Empirical relationships between body tissue composition and bioelectrical impedance of brook trout Salvelinus fontinalis from a Rocky Mountain Stream

Bioelectrical impedance analysis (BIA) analysis was carried out in the field on anaesthetized Salvelinus fontinalis electrofished from a mountain stream in Alberta, Canada; the fish were then sacrificed for subsequent analysis of tissue composition. Water content was assessed by comparing wet and dry mass, and total body lipid content was measured by Soxhlet extraction with petroleum ether. A multivariate analysis of body composition and size metric against impedance measurements was carried out, and the main findings were (1) body size and related metrics were strongly related to volumetric impedance measures, as shown in several previous studies, (2) lipid content (%) and water content (%) were both well predicted by regression models whose main predictor was reactance and (3) reactance and resistance measures that were series-based produced excellent predictions of tissue composition, whereas the corresponding parallel-based models were crude. The BIA measurements are quick and easy to conduct and appear to provide excellent predictions of a number of proximate body components, without the need to kill the fish; however, more studies are required to provide improved understanding of possible effects of region, season, life stage and species on measurements.     

Common relationships among proximate composition components in fishes

Relationships between the various body proximate components and dry matter content were examined for five species of fishes, representing anadromous, marine and freshwater species: chum salmon Oncorhynchus keta, Chinook salmon Oncorhynchus tshawytscha, brook trout Salvelinus fontinalis, bluefish Pomatomus saltatrix and striped bass Morone saxatilis. The dry matter content or per cent dry mass of these fishes can be used to reliably predict the per cent composition of the other components. Therefore, with validation it is possible to estimate fat, protein and ash content of fishes from per cent dry mass information, reducing the need for costly and time‐consuming laboratory proximate analysis. This approach coupled with new methods of non‐lethal estimation of per cent dry mass, such as from bioelectrical impedance analysis, can provide non‐destructive measurements of proximate composition of fishes.     

USE OF BIOELECTRICAL IMPEDANCE ANALYSIS TO ASSESS BODY COMPOSITION OF SEALS

Abstract: Bioelectrical impedance analysis (BIA) measures resistance and reactance of a current as it passes through an organism. The validity of using BIA as a tool to measure body water content, and hence body composition and condition, was tested on harp and ringed seals. The resistance and reactance readings from BIA were compared to estimates of total body water (TBW) determined via tritiated water dilution. The relationship between resistance and TBW (% of body mass) was linear after logarithmic transformation and the two variables were highly correlated. We describe the electrode configuration and placements which provide reliable results in these seals. Our findings indicate that BIA has considerable potential as an inexpensive, rapid, and reliable technique for estimating body composition of phocid seals.     

Validity of bioelectric impedance for body composition assessment in children

Whole-body bioelectrical impedance analysis (BIA) was evaluated for its reliability and accuracy in estimating body composition in children. The hypothesis that the index, body height2 divided by resistance (RI), can accurately predict fat-free body mass (FFB) and percent fat (%FAT) in children was tested on 94 caucasian children 10-14 yr old. Criterion variables were FFB and %FAT estimated using multicomponent equations developed for children. BIA measurements (resistance and reactance) were found to be reliable. Prediction accuracy (standard error of the estimate, SEE) for FFB from RI alone was 2.6 kg and for %FAT from RI and body weight was 4.2%. For RI, anthropometric variables and reactance, the SEE improved to 1.9 kg FFB. For RI and anthropometric variables, the SEE was 3.3% FAT. For anthropometric variables alone, the SEE's were 2.1 kg FFB and 3.2% FAT. Adult FFB and %FAT prediction equations cross-validated with this sample resulted in SEE's similar to those for adult samples. We conclude that RI together with anthropometry is a reliable and an acceptably accurate method of estimating FFB mass and %FAT in children.     

Reliability and variability of bioimpedance measures in normal adults: effects of age, gender, and body mass

This study aimed to analyze the reliability and evaluate the causes of variability of bioimpedance parameters. Direct measures were analyzed because they are not affected by inappropriate prediction models. Resistance (R), reactance (Xc), and phase angle (PA) were determined at three fixed frequencies (5, 50, and 100 kHz) in 653 normal Germans (244 males and 409 females), aged 20-90 years, using a phase-sensitive whole-body tetrapolar bioimpedance analyzer (BIA 2000-M, Data Input, Germany). From these values, six bioimpedance ratios were calculated (R(5)/R(50), R(5)/R(100), Xc(5)/Xc(50), Xc(5)/Xc(100), PA(5)/PA(50), and PA(5)/PA(100)). Reliability of duplicate measurements, as determined by technical error, is high. ANOVA for repeated measurements yields a significant frequency main effect (within-subjects factor) and significant effects of age and gender (between-subject factors) on variation of resistance, reactance, and phase angle. Multiple regression analyses indicate independent effects of age, gender, and body mass index on variability of resistance, reactance, and phase angle at the three frequencies. Gender primarily influences variation in resistance (smaller values in males), whereas age mainly affects variations in reactance and phase angle (smaller values in older adults). Obesity is associated with smaller resistance (at all frequencies) and smaller reactance (high frequencies), but larger phase-angle values (low frequency). The study shows that variability of direct bioimpedance measures depends on age, gender, and body mass characteristics of the study population. The potential benefit for using both low and high frequencies in R measures is to differentiate between extra- and intracellular fluid spaces, which may be altered during human growth and aging.     

Reliability and validity of body composition measures in female athletes.

The purpose of this investigation was to determine the reliability and validity of bioelectrical impedance (BIA) and near-infrared interactance (NIR) for estimating body composition in female athletes. Dual-energy X-ray absorptiometry was used as the criterion measure for fat-free mass (FFM). Studies were performed in 132 athletes [age = 20.4 +/- 1.5 (SD) yr]. Intraclass reliabilities (repeat and single trial) were 0.987-0.997 for BIA (resistance and reactance) and 0.957-0.980 for NIR (optical densities). Validity of BIA and NIR was assessed by double cross-validation. Because correlations were high (r = 0.969-0.983) and prediction errors low, a single equation was developed by using all 132 subjects for both BIA and NIR. Also, an equation was developed for all subjects by using height and weight only. Results from dual-energy X-ray absorptiometry analysis showed FFM = 49.5 +/- 6.0 kg, which corresponded to %body fat (%BF) of 20.4 +/- 3.1%. BIA predicted FFM at 49.4 +/- 5.9 kg (r = 0.981, SEE = 1.1), and NIR prediction was 49. 5 +/- 5.8 kg (r = 0.975, SEE = 1.2). Height and weight alone predicted FFM at 49.4 +/- 5.7 kg (r = 0.961, SEE = 1.6). When converted to %BF, prediction errors were approximately 1.8% for BIA and NIR and 2.9% for height and weight. Results showed BIA and NIR to be extremely reliable and valid techniques for estimating body composition in college-age female athletes.     

What does body size mean,from the “plant's eye view”?

Alternative metrics exist for representing variation in plant body size, but the vast majority of previous research for herbaceous plants has focused on dry mass. Dry mass provides a reasonably accurate and easily measured estimate for comparing relative capacity to convert solar energy into stored carbon. However, from a “plant's eye view”, its experience of its local biotic environment of immediate neighbors (especially when crowded) may be more accurately represented by measures of “space occupancy” (S–O) recorded in situ—rather than dry mass measured after storage in a drying oven. This study investigated relationships between dry mass and alternative metrics of S–O body size for resident plants sampled from natural populations of herbaceous species found in Eastern Ontario. Plant height, maximum lateral canopy extent, and estimated canopy area and volume were recorded in situ (in the field)—and both fresh and dry mass were recorded in the laboratory—for 138 species ranging widely in body size and for 20 plants ranging widely in body size within each of 10 focal species. Dry mass and fresh mass were highly correlated (r² > .95) and isometric, suggesting that for some studies, between‐species (or between‐plant) variation in water content may be unimportant and fresh mass can therefore substitute for dry mass. However, several relationships between dry mass and other S–O body size metrics showed allometry—that is, plants with smaller S–O body size had disproportionately less dry mass. In other words, they have higher “body mass density” (BMD) — more dry mass per unit S–O body size. These results have practical importance for experimental design and methodology as well as implications for the interpretation of “reproductive economy”—the capacity to produce offspring at small body sizes—because fecundity and dry mass (produced in the same growing season) typically have a positive, isometric relationship. Accordingly, the allometry between dry mass and S–O body size reported here suggests that plants with smaller S–O body size—because of higher BMD—may produce fewer offspring, but less than proportionately so; in other words, they may produce more offspring per unit of body size space occupancy.     

Effect of high contents of dietary animal-derived protein or carbohydrates on canine faecal microbiota

Background

Few equations have been developed in veterinary medicine compared to human medicine to predict body composition. The present study was done to evaluate the influence of weight loss on biometry (BIO), bioimpedance analysis (BIA) and ultrasonography (US) in cats, proposing equations to estimate fat (FM) and lean (LM) body mass, as compared to dual energy x-ray absorptiometry (DXA) as the referenced method. For this were used 16 gonadectomized obese cats (8 males and 8 females) in a weight loss program. DXA, BIO, BIA and US were performed in the obese state (T0; obese animals), after 10% of weight loss (T1) and after 20% of weight loss (T2). Stepwise regression was used to analyze the relationship between the dependent variables (FM, LM) determined by DXA and the independent variables obtained by BIO, BIA and US. The better models chosen were evaluated by a simple regression analysis and means predicted vs. determined by DXA were compared to verify the accuracy of the equations.

Results

The independent variables determined by BIO, BIA and US that best correlated (p?<?0.005) with the dependent variables (FM and LM) were BW (body weight), TC (thoracic circumference), PC (pelvic circumference), R (resistance) and SFLT (subcutaneous fat layer thickness). Using Mallows??Cp statistics, p value and r ² , 19 equations were selected (12 for FM, 7 for LM); however, only 7 equations accurately predicted FM and one LM of cats.

Conclusions

The equations with two variables are better to use because they are effective and will be an alternative method to estimate body composition in the clinical routine. For estimated lean mass the equations using body weight associated with biometrics measures can be proposed. For estimated fat mass the equations using body weight associated with bioimpedance analysis can be proposed.     

Density‐dependent polyphenism and baculovirus resistance in teak defoliator,Hyblaea puera (Cramer)

1. Field populations of the teak defoliator larvae, Hyblaea puera Cramer exhibit colour polyphenism under different population densities: greyish‐green with black‐ and orange‐coloured dorsal bands in low‐density endemic populations and uniformly black or intermediate colour during high‐density population. 2. The density dependence of colour polyphenism was confirmed by field monitoring of H. puera populations during 2008–2010. 3. The above findings were later substantiated by rearing H. puera larvae under different densities (i.e. solitary and crowded in the laboratory). Ninety one per cent of the solitary reared laboratory population developed bright coloration whereas, 92% of the group reared larvae turned to black. Eight per cent of larvae from both the rearing densities were of intermediate colour. 4. Density‐dependent resistance build‐up against H. puera nucleopolyhedrovirus by H. puera were tested using the fifth instar larvae. The results showed three‐fold increase of median lethal dose (LD₅₀) value for the group reared larvae (5332 polyhedral occlusion bodies/larvae) compared to the solitary reared ones (1727 polyhedral occlusion bodies/larva) and also significant difference for the mean time to death (3.6 and 3.3 days, respectively). 5. The study revealed the strong influence of larval density on H. puera larval melanism and resistance build‐up against H. puera nucleopolyhedrovirus.     

Assessing Body Composition among 3‐ to 8‐Year‐Old Children: Anthropometry,BIA, and DXA

Objective: To examine the inter‐relationships of body composition variables derived from simple anthropometry [BMI and skinfolds (SFs)], bioelectrical impedance analysis (BIA), and dual energy x‐ray (DXA) in young children. Research Methods and Procedures: Seventy‐five children (41 girls, 34 boys) 3 to 8 years of age were assessed for body composition by the following methods: BMI, SF thickness, BIA, and DXA. DXA served as the criterion measure. Predicted percentage body fat (%BF), fat‐free mass (FFM; kilograms), and fat mass (FM; kilograms) were derived from SF equations [Slaughter (SL)1 and SL2, Deurenberg (D) and Dezenberg] and BIA. Indices of truncal fatness were also determined from anthropometry. Results: Repeated measures ANOVA showed significant differences among the methods for %BF, FFM, and FM. All methods, except the D equation (p = 0.08), significantly underestimated measured %BF (p < 0.05). In general, correlations between the BMI and estimated %BF were moderate (r = 0.61 to 0.75). Estimated %BF from the SL2 also showed a high correlation with DXA %BF (r = 0.82). In contrast, estimated %BF derived from SFs showed a low correlation with estimated %BF derived from BIA (r = 0.38); likewise, the correlation between DXA %BF and BIA %BF was low (r = 0.30). Correlations among indicators of truncal fatness ranged from 0.43 to 0.98. Discussion: The results suggest that BIA has limited utility in estimating body composition, whereas BMI and SFs seem to be more useful in estimating body composition during the adiposity rebound. However, all methods significantly underestimated body fatness as determined by DXA, and, overall, the various methods and prediction equations are not interchangeable.     

Limited mass‐independent individual variation in resting metabolic rate in a wild population of snow voles (Chionomys nivalis)

Resting metabolic rate (RMR) is a potentially important axis of physiological adaptation to the thermal environment. However, our understanding of the causes and consequences of individual variation in RMR in the wild is hampered by a lack of data, as well as analytical challenges. RMR measurements in the wild are generally characterized by large measurement errors and a strong dependency on mass. The latter is problematic when assessing the ability of RMR to evolve independently of mass. Mixed models provide a powerful and flexible tool to tackle these challenges, but they have rarely been used to estimate repeatability of mass‐independent RMR from field data. We used respirometry to obtain repeated measurements of RMR in a long‐term study population of snow voles (Chionomys nivalis) inhabiting an environment subject to large circadian and seasonal fluctuations in temperature. Using both uni‐ and bivariate mixed models, we quantify individual repeatability in RMR and decompose repeatability into mass‐dependent and mass‐independent components, while accounting for measurement error. RMR varies among individuals, that is, is repeatable (R = .46) and strongly co‐varies with BM. Indeed, much of the repeatability of RMR is attributable to individual variation in BM, and the repeatability of mass‐independent RMR is reduced by 41% to R = .27. These empirical results suggest that the evolutionary potential of RMR independent of mass may be severely constrained. This study illustrates how to leverage bivariate mixed models to model field data for metabolic traits, correct for measurement error and decompose the relative importance of mass‐dependent and mass‐independent physiological variation.     

Selective herbivory by an invasive cyprinid,the rudd Scardinius erythrophthalmus

相似文献   

New Technology for Estimating Seed Production of Moist-Soil Plants

ABSTRACT Waterfowl biologists estimate seed production in moist-soil wetlands to calculate duck-energy days (DEDs) and evaluate management techniques. Previously developed models that predict plant seed yield using morphological measurements are tedious and time consuming. We developed simple linear regression models that indirectly and directly related seed-head area to seed production for 7 common moist-soil plants using portable and desktop scanners and a dot grid, and compared time spent processing samples and predictive ability among models. To construct models, we randomly collected approximately 60 plants/species at the Tennessee National Wildlife Refuge, USA, during September 2005 and 2006, threshed and dried seed from seed heads, and related dry mass to seed-head area. All models explained substantial variation in seed mass (R²< 0.87) and had high predictive ability (R²_predicted < 0.84). Processing time of seed heads averaged 22 and 3 times longer for the dot grid and portable scanner, respectively, than for the desktop scanner. We recommend use of desktop scanners for accurate and rapid estimation of moist-soil plant seed production. Seed predictions per plant from our models can be used to estimate total seed production and DEDs in moist-soil wetlands.     

Effect of Influenza-Induced Fever on Human Bioimpedance Values

Background and Aims

Bioelectrical impedance analysis (BIA) is a widely used technique to assess body composition and nutritional status. While bioelectrical values are affected by diverse variables, there has been little research on validation of BIA in acute illness, especially to understand prognostic significance. Here we report the use of BIA in acute febrile states induced by influenza.

Methods

Bioimpedance studies were conducted during an H1N1 influenza A outbreak in Venezuelan Amerindian villages from the Amazonas. Measurements were performed on 52 subjects between 1 and 40 years of age, and 7 children were re-examined after starting Oseltamivir treatment. Bioelectrical Impedance Vector Analysis (BIVA) and permutation tests were applied.

Results

For the entire sample, febrile individuals showed a tendency toward greater reactance (p=0.058) and phase angle (p=0.037) than afebrile individuals, while resistance and impedance were similar in the two groups. Individuals with repeated measurements showed significant differences in bioimpedance values associated with fever, including increased reactance (p<0.001) and phase angle (p=0.007), and decreased resistance (p=0.007) and impedance (p<0.001).

Conclusions

There are bioelectrical variations induced by influenza that can be related to dehydration, with lower extracellular to intracellular water ratio in febrile individuals, or a direct thermal effect. Caution is recommended when interpreting bioimpedance results in febrile states.     

A new BIA equation estimating the body composition of young children

Bioelectric impedance analyses (BIA) provides a valid and reliable measure of body composition in field, clinical, and research settings if standard protocol procedures are followed, and population-specific equations are available and utilized. The objective of this study was to create and cross-validate a new BIA body composition equation with representative healthy weight (HW), overweight (OW), and obese (OB) young children. Participants were 436 children who were 5-11 years of age. Dual-energy absorptiometry fat-free mass (FFM) was used as the criterion measure and a single frequency tetra-polar BIA device was used to create the new BIA equation. The new BIA equation explained 95.2% of the variance in FFM with no statistical shrinkage upon cross-validation. The use of this equation may help to identify effective intervention strategies to prevent or combat childhood obesity, and may assist in additional conditions or treatments where information concerning body composition measures would provide greater accuracy and sensitivity measures for preventing or combating disease.     

Photosynthesis and Leaf Structure in Domesticated Cassava (Euphorbiaceae) and a Close Wild Relative: Have Leaf Photosynthetic Parameters Evolved Under Domestication?

Broad patterns across wild plant species show that leaf composition and morphology vary predictably among habitats, richer habitats favoring resource‐acquisition strategies and poorer habitats favoring resource‐conservation strategies. Domestication is often accompanied by a shift to richer habitats, and might thus be expected to lead to a shift in leaf composition and morphology and hence in photosynthetic parameters. We compared leaf photosynthetic parameters in domesticated cassava (Manihot esculenta) and a close wild relative, using greenhouse‐grown plants. In domesticated cassava, CO₂ exchange rate expressed per unit mass and specific leaf area (SLA, m²/kg dry mass) were greater than in the wild relative, whereas leaf dry matter content (LDMC, dry mass/fresh mass) was lower in the domesticate. These results suggest that SLA and net photosynthetic rates may both have increased in the evolution of cassava under domestication, enabling more rapid growth in relatively resource‐rich and protected agricultural habitats. Previous comparisons of photosynthetic rates in domesticated plants and wild relatives have usually considered only leaf area‐based measures. Here, we discuss the interest of using mass‐based rates to study the evolution of ecological strategies under domestication.     

Crystal structure of norcoclaurine‐6‐O‐methyltransferase,a key rate‐limiting step in the synthesis of benzylisoquinoline alkaloids

Growing pharmaceutical interest in benzylisoquinoline alkaloids (BIA) coupled with their chemical complexity make metabolic engineering of microbes to create alternative platforms of production an increasingly attractive proposition. However, precise knowledge of rate‐limiting enzymes and negative feedback inhibition by end‐products of BIA metabolism is of paramount importance for this emerging field of synthetic biology. In this work we report the structural characterization of (S)‐norcoclaurine‐6‐O‐methyltransferase (6OMT), a key rate‐limiting step enzyme involved in the synthesis of reticuline, the final intermediate to be shared between the different end‐products of BIA metabolism, such as morphine, papaverine, berberine and sanguinarine. Four different crystal structures of the enzyme from Thalictrum flavum (Tf 6OMT) were solved: the apoenzyme, the complex with S‐adenosyl‐l ‐homocysteine (SAH), the complexe with SAH and the substrate and the complex with SAH and a feedback inhibitor, sanguinarine. The Tf 6OMT structural study provides a molecular understanding of its substrate specificity, active site structure and reaction mechanism. This study also clarifies the inhibition of Tf 6OMT by previously suggested feedback inhibitors. It reveals its high and time‐dependent sensitivity toward sanguinarine.     

Bioimpedance for severe obesity: comparing research methods for total body water and resting energy expenditure

Objective: As the acceptance of surgical procedures for weight loss in morbid obesity is increasing, clinically useful baseline and follow‐up measures of total body water (TBW) and resting energy expenditure (REE) are important. Research methods such as deuterium (D²O) dilution and metabolic carts are problematic in the clinical setting. We compared bioimpedance analysis (BIA) predicted (Tanita TBF‐310) and measured TBW and REE. Methods and Procedures: Forty‐two paired presurgery studies were completed using BIA and D²O in patients with BMI (mean ± s.d.) 50.2 ± 8.8 kg/m² for TBW, and 30 patients with BMI 51.0 ± 13 kg/m² completed paired determinations of REE with metabolic carts and the Tanita balance with weight, height, sex, and age modifiers. Regression analysis and Bland‐Altman plots were applied. Results: When regression analysis was completed for TBW, regression line was consistent with the identity line “y = x.” The intercept was not different from 0 (95% confidence interval ?2.5 ± 7.0). The slope of the line was not different from 1.0 ± 0.1. The measured TBW 51.2 ± 10.1 l had a correlation with the predicted 49.5 ± 11.27 l of 0.92. There also was no significant difference (P = 0.33) between predicted (2,316 ± 559 kcal/day) and measured REE (2,383 ± 576 kcal/day);δ 66.7 ± 273 kcal/day. The two measures were highly correlated (r = 0.88) with no bias detected. Discussion: These observations support the use of the BIA system calibration in subjects with severe obesity. Without the use of complex, costly equipment and invasive procedures, BIA measurements can easily be obtained in clinical practice to monitor patient responses to treatment.     

Sensitivity of continental United States atmospheric budgets of oxidized and reduced nitrogen to dry deposition parametrizations

Reactive nitrogen (N_r) is removed by surface fluxes (air–surface exchange) and wet deposition. The chemistry and physics of the atmosphere result in a complicated system in which competing chemical sources and sinks exist and impact that removal. Therefore, uncertainties are best examined with complete regional chemical transport models that simulate these feedbacks. We analysed several uncertainties in regional air quality model resistance analogue representations of air–surface exchange for unidirectional and bi-directional fluxes and their effect on the continental N_r budget. Model sensitivity tests of key parameters in dry deposition formulations showed that uncertainty estimates of continental total nitrogen deposition are surprisingly small, 5 per cent or less, owing to feedbacks in the chemistry and rebalancing among removal pathways. The largest uncertainties (5%) occur with the change from a unidirectional to a bi-directional NH₃ formulation followed by uncertainties in bi-directional compensation points (1–4%) and unidirectional aerodynamic resistance (2%). Uncertainties have a greater effect at the local scale. Between unidirectional and bi-directional formulations, single grid cell changes can be up to 50 per cent, whereas 84 per cent of the cells have changes less than 30 per cent. For uncertainties within either formulation, single grid cell change can be up to 20 per cent, but for 90 per cent of the cells changes are less than 10 per cent.     

Bioelectrical impedance vs. four-compartment model to assess body fat change in overweight adults

Objective: The Tanita TBF‐305 body fat analyzer is marketed for home and clinical use and is based on the principles of leg‐to‐leg bioelectrical impedance analysis (BIA). Few studies have investigated the ability of leg‐to‐leg BIA to detect change in percentage fat mass (%FM) over time. Our objective was to determine the ability of leg‐to‐leg BIA vs. the four‐compartment (4C) model to detect small changes in %FM in overweight adults. Research Methods and Procedures: Thirty‐eight overweight adults (BMI, 25.0 to 29.9 kg/m²; age, 18 to 44 years; 31 women) participated in a 6‐month, randomized, double‐blind, placebo‐controlled study of a nutritional supplement. Body composition was measured at 0 and 6 months using the Tanita TBF‐305 body fat analyzer [using equations derived by the manufacturer (%FM_T‐Man) and by Jebb et al. (%FM_T‐Jebb)] and the 4C model (%FM_4C). Results: Subjects in the experimental group lost 0.9%FM_4C (p = 0.03), a loss that did not reach significance using leg‐to‐leg BIA (0.6%FM_T‐Man, p = 0.151; 0.6%FM_T‐Jebb, p = 0.144). We observed large standard deviations (SDs) in the mean difference in %FM between the 4C model and the Tanita_Manufacturer (2.5%) and Tanita_Jebb (2.2%). Ten subjects fell outside ±1 SD of the mean differences at 0 and 6 months; those individuals were younger and shorter than those within ±1 SD. Discussion: Leg‐to‐leg BIA performed reasonably well in predicting decreases in %FM in this group of overweight adults but resulted in wide SDs vs. %FM_4C in individuals. Cross‐sectional determinations of %FM of overweight individuals using leg‐to‐leg BIA should be interpreted with caution.