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. 2023 Jul 16;9(7):e18125.
doi: 10.1016/j.heliyon.2023.e18125. eCollection 2023 Jul.

Recovery of the autonomic nervous system following football training among division I collegiate football athletes: The influence of intensity and time

Affiliations

Recovery of the autonomic nervous system following football training among division I collegiate football athletes: The influence of intensity and time

S Howard Wittels et al. Heliyon. .

Abstract

The autonomic nervous system (ANS) is profoundly affected by high intensity exercise. However, evidence is less clear on ANS recovery and function following prolonged bouts of high intensity exercise, especially in non-endurance athletes. Therefore, this study aimed to investigate the relationships between duration and intensity of acute exercise training sessions and ANS recovery and function in Division I football athletes. Fifty, male football athletes were included in this study. Subjects participated in 135 days of exercise training sessions throughout the 25-week season and wore armband monitors (Warfighter Monitor, Tiger Tech Solutions) equipped with electrocardiography capabilities. Intensity was measured via heart rate (HR) during an 'active state', defined as HR ≥ 85 bpm. Further, data-driven intensity thresholds were used and included HR < 140 bpm, HR < 150 bpm, HR < 160 bpm, HR ≥ 140 bpm, HR ≥ 150 bpm and HR ≥ 160 bpm. Baseline HR and HR recovery were measured and represented ANS recovery and function 24h post-exercise. Linear regression models assessed the relationships between time spent at the identified intensity thresholds and ANS recovery and function 24h post-exercise. Statistical significance set at α < 0.05. Athletes participated in 128 training sessions, totaling 2735 data points analyzed. Subjects were predominantly non-Hispanic black (66.0%), aged 21.2 (±1.5) years and average body mass index of 29.2 (4.7) kg⋅(m2)-1. For baseline HR, statistically significant associations between duration and next-day ANS recovery were observed at HR < 140 bpm (β = -0.08 ± 0.02, R2 = 0.31, p < 0.001), HR above 150 and 160 bpm intensity thresholds (β = 0.25 ± 0.02, R2 = 0.69, p < 0.0000 and β = 0.59 ± 0.06, R2 = 0.71, p < 0.0000). Similar associations were observed for HR recovery: HR < 140 bpm (β = 0.15 ± 0.03, R2 = 0.43, p < 0.0000) and HR above 150 and 160 bpm (β = -0.33 ± 0.03, R2 = 0.73, p < 0.0000 and β = -0.80 ± 0.06, R2 = 0.71, p < 0.0000). The strengths of these associations increased with increasing intensity, HR ≥ 150 and 160 bpm (baseline HR: β range = 0.25 vs 0.59, R2: 0.69 vs 0.71 and HR recovery: β range = -0.33 vs -0.80, R2 = 0.73 vs 0.77). Time spent in lower intensity thresholds, elicited weaker associations with ANS recovery and function 24h post-exercise, with statistical significance observed only at HR < 140 bpm (β = -0.08 ± 0.02, R2 = 0.31, p < 0.001). The findings of this study showed that ANS recovery and function following prolonged high intensity exercise remains impaired for more than 24h. Strength and conditioning coaches should consider shorter bouts of strenuous exercise and extending recovery periods within and between exercise training sessions.

Keywords: Collegiate football; Conditioning; Exercise training; Overtraining; Sports; Strength.

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Conflict of interest statement

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Samantha M McDonald reports financial support was provided by TigerTech Solutions, Inc. S. Howard Wittels reports financial support was provided by TigerTech Solutions, Inc. Eva D Wittels reports financial support was provided by TigerTech Solutions. Stephanie Hendricks reports financial support was provided by TigerTech Solutions, Inc. Michael Joseph Wishon reports financial support was provided by TigerTech Solutions, Inc. Dustin Hecocks reports financial support was provided by TigerTech Solutions, Inc. Stephanie Chong reports financial support was provided by TigerTech Solutions, Inc. Harrison L Wittels reports financial support was provided by TigerTech Solutions, Inc. Harrison L. Wittels, the founder of TigerTech Solutions, possesses trade secret protection for the Warfighter Monitor used to collect the data analyzed and presented in the current manuscript.

Figures

Fig. 1
Fig. 1
The 25-week football training and measurement schematic.
Fig. 2
Fig. 2
Adjusted linear regression correlations between time spent in (a) HRs below 140 bpm and (b) baseline HR and HR recovery 24h post-exercise, in a sample of Division I male, football athletes.
Fig. 3
Fig. 3
Adjusted linear regression correlations between time spent in (a) HRs below 150 bpm and (b) baseline HR and HR recovery 24h post-exercise, in a sample of Division I male, football athletes.
Fig. 4
Fig. 4
Adjusted linear regression correlations between time spent in (a) HRs below 160 bpm and (b) baseline HR and HR recovery 24h post-exercise, in a sample of Division I male, football athletes.
Fig. 5
Fig. 5
Adjusted linear regression correlations between time spent in (a) HRs above 140 bpm and (b) baseline HR and HR recovery 24h post-exercise, in a sample of Division I male, football athletes.
Fig. 6
Fig. 6
Adjusted linear regression correlations between time spent in (a) HRs above 150 bpm and (b) baseline HR and HR recovery 24h post-exercise, in a sample of Division I male, football athletes.
Fig. 7
Fig. 7
Adjusted linear regression correlations between time spent in (a) HRs above 160 bpm and (b) baseline HR and HR recovery 24h post-exercise, in a sample of Division I male, football athletes.

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