Key result
Novel model accurately predicts heart rate slow component using exercise intensity, age, and sex.
Why the study?
Unless the heart rate slow component is accounted for, exercise prescription using HR targets leads to an undesired reduction in metabolic intensity over time.
Can the dynamic of the heart rate slow component be predicted across different exercise intensities, ages, and sexes to maintain a constant metabolic stimulus?
Cross-Sectional (n=101)
Randomized and counterbalanced constant-work-rate order
No
Can the dynamic of the heart rate slow component be predicted across different exercise intensities, ages, and sexes to maintain a constant metabolic stimulus?
The heart rate slow component can be dynamically predicted based on relative exercise intensity, sex, and age, providing a valid strategy to adjust heart rate targets over time to prevent undesired reductions in metabolic training load.
Answers are grounded in this paper and cite their sources.
Accurately predicts scHR across intensities; leaves open whether dynamic HR adjustments preserve metabolic stimulus in prospective training studies.
The heart rate slow component (scHR) is an intensity-dependent HR increment that emerges during constant exercises, partially dissociated from metabolism (V˙O2). The scHR has been observed during constant-workload exercise in young and older adults. Unless this scHR is accounted for, exercise prescription using HR targets lead to an undesired reduction in metabolic intensity over time. Purpose: The purpose of this study is to characterize scHR across intensities, sex, and age to develop and validate a predictive equation able to maintain the desired metabolic stimulus over time in a constant aerobic exercise session. Methods: In our study, 66 individuals (35 females; 35 ± 13 yrs) performed the following: (i) a ramp-test for respiratory exercise threshold (GET and RCP) and maximal oxygen uptake (V˙O2max) detection, and (ii) 6 × 9-minute constant exercises at different intensities. The scHR was calculated by linear fitting from the fifth minute of exercise (bpm⋅min−1). A multiple-linear equation was developed to predict the scHR based on individual and exercise variables. The validity of the equation was tested on an independent sample by a Pearson correlation and Bland–Altman analysis between the measured and estimated HR during constant exercises. Results: The scHR increases with intensity and is larger in males (p < 0.05). A multiple-linear equation predicts the scHR based on the relative exercise intensity to RCP, age, and sex (r2 = 0.54, SEE = 0.61 bpm⋅min−1). scHR (bpm⋅min−1) = −0.0514 + (0.0240 × relative exercise intensity to RCP) − (0.0172 × age) − (0.347 × Sex (males = 0 and females score = 1)). In the independent sample, we found an excellent correlation between the measured and estimated HR (r2 = 0.98, p < 0.001) with no bias (−0.01 b·min−1, z-score= −0.04) and a fair precision (±4.09 b·min−1). Conclusions: The dynamic of the scHR can be predicted in a heterogeneous sample accounting for the combined effects of relative intensity, sex, and age. The above equation provides the means to dynamically adapt HR targets over time, avoiding an undesired reduction in the absolute and relative training load. This strategy would allow the maintenance of the desired metabolic stimulus (V˙O2) throughout an exercise session in a heterogeneous population.
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Teso et al. (2025) conducted a cross-sectional in Healthy adults (n=101). Constant workload aerobic exercise was evaluated on Correlation between measured and estimated end-exercise heart rate (validating the slow component prediction model) (r2 = 0.98, p=<0.001). A multiple-linear equation based on relative exercise intensity, age, and sex accurately predicted the heart rate slow component in an independent sample.
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