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Accuracy of predictive equations for the measurement of resting energy expenditure in older subjects.
Clin Nutr. 2014 Aug; 33(4):613-9.CN

Abstract

BACKGROUND AND AIMS

The measurement of resting energy expenditure (REE) is important to assess individual total energy requirements in older subjects. The validity of REE prediction equations in this population has not been thoroughly evaluated and therefore the main aim of this analysis was to assess the accuracy of REE prediction equations in older subjects.

METHODS

Weight, height and body mass index (BMI) were measured. REE was measured by indirect calorimetry (IC) in 68 older subjects (age: 60-94 years, M/F: 13/55, BMI: 26.3 ± 5.0 kg/m(2)). Measured REE was compared to 14 equations for the calculation of REE estimates. In addition, two novel approaches (Aggregate model and meta-regression equations) for the prediction of REE were evaluated. Paired t test and Bland-Altman method were used to assess the agreement of the equations.

RESULTS

The average measured REE was 1298 ± 264 kcal/day. The equation with the smallest bias was proposed by Muller (Bias ± 2SD = +3 ± 294 kcal/day) whereas the Mifflin equation was associated with the largest error (Bias ± 2SD = -172 ± 282 kcal/day). The Aggregate, Muller, Harris-Benedict and Fredrix equations were characterised by a prediction within ±10% of measured REE in more than 60% of subjects. Of the four algorithms, only the Aggregate equation did not show a significant association of the measurement bias with age, BMI and gender.

CONCLUSIONS

The Aggregate algorithm was characterised by a higher, overall accuracy for the prediction of REE in older subjects and its use should be advocated in older subjects. However, due to the large variability of the estimates, the measurement of REE by IC is still recommended for an accurate assessment of individual REE.

Authors+Show Affiliations

Human Nutrition Research Centre, Institute for Ageing and Health, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne NE4 5PL, UK. Electronic address: mario.siervo@ncl.ac.uk.International Center for the Assessment of Nutritional Status, (ICANS), Department of Food, Environmental and Nutritional Science (DeFENS), Università degli Studi di Milano, Via Colombo 60, 20133 Milano, Italy.International Center for the Assessment of Nutritional Status, (ICANS), Department of Food, Environmental and Nutritional Science (DeFENS), Università degli Studi di Milano, Via Colombo 60, 20133 Milano, Italy.Childhood Nutrition Research Centre, UCL Institute of Child Health, 30 Guilford Street, London WC1N 1EH, UK.Human Nutrition Research Centre, Institute for Ageing and Health, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne NE4 5PL, UK.Human Nutrition and Eating Disorders Research Centre, Department of Public Health, Experimental and Forensic Medicine, University of Pavia, Via Bassi 21, 27100 Pavia, Italy.Human Nutrition and Eating Disorders Research Centre, Department of Public Health, Experimental and Forensic Medicine, University of Pavia, Via Bassi 21, 27100 Pavia, Italy.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't
Validation Study

Language

eng

PubMed ID

24094813

Citation

Siervo, M, et al. "Accuracy of Predictive Equations for the Measurement of Resting Energy Expenditure in Older Subjects." Clinical Nutrition (Edinburgh, Scotland), vol. 33, no. 4, 2014, pp. 613-9.
Siervo M, Bertoli S, Battezzati A, et al. Accuracy of predictive equations for the measurement of resting energy expenditure in older subjects. Clin Nutr. 2014;33(4):613-9.
Siervo, M., Bertoli, S., Battezzati, A., Wells, J. C., Lara, J., Ferraris, C., & Tagliabue, A. (2014). Accuracy of predictive equations for the measurement of resting energy expenditure in older subjects. Clinical Nutrition (Edinburgh, Scotland), 33(4), 613-9. https://doi.org/10.1016/j.clnu.2013.09.009
Siervo M, et al. Accuracy of Predictive Equations for the Measurement of Resting Energy Expenditure in Older Subjects. Clin Nutr. 2014;33(4):613-9. PubMed PMID: 24094813.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Accuracy of predictive equations for the measurement of resting energy expenditure in older subjects. AU - Siervo,M, AU - Bertoli,S, AU - Battezzati,A, AU - Wells,J C, AU - Lara,J, AU - Ferraris,C, AU - Tagliabue,A, Y1 - 2013/09/25/ PY - 2013/04/13/received PY - 2013/07/30/revised PY - 2013/09/17/accepted PY - 2013/10/8/entrez PY - 2013/10/8/pubmed PY - 2015/2/6/medline KW - Ageing KW - Indirect calorimetry KW - Prediction equations KW - Resting energy expenditure SP - 613 EP - 9 JF - Clinical nutrition (Edinburgh, Scotland) JO - Clin Nutr VL - 33 IS - 4 N2 - BACKGROUND AND AIMS: The measurement of resting energy expenditure (REE) is important to assess individual total energy requirements in older subjects. The validity of REE prediction equations in this population has not been thoroughly evaluated and therefore the main aim of this analysis was to assess the accuracy of REE prediction equations in older subjects. METHODS: Weight, height and body mass index (BMI) were measured. REE was measured by indirect calorimetry (IC) in 68 older subjects (age: 60-94 years, M/F: 13/55, BMI: 26.3 ± 5.0 kg/m(2)). Measured REE was compared to 14 equations for the calculation of REE estimates. In addition, two novel approaches (Aggregate model and meta-regression equations) for the prediction of REE were evaluated. Paired t test and Bland-Altman method were used to assess the agreement of the equations. RESULTS: The average measured REE was 1298 ± 264 kcal/day. The equation with the smallest bias was proposed by Muller (Bias ± 2SD = +3 ± 294 kcal/day) whereas the Mifflin equation was associated with the largest error (Bias ± 2SD = -172 ± 282 kcal/day). The Aggregate, Muller, Harris-Benedict and Fredrix equations were characterised by a prediction within ±10% of measured REE in more than 60% of subjects. Of the four algorithms, only the Aggregate equation did not show a significant association of the measurement bias with age, BMI and gender. CONCLUSIONS: The Aggregate algorithm was characterised by a higher, overall accuracy for the prediction of REE in older subjects and its use should be advocated in older subjects. However, due to the large variability of the estimates, the measurement of REE by IC is still recommended for an accurate assessment of individual REE. SN - 1532-1983 UR - https://www.unboundmedicine.com/medline/citation/24094813/Accuracy_of_predictive_equations_for_the_measurement_of_resting_energy_expenditure_in_older_subjects_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S0261-5614(13)00247-1 DB - PRIME DP - Unbound Medicine ER -