Measurement Of Fat-free Mass Research Articles

Body composition trajectories before the diagnosis of type 2 diabetes mellitus in Whitehall II study

Abstract Background The trajectories of anthropometric and body composition measures (important predictors of diabetes) are rarely explored before diabetes diagnosis. Our study aimed to compare trajectories of fat mass (FM), fat-free mass (FFM), body mass index (BMI), and waist circumference (WC) preceding type 2 diabetes mellitus (T2DM) to aging trajectories of individuals without diabetes during follow-up. Methods We used data from the Whitehall II study, a prospective cohort of British civil servants. 5-yearly BMI and WC were available for up to 20 years, while 5-yearly FM and FFM measures were available for up to 10 years. Linear mixed models with a backward timescale (from diabetes diagnosis or end of follow-up) were performed stratified by sex and adjusted for age, occupational grade, ethnicity, and lifestyle factors. Results A total of 1674/990 (anthropometric/body composition analysis) women (233/81 incident diabetes) and 3917/2710 men (479/217 incident diabetes) 49.81 [0.08]/60.91 [0.9] (mean [SE]) years of age at baseline were included. All outcomes were higher in cases compared to controls. Women’s FM, BMI, and WC followed a quadratic increase in both groups with a faster increase among incident diabetes cases (dBMI 0.04 [0.01] kg/m2/year, dFM 0.19 [0.09] kg/year, dWC 0.2 cm/year [0.05]). FFM decreased linearly with similar slopes in cases and controls. Men’s FM, BMI, and WC also showed a quadratic increase with faster increase in incident cases compared to controls (dBMI 0.03 [0.01] kg/m2/year, dFM 0.23 [0.04] kg/year, dWC 0.08 [0.02] cm/year). FFM followed a quadratic decrease in both groups with a slower rate (0.06 [0.03] kg/year) in incident cases. Conclusions Incident diabetes cases have higher anthropometric and body composition measures 10-20 years before diabetes diagnosis compared to controls. Furthermore, incident cases showed faster increases in these measures except for FFM that decreased during follow-up with similar or lower speeds in cases than controls. Key messages • Traditional anthropometric measures do not capture the underlying changes in body composition. • The inclusion of body composition in risk calculators may result in more precise diabetes prediction.

Development and validation of reference equations for dual-energy X-ray absorptiometry-derived measures of fat-free mass in adults aged 45-85 years: results from the Canadian Longitudinal Study on Aging.

Reference equations for fat-free mass (FFM) and lean soft tissue mass (LM) measures obtained from dual-energy X-ray absorptiometry (DEXA) are important for the interpretation of body composition. This study developed and validated reference equations for FFM and LM using DEXA from the Canadian Longitudinal Study on Aging. Reference equations were developed using data from a random population-based sample of ostensibly healthy and functionally independent adults aged 45-85 years. Reference equations for absolute (accounting for age, sex, height, and body mass) and height-adjusted aka index (accounting for age, sex, and body mass index) measures of FFM and LM were developed using quantile regression. Reference equations were respectively developed and validated in derivation (80%) and validation cohorts (20%). Reference equations were applied to symptomatic adults with self-reported chronic obstructive pulmonary disease (COPD) or heart disease to assess discriminant validity; and compared with other published equations to assess performance. Bland-Altman analyses and Lin's concordance correlation coefficients were utilised to assess agreement. Reference equations for 5th, 10th, 50th, 90th, and 95th percentiles were developed for DEXA-derived estimates of FFM and LM based on 1881 healthy participants (57% male) aged 55 [IQR: 50-61] years. Reference equations performed comparably in the validation cohort and discriminated reference values between ostensibly healthy adults and people with symptomatic COPD or heart disease. Previously published reference equations tended to over- or under-predict estimates of LM compared with the current reference equations. This study provides a comprehensive and validated set of reference equations for estimating and interpreting FFM and LM from DEXA in Canadian adults aged 45-85 years, although additional validation may be required for those>75 years.

Advancing body composition assessment in patients with cancer: First comparisons of traditional versus multicompartment models

Background and aimsMeasurement of body composition using computed tomography (CT) scans may be a viable clinical tool for low muscle mass assessment in oncology. However, longitudinal assessments are often infeasible with CT. Clinically accessible body composition technologies can be used to track changes in fat-free mass (FFM) or muscle, though their accuracy may be impacted by cancer-related physiological changes. The purpose of this study was to examine the agreement among accessible body composition method with criterion methods for measures of whole-body FFM measurements and, when possible, muscle mass for the classification of low muscle in patients with cancer. MethodsPatients with colorectal cancer were recruited to complete measures of whole-body DXA, air displacement plethysmography (ADP), and bioelectrical impedance analysis (BIA). These measures were used alone, or in combination to construct the criterion multicompartment (4C) mode for estimating FFM. Patients also underwent abdominal CT scans as part of routine clinical assessment. Agreement of each method with 4C model was analyzed using mean constant error (CE = criterion – alternative), linear regression including root mean square error (RMSE), Bland-Altman limits of agreement (LoA) and mean percentage difference (MPD). Additionally, appendicular lean soft tissue index (ALSTI) measured by DXA and predicted by CT were compared for the absolute agreement, while the ALSTI values and skeletal muscle index by CT were assessed for agreement on the classification of low muscle mass. ResultsForty-five patients received all measures for the 4C model and 25 had measures within proximity of clinical CT measures. Compared to 4C, DXA outperformed ADP and BIA by showing the strongest overall agreement (CE = 1.96 kg, RMSE = 2.45 kg, MPD = 98.15 ± 2.38%), supporting its use for body composition assessment in patients with cancer. However, CT cutoffs for skeletal muscle index or CT-estimated ALSTI were lower than DXA ALSTI (average 1.0 ± 1.2 kg/m2) with 24.0% to 32.0% of patients having a different low muscle classification by CT when compared to DXA. ConclusionsDespite discrepancies between clinical body composition assessment and the criterion multicompartment model, DXA demonstrates the strongest agreement with 4C. Disagreement between DXA and CT for low muscle mass classification prompts further evaluation of the measures and cutoffs used with each technique. Multicompartment models may enhance our understanding of body composition variations at the individual patient level and improve the applicability of clinically accessible technologies for classification and monitoring change over time.

New role of fat-free mass in cancer risk linked with genetic predisposition

Cancer risk is associated with the widely debated measure body mass index (BMI). Fat mass and fat-free mass measurements from bioelectrical impedance may further clarify this association. The UK Biobank is a rare resource in which bioelectrical impedance and BMI data was collected on ~ 500,000 individuals. Using this dataset, a comprehensive analysis using regression, principal component and genome-wide genetic association, provided multiple levels of evidence that increasing whole body fat (WBFM) and fat-free mass (WBFFM) are both associated with increased post-menopausal breast cancer risk, and colorectal cancer risk in men. WBFM was inversely associated with prostate cancer. We also identified rs615029[T] and rs1485995[G] as associated in independent analyses with both PMBC (p = 1.56E–17 and 1.78E–11) and WBFFM (p = 2.88E–08 and 8.24E–12), highlighting splice variants of the intriguing long non-coding RNA CUPID1 (LINC01488) as a potential link between PMBC risk and fat-free mass.

Fat and fat-free mass measurement agreement by dual-energy X-ray absorptiometry versus bioelectrical impedance analysis: Effects of posture and waist circumference.

Bioelectrical impedance analysis (BIA) operates under the assumption that the conductor has a uniform cylindrical shape. However, this assumption may be violated if measures are taken in the seated position, especially in people with a high waist circumference (WC). The aims of this research were to determine whether posture (supine, standing, and seated) and WC affect agreement between BIA and dual-energy X-ray absorptiometry (DXA) measures of fat mass (FM) and fat-free mass (FFM). Baseline data were collected from 28 adults (mean=61.4±6.9years, 64.3% female) with obesity (BMI 38.6±5.0kg/m2). Body composition was measured using BIA in the supine, standing, and seated positions and by DXA while supine. Intraclass correlation coefficient (ICC) analyses with two-way mixed effects and absolute agreement were performed to determine agreement. Point estimates were excellent for FM and FFM while supine, excellent for FM and good for FFM while standing, and moderate for FM and good for FFM while seated. BIA measures in the supine position resulted in the narrowest 95% confidence intervals compared with other positions. Better agreement was observed across all positions in participants with a WC below the median (118.3cm). Despite the potential pragmatic value of measuring with BIA in a seated position, the results of this analysis demonstrate the poorest agreement between DXA and BIA methods, especially in individuals with high WC. Findings from this study demonstrate that BIA, particularly when measured in a supine position, can serve as a viable alternative to DXA for measuring body composition in people with obesity.

The Development of a Resting Metabolic Rate Prediction Equation for Professional Male Rugby Union Players.

Determining resting metabolic rate (RMR) is an important aspect when calculating energy requirements for professional rugby union players. Prediction equations are often used for convenience to estimate RMR. However, the accuracy of current prediction equations for professional rugby union players remains unclear. The aims of this study were to examine the RMR of professional male rugby union players compared to nine commonly used prediction equations and develop and validate RMR prediction equations specific to professional male rugby union players. One hundred and eight players (body mass (BM) = 102.9 ± 13.3 kg; fat-free mass (FFM) = 84.8 ± 10.2 kg) undertook Dual-energy X-ray Absorptiometry scans to assess body composition and indirect calorimetry to determine RMR. Mean RMR values of 2585 ± 176 kcal∙day-1 were observed among the group with forwards (2706 ± 94 kcal·day-1), demonstrating significantly (p < 0.01; d = 1.93) higher RMR compared to backs (2465 ± 156 kcal·day-1), which appeared to be due to their higher BM and FFM measures. Compared to the measured RMR for the group, seven of the nine commonly used prediction equations significantly (p < 0.05) under-estimated RMR (-104-346 kcal·day-1), and one equation significantly (p < 0.01) over-estimated RMR (192 kcal·day-1). This led to the development of a new prediction equation using stepwise linear regression, which determined that the strongest predictor of RMR for this group was FFM alone (R2 = 0.70; SEE = 96.65), followed by BM alone (R2 = 0.65; SEE = 104.97). Measuring RMR within a group of professional male rugby union players is important, as current prediction equations may under- or over-estimate RMR. If direct measures of RMR cannot be obtained, we propose the newly developed prediction equations be used to estimate RMR within professional male rugby union players. Otherwise, developing team- and/or group-specific prediction equations is encouraged.

Development and validation of a rapid multicompartment body composition model using 3-dimensional optical imaging and bioelectrical impedance analysis

Background & AimsThe multicompartment approach to body composition modeling provides a more precise quantification of body compartments in healthy and clinical populations. We sought to develop and validate a simplified and accessible multicompartment body composition model using 3-dimensional optical (3DO) imaging and bioelectrical impedance analysis (BIA). MethodsSamples of adults and collegiate-aged student-athletes were recruited for model calibration. For the criterion multicompartment model (Wang-5C), participants received measures of scale weight, body volume (BV) via air displacement, total body water (TBW) via deuterium dilution, and bone mineral content (BMC) via dual energy x-ray absorptiometry. The candidate model (3DO-5C) used stepwise linear regression to derive surrogate measures of BV using 3DO, TBW using BIA, and BMC using demographics. Test-retest precision of the candidate model was assessed via root mean square error (RMSE). The 3DO-5C model was compared to criterion via mean difference, concordance correlation coefficient (CCC), and Bland-Altman analysis. This model was then validated using a separate dataset of 20 adults. Results67 (31 female) participants were used to build the 3DO-5C model. Fat-free mass (FFM) estimates from Wang-5C (60.1 ± 13.4 kg) and 3DO-5C (60.3 ± 13.4 kg) showed no significant mean difference (-0.2 ± 2.0 kg; 95% limits of agreement [LOA] -4.3 to +3.8) and the CCC was 0.99 with a similar effect in fat mass that reflected the difference in FFM measures. In the validation dataset, the 3DO-5C model showed no significant mean difference (0.0 ± 2.5 kg; 95% LOA -3.6 to +3.7) for FFM with almost perfect equivalence (CCC = 0.99) compared to the criterion Wang-5C. Test-retest precision (RMSE = 0.73 kg FFM) supports the use of this model for more frequent testing in order to monitor body composition change over time. ConclusionsBody composition estimates provided by the 3DO-5C model are precise and accurate to criterion methods when correcting for field calibrations. The 3DO-5C approach offers a rapid, cost-effective, and accessible method of body composition assessment that can be used broadly to guide nutrition and exercise recommendations in athletic settings and clinical practice.

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.

Body fat distribution, fat-free mass and cardiovascular function in the UK Biobank

Abstract Background Excess adiposity and high body mass index have been associated with cardiac dysfunction and heart failure. However, the role of whole body imaging and independent associations of regional fat and fat-free mass on left ventricular and vascular function is unclear. Purpose This study determined the cross-sectional associations of regional fat depots and fat-free mass on left ventricular function and arterial stiffness to explain obesity-related cardiac dysfunction. Methods Participants who underwent whole body magnetic resonance imaging (MRI) and dual energy X-ray absorptiometry (DXA) in an ongoing imaging study of 100,000 individuals in the UK were included in this analysis. Analyses exclude individuals with major cardiac and vascular diseases at initial baseline assessment. Regional fat distribution was quantified using MRI while body fat-free mass was quantified with DXA. Cardiac MRI was used to measure left ventricular (LV) ejection fraction and LV mass while pulse wave velocity from finger photo-plethysmography was used to measure arterial stiffness index. Associations of body fat distribution (visceral fat, abdominal subcutaneous fat, other body fat) and fat-free mass with each of LV ejection fraction, LV mass and arterial stiffness index, after mutual adjustment for one another and potential confounders were determined using multivariable linear regression. Results We included 31,088 individuals (mean age 63.4 years, 53% women). Among regional body fat measures, higher visceral fat was associated with lower LVEF (β=-0.43; 95% CI: -0.55, -0.31 per SD) and higher arterial stiffness index (β=0.44; 95% CI: 0.34, 0.54 per SD) while none of the regional fat and fat-free mass showed significant association with LV function or arterial stiffness. None of the fat or fat-free mass measures showed significant association with LV mass. These associations were not explained by inflammatory markers, blood pressure or glycaemic profile. Conclusion Visceral fat is the main driver of obesity-related cardiac and vascular dysfunction. There is need for further studies to understand the biological causal pathways of obesity-heart disease.Figure 1Figure 2

PSXIV-29 Seminal Plasma Uterine Priming in Embryo-Recipient Beef Cows Alters Preweaning Offspring Growth But Not Indices of Body Composition

Abstract Seminal plasma primes the uterus for pregnancy through the recruitment of cells aiding in microbial clearance, tissue remodeling and angiogenesis, and embryo implantation and growth. Less is known about the effects of seminal plasma uterine priming in practices devoid of seminal plasma, specifically evaluating offspring growth in embryo-recipient beef cows. In the present study, we sought to determine the effects of seminal plasma uterine priming on postnatal body weights, carcass ultrasound measures, and indices of body composition. To realize these objectives, embryo-recipient cows randomly received 0.5 mL of pooled seminal plasma or no treatment (control) at estrus and underwent embryo transfer seven days later. Following parturition, offspring pre-weaning body weights were collected at 30, 90, and 180 days of age. Indices of body composition, carcass ultrasounds and bioelectrical impedance analysis (BIA), were collected pre-weaning at an average 209 days of age. Weaning weights and hip heights were collected at an average of 212 days of age. Ultrasound, BIA, and weaning weight data were analyzed using the MIXED procedure of SAS for fixed effects of treatment. Pre-weaning body weights were analyzed similarly with repeated measures for treatment, day, and their interaction. Covariates of sire, dam, sex, and age were included in all models if P ≤ 0.10. Correlations between carcass ultrasounds and BIA parameters of fat-free mass and fat-free soft tissue were analyzed using the CORR procedure of SAS. Significance is declared at P ≤ 0.05 and data were presented as means ± standard error. A treatment by day interaction was not observed for pre-weaning body weight. However, a main effect of treatment was observed for pre-weaning body weights, which was decreased (P = 0.0130) in seminal plasma calves compared with controls. Weaning weights and hip height were not different between treatments. There was not an effect of treatment on carcass ultrasound measures, including ribeye area, ribeye area adjusted by body weight, rib fat, intramuscular fat, or rump fat. Similarly, BIA measures of fat-free mass and fat-free soft tissue were not different between treatments. Ribeye area and rib fat ultrasound were moderately correlated (P &amp;lt; 0.05) with BIA measures of fat-free mass and fat-free soft tissue. Interestingly, previously reported data from this project show offspring from seminal plasma treated cows had decreased embryo size at days 35, 40, and 45 of gestation, and decreased birth weights. It appears seminal plasma uterine priming prior to embryo transfer negatively impacts offspring growth pre-weaning, however, by weaning this difference is diminished. It is less clear why pre-weaning weights differ due to similar body composition among treatment and control calves; however, these measures may have been collected after the period of compensatory gain occurred.

Validation of skinfold equations and alternative methods for the determination of fat-free mass in young athletes.

To cross-validate skinfold (SKF) equations, impedance devices, and air-displacement plethysmography (ADP) for the determination of fat-free mass (FFM). Male and female youth athletes were evaluated (n = 91[mean ± SD] age: 18.19 ± 2.37 year; height: 172.1 ± 9.8 cm; body mass: 68.9 ± 14.5 kg; BMI: 23.15 ± 3.2 kg m-2; body fat: 19.59 ± 6.9%) using underwater weighing (UWW), ADP, and SKF assessments. A 3-compartment (3C) model (i.e., UWW and total body water) served as the criterion, and alternate body density (Db) estimates from ADP and multiple SKF equations were obtained. Validity metrics were examined to establish each method's performance. Bioelectrical impedance analysis (BIA), bioimpedance spectroscopy (BIS), and the SKF equations of Devrim-Lanpir, Durnin and Womersley, Jackson and Pollock (7-site), Katch, Loftin, Lohman, Slaughter, and Thorland differed from criterion. For females, Pearson's correlations between the 3C model and alternate methods ranged from 0.51 to 0.92, the Lin's concordance correlation coefficient (CCC) ranged from 0.41 to 0.89, with standard error of the estimate (SEE) ranges of 1.9-4.6 kg. For SKF, the Evans 7-site and J&P 3 Site equations performed best with CCC and SEE values of 0.82, 2.01 kg and 0.78, 2.21 kg, respectively. For males, Pearson's correlations between the 3C model and alternate methods ranged from 0.50 to 0.95, CCC ranges of 0.46-0.94, and SEE ranges of 3.3-7.6 kg. For SKF, the Evans 3-site equation performed best with a mean difference of 1.8 (3.56) kg and a CCC of 0.93. The Evans 7-site and 3-site SKF equations performed best for female and male athletes, respectively. The field 3C model can provide an alternative measure of FFM when necessary.

Reproducibility of Body Fat and Fat-Free Mass Measurements by Bioimpedance and Ultrasound Scanning Analysis in a Group of Young Adults

Reproducibility of Body Fat and Fat-Free Mass Measurements by Bioimpedance and Ultrasound Scanning Analysis in a Group of Young Adults

Air Displacement Plethysmography is an Accurate and Feasible Noninvasive Measure of Fat-Free Mass in Children With Intestinal Failure.

The nutritional status of children with intestinal failure (IF) can be difficult to determine using body weight and currently available anthropometric techniques. Air displacement plethysmography (ADP) is a noninvasive measure of whole-body composition that measures body mass and volume, with a calculation of percent body fat (%BF) and fat-free mass (FFM) that may be useful during the provision of specialized nutrition. To evaluate the validity and feasibility of measuring body composition in children with IF using ADP compared with deuterium dilution (DD), as well as secondarily with other measures of body composition, namely bioelectrical impedance analysis (BIA), dual-energy X-ray absorptiometry (DXA), and four-site skinfold anthropometry. We conducted a prospective cohort study of 18 children recruited through the Center for Advanced Intestinal Rehabilitation at Boston Children's Hospital. Patients 2-17 years of age with IF dependent on parenteral nutrition (PN) for more than 90 days were included. Spearman rank correlation and Bland-Altman limits of agreement (LOA) analysis were used to compare ADP to 4 alternative measures of body composition. Eighteen children with IF, median age 7.1 [interquartile range (IQR) 5.4-9.3] years, 9 female (50%), and median residual bowel length 31 (IQR 22-85) cm were enrolled. Median PN energy intake was 46 (IQR 39-49) kcal/kg/day. Incomplete bladder emptying lead to invalid measures of DD in 4 subjects. Spearman correlation coefficients for %BF were low to moderate between ADP and DD ( r = 0.29), DXA ( r = 0.62), BIA ( r = 0.50), and skinfold ( r = 0.40). Correlations for FFM were high between ADP and these other measures (range 0.95-0.98). Comparing ADP with DD and skinfold measures, Bland-Altman analysis showed small mean bias (-1.9 and +1.5 kg) and acceptable 95% LOA ranges (10.7 and 22.9 kg), respectively, with larger bias (-10.7 and -7.7 kg) and LOA ranges (38.7 and 45.2 kg) compared to DXA and BIA. %BF by ADP and skinfold thickness were moderately correlated ( r = 0.43) with low bias (-0.2%) but very wide LOA (25.7%). Body composition via ADP is feasible and valid in children with IF as a measure of FFM but appears less suitable for the measurement of %BF. The technique holds promise as a noninvasive measure of body composition to assess the efficacy of nutritional, medical, and surgical interventions.

Repeatability of Body Fat and Fat-Free Mass Measurements by Bioimpedance and Ultrasound Scanning Analysis in the Group of Young Adults

Repeatability of the body fat and fat-free mass measurements obtained by two indirect methods (bioimpedance – BIA and ultrasound scanning analysis – US) was performed in the group of young adults. To evaluate repeatability, the repeated body composition measurements by the bioimpedance analyzer ABC-02 “Medas” and the ultrasound scanner BodyMetrixTM were done in the group of adult males and females. The performed study indicates accuracy of the estimates in the individuals and in the group at all as well as high repeatability of measurements obtained by BIA and US. Positive significant correlation between the body composition measurements obtained by the bioimpedance analyzer ABC-02 “Medas” and the ultrasound scanner BodyMetrixTM as well as between repeated measurements was found. The study indicates high repeatability of body fat and fat-free mass measurements obtained by the bioimpedance analyzer ABC-02 “Medas” and the ultrasound scanner BodyMetrixTM in the group of young adult males and females. Particularly, the highest repeatability was for the fat-free mass measurements.

Bioimpedance Spectroscopy in Heart Transplantation: Posttransplant Changes in Body Composition and Effects in Outcomes.

Bioimpedance spectroscopy yields measurements of fat-free mass, fat mass, phase angle, and other measures. Bioimpedance spectroscopy has been validated as a preoperative assessment tool in cardiac surgical studies, in which low phase angle predicted morbidity and mortality. No studies have evaluated bioimpedance spectroscopy following heart transplantation. We evaluated body composition, nutrition status (Subjective Global Assessment, body mass index, midarm muscle circumference, and triceps skinfolds), and functional status (handgrip strength and 6-min walk test) in 60 adults. Body composition measurements via a 256-frequency bioimpedance spectroscopy device included fat and fat-free mass as well as phase angle calculated at 50 kHz. Testing was completed at baseline and 1, 3, 6, and 12 mo following heart transplantation. Mortality and hospital readmissions were analyzed. Phase angle and fat mass increased while fat-free mass decreased; grip strength and 6-min walk test improved after transplantation (all P < 0.001). Improvement in phase angle in the first month postoperatively was associated with reduced risk of readmission. Low perioperative and 1-mo phase angles were associated with prolonged posttransplant length of stay (median: 13 versus 10 d, P = 0.03), increased infection-related readmissions (40% versus 5%, P = 0.001), and increased 4-y mortality (30% versus 5%, P = 0.01). Phase angle, grip strength, and 6-min walk test distance improved after heart transplantation. Low phase angle appears to be associated with suboptimal outcomes and may be a feasible and affordable method to predict outcomes. Further research should ascertain whether preoperative phase angle can predict outcomes.

Trends in measuring BMR and RMR after spinal cord injury: a comprehensive review.

Studying factors that contribute to our understanding of maintaining normal energy balance are of paramount significance following spinal cord injury (SCI). Accurate determination of energy needs is crucial for providing nutritional guidance and managing the increasing prevalence of malnutrition or obesity after SCI. BMR represents 75-80 % of the total energy expenditure in persons with SCI. Accurately measuring BMR is an important component for calculating total energetic needs in this population. Indirect calorimetry is considered the gold-standard technique for measuring BMR. However, technical challenges may limit its applications in large cohort studies and alternatively rely on prediction equations. Previous work has shown that BMR changes in response to disuse and exercise in the range of 15-120 %. Factors including sex, level of injury and type of assistive devices may influence BMR after SCI. RMR is erroneously used interchangeably for BMR, which may result in overestimation of energetic intake when developing nutritional plans. To address this concern, we comprehensively reviewed studies that conducted BMR (n=15) and RMR (n=22) in persons with SCI. The results indicated that RMR is 9 % greater than BMR in persons with SCI. Furthermore, the SCI-specific prediction equations that incorporated measures of fat-free mass appeared to accurately predict BMR. Overall, the current findings highlighted the significance of measuring BMR as well as encouraging the research and clinical community to effectively establish countermeasures to combat obesity after SCI.

Efficacy of interventions to alter measures of fat-free mass in people with COPD: a systematic review and meta-analysis.

Low fat-free mass (FFM) is linked to poor health outcomes in COPD, including impaired exercise tolerance and premature death. The aim of this systematic review was to synthesise evidence on the effectiveness of interventions for increasing FFM in COPD. Searches of electronic databases (MEDLINE, Cochrane Library, Embase, Web of Science, Scopus) and trial registers (ClinicalTrials.gov) were undertaken from inception to August 2022 for randomised studies of interventions assessing measures of FFM in COPD. The primary outcome was change in FFM (including derivatives). Secondary outcomes were adverse events, compliance and attrition. 99 studies (n=5138 people with COPD) of 11 intervention components, used alone or in combination, were included. Exercise training increased mid-thigh cross-sectional area (k=3, standardised mean difference (SMD) 1.04, 95% CI 0.02-2.06; p=0.04), but not FFM (k=4, SMD 0.03, 95% CI -0.18-0.24; p=0.75). Nutritional supplementation significantly increased FFM index (k=11, SMD 0.31, 95% CI 0.13-0.50; p<0.001), but not FFM (k=19, SMD 0.16, 95% CI -0.06-0.39; p=0.16). Combined exercise training and nutritional supplementation increased measures related to FFM in 67% of studies. Anabolic steroids increased FFM (k=4, SMD 0.98, 95% CI 0.24-1.72; p=0.009). Neuromuscular electrical stimulation increased measures related to FFM in 50% of studies. No interventions were more at risk of serious adverse events, low compliance or attrition. Exercise training and nutritional supplementation were not effective in isolation to increase FFM, but were for localised muscle and index measures, respectively. Combined, exercise and nutritional supplementation shows promise as a strategy to increase FFM in COPD. Anabolic steroids are efficacious for increasing FFM in COPD.

Calculation of protein requirements; a comparison of calculations based on bodyweight and fat free mass.

In dietary practice, it is common to estimate protein requirements on actual bodyweight, but corrected bodyweight (in cases with BMI <20kg/m2 and BMI ≥30kg/m2) and fat free mass (FFM) are also used. Large differences on individual level are noticed in protein requirements using these different approaches. To continue this discussion, the answer is sought in a large population to the following question: Will choosing actual bodyweight, corrected bodyweight or FFM to calculate protein requirements result in clinically relevant differences? This retrospective database study, used data from healthy persons ≥55 years of age and in- and outpatients ≥18 years of age. FFM was measured by air displacement plethysmography technology or bioelectrical impedance analysis. Protein requirements were calculated as 1) 1.2g (g) per kilogram (kg) actual bodyweight or 2) corrected bodyweight or 3) 1.5g per kg FFM. To compare these three approaches, the approach in which protein requirement is based on FFM, was used as reference method. Bland-Altman plots with limits of agreement were used to determine differences, analyses were performed for both populations separately and stratified by BMI category and gender. In total 2291 subjects were included. In the population with relatively healthy persons (n=506, ≥55 years of age) mean weight is 86.5±18.2kg, FFM is 51±12kg and in the population with adult in- and outpatients (n=1785, ≥18 years of age) mean weight is 72.5±18.4kg, FFM is 51±11kg. Clinically relevant differences were found in protein requirement between actual bodyweight and FFM in most of the participants with overweight, obesity or severe obesity (78-100%). Using corrected bodyweight, an overestimation in 48-92% of the participants with underweight, healthy weight and overweight is found. Only in the Amsterdam UMC population, protein requirement is underestimated when using the approach of corrected bodyweight in participants with severe obesity. The three approaches in estimation of protein requirement show large differences. In the majority of the population protein requirement based on FFM is lower compared to actual or corrected bodyweight. Correction of bodyweight reduces the differences, but remain unacceptably large. It is yet unknown which method is the best for estimation of protein requirement. Since differences vary by gender due to differences in body composition, it seems more accurate to estimate protein requirement based on FFM. Therefore, we would like to advocate for more frequent measurement of FFM to determine protein requirements, especially when a deviating body composition is to be expected, for instance in elderly and persons with overweight, obesity or severe obesity.

Agreement between vector analysis and body composition measurements by four types of bioelectrical impedance technology in hemodialysis patients.

Background: the differences in bioelectrical impedance vector analysis (BIVA) results from different analyzers that use different bioelectrical impedance analysis (BIA) measurement technologies are not known. This study aimed to identify the degree of agreement between the BIVA results of four different BIA measurement techniques and to evaluate the degree of agreement between their estimates of fat-free mass (FFM) and fat mass (FM) and those determined by the gold-standard method of dual-energy X-ray absorptiometry (DEXA) in a subgroup of patients without overhydration. Methods: a cross-sectional study was conducted with hemodialysis (HD) patients with end-stage renal disease (ESRD) aged 18 to 65 years. BIA was measured with four different techniques: spectroscopic (BIA-BIS), multifrequency (BIA-MF), single-frequency (BIA-SF), and segmental multifrequency (BIA-MS) techniques. The differences and concordance between the components of the BIA (resistance, reactance, and phase angle) of the four devices were analyzed. Patients with a normal hydration status were identified, and concordance between FM and FFM measurements with each impedance device and DEXA was observed only in these patients. Results: thirty patients were included. The concordance between the components of BIA ranged from good to excellent (phase angle: intraclass correlation coefficient (ICC) = 0.82, 95 % confidence interval (CI): 0.77-0.93; resistance: ICC = 0.98, 95 % CI: 0.92-0.99). The overall concordance for BIVA diagnosis between the analyzers was substantial for hydration (k = 0.71, 95 % CI: 0.71-0.72) and for body tissues (k = 0.68, 95 % CI: 0.67-0.68). Bland-Altman plots showed the lowest bias between BIA-BIS and DEXA for both FM and FFM. Conclusions: the agreement among the four devices was good for diagnosis by BIVA. The BIA-BIS analyzer and DEXA had the lowest bias for both FFM and FM, although with higher limits of agreement. The lowest limits of agreement were found with the BIA-MS analyzer.

Assessment of clinical measures of total and regional body composition from a commercial 3-dimensional optical body scanner

The accurate assessment of total body and regional body circumferences, volumes, and compositions are critical to monitor physical activity and dietary interventions, as well as accurate disease classifications including obesity, metabolic syndrome, sarcopenia, and lymphedema. We assessed body composition and anthropometry estimates provided by a commercial 3-dimensional optical (3DO) imaging system compared to criterion measures. Participants of the Shape Up! Adults study were recruited for similar sized stratifications by sex, age (18-40, 40-60, >60 years), BMI (under, normal, overweight, obese), and across five ethnicities (non-Hispanic [NH] Black, NH White, Hispanic, Asian, Native Hawaiian/Pacific Islander). All participants received manual anthropometry assessments, duplicate whole-body 3DO (Styku S100), and dual-energy X-ray absorptiometry (DXA) scans. 3DO estimates provided by the manufacturer for anthropometry and body composition were compared to the criterion measures using concordance correlation coefficient (CCC) and Bland-Altman analysis. Test-retest precision was assessed by root mean square error (RMSE) and coefficient of variation. A total of 188 (102 female) participants were included. The overall fat free mass (FFM) as measured by DXA (54.1±15.2kg) and 3DO (55.3±15.0kg) showed a small mean difference of 1.2±3.4kg (95% limits of agreement-7.0 to+5.6) and the CCC was 0.97 (95% CI: 0.96-0.98). The CCC for FM was 0.95 (95% CI: 0.94-0.97) and the mean difference of 1.3±3.4kg (95% CI:-5.5 to+8.1) reflected the difference in FFM measures. 3DO anthropometry and body composition measurements showed high test-retest precision for whole body volume (1.1L), fat mass (0.41kg), percent fat (0.60%), arm and leg volumes, (0.11 and 0.21L, respectively), and waist and hip circumferences (all <0.60cm). No group differences were observed when stratified by body mass index, sex, or race/ethnicity. The anthropometric and body composition estimates provided by the 3DO scanner are precise and accurate to criterion methods if offsets are considered. This method offers a rapid, broadly available, and automated method of body composition assessment regardless of body size. Further studies are recommended to examine the relationship between measurements obtained by 3DO scans and metabolic health in healthy and clinical populations.