Predicting Heart Rate Slow Component Dynamics: A Model Across Exercise Intensities, Age, and Sex
The heart rate slow component (<sub>sc</sub>HR) is an intensity-dependent HR increment that emerges during constant exercises, partially dissociated from metabolism (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><sema...
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2025-02-01
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| author | Massimo Teso Alessandro L. Colosio Maura Loi Jan Boone Silvia Pogliaghi |
| author_facet | Massimo Teso Alessandro L. Colosio Maura Loi Jan Boone Silvia Pogliaghi |
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| description | The heart rate slow component (<sub>sc</sub>HR) is an intensity-dependent HR increment that emerges during constant exercises, partially dissociated from metabolism (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mrow><mi mathvariant="normal">V</mi></mrow><mo>˙</mo></mover></mrow></semantics></math></inline-formula>O<sub>2</sub>). The <sub>sc</sub>HR has been observed during constant-workload exercise in young and older adults. Unless this <sub>sc</sub>HR 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 <sub>sc</sub>HR 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 (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mrow><mi mathvariant="normal">V</mi></mrow><mo>˙</mo></mover></mrow></semantics></math></inline-formula>O<sub>2max</sub>) detection, and (ii) 6 × 9-minute constant exercises at different intensities. The <sub>sc</sub>HR was calculated by linear fitting from the fifth minute of exercise (bpm⋅min<sup>−1</sup>). A multiple-linear equation was developed to predict the <sub>sc</sub>HR 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 <sub>sc</sub>HR increases with intensity and is larger in males (<i>p</i> < 0.05). A multiple-linear equation predicts the <sub>sc</sub>HR based on the relative exercise intensity to RCP, age, and sex (<i>r</i><sup>2</sup> = 0.54, SEE = 0.61 bpm⋅min<sup>−1</sup>). <sub>sc</sub>HR (bpm⋅min<sup>−1</sup>) = −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 (r<sup>2</sup> = 0.98, <i>p</i> < 0.001) with no bias (−0.01 b·min<sup>−1</sup>, z-score= −0.04) and a fair precision (±4.09 b·min<sup>−1</sup>). Conclusions: The dynamic of the <sub>sc</sub>HR 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 (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mrow><mi mathvariant="normal">V</mi></mrow><mo>˙</mo></mover></mrow></semantics></math></inline-formula>O<sub>2</sub>) throughout an exercise session in a heterogeneous population. |
| format | Article |
| id | doaj-art-04b002dc60aa4836acd3ef13eeb6875f |
| institution | DOAJ |
| issn | 2075-4663 |
| language | English |
| publishDate | 2025-02-01 |
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| series | Sports |
| spelling | doaj-art-04b002dc60aa4836acd3ef13eeb6875f2025-08-20T03:12:16ZengMDPI AGSports2075-46632025-02-011324510.3390/sports13020045Predicting Heart Rate Slow Component Dynamics: A Model Across Exercise Intensities, Age, and SexMassimo Teso0Alessandro L. Colosio1Maura Loi2Jan Boone3Silvia Pogliaghi4College of Health and Life Sciences, Hamad Bin Khalifa University, Doha P.O. Box 34110, QatarLaboratoire Interuniversitaire de Biologie de la Motricité, Jean Monnet University, 42100 Saint-Étienne, FranceDepartment of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37129 Verona, ItalyDepartment of Movement and Sports Sciences, Ghent University, Watersportlaan 2, 9000 Ghent, BelgiumDepartment of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37129 Verona, ItalyThe heart rate slow component (<sub>sc</sub>HR) is an intensity-dependent HR increment that emerges during constant exercises, partially dissociated from metabolism (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mrow><mi mathvariant="normal">V</mi></mrow><mo>˙</mo></mover></mrow></semantics></math></inline-formula>O<sub>2</sub>). The <sub>sc</sub>HR has been observed during constant-workload exercise in young and older adults. Unless this <sub>sc</sub>HR 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 <sub>sc</sub>HR 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 (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mrow><mi mathvariant="normal">V</mi></mrow><mo>˙</mo></mover></mrow></semantics></math></inline-formula>O<sub>2max</sub>) detection, and (ii) 6 × 9-minute constant exercises at different intensities. The <sub>sc</sub>HR was calculated by linear fitting from the fifth minute of exercise (bpm⋅min<sup>−1</sup>). A multiple-linear equation was developed to predict the <sub>sc</sub>HR 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 <sub>sc</sub>HR increases with intensity and is larger in males (<i>p</i> < 0.05). A multiple-linear equation predicts the <sub>sc</sub>HR based on the relative exercise intensity to RCP, age, and sex (<i>r</i><sup>2</sup> = 0.54, SEE = 0.61 bpm⋅min<sup>−1</sup>). <sub>sc</sub>HR (bpm⋅min<sup>−1</sup>) = −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 (r<sup>2</sup> = 0.98, <i>p</i> < 0.001) with no bias (−0.01 b·min<sup>−1</sup>, z-score= −0.04) and a fair precision (±4.09 b·min<sup>−1</sup>). Conclusions: The dynamic of the <sub>sc</sub>HR 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 (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mrow><mi mathvariant="normal">V</mi></mrow><mo>˙</mo></mover></mrow></semantics></math></inline-formula>O<sub>2</sub>) throughout an exercise session in a heterogeneous population.https://www.mdpi.com/2075-4663/13/2/45heart rateexercise testaerobic exerciseslow componentHR driftcardiovascular drift |
| spellingShingle | Massimo Teso Alessandro L. Colosio Maura Loi Jan Boone Silvia Pogliaghi Predicting Heart Rate Slow Component Dynamics: A Model Across Exercise Intensities, Age, and Sex Sports heart rate exercise test aerobic exercise slow component HR drift cardiovascular drift |
| title | Predicting Heart Rate Slow Component Dynamics: A Model Across Exercise Intensities, Age, and Sex |
| title_full | Predicting Heart Rate Slow Component Dynamics: A Model Across Exercise Intensities, Age, and Sex |
| title_fullStr | Predicting Heart Rate Slow Component Dynamics: A Model Across Exercise Intensities, Age, and Sex |
| title_full_unstemmed | Predicting Heart Rate Slow Component Dynamics: A Model Across Exercise Intensities, Age, and Sex |
| title_short | Predicting Heart Rate Slow Component Dynamics: A Model Across Exercise Intensities, Age, and Sex |
| title_sort | predicting heart rate slow component dynamics a model across exercise intensities age and sex |
| topic | heart rate exercise test aerobic exercise slow component HR drift cardiovascular drift |
| url | https://www.mdpi.com/2075-4663/13/2/45 |
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