Relationship between resting metabolic rate and the composition of the fat-free mass
Although a low resting metabolic rate (RMR) has been shown to be a risk factor for future weight gain, little is known about the mechanisms determining its level. We tested the hypothesis that the composition of the fat-free mass (FFM) is a main determinant of RMR. If this hypothesis is true, a regr...
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Veröffentlicht in: | Metabolism, clinical and experimental clinical and experimental, 1997-10, Vol.46 (10), p.1225-1230 |
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creator | Sparti, Andrea DeLany, James P. de la Bretonne, Jacques A. Sander, Gary E. Bray, George A. |
description | Although a low resting metabolic rate (RMR) has been shown to be a risk factor for future weight gain, little is known about the mechanisms determining its level. We tested the hypothesis that the composition of the fat-free mass (FFM) is a main determinant of RMR. If this hypothesis is true, a regression model including internal organ masses as independent variables should explain a larger fraction of the variance in RMR than is explained using only FFM as a predictor. We measured fat mass by hydrodensitometry, liver and kidney volumes by computed tomography (CT), heart mass by echocardiography, muscle mass by dual-energy x-ray absorptiometry (DEXA), and RMR by calorimetry in 40 subjects. FFM and fat mass explained 83% of the variability in RMR (standard error of the estimate [SEE], 420 kJ/d) in a multiple regression analysis. Combinations of organ and muscle masses performed as well as but not better than stepwise multiple regression models. The fact that the composition of the lean mass could not improve the prediction of RMR in comparison to the traditional FFM-fat mass model suggests that the weight of internal organs is not a main determinant of RMR. This may indicate that the variability in RMR is associated with variation in energy expenditure per kilogram of tissue of the individual organs. |
doi_str_mv | 10.1016/S0026-0495(97)90222-5 |
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We tested the hypothesis that the composition of the fat-free mass (FFM) is a main determinant of RMR. If this hypothesis is true, a regression model including internal organ masses as independent variables should explain a larger fraction of the variance in RMR than is explained using only FFM as a predictor. We measured fat mass by hydrodensitometry, liver and kidney volumes by computed tomography (CT), heart mass by echocardiography, muscle mass by dual-energy x-ray absorptiometry (DEXA), and RMR by calorimetry in 40 subjects. FFM and fat mass explained 83% of the variability in RMR (standard error of the estimate [SEE], 420 kJ/d) in a multiple regression analysis. Combinations of organ and muscle masses performed as well as but not better than stepwise multiple regression models. The fact that the composition of the lean mass could not improve the prediction of RMR in comparison to the traditional FFM-fat mass model suggests that the weight of internal organs is not a main determinant of RMR. This may indicate that the variability in RMR is associated with variation in energy expenditure per kilogram of tissue of the individual organs.</description><identifier>ISSN: 0026-0495</identifier><identifier>EISSN: 1532-8600</identifier><identifier>DOI: 10.1016/S0026-0495(97)90222-5</identifier><identifier>PMID: 9322812</identifier><language>eng</language><publisher>New York, NY: Elsevier Inc</publisher><subject>Adipose Tissue - anatomy & histology ; Adult ; Basal Metabolism ; Biological and medical sciences ; Body Constitution ; Body Height ; Body Weight ; Echocardiography ; Female ; Fundamental and applied biological sciences. 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We tested the hypothesis that the composition of the fat-free mass (FFM) is a main determinant of RMR. If this hypothesis is true, a regression model including internal organ masses as independent variables should explain a larger fraction of the variance in RMR than is explained using only FFM as a predictor. We measured fat mass by hydrodensitometry, liver and kidney volumes by computed tomography (CT), heart mass by echocardiography, muscle mass by dual-energy x-ray absorptiometry (DEXA), and RMR by calorimetry in 40 subjects. FFM and fat mass explained 83% of the variability in RMR (standard error of the estimate [SEE], 420 kJ/d) in a multiple regression analysis. Combinations of organ and muscle masses performed as well as but not better than stepwise multiple regression models. The fact that the composition of the lean mass could not improve the prediction of RMR in comparison to the traditional FFM-fat mass model suggests that the weight of internal organs is not a main determinant of RMR. This may indicate that the variability in RMR is associated with variation in energy expenditure per kilogram of tissue of the individual organs.</description><subject>Adipose Tissue - anatomy & histology</subject><subject>Adult</subject><subject>Basal Metabolism</subject><subject>Biological and medical sciences</subject><subject>Body Constitution</subject><subject>Body Height</subject><subject>Body Weight</subject><subject>Echocardiography</subject><subject>Female</subject><subject>Fundamental and applied biological sciences. 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Psychology</topic><topic>Heart - anatomy & histology</topic><topic>Humans</topic><topic>Intermediate and energetic metabolism</topic><topic>Kidney - anatomy & histology</topic><topic>Liver - anatomy & histology</topic><topic>Male</topic><topic>Metabolisms and neurohumoral controls</topic><topic>Models, Biological</topic><topic>Regression Analysis</topic><topic>Risk Factors</topic><topic>Tomography, X-Ray Computed</topic><topic>Vertebrates: anatomy and physiology, studies on body, several organs or systems</topic><topic>Weight Gain</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sparti, Andrea</creatorcontrib><creatorcontrib>DeLany, James P.</creatorcontrib><creatorcontrib>de la Bretonne, Jacques A.</creatorcontrib><creatorcontrib>Sander, Gary E.</creatorcontrib><creatorcontrib>Bray, George A.</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Metabolism, clinical and experimental</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sparti, Andrea</au><au>DeLany, James P.</au><au>de la Bretonne, Jacques A.</au><au>Sander, Gary E.</au><au>Bray, George A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Relationship between resting metabolic rate and the composition of the fat-free mass</atitle><jtitle>Metabolism, clinical and experimental</jtitle><addtitle>Metabolism</addtitle><date>1997-10-01</date><risdate>1997</risdate><volume>46</volume><issue>10</issue><spage>1225</spage><epage>1230</epage><pages>1225-1230</pages><issn>0026-0495</issn><eissn>1532-8600</eissn><abstract>Although a low resting metabolic rate (RMR) has been shown to be a risk factor for future weight gain, little is known about the mechanisms determining its level. We tested the hypothesis that the composition of the fat-free mass (FFM) is a main determinant of RMR. If this hypothesis is true, a regression model including internal organ masses as independent variables should explain a larger fraction of the variance in RMR than is explained using only FFM as a predictor. We measured fat mass by hydrodensitometry, liver and kidney volumes by computed tomography (CT), heart mass by echocardiography, muscle mass by dual-energy x-ray absorptiometry (DEXA), and RMR by calorimetry in 40 subjects. FFM and fat mass explained 83% of the variability in RMR (standard error of the estimate [SEE], 420 kJ/d) in a multiple regression analysis. Combinations of organ and muscle masses performed as well as but not better than stepwise multiple regression models. The fact that the composition of the lean mass could not improve the prediction of RMR in comparison to the traditional FFM-fat mass model suggests that the weight of internal organs is not a main determinant of RMR. This may indicate that the variability in RMR is associated with variation in energy expenditure per kilogram of tissue of the individual organs.</abstract><cop>New York, NY</cop><pub>Elsevier Inc</pub><pmid>9322812</pmid><doi>10.1016/S0026-0495(97)90222-5</doi><tpages>6</tpages></addata></record> |
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subjects | Adipose Tissue - anatomy & histology Adult Basal Metabolism Biological and medical sciences Body Constitution Body Height Body Weight Echocardiography Female Fundamental and applied biological sciences. Psychology Heart - anatomy & histology Humans Intermediate and energetic metabolism Kidney - anatomy & histology Liver - anatomy & histology Male Metabolisms and neurohumoral controls Models, Biological Regression Analysis Risk Factors Tomography, X-Ray Computed Vertebrates: anatomy and physiology, studies on body, several organs or systems Weight Gain |
title | Relationship between resting metabolic rate and the composition of the fat-free mass |
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