Reliability of upper and lower extremity anthropometric measurements and the effect on tissue mass predictions

Accurate modeling of soft tissue motion effects relative to bone during impact requires knowledge of the mass of soft and rigid tissues in living people. Holmes et al., [2005. Predicting in vivo soft tissue masses of the lower extremity using segment anthropometric measures and DXA. Journal of Applied Biomechanics, 21, 371–382] developed and validated regression equations to predict the individual tissue masses of lower extremity segments of young healthy adults, based on simple anthropometric measurements. However, the reliability of these measurements and the effect on predicted tissue mass estimates from the equations has yet to be determined. In the current study, two measurers were responsible for collecting two sets of unilateral measurements (25 male and 25 female subjects) for the right upper and lower extremities. These included 6 lengths, 6 circumferences, 8 breadths, and 4 skinfold thicknesses. Significant differences were found between measurers and between sexes, but these differences were relatively small in general (75–80% of between-measurer differences were <1 cm). Within-measurer measurement differences were smaller and more consistent than those between measurers in most cases. Good to excellent reliability was demonstrated for all measurement types, with intra-class correlation coefficients of 0.79, 0.86, 0.85 and 0.86 for lengths, circumferences, breadth and skinfolds, respectively. Predicted tissue mass magnitudes were moderately affected by the measurement differences. The maximum mean errors between measurers ranged from 3.2% to 24.2% for bone mineral content and fat mass, for the leg and foot, and the leg segments, respectively.     

Upper extremity soft and rigid tissue mass prediction using segment anthropometric measures and DXA

Regression equations for predicting bone mineral content (BMC), fat mass (FM), lean mass (LM), and wobbling mass (WM) of living people from simple anthropometric measures (segment lengths, circumferences, breadths, and skin folds) have been reported in the literature for the lower extremities, but are lacking for the upper extremities. Multiple linear stepwise regression was used to generate such equations for the arm, forearm, and forearm and hand segments of healthy university aged people (38 males, 38 females). Actual tissue masses were obtained from full body Dual-energy X-ray Absorptiometry (DXA) scans and were used to validate the developed equations with an independent sample of 24 participants (12 male, 12 female). Prediction equations exhibited very high adjusted R² values (range from 0.854 to 0.968), with more explained variance for LM and WM than for BMC and FM. Scatter plots of actual versus predicted tissue masses revealed a close relationship (R² range from 0.681 to 0.951). Relative errors between the predicted and actual tissue masses for the validation group ranged from ?2.2% to 15.5%, and the root-mean-squared error (RMS_error) ranged from 7.92 to 180.26 g, for BMC of the forearm and LM of the arm, respectively. These results suggest that accurate estimates of in-vivo tissue masses for the upper extremities can be predicted from simple anthropometric measurements in young adults. Access to tissue masses such as these will enable the development of more accurate models for predicting dynamic in-vivo response of the body to activities involving impact.     

Predicting in vivo soft tissue masses of the lower extremity using segment anthropometric measures and DXA

The purpose of this study was to derive and validate regression equations for the prediction of fat mass (FM), lean mass (LM), wobbling mass (WM), and bone mineral content (BMC) of the thigh, leg, and leg + foot segments of living people from easily measured segmental anthropometric measures. The segment masses of 68 university-age participants (26 M, 42 F) were obtained from full-body dual photon x-ray absorptiometry (DXA) scans, and were used as the criterion values against which predicted masses were compared. Comprehensive anthropometric measures (6 lengths, 6 circumferences, 8 breadths, 4 skinfolds) were taken bilaterally for the thigh and leg for each person. Stepwise multiple linear regression was used to derive a prediction equation for each mass type and segment. Prediction equations exhibited high adjusted R2 values in general (0.673 to 0.925), with higher correlations evident for the LM and WM equations than for FM and BMC. Predicted (equations) and measured (DXA) segment LM and WM were also found to be highly correlated (R2 = 0.85 to 0.96), and FM and BMC to a lesser extent (R2 = 0.49 to 0.78). Relative errors between predicted and measured masses ranged between 0.7% and -11.3% for all those in the validation sample (n = 16). These results on university-age men and women are encouraging and suggest that in vivo estimates of the soft tissue masses of the lower extremity can be made fairly accurately from simple segmental anthropometric measures.     

The measurement of body segment inertial parameters using dual energy X-ray absorptiometry

Accurate body segment parameter (BSP) information is required for dynamic analyses of motion and the current methods available for obtaining these BSPs have been criticized. The purpose of this study was to determine whether dual energy X-ray absorptiometry (DXA) could accurately measure the BSPs of scanned objects and thus be used as a tool for measuring the BSPs of human subjects. Whole body mass (WBM) of 11 males was measured from a DXA scan and the values were compared to criterion scale-measured values by calculating the mean percent error. Two objects (plastic cylinder, human cadaver leg) were also scanned and DXA measurements of mass, length, centre of mass location (CM) and moment of inertia about the centre of mass (I_CM) were made using custom software. Criterion BSP measurements were then made and compared to DXA BSP values by calculating the percent error. Criterion I_CM measurements of the two objects were made using a pendulum technique and a second criterion I_CM calculation was made for the cylinder using a geometric formula. A mean percent error of −1.05% ±1.32% was found for WBM measurements of the human subjects. Errors for the cylinder and cadaver leg were under 3.2% for all BSPs except for I_CM when DXA was compared to the pendulum method (14.3% and 8.2% for cylinder and leg, respectively). The errors between DXA and the pendulum method were attributed to uncertainty in the pendulum technique (J. Biomech. 2002, in Review). I_CM error of the cylinder when DXA was compared to the geometric calculation was 2.63%. This error, combined with the low errors for all other BSPs, indicated that DXA can be used as a simple and accurate means of obtaining direct BSP information on living humans.     

Profiles of musculoskeletal development in limbs of college Olympic weightlifters and wrestlers

To investigate the event-related profiles of musculoskeletal development in weight-categorized athletes, we measured the cross-sectional areas (CSA) of bone and muscle in the forearm, upper arm, lower leg and thigh, using a B-mode ultrasound apparatus, in college Olympic weightlifters (OWL, n = 19) and wrestlers (WR, n = 17) and untrained men (UM, n = 24), whose body masses were within the range from 55 kg to 78 kg. Both bone and muscle CSA at all sites were significantly correlated to the two-thirds power of fat-free mass (FFM(2/3)) with correlation coefficients of 0.430-40.741 (P < 0.05) and 0.608-0.718 (P < 0.05), respectively. Moreover, there were significant correlations between bone and muscle CSA at all sites (r = 0.664-0.829, P < 0.05). Even when bone and muscle CSA were expressed relative value to FFM(2/3), both OWL and WR showed significantly greater values than UM at all sites except for the lower leg. Furthermore, the comparison of the lean (bone + muscle) CSA ratio from site to site indicated a higher distribution of lean tissues in the upper extremities in OWL and WR compared to UM. While there was no significant difference between the two athlete groups in FFM(2/3), OWL showed significantly larger values than WR in the bone CSA of the upper arm and thigh and in the muscle CSA of the lower leg and thigh. However, lean CSA ratios of the upper extremities to the lower ones were significantly higher in WR than in OWL. Thus, the present results indicated that, compared to UM, OWL and WR had a greater lean tissue CSA in limbs, especially in the upper extremities, even when the difference in FFM was normalized. Moreover, the relative distribution of lean tissues in limbs differed between the two weight-categorized athletes in spite of there being no difference in FFM, which may be attributable to their own training regimens and/or competition style.     

Bioimpedance analysis: a useful technique for assessing appendicular lean soft tissue mass and distribution.

The present study was aimed at evaluating the feasibility and reliability of lower limb skeletal muscle (SM) mass estimates obtained by bioimpedance analysis (BIA). BIA estimates were compared with the estimates obtained by dual-energy X-ray absorptiometry (DXA). Ten normal weight and 10 obese women had BIA and DXA evaluations. Lower limb SM mass was then derived from DXA appendicular lean soft tissue estimates. Lower limb SM mass and SM distribution were also estimated from BIA modeling that fits measured resistance values along the leg. SM mass (mean +/- SD) was 5.8 +/- 1.0 kg by BIA vs. 5.8 +/- 1.1 kg by DXA in normal weight subjects and 7.2 +/- 1.4 kg by BIA vs. 7.2 +/- 1.2 kg by DXA in obese subjects. Mean +/- SD of the absolute value of the relative error was 7.0 +/- 3.4 and 5.9 +/- 3.4% in the two groups, respectively. Similar results were obtained by using five resistance values for the analysis. In conclusion, the proposed BIA model provides an adequate means of evaluating appendicular SM mass.     

The influence of soft tissue movement on ground reaction forces, joint torques and joint reaction forces in drop landings

The aim of this study was to determine the effects that soft tissue motion has on ground reaction forces, joint torques and joint reaction forces in drop landings. To this end a four body-segment wobbling mass model was developed to reproduce the vertical ground reaction force curve for the first 100 ms of landing. Particular attention was paid to the passive impact phase, while selecting most model parameters a priori, thus permitting examination of the rigid body assumption on system kinetics. A two-dimensional wobbling mass model was developed in DADS (version 9.00, CADSI) to simulate landing from a drop of 43 cm. Subject-specific inertia parameters were calculated for both the rigid links and the wobbling masses. The magnitude and frequency response of the soft tissue of the subject to impulsive loading was measured and used as a criterion for assessing the wobbling mass motion. The model successfully reproduced the vertical ground reaction force for the first 100 ms of the landing with a peak vertical ground reaction force error of 1.2% and root mean square errors of 5% for the first 15 ms and 12% for the first 40 ms. The resultant joint forces and torques were lower for the wobbling mass model compared with a rigid body model, up to nearly 50% lower, indicating the important contribution of the wobbling masses on reducing system loading.     

Sex and limb-specific ischemic reperfusion and vascular reactivity

With little known regarding sex and limb heterogeneity, we investigated vascular reactivity and ischemic reperfusion (IR) in the upper and lower extremities of 15 healthy men (26 +/- 2 yr) and women (23 +/- 1 yr). Doppler ultrasound was used to evaluate IR and flow-mediated dilation (FMD) after suprasystolic cuff occlusion in both the arm [brachial artery (BA)] and the leg [popliteal artery (PA)]. Cumulative IR [area under the curve (AUC)], normalized for muscle mass, revealed no sex-related differences in either limb (forearm: men 38 +/- 3 and women 44 +/- 4 ml/100 g; lower leg: men 12 +/- 2 and women 14 +/- 2 ml/100 g), while both groups revealed a greater IR per unit of arm muscle mass (AUC) compared with the lower leg (P < 0.05). The BA and PA were smaller in women (BA 0.31 +/- 0.1, PA 0.47 +/- 0.1 cm) than in men (BA 0.41 +/- 0.1, PA 0.6 +/- 0.2 cm). Absolute FMD/shear rate revealed attenuated vascular function in the PA of the women [women 3.3 +/- 0.6, men 5.0 +/- 0.8 (all x10(-6)) cm/s(-1).s] and no sex difference in the BA [women 1.2 +/- 0.2, men 1.6 +/- 0.1 (all x10(-6)) cm/s(-1).s]. In both sexes the PA demonstrated greater vascular reactivity than the BA. Thus vascular reactivity in healthy young people is greater in the legs, regardless of sex, and women have vascular function similar to men in the upper extremities but appear to have poorer vascular function normalized for shear rate in the lower extremities.     

Reference Values for Body Composition and Anthropometric Measurements in Athletes

Background

Despite the importance of body composition in athletes, reference sex- and sport-specific body composition data are lacking. We aim to develop reference values for body composition and anthropometric measurements in athletes.

Methods

Body weight and height were measured in 898 athletes (264 female, 634 male), anthropometric variables were assessed in 798 athletes (240 female and 558 male), and in 481 athletes (142 female and 339 male) with dual-energy X-ray absorptiometry (DXA). A total of 21 different sports were represented. Reference percentiles (5^th, 25^th, 50^th, 75^th, and 95^th) were calculated for each measured value, stratified by sex and sport. Because sample sizes within a sport were often very low for some outcomes, the percentiles were estimated using a parametric, empirical Bayesian framework that allowed sharing information across sports.

Results

We derived sex- and sport-specific reference percentiles for the following DXA outcomes: total (whole body scan) and regional (subtotal, trunk, and appendicular) bone mineral content, bone mineral density, absolute and percentage fat mass, fat-free mass, and lean soft tissue. Additionally, we derived reference percentiles for height-normalized indexes by dividing fat mass, fat-free mass, and appendicular lean soft tissue by height squared. We also derived sex- and sport-specific reference percentiles for the following anthropometry outcomes: weight, height, body mass index, sum of skinfold thicknesses (7 skinfolds, appendicular skinfolds, trunk skinfolds, arm skinfolds, and leg skinfolds), circumferences (hip, arm, midthigh, calf, and abdominal circumferences), and muscle circumferences (arm, thigh, and calf muscle circumferences).

Conclusions

These reference percentiles will be a helpful tool for sports professionals, in both clinical and field settings, for body composition assessment in athletes.     

Mutual influences of upper and lower extremities during cyclic movements

The possibility for the activation of muscles in a passive arm during its cyclic movements imposed by active movements of the contralateral arm or by an experimenter and the effect that the movements of lower extremities have on the activity of the arm muscles have been studied. In addition, the activity of the leg muscles was studied as dependent on the motor task performed by the arms. Ten healthy subjects performed antiphase arm movements with and without stepping-like movements of both legs in the supine position. The experiment was performed under three conditions for the arm movements: (1) both arms performed active movements; (2) one arm performed active movements, and the contralateral arm, being entirely passive, was forced to participate in movements; (3) the movement of the passive arm was caused by an experimenter. Under condition (2), additional loadings of 30 and 60 N were applied to the active arm. Under all conditions, the arm movements were performed with and without leg movements. The possibility for the activation of muscles in the arm performing passive movements has been demonstrated. To a large extent, this is possible due to an increase in the afferent inflow from the muscles of the contralateral arm. The electrical activity was modulated during cyclic arm movements and depended on the level of loading of the active arm. During the combined active movements of the arms and legs, the reduction in the activity of the flexor muscles of the shoulder and forearm was observed. In the case of passive stepping-like movements, the concomitant arm movements increased the magnitude of electromyographic bursts in most of the examined leg muscles. During active leg movements, a similar increase in electromyographic bursts was observed only in the m. biceps femoris (BF) and the anterior tibial muscle. An increase in the loading of one arm caused a significant increase in the EMG activity in most examined muscles of the legs. The data obtained provide additional proof for the existence of a functionally significant neuronal interaction between the arms, as well as between the upper and lower extremities, which is probably due to intraspinal neuronal connections.     

Gender differences in regional body composition and somatotrophic influences of IGF-I and leptin.

This study evaluated the arm, trunk, and leg for fat mass, lean soft tissue mass, and bone mineral content (BMC) assessed via dual-energy X-ray absorptiometry in a group of age-matched (approximately 29 yr) men (n = 57) and women (n = 63) and determined their relationship to insulin-like growth factor I (IGF-I) and leptin. After analysis of covariance adjustment to control for differences in body mass between genders, the differences that persisted (P < or = 0.05) were for lean soft tissue mass of the arm (men: 7.1 kg vs. women: 6.4 kg) and fat mass of the leg (men: 5.3 kg vs. women: 6.8 kg). Men and women had similar (P > or = 0.05) values for fat mass of the arms and trunk and lean soft tissue mass of the legs and trunk. Serum IGF-I and insulin-like growth factor binding protein-3 correlated (P < or = 0.05) with all measures of BMC (r values ranged from 0.31 to 0.39) and some measures of lean soft tissue mass for women (r = 0.30) but not men. Leptin correlated (P < or = 0.05) similarly for measures of fat mass for both genders (r values ranging from 0.74 to 0.85) and for lean soft tissue mass of the trunk (r = 0.40) and total body (r = 0.32) for men and for the arms in women (r = 0.56). These data demonstrate that 1) the main phenotypic gender differences in body composition are that men have more of their muscle mass in their arms and women have more of their fat mass in their legs and 2) gender differences exist in the relationship between somatotrophic hormones and lean soft tissue mass.     

Dual X-ray absorptiometry model for characterizing water in the human forearm using multiple frequency bioimpedance analysis

The purpose of this study was to develop a method for measuring intracellular (ICW) and extracellular water (ECW) in the human forearm using multiple frequency bioimpedance analysis (MFBIA). The approach was (i) to measure whole-body and forearm fat-free mass using dual X-ray absorptiometry (DXA); (ii) to use these measurements to estimate the fat-free mass (FFM) resistivity in both the forearm and in the whole body; and (iii) to use the ratio of these FFM resistivities to estimate the resistivity in the ICW and ECW compartments of the forearm. To first demonstrate the accuracy of the DXA software in differentiating lean body mass from fat and bone within a volume of tissue, ex-vivo bovine muscle tissue samples (n = 3) were used to approximate the physical properties of the human forearm. It was found that although the human whole-body software overestimates FFM, it was slightly underestimated by the small animal software. Using this technique, DXA measures of FFM were obtained from human volunteers (n = 11; age = 20 +/- 5 years; height = 170 +/- 12 cm; mass = 64 +/- 16 kg). These measures were used in conjunction with MFBIA measures of impedance of the whole body and of the forearm to determine the resistivities of the ICW and ECW compartments of the forearm, namely 375.8 +/- 25.2 ohms cm and 55.6 +/- 3.7 ohms cm, respectively. These were used in MFBIA equations to calculate the ICW, ECW, and total arm water (TAW) volumes of the human forearm. The calculated TAW and the ECW (+/- SD) volume fraction (667.29 +/- 200.15 mL and 0.169 +/- 0.039 mL, respectively) were in agreement with literature values. MFBIA results were compared with those obtained using nuclear magnetic resonance relaxometry (NMRR). MFBIA was performed on 15 subjects before and after an intense maximal handgrip exercise to estimate changes in water volume in muscle. Following exercise, the total and intracellular water of the forearm increased on average by 8% +/- 3% and 10% +/- 4% (mean +/- SD), respectively. In 5 healthy volunteers, MFBIA and NMRR were performed before and after a similar exercise of the forearm muscle. The changes with exercise of intracellular and total arm water volumes as measured by MFBIA were estimated. The percent increases in total water were found to be 9.4% +/- 4.2% and 9.4% +/- 2.6% and in intracellular water were found to be 10.6% +/- 4.6% and 12.0% +/- 2.8% (mean +/- SD) for NMRR and MFBIA, respectively. The results show that the exercise-induced changes in ICW and TAW determined with the MFBIA model are consistent with those observed with NMRR and radiotracer literature.     

Comparison of gross body fat‐water magnetic resonance imaging at 3 Tesla to dual‐energy X‐ray absorptiometry in obese women

Objective:

Improved understanding of how depot‐specific adipose tissue mass predisposes to obesity‐related comorbidities could yield new insights into the pathogenesis and treatment of obesity as well as metabolic benefits of weight loss. We hypothesized that three‐dimensional (3D) contiguous “fat‐water” MR imaging (FWMRI) covering the majority of a whole‐body field of view (FOV) acquired at 3 Tesla (3T) and coupled with automated segmentation and quantification of amount, type, and distribution of adipose and lean soft tissue would show great promise in body composition methodology.

Design and Methods:

Precision of adipose and lean soft tissue measurements in body and trunk regions were assessed for 3T FWMRI and compared to dual‐energy X‐ray absorptiometry (DXA). Anthropometric, FWMRI, and DXA measurements were obtained in 12 women with BMI 30‐39.9 kg/m².

Results:

Test–retest results found coefficients of variation (CV) for FWMRI that were all under 3%: gross body adipose tissue (GBAT) 0.80%, total trunk adipose tissue (TTAT) 2.08%, visceral adipose tissue (VAT) 2.62%, subcutaneous adipose tissue (SAT) 2.11%, gross body lean soft tissue (GBLST) 0.60%, and total trunk lean soft tissue (TTLST) 2.43%. Concordance correlation coefficients between FWMRI and DXA were 0.978, 0.802, 0.629, and 0.400 for GBAT, TTAT, GBLST, and TTLST, respectively.

Conclusions:

While Bland–Altman plots demonstrated agreement between FWMRI and DXA for GBAT and TTAT, a negative bias existed for GBLST and TTLST measurements. Differences may be explained by the FWMRI FOV length and potential for DXA to overestimate lean soft tissue. While more development is necessary, the described 3T FWMRI method combined with fully‐automated segmentation is fast (<30‐min total scan and post‐processing time), noninvasive, repeatable, and cost‐effective.     

Non-invasive measure of body composition of snakes using dual-energy X-ray absorptiometry

Non-invasive techniques to measure body composition are critical for longitudinal studies of energetics and life histories and for investigating the link between body condition and physiology. Previous attempts to determine, non-invasively, the body composition of snakes have proven problematic. Therefore, we explored whether dual-energy X-ray absorptiometry (DXA) could be used to determine the body composition of snakes. We analyzed 20 adult diamondback water snakes (Nerodia rhombifer) with a DXA instrument and subsequently quantified their body composition by gravimetric and chemical extraction methods. Body composition components scaled with body mass with mass exponents between 0.88 and 1.53. DXA values for lean tissue mass, fat mass and total-body bone mineral mass were significantly correlated with observed masses of lean tissue, fat and ash from chemical analysis. Using regression models incorporating DXA values we predicted the fat-free tissue mass, lean tissue mass, fat mass, ash mass and total body water content for this sample of water snakes. A cross-validation procedure demonstrated that these models estimated fat-free tissue mass, lean tissue mass, fat mass, ash mass and total-body water content with respective errors of 2.2%, 2.3%, 16.0%, 6.6% and 3.5%. Compared to other non-invasive techniques, include body condition indices, total body electrical conductivity (TOBEC) and cyclopropane absorption, DXA can more easily and accurately be used to determine the body composition of snakes.     

Lower limb skeletal muscle mass: development of dual-energy X-ray absorptiometry prediction model.

Although magnetic resonance imaging (MRI) can accurately measure lower limb skeletal muscle (SM) mass, this method is complex and costly. A potential practical alternative is to estimate lower limb SM with dual-energy X-ray absorptiometry (DXA). The aim of the present study was to develop and validate DXA-SM prediction equations. Identical landmarks (i.e., inferior border of the ischial tuberosity) were selected for separating lower limb from trunk. Lower limb SM was measured by MRI, and lower limb fat-free soft tissue was measured by DXA. A total of 207 adults (104 men and 103 women) were evaluated [age 43 +/- 16 (SD) yr, body mass index (BMI) 24.6 +/- 3.7 kg/m(2)]. Strong correlations were observed between lower limb SM and lower limb fat-free soft tissue (R(2) = 0.89, P < 0.001); age and BMI were small but significant SM predictor variables. In the cross-validation sample, the differences between MRI-measured and DXA-predicted SM mass were small (-0.006 +/- 1.07 and -0.016 +/- 1.05 kg) for two different proposed prediction equations, one with fat-free soft tissue and the other with added age and BMI as predictor variables. DXA-measured lower limb fat-free soft tissue, along with other easily acquired measures, can be used to reliably predict lower limb skeletal muscle mass.     

Segmentation of multi-isotope imaging mass spectrometry data for semi-automatic detection of regions of interest

Multi-isotope imaging mass spectrometry (MIMS) associates secondary ion mass spectrometry (SIMS) with detection of several atomic masses, the use of stable isotopes as labels, and affiliated quantitative image-analysis software. By associating image and measure, MIMS allows one to obtain quantitative information about biological processes in sub-cellular domains. MIMS can be applied to a wide range of biomedical problems, in particular metabolism and cell fate [1], [2], [3]. In order to obtain morphologically pertinent data from MIMS images, we have to define regions of interest (ROIs). ROIs are drawn by hand, a tedious and time-consuming process. We have developed and successfully applied a support vector machine (SVM) for segmentation of MIMS images that allows fast, semi-automatic boundary detection of regions of interests. Using the SVM, high-quality ROIs (as compared to an expert's manual delineation) were obtained for 2 types of images derived from unrelated data sets. This automation simplifies, accelerates and improves the post-processing analysis of MIMS images. This approach has been integrated into "Open MIMS," an ImageJ-plugin for comprehensive analysis of MIMS images that is available online at http://www.nrims.hms.harvard.edu/NRIMS_ImageJ.php.     

Validity and reliability of dual-energy X-ray absorptiometry for the assessment of abdominal adiposity.

A number of methods exist for the estimation of abdominal obesity, ranging from waist-to-hip ratio to computed tomography (CT). Although dual-energy X-ray absorptiometry (DXA) was originally used to measure bone density and total body composition, recent improvements in software allow it to determine abdominal fat mass. Sixty-five men and women aged 18-72 yr participated in a series of studies to examine the validity and reliability of the DXA to accurately measure abdominal fat. Total body fat and abdominal regional fat were measured by DXA using a Lunar DPX-IQ. Multislice CT scans were performed between L1 and L4 vertebral bodies (region of interest) using a Picker PQ5000 CT scanner, and volumetric analyses were carried out on a Voxel Q workstation. Both abdominal total tissue mass (P = 0.02) and abdominal fat mass (P < 0.0001) in the L1-L4 region of interest were significantly lower as measured by DXA compared with multislice CT. However, Bland-Altman analysis demonstrated good concordance between DXA and CT for abdominal total tissue mass (i.e., limits of agreement = -1.56-2.54 kg) and fat mass (i.e., limits of agreement = -0.40-1.94 kg). DXA also showed excellent reliability among three different operators to determine total, fat, and lean body mass in the L1-L4 region of interest (intraclass correlations, R = 0.94, 0.97, and 0.89, respectively). In conclusion, the DXA L1-L4 region of interest compared with CT proved to be both reliable and accurate method to determine abdominal obesity.     

Dual-energy X-ray absorptiometry: analysis of pediatric fat estimate errors due to tissue hydration effects.

Dual-energy X-ray absorptiometry (DXA) percent (%) fat estimates may be inaccurate in young children, who typically have high tissue hydration levels. This study was designed to provide a comprehensive analysis of pediatric tissue hydration effects on DXA %fat estimates. Phase 1 was experimental and included three in vitro studies to establish the physical basis of DXA %fat-estimation models. Phase 2 extended phase 1 models and consisted of theoretical calculations to estimate the %fat errors emanating from previously reported pediatric hydration effects. Phase 1 experiments supported the two-compartment DXA soft tissue model and established that pixel ratio of low to high energy (R values) are a predictable function of tissue elemental content. In phase 2, modeling of reference body composition values from birth to age 120 mo revealed that %fat errors will arise if a "constant" adult lean soft tissue R value is applied to the pediatric population; the maximum %fat error, approximately 0.8%, would be present at birth. High tissue hydration, as observed in infants and young children, leads to errors in DXA %fat estimates. The magnitude of these errors based on theoretical calculations is small and may not be of clinical or research significance.