Body Composition Changes in Caucasian and African American Children and Adolescents with Obesity Using Dual-Energy X-ray Absorptiometry Measurements after a 10-Week Weight Loss Program

Objective : Changes in body composition during a weight loss program have not been described in children. We wanted to test the hypothesis that weight loss can be achieved while maintaining total body fat-free mass. Research Methods and Procedures : We determined body composition changes by using dual-energy X-ray absorptiometry measured at baseline and after the first 10 weeks of a multidisciphnary weight loss program. The program consisted of 10 weekly group sessions where the children were provided instruction in lifestyle modification, including diet and exercise. Program leaders included a pediatrician, psychologist, registered dietitian, and exercise instructor. Results : We studied 59 obese children, mean (± SD) age 12.8 ± 2.6 years, 29% boys and 71% girls, 49% Caucasian, and 51% African American. At enrollment, the children's mean height and body mass index were 157 cm and 38.9 kg/m², respectively. The children's dual-energy X-ray absorptiometry-derived mean at baseline and at 10 weeks and corresponding p values were: weight (94.6 kg vs. 92.3 kg, p<0.0001), total body fat mass (46.9 kg vs. 44.3 kg, p<0.0001), percentage total body fat (49.2% vs. 47.5%, p<0.0001), total trunk mass (43.0 kg vs. 41.5 kg,p<0.0001), total trunk fat (21.2 kg vs. 20.0 kg, p<0.0001), total body fat-free mass (47.6 kg vs. 47.9 kg, p = 0.33), total body bone mass (2.7 kg vs. 2.7 kg, p = 0.99), and total body bone mineral density (1.14 g/cm² vs. 1.15 g/cm², p = 0.0119). The children's race, gender, or Tanner stage did not affect these changes. Discussion : Decreases in total body fat mass was achieved, and total body fat-free mass was maintained among boy and girl Caucasian and African American children participating in this lifestyle modification weight loss program.     

Rate of Fat Gain Is Faster in Girls Undergoing Early Adiposity Rebound

Objective: To determine the changes in body composition (fat and lean mass) occurring in children during adiposity rebound (AR). Research Methods and Procedures: Thirty‐nine girls, 3 to 6 years of age at baseline, underwent yearly DXA scans for 2 years. An additional DXA scan was obtained 4 to 5 years after baseline. Age at AR was determined by modeling, and the velocity of change in height, weight, fat mass, and lean mass was estimated for each child using random coefficient models. Girls with an AR <5 years of age were classified as having an early AR, and those having an AR ≥5 years were classified as late AR. Results: Although body composition was similar at age 5, by age 9, girls with an early AR were significantly taller (3.5% more) and heavier (14.4%), with greater fat mass (50%) and percentage body fat (27%) than girls with a later AR. In addition, more girls were overweight according to BMI (18% vs. 6%) or percentage body fat (29% vs. 11%) at this time, despite no differences at baseline. Annual velocity of fat mass gain was over 2‐fold higher in early compared with late rebounders (17.1% vs. 6.5%, p < 0.0001), with no difference in lean mass velocity (13.1% vs. 12.5%, p = 0.116). Discussion: Differences in BMI during AR were caused specifically by alterations in body fat and not by alterations in lean mass or height. Children undergoing early AR gained fat at a faster rate than children who rebounded at a later age.     

Comparison of three bioelectrical impedance methods with DXA in overweight and obese men

Objective: To compare bioelectrical impedance analysis (BIA) of body composition using three different methods against DXA in overweight and obese men. Research Methods and Procedures: Forty‐three healthy overweight or obese men (ages 25 to 60 years; BMI, 28 to 43 kg/m²) underwent BIA assessment of body composition using the ImpediMed SFB7 (version 6; ImpediMed, Ltd., Eight Mile Plains, Queensland, Australia) in multifrequency mode (Imp‐MF) and DF50 single‐frequency mode (Imp‐SF) and the Tanita UltimateScale (Tanita Corp., Tokyo, Japan). Validity was assessed by comparison against DXA using linear regression and limits of agreement analysis. Results: All three BIA methods showed good relative agreement with DXA [Imp‐MF: fat mass (FM), r² = 0.81; fat‐free mass (FFM), r² = 0.81; percentage body fat (BF%), r² = 0.69; Imp‐SF: FM, r² = 0.65; FFM, r² = 0.76; BF%, r² = 0.40; Tanita: BF%, r² = 0.44; all p < 0.001]. Absolute agreement between DXA and Imp‐MF was poor, as indicated by a large bias and wide limits of agreement (bias, ±1.96 standard deviation; FM, ?6.6 ± 7.7 kg; FFM, 8.0 ± 7.1 kg; BF%, ?7.0 ± 6.6%). Imp‐SF and Tanita exhibited a smaller bias but wide limits of agreement (Imp‐SF: FM, ?1.1 ± 8.5 kg; FFM, 2.5 ± 7.9 kg; BF%, ?1.7 ± 7.3% Tanita: BF%, 1.2 ± 9.5%). Discussion: Compared with DXA, Imp‐MF produced large bias and wide limits of agreement, and its accuracy estimating body composition in overweight or obese men was poor. Imp‐SF and Tanita demonstrated little bias and may be useful for group comparisons, but their utility for assessment of body composition in individuals is limited.     

Assessing Body Composition among 3‐ to 8‐Year‐Old Children: Anthropometry,BIA, and DXA

Objective: To examine the inter‐relationships of body composition variables derived from simple anthropometry [BMI and skinfolds (SFs)], bioelectrical impedance analysis (BIA), and dual energy x‐ray (DXA) in young children. Research Methods and Procedures: Seventy‐five children (41 girls, 34 boys) 3 to 8 years of age were assessed for body composition by the following methods: BMI, SF thickness, BIA, and DXA. DXA served as the criterion measure. Predicted percentage body fat (%BF), fat‐free mass (FFM; kilograms), and fat mass (FM; kilograms) were derived from SF equations [Slaughter (SL)1 and SL2, Deurenberg (D) and Dezenberg] and BIA. Indices of truncal fatness were also determined from anthropometry. Results: Repeated measures ANOVA showed significant differences among the methods for %BF, FFM, and FM. All methods, except the D equation (p = 0.08), significantly underestimated measured %BF (p < 0.05). In general, correlations between the BMI and estimated %BF were moderate (r = 0.61 to 0.75). Estimated %BF from the SL2 also showed a high correlation with DXA %BF (r = 0.82). In contrast, estimated %BF derived from SFs showed a low correlation with estimated %BF derived from BIA (r = 0.38); likewise, the correlation between DXA %BF and BIA %BF was low (r = 0.30). Correlations among indicators of truncal fatness ranged from 0.43 to 0.98. Discussion: The results suggest that BIA has limited utility in estimating body composition, whereas BMI and SFs seem to be more useful in estimating body composition during the adiposity rebound. However, all methods significantly underestimated body fatness as determined by DXA, and, overall, the various methods and prediction equations are not interchangeable.     

Four‐Compartment Cellular Level Body Composition Model: Comparison of Two Approaches**

Objective: The aim of this study was to develop and compare two DXA‐based four‐compartment [body weight = body cell mass (BCM) + extracellular fluid (ECF) + extracellular solids (ECS) + fat] cellular level models. Research Methods and Procedures: Total body potassium (TBK) model: BCM from TBK by whole‐body counting—ECF_TBK = LST ? [BCM_TBK + 0.73 × osseous mineral (Mo)]. Bromide model: ECF from sodium bromide dilution—BCM_BROMIDE = LST ? (ECF_BROMIDE + 0.73 × Mo); Mo and LST measurements came from DXA. The two approaches were evaluated in 99 healthy men and 118 women. Results: BCM estimates were highly correlated (r = 0.97, p < 0.001), as were ECF estimates (r = 0.87, p < 0.001); a small statistically significant mean difference was present (mean ± SD; BCM_TBK model, 30.4 ± 8.9 kg; BCM_BROMIDE, 31.4 ± 9.3 kg; Δ = 1.0 ± 2.8 kg; p < 0.001; ECF_TBK, 18.5 ± 4.2 kg; ECF_BROMIDE, 17.5 ± 3.6 kg; Δ = 1.0 ± 2.8 kg; p < 0.001). A high correlation (r = 0.97, p < 0.001) and good agreement (38.9 ± 9.5 vs. 38.9 ± 9.5 kg; Δ = 0.0 ± 2.4 kg; p = 0.39) were present between TBW, derived as the sum of intracellular water from TBK and ECW from bromide, and measured TBW by ²H₂O dilution. Discussion: Two developed four‐compartment cellular level DXA models, one of which is appropriate for use in most clinical and research settings, provide comparable results and are applicable for BCM and ECF estimation of subject groups with hydration disturbances.     

Body Composition at 6 months of Life: Comparison Of Air Displacement Plethysmography and Dual‐Energy X‐Ray Absorptiometry

Body composition assessment during infancy is important because it is a critical period for obesity risk development, thus valid tools are needed to accurately, precisely, and quickly determine both fat and fat‐free mass. The purpose of this study was to compare body composition estimates using dual‐energy x‐ray absorptiometry (DXA) and air displacement plethysmography (ADP) at 6 months old. We assessed the agreement between whole body composition using DXA and ADP in 84 full‐term average‐for‐gestational‐age boys and girls using DXA (Lunar iDXA v11–30.062; Infant whole body analysis enCore 2007 software, GE, Fairfield, CT) and ADP (Infant Body Composition System v3.1.0, COSMED USA, Concord, CA). Although the correlations between DXA and ADP for %fat (r = 0.925), absolute fat mass (r = 0.969), and absolute fat‐free mass (r = 0.945) were all significant, body composition estimates by DXA were greater for both %fat (31.1 ± 3.6% vs. 26.7 ± 4.7%; P < 0.001) and absolute fat mass (2,284 ± 449 vs. 1,921 ± 492 g; P < 0.001), and lower for fat‐free mass (5,022 ± 532 vs. 5,188 ± 508 g; P < 0.001) vs. ADP. Inter‐method differences in %fat decreased with increasing adiposity and differences in fat‐free mass decreased with increasing infant age. Estimates of body composition determined by DXA and ADP at 6 months of age were highly correlated, but did differ significantly. Additional work is required to identify the technical basis for these rather large inter‐method differences in infant body composition.     

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).     

Total and Regional Fat and Serum Cardiovascular Disease Risk Factors in Lean and Obese Children and Adolescents

Objective: This study was conducted to evaluate the association of total and central adiposity with serum cardiovascular disease (CVD) risk factors in lean and obese Portuguese children and adolescents. Research Methods and Procedures: A total of 87 girls (13.2 ± 1.6 years old, 29.9 ± 6.4% body fat [mean ± SD]) and 72 boys (13.2 ± 1.6 years old, 20.8 ± 9.9% body fat) volunteered for the study. Whole‐body composition and fat distribution, from DXA and anthropometry, and serum lipids, lipoproteins, and apolipoproteins were evaluated. Results: The sum of three trunk skinfolds (STS) was highly correlated with total trunk fat mass measured by DXA (p < 0.001). Body mass index, DXA‐measured percentage of body fat, trunk fat mass, STS, and the waist‐to‐height ratio were generally found to be associated with triacylglycerol, the ratio of total cholesterol (TC) to high density lipoprotein‐cholesterol (HDL‐C), low density lipoprotein‐cholesterol (LDL‐C), and apolipoprotein B levels, (significant age‐adjusted r between 0.16 and 0.27, p < 0.05). Body mass index, STS, and the waist circumference were also associated with HDL‐C (p < 0.05), whereas no body composition variable significantly correlated with TC or apolipoproteins A‐I. The STS was significantly correlated with HDL‐C (p < 0.01), TC/HDL‐C (p < 0.05), and apolipoproteins A‐I (p < 0.05) independently of whole‐body fatness. Obese subjects (n = 73) had higher TC, LDL‐C, TC/HDL‐C, and apolipoprotein B than did non‐obese subjects (n = 86), and significant associations between central adiposity and some lipid variables (triacylglycerol and HDL‐C) were found in obese children and adolescents that were not present in leaner individuals. Discussion: DXA‐ and anthropometry‐based whole‐body and central fat measures are associated with serum CVD risk factors in Portuguese boys and girls. Obese children and adolescents have a poorer lipid profile than do their leaner counterparts. Trunk skinfolds, which are easy to obtain even in large samples, predict CVD risk factors to the same extent as DXA‐based variables, in some cases, independently of total fatness.     

Percentage Fat in Overweight and Obese Children: Comparison of DXA and Air Displacement Plethysmography**

Objective: To compare percentage body fat (percentage fat) estimates from DXA and air displacement plethysmography (ADP) in overweight and obese children. Research Methods and Procedures: Sixty‐nine children (49 boys and 20 girls) 14.0 ± 1.65 years of age, with a BMI of 31.3 ± 5.6 kg/m² and a percentage fat (DXA) of 42.5 ± 8.4%, participated in the study. ADP body fat content was estimated from body density (D_b) using equations devised by Siri (ADP_Siri) and Lohman (ADP_Loh). Results: ADP estimates of percentage fat were highly correlated with those of DXA in both male and female subjects (r = 0.90 to 0.93, all p < 0.001; standard error of estimate = 2.50% to 3.39%). Compared with DXA estimates, ADP_Siri and ADP_Loh produced significantly (p < 0.01) lower estimates of mean body fat content in boys (?2.85% and ?4.64%, respectively) and girls (?2.95% and ?5.15%, respectively). Agreement between ADP and DXA methods was further examined using the total error and methods of Bland and Altman. Total error ranged from 4.46% to 6.38% in both male and female subjects. The 95% limits of agreement were relatively similar for all percentage fat estimates, ranging from ±6.73% to ±7.94%. Discussion: In this study, conversion of D_b using the Siri equation led to mean percentage fat estimates that agreed better with those determined by DXA compared with the Lohman equations. However, relatively high limits of agreement using either equation resulted in percentage fat estimates that were not interchangeable with percentage fat determined by DXA.     

Obesity and Sarcopenia after Menopause Are Reversed by Sex Hormone Replacement Therapy

Objective: Menopause is linked to an increase in fat mass and a decrease in lean mass exceeding age‐related changes, possibly related to reduced output of ovarian steroids. In this study we examined the effect of combined postmenopausal hormone replacement therapy (HRT) on the total and regional distribution of fat and lean body mass. Research Methods and Procedures: Sixteen healthy postmenopausal women (age: 55 ± 3 years) were studied in a placebo‐controlled, crossover study and were randomized to 17β estradiol plus cyclic norethisterone acetate (HRT) or placebo in two 12‐week periods separated by a 3‐month washout. Total and regional body composition was measured by DXA at baseline and in the 10th treatment week in both periods. Changes were compared by a paired Student's t test. Results: The change in body weight during HRT was equal to the change during placebo (?24.6 g vs. ?164 g, p = 0.42), but relative fat mass was significantly reduced (?0.5% vs. +1.24%, p < 0.01). During HRT, compared with during placebo, lean body mass increased (+347 g vs. ?996 g, p < 0.01) and total fat mass decreased (?400 g vs. +836 g, p = 0.06). Total bone mineral content increased (+28.9 g vs. ?4.4 g, p = 0.04) and abdominal fat decreased (?185 g vs. +253 g, p = 0.04) during HRT compared with placebo. Discussion: HRT is linked to the reversal of both menopause‐related obesity and loss of lean mass, without overall change in body weight. The increase in lean body mass during HRT is likely explained by muscle anabolism, which in turn, prevents disease in the elderly.     

Precision and Accuracy of Dual‐Energy X‐ray Absorptiometry for Determining in Vivo Body Composition of Mice

Objective: To evaluate the precision and accuracy of dual‐energy X‐ray absorptiometry (DXA) for the measurement of total‐bone mineral density (TBMD), total‐body bone mineral (TBBM), fat mass (FM), and bone‐free lean tissue mass (LTM) in mice. Research Methods and Procedures: Twenty‐five male C57BL/6J mice (6 to 11 weeks old; 19 to 29 g) were anesthetized and scanned three times (with repositioning between scans) using a peripheral densitometer (Lunar PIXImus). Gravimetric and chemical extraction techniques (Soxhlet) were used as the criterion method for the determination of body composition; ash content was determined by burning at 600°C for 8 hours. Results: The mean intraindividual coefficients of variation (CV) for the repeated DXA analyses were: TBMD, 0.84%; TBBM, 1.60%; FM, 2.20%; and LTM, 0.86%. Accuracy was determined by comparing the DXA‐derived data from the first scan with the chemical carcass analysis data. DXA accurately measured bone ash content (p = 0.942), underestimated LTM (0.59 ± 0.05g, p < 0.001), and overestimated FM (2.19 ± 0.06g, p < 0.001). Thus, DXA estimated 100% of bone ash content, 97% of carcass LTM, and 209% of carcass FM. DXA‐derived values were then used to predict chemical values of FM and LTM. Chemically extracted FM was best predicted by DXA FM and DXA LTM [FM = ?0.50 + 1.09(DXA FM) ? 0.11(DXA LTM), model r² = 0.86, root mean square error (RMSE) = 0.233 g] and chemically determined LTM by DXA LTM [LTM = ?0.14 + 1.04(DXA LTM), r² = 0.99, RMSE = 0.238 g]. Discussion: These data show that the precision of DXA for measuring TBMD, TBBM, FM, and LTM in mice ranges from a low of 0.84% to a high of 2.20% (CV). DXA accurately measured bone ash content but overestimated carcass FM and underestimated LTM. However, because of the close relationship between DXA‐derived data and chemical carcass analysis for FM and LTM, prediction equations can be derived to more accurately predict body composition.     

Waist Circumference and Cardiovascular Risk Factors in Prepubertal Children

Objective: Intra‐abdominal fat has been identified as being the most clinically relevant type of fat in humans. Therefore, an assessment of body‐fat distribution could possibly identify subjects with the highest risk of adverse lipid profile and hypertension. Few data on the relationship between body‐fat distribution and cardiovascular risk factors are available in children, especially before puberty. Research Methods and Procedures: This cross‐sectional study was undertaken to explore the relationship between anthropometric variables, lipid concentrations, and blood pressure (BP) in a sample of 818 prepubertal children (ages 3 to 11 years) and to assess the clinical relevance of waist circumference in identifying prepubertal children with higher cardiovascular risk. Height, weight, triceps and subscapular skinfolds, waist circumference, and BP were measured. Plasma levels for triacylglycerol, total cholesterol, high‐density lipoprotein (HDL) cholesterol, low‐density lipoprotein cholesterol, apolipoprotein A1 (ApoA1), and apolipoprotein B (ApoB) were determined. Results: Females were fatter than males (5.8 [3.5] vs. 4.8 [3.3] kg of fat mass; p < 0.01). Males had higher HDL cholesterol and ApoA1/ApoB plasma concentrations than females (p < 0.001 and p < 0.01, respectively). Waist circumference had a higher correlation with systolic and diastolic BP (r = 0.40 and 0.29, respectively; p < 0.001) than triceps (r = 0.35 and 0.21, respectively; p < 0.001) and subscapular (r = 0.28 and 0.16, respectively; p < 0.001) skinfolds and relative body weight (0.33 and 0.23, respectively; p < 0.001). Multivariate linear model analysis showed that ApoA1/ApoB, HDL cholesterol, total cholesterol/HDL cholesterol, and systolic as well as diastolic BP were significantly associated with waist circumference and triceps and subscapular skinfolds, independently of age, gender, and body mass index. Discussion: Waist circumference as well as subscapular and triceps skinfolds may be helpful parameters in identifying prepubertal children with an adverse blood‐lipids profile and hypertension. However, waist circumference, which is easy to measure and more easily reproducible than skinfolds, may be considered in clinical practice. Children with a waist circumference greater than the 90th percentile are more likely to have multiple risk factors than children with a waist circumference that is less than or equal to the 90th percentile.     

Anthropometrics Do Not Influence Dual X-ray Absorptiometry (DXA) Measurement of Fat in Normal to Obese Adults: A Comparison with In Vivo Neutron Activation Analysis (IVNA)

Dual-energy X-ray absorptiometry (DXA) is now a commonly used method for the determination of bone mineral status and body composition in humans. The purposes of this study were to compare fat mass by in vivo neutron activation analysis (FM_IVNA) with that by DXA (FM_DXA) in an anthropometrically heterogeneous sample of healthy adult men (n=33) and women (n=36) (19=≤BMI≤39), and to determine whether differences in fat mass estimates between the two methods (ΔFM) were attributable to subject anthropometry as defined by several circumference (waist, iliac crest, thigh) and skinfold thickness (umbilical, suprailiac, abdominal) measurements. No significant differences between FM_DXA and FM_IVNA were observed in men (p=0.46) or women (p=0.09). The two methods were very highly correlated in both sexes (women r²=0.97, p<0.001, men r²=0.91, p<0.001), although the regression line for men was significantly different from the line of identity (p=0.043). These results suggest modest trends toward underestimation of FM_DXA in men when FM_IVNA<18 kg, and overestimation in men when FM_IVNA>18 kg. ΔFM (IVNA-DXA) was not significantly related to any combination of skinfold thicknesses and circumferences in either gender. Age explained 27% of the variance in ΔFM for the men (p=0.008). Furthermore, ΔFM was not significantly related to inter-method disparity in total-body bone mineral measurements in men or women (p<0.05). The present study demonstrates strong correlation in fat measurements between IVNA and DXA in men and women ranging from normal to markedly obese. Correction for subject anthropometry does not significantly improve this relationship.     

Relationships between Dietary Fat,Body Fat,and Serum Lipid Profile in Prepubertal Children

KU, CHING YI, BARBARA A. GOWER, TIM R. NAGY, MICHAEL I. GORAN. Relationships between dietary fat, body fat, and serum lipid profile in prepubertal children. Obes Res. 1998;6:400–407. Objective : The purpose of the study was to test the hypothesis that dietary fat components were associated with the serum lipid profile independent of ethnicity, body fat, and fat distribution in prepubertal children. Research Methods and Procedures : Sixty-six children (45 African American and 21 Caucasian), aged from 4 to 10 years, were recruited into the study. Dietary total fat, saturated fat, monounsaturated fat, and polyunsaturated fat were estimated by averaging two 24-hour diet recalls. Fasting serum triacylglycerol, total cholesterol, and high-density lipoprotein cholesterol were analyzed, and low-density lipoprotein cholesterol (LDL-C) was calculated by the method of Friedewald. Body composition and fat distribution were measured by dual energy X-ray absorptiometry and computed tomography. Results : Children in both ethnic groups tended to overreport their dietary intake relative to total energy expenditure by 18%. African American children consumed more energy from total fat (35.3% vs. 31.5%, p<0.05), saturated fat (13.7% vs 12.2%, p<0.05), protein (16.4% vs. 13.2%, p = 0.02), and less from carbohydrate (48% vs. 57.1%, p<0.01) than Caucasian children. There was no significant correlation between dietary fat and either serum lipids or body fat indices after adjusting for nonfat energy intake and total lean tissue mass. Total body fat (r = 0.32), subcutaneous abdominal adipose tissue (r = 0.39), and intraabdominal adipose tissue (r = 0.42) were positively related to serum triacylglycerol; these associations remained significant in a multiple linear regression model in which body fat indices were adjusted for ethnicity, total lean tissue, dietary total fat, and nonfat intake. Discussion : Our results do not support a link between dietary fat and serum lipids; instead, our data suggest that body fat may play a more important role than dietary fat in the course of cardiovascular disease development in prepubertal children.     

Serum Leptin Concentrations and Weight Gain in Postobese,Postmenopausal Women

Objective : This study was designed to determine if serum leptin concentrations (adjusted for fat mass) after weight loss on a low-calorie diet predict subsequent weight gain. Research Methods and Procedures : Body composition and serum leptin concentrations were determined on 14 moderately obese, postmenopausal, nondiabetic women with a familial predisposition to obesity. Assessments were obtained under tightly controlled metabolic ward conditions of macronutrient intake and weight maintenance both before (obese state) and after a mean weight loss of 12.0 kg to normal body weight (postobese state). Four years later, without intervention, body weight and body composition were reassessed. Results : Weight loss resulted in significant decreases in fat mass (29.7 ± 5.4 vs. 20.3 ± 4.7; kg), body mass index (27.7 ± 1.6 vs. 23.0 ± 1.5; kg/m2), percent body fat (40.7 ± 4.3 vs. 33.1 ± 5.0), and serum leptin concentrations (31.8 ± 16.0 vs. 11.5 ± 5.4; ng/mL). Serum leptin concentrations were positively correlated (p<<0.05) with fat mass in both the obese and postobese states (r = 0.67 and r = 0.56, respectively). However, residual serum leptin concentrations (adjusted for fat mass) in the obese and postobese states were not related to changes in body weight (p<= 0.61 and 0.52), fat mass (p = 0.72 and 0.42), body mass index (p = 0.59 and 0.33), or percent body fat (p = 0.84 and 0.46) over the follow-up period. Discussion : These finding do not support the hypothesis that relatively low concentrations of leptin predict weight regain after weight loss. However, because the number of subjects in this study was limited, further studies are warranted.     

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.     

Body mass, body composition and sleeping metabolic rate before, during and after endurance training

Metabolic rate, more specifically resting metabolic rate (RMR) or sleeping metabolic rate (SMR), of an adult subject is usually expressed as a function of the fat-free mass (FFM). Chronic exercise is thought to increase FFM and thus to increase RMR and SMR. We determined body mass (BM), body composition, and SMR before, during, and after an endurance training programme without interfering with energy intake. The subjects were 11 women and 12 men, aged 37 (SD 3) years and body mass index 22.3 (SD 1.5) kg · m^–2. The endurance training prepared subjects to run a half marathon competition after 44 weeks. The SMR was measured overnight in a respiration chamber. Body composition was measured by hydrostatic weighing. Measurements were performed at 0, 8, 20, 40, and 90 weeks after the start of the training. The BM had decreased from a mean value of 66.6 (SD 6.9) to 65.6 (SD 6.7) kg (P<0.01), fat mass (FM) had decreased from 17.1 (SD 3.9) to 13.5 (SD 3.6) kg (P<0.001), and FFM had increased from 49.5 (SD 7.3) to 52.2 (SD 7.6) kg (P<0.001) at 40 weeks. Mean SMR before and after 40 weeks training was 6.5 (SD 0.7) and 6.2 (SD 0.6) MJ · day^–1 (P<0.05). The decrease in SMR was related to the decrease in BM (r=0.62,P=0.001). At 90 weeks, when most subjects had not trained for nearly a year, BM and SMR were not significantly different from the initial value while FM and FFM had not changed since week 40 of training. In conclusion, it was found that an exercise induced increase in FFM did not result in an increase in SMR. There was an indication of the opposite effect, a decrease in SMR in the long term during training, possibly as a defence mechanism of the body in the maintenance of BM.     

A Weight Reduction Program Preserves Fat‐Free Mass but Not Metabolic Rate in Obese Adolescents

Objective: To determine the effects of a multidisciplinary weight reduction program on body composition and energy expenditure (EE) in severely obese adolescents. Research Methods and Procedures: Twenty‐six severely obese adolescents, 12 to 16 years old [mean BMI: 33.9 kg/m²; 41.5% fat mass (FM)] followed a 9‐month weight reduction program including moderate energy restriction and progressive endurance and resistance training. Body composition was assessed by DXA, basal metabolic rate by indirect calorimetry, and EE by whole‐body indirect calorimetry with the same activity program over 36‐hour periods before starting and 9 months after the weight reduction period. Results: Adolescents gained (least‐square mean ± SE) 2.9 ± 0.2 cm in height, lost 16.9 ± 1.3 kg body weight (BW), 15.2 ± 0.9 kg FM, and 1.8 ± 0.5 kg fat‐free mass (FFM) (p < 0.001). Basal metabolic rate, sleeping, sedentary, and daily EE were 8% to 14% lower 9 months after starting (p < 0.001) and still 6% to 12% lower after adjustment for FFM (p < 0.05). Energy cost of walking decreased by 22% (p < 0.001). The reduction in heart rate during sleep and sedentary activities (?10 to ?13 beats/min), and walking (?20 to ?25 beats/min) (p < 0.001) resulted from both the decrease in BW and physical training. Discussion: A weight reduction program combining moderate energy restriction and physical training in severely obese adolescents resulted in great BW and FM losses and improvement of cardiovascular fitness but did not prevent the decline in EE even after adjustment for FFM.     

Sex‐Specific Fat Distribution Is Not Linear Across Pubertal Groups in a Multiethnic Study

Objective: To investigate sexual dimorphism and race differences in fat distribution (android/gynoid) before and during puberty. Research Methods and Procedures: Fat distribution was measured by skinfold thickness and DXA in healthy African‐American, Asian, and white subjects (n = 920), divided into pre‐, early, and late pubertal groups. Results: Gynoid fat masses adjusted for covariates were lower in late pubertal compared with prepubertal boys, but were not consistently greater in late pubertal compared with prepubertal girls. Progression of sex‐specific fat distribution with increasing maturation was present in Asians only. Among African‐American and white subjects, early pubertal boys had greater gynoid fat mass compared with the prepubertal group, whereas early pubertal girls had less gynoid fat mass compared with the prepubertal group. Sexual dimorphism in fat distribution was present in all pubertal groups, except among whites at early puberty. Among girls, Asians had lower gynoid fat than whites and African Americans in all pubertal groups. Among boys, Asians had less gynoid fat by DXA in early puberty and late puberty. Discussion: Comparison among races demonstrated differences in sexual dimorphism and sex‐specific fat distribution with progression in pubertal group. However, in all race groups, the fat distribution of late pubertal boys was more “male” or “android” than prepubertal boys, but late pubertal girls did not differ consistently from prepubertal girls. These findings suggested that the greater sexual dimorphism of fat distribution in late puberty compared with prepuberty may be attributable to larger changes in boys with smaller changes in girls.     

Relationship of Body Composition to Body‐Fatness Estimation in Japanese University Students

Objective: To examine the relationship between self‐estimated whole body size and fatness and whole body and regional composition, and the relationship between self‐estimated whole body fatness and self‐estimated regional fatness in Japanese university students. Research Methods and Procedures: This was a cross‐sectional study using Japanese university students (110 men and 79 women). The percentage of body fat, fat mass (FM), and fat‐free mass (FFM) were measured by underwater weighing and used as body composition variables. Subcutaneous fat thicknesses were determined at seven sites by ultrasonography to estimate regional body composition, and six circumferences and four breadths to estimate regional size. Relative body size and fatness were self‐estimated using a questionnaire. Results: Only women tended to estimate themselves as being fatter than they actually were. Self‐estimated body fatness moderately correlated with the percentage of body fat (men, r = 0.41; women, r = 0.40) FM (men, r = 0.50; women, r = 0.51), and body mass index (r = 0.56 for men and 0.56 for women). After adjusting for the percentages of body fat and FM, self‐estimated fatness correlated with body mass index (r = 0.31 for men and r = 0.37 for women). Among self‐estimated regional fatness, self‐estimated abdominal fatness had the strongest correlation with self‐estimated whole body fatness in both genders. Discussion: The low correlation between estimated and actual body fatness in both genders indicates that Japanese university students, especially women, inaccurately estimate their percentage of body fat. In fact, both men and women primarily estimate their whole body fatness by body weight relative to height.