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PurposeTotal and regional body composition are important indicators of health and mortality risk, but their measurement is usually restricted to controlled environments in clinical settings with expensive and specialized equipment. A method that approaches the accuracy of the current gold standard method, dual-energy x-ray absorptiometry (DXA), while only requiring input from widely available consumer grade equipment, would enable the measurement of these important biometrics in the wild, enabling data collection at a scale that would have previously been prohibitive in time and expense. We describe an algorithm for predicting three-dimensional (3D) body shape and composition from a single frontal 2-dimensional image acquired with a digital consumer camera.MethodsDuplicate 3D optical scans, two-dimensional (2D) optical images, and DXA whole-body scans were available for 183 men and 233 women from the Shape Up! Adults Study. A principal component analysis vector basis was fit to 3D point clouds of a training subset of 152 men and 194 women. The relationship between this vector space and DXA-derived body composition was modeled with linear regression. The principal component 3D shape was then fitted to match a silhouette extracted from a 2D photograph of a novel body. Body composition was predicted from the resulting 3D shape match using the linear mapping between the principal component parameters and the DXA metrics. Accuracy of body composition estimates from the silhouette method was evaluated against a simple model using height and weight as a baseline, and against DXA measurements as ground truth. Test-retest precision of the silhouette method was evaluated using the duplicate 2D optical images and compared against precision of the duplicate DXA scans. Paired t-tests were performed to detect significant differences between the sets.ResultsResults were reported on a held-out set. Body composition prediction achieved R2 s of 0.81 and 0.74 for percent fat prediction of males and females, respectively, on a held-out test set consisting of 31 males and 39 females. Precision estimates for fat mass were 2.31% and 2.06% for males and females, respectively, compared to 1.26% and 0.68% for DXA scans. The t-tests revealed no statistically significant differences between the silhouette method measurements and DXA measurements, or between retests.ConclusionTotal and regional body composition measures can be estimated from a single frontal photograph of a human body. Body composition prediction using consumer level photography can enable early screening and monitoring of possible physiological indicators of metabolic disease in regions where medical imagery or clinical assessment is inaccessible.

Quantifying skeletal muscle size is necessary to identify those at risk for conditions that increase frailty, morbidity, and mortality, as well as decrease quality of life. Although muscle strength, muscle quality, and physical performance have been suggested as important assessments in the screening, prevention, and management of sarcopenic and cachexic individuals, skeletal muscle size is still a critical objective marker. Several techniques exist for estimating skeletal muscle size; however, each technique presents with unique characteristics regarding simplicity/complexity, cost, radiation dose, accessibility, and portability that are important factors for assessors to consider before applying these modalities in practice. This narrative review presents a discussion centred on the theory and applications of current non‐invasive techniques for estimating skeletal muscle size in diverse populations. Common instruments for skeletal muscle assessment include imaging techniques such as computed tomography, magnetic resonance imaging, peripheral quantitative computed tomography, dual‐energy X‐ray absorptiometry, and Brightness‐mode ultrasound, and non‐imaging techniques like bioelectrical impedance analysis and anthropometry. Skeletal muscle size can be acquired from these methods using whole‐body and/or regional assessments, as well as prediction equations. Notable concerns when conducting assessments include the absence of standardised image acquisition/processing protocols and the variation in cut‐off thresholds used to define low skeletal muscle size by clinicians and researchers, which could affect the accuracy and prevalence of diagnoses. Given the importance of evaluating skeletal muscle size, it is imperative practitioners are informed of each technique and their respective strengths and weaknesses. [ABSTRACT FROM AUTHOR]

Objective: The objective of the study was to test whether there are sustained effects of the Look AHEAD intensive lifestyle intervention (ILI), versus diabetes support and education (DSE), on weight and body composition 12 to 16 years after randomization. Methods: Participants were a subset of enrollees in the Look AHEAD dual‐energy x‐ray absorptiometry substudy who completed the final visit, composed of men (DSE = 99; ILI = 94) and women (DSE = 134; ILI = 135) with type 2 diabetes and mean (SD) age 57.2 (6.4) years and BMI 34.9 (5.1) kg/m2 at randomization. Dual‐energy x‐ray absorptiometry measured total and regional fat and lean masses at randomization, at Years 1, 4, and 8, and at the final visit. Linear mixed‐effects regressions were applied with adjustment for group, clinic, sex, age, race/ethnicity, and baseline body composition. Results: Weight and most body compartments were reduced by 2% to 8% (and BMI 4%) in ILI versus DSE in men but not women. ILI‐induced loss of lean tissue did not show a lower percent lean mass versus DSE at 16 years after randomization. Conclusion: ILI‐related changes in weight, fat, and lean mass were detectable 12 to 16 years after randomization in men but, for unknown reasons, not in women. There was no evidence that the intervention led to a disproportionate loss of lean mass by the end of the study. [ABSTRACT FROM AUTHOR]

Digital anthropometry by three-dimensional optical imaging systems and smartphones has recently been shown to provide non-invasive, precise, and accurate anthropometric and body composition measurements. To our knowledge, no previous study performed smartphone-based digital anthropometric assessments in young athletes. The aim of this study was to investigate the reproducibly and validity of smartphone-based estimation of anthropometric and body composition parameters in youth soccer players. A convenience sample of 124 male players and 69 female players (median ages of 16.2 and 15.5 years, respectively) was recruited. Measurements of body weight and height, one whole-body Dual-Energy X-ray Absorptiometry (DXA) scan, and acquisition of optical images (performed in duplicate by the Mobile Fit app to obtain two avatars for each player) were performed. The reproducibility analysis showed percent standard error of measurement values < 10% for all anthropometric and body composition measurements, thus indicating high agreement between the measurements obtained for the two avatars. Mobile Fit app overestimated the body fat percentage with respect to DXA (average overestimation of + 3.7% in males and + 4.6% in females), while it underestimated the total lean mass (− 2.6 kg in males and − 2.5 kg in females) and the appendicular lean mass (− 10.5 kg in males and − 5.5 kg in females). Using data of the soccer players, we reparameterized the equations previously proposed to estimate the body fat percentage and the appendicular lean mass and we obtained new equations that can be used in youth athletes for body composition assessment through conventional anthropometrics-based prediction models. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Total and regional appendicular skeletal muscle mass prediction from dual-energy X-ray absorptiometry body composition models" published in Scientific Reports. The original article contained errors in Figures 2 and 3, where the labels and text did not display correctly. The corrected figures and accompanying legends are provided in the document. The authors of the article are Cassidy McCarthy, Grant M. Tinsley, Anja Bosy-Westphal, Manfred J. Müller, John Shepherd, Dympna Gallagher, and Steven B. Heymsfield. [Extracted from the article]

Sarcopenia, sarcopenic obesity, frailty, and cachexia have in common skeletal muscle (SM) as a main component of their pathophysiology. The reference method for SM mass measurement is whole-body magnetic resonance imaging (MRI), although dual-energy X-ray absorptiometry (DXA) appendicular lean mass (ALM) serves as an affordable and practical SM surrogate. Empirical equations, developed on relatively small and diverse samples, are now used to predict total body SM from ALM and other covariates; prediction models for extremity SM mass are lacking. The aim of the current study was to develop and validate total body, arm, and leg SM mass prediction equations based on a large sample (N = 475) of adults evaluated with whole-body MRI and DXA for SM and ALM, respectively. Initial models were fit using ordinary least squares stepwise selection procedures; covariates beyond extremity lean mass made only small contributions to the final models that were developed using Deming regression. All three developed final models (total, arm, and leg) had high R2s (0.88–0.93; all p < 0.001) and small root-mean square errors (1.74, 0.41, and 0.95 kg) with no bias in the validation sample (N = 95). The new total body SM prediction model (SM = 1.12 × ALM – 0.63) showed good performance, with some bias, against previously reported DXA-ALM prediction models. These new total body and extremity SM prediction models, developed and validated in a large sample, afford an important and practical opportunity to evaluate SM mass in research and clinical settings. [ABSTRACT FROM AUTHOR]

Background: Many predictors of morbidity caused by metabolic disease are associated with body shape. 3D optical (3DO) scanning captures body shape and has been shown to accurately and precisely predict body composition variables associated with mortality risk. 3DO is safer, less expensive, and more accessible than criterion body composition assessment methods such as dual‐energy X‐ray absorptiometry (DXA). However, 3DO scanning has not been standardized across manufacturers for pose, mesh resolution, and post processing methods. Purpose: We introduce a scanner‐agnostic algorithm that automatically fits a topologically consistent human mesh to 3DO scanned point clouds and predicts clinically important body metrics using a standardized body shape model. Our models transform raw scans captured by any 3DO scanner into fixed topology meshes with anatomical consistency, standardizing the outputs of 3DO scans across manufacturers and allowing for the use of common prediction models across scanning devices. Methods: A fixed‐topology body mesh template was automatically registered to 848 training scans from three different 3DO systems. Participants were between 18 and 89 years old with body mass index ranging from 14 to 52 kg/m2. Scans were registered by first performing a coarse nearest neighbor alignment between the template and the input scan with an anatomically constrained principal component analysis (PCA) domain deformation using a device and gender specific bootstrap basis trained on 70 seed scans each. The template mesh was then optimized to fit the target with a smooth per‐vertex surface‐to‐surface deformation. A combined unified PCA model was created from the superset of all automatically fit training scans including all three devices. Body composition predictions to DXA measurements were learned from the training mesh PCA coefficients using linear regression. Using this final unified model, we tested the accuracy of our body composition models on a withheld sample of 562 scans by fitting a PCA parameterized template mesh to each raw scan and predicting the expected body composition metrics from the principal components using the learned regression model. Results: We achieved coefficients of determination (R2) above 0.8 on all nine fat and lean predictions except female visceral fat (0.77). R2 was as high as 0.94 (total fat and lean, trunk fat), and all root‐mean‐squared errors were below 3.0 kg. All predicted body composition variables were not significantly different from reference DXA measurements except for visceral fat and female trunk fat. Repeatability precision as measured by the coefficient of variation (%CV) was around 2–3x worse than DXA precision, with visceral fat %CV below 2x DXA %CV and female total fat mass at 5x. Conclusions: Our method provides an accurate, automated, and scanner agnostic framework for standardizing 3DO scans and a low cost, radiation‐free alternative to criterion radiology imaging for body composition analysis. We published a web‐app version of this work at https://shapeup.shepherdresearchlab.org/3do‐bodycomp‐analyzer/ that accepts mesh file uploads and returns templated meshes with body composition predictions for demo purposes. [ABSTRACT FROM AUTHOR]

Objective: Given the importance of body fat distribution in chronic disease development, feasible methods to assess body fat are essential. This study compared dual‐energy x‐ray absorptiometry (DXA) in measuring visceral and subcutaneous adipose tissue (VAT and SAT) with magnetic resonance imaging (MRI). Methods: VAT and SAT were assessed using similar DXA and MRI protocols among 1,795 elderly participants of the Adiposity Phenotype Study (APS) and 309 children/adolescents in Shape Up! Kids (SKids). Spearman correlations, Bland–Altman plots, and coefficients of determination (R2) assessed agreement between DXA and MRI measures. Results: DXA overestimated SAT values in APS (315 vs. 229 cm2) and SKids (212 vs. 161 cm2), whereas DXA underestimated VAT measures (141 vs. 167 cm2) in adults only. The correlations between DXA and MRI values were stronger for SAT than VAT (APS: r = 0.92 vs. 0.88; SKids: 0.90 vs. 0.74). Bland–Altman plots confirmed better agreement for SAT than VAT despite differences by sex, ethnicity, and weight status with respective R2 values for SAT and VAT of 0.88 and 0.84 (APS) and 0.81 and 0.69 (SKids). Conclusion: These findings indicate that SAT by DXA reflects MRI measures in children and older adults, whereas agreement for VAT is weaker for individuals with low VAT levels. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to investigate whether digitally re‐posing three‐dimensional optical (3DO) whole‐body scans to a standardized pose would improve body composition accuracy and precision regardless of the initial pose. Methods: Healthy adults (n = 540), stratified by sex, BMI, and age, completed whole‐body 3DO and dual‐energy X‐ray absorptiometry (DXA) scans in the Shape Up! Adults study. The 3DO mesh vertices were represented with standardized templates and a low‐dimensional space by principal component analysis (stratified by sex). The total sample was split into a training (80%) and test (20%) set for both males and females. Stepwise linear regression was used to build prediction models for body composition and anthropometry outputs using 3DO principal components (PCs). Results: The analysis included 472 participants after exclusions. After re‐posing, three PCs described 95% of the shape variance in the male and female training sets. 3DO body composition accuracy compared with DXA was as follows: fat mass R2 = 0.91 male, 0.94 female; fat‐free mass R2 = 0.95 male, 0.92 female; visceral fat mass R2 = 0.77 male, 0.79 female. Conclusions: Re‐posed 3DO body shape PCs produced more accurate and precise body composition models that may be used in clinical or nonclinical settings when DXA is unavailable or when frequent ionizing radiation exposure is unwanted. [ABSTRACT FROM AUTHOR]

Summary: Accurate and precise body composition estimates, notably of total body adiposity, are a vital component of in vivo physiology and metabolic studies. The reference against which other body composition approaches are usually validated or calibrated is the family of methods referred to as multicomponent "body density" models. These models quantify three to six components by combining measurements of body mass, body volume, total body water, and osseous mineral mass. Body mass is measured with calibrated scales, volume with underwater weighing or air‐displacement plethysmography, total body water with isotope dilution, and osseous mineral mass by dual‐energy X‐ray absorptiometry. Body density is then calculated for use in model as body mass/volume. Studies over the past decade introduced a new approach to quantifying body volume that relies on dual‐energy X‐ray absorptiometry measurements, an advance that simplifies multicomponent density model development by eliminating the need for underwater weighing or air‐displacement plethysmography systems when these technologies are unavailable and makes these methods more accessible to research and clinical programs. This review critically examines these new dual‐energy X‐ray approaches for quantifying body volume and density, explores their shortcomings, suggests alternative derivation approaches, and introduces ideas for potential future research studies. [ABSTRACT FROM AUTHOR]

Background: Reference ranges for lean mass (LM) and fat mass (FM) are essential in identifying soft tissue disorders; however, no such reference ranges exist for the most commonly used Hologic dual‐energy X‐ray absorptiometry (DXA) machine in Australia. Methods: Cross‐sectional study of community‐dwelling adults (aged 18–88 years) who underwent a Hologic DXA scan at one of three commercialized densitometry centres in Australia. Age‐specific and sex‐specific percentile curves were generated for LM [LM, appendicular lean mass (ALM), ALM adjusted for height squared (ALM/h2), and ALM adjusted for body mass index (ALM/BMI)] and FM [FM, FM adjusted for height squared (FM/h2), appendicular fat mass, and android and gynoid fat] parameters using the LMS statistical method. Cutpoints equivalent to T‐scores of −1, −2, and −2.5 standard deviations below the young mean reference group (20–29 years) were also generated for LM parameters. Results: A total of 15 479 community‐dwelling adults (54% men) with a median age of 33 years (interquartile range: 28, 42) were included. LM, ALM, and ALM/h2 remained stable until age 50, after which these parameters started to decline in both sexes. Compared with age 50, median percentiles of LM, ALM, and ALM/h2 declined by −5.9 kg, −3.7 kg, and −0.86 kg/m2 in men and by −2.5 kg, −1.8 kg, and −0.10 kg/m2 in women at age 70, respectively. Adjusting ALM for BMI (rather than height squared) resulted in different trends, with ALM/BMI decreasing from as early as age 20. Compared with age 20, median percentiles of ALM/BMI at age 40 declined by −0.10 kg/kg/m2 in men and by −0.06 kg/kg/m2 in women; and at age 70, ALM/BMI declined by −0.25 kg/kg/m2 in men and by −0.20 kg/kg/m2 in women. Cutpoints equivalent to T‐scores of −1, −2, and −2.5 standard deviations for ALM/BMI were 1.01, 0.86, and 0.77 kg/kg/m2 in men and 0.70, 0.59, and 0.53 kg/kg/m2 in women, respectively. All FM parameters progressively increased from age 20 and continued up until age 70. Conclusions: We developed reference ranges for LM and FM parameters from Hologic DXA machines in a large cohort of Australian adults, which will assist researchers and clinicians in identifying soft tissue disorders such as obesity, sarcopenia, and cachexia. [ABSTRACT FROM AUTHOR]

Purpose: Anthropometry is a method for quantifying body size and shape often used to derive body composition and health risk prediction models. Recent technology advancements led to development of three‐dimensional (3D) optical scanners that can overcome most of the limitations associated with manual anthropometric data collection. However, each of the currently available devices offers proprietary measurements that do not match conventional anthropometric definitions. The aim of the current study was to develop and then evaluate the precision and accuracy of new "universal" 3D optical analysis software that calculates digital anthropometric volumes using identical standard landmarks across scanners. Methods: Dual‐energy x‐ray absorptiometry (DXA) and air displacement plethysmography (ADP) total body and regional volume and fat mass reference measurements and 3D optical scans from two proprietary devices were collected from 356 participants to evaluate the robustness of total body and regional volume and fat mass measurements calculated by the developed software. Linear regression modeling with threefold cross validation was used to evaluate total body and regional fat masses from 3D scans. Results: Total body and regional volumes measured by DXA and ADP had strong associations with corresponding estimates from the commercial 3D optical scanners coupled with the universal software (e.g., R2 = 0.98 for Styku and R2 = 1.00 for SS20, for both DXA and ADP comparisons). Regional body volumes also had strong correlation between DXA and the 3DO scanners (e.g., for arm, leg and trunk, respective R2s of 0.75, 0.86, and 0.97 for Styku and 0.79, 0.89, and 0.98 for SS20). Similarly, there were strong associations between DXA‐ measured total body and regional fat mass and 3D optical estimates calculated by the universal software (e.g., for total body, arm, leg and trunk, respective R2s of 0.86, 0.72, 0.77, and 0.88 for Styku and 0.84, 0.76, 0.78, and 0.85 for SS20). Absolute differences in volumes and fat mass between the reference methods and the universal software values revealed underlying proprietary scanner differences that can be improved when designing future devices. Conclusions: The current study suggests that, when compared against values calculated using DXA and ADP, the universal software was able to measure total and regional body volumes reliably from scans obtained by two different scanners. The universal software, with future refinements, combined with potential optical scanner design improvements, creates new opportunities for developing large multicenter anthropometric databases with uniformly defined body dimensions that can be used for modeling health risks. Clinical Trial Registration ID: Shape Up! Adults Study, NCT0363785. [ABSTRACT FROM AUTHOR]

Objectives: As rates of obesity around the world have increased, so has the detection of high level of liver fat in children and adolescents. This may put them at risk for cardiovascular disease later in life. This analysis of a cross‐sectional population‐based study of children and adolescents evaluated demographic and lifestyle determinants of percent liver fat. Methods: Healthy participants (123 girls and 99 boys aged 5–17 years) recruited by convenience sampling in three locations completed questionnaires, anthropometric measurements, and dual X‐ray absorptiometry and magnetic resonance imaging (MRI) assessment. General linear models were applied to estimate the association of demographic, anthropometric, and dietary factors as well as physical activity with MRI‐based percent liver fat. Results: The strongest predictor of liver fat was body mass index (BMI; p < 0.0001); overweight and obesity were associated with 0.5% and 1% higher liver fat levels. The respective adjusted mean percent values were 2.9 (95% CI 2.7, 3.1) and 3.4 (95% CI 3.2, 3.6) as compared to normal weight (2.4; 95% CI 2.3, 2.6). Mean percent liver fat was highest in Whites and African Americans, intermediate in Hispanic, and lowest among Asians and Native Hawaiians/Pacific Islanders (p < 0.0001). Age (p = 0.67), sex (p = 0.28), physical activity (p = 0.74), and diet quality (p = 0.70) were not significantly related with liver fat. Conclusions: This study in multiethnic children and adolescents confirms the strong relationship of BMI with percent liver fat even in a population with low liver fat levels without detecting an association with age, sex, and dietary or physical activity patterns. [ABSTRACT FROM AUTHOR]

Background: Current consensus is to combine a functional measure with muscle quantity to assess/confirm sarcopenia. However, the proper body size adjustment for muscle quantity is debated and sarcopenia in obesity is not well described. Further, functional measures are not muscle-specific or sensitive to etiology, and can be confounded by, for example, fitness/pain. For effective detection/treatment/follow-up, muscle-specific biomarkers linked to function are needed.Methods: Nine thousand six hundred and fifteen participants were included and current sarcopenia thresholds (EWGSOP2: DXA, hand grip strength) applied to investigate prevalence. Fat-tissue free muscle volume (FFMV) and muscle fat infiltration (MFI) were quantified through magnetic resonance imaging (MRI) and sex-and-body mass index (BMI)-matched virtual control groups (VCGs) were used to extract each participant's FFMV/height2 z-score (FFMVVCG). The value of combining FFMVVCG and MFI was investigated through hospital nights, hand grip strength, stair climbing, walking pace, and falls.Results: Current thresholds showed decreased sarcopenia prevalence with increased BMI (underweight 8.5%/normal weight 4.3%/overweight 1.1%/obesity 0.1%). Contrary, the prevalence of low function increased with increasing BMI. Previously proposed body size adjustments (division by height2/weight/BMI) introduced body size correlations of larger/similar magnitude than before. VCG adjustment achieved normalization and strengthened associations with hospitalization/function. Hospital nights, low hand grip strength, slow walking pace, and no stair climbing were positively associated with MFI (p < .05) and negatively associated with FFMVVCG (p < .01). Only MFI was associated with falls (p < .01). FFMVVCG and MFI combined resulted in highest diagnostic performance detecting low function.Conclusions: VCG-adjusted FFMV enables proper sarcopenia assessment across BMI classes and strengthened the link to function. MFI and FFMV combined provides a more complete, muscle-specific description linked to function enabling objective sarcopenia detection. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to explore the accuracy and precision of three-dimensional optical (3DO) whole-body scanning for automated anthropometry and estimating total and regional body composition.Methods: Healthy children and adolescents (n = 181, ages 5-17 years) were recruited for the Shape Up! Kids study. Each participant underwent whole-body dual-energy x-ray absorptiometry and 3DO scans; multisite conventional tape measurements served as the anthropometric criterion measure. 3DO body shape was described using automated body circumference, length, and volume measures. 3DO estimates were compared with criterion measures using simple linear regression by the stepwise selection method.Results: Of the 181 participants, 112 were used for the training set, 49 were used for the test set, and 20 were excluded for technical reasons. 3DO body composition estimates were strongly associated with dual-energy x-ray absorptiometry measures for percent body fat, fat mass, and fat-free mass (R2 : 0.83, 0.96, and 0.98, respectively). 3DO provided reliable measurements of fat mass (coefficient of variation, 3.30; root mean square error [RMSE], 0.53), fat-free mass (coefficient of variation, 1.34; RMSE, 0.53 kg), and percent body fat (RMSE = 1.2%).Conclusions: 3DO surface scanning provides accurate and precise anthropometric and body composition estimates in children and adolescents with high precision. 3DO is a safe, accessible, and practical method for evaluating body shape and composition in research and clinical settings. [ABSTRACT FROM AUTHOR]

Background: Low appendicular skeletal muscle mass (ASM) is associated with negative outcomes, but its assessment requires proper limb muscle evaluation. We aimed to verify how anthropometric circumferences are correlated to ASM and to develop new prediction equations based on calf circumference and other anthropometric measures, using dual-energy X-ray absorptiometry (DEXA) as the reference method.Methods: DEXA and anthropometric information from 15,293 adults surveyed in the 1999-2006 NHANES were evaluated. ASM was defined by the sum of the lean soft tissue from the limbs. Anthropometric data included BMI and calf, arm, thigh, and waist circumferences. Correlations were assessed by Pearson's correlation, and multivariable linear regression produced 4 different ASM prediction equations. The concordance and the overall 95% limits of agreement between measured and estimated ASM were assessed using Lin's coefficient and Bland-Altman's approach.Results: Calf and thigh circumferences were highly correlated with ASM, independent of age and ethnicity. Among the models, the best performance came from the equation constituted solely by calf circumference, sex, race, and age as independent variables, which was able to explain almost 90% of the DEXA-measured ASM variation. The inclusion of different anthropometric parameters in the model increased collinearity without improving estimates. Concordance between the four developed equations and DEXA-measured ASM was high (Lin's concordance coefficient >0.90).Conclusion: Despite the good performance of the four developed equations in predicting ASM, the best results came from the equation constituted only by calf circumference, sex, race, and age. This equation allows satisfactory ASM estimation from a single anthropometric measurement. [ABSTRACT FROM AUTHOR]

The term sarcopenia was introduced in 1988. The original definition was a "muscle loss" of the appendicular muscle mass in the older people as measured by dual energy x‐ray absorptiometry (DXA). In 2010, the definition was altered to be low muscle mass together with low muscle function and this was agreed upon as reported in a number of consensus papers. The Society of Sarcopenia, Cachexia and Wasting Disorders supports the recommendations of more recent consensus conferences, i.e. that rapid screening, such as with the SARC‐F questionnaire, should be utilized with a formal diagnosis being made by measuring grip strength or chair stand together with DXA estimation of appendicular muscle mass (indexed for height2). Assessments of the utility of ultrasound and creatine dilution techniques are ongoing. Use of ultrasound may not be easily reproducible. Primary sarcopenia is aging associated (mediated) loss of muscle mass. Secondary sarcopenia (or disease‐related sarcopenia) has predominantly focused on loss of muscle mass without the emphasis on muscle function. Diseases that can cause muscle wasting (i.e. secondary sarcopenia) include malignant cancer, COPD, heart failure, and renal failure and others. Management of sarcopenia should consist of resistance exercise in combination with a protein intake of 1 to 1.5 g/kg/day. There is insufficient evidence that vitamin D and anabolic steroids are beneficial. These recommendations apply to both primary (age‐related) sarcopenia and secondary (disease related) sarcopenia. Secondary sarcopenia also needs appropriate treatment of the underlying disease. It is important that primary care health professionals become aware of and make the diagnosis of age‐related and disease‐related sarcopenia. It is important to address the risk factors for sarcopenia, particularly low physical activity and sedentary behavior in the general population, using a life‐long approach. There is a need for more clinical research into the appropriate measurement for muscle mass and the management of sarcopenia. Accordingly, this position statement provides recommendations on the management of sarcopenia and how to progress the knowledge and recognition of sarcopenia. [ABSTRACT FROM AUTHOR]

Objective: Chronic positive energy balance leads to obesity, and the "excess" weight is usually described as consisting solely of adipose tissue (AT) or its two components, fat and fat-free mass (nonfat cell mass, extracellular fluid). This study aimed to clarify the nature of "obesity" tissue.Methods: A total of 333 adults had AT, skin, skeletal muscle, bone, heart, liver, kidney, spleen, brain, and residual mass measured or derived using magnetic resonance imaging and dual-energy x-ray absorptiometry. First, associations between these components and AT were examined by developing multiple regression models. Next, obesity-tissue composition was developed by deriving mean component mass differences between participant groups with normal weight (BMI < 25 kg/m2 ) and those with obesity (BMI > 29.9 kg/m2 ); respective resting energy expenditures and metabolizable energy and protein contents were calculated.Results: AT significantly predicted organ-tissue mass in 17 of 18 multiple regression models. In addition to AT and skeletal muscle, the following associations were found: skin, liver, and bone were main contributors to obesity-tissue composition; liver, kidneys, and heart to resting energy expenditure; and skin, liver, and bone to metabolizable energy and protein contents. A pronounced sexual dimorphism was present in all three models.Conclusions: Obesity is characterized not only by excess AT but by increases in the masses of other "companion" organs and tissues and their related metabolic properties. [ABSTRACT FROM AUTHOR]

Background: Measures of skeletal muscle function decline at a faster rate with ageing than do indices of skeletal muscle mass. These observations have been attributed to age‐related changes in muscle quality, another functional determinant separate from skeletal muscle mass. This study tested the hypothesis that improved predictions of skeletal muscle strength can be accomplished by combining clinically available measures of skeletal muscle mass and quality. Methods: The participants included 146 healthy adult (age ≥ 18 years, range 18–77 years; X ± SD 47 ± 17 years and body mass index 16.5–51.8 kg/m2; 27.7 ± 6.2 kg/m2) men (n = 60) and women (n = 86) in whom skeletal muscle mass was estimated as appendicular lean soft tissue (LST) measured by dual‐energy X‐ray absorptiometry and skeletal muscle quality as bioimpedance analysis‐derived phase angle and B‐mode‐evaluated echogenicity of mid‐thigh skeletal muscle. Strength of the right leg and both arms was quantified as knee isokinetic extension and handgrip strength using dynamometers. The statistical significance of adding phase angle or echogenicity to strength prediction multiple regression models that included extremity‐specific LST and other covariates (e.g. age and sex) was evaluated to test the study hypothesis. Results: Right leg LST mass alone was significantly (P < 0.0001) correlated with isokinetic right leg strength (R2 = 0.57). The addition of segmental phase angle measured in the right leg at 50 kHz increased the R2 of this model to 0.66 (P < 0.0001); other phase angle frequencies (5 and 250 kHz) did not contribute significantly to these models. Results were similar for both right and left arm handgrip strength prediction models. Adding age and sex as model covariates increased the R2 values of these models further (e.g. right leg strength model R2 increased to 0.71), but phase angle continued to remain a significant (all P < 0.01) predictor of extremity strength. Similarly, when predicting isokinetic right leg strength, mid‐thigh skeletal muscle echogenicity added significantly (P < 0.0001) to right leg LST, increasing R2 from 0.57 to 0.64; age was a significant (P < 0.0001) covariate in this model, increasing R2 further to 0.68. Conclusions: The hypothesis of the current study was confirmed, strongly supporting and extending earlier reports by quantifying the combined independent effects of skeletal muscle mass and quality on lower‐body and upper‐body measures of strength. These observations provide a clinically available method for future research aimed at optimizing sarcopenia and frailty risk prediction models. [ABSTRACT FROM AUTHOR]

Background/Objectives: Body mass index (BMI) is a proxy for obesity that is commonly used in spite of its limitation in estimating body fatness. Trained observers with repeated exposure to different body types can estimate body fat (BF) of individuals compared to criterion methods with reasonable accuracy. The purpose of this study was to develop and validate a computer algorithm to provide a valid estimate %BF using digital photographs. Subjects/Methods: Our sample included 97 children and 226 adults (age in years: 11.3±3.3; 38.1±11.6, respectively). Measured height and weight were used (BMI in kg/m2: 20.4±4.4; 28.7±6.6 for children and adults, respectively). Dual x-ray absorptiometry (DXA) was the criterion method. Body volume (BVPHOTO) and body shape (BSPHOTO) were derived from two digital images. Final support vector regression (SVR) models were trained using age, sex, race, BMI for % BFNOPHOTO, plus BVPHOTO and BSPHOTO for %BFPHOTO. Separate validation models were used to evaluate the learning algorithm in children and adults. The differences in correlations between %BFDXA, %BFNOPHOTO and %BFPHOTO were tested using the Fisher’s Z-score transformation. Results: Mean BFDXA and BFPHOTO were 27.0%±9.2 vs. 26.7%± 7.4 in children and 32.9± 10.4% vs. 32.8%±9.3 in adults. SVR models produced %BFPHOTO values strongly correlated with %BFDXA. Our final model produced correlations of rDP = 0.80 and rDP = 0.87 in children and adults, respectively for %BFPHOTO vs. %BFDXA. The correlation between %BFNOPHOTO and %BFDXA was moderate, yet statistically significant in both children rDB = 0.70; p <0.0001 and adults rDB = 0.86; p<0.0001. However, the correlations for rDP were statistically higher than rDB (%BFDXA vs. %BFNOPHOTO) in both children and adults (children: Z = 5.95, p<0.001; adults: Z = 3.27, p<0.0001). Conclusions: Our photographic method produced valid estimates of BF in both children and adults. Further research is needed to create norms for subgroups by sex, race/ethnicity, and mobility status. [ABSTRACT FROM AUTHOR]

Background: Ascites in cirrhotic patients interfere with accurate assessment of skeletal muscle when diagnosing sarcopenia. We hypothesized measurement of appendicular skeletal muscle index (ASMI) with dual-energy x-ray absorptiometry (DXA) improves the diagnosis of sarcopenia in cirrhotic patients as ASMI does not include the fluid-filled abdominal compartment.Objective: To evaluate if ASMI is influenced by ascites, lower limb edema (LLE) and predicts mortality alone or combined with handgrip strength (HGS) in cirrhotic patients.Design: ASMI, HGS, and 36-month mortality were obtained in 144 men with cirrhosis. ASMI was compared before and after paracentesis in 20 men with ascites and to results from 20 matched controls. The prognostic value of ASMI alone and with HGS was tested in a survival. Survival probabilities were obtained for sarcopenia diagnosed by standard ASMI and HGS European Working Group on Sarcopenia in Older People (EWGSOP) cutoffs and a new cutoff calculated from our ASMI + HGS tertiles.Results: ASMI did not change after paracentesis, was lower in patients than in controls (P < .001), and was not influenced by LLE (D = 0.30 kg/m2, P = .068; R2 = 2.40%). Mortality was influenced by ASMI and HGS (Pinteraction = 0.028). Sarcopenia diagnosed by EWGSOP was also diagnosed by our new cutoff; both predicted mortality with the latter more sensitive for mortality risk prediction (P = .011).Conclusions: DXA-measured ASMI is not influenced by ascites or LLE in cirrhotic patients; can diagnose low skeletal muscle/sarcopenia; and predicts mortality, particularly when combined with HGS. [ABSTRACT FROM AUTHOR]

Background: Raw bioimpedance parameters (eg, 50-kHz phase angle [PA] and 200-kHz/5-kHz impedance ratio [IR]) have been investigated as predictors of nutrition status and/or clinical outcomes. However, their validity as prognostic measures depends on the availability of appropriate reference data. Using a large and ethnically diverse data set, we aimed to determine if ethnicity influences these measures and provide expanded bioimpedance reference data for the U.S.Population: Methods: The National Health and Nutrition Examination Survey (NHANES) is an ongoing compilation of studies conducted by the U.S. Centers for Disease Control and Prevention designed to monitor nutrition status of the U.S.Population: The NHANES data sets analyzed were from the years 1999-2000, 2001-2002, and 2003-2004.Results: Multivariate analysis showed that PA and IR differed by body mass index (BMI), age, sex, and ethnicity (n = 6237; R2 = 41.2%, P < .0001). Suggested reference cut-points for PA stratified by age decade, ethnicity, and sex are provided.Conclusion: Ethnicity is an important variable that should be accounted for when determining population reference values for PA and IR. We have provided sex-, ethnicity-, and age decade-specific reference values from PA for use by future studies in U.S.Populations: Interdevice differences are likely to be important contributors to variability across published population-specific reference data and, where possible, should be evaluated in future research. Ultimately, further validation with physiologically relevant reference measures (eg, dual-energy x-ray absorptiometry) is necessary to determine if PA/IR are appropriate bedside tools for the assessment of nutrition status in a clinical population. [ABSTRACT FROM AUTHOR]

Dual-energy X-ray absorptiometry (DXA) is widely used in body composition measurement and evaluation. Because of its numerous applications, the probability of instrument discrepancies has increased dramatically. This study quantitatively compares 2 different DXA systems. In this study, 96 subjects (60 female and 36 male, aged 19–82 years) were recruited and scanned using a General Electric Lunar iDXA and a Hologic Discovery scanner. Four measurements (percent fat, total mass, bone mineral density [BMD], and bone mineral content [BMC]) were quantitatively compared in the whole body and in specific anatomic regions (arms, legs, trunk, android, gynoid, head, ribs, and pelvis). A simple linear regression of each measurement was performed to examine the correlation between the 2 systems. Percent fat, total mass, BMC, and BMD were highly correlated between the 2 DXA systems, with correlation r values greater than 0.854 for both the whole body and the individual anatomic regions except for BMC and BMD in ribs. The high correlation between the 2 DXA systems with systematic differences enabled development of calibration equations for extending the multisystem measurements to advanced quantitative analyses. [ABSTRACT FROM AUTHOR]

Current bioelectric impedance analysis (BIA) systems are often large, cumbersome devices which require strict electrode placement on the user, thus inhibiting mobile capabilities. In this work, we developed a handheld BIA device that measures impedance from multiple frequencies (5 kHz~200 kHz) with four contact electrodes and evaluated the BIA device against standard body composition analysis systems: a dual-energy X-ray absorptiometry (DXA) system (GE Lunar Prodigy, GE Healthcare, Buckinghamshire, UK) and a whole-body BIA system (InBody S10, InBody, Co. Ltd, Seoul, Korea). In the study, 568 healthy participants, varying widely in body mass index, age, and gender, were recruited at two research centers: the Samsung Medical Center (SMC) in South Korea and the Pennington Biomedical Research Center (PBRC) in the United States. From the measured impedance data, we analyzed individual body fat and skeletal muscle mass by applying linear regression analysis against target reference data. Results indicated strong correlations of impedance measurements between the prototype pathways and corresponding InBody S10 electrical pathways (R = 0.93, p < 0.0001). Additionally, body fat estimates from DXA did not yield significant differences (p > 0.728 (paired t-test), DXA mean body fat 29.45 ± 10.77 kg, estimated body fat 29.52 ± 12.53 kg). Thus, this portable BIA system shows a promising ability to estimate an individual's body composition that is comparable to large stationary BIA systems. [ABSTRACT FROM AUTHOR]

ABSTRACT Objectives Adult body mass (MB) empirically scales as height (Ht) squared (MB ∝ Ht2), but does regional body mass and body composition as a whole also scale as Ht2? This question is relevant to a wide range of biological topics, including interpretation of body mass index (BMI). Methods Dual-energy X-ray absorptiometry (DXA) was used to quantify regional body mass [head (MH), trunk, arms, and legs] and whole-body composition [fat, lean soft tissue (LST), and bone mineral content (BMC)] in non-Hispanic (NH) white, NH black, Mexican American, and Korean adults participating in the National Health and Nutrition Examination Survey (NHANES; n = 17,126) and Korean NHANES ( n = 8,942). Regression models were developed to establish Ht scaling powers for each measured component with adjustments for age and adiposity. Results Exploratory analyses revealed a consistent scaling pattern across men and women of the four population groups: regional mass powers, head (∼0.8-1) < arms and trunk (∼1.8-2.3) < legs (∼2.3-2.6); and body composition, LST (∼2.0-2.3) < BMC (∼2.1-2.4). Small sex and population differences in scaling powers were also observed. As body mass scaled uniformly across the eight sex and population groups as Ht∼2, tall and short subjects differed in body shape (e.g., MH/MB ∝ Ht−∼1) and composition. Conclusions Adult human body shape and relative composition are a function of body size as represented by stature, a finding that reveals a previously unrecognized phenotypic heterogeneity as defined by BMI. These observations provide new pathways for exploring mechanisms governing the interrelations between adult stature, body morphology, biomechanics, and metabolism. Am. J. Hum. Biol., 27:372-379, 2015. . [ABSTRACT FROM AUTHOR]

Previous studies have shown an inverse correlation between bone marrow adipose tissue and bone mineral density in cancellous bone; however, such relationships in cortical bone are less studied, especially in children. A total of 185 healthy children and adolescents (76 females and 109 males, aged 5–18 years) were included in this study. Right femoral bone marrow adipose tissue area (BMA), right femoral cortical bone area (CBA), subcutaneous adipose tissue, visceral adipose tissue, and skeletal muscle were accessed by whole-body magnetic resonance imaging. In regression analysis with CBA as the dependent variable and BMA as the independent variable, BMA negatively contributed to CBA after adjusting for weight and total body fat or subcutaneous adipose tissue, visceral adipose tissue, and skeletal muscle ( β = −0.201 to −0.272, p < 0.001). These results suggest an inverse relationship between BMA and CBA in children and adolescents after adjustment of body weight or body composition. The data support the hypothesis that a competitive relationship exists between bone and marrow fat in cortical bone and is consistent with a similar finding in cancellous bone in previous studies. Future research is needed to clarify the role of marrow fat in childhood fractures that are related to cortical bone quality. [ABSTRACT FROM AUTHOR]

Abstract: Several large-scale studies have reported the presence of an inverse relationship between bone mineral density (BMD) and bone marrow adipose tissue (BMAT) in adults. We aim to determine if there is an inverse relationship between pelvic volumetric BMD (vBMD) and pelvic BMAT in children and to compare this relationship in children and adults. Pelvic BMAT and bone volume (BV) was evaluated in 181 healthy children (5–17yr) and 495 healthy adults (≥18yr) with whole-body magnetic resonance imaging (MRI). Pelvic vBMD was calculated using whole-body dual-energy X-ray absorptiometry to measure pelvic bone mineral content and MRI-measured BV. An inverse correlation was found between pelvic BMAT and pelvic vBMD in both children (r =−0.374, p <0.001) and adults (r =−0.650, p <0.001). In regression analysis with pelvic vBMD as the dependent variable and BMAT as the independent variable, being a child or adult neither significantly contribute to the pelvic BMD (p =0.995) nor did its interaction with pelvic BMAT (p =0.415). The inverse relationship observed between pelvic vBMD and pelvic BMAT in children extends previous findings that found the inverse relationship to exist in adults and provides further support for a reciprocal relationship between adipocytes and osteoblasts. [Copyright &y& Elsevier]

Objective The purpose of this study was to determine reproducibility and clinical thresholds for DXA-derived visceral adipose tissue (VAT). Design and Methods The sample included 2317 white and African American adults 18-74 years of age. VAT areas (cm2) were measured using a Hologic DXA scanner equipped with APEX 4.0 software. Reproducibility was assessed using repeated measurements on 101 participants scanned 14 days apart. Receiver Operating Characteristic (ROC) curves were used to assess clinical utility and select thresholds that identified elevated cardiometabolic risk, defined as the presence of ≥2 risk factors. Results Reproducibility of DXA-VAT was 8.1%. The areas under the ROC curves ranged from 0.754 in African American men to 0.807 in white women. The thresholds were higher in white men (154 cm2) and women (143 cm2) compared to African American men (101 cm2) and women (114 cm2). Conclusion The results demonstrated that DXA VAT is a useful clinical marker of cardiometabolic risk; however, further research is required to determine associations with health outcomes using longitudinal studies. [ABSTRACT FROM AUTHOR]

Introduction: Chinese are reported to have a higher percent body fat (%BF) and a higher percent trunk fat (%TF) than whites for a given body mass index (BMI). However, the associations of these ethnic differences in body composition with metabolic risks remain unknown. Methods and Procedures: A total of 1 029 Chinese from Hangzhou, China, and 207 whites from New York, NY, USA, were recruited in the present study. Body composition was measured using dual-energy X-ray absorptiometry (DXA). Analysis of covariance was used to assess the ethnic differences in fat, fat distribution, and metabolic risk factors. Results: After adjusting for BMI, age, and height, Chinese men had an average of 3.9% more %BF and 12.1% more %TF than white men; Chinese women had an average of 2.3% more %BF and 11.8% more %TF than white women. Compared with whites, higher metabolic risks were detected in Chinese for a given BMI after adjusting for age and height. Further adjustment for %BF did not change these ethnic disparities. However, after adjusting for %TF, the ethnic differences decreased and become insignificant in triglyceride, high-density lipoprotein cholesterol, and blood pressure (except for systolic blood pressure in men). For fasting plasma glucose, the ethnic differences persisted after adjustment for %BF, but decreased significantly from 0.910 to 0.686 mmol/L among men, and from 0.629 to 0.355 mmol/L among women, when the analyses were further controlled for %TF. Discussion: Chinese have both higher %BF and %TF than white people for a given BMI. However, only %TF could in part account for the higher metabolic risk observed in Chinese men and women. [ABSTRACT FROM AUTHOR]

Based on cross-sectional analyses, it was suggested that hip circumference divided by height1.5 −18 (the body adiposity index (BAI)), could directly estimate percent body fat without the need for further correction for sex or age. We compared the prediction of percent body fat, as assessed by dual-energy X-ray absorptiometry (PBFDXA), by BAI, BMI, and circumference (waist and hip) measurements among 1,151 adults who had a total body scan by DXA and circumference measurements from 1993 through 2005. After accounting for sex, we found that PBFDXA was related similarly to BAI, BMI, waist circumference, and hip circumference. In general, BAI underestimated PBFDXA among men (2.5%) and overestimated PBFDXA among women (4%), but the magnitudes of these biases varied with the level of body fatness. The addition of covariates and quadratic terms for the body size measures in regression models substantially improved the prediction of PBFDXA, but none of the models based on BAI could more accurately predict PBFDXA than could those based on BMI or circumferences. We conclude that the use of BAI as an indicator of adiposity is likely to produce biased estimates of percent body fat, with the errors varying by sex and level of body fatness. Although regression models that account for the nonlinear association, as well as the influence of sex, age, and race, can yield more accurate estimates of PBFDXA, estimates based on BAI are not more accurate than those based on BMI, waist circumference, or hip circumference. [ABSTRACT FROM AUTHOR]

Objectives: A classic association is the link between brain mass and body mass across mammals that has now been shown to derive from fat-free mass (FFM) and not fat mass (FM). This study aimed to establish for the first time the associations between human brain mass and body composition and to compare these relations with those established for liver as a reference organ. Methods: Subjects were 112 men and 148 women who had brain and liver mass measured by magnetic resonance imaging with FM and FFM measured by dual-energy X-ray absorptiometry. Results: Brain mass scaled to height (H) with powers of ≤0.6 in men and women; liver mass and FFM both scaled similarly as H∼2. The fraction of FFM as brain thus scaled inversely to height ( P < 0.001) while liver mass/FFM was independent of height. After controlling for age, brain, and liver mass were associated with FFM while liver was additionally associated with FM (all models P ≤ 0.01). After controlling for age and sex, FFM accounted for ∼5% of the variance in brain mass while levels were substantially higher for liver mass (∼60%). Brain mass was significantly larger ( P < 0.001) in men than in women, even after controlling for age and FFM. Conclusions: As across mammals, human brain mass associates significantly, although weakly, with FFM and not FM; the fraction of FFM as brain relates inversely to height; brain differs in these relations from liver, another small high metabolic rate organ; and the sexual dimorphism in brain mass persists even after adjusting for age and FFM. Am. J. Hum. Biol., 2012. © 2012 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Balance methods reveal changes in body energy, nitrogen, macro- and micronutrients as well as fluid in response to different feeding regimens. Under metabolic ward conditions, where physical activity is restricted and activity and food intake are controlled, the errors of estimates of energy intake, energy expenditure, and energy losses are about 2, 4, and 2%, respectively. Balance techniques can be used to validate techniques of in vivo body composition analysis (BCA). This is necessary since immediate and transient changes in body composition in response to a change in diet adversely affect the validity of techniques by violating the assumptions underlying standard methods (i.e., a constant composition or hydration of lean mass). Using two compartment reference methods, like densitometry, dual X-ray absorptiometry (DXA) or deuterium dilution, changes in fat mass with caloric restriction and overfeeding can be measured with a minimal detectable change (MDC) of 1.0-2.0 kg. However, when compared against balance data, the validity of these techniques to measure short-term changes in body composition is poor. The noninvasive and rapid new quantitative magnetic resonance (QMR) technique has a high precision with a MDC of 0.18 kg of fat mass. The validity of QMR to assess short-term changes in fat mass is challenged by comparison to balance data. Today, techniques used for in vivo BCA should be related to steady state conditions only, while in the nonsteady state, the use of balance methods is recommended to assess short-term changes in body composition. [ABSTRACT FROM AUTHOR]

In 2008 the National Center for Health Statistics released a dual energy x-ray absorptiometry (DXA) whole body dataset from the NHANES population-based sample acquired with modern fan beam scanners in 15 counties across the United States from 1999 through 2004. The NHANES dataset was partitioned by gender and ethnicity and DXA whole body measures of %fat, fat mass/height², lean mass/height², appendicular lean mass/height², %fat trunk/%fat legs ratio, trunk/limb fat mass ratio of fat, bone mineral content (BMC) and bone mineral density (BMD) were analyzed to provide reference values for subjects 8 to 85 years old. DXA reference values for adults were normalized to age; reference values for children included total and sub-total whole body results and were normalized to age, height, or lean mass. We developed an obesity classification scheme by using estabbody mass index (BMI) classification thresholds and prevalences in young adults to generate matching classification thresholds for Fat Mass Index (FMI; fat mass/height²). These reference values should be helpful in the evaluation of a variety of adult and childhood abnormalities involving fat, lean, and bone, for establishing entry criteria into clinical trials, and for other medical, research, and epidemiological uses. [ABSTRACT FROM AUTHOR]

Background: Skeletal muscle (SM) is an important compartment but is difficult to quantify in children and adolescents. Objective: We investigated the potential of dual-energy X-ray absorptiometry (DXA) for measuring total-body SM in pediatric subjects. Design: A previously published adult DXA SM prediction formula was evaluated in children and adolescents aged 5-17 y(n = 99) who varied in pubertal maturation stage. SM estimated by whole-body magnetic resonance imaging (MRI) was used as the reference. The adult SM model was not accurate for subjects below Tanner stage 5 (n = 65; aged 5-14 y). New pediatric SM prediction models were therefore developed and validated in a separate group (n = 18). Results: The adult DXA SM prediction model was valid in subjects at Tanner stage 5 but significantly (P < 0.001) overestimated SM in subjects below Tanner stage 5. New SM prediction formulas were developed with appendicular lean soft tissue (ALST) estimates by DXA as the main predictor variable (eg, model 1, ALST alone: R2 = 0.982, SEE = 0.565 kg, P < 0.001). The new models were validated by the leave-one-out method and were cross-validated in a separate validation group. Conclusions: A previously reported adult DXA SM prediction model is applicable in children and adolescents late in pubertal development (Tanner stage 5). A new DXA SM prediction model was developed for prepubertal and pubertal subjects (Tanner stage ⩽4) aged ⩾5 y. DXA thus provides an important opportunity for quantifying total-body SM mass across most of the human life span. [ABSTRACT FROM AUTHOR]

Abstract: We compared bone mineral density (BMD) and body fat percentage (%fat) between two pencil-beam (Lunar DPX and DPX-L) and two fan-beam (Lunar Prodigy, Hologic Delphi A) dual-energy X-ray absorptiometry (DXA) systems. We examined these values in the total-body, spine, femur, and forearm scans in 78 healthy adults across these four DXA systems. BMD and %fat values were highly correlated among the four instruments. DPX-L gave the lowest mean %fat and Prodigy gave the highest mean %fat for both sexes. The means were system dependent for %fat estimates across the four DXA machines. There was a significant difference detected in BMD estimates across manufacturers, with the Delphi A providing systematically lower values than the Lunar systems in the whole body, spine, and femur sites but higher values than the Lunar systems in the forearm. The present study results show that both %fat and bone mineral estimates between pencil-beam and fan-beam systems are highly correlated, but vary by system. Significant differences exist between the instruments, especially between different manufacturers, and most of the comparisons are sex dependent. We conclude that longitudinal studies should always be evaluated on the same system when possible, and translation models should be used to assess cross-instrument differences. [Copyright &y& Elsevier]

Background: Limited research has been done to explore differences between ethnic groups, including Hispanic Americans (HAs), in the association between percentage body fat (PBF) and body mass index (BMI; in kg/m2); the numbers of HAs are increasing in the US population. Objective:We investigated whether the relation between PBF and BMI in adult HAs differed from that of African Americans (AAs) and European Americans (EAs). Design:We used a multiple regression model in which PBF measured with dual energy X-ray absorptiometry was predicted by the reciprocal of BMI (1/BMI; in m2/kg) in a sample of 487 men (nEA = 192, nAA = 148, and nHA = 147) and 933 women (nEA = 448, nAA = 304, and nHA = 181). Results: For men, our results showed no significant differences between HAs and EAs, AAs and EAs, or HAs and AAs in the slope of the line relating 1/BMI to PBF. In women, there were significant differences in PBF as predicted by BMI between HAs and EAs (P < 0.002) and AAs and HAs (P = 0.020), but not between AAs and EAs. When PBF was estimated on the basis of predicting equations, the trend of the predicted PBF value in women differed according to ethnic group and BMI category. At a BMI < 30, HAs tended to have more body fat than did EAs and AAs, and at a BMI > 35, EAs tended to have more body fat than did the other groups. Conclusions: Our results show that the relation between PBF and BMI in HA women differs from that of EA and AA women. [ABSTRACT FROM AUTHOR]

Background: Skeletal muscle (SM) is an important body-composition component that remains difficult and impractical to quantify by most investigators outside of specialized research centers. A large proportion of total-body SM is found in the extremities, and a large proportion of extremity lean soft tissue is SM. A strong link should thus exist between appendicular lean soft tissue (ALST) mass and total-body SM mass. Objective: The objective was to develop prediction models linking ALST estimated by dual-energy X-ray absorptiometry (DXA) with total-body SM quantified by multislice magnetic resonance imaging in healthy adults. Design: ALST and total-body SM were evaluated with a crosssectional design in adults [body mass index (in kg/m2) < 35] with an SM-prediction model developed and validated in model-development and model-validation groups, respectively. The modeldevelopment and model-validation groups included 321 and 93 ethnically diverse adults, respectively. Results: ALST alone was highly correlated with total-body SM (model 1: R2 = 0.96, SEE = 1.63 kg, P < 0.001), although multiple regression analyses showed 2 additional predictor variables: age (model 2: 2-variable combined R2 = 0.96, SEE = 1.58 kg, P < 0.001) and sex (model 3: 3-variable combined R2 = 0.96, SEE = 1.58 kg, P < 0.001). All 3 models performed well in the validation group. An SM-prediction model based on the SM-ALST ratio was also developed, although this model had limitations when it was applied across all subjects. Conclusion: Total-body SM can be accurately predicted from DXAestimated ALST, thus affording a practical means of quantifying the large and clinically important SM compartment. [ABSTRACT FROM AUTHOR]

Summary: Excess fat on the body impacts obesity‐related co‐morbidity risk; however, the location of fat stores affects the severity of these risks. The purpose of this study was to examine segmental fat accumulation patterns by sex and ethnicity using international datasets. An amalgamated and cross‐calibrated dataset of dual x‐ray absorptiometry (DXA)‐measured variables compiled segmental mass for bone mineral content (BMC), lean mass (LM), and fat mass (FM) for each participant; percentage of segment fat (PSF) was calculated as PSFsegment = (FMsegment/(BMCsegment + LMsegment + FMsegment)) × 100. A total of 30 587 adults (N = 16 490 females) from 13 datasets were included. A regression model was used to examine differences in regional fat mass and PSF. All populations followed the same segmental fat mass accumulation in the ascending order with statistical significance (arms < legs < trunk), except for Hispanic/Latinx males (arms < [legs = trunk]). Relative fat accumulation patterns differed between those with greater PSF in the appendages (Arab, Mexican, Asian, Black, American Caucasian, European Caucasian, and Australasian Caucasian females; Black males) and those with greater PSF in the trunk (Mexican, Asian, American Caucasian, European Caucasian, and Australasian Caucasian males). Greater absolute and relative fat accumulation in the trunk could place males of most ethnicities in this study at a higher risk of visceral fat deposition and associated co‐morbidities. [ABSTRACT FROM AUTHOR]

This study extended initial observations that indicated the potential of dual-photon absorptiometry (DPA) to measure total-body bone mineral (TBBM) and fat in vivo. DPA-derived TBBM and fat were compared with established methods in 13 subjects (aged 24- 94 y) who underwent measurement of body density (Db), total-body water (TBW), potassium (TBK), calcium (TBCa, delayed-γ neutron activation), and nitrogen (prompt-γ neutron activation). TBBM was highly correlated with TBCa (r = 0.95, p < 0.00 1) and the slope of TBCa vs TBBM (0.34) was similar to Ca content of ashed skeleton (0.34-0.38). DPA-measured fat (x ± SD, 16.7 ± 4.9 kg)correlated significantly(r = O.79-0.94;p < 0.01-0.001) with fat established by Db (1 6.3 ± 5.4 kg), TBW (16.0 ± 4.3 kg), TBK (1 7.7 ± 4.6 kg), combined TBW-neutron activation (17.6 ± 5.9 kg), and means of all four methods (16.9 ± 4.8 kg). DPA thus offers a new opportunity to study human skeleton in vivo and to quantify fat by a method independent from the classical assumption that bone represents a fixed fraction of fat-free body mass. [ABSTRACT FROM AUTHOR]

In this article the authors comment that the technique dual energy x-ray absorptiometry (DEXA) should be used with caution in body composition. Topics discussed include its advantages in measurement of total bone mineral on the basis of calcium, hydrogen, oxygen and carbon content, provision of simultaneous measurement of bone mineral, fat and nonbone lean tissue and limitations of DEEXA such as uniform hydration, accuracy of the technique in soft tissues.

Objectives: The scaling of structural components to body size is well studied in mammals, although comparable human observations in a large and diverse sample are lacking. The current study aimed to fill this gap by examining the scaling relationships between total body (TB) and regional bone and skeletal muscle (SM) mass with body size, as defined by stature, in a nationally representative sample of the US population. Methods: Subjects were 17,126 non‐Hispanic (NH) white, NH black, and Mexican American men and women, aged ≥18 years, evaluated in the National Health and Nutrition Examination Survey who had TB and regional bone mineral (BMin) and lean soft tissue (LST) mass measured by dual‐energy X‐ray absorptiometry. BMin and appendicular LST served as surrogate bone and SM mass measures, respectively. The allometric model, BMin or LST = α(height)β, in a logarithmic form was used to generate scaling exponents. Results: The findings were similar across all gender and race groups: body mass scaled to height with powers of ~2.0 (mean β ± SE, 1.94 ± 0.08‐2.29 ± 0.09) while TB and appendicular BMin and appendicular LST scaled to height with consistently larger powers than those for body mass (eg, all P < .05 in NH white men and women); the largest BMin and LST scaling powers to height were observed in the lower extremities. Conclusions: Bone and SM mass, notably those of the lower extremities, increase as proportions of body mass with greater adult height. Metabolic and biomechanical implications emerge from these observations, the first of their kind in a representative adult US population sample. [ABSTRACT FROM AUTHOR]

Body composition measurements from DXA have been available since DXA technology was developed 30 years ago, but are historically underutilized. Recently, there have been rapid developments in body composition assessment including the analysis and publication of representative data for the US, official usage guidance from the International Society for Clinical Densitometry, and development of regional body composition measures with clinical utility. DXA body composition is much more than whole body percent fat. In this paper celebrating 30 years of DXA for body composition, we will review the principles of DXA soft tissue analysis, practical clinical and research applications, and what to look for in the future. [ABSTRACT FROM AUTHOR]

Purpose: Mechanisms in energy balance (EB) regulation may include compensatory changes in energy intake (EI) and metabolic adaption (MA), but information is unavailable in athletes who often change EB components. We aim to investigate EB regulation compensatory mechanisms over one athletic season. Methods: Fifty-seven athletes (39 males/18 females; handball, volleyball, basketball, triathlon, and swimming) were evaluated from the beginning to the competitive phase of the season. Resting and total energy expenditure (REE and TEE, respectively) were assessed by indirect calorimetry and doubly labeled water, respectively, and physical activity energy expenditure was determined as TEE - 0.1(TEE) - REE. Fat mass (FM) and fat-free mass (FFM) were evaluated by dual-energy x-ray absorptiometry and changed body energy stores was determined by 1.0(ΔFFM/Δtime) + 9.5(ΔFM/Δtime). EI was derived as TEE + EB. REE was predicted from baseline FFM, FM, sex, and sports. %MA was calculated as 100(measured REE/predicted REE-1) and MA (kcal) as %MA/100 multiplied by baseline measured REE. Average EI minus average physical activity energy expenditure was computed as a proxy of average energy availability, assuming that a constant nonexercise EE occurred over the season. Results: Body mass increased by 0.8 ± 2.5 kg (P < 0.05), but a large individual variability was found ranging from -6.1 to 5.2 kg. The TEE raise (16.8% ± 11.7%) was compensated by an increase EI change (16.3% ± 12.0%) for the whole group (P < 0.05). MA was found in triathletes, sparing 128 ± 168 kcal⋅d-1, and basketball players, dissipating 168 ± 205 kcal⋅d-1 (P < 0.05). MA was associated (P < 0.05) with EB and energy availability (r = 0.356 and r = 0.0644, respectively). Conclusion: TEE increased over the season without relevant mean changes in weight, suggesting that EI compensation likely occurred. The thrifty or spendthrift phenotypes observed among sports and the demanding workloads these athletes are exposed to highlight the need for sport-specific energy requirements. [ABSTRACT FROM AUTHOR]

Abstract: Several studies have documented relationships between adipose tissue and bone mineral density (BMD); however, the degree to which there are racial differences in this relationship is not known. The purpose of this study was to examine the relationships between abdominal visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) and BMD among white and African American adults. The sample included 330 white women, 328 African American women, 307 white men, and 116 African American men 18–74years of age. Dual-energy X-ray absorptiometry scans were used to measure BMD and computed tomography scans were used to measure abdominal VAT and SAT. Linear regression was used to assess the relationships between abdominal adiposity and BMD and to explore possible sex and race differences in the associations. In the total sample as well as in all sex-by-race groups, VAT and SAT were negatively related to BMD, after adjustment for lean body mass (LBM) and several covariates. The VAT model (including covariates) explained 33.3% of the variance in BMD and the SAT model (including covariates) explained 32.7% of the variance in BMD. Being African American, being male, and having high LBM were all associated with higher BMD. Race and sex interactions were not significant, indicating that the relationships were similar across race and sex groups. In conclusion, BMD was inversely related to abdominal VAT and SAT in white and African American adults after adjustment for LBM. This article is part of a Special Issue entitled: Interactions Between Bone, Adipose Tissue and Metabolism. [Copyright &y& Elsevier]