Measurement Precision of Body Composition Variables Using the Lunar DPX-L Densitometer

Kiebzak, Gary M.; Leamy, Larry J.; Pierson, Lee M.; Nord, Russell H.; Zhang, Zhi Y.

doi:10.1385/jcd:3:1:035

Cited by 159 publications

(93 citation statements)

References 21 publications

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“…Precision of total body water in our laboratory is B1% (Wells et al, 1999). Precision of body volume from duplicate measurements in obese children and adolescents was 0.24 l. Precision of bone mineral content, according to published data for Lunar Prodigy Instrumentation, is 1.1% for bone mineral content (Kiebzak et al, 2000).…”

Section: Methodsmentioning

confidence: 64%

Evaluation of lean tissue density for use in air displacement plethysmography in obese children and adolescents

Wells¹,

Haroun²,

Williams³

et al. 2011

Eur J Clin Nutr

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Background/Objectives: Body composition techniques are required for monitoring response to treatment in individual obese children, and assessing the efficacy of weight loss programmes. Densitometry is readily undertaken, using air displacement plethysmography (ADP), but requires appropriate information on the density of lean tissue (D LT ). The aims of this study were to develop predictive equations for D LT in obese children and adolescents, and to test the accuracy of ADP when using such predicted D LT values in an independent longitudinal sample using the four-component model as the reference method.

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Section: Methodsmentioning

confidence: 64%

Evaluation of lean tissue density for use in air displacement plethysmography in obese children and adolescents

Wells¹,

Haroun²,

Williams³

et al. 2011

Eur J Clin Nutr

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“…Our CV's for total body, arm, and leg BMD are similar to those published. 26 For speci®c regional scans (software v1.35), the in vivo CV's in our laboratory are: lumbar spine BMD 0.67%, and for the hip region, femoral neck BMD 1.41%, Ward's triangle BMD 2.34%, and trochanter 1.53%. These precision measures for DEXA scanning are also similar to those published.…”

Section: Methodsmentioning

confidence: 99%

Intensive exercise may preserve bone mass of the upper limbs in spinal cord injured males but does not retard demineralisation of the lower body

2002

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Study design: Cross-sectional study comparing a group of active spinal cord injured (SCI) males carefully matched for age, height, and weight with active able-bodied male controls. Objectives: To compare bone mass of the total body, upper and lower limbs, hip, and spine regions in active SCI and able-bodied individuals. Setting: Outpatient study undertaken in two centres in New Zealand. Methods: Dual energy X-ray absorptiometry (DEXA) scanning was used to determine bone mass. Questionnaires were used to ascertain total time spent in weekly physical activity for each individual. The criterion for entry into the study was regular participation in physical activity of more than 60 min per week, over and above that required for rehabilitation. Results: Seventeen SCI and their able-bodied controls met our required activity criterion. Bone mineral density (BMD) values of the total body and hip regions were signi®cantly lower in the SCI group than in their controls (P=0.0001). Leg BMD and bone mineral content (BMC) were also signi®cantly lower in the SCI group (P=0.0001). By contrast, lumbar spine BMD and arm BMD and BMC did not di er between the SCI and control groups. Arm BMD and BMC were greater (not signi®cant) than the reference norms (LUNAR database) for both groups.

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“…The lean body mass (LBM) was calculated by using the following equation: LBM ¼ weight Á bodyfat)=100. The total body, android, and gynoid fat contents were measured by dual energy X-ray absorptiometry (DEXA) (Kiebzak et al, 2000) and the android/gynoid ratio was calculated. The visceral (VAT) and subcutaneous (SAT) fat content were determined by magnetic resonance imaging (MRI) of 16 transaxial scans reaching at the fourth and fifth lumbar interspace (Hu et al, 2011).…”

Section: Association Of Metabolite Profiles and Body Fat Distributionmentioning

confidence: 99%

Gender-Dependent Associations of Metabolite Profiles and Body Fat Distribution in a Healthy Population with Central Obesity: Towards Metabolomics Diagnostics

Szymańska

Bouwman

Strassburg

et al. 2012

OMICS: A Journal of Integrative Biology

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Gender-dependent associations of metabolite profiles and body fat distribution in a healthy population with central obesity: towards metabolomics diagnostics Szymanska, E.; Bouwman, J.; Strassburg, K.; Vervoort, J.; Kangas, A.J.; Soininen, P.; AlaKorpela, M.; Westerhuis, J.A.; van Duynhoven, J.P.M.; Mela, D.J.; Macdonald, I.A.; Vreeken, R.J.; Smilde, A.K.; Jacobs, D.M. Published in: Omics DOI:10.1089/omi.2012.0062 Link to publication Citation for published version (APA):Szymaska, E., Bouwman, J., Strassburg, K., Vervoort, J., Kangas, A. J., Soininen, P., ... Jacobs, D. M. (2012). Gender-dependent associations of metabolite profiles and body fat distribution in a healthy population with central obesity: towards metabolomics diagnostics. Omics, 16(12), 652-667. DOI: 10.1089/omi.2012.0062 General rightsIt is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulationsIf you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. AbstractObesity is a risk factor for cardiovascular diseases and type 2 diabetes especially when the fat is accumulated to central depots. Novel biomarkers are crucial to develop diagnostics for obesity and related metabolic disorders. We evaluated the associations between metabolite profiles (136 lipid components, 12 lipoprotein subclasses, 17 low-molecular-weight metabolites, 12 clinical markers) and 28 phenotype parameters (including different body fat distribution parameters such as android (A), gynoid (G), abdominal visceral (VAT), subcutaneous (SAT) fat) in 215 plasma/serum samples from healthy overweight men (n = 32) and women (n = 83) with central obesity.(Partial) correlation analysis and partial least squares (PLS) regression analysis showed that only specific metabolites were associated to A:G ratio, VAT, and SAT, respectively. These association patterns were gender dependent. For example, insulin, cholesterol, VLDL, and certain triacylglycerols (TG 54:1-3) correlated to VAT in women, while in men VAT was associated with TG 50:1-5, TG 55:1, phosphatidylcholine (PC 32:0), and VLDL ((X)L). Moreover, multiple regression analysis revealed that waist circumference and total fat were sufficient to predict VAT and SAT in women. In contrast, only VAT but not SAT could be predicted in men and only when plasma metabolites were included, with PC 32:0 being most strongly associated with VAT. These findings collectively highlight the p...

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Measurement Precision of Body Composition Variables Using the Lunar DPX-L Densitometer

Cited by 159 publications

References 21 publications

Evaluation of lean tissue density for use in air displacement plethysmography in obese children and adolescents

Evaluation of lean tissue density for use in air displacement plethysmography in obese children and adolescents

Intensive exercise may preserve bone mass of the upper limbs in spinal cord injured males but does not retard demineralisation of the lower body

Gender-Dependent Associations of Metabolite Profiles and Body Fat Distribution in a Healthy Population with Central Obesity: Towards Metabolomics Diagnostics

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