Autonomic Rebound Following Maximal Exercise In Bodybuilders And Recreationally Active Participants

BACKGROUND: Bodybuilding is a competitive sportinvolves heavily structured weightlifting routines and diets. For bodybuilders, the bulking phase training loads and fluctuations in caloric intake may to lead to insufficient recovery and overtraining. The activity of the autonomic nervous system (ANS) plays a pivotal role in the recovery from exercise challenges and is shown to become impaired by overtraining. Therefore, the purpose of this study was to evaluate resting ANS activity and its recovery following a bout of exercise in natural bodybuilders who are in the bulking phase. Additionally, these results were compared to those of recreationally active individuals. METHODS: Fifteen males participated in this study; 7 recreationally active (RA)(24.6 ± 2.1 yrs, 178.6 ± 9.6 cm, 81.1 ± 10.8 kg) and 8 natural bodybuilders (BB)(21.8 ± 2.9 yrs, 176.6 ± 7.2 cm, 89.3 ± 13.0 kg). Participants were asked to arrive at the lab for one visit. Heart Rate Variability (HRV) was measured at rest via electrocardiogram (Finapres, NOVA), for 10-minutes (PRE). Immediately following, participants underwent a treadmill graded exercise test. Upon completion, participant a 45-min HRV recovery was measured. HRV was measured and analyzed in five minutes segments; PRE, 5-10, 10-15, 15-20, 20-25, 25-30, 30-35, 35-40, and 40-45 minutes via online software Kubios HRV Standard (version 3.5.1) for analysis of HRV metrics: root mean square of successive differences (RMSSD), standard deviation of normal-to-normal sinus beats (SDNN), high frequency (HF), and low frequency (LF). SPSS (version 28.0.1.1) was used, and alpha was set to 0.05. RESULTS: HRV data violated normality and underwent a natural log transformation (ln). A One-Way Analysis of Variance Analysis showed no differences for any resting marker of HRV, HR, and HR recovery. No significant differences were observed between PRE, 5-10, 10-15, and 15-20 for any marker of HRV. Significant differences were observed for lnRMSSD at 20-25, 25-30, and 40-45 (p < 0.05), lnSDNN at 20-25, 25-30, 35-40, and 40-45 (p < 0.05), lnHF at 15-20, 20-25, 30-35, and 40-45 (p < 0.05), and lnLF 15-20, 25-30, 30-35, 35-40, and 40-45 (p < 0.05). CONCLUSIONS: The BB group during off-season training exhibit a depressed HRV recovery following maximal exercise when compared with recreationally trained males.

Authors

Institutions

Publication Details

Journal
Medicine & Science in Sports & Exercise
Published
2024-09-16
DOI
https://doi.org/10.1249/01.mss.0001056104.41045.8a
Primary Topic
Vehicle emissions and performance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Autonomic Rebound Following Maximal Exercise In Bodybuilders And Recreationally Active Participants

Cherilyn McLester, Robert Buresh, Brian Kliszczewicz, Gabe Wilner et al.
Medicine & Science in Sports & Exercise
Vehicle emissions and performance
article

Autonomic Rebound Following Maximal Exercise In Bodybuilders And Recreationally Active Participants

Cherilyn McLester, Robert Buresh, Brian Kliszczewicz, Gabe Wilner, Andre Canino, Pedro Chung, Inusha Aryal, Keilah Vaughan
article en

Abstract

BACKGROUND: Bodybuilding is a competitive sportinvolves heavily structured weightlifting routines and diets. For bodybuilders, the bulking phase training loads and fluctuations in caloric intake may to lead to insufficient recovery and overtraining. The activity of the autonomic nervous system (ANS) plays a pivotal role in the recovery from exercise challenges and is shown to become impaired by overtraining. Therefore, the purpose of this study was to evaluate resting ANS activity and its recovery following a bout of exercise in natural bodybuilders who are in the bulking phase. Additionally, these results were compared to those of recreationally active individuals. METHODS: Fifteen males participated in this study; 7 recreationally active (RA)(24.6 ± 2.1 yrs, 178.6 ± 9.6 cm, 81.1 ± 10.8 kg) and 8 natural bodybuilders (BB)(21.8 ± 2.9 yrs, 176.6 ± 7.2 cm, 89.3 ± 13.0 kg). Participants were asked to arrive at the lab for one visit. Heart Rate Variability (HRV) was measured at rest via electrocardiogram (Finapres, NOVA), for 10-minutes (PRE). Immediately following, participants underwent a treadmill graded exercise test. Upon completion, participant a 45-min HRV recovery was measured. HRV was measured and analyzed in five minutes segments; PRE, 5-10, 10-15, 15-20, 20-25, 25-30, 30-35, 35-40, and 40-45 minutes via online software Kubios HRV Standard (version 3.5.1) for analysis of HRV metrics: root mean square of successive differences (RMSSD), standard deviation of normal-to-normal sinus beats (SDNN), high frequency (HF), and low frequency (LF). SPSS (version 28.0.1.1) was used, and alpha was set to 0.05. RESULTS: HRV data violated normality and underwent a natural log transformation (ln). A One-Way Analysis of Variance Analysis showed no differences for any resting marker of HRV, HR, and HR recovery. No significant differences were observed between PRE, 5-10, 10-15, and 15-20 for any marker of HRV. Significant differences were observed for lnRMSSD at 20-25, 25-30, and 40-45 (p < 0.05), lnSDNN at 20-25, 25-30, 35-40, and 40-45 (p < 0.05), lnHF at 15-20, 20-25, 30-35, and 40-45 (p < 0.05), and lnLF 15-20, 25-30, 30-35, 35-40, and 40-45 (p < 0.05). CONCLUSIONS: The BB group during off-season training exhibit a depressed HRV recovery following maximal exercise when compared with recreationally trained males.

Medicine & Science in Sports & ExerciseVol. 56(10S)
Kennesaw State University (US)
Decent work and economic growth
Openalex Percentile: Top 84%
Vehicle emissions and performance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.