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Development and validation of new predictive equations for the resting metabolic rate of older adults aged ≥65 y.
Porter, Judi; Ward, Leigh C; Nguo, Kay; Davidson, Zoe; Gibson, Simone; Prentice, Ross; Neuhouser, Marian L; Truby, Helen.
Affiliation
  • Porter J; Institute of Physical Activity and Nutrition, School of Exercise and Nutrition Science, Deakin University, Burwood, Melbourne, Victoria, Australia. Electronic address: judi.porter@deakin.edu.au.
  • Ward LC; Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Queensland, Australia.
  • Nguo K; Department of Nutrition, Dietetics and Food, Monash University, Notting Hill, Melbourne, Victoria, Australia.
  • Davidson Z; Department of Nutrition, Dietetics and Food, Monash University, Notting Hill, Melbourne, Victoria, Australia.
  • Gibson S; Department of Nutrition, Dietetics and Food, Monash University, Notting Hill, Melbourne, Victoria, Australia.
  • Prentice R; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
  • Neuhouser ML; Fred Hutchinson Cancer Research Center and School of Public Health and Community Medicine, University of Washington, Seattle, Washington, USA.
  • Truby H; School of Human Movement and Nutrition Sciences, The University of Queensland, Brisbane, Queensland, Australia.
Am J Clin Nutr ; 117(6): 1164-1173, 2023 06.
Article in En | MEDLINE | ID: mdl-37054885
ABSTRACT

BACKGROUND:

The aging process alters the resting metabolic rate (RMR), but it still accounts for 50%-70% of the total energy needs. The rising proportion of older adults, especially those over 80 y of age, underpins the need for a simple, rapid method to estimate the energy needs of older adults.

OBJECTIVES:

This research aimed to generate and validate new RMR equations specifically for older adults and to report their performance and accuracy.

METHODS:

Data were sourced to form an international dataset of adults aged ≥65 y (n = 1686, 38.5% male) where RMR was measured using the reference method of indirect calorimetry. Multiple regression was used to predict RMR from age (y), sex, weight (kg), and height (cm). Double cross-validation in a randomized, sex-stratified, age-matched 5050 split and leave one out cross-validation were performed. The newly generated prediction equations were compared with the existing commonly used equations.

RESULTS:

The new prediction equation for males and females aged ≥65 y had an overall improved performance, albeit marginally, when compared with the existing equations. It is described as follows RMR (kJ/d) = 31.524 × W (kg) + 25.851 × H (cm) - 24.432 × Age (y) + 486.268 × Sex (M = 1, F = 0) + 530.557. Equations stratified by age (65-79.9 y and >80 y) and sex are also provided. The newly created equation estimates RMR within a population mean prediction bias of ∼50 kJ/d (∼1%) for those aged ≥65 y. Accuracy was reduced in adults aged ≥80 y (∼100 kJ/d, ∼2%) but was still within the clinically acceptable range for both males and females. Limits of agreement indicated a poorer performance at an individual level with 1.96-SD limits of approximately ±25%.

CONCLUSIONS:

The new equations, using simple measures of weight, height, and age, improved the accuracy in the prediction of RMR in populations in clinical practice. However, no equation performs optimally at the individual level.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Basal Metabolism Type of study: Clinical_trials / Prognostic_studies / Risk_factors_studies Limits: Aged / Female / Humans / Male Language: En Journal: Am J Clin Nutr Year: 2023 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Basal Metabolism Type of study: Clinical_trials / Prognostic_studies / Risk_factors_studies Limits: Aged / Female / Humans / Male Language: En Journal: Am J Clin Nutr Year: 2023 Document type: Article
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