Body composition: Where and when

Body composition and peri- and postoperative complications in patients with gynaecological malignancies: A systematic review

BACKGROUND

In general abdominal surgery, the ratio of fat to muscle mass, or body composition measures, shows a stronger association with complications than body mass index. These studies include male and female patients. Women have a different body composition than men. Therefore, findings from general abdominal surgery cannot be extrapolated to women with cancer. The aim of this systematic review is to summarise the evidence on the association between body composition and peri- and postoperative complications in patients with gynaecological cancer.

METHODS

Pubmed, Embase and the Cochrane Central databases were searched in June 2023. Studies were eligible if they included patients undergoing surgery for gynaecological cancer and reported on the association between body composition (muscle or fat mass) and surgical complications. The quality of the studies was assessed using the Newcastle-Ottawa quality assessment scale. A best-evidence synthesis was used to summarise the level of evidence.

RESULTS

Fifteen studies were included that assessed muscle mass (n = 9) or fat mass (n = 6). We found strong evidence that there was no association between visceral fat and length of hospital stay. We found moderate evidence that a higher amount of good quality muscle was associated with a lower risk of postoperative complications. We found moderate evidence that there was no association between muscle or fat mass (i.e., muscle- or subcutaneous fat) and postoperative complications or fat mass and intraoperative complications. There was insufficient evidence for an association between visceral fat and intraoperative or postoperative complications, and for an association between muscle mass or -quality and length of hospital stay. There was high heterogeneity in the methods used to measure body composition, hampering meta-analyses.

CONCLUSION

The association between body composition, particularly adipose tissue and muscle quality, and complications suggests that these measures may be of interest in determining postoperative risk in women undergoing surgery for gynaecological cancer.

Dietary supplementation with black cricket (Gryllus assimilis) reverses protein-energy malnutrition and modulates renin-angiotensin system expression in adipose tissue

Edible insects are recognized as promising food sources due to their nutritional composition. Some species, such as Gryllus assimilis, contain proteins, lipids, and carbohydrates of high biological value, which regulate several metabolic functions, including the Renin-Angiotensin System (RAS). In this context, the present study aimed to assess the effects of dietary supplementation with whole Gryllus assimilis powder on the metabolism of malnourished mice. Thirty-two male Swiss mice were used and divided into four treatment groups. The groups were identified as (AIN93-M); AIN93-M + Gryllus assimilis diet (AIN93-M + GA); AIN93-M + Renutrition diet (AIN93-M + REN) and AIN93-M + Renutrition diet + Gryllus assimilis (AIN93-M + REN + GA). The results showed that whole Gryllus assimilis powder inclusion promotes recovery from protein-energy malnutrition, reduces adiposity, and improves glucose tolerance and insulin sensitivity. It also reduces total cholesterol, triglycerides, VLDL, and adipocyte area. We also observed a significant increase in the expression of RAS-related genes, such as ACE2 and MasR, followed by a reduction in Angiotensinogen and ACE. The main findings of the present study suggest the use of black cricket as a viable strategy for the prevention and treatment of protein-energy malnutrition, as well as the reduction of adiposity, and improvement of lipid and glycemic parameters, with antihypertensive potential.

Preoperative body composition measured by bioelectrical impedance analysis can predict pancreatic fistula after pancreatic surgery

BACKGROUND

Postoperative pancreatic fistula (POPF) remains one of the most severe complications after pancreatic surgery. The methods for predicting pancreatic fistula are limited. We aimed to investigate the predictive value of body composition parameters measured by preoperative bioelectrical impedance analysis (BIA) on the development of POPF.

METHODS

A total of 168 consecutive patients undergoing pancreatic surgery from March 2022 to December 2022 at our institution were included in the study and randomly assigned at a 3:2 ratio to the training group and the validation group. All data, including previously reported risk factors for POPF and parameters measured by BIA, were collected. Risk factors were analyzed by univariable and multivariable logistic regression analysis. A prediction model was established to predict the development of POPF based on these parameters.

RESULTS

POPF occurred in 41 of 168 (24.4%) patients. In the training group of 101 enrolled patients, visceral fat area (VFA) (odds ratio [OR] = 1.077, P = 0.001) and fat mass index (FMI) (OR = 0.628, P = 0.027) were found to be independently associated with POPF according to multivariable analysis. A prediction model including VFA and FMI was established to predict the development of POPF with an area under the receiver operating characteristic curve (AUC) of 0.753. The efficacy of the prediction model was also confirmed in the internal validation group (AUC 0.785, 95% CI 0.659-0.911).

CONCLUSIONS

Preoperative assessment of body fat distribution by BIA can predict the risk of POPF after pancreatic surgery.

Body composition in early pubescent children with obesity: effects following 1 year of nonintervention

Little is known about whether body composition changes differently between children with and without obesity following 1 year of nonintervention. Therefore, we investigated body composition in early pubescent children (8-12 yr) with and without obesity before and after a period of 1 year of nonintervention. Early pubescent children (8-12 yr; Tanner stage ≤ 3) with (body mass index, BMI ≥ 95th percentile) and without obesity (15th < BMI < 85th percentile) were recruited. At baseline, 88 children (n = 25 without obesity) completed dual-energy X-ray absorptiometry imaging (DXA) for body composition measurements [%body fat, fat mass, fat-free mass (FFM)]. One year later, 47 participants (n = 15 without obesity) returned for repeat testing. The children without obesity were older (11.0 ± 1.0 vs. 10.0 ± 1.2 yr; means ± SD) (P = 0.013). There was no group difference in height, and both groups increased in height similarly after 1 year (147.7 ± 8.9 to 154.5 ± 9.2 cm without vs. 145.6 ± 5.8 to 152.5 ± 5.9 cm with obesity) (P < 0.001). Weight was greater (P < 0.001) in children with obesity at baseline as was the increase in weight after 1 yr (9.25 vs. 5.82 kg) (interaction, P = 0.005). Fat mass increased by 4.4 kg in children with obesity and by 1.1 kg in children without obesity (interaction, P < 0.001). However, there was no difference in fat-free mass between those with and without obesity at baseline (29.9 ± 5.9 vs. 31.6 ± 4.8 kg) (P = 0.206) with both groups increasing similarly over 1 year (gain of 4.87 vs. 4.85 kg with and without obesity, respectively). Without intervention, the increase in fat mass is four times greater in children with obesity after 1 year as compared with children without obesity.NEW & NOTEWORTHY Little is known about changes in body composition in children with and without obesity following 1 year of nonintervention. We report that without intervention, fat mass gain is significantly greater in children with obesity after 1 year compared with those without obesity. Body mass index (BMI) and %body fat measurements after 1 year yielded no significant increase suggesting that BMI and %fat alone are not suitable measures for tracking changes in adiposity among children.

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.

Phase Angle in Head and Neck Cancer: A Sex-Differential Analysis from Biological and Clinical Behavior to Health-Related Quality of Life

Head and neck cancer (H&NC) is a diverse category of tumors related to malignancies in the common aerodigestive pathway, with high metabolic rate, poor nutritional and treatment outcomes, and elevated mortality despite the best standard treatment. Herein, we focus on determining how the phase angle (PA) differs across sex as a predictor of poor prognosis, low quality-of-life (QoL) scores, and mortality in patients with head and neck cancer. This follow-up study presents a sex-differential analysis in a prospective cohort of 139 head and neck cancer patients categorized by sex as male (n = 107) and female (n = 32). Patients were compared in terms of nutritional, biochemical, and quality-of-life indicators between low and normal PA in women (<3.9° (n = 14, 43.75%) and ≥3.9°) and men (<4.5° (n = 62, 57.9%) and ≥4.5°). Our results show that most patients were in locally advanced clinical stages (women: n = 21 (65.7%); men: n = 67 (62.6%)) and that patients with low PA had a lower punctuation in parameters such as handgrip strength, four-meter walking speed, albumin, C-reactive protein (CRP), and CRP/albumin ratio (CAR), as well as the worst QoL scores in functional and symptomatic scales in both the male and female groups. A comparison between sexes revealed significant disparities; malnourishment and tumor cachexia related to an inflammatory state was more evident in the women's group.

Efficacy of cardiometabolic drugs in reduction of epicardial adipose tissue: a systematic review and meta-analysis

BACKGROUND

Epicardial adipose tissue (EAT) plays an important role in cardiometabolic risk. EAT is a modifiable risk factor and could be a potential therapeutic target for drugs that already show cardiovascular benefits. The aim of this study is to evaluate the effect of cardiometabolic drugs on EAT reduction.

METHODS

A detailed search related to the effect on EAT reduction due to cardiometabolic drugs, such as glucagon-like peptide-1 receptor agonist (GLP-1 RA), sodium-glucose cotransporter-2 inhibitors (SGLT2-i), and statins was conducted according to PRISMA guidelines. Eighteen studies enrolling 1064 patients were included in the qualitative and quantitative analyses.

RESULTS

All three analyzed drug classes, in particular GLP-1 RA, show a significant effect on EAT reduction (GLP-1 RA standardize mean difference (SMD) = - 1.005; p < 0.001; SGLT2-i SMD = - 0.552; p < 0.001, and statin SMD = - 0.195; p < 0.001). The sensitivity analysis showed that cardiometabolic drugs strongly benefit EAT thickness reduction, measured by ultrasound (overall SMD of - 0.663; 95%CI - 0.79, - 0.52; p < 0.001). Meta-regression analysis revealed younger age and higher BMI as significant effect modifiers of the association between cardiometabolic drugs and EAT reduction for both composite effect and effect on EAT thickness, (age Z: 3.99; p < 0.001 and Z: 1.97; p = 0.001, respectively; BMI Z: - 4.40; p < 0.001 and Z: - 2.85; p = 0.004, respectively).

CONCLUSIONS

Cardiometabolic drugs show a significant beneficial effect on EAT reduction. GLP-1 RA was more effective than SGLT2-i, while statins had a rather mild effect. We believe that the most effective treatment with these drugs should target younger patients with high BMI.

Changes in the body composition of boys aged 11-18 years due to COVID-19 measures in the Czech Republic

BACKGROUND

The lockdown measures related to coronavirus disease 2019 (COVID) impacted the health of adolescents by reducing physical activity (PA). The physical changes in response to decreases in PA can be measured with full body composition analysis. The aim of this study was to evaluate the effects of long-term PA restrictions on body fat (BF), fat-free mass (FFM) and skeletal muscle mass (SMM) in adolescents.

METHODS

A total of 1669 boys (before PA restriction (G1): 998; after PA restrictions ended (G2): 671; between the ages of 11 and 18 were included. The measured parameters were body mass (BM), visceral fat area (VFA), BF, FFM and SMM. The whole-body composition was evaluated using bioelectrical impedance analysis (BIA).

RESULTS

Compared to G1, G2 exhibited an increase in BF between 1.2 and 5.1%. This difference was significant in boys aged 13 to 18 years (p < 0.05). VFA increased between 5.3 and 20.5 cm²; this increase was significant in boys aged 13 to 18 years (p < 0.05). SMM decreased between 2.6 and 3.8%, and this decrease was significant in all age groups (p < 0.05). Changes in body composition were not accompanied by any significant changes in BM.

CONCLUSIONS

COVID-19 restrictions reduced PA, resulting in a significant decrease in SMM. This decrease may impact boys' ability to engage in sufficiently varied PA, which may lead to a further decline in PA and subsequent medical consequences in adulthood.

Ultra-processed food consumption is associated with increase in fat mass and decrease in lean mass in Brazilian women: A cohort study

Objective

To investigate the association between ultra-processed food consumption at 23–25 years of age and measurements of body composition–fat mass, fat mass distribution and lean mass at 37–39 years of age in Brazilian adults.

Methods

1978/1979 birth cohort study conducted with healthy adults from Ribeirão Preto, São Paulo, Brazil. A total of 1,021 individuals participated in the fat mass analysis (measured by air displacement plethysmography) and 815 in the lean mass analysis and fat mass distribution (assessed by dual energy X-ray absorptiometry). Food consumption was evaluated by a food frequency questionnaire. Food items were grouped according to the level of processing as per the NOVA classification. Ultra-processed food consumption was expressed as a percentage of total daily intake (g/day). Linear regression models were used to estimate the effect of ultra-processed food consumption (g/day) on body mass index, body fat percentage, fat mass index, android fat, gynoid fat, android-gynoid fat ratio, lean mass percentage, lean mass index and appendicular lean mass index. Marginal plots were produced to visualize interactions.

Results

The mean daily ultra-processed food consumption in grams was 35.8% (813.3 g). There was an association between ultra-processed food consumption and increase in body mass index, body fat percentage, fat mass index, android fat and gynoid fat and decrease in lean mass percentage, only in women.

Conclusion

A high ultra-processed food consumption is associated with a long-term increase in fat mass and a decrease in lean mass in adult women.

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 Relationship between Phase Angle, Nutrition Status, and Complications in Patients with Pancreatic Head Cancer

Phase angle (PhA), a bioimpedance parameter, is used to assess the nutrition status and body composition of patients. Patients with pancreatic head cancer often present with body composition changes that relate to adverse outcomes. PhA may be useful to evaluate prognosis in these patients, but data are deficient. We aim to explore the effects of PhA on nutrition evaluation and short-term outcome prediction in these patients. This prospective study included 49 participants with pancreatic head cancer who underwent pancreaticoduodenectomy (PD). All participants’ nutritional status and postoperative complications were assessed using nutrition assessment tools and the Clavien−Dindo classification method, respectively. Spearman correlation analyses were used to evaluate the association between PhA, nutrition status, and postoperative complications. ROC curves were generated to evaluate the ability of PhA to predict malnutrition and complications and to determine the cutoff value. The PhA values of the nutritional risk group and the malnourished group were significantly lower than those of the well-nourished group (p < 0.05). PhA positively correlated with patients’ nutrition status. Nineteen patients had postoperative complications, and the PhA value of the complication group was significantly lower than that of the non-complication group (4.94 vs. 5.47, p = 0.013). ROC curves showed that the cutoff point of PhA to predict malnutrition was 5.45 (AUC: 0.744), and the cutoff point of PhA to predict postoperative complications was 5.35 (AUC: 0.717). Our study indicates that PhA was associated with nutrition status and could be considered a nutrition assessment tool for pancreatic head cancer patients and predict the postoperative complications of these patients who have undergone PD.

Body Mass Index (BMI): A Screening Tool Analysis

Body mass index (BMI), a measurement based on a person’s height and weight, allows the classification of individuals into categories such as obese or overweight. With these classifications, we can assess risk for hypertension, diabetes, cancer, hypercholesterolemia, and other chronic diseases. Furthermore, childhood BMI serves as a prediction method for health and disease later in life. Along with BMI, researchers also study waist circumference and waist-to-hip ratio in correlation with the above-mentioned chronic illnesses. This brief review explores the associations between body mass index, waist circumference, and the waist-hip ratio as measurements and their capability as predictors for persistent conditions like diabetes and hypertension.

The Association of Dietary Energy Density and Body Composition Components in a Sample of Iranian Adults

Background: We aimed to investigate the association between the energy density (ED) of diet and body composition components in Iranian adults.

Methods: We conducted a cross-sectional study on 267 adults in Tehran. We obtained ED (kcal/g) using the two most common methods: ED1, ED from foods only with the exclusion of all beverages and ED2, from foods and all beverages. Body composition was measured using a multifrequency bio-impedance analysis. To find a strong association, we used both the linear and binary regression analysis in the three adjusted models.

Results: The mean of ED1 and ED2 was 1.34 ± 0.23 and 0.89 ± 0.20 kcal/g, respectively. Increasing the ED of diet in both methods was associated with a high intake of dietary fat, of saturated fatty acid (SFA), of monounsaturated fatty acid (MUFA), of polyunsaturated fatty acid (PUFA), of oleic and linoleic acids, accompanied by a low intake of fruits, vegetables, and some vitamins and minerals. There was a significant positive relationship between fat-free mass index (FFMI) and ED1 (β = 4.44, p = 0.02). However, we found no significant association between the consumption of ED1 and fat mass index (FMI) (0.28; 95% CI 0.08, 0.98; p = 0.07), and abdominal obesity (0.91; 95% CI 0.43, 1.94; p = 0.82). Also, ED2 had no association with FMI (0.86; 95% CI 0.26, 2.80; p = 0.81) and abdominal obesity (0.78; 95% CI 0.35, 1.72; p = 0.54). No significant associations were found between ED and other anthropometric indices and body composition components after considering the confounders.

Conclusion: This study supports the positive association between ED and poor dietary quality. However, our findings did not show significant associations of dietary energy density (DED) with anthropometric indices and body composition components. Further well-designed studies are required to investigate the exact link between DED and body composition.

Normal anthropometry does not equal normal body composition in pediatric intestinal failure

BACKGROUND

Published reports on abnormal body composition in pediatric patients with intestinal failure have been in patients with poor growth. The goal of the current study is to report the body composition of normally growing patients with intestinal failure.

METHODS

Children 8-18 years old with a dual-energy x-ray absorptiometry (DXA) between January 1, 2013, and July 15, 2018, were included in the study. Data were retrospectively collected from the medical charts and included demographics, residual bowel anatomy, nutrition support, height, and weight. DXA data, including total body less head bone mineral density (BMD), fat mass (FM), and fat-free mass (FFM), were collected and compared with published literature controls matched for age and sex.

RESULTS

Thirty-four children met inclusion criteria. Mean age at the time of DXA was 9.6 ± 1.8 years. Weight- and height-for-age z-scores were -0.4 ± 0.9 and -0.5 ± 1.0, respectively. Mean BMD z-score was -1.0 ± 1.3. Twenty-six percent of patients (n = 9) had reduced BMD. Patients with intestinal failure had higher FM (P = .02) and lower FFM (P = .02) compared with controls.

CONCLUSIONS

These data show that, despite reference range z-scores for height and weight, children with intestinal failure are at risk for abnormal body composition. Body composition should be routinely measured in children with intestinal failure to direct nutrition interventions.

Body composition in patients with rheumatoid arthritis: a narrative literature review

There is growing interest in the alterations in body composition (BC) that accompany rheumatoid arthritis (RA). The purpose of this review is to (i) investigate how BC is currently measured in RA patients, (ii) describe alterations in body composition in RA patients and (iii) evaluate the effect on nutrition, physical training, and treatments; that is, corticosteroids and biologic Disease Modifying Anti-Rheumatic Disease (bDMARDs), on BC in RA patients. The primary-source literature for this review was acquired using PubMed, Scopus and Cochrane database searches for articles published up to March 2021. The Medical Subject Headings (MeSH) terms used were 'Arthritis, Rheumatoid', 'body composition', 'sarcopenia', 'obesity', 'cachexia', 'Absorptiometry, Photon' and 'Electric Impedance'. The titles and abstracts of all articles were reviewed for relevant subjects. Whole-BC measurements were usually performed using dual energy x-ray absorptiometry (DXA) to quantify lean- and fat-mass parameters. In RA patients, lean mass is lower and adiposity is higher than in healthy controls, both in men and women. The prevalence of abnormal BC conditions such as overfat, sarcopenia and sarcopenic obesity is significantly higher in RA patients than in healthy controls; these alterations in BC are observed even at an early stage of the disease. Data on the effect treatments on BC in RA patients are scarce. In the few studies published, (a) creatine supplementation and progressive resistance training induce a slight and temporary increase in lean mass, (b) exposure to corticosteroids induces a gain in fat mass and (c) tumour necrosis factor alpha (TNFα) inhibitors might be associated with a gain in fat mass, while tocilizumab might be associated with a gain in lean mass. The available data clearly demonstrate that alterations in BC occur in RA patients, but data on the effect of treatments, especially bDMARDs, are inconsistent and further studies are needed in this area.

Reproducibility of total and regional body composition using dual-energy X-ray absorptiometry in rheumatoid arthritis and ankylosing spondylitis

Several studies have reported changes in body composition in rheumatoid arthritis (RA) and ankylosing spondylitis (AS). Our study showed that body composition measurements obtained by absorptiometry were highly reproducible in patients suffering from these diseases. This study justifies the use of absorptiometry measurements in longitudinal studies in this population.

PURPOSE

Our study aimed to assess the reproducibility of total and regional body composition in patients with rheumatoid arthritis (RA) and with ankylosing spondylitis (AS) and to compare them to healthy subjects.

METHODS

The study enrolled 80 subjects including 32 healthy subjects, 31 RA patients, and 17 AS patients. Each subject had two scans in one day under the same standard conditions and none ate nor drunk before being repositioned on the table. The reproducibility was assessed through the coefficient of variation (CV), the least significant change (LSC), the intraclass correlation (ICC), and the smallest significant difference (SDD).

RESULTS

Total body composition measurements obtained by dual-energy X-ray absorptiometry (DXA) were highly reproducible, and there was no statistically significant difference between reproducibility in healthy subjects, patients with RA, and patients with AS. For total body fat mass (FM), lean mass (LM), and bone mineral content (BMC) in the total population, CV values were 1.71%, 1.25%, and 1.74%, respectively; ICC values were 0.998, 0.996, and 0.993, respectively; LSC values were 4.88%, 3.7%, and 5.2%, respectively; and SDD values were ± 1.23 Kg, ± 1.47 Kg, and ± 126.0 g, respectively. For regional body FM, LM, and BMC in the total population, CV values in the arms were 8.46%, 4.17%, and 3.79%, respectively; in the legs 6.24%, 3.59%, and 2.04%, respectively, and in the trunk 5.02%, 2.92%, and 5.24%, respectively.

CONCLUSION

Total body tissue mass, FM percentage, FM, LM, and BMC measurements obtained by DXA are highly reproducible in RA and AS.

Concurrent validity of five prediction equations to evaluate fat percentage in a sports group expected to yield high performance from Medellín, Colombia

INTRODUCTION

No equations to predict the body composition of athletes from Medellín expected to have high performance have been constructed and, thus, decisions regarding their training and nutrition plans lack support.

OBJECTIVE

To calculate the concurrent validity of five prediction equations for fat percentage in a group of athletes from Medellín, Colombia, expected to yield high performance.

MATERIALS AND METHODS

We conducted a cross-sectional analysis to validate diagnostic tests using secondary-source data of athletes under the age of 18 who were part of the "Medellín Team". The gold standard was dual-energy X-ray densitometry (DEXA). We analyzed the Slaughter, Durnin and Rahaman, Lohman, and Johnston prediction equations, as well as the five-component model. We used the intraclass correlation coefficient to assess the consistency of the methods and the Bland-Altman plot to calculate the average bias and agreement limits of each of the equations.

RESULTS

We included 101 athletes (50,5 % of them women). The median age was 14,8 years (IR: 13,0 - 16,0). The concurrent validity was "good/excellent" for the Johnston and the Durnin and Rahaman equations and the five-components model. The Lohman equation overestimated the fat percentage in 12,7 points. All of the equations showed broad agreement limits.

CONCLUSIONS

The Durnin and Rahaman and the Johnston equations, as well as the fivecomponent model, can be used to predict the FP in the study population as they showed a "good/excellent" concurrent validity and a low average bias. The equations analyzed have low accuracy, which hinders their use to diagnose the individual fat percentage within this population.

Ultrasound imaging, a stethoscope for body composition assessment

Dysregulation of the human's energy balance, mediated by non-performing endocrine organs (liver, skeletal muscle and adipose tissue, above all), can be related to human metabolic disorders characterized by an impaired body composition (BC), such as obesity and sarcopenia. While it is possible to monitor the BC and its variations at different levels, the tissue-organ composition studies have been proven to provide the most clinically applicable information. Ultrasonography (US), a fast, non-invasive, low-cost and widely available technique, holds great potential in the study of BC, as it can directly measure muscles, organs, visceral and subcutaneous fat tissue in different sections of the abdomen and body, overcoming some limits of anthropometric evaluation and other imaging techniques. Purpose of this review article is to explore the technical aspects and the applied methods of US examination to assess the potential clinical role of this technique in the context of BC characterization, investigating four pivotal topics [abdominal fat compartments, subcutaneous adipose tissue (SAT), skeletal muscle, liver].

Magnetic resonance imaging assessment of body composition parameters in Crohn's disease

BACKGROUND

Body composition, currently evaluated by computed tomography scan, is related to poor evolution and severity of Crohn's disease (CD). Few MRI studies have been performed, yet it is the most commonly used imaging modality for the surveillance of the disease.

AIM

Evaluate the feasibility of MRI body composition measurement and compare the variation according to the activity of the disease.

METHODS

A cohort of 132 consecutive patients was studied. The visceral adiposity index (VAI), subcutaneous adiposity index (SAI) and skeletal muscle index (SMI) were measured. Patients were divided into 2 groups according to disease activity. Sarcopenic status was defined according to the cut off value (SMI < 38.9 cm²/m² in women and < 54.4 cm²/m² in men).

RESULTS

MRI measurements of body composition parameters were feasible and reproducible. After adjustment, sarcopenia was more common (2.07 [1.02; 4.27], p = 0.046), and the SMI (-4.90 [-9.36; -0.431], p = 0.032) was lower in active disease. The SAI was lower (-14.7 [-29.8; 0.258], p = 0.054) in active disease. The VAI tended to be higher with active disease (3.91 [-3.50; 11.9], p = 0.34), and the VAI/SAI+VAI ratio was higher (9.40 [4.72; 14.1], p<0.001).

CONCLUSION

Assessment of body composition is feasible and reproducible in routine MR and parameters are related to disease activity.

ABCNet: A new efficient 3D dense-structure network for segmentation and analysis of body tissue composition on body-torso-wide CT images

PURPOSE

Quantification of body tissue composition is important for research and clinical purposes, given the association between the presence and severity of several disease conditions, such as the incidence of cardiovascular and metabolic disorders, survival after chemotherapy, etc., with the quantity and quality of body tissue composition. In this work, we aim to automatically segment four key body tissues of interest, namely subcutaneous adipose tissue, visceral adipose tissue, skeletal muscle, and skeletal structures from body-torso-wide low-dose computed tomography (CT) images.

METHOD

Based on the idea of residual Encoder-Decoder architecture, a novel neural network design named ABCNet is proposed. The proposed system makes full use of multiscale features from four resolution levels to improve the segmentation accuracy. This network is built on a uniform convolutional unit and its derived units, which makes the ABCNet easy to implement. Several parameter compression methods, including Bottleneck, linear increasing feature maps in Dense Blocks, and memory-efficient techniques, are employed to lighten the network while making it deeper. The strategy of dynamic soft Dice loss is introduced to optimize the network in coarse-to-fine tuning. The proposed segmentation algorithm is accurate, robust, and very efficient in terms of both time and memory.

RESULTS

A dataset composed of 38 low-dose unenhanced CT images, with 25 male and 13 female subjects in the age range 31-83 yr and ranging from normal to overweight to obese, is utilized to evaluate ABCNet. We compare four state-of-the-art methods including DeepMedic, 3D U-Net, V-Net, Dense V-Net, against ABCNet on this dataset. We employ a shuffle-split fivefold cross-validation strategy: In each experimental group, 18, 5, and 15 CT images are randomly selected out of 38 CT image sets for training, validation, and testing, respectively. The commonly used evaluation metrics - precision, recall, and F1-score (or Dice) - are employed to measure the segmentation quality. The results show that ABCNet achieves superior performance in accuracy of segmenting body tissues from body-torso-wide low-dose CT images compared to other state-of-the-art methods, reaching 92-98% in common accuracy metrics such as F1-score. ABCNet is also time-efficient and memory-efficient. It costs about 18 h to train and an average of 12 sec to segment four tissue components from a body-torso-wide CT image, on an ordinary desktop with a single ordinary GPU.

CONCLUSIONS

Motivated by applications in body tissue composition quantification on large population groups, our goal in this paper was to create an efficient and accurate body tissue segmentation method for use on body-torso-wide CT images. The proposed ABCNet achieves peak performance in both accuracy and efficiency that seems hard to improve any more. The experiments performed demonstrate that ABCNet can be run on an ordinary desktop with a single ordinary GPU, with practical times for both training and testing, and achieves superior accuracy compared to other state-of-the-art segmentation methods for the task of body tissue composition analysis from low-dose CT images.

Agreement between software programmes of body composition analyses on abdominal computed tomography scans of obese adults

Objective A large number of studies have used abdominal computed tomography (CT) to quantify body composition, and different software programmes have been used to perform these analyses. Thus, this comparison is important to enable researchers to know the performance of more accessible software. Subjects and methods Fifty-four abdominal CT scans of obese (BMI 30 to 39.9 kg/m2), sedentary adults (24-41 years) patients from a Brazilian single center were selected. Two software programs were compared: Slice-O-Matic (Tomovision, Canada) version 5.0 and OsiriX version 5.8.5. The body composition analysis were segmented using standard Hounsfield unit (HU) (adipose tissue: -190 to +30 and skeletal muscle: -29 to +150) and measured at the mid third lumbar vertebra (L3) level on a slice showing both transversal processes. Bland-Altman limits of agreement analyses were used to assess the level of agreement between Slice-O-Matic and OsiriX. Results A total of fifty-four participants were evaluated, with majority women (69%), mean of age 31.3 (SD 6.5) years and obesity grade I most prevalent (74.1%). The agreement, in Bland-Altman analysis, between Slice-O-Matic and OsiriX analisys for the muscle mass tissue, visceral adipose tissue and subcutaneous adipose tissue were excellent (≥ 0.954) with P-values < 0.001. Conclusion These findings show that Slice-O-Matic and OsiriX softwares agreement in measurements of skeletal muscle and adipose tissue and sarcopenia diagnosis in obese patients, suggesting good applicability in studies with body composition in this population and clinical practice.

Body composition in children with chronic inflammatory diseases: A systematic review

BACKGROUND & AIMS

Aberrations in body composition are expected in children suffering from chronic inflammatory conditions. The objective is to examine whether children with inflammatory bowel disease (IBD: Crohn's disease and ulcerative colitis), coeliac disease, asthma and juvenile idiopathic arthritis (JIA) have an altered body composition as compared to healthy children.

METHODS

A systematic review, registered in Prospero (registration number: CRD42018107645), was conducted according to PRISMA guidelines. We conducted a search of three databases, Pubmed, Cochrane and Scopus. An assessment of the quality of the study was performed.

RESULTS

Data from 50 studies, 32 with IBD, 8 with coeliac disease, 2 with asthma and 8 with JIA, involving 2399 children were selected for review after applying the eligibility criteria. In all but 4 studies, children with Crohn's disease exhibited decreased amounts of fat mass and fat free mass. Reductions in fat mass were also evident in studies in children with coeliac disease. It is uncertain whether body composition is altered in children with asthma or JIA.

CONCLUSIONS

Children with Crohn's disease manifest with lowered adiposity and lean mass and therefore are likely to be at risk for suffering malnutrition-related clinical complications. Apart from Crohn's disease, data examining body composition in children with chronic inflammatory conditions are scarce and there is a paucity of reports examining the relationship between inflammation and body composition. Interpretation of the current study results is hampered by the low quality of the studies and due to the fact that the analyses have been habitually secondary outcomes.

Genomics of body fat percentage may contribute to sex bias in anorexia nervosa

Anorexia nervosa (AN) occurs nine times more often in females than in males. Although environmental factors likely play a role, the reasons for this imbalanced sex ratio remain unresolved. AN displays high genetic correlations with anthropometric and metabolic traits. Given sex differences in body composition, we investigated the possible metabolic underpinnings of female propensity for AN. We conducted sex-specific GWAS in a healthy and medication-free subsample of the UK Biobank (n = 155,961), identifying 77 genome-wide significant loci associated with body fat percentage (BF%) and 174 with fat-free mass (FFM). Partitioned heritability analysis showed an enrichment for central nervous tissue-associated genes for BF%, which was more prominent in females than males. Genetic correlations of BF% and FFM with the largest GWAS of AN by the Psychiatric Genomics Consortium were estimated to explore shared genomics. The genetic correlations of BF%male and BF%female with AN differed significantly from each other (p < .0001, δ = -0.17), suggesting that the female preponderance in AN may, in part, be explained by sex-specific anthropometric and metabolic genetic factors increasing liability to AN.

Obesity and sarcoidosis: consequence or contributor?

PURPOSE OF REVIEW

Sarcoidosis is a multisystem disease of unknown cause. Obesity can affect many physiological factors. The relationship between obesity and sarcoidosis is unclear, and can been described as posing a 'chicken and egg' scenario for the patient as it is not always clear whether it is a consequence of, or a risk factor for any disease. The purpose of this review is to examine the dual roles of obesity on sarcoidosis morbidity and the incidence.

RECENT FINDINGS

Obesity magnifies the symptoms of sarcoidosis and corticosteroid therapy increases BMI. Prospective epidemiologic studies started to explore the role of obesity as a potential risk factor for sarcoidosis. Three studies in the United States, and one study in Denmark, have demonstrated significantly increased risks of sarcoidosis among obese compared with nonobese patients; risk estimates ranged from 1.42 [95% confidence interval (CI), 1.07-1.89] to 3.59 (95% CI, 2.31-5.57).

SUMMARY

Obesity can be both a consequence of sarcoidosis treatment, and a contributor to disease risk likely through the pro-inflammatory environment of obesity. Prospective epidemiologic cohort studies are needed to explore the cause of sarcoidosis and insight into possible avenues of treatment development and prevention.

Challenges and opportunities to tackle the rising prevalence of diet-related non-communicable diseases in Africa

Africa is experiencing a sharp rise in non-communicable diseases (NCD) related to rapid globalisation and urbanisation leading to shifts in dietary and lifestyle patterns characterised by increased energy intake and physical inactivity. However, unlike more resource-endowed regions, Africa has a double burden of disease: NCD co-exist with infectious diseases including lower respiratory tract infections, HIV/AIDS and diarrhoeal diseases. The African economy is also relatively weaker, making it difficult to cope with this burden. It is postulated that NCD will soon overtake infectious diseases as the number one cause of death in the African region. The recognition of NCD as diseases and obesity as a related risk factor is weak in Africa, compounded by stigma associated with wasting in HIV/AIDS and obesity being perceived as a sign of wealth, achievement and care. There is also a dearth of data on overweight and obesity in the region and little knowledge that infant feeding practices, such as breast-feeding, are linked to reduced risk of NCD in both children and mothers. While complex multi-sectoral approaches to address this NCD menace are needed, Africa may benefit from taking simple initial steps to address NCD risk factors including: (1) behaviour change communication to challenge perceptions on NCD; (2) promoting and protecting breast-feeding; (3) formulating policies and regulations limiting wide availability of unhealthy foods; (4) mainstream nutrition education in school curricula and (5) collection of accurate data based on indicators that can reflect the double burden of disease and malnutrition; and fostering multi-sectoral actions against NCD.

Percentage of Body Fat and Fat Mass Index as a Screening Tool for Metabolic Syndrome Prediction in Colombian University Students

High body fat is related to metabolic syndrome (MetS) in all ethnic groups. Based on the International Diabetes Federation (IDF) definition of MetS, the aim of this study was to explore thresholds of body fat percentage (BF%) and fat mass index (FMI) for the prediction of MetS among Colombian University students. A cross-sectional study was conducted on 1687 volunteers (63.4% women, mean age = 20.6 years). Weight, waist circumference, serum lipids indices, blood pressure, and fasting plasma glucose were measured. Body composition was measured by bioelectrical impedance analysis (BIA) and FMI was calculated. MetS was defined as including more than or equal to three of the metabolic abnormalities according to the IDF definition. Receiver operating curve (ROC) analysis was used to determine optimal cut-off points for BF% and FMI in relation to the area under the curve (AUC), sensitivity, and specificity in both sexes. The overall prevalence of MetS was found to be 7.7%, higher in men than women (11.1% vs. 5.3%; p < 0.001). BF% and FMI were positively correlated to MetS components (p < 0.05). ROC analysis indicated that BF% and FMI can be used with moderate accuracy to identify MetS in university-aged students. BF% and FMI thresholds of 25.55% and 6.97 kg/m² in men, and 38.95% and 11.86 kg/m² in women, were found to be indicative of high MetS risk. Based on the IDF criteria, both indexes’ thresholds seem to be good tools to identify university students with unfavorable metabolic profiles.

Body composition estimation from selected slices: equations computed from a new semi-automatic thresholding method developed on whole-body CT scans

Background

Estimating volumes and masses of total body components is important for the study and treatment monitoring of nutrition and nutrition-related disorders, cancer, joint replacement, energy-expenditure and exercise physiology. While several equations have been offered for estimating total body components from MRI slices, no reliable and tested method exists for CT scans. For the first time, body composition data was derived from 41 high-resolution whole-body CT scans. From these data, we defined equations for estimating volumes and masses of total body AT and LT from corresponding tissue areas measured in selected CT scan slices.

Methods

We present a new semi-automatic approach to defining the density cutoff between adipose tissue (AT) and lean tissue (LT) in such material. An intra-class correlation coefficient (ICC) was used to validate the method. The equations for estimating the whole-body composition volume and mass from areas measured in selected slices were modeled with ordinary least squares (OLS) linear regressions and support vector machine regression (SVMR).

Results and Discussion

The best predictive equation for total body AT volume was based on the AT area of a single slice located between the 4th and 5th lumbar vertebrae (L4-L5) and produced lower prediction errors (|PE| = 1.86 liters, %PE = 8.77) than previous equations also based on CT scans. The LT area of the mid-thigh provided the lowest prediction errors (|PE| = 2.52 liters, %PE = 7.08) for estimating whole-body LT volume. We also present equations to predict total body AT and LT masses from a slice located at L4-L5 that resulted in reduced error compared with the previously published equations based on CT scans. The multislice SVMR predictor gave the theoretical upper limit for prediction precision of volumes and cross-validated the results.