ArticleThe American journal of clinical nutrition2023
Development and validation of new predictive equations for the resting metabolic rate of older adults aged ≥65 y.
Article in The American journal of clinical nutrition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Review
- Recalibrating Resting Energy Expenditure Prediction Equations in Asian Older Adults with Multimorbidity.Nutrients · 2026Article
- Investigating the impact of body composition on the estimation of resting metabolic rate: new equations for adults aged ≥65 years developed using cross-sectional data.The American journal of clinical nutrition · 2025Article
- Development and validation of age-specific predictive equations for total energy expenditure and physical activity levels for older adults.The American journal of clinical nutrition · 2024Article
- Development of New Predictive Equations for the Resting Metabolic Rate (RMR) of Women with Lipedema.Metabolites · 2024Article
- Older Adult Compendium of Physical Activities: Energy costs of human activities in adults aged 60 and older.Journal of sport and health science · 2024Review
- Reversal of Soleus Muscle Atrophy in Older Adults: A Non-Volitional Exercise Intervention for a Changing Climate.Clinical interventions in aging · 2024Review
- Prediction of resting energy expenditure in Italian older adults with severe obesity.Frontiers in endocrinology · 2023Article
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Authors and funding
8 authors.
Funding
Abstract
backgroundThe 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.
objectivesThis research aimed to generate and validate new RMR equations specifically for older adults and to report their performance and accuracy.
methodsData 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 50:50 split and leave one out cross-validation were performed. The newly generated prediction equations were compared with the existing commonly used equations.
resultsThe 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%.
conclusionsThe 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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