The Effect of Surgical Mask Use in Anaerobic Running Performance

restrictions stipulate the mandatory use of surgical masks during outdoor and indoor physical activities. The impact of this on athletic performance and especially on anaerobic physical activities is poorly known. The aim of the present research was to analyze the effect of surgical mask use on the anaerobic running performance of athletes. Modi cations in running time, blood lactate, blood glucose, blood oxygen saturation, subjective perceived stress, rating of perceived exertion, and heart rate variability were measured in 50 m and 400 m maximal running tests with and without the use of surgical masks in 72 athletes. The use of a surgical mask increased blood lactate concentration, sympathetic autonomic modulation, perceived exertion, perceived stress, and decreased blood oxygen saturation in 50 and 400 m running tests. Thus, the higher levels of blood lactate and lower blood oxygen saturation require adaptation of the athlete's rest and recovery periods to the acute workload. The higher level of sympathetic activation makes the acute and chronic control of autonomic modulation essential for an ef cient training periodization. Finally, the use of acid buffers such as bicarbonate or sodium citrate would

Thus, the higher levels of blood lactate and lower blood oxygen saturation require adaptation of the athlete's rest and recovery periods to the acute workload. The higher level of sympathetic activation makes the acute and chronic control of autonomic modulation essential for an ef cient training periodization. Finally, the use of acid buffers such as bicarbonate or sodium citrate would be a recommended ergogenic strategy. Keywords:COVID-19; blood oxygen saturation; rating of perceived exertion; glucose; sport performance 1. Introduction COVID-19 is an infectious disease caused by the severe acute respiratory syndrome coronavirus (SARS-CoV-2), the rapid spread and contagiousness of which has led to the COVID-19 pandemic [1]. Governments have been forced to adopt containment measures to control its spread and to prevent healthcare systems from collapsing. Thus, restrictive and limiting measures were taken in public spaces, such as the mandatory use of face masks. This policy was extended to sports practice due to the impossibility of maintaining social distance, and while exercising either outdoors and indoors due to increased respiratory volume and greater risk of contagiousness [2]. Authors relate that one of the populations that could suffer more from the consequences and restrictions of COVID-19 are athletes, especially professional ones [3]. Their daily routines are in con ict with the limitations and restrictions, which could be a cause of loss of performance and adaptations, limiting the acquisition of new abilities and performance improvements [4]. Athletes already perceive COVID-19 to be having a negative effect on their physical activity pro le [5]. Some authors suggest interventions to improve psychological exibility and coping to reach an optimal and adaptive psychophysiological status [4,6]. Regarding masks, there is a large controversy around their use while exercising, es- pecially among athletes. Authors suggest that wearing a mask forms a closed circuit of inspired and expired air, which induces a hypercapnic environment due to inadequate oxygen supply and rebinding of carbon dioxide [7]. Thus, producing an acidic environment Appl. Sci.2021,11, 6555.

mask forms a closed circuit of inspired and expired air, which induces a hypercapnic environment due to inadequate oxygen supply and rebinding of carbon dioxide [7]. Thus, producing an acidic environment Appl. Sci.2021,11, 6555.

Appl. Sci.2021,11, 6555 2 of 8 both at the alveolar and blood vessel levels, leading to physiological alterations [8] and symptoms such as fatigue, discomfort, dizziness, headache, shortness of breath, muscular weakness, and drowsiness [9]. This situation may lead to decreased hemoglobin saturation due to the to increased CO2partial pressure, and increase aortic pressure and left ventricu- lar pressure, leading to an upsurge of cardiac overload and coronary demand [10] capable of directly affecting sports performance. However, other authors suggest no impact on exercise capacity and performance [11], even while wearing a FPP2/N95 mask. Further- more, a recent review suggested that wearing face masks while exercising has only small effects on physiological responses and no effect on exercise performance [12]. In line with this, authors showed that a 1 h treadmill walk at 50–60% of maximal workload predicted maximal heart rate [13] (5.6 km/h, 0% grade) [14]; 30 min steady-state cycling at 50% of maximal workload [15], 10 min walk on a treadmill [16], or a 6 min treadmill walk (4 km/h, 10% grade) [17] while wearing a mask have no effects on performance. However, these studies suggesting non-impaired physical performance focus on a healthy population and medium to light physical activity, but high intensity activity is not considered. Thus, information about the effect of mask use in high intensity physical activities is still poorly known. For this reason, we proposed the present research with the aim of analyzing the effect of surgical mask use on the anaerobic running performance of athletes. The initial hypothesis was that there would be a decrease of anaerobic running performance wearing a surgical mask. 2. Material and Methods 2.1. Participants We analyzed 72 recreational athletes (27 women, 45 men, 28.1 5.8 years,169.3 9.4 cm, 70.7 10.1 kg, 7.0 3.2 years of training in athletics club). The research procedure was done following the Declaration of Helsinki (revised in Brazil, 2013) and approved by the Ethics Committee of the University (CIPI/18/074). Before starting the study, all participants were informed about the process to be carried out and gave their voluntary written informed consent. 2.2. Procedure To

70.7 10.1 kg, 7.0 3.2 years of training in athletics club). The research procedure was done following the Declaration of Helsinki (revised in Brazil, 2013) and approved by the Ethics Committee of the University (CIPI/18/074). Before starting the study, all participants were informed about the process to be carried out and gave their voluntary written informed consent. 2.2. Procedure To reach the study aim, participants performed two anerobic running tests (50 m and 400 m) in an outdoor running track eld with and without surgical mask, between 8:30 a.m. and 10.50 a.m., temperature of 22.1 0.5 C, and 40.2 2.3% of humidity, in two different days separated by 48 h. The inclusion criteria were membership in an athletic club, a minimum of ve years of training and experience, and negative PCR result one week before testing. The exclusion criteria were use of ergogenic aids, use of any other non- surgical mask, injury in the last 3 months, presence of COVID-19 symptomatology/positive in the last 4 months, presence of COVID-19 symptomatology during the week of the test, or direct contact with a positive case. Participants were then randomly divided into two groups, the rst group conducted the rst evaluation day of the test with mask and the second evaluation day without the mask. The other group conducted the rst evaluation day without mask and the second evaluation day with the mask. In both days, participants provided a basal sample, then began a standardized warm up consisted of 5 min of running (light aerobic), joint mobility of the main joint axes, ballistic stretching, and 5 speed progressions as reported in previous research [18]. Then, they conducted a 50 m sprint test at maximum intensity and after 20 min of recovery performed a 400 m test at maximum intensity. These two tests are both considered anaerobic, excellent tests of this metabolic pathway. The 50 m is an eminently anaerobic alactic test, while 400 m is a lactic acid power test. Before and after tests the following parameters were evaluated [18]: Body height and weight by a SECA model 714 following previous procedures [19].

400 m test at maximum intensity. These two tests are both considered anaerobic, excellent tests of this metabolic pathway. The 50 m is an eminently anaerobic alactic test, while 400 m is a lactic acid power test. Before and after tests the following parameters were evaluated [18]: Body height and weight by a SECA model 714 following previous procedures [19]. Rating of perceived exertion by the Borg Scale (6–20) [20]. Subjective Perceived Stress (0–100) [21] as in previous psychophysiological research.

Appl. Sci.2021,11, 6555 3 of 8 Blood oxygen saturation by an oximeter OXYM4000 (Quirumed, Madrid, Spain), placed in the index nger of the right arm. Blood glucose concentration by the analysis of 5 L of capillary nger blood using a portable analyzer (One Touch Basic, LifeScan Inc., Madrid, Spain). Heart Rate (HR) and Heart Rate Variability (HRV) was recorded by Polar Team Pro Sensor, Polar Electro, Kempele, Finland) during the 15 min prior to warming up and during the athletic tests, following the procedures of previous research [22]. The Polar system has a sampling frequency of 1000 Hz and is able to register the RR intervals (time interval between R waves of the electrocardiogram) for the analysis of HRV and the number of beats per minute for the HR analysis. The HRV data collected was analyzed by the Kubios HRV v2.2 software program (University of Kuopio, Kuopio, Finland) with no correction factor, since the measurements obtained were clean and free of noise. The following HRV variables were analyzed [23]: # Time-Domain. RMSSD (root mean square of successive differences between normal heartbeats, which re ects the beat-to-beat variance in HR and is the primary time- domain measure used to estimate the vagally mediated changes re ected in HRV), PNN50% (the percentage of adjacent NN intervals that differ from each other by more than 50 m, closely correlated with PNS activity) and SDNN (the standard deviation of the average normal-to-normal (NN) intervals for each of the 5 min segments) were analyzed. # Frequency-Domain (Spectral Measures) Analysis. We analyzed the low-frequency (LF) and high-frequency (HF) power components in normalized units (n.u). The frequency ranges where, HF: 0.15–0.40 Hz and LF: 0.04–0.15 Hz. # Nonlinear domain analysis. SD1 and SD2 were measured to re ect the uctuations of the HRV via a Poincar²chart, physiologically, on the transverse axis. SD1 re ects parasympathetic activity while SD2 re ect the long-term changes of RR intervals and is considered an inverse indicator of sympathetic activity. 2.3. Statistical Analysis The SPSS statistical package (version 21.0; SPSS, Inc., Chicago, IL, USA) was used to analyze the data. Normality assumptions

ect the uctuations of the HRV via a Poincar²chart, physiologically, on the transverse axis. SD1 re ects parasympathetic activity while SD2 re ect the long-term changes of RR intervals and is considered an inverse indicator of sympathetic activity. 2.3. Statistical Analysis The SPSS statistical package (version 21.0; SPSS, Inc., Chicago, IL, USA) was used to analyze the data. Normality assumptions were checked with a Kolmogorov–Smirnov test. A two-factor mixed ANOVA test was used to compare the effect of the test (basal, 50 m, 400 m), the effect of wearing a surgical mask, and the interaction between the type of test and the effect of wearing a surgical mask, together with a Bonferroni post hoc test to analyze comparisons pairwise. The level of signi cance for all the comparisons was set at p 0.05. 3. Results The results are reported with their mean and standard deviation. Table results of psychophysiological results of tests. There was a signi cant effect of surgical masks in the performance of tests. Participants not wearing surgical masks had better time (p< 0.05) in both tests (8.55 s vs. 9.62 s in 50 m, 74.9 s vs. 79.4 s in 400 m). There was a signi cant effect of surgical masks on glucose and blood lactate levels. Participants not wearing a surgical mask had lower values of glucose (p< 0.05) (92.8 mg/dL vs. 106.0 mg/dL) and blood lactate (8.96 mmol/L vs. 13.0 mmol/L) at the 400 m test. There was a signi cant effect of surgical mask wearing on the rating of perceived exertion (RPE). Participants not wearing surgical masks had lower values of RPE (p< 0.05) at the 400 m test (17.5 vs. 18.7). There was a signi cant effect of surgical masks on the blood oxygen saturation (BOS) in all tests. Participants not wearing surgical masks had higher values of BOS (p< 0.05) at the 50 m test (97.8% vs. 95.2%), and 400 m test (98.1% vs. 96.7%). In general, there were higher means of stress, RPE and HR at the 400 m vs. 50 m and basal, and between 50 m and basal too.

oxygen saturation (BOS) in all tests. Participants not wearing surgical masks had higher values of BOS (p< 0.05) at the 50 m test (97.8% vs. 95.2%), and 400 m test (98.1% vs. 96.7%). In general, there were higher means of stress, RPE and HR at the 400 m vs. 50 m and basal, and between 50 m and basal too.

Appl. Sci.2021,11, 6555 4 of 8 Table 1.Psychophysiological modi cations in the 50 m and 400 m tests with and without mask. Basal Test 50 m Test 400 m Test No Mask Mask No Mask Mask No Mask Mask Mask and Test Effect M SD M SD M SD M SD M SD M SD F p 2 Time (s) N/A N/A N/A N/A 8.55 *, ‡‡‡ 0.84 9.62 *, ‡‡‡ 1.76 74.9 *, ‡‡ 9.38 89.2 *, ‡‡ 13.9 2.582 0.011 0.025 Lactate (mmol/L) N/A N/A N/A N/A 5.12 ‡‡‡ 2.74 5.88 ‡‡‡ 3.70 8.96 *, ‡‡ 3.38 13.0 *, ‡‡ 4.98 0.941 0.034 0.008 Glucose (mg/dL) 97.5 9.42 95.7 ‡‡ 8.36 96.2 ‡, ‡‡‡ 20.3 93.6 ‡, ‡‡‡ 22.5 92.8 *, ‡, ‡‡‡ 16.95 106.0 *, ‡, ‡‡‡ 21.6 19.001 0.000 0.136 RPE (0-20 rank) 7.57 ‡‡, ‡‡‡ 1.24 7.85 ‡‡, ‡‡‡ 2.00 13.7 ‡, ‡‡‡ 3.75 13.4 ‡, ‡‡‡ 2.9 17.5 *, ‡, ‡‡ 1.82 18.7 *, ‡, ‡‡ 1.65 3.117 0.045 0.050 SPS (0-100 rank) 28.1 ‡‡, ‡‡‡ 20.7 21.9 ‡‡, ‡‡‡ 22.8 37.0 ‡, ‡‡‡ 25.7 36.7 ‡, ‡‡‡ 24.5 52.1 ‡, ‡‡ 6.1 61.6 *, ‡, ‡‡ 9.42 0.587 0.036 0.005 HR (bpm) 70.8 ‡‡, ‡‡‡ 15.5 72.0 ‡‡, ‡‡‡ 11.8 106.3 ‡ 35.3 110.6 ‡ 35.1 152.4 ‡ 15.9 167.6 ‡ 25.92 0.093 0.911 0.001 BOS (%) 97.5 0.97 97.8 ‡‡, ‡‡‡ 0.78 97.8 * 1.49 95.2 *, ‡, ‡‡‡ 6.02 98.1 * 1.31 96.7 *, ‡, ‡‡ 3.06 7.397 0.003 0.059 M: Mean. SD: Standard Deviation. F: Fisher-Snedecor test. 2: Partial eta squared. N/A: Not available. RPE: Rate of Perceived Exertion. SPS: Subjective Perceived Stress. HR: Heart Rate. BOS: Blood Oxygen Saturation. HGS: Handgrip Strength.‡Difference with basal test (p< 0.05). ‡‡Difference with 50 m test (p< 0.05).‡‡‡Difference with 400 m test (p< 0.05). * Differences between no mask/mask groups (p< 0.05). Table surgical masks in RMSSD values. Participants not wearing surgical masks had lower values(p< 0.05) at the 50 m test (9.72 ms vs. 21.2 ms). There was a signi cant effect of surgical masks on pNN50 values. Participants not wearing surgical

50 m test (p< 0.05).‡‡‡Difference with 400 m test (p< 0.05). * Differences between no mask/mask groups (p< 0.05). Table surgical masks in RMSSD values. Participants not wearing surgical masks had lower values(p< 0.05) at the 50 m test (9.72 ms vs. 21.2 ms). There was a signi cant effect of surgical masks on pNN50 values. Participants not wearing surgical masks had lower values (p< 0.05) at the 400 m test (0.00% vs. 0.32%). There was a signi cant effect of surgical masks on SD1 values. Participants not wearing surgical masks had lower values (p< 0.05)at the 50 m test (6.89 ms vs 9.02 ms). There was a signi cant effect of surgical masks on HF values. Participants not wearing surgical masks had higher values (p< 0.05) at the basal test (29.7 vs. 21.4). If we take time domain HRV measurements by group, values are usually higher in basal vs. 50 m and 400 m tests, and in 50 m and 400 m test. The opposite happens if frequency domain values are observed, usually being higher in 400 m vs. 50 m and basal, and in 50 m vs basal test. Table 2.Heart rate variability modi cations in the 50 m and 400 m tests with and without mask. Basal Test 50 m Test 400 m Test No Mask Mask No Mask Mask No Mask Mask Mask and Test Effect M SD M SD M SD M SD M SD M SD F p 2 SDNN (ms) 32.5 ‡‡, ‡‡‡ 10.6 31.7 ‡‡, ‡‡‡ 7.16 24.27 ‡, ‡‡‡ 16.2 31.7 ‡, ‡‡‡ 7.16 8.86 ‡, ‡‡ 5.70 12.8 ‡, ‡‡ 24.0 1.574 0.211 0.013 RMSSD (ms) 23.0 ‡‡, ‡‡‡ 6.37 21.2 ‡‡, ‡‡‡ 6.02 21.2 *, ‡, ‡‡‡ 6.39 9.72 *, ‡ 6.02 17.17 *, ‡, ‡‡‡ 2.59 8.20 ‡, ‡‡ 5.19 4.716 0.010 0.038 pNN50 (%) 4.29 ‡‡, ‡‡‡ 3.14 3.78 ‡‡, ‡‡‡ 3.52 0.60 ‡, ‡‡‡ 1.52 1.12 ‡, ‡‡‡ 1.79 0.00 *, ‡, ‡‡ 0.00 0.32 *, ‡, ‡‡ 1.01 1.815 0.176 0.015 LF (n.u.) 70.4 *, ‡‡, ‡‡‡ 18.7 78.6 *, ‡‡, ‡‡‡ 11.1 80.6 ‡,

*, ‡ 6.02 17.17 *, ‡, ‡‡‡ 2.59 8.20 ‡, ‡‡ 5.19 4.716 0.010 0.038 pNN50 (%) 4.29 ‡‡, ‡‡‡ 3.14 3.78 ‡‡, ‡‡‡ 3.52 0.60 ‡, ‡‡‡ 1.52 1.12 ‡, ‡‡‡ 1.79 0.00 *, ‡, ‡‡ 0.00 0.32 *, ‡, ‡‡ 1.01 1.815 0.176 0.015 LF (n.u.) 70.4 *, ‡‡, ‡‡‡ 18.7 78.6 *, ‡‡, ‡‡‡ 11.1 80.6 ‡, ‡‡‡ 20.8 77.6 ‡‡‡ 16.8 47.8 ‡, ‡‡ 19.0 53.4 ‡, ‡‡ 24.2 2.640 0.073 0.021 HF (n.u.) 29.7 *, ‡‡, ‡‡‡ 18.6 21.4 *, ‡‡, ‡‡‡ 11.1 29.7 ‡, ‡‡‡ 18.6 22.1 ‡‡‡ 16.5 52.3 ‡, ‡‡ 18.8 46.0 ‡, ‡‡ 23.8 2.782 0.064 0.022

This study analyzes how surgical masks affect anaerobic running performance.