Comparison between methods to estimate total body fat mass in triathletes: dual X-ray absorptiometry, bioelectrical impedance and anthropometric equations

The purpose of this pilot study was to compare estimates of percentage body fat mass (FM) by bioelectric impedance analysis (BIA) and skinfold measurements (SF) with estimates obtained from dual-energy x-ray absorptiometry (DEXA) in 47 HIV-infected male subjects receiving highly active antiretroviral therapy (HAART). As different patterns of abdominal fat accumulation might affect the body FM estimation, correlation and agreement of these methods were also compared in patients with waist to hip ratio (WHR) < or =0.9 and >0.9. Body FM was estimated by BIA and by measuring skinfold thickness at biceps, triceps, and subscapular area, and was compared with DEXA as the reference method using paired t-test. Estimates by SF were significantly higher and by BIA were significantly lower compared with DEXA for all subjects. This relationship persisted only in those with WHR >0.9. Both BIA and SF correlated significantly with DEXA, but they did not agree. However, both techniques showed a small intermethod bias, and the precision was within the acceptable range. This relationship persisted in those with WHR >0.9. In comparison with measurement by BIA, SF showed poorer agreement (larger bias and error). For population studies and perhaps to monitor changes over time for intervention studies, the bias for both BIA and SF methods is relatively small and errors and precisions are within the acceptable range when compared with DEXA, and thus all 3 techniques can be used for routine monitoring of total body FM in male subjects with HIV infection.

Lean body mass is an important predictor of survival and functional status in patients with AIDS wasting. The bias between different techniques for assessing body composition in AIDS wasting is not known. We compared total body potassium (TBK) with fat-free mass (FFM) determined by dual-energy X-ray absorptiometry (DXA), bioelectrical impedance analysis (BIA), and skinfold-thickness measurement (SKF) in 132 patients (63 men, 69 women) with AIDS wasting (weight < 90% of ideal body weight, or weight loss > 10% of original, or both). None of the subjects exhibited clinical lipodystrophy. Comparisons were made by using different BIA equations. Lean body mass determined by DXA was highly correlated with TBK in men (r = 0.79, P: < 0.0001) and women (r = 0.84, P: < 0.0001). FFM(BIA) and FFM(DXA) were significantly different (P: < 0.01 in men and P: < 0.0001 in women). The difference between FFM(DXA) and FFM(BIA) was significantly greater with greater weight and body fat, particularly in HIV-infected women (r = -0.39, P: = 0.001 for weight; r = -0.60, P: < 0.0001 for fat). The comparability of FFM and fat mass determined by DXA and BIA was dependent on the specific BIA equation used. Among men, no single BIA equation was more highly predictive of fat mass and FFM in comparison with DXA. The differences between DXA, BIA, and SKF in the determination of fat mass and FFM are significant in patients with AIDS wasting. BIA overestimates FFM compared with DXA in those with greater body fat. Standard BIA equations may not accurately estimate FFM and fat mass in men and women with AIDS wasting.

Comparison of methods to assess change in children's body composition

Bioelectrical impedance analysis (BIA) is more commonly employed in outpatient evaluations and epidemiological studies as it is cheaper and less time-consuming. Therefore, we aimed to compare fat mass (FM) and fat-free mass (FFM) estimated by BIA and dual-energy x-ray absorptiometry (DXA) in Portuguese adults, and to calibrate BIA estimates. We analyzed data from two population-based cohorts: EPIPorto (n = 391; <65 y) and EPITeen (n = 973; 27 y). Both completed single-frequency leg-to-leg BIA (Tanita TBF-300) and DXA (QDR 4500A Hologic). Agreement between BIA and DXA (FM/FFM) was evaluated by Bland and Altman. To calibrate the BIA estimates, the coefficients were estimated by linear regression using univariate (FM or FFM, separately) and multivariate models (FM and FFM in the same model). The correlation between BIA and DXA was high for FFM and for FM (FFM: r = 0.946/r = 0.954; FM: r = 0.926/r = 0.921, for EPIPorto and EPITeen, respectively). However, BIA underestimated FM (19.4% EPIPorto; 24.3% EPITeen) and overestimated FFM (11.3% EPIPorto; 14.4% EPITeen). Using the multivariate constrained model to have an absolute equal intercept for FFM and FM, the following calibration equations for BIA measurements were obtained for EPIPorto: FFMcalibrated = -5.119 + 0.995 × FFMBIA; FMcalibrated = +5.119 + 0.980 × FMBIA; and for EPITeen: FFMcalibrated = -5.707 + 0.984 × FFMBIA; FMcalibrated = +5.707 + 0.975 × FMBIA. FM assessed by single-frequency leg-to-leg BIA was largely underestimated and FFM overestimated in comparison to DXA, suggesting the use of BIA model-specific calibration equations to calibrate FM and FFM estimates in clinical settings and research studies.

To compare single estimations of fat-free mass (FFM) and to track FFM using single-frequency bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA) compared with a four-compartment (4C) model in healthy elderly Americans. Thirty-four men and thirty-eight women (Caucasian, ≥ 65 years) were included in the study. Subjects participated in either the control group or the exercise group. All testing and training took place during the 21-week investigation. Body composition assessments using nine BIA equations, DXA and a 4C model were performed during weeks 1, 12 and 24 of the study. Single estimations for DXA and BIA produced high r values (0.79-0.95) and low standard error of estimate values (1.62-3.3 kg), producing subjective ratings of 'ideal' for men and 'excellent' for women. Both DXA and two BIA equations revealed the same significance when comparing groups and times with the 4C model. Individual accuracy for tracking changes was similar among BIA equations and DXA compared with the 4C model, with a total agreement of 25% for BIA and 27% for DXA compared with the 4C model. The current data in combination with the reliability errors for both BIA and DXA FFM estimations suggest that individual results should be interpreted with caution if FFM changes are <5 kg. However, DXA and BIA are both valid methods that can be used interchangeably to estimate FFM at a single time point or for tracking changes in FFM in small groups (15-22) of healthy American older adults.

A variety of easy-to-use commercial bioelectrical impedance appliances are available. The aim of this study was to examine the usefulness of a commercially available body composition meter using bioelectrical impedance analysis (BIA) by comparing its measurement results with those obtained from dual-energy X-ray absorptiometry (DXA). The participants were 443 children aged from 10 to 14 years (226 boys and 217 girls). Fat mass, fat-free mass, lean body mass, percentage of body fat, and bone mineral contents were evaluated for all participants using BIA and DXA. The agreement in the anthropometric data obtained from both devices was analyzed using correlation analysis, intraclass correlation coefficient (ICC), Lin’s concordance correlation coefficient (CCC), Bland–Altman plots, and ordinary least products regression analysis. Equivalence between both devices was tested by two one-sided t-test. All measured indicators showed strong linear correlations between the two measurement systems (r, 0.853–1.000). Fat mass, fat-free mass, and lean body mass showed absolute concordance (ICC, 0.902–0.972; Lin’s CCC, 0.902–0.972). BIA overestimated bone mineral content (62.7–66.5%) and underestimated percentage of body fat (− 8.9 to − 0.8%), lean body mass (− 3.5 to − 1.8%), and body mass (− 0.8 to − 0.5%). For fat mass and fat-free mass, the overestimate or underestimate varied according to the sex and statistical analysis test. Bland–Altman analysis and ordinary least products analysis showed fixed bias and proportional bias in all indicators. Results according to quartiles of body mass index showed poor agreement for fat mass and percentage of body fat in both boys and girls in the lowest body mass index quartile. The present results revealed strong linear correlations between BIA and DXA, which confirmed the validity of the present single-frequency BIA-derived parameters. Our results suggest that BIA cannot provide the exact same values as DXA for some body composition parameters, but that performance is sufficient for longitudinal use within an individual for daily health management and monitoring.

Skeletal muscle mass in hospitalized elderly patients: Comparison of measurements by single-frequency BIA and DXA

Background: Patients with chronic kidney disease (CKD) are vulnerable to loss of muscle mass due to several metabolic alterations derived from the uremic syndrome. Reference methods for body composition evaluation are usually unfeasible in clinical settings.Aims: To evaluate the accuracy of predictive equations based on bioelectrical impedance analyses (BIA) and anthropometry parameters for estimating fat free mass (FFM) and appendicular FFM (AFFM), compared to dual energy X-ray absorptiometry (DXA), in CKD patients.Methods: We performed a longitudinal study with patients in non-dialysis-dependent, hemodialysis, peritoneal dialysis and kidney transplant treatment. FFM and AFFM were evaluated by DXA, BIA (Sergi, Kyle, Janssen and MacDonald equations) and anthropometry (Hume, Lee, Tian, and Noori equations). Low muscle mass was diagnosed by DXA analysis. Intra-class correlation coefficient (ICC), Bland-Altman graphic and multiple regression analysis were used to evaluate equation accuracy, linear regression analysis to evaluate bias, and ROC curve analysis and kappa for reproducibility.Results: In total sample and in each CKD group, the predictive equation with the best accuracy was AFFMSergi (men, n = 137: ICC = 0.91, 95% CI = 0.79–0.96, bias = 1.11 kg; women, n = 129: ICC = 0.94, 95% CI = 0.92–0.96, bias = −0.28 kg). AFFMSergi also presented the best performance for low muscle mass diagnosis (men, kappa = 0.68, AUC = 0.83; women, kappa = 0.65, AUC = 0.85). Bias between AFFMSergi and AFFMDXA was mainly affected by total body water and fat mass. None of the predictive equations was able to accurately predict changes in AFFM and FFM, with all ICC lower than 0.5.Conclusion: The predictive equation with the best performance to asses muscle mass in CKD patients was AFFMSergi, including evaluation of low muscle mass diagnosis. However, assessment of changes in body composition was biased, mainly due to variations in fluid status together with adiposity, limiting its applicability for longitudinal evaluations.

Malnutrition is a consistent finding in hemodialysis (HD) patients and is associated with high mortality. The aim was to compare nutrition status indicators using dual-energy x-ray absorptiometry (DXA) as reference in HD patients. Observational cross-sectional study with 42 patients, 55.8 years (±14.6) old, 60% male, HD 2-3 times per week for ≥3 months. HD ranged from 3 months to 28 years (median, 17.3; interquartile range, 8.73-39.0). We used body mass index (BMI) and fat mass (FM) by skinfold thickness (SFT), bioelectrical impedance analysis (BIA), and DXA. Statistical analyses used Bland-Altman plots, Lin's concordance correlation coefficient, the paired t-test, and Pearson or Spearman correlation. P < .05 was significant. SFT and DXA presented the lowest prevalence of malnutrition (2.4%) and BMI the highest (28.6%). BMI, BIA FM, and SFT FM presented strong positive correlations with DXA FM (r = 0.915; r = 0.976; r = 0.910, P < .001, respectively). BIA FM and fat-free mass (FFM) demonstrated substantial agreement with DXA values (ρ = 0.974 and 0.960, P < .001). Thus, the measurement procedures used, SFT and BIA, underestimated %FM (-4.65% and -2.13%) and overestimated FFM (3.12 kg and 1.0 kg) according to DXA. No differences were found between mean values of BIA FM and DXA (P = .178). Compared with DXA, BIA was the most appropriate nutrition indicator for measuring body composition.

The aim of this study is to compare total weight, % body fat (% BF), fat mass (FM) and fat-free mass (FFM) measured by bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA). This cross-sectional study included 159 women (mean age: 49.1 +/- 10.0 years) and 124 men (mean age: 51.4 +/- 8.0 years) subdivided according to sex and body mass index (BMI): BMI < 30 kg/m(2) (66 women and 50 men); BMI 30-35 kg/m(2) (53 women and 44 men) and BMI > or = 35 kg/m(2) (40 women and 30 men). Bioelectrical impedance was performed in the fasting state on a Tanita TBF-215 leg-to-leg analyser (Tanita, Tokyo, Japan). Whole-body DXA scans were performed on a Hologic QDR 4500 A bone densitometer (Hologic, Bedford, MA, USA). Total weight, % BF, FM and FFM were tested for intermethod differences. Linear regression and correlation analysis was performed. Limits of agreement and Bland-Altman plots were built. DXA-derived body composition parameters were not significantly different from BIA estimates and were highly correlated (e.g. for FFM, r = 0.82-0.95). In lean individuals, BIA tended to produce lower values for FM and % BF and higher ones for FFM in comparison with DXA. This trend was reversed at BMI > 35 kg/m(2). The correlations decreased with increasing BMI. The limits of agreement were much better in men than in women and increased with increasing BMI in both sexes. Compared with DXA, the leg-to-leg Tanita TBF-215 analyser accurately assessed body composition in a heterogeneous group of both sexes. In the very obese women (BMI > 35 kg/m(2)), BIA measurements should be viewed with caution.

In the present study, hand-to-hand bioelectrical impedance analysis (BIA), skinfold (SKF) thickness and height-weight (body mass index, BMI)-based equations and dual-energy X-ray absorptiometry (DEXA), as a criterion method, were compared with each other in the assessment of body fat percentage (BF%) in 17-18-year-old Estonian conscripts (n = 32). The Omron BF body fat monitor estimated that BF% was lower than that of the criterion method DEXA. The difference between DEXA and Omron BF 300 (III) was higher (1.1 +/- 3.0%; P = 0.04) and that between DEXA and Omron BF 306 lower (0.2 +/- 3.0%; P>0.05). Omron BF 300 (I) and (II) (series 8) had intermediate difference (0.9 +/- 3.0 and 0.9 +/- 3.0; P>0.05) when compared with DEXA. Three anthropometric equations estimated a higher BF% than cthat of DEXA. The Durnin & Womersley SKF equation BF% (1.0 +/- 2.4; P = 0.03) was higher than that of the DEXA. Deurenberg et al. and Gallagher et al. BMI-based equations overestimation yielded 0.9 +/- 3.7 and 0.6 +/- 3.8 BF% (P>0.05). From the anthropometric equations, only the Deurenberg et al. SKF equation slightly underestimated 0.5 +/- 3.4 BF% (P>0.05). DEXA-assessed BF% had highest correlation with SKF equations (r = 0.93), less so with BIA (r = 0.88-0.89) and lowest with BMI equation-assessed BF% (r = 0.81-0.84). All values were significant at P<0.001. We can conclude that the Omron BF 306 body fat monitor and the anthropometric Deurenberg et al. SKF equation yielded results close to the DEXA BF%.

Estimating Body Fatness from Bioelectrical Impedance Analysis and Skinfolds in Children

In obese patients, subtle variations of the hydration of soft tissues can propagate errors in bioelectrical impedance analysis (BIA) measures of body composition. Bioelectrical impedance vector analysis (BIVA) is a useful method to evaluate tissue hydration. Laparoscopic adjustable gastric banding (LAGB) is a purely restrictive bariatric surgical procedure resulting in lower fat-free mass (FFM) loss than other malabsorptive or mixed intervention. The aim of this study was to evaluate the 6- and 12-month changes in body composition in a homogeneous group of premenopausal morbidly obese women treated by LAGB by comparing the results of conventional BIA and BIVA with dual-energy X-ray absorptiometry (DXA) method. Forty-five consecutive morbidly obese patients (mean age, 35.3 +/- 9.1 years; body mass index, 34.5-48.7 kg/m(2)) were prospectively evaluated at the Endocrinology Unit of the Department of Molecular and Clinical Endocrinology and Oncology. The LAGB device (Lap-Band System; Inamed Health, Santa Barbara, CA, USA) was inserted laparoscopically. Soft tissue hydration was evaluated by BIVA; fat mass (FM) and FFM were evaluated by BIA (BIA 101 RJL, Akern Bioresearch, Firenze, Italy) and by DXA (Hologic QDR 4500A S/N 45622; Hologic Inc., Bedford, MA, USA). Pre- and postoperative BIVA vectors indicated a normal hydration in all patients. Postoperatively, the excess of body weight loss was mainly due to a decrease in FM. The regression analysis of BIA and DXA methods at baseline and at the 6- and 12-month follow-up for FM r (2) values were 0.98, 0.94, and 0.99, respectively (p < 0.001); FM% r (2) values were 0.91, 0.89, and 0.98, respectively (p < 0.001); and FFM r (2) values were 0.87, 0.82, 0.99, respectively (p < 0.001). BIA and DXA measurements of body composition exhibit a high relative agreement in the study group of normo-hydrated obese subjects. BIA tends to overestimate FFM, but this effect is reduced along with the weight loss during the follow-up. Under the stable hydration, the BIA method may be useful as an alternative to DXA in a selected clinical setting when repeated comparisons of body composition are required.

Interest in evaluating the composition of specific anatomical regions has become commonplace in a variety of settings. Appendicular lean soft tissue (ALST) estimates are considered in the diagnosis of sarcopenia. While dual-energy x-ray absorptiometry (DXA) is viewed as a reference method for regional assessments, its availability is limited. Thus, explaining discrepancies in regional body composition estimates between DXA and the more accessible bioelectrical impedance analysis (BIA) is of utmost importance. PURPOSE: To assess the anthropometric and physiological predictors of variations between BIA and DXA segmental lean soft tissue (LST) estimates. METHODS: During a single visit, 179 participants (103 females, 76 males; Mean ± SD: 33.6 ± 15.3 years; 73.4 ± 16.2 kg; 171.2 ± 9.2 cm; 28.2 ± 8.9% DXA body fat %) underwent body composition assessments via DXA and 8-point single-frequency BIA. Potential predictors of discrepancies between DXA and BIA LST estimates were obtained from these methods and additional laboratory techniques. Specifically, air displacement plethysmography, 3-dimensional optical scanning, and bioimpedance spectroscopy were used to estimate body volume, anthropometrics, and hydration variables, respectively. Significant predictors (p ≤ 0.05) of the mean difference between DXA and BIA estimates of trunk LST (TLST) and ALST were established using ordinary least squares regression. Standardized model coefficients, p-values for coefficients, and R2 values were generated. RESULTS: For both TLST and ALST, extracellular fluid percentage, LST hydration, height, total LST mass, the male sex, and racial identification as Black significantly predicted discrepancies between DXA and BIA. Additional predictors for TLST discrepancies were DXA total fat mass (FM) to LST ratio and DXA TLST, while additional predictors of ALST discrepancies included DXA ALST, DXA FM to LST ratio of the legs, DXA appendicular FM, and DXA-derived volume of the arms and legs. Regression models including these significant predictor variables produced R2 values of 0.92 and 0.95 for TLST and ALST, respectively. CONCLUSIONS: Hydration variables, the quantity of LST in the region of interest, and height were the most influential predictor variables for discrepancies between DXA and BIA segmental LST estimates.

Background: This study aimed to evaluate whether Bioelectrical Impedance Analysis (BIA) can serve as a practical alternative to Dual- Energy X-ray Absorptiometry (DEXA) for measuring body composition in clinical settings.Methods: BIA (InBody970, InBody770, InBody770C, and InBody270C) and DEXA were repeatedly used for measurements on the same day (n=100). Participants fasted for at least 4 hours and stood upright for 10 minutes before the measurements to stabilize body water composition.Results: All four BIA devices (InBody970, InBody770, InBody770C, and InBody270C) showed a high correlation with DEXA, with Pearson correlation coefficients (r) of ≥0.97 for both muscle mass and body fat mass. Among them, the InBody770C demonstrated a slightly higher correlation in body fat mass measurements (P&lt;0.05). However, Lin’s Concordance Correlation Coefficient ranged from 0.939 to 0.941, indicating only moderate agreement. In addition, Bland–Altman analysis revealed statistically significant mean biases and wide limits of agreement across all devices, suggesting that strong correlation does not necessarily imply measurement equivalence.Conclusions: Given the high correlation between BIA and DEXA, BIA may serve as a useful tool for tracking body composition. However, moderate agreement levels suggest that caution is warranted when interpreting BIA as a substitute for DEXA in clinical practice.