|Year : 2017 | Volume
| Issue : 3 | Page : 133-136
Assessment of the cardio-autonomic status by short-term heart rate variability in young football players
Kuppusamy Maheshkumar1, Sundareswaran Loganathan2, Arbind Kumar Choudhary3
1 Department of Physiology, Sri Ramachandra Medical College and Research Institute, Chennai, Tamil Nadu, India
2 Department of Physiology, ALMPG IBMS, University of Madras, Chennai, Tamil Nadu, India
3 Department of Physiology, The People's College of Medical Sciences and Research, Bhopal, Madhya Pradesh, India
|Date of Web Publication||9-Aug-2017|
Department of Physiology, ALMPG IBMS, University of Madras, Chennai, Tamil Nadu
Source of Support: None, Conflict of Interest: None
Background/Objectives: The present study was done to explain the importance of physical activity (PA) on autonomic nervous system. We have compared the short-term heart rate variability (HRV) between football players and normal controls lacking PA, fitness, and exercise.
Design: Case–control study.
Methods: The sample included 40 football players and 40 controls with age group between 17 and 26 years. Individuals with minimum 5 years of football practice were included and morphological variables (weight, height, and body mass index) were recorded in all of them. Five minutes lead II electrocardiography recorded in supine position in the morning and R-R intervals were analyzed in Kubios software.
Results: Time domain parameters of average mean R-R interval (1014 ± 286.12 ms vs. 860.28 ± 362.4 ms), standard deviation of the NN (89.81 ± 18.14 ms vs. 63.9 ± 31.27 ms), root mean square of successive difference (76.95 ± 24.20 ms vs. 43.19 ± 29.83 ms), and pNN 50% (39.16 ± 16.87% vs. 23.46 ± 19.43%) were significantly higher in the study group than the control group. Higher frequency power band (71.23 ± 11.59 n.u vs. 54.90 ± 17.3 n.u) showed significant higher value while low-frequency (LF) power band (29.66 ± 15.13 n.u vs. 47.23 ± 13.84 n.u) and LF/high-frequency ratio (0.964 ± 0.286 vs. 2.04 ± 0.459) of frequency domain parameters showed significant reduction among the football players.
Conclusion: The present study explains that regular PA in the form of football shifts the autonomic system toward parasympathetic domination. The indices of HRV can be useful to monitor the effects of football training on parasympathetic modulation and to the periods of stress and recovery.
Keywords: Autonomic nervous system, football, heart rate variability, training
|How to cite this article:|
Maheshkumar K, Loganathan S, Choudhary AK. Assessment of the cardio-autonomic status by short-term heart rate variability in young football players. Int J Health Allied Sci 2017;6:133-6
|How to cite this URL:|
Maheshkumar K, Loganathan S, Choudhary AK. Assessment of the cardio-autonomic status by short-term heart rate variability in young football players. Int J Health Allied Sci [serial online] 2017 [cited 2020 Jan 26];6:133-6. Available from: http://www.ijhas.in/text.asp?2017/6/3/133/212596
| Introduction|| |
Football players undergo a high-intensity training program to build up their speed, muscular strength, and cardiorespiratory endurance compared to the normal. Sympathetic and parasympathetic alterations in high endurance training induce rapid physiological response such as increases in heart rate (HR) and blood pressure  by the involvement of the hypothalamic–pituitary–adrenal and sympathoadrenomedullary axes. The sympathetic and parasympathetic activity differs accordingly based on the individual's physical activity (PA). Everyone perform PA to sustain their life. However, the amount varies to personal choice from person to person. PA and exercise have an important influence on the relationship between psychosocial stress and cardiovascular disease. Reduction in the mortality rate of healthier old and young men is well linked with the increased training and regular exercise. Increased fitness level has little effect on HR variability (HRV), which reflects the sympathetic and parasympathetic modulation of HR. In general, HRV is mainly caused by autonomic modulation on the sinoatrial node and acts as a good indicator of autonomic control related to cardiovascular health. As a noninvasive method to assess the autonomic nervous system, HRV is a valuable tool for several physiological conditions such as different body positions and physical training. Hence, to explain the importance of PA on the autonomic nervous system, we aimed to compare short-term HRV between football players and normal controls lacking PA and exercise in the present modern world.
| Methods|| |
The present study was conducted on 40 male football players aged 17–30 years and 40 untrained male controls aged 18–29 years from April 2015 to December 2015. Institutional ethical clearance was obtained. Players in the football group who have been doing endurance training for more than 5 years and participated in university level football matches were included in this study. Individuals with any form of regular PA more than 3 days, any metabolic diseases, recent surgery, acute illness, and on any regular medication were excluded. All of them in both groups were in normal health, based on a routine clinical examination. Informed consent was obtained from all individuals before their participation. Individuals were weighed in minimal clothing to the nearest 0.1 kg and their height was measured to the nearest 0.1 cm. Body mass index (BMI) was calculated using the formula weight in Kg/height in m 2 (Quetelet formula). The individuals reported to the laboratory in the early morning before the start of the recording and provided a standard light breakfast. Participants were advised to abstain from caffeinated food and beverages and avoid exercise for at least 24 h before the assessment. Before starting of the recording individuals were instructed to void the urine. HRV was evaluated in a quiet, temperature-controlled room with minimum light in accordance with procedures developed by the Task Force for Pacing and Electrophysiology. Electrocardiography (ECG) was recorded after 20 min of supine rest with normal breathing. Lead II ECG was acquired at a rate of 1000 samples/s using BIOPAC systems Inc., Model MP36 data acquisition system (USA). Ectopic and artifacts were checked visually in offline and removed from the recorded ECG. R-R interval was obtained from 5 min ECG and saved in notepad format which was later used offline for HRV analysis. HRV analysis was done using Kubios HRV software version 2.2 (bio-signal analysis group, Finland).
Linear model HRV analysis was carried out in this study, analyzed in the time and frequency domain. In the time domain, the standard deviation of the NN (SDNN) interval, the square root of the mean squared differences of successive NN intervals (root mean square of successive difference [RMSSD]), the number of interval differences of successive NN intervals >50 ms (NN50), and the proportion derived by dividing NN50 by the total number of NN intervals (pNN50) were used. In the frequency domain, power spectral density analysis in nonparametric method (fast fourier transform [FFT]) was used. They were low frequency (LF, 0.04–0.15 Hz) and high frequency (HF, 0.15–0.40 Hz) in square milliseconds (ms 2) as well as normalized units (LF n.u and HF n.u, respectively), and LF/HF ratio.
Data were expressed in mean and standard deviation data were analyzed by R statistical software version 3.2.0. Independent t-test was performed to compare the inter group variation of short-term HRV parameters.
| Results|| |
[Table 1] shows the anthropometric and cardiovascular parameter between control and football players and there was no significant difference was found in age, height, and weight. BMI was observed slightly higher in football players but not significant. Resting HR found in football players was significantly (P < 0.01) lower than the control group. They also had significantly (P < 0.01) lower systolic blood pressure and diastolic blood pressure than untrained controls. In time, domain parameters of short-term HRV [Table 2] showed a significant (P < 0.05) higher value in mean NN, SDNN, RMSSD, and pNN50.
|Table 1: Anthropometric and cardiovascular parameters of the control and football players|
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|Table 2: Comparison of time domain heart rate variability parameters of the control and football players|
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[Table 3] represents the parameters of HRV in frequency domain. Football players showed significantly (P < 0.05) higher value of HF band and comparatively decreased level LF band in normalized unit (n.u). LF/HF ratio also showed a significant reduction in football players group compared with control at rest.
|Table 3: Comparison of frequency domain heart rate variability parameters of the control and football players|
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| Discussion|| |
In short-term HRV, LF band of frequency domain expressed in normalized unit (n.u) is mainly related to sympathetic modulation and HF band (n.u) reflect the efferent vagal activity of the heart. The LF/HF ratio is correlated with sympathovagal balance. Time domain parameter of mean NN, SDNN, RMSSD, and pNN50 represents the activity of parasympathetic nervous system. From the present study, we identified that football players were in the state of parasympathetic dominance. The increase in HF power and the decrease in LF power and LF/HF ratio of frequency domain parameters in trained football players reflect the shift toward the vagal domination. Decreased resting HR in players has been well observed in various studies, and it could be due to the long-term endurance training. This training is also associated with the improved heart function by increasing the stroke volume and left ventricular mass. However, endurance training also decreases the metabolic load on the heart at rest and during submaximal exercise training conditions. Normally, long-term physical training influences the cardiac rhythm by inducing sinus bradycardia in resting condition and slow increase in HR at various degrees of submaximal exercise is due to a shift of the sympathovagal balance  toward parasympathetic dominance. Studies showed that aerobically trained athletes have a higher mean NN (lower HR) compared with the control group with the higher value of RMSSD and pNN50 in standing as well as in supine position. It was further supported by another study  where larger HF component was observed in aerobically trained athletes demonstrated by FFT wavelet analysis. The HRV changes in football players compared with control in the present study also nearly matched with the earlier studies performed in different age groups (n = 14, 33–55 years) and various disciplines such as cycling, canoeing, athletics, roller-skating, and volley ball.,,,,, There are several cross-sectional and longitudinal studies on the resting HRV between endurance-trained and untrained individuals. Some studies showed that endurance-trained individuals has higher values of power spectral HRV (indicating increasing vagal activity).,,,, In contrast to this result, on the other hand, studies with higher values of the LF component of HRV suggesting predominant sympathetic activity also reported , and few studies presented with decreased sympathetic activity  and vagal activity  and finally a study also showed no significant differences between trained and untrained individuals.
| Conclusion|| |
Apart from these various conflicting results, our findings clearly explain that high endurance training in football players may cause the state of parasympathetic domination and this observed base line parasympathetic predominance in autonomic nervous system was balanced with better neuromuscular contribution and their preparedness for higher performance.
The research team would like to acknowledge the football players involved in this study and Dr. R Ravindran and Dr. R Sheela Devi for the permission and support to conduct this study.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Motriz RC, Bara-Filho MG, Freitas DS, Moreira D, Matta MO, Perrout de Lima JR, et al
. Heart rate variability and soccer training: A case study. Rev Educação Fís 2013;19:171-7.
Goldstein DS, Kopin IJ. Evolution of concepts of stress. Stress 2007;10:109-20.
Hamer M. Psychosocial stress and cardiovascular disease risk: The role of physical activity. Psychosom Med 2012;74:896-903.
Corrales M, Torres B, Esquivel A, Salazar M, Naranjo Orellana J. Normal values of heart rate variability at rest in a young, healthy and active Mexican population. Health 2012;4:4949-98.
Stein PK, Ehsani AA, Domitrovich PP, Kleiger RE, Rottman JN. Effect of exercise training on heart rate variability in healthy older adults. Am Heart J 1999;138:567-76.
Martinelli FS, Chacon-Mikahil MP, Golfetti R, Martins LE, Lima-Filho EC, Gallo L Jr. Heart rate variability in cyclists and sedentary young men at rest and during head-up tilt. Physiologist 2000;43:A14-7.
Garrow JS, Webster J. Quetelet's index (W/H2) as a measure of fatness. Int J Obes 1985;9:147-53.
Heart rate variability: Standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and electrophysiology. Circulation 1996;93:1043-65.
Malliani A, Pagani M, Lombardi F, Cerutti S. Cardiovascular neural regulation explore in the frequency domain. Circulation 1991;84:482-92.
Uusitalo AL, Tahvanainen KU, Uusitalo AJ, Rusko HK. Non-invasive evaluation of sympathovagal balance in athletes by time and frequency domain analyses of heart rate and blood pressure variability. Occup Health Ind Med 1997;2:94-5.
Seals DR, Chase PB. Influence of physical training on heart rate variability and baroreflex circulatory control. J Appl Physiol (1985) 1989;66:1886-95.
Aubert AE, Beckers F, Ramaekers D. Short-term heart rate variability in young athletes. J Cardiol 2001;37 Suppl 1:85-8.
Verlinde D, Beckers F, Ramaekers D, Aubert AE. Wavelet decomposition analysis of heart rate variability in aerobic athletes. Auton Neurosci 2001;90:138-41.
Dixon EM, Kamath MV, McCartney N, Fallen EL. Neural regulation of heart rate variability in endurance athletes and sedentary controls. Cardiovasc Res 1992;26:713-9.
Goldsmith RL, Bigger JT Jr., Steinman RC, Fleiss JL. Comparison of 24-hour parasympathetic activity in endurance-trained and untrained young men. J Am Coll Cardiol 1992;20:552-8.
Puig J, Freitas J, Carvalho MJ, Puga N, Ramos J, Fernandes P, et al.
Spectral analysis of heart rate variability in athletes. J Sports Med Phys Fitness 1993;33:44-8.
Jensen-Urstad K, Saltin B, Ericson M, Storck N, Jensen-Urstad M. Pronounced resting bradycardia in male elite runners is associated with high heart rate variability. Scand J Med Sci Sports 1997;7:274-8.
Macor F, Fagard R, Amery A. Power spectral analysis of RR interval and blood pressure short-term variability at rest and during dynamic exercise: Comparison between cyclists and controls. Int J Sports Med 1996;17:175-81.
Shin K, Minamitani H, Onishi S, Yamazaki H, Lee M. Autonomic differences between athletes and nonathletes: Spectral analysis approach. Med Sci Sports Exerc 1997;29:1482-90.
Yamamoto K, Miyachi M, Saitoh T, Yoshioka A, Onodera S. Effects of endurance training on resting and post-exercise cardiac autonomic control. Med Sci Sports Exerc 2001;33:1496-502.
Furlan R, Piazza S, Dell'Orto S, Gentile E, Cerutti S, Pagani M, et al.
Early and late effects of exercise and athletic training on neural mechanisms controlling heart rate. Cardiovasc Res 1993;27:482-8.
Pichot V, Roche F, Gaspoz JM, Enjolras F, Antoniadis A, Minini P, et al.
Relation between heart rate variability and training load in middle-distance runners. Med Sci Sports Exerc 2000;32:1729-36.
Loimaala A, Huikuri H, Oja P, Pasanen M, Vuori I. Controlled 5-mo aerobic training improves heart rate but not heart rate variability or baroreflex sensitivity. J Appl Physiol (1985) 2000;89:1825-9.
Perini R, Orizio C, Comandè A, Castellano M, Beschi M, et al.
(1989) Plasma norepinephrine and heart rate dynamics during recovery from submaximal exercise in man. Eur J Appl Physiol Occup Physiol 58: 879-883.
[Table 1], [Table 2], [Table 3]