Application of standards and models in body composition analysis

Prediction of individual weight loss using supervised learning: findings from the comprehensive assessment of long-term effects of reducing intake of energy phase 2 study

BACKGROUND

Predicting individual weight loss (WL) responses to lifestyle interventions is challenging but might help practitioners and clinicians select the most promising approach for each individual.

OBJECTIVE

The primary aim of this study was to develop machine learning (ML) models to predict individual WL responses using only variables known before starting the intervention. In addition, we used ML to identify pre-intervention variables influencing the individual WL response.

METHODS

We used 12-mo data from the comprehensive assessment of long-term effects of reducing intake of energy phase 2 study, which aimed to analyze the long-term effects of caloric restriction on human longevity. On the basis of the data from 130 subjects in the intervention group, we developed classification models to predict binary ("Success" and "No/low success") or multiclass ("High success," "Medium success," and "Low/no success") WL outcomes. Additionally, regression models were developed to predict individual weight change (percent). Models were evaluated on the basis of accuracy, sensitivity, specificity (classification models), and root mean squared error (RMSE; regression models).

RESULTS

Best classification models used 20-40 predictors and achieved 89%-97% accuracy, 91%-100% sensitivity, and 56%-86% specificity for binary classification. For multiclass classification, accuracy (69%) and sensitivity (50%) tended to be lower. The best regression performance was obtained with 36 variables with an RMSE of 2.84%. Among the 21 variables predicting individual weight change most consistently, we identified 2 novel predictors, namely orgasm satisfaction and sexual behavior/experience. Other common predictors have previously been associated with WL (16) or are already used in traditional prediction models (3).

CONCLUSIONS

The prediction models could be implemented by practitioners and clinicians to support the decision of whether lifestyle interventions are sufficient or more aggressive interventions are needed for a given individual, thereby supporting better, faster, data-driven, and unbiased decisions. The CALERIE phase 2 study was registered at clinicaltrials.gov as NCT00427193.

Body composition in second trimester is associated with dyslipidemia in third trimester

OBJECTIVE

The aim of this study was to examine the correlation between maternal body composition during the second trimester and the occurrence of dyslipidemia in the third trimester.

METHODS

A cohort of 1508 pregnant women who underwent antenatal testing at Shanghai Sixth People's Hospital, affiliated with Shanghai Jiao Tong University School of Medicine, were included in this study. Maternal body composition was assessed using bioimpedance analysis between 14 and 22 weeks of gestation.

RESULTS

Among the 1508 participants, a total of 1420 individuals (94.2%) were diagnosed with dyslipidemia. Notably, there were significant differences in body composition between the normal lipid group and the dyslipidemia group. Logistic regression analysis revealed that various factors including BMI, total body water (TBW), intra-cellular water (ICW), extra-cellular water (ECW), percent body fat (PBF), visceral fat area (VFA), fat-free mass (FFM) and arm circumference (AC) during the second trimester were all found to be associated with dyslipidemia in the third trimester.

CONCLUSION

The present study found that maternal body composition was associated with dyslipidemia. The BMI, TBW, ICW, ECW, PBF, VFA, FFM and AC in second trimester were associated with dyslipidemia in third trimester.

Adaptive thermogenesis, at the level of resting energy expenditure, after diet alone or diet plus bariatric surgery

OBJECTIVE

The objective of this study was to compare the magnitude of adaptive thermogenesis (AT), at the level of resting energy expenditure (REE), after a very low-energy diet alone or combined with Roux-en-Y gastric bypass or sleeve gastrectomy, as well as to investigate the association between AT and changes in appetite.

METHODS

A total of 44 participants with severe obesity underwent 10 weeks of a very low-energy diet alone or combined with Roux-en-Y gastric bypass or sleeve gastrectomy. Body weight and composition, REE, subjective appetite feelings, and plasma concentrations of gastrointestinal hormones were measured at baseline and week 11. AT, at the level of REE, was defined as a significantly lower measured versus predicted (using a regression model with baseline data) REE.

RESULTS

Participants lost 18.4 ± 3.9 kg of body weight and experienced AT, at the level of REE (-121 ± 188 kcal/day; p < 0.001), with no differences among groups. The larger the AT, at the level of REE, the greater the reduction in fasting ghrelin concentrations and the smaller the reduction in feelings of hunger and desire to eat in the postprandial state.

CONCLUSIONS

Weight-loss modality does not seem to modulate the magnitude of AT, at the level of REE. The greater the AT, at the level of REE, the greater the drive to eat following weight loss.

Influence of malnutrition according to the glim criteria on the chemotherapy toxicities in patients with advanced lung cancer

BACKGROUND

Cancer-associated malnutrition is highly prevalent in advanced lung cancer, and 50% of global cancer-related deaths are attributed to cancer-associated malnutrition. Platinum-containing chemotherapy is the standard treatment for advanced lung cancer. Unfortunately, it can cause exacerbated toxicities, which can also have a negative impact on patient's prognosis and quality of life. The Global Leadership Initiative on Malnutrition (GLIM) criteria have been proposed as the world's first accepted diagnostic criteria for malnutrition. However, the effectiveness of GLIM criteria in predicting chemotherapy toxicities in patients with advanced lung cancer is unclear. The aim of this study was to apply the GLIM criteria to assess the prevalence of pre-treatment diagnosis of malnutrition in patients with advanced non-small cell lung cancer (NSCLC) and to determine the impact of nutritional status on patient's chemotherapy toxicity.

METHODS

We conducted a study of hospitalized patients with pathologically and clinically diagnosed advanced NSCLC who presented to our hospital from May 2021 to January 2022. Initially, the Nutritional Risk Screening-2002 (NRS-2002) was used for nutritional risk screening, and nutritional status was assessed using the Scored Patient-Generated Subjective Global Assessment (PG-SGA) and GLIM criteria. Chemotherapy toxicity was assessed and graded according to CTCAE5.0, and chemotherapy efficacy was assessed according to RECIST1.1. Kappa test was used to analyze the agreement between PG-SGA and GLIM criteria. Univariate and multivariate logistic regression analyses were used to determine the relationship between malnutrition and chemotherapy toxicity.

RESULTS

A total of 215 patients with advanced NSCLC were evaluated for nutritional status. Most of the patients had normal BMI (61.86%) before the start of treatment, 40% were well-nourished as assessed by the PG-SGA tool, and 51.17% were well-nourished as assessed by GLIM criteria. Consistency analysis showed moderate agreement (Kappa = 0.463, P < 0.001) and their correlation was also moderate (Spearman, rs = 0.475, P < 0.001). The objective response rate (ORR) (P = 0.040) and disease control rate (DCR) (P < 0.001) were significantly lower in malnourished patients diagnosed according to GLIM criteria than in well-nourished patients. Multivariate analysis showed that malnutrition (OR = 1.531,95%CI 0.757-3.009; OR = 6.623,95%CI 1.390-31.567, P = 0.046) diagnosed by GLIM criteria was an independent predictor of chemotherapy toxicity. Conclusions Malnutrition diagnosed by GLIM criteria better predicts toxicity during chemotherapy, determines the degree of clinical benefit of chemotherapy, and may affect patient prognosis.

Unexpectedly Rapid Onset of Severe Sarcopenia in an Elderly Diabetic Man following SGLT2i Administration: A Case Report

Sarcopenia is characterized by the progressive loss of muscle mass, strength, and function and poses a significant health challenge among people with diabetes. Sodium-glucose cotransporter-2 inhibitors (SGLT2is) are the backbone of type 2 diabetes treatment. The interplay between SGLT2is and sarcopenia is an area of active research with inconclusive results. This article presents an unexpectedly rapid weight reduction, along with physical performance deterioration, in an elderly patient with type 2 diabetes, which led to treatment discontinuation. A bioelectrical impedance analysis confirmed severe sarcopenia development. Until more data are available, sarcopenia and body composition screening and monitoring may be warranted whenever SGLT2is are prescribed.

Reduced skeletal muscle mass to visceral fat area ratio is independently associated with reduced cognitive function in type 2 diabetes mellitus

AIM

Skeletal muscle mass to visceral fat area ratio (SVR) has been recognised as an index of sarcopenic obesity. SVR is associated with type 2 diabetes mellitus (T2DM), metabolic syndrome and arterial stiffness which are known risk factors for cognitive dysfunction. We aimed to investigate association between SVR and cognitive function in patients with T2DM.

METHODS

This was a cross-sectional study of 1326 patients with T2DM and mean age 61.3 ± 8.0 years. SVR was assessed based on bioelectrical impedance measurements of muscle mass and visceral fat area (VFA). Cognitive function was assessed using Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Linear regression was used to examine the association between SVR in quartiles and RBANS score, adjusting for demographics, education, presence of depressive symptoms, clinical covariates and medications.

RESULTS

The lower SVR quartiles were negatively associated with RBANS total score in the unadjusted analysis. The corresponding coefficients for Quartiles 1 and 2 SVR were -3.79 (95 % CI -5.39 to -2.19; p < 0.001) and -1.47 (95 % CI -2.86 to -0.07; p = 0.039) in fully adjusted analysis. The negative association between Quartile 1 SVR and RBANS score was evident in immediate memory, delayed memory, visuo-spatial construction, language and attention domains. Muscle mass and VFA alone had weaker associations with RBANS scores.

CONCLUSION

Our study demonstrated, for the first time, an independent association between reduced SVR and lower cognitive function. This is evident in global and multiple cognitive domains. The synergistic effects of reduced muscle mass and visceral obesity may be more pronounced than their independent effects on cognitive function.

The Effects of Sodium-Glucose Cotransporter 2 Inhibitors on Body Composition in Type 2 Diabetes Mellitus: A Narrative Review

Body composition is related to cardiometabolic disorders and is a major driver of the growing incidence of type 2 diabetes mellitus (T2DM). Altered fat distribution and decreased muscle mass are related to dysglycemia and impose adverse health-related outcomes in people with T2DM. Hence, improving body composition and maintaining muscle mass is crucial in T2DM. Sodium-glucose cotransporter 2 (SGLT2) inhibitors are novel glucose-lowering medications gaining popularity because of their cardiorenal-protective effects and weight-lowering characteristics. However, reports on myopathy secondary to SGLT2 inhibitor treatment raised a safety concern. The importance of maintaining muscle mass in people with T2DM necessitates further investigation to explore the impact of novel medications on body composition. In this review, we discussed current evidence on the impact of SGLT2 inhibitors on body composition in people with T2DM.

Association of Plasma Zinc and Copper with Body Composition, Lipids and Inflammation in a Cross-Sectional General Population Sample from Germany

We aimed to relate circulating plasma zinc and copper to a broad spectrum of adiposity-related traits in a cross-sectional Northern German study (n = 841, 42% female, age: 61 ± 12 years). Zinc and copper were measured by inductively coupled plasma-mass spectrometry. Subcutaneous (SAT) and visceral (VAT) adipose tissue and liver fat were derived from 534 and 538 participants, respectively, via magnet resonance imaging. Associations were assessed using multivariable-adjusted linear regression analysis. An increase per one standard deviation (SD) in zinc was associated with direct linear increases in body mass index (BMI) (1.17%; 95% confidence interval (95%CI) 0.15-2.20%), waist circumference (0.85%; 95%CI 0.04-1.67%) and waist-to-hip ratio (0.64%; 95%CI 0.18-1.09%). A 1-SD increment in copper was directly associated with BMI (1.64%; 0.41-2.88%) and waist circumference (1.22%; 95%CI 0.25-2.20%) but not waist-to-hip ratio. Independent of fat intake, zinc displayed associations with VAT (5.73%; 95%CI 2.04-9.56%) and with liver fat (3.84%; 95%CI 1.49-6.25%), the latter association being also independent of BMI. Copper was directly associated with SAT (4.64%; 95%CI 0.31-9.15%) before accounting for BMI, but showed no association with VAT or liver fat. Observed associations suggest a possible relevance of zinc and copper to adiposity. Particularly zinc displayed associations with traits of abdominal adiposity and liver fat.

Assessment of body composition in pediatric intestinal failure: A comparison study

BACKGROUND

The objective of the study was to compare bioelectrical impedance analysis (BIA) and skinfolds with dual energy x-ray absorptiometry (DXA) in the assessment of body composition of children with intestinal failure. DXA is the reference method for body composition assessment in clinical settings.

METHODS

Children aged 1-18 years with intestinal failure whohave DXA as part of routine clinical monitoring were eligible. BIA measured total body water on the same day as DXA. Skinfold measurements were taken at four sites: triceps, biceps, subscapular, and suprailiac. Percentage of fat mass (%FM) and fat-free mass (%FFM) were derived from resistance and reactance measured by BIA by using age-specific equations. Percentage of FM was calculated from skinfold measures by using age-specific equations. Data on patient characteristics, intestinal failure-related factors, and feeding method were collected. Paired t test examined differences in %FM and %FFM and Bland-Altman analysis determined the agreement between BIA, skinfolds, and DXA. Marginal linear model assessed the effect of age, sex, and feeding method on the difference in body composition obtained between DXA and BIA and between DXA and skinfolds.

RESULTS

Sixty-eight children with intestinal failure, mean age 8.9 ± 4.2 years, were studied. There was no difference between %FFM and %FM obtained by DXA and BIA (P = 0.26), with a mean bias (95% CI) of -0.69 (-1.9 to 0.5) for %FFM. Sex and age were individually and jointly associated with the bias observed between DXA and BIA (P < 0.05). Skinfold and DXA measurements were significantly different (P < 0.05).

CONCLUSIONS

BIA is an acceptable clinical tool for assessing body composition in pediatric intestinal failure.

Low Muscle and High Fat Percentages Are Associated with Low Natural Killer Cell Activity: A Cross-Sectional Study

This study aimed to investigate whether body fat and muscle percentages are associated with natural killer cell activity (NKA). This was a cross-sectional study, conducted on 8058 subjects in a medical center in Korea. The association between the muscle and fat percentage tertiles and a low NKA, defined as an interferon-gamma level lower than 500 pg/mL, was assessed. In both men and women, the muscle mass and muscle percentage were significantly low in participants with a low NKA, whereas the fat percentage, white blood cell count, and C-reactive protein (CRP) level were significantly high in those with a low NKA. Compared with the lowest muscle percentage tertile as a reference, the fully adjusted odd ratios (ORs) (95% confidence intervals (CIs)) for a low NKA were significantly lower in T2 (OR: 0.69; 95% CI: 0.55-0.86) and T3 (OR: 0.74; 95% CI: 0.57-0.95) of men, and T3 (OR: 0.76; 95% CI: 0.59-0.99) of women. Compared with the lowest fat percentage tertile as a reference, the fully adjusted OR was significantly higher in T3 of men (OR: 1.31; 95% CI: 1.01-1.69). A high muscle percentage was significantly inversely associated with a low NKA in men and women, whereas a high fat percentage was significantly associated with a low NKA in men.

Laser-Based 3D Body Scanning Reveals a Higher Prevalence of Abdominal Obesity than Tape Measurements: Results from a Population-Based Sample

BACKGROUND

The global obesity epidemic is a major public health concern, and accurate diagnosis is essential for identifying at-risk individuals. Three-dimensional (3D) body scanning technology offers several advantages over the standard practice of tape measurements for diagnosing obesity. This study was conducted to validate body scan data from a German population-based cohort and explore clinical implications of this technology in the context of metabolic syndrome.

METHODS

We performed a cross-sectional analysis of 354 participants from the Study of Health in Pomerania that completed a 3D body scanning examination. The agreement of anthropometric data obtained from 3D body scanning with manual tape measurements was analyzed using correlation analysis and Bland-Altman plots. Classification agreement regarding abdominal obesity based on IDF guidelines was assessed using Cohen's kappa. The association of body scan measures with metabolic syndrome components was explored using correlation analysis.

RESULTS

Three-dimensional body scanning showed excellent validity with slightly larger values that presumably reflect the true circumferences more accurately. Metabolic syndrome was highly prevalent in the sample (31%) and showed strong associations with central obesity. Using body scan vs. tape measurements of waist circumference for classification resulted in a 16% relative increase in the prevalence of abdominal obesity (61.3% vs. 52.8%).

CONCLUSIONS

These results suggest that the prevalence of obesity may be underestimated using the standard method of tape measurements, highlighting the need for more accurate approaches.

Resilience and stability of the CF- intestinal and respiratory microbiome during nutritional and exercise intervention

BACKGROUND

Impaired respiratory and intestinal microbiome composition is linked to cystic fibrosis lung disease severity. In people with cystic fibrosis (pwCF), regular exercise is recommended to delay disease progression and preserve a stable lung function. An optimal nutritional status is vital for best clinical outcomes. Our study investigated whether regular and monitored exercise and nutritional support promotes CF microbiome health.

METHODS

A personalized nutrition and exercise program promoted nutritional intake and physical fitness in 18 pwCF for 12 months. Throughout the study, patients performed strength and endurance training monitored by a sports scientist via an internet platform. After three months, food supplementation with Lactobacillus rhamnosus LGG was introduced. Nutritional status and physical fitness were assessed before the study started, after three and nine months. Sputum and stool were collected, and microbial composition was analyzed by 16S rRNA gene sequencing.

RESULTS

Sputum and stool microbiome composition remained stable and highly specific to each patient during the study period. Disease-associated pathogens dominated sputum composition. Lung disease severity and recent antibiotic treatment had the highest impact on taxonomic composition in stool and sputum microbiome. Strikingly, the long-term antibiotic treatment burden had only a minor influence.

CONCLUSION

Despite the exercise and nutritional intervention, respiratory and intestinal microbiomes proved to be resilient. Dominant pathogens drove the composition and functionality of the microbiome. Further studies are required to understand which therapy could destabilize the dominant disease-associated microbial composition of pwCF.

Primary Validation of the Submandibular Skinfold as an Anthropometric Measurement of Cardiometabolic Risk in People with Intellectual Disabilities

The accumulation of body fat is an important cardiometabolic risk factor; however, there is no consensus about which measure is more reliable for the assessment of cardiometabolic risk in people with intellectual disabilities. The aim of the present study was to primarily validate the submandibular skinfold as an anthropometric measurement of cardiometabolic risk in children, adolescents, and adults with intellectual disabilities, using a cross-sectional study made up of 131 people (67.2% men) with mild and moderate intellectual disability. The cardiometabolic risk indicators used were: body mass index (kg/m2), neck circumference (cm), waist circumference (cm), calf circumference (cm) and waist-to-height ratio. Moderate correlations were demonstrated between the submandibular skinfold measure and the anthropometric measurements analyzed in the three age categories, showing the highest correlation (r = 0.70) between the submandibular skinfold and BMI in the adolescent group and waist-to-height ratio in adults. The implementation of the submandibular skinfold measurement is suggested as an easy, fast, and minimally invasive anthropometric measurement as part of the physical and nutritional evaluation for the assessment of cardiometabolic risk in people with intellectual disabilities.

Noninvasive monitoring of muscle atrophy and bone metabolic disorders using dual-energy X-ray absorptiometry in diabetic mice

Tracking metabolic changes in skeletal muscle and bone using animal models of diabetes mellitus (DM) provides important insights for the management of DM complications. In this study, we aimed to establish a method for monitoring changes in body composition characteristics, such as fat mass, skeletal muscle mass (lean mass), bone mineral density, and bone mineral content, during DM progression using a dual-energy X-ray absorptiometry (DXA) system in a mouse model of streptozotocin (STZ)-induced type 1 DM. In the DM model, STZ administration resulted in increased blood glucose levels, increased water and food intake, and decreased body weight. Serum insulin levels were significantly decreased on day 30 of STZ administration. The DXA analysis revealed significant and persistent decreases in fat mass, lower limb skeletal muscle mass, and bone mineral content in DM mice. We measured tibialis anterior (TA) muscle weight and performed a quantitative analysis of tibial microstructure by micro-computed tomography imaging in DM mice. The TA muscle weight of DM mice was significantly lower than that of control mice. In addition, the trabecular bone volume fraction, trabecular thickness, trabecular number, and cortical thickness were significantly decreased in DM mice. Pearson's product-moment correlation coefficient analysis showed a high correlation between the DXA-measured and actual body composition. In conclusion, longitudinal measurement of body composition changes using a DXA system may be useful for monitoring abnormalities in muscle and bone metabolism in animal models of metabolic diseases such as DM mice.

Determination gender-based hybrid artificial intelligence of body muscle percentage by photoplethysmography signal

BACKGROUND AND OBJECTIVE

Muscle mass is one of the critical components that ensure muscle function. Loss of muscle mass at every stage of life can cause many adverse effects. Sarcopenia, which can occur in different age groups and is characterized by a decrease in muscle mass, is a critical syndrome that affects the quality of life of individuals. Aging, a universal process, can also cause loss of muscle mass. It is essential to monitor and measure muscle mass, which should be sufficient to maintain optimal health. Having various disadvantages with the ordinary methods used to estimate muscle mass increases the need for the new high technology methods. This study aims to develop a low-cost and trustworthy Body Muscle Percentage calculation model based on artificial intelligence algorithms and biomedical signals.

METHODS

For the study, 327 photoplethysmography signals of the subject were used. First, the photoplethysmography signals were filtered, and sub-frequency bands were obtained. A quantity of 125 time-domain features, 25 from each signal, have been extracted. Additionally, it has reached 130 features in demographic features added to the model. To enhance the performance, the spearman feature selection algorithm was used. Decision trees, Support Vector Machines, Ensemble Decision Trees, and Hybrid machine learning algorithms (the combination of three methods) were used as machine learning algorithms.

RESULTS

The recommended Body Muscle Percentage estimation model have the perfomance values for all individuals R=0.95, for males R=0.90 and for females R=0.90 in this study.

CONCLUSION

Regarding the study results, it is thought that photoplethysmography-based models can be used to predict body muscle percentage.

The Incidence of Body Posture Abnormalities in Relation to the Segmental Body Composition in Early School-Aged Children

Children are exposed to multiple factors that contribute to an increase in body mass and the development of posture defects. The aim of the study is to assess the relationship between the segmental distribution of fat mass and muscle mass and the incidence of body posture abnormalities in early school-aged children. A total of 190 children aged 7-9 were included in the research project. The examined children were divided according to age (class level) into three groups. Height, weight and body composition, BMI, and body posture were determined. Thoracic and lumbar spine abnormalities occurred most frequently in the examined children (7-95%, 8-92%, 9-89.5%). During the assessment of the segmental body composition, the lowest fat-fat-free index was found in the trunk. The number of abnormalities of the cervical spine, pelvis, and lower extremities increases with age. The number of abnormalities of the thoracic and lumbar spine, as well as of upper extremities and the pectoral girdle decreases with age. Body posture abnormalities are correlated with body composition and in particular with the fat mass percentage. The segmental body com-position analyzer can be used to screen for posture defects.

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.

Obesity history, physical exam, laboratory, body composition, and energy expenditure: An Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) 2022

Background

This Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) on History, Physical Exam, Body Composition and Energy Expenditure is intended to provide clinicians an overview of the clinical and diagnostic evaluation of patients with pre-obesity/obesity.

Methods

The scientific information for this CPS is based upon published scientific citations, clinical perspectives of OMA authors, and peer review by the Obesity Medicine Association leadership.

Results

This CPS outlines important components of medical, dietary, and physical activity history as well as physical exams, with a focus on specific aspects unique to managing patients with pre-obesity or obesity. Patients with pre-obesity/obesity benefit from the same preventive care and general laboratory testing as those without an increase in body fat. In addition, patients with pre-obesity/obesity may benefit from adiposity-specific diagnostic testing - both generally and individually - according to patient presentation and clinical judgment. Body composition testing, such as dual energy x-ray absorptiometry, bioelectrical impedance, and other measures, each have their own advantages and disadvantages. Some patients in clinical research, and perhaps even clinical practice, may benefit from an assessment of energy expenditure. This can be achieved by several methods including direct calorimetry, indirect calorimetry, doubly labeled water, or estimated by equations. Finally, a unifying theme regarding the etiology of pre-obesity/obesity and effectiveness of treatments of obesity centers on the role of biologic and behavior efficiencies and inefficiencies, with efficiencies more often associated with increases in fat mass and inefficiencies more often associated with decreases in fat mass.

Conclusion

The Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) on History, Physical Exam, Body Composition and Energy Expenditure is one of a series of OMA CPSs designed to assist clinicians in the care of patients with the disease of pre-obesity/obesity.

Personalized Diet in Obesity: A Quasi-Experimental Study on Fat Mass and Fat-Free Mass Changes

Considering that the prevalence of overweight and obesity in Southeast of Spain is high, the aim of this work was to analyze the relation between the adherence to a personalized diet and the effectiveness of changes in the body composition in overweight and obese adults in this region. This quasi-experimental study presents the following selection criteria: attendance at the consultation between 2006 and 2012, subjects ≥ 19 years of age with overweight or obesity. In total, 591 overweight or obese individuals were involved in this study, attending 4091 clinic consultations in total. Most of the sample consisted of subjects who attended >3 consultations (>1.5 months), and were females aged 19-64 years who obtained clinically significant changes in fat mass (FM, ≥5%) and recommended changes in fat-free mass (FFM, ≥0%). Based on the results obtained and the experience gained from this research, the following recommendations are established: (i) record fat mass and fat-free mass index as a complement to body mass index; (ii) use FM and FFM to evaluate effectiveness of interventions with the aim of obtaining body composition changes; (iii) use personalized diet to achieve significant changes in FM and avoid non-recommended changes in FFM.

Validation of skeletal muscle mass estimation equations in active young adults: A preliminary study

We analyzed the validity of the estimation equations for skeletal muscle mass (SMM) using mass of appendicular lean soft tissue (ALST), evaluated by dual-energy X-ray absorptiometry (DXA), in healthy young males undergoing training, and compared it with the results obtained using whole-body magnetic resonance imaging (MRI). We hypothesized that a novel variable, that is, trunk and trunk-to-appendicular ratio of lean soft tissues (trunk/ALST), would be useful in reducing estimation errors in athletes or physically active participants. We analyzed the data of 30 participants (mean age 19.9 ± 1.8 years). SMM was measured using whole-body MRI, while mass of trunk and ALST was assessed using DXA. Three previously utilized estimation equations were retrieved from the literature and used for comparison. The estimated SMM values using previous equations highly correlated with measured SMM, which was determined by MRI, but the mean estimated SMM values were significantly lower than the measured-SMM values. Stepwise regression analysis revealed that mass of ALST, trunk/ALST ratio, and percent body fat were significant predictors of SMM and were incorporated as the new suggested variables. This equation accounted for 90.3% of the variance in SMM. While the previous equations' estimated SMM correlated with measured-SMM in participants with trunk/ALST ratios ≤1.05, they underestimated SMMs in those with trunk/ALST ratios >1.05. The present study confirms that the previously used equations underestimate the actual SMM, particularly in participants with high trunk/ALST ratios (>1.05). The current equation may be used in healthy and active young males, including athletes, as a preliminary tool.

Diagnosis of obesity based on body composition-associated health risks-Time for a change in paradigm

Traditional diagnosis and understanding of the pathophysiology of obesity are based on excessive fat storage due to a chronically positive energy balance characterized by body mass index (BMI). Quantitative and qualitative analysis of lean and adipose tissue compartments by body composition analysis reveals that characterization of obesity as "overfat" does not facilitate a comprehensive understanding of obesity-associated health risk. Instead of being related to fat mass, body composition characteristics underlying BMI-associated prognosis may depend (i) on accelerated growth by a gain in lean mass or fat-free mass (FFM) in children with early BMI rebound or adolescents with early puberty; (ii) on a low muscle mass in aging, associated chronic disease, or severe illness; and (iii) on impaired adipose tissue expandability with respect to cardiometabolic risk. It is therefore time to call the adipocentric paradigm of obesity into question and to avoid the use of BMI and body fat percentage. By contrast, obesity should be seen in face of a limited FFM/muscle mass together with a limited capacity of fat storage.

Nuchal Skinfold Thickness in Pediatric Brain Tumor Patients

BACKGROUND

Severe obesity and tumor relapse/progression have impact on long-term prognosis in pediatric brain tumor patients.

METHODS

In a cross-sectional study, we analyzed nuchal skinfold thickness (NST) on magnetic-resonance imaging (MRI) follow-up monitoring as a parameter for assessment of nuchal adipose tissue in 177 brain tumor patients (40 World Health Organization (WHO) grade 1-2 brain tumor; 31 grade 3-4 brain tumor; 106 craniopharyngioma), and 53 healthy controls. Furthermore, body mass index (BMI), waist-to-height ratio, caliper-measured skinfold thickness, and blood pressure were analyzed for association with NST.

RESULTS

Craniopharyngioma patients showed higher NST, BMI, waist-to-height ratio, and caliper-measured skinfold thickness when compared to other brain tumors and healthy controls. WHO grade 1-2 brain tumor patients were observed with higher BMI, waist circumference and triceps caliper-measured skinfold thickness when compared to WHO grade 3-4 brain tumor patients. NST correlated with BMI, waist-to-height ratio, and caliper-measured skinfold thickness. NST, BMI and waist-to-height ratio were associated with increased blood pressure. In craniopharyngioma patients with hypothalamic involvement/lesion or gross-total resection, rate and degree of obesity were increased.

CONCLUSIONS

NST could serve as a novel useful marker for regional nuchal adipose tissue. NST is highly associated with body mass and waist-to-height ratio, and easily measurable in routine MRI monitoring of brain tumor patients.

Establishment of normative biometric data for body composition based on computed tomography in a North American cohort

BACKGROUND & AIMS

Accurate and reproducible biomarkers are required to allow a more personalized approach to patient care. Body composition is one such biomarker affecting outcomes in a range of surgical and oncological conditions. The aim of this study is to determine the age and sex specific distribution of body composition data, based on information gathered from computed tomography (CT).

METHODS

This prospective study used healthy subjects from the medical records linkage of the Rochester Epidemiology Project, based in Minnesota, USA. Each patient had a CT scan without intravenous contrast performed between 1999 and 2001. Quantification was performed using previously validated semi-automated in-house developed software for body composition analysis. Subcutaneous adipose tissue area, visceral adipose tissue area, intermuscular adipose tissue area and skeletal muscle area were measured and indexed to subject height. Generalized Additive Models for Location, Scale and Shape were used to assess the location, scale, and shape of each variable across age, stratified by sex. Z-scores specific to sex were assessed for each of the parameters analyzed. Age-specific z-scores were calculated using the formula: Z = (Index Variable - μ)/σ or Z = (√ (Index Variable) - μ)/σ.

RESULTS

There were 692 subjects enrolled in the study. The fitted model equation was offered for each variable with values presented for μ and σ. Modelling with penalized splines was performed for VAT index, IMAT index and total adipose tissue index. Scatterplots of each variable were produced with lines of Z-scores as a visual representation.

CONCLUSION

This study offers comparative data to allow comparison amongst multiple populations. This will form an important reference for future research and clinical practice.

Body Composition Using Air Displacement Plethysmography in Children With Inflammatory Bowel Disease

OBJECTIVE

The aim of the study was to assess the body composition of children with inflammatory bowel disease (IBD) and to study the accuracy of clinically available tools in predicting excess body fatness. We aimed at also exploring the influence of adiposity on pharmacokinetics during early Infliximab exposure.

METHODS

Prospective cohort study in 5- to 17-year-old children with IBD initiating Infliximab therapy. Patient demographic, phenotypic, and laboratory data at the time of Infliximab initiation were recorded. Body composition was assessed using air displacement plethysmography (ADP). fat mass index (FMI = fat mass [kg]/(height [m])) was calculated to determine excess adiposity (defined as FMI ≥75th centile). Anthropometrics (weight, height, mid upper arm circumference [MUAC] and triceps skin fold thickness [TSF]) were obtained and MUAC and TSF measurements were used to calculate arm fat area (AFA) and arm muscle area z-scores. Statistical analysis was applied as appropriate.

RESULTS

Fifty-three (68% male; 55% Crohn disease [CD], 45% ulcerative colitis [UC], median [IQR] age 15 [13-16] years) children with IBD were included. Twenty-four percentage of children with IBD (21% CD, 29% UC) had excess adiposity. Four children (31%) with FMI ≥75th centile were not identified by body mass index (BMI) alone (kappa of 0.60), and 2 children (15%) were not identified by AFA z-score alone. The intra- and interobserver reliability of MUAC and TSFT measurements was excellent. There was no difference in Infliximab trough levels at the end of induction between those with FMI less than or ≥75th centile.

CONCLUSIONS

Excess adiposity affects approximately 1 in 4 young patients with IBD and can be missed by routine obesity screening. Our exploratory study did not raise concerns of underexposure to infliximab in those children with excess adiposity during early drug exposure.

Evidences from Clinical Trials in Down Syndrome: Diet, Exercise and Body Composition

Down syndrome (DS) is related to diseases like congenital heart disease, obstructive sleep apnea, obesity and overweight. Studies focused on DS associated with obesity and overweight are still scarce. The main objective of this work was to analyze the relationship between dietary intervention, physical exercise and body composition, in DS with overweight and obesity. This review is based on the PRISMA guidelines (Preferred Reporting Items for Systematic reviews and Meta-Analyses). Selection criteria for this analysis were: publications between January 1997 and December 2019; DS individuals with overweight and obesity; clinical trials using dietary intervention and physical exercise paying attention to changes in body composition. Selected clinical trials were focused on an exclusive intervention based on physical exercise. The anthropometric measures analyzed were body fat, BMI, waist circumference, body weight and fat free mass. The main conclusion is that prescribing structured physical exercise intervention may be related to a greater variation in body composition. Despite limited number of clinical trials analyzed, it can be assumed that the reported studies have not achieved optimal results and that the design of future clinical trials should be improved. Some guidelines are proposed to contribute to the improvement of knowledge in this field.

The drive to eat in homo sapiens: Energy expenditure drives energy intake

The drive to eat is a component of appetite control, independent of the omnivorous habit of humans, and separate from food choice, satiety and food reward. The drive forms part of the tonic component of appetite and arises from biological needs; it is distinct from episodic aspects of appetite which are heavily influenced by culture and the environment (and which reflect the omnivorous habit). It is proposed that the tonic drive to eat reflects a need state generated by metabolic energy expenditure (EE) required to maintain the functioning and integrity of vital organs. Specifically, the tonic drive is quantitatively associated with fat-free mass (FFM) and resting metabolic rate (RMR). A rational proposition is that high metabolic rate organs (such as heart, liver, kidneys, brain) together with skeletal muscle generate a metabolic need which drives energy intake (EI). The basic phenomenon of a relationship between FFM, RMR and EI, first published in 2011, has been substantially replicated and there are at least 14 concordant published studies carried out in 9 different countries (and 4 continents) with various ethnic groups of lean and obese humans. These studies demonstrate that FFM and RMR represent major determinants of the drive to eat, and this is rational from an evolutionary perspective. The EE of bodily movements through skeletal muscle activity (namely physical activity and exercise) represents another driver which is clearly but more weakly associated with an increase in EI. This account of appetite control, developed within an energy balance framework, is consistent with the apparent inexorable escalation of fatness in individual humans, and for the progressive increase in the prevalence of obesity which, among other factors, reflects the difficulty of managing the biological drive to eat.

Effect of Over- and Underfeeding on Body Composition and Related Metabolic Functions in Humans

PURPOSE OF REVIEW

Methodological limitations of body composition methods limit the validity of changes in body composition that are used to interpret metabolic outcome parameters of weight loss and weight gain.

RECENT FINDINGS

Direct assessment of energy balance is necessary for the assessment of early weight changes (i.e., within the 1st week of weight change), whereas body composition analysis with a high accuracy and a low minimal detectable change is recommended to assess ongoing changes. The sequence of underfeeding and overfeeding impacts the method inherent assumptions, and the considerable day-to-day and inter-individual variance in body composition changes is a challenge to the precision of methods. Weight loss-associated changes in body composition do not resemble their changes with subsequent hypercaloric re-feeding. Individual body components are related to specific metabolic functions where the structure-function relationships change with changes in energy balance. Analysis of structure-function relationships in response to weight changes needs to address (a) the validity, precision, and different outcome parameters of body composition methods and (b) the variance of results taking into account study protocols and the dynamics of weight changes. As for future studies, repeated measurements of body weight, body composition, and metabolic functions are needed before, during, and after weight changes focusing on the intra- and interindividual variances of weight change rather than on mean data only.

The Relationship Between Tri-ponderal Mass Index and Metabolic Syndrome and Its Components in Youth Aged 10-20 Years

The current study aimed to evaluate the distribution of the tri-ponderal mass index (TMI) according to sex and age and the relationship of obesity groups according to sex- and age-specific TMI with metabolic syndrome (MetS) and its components. A total of 8,464 subjects aged 10-20 years were classified into 4 groups according to sex- and age-specific TMI: (i) underweight, (ii) normal weight, (iii) overweight, and (iv) obese. The range of the 50th percentiles of TMI was from 13.24 kg/m3 at 10 years to 12.94 kg/m3 at 20 years among males and from 12.19 kg/m3 to 12.84 kg/m3 among females. In the analysis of covariance, obesity groups according to sex- and age-specific TMI were positively correlated with waist circumference (WC) standard deviation score; systolic blood pressure (BP); diastolic BP; and levels of glucose, total cholesterol, triglycerides (TGs), and low-density lipoprotein cholesterol, but for both sexes, the obesity groups were negatively related to high-density lipoprotein cholesterol (HDL-C). In the multiple logistic regression, subjects in the overweight group had higher odds ratios (ORs) for elevated WC (29.18), elevated BP (1.33), elevated TGs (2.55), reduced HDL-C (2.31), and MetS (8.93) than those with normal weight. Participants in the obesity group had increased ORs for elevated WC (154.67), elevated BP (2.22), elevated glucose (3.54), elevated TGs (4.12), reduced HDL-C (3.69), and MetS (25.57) compared to participants with normal weight after adjustment for confounders. Our results suggest that sex- and age-specific TMI may be applicable in the clinical setting as a useful screening tool.

Practical Guidance for Interventions in Adults with Metabolic Syndrome: Diet and Exercise vs. Changes in Body Composition

(1) Objective: to establish practical guidance for the design of future clinical trials in MS (metabolic syndrome) patients aged 18 and older, based on a systematic review of randomized clinical trials connecting diet, physical exercise and changes in body composition. (2) Method: this systematic review of randomized clinical trials (RCT) is based on the guidelines recommended by PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses). Criteria of selection: ≥18 years of age; patients diagnosed with MS; intervention programs including diet, physical exercise and/or modifications in the style of life as treatment, as well as the magnitude of changes in body composition (BC); randomized clinical trial published between 2004 and 2018. (3) Results: the multidisciplinary interventions describe major changes in BC, and the recurring pattern in these clinical trials is an energy reduction and control in the percentage of intake of macronutrients along with the performance of regularly structured exercise; the most analyzed parameter was waist circumference (88.9% of the trials), followed by body weight (85.2%), BMI (77.8%) and body fat (55.6%). (4) Conclusions: The analysis of the information here reported sheds light for the design of future clinical trials in adults with MS. The best anthropometric parameters and units of measurement to monitor the interventions are related to dietary and physical exercise interventions. A list of practical advice that is easy to implement in daily practice in consultation is here proposed in order to guarantee the best results in changes of body composition.

Comparative Meta-Analysis of the Effect of Concentrated, Hydrolyzed, and Isolated Whey Protein Supplementation on Body Composition of Physical Activity Practitioners

Whey protein (WP) is a dairy food supplement and, due to its effects on fat-free mass (FFM) gain and fat mass (FM) loss, it has been widely consumed by resistance training practitioners. This review analyzed the impact of WP supplementation in its concentrated (WPC), hydrolyzed (WPH) and isolated (WPI) forms, comparing it exclusively to isocaloric placebos. Random effect meta-analyses were performed from the final and initial body composition values of 246 healthy athletes undergoing 64.5 ± 15.3 days of training in eight randomized clinical trials (RCT) collected systematically from five scientific databases. The weighted mean difference (WMD) was statistically significant for FM loss (WMD = −0.96, 95% CI = −1.37, −0.55, p < 0.001) and, in the analysis of subgroups, this effect was maintained for the WPC (WMD = −0.63, 95% CI = −1.19, −0.06, p = 0.030), with protein content between 51% and 80% (WMD = −1.53; 95% CI = −2.13, −0.93, p < 0.001), and only for regular physical activity practitioners (WMD = −0.95; 95% CI = −1.70, −0.19, p = 0.014). There was no significant effect on FFM in any of the scenarios investigated (p > 0.05). Due to several and important limitations, more detailed analyses are required regarding FFM gain.

Sub-phenotyping Metabolic Disorders Using Body Composition: An Individualized, Nonparametric Approach Utilizing Large Data Sets

OBJECTIVE

This study performed individual-centric, data-driven calculations of propensity for coronary heart disease (CHD) and type 2 diabetes (T2D), utilizing magnetic resonance imaging-acquired body composition measurements, for sub-phenotyping of obesity and nonalcoholic fatty liver disease (NAFLD).

METHODS

A total of 10,019 participants from the UK Biobank imaging substudy were included and analyzed for visceral and abdominal subcutaneous adipose tissue, muscle fat infiltration, and liver fat. An adaption of the k-nearest neighbors algorithm was applied to the imaging variable space to calculate individualized CHD and T2D propensity and explore metabolic sub-phenotyping within obesity and NAFLD.

RESULTS

The ranges of CHD and T2D propensity for the whole cohort were 1.3% to 58.0% and 0.6% to 42.0%, respectively. The diagnostic performance, area under the receiver operating characteristic curve (95% CI), using disease propensities for CHD and T2D detection was 0.75 (0.73-0.77) and 0.79 (0.77-0.81). Exploring individualized disease propensity, CHD phenotypes, T2D phenotypes, comorbid phenotypes, and metabolically healthy phenotypes were found within obesity and NAFLD.

CONCLUSIONS

The adaptive k-nearest neighbors algorithm allowed an individual-centric assessment of each individual's metabolic phenotype moving beyond discrete categorizations of body composition. Within obesity and NAFLD, this may help in identifying which comorbidities a patient may develop and consequently enable optimization of treatment.

Energy balance dynamics during short-term high-intensity functional training

CrossFit (CF; CrossFit Inc., Washington, DC, USA) is a form of high-intensity functional training that focuses on training across the entire spectrum of physical fitness. CF has been shown to improve a number of indicators of health but little information assessing energy balance exists. The purpose of the present study was to investigate energy balance during 1 week of CF training. Men and women (n = 21; mean ± SD; age, 43.5 ± 8.4 years; body mass index, 27.8 ± 4.9 kg·m−2), with ≥3 months CF experience, had body composition assessed via air displacement plethysmography before and after 1 week of CF training. Participants wore ActiHeart monitors to assess total energy expenditure (TEE), activity energy expenditure, and CF energy expenditure (CF EE). Energy intake was assessed from TEE and Δ body composition. CF EE averaged 605 ± 219 kcal per 72 ± 10 min session. Weekly CF EE was 2723 ± 986 kcal. Participants were in an energy deficit (TEE: 3674 ± 855 kcal·day−1; energy intake: 3167 ± 1401 kcal·day−1). Results of the present study indicate that CF training can account for a significant portion of daily activity energy expenditure. The weekly expenditure is within levels shown to induce clinically meaningful weight loss in overweight/obese populations.

Body composition-related functions: a problem-oriented approach to phenotyping

AIM

The objective of this study is to generate metabolic phenotypes based on structure-function relationships.

METHODS

In 459 healthy adults (54% females, 18 and 40 years old), we analyzed body composition by air-displacement densitometry (to assess fat mass, (FM) and fat-free mass (FFM)) and whole-body magnetic resonance imaging (to assess skeletal muscle mass (SMM) and masses of brain, heart, liver, kidneys, and subcutaneous (SAT) and visceral adipose tissue (VAT)), resting energy expenditure (REE) by indirect calorimetry, and plasma concentrations of insulin (Ins) and leptin (Lep).

RESULTS

Three "functional body composition-derived phenotypes" (FBCPs) were derived: (1) REE on FFM-FBCP, (2) Lep on FM-FBCP, and (3) Ins on VAT-FBCP. Assuming that being within the ± 5% range of the respective regression lines reflects a "normal" structure-function relationship, three "normal" FBCPs were generated with prevalences of 9.0%, 5.1%, and 6.8%, respectively, of the study population. The three "FBCPs" did not overlap and were independent from each other. When compared with the two other FBCPs, the "Lep on FM-FBCP" was leanest, whereas the "REE on FFM-FBCP" had the highest BMI and SAT. Taking into account FFM composition, a hierarchical multi-level model is proposed with brain at level 1, the liver at level 2, and SMM and FM at level 3 with insulin coordinating the interplay between level 1 and 2, whereas variance in plasma insulin levels impacts energy and substrate metabolism in SMM and AT.

CONCLUSION

Structure-function relationships can be used to generate FBCPs. Different FBCPs reflect different dimensions of normality (or health). This is evidence for the idea that there is no across the board "normal" state.

Human energy expenditure: advances in organ-tissue prediction models

Humans expend energy at rest (REE), and this major energy exchange component is now usually estimated using statistical equations that include weight and other predictor variables. While these formulas are useful in evaluating an individual's or group's REE, an important gap remains: available statistical models are inadequate for explaining underlying organ-specific and tissue-specific mechanisms accounting for resting heat production. The lack of such systems level REE prediction models leaves many research questions unanswered. A potential approach that can fill this gap began with investigators who first showed in animals and later in humans that REE reflects the summated heat production rates of individual organs and tissues. Today, using advanced imaging technologies, REE can be accurately estimated from the measured in vivo mass of 10 organ-tissue mass components combined with their respective mass-specific metabolic rates. This review examines the next frontier of energy expenditure models and discusses how organ-tissue models have the potential not only to better predict REE but also to provide insights into how perturbations in organ mass lead to structure-function changes across other interacting organ systems. The introductory ideas advanced in this review provide a framework for future human energy expenditure modelling research.

Recent advances in understanding body weight homeostasis in humans

Presently, control of body weight is assumed to exist, but there is no consensus framework of body weight homeostasis. Three different models have been proposed, with a "set point" suggesting (i) a more or less tight and (ii) symmetric or asymmetric biological control of body weight resulting from feedback loops from peripheral organs and tissues (e.g. leptin secreted from adipose tissue) to a central control system within the hypothalamus. Alternatively, a "settling point" rather than a set point reflects metabolic adaptations to energy imbalance without any need for feedback control. Finally, the "dual intervention point" model combines both paradigms with two set points and a settling point between them. In humans, observational studies on large populations do not provide consistent evidence for a biological control of body weight, which, if it exists, may be overridden by the influences of the obesogenic environment and culture on personal behavior and experiences. To re-address the issue of body weight homeostasis, there is a need for targeted protocols based on sound concepts, e.g. lean rather than overweight subjects should be investigated before, during, and after weight loss and weight regain. In addition, improved methods and a multi-level-multi-systemic approach are needed to address the associations (i) between masses of individual body components and (ii) between masses and metabolic functions in the contexts of neurohumoral control and systemic effects. In the future, simplifications and the use of crude and non-biological phenotypes (i.e. body mass index and waist circumference) should be avoided. Since changes in body weight follow the mismatch between tightly controlled energy expenditure at loosely controlled energy intake, control (or even a set point) is more likely to be about energy expenditure rather than about body weight itself.

Normalizing resting energy expenditure across the life course in humans: challenges and hopes

Whole-body daily energy expenditure is primarily due to resting energy expenditure (REE). Since there is a high inter-individual variance in REE, a quantitative and predictive framework is needed to normalize the data. Complementing the assessment of REE with data normalization makes individuals of different sizes, age, and sex comparable. REE is closely correlated with body mass suggesting its near constancy for a given mass and, thus, a linearity of this association. Since body mass and its metabolic active components are the major determinants of REE, they have been implemented into allometric modeling to normalize REE for quantitative differences in body weight and/or body composition. Up to now, various size and allometric scale laws are used to adjust REE for body mass. In addition, the impact of the anatomical and physical properties of individual body components on REE has been quantified in large populations and for different age groups. More than 80% of the inter-individual variance in REE is explained by FFM and its composition. There is evidence that the impact of individual organs on REE varies between age groups with a higher contribution of brain and visceral organs in children/adolescents compared with adults where skeletal muscle mass contribution is greater than in children/adolescents. However, explaining REE variations by FFM and its composition has its own limitations (inter-correlations of organs/tissues). In future, this could be overcome by re-describing the organ-to-organ variation using principal components analysis and then using the scores on the components as predictors in a multiple regression analysis.

Association between fat mass, adipose tissue, fat fraction per adipose tissue, and metabolic risks: a cross-sectional study in normal, overweight, and obese adults

BACKGROUND/OBJECTIVES

We investigated whether fat mass (FM) and total adipose tissue (TAT) can be used interchangeably and FM per TAT adds to metabolic risk assessment.

SUBJECTS/METHODS

Cross-sectional data were assessed in 377 adults (aged 18-60 years; 51.2% women). FM was measured by either 4-compartment (4C) model or quantitative magnetic resonance (QMR); total-, subcutaneous- and visceral adipose tissue (TAT, SAT, VAT), and liver fat by whole-body MRI; leptin, insulin, homeostasis model assessment of insulin resistance (HOMA-IR), C-reactive protein (CRP), and triglycerides; resting energy expenditure and respiratory quotient by indirect calorimetry were determined. Correlations and stepwise multivariate regression analyses were performed.

RESULTS

FM_4C and FM_QMR were associated with TAT (r_4C = 0.96, r_QMR = 0.99) with a mean FM per TAT of 0.85 and 1.01, respectively. Regardless of adiposity, there was a considerable inter-individual variance of FM/TAT-ratio (FM_4C/TAT-ratio: 0.77-0.94; FM_QMR/TAT-ratio: 0.89-1.10). Both, FM_4C and TAT were associated with metabolic risks. Further, FM_4C/TAT-ratio was positively related to leptin but inversely with CRP. There was no association between FM_4C/TAT-ratio and VAT/SAT or liver fat. FM_4C/TAT-ratio added to the variance of leptin and CRP.

CONCLUSIONS

Independent of FM or TAT, FM_4C/TAT-ratio adds to metabolic risk assessment. Therefore, the interchangeable use of FM and TAT to assess metabolic risks is questionable as both parameters may complement each other.

Abdominal obesity is a common finding in normal and overweight subjects of Chile and is associated with increased frequency of cardiometabolic risk factors

Background/Objectives

Abdominal obesity (AO) is associated with elevated risk for cardiovascular diseases; however, this association is less clear for non-obese people. We estimated the association of AO and cardiovascular risk factors (CVRF) and disease in non-obese adult individuals from Chile.

Subjects/Methods

5248 adults (15 years of age or older) of both sexes from the Chilean National Health Survey (October 2009 –September 2010, response rate 85%.) were included. Information on myocardial infarction and stroke was self-reported. BMI, waist circumference (WC), arterial pressure, plasma glucose, and cholesterol levels were measured. Predictive accuracy of WC was evaluated by area under curve of receiver operating characteristic analysis and cut off points were established by Youden Index. Relationship between AO and CVRF was analyzed by Chi-squared tests.

Results

Normal weight/overweight/obesity were present in 34.4%/45.2%/18.1% of men and 33.4%/33.6%/27.5% of women. Predictive accuracy of WC to identify at least one CVRF was 0.70/0.67 and optimal cutoff points for WC in non-obese subjects were 91/83 cm in men/women, respectively. AO was present in 98.2%/99.1% of obese, 70.5%/77.4% of overweight and 12.4%/16.4% of normal weight men/women. AO was associated with increased frequency of CVRF in overweight men (6/8 and stroke) and women (4/8) and higher frequency in normal weight men (8/8 and myocardial infarction/stroke) and women (6/8 and myocardial infarction).

Conclusions

WC cutoff points calculated for non-obese chilean population discriminate more differences in CVRF in normal weight woman. AO significantly increases the frequency of CVRF and diseases in overweight and especially normal weight individuals. WC can be used as a low cost, feasible and reproducible predictor for CVRF in non-obese individuals in most clinical settings.

Resting metabolic rate of obese patients under very low calorie ketogenic diet

Background

The resting metabolic rate (RMR) decrease, observed after an obesity reduction therapy is a determinant of a short-time weight regain. Thus, the objective of this study was to evaluate changes in RMR, and the associated hormonal alterations in obese patients with a very low-calorie ketogenic (VLCK)-diet induced severe body weight (BW) loss.

Method

From 20 obese patients who lost 20.2 kg of BW after a 4-months VLCK-diet, blood samples and body composition analysis, determined by DXA and MF-Bioimpedance, and RMR by indirect calorimetry, were obtained on four subsequent visits: visit C-1, basal, initial fat mass (FM) and free fat mass (FFM); visit C-2, − 7.2 kg in FM, − 4.3 kg in FFM, maximal ketosis; visit C-3, − 14.4 kg FM, − 4.5 kg FFM, low ketosis; visit C-4, − 16.5 kg FM, − 3.8 kg FFM, no ketosis. Each subject acted as his own control.

Results

Despite the large BW reduction, measured RMR varied from basal visit C-1 to visit C-2, − 1.0%; visit C-3, − 2.4% and visit C-4, − 8.0%, without statistical significance. No metabolic adaptation was observed. The absent reduction in RMR was not due to increased sympathetic tone, as thyroid hormones, catecholamines, and leptin were reduced at any visit from baseline. Under regression analysis FFM, adjusted by levels of ketonic bodies, was the only predictor of the RMR changes (R² = 0.36; p < 0.001).

Conclusion

The rapid and sustained weight and FM loss induced by VLCK-diet in obese subjects did not induce the expected reduction in RMR, probably due to the preservation of lean mass.

Trial registration

This is a follow up study on a published clinical trial.

Electronic supplementary material

The online version of this article (10.1186/s12986-018-0249-z) contains supplementary material, which is available to authorized users.

Functional correlates of detailed body composition in healthy elderly subjects

Methods of body composition analysis are now widely used to characterize health status, i.e., nutritional status, metabolic rates, and cardiometabolic risk factors. However, the functional correlates of individual body components have not been systematically analyzed. In this study, we have used a two-compartment model, which was assessed by air displacement plethysmography. Detailed body composition was measured by whole body magnetic resonance imaging in a healthy population of 40 Caucasians, aged 65–81 yr (20 men; body mass index range: 18.6–37.2 kg/m2). Physical, metabolic, as well as endocrine functions included pulmonary function, handgrip strength, gait speed, sit-to-stand test, physical activity, blood pressure, body temperature, resting energy expenditure (REE), liver and kidney functions (glomerular filtration rate), insulin sensitivity [homeostasis model assessment (HOMA)], plasma lipids, plasma leptin, testosterone, dehydroepiandrosterone, insulin-like growth factor I levels, thyroid status, vitamins, and inflammation. Individual body compartments were intercorrelated, e.g., skeletal muscle mass (SM) correlated with visceral adipose tissue ( r = 0.53) and kidneys ( r = 0.62). For the functional correlates, SM ( r = 0.58) and liver volume ( r = 0.63) were associated with REE, SM correlated with handgrip strength ( r = 0.57), and kidneys with glomerular filtration rate ( r = 0.57). While visceral adipose tissue correlated with HOMA ( r = 0.59), subcutaneous adipose tissue was related to plasma leptin levels ( r = 0.84). The subcutaneous adipose tissue-to-leptin relationship was moderated by inflammation increasing the explained variance of leptin levels by 4.0%. In linear regression analysis, detailed body composition explained variances in REE (75.0%), HOMA (41.0%), and leptin (78.0%) compared with a body mass index-based model (REE 16.0%, HOMA 31.0%, leptin 45.0%). In addition, detailed body composition explained 39.0% of the variance in kidney function.

NEW & NOTEWORTHY BCA should be used to address specific body functions only. In clinical practice, there is need of a clear focus on the specific research question related to physical, metabolic, or endocrine functions.

An Investigation Into the Differences in Bone Density and Body Composition Measurements Between 2 GE Lunar Densitometers and Their Comparison to a 4-Component Model

We describe a study to assess the precision of the GE Lunar iDXA and the agreement between the iDXA and GE Lunar Prodigy densitometers for the measurement of regional- and total-body bone and body composition in normal to obese healthy adults. We compare the whole-body fat mass by dual-energy X-ray absorptiometry (DXA) to measurements by a 4-component (4-C) model. Sixty-nine participants, aged 37 ± 12 yr, with a body mass index of 26.2 ± 5.1 kg/cm², were measured once on the Prodigy and twice on the iDXA. The 4-C model estimated fat mass from body mass, total body water by deuterium dilution, body volume by air displacement plethysmography, and bone mass by DXA. Agreements between measurements made on the 2 instruments and by the 4-C model were analyzed by Bland-Altman and linear regression analyses. Where appropriate, translational cross-calibration equations were derived. Differences between DXA software versions were investigated. iDXA precision was less than 2% of the measured value for all regional- and whole-body bone and body composition measurements with the exception of arm fat mass (2.28%). We found significant differences between iDXA and Prodigy (p < 0.05) whole-body and regional bone, fat mass (FM), and lean mass, with the exception of hip bone mass, area and density, and spine area. Compared to iDXA, Prodigy overestimated FM and underestimated lean mass. However, compared to 4-C, iDXA showed a smaller bias and narrower limits of agreement than Prodigy. No significant differences between software versions in FM estimations existed. Our results demonstrate excellent iDXA precision. However, significant differences exist between the 2 GE Lunar instruments, Prodigy and iDXA measurement values. A divergence from the reference 4-C observations remains in FM estimations made by DXA even following the recent advances in technology. Further studies are particularly warranted in individuals with large FM contents.

Stress-Related Changes in Body Form: Results from the Whitehall II Study

OBJECTIVE

Stress is associated with body mass gain in some people but with body mass loss in others. When the stressor persists, some people adapt with their stress responses, whereas others do not. Heart rate variability (HRV) reflects autonomic variability and is related to stress responses to psychosocial challenges. It was hypothesized that the combined effects of stress exposure and autonomic variability predict long-term changes in body form.

METHODS

Data of 1,369 men and 612 women from the Whitehall II cohort were analyzed. BMI, hip-to-height ratio, and waist-to-height ratio were measured at three time points over a 10-year period. HRV and psychological distress (General Health Questionnaire) were assessed.

RESULTS

Men with high psychological distress were at risk of developing an increased waist-to-height ratio (F = 3.4, P = 0.038). Men with high psychological distress and low HRV were prone to develop an increased body mass and hip-to-height ratio (psychological distress: F = 4.3, P = 0.016; HRV: F = 5.0, P = 0.008). Statistical trends showed that women displayed similar patterns of stress-related changes in body form (P = 0.061; P = 0.063).

CONCLUSIONS

Assessing psychological distress and autonomic variability predicts changes in body form. Psychological distress was found to be associated with an increased risk of developing the wide-waisted phenotype, while psychological distress combined with low autonomic variability was associated with an increased risk of developing the corpulent phenotype.

Association of body composition assessed by bioelectrical impedance analysis with metabolic risk factor clustering among middle-aged Chinese

Body composition monitor (BCM) based on the bioelectric impedance analysis is very convenient to use. However, whether percentage body fat (PBF) and visceral fat index (VFI) that acquired by BCM are superior to anthropometric measures is unknown. The study explored whether PBF and VFI are better than anthropometric indexes [body mass index (BMI), waist circumference (WC) and waist circumference to height ratio(WHtR)] in predicating metabolic risk factor clustering in a representive sample across China which included 9574 Chinese men and women that were investigated in 2009–2010. PBF and VFI were compared with the BMI, WC, and WHtR through the area under the curve (AUC) of the receiver operating characteristic (ROC) curve and logistic regression. The results showed that the AUC for VFI was higher than BMI and PBF but lower than WHtR and WC in both men and Women. The AUC for WHtR, WC, VFI, BMI and PBF was 0.710, 0.706, 0.700, 0.693, 0.656 in men and 0.705, 0.699, 0.698, 0.675, 0.657 in women, respectively. After adjusting for the potential confounding factors, the odds ratios (ORs) tended to increase with all the indexes. The curve of ORs for WHtR was steepest and the curve for PBF was flattest in both men and women; the curve for VFI was similar to WC in women, but flatter than WC in men. From the data we concluded that VFI seems better than BMI and PBF, but not superior to WC and WHtR in predicating metabolic risk factor clustering in the middle-aged Chinese.

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Controversy remains with regard to the best index for diagnosis of obesity.

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A representive sample of 9574 middle-aged Chinese across China were analyzed.

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The value of Visceral fat index (VFI) and percentage body fat (PBF) were explored.

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VFI seems better than BMI and PBF in predicating metabolic risk factor clustering.

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VFI is not superior to WC and WHtR in predicating metabolic risk factor clustering.