Influence of methods used in body composition analysis on the prediction of resting energy expenditure

Korth, Oliver; Bosy‐Westphal, Anja; Zschoche, P; Glüer, Claus‐C.; Heller, Martin; Müller, Manfred J.

doi:10.1038/sj.ejcn.1602556

Cited by 98 publications

(79 citation statements)

References 27 publications

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“…Fat mass was assessed either by air-displacement plethysmography (BOD-POD Body Composition System, Life Measurement Instruments, Concord, CA, USA; n ¼ 4) or by hydrodensitometry (Borngässer Waagenbau, Grebbin, Germany; n ¼ 6) as described previously. 25,26 In a previous study, we had demonstrated a strong agreement between both methods in healthy young men (r ¼ 0.93). 26 calculated as the difference between body weight and fat mass.…”

Section: Anthropometric Measurements and Body Composition Analysismentioning

confidence: 99%

Effects of brief perturbations in energy balance on indices of glucose homeostasis in healthy lean men

et al. 2011

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BACKGROUND:Little is known about the effects of short-term caloric restriction (CR) and overfeeding (OF) on glucose homeostasis in healthy lean individuals. In addition, it remains unclear whether the effects of CR and OF are reversed by a complementary feeding period. METHODS: Ten healthy men participated in two cycles of controlled 7-day periods of CR and refeeding (RF; protocol A), and OF and CR (protocol B) at ±60% energy requirement. At baseline, insulin sensitivity (IS) was assessed by euglycemic clamp (M). Before and during each feeding cycle, fasting and oral glucose tolerance test-derived indices were used to estimate glucose tolerance, IS and glucose-stimulated insulin secretion. RESULTS: Clamp tests revealed normal IS at baseline (M-values 9.4 ± 2.1 mg kg À1 min À1 , coefficient of variation (CV) inter 22%). M-values were significantly correlated with indices of IS. In protocol A, CR-induced weight loss (À3.0±0.4 kg) was associated with an increase in fasting IS. Postprandial IS and glucose-stimulated insulin secretion remained unchanged, but glucose tolerance decreased. RF decreased fasting and postprandial IS at increased glucose-stimulated insulin secretion. In protocol B, OF significantly increased the body weight ( þ 1.6±0.9 kg). Concomitantly, fasting and postprandial IS decreased at increased glucose-stimulated insulin secretion. Subsequent CR reversed these effects. Inter-individual variability in indices of glucose metabolism was high with coefficients of variation ranging from 9 to 59%. CONCLUSION: Significant changes in glucose metabolism are evident within 7-day periods of controlled OF and underfeeding. Although IS was impaired at the end of the CR --RF cycle, IS was normalized after the OF --CR cycle. At different feeding regimens, homeostatic responses of glucose metabolism were highly variable. Keywords: insulin secretion; insulin sensitivity; glucose homeostasis; weight gain; energy balance INTRODUCTION Long-term perturbations in energy balance, either by overfeeding (OF) or underfeeding, are known to modulate insulin sensitivity (IS). Chronic OF and obesity are commonly characterized by insulin resistance, 1 which has been shown to be completely 2 or partially reversed by acute caloric restriction (CR), as well as by moderate weight loss. 3 --5 On the other hand, IS is preserved or even improved with chronic CR in patients with anorexia nervosa and returned to normal values at the end of refeeding (RF). 6 Although considerable research has been devoted to individuals outside the normal range of body weight, there are only few studies examining the effects of short-term controlled perturbations in energy balance on IS in lean subjects without confounding metabolic abnormalities. 7 --17 Moreover, these studies provide discordant findings that may depend on duration and degree of energy imbalance and macronutrient composition of the diets. Fasting (1 --3 days) consistently caused a decline in IS assessed by clamp-and intravenous glucose tolerance test. 7,8,17 Studies with less severe ...

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Section: Anthropometric Measurements and Body Composition Analysismentioning

confidence: 99%

Effects of brief perturbations in energy balance on indices of glucose homeostasis in healthy lean men

et al. 2011

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“…Data obtained from large populations covering a wide weight range suggest that FFM is the major determinant of energy expenditure, explaining about 60-80% of its variance (Ravussin and Bogardus, 1989;Elia, 1992;Korth et al, 2007). The higher the FFM the higher is the REE.…”

Section: Functional Aspects Of Fat Mass and Ffmmentioning

confidence: 99%

Functional body composition: insights into the regulation of energy metabolism and some clinical applications

et al. 2009

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The application of advanced methods and techniques and their continuous development enable detailed body composition analyses (BCAs) and modeling of body composition at different levels (e.g., at atomic, molecular, organ-tissue and whole body level). Functional body composition integrates body components into regulatory systems (e.g., on energy balance). Regulation of body weight is closely linked to the mass and function of individual body components. Fat mass is part of the energy intake regulatory feedback system. In addition, fat-free mass (FFM) and fat mass are both determinants of resting energy expenditure (REE). Up to 80% of the variance in energy intake and energy expenditure is explained by body composition. A deviation from normal associations between body components and function suggests a metabolic disequilibrium (e.g., in the REE-FFM relationship or in the plasma leptin-fat mass association) that may occur in response to weight changes and diseases. The concept of functional body composition adds to a more sophisticated view on nutritional status and diseases, as well as to a characterization of biomedical traits that will provide functional evidence relating genetic variants.

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“…FM was calculated from body volume (by air-displacement plethysmography), total body water (TBW by deuterium dilution), and bone mineral content (BMC by dual-energy X-ray absorptiometry) by using the equation of Fuller et al (35) A detailed description of each method and its precision was previously reported (36). FFM was calculated as the difference between body mass and FM.…”

Section: Four-compartment Modelmentioning

confidence: 99%

Contribution of individual organ mass loss to weight loss–associated decline in resting energy expenditure

Bosy‐Westphal

Kossel

Goele

et al. 2009

The American Journal of Clinical Nutrition

145

163

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Background: Weight loss leads to reduced resting energy expenditure (REE) independent of fat-free mass (FFM) and fat mass (FM) loss, but the effect of changes in FFM composition is unclear. Objective: We hypothesized that a decrease in REE adjusted for FFM with weight loss would be partly explained by a disproportionate loss in the high metabolic activity component of FFM. Design: Forty-five overweight and obese women [body mass index (in kg/m 2 ): 28.7-46.8] aged 22-46 y followed a low-calorie diet for 12.7 6 2.2 wk. Body composition was measured by magnetic resonance imaging, dual-energy X-ray absorptiometry, and a 4-compartment model. REE measured by indirect calorimetry (REEm) was compared with REE calculated from detailed body-composition analysis (REEc) by using specific organ metabolic rates (ie, organ REE/mass). Results: Weight loss was 9.5 6 3.4 kg (8.0 6 2.9 kg FM and 1.5 6 3.1 kg FFM). Decreases in REE (28%), free triiodothyronine concentrations (28%), muscle (23%), heart (25%), liver (24%), and kidney mass (26%) were observed (all P , 0.05). Relative loss in organ mass was significantly higher (P , 0.01) than was the change in low metabolically active FFM components (muscle, bone, and residual mass). After weight loss, REEm 2 REEc decreased from 0.24 6 0.58 to 0.01 6 0.44 MJ/d (P = 0.01) and correlated with the decrease in free triiodothyronine concentrations (r = 0.33, P , 0.05). Women with high adaptive thermogenesis (defined as REEm 2 REEc , 20.17 MJ/d) had less weight loss and conserved FFM, liver, and kidney mass. Conclusions: After weight loss, almost 50% of the decrease in REEm was explained by losses in FFM and FM. The variability in REEm explained by body composition increased to 60% by also considering the weight of individual organs.Am J Clin Nutr 2009;90:993-1001.

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Influence of methods used in body composition analysis on the prediction of resting energy expenditure

Cited by 98 publications

References 27 publications

Effects of brief perturbations in energy balance on indices of glucose homeostasis in healthy lean men

Effects of brief perturbations in energy balance on indices of glucose homeostasis in healthy lean men

Functional body composition: insights into the regulation of energy metabolism and some clinical applications

Contribution of individual organ mass loss to weight loss–associated decline in resting energy expenditure

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