Background Three-dimensional optical (3DO) body scanning has been proposed for automatic anthropometry. However, conventional measurements fail to capture detailed body shape. More sophisticated shape features could better indicate health status. Objectives The objectives were to predict DXA total and regional body composition, serum lipid and diabetes markers, and functional strength from 3DO body scans using statistical shape modeling. Methods Healthy adults underwent whole-body 3DO and DXA scans, blood tests, and strength assessments in the Shape Up! Adults cross-sectional observational study. Principal component analysis was performed on registered 3DO scans. Stepwise linear regressions were performed to estimate body composition, serum biomarkers, and strength using 3DO principal components (PCs). 3DO model accuracy was compared with simple anthropometric models and precision was compared with DXA. Results This analysis included 407 subjects. Eleven PCs for each sex captured 95% of body shape variance. 3DO body composition accuracy to DXA was: fat mass R2 = 0.88 male, 0.93 female; visceral fat mass R2 = 0.67 male, 0.75 female. 3DO body fat test-retest precision was: root mean squared error = 0.81 kg male, 0.66 kg female. 3DO visceral fat was as precise (%CV = 7.4 for males, 6.8 for females) as DXA (%CV = 6.8 for males, 7.4 for females). Multiple 3DO PCs were significantly correlated with serum HDL cholesterol, triglycerides, glucose, insulin, and HOMA-IR, independent of simple anthropometrics. 3DO PCs improved prediction of isometric knee strength (combined model R2 = 0.67 male, 0.59 female; anthropometrics-only model R2 = 0.34 male, 0.24 female). Conclusions 3DO body shape PCs predict body composition with good accuracy and precision comparable to existing methods. 3DO PCs improve prediction of serum lipid and diabetes markers, and functional strength measurements. The safety and accessibility of 3DO scanning make it appropriate for monitoring individual body composition, and metabolic health and functional strength in epidemiological settings. This trial was registered at clinicaltrials.gov as NCT03637855.

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.

Background/Objectives-Three-dimensional optical (3DO) imaging systems that rapidly and accurately provide body shape and composition information are increasingly available in research and clinical settings. Recently, relatively low cost and space efficient 3DO systems with the ability to report and track individual assessments were introduced to the consumer market for home use. This study critically evaluated the first 3DO imaging device intended for personal operation, the Naked Body Scanner (NBS), against reference methods. Participants/Methods-Circumferences at six standardized anatomic sites were measured with a flexible tape in 90 participants ranging in age (5-74 years), ethnicity, and adiposity. Regression analysis and Bland-Altman plots compared these direct measurements and dual-energy X-ray absorptiometry (DXA) %fat estimates to corresponding NBS values. Method precision was analyzed from duplicate anthropometric and NBS measurements in a subgroup of 51 participants. Results-The NBS exhibited greater variation in test-retest reliability (CV, 0.4%−2.7%) between the six measured anatomic locations when compared to manually measured counterparts (0.2% −0.4%). All six device-derived circumferences correlated with flexible tape references (R 2 s, 0.84-0.97; p < 0.0001). Measurement bias was apparent for three anatomic sites while mean differences were present for five. The NBS's %fat estimates also correlated with DXA results (R 2 =0.73, p < 0.0001) with no significant bias. Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:

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.

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.

Phenotyping adults for excess adiposity and related health risks usually include three body size measurements: height, weight and waist circumference (WC). Height and weight are now widely used as components of the body shape measure, body mass index (BMI, weight/height 2 ), with the height power referred to as the scaling factor, α. At present, WC is usually not adjusted for height or is expressed as WC/height in which α = 1. Although other α values have been proposed, a critical review of these shape measures is lacking. Here, we examine classical pathways by which the scaling exponent for height used in BMI was developed and then apply this strategy to identify the optimum WC index characteristic of adult shape. Our analyses explored anthropometric, body composition and clinically-relevant data from US and Korean National Health and Nutrition Surveys. Our findings provide further support for the WC index of WC/height 0.5 as having the strongest associations with adiposity while having the weakest correlations with height across non-Hispanic white and black, Mexican American and Korean men and women. The WC index, defined as WC/height 0.5 , when combined with BMI, can play an important role when phenotyping adults for excess adiposity and associated health risks in research and clinical settings. KEYWORDS adiposity, allometric analysis, body composition, body shape 1 | INTRODUCTION The search for diagnostic markers of excess adiposity and accompanying health risks is ongoing, with two main screening measures in current use: body mass index (BMI) and waist circumference (WC). 1 Current guidelines for the identification, evaluation and treatment of obesity incorporate both of these respective body shape and size measures as part of patient evaluation protocols. 2 Although the application of BMI (i.e. body weight/height 2 ) is relatively straightforward, less clarity surrounds the most appropriate index for waist circumference that reflects excess adiposity and health risks. Specifically, current obesity and metabolic syndrome guidelines promote the use of absolute waist circumference with sex and ethnicity-specific cut-off values, 3-5 and a large and growing literature advances observations surrounding the waist circumference/height ratio (WHtR) 6 or other similar waist circumference-stature ratios. 7,8 Should WC be adjusted for height (Ht)? If so, what is the optimum value of α in the index WC/Ht α ? The value of α in the WHtR is 1.0, and α in BMI (i.e. the height 'power' term) is 2.0. Over the past several years, our group has examined aspects of these questions 9-15 ; although there remains a specific need to clarify if and how to adjust waist circumference for between-individual differences in stature.

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.

Background: Previous studies link tall stature with a reduced ischemic stroke risk. One theory posits that tall people have larger cerebral artery lumens and therefore have a lower plaque occlusion risk than those who are short. Previous studies have not critically evaluated the associations between height and cerebral artery structure independent of confounding factors. Methods: The hypothesis linking stature with cerebral artery lumen size was tested in 231 adults by measuring the associations between height and common carotid artery diameter (CCAD) and intima–media thickness (IMT) after controlling for recognized vascular influencing factors (e.g., adiposity, blood pressure, plasma lipids, etc.). Results: Height remained a significant CCAD predictor across all developed multiple regression models. These models predict a ~0.03 mm increase in CCAD for each 1-cm increase in height in this sample. This magnitude of CCAD increase with height represents over a 60% enlargement of the artery’s lumen area across adults varying in stature from short (150 cm) to tall (200 cm). By contrast, IMT was non-significantly correlated with height across all developed regression models. Conclusions: People who are tall have a larger absolute CCAD than people who are short, while IMT is independent of stature. These observations potentially add to the growing cardiovascular literature aimed at explaining the lower risk of ischemic strokes in tall people.