Development of bioelectrical impedance-derived indices of fat and fat-free mass for assessment of nutritional status in childhood [Corrigendum: 2008 May, v. 62, issue 5, p. 686.]
Objectives: (1) To develop a method of manipulating bioelectrical impedance (BIA) that gives indices of lean and fat adjusted for body size, using a large normative cohort of children. (2) To assess the discriminant validity of the method in a group of children likely to have abnormal body compositi...
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| Published in | European journal of clinical nutrition Vol. 62; no. 2; pp. 210 - 217 |
|---|---|
| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Nature Publishing Group UK
01.02.2008
Nature Publishing Nature Publishing Group |
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| Online Access | Get full text |
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| Abstract | Objectives: (1) To develop a method of manipulating bioelectrical impedance (BIA) that gives indices of lean and fat adjusted for body size, using a large normative cohort of children. (2) To assess the discriminant validity of the method in a group of children likely to have abnormal body composition. Design: Two prospective cohort studies. Setting: Normative data: Avon Longitudinal Study of Parents and Children (ALSPAC), population based cohort; proof of concept study: tertiary feeding clinic and special needs schools. Subjects: Normative data: 7576 children measured aged between 7.25 and 8.25 (mean 7.5) (s.d.=0.2) years; proof of concept study: 29 children with either major neurodisability or receiving artificial feeding, or both, mean age 7.6 (s.d.=2) years. Measures: Leg-to-leg (Z(T)) and arm-to-leg (Z(B)) BIA, weight and height. Total body water (TBW) was estimated from the resistance index (RI=height2/Z), and fat-free mass was linearly related to TBW. Fat mass was obtained by subtracting fat-free mass from total weight. Fat-free mass was log-transformed and the reciprocal transform was taken for fat mass to satisfy parametric model assumptions. Lean and fat mass were then adjusted for height and age using multiple linear regression models. The resulting standardized residuals gave the lean index and fat index, respectively. Results: In the normative cohort, the lean index was higher and fat index lower in boys. The lean index rose steeply to the middle of the normal range of body mass index (BMI) and then slowly for higher BMI values, whereas the fat index rose linearly through and above the normal range. In the proof of concept study, the children as a group had low lean indices (mean (s.d.) -1.5 (1.7)) with average fat indices (+0.21 (2.0)) despite relatively low BMI standard deviation scores (-0.60 (2.3)), but for any given BMI, individual children had extremely wide ranges of fat indices. The lean index proved more stable and repeatable than BMI. Conclusions: This clinical method of handling BIA reveals important variations in nutritional status that would not be detected using anthropometry alone. BIA used in this way would allow more accurate assessment of energy sufficiency in children with neurodisability and may provide a more valid identification of children at risk of underweight or obesity in field and clinical settings. |
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| AbstractList | Objectives: (1) To develop a method of manipulating bioelectrical impedance (BIA) that gives indices of lean and fat adjusted for body size, using a large normative cohort of children. (2) To assess the discriminant validity of the method in a group of children likely to have abnormal body composition. Design: Two prospective cohort studies. Setting: Normative data: Avon Longitudinal Study of Parents and Children (ALSPAC), population based cohort; proof of concept study: tertiary feeding clinic and special needs schools. Subjects: Normative data: 7576 children measured aged between 7.25 and 8.25 (mean 7.5) (s.d.=0.2) years; proof of concept study: 29 children with either major neurodisability or receiving artificial feeding, or both, mean age 7.6 (s.d.=2) years. Measures: Leg-to-leg (Z(T)) and arm-to-leg (Z(B)) BIA, weight and height. Total body water (TBW) was estimated from the resistance index (RI=height2/Z), and fat-free mass was linearly related to TBW. Fat mass was obtained by subtracting fat-free mass from total weight. Fat-free mass was log-transformed and the reciprocal transform was taken for fat mass to satisfy parametric model assumptions. Lean and fat mass were then adjusted for height and age using multiple linear regression models. The resulting standardized residuals gave the lean index and fat index, respectively. Results: In the normative cohort, the lean index was higher and fat index lower in boys. The lean index rose steeply to the middle of the normal range of body mass index (BMI) and then slowly for higher BMI values, whereas the fat index rose linearly through and above the normal range. In the proof of concept study, the children as a group had low lean indices (mean (s.d.) -1.5 (1.7)) with average fat indices (+0.21 (2.0)) despite relatively low BMI standard deviation scores (-0.60 (2.3)), but for any given BMI, individual children had extremely wide ranges of fat indices. The lean index proved more stable and repeatable than BMI. Conclusions: This clinical method of handling BIA reveals important variations in nutritional status that would not be detected using anthropometry alone. BIA used in this way would allow more accurate assessment of energy sufficiency in children with neurodisability and may provide a more valid identification of children at risk of underweight or obesity in field and clinical settings. Objectives: (1) To develop a method of manipulating bioelectrical impedance (BIA) that gives indices of lean and fat adjusted for body size, using a large normative cohort of children. (2) To assess the discriminant validity of the method in a group of children likely to have abnormal body composition. Design: Two prospective cohort studies. Setting: Normative data: Avon Longitudinal Study of Parents and Children (ALSPAC), population based cohort; proof of concept study: tertiary feeding clinic and special needs schools. Subjects: Normative data: 7576 children measured aged between 7.25 and 8.25 (mean 7.5) (s.d.=0.2) years; proof of concept study: 29 children with either major neurodisability or receiving artificial feeding, or both, mean age 7.6 (s.d.=2) years. Measures: Leg-to-leg ( Z T ) and arm-to-leg ( Z B ) BIA, weight and height. Total body water (TBW) was estimated from the resistance index (RI=height 2 / Z ), and fat-free mass was linearly related to TBW. Fat mass was obtained by subtracting fat-free mass from total weight. Fat-free mass was log-transformed and the reciprocal transform was taken for fat mass to satisfy parametric model assumptions. Lean and fat mass were then adjusted for height and age using multiple linear regression models. The resulting standardized residuals gave the lean index and fat index, respectively. Results: In the normative cohort, the lean index was higher and fat index lower in boys. The lean index rose steeply to the middle of the normal range of body mass index (BMI) and then slowly for higher BMI values, whereas the fat index rose linearly through and above the normal range. In the proof of concept study, the children as a group had low lean indices (mean (s.d.) −1.5 (1.7)) with average fat indices (+0.21 (2.0)) despite relatively low BMI standard deviation scores (−0.60 (2.3)), but for any given BMI, individual children had extremely wide ranges of fat indices. The lean index proved more stable and repeatable than BMI. Conclusions: This clinical method of handling BIA reveals important variations in nutritional status that would not be detected using anthropometry alone. BIA used in this way would allow more accurate assessment of energy sufficiency in children with neurodisability and may provide a more valid identification of children at risk of underweight or obesity in field and clinical settings. Objectives: (1) To develop a method of manipulating bioelectrical impedance (BIA) that gives indices of lean and fat adjusted for body size, using a large normative cohort of children. (2) To assess the discriminant validity of the method in a group of children likely to have abnormal body composition. Design: Two prospective cohort studies. Setting: Normative data: Avon Longitudinal Study of Parents and Children (ALSPAC), population based cohort; proof of concept study: tertiary feeding clinic and special needs schools. Subjects: Normative data: 7576 children measured aged between 7.25 and 8.25 (mean 7.5) (s.d.=0.2) years; proof of concept study: 29 children with either major neurodisability or receiving artificial feeding, or both, mean age 7.6 (s.d.=2) years. Measures: Leg-to-leg (Z (T)) and arm-to-leg (Z (B)) BIA, weight and height. Total body water (TBW) was estimated from the resistance index (RI=height(2)/Z), and fat-free mass was linearly related to TBW. Fat mass was obtained by subtracting fat-free mass from total weight. Fat-free mass was log-transformed and the reciprocal transform was taken for fat mass to satisfy parametric model assumptions. Lean and fat mass were then adjusted for height and age using multiple linear regression models. The resulting standardized residuals gave the lean index and fat index, respectively .Results: In the normative cohort, the lean index was higher and fat index lower in boys. The lean index rose steeply to the middle of the normal range of body mass index (BMI) and then slowly for higher BMI values, whereas the fat index rose linearly through and above the normal range. In the proof of concept study, the children as a group had low lean indices (mean (s.d.) -1.5 (1.7)) with average fat indices (+0.21 (2.0)) despite relatively low BMI standard deviation scores (-0.60 (2.3)), but for any given BMI, individual children had extremely wide ranges of fat indices. The lean index proved more stable and repeatable than BMI. Conclusions: This clinical method of handling BIA reveals important variations in nutritional status that would not be detected using anthropometry alone. BIA used in this way would allow more accurate assessment of energy sufficiency in children with neurodisability and may provide a more valid identification of children at risk of underweight or obesity in field and clinical settings. [PUBLICATION ABSTRACT] (1) To develop a method of manipulating bioelectrical impedance (BIA) that gives indices of lean and fat adjusted for body size, using a large normative cohort of children. (2) To assess the discriminant validity of the method in a group of children likely to have abnormal body composition. Two prospective cohort studies. Normative data: Avon Longitudinal Study of Parents and Children (ALSPAC), population based cohort; proof of concept study: tertiary feeding clinic and special needs schools. Normative data: 7576 children measured aged between 7.25 and 8.25 (mean 7.5) (s.d.=0.2) years; proof of concept study: 29 children with either major neurodisability or receiving artificial feeding, or both, mean age 7.6 (s.d.=2) years. Leg-to-leg (Z (T)) and arm-to-leg (Z (B)) BIA, weight and height. Total body water (TBW) was estimated from the resistance index (RI=height(2)/Z), and fat-free mass was linearly related to TBW. Fat mass was obtained by subtracting fat-free mass from total weight. Fat-free mass was log-transformed and the reciprocal transform was taken for fat mass to satisfy parametric model assumptions. Lean and fat mass were then adjusted for height and age using multiple linear regression models. The resulting standardized residuals gave the lean index and fat index, respectively. In the normative cohort, the lean index was higher and fat index lower in boys. The lean index rose steeply to the middle of the normal range of body mass index (BMI) and then slowly for higher BMI values, whereas the fat index rose linearly through and above the normal range. In the proof of concept study, the children as a group had low lean indices (mean (s.d.) -1.5 (1.7)) with average fat indices (+0.21 (2.0)) despite relatively low BMI standard deviation scores (-0.60 (2.3)), but for any given BMI, individual children had extremely wide ranges of fat indices. The lean index proved more stable and repeatable than BMI. This clinical method of handling BIA reveals important variations in nutritional status that would not be detected using anthropometry alone. BIA used in this way would allow more accurate assessment of energy sufficiency in children with neurodisability and may provide a more valid identification of children at risk of underweight or obesity in field and clinical settings. Objectives:(1) To develop a method of manipulating bioelectrical impedance (BIA) that gives indices of lean and fat adjusted for body size, using a large normative cohort of children. (2) To assess the discriminant validity of the method in a group of children likely to have abnormal body composition.Design:Two prospective cohort studies.Setting:Normative data: Avon Longitudinal Study of Parents and Children (ALSPAC), population based cohort; proof of concept study: tertiary feeding clinic and special needs schools.Subjects:Normative data: 7576 children measured aged between 7.25 and 8.25 (mean 7.5) (s.d.=0.2) years; proof of concept study: 29 children with either major neurodisability or receiving artificial feeding, or both, mean age 7.6 (s.d.=2) years.Measures:Leg-to-leg (Z sub(T)) and arm-to-leg (Z sub(B)) BIA, weight and height. Total body water (TBW) was estimated from the resistance index (RI=height super(2)/Z), and fat-free mass was linearly related to TBW. Fat mass was obtained by subtracting fat-free mass from total weight. Fat-free mass was log-transformed and the reciprocal transform was taken for fat mass to satisfy parametric model assumptions. Lean and fat mass were then adjusted for height and age using multiple linear regression models. The resulting standardized residuals gave the lean index and fat index, respectively. Results:In the normative cohort, the lean index was higher and fat index lower in boys. The lean index rose steeply to the middle of the normal range of body mass index (BMI) and then slowly for higher BMI values, whereas the fat index rose linearly through and above the normal range. In the proof of concept study, the children as a group had low lean indices (mean (s.d.) -1.5 (1.7)) with average fat indices (+0.21 (2.0)) despite relatively low BMI standard deviation scores (-0.60 (2.3)), but for any given BMI, individual children had extremely wide ranges of fat indices. The lean index proved more stable and repeatable than BMI. Conclusions:This clinical method of handling BIA reveals important variations in nutritional status that would not be detected using anthropometry alone. BIA used in this way would allow more accurate assessment of energy sufficiency in children with neurodisability and may provide a more valid identification of children at risk of underweight or obesity in field and clinical settings.European Journal of Clinical Nutrition (2008) 62, 210-217; doi:10.1038/sj.ejcn.1602714; published online 14 March 2007 OBJECTIVES(1) To develop a method of manipulating bioelectrical impedance (BIA) that gives indices of lean and fat adjusted for body size, using a large normative cohort of children. (2) To assess the discriminant validity of the method in a group of children likely to have abnormal body composition. DESIGNTwo prospective cohort studies. SETTINGNormative data: Avon Longitudinal Study of Parents and Children (ALSPAC), population based cohort; proof of concept study: tertiary feeding clinic and special needs schools. SUBJECTSNormative data: 7576 children measured aged between 7.25 and 8.25 (mean 7.5) (s.d.=0.2) years; proof of concept study: 29 children with either major neurodisability or receiving artificial feeding, or both, mean age 7.6 (s.d.=2) years. MEASURESLeg-to-leg (Z (T)) and arm-to-leg (Z (B)) BIA, weight and height. Total body water (TBW) was estimated from the resistance index (RI=height(2)/Z), and fat-free mass was linearly related to TBW. Fat mass was obtained by subtracting fat-free mass from total weight. Fat-free mass was log-transformed and the reciprocal transform was taken for fat mass to satisfy parametric model assumptions. Lean and fat mass were then adjusted for height and age using multiple linear regression models. The resulting standardized residuals gave the lean index and fat index, respectively. RESULTSIn the normative cohort, the lean index was higher and fat index lower in boys. The lean index rose steeply to the middle of the normal range of body mass index (BMI) and then slowly for higher BMI values, whereas the fat index rose linearly through and above the normal range. In the proof of concept study, the children as a group had low lean indices (mean (s.d.) -1.5 (1.7)) with average fat indices (+0.21 (2.0)) despite relatively low BMI standard deviation scores (-0.60 (2.3)), but for any given BMI, individual children had extremely wide ranges of fat indices. The lean index proved more stable and repeatable than BMI. CONCLUSIONSThis clinical method of handling BIA reveals important variations in nutritional status that would not be detected using anthropometry alone. BIA used in this way would allow more accurate assessment of energy sufficiency in children with neurodisability and may provide a more valid identification of children at risk of underweight or obesity in field and clinical settings. Objectives:(1) To develop a method of manipulating bioelectrical impedance (BIA) that gives indices of lean and fat adjusted for body size, using a large normative cohort of children. (2) To assess the discriminant validity of the method in a group of children likely to have abnormal body composition.Design:Two prospective cohort studies.Setting:Normative data: Avon Longitudinal Study of Parents and Children (ALSPAC), population based cohort; proof of concept study: tertiary feeding clinic and special needs schools.Subjects:Normative data: 7576 children measured aged between 7.25 and 8.25 (mean 7.5) (s.d.=0.2) years; proof of concept study: 29 children with either major neurodisability or receiving artificial feeding, or both, mean age 7.6 (s.d.=2) years.Measures:Leg-to-leg (ZT) and arm-to-leg (ZB) BIA, weight and height. Total body water (TBW) was estimated from the resistance index (RI=height2/Z), and fat-free mass was linearly related to TBW. Fat mass was obtained by subtracting fat-free mass from total weight. Fat-free mass was log-transformed and the reciprocal transform was taken for fat mass to satisfy parametric model assumptions. Lean and fat mass were then adjusted for height and age using multiple linear regression models. The resulting standardized residuals gave the lean index and fat index, respectively.Results:In the normative cohort, the lean index was higher and fat index lower in boys. The lean index rose steeply to the middle of the normal range of body mass index (BMI) and then slowly for higher BMI values, whereas the fat index rose linearly through and above the normal range. In the proof of concept study, the children as a group had low lean indices (mean (s.d.) −1.5 (1.7)) with average fat indices (+0.21 (2.0)) despite relatively low BMI standard deviation scores (−0.60 (2.3)), but for any given BMI, individual children had extremely wide ranges of fat indices. The lean index proved more stable and repeatable than BMI.Conclusions:This clinical method of handling BIA reveals important variations in nutritional status that would not be detected using anthropometry alone. BIA used in this way would allow more accurate assessment of energy sufficiency in children with neurodisability and may provide a more valid identification of children at risk of underweight or obesity in field and clinical settings. |
| Audience | Professional Academic |
| Author | Ward, S.C.G McColl, J.H Wright, C.M Ness, A.R Sherriff, A Reilly, J.J |
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| Copyright | Springer Nature Limited 2008 2008 INIST-CNRS COPYRIGHT 2008 Nature Publishing Group Copyright Nature Publishing Group Feb 2008 Nature Publishing Group 2008. |
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| Keywords | epidemiology fat-free mass body composition bioelectrical impedance child Human Nutrition Lean body mass Metabolic diseases Impedance Child Epidemiology Body composition Nutritional status |
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| PublicationTitle | European journal of clinical nutrition |
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| References | Sullivan, PB, Alder, N, Bachlet, AM, Grant, H, Juszczak, E, Henry, J 2006; 48 Schaefer, F, Georgi, M, Zieger, A, Scharer, K 1994; 35 Lohman, TG 1989; 1 Chad, KE, McKay, HA, Zello, GA, Bailey, DA, Faulkner, RA, Snyder, RE 2000; 42 Bland, J, Altman, D 1995; 346 Houtkooper, LB, Lohman, TG, Going, SB, Howell, WH 1996; 64 Rennie, KL, Livingstone, MB, Wells, JC, McGloin, A, Coward, WA, Prentice, AM 2005; 82 Maynard, LM, Wisemandle, W, Roche, AF, Chumlea, WC, Guo, SS, Siervogel, RM 2001; 107 Wells, JC 2003; 62 Wells, JC, Fuller, NJ, Dewit, O, Fewtrell, MS, Elia, M, Cole, TJ 1999; 69 Liu, LF, Roberts, R, Moyer-Mileur, L, Samson-Fang, L 2005; 105 Stallings, VA, Cronk, CE, Zemel, BS, Charney, EB 1995; 126 Foster, KR, Lukaski, HC 1996; 64 Parker, L, Reilly, JJ, Slater, C, Wells, JC, Pitsiladis, Y 2003; 11 Jebb, SA, Cole, TJ, Doman, D, Murgatroyd, PR, Prentice, AM 2000; 83 Wells, JC, Cole, TJ 2002; 26 Freeman, JV, Cole, TJ, Chinn, S, Jones, PRM, White, EM, Preece, MA 1995; 73 Reilly, J, Wilson, J, McColl, J, Carmichael, M, Durnin, J 1996; 39 Davies, PS, Preece, MA, Hicks, CJ, Halliday, D 1988; 15 Azcue, MP, Zello, GA, Levy, LD, Pencharz, PB 1996; 129 Kushner, RF, Schoeller, DA, Fjeld, CR, Danford, L 1992; 56 Deurenberg, P, Smit, HE, Kusters, CS 1989; 43 Fung, EB, Samson-Fang, L, Stallings, VA, Conaway, M, Liptak, G, Henderson, RC 2002; 102 Goran, MI, Shewchuk, R, Gower, BA, Nagy, TR, Carpenter, WH, Johnson, RK 1998; 67 Golding, J, Pembrey, M, Jones, R 2001; 15 Fomon, S, Haschke, F, Ziegler, E, Nelson, S 1982; 35 Smye, S, Sutcliffe, J, Pitt, E 1993; 14 Smye, Sutcliffe, Pitt (CR22) 1993; 14 Sullivan, Alder, Bachlet, Grant, Juszczak, Henry (CR24) 2006; 48 Deurenberg, Smit, Kusters (CR5) 1989; 43 Fomon, Haschke, Ziegler, Nelson (CR6) 1982; 35 Wells, Cole (CR25) 2002; 26 Jebb, Cole, Doman, Murgatroyd, Prentice (CR13) 2000; 83 Liu, Roberts, Moyer-Mileur, Samson-Fang (CR15) 2005; 105 Schaefer, Georgi, Zieger, Scharer (CR21) 1994; 35 Chad, McKay, Zello, Bailey, Faulkner, Snyder (CR3) 2000; 42 Houtkooper, Lohman, Going, Howell (CR12) 1996; 64 Azcue, Zello, Levy, Pencharz (CR1) 1996; 129 Wells, Fuller, Dewit, Fewtrell, Elia, Cole (CR26) 1999; 69 Maynard, Wisemandle, Roche, Chumlea, Guo, Siervogel (CR17) 2001; 107 Rennie, Livingstone, Wells, McGloin, Coward, Prentice (CR20) 2005; 82 Golding, Pembrey, Jones (CR10) 2001; 15 Freeman, Cole, Chinn, Jones, White, Preece (CR8) 1995; 73 Lohman (CR16) 1989; 1 Goran, Shewchuk, Gower, Nagy, Carpenter, Johnson (CR11) 1998; 67 Stallings, Cronk, Zemel, Charney (CR23) 1995; 126 Parker, Reilly, Slater, Wells, Pitsiladis (CR18) 2003; 11 Reilly, Wilson, McColl, Carmichael, Durnin (CR19) 1996; 39 Wells (CR27) 2003; 62 Bland, Altman (CR2) 1995; 346 Fung, Samson-Fang, Stallings, Conaway, Liptak, Henderson (CR9) 2002; 102 Kushner, Schoeller, Fjeld, Danford (CR14) 1992; 56 Foster, Lukaski (CR7) 1996; 64 Davies, Preece, Hicks, Halliday (CR4) 1988; 15 Eur J Clin Nutr. 2008 May;62(5):686 SA Jebb (BF1602714_CR13) 2000; 83 JC Wells (BF1602714_CR27) 2003; 62 KR Foster (BF1602714_CR7) 1996; 64 RF Kushner (BF1602714_CR14) 1992; 56 S Smye (BF1602714_CR22) 1993; 14 LF Liu (BF1602714_CR15) 2005; 105 P Deurenberg (BF1602714_CR5) 1989; 43 LB Houtkooper (BF1602714_CR12) 1996; 64 PS Davies (BF1602714_CR4) 1988; 15 KE Chad (BF1602714_CR3) 2000; 42 EB Fung (BF1602714_CR9) 2002; 102 JC Wells (BF1602714_CR26) 1999; 69 MI Goran (BF1602714_CR11) 1998; 67 F Schaefer (BF1602714_CR21) 1994; 35 JV Freeman (BF1602714_CR8) 1995; 73 S Fomon (BF1602714_CR6) 1982; 35 VA Stallings (BF1602714_CR23) 1995; 126 MP Azcue (BF1602714_CR1) 1996; 129 LM Maynard (BF1602714_CR17) 2001; 107 J Reilly (BF1602714_CR19) 1996; 39 TG Lohman (BF1602714_CR16) 1989; 1 J Golding (BF1602714_CR10) 2001; 15 KL Rennie (BF1602714_CR20) 2005; 82 J Bland (BF1602714_CR2) 1995; 346 L Parker (BF1602714_CR18) 2003; 11 JC Wells (BF1602714_CR25) 2002; 26 PB Sullivan (BF1602714_CR24) 2006; 48 |
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| Snippet | Objectives: (1) To develop a method of manipulating bioelectrical impedance (BIA) that gives indices of lean and fat adjusted for body size, using a large... Objectives: (1) To develop a method of manipulating bioelectrical impedance (BIA) that gives indices of lean and fat adjusted for body size, using a large... (1) To develop a method of manipulating bioelectrical impedance (BIA) that gives indices of lean and fat adjusted for body size, using a large normative cohort... Objectives:(1) To develop a method of manipulating bioelectrical impedance (BIA) that gives indices of lean and fat adjusted for body size, using a large... OBJECTIVES(1) To develop a method of manipulating bioelectrical impedance (BIA) that gives indices of lean and fat adjusted for body size, using a large... |
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| SubjectTerms | accuracy Adipose Tissue - anatomy & histology Adipose Tissue - metabolism anthropometric measurements Anthropometry Arm Avon Longitudinal Study of Parents and Children bioelectrical impedance Bioelectricity Biological and medical sciences Body Composition Body fat Body Mass Index Body size Body water Body Water - metabolism body weight Body Weight - physiology Child child nutrition Child Nutrition Disorders - diagnosis Children Children & youth Clinical Nutrition Cohort Studies Electric currents Electric Impedance Epidemiology fat free mass Fat-free Fat-free body mass Feeding. Feeding behavior Female Fundamental and applied biological sciences. Psychology Health aspects human diseases Humans Impedance Impedance, Bioelectric Internal Medicine Leg Longitudinal Studies Male Mean Measurement Medical sciences Medicine Medicine & Public Health Metabolic Diseases Muscle, Skeletal - anatomy & histology Muscle, Skeletal - metabolism nervous system diseases Nutrition Nutrition assessment Nutritional Status Obesity original-article Prospective Studies Public Health Regression analysis Regression models Schools Sex Factors Standard deviation Test methods Underweight validity Vertebrates: anatomy and physiology, studies on body, several organs or systems Weight |
| Title | Development of bioelectrical impedance-derived indices of fat and fat-free mass for assessment of nutritional status in childhood [Corrigendum: 2008 May, v. 62, issue 5, p. 686.] |
| URI | http://dx.doi.org/10.1038/sj.ejcn.1602714 https://link.springer.com/article/10.1038/sj.ejcn.1602714 https://www.ncbi.nlm.nih.gov/pubmed/17356557 https://www.proquest.com/docview/219667516 https://www.proquest.com/docview/2642624519 https://search.proquest.com/docview/70274367 https://search.proquest.com/docview/754894911 |
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