 +/-38 kcal/d (P less than 0.002) higher in males than females after adjusting for differences in fat-free mass, fat mass, and age. Spontaneous physical activity was not significantly different between males and females. Since adjusted 24EE was 106 +/-39 kcal/d (P less than 0.01) higher in females during the luteal phase of the menstrual cycle compared with females during the follicular phase, energy expenditure was analyzed in a subset (greater than 50 yr) to minimize the confounding effect of menstrual status. 24EE (160 +/-66 kcal/d; P less than 0.03), BMR (116 +/-45; P less than 0.02), and SMR (208 +/-68 kcal/d; P less than 0.005) were higher in males compared with females of the older subset after adjusting for differences in body composition, age, and activity. In summary, sedentary 24EE is approximately 5-10% lower in females compared with males after adjusting for differences in body composition, age, and activity.

The glycemic index concept neglects the insulin secretion factor and has not been systematically studied during mixed meals. Six starch-rich foods were tested alone and in an isoglucido-lipido-protidic meal in 18 NIDDs and compared with a glucose challenge. These test meals were randomly assigned using a three factor experiment design. All three tests contained 50 g carbohydrate; mixed meals were adjusted to bring the same amount of fat (20 g), protein (24 g), water (300 mL), and calories (475 kcal) but not the same amount of fiber. Whatever the tested meals, foods elicited a growing glycemic index hierarchy from beans to lentils, rice, spaghetti, potato, and bread (mean range: 0.21 +/- 0.12-92 +/- 0.12, p less than 0.001). Mixing the meals significantly increased the insulinemic indexes (p less than 0.05) and introduced a positive correlation between glycemic and insulinemic indexes (n = 6, r = 0.903; p less than 0.05). The glycemic index concept remains discriminating, even in the context of an iso-glucido-lipido-protidic meal. Insulinemic indexes do not improve discrimination between foods taken alone in type 2 diabetics: they only discriminate between foods during mixed meals, similarly to glycemic indexes.

The agreement between the two modes of administration of the questionnaire suggests that the self-administered version of the MAQ is a valuable tool to assess past-year physical activity and inactivity in self-administered conditions. This instrument could be used in large-scale population studies investigating the relationships between physical activity and health outcomes.

OBJECTIVES: To investigate the relationships between physical activity, dietary intake and body composition in children. DESIGN: A cross-sectional study on physical activity, nutritional intakes and body composition conducted in 86 healthy 10 y old French children. In addition, growth parameters and nutritional intakes were available from the age of 10 months. MEASUREMENTS: Physical activity level (using a validated activity questionnaire over the past year), nutritional intake (dietary history method), anthropometric measurements (body weight, height, arm circumference, triceps and subscapular skinfolds, Body Mass Index (BMI), arm muscle and arm fat areas calculated from these measurements) at the age of 10 y. Anthropometric measurements and nutritional intakes were recorded in the same children at the age of 10 months and every 2 y from the age of 2 y. RESULTS: At the age of 10 y, active children ingested signi®cantly more energy than less active children, mostly due to higher energy intake at breakfast and in the afternoon. This higher energy intake was accounted for by increased consumption of carbohydrates (281 g vs 246 g; 49.6% vs 47.4% of total energy). Even if the amounts of fat consumed were similar in both groups (90 g vs 84 g; P 0.09), the percentage of fat intake was lower in active children (35.4% vs 37.4%; P 0.04). The percentage of protein was not different (14.9% vs 15.3%; P 0.33). In spite of a higher energy intake in the active group, active and less active children had similar BMI at the age of 10 y. However, their body composition differed signi®cantly: active children had a higher proportion of fat-free mass, a lower proportion of fatmass as measured in the arm and they had a later adiposity rebound. Fatness was signi®cantly and positively associated with the time spent watching television and video games. CONCLUSIONS: Physical activity was associated with improved body composition and growth pattern. This association may be related to nutritional changes: active children consumed more energy by increasing carbohydrate, thus reducing the relative fat content of their diet. These results provide support to encourage physical activity during childhood.

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It is currently unclear whether age-specific equations should be used for assessing body composition from bioelectrical resistance. Kushner et al. (Am. J. Clin. Nutr. 56: 835-839, 1992) showed that the relationship between height2/resistance and total body water (TBW) is robust across a wide age range, although uncertainty remained over the relationship in preschool children. We therefore cross-validated the Kushner equation for predicting total body water in 4- to 6-yr-old children in two independent laboratories. TBW was measured from H2 18O dilution, and bioelectrical resistance and reactance were measured using an RJL 101A analyzer in 31 children (15 females, 16 males; 5 +/- 0.8 yr) studied in Burlington, Vermont, and 30 children (14 females, 16 males; 5 +/- 0.2 yr) studied in Phoenix, Arizona. There was no significant difference between TBW predicted from the Kushner equation and that measured in children in Burlington (11.76 +/- 2.00 vs. 11.91 +/- 2.46 kg; r = 0.94) or in Phoenix (11.53 +/- 1.64 vs. 11.66 +/- 1.90 kg; r = 0.94). The Kushner equation for TBW can be transformed into an equation for fat-free mass (FFM) by using published age- and gender-specific constants for the hydration of FFM: hydration of FFM = 76.9 - 0.25 age (yr) - 1.9 gender where female equals 0 and male equals 1. The intraclass reliability for estimates of fat mass and FFM with the use of bioelectrical resistance in an independent group of 26 children (5.0 +/- 0.8 yr, 20.2 +/- 3.0 kg) was > 0.99 for duplicate observations performed 2 wk apart.(ABSTRACT TRUNCATED AT 250 WORDS)