Some applications of indirect calorimetry to sports medicine

Some applications of indirect calorimetry to sports medicine are discussed and exemplified by case reports. In particular, it is suggested that oxigen consumption can be employed to assess the effects of physical activity on fat-free tissues and that the respiratory quotient may offer some insights into the food habits of athletes

Healthy status and energy balance in pediatrics

During growth, the human body increases in size and changes proportion of various components due to hormones mediators. Nutritional status is the result of introduction, absorption and utilization of the nutrients and it has a new definition in the relationship between nutritional status and healthy status. In this view energy balance, body function and body composition are three entities correlated each other. This mini-review article examines issues and techniques specifically related to a pediatric population in the field of body composition and energy expenditure. It is broadly divided into two sections. The first section discusses body composition measurements underlying principles, advantages, disadvantages and consensus. The second section reviews energy expenditure and physical activity measurement techniques. In conclusion general clinical suggestions are offered regarding pediatric body composition, healthy status and energy balance

A role for bioipendace analisys (BIA)

The measurement of body components is central to the study of body composition in animals and humans. The principle underlying the use of bioimpedance analysis (BIA) for assessing body composition is the relationship between body composition and the water content of the body. Resistance and reactance, the two main determinants of impedance, respond differently at any given frequency to intra-cellular and extra-cellular fluids. Estimation of fat and fat free mass is discussed. Footpad Vs lying position in term of measurement approach as well as accuracy are presented.Using BIA we can measure water content of the body at population level and using specific and appropriate equations we will have the possibility of detecting subjects at risk of overweight and obesity

A new device for measuring resting energy expenditure (REE) in healthy subjects.

Lifestyle change targeted towards increasing daily resting energy expenditure (REE) is one of the cornerstones of obesity treatment. Measurements of energy expenditure and substrate utilization are essential to understanding the metabolic basis of obesity, and the physiological responses to perturbations in habitual food intake. REE is the largest part of human energy expenditure (60-70%) and an increase or decrease in REE would have a large impact on total energy. Accurate and easy-to-use methods for measuring REE are needed, to be applied by clinicians in daily clinical settings to assess the validity of a new instrument to estimate REE in normal weight, healthy adults. METHODS: Ninety-nine subjects (52 females and 47 males) (mean+/-SD, age 38+/-14 years; body mass index (BMI) 23+/-3 kg/m(2)) were tested. REE was assessed using a Sensor Medics Vmax metabolic cart with a ventilated canopy and with the SenseWear armband. Body composition, percentage fat mass (%FM) and percentage fat free mass (%FFM) were assessed by skinfold thickness measurements (SF), bio-electrical impedance analysis (BIA) and air displacement plethysmography (BOD-POD). RESULTS: No significant difference was found among measurements of FFM using the three different techniques. Both SenseWear and Sensor Medics Vmax showed a high correlation, r=0.42 and r=0.40 (p<0.0001) respectively, with BMI. No significant difference was found in mean REE between SenseWear (1540+/-280 kcal/day) and Sensor Medics Vmax (1700+/-330 kcal/day) (p=ns) and the correlation between REE measured by SenseWear and Sensor Medics Vmax was high (r=0.86, p<0.0001). Bland-Altman plot showed no difference in REE determination between SenseWear and Sensor Medics Vmax. %FFM determined by BOD-POD correlated with SenseWear (r=0.42, p<0.0001) as well as Sensor Medics Vmax (r=0.38, p<0.001). CONCLUSION: SF, BIA and BOD-POD provide valid and reliable measurements of FFM. Our results suggest that the SenseWear armband is an acceptable device to accurately measure REE in healthy subjects. Its characteristics have the potential to reduce measurement times and make the SenseWear armband useful for epidemiological studies

Growth-Healthy status and active food model in pediatrics

OBJECTIVE: The brain integrates peripheral signals of nutrition in order to maintain a stable body weight. Nutritional status defined as the results of introduction, absorption, and utilization of the nutrients could be interpreted with the base of the relationship between nutritional status and healthy status. In this view, energy balance, body function, and body composition are three entities correlated to each other to the healthy status. AIM: To discuss the nutritional status in relation with healthy status, and its relationship with growth and nutrients. METHODS: A review of the available literature on food patterns and active food model was carried out. RESULTS: In the reviewed studies, strategies that could offer promising results to prevent overweight and obesity were discussed, in particular in the light of functional foods that effect energy metabolism and fat partitioning. CONCLUSION: At this moment it is necessary to proactively discuss and promote healthy eating behaviors among children at an early age and empower parents to promote children's ability to self-regulate energy intake while providing appropriate structure and boundaries around eating

Reliability of Multisensor Armband in Estimating Energy Expenditure According to Degree of Obesity

Resting energy expenditure (REE) represents the amount of calories required by the body to maintain vital bodyfunctions. One of the most commonly used methods for estimating REE is indirect calorimetry. Recent studies ondifferent populations have validated a highly innovative instrument, the SenseWear® Armband (SWA), which evaluatestotal energy expenditure and, when used in resting conditions, could also evaluate REE. The purpose of this study wasto determine the agreement of the SWA in assessing REE in obese subjects and, see how this agreement varies withdifferent obesity degree.89 obese subjects (59 women and 30 men), with an age range from 35-65 years and body mass index (BMI)34.5 4.5 kg/m2 were studied. REE was measured by IC Sensor Medics Vmax (SM-29N) and by SWA. Fat mass(FM) and fat-free mass (FFM) was determined by anthropometry and bio-impedance measurements. No statisticaldifference was found between REE measured by SWA (1693±276) and REE measured by SM-29N (1627±293). Thetwo methods showed similar assessments (r=0.8, p 35 kg/m2), the agreement decreases (r =0.6 p 35

Effect of intense military training on body composition

Individuals in a structural physical training program can show beneficial changes in body composition, such as body fat reduction and muscle mass increase. This study measured body composition changes by using 3 different techniques-skinfold thickness (SF) measurements, air displacement plethysmography (BOD-POD), and dual-energy x-ray absorptiometry (DXA)-during 9 months of intense training in healthy young men engaged in military training. Twenty-seven young men were recruited from a special faction of the Italian Navy. The program previewed three phases: ground combat, sea combat, and amphibious combat. Body composition was estimated at the beginning, in the middle, and at the end of the training. After the subjects performed the ground combat phase, body composition variables significantly decreased: body weight (P < 0.05), fat-free mass (FFM) (P < 0.001), and fat mass (FM) (P < 0.03). During the amphibious combat phase, body weight increased significantly (P < 0.01), mainly because of an increase in FFM (P < 0.001) and a smaller mean decrease in FM. There was a significant difference (P < 0.05) in circumferences and SF at various sites after starting the training course. Bland-Altman analysis did not show any systematic difference between FM and FFM measured with the 3 different techniques on any occasion. On any visit, FFM and FM correlation measured by BOD-POD (P = 0.90) and DXA was significantly greater than measured by SF. A significant difference was found in body mass index (BMI) measured during the study. BOD-POD and SF, compared with DXA, provide valid and reliable measurement of changes in body composition in healthy young men engaged in military training. In conclusion, the findings suggest that for young men of normal weight, changes in body weight alone and in BMI are not a good measure to assess the effectiveness of intense physical training programs, because lean mass gain can masquerade fat weight loss

Relationship between body composition and bone mineral content in young and elderly women.

PRIMARY OBJECTIVE: To study the relationship between bone mineral content (BMC), lean tissue mass (LTM) and fat mass (FM) in a large sample of young and elderly women. RESEARCH DESIGN: Cross-sectional. METHODS AND PROCEDURES: BMC, LTM and FM were measured by dual-energy X-ray absorptiometry in 2009 free-dwelling Caucasian women aged 63 +/- 7 years (mean +/- SD; range: 37-88 years). The majority of women were postmenopausal (96%). RESULTS: LTM explained 13% more variance of BMC than FM (R(2)(adj) = 0.39 vs 0.26, p < 0.0001) but weight (Wt) explained 5% more variance of BMC than LTM (R(2)(adj) = 0.44, p < 0.0001). The prediction of BMC obtained from LTM and FM (R(2)(adj)= 0.46, p < 0.0001) was only slightly better than that obtained from Wt. After the effects of age, Wt and height (Ht) on BMC were taken into account by multiple regression, the contribution of LTM and FM to BMC was just one-fifth of that of Wt (R(2)(adj) for full models < or =0.56, p < 0.0001). After a further correction for bone area (BA), the contribution of LTM and FM to BMC was just one-tenth of that of BA and not different from that of Wt and Ht on practical grounds (R(2)(adj) for full models = 0.84, p < 0.0001). Thus, after inter-individual differences in age, Wt, Ht (and bone size) are taken into account, the relationship between body composition and BMC is substantially weakened. CONCLUSIONS: In Caucasian women, (1) LTM is a stronger predictor of BMC than FM, but (2) Wt is a better predictor of BMC than body composition for practical purposes, and (3) Wt and body composition are not able to explain more than 46% of BMC variance

Sensitivity and specificity of body mass index and skinfold thicknesses in detecting excess adiposity in children aged 8-12 years

Primary objective: The study aimed to evaluate the sensitivity (SN) and specificity (SP) of body mass index (BMI) and skinfold thicknesses in detecting excess adiposity in children. Research design: Cross-sectional. Materials and methods: 986 children (500 females and 486 males) aged 10 +/- 1 years (mean +/- SD; range: 8-12 years) were studied. All underwent anthropometric measurements and bioelectrical impedance analysis (BIA). Dual-energy X-ray absorptiometry (DXA) was performed in 52 children to develop a population-specific algorithm for the assessment of fat-free mass (FFM) from BIA. The algorithm was applied to the remaining 934 children to estimate their FFM. Fat mass (FM) was obtained by subtracting FFM from weight (Wt). Values of FM:Wt were transformed in Z-scores and converted into 19 percentile categories (from 5 to 95 in steps of 5). The same procedure was performed with BMI and the log-transformed sum of four skinfold thicknesses (triceps, biceps, subscapular and suprailiac; lt-4SF). Excess adiposity was defined as a level of FM:Wt greater than the internally derived 85th percentile. SN and SP of each internally derived percentile of BMI and lt-4SF in detecting excess adiposity were calculated. Results: In the pooled sample (n = 934), SN and SP were 0.39 and 0.99 for the 95th percentile of BMI, 0.65 and 0.95 for the 85th percentile of BMI, and 0.75 and 0.94 for the 85th percentile of lt-4SF. Conclusions: BMI percentiles employed in the present study have a high SP but a low SN in detecting excess adiposity in 8-12-year-old children. The use of the sum of four skinfolds has the potential to increase the SN of a screening programme for excess adiposity in children of this age