Dual-energy X-ray Absorptiometry Fat Mass Research Articles

Measuring body composition in pediatric patients with complex diagnoses: Acceptability, practicality, and validation of different techniques.

Body composition could help identify malnutrition in pediatric patients, but there is uncertainty over which techniques are most suitable and prevailing opinion that measurements are difficult to obtain in practice. This study examined the acceptability, practicality, reliability, and validity of different anthropometric and body composition measurements in patients with complex diagnoses in a tertiary pediatric hospital. A total of 152 children aged 5-18 years had weight, height, body mass index (BMI), mid-upper arm circumference (MUAC), 4-site skinfold thicknesses (SFT), bioelectrical impedance analysis (BIA), and dual-energy x-ray absorptiometry (DXA) assessed on admission and discharge. Acceptability was assessed in a continuous scale, practicality with number/percentage of successful measurements, reliability with intraclass correlation coefficients and coefficients of repeatability, and validity between "simpler" techniques and DXA with Bland-Altman analysis of agreement and Cohen kappa. Techniques were overall acceptable. Measurements were successful in >50%, with patient refusal uncommon. Coefficients of repeatability were good (0.3 cm MUAC and height, 0.2 kg weight, and 1.0 mm SFTs). All techniques significantly overestimated DXA fat mass, but BMI and triceps SFT better identified abnormal fat mass (κ = 0.46 and 0.49). BIA fat-free mass was not significantly different from DXA, with substantial agreement between techniques (κ = 0.65). Body composition by a range of techniques is acceptable, practical, and reliable in a diverse group of children with complex diagnoses. BIA seems a good alternative to DXA for assessing fat-free mass, triceps SFT, and BMI for fat mass but should be used with care as it could overestimate total fat mass in individuals.

Accuracy and precision of multiple body composition methods and associations with muscle strength in athletes of varying hydration: The Da Kine Study

BackgroundAthletes vary in hydration status due to ongoing training regimes, diet demands, and extreme exertion. With water being one of the largest body composition compartments, its variation can cause misinterpretation of body composition assessments meant to monitor strength and training progress. In this study, we asked what accessible body composition approach could best quantify body composition in athletes with a variety of hydration levels. MethodsThe Da Kine Study recruited collegiate and intramural athletes to undergo a variety of body composition assessments including air-displacement plethysmography (ADP), deuterium-oxide dilution (D2O), dual-energy X-ray absorptiometry (DXA), underwater-weighing (UWW), 3D-optical (3DO) imaging, and bioelectrical impedance (BIA). Each of these methods generated 2- or 3-compartment body composition estimates of fat mass (FM) and fat-free mass (FFM) and was compared to equivalent measures of the criterion 6-compartment model (6CM) that accounts for variance in hydration. Body composition by each method was used to predict abdominal and thigh strength, assessed by isokinetic/isometric dynamometry. ResultsIn total, 70 (35 female) athletes with a mean age of 21.8 ± 4.2 years were recruited. Percent hydration (Body Water6CM/FFM6CM) had substantial variation in both males (63- 73%) and females (58- 78%). ADP and DXA FM and FF M had moderate to substantial agreement with the 6C model (Lin’s Concordance Coefficient [CCC] = 0.90-0.95) whereas the other measures had lesser agreement (CCC < 0.90) with one exception of 3DO FFM in females (CCC = 0.91). All measures of FFM produced excellent precision with %CV < 1.0 %. However, FM measures in general had worse precision (% CV < 2.0%). Increasing quartiles (significant p<0.001 trend) of 6CM FFM resulted in increasing strength measures in males and females. Moreover, the stronger the agreement between the alternative methods to the 6CM, the more robust their correlation with strength, irrespective of hydration status. ConclusionThe criterion 6CM showed the best association to strength regardless of the hydration status of the athletes for both males and females. Simpler methods showed high precision for both FM and FFM and those with the strongest agreement to the 6CM had the highest strength associations. Summary BoxThis study compared various body composition analysis methods in 70 athletes with varying states of hydration to the criterion 6-compartment model and assessed their relationship to muscle strength. The results showed that accurate and precise estimates of body composition can be determined in athletes, and a more accurate body composition measurement produces better strength estimates. The best laboratory-based techniques were air displacement plethysmography and dual-energy x-ray absorptiometry, while the commercial methods had moderate-poor agreement. Prioritizing accurate body composition assessment ensures better strength estimates in athletes.

DXA-Derived vs Standard Anthropometric Measures for Predicting Cardiometabolic Risk in Middle-Aged Australian Men and Women

It is not clear if dual-energy X-ray absorptiometry (DXA) adiposity measures are superior to standard anthropometric measures for predicting cardiometabolic (CM) risk factors in a middle-aged general population. In the Busselton Healthy Ageing Study, we assessed a range of standard anthropometric and DXA-derived adiposity measures to predict metabolic syndrome (MetS) and CM risk factors in 4831 “baby boomers” aged 45–69 yr. Anthropometric and whole body DXA (GE Lunar Prodigy) measures were collected. Cross-sectional relationships of overall adiposity (BMI; DXA fat mass index, body fat %), central adiposity (waist circumference (WC); DXA trunk fat, android fat, abdominal visceral adipose tissue (VAT)) and ratio index (waist-to-hip ratio; DXA trunk/legs fat, android/gynoid ratio, VAT/total fat) with MetS and its components (as both continuous and binary outcomes) were evaluated using linear and logistic regression adjusting for age and lifestyle factors. Youden's Index was used to determine the optimal cut-points for predicting MetS. In linear regression analyses, central adiposity measures showed stronger associations with MetS score and CM risk factors than overall adiposity measures and fat ratio index, and DXA-VAT provided stronger associations than WC. Logistic regression models showed similar findings. For MetS diagnosis present in 35.9% of males and 24.4% of females, the highest odds ratio (95% CI) per SD change was observed for DXA-VAT (males: 5.02 [4.28, 5.88]; females: 3.91 [3.40, 4.49]), which remained significant (all p < 0.001) after further adjustment for BMI (males: 3.27 [2.65, 4.02]; females: 3.37 [2.79, 4.06]) or WC (males: 2.46 [1.95, 3.10]; females: 2.75 [2.21, 3.43]). The optimal DXA-VAT mass cut-point for predicting MetS was 1608 grams in males and 893 grams in females. DXA-VAT was superior to standard anthropometric and other DXA-derived adiposity measures for prediction of cardiometabolic risk factors, and has clinical utility for identifying middle-aged individuals at increased risk of MetS.

Measures of body composition via Dual-energy X-ray absorptiometry, ultrasound and skinfolds are not impacted by the menstrual cycle in active eumenorrheic females

Objectives(1) Compare changes in body composition estimates over the menstrual cycle in active females using Dual-energy X-ray absorptiometry, standardised brightness-mode ultrasound and skinfolds (2) Compare the predictability of Dual-energy X-ray absorptiometry fat mass estimate via standardised brightness-mode ultrasound versus skinfolds measurements. DesignThirty active females (27 ± 5 y) with regularly occurring menstrual cycles participated in a cross sectional study. MethodsParticipants completed four assessment sessions scheduled according to each individual's menstrual cycle. These sessions took place during their (1) early follicular, (2) mid-to-late follicular, (3) mid-luteal and (4) second early follicular phases. Body composition estimates were acquired using Dual-energy X-ray absorptiometry, subcutaneous adipose tissue thickness was measured at eight sites using standardised brightness-mode ultrasound and skinfolds. ResultsThe sum of eight subcutaneous adipose tissue thickness measured using standardised brightness-mode ultrasound and skinfolds were not different between the cycle phases (p > 0.05). Body mass and Dual-energy X-ray absorptiometry total mass estimate as well as Dual-energy X-ray absorptiometry estimates of total and regional lean and fat mass were also not different between cycle phases (p > 0.05) and any changes were within the 95% confidence intervals of their respective least significant change values. ConclusionsThere were no true and meaningful changes in the sum of eight subcutaneous adipose tissue thickness measured via standardised brightness-mode ultrasound and skinfolds or Dual-energy X-ray absorptiometry total and regional tissue mass estimates across the menstrual cycle in active eumenorrheic females. Body composition may thus be assessed via these methods in this population at any cycle phase with standardised participant presentation.

Cross-sectional and longitudinal associations between subcutaneous adipose tissue thickness and dual-energy X-ray absorptiometry fat mass.

The present study examined cross-sectional and longitudinal relationships between total and segmental subcutaneous tissue thicknesses from ultrasonography (US) and total and segmental fat mass (FM) estimates from dual-energy X-ray absorptiometry (DXA). Traditional US FM estimates were also examined. Twenty resistance-trained males (mean±SD; age: 22.0±2.6years; body mass: 74.8±11.5kg; DXA fat: 17.5±4.5%) completed a 6-week supervised resistance training programme while consuming a hypercaloric diet. Pre- and post-intervention body composition was assessed by DXA and B-mode US. Data were analysed using Pearson's correlation (r), Lin's correlation coefficient (CCC), paired t-tests, Wilcoxon signed-rank tests and Bland-Altman analysis, as appropriate. Cross-sectionally, correlations were observed between total DXA FM and total subcutaneous tissue thickness (r=0.88). Longitudinally, a correlation was observed between total DXA FM changes and total subcutaneous tissue changes (r=0.49, CCC=0.38). Correlations of similar magnitudes were observed for the upper body and trunk estimates, but DXA FM changes were unrelated to subcutaneous tissue changes for the lower body and arms. Cross-sectionally, US 2-compartment FM and DXA FM were correlated (r=0.91, CCC=0.83). Longitudinally, a weaker correlation was observed (r=0.47, CCC=0.33). In summary, longitudinal associations between US and DXA are weaker than cross-sectional relationships; additionally, correlations between US subcutaneous tissue and whole-body DXA FM appear to be driven by the trunk region rather than appendages. Reporting raw skinfold thicknesses rather than FM estimates alone may improve the utility of techniques based on subcutaneous tissue thickness, such as US and skinfolds.

Acute feeding has minimal effect on the validity of body composition and metabolic measures: dual-energy X-ray absorptiometry and a multi-compartment model.

Understanding the effects of acute feeding on body composition and metabolic measures is essential to the translational component and practical application of measurement and clinical use. To investigate the influence of acute feeding on the validity of dual-energy X-ray absorptiometry (DXA), a four-compartment model (4C) and indirect calorimetry metabolic outcomes, thirty-nine healthy young adults (n 19 females; age: 21·8 (sd 3·1) years, weight; 71·5 (sd 10·0) kg) participated in a randomised cross-over study. Subjects were provided one of four randomised meals on separate occasions (high carbohydrate, high protein, ad libitum or fasted baseline) prior to body composition and metabolic assessments. Regardless of macronutrient content, acute feeding increased DXA percent body fat (%fat) for the total sample and females (average constant error (CE):-0·30 %; total error (TE): 2·34 %), although not significant (P = 0·062); the error in males was minimal (CE: 0·11 %; TE: 0·86 %). DXA fat mass (CE: 0·26 kg; TE: 0·75 kg) and lean mass (LM) (CE: 0·83 kg; TE: 1·23 kg) were not altered beyond measurement error for the total sample. 4C %fat was significantly impacted from all acute feedings (avg CE: 0·46 %; TE: 3·7 %). 4C fat mass (CE: 0·71 kg; TE: 3·38 kg) and fat-free mass (CE: 0·55 kg; TE: 3·05 kg) exceeded measurement error for the total sample. RMR was increased for each feeding condition (TE: 1666·9 kJ/d; 398 kcal/d). Standard pre-testing fasting guidelines may be important when evaluating DXA and 4C %fat, whereas additional DXA variables (fat mass and LM) may not be significantly impacted by an acute meal. Measuring body composition via DXA under less stringent pre-testing guidelines may be valid and increase feasibility of testing in clinical settings.

The acute effect of the menstrual cycle and oral contraceptive cycle on measures of body composition.

This study aimed to investigate the effect of fluctuating female hormones during the menstrual cycle (MC) and oral contraceptive (OC) cycle on different measures of body composition. Twenty-two women with a natural MC and thirty women currently taking combined monophasic OC were assessed over three phases of the menstrual or oral contraceptive cycle. Body weight, skinfolds, bioelectric impedance analysis (BIA), ultrasound, dual-energy X-ray absorptiometry (DXA), and peripheral quantitative computed tomography (pQCT) measurements were performed to assess body composition. Urine specific gravity (USG) was measured as an indication of hydration, and serum oestradiol and progesterone were measured to confirm cycle phases. Five participants with a natural MC were excluded based on the hormone analysis. For the remaining participants, no significant changes over the MC and OC cycle were found for body weight, USG, skinfolds, BIA, ultrasound and pQCT measures. However, DXA body fat percentage and fat mass were lower in the late follicular phase compared to the mid-luteal phase of the MC, while for the OC cycle, DXA body fat percentage was higher and lean mass lower in the early hormone phase compared with the late hormone phase. Our findings suggest that assessment of body fat percentage through BIA and skinfolds may be performed without considering the MC or OC cycle. Body adiposity assessment via DXA, however, may be affected by female hormone fluctuations and therefore, it may be advisable to perform repeat testing using DXA during the same phase of the MC or OC cycle.

Body Composition by CT vs. DXA: Long-Term Prediction of Mortality in the Health Health ABC Cohort

Background: Early work in the Health ABC cohort found that strength, but not muscle size predicted mortality. Recent literature suggests that body composition by computerized tomography (CT) and magnetic resonance imaging (MRI) predicts adverse health outcomes in diverse populations, but has not been directly compared to dual-energy X-ray absorptiometry (DXA) for predicting mortality. Objective: With long term follow-up, we reexamined body composition and mortality in Health ABC, comparing DXA and CT measures of muscle and fat. Methods: The Health ABC study assessed body composition in 2911 older adults (age 73.6±2.9 years) in 1996-97. Mid-thigh CTs were read for muscle area, inter-muscular, subcutaneous-fat areas and muscle density (HU). DXAs were read for whole body fat mass and appendicular lean mass (ALM). Mortality was assessed every 6-months through 2014 (maximum 17.4 years). Cox proportional hazards models, adjusting for age, sex, race, height, weight, physical activity, smoking and comorbidities were used to assess mortality risk. Results: Strong correlations were observed between mid-thigh muscle and subcutaneous fat areas by CT and leg lean and fat mass by DXA (P<0.05). Lower mortality rates, per SD, were associated with higher CT muscle area (HR-men=0.76 [95%CI: 0.68-0.86]; HR-women=0.84 [0.75-0.94]), muscle density (HR-men=0.86 [0.79-0.93]; HR-women=0.89 [0.81-0.97]) and higher subcutaneous-fat (HR-men=0.90 [0.81-0.99]; HR-women=0.87 [0.77-0.98]), adjusting for covariates. Similarly for DXA, greater ALM (HR-men=0.56 [0.44-0.71]; HR-women=0.77 [0.59-1.01]) and higher total fat mass (HR-men=0.53 [0.40-0.72]; HR-women=0.58 [0.37-0.90]) were associated with lower risk of death. Conclusion: With long term follow-up, both CT and DXA assessments of body composition predicted all-cause mortality risk.

Development Of A Dxa-derived Body Volume Equation In Hispanic Adults For Administering In 4-compartment Models

PURPOSE: The purpose of the current study was two-fold: 1) to develop a new dual energy X-ray absorptiometry (DXA)-derived body volume (BV) equation with the GE-Lunar Prodigy while utilizing underwater weighing (UWW) as a criterion and 2) cross-validate 4-compartment(4C) models when utilizing the new DXA-derived BV equation (4C-DXANICKERSON), Wilson DXA-derived BV equation (4C-DXAWILSON), and air displacement plethysmography (ADP)-derived BV (4C-ADP) in Hispanic adults. METHODS: 191 Hispanic adults (18-45yrs) participated in the current study. The development sample consisted of 60 females and 60 males whereas the cross-validation sample comprised of 41 females and 30 males. Criterion body fat percentage (BF%) and fat-free mass (FFM) were determined using a 4C model with UWW as a criterion for BV (4C-UWW). The new DXA-derived BV equation (Nickerson) was developed by linearly regressing UWW-derived BV with DXA fat mass (FM), lean mass (LM), and bone mineral content (BMC). 4C-DXANICKERSON, 4C-DXAWILSON, and 4C-ADP were compared against 4C-UWW in the cross-validation sample. RESULTS: The new DXA-derived BV equation (L) was generated in the development sample as follows: (FM/0.91) + (LM/1.06) + (BMC/16.95) + 0.268. 4C-DXANICKERSON, 4C-DXAWILSON, and 4C-ADP all produced similar mean values (BF%=21.04±5.99, 22.23±6.93, and 20.62±6.26%, respectively) when compared to 4C-UWW (21.29±6.14%) in Hispanic males (all p>0.05). 4C-DXANICKERSON also yielded similar BF% and FFM values as 4C-UWW when evaluating the constant error (CE) in Hispanic females (CE=-0.79% and 0.38kg; p=0.060 and 0.174, respectively). However, 4C-DXAWILSON produced significantly different BF% and FFM values (CE=3.22% and -2.20kg, respectively; both p<0.001). Additionally, 4C-DXAWILSON yielded significant proportional bias when estimating BF% (coefficient=0.226; p<0.001) whereas 4C-ADP produced significant proportional bias for BF% and FFM (coefficient=0.188 and -0.084; both p<0.05) when evaluated in Hispanic females. CONCLUSIONS: Current study findings demonstrate that 4C-DXANICKERSON is a valid measure of BV in Hispanics and is recommended for use in clinics where DXA is the main body composition assessment technique.

Explaining Segmental Lean Soft Tissue Discrepancies Between Bioelectrical Impedance Analysis And Dual-Energy X-Ray Absorptiometry

Interest in evaluating the composition of specific anatomical regions has become commonplace in a variety of settings. Appendicular lean soft tissue (ALST) estimates are considered in the diagnosis of sarcopenia. While dual-energy x-ray absorptiometry (DXA) is viewed as a reference method for regional assessments, its availability is limited. Thus, explaining discrepancies in regional body composition estimates between DXA and the more accessible bioelectrical impedance analysis (BIA) is of utmost importance. PURPOSE: To assess the anthropometric and physiological predictors of variations between BIA and DXA segmental lean soft tissue (LST) estimates. METHODS: During a single visit, 179 participants (103 females, 76 males; Mean ± SD: 33.6 ± 15.3 years; 73.4 ± 16.2 kg; 171.2 ± 9.2 cm; 28.2 ± 8.9% DXA body fat %) underwent body composition assessments via DXA and 8-point single-frequency BIA. Potential predictors of discrepancies between DXA and BIA LST estimates were obtained from these methods and additional laboratory techniques. Specifically, air displacement plethysmography, 3-dimensional optical scanning, and bioimpedance spectroscopy were used to estimate body volume, anthropometrics, and hydration variables, respectively. Significant predictors (p ≤ 0.05) of the mean difference between DXA and BIA estimates of trunk LST (TLST) and ALST were established using ordinary least squares regression. Standardized model coefficients, p-values for coefficients, and R2 values were generated. RESULTS: For both TLST and ALST, extracellular fluid percentage, LST hydration, height, total LST mass, the male sex, and racial identification as Black significantly predicted discrepancies between DXA and BIA. Additional predictors for TLST discrepancies were DXA total fat mass (FM) to LST ratio and DXA TLST, while additional predictors of ALST discrepancies included DXA ALST, DXA FM to LST ratio of the legs, DXA appendicular FM, and DXA-derived volume of the arms and legs. Regression models including these significant predictor variables produced R2 values of 0.92 and 0.95 for TLST and ALST, respectively. CONCLUSIONS: Hydration variables, the quantity of LST in the region of interest, and height were the most influential predictor variables for discrepancies between DXA and BIA segmental LST estimates.

Comparison of Body Mass Index, Skinfold Thickness, and Bioelectrical Impedance Analysis With Dual-Energy X-Ray Absorptiometry in Hemodialysis Patients.

Malnutrition is a consistent finding in hemodialysis (HD) patients and is associated with high mortality. The aim was to compare nutrition status indicators using dual-energy x-ray absorptiometry (DXA) as reference in HD patients. Observational cross-sectional study with 42 patients, 55.8 years (±14.6) old, 60% male, HD 2-3 times per week for ≥3 months. HD ranged from 3 months to 28 years (median, 17.3; interquartile range, 8.73-39.0). We used body mass index (BMI) and fat mass (FM) by skinfold thickness (SFT), bioelectrical impedance analysis (BIA), and DXA. Statistical analyses used Bland-Altman plots, Lin's concordance correlation coefficient, the paired t-test, and Pearson or Spearman correlation. P < .05 was significant. SFT and DXA presented the lowest prevalence of malnutrition (2.4%) and BMI the highest (28.6%). BMI, BIA FM, and SFT FM presented strong positive correlations with DXA FM (r = 0.915; r = 0.976; r = 0.910, P < .001, respectively). BIA FM and fat-free mass (FFM) demonstrated substantial agreement with DXA values (ρ = 0.974 and 0.960, P < .001). Thus, the measurement procedures used, SFT and BIA, underestimated %FM (-4.65% and -2.13%) and overestimated FFM (3.12 kg and 1.0 kg) according to DXA. No differences were found between mean values of BIA FM and DXA (P = .178). Compared with DXA, BIA was the most appropriate nutrition indicator for measuring body composition.

Association of Daily Rest-Activity Patterns With Adiposity and Cardiometabolic Risk Measures in Teens

PurposeEmerging data indicate that the timing and rhythms of energetic behaviors may influence metabolism and obesity risk. Our aim was to derive diurnal rest-activity patterns from actigraphy in adolescents and analyze associations with adiposity measures and cardiometabolic risk factors. MethodsAdolescents in the Project Viva cohort wore a wrist actigraph over 7 days. We derived markers of daily rest-activity patterns from actigraphy using nonparametric models, generating measurements of relative amplitude (RA). RA reflects the normalized difference in activity measured during the most active 10-hour period and the least active 5-hour period, averaged over multiple 24-hour periods. Using multivariable-adjusted linear regression models, we estimated associations of RA and its components with markers of adiposity (body mass index, waist circumference, skinfolds, dual-energy X-ray absorptiometry fat mass) and cardiometabolic health (cardiometabolic risk score, derived as the mean of five sex-specific internal z-scores for waist circumference, systolic blood pressure, high-density lipoprotein cholesterol scaled inversely, and log-transformed triglycerides and homeostatic model assessment of insulin resistance). ResultsA total of 778 adolescents provided at least 5 days of valid actigraphy data. The average age was 13.2 (±.9) years, 52% were female, and the average RA was .9 (±.1). A higher RA reflecting higher activity during wakefulness and lower activity during the night was associated with more favorable indices of adiposity (e.g., −.35 kg/m2 lower body mass index per each .04 units increment of RA; 95% confidence interval: −.60 to −.09). ConclusionsIn this large sample of adolescents, a higher RA emerged as a novel biomarker, associated with more favorable cardiometabolic profiles.

Assessing the accuracy of measurements obtained by dual-energy X-ray absorptiometry on pig carcasses and primal cuts

Accuracy, trueness, and precision of dual-energy X-ray absorptiometry (DXA) assessment of pig carcasses and primal cuts dissected tissues were evaluated using available region of interests (ROI) and Total Body and Small Animal software modes. Fat mass, lean mass, and bone mineral content (BMC) DXA values were compared to dissected tissue weights (fat, muscle, and bones). Used ROI influenced (P < 0.05) DXA measurements of BMC, fat mass, and lean mass. Configuration modes influenced (P < 0.05) DXA fat mass in shoulders and bellies, whereas BMC estimates differed (P < 0.05) among configuration modes. Equations predicting dissected composition on the basis of DXA measurements showed high coefficients of determination, particularly for fat and lean masses. DXA is able to accurately evaluate the composition of pig carcasses and primal cuts. From a methodological viewpoint, and considering the variations observed in this study, the method for image acquisition and analysis should be chosen on the basis of the item to be evaluated.

Longitudinal Changes in Body Composition Assessed Using DXA and Surface Anthropometry Show Good Agreement in Elite Rugby Union Athletes.

Rugby union athletes have divergent body composition based on the demands of their on-field playing position and ethnicity. With an established association between physique traits and positional requirements, body composition assessment is routinely undertaken. Surface anthropometry and dual-energy X-ray absorptiometry (DXA) are the most common assessment techniques used, often undertaken synchronously. This study aims to investigate the association between DXA and surface anthropometry when assessing longitudinal changes in fat-free mass (FFM) and fat mass (FM) in rugby union athletes. Thirty-nine elite male rugby union athletes (age: 25.7 ± 3.1years, stature: 187.6 ± 7.7cm, and mass: 104.1 ± 12.2kg) underwent assessment via DXA and surface anthropometry multiple times over three consecutive international seasons. Changes in the lean mass index, an empirical measure to assess proportional variation in FFM, showed large agreement with changes in DXA FFM (r = .54, standard error of the estimate = 1.5%, p < .001); the strength of association was stronger among forwards (r = .63) compared with backs (r = .38). Changes in the sum of seven skinfolds showed very large agreement with changes in DXA FM (r = .73, standard error of the estimate = 5.8%, p < .001), with meaningful differences observed regardless of ethnicity (Whites: r = .75 and Polynesians: r = .62). The lean mass index and sum of seven skinfolds were able to predict the direction of change in FFM and FM 86% and 91% of the time, respectively, when DXA change was >1kg. Surface anthropometry measures provide a robust indication of the direction of change in FFM and FM, although caution may need to be applied when interpreting magnitude of change, particularly with FM.

Effects of Graded Whey Supplementation During Extreme-Volume Resistance Training.

We examined hypertrophic outcomes of weekly graded whey protein dosing (GWP) vs. whey protein (WP) or maltodextrin (MALTO) dosed once daily during 6 weeks of high-volume resistance training (RT). College-aged resistance-trained males (training age = 5 ± 3 years; mean ± SD) performed 6 weeks of RT wherein frequency was 3 d/week and each session involved 2 upper- and 2 lower-body exercises (10 repetitions/set). Volume increased from 10 sets/exercise (week 1) to 32 sets/exercise (week 6), which is the highest volume investigated in this timeframe. Participants were assigned to WP (25 g/d; n = 10), MALTO (30 g/d; n = 10), or GWP (25–150 g/d from weeks 1–6; n = 11), and supplementation occurred throughout training. Dual-energy x-ray absorptiometry (DXA), vastus lateralis (VL), and biceps brachii ultrasounds for muscle thicknesses, and bioelectrical impedance spectroscopy (BIS) were performed prior to training (PRE) and after weeks 3 (MID) and 6 (POST). VL biopsies were also collected for immunohistochemical staining. The GWP group experienced the greatest PRE to POST reduction in DXA fat mass (FM) (−1.00 kg, p < 0.05), and a robust increase in DXA fat- and bone-free mass [termed lean body mass (LBM) throughout] (+2.93 kg, p < 0.05). However, the MALTO group also experienced a PRE to POST increase in DXA LBM (+2.35 kg, p < 0.05), and the GWP and MALTO groups experienced similar PRE to POST increases in type II muscle fiber cross-sectional area (~+300 μm2). When examining the effects of training on LBM increases (ΔLBM) in all participants combined, PRE to MID (+1.34 kg, p < 0.001) and MID to POST (+0.85 kg, p < 0.001) increases were observed. However, when adjusting ΔLBM for extracellular water (ECW) changes, intending to remove the confounder of edema, a significant increase was observed from PRE to MID (+1.18 kg, p < 0.001) but not MID to POST (+0.25 kg; p = 0.131). Based upon DXA data, GWP supplementation may be a viable strategy to improve body composition during high-volume RT. However, large LBM increases observed in the MALTO group preclude us from suggesting that GWP supplementation is clearly superior in facilitating skeletal muscle hypertrophy. With regard to the implemented RT program, ECW-corrected ΔLBM gains were largely dampened, but still positive, in resistance-trained participants when RT exceeded ~20 sets/exercise/wk.

Anthropometric Indices Based on Waist Circumference as Measures of Adiposity in Children.

The aim of this study was to compare the accuracy of body fat patterns and single measures in assessing body fat and to clarify the use of indices based on waist circumference as measures of adiposity in children. This study included 2,531 7-year-old children from the Generation XXI birth cohort (Porto, Portugal). Anthropometrics were obtained by trained personnel and whole-body dual-energy x-ray absorptiometry (DXA) scans were performed. Principal component analysis identified two body fat patterns. Pattern 1 (BMI, fat mass index from tetra-polar bioelectric impedance, and waist-to-height ratio) showed strong correlations with DXA fat mass index (r = 0.85; P < 0.001), and pattern 2 (waist-to-hip, waist-to-thigh, and waist-to-weight ratios) showed moderate correlations with DXA central fat (r = 0.35; P < 0.001). Compared with single measures, body fat patterns showed similar correlations with DXA-derived measures. Compared with single anthropometric indices, body fat patterns seem to add little value for estimating body fat in children. Waist-to-height ratio seems to be a proxy for total fat, while waist-to-hip, waist-to-thigh, and waist-to-weight ratios seem to be proxies for central fat. Further studies should address the predictive ability of waist-to-weight ratio to identify children at risk of developing cardiometabolic disease, as this was the first time describing its potential usefulness.

Stress and psychological constructs related to eating behavior are associated with anthropometry and body composition in young adults

BackgroundThe transition to college is associated with weight gain, but the relation between eating behavior indicators and anthropometric outcomes during this period remains unclear. ObjectiveWe aimed to evaluate sex differences in stress, emotional eating, tendency to overeat, and restrained eating behavior, and determine whether the psycho-behavioral constructs assessed immediately prior to starting college are associated with anthropometry and adiposity at the start of college, and with first-semester weight gain. MethodsA prospective study administered the Three Factor Eating Questionnaire (TFEQ), Satter Eating Competence Inventory, and Perceived Stress Scale (PSS) to 264 participants one month before college. Body composition was assessed via dual energy X-ray absorptiometry (DXA) at the start of college, and anthropometry (weight, height, waist circumference [WC]) was collected at the beginning and end of the first semester. Ordinary least squares regression tested the cross-sectional association of baseline psychological and behavioral scales with baseline DXA and anthropometry, and the longitudinal association with change in anthropometry. ResultsAmong 264 participants, 91% (241) had baseline data, and 66% (173) completed follow-up. In sex-adjusted linear regression models, baseline TFEQ disinhibited and emotional (DE; EE) eating sub-scales were positively associated with baseline weight (P = 0.003; DE, P = 0.014; EE), body mass index (BMI, P = 0.002; DE, P = 0.001; EE), WC (P = 0.004; DE, P = 0.006; EE) and DXA fat mass index (P = 0.023; DE, P = 0.014; EE). Baseline PSS was positively associated with subsequent changes in weight and WC among males only (Pinteraction = 0.0268 and 0.0017 for weight and WC, respectively). ConclusionCollege freshmen with questionnaire scores indicating a greater tendency to overeat in response to external cues and emotions tended to have greater weight, BMI, and WC at the start of college. Males with higher perceived stress at college entrance subsequently gained significantly more weight in the first semester, but no such relation was evident in females.

Validity and reliability of a 4-compartment body composition model using dual energy x-ray absorptiometry-derived body volume

Body volume (BV), one component of a four-compartment (4C) body composition model, is commonly assessed using air displacement plethysmography (BodPod). However, dual-energy x-ray absorptiometry (DEXA) has been proposed as an alternative method for calculating BV. This investigation evaluated the validity and reliability of DEXA-derived BV measurement and a DEXA-derived 4C model (DEXA-4C) for percent body fat (%BF), fat mass (FM), and lean mass (LM). A total sample of 127 men and women (Mean±SD; Age: 35.8±9.4 years; Body Mass: 98.1±20.9kg; Height: 176.3±9.2cm) completed a traditional 4C body composition reference assessment. A DEXA-4C model was created by linearly regressing BodPod BV with DEXA FM, LM, and bone mineral content as independent factors. The DEXA-4C model was validated in a random sub-sample of 27 subjects. Reliability was evaluated in a sample of 40 subjects that underwent a second session of identical testing. When BV derived from DEXA was applied to a 4C model, there were no significant differences in %BF (p=0.404), FM (p=0.295), or LM (p=0.295) when compared to the traditional 4C model. The approach was also reliable; BV was not different between trials (p=0.170). For BV, %BF, FM, and LM relative consistency values ranged from 0.995 to 0.998. Standard error of measurement for BV was 0.62L, ranging from 0.831 to 0.960kg. There were no significant differences between visits for %BF (p=0.075), FM (p=0.275), or LM (p=0.542). The DEXA-4C model appears to be a valid and reliable method of estimating %BF, FM, and LM. The prediction of BV from DEXA simplifies the acquisition of 4C body composition by eliminating the need for an additional BV assessment.

Validity of a Multi-compartment Body Composition Model Using Body Volume Derived from Dual-Energy X-ray Absorptiometry

Measuring body composition may serve as an important clinical tool in assessing health risks. A four-compartment (4C) model utilizing body mass, body volume (BV), total body water (TBW), and bone mineral content (BMC) is a widely accepted criterion method for predicting body composition. BV is commonly assessed using air displacement plethysmography (BodPod). However, dual-energy x-ray absorptiometry (DXA) has been proposed as an alternative method for BV, reducing time and equipment required for a multi-compartment model. PURPOSE: To assess the validity of a DXA-derived body volume 4C model for calculation of percent body fat (%BF), fat mass (FM), and lean mass (LM). METHODS: A total sample of 126 men and women (Mean ± SD; Age: 35.8 ± 9.4 years; Body Mass: 97.31 ± 20.4 kg; Height: 176.04 ± 9.2 cm) completed a 4C body composition reference assessment, including BV from Bodpod, TBW from bioelectrical impedance spectroscopy, and BMC from DXA. Using a sample of 99 subjects, a DXA-derived body volume 4C model (4C DXA) was created by linearly regressing BodPod BV with DXA FM, LM, and BMC as independent factors. The 4C DXA model was validated in a sub-sample of 27 subjects. RESULTS: The density coefficients of FM, LM, and BMC determined to predict BV were 0.84 (p CONCLUSIONS: The 4C DXA model using the determined coefficients was demonstrated to be a valid method of estimating FM, LM, and %BF when compared to a traditional 4C model. The alternative method of predicting BV using DXA may eliminate the need for a BodPod when using a 4C model to assess body composition.

Smart Multi-Frequency Bioelectrical Impedance Spectrometer for BIA and BIVA Applications.

Bioelectrical impedance analysis (BIA) is a noninvasive and commonly used method for the assessment of body composition including body water. We designed a small, portable and wireless multi-frequency impedance spectrometer based on the 12 bit impedance network analyzer AD5933 and a precision wide-band constant current source for tetrapolar whole body impedance measurements. The impedance spectrometer communicates via Bluetooth with mobile devices (smart phone or tablet computer) that provide user interface for patient management and data visualization. The export of patient measurement results into a clinical research database facilitates the aggregation of bioelectrical impedance analysis and biolectrical impedance vector analysis (BIVA) data across multiple subjects and/or studies. The performance of the spectrometer was evaluated using a passive tissue equivalent circuit model as well as a comparison of body composition changes assessed with bioelectrical impedance and dual-energy X-ray absorptiometry (DXA) in healthy volunteers. Our results show an absolute error of 1% for resistance and 5% for reactance measurements in the frequency range of 3 kHz to 150 kHz. A linear regression of BIA and DXA fat mass estimations showed a strong correlation (r(2)=0.985) between measures with a maximum absolute error of 6.5%. The simplicity of BIA measurements, a cost effective design and the simple visual representation of impedance data enables patients to compare and determine body composition during the time course of a specific treatment plan in a clinical or home environment.