61 resultados para fat free mass
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Background Diagnosis of the HIV-associated lipodystrophy syndrome is based on clinical assessment, in lack of a consensus about case definition and reference methods. Three bedside methods were compared in their diagnostic value for lipodystrophy. Patients and Methods. Consecutive HIV-infected outpatients (n = 278) were investigated, 128 of which also had data from 1997 available. Segmental bioelectrical impedance analysis (BIA) and waist, hip and thigh circumferences were performed. Changes in seven body regions were rated by physicians and patients using linear analogue scale assessment (LASA). Diagnostic cut-off values were searched by receiver operator characteristics. Results. Lipodystrophy was diagnosed in 85 patients (31%). BIA demonstrated higher fat-free mass in patients with lipodystrophy but not after controlling for body mass index and sex. Segmental BIA was not superior to whole body BIA in detecting lipodystrophy. Fat-free mass increased from 1997 to 1999 independent from lipodystrophy. Waist-hip and waist-thigh ratios were higher in patients with lipodystrophy. BIA, anthropometry and LASA did not provide sufficient diagnostic cut-off values for lipodystrophy. Agreement between methods, and between patient and physician rating, was poor. Conclusion: These methods do not fulfil the urgent need for quantitative diagnostic tools for lipodystrophy. BIA estimates of fat free mass may be biased by lipodystrophy, indicating a need for re-calibration in HIV infected populations. (C) 2001 Harcourt Publishers Ltd.
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The purpose of this investigation was to assess changes in total energy expenditure (TEE), body weight (BW) and body composition following a peripheral blood stem cell transplant and following participation in a 3-month duration, moderate-intensity, mixed-type exercise programme. The doubly labelled and singly labelled water methods were used to measure TEE and total body water (TBW). Body weight and TBW were then used to calculate percentage body fat (%BF), and fat and fat-free mass (FFM). TEE and body composition measures were assessed pretransplant (PI), immediately post-transplant (PII) and 3 months post-PII (PIII). Following PII, 12 patients were divided equally into a control group (CG) or exercise intervention group (EG). While there was no change in TEE between pre- and post-transplant, BW (P
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Background: A knowledge of energy expenditure in infancy is required for the estimation of recommended daily amounts of food energy, for designing artificial infant feeds, and as a reference standard for studies of energy metabolism in disease states. Objectives: The objectives of this study were to construct centile reference charts for total energy expenditure (TEE) in infants across the first year of life. Methods: Repeated measures of TEE using the doubly labeled water technique were made in 162 infants at 1.5, 3, 6, 9 and 12 months. In total, 322 TEE measurements were obtained. The LMS method with maximum penalized likelihood was used to construct the centile reference charts. Centiles were constructed for TEE expressed as MJ/day and also expressed relative to body weight (BW) and fat-free mass (FFM). Results: TEE increased with age and was 1.40,1.86, 2.64, 3.07 and 3.65 MJ/day at 1.5, 3, 6, 9 and 12 months, respectively. The standard deviations were 0.43, 0.47, 0.52, 0.66 and 0.88, respectively. TEE in MJ/kg increased from 0.29 to 0.36 and in MJ/day/kg FFM from 0.36 to 0.48. Conclusions: We have presented centile reference charts for TEE expressed as MJ/day and expressed relative to BW and FFM in infants across the first year of life. There was a wide variation or biological scatter in TEE values seen at all ages. We suggest that these centile charts may be used to assess and possibly quantify abnormal energy metabolism in disease states in infants.
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The prevalence of obesity in the western world is dramatically rising, with many of these individuals requiring therapeutic intervention for a variety of disease states. Despite the growing prevalence of obesity there is a paucity of information describing how doses should be adjusted, or indeed whether they need to be adjusted, in the clinical setting. This review is aimed at identifying which descriptors of body size provide the most information about the relationship between dose and concentration in the obese. The size descriptors, weight, lean body weight, ideal body weight, body surface area, body mass index, fat-free mass, percent ideal body weight, adjusted body weight and predicted normal body weight were considered as potential size descriptors. We conducted an extensive review of the literature to identify studies that have assessed the quantitative relationship between the parameters clearance (CL) and volume of distribution (V) and these descriptors of body size. Surprisingly few studies have addressed the relationship between obesity and CL or V in a quantitative manner. Despite the lack of studies there were consistent findings: (i) most studies found total body weight to be the best descriptor of V. A further analysis of the studies that have addressed V found that total body weight or another descriptor that incorporated fat mass was the preferred descriptor for drugs that have high lipophilicity; (ii) in contrast, CL was best described by lean body mass and no apparent relationship between lipophilicity or clearance mechanism and preference for body size descriptor was found. In conclusion, no single descriptor described the influence of body size on both CL and V equally well. For drugs that are dosed chronically, and therefore CL is of primary concern, dosing for obese patients should not be based on their total weight. If a weight-based dose individualization is required then we would suggest that chronic drug dosing in the obese subject should be based on lean body weight, at least until a more robust size descriptor becomes available.
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Objectives: Obesity is a disease with excess body fat where health is adversely affected. Therefore it is prudent to make the diagnosis of obesity based on the measure of percentage body fat. Body composition of a group of Australian children of Sri Lankan origin were studied to evaluate the applicability of some bedside techniques in the measurement of percentage body fat. Methods: Height (H) and weight (W) was measured and BMI (W/H-2) calculated. Bioelectrical impedance analysis (BIA) was measured using tetra polar technique with an 800 mu A current of 50 Hz frequency. Total body water was used as a reference method and was determined by deuterium dilution and fat free mass and hence fat mass (FM) derived using age and gender specific constants. Percentage FM was estimated using four predictive equations, which used BIA and anthropometric measurements. Results: Twenty-seven boys and 15 girls were studied with mean ages being 9.1 years and 9.6 years, respectively. Girls had a significantly higher FM compared to boys. The mean percentage FM of boys (22.9 +/- 8.7%) was higher than the limit for obesity and for girls (29.0 +/- 6.0%) it was just below the cut-off. BMI was comparatively low. All but BIA equation in boys under estimated the percentage FM. The impedance index and weight showed a strong association with total body water (r(2)= 0.96, P < 0.001). Except for BIA in boys all other techniques under diagnosed obesity. Conclusions: Sri Lankan Australian children appear to have a high percentage of fat with a low BMI and some of the available indirect techniques are not helpful in the assessment of body composition. Therefore ethnic and/or population specific predictive equations have to be developed for the assessment of body composition, especially in a multicultural society using indirect methods such as BIA or anthropometry.
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Background: Body mass index ( BMI) is used to diagnose obesity. However, its ability to predict the percentage fat mass (% FM) reliably is doubtful. Therefore validity of BMI as a diagnostic tool of obesity is questioned. Aim: This study is focused on determining the ability of BMI- based cut- off values in diagnosing obesity among Australian children of white Caucasian and Sri Lankan origin. Subjects and methods: Height and weight was measured and BMI ( W/H-2) calculated. Total body water was determined by deuterium dilution technique and fat free mass and hence fat mass derived using age- and gender- specific constants. A % FM of 30% for girls and 20% for boys was considered as the criterion cut- off level for obesity. BMI- based obesity cut- offs described by the International Obesity Task Force ( IOTF), CDC/ NCHS centile charts and BMI- Z were validated against the criterion method. Results: There were 96 white Caucasian and 42 Sri Lankan children. Of the white Caucasians, 19 ( 36%) girls and 29 ( 66%) boys, and of the Sri Lankans 7 ( 46%) girls and 16 ( 63%) boys, were obese based on % FM. The FM and BMI were closely associated in both Caucasians ( r = 0.81, P < 0.001) and Sri Lankans ( r = 0.92, P< 0.001). Percentage FM and BMI also had a lower but significant association. Obesity cut- off values recommended by IOTF failed to detect a single case of obesity in either group. However, NCHS and BMI- Z cut- offs detected cases of obesity with low sensitivity. Conclusions: BMI is a poor indicator of percentage fat and the commonly used cut- off values were not sensitive enough to detect cases of childhood obesity in this study. In order to improve the diagnosis of obesity, either BMI cut- off values should be revised to increase the sensitivity or the possibility of using other indirect methods of estimating the % FM should be explored.
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Background: Lean bodyweight (LBW) has been recommended for scaling drug doses. However, the current methods for predicting LBW are inconsistent at extremes of size and could be misleading with respect to interpreting weight-based regimens. Objective: The objective of the present study was to develop a semi-mechanistic model to predict fat-free mass (FFM) from subject characteristics in a population that includes extremes of size. FFM is considered to closely approximate LBW. There are several reference methods for assessing FFM, whereas there are no reference standards for LBW. Patients and methods: A total of 373 patients (168 male, 205 female) were included in the study. These data arose from two populations. Population A (index dataset) contained anthropometric characteristics, FFM estimated by dual-energy x-ray absorptiometry (DXA - a reference method) and bioelectrical impedance analysis (BIA) data. Population B (test dataset) contained the same anthropometric measures and FFM data as population A, but excluded BIA data. The patients in population A had a wide range of age (18-82 years), bodyweight (40.7-216.5kg) and BMI values (17.1-69.9 kg/m(2)). Patients in population B had BMI values of 18.7-38.4 kg/m(2). A two-stage semi-mechanistic model to predict FFM was developed from the demographics from population A. For stage 1 a model was developed to predict impedance and for stage 2 a model that incorporated predicted impedance was used to predict FFM. These two models were combined to provide an overall model to predict FFM from patient characteristics. The developed model for FFM was externally evaluated by predicting into population B. Results: The semi-mechanistic model to predict impedance incorporated sex, height and bodyweight. The developed model provides a good predictor of impedance for both males and females (r(2) = 0.78, mean error [ME] = 2.30 x 10(-3), root mean square error [RMSE] = 51.56 [approximately 10% of mean]). The final model for FFM incorporated sex, height and bodyweight. The developed model for FFM provided good predictive performance for both males and females (r(2) = 0.93, ME = -0.77, RMSE = 3.33 [approximately 6% of mean]). In addition, the model accurately predicted the FFM of subjects in population B (r(2) = 0.85, ME -0.04, RMSE = 4.39 [approximately 7% of mean]). Conclusions: A semi-mechanistic model has been developed to predict FFM (and therefore LBW) from easily accessible patient characteristics. This model has been prospectively evaluated and shown to have good predictive performance.
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Background: Changes in body composition are commonly reported in pediatric survivors of acute lymphoblastic leukemia (ALL). However, the effect of ALL and of its treatment on body composition in children in remission from ALL has not been fully examined with the use of a reference method. Objectives: We aimed to determine the body composition and composition of fat-free mass (FFM) in children in remission from ALL. We also aimed to compare the effects that prednisolone and dexamethasone had on the body composition of an ALL survivor population. Design: This cross-sectional study measured height, weight, body volume, total body water, and bone mineral content in 24 children in remission from ALL and 24 age-matched, healthy control subjects. Body composition and FFM composition were evaluated by using the 4-component model. Results: The mean body mass index and fat mass index were significantly (P = 0.05 for both) higher in the ALL survivors than in age-matched control subjects. The composition of the FFM in the 2 treatment groups was not observed to differ significantly. Examination of the composition of FFM made it evident that children in remission from ALL had both significantly greater hydration (P = 0.001) and lower density (P = 0.0001) of FFM than did the control children. Conclusions: Children in remission from ALL may develop excess body fat. To measure body composition accurately in an ALL population, the high hydration and low density of FFM in this population should be taken into consideration.
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Objective: The objective of this study was to investigate changes in body weight, BMI, body composition, and fat distribution among freshman women during their 1st year of college. Research Methods and Procedures: Freshman women during the 2004 to 2005 academic year were recruited to participate. The initial baseline visit occurred within the first 6 weeks of the fall 2004 semester, with the follow-up visit occurring during the last 6 weeks of the spring 2005 semester. At each visit, height, weight, BMI, waist and hip circumferences, and body composition (by DXA) were obtained. Results: One hundred thirty-seven participants completed both the fall and spring visits. Significant (p < 0.0001) increases between the fall and spring visits were observed for body weight (58.6 vs. 59.6 kg), BMI (21.9 vs. 22.3), percentage body fat (28.9 vs. 29.7), total fat mass (16.9 vs. 17.7 kg), fat-free mass (38.1 vs. 38.4 kg), waist circumference (69.4 vs. 70.3 cm), and hip circumference (97.4 vs. 98.6 cm), with no significant difference observed in the waist-to-hip ratio (0.71 vs. 0.71; p = 0.78). Discussion: Although statistically significant, changes in body weight, body composition, and fat mass were modest for women during their freshman year of college. These results do not support the purported freshman 15 weight gain publicized in the popular media.
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OBJECTIVE: To use magnetic resonance imaging (MRI) to validate estimates of muscle and adipose tissue (AT) in lower limb sections obtained by dual-energy X-ray absorptiometry (DXA) modelling. DESIGN: MRI measurements were used as reference for validating limb muscle and AT estimates obtained by DXA models that assume fat-free soft tissue (FFST) comprised mainly muscle: model A accounted for bone hydration only; model B also applied constants for FFST in bone and skin and fat in muscle and AT; model C was as model B but allowing for variable fat in muscle and AT. SUBJECTS: Healthy men (n = 8) and women (n = 8), ages 41 - 62 y; mean (s.d.) body mass indices (BMIs) of 28.6 (5.4) kg/m(2) and 25.1 (5.4) kg/m2, respectively. MEASUREMENTS: MRI scans of the legs and whole body DXA scans were analysed for muscle and AT content of thigh (20 cm) and lower leg (10 cm) sections; 24 h creatinine excretion was measured. RESULTS: Model A overestimated thigh muscle volume (MRI mean, 2.3 l) substantially (bias 0.36 l), whereas model B underestimated it by only 2% (bias 0.045 l). Lower leg muscle (MRI mean, 0.6 l) was better predicted using model A (bias 0.04 l, 7% overestimate) than model B (bias 0.1 l, 17% underestimate). The 95% limits of agreement were high for these models (thigh,+/- 20%; lower leg,+/- 47%). Model C predictions were more discrepant than those of model B. There was generally less agreement between MRI and all DXA models for AT. Measurement variability was generally less for DXA measurements of FFST (coefficient of variation 0.7 - 1.8%) and fat (0.8 - 3.3%) than model B estimates of muscle (0.5-2.6%) and AT (3.3 - 6.8%), respectively. Despite strong relationships between them, muscle mass was overestimated by creatinine excretion with highly variable predictability. CONCLUSION: This study has shown the value of DXA models for assessment of muscle and AT in leg sections, but suggests the need to re-evaluate some of the assumptions upon which they are based.
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Our objective was to assess the contribution of lean body mass (LBM) and fat body mass (FBM) to areal bone mineral density (aBMD) in women during the years surrounding menopause. We used a 12-year observational design. Participants included 75 Caucasian women who were premenopausal, 53 of whom were available for follow-up. There were two measurement periods: baseline and 12-year follow-up. At both measurement periods, bone mineral content and aBMD of the proximal femur, posterior-anterior lumbar spine, and total body was assessed using dual-energy X-ray absorptiometry (DXA). LBM and FBM were derived from the total-body scans. General health, including current menopausal status, hormone replace therapy use, medication use, and physical activity, was assessed by questionnaires. At the end of the study, 44% of the women were postmenopausal. After controlling for baseline aBMD, current menopausal status, and current hormone replacement therapy, we found that change in LBM was independently associated with change in aBMD of the proximal femur (P = 0.001). The cross-sectional analyses also indicated that LBM was a significant determinant of aBMD of all three DXA-scanned sites at both baseline and follow-up. These novel longitudinal data highlight the important contribution of LBM to the maintenance of proximal femur bone mass at a key time in women's life span, the years surrounding menopause.
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Eggs from the Heron Island, Great Barrier Reef, nesting population of green turtles (Chelonia mydas) were incubated at all-male-determining (26 degreesC) and all-female-determining (30 degreesC) temperatures. Oxygen consumption and embryonic growth were monitored throughout incubation, and hatchling masses and body dimensions were measured from both temperatures. Eggs hatched after 79 and 53 days incubation at 26 degreesC and 30 degreesC respectively. Oxygen consumption at both temperatures increased to a peak several days before hatching, a pattern typical of turtle embryos, and the rate of oxygen was higher at 30 degreesC than 26 degreesC. The total amount of energy consumed during incubation, and hatchling dimensions, were similar at both temperatures, but hatchlings from 26 degreesC had larger mass, larger yolk-free mass and smaller residual yolks than hatchlings from 30 degreesC. Because of the difference in mass of hatchlings, hatchlings from 30 degreesC had a higher production cost.
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Objective: To develop a standard weight descriptor that can be used for estimation of patient size for obese patients. Patients and methods: Data were available from 3849 patients: 2839 from oncology patients (index data set) and 1010 from general medical patients (validation data set). The patients had a wide range of age (16-100 years), weight (25-165kg) and body mass index (BMI) [12-52 kg/m(2)] in both data sets. From the normal-weight patients in the oncology data set, an equation for male and female patients was developed to predict their normal weight as the sum of the lean body mass and normal fat body mass. The equations were evaluated by predicting the weight of patients in the general medical data set who had a normal BMI (30 kg/m(2)).