Emergence of the obesity epidemic: 6-decade visualization with humanoid avatars

The Critical Role of Body Composition Assessment in Advancing Research and Clinical Health Risk Assessment across the Lifespan

Obesity and low muscle mass are major public health concerns, especially in older adults, due to their strong links to cardiovascular disease, cancer, and mortality. Beyond body mass index, body composition metrics including skeletal muscle, fat mass, and visceral adipose tissue offer deeper insights into nutrition and disease risk. These measures are essential for both cross-sectional assessments and longitudinal tracking, providing a clearer picture of health changes over time. Selecting body composition assessment tools requires balancing cost, practicality, accuracy, and data quality. The right tools enhance research, refine clinical assessments, and inform targeted interventions. Aligning methods with specific research or clinical goals improves disease risk stratification and advances personalized treatments. This review highlights the importance of integrating body composition assessment into research and clinical practice, addressing knowledge gaps across diverse populations and emphasizing its potential in advancing precision medicine. It also highlights recent advancements in body composition assessment techniques that warrant consideration when evaluating techniques for a specific application. Future efforts should focus on refining these tools, expanding their accessibility, and developing comprehensive risk models that incorporate body composition alongside behavioral, environmental, and genetic factors to improve disease prediction and prevention strategies.

Assessing the prevalence of obesity in a Russian adult population by six indices and their associations with hypertension, diabetes mellitus and hypercholesterolaemia

The anthropometric index that best predicts cardiometabolic risk remains inconclusive. This study therefore assessed the prevalence of obesity using six indices and compared their associations with obesity-related cardiometabolic disorders. We determined obesity prevalence according to body mass index, waist circumference, waist-to-hip ratio, waist-to-height ratio (WHtR), body fat percentage and fat mass index (FMI) using data from the Know Your Heart study (n = 4495, 35-69 years). The areas under the receiver operating characteristic curves (AUCs) provided predictive values of each index for detecting the presence of hypertension, hypercholesterolaemia and diabetes. Age-standardised obesity prevalence significantly varied according to anthropometric index: from 17.2% (FMI) to 75.8% (WHtR) among men and from 23.6% (FMI) to 65.0% (WHtR) among women. WHtR had the strongest association with hypertension (AUC = 0.784; p < 0.001) and with a combination of disorders (AUC = 0.779; p < 0.001) in women. In women, WHtR also had the largest AUCs for hypercholesterolaemia, in men - for hypertension, diabetes and a combination of disorders, although not all the differences from other obesity indices were significant. WHtR exhibited the closest association between hypertension and a combination of disorders in women and was non-inferior compared to other indices in men.

Accurate prediction of three-dimensional humanoid avatars for anthropometric modeling

OBJECTIVE

To evaluate the hypothesis that anthropometric dimensions derived from a person's manifold-regression predicted three-dimensional (3D) humanoid avatar are accurate when compared to their actual circumference, volume, and surface area measurements acquired with a ground-truth 3D optical imaging method. Avatars predicted using this approach, if accurate with respect to anthropometric dimensions, can serve multiple purposes including patient body composition analysis and metabolic disease risk stratification in clinical settings.

METHODS

Manifold regression 3D avatar prediction equations were developed on a sample of 570 adults who completed 3D optical scans, dual-energy X-ray absorptiometry (DXA), and bioimpedance analysis (BIA) evaluations. A new prospective sample of 84 adults had ground-truth measurements of 6 body circumferences, 7 volumes, and 7 surface areas with a 20-camera 3D reference scanner. 3D humanoid avatars were generated on these participants with manifold regression including age, weight, height, DXA %fat, and BIA impedances as potential predictor variables. Ground-truth and predicted avatar anthropometric dimensions were quantified with the same software.

RESULTS

Following exploratory studies, one manifold prediction model was moved forward for presentation that included age, weight, height, and %fat as covariates. Predicted and ground-truth avatars had similar visual appearances; correlations between predicted and ground-truth anthropometric estimates were all high (R2s, 0.75-0.99; all p < 0.001) with non-significant mean differences except for arm circumferences (%Δ ~ 5%; p < 0.05). Concordance correlation coefficients ranged from 0.80-0.99 and small but significant bias (p < 0.05-0.01) was present with Bland-Altman plots in 13 of 20 total anthropometric measurements. The mean waist to hip circumference ratio predicted by manifold regression was non-significantly different from ground-truth scanner measurements.

CONCLUSIONS

3D avatars predicted from demographic, physical, and other accessible characteristics can produce body representations with accurate anthropometric dimensions without a 3D scanner. Combining manifold regression algorithms into established body composition methods such as DXA, BIA, and other accessible methods provides new research and clinical opportunities.

Trunk-to-leg volume and appendicular lean mass from a commercial 3-dimensional optical body scanner for disease risk identification

BACKGROUND & AIMS

Body shape expressed as the trunk-to-leg volume ratio is associated with diabetes and mortality due to the associations between higher adiposity and lower lean mass with Metabolic Syndrome (MetS) risk. Reduced appendicular muscle mass is associated with malnutrition risk and age-related frailty, and is a risk factor for poor treatment outcomes related to MetS and other clinical conditions (e.g.; cancer). These measures are traditionally assessed by dual-energy X-ray absorptiometry (DXA), which can be difficult to access in clinical settings. The Shape Up! Adults trial (SUA) demonstrated the accuracy and precision of 3-dimensional optical imaging (3DO) for body composition as compared to DXA and other criterion measures. Here we assessed whether trunk-to-leg volume estimates derived from 3DO are associated with MetS risk in a similar way as when measured by DXA. We further explored if estimations of appendicular lean mass (ALM) could be made using 3DO to further improve the accessibility of measuring this important frailty and disease risk factor.

METHODS

SUA recruited participants across sex, age (18-40, 40-60, >60 years), BMI (under, normal, overweight, obese), and race/ethnicity (non-Hispanic [NH] Black, NH White, Hispanic, Asian, Native Hawaiian/Pacific Islander) categories. Each participant had whole-body DXA and 3DO scans, and measures of cardiovascular health. The 3DO measures of trunk and leg volumes were calibrated to DXA to express equivalent trunk-to-leg volume ratios. We expressed each blood measure and overall MetS risk in quartile gradations of trunk-to-leg volume previously defined by National Health and Nutrition Examination Survey (NHANES). Finally, we utilized 3DO measures to estimate DXA ALM using ten-fold cross-validation of the entire dataset.

RESULTS

Participants were 502 (273 female) adults, mean age = 46.0 ± 16.5y, BMI = 27.6 ± 7.1 kg/m2 and a mean DXA trunk-to-leg volume ratio of 1.47 ± 0.22 (females: 1.43 ± 0.23; males: 1.52 ± 0.20). After adjustments for age and sex, each standard deviation increase in trunk-to-leg volume by 3DO was associated with a 3.3 (95% odds ratio [OR] = 2.4-4.2) times greater risk of MetS, with individuals in the highest quartile of trunk-to-leg at 27.4 (95% CI: 9.0-53.1) times greater risk of MetS compared to the lowest quartile. Risks of elevated blood biomarkers as related to high 3DO trunk-to-leg volume ratios were similar to previously published comparisons using DXA trunk-to-leg volume ratios. Estimated ALM by 3DO was correlated to DXA (r2 = 0.96, root mean square error = 1.5 kg) using ten-fold cross-validation.

CONCLUSION

Using thresholds of trunk-to-leg associated with MetS developed on a sample of US-representative adults, trunk-to-leg ratio by 3DO after adjustments for offsets showed significant associations to blood parameters and MetS risk. 3DO scans provide a precise and accurate estimation of ALM across the range of body sizes included in the study sample. The development of these additional measures improves the clinical utility of 3DO for the assessment of MetS risk as well as the identification of low muscle mass associated with poor cardiometabolic and functional health.

Accurate Prediction of Three-Dimensional Humanoid Avatars for Anthropometric Modeling

Objective

To evaluate the hypothesis that anthropometric dimensions derived from a person's manifold-regression predicted three-dimensional (3D) humanoid avatar are accurate when compared to their actual circumference, volume, and surface area measurements acquired with a ground-truth 3D optical imaging method. Avatars predicted using this approach, if accurate with respect to anthropometric dimensions, can serve multiple purposes including patient metabolic disease risk stratification in clinical settings.

Methods

Manifold regression 3D avatar prediction equations were developed on a sample of 570 adults who completed 3D optical scans, dual-energy X-ray absorptiometry (DXA), and bioimpedance analysis (BIA) evaluations. A new prospective sample of 84 adults had ground-truth measurements of 6 body circumferences, 7 volumes, and 7 surface areas with a 20-camera 3D reference scanner. 3D humanoid avatars were generated on these participants with manifold regression including age, weight, height, DXA %fat, and BIA impedances as potential predictor variables. Ground-truth and predicted avatar anthropometric dimensions were quantified with the same software.

Results

Following exploratory studies, one manifold prediction model was moved forward for presentation that included age, weight, height, and %fat as covariates. Predicted and ground-truth avatars had similar visual appearances; correlations between predicted and ground-truth anthropometric estimates were all high (R2s, 0.75-0.99; all p < 0.001) with non-significant mean differences except for arm circumferences (%D ~ 5%; p < 0.05). Concordance correlation coefficients ranged from 0.80-0.99 and small but significant bias (p < 0.05 - 0.01) was present with Bland-Altman plots in 13 of 20 total anthropometric measurements. The mean waist to hip circumference ratio predicted by manifold regression was non-significantly different from ground-truth scanner measurements.

Conclusions

3D avatars predicted from demographic, physical, and other accessible characteristics can produce body representations with accurate anthropometric dimensions without a 3D scanner. Combining manifold regression algorithms into established body composition methods such as DXA, BIA, and other accessible methods provides new research and clinical opportunities.

Triptolide Administration Alters Immune Responses to Mitigate Insulin Resistance in Obese States

Individuals who are overweight or obese are at increased risk of developing prediabetes and type 2 diabetes, yet the direct molecular mechanisms that connect diabetes to obesity are not clear. Chronic, sustained inflammation is considered a strong risk factor in these interactions, directed in part by the short-lived gene expression programs encoding for cytokines and pro-inflammatory mediators. In this study, we show that triptolide administration in the C57BL/6 diet-induced obese mice at up to 10 μg/kg/day for 10 weeks attenuated the development of insulin resistance and diabetes, but not obesity, in these animals. Significant reductions in adipose tissue inflammation and improved insulin sensitivity were observed in the absence of changes in food intake, body weight, body composition, or energy expenditure. Analysis of the core cluster of biomarkers that drives pro-inflammatory responses in the metabolic tissues suggested TNF-α as a critical point that affected the co-development of inflammation and insulin resistance, but also pointed to the putatively protective roles of increased COX-2 and IL-17A signaling in the mediation of these pathophysiological states. Our results show that reduction of diet-induced inflammation confers partial protection against insulin resistance, but not obesity, and suggest the possibility of achieving overweight phenotypes that are accompanied by minimal insulin resistance if inflammation is controlled.

Accuracy and Precision of 3-dimensional Optical Imaging for Body Composition by Age, BMI, and Ethnicity

BACKGROUND

The obesity epidemic brought a need for accessible methods to monitor body composition, as excess adiposity has been associated with cardiovascular disease, metabolic disorders, and some cancers. Recent 3-dimensional optical (3DO) imaging advancements have provided opportunities for assessing body composition. However, the accuracy and precision of an overall 3DO body composition model in specific subgroups are unknown.

OBJECTIVES

This study aimed to evaluate 3DO's accuracy and precision by subgroups of age, body mass index, and ethnicity.

METHODS

A cross-sectional analysis was performed using data from the Shape Up! Adults study. Each participant received duplicate 3DO and dual-energy X-ray absorptiometry (DXA) scans. 3DO meshes were digitally registered and reposed using Meshcapade. Principal component analysis was performed on 3DO meshes. The resulting principal components estimated DXA whole-body and regional body composition using stepwise forward linear regression with 5-fold cross-validation. Duplicate 3DO and DXA scans were used for test-retest precision. Student's t tests were performed between 3DO and DXA by subgroup to determine significant differences.

RESULTS

Six hundred thirty-four participants (females = 346) had completed the study at the time of the analysis. 3DO total fat mass in the entire sample achieved R2 of 0.94 with root mean squared error (RMSE) of 2.91 kg compared to DXA in females and similarly in males. 3DO total fat mass achieved a % coefficient of variation (RMSE) of 1.76% (0.44 kg), whereas DXA was 0.98% (0.24 kg) in females and similarly in males. There were no mean differences for total fat, fat-free, percent fat, or visceral adipose tissue by age group (P > 0.068). However, there were mean differences for underweight, Asian, and Black females as well as Native Hawaiian or other Pacific Islanders (P < 0.038).

CONCLUSIONS

A single 3DO body composition model produced accurate and precise body composition estimates that can be used on diverse populations. However, adjustments to specific subgroups may be warranted to improve the accuracy in those that had significant differences. This trial was registered at clinicaltrials.gov as NCT03637855 (Shape Up! Adults).

Humans have a basic physical and psychological need to move the body: Physical activity as a primary drive

Physical activity, while less necessary for survival in modern times, is still essential for thriving in life, and low levels of movement are related to numerous physical and mental health problems. However, we poorly understand why people move on a day-to-day basis and how to promote greater energy expenditure. Recently, there has been a turn to understand automatic processes with close examination of older theories of behavior. This has co-occurred with new developments in the study of non-exercise activity thermogenesis (NEAT). In this narrative review, it is hypothesized that psycho-physiological drive is important to understand movement in general and NEAT, specifically. Drive, in short, is a motivation state, characterized by arousal and felt tension, energizing the organism to acquire a basic need. Movement is a biological necessity, like food, water, and sleep, but varies across the lifespan and having the greatest impact before adolescence. Movement meets various criteria for a primary drive: (a) deprivation of it produces feelings of tension, such as an urge or craving, known as affectively-charged motivation states, and particularly the feelings of being antsy, restless, hyper or cooped up, (b) provision of the need quickly reduces tension - one can be satiated, and may even over-consume, (c) it can be provoked by qualities of the environment, (d) it is under homeostatic control, (e) there is an appetite (i.e., appetence) for movement but also aversion, and (f) it has a developmental time course. Evidence for drive has mainly come from children and populations with hyperkinetic disorders, such as those with anorexia nervosa, restless legs syndrome, and akathisia. It is also stimulated in conditions of deprivation, such as bed rest, quarantine, long flights, and physical restraint. It seems to be lacking in the hypokinetic disorders, such as depression and Parkinson's. Thus, drive is associated with displeasure and negative reinforcement, subsuming it within the theory of hedonic drive, but it may fit better within new paradigms, such as the WANT model (Wants and Aversions for Neuromuscular Tasks). Recently developed measurement tools, such as the CRAVE scale, may permit the earnest investigation of movement drive, satiation, and motivation states in humans.

Monitoring body composition change for intervention studies with advancing 3D optical imaging technology in comparison to dual-energy X-ray absorptiometry

BACKGROUND

Recent 3-dimensional optical (3DO) imaging advancements have provided more accessible, affordable, and self-operating opportunities for assessing body composition. 3DO is accurate and precise in clinical measures made by DXA. However, the sensitivity for monitoring body composition change over time with 3DO body shape imaging is unknown.

OBJECTIVES

This study aimed to evaluate the ability of 3DO in monitoring body composition changes across multiple intervention studies.

METHODS

A retrospective analysis was performed using intervention studies on healthy adults that were complimentary to the cross-sectional study, Shape Up! Adults. Each participant received a DXA (Hologic Discovery/A system) and 3DO (Fit3D ProScanner) scan at the baseline and follow-up. 3DO meshes were digitally registered and reposed using Meshcapade to standardize the vertices and pose. Using an established statistical shape model, each 3DO mesh was transformed into principal components, which were used to predict whole-body and regional body composition values using published equations. Body composition changes (follow-up minus the baseline) were compared with those of DXA using a linear regression analysis.

RESULTS

The analysis included 133 participants (45 females) in 6 studies. The mean (SD) length of follow-up was 13 (5) wk (range: 3-23 wk). Agreement between 3DO and DXA (R2) for changes in total FM, total FFM, and appendicular lean mass were 0.86, 0.73, and 0.70, with root mean squared errors (RMSEs) of 1.98 kg, 1.58 kg, and 0.37 kg, in females and 0.75, 0.75, and 0.52 with RMSEs of 2.31 kg, 1.77 kg, and 0.52 kg, in males, respectively. Further adjustment with demographic descriptors improved the 3DO change agreement to changes observed with DXA.

CONCLUSIONS

Compared with DXA, 3DO was highly sensitive in detecting body shape changes over time. The 3DO method was sensitive enough to detect even small changes in body composition during intervention studies. The safety and accessibility of 3DO allows users to self-monitor on a frequent basis throughout interventions. This trial was registered at clinicaltrials.gov as NCT03637855 (Shape Up! Adults; https://clinicaltrials.gov/ct2/show/NCT03637855); NCT03394664 (Macronutrients and Body Fat Accumulation: A Mechanistic Feeding Study; https://clinicaltrials.gov/ct2/show/NCT03394664); NCT03771417 (Resistance Exercise and Low-Intensity Physical Activity Breaks in Sedentary Time to Improve Muscle and Cardiometabolic Health; https://clinicaltrials.gov/ct2/show/NCT03771417); NCT03393195 (Time Restricted Eating on Weight Loss; https://clinicaltrials.gov/ct2/show/NCT03393195), and NCT04120363 (Trial of Testosterone Undecanoate for Optimizing Performance During Military Operations; https://clinicaltrials.gov/ct2/show/NCT04120363).

A comparative evaluation of propranolol pharmacokinetics in obese versus ideal weight individuals: A blueprint towards a personalised medicine

The pharmacokinetics of propranolol were investigated in obese and healthy weight groups. Research studies in relation to the presented topic were gathered, evaluated, and compared to distinguish variabilities involved amongst different lipophilic drugs and how they impacted the clinical effectiveness. Propranolol is a lipophilic drug so it was predicted that the pharmacokinetics would differ between obese and ideal-weight individuals. Previous research in other lipophilic drugs shows a trend to increase the volume of distribution and half-life in obese compared to ideal weight individuals. However, the majority of both clinical and preclinical studies gathered in this review, found a decrease in the volume of distribution (V_D) and clearance, and minimal significant difference in the half-life, in the obese group when compared with the ideal weight group. Different explanations for this comparison have been theorised including differing tissue blood flow, plasma protein binding, or hepatic clearance in obese compared with ideal weight populations; though the exact reasoning as to why propranolol does not follow the general trend for lipophilic drugs is yet to be determined. These findings regarding propranolol pharmacokinetics can be utilised towards further research and development in personalised medicine for patients with obesity and comorbid cardiovascular disease. The comparative studies highlighted the pharmacokinetic parameters which demonstrated a need for personalised dosage regimes for propranolol and a proposed research direction to understand why the difference exists between these population groups. With the prevalence of obesity continuing to rise, the relative pharmacokinetics of drugs must be evaluated in obese patient groups in order to inform drug dosing regimens and improve current clinical practice.

Essential Minerals and Metabolic Adaptation of Immune Cells

Modern lifestyles deviated considerably from the ancestral routines towards major shifts in diets and increased sedentarism. The trace elements status of the human body is no longer adequately supported by micronutrient-inferior farmed meats and crop commodities produced by the existing agricultural food systems. This is particular evident in the increased obesogenic adipogenesis and low-grade inflammation that fails to resolve with time. The metabolically restrictive environment of the inflamed tissues drives activation and proliferation of transient and resident populations of immune cells in favor of pro-inflammatory phenotypes, as well as a part of the enhanced autoimmune response. As different stages of the immune activation and resolution depend on the availability of specific minerals to maintain the structural integrity of skin and mucus membranes, activation and migration of immune cells, activation of the complement system, and the release of pro-inflammatory cytokines and chemokines, this review discusses recent advances in our understanding of the contribution of select minerals in optimizing the responses of innate and adaptive immune outcomes. An abbreviated view on the absorption, transport, and delivery of minerals to the body tissues as related to metabolic adaptation is considered.

Epidemische Entwicklung der Adipositas über 6 Jahrzehnte nachgezeichnet

Im Rahmen von Erhebungen aus den Jahren 2015–2018 erwiesen sich mehr als 2/3 der erwachsenen USA-Amerikaner als übergewichtig oder adipös. M. C. Wong et al. haben nun Daten aus 6 Jahrzehnten ausgewertet, um basierend auf optischen 3D-Scans humanoide Avatare zu generieren. Ziel war es, die Veränderungen der Körperform über den Zeitverlauf zu visualisieren.

Emergence of the adolescent obesity epidemic in the United States: five-decade visualization with humanoid avatars

BACKGROUND/OBJECTIVES

Body size and shape have increased over the past several decades with one in five adolescents now having obesity according to objective anthropometric measures such as weight, height, and body mass index (BMI). The gradual physical changes and their consequences may not be fully appreciated upon visual inspection by those managing the long-term health of adolescents. This study aimed to develop humanoid avatars representing the gradual changes in adolescent body size and shape over the past five decades and to align avatars with key BMI percentile cut points for underweight, normal weight, overweight, and obesity.

PARTICIPANTS/METHODS

Participants included 223 children and adolescents between the ages of 5 and 18 years approximately representative of the race/ethnicity and BMI of the noninstitutionalized US population. Each participant completed a three-dimensional whole-body scan, and the collected data was used to develop manifold regression models for generating humanoid male and female avatars from specified ages, weights, and heights. Secular changes in the mean weights and heights of adolescents were acquired from six U.S. National Health and Nutrition Surveys beginning in 1971-1974 and ending in 2015-2018. Male and female avatars at two representative ages, 10 and 15 years, were developed for each survey and at the key BMI percentile cut points based on data from the 2015-2018 survey.

RESULTS

The subtle changes in adolescent Americans' body size and shape over the past five decades are represented by 24 male and female 10- and 15-year-old avatars and 8 corresponding BMI percentile cut points.

CONCLUSIONS

The current study, the first of its kind, aligns objective physical examination weights and heights with the visual appearance of adolescents. Aligning the biometric and visual information may help improve awareness and appropriate clinical management of adolescents with excess adiposity passing through health care systems.

TRIAL REGISTRATION

ClinicalTrials.Gov NCT03706612.

Digital Anthropometry for Body Circumference Measurements: European Phenotypic Variations throughout the Decades

This review summarizes body circumference-based anthropometrics that are in common use for research and in some cases clinical application. These include waist and hip circumference-based central body indices to predict cardiometabolic risk: waist circumference, waist-to-hip ratio, waist-to-height ratio, waist-to-thigh ratio, body adiposity index, a body shape index (ABSI), hip index (HI), and body roundness index (BRI). Limb circumference measurements are most often used to assess sarcopenia and include: thigh circumference, calf circumference, and mid-arm circumference. Additionally, this review presents fascinating recent developments in optic-based imaging technologies that have elucidated changes over the last decades in average body size and shape in European populations. The classical apple and pear shape concepts of body shape difference remain useful, but novel and exciting 3-D optical "e-taper" measurements provide a potentially powerful new future vista in anthropometrics.

What Is a 2021 Reference Body?

The historical 1975 Reference Man is a ‘model’ that had been used as a basis for the calculation of radiation doses, metabolism, pharmacokinetics, sizes for organ transplantation and ergonomic optimizations in the industry, e.g., to plan dimensions of seats and other formats. The 1975 Reference Man was not an average individual of a population; it was based on the multiple characteristics of body compositions that at that time were available, i.e., mainly from autopsy data. Faced with recent technological advances, new mathematical models and socio-demographic changes within populations characterized by an increase in elderly and overweight subjects a timely ‘state-of-the-art’ 2021 Reference Body are needed. To perform this, in vivo human body composition data bases in Kiel, Baton Rouge, San Francisco and Honolulu were analyzed and detailed 2021 Reference Bodies, and they were built for both sexes and two age groups (≤40 yrs and >40 yrs) at BMIs of 20, 25, 30 and 40 kg/m2. We have taken an integrative approach to address ‘structure−structure’ and ‘structure−function’ relationships at the whole-body level using in depth body composition analyses as assessed by gold standard methods, i.e., whole body Magnetic Resonance Imaging (MRI) and the 4-compartment (4C-) model (based on deuterium dilution, dual-energy X-ray absorptiometry and body densitometry). In addition, data obtained by a three-dimensional optical scanner were used to assess body shape. The future applications of the 2021 Reference Body relate to mathematical modeling to address complex metabolic processes and pharmacokinetics using a multi-level/multi-scale approach defining health within the contexts of neurohumoral and metabolic control.