Interval Hypoxic Training Enhances Athletic Performance and Does Not Adversely Affect Immune Function in Middle- and Long-Distance Runners

This study evaluated the e ects of intermittent interval training in hypoxic conditions for six weeks compared with normoxic conditions, on hemodynamic function, autonomic nervous system (ANS) function, immune function, and athletic performance in middle- and long-distance runners. Twenty athletes were divided into normoxic training (normoxic training group (NTG); n=10; residing and training at sea level) and hypoxic training (hypoxic training group (HTG); n=10; residing at sea level but training in 526-mmHg hypobaric hypoxia) groups. All dependent variables were measured before, and after, training. The training frequency was 90 min, 3 d per week for six weeks. Body composition showed no signi cant di erence between the two groups. However, the HTG showed more signi cantly improved athletic performance (e.g., maximal oxygen uptake). The hemodynamic function (e.g., oxygen uptake, oxygen pulse, and cardiac output) during submaximal exercise and ANS function (e.g., standard deviation and root mean square of successive di erences, high frequency, and low/high frequency) improved more in the HTG. Immune function parameters were stable within the normal range before and after training in both groups. Therefore, hypoxic training was more e ective in enhancing athletic performance, and improving hemodynamic and ANS function; further, it did not adversely a ect immune function in competitive runners. Keywords: interval hypoxic training; hemodynamic function; autonomic nervous system balance; exercise performance; immune function; competitive middle- and long-distance runners 1. Introduction Endurance exercise performance is related to various factors that can be altered by diverse hypoxic training methods, including erythropoiesis, exercise economy, capillary density, hemodynamic function, and acid-base response in the skeletal muscle

a ect immune function in competitive runners. Keywords: interval hypoxic training; hemodynamic function; autonomic nervous system balance; exercise performance; immune function; competitive middle- and long-distance runners 1. Introduction Endurance exercise performance is related to various factors that can be altered by diverse hypoxic training methods, including erythropoiesis, exercise economy, capillary density, hemodynamic function, and acid-base response in the skeletal muscle [1,2]. Enhancing these factors, which are related to endurance exercise performance, increases the e ciency of aerobic energy production and consequently enhances maximum oxygen uptake (VO2max). It also enhances athletic performance by improving time until fatigue and increasing exercise intensity [3–6]. In particular, endurance exercise performance is reported to be the most a ected by hemodynamic function, which is an indicator of oxygen transport and utilization ability [7]. Currently, altitude/hypoxic training is a common and popular practice for enhancing athletic performance in normoxic conditions among various athletes [8]. The most typical altitude/hypoxic training regimens proposed include living high-training high (LHTH), living high-training low (LHTL), and living low-training high (LLTH) methods. The LHTH method involves living and training at Int. J. Environ. Res. Public Health2020,17, 1934; doi:10.3390 /ijerph17061934 /journal/ijerph

Int. J. Environ. Res. Public Health2020,17, 1934 2 of 15 1500–4000 m in natural altitude environments, while the LHTL method involves living at or near sea level but training under a natural or simulated altitude condition of 2000–3000 m [3,4,6]. The LLTH method may be of particular interest to athletes because this training commonly involves shorter hypoxic exposure (approximately two to ve sessions per week of<3 h), lower cost, lesser e ort, and lesser time than the LHTH and LHTL methods [1]. Further, the LLTH method, includes interval hypoxic training (IHT), repeated sprint training in hypoxia, and resistance training in hypoxic conditions; it has become an increasingly popular altitude/hypoxic practice, where athletes live at or near sea level but train in 2000–4500 m simulated hypobaric or normobaric hypoxic conditions [9–11]. Among the various LLTH methods, IHT consists of repeated exposures to 5–7 min of steady or progressive hypoxia, interrupted by equal periods of recovery; it can modify oxygen transport and energy utilization and induce permanent modi cations in cardiac function [12]. Short-term repeated exposure to hypoxic conditions with high-intensity exercise enhances athletic performance via the metabolic and oxygen utilizing capacity [11,13–15]. However, some studies have not supported the enhancing e ect of high-intensity training in hypoxic conditions on athletic performance [16–19]. These con icting results are attributed to the fact that the enhancement of athletic performance was not veri ed on the basis of changes in hemodynamic function. Heart rate (HR) variability (HRV) is a widely used marker re ecting cardiac modulation by sympathetic and vagal components and autonomic nervous system (ANS) activity. Dynamic adjustments in cardiac and peripheral vascular control, including their regulation by the ANS, occur in response to rapid changes in the HR [20,21]. Change in HRV with exercise training have often been interpreted as increase in vagal activity or ANS balance function, which is related to athletic performance [21]. Herzig et al. [22] reported that HRV markers of vagal activity are moderately associated with athletic performance variables, such as 10-mi race time. Dong [23] explained that HRV was becoming one of the most useful tools for

with exercise training have often been interpreted as increase in vagal activity or ANS balance function, which is related to athletic performance [21]. Herzig et al. [22] reported that HRV markers of vagal activity are moderately associated with athletic performance variables, such as 10-mi race time. Dong [23] explained that HRV was becoming one of the most useful tools for tracking the time course of exercise training adaptation of athletes and for setting the optimal exercise intensity that leads to enhanced athletic performance. Therefore, it is essential to examine the e ectiveness of exercise training in hypoxic conditions with changes in HRV, which is useful in enhancing the athletic performance. Exercise in hypoxic conditions acts as a stressor to yield greater physiological and metabolic functions than exercise in normoxic conditions, thereby causing changes in the neuroendocrine system and a ecting immune function [24,25]. Further, exposure to hypoxic conditions stimulates the release of epinephrine in the adrenal medulla, increases the sympathetic nervous system activity, and increases the concentration of cortisol and adrenal cortical hormone in the blood [26,27]. The most representative changes in immune function following exposure to hypoxic conditions include decreased CD4+T cell count; decreased T cell activation and proliferation; lymphocytosis; neutropenia; and in ammatory upregulation of cytokines, such as interleukin (IL)-6, IL-1, C-reactive protein, and tumor necrosis factor (TNF)- [25,28–31]. As described above, exposure to hypoxic conditions results in a change in immune function based on various changes in the physiological, metabolic, and neuroendocrine systems. However, studies on changes in immune function following exercise training in hypoxic conditions are scarce. Considering that various hypoxic training regimens are commonly used to enhance athletic performance in normoxic conditions based on hematological and non-hematological changes, it is important to examine the e ects on immune function in terms of health and conditioning. Moreover, the World Anti-Doping Agency is concerned that various hypoxic training regimens can have a potentially negative e ect on health [32]. Thus, an essential task for elite athletes is to examine how exercise training in hypoxic conditions a ects their immune function, and establish the e cacy and stability

ects on immune function in terms of health and conditioning. Moreover, the World Anti-Doping Agency is concerned that various hypoxic training regimens can have a potentially negative e ect on health [32]. Thus, an essential task for elite athletes is to examine how exercise training in hypoxic conditions a ects their immune function, and establish the e cacy and stability of hypoxic training. Therefore, this study aimed to investigate the e ects of intermittent interval training on hemodynamic function, ANS function, immune function, and athletic performance of competitive middle- and long-distance runners in a hypoxic condition versus that in a normoxic condition. We hypothesized that intermittent interval training in a hypoxic condition would enhance

Int. J. Environ. Res. Public Health2020,17, 1934 3 of 15 hemodynamic function, ANS function, and athletic performance more than in a normoxic condition, and would not adversely a ect immune function in competitive middle- and long-distance runners. 2. Materials and Methods 2.1. Subjects Subjects, whose characteristics are presented in Table, were men and were competitive, moderately trained, middle- and long-distance runners (n=20) registered with the Korea Association of Athletics Federations. They were assigned equally to the normoxic (NTG) and hypoxic (HTG) training group based on their body composition and athletic performance. We explained the experiment and possible adverse e ects before the start of the study to participants and obtained their signed informed consent to participate in this study. This study was approved by the institutional review board of Konkuk University (7001355-2020002-HR-359) and was conducted in accordance with the provisions of the Declaration of Helsinki. Table 1.Characteristics of the athletes. Variables NTG HTG t-Value p-Value Number (n) n=10 n=10 - - Environmental condition (mmHg) Sea level (760 mmHg) 3000-m simulated altitude (526 mmHg) - - Age (year) 25.9 1.2 26.3 1.5 0.499 0.624 Height (cm) 176.9 7.6 178.2 3.5 0.514 0.616 Weight (kg) 70.8 5.8 71.2 6.3 0.490 0.630 BMI (kg/m 2 ) 23.1 1.5 22.8 0.9 1.554 0.138 FFM (kg) 51.1 4.4 52.1 4.8 0.490 0.630 Percent body fat (%) 17.5 2.7 18.4 1.8 0.882 0.389 Values are expressed as means standard deviations. NTG=normoxic training group, HTG=hypoxic training group, BMI=body mass index, FFM=free fat mass. 2.2. Study Design The study design is shown in Figure. Twenty athletes were equally divided into the NTG ( n=10; intermittent interval training in a normoxic condition; 760 mmHg) and HTG (n=10; intermittent interval training in a hypoxic condition; 526 mmHg; simulated altitude of 3000 m). All testing and training were performed in a 9-m (width) 7-m (length) 3-m (height) chamber with a temperature of 22 1 C and humidity of 50 5% regulated by an environmental control chamber (NCTC-1, Nara control, Seoul, Korea). The present study comprised a 5-day pre-test period (i.e., 3 testing days and 1 rest day between the testing days),

3000 m). All testing and training were performed in a 9-m (width) 7-m (length) 3-m (height) chamber with a temperature of 22 1 C and humidity of 50 5% regulated by an environmental control chamber (NCTC-1, Nara control, Seoul, Korea). The present study comprised a 5-day pre-test period (i.e., 3 testing days and 1 rest day between the testing days), 6-week training period under each environmental condition, and 5-day post-test period. The post-test period began 3 d after the nal training session. On the rst pre- and post-testing days, blood samples were collected between 8:00 and 10:00 a.m. after 12 h of fasting for the analysis of blood variables related to immune function in the normoxic condition. Thereafter, body composition and ANS function were measured. Subsequently, the VO2max was measured to evaluate exercise performance in the afternoon. On the second pre- and post-testing days, hemodynamic function parameters were measured during a 30-min bout of submaximal cycle ergometer exercise. The exercise intensity was set at individual cycle ergometer exercise load values corresponding to 80% maximal HR (HRmax) obtained during the pre-test period. On the third testing day, a 3000-m time trial record was measured on an authorized track stadium at sea level.

Int. J. Environ. Res. Public Health2020,17, 1934 4 of 15 Figure 1. Study design of the present study. All athletes performed the following in 90-min sessions: warm-up, interval training, and cool- down. The training frequency was 90 min, 3 d per week for 6 weeks. Warm-up and cool-down were set at 50% HRmax for each participant for 5 min, which was then increased by 10% HRmax every 5 min and performed for 15 min. The interval training sessions consisted of 10 repetitions of interval running exercise (5 min of exercise corresponding to 90–95% HRmax and 1 min of rest) on a treadmill. All exercise training sessions in the hypoxic conditions were supervised by directors, coaches, and the researchers. 2.3. Blood Composition Body composition parameters, such as weight, free fat mass, and percentage body fat were analyzed using Inbody 770 (Inbody, Seoul, Republic of Korea). 2.4. Hemodynamic Function Hemodynamic function was measured before and after training while the participants performed submaximal cycle ergometer exercise corresponding to 80% HRmax obtained during the pre-test period for 30 min at sea level [1,11]. The oxygen uptake (VO 2) was measured using the K5 auto metabolism analyzer (Cosmed, Rome, Italy) and a breathing valve in the form of a facemask. The HR, stroke volume index (SVi), and cardiac output index (COi) were assessed non-invasively using a thoracic bioelectrical impedance device (PhysioFlow PF-05, Paris, France). The oxygen pulse (O 2 pulse) was calculated as VO2/HR. 2.5. ANS Function ANS function was assessed by measuring HRV. After approximately 10 min of rest, four pads were placed on the wrists and ankles using an HRV meter (LAXTHA; CANS-3000, Daejeon, Republic of Korea), and participants’ HRV was measured in the resting condition. The following parameters were evaluated: standard deviation (SD) of successive differences (SDNN) and root mean square of successive differences (RMSSD) for the time domain methods and low frequency (LF) band, high frequency (HF) band, and LH/HF band ratio for the frequency domain methods [33]. Figure 1.Study design of the present study. All athletes performed the following in 90-min sessions: Warm-up, interval training, and cool-down. The training frequency

(SD) of successive differences (SDNN) and root mean square of successive differences (RMSSD) for the time domain methods and low frequency (LF) band, high frequency (HF) band, and LH/HF band ratio for the frequency domain methods [33]. Figure 1.Study design of the present study. All athletes performed the following in 90-min sessions: Warm-up, interval training, and cool-down. The training frequency was 90 min, 3 d per week for 6 weeks. Warm-up and cool-down were set at 50% HRmax for each participant for 5 min, which was then increased by 10% HRmax every 5 min and performed for 15 min. The interval training sessions consisted of 10 repetitions of interval running exercise (5 min of exercise corresponding to 90–95% HRmax and 1 min of rest) on a treadmill. All exercise training sessions in the hypoxic conditions were supervised by directors, coaches, and the researchers. 2.3. Blood Composition Body composition parameters, such as weight, free fat mass, and percentage body fat were analyzed using Inbody 770 (Inbody, Seoul, Korea). 2.4. Hemodynamic Function Hemodynamic function was measured before and after training while the participants performed submaximal cycle ergometer exercise corresponding to 80% HRmax obtained during the pre-test period for 30 min at sea level [1,11]. The oxygen uptake (VO2) was measured using the K5 auto metabolism analyzer (Cosmed, Rome, Italy) and a breathing valve in the form of a facemask. The HR, stroke volume index (SVi), and cardiac output index (COi) were assessed non-invasively using a thoracic bioelectrical impedance device (PhysioFlow PF-05, Paris, France). The oxygen pulse (O2pulse) was calculated as VO2/HR. 2.5. ANS Function ANS function was assessed by measuring HRV. After approximately 10 min of rest, four pads were placed on the wrists and ankles using an HRV meter (LAXTHA; CANS-3000, Daejeon, Korea), and participants' HRV was measured in the resting condition. The following parameters were evaluated: Standard deviation (SD) of successive di erences (SDNN) and root mean square of successive di erences

Daejeon, Korea), and participants' HRV was measured in the resting condition. The following parameters were evaluated: Standard deviation (SD) of successive di erences (SDNN) and root mean square of successive di erences

Int. J. Environ. Res. Public Health2020,17, 1934 5 of 15 (RMSSD) for the time domain methods and low frequency (LF) band, high frequency (HF) band, and LH/HF band ratio for the frequency domain methods [33]. 2.6. Immune Function To assess immune function, white blood cell (WBC), eosinophil, neutrophil, basophil, natural killer (NK) cell, B cell and T cell counts were measured before and after the intervention. Three milliliters of blood were collected between 8:00 and 10:00 a.m. after 12 h of fasting. All blood samples were placed in an anticoagulant heparin tube and centrifuged at 3500 rpm for 10 min, and the serum was collected and rapidly frozen at 70 C. Thereafter, the frozen or refrigerated serum was commissioned by the Clinical Laboratory of Green Cross Medical Foundation and analyzed using the method described below. In detail, WBC, neutrophil, eosinophil, and basophil counts were measured via ow cytometry using a cellpack kit (Sysmex, Kobe, Japan). NK cell, B cell, and T cell counts were analyzed using FC500 (Beckman Counter, CA, USA) and measured via ow cytometry using an NK cell kit (Beckman Coulter, Paris, France), a CD19-PE kit (Beckman Coulter, Paris, France), and a CD3-PC5 kit (Beckman Coulter, Paris, France), respectively. 2.7. Athletic Performance To evaluate athletic performance, VO2max was measured before and after the intervention with the modi ed BRUCE protocol for graded exercise testing on a treadmill (S25TX, SFET, Seoul, Korea) using a K5 breath by breath auto metabolism analyzer (K5, Cosmed, Rome, Italy). The graded exercise test was completed when the following three criteria were satis ed: (1) VO2plateau: No further increase in oxygen use per minute even with an increase in work performed, (2) HR within 10 beats of the age-predicted HRmax: This is the basis for using participants' HRmax as a surrogate for the VO2max when designing personal training programs, and (3) plasma (blood) lactate concentrations of >7 mmol/L. The 3000-m time trial records were measured on a 400-m track at sea level in Seoul between 9:00 and 10:00 a.m. (temperature=22–24 C; humidity=60–80%; wind=0–10 km/h). To avoid the e ect of racing strategies, all starts

for using participants' HRmax as a surrogate for the VO2max when designing personal training programs, and (3) plasma (blood) lactate concentrations of >7 mmol/L. The 3000-m time trial records were measured on a 400-m track at sea level in Seoul between 9:00 and 10:00 a.m. (temperature=22–24 C; humidity=60–80%; wind=0–10 km/h). To avoid the e ect of racing strategies, all starts were staggered by at least 2 min. 2.8. Statistical Analysis Means and SDs were calculated for each primary dependent variable. Normality of distribution of all outcome variables was veri ed using the Sharpiro-Wilk test. The two-way analysis (time group) of variance with repeated measures of the “time” factor was used to analyze the e ects of the training methods on each dependent variable. Partial eta-squared ( 2) values were calculated as measures of the e ect size. When a signi cant interaction e ect was found, the Bonferroni post-hoc test was used to identify within-group changes over time. Additionally, the pairedt-test was used to compare between the post- and pre-training values of the dependent variables in each group separately. A priori power analysis was performed with G-power for the energy metabolic parameter (VO2during 30-min of submaximal exercise) based on previous research [1], indicating that a sample size of 14 participants (7 subjects per group) would be required to provide 80% power at an -level of 0.05. We anticipated a dropout rate of>10% and aimed for a starting population of 20. All analyses were performed using the Statistical Package for the Social Sciences version 24.0 (IBM Corp., Armonk, NY, USA). The level of signi cance was set at 0.05 (a priori). 3. Results 3.1. Body Composition Data on the body composition in both groups before and after training are shown in Table. No signi cant interaction was observed in all body composition parameters, i.e., body composition did not a ect the change in the other dependent variables.

The study investigates hypoxic training's impact on athletic performance and immune function in runners.