Validity of the BOD POD for assessing body composition in athletic high school boys

The purpose of this study was to validate the percentage of body fat (%BF) values estimated from the BOD POD (BP) with those obtained from hydrostatic weighing (HW) in athletic American high school boys. Additionally, the %BF values measured via near-infrared interactance (NIR), bioelectrical impedance (BIA), and skinfold (SF) were compared to HW to determine the validity of these measures. Thirty white boys (mean age +/- SD = 15.8 +/- 1.0 years) who where currently participating in organized sports volunteered to have their %BF estimated. Measurements were obtained from NIR, BP, BIA, and SF in random order and concluded with HW. The findings from the present study indicated that the NIR and BIA instruments produced significant (P < 0.008) constant error (CE) and total error (TE) values that were too large to be of practical value (TE > 4.0%BF). The BP produced a significantly (P < 0.008) higher CE with acceptable TE values compared to HW, but compared to all three SF estimations, the BP TE values were higher. Two of the SF equations were nonsignificant (P > 0.008) and had the lowest TE values compared to HW. These data suggest that the BP can produce acceptable body fat measures for athletic white boys but is not superior to estimates made by the SF equations used in this study.     

Use of bioelectrical impedance to assess body composition changes at high altitude.

This study determined the feasibility of using bioelectrical impedance analysis (BIA) to assess body composition alterations associated with body weight (BW) loss at high altitude. The BIA method was also evaluated relative to anthropometric assessments. Height, BW, BIA, skinfold (SF, 6 sites), and circumference (CIR, 5 sites) measurements were obtained from 16 males (23-35 yr) before, during, and after 16 days of residence at 3,700-4,300 m. Hydrostatic weighings (HW) were performed pre- and postaltitude. Results of 13 previously derived prediction equations using various combinations of height, BW, age, BIA, SF, or CIR measurements as independent variables to predict fat-free mass (FFM), fat mass (FM), and percent body fat (%Fat) were compared with HW. Mean BW decreased from 84.74 to 78.84 kg (P less than 0.01). As determined by HW, FFM decreased by 2.44 kg (P less than 0.01), FM by 3.46 kg (P less than 0.01), and %Fat by 3.02% (P less than 0.01). The BIA and SF methods overestimated the loss in FFM and underestimated the losses in FM and %Fat (P less than 0.01). Only the equations utilizing the CIR measurements did not differ from HW values for changes in FFM, FM, and %Fat. It was concluded that the BIA and SF methods were not acceptable for assessing body composition changes at altitude.     

Comparison of body composition methods in obese African-American women

Objective : To compare the accuracy of percentage body fat (%BF) estimates between bioelectrical impedance analysis (BIA) and DXA in obese African‐American women. Research Methods and Procedures : Fifty‐five obese African‐American women (mean age, 45 years; mean BMI, 38; mean %BF, 48%) were studied. BF was assessed by both BIA (RJL Systems BIA 101Q; RJL Systems, Clinton Township, MI) and DXA (Hologic QDR‐2000 Bone Densitometer; Hologic Inc., Bedford, MA). Generalized and ethnicity‐ and obese‐specific equations were used to calculate %BF from the BIA. Bland‐Altman analyses were used to compare the agreement between the BIA and the DXA, with the DXA serving as the criterion measure. Results : Two of the generalized equations provided consistent estimates across the weight range in comparison with the DXA estimates, whereas most of the other equations increasingly underestimated %BF as BF increased. One of the generalized and one of the ethnicity‐specific equations had mean differences that were not significantly different from the DXA value. Discussion : The findings show that the Lukaski equation provided the most precise and accurate estimates of %BF in comparison with the QDR 2000 and provide preliminary support for the use of this equation for obese African‐American women.     

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.     

Evaluation of the BOD POD and leg-to-leg bioelectrical impedance analysis for estimating percent body fat in National Collegiate Athletic Association Division III collegiate wrestlers

The purpose of this study was to compare percent body fat (%BF) estimated by air displacement plethysmography (ADP) and leg-to-leg bioelectrical impedance analysis (LBIA) with hydrostatic weighing (HW) in a group (n = 25) of NCAA Division III collegiate wrestlers. Body composition was assessed during the preseason wrestling weight certification program (WCP) using the NCAA approved methods (HW, 3-site skinfold [SF], and ADP) and LBIA, which is currently an unaccepted method of assessment. A urine specific gravity less than 1.020, measured by refractometry, was required before all testing. Each subject had all of the assessments performed on the same day. LBIA measurements (Athletic mode) were determined using a Tanita body fat analyzer (model TBF-300A). Hydrostatic weighing, corrected for residual lung volume, was used as the criterion measurement. The %BF data (mean +/- SD) were LBIA (12.3 +/- 4.6), ADP (13.8 +/- 6.3), SF (14.2 +/- 5.3), and HW (14.5 +/- 6.0). %BF estimated by LBIA was significantly (p < 0.01) smaller than HW and SF. There were no significant differences in body density or %BF estimated by ADP, SF, and HW. All methods showed significant correlations (r = 0.80-0.96; p < 0.01) with HW. The standard errors of estimate (SEE) for %BF were 1.68, 1.87, and 3.60%; pure errors (PE) were 1.88, 1.94, and 4.16% (ADP, SF, and LBIA, respectively). Bland-Atman plots for %BF demonstrated no systematic bias for ADP, SF, and LBIA when compared with HW. These preliminary findings support the use of ADP and SF for estimating %BF during the NCAA WCP in Division III wrestlers. LBIA, which consistently underestimated %BF, is not supported by these data as a valid assessment method for this athletic group.     

Validity of optical device lipometer and bioelectric impedance analysis for body fat assessment in men and women

The aims of this study were to validate different subcutaneous adipose tissue layers (SAT-layers) measured by lipometer for body fat percentage (BF%) assessment with dual-energy X-ray absorptiometry (DXA) and to compare the validity of lipometer and bioelectrical impedance analysis (BIA). The subjects were 21 male (18-60 years) and 19 female (23-54 years) healthy Estonian volunteers. SAT-layers were measured by lipometer using 15 standardized SAT-layers. Sum of arms, legs and trunk SAT-layers were calculated and compared with arms, legs and trunk fat percentage measured by DXA. BF% was calculated by BIA using the equations of Lukaski et al. and Chumlea et al. for both genders and the equations of Segal et al. for males and Van Loan and Mayclin for females. BF% measured by DXA was significantly higher than calculated by Lukaski et al. and Chumlea et al. in both genders. The correlation was highest between the BF% measured by DXA and using Segal et al. equation in males (r = 0.94) and Van Loan and Mayclin equation in females (r = 0.84). High relationship was observed between BF% measured by DXA and sum of 15 SAT-layers (r = 0.88 in males and r = 0.91 in females). Stepwise multiple regression analysis indicated that two selected SAT-layers explained 85.9% and 86.7% (R2 x 100) of the total variance in BF% measured by DXA in males and females, respectively: [BF% = 1.308 neck + 0.638 hip + 6.971 (males; SEE = 2.59) and BF% = 1.152 hip + 1.797 calf + 12.347 (females; SEE = 3.46)]. In conclusion, lipometer and BIA give a similar mean estimation of BF% when compared with DXA. However, there is a wide range of variance for the upper and lower limits of agreement between the methods, and the methods are not interchangeable. Lipometer seems to be superior to BIA.     

Evaluation of the BOD POD for estimating percent fat in female college athletes

The purpose of this investigation was to examine the accuracy of percent body fat (%BF) estimates obtained by air displacement plethysmography (ADP) using the BOD POD Body Composition System compared with hydrostatic weighing (HW) in a group of female college athletes (n = 80). In addition, %BF estimates by skinfold measures (SF) were also obtained for comparison. A lean subset (n = 39) of the sample was also examined. Mean %BF estimated for the entire sample by ADP (21.2 +/- 5.9%) was significantly greater than that determined by HW (19.4 +/- 6.4%) and SF (18.8 +/- 5.5%). Results from the lean subset also revealed that %BF determined by ADP (17.1 +/- 3.7%) was significantly higher than %BF estimates by HW (14.3 +/- 2.8%) and SF (15.2 +/- 3.2%). The regression equation for the entire sample (%BF HW = 0.937%BF ADP - 0.452, r(2) = 0.73, standard error of estimates (SEE) = 3.34) did not differ from the line of identity. In contrast, the line of identity differed significantly from the regression equation for the lean subset of female athletes (%BF HW = 0.48%BF ADP + 6.115, r(2) = 0.41, SEE = 2.18). The results of this investigation indicate that ADP significantly overestimated %BF by 8% in female athletes and by 16% for a leaner subset of the sample compared with HW. It appears that %BF estimates by SF may be more accurate than those obtained by ADP for female college athletes, regardless of body composition. Coaches and trainers evaluating body composition should consider the use of SF before ADP when measuring %BF in female college athletes. Sports scientists should continue to examine the possible gender and body composition bias for ADP.     

Body composition assessment in extreme obesity and after massive weight loss induced by gastric bypass surgery

Body composition methods were examined in 20 women [body mass index (BMI) 48.7 +/- 8.8 kg/m(2)] before and after weight loss [-44.8 +/- 14.6 (SD) kg] after gastric bypass (GBP) surgery. The reference method, a three-compartment (3C) model using body density by air displacement plethysmography and total body water (TBW) by H(2)18O dilution (3C-H(2)18O), showed a decrease in percent body fat (%BF) from 51.4 to 34.6%. Fat-free mass hydration was significantly higher than the reference value (0.738) in extreme obesity (0.756; P < 0.001) but not after weight reduction (0.747; P = 0.16). %BF by H(2)18O dilution and air displacement plethysmography differed significantly from %BF by 3C-H(2)18O in extreme obesity (P < 0.05) and 3C models using (2)H(2)O or bioelectrical impedance analysis (BIA) to determine TBW improved mean %BF estimates over most other methods at both time points. BIA results varied with the equation used, but BIA better predicted %BF than did BMI at both time points. All methods except BIA using the Segal equation were comparable to the reference method for determining changes over time. A simple 3C model utilizing air displacement plethysmography and BIA is useful for clinical evaluation in this population.     

Evaluation of the BOD POD for estimating percent body fat in collegiate track and field female athletes: a comparison of four methods

This investigation examined the accuracy of the BOD POD on a group of Division I collegiate track and field female athletes (N = 30). Hydrostatic weighing (HW) was used as the gold standard method. Body density (Db) values obtained from the BOD POD (Db BP) were compared with those determined by HW (Db HW). Both Db values were converted to percent body fat (%BF) using the Siri equation for comparison. Percent body fat values obtained from the BOD POD (BF BP) were also compared with those obtained from dual-energy X-ray absorptiometry (DXA, BF DXA) and skinfold (SF, BF SF). The validity of the BOD POD was assessed using repeated-measures analysis of variance (ANOVA), and the relationship between the methods was examined through Pearson correlation. Average Db BP was 0.00890 g x cm(-3) lower (p < 0.05) than Db HW, resulting in a significant overestimation of %BF (p < 0.05) by the BOD POD. Values for BFDXA and BFBP also differed significantly (p < 0.05). On the other hand, BFSF and BF BP were not significantly different. The correlation between percent body fat values obtained from HW (BFHW) and BF BP was good (r = 0.88, SEE = 2.30) as well as between BF SF and BF BP (r = 0.85, SEE = 2.05). Conversely, the correlation between BFDXA and BF BP was poor (r = 0.25, SEE = 5.73). The strong correlation between BF BP and BF HW presented here suggests that the BOD POD has the potential to be used as a body composition analysis tool for female athletes. The advantages of the BOD POD over HW encourage further investigation of this instrument. However, the fact that the BOD POD and SF results did not differ significantly might suggest that the SF could be used in its place until a better rate of accuracy for this instrument is established.     

Validity of leg-to-leg bioelectrical impedance measurement in highly active women

The aim of this study was to compare the validity of the leg-to-leg bioelectrical impedance analysis (BIA) method with that of anthropometry using hydrostatic weighing (HW) as the criterion test. A secondary objective was to cross-validate previously developed anthropometric regression equations as well as to develop a new regression equation formula based on the anthropometric data collected in this study. Three methods for assessing body composition (HW, BIA, and anthropometric) were applied to 60 women university athletes. The means and standard deviations of age, weight, height, and body mass index (BMI) of athletes were as follows: age, 20.70 +/- 1.43; weight, 56.19 +/- 7.83 kg; height, 163.33 +/- 6.11 cm; BMI, 21.01 +/- 2.63 kg x m(-2). Leg-to-leg BIA (11.82 +/- 2.39) has shown no statistical difference between percentage body fat determined by HW (11.63 +/- 2.42%) in highly active women (p > 0.05). This result suggests that the leg-to-leg BIA and HW methods were somewhat interchangeable in highly active women (R = 0.667; standard error of estimate [SEE] = 1.81). As a result of all cross-validation analyses, anthropometric and BIA plus anthropometric results have generally produced lower regression coefficients and higher SEEs for highly active women between the ages of 18 and 25 years. The regression coefficients (0.903, 0.926) and SEE (1.08, 0.96) for the new regression formulas developed from this study were better than the all the other formulas used in this study.     

Estimation of human body composition by electrical impedance methods: a comparative study

This study 1) further validated the relationship between total body electrical conductivity (TOBEC) and densitometrically determined lean body mass (LBMd) and 2) compared with existing body composition techniques (densitometry, total body water, total body potassium, and anthropometry) two new electrical methods for the estimation of LBM: TOBEC, a uniform current induction method, and bioelectrical impedance analysis (BIA), a localized current injection method. In a sample of 75 male and female subjects ranging from 4.9 to 54.9% body fat the correlation between LBMd and LBM predicted from TOBEC by use of a previously developed regression equation was extremely strong (r = 0.962), thus confirming the validity of the TOBEC method. LBM predicted from BIA by use of prediction equations provided with the instrument also correlated with LBMd (r = 0.912) but overestimated LBM compared with LBMd in obese subjects. However, no such systematic error was apparent when new prediction equations derived from this heterogeneous sample of subjects were applied. Thus the TOBEC and BIA methods, which are based on the differing electrical properties of lean tissue and fat and which are convenient, rapid, and safe, correlate well with more cumbersome human body composition techniques.     

Improved Prediction of Body Fat by Measuring Skinfold Thickness,Circumferences, and Bone Breadths

Objective: To develop improved predictive regression equations for body fat content derived from common anthropometric measurements. Research Methods and Procedures: 117 healthy German subjects, 46 men and 71 women, 26 to 67 years of age, from two different studies were assigned to a validation and a cross‐validation group. Common anthropometric measurements and body composition by DXA were obtained. Equations using anthropometric measurements predicting body fat mass (BFM) with DXA as a reference method were developed using regression models. Results: The final best predictive sex‐specific equations combining skinfold thicknesses (SF), circumferences, and bone breadth measurements were as follows: BFM_New (kg) for men = ?40.750 + [(0.397 × waist circumference) + [6.568 × (log triceps SF + log subscapular SF + log abdominal SF)]] and BFM_New (kg) for women = ?75.231 + [(0.512 × hip circumference) + [8.889 × (log chin SF + log triceps SF + log subscapular SF)] + (1.905 × knee breadth)]. The estimates of BFM from both validation and cross‐validation had an excellent correlation, showed excellent correspondence to the DXA estimates, and showed a negligible tendency to underestimate percent body fat in subjects with higher BFM compared with equations using a two‐compartment (Durnin and Womersley) or a four‐compartment (Peterson) model as the reference method. Discussion: Combining skinfold thicknesses with circumference and/or bone breadth measures provide a more precise prediction of percent body fat in comparison with established SF equations. Our equations are recommended for use in clinical or epidemiological settings in populations with similar ethnic background.     

The influence of posture change on measurements of relative body fat in the bioimpedance analysis method

The purpose of this study was to clarify the influence of posture change on relative body fat in the bioelectrical impedance analysis (BIA) method. The subjects were 30 Japanese healthy young adult males (age: 19.8 +/- 1.4 years, height: 172.3 +/- 5.8 cm, weight: 67.1 +/- 8.2 kg). We used devices with different body segment inductions, between the hand and foot (H-F BIA) and between hands (H-H BIA), and set four measurement conditions differing in posture (supine or sitting), during rest and measurement. The reliabilities of %BF in the H-H and H-F BIA methods were very high (r = 0.995, 0.966), and the relationship in %BF between the UW method and each BIA method was mid-range (r = 0.767, 0.709). Although there were no differences in %BF among different measurement postures in the H-F BIA method, %BF in the H-H BIA method increased significantly when the posture was changed just before measurement. This indicated that it is necessary to pay attention to the posture change just before measurement in the H-H BIA method.     

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.     

Cross-Validation of Fat-Free Mass Estimated From Body Density Against Bioelectrical Resistance: Effects of Obesity and Gender

GORAN, MICHAEL I AND M ABU KHALED. Cross-validation of fat-free mass estimated from body density against bioelectrical resistance: effects of obesity and gender. Obes Res. The major purpose of this study was to examine whether estimates of body composition from bioelectrical resistance were systematically biased by obesity and/or gender (using hydrodensitometry as a comparison method). We compared fat-free mass (FFM) by bioelectrical resistance (BR) using 5 equations (Lukaski, Kushner, Rising, Khaled, and Segal) to FFM by hydrodensitometry (HD) in 20 lean men, 30 lean women, 33 obese men and 22 obese women. None of the BR equations was successfully cross-validated against FFM by HD in all 4 sub-groups. The Lukaski equation significantly underestimated FFM in all 4 groups by 2.7 to 4.7 kg; the Kushner equation significantly underestimated FFM by 2.0 to 2.9 kg except in obese women; the Rising equation significantly overestimated FFM in obese women (5.3 kg) and men (2.9 kg); the Khaled equation successfully predicted FFM in all groups except obese men; and the Segal equation successfully predicted FFM in all groups except lean men. In some groups, a portion of the discrepancy could be explained by bias originating from body fat. Analysis of our data by forward regression analysis demonstrated that height²/resistance, body weight, gender and suprailiac skinfold thickness provide the most accurate estimates of FFM (R²=0.92; SEE = 3.58kg) that are free of bias originating from gender and body fat. We conclude that the estimation of fat-free mass by BR is significantly influenced by gender and obesity. An alternative equation is proposed for estimating fat-free mass based on measurement of height²/resistance, body weight, gender and suprailiac skinfold thickness.     

Percentage of total body fat as estimated by three automatic bioelectrical impedance analyzers

The present study aimed to compare the accuracy of estimating the percentage of total body fat (%TBF) among three bioelectrical impedance analysis (BIA) devices: a single-frequency BIA with four tactile electrodes (SF-BIA4), a single-frequency BIA with eight tactile electrodes (SF-BIA8) and a multi-frequency BIA with eight tactile electrodes (MF-BIA8). Dual-energy x-ray absorptiometry (DXA) and hydrostatic weighing (HW) were used as references for the measured values. Forty-five healthy college student volunteers (21 males: 172.9 +/- 5.5 cm and 65.8 +/- 9.1 kg and 24 females: 160.7 +/- 6.6 cm, 52.6 +/- 6.2 kg) were the subjects. Correlation coefficients between the BIA measurements and the references were calculated. The standard error of estimation (SEE) was calculated by regression analysis when estimating the reference measures (DXA and HW) from the predictor (SF-BIA4, SF-BIA8 and MF-BIA8). The differences in %TBF between the reference and the predictor, calculated by the reference minus the predictor, were plotted against the %TBF measured by the references. The MF-BIA 8 here showed the highest correspondence to the reference and the least estimation error compared with the other BIA methods. It is considered that there is a limit to directly estimate FFM from a regression equation using impedance, weight, height and age as independent variables, and that %TBF can be more accurately estimated by measuring segmental impedances using eight electrodes and multi-frequency electric currents and then estimating total body water from these impedances.     

Noninvasive estimation of body composition in small mammals: a comparison of conductive and morphometric techniques

Body fat stores may serve as an index of condition in mammals. Thus, techniques that measure fat content accurately are important for assessing the ecological correlates of condition in mammal populations. We compared the ability of two conductive techniques, bioelectrical impedance analysis (BIA) and total body electrical conductivity (TOBEC), to predict body composition with that of morphometric methods in three small mammal species: red squirrels (n=13), snowshoe hares (n=30), and yellow-bellied marmots (n=4). Animals were livetrapped in northern Idaho; BIA (all subjects) and TOBEC (squirrels only) measurements were taken following chemical immobilization in the field, and morphometric measurements were taken postmortem. Information provided by BIA and TOBEC failed to improve upon the predictive power of morphometric equations for total body water (TBW) and lean body mass (LBM) in squirrels and hares, which do not store substantial amounts of fat (<5% body mass comprised of fat). Although the same pattern held with respect to LBM in marmots, which accumulate substantial amounts of body fat (>10% body mass), a BIA-based model proved best at estimating TBW, suggesting that the usefulness of conductive techniques may be a function of fat deposition. However, regardless of the technique used to predict body composition, estimates of body fat furnished by our equations failed to approximate actual fat levels accurately in all three test species, probably because these techniques only provide indirect estimates of fat content. These results highlight the limitations inherent in contemporary methods of animal fat estimation and underscore the need for the development of direct and accurate measures of body fat in mammals.     

Prediction of Percentage Body Fat in Rural Thai Population Using Simple Anthropometric Measurements

Objective: To develop and validate sex‐specific equations for predicting percentage body fat (%BF) in rural Thai population, based on BMI and anthropometric measurements. Research Methods and Procedures: %BF (DXA; GE Lunar Corp., Madison, WI) was measured in 181 men and 255 women who were healthy and between 20 and 84 years old. Anthropometric measures such as weight (kilograms), height (centimeters), BMI (kilograms per meter squared), waist circumference (centimeters), hip circumference (centimeters), thickness at triceps skinfold (millimeters), biceps skinfold (millimeters), subscapular skinfold (millimeters), and suprailiac skinfold (millimeters) were also measured. The sample was randomly divided into a development group (98 men and 125 women) and a validation group (83 men and 130 women). Regression equations of %BF derived from the development group were then evaluated for accuracy in the validation group. Results: The equation for estimating %BF in men was: %BF(men) = 0.42 × subscapular skinfold + 0.62 × BMI ? 0.28 × biceps skinfold + 0.17 × waist circumference ? 18.47, and in women: %BF(women) = 0.42 × hip circumference + 0.17 × suprailiac skinfold + 0.46 × BMI ? 23.75. The coefficient of determination (R²) for both equations was 0.68. Without anthropometric variables, the predictive equation using BMI, age, and sex was: %BF = 1.65 × BMI + 0.06 × age ? 15.3 × sex ? 10.67 (where sex = 1 for men and sex = 0 for women), with R² = 0.83. When these equations were applied to the validation sample, the difference between measured and predicted %BF ranged between ±9%, and the positive predictive values were above 0.9. Discussion: These results suggest that simple, noninvasive, and inexpensive anthropometric variables may provide an accurate estimate of %BF and could potentially aid the diagnosis of obesity in rural Thais.     

Reliability of Multifrequency Bioelectrical Impedance Analysis to Quantify Body Composition in Patients After Musculoskeletal Trauma

BackgroundChanges in body composition, especially loss of lean mass, commonly occur in the orthopedic trauma population due to physical inactivity and inadequate nutrition. The purpose of this study was to assess inter-rater and intra-rater reliability of a portable bioelectrical impedance analysis (BIA) device to measure body composition in an orthopedic trauma population after operative fracture fixation. BIA uses a weak electric current to measure impedance (resistance) in the body and uses this to calculate the components of body composition using extensively studied formulas.MethodsTwenty subjects were enrolled, up to 72 hours after operative fixation of musculoskeletal injuries and underwent body composition measurements by two independent raters. One measurement was obtained by each rater at the time of enrollment and again between 1-4 hours after the initial measurement. Reliability was assessed using intraclass correlation coefficients (ICC) and minimum detectable change (MDC) values were calculated from these results.ResultsInter-rater reliability was excellent with ICC values for body fat mass (BFM), lean body mass (LBM), skeletal muscle mass (SMM), dry lean mass (DLM), and percent body fat (PBF) of 0.993, 0.984, 0.984, 0.979, and 0.986 respectively. Intra-rater reliability was also high for BFM, LBM, SMM, DLM, and PBF, at 0.994, 0.989, 0.990, 0.983, 0.987 (rater 1) and 0.994, 0.988, 0.989, 0.985, 0.989 (rater 2). MDC values were calculated to be 4.05 kg for BFM, 4.10 kg for LBM, 2.45 kg for SMM, 1.21 kg for DLM, and 4.83% for PBF.ConclusionPortable BIA devices are a versatile and attractive option that can reliably be used to assess body composition and changes in lean body mass in the orthopedic trauma population for both research and clinical endeavors. Level of Evidence: III     

No apparent progress in bioelectrical impedance accuracy: validation against metabolic risk and DXA

Bioelectrical impedance (BIA) is quick, easy, and safe when quantifying fat and lean tissue. New BIA models (Tanita BC-418 MA, abbreviated BIA(8)) can perform segmental body composition analysis, e.g., estimate %trunkal fatness (%TF). It is not known, however, whether new BIA models can detect metabolic risk factors (MRFs) better than older models (Tanita TBF-300, abbreviated BIA(4)). We therefore tested the correlation between MRF and percentage whole-body fat (%BF) from BIA(4) and BIA(8) and compared these with the correlation between MRF and dual-energy X-ray absorptiometry (DXA, used as gold standard), BMI and waist circumference (WC). The sample consisted of 136 abdominally obese (WC >or= 88 cm), middle-aged (30-60 years) women. MRF included fasting blood glucose and insulin; high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides; high sensitive C-reactive protein, plasminogen activator inhibitor-1 (PAI-1), and fibrinogen; and alanine transaminase (ALT) liver enzyme. We found that similar to DXA, but in contrast to BMI, neither %BF BIA(4) nor %BF BIA(8) correlated with blood lipids or ALT. In the segmental analysis of %TF, BIA(8) only correlated with inflammatory markers, but not insulin, blood lipids, or ALT liver enzyme (in contrast to WC and %TF DXA). %TF DXA was associated with homeostatic model assessment insulin resistance (HOMA-IR) independently of WC (P = 0.03), whereas %TF BIA(8) was not (P = 0.53). Receiver-operating characteristic (ROC) curves confirmed that %TF BIA(8) did not differ from chance in the detection of insulin resistance (P = 0.26). BIA estimates of fatness were, at best, weakly correlated with obesity-related risk factors in abdominally obese women, even the new eight-electrode model. Our data support the continued use of WC and BMI.