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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]

Background: The metabolic load‐capacity index (LCI), which represents the ratio of adipose to skeletal muscle tissue‐containing compartments, is potentially associated with cardiometabolic diseases. Objectives: To examine the associations between the LCI and cardiometabolic risk factors in children and youth with obesity. Methods: This is a cross‐sectional study including 10–18 years‐old participants with a BMI of ≥95th. LCI by air‐displacement plethysmography (ADP) was calculated as fat mass divided by fat‐free mass, and LCI by ultrasound (US) as subcutaneous adipose tissue divided by skeletal muscle thickness. Sex‐specific medians stratified participants into high versus low LCI. Single (inflammation, insulin resistance, dyslipidemia and hypertension) and clustered cardiometabolic risk factors were evaluated. Linear and logistic regression models tested the associations between these variables, adjusted for sexual maturation. Results: Thirty‐nine participants (43.6% males; 59% mid‐late puberty) aged 12.5 (IQR: 11.1–13.5) years were included. LCI by ADP was positively associated with markers of inflammation and dyslipidemia; having a higher LCI predicted dyslipidemia in logistic regression. Similarly, LCI by US was positively associated with markers of dyslipidemia and blood pressure. In mid‐late pubertal participants, LCI by US was positively associated with markers of insulin resistance and inflammation. Conclusions: Participants with unfavourable cardiometabolic profile had higher LCI, suggesting its potential use for predicting and monitoring cardiometabolic health in clinical settings. [ABSTRACT FROM AUTHOR]

Background: The Global Leadership Initiative on Malnutrition (GLIM) approach to malnutrition diagnosis is based on assessment of three phenotypic (weight loss, low body mass index, and reduced skeletal muscle mass) and two etiologic (reduced food intake/assimilation and disease burden/inflammation) criteria, with diagnosis confirmed by fulfillment of any combination of at least one phenotypic and at least one etiologic criterion. The original GLIM description provided limited guidance regarding assessment of inflammation, and this has been a factor impeding further implementation of the GLIM criteria. We now seek to provide practical guidance for assessment of inflammation. Methods: A GLIM‐constituted working group with 36 participants developed consensus‐based guidance through a modified Delphi review. A multiround review and revision process served to develop seven guidance statements. Results: The final round of review was highly favorable, with 99% overall "agree" or "strongly agree" responses. The presence of acute or chronic disease, infection, or injury that is usually associated with inflammatory activity may be used to fulfill the GLIM disease burden/inflammation criterion, without the need for laboratory confirmation. However, we recommend that recognition of underlying medical conditions commonly associated with inflammation be supported by C‐reactive protein (CRP) measurements when the contribution of inflammatory components is uncertain. Interpretation of CRP requires that consideration be given to the method, reference values, and units (milligrams per deciliter or milligram per liter) for the clinical laboratory that is being used. Conclusion: Confirmation of inflammation should be guided by clinical judgment based on underlying diagnosis or condition, clinical signs, or CRP. [ABSTRACT FROM AUTHOR]

Objective: This study's objective was to develop models predicting the relative reduction in skeletal muscle (SM) mass during periods of voluntary calorie restriction (CR) and to validate model predictions in longitudinally monitored samples. Methods: The model development group included healthy nonexercising adults (n = 897) who had whole‐body SM mass measured with magnetic resonance imaging. Model predictions of relative SM changes with CR were evaluated in two longitudinal studies, one 12 to 14 weeks in duration (n = 74) and the other 12 months in duration (n = 26). Results: A series of SM prediction models were developed in a sample of 415 males and 482 females. Model‐predicted changes in SM mass relative to changes in body weight (i.e., ΔSM/Δbody weight) with a representative model were (mean ± SE) 0.26 ± 0.013 in males and 0.14 ± 0.007 in females (sex difference, p < 0.001). The actual mean proportions of weight loss as SM in the longitudinal studies were 0.23 ± 0.02/0.20 ± 0.06 in males and 0.10 ± 0.02/0.17 ± 0.03 in females, similar to model‐predicted values. Conclusions: Nonelderly males and females with overweight and obesity experience respective reductions in SM mass with voluntary CR in the absence of a structured exercise program of about 2 to 2.5 kg and 1 to 1.5 kg per 10‐kg weight loss, respectively. These estimates are predicted to be influenced by interactions between age and body mass index in males, a hypothesis that needs future testing. [ABSTRACT FROM AUTHOR]

Lack of efficacy of weight loss(WL) interventions is attributed in-part to low adherence to dietary/physical activity(PA) recommendations. However, some compensation may occur in PA as a response to energy restriction such as a decrease in non-exercise PA(NEPA) or non-exercise activity thermogenesis(NEAT). The current study aim was (1) to investigate whether adaptive thermogenesis(AT) in NEAT occurs after WL, and (2) to understand the associations of these compensations with WL. Ninety-four former athletes [mean±SD, age: 43.0±9.4y, BMI: 31.1±4.3 kg/m2, 34.0% female] were recruited and randomly assigned to intervention or control groups (IG, CG). The IG underwent a one-year lifestyle WL-intervention; no treatments were administered to the CG. PA was measured using accelerometery and NEAT was predicted with a model including sample baseline characteristics. AT was calculated as measuredNEAT4mo/12mo(kcal/d)–predictedNEAT4mo/12mo(kcal/d)-measuredNEATbaseline(kcal/d)–predictedNEATbaseline(kcal/d). Dual-energy x-ray absorptiometry was used to assess fat-free mass and fat mass. No differences were found in the IG for NEAT or NEPA after WL. Considering mean values, AT was not found for either group. The SD of individual response (SDIR) for AT was −2(4-months) and 24(12-months) (smallest worthwhile change = 87kcal/d), suggesting that the interindividual variability regarding AT in NEAT is not relevant and the variability in this outcome might reflect a large within-subject variability and/or a large degree of random measurement error. No associations were found between AT in NEAT and changes in body composition. Further studies are needed to clarify the mechanisms behind the large variability in AT observed in NEAT and related changes in NEPA to better implement lifestyle-induced WL interventions. Highlights No significant differences were found for non-exercise activity thermogenesis (NEAT) or non-exercise physical activity (NEPA) after the weight loss (WL) intervention; Although a large variability was found for NEAT and NEPA, the interindividual variability regarding these outcomes is not relevant. The variability in these outcomes might reflect a large within-subject variability and/or a large degree of random measurement error; Although no energy conservation was observed in NEAT after moderate WL (mean values), further studies are needed to clarify the mechanisms behind the large variability in adaptive thermogenesis observed in NEAT and related changes in NEPA to better implement lifestyle-induced WL interventions. Trial registration: ClinicalTrials.gov identifier: NCT03031951. [ABSTRACT FROM AUTHOR]

In some cases, it is not possible to either experimentally determine I V i SB I d i sb /TBW or calculate it, so in this case population data ranges could be used to give the best estimation for I V i SB I d i sb /TBW for an individual. Using a previously collected data set of TBW measured using isotope dilution we have been able to calculate the I V i SB I d i sb of everyone in the study [[5]] by converting TBW to I V i SB I d i sb using Equation 2. [Extracted from the article]

Adaptive thermogenesis (AT) is the mass‐independent decrease in energy expenditure (EE) in response to caloric restriction and weight loss. AT becomes manifest throughout all periods of weight loss and persists during subsequent weight maintenance. AT occurs in resting and nonresting energy expenditure as ATREE and ATNREE, respectively. ATREE appears in different phases of weight loss, each with likely different mechanisms. By contrast, during weight maintenance after weight loss, ATNREE exceeds ATREE. Some of the mechanisms of AT are known now and others are not. Future studies on AT will need an appropriate conceptual framework within which to design experiments and interpret results. [ABSTRACT FROM AUTHOR]

Physical performance decrements observed during multi‐stressor military operations may be attributed, in part, to cellular membrane dysfunction, which is quantifiable using phase angle (PhA) derived from bioelectrical impedance analysis (BIA). Positive relationships between PhA and performance have been previously reported in cross‐sectional studies and following longitudinal exercise training programs, but whether changes in PhA are indicative of acute decrements in performance during military operations is unknown. Data from the Optimizing Performance for Soldiers II study, a clinical trial examining the effects of exogenous testosterone administration on body composition and performance during military stress, was used to evaluate changes in PhA and their associations with physical performance. Recreationally active, healthy males (n = 34; 26.6 ± 4.3 years; 77.9 ± 12.4 kg) were randomized to receive testosterone undecanoate or placebo before a 20‐day simulated military operation, which was followed by a 23‐day recovery period. PhA of the whole‐body (Whole) and legs (Legs) and physical performance were measured before (PRE) and after (POST) the simulated military operation as well as in recovery (REC). Independent of treatment, PhAWhole and PhALegs decreased from PRE to POST (p < 0.001), and PhALegs, but not PhAWhole, remained lower at REC than PRE. PhAWhole at PRE and REC were associated with vertical jump height and Wingate peak power (p < 0.001–0.050), and PhAWhole at PRE was also associated with 3‐RM deadlift mass (p = 0.006). However, PhA at POST and changes in PhA from PRE to POST were not correlated with any performance measure (p > 0.05). Additionally, PhA was not associated with aerobic performance at any timepoint. In conclusion, reduced PhA from PRE to POST provides indirect evidence of cellular membrane disruption. Associations between PhA and strength and power were only evident at PRE and REC, suggesting PhA may be a useful indicator of strength and power, but not aerobic capacity, in non‐stressed conditions, and not a reliable indicator of physical performance during severe physiological stress. [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: A previous report from our group identified directionally unfavorable dietary and lifestyle behavior trends in longitudinally monitored children and adolescents with obesity early in the COVID‐19 pandemic lockdown. The current study aimed at extending these previous observations in youths with obesity on the dietary and lifestyle behavioral consequences of the extended COVID‐19 lockdown in Verona, Italy. Methods: The sample included 32 children and adolescents with obesity participating in the longitudinal OBELIX study. Diet and lifestyle information were collected pre‐pandemic, 3 weeks into the national lockdown, and 9 months later when home confinement continued to be mandatory. Changes in outcomes over the study time points were evaluated for significance using repeated‐measures ANOVA and post‐hoc pairwise t‐tests with Bonferroni corrections. Results: As previously reported, meals/day, fried potato intake, and red meat ingestion increased significantly (p < 0.001) during the initial lockdown. Sleep time and screen time increased and sports participation decreased significantly (p < 0.001) during the initial lockdown. These changes in health behaviors remained significantly different from baseline at the second lockdown assessment, with the exception sleep time returned to baseline levels. Conclusions: Unfavorable diet and lifestyle behavioral changes in response to the initial COVID‐19 lockdown in children and adolescents with obesity have largely been sustained over the course of the pandemic. There is an urgent need to intervene on these behaviors to prevent further deleterious effects on long‐term child health; access to weight management care is critically important for these children. In addition to intervening on these behaviors, our findings should help to inform ongoing lockdown policies. [ABSTRACT FROM AUTHOR]

Objective: This study examined whether body shape and composition obtained by three-dimensional optical (3DO) scanning improved the prediction of metabolic syndrome (MetS) prevalence compared with BMI and demographics.Methods: A diverse ambulatory adult population underwent whole-body 3DO scanning, blood tests, manual anthropometrics, and blood pressure assessment in the Shape Up! Adults study. MetS prevalence was evaluated based on 2005 National Cholesterol Education Program criteria, and prediction of MetS involved logistic regression to assess (1) BMI, (2) demographics-adjusted BMI, (3) 85 3DO anthropometry and body composition measures, and (4) BMI + 3DO + demographics models. Receiver operating characteristic area under the curve (AUC) values were generated for each predictive model.Results: A total of 501 participants (280 female) were recruited, with 87 meeting the criteria for MetS. Compared with the BMI model (AUC = 0.819), inclusion of age, sex, and race increased the AUC to 0.861, and inclusion of 3DO measures further increased the AUC to 0.917. The overall integrated discrimination improvement between the 3DO + demographics and the BMI model was 0.290 (p < 0.0001) with a net reclassification improvement of 0.214 (p < 0.0001).Conclusions: Body shape measures from an accessible 3DO scan, adjusted for demographics, predicted MetS better than demographics and/or BMI alone. Risk classification in this population increased by 29% when using 3DO scanning. [ABSTRACT FROM AUTHOR]

The Global Leadership Initiative on Malnutrition (GLIM) provides consensus criteria for the diagnosis of malnutrition that can be widely applied. The GLIM approach is based on the assessment of three phenotypic (weight loss, low body mass index, and low skeletal muscle mass) and two etiologic (low food intake and presence of disease with systemic inflammation) criteria, with diagnosis confirmed by any combination of one phenotypic and one etiologic criterion fulfilled. Assessment of muscle mass is less commonly performed than other phenotypic malnutrition criteria, and its interpretation may be less straightforward, particularly in settings that lack access to skilled clinical nutrition practitioners and/or to body composition methodologies. In order to promote the widespread assessment of skeletal muscle mass as an integral part of the GLIM diagnosis of malnutrition, the GLIM consortium appointed a working group to provide consensus‐based guidance on assessment of skeletal muscle mass. When such methods and skills are available, quantitative assessment of muscle mass should be measured or estimated using dual‐energy x‐ray absorptiometry, computerized tomography, or bioelectrical impedance analysis. For settings where these resources are not available, then the use of anthropometric measures and physical examination are also endorsed. Validated ethnic‐ and sex‐specific cutoff values for each measurement and tool are recommended when available. Measurement of skeletal muscle function is not advised as surrogate measurement of muscle mass. However, once malnutrition is diagnosed, skeletal muscle function should be investigated as a relevant component of sarcopenia and for complete nutrition assessment of persons with malnutrition. [ABSTRACT FROM AUTHOR]

There are an increasing number of individuals undergoing gender‐affirming hormonal treatment (GAHT) to treat gender dysphoria. Current forensic alcohol calculations require knowledge of the sex of the individual, but this may disadvantage trans people as research has demonstrated that there are physiological changes in individuals who are undergoing GAHT. Using previously published studies on total body water (TBW) in cis individuals, and the known changes in lean body mass and hematocrit in trans individuals, it is possible to estimate TBW in trans individuals and compare them to those cis equation estimations. When using these revised rubrics, we determined that for trans women the use of the cis male anthropometric TBW equation only gives a small underestimation of TBW (0.9%) compared to the underestimation of TBW using the cis female TBW equation (−17.7%). For trans men, the use of the cis female TBW equation gives the largest disadvantage, underestimating TBW by −10.8% compared to the cis male TBW equation, that overestimates TBW by 6.6%. For this reason, we recommend that if the sex at birth of an individual is not known or disclosed, any forensic alcohol calculations in a forensic alcohol reports are made assuming that the gender declared by the individual is their sex at birth. Further research to develop validated anthropometric TBW equations are urgently needed as to not disadvantage trans people when forensic alcohol calculations are carried out. [ABSTRACT FROM AUTHOR]

Objective: Three‐dimensional (3D) imaging systems are increasingly being used in health care settings for quantifying body size and shape. The potential exists to provide similar phenotyping capabilities outside of professional settings using smartphone applications (apps). The current study aim was to compare waist, hip, upper arm, and midthigh circumference measurements acquired by a free downloadable app (MeThreeSixty; Size Stream, Cary, North Carolina) and a conventional 20‐camera 3D system (SS20; Size Stream) with those measured with a flexible tape at the same anatomic sites. Methods: Fifty‐nine adults were scanned with the app and SS20; the same software was used to generate circumference estimates from device‐acquired object files that were then compared with reference tape measurements. Results: The app and SS20 had similar coefficients of variation that were minimally larger than those by the tape (e.g., waist, 0.93%, 0.87%, and 0.06%). Correlations of the app and of SS20 with tape circumferences were all strong (p < 0.001) and similar in magnitude (R2s: 0.72‐0.93 and 0.78‐0.95, respectively); minimally significant (p < 0.05 to p < 0.01) bias was present between both imaging approaches and some tape measurements. Conclusion: These proof‐of‐concept observations combined with ubiquitous smartphone availability create the possibility of phenotyping adult body size and shape, with important clinical and research implications, on a global scale. [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]

Objective: Mathematical equations that predict resting energy expenditure (REE) are widely used to derive calorie prescriptions during weight‐loss interventions. Although such equations are known to introduce group‐ and individual‐level error into REE prediction, their validity has largely been assessed in weight‐stable populations. Therefore, this study sought to characterize how weight change affects the validity of commonly used REE predictive models throughout a 12‐month weight‐loss intervention. Methods: Changes in predictive error of four models (Mifflin‐St‐Jeor, Harris‐Benedict, Owen, and World Health Organization/Food and Agriculture) were assessed at 1‐, 6‐, and 12‐month time points in adults (n = 66, 76% female, aged 18‐55 years, BMI = 27‐45 kg/m2) enrolled in a randomized clinical weight‐loss trial. Results: All equations experienced significant negative shifts in bias (measured − predicted REE) toward overprediction from baseline to 1 month (p < 0.05). Three equations showed reversal of bias in the positive direction (toward underprediction) from baseline to 12 months (p < 0.05). Early changes in bias were correlated with decreased fat‐free mass (p ≤ 0.01). Conclusions: Changes in body composition and mass during a 12‐month weight‐loss intervention significantly affected REE predictive error in adults with overweight and obesity. Weight history should be considered when using mathematical models to predict REE during periods of weight fluctuation. [ABSTRACT FROM AUTHOR]

Introduction: Muscle fibers are lost and replaced by fat‐ and fibrous‐tissue infiltration during aging. This process decreases muscle quality and influences tissue appearance on ultrasound images over time. Increased muscle "echogenicity" represents changes caused by fat‐ and fibrous‐tissue infiltration and can be quantified with recently developed software. Objective: To investigate skeletal muscle quality through echogenicity, estimates according to participant's body mass index (BMI) and age were taken. Methods: This was a cross‐sectional study performed at the Pennington Biomedical Research Center, Baton Rouge, Louisiana with 117 participants (57 men and 60 women), with mean age (±SD) 38.9 ± 17.0 years and BMI 28.6 ± 6.2 kg/m². All participants were examined by ultrasound (LOGIQ GE Healthcare), using a 5.0‐MHz linear transducer. Participants had muscle thickness measured by ultrasound at 4 anatomic locations (biceps and triceps brachial, femoral quadriceps, and calf triceps). Echogenicity was analyzed with specific software (Pixel Health) that evaluated the image in gray scale. Results: According to BMI, 41% of participants were obese. There was a positive correlation between age and thigh‐muscle echogenicity (rp = 0.534, P <.0001) and a negative correlation between thigh‐muscle echogenicity and thickness (rp = –0.395, P <.0001). There was high muscle echogenicity in participants with overweight and obesity aged 50 years or older (P <.05). Conclusion: Older age and higher BMI were associated with stronger echogenicity signals and smaller muscle thickness. People with overweight, obesity, and/or older than 50 years old have reduced muscle quality with smaller muscle thickness, as observed with ultrasound. [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]

Objectives: Body surface area (SA) is a widely used physical measure incorporated into multiple thermophysiology and evolutionary biology models currently estimated in humans either with empirical prediction equations or costly whole‐body laser imaging systems. The introduction of low‐cost 3D scanners provides a new opportunity to quantify total body (TB) and regional SA, although a critical question prevails: can these devices acquire the quality of depth information and process this initial data to form a mesh that has the fidelity needed to generate accurate SA estimates? Materials and methods: This question was answered by comparing SA estimates calculated using images from four commercial 3D scanners in 108 adults to corresponding estimates acquired with a whole‐body laser system. This was accomplished by processing initial mesh data from all devices, including the laser system, with the same universal software adapted specifically for repairing mesh gaps, identifying landmarks, and generating SA measurements. Results: TB SA measured on all four 3D scanners was highly correlated with corresponding laser system estimates (R2s, 0.98–0.99; all p < 0.001) with some small but significant mean differences (−0.19 to 0.06 m2); root‐mean square errors (RMSEs) were small (0.02–0.03 m2); and significant bias was present for one device. Qualitatively similar results (e.g., R2s, 0.78–0.95; mean Δs, −0.05 to 0.02 m2; RMSEs, 0.01–0.03 m2) were present for trunk, arm, and leg SA comparisons. Discussion: The current study observations demonstrate that low‐cost and practical 3D optical scanners are capable of accurately quantifying TB and regional SA, thus opening new opportunities for evaluating human phenotypes and related physiological characteristics. [ABSTRACT FROM AUTHOR]

We aimed to validate bioelectrical impedance spectroscopy (BIS), compared with tracer dilution measurements, for assessing total body water (TBW), intracellular water (ICW), and extracellular water (ECW) in athletes differing in hydration status. A total of 201 athletes participated. Reference TBW and ECW were determined by deuterium and bromide dilution methods, respectively; ICW was calculated as TBW‐ECW. Water compartments were estimated by BIS. Urine specific gravity (USG) classified athletes into well‐hydrated (WH) (USG < 1.023), euhydrated (EH) (USG:1.024–1.026), and dehydrated (DH) (USG>1.027). No significant differences were found between BIS and the reference methods for WH, EH, and DH athletes for TBW, ICW nor ECW (p>0.05). Concordance of TBW and its compartments by method was significant (p < 0.001) with coefficients of determination ranging by hydration classification [EH:52–96%;DH:56–98%;WH:71–96%]. Bland‐Altman analyses showed no trend for TBW and its compartments with the exception of ICW in the WH athletes. The 95% confidence BIS intervals for the WH group ranged from −3.08 to 2.68 kg for TBW, −4.28 to 4.14 kg for ICW, and −3.29 to 3.02 kg for ECW. For the EH athletes, the 95% confidence intervals ranged from −2.78 to 2.24 kg for TBW, −4.10 to 3.94 kg for ICW, and −3.44 to 3.06 kg for ECW. In DH group, TBW ranged between −1.99 and 2.01 kg, ICW between −3.78 and 6.34 kg, and ECW between −6.22 and 3.74 kg. These findings show that BIS is useful at a group level in assessing water compartments in athletes differing in hydration status. However, the usefulness of BIS is limited at an individual level, especially in dehydrated athletes. [ABSTRACT FROM AUTHOR]

In this Perspective Statement from The Obesity Society, the Clinical Committee discusses the use of weight loss supplements in the United States and the lack of regulatory oversight and rigorous testing of their efficacy and safety. A number of products and services claiming to promote weight loss are directly marketed to individuals with obesity and those wanting to lose weight. These products are not regulated as "drugs" by the Federal Drug Administration but, rather, are treated as dietary supplements if ingredients are "generally regarded as safe," requiring little or no testing to show efficacy or safety. Health care providers should be aware of the lack of evidence and deficiencies in regulatory oversight of dietary supplements marketed for weight loss. Regulatory authorities should protect consumers by ensuring accurate and safe marketing claims and preventing promotion of unproven and potentially unsafe products and claims. [ABSTRACT FROM AUTHOR]

Objective: Dietary supplements and alternative therapies are commercialized as a panacea for obesity/weight gain as a result of the minimal regulatory requirements in demonstrating efficacy. These products may indirectly undermine the value of guideline-driven obesity treatments. Included in this study is a systematic review of the literature of purported dietary supplements and alternative therapies for weight loss.Methods: A systematic review was conducted to evaluate the efficacy of dietary supplements and alternative therapies for weight loss in participants aged ≥18 years. Searches of Medline (PubMed), Cochrane Library, Web of Science, CINAHL, and Embase (Ovid) were conducted. Risk of bias and results were summarized qualitatively.Results: Of the 20,504 citations retrieved in the database search, 1,743 full-text articles were reviewed, 315 of which were randomized controlled trials evaluating the efficacy of 14 purported dietary supplements, therapies, or a combination thereof. Risk of bias and sufficiency of data varied widely. Few studies (n = 52 [16.5%]) were classified as low risk and sufficient to support efficacy. Of these, only 16 (31%) noted significant pre/post intergroup differences in weight (range: 0.3-4.93 kg).Conclusions: Dietary supplements and alternative therapies for weight loss have a limited high-quality evidence base of efficacy. Practitioners and patients should be aware of the scientific evidence of claims before recommending use. [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]

Summary Beyond obesity, excess levels of visceral adipose tissue (VAT) significantly contribute to the risk of developing metabolic syndrome (MetS), although thresholds for increased risk vary based on population, regions of interest, and units of measure employed. We sought to determine whether a common threshold exists that is indicative of heightened MetS risk across all populations, accounting for sex, age, BMI, and race/ethnicity. A systematic literature review was conducted in September 2023, presenting threshold values for elevated MetS risk. Standardization equations harmonized the results from DXA, CT, and MRI systems to facilitate a comparison of threshold variations across studies. A total of 52 papers were identified. No single threshold could accurately indicate elevated risk for both males and females across varying BMI, race/ethnicity, and age groups. Thresholds fluctuated from 70 to 165.9 cm2, with reported values consistently lower in females. Generally, premenopausal females and younger adults manifested elevated risks at lower VAT compared to their older counterparts. Notably, Asian populations exhibited elevated risks at lower VAT areas (70–136 cm2) compared to Caucasian populations (85.6–165.9 cm2). All considered studies reported associations of VAT without accommodating covariates. No single VAT area threshold for elevated MetS risk was discernible post‐harmonization by technology, units of measure, and region of interest. This review summarizes available evidence for MetS risk assessment in clinical practice. Further exploration of demographic‐specific interactions between VAT area and other risk factors is imperative to comprehensively delineate overarching MetS risk. [ABSTRACT FROM AUTHOR]

The basis of heat generated by the human body has been a source of speculation and research for more than 2,000 years. Basal heat production, now usually referred to as resting energy expenditure (REE), is currently recognized as deriving from biochemical reactions at subcellular and cellular levels that are expressed in the energy expended by the body's 78 organs and tissues. These organs and tissues, and the 11 systems to which they belong, influence body size and shape. Connecting these subcellular-/cellular-level reactions to organs and tissues, and then on to body size and shape, provides a comprehensive understanding of individual differences in REE, a contemporary topic of interest in obesity research and clinical practice. This review critically examines these linkages, their association with widely used statistical and physiological REE prediction formulas, and often-unappreciated aspects of measuring basal heat production in humans. [ABSTRACT FROM AUTHOR]

Background/Objective: Digital anthropometric (DA) assessments are increasingly being administered with three‐dimensional (3D) optical devices in clinical settings that manage patients with obesity and related metabolic disorders. However, anatomic measurement sites are not standardized across manufacturers, precluding use of published reference values and pooling of data across research centers. Subjects/Methods: This study aimed to develop universal 3D analysis software by applying novel programming strategies capable of producing device‐independent DA estimates that agree with conventional anthropometric (CA) measurements made at well‐defined anatomic sites. A series of technical issues related to proprietary methods of 3D geometrical reconstruction and image analysis were addressed in developing major software components. To evaluate software accuracy, comparisons were made to CA circumference measurements made with a flexible tape at eleven standard anatomic sites in up to 35 adults scanned with three different commercial 3D optical devices. Results: Overall, group mean CA and DA values across the three systems were in good agreement, with ∼2 cm systematic differences; CA and DA estimates were highly correlated (all p‐values <0.01); root‐mean square errors were low (0.51–3.27 cm); and CA‐DA bias tended to be small, but significant depending on anatomic site and device. Conclusions: Availability of this software, with future refinements, has the potential to facilitate clinical applications and creation of large pooled uniform anthropometric databases. [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]

Purpose: Total 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. Methods: Duplicate 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. Results: Results were reported on a held‐out set. Body composition prediction achieved R2s 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. Conclusion: Total 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. [ABSTRACT FROM AUTHOR]

Summary: Accurate measurement of body composition is required to improve health outcomes in children and adolescents with overweight or obesity. This systematic review aimed to summarize the reliability and validity of field and laboratory body composition techniques employed in pediatric obesity studies to facilitate technique selection for research and clinical practice implementation. A systematic search in MEDLINE (via PubMed), EMBASE, CINAHL, and SPORTDiscus from inception up to December 2019 was conducted, using a combination of the following concepts: body composition, pediatric overweight/obesity, and reliability/validity. The search strategy resulted in 66 eligible articles reporting reliability (19.7%), agreement between body composition techniques cross sectionally (80.3%), and/or diagnostic test accuracy (10.6%) in children and adolescents with overweight or obesity (mean age range = 7.0–16.5 years). Skinfolds, air‐displacement plethysmography (ADP), dual‐energy X‐ray absorptiometry (DXA), and ultrasound presented as reliable techniques. DXA, ADP, and isotope dilution showed similar and the best agreement with reference standards. Compared with these laboratory techniques, the validity of estimating body composition by anthropometric equations, skinfolds, and BIA was inferior. In conclusion, the assessment of body composition by laboratory techniques cannot be replaced by field techniques due to introduction of measurement errors, which potentially conceal actual changes in body components. [ABSTRACT FROM AUTHOR]

Summary: Body composition estimates are widely used in clinical research and field studies as measures of energy‐nutrient balance, functionality and health. Despite their broad relevance and multiple applications, important gaps remain in techniques available for accurately and precisely quantifying body composition in infants and children from birth through 5 years. Identifying these gaps and highlighting research needs in this age group were the topics of a National Institutes of Health workshop held in Bethesda, MD, USA, 30–31 May 2019. Experts reviewed available methods (multicompartment models, air‐displacement plethysmography, dual‐energy X‐ray absorptiometry, weight‐length and height indices, bioimpedance analysis, anthropometry‐skinfold techniques, quantitative magnetic resonance, optical imaging, omics and D3‐creatine dilution), their limitations in this age range and high priority research needs. A summary of their individual and collective workshop deliberations is provided in this report. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to test the hypothesis that youths with obesity, when removed from structured school activities and confined to their homes during the coronavirus disease 2019 pandemic, will display unfavorable trends in lifestyle behaviors.Methods: The sample included 41 children and adolescents with obesity participating in a longitudinal observational study located in Verona, Italy. Lifestyle information including diet, activity, and sleep behaviors was collected at baseline and 3 weeks into the national lockdown during which home confinement was mandatory. Changes in outcomes over the two study time points were evaluated for significance using paired t tests.Results: There were no changes in reported vegetable intake; fruit intake increased (P = 0.055) during the lockdown. By contrast, potato chip, red meat, and sugary drink intakes increased significantly during the lockdown (P value range, 0.005 to < 0.001). Time spent in sports activities decreased by 2.30 (SD 4.60) h/wk (P = 0.003), and sleep time increased by 0.65 (SD 1.29) h/d (P = 0.003). Screen time increased by 4.85 (SD 2.40) h/d (P < 0.001).Conclusions: Recognizing these adverse collateral effects of the coronavirus disease 2019 pandemic lockdown is critical in avoiding depreciation of weight control efforts among youths afflicted with excess adiposity. Depending on duration, these untoward lockdown effects may have a lasting impact on a child's or adolescent's adult adiposity level. [ABSTRACT FROM AUTHOR]

Bioelectrical impedance (BI) has been widely used but clarification about the behaviour of raw BI measurements under specific athletic conditions is required. Thus, we determined the usefulness of raw BI measures in tracking body fluids changes during the preparation period prior to competition in elite Judo athletes. At baseline (weight stability), 27 male athletes were evaluated (23.2 ± 2.8y) and again 1–3 days before competition (∼1–2 months apart). Athletes were free to gain/lost weight based upon specific competition needs. Using dilution techniques (deuterium and bromide), total-body water (TBW) and extracellular water were estimated, and intracellular water calculated as TBW minus extracellular water. Body fluid distribution was determined as Extra-to-/Intracellular water (E/I). Fat and fat-free mass (FFM) was assessed by dual-energy x-ray absorptiometry. Resistance, reactance, and phase angle (PhA) were obtained from bioelectrical impedance spectroscopy (50-kHz frequency). No differences in raw BI measures were observed between athletes that lost (N = 17) or gain weight (N = 10), except for fat, FFM, extracellular water, and EI (p < 0.05). After adjusting for FFM and height, resistance explained TBW (β = −0.047, p = 0.002) and extracelular water (β = −0.025, p = 0.001). Reactance explained ECW (β = −0.098, p = 0.004) and EI (β = −0.004, p = 0.006), while PhA predicted TBW (β = 1.609, p = 0.047), ICW (β = 1.899, p = 0.001) and EI (β = −0.056, p = 0.001). Regardless of body composition changes, athletes who increase reactance and resistance reduced extracellular water and body fluids while those who raised PhA increased intracellular water. Judo athletes who reduced weight, decreased FFM but cellular health was not compromised, as PhA remained stable and, consequently, cell hydration. [ABSTRACT FROM AUTHOR]

Objectives: Recent reports on body regional mass scalings to height have advanced understanding differences in adult heights. These studies resulted in conjectures on how regional lengths and circumferences may scale to height. We provide evidence for these conjectures by analyzing a large sample of regional limb, trunk, chest, and head lengths and circumferences in a large sample of US Army basic training recruits. Methods: Participants consisted of 10 271 males and 2760 females ages 17 to 21 years old who reported for basic training at Fort Jackson, SC. Participants were imaged by a three‐dimensional (3D) body scanner for uniform sizing which yielded 159 body measurements of total mass, lengths and circumferences at regional sites of arms, legs, trunk, chest, and head. The allometric model, Body Measurei=αiHβi was applied to derive scaling exponents which were applied to estimate regional mass scalings. Results: Body mass scaled to height with powers of ∼2.0 (mean β ± SE, 1.98 ± 0.04, 1.93 ± 0.06). Arm and leg lengths scaled to exponents larger than 1.0 and head height and circumferences at regional sites scaled to exponents smaller than 1.0. The leg, arm, and trunk mass scaling exponents were all above 2.0. Head mass scaled to powers smaller than 2.0. Conclusions: The 3D scanner allowed hundreds of anthropometric measurements to be obtained within seconds. The ensuing analysis revealed that greater height yielded disproportional increases in limb lengths, limb mass and trunk mass. These analyses provide evidence that could not be previously measured that further both biomechanical and metabolic conjectures. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to evaluate ertugliflozin in patients with overweight and obesity with type 2 diabetes mellitus.Methods: Data from three placebo-controlled, randomized, Phase 3 studies were pooled. Patients with baseline BMI ≥ 25 (1,377/1,544; 89%) were assessed with a stratification by BMI subgroup.Results: At week 26, reductions from baseline in glycated hemoglobin A1c (HbA1c), fasting plasma glucose, body weight (BW), and systolic blood pressure (SBP) were greater with ertugliflozin versus placebo. For placebo, ertugliflozin 5 mg, and ertugliflozin 15 mg, respectively, least squares mean change was 0.1%, -0.8%, and -0.9% for HbA1c and -1.2 kg, -3.1 kg, and -3.2 kg for BW. HbA1c reductions were consistent across BMI subgroups. For ertugliflozin 5 mg and 15 mg, least squares mean change (placebo adjusted) in absolute BW was -1.4 kg and -1.2 kg for BMI 25 to < 30, -1.8 kg and -1.9 kg for BMI 30 to < 35, and -2.5 kg and -2.9 kg for BMI ≥ 35. Percent BW changes were similar across BMI subgroups. Incidence of adverse events was 52.5%, 44.6%, and 50.1% with placebo, ertugliflozin 5 mg, and ertugliflozin 15 mg, respectively.Conclusions: Meaningful reductions in HbA1c, fasting plasma glucose, BW, and SBP were observed with ertugliflozin in patients with overweight and obesity with type 2 diabetes mellitus. Ertugliflozin improved HbA1c and SBP and reduced BW across BMI subgroups. Ertugliflozin was generally well tolerated. [ABSTRACT FROM AUTHOR]

Summary: Being able to draw accurate conclusions from childhood obesity trials is important to make advances in reversing the obesity epidemic. However, obesity research sometimes is not conducted or reported to appropriate scientific standards. To constructively draw attention to this issue, we present 10 errors that are commonly committed, illustrate each error with examples from the childhood obesity literature, and follow with suggestions on how to avoid these errors. These errors are as follows: using self‐reported outcomes and teaching to the test; foregoing control groups and risking regression to the mean creating differences over time; changing the goal posts; ignoring clustering in studies that randomize groups of children; following the forking paths, subsetting, p‐hacking, and data dredging; basing conclusions on tests for significant differences from baseline; equating "no statistically significant difference" with "equally effective"; ignoring intervention study results in favor of observational analyses; using one‐sided testing for statistical significance; and stating that effects are clinically significant even though they are not statistically significant. We hope that compiling these errors in one article will serve as the beginning of a checklist to support fidelity in conducting, analyzing, and reporting childhood obesity research. [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]