Estimate Body Composition Research Articles

Effect of Menstrual Cycle Phase and Hormonal Contraceptives on Resting Metabolic Rate and Body Composition.

The cyclical changes in sex hormones across the menstrual cycle (MC) are associated with various biological changes that may alter resting metabolic rate (RMR) and body composition estimates. Hormonal contraceptive (HC) use must also be considered given their impact on endogenous sex hormone concentrations and synchronous exogenous profiles. The purpose of this study was to determine if RMR and dual-energy X-ray absorptiometry body composition estimates change across the MC and differ compared with HC users. This was accomplished during a 5-week training camp involving naturally cycling athletes (n = 11) and HC users (n = 7 subdermal progestin implant, n = 4 combined monophasic oral contraceptive pill, n = 1 injection) from the National Rugby League Indigenous Women's Academy. MC phase was retrospectively confirmed via serum estradiol and progesterone concentrations and a positive ovulation test. HC users had serum estradiol and progesterone concentrations assessed at the time point of testing. Results were analyzed using general linear mixed model. There was no effect of MC phase on absolute RMR (p = .877), relative RMR (p = .957), or dual-energy X-ray absorptiometry body composition estimates (p > .05). There was no effect of HC use on absolute RMR (p = .069), relative RMR (p = .679), or fat mass estimates (p = .766), but HC users had a greater fat-free mass and lean body mass than naturally cycling athletes (p = .028). Our findings suggest that RMR and dual-energy X-ray absorptiometry body composition estimates do not significantly differ due to changes in sex hormones in a group of athletes, and measurements can be compared between MC phases or with HC usage without variations in sex hormones causing additional noise.

Body composition and resting energy expenditure in a group of children with achondroplasia

BackgroundPersons with achondroplasia develop early obesity, which is a comorbidity associated with other complications. Currently, there are no validated specific predictive equations to estimate resting energy expenditure in achondroplasia. MethodsWe analyzed the influence of body composition on this parameter and determined whether predictive models used for children with standard height are adjusted to achondroplasia. In this cross-sectional study, we measured anthropometric parameters in children with achondroplasia. Fat mass was obtained using the Slaughter skinfold-thickness equation and resting energy expenditure was determined with a Fitmate-Cosmed calorimeter and with predictive models validated for children with average height (Schofield, Institute of Medicine, and Tverskaya). ResultsAll of the equations yielded a lower mean value than resting energy expenditure with indirect calorimetry (1256±200 kcal/day [mean±SD]) but the closest was the Tverskaya equation (1017 ± 64 kcal/day), although the difference remained statistically significant. We conclude that weight and height have the greatest influence on resting energy expenditure. ConclusionWe recommend studying the relationship between body composition and energy expenditure in achondroplasia in more depth. In the absence of valid predictive models suitable for clinical use to estimate body composition and resting energy expenditure in achondroplasia, it is recommended to use the gold standard methods by taking into account certain anthropometric parameters.

A Case Study of the Short-Term Development of Body Composition and Substrate Utilization Following Prolonged Low-Intensity Ski Trekking with Inadequate Energy Intake in Svalbard

This case study aimed to examine the short-term development of body composition and substrate utilization (i.e., contribution of fat and carbohydrates to energy supply) following prolonged low-intensity ski trekking (LIST) with inadequate energy intake in an Arctic region. For 23 days, two highly aerobically fit, male recreational athletes (24 and 26 years) performed ~2 – 11 hours of LIST each day, while pulling supply sledges (initially ~80 kg) across the length of Svalbard’s largest island, Spitsbergen (~640 km). We estimated body composition using bioelectrical impedance analysis (BIA). For evaluation of substrate utilization, we analyzed pulmonary respiratory gas-exchange ratio (RER) using an ergospirometry system during treadmill trekking (ski trekking simulation). Results indicated that the energy intake of each participant during this unsupported expedition was ~21.4 MJ·day-1 (~5107 kcal·day-1), of which ~33% (~5.0 g·kg-1·day-1), ~51% (~3.4 g·kg-1·day-1), and ~16% (~2.4 g·kg-1·day-1) came from carbohydrates, fat, and proteins, respectively. Body mass decreased by 7.2 kg (8.4%) in Subject A, and 4.4 kg (5.2%) in Subject B. Absolute fat mass decreased by 5.4 kg (37%) and 4.7 kg (30%) in Subject A and Subject B, respectively, whereas the changes in fat-free mass (–1.8 kg in Subject A, and +0.3 kg in Subject B) were within the random measurement error of the BIA analyser. Changes in RER in Subject A (–0.01 to –0.02 units) were within the random measurement error, whereas the RER data in Subject B were not interpretable due to excessive fluctuations in ventilatory equivalent for oxygen. In conclusion, this study indicates that short-term, prolonged LIST, performed with an energy deficit corresponding to a weight loss of ~2 kg·week-1, can lead to leaner body composition without notable changes in fat-free mass in well-trained, male recreational athletes. Furthermore, substrate utilization does not appear to be affected by short-term, prolonged LIST in this subgroup of athletes.

14–21 éves sportolók klasszikus antropometriai és modern műszeres technikákkal becsült testzsírszázalékának összehasonlító elemzése

Currently, one of the most accurate measurements of body composition components, including the fat content of the body is based on the method of dual X-ray absorptiometry (DEXA). The application of the DEXA method in clinical setting is usually limited to the assessment of bone health status due to the device’s cost and immobile nature, therefore in sport diagnostics the body composition estimation is usually carried out with other methods, such as bioimpedance analysis or anthropometrical methods based on the measurement of body dimensions, which ensure a rapid, accurate and frequently repeatable way of examination. For our research goal we choose the comparison of the most frequently used body fat percentage estimation methods. The accuracy of the other methods in the light of the DEXA estimations is presented. Sport Sciences and Diagnostic Research Centre of the Hungarian Handball Federation coordinated the assessment of 171 young elite handball players (14–21-year-olds), whose body composition estimations were performed in the spring and summer of 2023. The preliminary analysis of body fat percentage estimates in handball players carried out with different methods showed that the rapid and cost-efficient estimations based on anthropometric skinfold measurements can substitute the body fat percentage estimation method based on the clinically acclaimed golden standard dual X-ray absorptiometry technology. Body fat percentage estimation via InBody 770 device showed significantly lower values compared to the DEXA method, however this difference was consistent, therefore body composition assessment via InBody device can serve as an alternative of monitoring personal progress and status. We also carried out examinations with a novel ultrasound technology aided by BodyMetrix device, its subcutaneous fat thickness measurement estimated accurately the skinfold thicknesses on human body, its body fat percentage estimation based the skinfold thicknesses was adequately accurate compared to the DEXA method. With the aid of available DEXA measurement results and with the aim of creating an alternative method with low instrument requirement for body fat percentage estimation, which can be used with the highest accuracy particularly considering the body composition of young elite athletes, we created a modified sport-specific body fat percentage estimation equation. Our new estimation method was based on classical anthropometric skinfold measurements, and it accurately correlated with the DEXA body fat% estimates in case of young elite handball players.

Athletic bioimpedance-based equations underestimate fat free mass components in male elite soccer players: development and validation of new soccer-specific predictive models

BackgroundBioelectrical impedance analysis (BIA) is a rapid and user-friendly technique for assessing body composition in sports. Currently, no sport-specific predictive equations are available, and the utilization of generalized formulas can introduce systematic bias. The objectives of this study were as follows: (i) to develop and validate new predictive models for estimating fat-free mass (FFM) components in male elite soccer players; (ii) to evaluate the accuracy of existing predictive equations.MethodsA total of 102 male elite soccer players (mean age 24.7 ± 5.7 years), participating in the Italian first league, underwent assessments during the first half of the in-season period and were randomly divided into development and validation groups. Bioelectrical resistance (R) and reactance (Xc), representing the bioimpedance components, were measured using a foot-to-hand BIA device at a single frequency of 50 kHz. Dual-energy X-ray absorptiometry was employed to acquire reference data for FFM, lean soft tissue (LST), and appendicular lean soft tissue (ALST). The validation of the newly developed predictive equations was conducted through regression analysis, Bland–Altman tests, and the area under the curves (AUC) of regression receiver operating characteristic (RROC) curves.ResultsDeveloped models were: FFM = − 7.729 + (body mass × 0.686) + (stature2/R × 0.227) + (Xc × 0.086) + (age × 0.058), R2 = 0.97, Standard error of estimation (SEE) = 1.0 kg; LST = − 8.929 + (body mass × 0.635) + (stature2/R × 0.244) + (Xc × 0.093) + (age × 0.048), R2 = 0.96, SEE = 0.9 kg; ALST = − 24.068 + (body mass × 0.347) + (stature2/R × 0.308) + (Xc × 0.152), R2 = 0.88, SEE = 1.4 kg. Train-test validation, performed on the validation group, revealed that generalized formulas for athletes underestimated all the predicted FFM components (p < 0.01), while the new predictive models showed no mean bias (p > 0.05), with R2 values ranging from 0.83 to 0.91, and no trend (p > 0.05). The AUC scores of the RROC curves indicated an accuracy of 0.92, 0.92, and 0.74 for FFM, LST, and ALST, respectively.ConclusionsThe utilization of generalized predictive equations leads to an underestimation of FFM and ALST in elite soccer players. The newly developed soccer-specific formulas enable valid estimations of body composition while preserving the portability of a field-based method.

Accuracy and precision of multiple body composition methods and associations with muscle strength in athletes of varying hydration: The Da Kine Study

BackgroundAthletes vary in hydration status due to ongoing training regimes, diet demands, and extreme exertion. With water being one of the largest body composition compartments, its variation can cause misinterpretation of body composition assessments meant to monitor strength and training progress. In this study, we asked what accessible body composition approach could best quantify body composition in athletes with a variety of hydration levels. MethodsThe Da Kine Study recruited collegiate and intramural athletes to undergo a variety of body composition assessments including air-displacement plethysmography (ADP), deuterium-oxide dilution (D2O), dual-energy X-ray absorptiometry (DXA), underwater-weighing (UWW), 3D-optical (3DO) imaging, and bioelectrical impedance (BIA). Each of these methods generated 2- or 3-compartment body composition estimates of fat mass (FM) and fat-free mass (FFM) and was compared to equivalent measures of the criterion 6-compartment model (6CM) that accounts for variance in hydration. Body composition by each method was used to predict abdominal and thigh strength, assessed by isokinetic/isometric dynamometry. ResultsIn total, 70 (35 female) athletes with a mean age of 21.8 ± 4.2 years were recruited. Percent hydration (Body Water6CM/FFM6CM) had substantial variation in both males (63- 73%) and females (58- 78%). ADP and DXA FM and FF M had moderate to substantial agreement with the 6C model (Lin’s Concordance Coefficient [CCC] = 0.90-0.95) whereas the other measures had lesser agreement (CCC < 0.90) with one exception of 3DO FFM in females (CCC = 0.91). All measures of FFM produced excellent precision with %CV < 1.0 %. However, FM measures in general had worse precision (% CV < 2.0%). Increasing quartiles (significant p<0.001 trend) of 6CM FFM resulted in increasing strength measures in males and females. Moreover, the stronger the agreement between the alternative methods to the 6CM, the more robust their correlation with strength, irrespective of hydration status. ConclusionThe criterion 6CM showed the best association to strength regardless of the hydration status of the athletes for both males and females. Simpler methods showed high precision for both FM and FFM and those with the strongest agreement to the 6CM had the highest strength associations. Summary BoxThis study compared various body composition analysis methods in 70 athletes with varying states of hydration to the criterion 6-compartment model and assessed their relationship to muscle strength. The results showed that accurate and precise estimates of body composition can be determined in athletes, and a more accurate body composition measurement produces better strength estimates. The best laboratory-based techniques were air displacement plethysmography and dual-energy x-ray absorptiometry, while the commercial methods had moderate-poor agreement. Prioritizing accurate body composition assessment ensures better strength estimates in athletes.

Phase Angle and Body Composition As a Prognostic Factor in Acute Lymphoblastic Leukemia

Acute lymphoblastic leukaemia (ALL) is a malignant proliferation of lymphoid cells blocked at an early stage of differentiation that can invade bone marrow, blood, and extramedullary sites. Age specific incidence is highest in children aged 1-4 years, then drops sharply through childhood (5-14 years), adolescence and young adulthood (AYA) (15-39 years), reaching the lowest point between 25 years and 45 years. Bioelectrical impedance analysis (BIA) is a method used to estimate body composition and cell membrane integrity. BIA is a useful tool as it is non-invasive, relatively inexpensive, can be performed on nearly any patient, does not expose the patient to ionizing radiation, is painless, and has both high intra and inter observer precision (coefficient of variation = 2.7%-4.0%). Phase angle (PhA) is obtained by BIA and is associated with cellular function. It is considered a reliable marker of malnutrition. PhA has been shown to predict survival in solid malignancies and hematopoietic stem cell transplant patients. To date, no studies have evaluated the usage of PhA in ALL patients. Therefore, this retrospective study sought to establish the prognostic significance of baseline PhA and lean mass index on OS and LFS in newly diagnosed ALL patients receiving intensive chemotherapy. Retrospective, cross-section, observational and descriptive study. The records of patients who received intensive chemotherapy from January 2019 to January 2023 were reviewed. Statistical analysis The qualitative variables were studied in frequencies and proportions, the quantitative variables were grouped into medians and ranges. OS and LFS were determined using Kaplan-Meier survival curves with log-Rank with a significant p &amp;lt;0.05 value. Statistical analysis was performed with SPSS version 25 and GraphPad Prism version 9.5.0. Results 85 patients were included, 56.7% (48) men and 43.5% (37) women. 79 patients with ALL-B and 6 patients ALL-T. The mean age was 25 years. 68 were AYA population and 17 not-AYA. The CR was 89%, ND MRD was 57%. The chemotherapy for AYA was CALGB 10403, and not AYA was Hyper-CVAD. Relapse was documented in 38%. The mean body mass index was 26.98±5.27 kg/m 2. The mean PhA was 4.547±0.9983°. The mean lean mass index was 17.8 (12.9-35.5) kg/m 2. The mean fat mass index was 9.195±4.425 kg/m 2. The mean OS was 86% at 1 year and OS at 3 years was 64.5%. The results that were statistically significant in LFS compared by Kaplan Meier curves were: male vs female p=0.0344, PhA &amp;gt;4, p=0.0235, lean mass index ≥16, p=0.0111. Conclusions In conclusion, our findings suggest that in newly diagnosed ALL patients undergoing intensive induction chemotherapy, PhA may provide important prognostic information for LFS and OS. PhA is an objective, repeatable, high-precision measure in ALL patients and, unlike other prognostic factors in this population, is potentially subject to intervention. Future studies of PhA in ALL patients should address the content validity of phase angle while further exploring the promising findings of the effect of strength training and nutritional supplementation on PhA and patient outcomes.

Neck circumference as a potential indicator of pre-sarcopenic obesity in a cohort of community-based individuals

ESPEN/EASO advocates screening for sarcopenic obesity based on the concomitant presence of an elevated body mass index (BMI) or waist circumference. Neck circumference (NC) is another simple and reliable anthropometric measurement for estimating obesity; however, its ability to detect sarcopenic obesity has not yet been established. The aim of the present study was to explore the association between NC and sarcopenic obesity in a Shanghai community population. The study included 1542 participants (622 men and 920 women) with a mean age of 58 years who underwent an examination for the detection of obesity at baseline in 2013-2014 and received a re-examination in 2015-2016. An automatic bioelectric impedance analyzer was used to estimate body composition, and magnetic resonance imaging was used to measure abdominal fat distribution. The definition of pre-sarcopenic obesity combined low skeletal muscle mass adjusted by weight (SMM/W) with obesity which defined according to overall adiposity or fat distribution as BMI ≥25kg/m2, fat percentage (fat%)≥25% in men and 30% in women, or visceral fat area (VFA)≥80cm2, respectively. In both men and women, subjects with low SMM/W had a higher level of NC than those without (both P<0.01). In turn, participants with elevated NC had a higher proportion of pre-sarcopenic obesity in both men and women, regardless of adiposity status assessed by BMI, fat%, or VFA (all P<0.01). During an average follow up of 2.1 years, for each 1cm increase in NC, multivariable-adjusted hazard ratios of pre-sarcopenic obesity in which adiposity status assessed by high BMI were 1.40 (1.11-1.76) in men and 1.32 (1.13-1.56) in women; in addition, such association remained between NC and pre-sarcopenic obesity assessed by high fat% or high VFA. NC is closely associated with the incidence of sarcopenic obesity, suggesting that it could be helpful for screening sarcopenic obesity in a community-based population.

Relationship Between Body Mass Index and Body Fat Percentage in a Group of Indian Participants: A Cross-Sectional Study From a Tertiary Care Hospital.

Background Body mass index (BMI) is an important indicator of overweight and obesity. Unlike BMI, body fat percentage (BF%) can be utilized to estimate body composition regardless of weight and height. The association between BMI and BF%, as well as the impact of age and gender, may help estimate the prevalence of obesity more clearly. This study aimed to assess the relationship between BMI and BF%, examine the effect of age and gender on this relationship, and establish the linearity/curvilinearity of this relationship. Methodology The body composition analysis of 1,150 participants in various institutional events (institution foundation day) during 2019 and 2023 was performed using the Accuniq bio-electrical impedance analyzer (BIA) (Accuniq, Netherlands). The participants included undergraduate, postgraduate medical, and PhD students, as well as employees of All India Institute of Medical Sciences, New Delhi. Age groups were categorized as under 17 years, young adults (18-25 years), adults (26-44 years), middle-aged adults (45-59 years), and older adults (≥60 years). Pearson's correlation coefficient (r) was used for analyzing the relationship between BMI and BF%. To assess the effect of age and gender on this relationship, multiple regression analysis was applied, and polynomial regression was applied to test its linearity. The data were analyzed using SPSS version 25 (IBM Corp., Armonk, NY, USA). Results Males made up a larger proportion of the participants (56.3%; 647). The mean age of the participants was 36.5 ± 13.6 years. The mean BMI and BF% were 24.7 ± 4.0 kg/m2 and 29.1 ± 8.7%, respectively. A significant and moderate positive correlation (r = 0.630, p < 0.01) was observed between BMI and BF%. The mean ± SD of BMI and BF% had a directly proportional relationship with age. Among both genders, females showed a greater correlation (r = 0.852). Both age and gender had a significant effect on this relationship, with gender impacting more than age (β = 0.488, p < 0.000). The curvilinear nature of the relationship between BMI and BF% was demonstrated with the female model showing a more precise fit (R2 = 0.72, standard error of the estimate = 3.3%). Conclusions The relationship between BMI and BF% was significant and positive in this group ofIndians. This relationship was significantly impacted by age and gender and was curvilinear in nature. Females had a higher association than males between BMI and BF%. The study suggests that BMI, BF%, and the effects of age and gender should be taken into consideration when predicting obesity.

Reference values for body composition in healthy urban Mexican children and adolescents.

Given the increasing incidence of chronic degenerative diseases related to changes in tissues, the availability of diagnostic tools with greater accuracy in the estimation of body composition (BC) has become necessary. Interpreting the BC values of individuals requires reference data obtained from a healthy population with the same ethnicity, to identify individuals at risk for the development of negative health outcomes. Generate reference values (RV) of body composition (BC) for Mexican children and adolescents. This was an urban-population-based cross-sectional study of healthy Mexican children and adolescents. BC estimations by anthropometry, multifrequency bioimpedance analysis (MF-BIA) and dual-energy X-ray absorptiometry (DXA) where used to create sex- and age-specific RV by means of generalized additive models for location, scale and shape (GAMLSS). We assessed 2104 subjects, and after confirming a clinically and metabolically healthy status, we measured 1659 subjects aged 5-20 years, [806 females (49%) and 853 males (51%)] by anthropometry, MF-BIA and DXA to create sex- and age- smoothed reference centiles, lambda (L), mu (M), and sigma (S) values. We also built sex- and age-smoothed graphic curves for each variable of interest. We present valid RV and curves for BC variables estimated by anthropometry, MF-BIA and DXA from clinically and metabolically healthy urban Mexican children and adolescents. These RV are different from those reported for other populations, and therefore, should be used for clinical and research purposes involving urban Mexican children and adolescents.

Body composition of infants at 6 months of age using a 3-compartment model.

Two compartment (2 C) models of body composition, including Air Displacement Plethysmography (ADP) and Deuterium Dilution (DD), assume constant composition of fat-free mass (FFM), while 3-compartment (3 C) model overcomes some of these assumptions; studies are limited in infants. The objective of the present study is to compare 3 C estimates of body composition in 6-mo. old infants from Australia, India, and South Africa, including FFM density and hydration, compare with published literature and to evaluate agreement of body composition estimates from ADP and DD. Body volume and water were measured in 176 healthy infants using ADP and DD. 3C-model estimates of fat mass (FM), FFM and its composition were calculated, compared between countries (age and sex adjusted) and with published literature. Agreement between estimates from ADP and DD were compared by Bland-Altman and correlation analyses. South African infants had significantly higher % FM (11.5%) and density of FFM compared to Australian infants. Australian infants had significantly higher % FFM (74.7 ± 4.4%) compared to South African infants (71.4 ± 5.0) and higher FFMI (12.7 ± 0.8 kg/m2) compared to South African (12.3 ± 1.2 kg/m2) and Indian infants (11.9 ± 1.0 kg/m2). FFM composition of present study differed significantly from literature. Pooled three country estimates of FM and FFM were comparable between ADP and DD; mean difference of -0.05 (95% CI: -0.64, +0.55) kg and +0.05 (95% CI: -0.55, +0.64) kg. 3C-model estimates of body composition in infants differed between countries; future studies are needed to confirm these findings and investigate causes for the differences.

Muscle Mass and Serum Creatinine Concentration by Race and Ethnicity among Hemodialysis Patients.

Serum creatinine is a product of skeletal muscle metabolism. Differences in serum creatinine concentration between Black and non-Black individuals have been attributed to differences in muscle mass but have not been thoroughly examined. Furthermore, other race and ethnic groups have not been considered. If differences in body composition explain differences in serum concentration by race or ethnicity, then estimates of body composition could be used in eGFR equations rather than race. Adjustment for intracellular water (ICW) as a proxy of muscle mass among patients with kidney failure in whom creatinine clearance should minimally influence serum concentration does not explain race- and ethnicity-dependent differences. Differences in serum creatinine concentration among groups defined by race and ethnicity have been ascribed to differences in muscle mass. We examined differences in serum creatinine by race and ethnicity in a cohort of patients receiving hemodialysis in whom creatinine elimination by the kidney should have little or no effect on serum creatinine concentration and considered whether these differences persisted after adjustment for proxies of muscle mass. We analyzed data from 501 participants in the A Cohort Study to Investigate the Value of Exercise in ESKD/Analyses Designed to Investigate the Paradox of Obesity and Survival in ESKD study who had been receiving hemodialysis for >1 year. We examined the independent associations among race and ethnicity (Black, Asian, non-Hispanic White, and Hispanic), serum creatinine, and ICW (L/m 2 ), a proxy for muscle mass, derived by whole-body multifrequency bioimpedance spectroscopy, using multivariable linear regression with adjustment for several demographic, clinical, and laboratory characteristics. We examined the association of race and ethnicity with serum creatinine concentration with and without adjustment for ICW. Black, Asian, and Hispanic patients had higher serum creatinine concentrations (+1.68 mg/dl [95% confidence interval (CI), 1.09 to 2.27], +1.61 mg/dl [95% CI, 0.90 to 2.32], and +0.83 [95% CI, 0.08 to 1.57], respectively) than non-Hispanic White patients. Overall, ICW was associated with serum creatinine concentration (0.26 mg/dl per L/m 2 ICW; 95% CI, 0.006 to 0.51) but was not statistically significantly different by race and ethnicity. Black, Asian, and Hispanic race and ethnicity remained significantly associated with serum creatinine concentration after adjustment for ICW. Among patients receiving dialysis, serum creatinine was higher in Black, Asian, and Hispanic patients than in non-Hispanic White patients. Differences in ICW did not explain the differences in serum creatinine concentration across race groups.

Bioimpedance analysis predicts the etiology of cirrhosis in a prospective cohort study.

Obesity is associated with an increased risk of developing cirrhosis. However, body mass index (BMI) and waist-to-hip ratio (WHR) may not be indicative of body composition parameters that predispose to cirrhosis. Bioimpedance analysis (BIA) is a noninvasive cost-efficient method for more detailed estimation of body composition. We examined patients with cirrhosis who underwent BIA as part of enrollment into a prospective cohort study. We examined the correlation between BIA variables, BMI, and WHR. We performed sex-adjusted and race-adjusted and race-specific multivariable logistic regression analyses to examine the association between anthropometric variables and risk factors [NAFLD, alcohol-associated liver disease (ALD), and HCV]. We analyzed data from 348 cirrhosis patients; 23.3% were women; 48.3% were non-Hispanic White; 19.3% were Hispanic; and 30.7% were African American. The cirrhosis etiology was 21.8% NAFLD, 56.9% HCV mostly cured, and 11.5% ALD. Several BIA variables correlated well with BMI, and others showed modest correlations, but none correlated well with WHR. Higher body fat mass and basal metabolic rate were positively associated, while higher lean body mass, dry lean mass, total body water, or skeletal muscle mass were negatively associated with NAFLD. Associations between these BIA parameters and ALD-related cirrhosis were in the opposite direction. These associations of BIA variables were seen only in Hispanic and non-Hispanic White patients but not non-Hispanic Blacks. BIA variables were more predictive of cirrhosis etiology than BMI or WHR. Among patients with cirrhosis, several BIA-derived measurements indicative of body fat and muscle are associated with NAFLD and ALD etiology. BIA variables show stronger associations, as well as race/ethnicity-specific associations, with cirrhosis etiology than those of BMI or WHR.

Association of pre-diagnostic physical exercise and peri-diagnostic body composition with mortality in non-metastatic colorectal cancer

PurposeSarcopenia and myosteatosis, quantified via computed tomography (CT), are associated with poor colorectal cancer outcomes. These body composition estimates can be influenced by physical exercise. We explored the correlation between pre-diagnostic physical exercise, body composition close to diagnosis, and the combined prognosis impact of these factors.MethodsWe studied 519 stage I–III colorectal cancer (CRC) cases diagnosed 2000–2016 with pre-diagnostic self-reported recreational physical exercise data collected in the prospective, population-based Northern Sweden Health and Disease Study, and CT-estimated skeletal muscle index (SMI) or skeletal muscle density (SMD). Risk estimates were calculated by multivariable logistic regression and Cox proportional hazards models.ResultsNo association was seen between low pre-diagnostic physical exercise and sarcopenia/myosteatosis in the multivariable model adjusted for age, sex, educational level, tumor stage, and tumor location. In multivariable Cox regression models, the combination of low pre-diagnostic physical exercise and either sarcopenia or myosteatosis at the time of diagnosis was associated with cancer-specific mortality compared to the reference group of high physical exercise combined with no sarcopenia/myosteatosis (adjusted HR 1.94 95% CI 1.00–3.76 for sarcopenia and adjusted HR 2.39 95% CI 1.16–4.94 for myosteatosis).ConclusionsThe combined presence of low pre-diagnostic physical exercise and sarcopenia or myosteatosis was associated with increased CRC-specific mortality. Despite the positive effect on prognosis, physical exercise did not alter body composition estimates at diagnosis, which could indicate attenuation from other factors.

Cross-sectional assessment of body composition and detection of malnutrition risk in participants with low body mass index and eating disorders using 3D optical surface scans

BackgroundNew recommendations for the assessment of malnutrition and sarcopenia include body composition, specifically reduced muscle mass. Three-dimensional optical imaging (3DO) is a validated, accessible, and affordable alternative to dual X-ray absorptiometry (DXA). ObjectiveIdentify strengths and weaknesses of 3DO for identification of malnutrition in participants with low body mass index (BMI) and eating disorders. DesignParticipants were enrolled in the cross-sectional Shape Up! Adults and Kids studies of body shape, metabolic risk, and functional assessment and had BMI of <20 kg/m2 in adults or <85% of median BMI (mBMI) in children and adolescents. A subset was referred for eating disorders evaluation. Anthropometrics, scans, strength testing, and questionnaires were completed in clinical research centers. Lin’s Concordance Correlation Coefficient (CCC) assessed agreement between 3DO and DXA; multivariate linear regression analysis examined associations between weight history and body composition. ResultsAmong 95 participants, mean ± SD BMI was 18.3 ± 1.4 kg/m2 in adult women (N = 56), 19.0 ± 0.6 in men (N = 14), and 84.2% ± 4.1% mBMI in children (N = 25). Concordance was excellent for fat-free mass (FFM, CCC = 0.97) and strong for appendicular lean mass (ALM, CCC = 0.86) and fat mass (FM, CCC = 0.87). By DXA, 80% of adults met the low FFM index criterion for malnutrition, and 44% met low ALM for sarcopenia; 52% of children and adolescents were <−2 z-score for FM. 3DO identified 95% of these cases. In the subset, greater weight loss predicted lower FFM, FM, and ALM by both methods; a greater percentage of weight regained predicted a higher percentage of body fat. Conclusions3DO can accurately estimate body composition in participants with low BMI and identify criteria for malnutrition and sarcopenia. In a subset, 3DO detected changes in body composition expected with weight loss and regain secondary to eating disorders. These findings support the utility of 3DO for body composition assessment in patients with low BMI, including those with eating disorders.This trial was registered at clinicaltrials.gov as NCT03637855.

Increased total daily energy expenditure in mild to moderate ALS: greater contribution from physical activity energy expenditure than hyper-metabolism

Objective It is unknown whether the relative contribution to energy imbalance in amyotrophic lateral sclerosis (ALS) is due to decreased energy intake, or increased energy expenditure from hyper-metabolism and/or physical activity, or both. Methods We studied 10 free-living sporadic ALS subjects with mild to moderate disease and 10 matched healthy controls to address this question. We estimated energy intake by 24-h recall in ALS subjects and three-day food diary in all. We estimated body composition by dual energy X-ray absorptiometry and resting metabolic rate by indirect calorimetry; and measured total daily energy expenditure (TEE) and physical activity-energy expenditure using doubly labeled water. Results Daily energy intake was no different between ALS subjects and controls. Despite lower fat-free mass, unadjusted TEE was higher in ALS subjects than controls (2844 ± 319 vs. 2505 ± 261 kcal/d, p = 0.005 by paired t-test). Compared to controls, hyper-metabolism occurred in 80% of ALS subjects. Physical activity-energy expenditure was higher in ALS subjects than controls (718 ± 262 kcal/d vs. 487 ± 196 kcal/d, p = 0.04). In controls, energy intake matched TEE; in ALS subjects TEE was higher than energy intake. Conclusions We found higher TEE in ALS subjects than controls, with larger contribution to difference from physical activity-energy expenditure than hyper-metabolism. Although daily energy intake in ALS subjects was similar to that in controls, they were unable to compensate for increased energy needs. To accurately determine energy balance and optimize nutrition in ALS, future studies should consider measuring energy intake, energy expenditure, and physical activity.

The bioelectrical impedance analysis (BIA) international database: aims, scope, and call for data.

Bioelectrical impedance analysis (BIA) is a technique widely used for estimating body composition and health-related parameters. The technology is relatively simple, quick, and non-invasive, and is currently used globally in diverse settings, including private clinicians' offices, sports and health clubs, and hospitals, and across a spectrum of age, body weight, and disease states. BIA parameters can be used to estimate body composition (fat, fat-free mass, total-body water and its compartments). Moreover, raw measurements including resistance, reactance, phase angle, and impedance vector length can also be used to track health-related markers, including hydration and malnutrition, and disease-prognostic, athletic and general health status. Body composition shows profound variability in association with age, sex, race and ethnicity, geographic ancestry, lifestyle, and health status. To advance understanding of this variability, we propose to develop a large and diverse multi-country dataset of BIA raw measures and derived body components. The aim of this paper is to describe the 'BIA International Database' project and encourage researchers to join the consortium. The Exercise and Health Laboratory of the Faculty of Human Kinetics, University of Lisbon has agreed to host the database using an online portal. At present, the database contains 277,922 measures from individuals ranging from 11 months to 102 years, along with additional data on these participants. The BIA International Database represents a key resource for research on body composition.

Associations between 3D surface scanner derived anthropometric measurements and body composition in a cross-sectional study.

3D laser-based photonic scanners are increasingly used in health studies to estimate body composition. However, too little is known about whether various 3D body scan measures estimate body composition better than single standard anthropometric measures, and which body scans best estimate it. Furthermore, little is known about differences by sex and age. 105 men and 96 women aged between 18 and 90 years were analysed. Bioelectrical Impedance Analysis was used to estimate whole relative fat mass (RFM), visceral adipose tissue (VAT) and skeletal muscle mass index (SMI). An Anthroscan VITUSbodyscan was used to obtain 3D body scans (e.g. volumes, circumferences, lengths). To reduce the number of possible predictors that could predict RFM, VAT and SMI backward elimination was performed. With these selected predictors linear regression on the respective body compositions was performed and the explained variations were compared with models using standard anthropometric measurements (Body Mass Index (BMI), waist circumference (WC) and waist-to-height-ratio (WHtR)). Among the models based on standard anthropometric measures, WC performed better than BMI and WHtR in estimating body composition in men and women. The explained variations in models including body scan variables are consistently higher than those from standard anthropometrics models, with an increase in explained variations between 5% (RFM for men) and 10% (SMI for men). Furthermore, the explained variation of body composition was additionally increased when age and lifestyle variables were added. For each of the body composition variables, the number of predictors differed between men and women, but included mostly volumes and circumferences in the central waist/chest/hip area and the thighs. 3D scan models performed better than standard anthropometric measures models to predict body composition. Therefore, it is an advantage for larger health studies to look at body composition more holistically using 3D full body surface scans.

КОМПОНЕНТНИЙ СКЛАД ТІЛА, ЯК ПОКАЗНИК ЗДОРОВ'Я МОЛОДІ

Currently, the task of preserving and strengthening the health of young people is an important one, and higher pedagogical education can play a crucial role in achieving this goal. The development of health-saving technologies must take into account the characteristics and initial state of the population group in order to ensure that these technologies are effective, appropriate, and accepted by the target population. By doing so, we can improve the health outcomes of populations and promote greater equity in healthcare. The analysis of estimation of component body composition is a useful tool for assessing various aspects of health and fitness. The purpose of the study is to determine the component composition of the body as an indicator of the health of female students of higher education at the Faculty of Physical Education.

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

BackgroundThe obesity epidemic brought a need for accessible methods to monitor body composition, as excess adiposity has been associated with cardiovascular disease, metabolic disorders, and some cancers. Recent 3-dimensional optical (3DO) imaging advancements have provided opportunities for assessing body composition. However, the accuracy and precision of an overall 3DO body composition model in specific subgroups are unknown. ObjectivesThis study aimed to evaluate 3DO’s accuracy and precision by subgroups of age, body mass index, and ethnicity. MethodsA cross-sectional analysis was performed using data from the Shape Up! Adults study. Each participant received duplicate 3DO and dual-energy X-ray absorptiometry (DXA) scans. 3DO meshes were digitally registered and reposed using Meshcapade. Principal component analysis was performed on 3DO meshes. The resulting principal components estimated DXA whole-body and regional body composition using stepwise forward linear regression with 5-fold cross-validation. Duplicate 3DO and DXA scans were used for test–retest precision. Student’s t tests were performed between 3DO and DXA by subgroup to determine significant differences. ResultsSix hundred thirty-four participants (females = 346) had completed the study at the time of the analysis. 3DO total fat mass in the entire sample achieved R2 of 0.94 with root mean squared error (RMSE) of 2.91 kg compared to DXA in females and similarly in males. 3DO total fat mass achieved a % coefficient of variation (RMSE) of 1.76% (0.44 kg), whereas DXA was 0.98% (0.24 kg) in females and similarly in males. There were no mean differences for total fat, fat-free, percent fat, or visceral adipose tissue by age group (P > 0.068). However, there were mean differences for underweight, Asian, and Black females as well as Native Hawaiian or other Pacific Islanders (P < 0.038). ConclusionsA single 3DO body composition model produced accurate and precise body composition estimates that can be used on diverse populations. However, adjustments to specific subgroups may be warranted to improve the accuracy in those that had significant differences.This trial was registered at clinicaltrials.gov as NCT03637855 (Shape Up! Adults).