Accuracy of Equations to Predict Basal Metabolic Rate in Older Women

Objective To assess the accuracy of several published equations for predicting basal metabolic rate (BMR) in older women. Design BMR was assessed in 116 healthy, older white women, aged 60 to 82 years, on three successive mornings by indirect calorimetry. Body composition was determined by dual ener...

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Bibliographic Details
Published inJournal of the American Dietetic Association Vol. 95; no. 12; pp. 1387 - 1392
Main Authors TAAFFE, DENNIS R., THOMPSON, JANICE, BUTTERFIELD, GAIL, MARCUS, ROBERT
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.12.1995
Elsevier Science Publishers
Elsevier Limited
Subjects
Absorptiometry, Photon
accuracy
Aged
Aged women
Aged, 80 and over
Aging
Aging - metabolism
Basal Metabolism
Body Composition
Body Weight
Calorimetry, Indirect
elderly nutrition
equations
Female
Humans
MATEMATICAS
MATHEMATIQUE
Measurement
MEDICION
MESURE
Metabolism
METABOLISME
METABOLISMO
Middle Aged
NUTRICION HUMANA
NUTRITION HUMAINE
Older people
PERSONNE AGEE
Physiological aspects
Regression Analysis
Reproducibility of Results
Statistics
TERCERA EDAD
Women
Women's Health
Online AccessGet full text
ISSN0002-8223
2212-2672
1878-3570
2212-2680
DOI10.1016/S0002-8223(95)00366-5

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Abstract Objective To assess the accuracy of several published equations for predicting basal metabolic rate (BMR) in older women. Design BMR was assessed in 116 healthy, older white women, aged 60 to 82 years, on three successive mornings by indirect calorimetry. Body composition was determined by dual energy X-ray absorptiometry or hydrostatic weighing. The measured BMRs were compared with values obtained from eight published prediction equations that used solely, or in various combinations, measures of height, weight, fat-free mass, age, and menopausal status. Statistical analyses performed The root mean squared prediction error (RMSPE) was used to determine how accurately predicted BMR matched actual BMR for each subject. In addition, regression analysis was used to evaluate accuracy of predicted BMR vs directly measured BMR. Results Predicted mean BMR determined using all eight equations was significantly correlated to measured BMR ( P=.0001), accounting for 30% to 52% of the variance of measured BMR. When analyzed by RMSPE, however, the equations of Owen et al (1986), Fredrix et al (1990), and Harris-Benedict (1919) predicted actual BMR for each subject within an average of 116 kcal/day, and the equation of Cunningham (1980) resulted in the largest prediction error at 208 kcal/day. Applications/conclusions The regression equations of Owen et al (1986), which used body weight, Fredrix et al (1990), which used body weight and age, and Harris-Benedict (1919), which used age, weight, and height as variables, were most accurate in predicting BMR in our sample of healthy older women. J Am Diet Assoc. 1995; 95:1387-1392.
AbstractList The accuracy of several published equations for predicting basal metabolic rate (BMR) in older women was assessed. Regression equations of Owen et al, which used body weight, and Fredrix et al, which used body weight and age, were among the most accurate in predicting BMR in healthy older women.
To assess the accuracy of several published equations for predicting basal metabolic rate (BMR) in older women. BMR was assessed in 116 healthy, older white women, aged 60 to 82 years, on three successive mornings by indirect calorimetry. Body composition was determined by dual energy X-ray absorptiometry or hydrostatic weighing. The measured BMRs were compared with values obtained from eight published prediction equations that used solely, or in various combinations, measures of height, weight, fat-free mass, age, and menopausal status. The root mean squared prediction error (RMSPE) was used to determine how accurately predicted BMR matched actual BMR for each subject. In addition, regression analysis was used to evaluate accuracy of predicted BMR vs directly measured BMR. Predicted mean BMR determined using all eight equations was significantly correlated to measured BMR (P = .0001), accounting for 30% to 52% of the variance of measured BMR. When analyzed by RMSPE, however, the equations of Owen et al (1986), Fredrix et al (1990), and Harris-Benedict (1919) predicted actual BMR for each subject within an average of 116 kcal/day, and the equation of Cunningham (1980) resulted in the largest prediction error at 208 kcal/day. The regression equations of Owen et al (1986), which used body weight, Fredrix et al (1990), which used body weight and age, and Harris-Benedict (1919), which used age, weight, and height as variables, were most accurate in predicting BMR in our sample of healthy older women.
To assess the accuracy of several published equations for predicting basal metabolic rate (BMR) in older women.OBJECTIVETo assess the accuracy of several published equations for predicting basal metabolic rate (BMR) in older women.BMR was assessed in 116 healthy, older white women, aged 60 to 82 years, on three successive mornings by indirect calorimetry. Body composition was determined by dual energy X-ray absorptiometry or hydrostatic weighing. The measured BMRs were compared with values obtained from eight published prediction equations that used solely, or in various combinations, measures of height, weight, fat-free mass, age, and menopausal status.DESIGNBMR was assessed in 116 healthy, older white women, aged 60 to 82 years, on three successive mornings by indirect calorimetry. Body composition was determined by dual energy X-ray absorptiometry or hydrostatic weighing. The measured BMRs were compared with values obtained from eight published prediction equations that used solely, or in various combinations, measures of height, weight, fat-free mass, age, and menopausal status.The root mean squared prediction error (RMSPE) was used to determine how accurately predicted BMR matched actual BMR for each subject. In addition, regression analysis was used to evaluate accuracy of predicted BMR vs directly measured BMR.STATISTICAL ANALYSES PERFORMEDThe root mean squared prediction error (RMSPE) was used to determine how accurately predicted BMR matched actual BMR for each subject. In addition, regression analysis was used to evaluate accuracy of predicted BMR vs directly measured BMR.Predicted mean BMR determined using all eight equations was significantly correlated to measured BMR (P = .0001), accounting for 30% to 52% of the variance of measured BMR. When analyzed by RMSPE, however, the equations of Owen et al (1986), Fredrix et al (1990), and Harris-Benedict (1919) predicted actual BMR for each subject within an average of 116 kcal/day, and the equation of Cunningham (1980) resulted in the largest prediction error at 208 kcal/day.RESULTSPredicted mean BMR determined using all eight equations was significantly correlated to measured BMR (P = .0001), accounting for 30% to 52% of the variance of measured BMR. When analyzed by RMSPE, however, the equations of Owen et al (1986), Fredrix et al (1990), and Harris-Benedict (1919) predicted actual BMR for each subject within an average of 116 kcal/day, and the equation of Cunningham (1980) resulted in the largest prediction error at 208 kcal/day.The regression equations of Owen et al (1986), which used body weight, Fredrix et al (1990), which used body weight and age, and Harris-Benedict (1919), which used age, weight, and height as variables, were most accurate in predicting BMR in our sample of healthy older women.APPLICATIONS/CONCLUSIONSThe regression equations of Owen et al (1986), which used body weight, Fredrix et al (1990), which used body weight and age, and Harris-Benedict (1919), which used age, weight, and height as variables, were most accurate in predicting BMR in our sample of healthy older women.
Objective To assess the accuracy of several published equations for predicting basal metabolic rate (BMR) in older women. Design BMR was assessed in 116 healthy, older white women, aged 60 to 82 years, on three successive mornings by indirect calorimetry. Body composition was determined by dual energy X-ray absorptiometry or hydrostatic weighing. The measured BMRs were compared with values obtained from eight published prediction equations that used solely, or in various combinations, measures of height, weight, fat-free mass, age, and menopausal status. Statistical analyses performed The root mean squared prediction error (RMSPE) was used to determine how accurately predicted BMR matched actual BMR for each subject. In addition, regression analysis was used to evaluate accuracy of predicted BMR vs directly measured BMR. Results Predicted mean BMR determined using all eight equations was significantly correlated to measured BMR ( P=.0001), accounting for 30% to 52% of the variance of measured BMR. When analyzed by RMSPE, however, the equations of Owen et al (1986), Fredrix et al (1990), and Harris-Benedict (1919) predicted actual BMR for each subject within an average of 116 kcal/day, and the equation of Cunningham (1980) resulted in the largest prediction error at 208 kcal/day. Applications/conclusions The regression equations of Owen et al (1986), which used body weight, Fredrix et al (1990), which used body weight and age, and Harris-Benedict (1919), which used age, weight, and height as variables, were most accurate in predicting BMR in our sample of healthy older women. J Am Diet Assoc. 1995; 95:1387-1392.
Objective: To assess the accuracy of several published equations for predicting basal metabolic rate (BMR) in older women. Design: BMR was assessed in 116 healthy, older white women, aged 60 to 82 years, on three successive mornings by indirect calorimetry. Body composition was determined by dual energy X-ray absorptiometry or hydrostatic weighing. The measured BMRs were compared with values obtained from eight published prediction equations that used solely, or in various combinations, measures of height, weight, fat-free mass, age, and menopausal status. Statistical analyses performed: The root mean squared prediction error (RMSPE) was used to determine how accurately predicted BMR matched actual BMR for each subject. In addition, regression analysis was used to evaluate accuracy of predicted BMR vs directly measured BMR. Results: Predicted mean BMR determined using all eight equations was significantly correlated to measured BMR (P=.0001), accounting for 30% to 52% of the variance of measured BMR. When analyzed by RMSPE, however, the equations of Owen et al (1986), Fredix et al (1990), and Harris-Benedict (1919) predicted actual BMR for each subject within an average of 116 kcal/day, and the equation of Cunningham (1980) resulted in the largest prediction error at 208 kcal/day. Applications/conclusions: The regression equations of Owen et al (1986), which used body weight, Fredrix et al (1990), which used body weight and age, and Harris-Benedict (1919), which used age, weight, and height as variables, were most accurate in predicting BMR in our sample of healthy older women.
Objective: To assess the accuracy of several published equations for predicting basal metabolic rate (BMR) in older women. Design: BMR was assessed in 116 healthy, older white women, aged 60 to 82 years, on three successive mornings by indirect calorimetry. Body composition was determined by dual energy X-ray absorptiometry or hydrostatic weighing. The measured BMRs were compared with values obtained from eight published prediction equations that used solely, or in various combinations, measures of height, weight, fat-free mass, age, and menopausal status. Statistical analyses performed: The root mean squared prediction error (RMSPE) was used to determine how accurately predicted BMR matched actual BMR for each subject. In addition, regression analysis was used to evaluate accuracy of predicted BMR vs directly measured BMR. Results: Predicted mean BMR determined using all eight equations was significantly correlated to measured BMR (P=.0001), accounting for 30% to 52% of the variance of measured BMR. When analyzed by RMSPE, however, the equations of Owen et al (1986), Fredix et al (1990), and Harris-Benedict (1919) predicted actual BMR for each subject within an average of 116 kcal/day, and the equation of Cunningham (1980) resulted in the largest prediction error at 208 kcal/day. Applications/conclusions: The regression equations of Owen et al (1986), which used body weight, Fredrix et al (1990), which used body weight and age, and Harris-Benedict (1919), which used age, weight, and height as variables, were most accurate in predicting BMR in our sample of healthy older women
Audience Professional
Academic
Author THOMPSON, JANICE
TAAFFE, DENNIS R.
BUTTERFIELD, GAIL
MARCUS, ROBERT
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  organization: D. R. Taaffe is a postdoctoral fellow, G. Butterfield is the director of nutrition studies, and R. Marcus is the director, the Aging Study Unit of the Geriatric Research, Education and Clinical Center, Veterans Affairs Medical Center, Palo Alto, Calif, USA
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  fullname: THOMPSON, JANICE
  organization: At the time of the study, J. Thompson was a postdoctoral fellow at the Veterans Affairs Medical Center. Currently, she is an assistant professor with the Department of Health Promotion and Kinesiology, University of North Carolina, Charlotte, USA
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  givenname: GAIL
  surname: BUTTERFIELD
  fullname: BUTTERFIELD, GAIL
  organization: D. R. Taaffe is a postdoctoral fellow, G. Butterfield is the director of nutrition studies, and R. Marcus is the director, the Aging Study Unit of the Geriatric Research, Education and Clinical Center, Veterans Affairs Medical Center, Palo Alto, Calif, USA
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  organization: D. R. Taaffe is a postdoctoral fellow, G. Butterfield is the director of nutrition studies, and R. Marcus is the director, the Aging Study Unit of the Geriatric Research, Education and Clinical Center, Veterans Affairs Medical Center, Palo Alto, Calif, USA
BackLink https://www.ncbi.nlm.nih.gov/pubmed/7594140$$D View this record in MEDLINE/PubMed
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Cites_doi 10.1093/ajcn/45.6.1420
10.1152/jappl.1969.27.1.96
10.1093/ajcn/51.2.241
10.1113/jphysiol.1949.sp004363
10.1093/ajcn/54.6.963
10.1016/0002-8223(93)92043-W
10.1093/ajcn/46.6.875
10.1249/00005768-199503000-00010
10.1093/ajcn/42.6.1170
10.1093/ajcn/55.3.626
10.1111/j.1532-5415.1993.tb06946.x
10.1093/ajcn/44.1.1
10.1152/jappl.1992.72.5.1741
10.1093/ajcn/58.2.141
10.1093/ajcn/33.11.2372
10.1093/ajcn/50.4.731
ContentType Journal Article
Copyright 1995 American Dietetic Association
COPYRIGHT 1995 Elsevier Science Publishers
Copyright American Dietetic Association Dec 1995
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References Heshka, Feld, Yang, Allison, Heymsfield (BIB5) 1993; 93
Butterfield, Gates, Fleming, Brooks, Sutton, Reeves (BIB6) 1992; 72
Turley, McBride, Wilmore (BIB19) 1993; 58
Soares, Sheela, Kurpacl, Kulkarni, Shetty (BIB21) 1989; 50
Cunningham (BIB14) 1980; 33
Mifflin, St Jeor, Hill, Scott, Daugherty, Koh (BIB1) 1990; 51
Owen, Kavle, Owen, Polansky, Caprio, Mozzoli, Kendrick, Bushman, Boden (BIB3) 1986; 44
Thompson, Manore, Skinner, Ravussin, Spraul (BIB18) 1995; 27
Segal (BIB20) 1987; 45
Arciero, Goran, Gardner, Ades, Tyzbir, Poehlman (BIB2) 1993; 41
Berke, Gardner, Goran, Poehlman (BIB17) 1992; 55
Siri (BIB10) 1956; vol 4
Fredrix, Soeters, Deerenberg, Kester, von Meyenfeldt, Saris (BIB13) 1990; 44
Owen, Holup, DAlessio, Craig, Polansky, Smalley, Kvale, Bushman, Owen, Mozzoli, Kendrick, Boden (BIB4) 1987; 46
Holloway, Butterfield, Hintz, Gesundheit, Marcus (BIB7) 1994; 79
Wilmore (BIB9) 1969; 27
Weir (BIB8) 1949; 109
Cunningham (BIB15) 1991; 54
Harris, Benedict (BIB11) 1919
(BIB12) 1985
Daly, Heymsfield, Head, Harvey, Nixon, Katzeff, Grossman (BIB16) 1985; 42
Cunningham (10.1016/S0002-8223(95)00366-5_BIB14) 1980; 33
Turley (10.1016/S0002-8223(95)00366-5_BIB19) 1993; 58
Wilmore (10.1016/S0002-8223(95)00366-5_BIB9) 1969; 27
Siri (10.1016/S0002-8223(95)00366-5_BIB10) 1956; vol 4
(10.1016/S0002-8223(95)00366-5_BIB12) 1985
Owen (10.1016/S0002-8223(95)00366-5_BIB4) 1987; 46
Butterfield (10.1016/S0002-8223(95)00366-5_BIB6) 1992; 72
Arciero (10.1016/S0002-8223(95)00366-5_BIB2) 1993; 41
Cunningham (10.1016/S0002-8223(95)00366-5_BIB15) 1991; 54
Berke (10.1016/S0002-8223(95)00366-5_BIB17) 1992; 55
Weir (10.1016/S0002-8223(95)00366-5_BIB8) 1949; 109
Holloway (10.1016/S0002-8223(95)00366-5_BIB7) 1994; 79
Thompson (10.1016/S0002-8223(95)00366-5_BIB18) 1995; 27
Heshka (10.1016/S0002-8223(95)00366-5_BIB5) 1993; 93
Mifflin (10.1016/S0002-8223(95)00366-5_BIB1) 1990; 51
Soares (10.1016/S0002-8223(95)00366-5_BIB21) 1989; 50
Daly (10.1016/S0002-8223(95)00366-5_BIB16) 1985; 42
Harris (10.1016/S0002-8223(95)00366-5_BIB11) 1919
Fredrix (10.1016/S0002-8223(95)00366-5_BIB13) 1990; 44
Owen (10.1016/S0002-8223(95)00366-5_BIB3) 1986; 44
Segal (10.1016/S0002-8223(95)00366-5_BIB20) 1987; 45
References_xml – volume: 46
  start-page: 875
  year: 1987
  end-page: 885
  ident: BIB4
  article-title: A reappraisal of the caloric requirements of men
  publication-title: Am J Clin Nutr.
– volume: 44
  start-page: 741
  year: 1990
  end-page: 747
  ident: BIB13
  article-title: Resting and sleeping energy expenditure in the elderly
  publication-title: Eur J Clin Nutr.
– volume: 27
  start-page: 347
  year: 1995
  end-page: 354
  ident: BIB18
  article-title: Daily energy expenditure in male endurance athletes with differing energy intakes
  publication-title: Med Sci Sports Exerc.
– volume: 41
  start-page: 389
  year: 1993
  end-page: 395
  ident: BIB2
  article-title: A practical equation to predict resting metabolic rate in older females
  publication-title: J Am Geriatr Soc.
– volume: 72
  start-page: 1741
  year: 1992
  end-page: 1748
  ident: BIB6
  article-title: Increased energy intake minimizes weight loss in men at high altitude
  publication-title: J Appl Physiol
– volume: 42
  start-page: 1170
  year: 1985
  end-page: 1174
  ident: BIB16
  article-title: Human energy requirements
  publication-title: Am J Clin Nutr.
– volume: 33
  start-page: 2372
  year: 1980
  end-page: 2374
  ident: BIB14
  article-title: A reanalysis of the factors influencing basal metabolic rate in normal adults
  publication-title: Am J Clin Nutr.
– volume: 44
  start-page: 1
  year: 1986
  end-page: 19
  ident: BIB3
  article-title: A reappraisal of the caloric requirements of women
  publication-title: Am J Clin Nutr.
– volume: 27
  start-page: 96
  year: 1969
  end-page: 100
  ident: BIB9
  article-title: A simplified method for the determination of residual lung volume
  publication-title: J Appl Physiol.
– volume: vol 4
  start-page: 239
  year: 1956
  end-page: 280
  ident: BIB10
  article-title: Gross composition of the body
  publication-title: Advances in Biological, Medical Physics.
– year: 1919
  ident: BIB11
  publication-title: Biometric Studies of Basal Metabolism in Man
– volume: 45
  start-page: 1420
  year: 1987
  end-page: 1423
  ident: BIB20
  article-title: Comparison of indirect calorimetric measurements of resting energy expenditure with a ventilated hood, face mask, and mouthpiece
  publication-title: Am J Clin Nutr.
– volume: 54
  start-page: 963
  year: 1991
  end-page: 969
  ident: BIB15
  article-title: Body composition as a determinant of energy expenditure
  publication-title: Am J Clin Nutr.
– volume: 51
  start-page: 241
  year: 1990
  end-page: 247
  ident: BIB1
  article-title: A new predictive equation for resting energy expenditure in healthy individuals
  publication-title: Am J Clin Nutr.
– year: 1985
  ident: BIB12
  publication-title: Energy and Protein Requirements
– volume: 50
  start-page: 731
  year: 1989
  end-page: 736
  ident: BIB21
  article-title: The influence of different methods on basal metabolic rate measurements in human subjects
  publication-title: Am J Clin Nutr.
– volume: 58
  start-page: 141
  year: 1993
  end-page: 144
  ident: BIB19
  article-title: Resting metabolic rate measured after subjects spent the night at home vs at a clinic
  publication-title: Am J Clin Nutr.
– volume: 79
  start-page: 470
  year: 1994
  end-page: 480
  ident: BIB7
  article-title: Effect of recombinant human growth hormone on metabolic indices, body composition, and bone turnover in healthy elderly women
  publication-title: J Clin Endocrinol Melab.
– volume: 93
  start-page: 1031
  year: 1993
  end-page: 1036
  ident: BIB5
  article-title: Resting energy expenditure in the obese
  publication-title: J Am Diet Assoc.
– volume: 109
  start-page: 1
  year: 1949
  end-page: 9
  ident: BIB8
  article-title: New method for calculating metabolic rate with special reference to protein metabolism
  publication-title: J Physiol.
– volume: 55
  start-page: 626
  year: 1992
  end-page: 629
  ident: BIB17
  article-title: Effect of pretesting environment on resting metabolic rate measurements
  publication-title: Am J Clin Nutr.
– year: 1985
  ident: 10.1016/S0002-8223(95)00366-5_BIB12
– volume: 45
  start-page: 1420
  year: 1987
  ident: 10.1016/S0002-8223(95)00366-5_BIB20
  article-title: Comparison of indirect calorimetric measurements of resting energy expenditure with a ventilated hood, face mask, and mouthpiece
  publication-title: Am J Clin Nutr.
  doi: 10.1093/ajcn/45.6.1420
– volume: 27
  start-page: 96
  year: 1969
  ident: 10.1016/S0002-8223(95)00366-5_BIB9
  article-title: A simplified method for the determination of residual lung volume
  publication-title: J Appl Physiol.
  doi: 10.1152/jappl.1969.27.1.96
– volume: 51
  start-page: 241
  year: 1990
  ident: 10.1016/S0002-8223(95)00366-5_BIB1
  article-title: A new predictive equation for resting energy expenditure in healthy individuals
  publication-title: Am J Clin Nutr.
  doi: 10.1093/ajcn/51.2.241
– volume: 109
  start-page: 1
  year: 1949
  ident: 10.1016/S0002-8223(95)00366-5_BIB8
  article-title: New method for calculating metabolic rate with special reference to protein metabolism
  publication-title: J Physiol.
  doi: 10.1113/jphysiol.1949.sp004363
– volume: 54
  start-page: 963
  year: 1991
  ident: 10.1016/S0002-8223(95)00366-5_BIB15
  article-title: Body composition as a determinant of energy expenditure
  publication-title: Am J Clin Nutr.
  doi: 10.1093/ajcn/54.6.963
– volume: 93
  start-page: 1031
  year: 1993
  ident: 10.1016/S0002-8223(95)00366-5_BIB5
  article-title: Resting energy expenditure in the obese
  publication-title: J Am Diet Assoc.
  doi: 10.1016/0002-8223(93)92043-W
– year: 1919
  ident: 10.1016/S0002-8223(95)00366-5_BIB11
– volume: 44
  start-page: 741
  year: 1990
  ident: 10.1016/S0002-8223(95)00366-5_BIB13
  article-title: Resting and sleeping energy expenditure in the elderly
  publication-title: Eur J Clin Nutr.
– volume: vol 4
  start-page: 239
  year: 1956
  ident: 10.1016/S0002-8223(95)00366-5_BIB10
  article-title: Gross composition of the body
– volume: 46
  start-page: 875
  year: 1987
  ident: 10.1016/S0002-8223(95)00366-5_BIB4
  article-title: A reappraisal of the caloric requirements of men
  publication-title: Am J Clin Nutr.
  doi: 10.1093/ajcn/46.6.875
– volume: 27
  start-page: 347
  year: 1995
  ident: 10.1016/S0002-8223(95)00366-5_BIB18
  article-title: Daily energy expenditure in male endurance athletes with differing energy intakes
  publication-title: Med Sci Sports Exerc.
  doi: 10.1249/00005768-199503000-00010
– volume: 42
  start-page: 1170
  year: 1985
  ident: 10.1016/S0002-8223(95)00366-5_BIB16
  article-title: Human energy requirements
  publication-title: Am J Clin Nutr.
  doi: 10.1093/ajcn/42.6.1170
– volume: 55
  start-page: 626
  year: 1992
  ident: 10.1016/S0002-8223(95)00366-5_BIB17
  article-title: Effect of pretesting environment on resting metabolic rate measurements
  publication-title: Am J Clin Nutr.
  doi: 10.1093/ajcn/55.3.626
– volume: 41
  start-page: 389
  year: 1993
  ident: 10.1016/S0002-8223(95)00366-5_BIB2
  article-title: A practical equation to predict resting metabolic rate in older females
  publication-title: J Am Geriatr Soc.
  doi: 10.1111/j.1532-5415.1993.tb06946.x
– volume: 44
  start-page: 1
  year: 1986
  ident: 10.1016/S0002-8223(95)00366-5_BIB3
  article-title: A reappraisal of the caloric requirements of women
  publication-title: Am J Clin Nutr.
  doi: 10.1093/ajcn/44.1.1
– volume: 72
  start-page: 1741
  year: 1992
  ident: 10.1016/S0002-8223(95)00366-5_BIB6
  article-title: Increased energy intake minimizes weight loss in men at high altitude
  publication-title: J Appl Physiol
  doi: 10.1152/jappl.1992.72.5.1741
– volume: 58
  start-page: 141
  year: 1993
  ident: 10.1016/S0002-8223(95)00366-5_BIB19
  article-title: Resting metabolic rate measured after subjects spent the night at home vs at a clinic
  publication-title: Am J Clin Nutr.
  doi: 10.1093/ajcn/58.2.141
– volume: 79
  start-page: 470
  year: 1994
  ident: 10.1016/S0002-8223(95)00366-5_BIB7
  article-title: Effect of recombinant human growth hormone on metabolic indices, body composition, and bone turnover in healthy elderly women
  publication-title: J Clin Endocrinol Melab.
– volume: 33
  start-page: 2372
  year: 1980
  ident: 10.1016/S0002-8223(95)00366-5_BIB14
  article-title: A reanalysis of the factors influencing basal metabolic rate in normal adults
  publication-title: Am J Clin Nutr.
  doi: 10.1093/ajcn/33.11.2372
– volume: 50
  start-page: 731
  year: 1989
  ident: 10.1016/S0002-8223(95)00366-5_BIB21
  article-title: The influence of different methods on basal metabolic rate measurements in human subjects
  publication-title: Am J Clin Nutr.
  doi: 10.1093/ajcn/50.4.731
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Snippet Objective To assess the accuracy of several published equations for predicting basal metabolic rate (BMR) in older women. Design BMR was assessed in 116...
Objective: To assess the accuracy of several published equations for predicting basal metabolic rate (BMR) in older women. Design: BMR was assessed in 116...
To assess the accuracy of several published equations for predicting basal metabolic rate (BMR) in older women. BMR was assessed in 116 healthy, older white...
The accuracy of several published equations for predicting basal metabolic rate (BMR) in older women was assessed. Regression equations of Owen et al, which...
To assess the accuracy of several published equations for predicting basal metabolic rate (BMR) in older women.OBJECTIVETo assess the accuracy of several...
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SubjectTerms Absorptiometry, Photon
accuracy
Aged
Aged women
Aged, 80 and over
Aging
Aging - metabolism
Basal Metabolism
Body Composition
Body Weight
Calorimetry, Indirect
elderly nutrition
equations
Female
Humans
MATEMATICAS
MATHEMATIQUE
Measurement
MEDICION
MESURE
Metabolism
METABOLISME
METABOLISMO
Middle Aged
NUTRICION HUMANA
NUTRITION HUMAINE
Older people
PERSONNE AGEE
Physiological aspects
Regression Analysis
Reproducibility of Results
Statistics
TERCERA EDAD
Women
Women's Health
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Title Accuracy of Equations to Predict Basal Metabolic Rate in Older Women
URI https://dx.doi.org/10.1016/S0002-8223(95)00366-5
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