The Intra‐ and Inter‐instrument Reliability of DXA Based on Ex Vivo Soft Tissue Measurements

Objective: Comparison of ex‐vivo soft tissue measurements using the GE/Lunar pencil (DPX‐L; GE/Lunar Co., Madison, WI) and fan beam (Prodigy dual‐energy X‐ray absorptiometers (DXA) GE/Lunar Co.). Research Methods and Procedures: Intra‐instrument reliability was assessed by repeatedly scanning soft tissue phantoms for lean tissue (water) and fat tissue (methanol) using one DPX‐L and two identical Prodigy DXAs at fast, medium, and slow scan modes. For each machine, 10 scans of each phantom were performed at each scan speed. The number of scans per instrument totaled 60. Data were analyzed using ANOVA to ascertain whether scan speed affected the intra‐instrument reliability and to test whether soft tissue measurements differed among instruments. Percentage fat (phantom density) was the outcome variable. Results: Intra‐instrument reliability, expressed as coefficient of variation, ranged between 0.7% and 5.2% for the DPX‐L and 0.4% and 4.5% for the Prodigy, with the lowest coefficients of variation observed when scanning the fat tissue phantom. Scan speed also affected the intra‐instrument reliability (p < 0.01). Furthermore, differences in the measurement of percentage body fat for both the lean and fat tissue phantoms were observed among all three absorptiometers (all p < 0.01). After adjusting for scan speed, differences persisted for all three instruments. Discussion: Intra‐ and inter‐instrument reliability of DXA machines, even those from the same manufacturer, remains unpredictable. Thus, when measuring body composition using DXA, it is important to consider that even in the absence of measurement bias, the use of different DXA machines, particularly when using a variety of speed settings, will increase the residual error around the true value.     

Regional Body Composition: Cross‐calibration of DXA Scanners—QDR4500W and Discovery Wi

Differences exist in body composition assessed by dual‐energy X‐ray absorptiometers (DXAs) between devices produced by different manufacturers and different models from the same manufacturer. Cross‐calibration is needed to allow body composition results to be compared in multicenter trials or when scanners are replaced. The aim was to determine reproducibility and extent of agreement between two fan‐beam DXA scanners (QDR4500W, Discovery Wi) for body composition of regional sites. The sample was: 39 women 50.6 ± 9.6 years old with BMI 26.8 ± 5.5 kg/m², body fat 33 ± 7%. Four whole body scans (two on each device) were performed over 3 weeks. Major variables were fat mass, nonosseous lean mass, and bone mineral content (BMC) for the truncal and appendicular regions. Extent of agreement was assessed using Bland and Altman plots. Both devices demonstrated good precision with mean test–retest differences close to zero for fat mass, nonosseous lean mass, and BMC of the truncal and appendicular regions. Evaluation of interdevice agreement revealed significant differences for truncal and appendicular BMC, nonosseous lean mass, and fat mass. The greatest interdevice difference was for truncal fat mass (0.69 ± 0.60 kg). Differences in truncal and appendicular fat mass increased in magnitude at higher mean values. Furthermore, differences in truncal and appendicular fat mass were strongly related to BMI (R = ?0.61, R = ?0.55, respectively). In conclusion, in vivo cross‐calibration is important to ensure comparability of regional body composition data between scanners, especially for truncal fat mass and for subjects with higher BMI.     

Comparison of Two Software Versions for Assessment of Body‐Composition Analysis by DXA

Objective: To compare two software versions provided by Lunar Co. for assessment of body composition analysis by DXA. Research Methods and Procedures: Soft‐tissue phantoms for lean tissue (water) and fat tissue (methanol) were repeatedly scanned using DXA machines (DPX‐L; Lunar Co., Madison, WI) and analyzed using software version 1.33 and the updated year 2000‐compatible version 1.35. For the intersoftware comparison, the phantoms were scanned 10 times (each scan was analyzed once) with both software versions using all three scanning modes (slow, medium, and fast) for a total of 60 scans and analyses. For the intermachine comparison, the same phantoms were scanned three times (each scan was analyzed once) with a second machine from the same manufacturer using all three scanning modes and version 1.35 only. Percentage of fat was the variable of interest. Results: For version 1.33, fat was 9.9 ± 0.4%, 10.0 ± 0.5%, and 11.0 ± 0.5% (mean ± SD) for the lean‐tissue phantom and 50.8 ± 0.3%, 50.9 ± 0.5%, and 51.1 ± 0.6% for the fat‐tissue phantom using the slow, medium, and fast scanning modes, respectively. For version 1.35, the respective fat values were 9.8 ± 0.7%, 9.9 ± 0.4%, and 10.3 ± 0.7%, and 50.6 ± 0.5%, 50.9 ± 0.6%, and 50.8 ± 0.8%, respectively. For the lean‐tissue phantom, the estimation of percentage of fat was significantly (p < 0.05) affected by scanning mode but not by software version. For the fat‐tissue phantom, the estimation of percentage of fat was not affected by either scanning mode or software version. The use of version 1.35 did not effect intermachine variability. Discussion: Versions 1.33 and 1.35 of the Lunar body composition software appear to be comparable. Soft‐tissue phantoms, such as the ones described in this paper, may be useful in monitoring the reproducibility of body composition analyses within and between DXA machines, particularly in longitudinal studies.     

Comparison of Hologic QDR‐1000/W and 4500W DXA Scanners in 13‐ to 18‐Year Olds

Objective: Body composition measurements made using Hologic QDR‐1000/W pencil‐beam and QDR‐4500W fan‐beam scanners (Bedford, MA) were compared in a sample of 13‐ to 18‐year‐old white and black youth (n = 219). Research Methods and Procedures: Total fat (FAT), fat‐free soft tissue (FFST), bone mineral content (BMC), bone mineral density (BMD), and percent body fat (%BF) were compared between repeated measurements using the QDR‐4500 and between the two scanners using mixed model ANOVA. Intraclass correlation coefficients and Bland‐Altman limits of agreement were used to evaluate inter‐ and intrascanner reliability. Results: Intraclass correlation coefficients for repeated measurements using the QDR‐4500 ranged from 0.997 to 0.999 for FAT, %BF, FFST, and BMC and 0.987 for BMD. Mean measurements made using the two scanners differed significantly for FAT, %BF, BMC, and BMD (p < 0.0001), and scan by sex interactions were significant (all p < 0.0005). There were no significant differences in mean measurements between repeat scans using the QDR‐4500 (all p > 0.19). Limits of agreement for measurements of FAT, FFST, and %BF made using the two scanners were approximately three times as wide as those for two measurements using the QDR‐4500. For lower values of FAT and %BF, the QDR‐4500 gave higher measurements than the QDR‐1000, whereas at higher values, this relationship was reversed. The QDR‐1000 tended to give higher BMC measurements, with larger differences for higher values. Discussion: Using different models of DXA scanners within a study may reduce precision of body composition measurement. This issue needs to be considered in the design of longitudinal studies.     

Body Composition Measured by Dual‐energy X‐ray Absorptiometry Half‐body Scans in Obese Adults

Dual‐energy X‐ray absorptiometry (DXA) has become a common measurement of human body composition. However, obese subjects have been understudied largely due to weight and scan area restrictions. Newer DXA instruments allow for heavier subjects to be supported by the DXA scanner, but the imaging area is still smaller than the body size of some obese subjects. In this study, we determined the validity of an automated half‐scan methodology by comparing to the standard whole‐body scans in a cohort of obese volunteers. Fifty‐two subjects whose BMI >30 kg/m² completed whole‐body iDXA (GE Lunar) scans. The resulting scans were analyzed in three ways: the standard whole‐body scan, total body estimated from the left side, and from the right side. Fat mass, nonbone lean mass, bone mineral content (BMC), and percent fat derived from each half scan were compared to the whole‐body scans. Total fat mass, nonbone lean mass, or percent fat was comparable for the whole‐body scans, left, and right side scans (>97% within individuals and >99.9% for the group). The BMC estimate using the right side scan was slightly but statistically higher than the whole‐body BMC (～30 g or 1%, P < 0.001), while the left side scan BMC estimate was lower than the whole‐body BMC by the same magnitude. No significant magnitude bias was found for any of the composition variables. We conclude that the new iDXA half‐body analysis in obese subjects appears to be closely comparable to whole‐body analysis for fat mass, nonbone lean mass, and percent fat.     

Assessing body composition with DXA and bioimpedance: effects of obesity, physical activity, and age

Objective: This study evaluated to what extent dual‐energy X‐ray absorptiometry (DXA) and two types of bioimpedance analysis (BIA) yield similar results for body fat mass (FM) in men and women with different levels of obesity and physical activity (PA). Methods and Procedures: The study population consisted of 37–81‐year‐old Finnish people (82 men and 86 women). FM% was estimated using DXA (GE Lunar Prodigy) and two BIA devices (InBody (720) and Tanita BC 418 MA). Subjects were divided into normal, overweight, and obese groups on the basis of clinical cutoff points of BMI, and into low PA (LPA) and high PA (HPA) groups. Agreement between the devices was calculated by using the Bland–Altman analysis. Results: Compared to DXA, both BIA devices provided on average 2–6% lower values for FM% in normal BMI men, in women in all BMI categories, and in both genders in both HPA and LPA groups. In obese men, the differences were smaller. The two BIA devices provided similar means for groups. Differences between the two BIA devices with increasing FM% were a result of the InBody (720) not including age in their algorithm for estimating body composition. Discussion: BIA methods provided systematically lower values for FM than DXA. However, the differences depend on gender and body weight status pointing out the importance of considering these when identifying people with excess FM.     

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.     

New percentage body fat prediction equations for Japanese females

Anthropometry is a simple and cost-efficient method for the assessment of body composition. However prediction equations to estimate body composition using anthropometry should be 'population-specific'. Most popular body composition prediction equations for Japanese females were proposed more than 40 years ago and there is some concern regarding their usefulness in Japanese females living today. The aim of this study was to compare percentage body fat (%BF) estimated from anthropometry and dual energy x-ray absorptiometry (DXA) to examine the applicability of commonly used prediction equations in young Japanese females. Body composition of 139 Japanese females aged between 18 and 27 years of age (BMI range: 15.1-29.1 kg/m(2)) was measured using whole-body DXA (Lunar DPX-LIQ) scans. From anthropometric measurements %BF was estimated using four equations developed from Japanese females. The results showed that the traditionally employed prediction equations for anthropometry significantly (p<0.01) underestimate %BF of young Japanese females and therefore are not valid for the precise estimation of body composition. New %BF prediction equations were proposed from the DXA and anthropometry results. Application of the proposed equations may assist in more accurate assessment of body fatness in Japanese females living today.     

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.     

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.     

Accuracy and precision of dual-energy X-ray absorptiometry for body composition measurements in rhesus monkeys

Accuracy of body composition measurements by dual-energy X-ray absorptiometry (DXA) was compared with direct chemical analysis in 10 adult rhesus monkeys. DXA was highly correlated (r-values > 0.95) with direct analyses of body fat mass (FM), lean mass (LM) and lumbar spine bone mineral content (BMC). DXA measurements of total body BMC were not as strongly correlated (r-value = 0.58) with total carcass ash content. DXA measurements of body FM, LM and lumbar spine BMC were not different from data obtained by direct analyses (P-values > 0.30). In contrast, DXA determinations of total BMC (TBMC) averaged 15%, less than total carcass ash measurements (P = 0.002). In conclusion, this study confirms the accurate measurement of fat and lean tissue mass by DXA in rhesus monkeys. DXA also accurately measured lumbar spine BMC but underestimated total body BMC as compared with carcass ash determinations.     

Accuracy of predicting chemical body composition of growing pigs using dual-energy X-ray absorptiometry

Studies in animal science assessing nutrient and energy efficiency or determining nutrient requirements benefit from gathering exact measurements of body composition or body nutrient contents. Those are acquired by standardized dissection or by grinding the body followed by wet chemical analysis, respectively. The two methods do not result in the same type of information, but both are destructive. Harnessing human medical imaging techniques for animal science can enable repeated measurements of individuals over time and reduce the number of individuals required for research. Among imaging techniques, dual-energy X-ray absorptiometry (DXA) is particularly promising. However, the measurements obtained with DXA do not perfectly match dissections or chemical analyses, requiring the adjustment of the DXA via calibration equations. Several calibration regressions have been published, but comparative studies of those regression equations and whether they are applicable to different data sets are pending. Thus, it is currently not clear whether existing regression equations can be directly used to convert DXA measurements into chemical values or whether each individual DXA device will require its own calibration. Our study builds prediction equations that relate body composition to the content of single nutrients in growing entire male pigs (BW range 20–100 kg) as determined by both DXA and chemical analyses, with R² ranging between 0.89 for ash and 0.99 for water and CP. Moreover, we show that the chemical composition of the empty body can be satisfactorily determined by DXA scans of carcasses, with the prediction error ranging between 4.3% for CP and 12.6% for ash. Finally, we compare existing prediction equations for pigs of a similar range of BWs with the equations derived from our DXA measurements and evaluate their fit with our chemical analysis data. We found that existing equations for absolute contents that were built using the same DXA beam technology predicted our data more precisely than equations based on different technologies and percentages of fat and lean mass. This indicates that the creation of generic regression equations that yield reliable estimates of body composition in pigs of different growth stages, sexes and genetic breeds could be achievable in the near future. DXA may be a promising tool for high-throughput phenotyping for genetic studies, because it efficiently measures body composition in a large number and wide array of animals.     

Comparison of DXA and CT in the Assessment of Body Composition in Premenopausal Women With Obesity and Anorexia Nervosa

Accurate methods for assessing body composition in subjects with obesity and anorexia nervosa (AN) are important for determination of metabolic and cardiovascular risk factors and to monitor therapeutic interventions. The purpose of our study was to assess the accuracy of dual‐energy X‐ray absorptiometry (DXA) for measuring abdominal and thigh fat, and thigh muscle mass in premenopausal women with obesity, AN, and normal weight compared to computed tomography (CT). In addition, we wanted to assess the impact of hydration on DXA‐derived measures of body composition by using bioelectrical impedance analysis (BIA). We studied a total of 91 premenopausal women (34 obese, 39 with AN, and 18 lean controls). Our results demonstrate strong correlations between DXA‐ and CT‐derived body composition measurements in AN, obese, and lean controls (r = 0.77–0.95, P < 0.0001). After controlling for total body water (TBW), the correlation coefficients were comparable. DXA trunk fat correlated with CT visceral fat (r = 0.51–0.70, P < 0.0001). DXA underestimated trunk and thigh fat and overestimated thigh muscle mass and this error increased with increasing weight. Our study showed that DXA is a useful method for assessing body composition in premenopausal women within the phenotypic spectrum ranging from obesity to AN. However, it is important to recognize that DXA may not accurately assess body composition in markedly obese women. The level of hydration does not significantly affect most DXA body composition measurements, with the exceptions of thigh fat.     

Body Composition at 6 months of Life: Comparison Of Air Displacement Plethysmography and Dual‐Energy X‐Ray Absorptiometry

Body composition assessment during infancy is important because it is a critical period for obesity risk development, thus valid tools are needed to accurately, precisely, and quickly determine both fat and fat‐free mass. The purpose of this study was to compare body composition estimates using dual‐energy x‐ray absorptiometry (DXA) and air displacement plethysmography (ADP) at 6 months old. We assessed the agreement between whole body composition using DXA and ADP in 84 full‐term average‐for‐gestational‐age boys and girls using DXA (Lunar iDXA v11–30.062; Infant whole body analysis enCore 2007 software, GE, Fairfield, CT) and ADP (Infant Body Composition System v3.1.0, COSMED USA, Concord, CA). Although the correlations between DXA and ADP for %fat (r = 0.925), absolute fat mass (r = 0.969), and absolute fat‐free mass (r = 0.945) were all significant, body composition estimates by DXA were greater for both %fat (31.1 ± 3.6% vs. 26.7 ± 4.7%; P < 0.001) and absolute fat mass (2,284 ± 449 vs. 1,921 ± 492 g; P < 0.001), and lower for fat‐free mass (5,022 ± 532 vs. 5,188 ± 508 g; P < 0.001) vs. ADP. Inter‐method differences in %fat decreased with increasing adiposity and differences in fat‐free mass decreased with increasing infant age. Estimates of body composition determined by DXA and ADP at 6 months of age were highly correlated, but did differ significantly. Additional work is required to identify the technical basis for these rather large inter‐method differences in infant body composition.     

A Comparison of Dual-Energy X-Ray Absorptiometry and Somatometrics for Determining Body Fat in Rhesus Macaques

COLMAN, RICKI J., JOHN C. HUDSON, HOWARD S. BARDEN, AND JOSEPH W. KEMNITZ. A comparison of dual-energy X-ray absorptiometry and somatometrics for determining body fat in rhesus macaques. Obes Res. 1999; 7:90–96. Objective : Various approaches have been used to assess fat and fat distribution in nonhuman primates, including measurements of body weight, body dimensions, and estimates derived from these, such as body mass index. Methods such as tritiated water dilution and dual-energy X-ray absorptiometry (DXA) have also been used. The aim of the present study was to evaluate and compare DXA measurements and somatometrics. Research Methods and Procedures : Body composition of 15 adult male rhesus macaques was measured by DXA and somatometrics at four time-points over a 4-year period. Additionally, DXA precision and somatometric variability were analyzed by repeated measurements of the same subjects. Results : DXA estimates of body fat were positively correlated with body weight, body mass index, body circumferences, and abdominal skinfold thicknesses. DXA assessments of soft tissue composition were precise, with coefficients of variation below 3.3% for all compartments analyzed. The majority of the observed variability in somatometrics was explained by subject variance, rather than by inter- or intraobserver variability, or by observer experience level. Discussion : We conclude that noninvasive DXA technology provides precise estimates of nonhuman primate body composition that correlate well with the traditional somatometric measures used in primate studies.     

DXA: Can It Be Used as a Criterion Reference for Body Fat Measurements in Children?

Objective: Dual‐energy X‐ray absorptiometry (DXA) is often cited as a criterion method for body composition measurements. We have previously shown that a new DXA software version (Hologic Discovery V12.1) will affect whole‐body bone mineral results for subjects weighing <40 kg. We wished to reanalyze pediatric whole‐body scans in order to assess the impact of the new software on pediatric soft‐tissue body composition estimates. Methods and Procedures: We reanalyzed 1,384 pediatric scans (for ages 1.7–17.2 years) using Hologic software V12.1, previously analyzed using V11.2. Regression analysis and ANCOVA were used to compare body fat (total body fat (TBF), percentage fat (%BF)), and non‐bone lean body mass (LBM) for the two versions, adjusting for gender, age and weight. Results: Software V12.1 yielded values that were higher for TBF, lower for LBM, and unchanged for DXA‐derived weight in subjects weighing <40 kg. Body composition values for younger, smaller subjects were most affected, and girls were more affected than boys. Using the new software, 14% of the girls and 10% of the boys were reclassified from the “normal” %BF range to “at risk of obesity,” while 7 and 5%, respectively, were reclassified as obese. Discussion: Hologic's newest DXA software has a significant effect on soft‐tissue results for children weighing <40 kg. The effect is greater for girls than boys. Comparison of TBF estimates with previous studies that use older DXA instruments and software should be done with caution. DXA has not yet achieved sufficient reliability to be considered a “gold standard” for body composition assessment in pediatric studies.     

Biases in Multicenter Longitudinal PET Standardized Uptake Value Measurements

This study investigates measurement biases in longitudinal positron-emission tomography/computed tomography (PET/CT) studies that are due to instrumentation variability including human error. Improved estimation of variability between patient scans is of particular importance for assessing response to therapy and multicenter trials. We used National Institute of Standards and Technology-traceable calibration methodology for solid germanium-68/gallium-68 (⁶⁸Ge/⁶⁸Ga) sources used as surrogates for fluorine-18 (¹⁸F) in radionuclide activity calibrators. One cross-calibration kit was constructed for both dose calibrators and PET scanners using the same 9-month half-life batch of ⁶⁸Ge/⁶⁸Ga in epoxy. Repeat measurements occurred in a local network of PET imaging sites to assess standardized uptake value (SUV) errors over time for six dose calibrators from two major manufacturers and for six PET/CT scanners from three major manufacturers. Bias in activity measures by dose calibrators ranged from -50% to 9% and was relatively stable over time except at one site that modified settings between measurements. Bias in activity concentration measures by PET scanners ranged from -27% to 13% with a median of 174 days between the six repeat scans (range, 29 to 226 days). Corresponding errors in SUV measurements ranged from -20% to 47%. SUV biases were not stable over time with longitudinal differences for individual scanners ranging from -11% to 59%. Bias in SUV measurements varied over time and between scanner sites. These results suggest that attention should be paid to PET scanner calibration for longitudinal studies and use of dose calibrator and scanner cross-calibration kits could be helpful for quality assurance and control.     

Segmental body composition assessment for obese Japanese adults by single-frequency bioelectrical impedance analysis with 8-point contact electrodes

This study aimed to determine the accuracy of segmental body composition variables estimated by single-frequency BIA with 8-point contact electrodes (SF-BIA8), compared with dual-energy X-ray absorptiometry (DXA). Subjects were 72 obese Japanese adults (43 males and 29 females) aged 30 to 66 years. Segmental body composition variables (fat free mass: FFM, fat mass: FM, and percent fat mass: %FAT) were measured by these techniques. The correlations between impedance values and FFM measured by DXA were calculated. To examine the consistency in predicted values (SF-BIA8) with the reference (DXA), significant mean differences were tested by t-test and the degree of the difference was assessed by effect size. Correlations between the reference and predicted values were calculated. Additionally, the standard error of estimation (SEE) when estimating the reference from the predictor and the relative value of the SEE to the mean value of the DXA measurement (%SEE) were calculated. Systematic error was examined by Bland-Altman plots. High correlations were found between impedance and FFM measured by SF-BIA8. FFM in the extremities showed high correlations with the reference values, but systematic error was found. SF-BIA8 tended to overestimate FFM in the trunk. The consistencies in %FAT and FM with the reference value are inferior to those for FFM, and SEE values in %FAT and FM were greater than those for FFM. The accuracy of the estimated values in the trunk (FFM, %FAT, and FM) are inferior to those of the total body and extremities.     

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.     

Dual Energy X-Ray Absorptiometry Body Composition Reference Values from NHANES

In 2008 the National Center for Health Statistics released a dual energy x-ray absorptiometry (DXA) whole body dataset from the NHANES population-based sample acquired with modern fan beam scanners in 15 counties across the United States from 1999 through 2004. The NHANES dataset was partitioned by gender and ethnicity and DXA whole body measures of %fat, fat mass/height², lean mass/height², appendicular lean mass/height², %fat trunk/%fat legs ratio, trunk/limb fat mass ratio of fat, bone mineral content (BMC) and bone mineral density (BMD) were analyzed to provide reference values for subjects 8 to 85 years old. DXA reference values for adults were normalized to age; reference values for children included total and sub-total whole body results and were normalized to age, height, or lean mass. We developed an obesity classification scheme by using estabbody mass index (BMI) classification thresholds and prevalences in young adults to generate matching classification thresholds for Fat Mass Index (FMI; fat mass/height²). These reference values should be helpful in the evaluation of a variety of adult and childhood abnormalities involving fat, lean, and bone, for establishing entry criteria into clinical trials, and for other medical, research, and epidemiological uses.