Magnitude and variation of ratio of total body potassium to fat-free mass: a cellular level modeling study

Potassium is an essential element of living organisms that is found almost exclusively in the intracellular fluid compartment. The assumed constant ratio of total body potassium (TBK) to fat-free mass (FFM) is a cornerstone of the TBK method of estimating total body fat. Although the TBK-to-FFM (TBK/FFM) ratio has been assumed constant, a large range of individual and group values is recognized. The purpose of the present study was to undertake a comprehensive analysis of biological factors that cause variation in the TBK/FFM ratio. A theoretical TBK/FFM model was developed on the cellular body composition level. This physiological model includes six factors that combine to produce the observed TBK/FFM ratio. The ratio magnitude and range, as well as the differences in the TBK/FFM ratio between men and women and variation with growth, were examined with the proposed model. The ratio of extracellular water to intracellular water (E/I) is the major factor leading to between-individual variation in the TBK/FFM ratio. The present study provides a conceptual framework for examining the separate TBK/FFM determinants and suggests important limitations of the TBK/FFM method used in estimating total body fat in humans and other mammals.     

Small birth weight and later body composition and fat distribution in adolescents: the Avena study

Objective: To assess the association between birth weight and body composition and fat distribution in adolescents, and to test the possible sex‐specific effect in these relationships. Methods and Procedures: A total of 1,223 adolescents 13–18.5 years old (553 male adolescents and 670 female adolescents) born at >35 weeks, were selected from a cross‐sectional multicenter study conducted in five Spanish cities in 2000–2002. BMI was calculated from weight and height. Triceps and subscapular skinfold thickness (ST) were measured on the left side, and fat mass (FM) and fat‐free mass (FFM) were estimated according to the equations of Slaughter et al. Subscapular skinfold adjusted by tricipital (ST) and waist circumference were used as markers of central adiposity. Results: Birth weight Z‐score was positively associated with FFM in female adolescents (P < 0.001), but not in male adolescents, after controlling for age, pubertal stage, gestational age, socioeconomic status, physical activity, and current height (P < 0.001 for interaction between adjusted birth weight Z‐score and sex). Adjusted birth weight Z‐score was inversely associated with central adiposity in male and female adolescents as measured by ST (P = 0.026). Discussion: These results provide further evidence that gender has an important influence on the programming effect of birth weight on later FFM in adolescents because the effect was only observed in female adolescents. Our results suggest that small size for gestational age at birth could program more central subcutaneous fat deposition in adolescents of both sexes, but further research is needed on this issue.     

Validity of fan-beam dual-energy X-ray absorptiometry for measuring fat-free mass and leg muscle mass. Health, Aging, and Body Composition Study--Dual-Energy X-ray Absorptiometry and Body Composition Working Group.

The aim of the study was to examine the accuracy of fan-beam dual-energy X-ray absorptiometry (DEXA) for measuring total body fat-free mass (FFM) and leg muscle mass (MM) in elderly persons. Participants were 60 men and women aged 70-79 yr and with a body mass index of 17.5-39.8 kg/m(2). FFM and MM at four leg regions were measured by using DEXA (Hologic 4500A, v8.21). A four-compartment body composition model (4C) and multislice computed tomography (CT) of the legs were used as the criterion methods for FFM and MM, respectively. FFM by DEXA was positively associated with FFM by 4C (R(2) = 0.98, SE of estimate = 1.6 kg). FFM by DEXA was higher [53.5 +/- 12.0 (SD) kg] than FFM by 4C (51.6 +/- 11.9 kg; P < 0.001). No association was observed between the difference and the mean of the two methods. MM by DEXA was positively associated with CT at all four leg regions (R(2) = 0.86-0.96). MM by DEXA was higher than by CT in three regions. The results of this study suggest that fan-beam DEXA offers considerable promise for the measurement of total body FFM and leg MM in elderly persons.     

Differences in skeletal and muscle mass with aging in black and white women

Previous cross-sectional studies using delayed gamma neutron activation analysis and whole body counting suggested that the relationship of total body calcium (TBCa) to total body potassium (TBK) (muscle mass, body cell mass) remained constant with age. This led to the hypothesis that the muscle mass and skeletal mass compartments are integrated in their response to aging. It had also been hypothesized that loss of skeletal and muscle mass was similar between races. In the current study, delayed gamma neutron activation analysis and whole body counting were performed on 90 black and 143 white women 20-69 yr of age. Black women had higher TBCa and TBK values than white women, even when the data were adjusted for age, height, and weight. TBCa was correlated with height and TBK with weight. The estimated decline of skeletal mass (TBCa) from 20 to 70 yr was 18% in black women and 19% in white women. However, the lifetime decline of TBK was only 8% for black women, compared with 22% for white women. Black women may lose TBK more slowly than TBCa with aging, compared with white women. In particular, correlation of TBCa and age was similar for blacks and whites (r = -0.44 and r = -0.54, respectively). However, for TBK these correlations were r = -0.14 and r = -0.42. These data confirm a higher musculoskeletal mass in black women and suggest that the loss of muscle mass with age may be lower in black than in white women. These ethnic differences do not support the hypothesis of an integrated musculoskeletal system, so that these two components should be considered separately. A prospective study is needed to confirm these findings.     

Prediction of Fatness by Standing 8‐Electrode Bioimpedance: A Multiethnic Adolescent Population

The objective of this study was to validate an 8‐electrode bioimpedance analysis (BIA₈) device (BC‐418; Tanita, Tokyo, Japan) for use in populations of European, Maori, Pacific Island, and Asian adolescents. Healthy adolescents (215 M, 216 F; 129 Pacific Island, 120 Asian, 91 Maori, and 91 European; age range 12–19 years) were recruited by purposive sampling of high schools in Auckland, New Zealand. Weight, height, sitting height, leg length, waist circumference, and whole‐body impedance were measured. Fat mass (FM) and fat‐free mass (FFM) derived from the BIA₈ manufacturer's equations were compared with measurements by dual‐energy X‐ray absorptiometry (DXA). DXA‐measured FFM was used as the reference to develop prediction equations based on impedance. A double cross‐validation technique was applied. BIA₈ underestimated FM by 2.06 kg (P < 0.0001) and percent body fat (%BF) by 2.84% (P < 0.0001), on average. However, BIA₈ tended to overestimate FM and %BF in lean and underestimate FM and %BF in fat individuals. Sex‐specific equations developed showed acceptable accuracy on cross‐validation. In the total sample, the best prediction equations were, for boys: FFM (kg) = 0.607 height (cm)²/impedance (Ω) + 1.542 age (y) + 0.220 height (cm) + 0.096 weight (kg) + 1.836 ethnicity (0 = European or Asian, 1 = Maori or Pacific) ? 47.547, R² = 0.93, standard error of estimate (SEE) = 3.09 kg; and, for girls: FFM (kg) = 0.531 height (cm)²/impedance (Ω) + 0.182 height (cm) + 0.096 weight (kg) + 1.562 ethnicity (0 = non‐Pacific, 1 = Pacific) ? 15.782, R² = 0.91, SEE = 2.19 kg. In conclusion, equations for fatness estimation using BIA₈ developed for our sample perform better than reliance on the manufacturer's estimates. The relationship between BIA and body composition in adolescents is ethnicity dependent.     

Interrelationships of serum testosterone and free testosterone index with FFM and strength in aging men

Muscle mass and strength losses during aging may be associated with declining levels of serum testosterone (T) in men. Few studies have shown a direct relationship between T and muscle mass and strength. Subjects were 262 men, aged 24-90 yr, from the Baltimore Longitudinal Study of Aging, who had T and sex hormone-binding globulin sex hormone-binding globulin (SHBG) measurements, from which the free T index (FTI) was calculated (T/SHBG) from serum samples collected longitudinally since 1963, total body fat mass and arm and leg fat-free mass (FFM) by dual-energy X-ray absorptiometry and arm and leg strength by dynanomometry. Mixed-effects models estimated T and FTI at the time of mass and strength measurements. Age, total body fat, arm and leg FFM, T, and FTI were significantly associated with concentric and eccentric strength. FTI, not T, was modestly, but directly, related to arm and leg strength after fat, arm and leg FFM, height, and age were accounted for and indirectly through body mass. FTI is a better predictor of arm and leg strength than T in aging men.     

Three-compartment model: critical evaluation based on neutron activation analysis

There is renewed interest in Siri's classic three-compartment (3C) body composition model, requiring body volume (BV) and total body water (TBW) estimates, because dual-energy X-ray absorptiometry (DEXA) and in vivo neutron activation (IVNA) systems cannot accommodate subjects with severe obesity. However, the 3C model assumption of a constant ratio (alpha) of mineral (M) to total body protein (TBPro) and related residual mass density (D(RES)) based on cadaver analyses might not be valid across groups differing in sex, race, age, and weight. The aim of this study was to derive new 3C model coefficients in vivo and to compare these estimates to those derived by Siri. Healthy adults (n = 323) were evaluated with IVNA and DEXA and the measured components used to derive alpha and D(RES). For all subjects combined, values of alpha and D(RES) (means +/- SD, 0.351 +/- 0.043; 1.565 +/- 0.023 kg/l) were similar to Siri's proposed values of 0.35 and 1.565 kg/l, respectively. However, alpha and D(RES) varied significantly as a function of sex, race, weight, and age. Expected errors in percent body fat arising by application of Siri's model were illustrated in a second group of 264 adults, including some whose size exceeded DEXA limits but whose BV and TBW had been measured by hydrodensitometry and (2)H(2)O dilution, respectively. Extrapolation of predictions by newly developed models to very high weights allows percent fat error estimation when Siri's model is applied in morbidly obese subjects. The present study results provide a critical evaluation of potential errors in the classic 3C model and present new formulas for use in selected populations.     

Reliability and validity of body composition measures in female athletes.

The purpose of this investigation was to determine the reliability and validity of bioelectrical impedance (BIA) and near-infrared interactance (NIR) for estimating body composition in female athletes. Dual-energy X-ray absorptiometry was used as the criterion measure for fat-free mass (FFM). Studies were performed in 132 athletes [age = 20.4 +/- 1.5 (SD) yr]. Intraclass reliabilities (repeat and single trial) were 0.987-0.997 for BIA (resistance and reactance) and 0.957-0.980 for NIR (optical densities). Validity of BIA and NIR was assessed by double cross-validation. Because correlations were high (r = 0.969-0.983) and prediction errors low, a single equation was developed by using all 132 subjects for both BIA and NIR. Also, an equation was developed for all subjects by using height and weight only. Results from dual-energy X-ray absorptiometry analysis showed FFM = 49.5 +/- 6.0 kg, which corresponded to %body fat (%BF) of 20.4 +/- 3.1%. BIA predicted FFM at 49.4 +/- 5.9 kg (r = 0.981, SEE = 1.1), and NIR prediction was 49. 5 +/- 5.8 kg (r = 0.975, SEE = 1.2). Height and weight alone predicted FFM at 49.4 +/- 5.7 kg (r = 0.961, SEE = 1.6). When converted to %BF, prediction errors were approximately 1.8% for BIA and NIR and 2.9% for height and weight. Results showed BIA and NIR to be extremely reliable and valid techniques for estimating body composition in college-age female athletes.     

Effect of constitution on mass of individual organs and their association with metabolic rate in humans--a detailed view on allometric scaling

Resting energy expenditure (REE)-power relationships result from multiple underlying factors including weight and height. In addition, detailed body composition, including fat free mass (FFM) and its components, skeletal muscle mass and internal organs with high metabolic rates (i.e. brain, heart, liver, kidneys), are major determinants of REE. Since the mass of individual organs scales to height as well as to weight (and, thus, to constitution), the variance in these associations may also add to the variance in REE. Here we address body composition (measured by magnetic resonance imaging) and REE (assessed by indirect calorimetry) in a group of 330 healthy volunteers differing with respect to age (17-78 years), sex (61% female) and BMI (15.9-47.8 kg/m(2)). Using three dimensional data interpolation we found that the inter-individual variance related to scaling of organ mass to height and weight and, thus, the constitution-related variances in either FFM (model 1) or kidneys, muscle, brain and liver (model 2) explained up to 43% of the inter-individual variance in REE. These data are the first evidence that constitution adds to the complexity of REE. Since organs scale differently as weight as well as height the "fit" of organ masses within constitution should be considered as a further trait.     

Are Ethnic and Gender Specific Equations Needed to Derive Fat Free Mass from Bioelectrical Impedance in Children of South Asian,Black African-Caribbean and White European Origin? Results of the Assessment of Body Composition in Children Study

Background

Bioelectrical impedance analysis (BIA) is a potentially valuable method for assessing lean mass and body fat levels in children from different ethnic groups. We examined the need for ethnic- and gender-specific equations for estimating fat free mass (FFM) from BIA in children from different ethnic groups and examined their effects on the assessment of ethnic differences in body fat.

Methods

Cross-sectional study of children aged 8–10 years in London Primary schools including 325 South Asians, 250 black African-Caribbeans and 289 white Europeans with measurements of height, weight and arm-leg impedance (Z; Bodystat 1500). Total body water was estimated from deuterium dilution and converted to FFM. Multilevel models were used to derive three types of equation {A: FFM = linear combination(height+weight+Z); B: FFM = linear combination(height²/Z); C: FFM = linear combination(height²/Z+weight)}.

Results

Ethnicity and gender were important predictors of FFM and improved model fit in all equations. The models of best fit were ethnicity and gender specific versions of equation A, followed by equation C; these provided accurate assessments of ethnic differences in FFM and FM. In contrast, the use of generic equations led to underestimation of both the negative South Asian-white European FFM difference and the positive black African-Caribbean-white European FFM difference (by 0.53 kg and by 0.73 kg respectively for equation A). The use of generic equations underestimated the positive South Asian-white European difference in fat mass (FM) and overestimated the positive black African-Caribbean-white European difference in FM (by 4.7% and 10.1% respectively for equation A). Consistent results were observed when the equations were applied to a large external data set.

Conclusions

Ethnic- and gender-specific equations for predicting FFM from BIA provide better estimates of ethnic differences in FFM and FM in children, while generic equations can misrepresent these ethnic differences.     

Muscularity and the density of the fat-free mass in athletes.

The purpose of this study was to use estimates of body composition from a four-component model to determine whether the density of the fat-free mass (D(FFM)) is affected by muscularity or musculoskeletal development in a heterogenous group of athletes and nonathletes. Measures of body density by hydrostatic weighing, body water by deuterium dilution, bone mineral by whole body dual-energy X-ray absorptiometry (DXA), total body skeletal muscle estimated from DXA, and musculoskeletal development as measured by the mesomorphy rating from the Heath-Carter anthropometric somatotype were obtained in 111 collegiate athletes (67 men and 44 women) and 61 nonathletes (24 men and 37 women). In the entire group, D(FFM) varied from 1.075 to 1.127 g/cm3 and was strongly related to the water and protein fractions of the fat-free mass (FFM; r = -0.96 and 0.89) and moderately related to the mineral fraction of the FFM (r = 0.65). Skeletal muscle (%FFM) varied from 40 to 68%, and mesomorphy varied from 1.6 to 9.6, but neither was significantly related to D(FFM) (r = 0.11 and -0.14) or to the difference between percent fat estimated from the four-component model and from densitometry (r = 0.09 and -0.16). We conclude that, in a heterogeneous group of young adult athletes and nonathletes, D(FFM) and the accuracy of estimates of body composition from body density using the Siri equation are not related to muscularity or musculoskeletal development. Athletes in selected sports may have systematic deviations in D(FFM) from the value of 1.1 g/cm3 assumed in the Siri equation, resulting in group mean errors in estimation of percent fat from densitometry of 2-5% body mass, but the cause of these deviations is complex and not simply a reflection of differences in muscularity or musculoskeletal development.     

Body cell mass: model development and validation at the cellular level of body composition

Existing models to estimate the metabolically active body cell mass (BCM) component in vivo remain incompletely developed. The classic Moore model is based on an assumed BCM potassium content of 120 mmol/kg. Our objectives were to develop an improved total body potassium (TBK)-independent BCM prediction model on the basis of an earlier model (Cohn SH, Vaswani AN, Yasumura S, Yuen K, and Ellis KJ. J Lab Clin Med 105: 305-311, 1985), to apply this improved model in subjects to explore the sex and age dependence of the TBK/BCM ratio, to develop a new TBK/BCM model on the basis of physiological associations between TBK and total body water (TBW) at the cellular level of body composition, and to fit this new model with available reference data. Subjects were 112 healthy adults who had the following components measured: TBW by 2H2O or 3H2O, extracellular water by NaBr, total body nitrogen by in vivo neutron activation, bone mineral by dual-energy X-ray absorptiometry, and TBK by whole body counting. Human reference data were collected from earlier published reports. The improved Cohn model-derived TBK/BCM ratio was (mean +/- SD) 109.0 +/- 10.9 mmol/kg and was not significantly related to sex and age. A simplified version of the new TBK-TBW model provided a TBK/BCM ratio almost identical (109.1 mmol/kg) to that derived by the improved Cohn model. The TBK-BCM prediction formula derived from the improved and new models [BCM (kg) = 1/109 x TBK (mmol); or BCM = 0.0092 x TBK] gives BCM estimates approximately 11% higher than the classic Moore model (BCM = 0.0083 x TBK) formulated on rough tissue composition estimates. The present analyses provide a physiologically based, improved, and validated TBK-BCM prediction formula that should prove useful in body composition and metabolism research.     

Relationship Between Basal Metabolic Rate,Gender, Age,and Body Composition in 8,780 White Obese Subjects

The objective of the present study was to explore the relationship between basal metabolic rate (BMR), gender, age, anthropometric characteristics, and body composition in severely obese white subjects. In total, 1,412 obese white children and adolescents (BMI > 97° percentile for gender and age) and 7,368 obese adults (BMI > 30 kg/m²) from 7 to 74 years were enrolled in this study. BMR was measured using an indirect calorimeter equipped with a canopy and fat free mass (FFM) were obtained using tetrapolar bioelectrical impedance analysis (BIA). Using analysis of covariance, we tested the effect of gender on the relationship between BMR, age, anthropometry, and body composition. In children and adolescents, the predictor × gender interaction was significant in all cases except for FFM × gender. In adults, all predictor × gender interactions were significant. A prediction equation based on body weight (BW), age, and gender had virtually the same accuracy of the one based on FFM, age, and gender to predict BMR in both children and adults (R²_adj = 0.59 and 0.60, respectively). In conclusion, gender was a significant determinant of BMR in children and adolescents but not in adults. Our results support the hypothesis that the age‐related decline in BMR is due to a reduction in FFM. Finally, anthropometric predictors of BMR are as accurate as body composition estimated by BIA.     

Cross-Validation of Fat-Free Mass Estimated From Body Density Against Bioelectrical Resistance: Effects of Obesity and Gender

GORAN, MICHAEL I AND M ABU KHALED. Cross-validation of fat-free mass estimated from body density against bioelectrical resistance: effects of obesity and gender. Obes Res. The major purpose of this study was to examine whether estimates of body composition from bioelectrical resistance were systematically biased by obesity and/or gender (using hydrodensitometry as a comparison method). We compared fat-free mass (FFM) by bioelectrical resistance (BR) using 5 equations (Lukaski, Kushner, Rising, Khaled, and Segal) to FFM by hydrodensitometry (HD) in 20 lean men, 30 lean women, 33 obese men and 22 obese women. None of the BR equations was successfully cross-validated against FFM by HD in all 4 sub-groups. The Lukaski equation significantly underestimated FFM in all 4 groups by 2.7 to 4.7 kg; the Kushner equation significantly underestimated FFM by 2.0 to 2.9 kg except in obese women; the Rising equation significantly overestimated FFM in obese women (5.3 kg) and men (2.9 kg); the Khaled equation successfully predicted FFM in all groups except obese men; and the Segal equation successfully predicted FFM in all groups except lean men. In some groups, a portion of the discrepancy could be explained by bias originating from body fat. Analysis of our data by forward regression analysis demonstrated that height²/resistance, body weight, gender and suprailiac skinfold thickness provide the most accurate estimates of FFM (R²=0.92; SEE = 3.58kg) that are free of bias originating from gender and body fat. We conclude that the estimation of fat-free mass by BR is significantly influenced by gender and obesity. An alternative equation is proposed for estimating fat-free mass based on measurement of height²/resistance, body weight, gender and suprailiac skinfold thickness.     

Determinants of resting energy expenditure in obese and non-obese children and adolescents

Resting energy expenditure (REE) is the largest component of total daily energy expenditure. Objectives of this study were to examine whether differences in REE exist after obesity develops in a group of children and adolescents, and to determine the effects of body composition, gender, age, pubertal development and parental obesity on REE. In 116 Caucasian children and adolescents (57 obese and 59 non-obese), aged 7.8 to 16.6 years, REE was assessed by open-circuit indirect calorimetry and different anthropometric variables and bioelectrical impedance were obtained (weight, height, skinfold thicknesses, waist and hip circumferences). Anthropometric indices and body compartments were calculated: the body mass index, surface area (SA), fat-free mass (FFM), fat-mass (FM) and percentage of FM. Differences between obese and non-obese subjects were tested and stepwise multiple regression analysis was performed with REE as dependent variable. Results show that REE was significantly higher in obese than in non-obese children and adolescents but REE/FFM ratio was not significantly different between these groups. In the non-obese group, FFM explained 73.1% of the variability in REE and gender, age and SA added 3.8%, 2.6%, and 2.6% to it, respectively. In the obese group, FFM was also the most powerful predictor of REE with 72.3%, followed by waist circumference and age with 2.5% and 2.1%, respectively. These results show that REE differences between obese and lean children do not seem to justify the maintenance of obesity. The main determinant of REE is FFM in both groups. No significant contribution of FM, pubertal development or parental obesity in REE was found in children and adolescents.     

Relation between fat mass, fat free mass and ventilatory function in children and adolescents

The aim of the present study was to evaluate the relation between fat mass (FM), fat free mass (FFM) and ventilatory function in children and adolescents. 1 174 healthy children and adolescents (583 males and 591 females) aged 10-18 years were selected from Heilongjiang Province through random sampling by means of questionnaire and physical examination, and measured for height, weight, waist to hip ratio (WHR), FM, FFM and ventilatory function. The data were analyzed by means of independent-samples t test, Pearson correlation analysis and multi-factors regression analysis. Regardless of sex, an independent positive correlation was found (P<0.001) between age and FFM index (FFMI). FM index (FMI) correlated negatively with age in males (P<0.001), but positively with age in females (P<0.001). Regardless of sex, FFMI correlated positively with forced vital capacity (FVC), forced expiratory volume in one second (FEV1), peak expiratory flow (PEF), forced expiratory flow at 25% of forced vital capacity (FEF25%), FEF50%, and maximal mid-expiratory flow (MMEF) (P<0.05), while negatively with FEV1/FVC (P<0.01). FFMI was correlated positively with FEF75% in males (P<0.05), but not correlated in females. In males, FMI correlated negatively with FEV1, FEV1/FVC, PEF, FEF25%, FEF50%, FEF75% and MMEF (P<0.05), but not correlated with FVC. No correlation was found between the ventilatory function indices and FMI in females. Except FEV1/FVC and FEF75% in males, the effect of FFMI in predicting ventilatory function was higher than FMI regardless of sex. Moreover, the predicting effect of FFMI was higher in males than that in females. Growth spurt of lung function occurred in the ages of 12-15 years in males, while in the ages of 12, 13 and 18 years in females. During the period of growth spurt of lung function, regardless of sex, the effect of FFMI in predicting the lung function was higher than that of age. In conclusion, regardless of sex, FFMI correlates positively with ventilatory function, as a reflection of muscle mass. The effect of FFM in predicting ventilatory function is higher in males than that in females. FM correlates negatively with ventilatory function in males, but not in females. The rapid growth of height and FFM are possibly the main reasons for growth spurt of lung function.     

Use of bioelectrical impedance to assess body composition changes at high altitude.

This study determined the feasibility of using bioelectrical impedance analysis (BIA) to assess body composition alterations associated with body weight (BW) loss at high altitude. The BIA method was also evaluated relative to anthropometric assessments. Height, BW, BIA, skinfold (SF, 6 sites), and circumference (CIR, 5 sites) measurements were obtained from 16 males (23-35 yr) before, during, and after 16 days of residence at 3,700-4,300 m. Hydrostatic weighings (HW) were performed pre- and postaltitude. Results of 13 previously derived prediction equations using various combinations of height, BW, age, BIA, SF, or CIR measurements as independent variables to predict fat-free mass (FFM), fat mass (FM), and percent body fat (%Fat) were compared with HW. Mean BW decreased from 84.74 to 78.84 kg (P less than 0.01). As determined by HW, FFM decreased by 2.44 kg (P less than 0.01), FM by 3.46 kg (P less than 0.01), and %Fat by 3.02% (P less than 0.01). The BIA and SF methods overestimated the loss in FFM and underestimated the losses in FM and %Fat (P less than 0.01). Only the equations utilizing the CIR measurements did not differ from HW values for changes in FFM, FM, and %Fat. It was concluded that the BIA and SF methods were not acceptable for assessing body composition changes at altitude.     

Development of models to predict anabolic response to testosterone administration in healthy young men

Considerable heterogeneity exists in the anabolic response to androgen administration; however, the factors that contribute to variation in an individual's anabolic response to androgens remain unknown. We investigated whether testosterone dose and/or any combination of baseline variables, including concentrations of hormones, age, body composition, muscle function, and morphometry or polymorphisms in androgen receptor could explain the variability in anabolic response to testosterone. Fifty-four young men were treated with a long-acting gonadotropin-releasing hormone (GnRH) agonist and one of five doses (25, 50, 125, 300, or 600 mg/wk) of testosterone enanthate (TE) for 20 wk. Anabolic response was defined as a change in whole body fat-free mass (FFM) by dual-energy X-ray absorptiometry (DEXA), appendicular FFM (by DEXA), and thigh muscle volume (by magnetic resonance imaging) during TE treatment. We used univariate and multivariate analysis to identify the subset of baseline measures that best explained the variability in anabolic response to testosterone supplementation. The three-variable model of TE dose, age, and baseline prostate-specific antigen (PSA) level explained 67% of the variance in change in whole body FFM. Change in appendicular FFM was best explained (64% of the variance) by the linear combination of TE dose, baseline PSA, and leg press strength, whereas TE dose, log of the ratio of luteinizing hormone to testosterone concentration, and age explained 66% of the variation in change in thigh muscle volume. The models were further validated by using Ridge analysis and cross-validation in data subsets. Only the model using testosterone dose, age, and PSA was a consistent predictor of change in FFM in subset analyses. The length of CAG tract was only a weak predictor of change in thigh muscle volume and lean body mass. Hence, the anabolic response of healthy, young men to exogenous testosterone administration can largely be predicted by the testosterone dose.     

Estimation of stature in Turkish adults using knee height

Body height is an important clinical indicator to derive body mass index (BMI), which is a useful screening tool for both excess adiposity and malnutrition. Height measurement in the elderly may impose some difficulties and the reliability is doubtful. Stature estimation from knee height is one of the commonly used methods; nevertheless no study has been carried out so far on the Turkish population. A cross sectional anthropometric study was conducted to develop body height estimation equations by using knee height measurement for Turkish people. Measurements of height and knee height were taken according to the International Biological Programme procedures from 1422 adults (610 males, 812 females) aged 18-90 years from Ankara, the capital city of Turkey. Samples were randomly split into two sub-samples, training and validation (control group) sub-samples. Height estimation equations were developed from the knee height measurements by linear regression analysis according to age groups and sexes. Males were significantly taller and have higher knee height values than females in all age groups. Height and the knee height variables showed a gradual decrease (P 50) with aging in females and males. Evaluated knee height equations for stature estimation were tested through the validation sample and the results showed high accuracy. The study presents sex and age specific regression equations for height estimation by using the knee height measurement for Turkish adults and suggests facilitating the accurate usage of knee height.     

Serial Measurements of Body Composition in Obese Subjects During a Very-Low-Energy Diet (VLED) Comparing Bioelectrical Impedance with Hydrodensitometry

Bioelectrical impedance analysis (BIA) is a convenient, inexpensive, and noninvasive technique for measuring body composition. BIA has been strongly correlated with total body water (TBW) and also has been validated against hydrodensitometry (HD). The accuracy and clinical utility of BIA and HD during periods of substantial weight loss remain controversial. We measured body composition in moderately and severely obese patients serially using both methods during a very-low-energy diet (VLED). Mean initial weight in these patients was 116 (± 30) kg (range, 74–196 kg). Mean weight loss was 24 (± 13) kg with a decrease in fat mass (FM) by HD of 20 kg (p<0.001) and a decrease in fat-free mass (FFM) of 3.6 kg (p<0.05). Loss of FFM is best predicted by the rate (kg/wk) of weight loss (r² = 0.86, p<0.0001). FFM, as predicted from BIA equations, was highly correlated with FFM as estimated by HD during all testing sessions (r=0.92-0.98). Although highly correlated, BIA overestimated FFM relative to HD and this difference appeared to be more pronounced for taller patients with greater truncal obesity. Although the discrepancy was no greater during weight-loss treatment, the level of disagreement was considerable. Therefore, the two methods cannot be used interchangeably to monitor relative changes in body composition in patients with obesity during treatment with VLED. The discrepancy between BIA and HD may be caused by body mass distribution considerations and by perturbations in TBW which affect the hydration quotient for FFM (BIA) and/or which affect the density constants for FFM and FM (HD).