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Quantifies intra-individual variability in resting metabolic rate in strength-trained athletes, suggesting measurement consistency is essential.
BACKGROUND: Resting Metabolic Rate (RMR) is measured in sport settings for health monitoring and nutrition planning; however, interpreting repeated measures requires an understanding of typical day-to-day variability under habitual, free-living conditions. This study quantified intra-individual variability in RMR among weight-stable strength-trained athletes, examined the impact of data processing approaches, and established protocol-specific least significant change (LSC) thresholds under ecological conditions. METHODS: A repeated-measures design was used to quantify intra-individual variability in RMR in 13 weight-stable strength-trained athletes (8 male, 5 female). RMR was measured on five consecutive mornings using the Parvo Medics TrueOne 2400 metabolic cart with a Hans Rudolph mouthpiece under standardized conditions. Breath-by-breath data were processed using multiple cleaning approaches to evaluate their impact on RMR estimates, with the most reliable method retained for analysis. Intra-individual variability was quantified and used to derive protocol-specific LSC thresholds. RESULTS: (10.4 ± 4.2%), representing the magnitude of change required to exceed expected within-subject variability under the conditions of this protocol. Fat-free mass (FFM) was positively associated with both absolute RMR and day-to-day variability, whereas prior-day training load and protein intake showed no clear association with RMR variability. CONCLUSIONS: Notable intra-individual variability occurs in repeated RMR measurements in strength-trained athletes under applied conditions. Meaningful interpretation of change requires protocol-specific reliability estimates to distinguish true physiological change from expected day-to-day variation. Session averaging improves measurement consistency and is recommended for mouthpiece-based indirect calorimetry systems. RMR should be interpreted relative to individual and context-specific variability rather than universal thresholds.
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Buechel et al. (2026) studied this question.
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