International journal of body composition research最新文献

OBJECTIVE: To determine if increasing fatness interferes with the measurement of fat and bone mineral density (BMD) by dual-energy X-ray absorptiometry (Lunar iDXA). METHODS: We performed measurements of BMD and fat on a section of a beef femur defatted by prolonged boiling in detergent, completely surrounded by increasing thicknesses of lard. Initially the bone was placed in the marked spine area, overlying a 6L plastic bottle which was placed in the marked trunk area of the iDXA. The plastic bottle was then removed and further measurements were carried out with increasing thicknesses of lard surrounding the bone. Measurements were repeated 4 times. RESULTS: The reported measurement of BMD progressively increased with each increased layer of lard surrounding the bone. All the iDXA BMD measurements were significantly (P<0.01) different from one another. When surrounded by 3 layers of lard the reported BMD was 20.5% greater than the reported BMD when the bone was not surrounded by any lard. The differences between the actual amount of fat measured by chemical analysis and weighing, and the reported measurement of fat by iDXA were significant with all 3 thicknesses of lard (P<0.01); the percentage difference between the fat measured by iDXA and that measured chemically decreased as the number of layers of lard increased. CONCLUSION: We found that iDXA overestimated fat by up to 11.1%. The percentage overestimation of fat diminished as the amount of fat increased. BMD was overestimated by 20.5% when surrounded by 3 layers of fat compared to when there was no surrounding fat. In contrast to fat, the percentage overestimation of BMD increased as increasing amounts of fat surrounding the bone Using earlier generation DXAs, others have reported that measurements were ± 20-50% inaccurate and differed according to the configuration of the phantoms. The measurement of BMD and fat is the main clinical purpose of iDXA; the present experiment has shown that there are substantial inaccuracies in the measurement of BMD and fat. It is not known how these inaccuracies compare with those of earlier generations of DXA machines.

OBJECTIVES: To examine the validity of body composition estimates obtained using foot-to-foot bio-electrical impedance analysis (BIA) in overweight and obese children by comparison to a reference four-compartment model (4-CM). SUBJECTS/METHODS: 38 males: age (mean +/- sd) 13.6 +/- 1.3 years, body mass index 30.3 +/- 6.0 kg.m(-2) and 14 females: age 14.7 +/- 2.2 years, body mass index 32.4 +/- 5.7 kg.m(-2) participated in the study. Estimates of fat-free mass (FFM), fat mass (FM) and percentage body fat (PBF) obtained using a Tanita model TBF-310 and a 4-CM (derived from body mass, body volume, total body water and total body bone mineral measurements) were compared using bias and 95% limits of agreement (Tanita minus 4-CM estimates). RESULTS: Body composition estimates obtained with the Tanita TBF-310 were not significantly different from 4-CM assessments: for all subjects combined the bias was -0.7kg for FM, 0.7kg for FFM and -1.3% for PBF. However, the 95% limits of agreement were substantial for individual children: males, up to +/-9.3kg for FFM and FM and +/-11.0% for PBF; females, up to +/-5.5kg for FFM and FM and +/-6.5% for PBF. CONCLUSIONS: The Tanita TBF-310 foot-to-foot BIA body composition analyser with the manufacturer's prediction equations is not recommended for application to individual children who are overweight and obese although it may be of use for obtaining group mean values.

OBJECTIVE: Bioelectrical impedance analysis (BIA) of hydration and body composition has made significant progress during the past 3 decades. With the development of Bioimpedance spectroscopy (BIS), bioimpedance has been expanded to reliably predict extracellular fluid (ECF) and total body water (TBW), allowing the calculation of fat-free mass (FFM) and fat mass (FM). In this study, a new BIS device (ImpediVet™), designed for body composition measurements in animals, was assessed for precision and accuracy in measuring TBW, FFM and FM in rats. METHODS: In a validation study, 25 rats were measured for body composition (TBW, FFM and FM) using BIS and chemical carcass analysis (CCA). BIS precision was assessed by the coefficient of variation using multiple BIS readings, while BIS accuracy was assessed by regression analysis of BIS and CCA values for each body compartment. In a cross-validation study, prediction equations generated from the validation group for TBW, FFM and FM were applied to an independent cohort of 25 rats that were measured by BIS and CCA. Linear regression analysis and paired t-tests were used to assess significance of relationships and measurement differences within groups. RESULTS: In the validation study, BIS was highly correlated with CCA for TBW (r(2)=0.988), FFM (r(2)=0.987) and FM (r(2)=0.966). Even so, BIS significantly underestimated TBW (mean: -31.07 g, -13.3%, p<0.001) and FFM (-50.69 g, -15.5%, p<0.001), while overestimating FM (+65.75 g, +63.5%, p<0.001). In the independent, cross-validation group of rats the prediction equations accurately predicted carcass values for TBW (-0.2%, p=0.350), FFM (-0.2%, p=0.457) and FM (+1.5%, p=0.508). CONCLUSION: Based on these results, BIS provided a precise and accurate means to determine in vivo body composition in rats.

BACKGROUND: Loss of subcutaneous (SAT) with sparing of visceral (VAT) adipose tissue (AT) has been documented in HIV + men and women. Intermuscular AT (IMAT) rivals VAT in independent associations with cardiovascular risk. OBJECTIVE: To determine whether the size and distribution of IMAT differs in HIV+ vs. HIV- men and/or women. DESIGN: We used whole-body MRI to measure VAT, IMAT and four SAT compartments and compared them by HIV status using whole-body skeletal muscle (SM) or total AT (TAT) as co-variates in multi-ethnic groups of healthy HIV- (n=86) and stable HIV+ (n=76) men and women. RESULTS: The sizes of AT depots (adjusting for SM) did not differ by HIV status, except for smaller gluteal SAT (lower trunk, between L(4)-L(5) to greater trochanter) in both sexes (P<0.05). The AT distribution (adjusting for TAT) was significantly different, with larger VAT (P<0.05) and smaller gluteal and limb SAT (P<0.05) in both HIV+ sexes; IMAT increased more with TAT in HIV+ vs. HIV- men (P<0.05 for slope interaction) but there were no significant differences in women. There were significant race by HIV interactions in AT distribution with more pronounced VAT differences in non-Hispanic white men and larger trunk SAT in African Americans HIV+ vs. HIV-. CONCLUSION: The AT distribution differed markedly in HIV+ vs. HIV- with limb and lower body SAT representing a smaller proportion of TAT in HIV+ in both sexes and IMAT representing a larger proportion of TAT in HIV+ vs. HIV- men.

OBJECTIVE: The aim of this study was to assess the precision and accuracy of a quantitative magnetic resonance (QMR) instrument for measuring body composition in live, non-anesthetized mice. METHODS: Forty-eight mice of varying strains, ages and body weights (15.3 to 50.2g) were scanned three times each in the QMR instrument. Animals were killed and chemical carcass analysis performed for comparison. Precision was assessed as the coefficient of variation (CV) for the triplicate scans and accuracy was determined by comparing the first QMR data with the chemical analysis. Prediction equations were generated by linear regression analysis and used in a cross-validation study in which 26 mice were scanned once each, killed, and chemical carcass analysis performed. RESULTS: The mean CV was 1.58% for fat mass (FM) and 0.78% for lean-tissue mass (LTM). QMR significantly (P<0.01) overestimated FM (7.76±5.93 vs. 6.03±5.17g) and underestimated LTM (20.73±6.19 vs. 22.48±6.75g) when compared with chemical carcass analysis. A strong relationship between QMR and chemical data (r(2)=0.99 and r(2)=0.97 for fat and LTM respectively; P<0.0001) allowed for the generation of correction equations that were applied to QMR data in the cross-validation study. There was no significant difference between data predicted from QMR and chemical carcass data for FM and LTM (P=0.15 and 0.10 respectively). CONCLUSION: The QMR instrument showed excellent precision and data was highly correlated with chemical carcass analysis. This combined with QMR's speed for whole animal analysis (95 seconds) make it a highly feasible and useful method for the determination of body composition in live, non-anesthetized mice.

OBJECTIVE: To assess the accuracy and reproducibility of dual-energy absorptiometry (DXA; PIXImus(™)) and time domain nuclear magnetic resonance (TD-NMR; Bruker Optics) for the measurement of body composition of lean and obese mice. SUBJECTS AND MEASUREMENTS: Thirty lean and obese mice (body weight range 19-67 g) were studied. Coefficients of variation for repeated (x 4) DXA and NMR scans of mice were calculated to assess reproducibility. Accuracy was assessed by comparing DXA and NMR results of ten mice to chemical carcass analyses. Accuracy of the respective techniques was also assessed by comparing DXA and NMR results obtained with ground meat samples to chemical analyses. Repeated scans of 10-25 gram samples were performed to test the sensitivity of the DXA and NMR methods to variation in sample mass. RESULTS: In mice, DXA and NMR reproducibility measures were similar for fat tissue mass (FTM) (DXA coefficient of variation [CV]=2.3%; and NMR CV=2.8%) (P=0.47), while reproducibility of lean tissue mass (LTM) estimates were better for DXA (1.0%) than NMR (2.2%) (

OBJECTIVE: Jackson and Pollock's (JP) ground-breaking research reporting generalized body density equations to estimate body fat was carried out in the late 1970s. Since then we have experienced an 'obesity epidemic'. Our aim was to examine whether the original quadratic equations established by Jackson and co-workers are valid in the 21st century. METHODS: Reanalyzing the original JP data, an alternative, more biologically sound exponential power-function model for body density is proposed that declines monotonically, and hence predicts body fat to rise monotonically, with increasing skin-fold thicknesses. The model also remains positive irrespective of the subjects' sum-of-skinfold thicknesses or age. RESULTS: Compared to the original quadratic model proposed by JP, our alternative exponential power-function model is theoretically and empirically more accurate when predicting body fat of obese subjects (sums of skinfolds >120mm). A cross-validation study on 14 obese subjects confirmed these observations, when the JP quadratic equations under estimated body fat predicted using dual energy x-ray absorptiometry (DXA) by 2.1% whereas our exponential power-function model was found to underestimate body fat by less than 1.0%. Otherwise, the agreement between the DXA fat (%) and the two models were found to be almost identical, with both coefficients of variation being 10.2%. CONCLUSIONS: Caution should be exercised when predicting body fat using the JP quadratic equations for subjects with sums of skinfolds>120 mm. For these subjects, we recommend estimating body fat using the tables reported in the present manuscript, based on the more biologically sound and empirically valid exponential power-function model.

During the past two decades, a major outgrowth of efforts by our research group at St. Luke's-Roosevelt Hospital is the development of body composition models that include cellular level models, models based on body component ratios, total body potassium models, multi-component models, and resting energy expenditure-body composition models. This review summarizes these models with emphasis on component ratios that we believe are fundamental to understanding human body composition during growth and development and in response to disease and treatments. In-vivo measurements reveal that in healthy adults some component ratios show minimal variability and are relatively 'stable', for example total body water/fat-free mass and fat-free mass density. These ratios can be effectively applied for developing body composition methods. In contrast, other ratios, such as total body potassium/fat-free mass, are highly variable in vivo and therefore are less useful for developing body composition models. In order to understand the mechanisms governing the variability of these component ratios, we have developed eight cellular level ratio models and from them we derived simplified models that share as a major determining factor the ratio of extracellular to intracellular water ratio (E/I). The E/I value varies widely among adults. Model analysis reveals that the magnitude and variability of each body component ratio can be predicted by correlating the cellular level model with the E/I value. Our approach thus provides new insights into and improved understanding of body composition ratios in adults.

The measurement of human body composition allows for the estimation of body tissues, organs, and their distributions in living persons without inflicting harm. From a nutritional perspective, the interest in body composition has increased multi-fold with the global increase in the prevalence of obesity and its complications. The latter has driven in part the need for improved measurement methods with greater sensitivity and precision. There is no single gold standard for body-composition measurements in-vivo. All methods incorporate assumptions that do not apply in all individuals and the more accurate models are derived by using a combination of measurements, thereby reducing the importance of each assumption. This review will discuss why the measurement of body composition or human phenotyping is important; discuss new areas where the measurement of body composition (human phenotyping) is recognized as having important application; and will summarize recent advances made in new methodology. Reference will also be made to areas we cannot yet measure due to the lack of appropriate measurement methodologies, most especially measurements methods that provide information on kinetic states (not just static state) and metabolic function.