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40 Potassium-related total body protein and body cell mass models: validation studies in patients with chronic diseases
ZiMian Wang, Daniel Stroud, Steven B. Heymsfield, and Boyd J. G. Strauss
41 Use of a reference four-component model to evaluate the ability of alternative methods and prediction
techniques to estimate body composition in Type 2 diabetes and its changes following insulin treatment
IC Packianathan, NJ Fuller, DB Peterson, A Wright, WA Coward and N Finer
42 Comparison of methods of body water determination in gastrointestinal cancer patients undergoing surgery
Alireza Aslani, Bruce A Cooper, Andre Sevette, Ross D Hansen and Ross C Smith
43 X-ray fluorescence analysis for determination of iodine concentration in the thyroid: A methodological study
M. Hansson1, G. Berg2, A. Larsson3, E. Nyström4, and M. Isaksson
44 Calibration models to measure body composition in taller subjects using DXA
Analiza M. Silva, Fátima Baptista, Claudia S. Minderico, Alexandra R. Rodrigues, Angelo Pietrobelli, Pedro J. Teixeira and Luis B. Sardinha
International Journal of Body Composition Research 2004, Vol. 2 No. 4: 133-139
ZiMian Wang1, Daniel Stroud2, Steven B. Heymsfield1, and Boyd J. G. Strauss2
1Obesity Research Center, St. Luke’s-Roosevelt Hospital, Columbia University College of Physicians and Surgeons, New York, USA; and 2Body Composition Laboratory, Monash Medical Centre, Department of Medicine, Monash University, Victoria, Australia
Total body protein (TBPro) and body cell mass (BCM) prediction models, based on total body potassium (TBK) measured by whole-body 40K counting, were developed and validated in healthy adults. However, the applicability of these models in healthy subjects across different laboratories and in patients with chronic diseases is unknown. The aim of this study was to cross validate the TBPro and BCM prediction models in healthy Australian adults and in patients with liver disease and to cross validate the TBPro prediction model in patients with growth hormone (GH) deficiency and chronic renal failure. Subjects were healthy adults (n = 43) and patients with liver disease (n = 151), GH deficiency (n = 39), and chronic renal failure (n = 17). Total body nitrogen (TBN) was measured by in vivo neutron activation analysis (IVNA), TBK by whole-body 40K counting, total body water by deuterium dilution, extracellular water by sodium bromide dilution, and bone mineral by dual-energy X-ray absorptiometry. TBPro and BCM were calculated from TBN and a TBK-independent IVNA model as the reference, respectively. There was no significant difference in TBPro estimates between TBN and TBK models in healthy subjects, but the TBK model overestimated TBPro by (mean ± SD) 0.6 ± 0.9 kg and 0.9 ± 0.8 kg for the patients with liver disease and chronic renal failure (both P < 0.001), and underestimated TBPro by 0.4 ± 0.9 kg for the patients with GH deficiency (P < 0.01). There was no significant difference in BCM estimates between multi-component IVNA and TBK models in healthy subjects and patients with liver disease, although a large bias between the two methods was observed in the patients with liver disease. The present study results support the use of TBK-based TBPro and BCM prediction formulas in healthy subjects and in patients with selected chronic clinical conditions.
International Journal of Body Composition Research 2004, Vol. 2 No. 4: 141-148
IC Packianathan1,2, NJ Fuller3, DB Peterson4, A Wright5, WA Coward5 and N Finer1,2
1Wellcome Trust Clinical Research Facility and Department of Endocrinology and Diabetes, Addenbrookes Hospital, Cambridge; 2Department of Diabetes and Endocrinology and Centre for Obesity Research, Luton and Dunstable Hospital, Luton; 3MRC Childhood Nutrition Research Centre, Institute of Child Health, London; 4Department of Diabetes and Metabolism, Royal London Hospital, London; 5Stable Isotope Group, MRC Human Nutrition Research, Elsie Widdowson Laboratory, Cambridge, UK
Aim of the study was to assess the ability of various techniques to estimate body composition in Type 2 diabetes before treatment, after 6 months of insulin treatment, and the changes following such therapy. Body composition (body fat, fat-free mass, total body water and total body protein) was assessed, at baseline and again after 6 months, using a number of techniques in 19 Type 2 diabetes patients (mean age, 60 (SD 8.3) yr; BMI, 25.3 (3.3) kg/m2), poorly controlled despite maximal oral hypoglycemic agents, receiving insulin (mean dose 40 (12.2) units/day). A four-component model was used as reference to assess the validity of these alternative techniques with bias and 95% limits of agreement. The three-component model was the most valid and least variable technique before and after insulin treatment and for assessing changes in body composition. Deuterium dilution, dual energy X-ray absorptiometry and air displacement plethysmography were less reliable, but were better predictors of absolute body composition and changes therein than bio-electrical impedance analysis or predictions based on anthropometry, which were misleading on both a group and an individual basis. It is concluded that, apart from the 3-component model, none of the methods were capable of either accurate or precise assessments of body composition before and after insulin therapy. Similarly changes in body composition were not tracked accurately or precisely using empirical techniques.
International Journal of Body Composition Research 2004, Vol. 2 No. 4: 149-154
Alireza Aslani1, Bruce A Cooper2, Andre Sevette3, Ross D Hansen4 and Ross C Smith3
1Department of Nuclear Medicine, 2Department of Renal Medicine, 3Department of Surgery, 4Gastrointestinal Investigation Unit, Royal North Shore Hospital, Pacific Highway, St Leonards, NSW 2065, Australia
Excess fluid retention can result in major morbidity in surgical patients. Understanding the degree of fluid retention will help to determine better strategies for fluid management. The aim of this study was, therefore, to identify the most efficient method of total body water (TBW) estimation in gastrointestinal cancer patients undergoing surgery. The TBW of 39 gastrointestinal cancer patients (19 females) was measured using the reference standard deuterium oxide dilution technique (TBWD2O) and compared to estimates derived via several equations: bioelectrical impedance analysis (Kushner, Pullicino, and Fredrix) equations; Watson’s equations; 73.2% of fat-free mass; and 58% body weight. All measurements were carried out concurrently. Analysis of variance and post-hoc tests showed that the 58% body weight method overestimated TBWD2O by 6.7 ± 10.1 kg (P= 0.002). The Fredrix, then the Kushner equations (mean overestimation of TBWD2O = 0.5 ± 7.4 kg and 1.2 ± 7.5 kg respectively; both P> 0.5) produced the narrowest limits of agreement and the least bias. These results indicate that the Fredrix equation may be an accurate, less time-consuming alternative to TBWD2O in determining TBW for groups of gastrointestinal cancer surgery patients. However, due to relatively wide limits of agreement, such measurements are probably of limited value for individual patient assessment.
International Journal of Body Composition Research 2004, Vol. 2 No. 4: 155-163
M. Hansson1, G. Berg2, A. Larsson3, E. Nyström4, and M. Isaksson1
1Department of Radiation Physics, Göteborg University, Sweden; 2Department of Oncology, Sahlgrenska University Hospital, Sweden; 3Department of Buildings and Services, Göteborg University, Sweden; 4Department of Medicine, Sahlgrenska University Hospital, Sweden
Knowledge of the amount of iodine stored in the thyroid may contribute to the understanding of thyroidal diseases. Hence, there is a need for non-invasive methods for assessment of the iodine pool in vivo. X-ray fluorescence (XRF) is such a method and the objective of the present study was to perform a methodological evaluation of the XRF technique in vitro, with emphasis on the influence of the analysed volume. A wellcalibrated system with 241Am as irradiating source was used. Porcine thyroids were measured with XRF and neutron activation analysis (NAA), to evaluate the accuracy of the system. An analysed volume small enough to fit within a lobe gave too low detector signal and an analysed volume completely enclosing a lobe resulted in a larger background and a higher radiation dose. For in vivo studies an analysed volume where the irradiating beam was fitted inside a thyroid lobe and the detected pulses originated from a volume well enclosing the irradiated thyroid was preferable. Such geometry gave a lower radiation dose and also a detector signal essentially only depending on the sample concentration and diameter. The iodine concentration of the thyroids measured with XRF and NAA showed a good agreement (r=0.93) and for the 241Am source an average minimum detectable concentration (MDC) of 0.06 mg/ml gave the effective dose 6 µSv. Accordingly XRF, if well calibrated, is a suitable tool for in vivo determination of iodine concentration in the thyroid.
International Journal of Body Composition Research 2004, Vol. 2 No. 4: 165-173
Analiza M. Silva1, Fátima Baptista1, Claudia S. Minderico1, Alexandra R. Rodrigues1, Angelo Pietrobelli2, Pedro J. Teixeira1 and Luis B. Sardinha1
1Exercise and Health Laboratory, Faculty of Human Movement-Technical University of Lisbon, Portugal; 2Pediatric Unit, Verona University Medical School, Italy
The aim of this study was to assess the accuracy of DXA whole body composition measurements of bone mineral content (BMC), fat mass (FM) and lean soft tissue (LST), performed with knees bent compared to the standard position in subjects during a whole body scan. DXA was used to measure body composition in 104 Caucasian males and females. Comparison of means and linear regression analysis were used to test the performance of DXA measurements and to develop calibration models. For the entire sample, using the knees bent, BMC and FM were overestimated by ~2.6% and ~9.2%, respectively, while LST was underestimated by ~4.0% (P<0.001). The regression between BMCKneesBent and the standard position did not differ from the line of identity for (FM) and lean soft tissue (LST, P >0.05), while the slope differed from 1 for FM and LST (P <0.05). New 17 models were developed for BMC, FM and LST. For FM, the significant predictors were FMKneesBent, age, lower limb fat mass (LLFM), and the knees bent height (KBH) while for LST, were LSTKneesBent, LLFM, age, and KBH. Finally, for BMC, BMCKneesBent, age, LLFM, and LLFM x sex interaction were associated with the reference BMC. These findings show that body composition measurements with knees bent differ from the standard position. Hence, the recommendation of this technique in subjects taller than the DXA scan area should be accomplished by using correction models for BMC, FM, and LST developed for specific DXA instrument.
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