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Article

COVID-19 as a Factor Influencing Maximal Heart Rates among Male University Students

by
Robert Podstawski
1,*,
Krzysztof Borysławski
2 and
Jacek Wąsik
3
1
Human Wellness Research Laboratory, Department of Physiotherapy, School of Public Health, University of Warmia and Mazury in Olsztyn, 10-957 Olsztyn, Poland
2
Institute of Health, Angelus Silesius University of Applied Sciences in Wałbrzych, 58-300 Wałbrzych, Poland
3
Institute of Physical Culture Sciences, Jan Dlugosz University in Czestochowa, 42-200 Czestochowa, Poland
*
Author to whom correspondence should be addressed.
Appl. Sci. 2024, 14(14), 6146; https://doi.org/10.3390/app14146146
Submission received: 12 June 2024 / Revised: 5 July 2024 / Accepted: 9 July 2024 / Published: 15 July 2024
(This article belongs to the Special Issue Advances in Physical Activity for Sport Performance)
Versions Notes

Abstract

:
Background: The present study aimed to explore the relationship between COVID-19 and HRmax during maximal exertion; Methods: The study was conducted on 66 male students aged 17.4 to 24.0 years, 50% of whom suffered from COVID-19. Their body composition was assessed via bioelectrical impedance analysis; their physical activity (PA)—using the International Physical Activity Questionnaire; and their HRmax—using the 12-Minute Cooper Test on a Rowing Ergometer (12-MCTRE); Results: Both the healthy students (G1) and non-hospitalized COVID-19 sufferers (G2) were significantly (p < 0.001) more engaged in PA than the hospitalized COVID-19 sufferers. They had significantly lower body mass, BMI, waist-to-hip ratio, and visceral fat level, with the G1 ones also having lower scores of body fat mass, fat-free mass, and skeletal muscle mass (p values: <0.001–0.017). The highest HRmax = 192 bpm was recorded for G1 students, being significantly higher than the values measured for G2 (by 7 bpm), and G3 (by 16 bpm); Conclusions: Men suffering from COVID-19 and hospitalized exhibited significantly lower levels of PA and motor fitness, and had poorer body composition markers (primarily adiposity to the point of severe overweight). This likely explains their diminished HRmax compared with healthy men.

1. Introduction

The increase in cardiac output during physical exertion is due to the increased heart rate and stroke volume. In effect, cardiac output can be calculated as a heart rate (HR) multiplied by a stroke volume (SV), the latter defined as the volume of blood pumped from the left ventricle within one contraction [1]. As such, the easiest way to assess cardiovascular response to exercise is by measuring and recording the associated spike in HR [2]. HR starts to increase almost immediately after the onset of exercise due to reduced cardiac parasympathetic activity, then stabilizes after 2–5 min at a level corresponding to the intensity of the effort. At <110 bpm, HR escalation is almost exclusively mediated by the inhibition of vagal activity. Once levels above 130–170 bpm are reached, the heart is almost completely disengaged from inhibitory parasympathetic mechanisms [3]. Additionally, a short time after the onset of exercise (5–20 s), cardiac sympathetic innervation and blood vessels start to increase in activity, further accelerating the HR. Finally, at peak effort, HR reaches its maximum value—HRmax [4]. The maximum heart rate (HRmax) is usually defined in terms of the highest HR attained during maximal exertion [5]. Its value shows limited interindividual variability, instead being strongly correlated with age [6]. Children and adolescents (20 and under) have an HRmax of approx. 200 bpm. Over the age of 20, the value decreases at intervals of approx. 1 bpm per year, meaning that the approximate HRmax of adults can be estimated from one of the several widely used formulae: HRmax = 220 − age [7], HRmax = 205 − 0.5 × age [8], HRmax = 208 − 0.7 × age [9], HRmax = 206 − 0.88 × age [10], and HRmax = 211 − 0.64 × age [11].
Age is not the only factor; however, HR values achieved at peak exercise can also differ depending on the type of exercise itself [12,13]. Age-based prediction equations have been used to assess HRmax in sport populations [14]. Maximal values are reached during those physical activities that engage larger numbers of muscles, such as running. Conversely, cycling produces slightly lower HR values [5]. Major modifiable risk factors that affect the heart—and thus its maximal performance—include high lipid values, diabetes, overweight, and obesity [15].
HRmax is a common metric of exercise intensity in sports training in general and in team sports in particular. Planning out sufficiently intense exercise programs is the “bread and butter” of coaches and fitness trainers [14]. Indeed, such coaches and fitness trainers often refer to HRmax when setting HR intensities for aerobic exercise regimes for athletes, using protocols such as the Karvonen method [16]. HRmax is also widely used as a health parameter against which medical professionals prescribe treatment [9]. Exercise tests that assess HRmax are performed in asymptomatic healthy people to detect hidden conditions, minimize exercise-related risks, and evaluate motor performance [5]. The earliest report of a 480 bpm ventricular rhythm in the medical literature was ascribed to supraventricular tachyarrhythmia, most likely atrial fibrillation triggered by the accessory ventricular pathways [17]. One way to achieve the highest heart rate (HR) is by conducting a maximum symptom-limited cardiopulmonary exercise test (CPET) [18], also known as the graded exercise test (GXT), which can be performed in a laboratory or in field conditions [14]. The choice between a treadmill and a cycle can have a huge impact on the test results [19]. The differences are not limited to HRmax, but extend to other performance metrics as well [20,21]. The running CPET tends to produce a higher score [20]. Conversely, cycling CPET is associated with lower rates of attributes, given the more stable position assumed for the exercise [19]. As a result, the cycling test tends to be used in situations that call for more accurate measurements (e.g., in clinical settings) [18,22].
Generally, untrained individuals have high HR values both in rest and maximal physical exertion states when compared to trained individuals [23,24]. Unfortunately, unlike in the case of athletes, research on measuring HRmax among common people is carried out very rarely [25]. One of the reasons is the high risk of adverse health effects that may occur after very intense exercise in people who are not necessarily sick but are not physically active [26,27]. Nonetheless, HRmax tests are performed, for example, in people struggling with obesity [28]. However, according to the standard protocol, such persons should be prepared for intense physical activity by implementing special physical activity programs several weeks prior to the actual measurement [29]. From a physiological point of view, an obese person with poor cardiometabolic parameters is not able to achieve such high HRmax values during physical exercise as a person with normal fat tissue content [30]. Hence, for the above reasons, some findings indicate that the “200 − 0.48 x age” equation, derived from a sample of obese adults, should be the first choice for training or rehabilitation centers at the time of predicting HRmax in adolescents with obesity [31].
University students represent a selected group with great social potential. Managerial staff have always come and will continue to come from the intelligentsia, and representatives of intellectuals belong to opinion-forming circles and can modulate social attitudes [32]. Motor fitness is absolutely one of the basic components of human health, and its relationship with the COVID-19 pandemic should be investigated in order to develop appropriate health-promoting programs for academic youth. It may be speculated that students who contracted COVID-19 have developed a set of features that are strongly negatively correlated with their motor skills [33] and that the nearly three-year-long pandemic has had a negative impact on their level of physical performance [34]. So far, there has been no record of scientific research addressing these issues. Moreover, taking into account the methodology of scientific research in the examined area, to the best of our knowledge, there has been no research harnessing the rowing ergometer to measure HRmax among physically inactive young adults with COVID-19. Physical inactivity refers to the lack of moderate-to-vigorous physical activity in a person’s lifestyle. It is distinct from sedentary behavior [35]. Investigations conducted in many countries [36,37] and showing mediocre results in the physical activity and motor fitness of university students indicate that it is crucial to get their attention and build their awareness to at least maintain a satisfactory level of physical activity and motor fitness [38]. An overview of the literature has revealed a lack of research assessing HRmax values in male students. The potential relationships of this parameter with COVID-19 disease have not been investigated either. There are also very few published studies that have harnessed the rowing ergometer to assess HRmax among athletes, and those that exist focus mainly on rowers [39,40]. Accordingly, the aim of this study was to examine the relationship between COVID-19, physical activity (PA), body composition, and physiological characteristics, with special attention paid to HRmax during peak effort in the 12-Minute Cooper Test on the Rowing Ergometer (12-MCTRE) performed by male university students.

2. Materials and Methods

2.1. Participant Selection

The study was conducted in May 2023 (during the summer term) on 66 male volunteers: full-time university students aged 17.4–24.0 years (19.93 ± 1.66). It included only men who did not practice any sports competitively, which allowed for the elimination of the results that could distort the natural image of the studied population due to the level of training and movement skills. Hence, the surveyed male students followed the same curriculum of fitness classes as their peers who were not recruited for the study. Due to limited logistic conditions, i.e., the possibility of carrying out the research in the shortest possible time and in very similar laboratory conditions, the measurements were limited only to men, especially because they represented the vast majority in the surveyed student groups. Furthermore, female participants could also be menstruating during the study, which would negatively affect their performance and the ultimate results of the experiment. The control group comprised 33 men (50% of all subjects) who were not infected with SARS-CoV-2 and did not have COVID-19. Potential participants were informed about the purpose of the study during obligatory classes of physiology and anthropomotorics at the University of Warmia and Mazury in Olsztyn (UWM). The students who agreed to participate in the study (76 men) were notified by e-mail and text message whether they met the inclusion criteria and were provided with the date of final recruitment. Ten students were excluded from the study due to not having a medical certificate confirming that they had contracted COVID-19. Sixty-six male university students (33 COVID-19 sufferers and 33 healthy controls) meeting the inclusion criteria were recruited for the study. Hospitalized COVID-19 sufferers were required to present a doctor’s certificate from the hospital in which they were examined and/or treated. During the physical pre-test, a physician verified that the subjects did not take any medications or dietary supplements, were in good health, and had no history of blood diseases or other diseases affecting biochemical and biomechanical markers. None of the evaluated participants had respiratory or circulatory disorders. Physical activity (PA) levels (for the quantitative analysis) were evaluated with the use of the Polish short version of the standardized and validated International Physical Activity Questionnaire (IPAQ) [41]. The participants declared their average weekly number of minutes dedicated to PA (a minimum of 10 min) prior to the study. The energy expenditure associated with the declared weekly PA levels was expressed in terms of MET-min/week [42]. The MET is the ratio of the work metabolic rate to the resting metabolic rate, and 1 MET denotes the amount of oxygen consumed in 1 min, which is estimated at 3.5 mL/kg/min. Based on the declared frequency, intensity, and duration of PA (“how often, how much, how long”), the respondents were classified into groups characterized by low PA (<600 MET-min/week), moderate PA (600 to 1500 METs per week), and high PA (≥1500 MET-min/week).

2.2. Ethical Statement

The research was performed in compliance with the guidelines and policies of the Health Science Council and the Declaration of Helsinki and approved by the Ethics Committee of the University of Warmia and Mazury (37/2011). Each participant was provided with detailed information about the purpose of the study, potential risks, and the research protocol followed. The latter contained detailed information about measurement methods and motor test techniques that could be practiced during training sessions directly before the study. All male students gave voluntary and informed consent to participate in the study by signing consent forms.

2.3. Procedures, Data Collection, and Equipment

The participants received comprehensive information about the rules regarding the maximum symptom-limited cardiopulmonary exercise test (the 12-min Cooper Test on Rowing Ergometer) preceding the study. They were asked to drink at least 1 L of water on the day of the test and 0.5 L of water 2 h before the session. The participants did not consume any foods or other fluids until the final body measurements, when the experiment was completed. Anthropometric measurements were performed before motor tests. The students were asked not to engage in any strenuous training on the day before the trial, and they assisted the authors in performing the measurements.

2.3.1. Anthropometric Measurements and Body Composition Analysis

Body height was measured to the nearest 1 mm with a calibrated InLab S50 stadiometer (InBody Co., Seoul, Republic of Korea) in accordance with the relevant guidelines. Body mass (measured to the nearest 0.1 kg), the body mass index (BMI), and body composition parameters, including percent body fat (PBF) and skeletal muscle mass (SMM), were determined by bioelectrical impedance with an InBody 270 Bioelectrical Impedance Analyzer (BIA) (Biospace Co., Inc., Seoul, Republic of Korea). This foot-to-foot, hand-to-hand, and hand-to-foot device features two stainless steel foot-pad electrodes mounted on a platform scale and a tetrapolar 8-point tactile electrode system with two stainless steel handles. Bioelectrical impedance analysis has been found to be a viable tool for body composition measurements and competitive with other methods, such as DXA [43,44]. The platform scale uses a single load cell to measure body mass (and stature) and calculate the BMI. The PBF is calculated by summing the results of segmental lean analysis to determine the total lean body mass, fat mass, and the proportion of fat mass to total body mass. Muscle mass percentage (M%) is calculated by evaluating water content in the segmental regions with the use of the provided equations. Visceral fat level (VFL) is estimated with the regression equations (provided), which—according to the manufacturer—were derived by comparing visceral fat in computerized tomography scans and impedance in the torso region in the segmental lean analysis.

2.3.2. Twelve-Minute Cooper Test on Rowing Ergometer (12-MCTRE)

The 12-MCTRE was performed on a Concept 2 PM5 standardized rowing ergometer (PH Markus, Szczecin, Poland), which is widely used to measure strength endurance (SE) in athletes [45]. The following parameters were measured during the rowing ergometer test: maximum, average, and minimum heart rate (HRmax,avg,min); total distance covered within 12 min; total power generated [W]; mean time-to-500 m; caloric burn rate [kcal] per hour; strokes per minute—SPM [s/m].
Each participant wore a Polar H10 heart rate sensor (Polar Electro Oy, Kempele, Finland) on a chest strap. The ergometer was programmed and paired with the ErgData app (https://www.concept2.com/support/ergdata, 1 February 2023) and the HR sensor. The test was initiated by a verbal start cue. The system activated automatically upon engaging the handle, deactivated automatically after 12 min, and logged the data in the app. The data from the ErgData app were recorded in an Excel spreadsheet. The participants were instructed on how to correctly perform the 12-MCTRE beforehand, and they were allowed some time to practice. The exact test was preceded by an active warm-up (10 min). The warm-up routine included 5 min of rowing and stretching exercises [46].

2.3.3. Correct 12-MCTRE Technique

The participants’ endurance strength abilities were evaluated based on the distance (in m) covered during the 12-MCTRE. The row stroke is divided into two phases according to the technique presented by Podstawski et al. [33].
Phase I (pulling the bar): from a starting position with the knees bent, arms straight, and the back arched forward (a), the lower limbs are gradually straightened (b), the torso is abducted backward to a maximum of 45° (c), and the bar is pulled towards the chest (d).
Phase II (reversal): from a position with the legs straight and the torso abducted and pulled back (d), the arms are extended, the torso is bent forward (c), the knees are bent as much as possible, with the torso bent forward and the arms straight (a).
The participants were expected to complete the distance within the assumed time limit (12 min).
Comments: When pulling the bar, the movement begins with the legs extended and the torso abducted backward, and ends with the arms (elbows) flexed and the bar pulled to the chest (between the nipples and the xiphoid process). During bar inversion, the movement begins with the arms straight and the torso bent forward and ends with the knees bent (and the heels as close to the buttocks as possible).

2.3.4. 12-MCTRE Procedure for Assessing HRmax

Due to the varying degrees of physical activity (PA) among the subjects (Table in Section 3.2, it was assumed that their endurance and strength performance would be heterogeneous as well. Accordingly, the following HRmax assessment protocol was used;
  • All subjects rowed at resistance setting 10;
  • Over the first 6 min, the subjects modulated exercise intensity at their own discretion to avoid excessive effort;
  • Six minutes in, the subjects started to reduce their time-to-500 m by 5 s every minute, up until the 10-min mark;
  • Over the last 2 min, the subjects rowed at maximum intensity so as to achieve the highest possible HR, as viewed on the PM5 monitor.

2.4. Statistical Analysis

Basic descriptive statistics (mean, SD and range of variation) were calculated for each parameter. Normality of data distribution was verified with the Shapiro–Wilk test (the skewness/As index was also examined). The values of all tested parameters followed a normal distribution.
The examined variables were analyzed across 3 groups: 1. no COVID-19 (n = 33), 2. non-hospitalized COVID sufferers (n = 22), and 3. hospitalized COVID-19 sufferers (n = 11). One-way analysis of variance (ANOVA) was used to compare the three resultant arithmetic means. If ANOVA indicated a significant difference, Tukey’s HSD (Honestly Significant Difference) test was used for post hoc analysis. The calculations were performed using Statistica13 at a significance level of α = 0.05.

3. Results

Table 1 shows the characteristics (parameters) of the subjects, including their PA and their anthropometric and physiological characteristics.

3.1. PA and Anthropometric Characteristics for the Entire Test Group

On average, the subjects engaged in high levels of PA (1975 METs). Their mean BMI was within the normal range (23.8 kg/m2), with PBF = 17.3% at BFM 13.6 kg or higher and FFM of 63.5 kg. It was probably based on these values that the “weight control” recommended losing 2.2 kg to attain a “target weight” of 74.9 kg, but with an associated drop in BFM control of 3.1 kg and an FFM increase of 0.9 kg. The mean VHR for the whole group excluded gynoidal or androidal obesity.

3.2. Physiological Characteristics for the Entire Test Group

In the course of the 12-MCTRE, the subjects rowed an average distance of 2413 m, produced an average power of 112 W, and burned an average of 136 kcal. The average (HRavg) and maximum (HRmax) heart rate values were 167 and 187 bpm, respectively. Plotting the duration of exercise across intensity zones, it was found that the subjects spent most of their exercise time (370 s on average) in the 162+ bpm zone (Table 1).
Table 2 shows the characteristics (parameters) of the subjects (PA, anthropometric and physiological characteristics) by group. Group 1 (G1)—no COVID-19, Group 2 (G2)—non-hospitalized COVID-19 sufferers, and Group 3 (G3)—hospitalized COVID-19 sufferers. Significant differences were found between the groups for most of the characteristics tested.

3.3. PA and Anthropometric Characteristics by Group

Both the healthy subjects (G1) and those with COVID-19 but not hospitalized (G2) engaged in significantly (p < 0.001) higher levels of PA (high) than the hospitalized COVID-19 sufferers (G3—moderate). Furthermore, the G1 and G2 students scored significantly lower with regard to the following parameters: body weight (p range: <0.001–0.017), TBW (G1 only), proteins (G1 only), minerals (G1 only), BFM, FFM (G1 only), SMM (G1 only), BMI, PBF, target weight, and weight control, BFM control, BMR (G1 only), WHR, and VFL. It was only for body height and FFM control that no significant differences were found (Table 2).

3.4. Physiological Characteristics by Group

Healthy controls had significantly (p < 0.001) better 12-min distances than the other groups (G2 and G3). Of the latter, G2 subjects rowed significantly (p < 0.001) longer distances than the G3 ones. Very similar differences between groups were found for the following physiological characteristics: power, energy expenditure, pace avg/500 m, and HRavg (p range: <0.001–0.003). HRmax values for the healthy students (G1) were significantly higher than for the hospitalized ones (G3). Indeed, the highest actual HRmax values were recorded for the COVID-19-free group (G1—192 bpm), being 7 bpm higher than HRmax for G2 and, notably, 16 bpm higher than G3. HRmax values for G2 students were also significantly (p < 0.001) higher than those for G3 subjects (by 8 bpm). Furthermore, the students from the G1 and G2 groups spent the majority of their time in intensity zone 5 (480.8 and 298.7 s, respectively), whereas those from the G3 group tended towards zone 4 (268.8 s) (Table 2).

4. Discussion

This study aimed to examine the relationship between COVID-19, physical activity (PA), body composition, and physiological characteristics, with special attention paid to HRmax during peak effort in the 12-Minute Cooper Test on the Rowing Ergometer (12-MCTRE) performed by male university students.
Taking the sample as a whole, it seems that the maximal heart rate values (HRmax = 187 bpm) were lower (by 13 bpm) than would be expected for 20-year-old men based on the traditional estimate: HRmax = 220 − age [7]. By grouping the subjects, we were able to conduct a more in-depth analysis, which showed that the hospitalized COVID-19 sufferers had the lowest HRmax (176 bpm), i.e., 24 bpm lower than the norm. The gap was less pronounced in the men infected with COVID-19 but not hospitalized (184 bpm–16 bpm lower) and smaller still in healthy students (192 bpm), who deviated from the “220 − age” norm by only 8 bpm. It should also be taken into account that the studied group of men included those with a BMI > 30 kg/m2. Therefore, as we have already emphasized, such individuals are unable to obtain HRmax values consistent with those indicated in equations intended for normal persons [7,8,9].
Results by group (G1–G3) also shed further light on the relationship between COVID-19 and the level of PA [47], physiological and anthropometric characteristics [6,48], and HRmax. Comparatively, the hospitalized COVID-19 sufferers (G3) exhibited lower (moderate) levels of PA, whereas G1 and G2 subjects engaged in high levels of PA. A systematic review of cross-sectional studies by Oliveira et al. [49] demonstrated that cardiac autonomic function is linked to cardiorespiratory fitness and physical activity. Physical activity is positively associated with parasympathetic activity, and after 30 days of exposure to exercise, there appear to be chronic physiological adaptations [50]. Studies on males have shown that, in general, the athletes of any given age had a slightly but significantly lower HRmax than the untrained men after muscular training, at least for certain efforts [51]. Adults who practiced high-intensity physical exercise when young would be more likely to perform an effective maximum effort if necessary [52]. However, the HRmax is related not only to age but seems not to depend on an individual’s current level of aerobic training [51]. On the other hand, the age-related decrease in HRmax is similar between genders and remains unaffected by training status [9]. In turn, Whyte et al. [53] have reported that HRmax is similar between elite aerobic and anaerobically trained athletes; however, the HRmax is significantly lower in the athletes compared with their age matched sedentary counterparts. Besides, HR can (daily) be influenced by various internal and external factors such as gender, circadian cycle, blood pressure, lifestyle factors, physical activity, and mental status [54], and the male students participating in the present study were partially differentiated in terms of these factors.
That being the case, scientific evidence shows that individuals with overweight and obesity have a higher prevalence of cardiovascular disease, which is supposed to be due to autonomic dysfunction and/or metabolic disorder [55]. Many factors have been pinpointed as putative causes of this relationship, including insulin resistance, hypertension, and low HDL [56]. Even a slight variation in autonomic cardiac regulation causes severe changes in HR and rhythm. Hence, it is important to emphasize the effect of overweight and obesity on HR variability (HRV), as decreased HRV significantly increases cardiovascular mortality risk [57]. Overweight and obesity have been reported to enhance sympathetic activity, thereby suppressing parasympathetic (vagal) activity, indicating poor autonomic cardiac rhythm control in obese individuals [55]. Scientific findings strongly suggest that motor fitness is associated with a favorable HR profile, which can be affected by overweight and obesity [58]. What is more, unlike in normal people, weight management, lack of motivation, and pain are the key PA motives and barriers in people with obesity [30]. As a result, severely overweight or obese people tend to have a lower level of PA and consequently poorer motor fitness, ultimately attaining significantly lower values of HRmax than they potentially could achieve normal body composition characteristics. The present study corroborates this relationship by showing that men who obtained the lowest values of HRmax and physiological characteristics (including distance rowed and power) were also those who happened to have the highest BMI (27.7 kg/m2), BFM (21.3 kg), PBF (23.3%), VFL (8.6), and WHR (0.91).
The present study did not investigate age-related changes in HRmax or how untrained individuals compare with trained athletes. Its aim was to explore significant correlations between HRmax and COVID-19 infection, in addition to the other variables of PA, physiological characteristics, and anthropometric parameters. Practicing physical exercise regularly is widely known to be one of the major components of a healthy lifestyle and is implicated in reducing the risk of cardiovascular mortality [59,60]. And indeed, current research on SARS-CoV-2 infection seems to play into this pattern. Everyone, regardless of age, can get infected with SARS-CoV-2 and develop COVID-19, though the illness is most severe in older people with pre-existing chronic conditions. The most susceptible patients are those with chronic cardiovascular and respiratory illnesses, low physical fitness, arterial hypertension, and/or diabetes [61]. Furthermore, the physiological and/or perceptive mechanisms that define the limit of maximal effort remain not fully understood or consensually accepted [62,63]. A study on Polish university students (females and males) has shown that COVID-19 causes a significant reduction in PA and endurance-strength ability [33]. Another study [64] has demonstrated that PA restriction during the COVID-19 pandemic has led to functional changes in the bodies of students, diminishing their physical performance and their bodies’ capacity to regenerate after strenuous activity. Both female and male university students showed a deterioration in motor fitness. There have also been reports suggesting that the COVID-19 lockdown negatively influences muscular fitness status in adolescents, especially boys [65]. The COVID-19 pandemic has led to significant changes in education in 2020. The vast majority of countries have closed all educational facilities for at least some time, switching to remote learning, and the main forms of students’ motor activity in conditions of prolonged hypokinesia were individual physical exercises [66].

Strength and Limitations

The most important limitation of this study is the lack of comparable pre-pandemic data. Therefore, the study cannot conclusively demonstrate if it was SARS-CoV-2 that caused the reduction in physical activity levels and the deterioration of body composition and physiological characteristics. A strength of the study is that it proves the new 12-MCTRE method to be an effective tool for measuring HRmax in less physically active individuals, not just athletes. The ergonomics of the rowing ergometer also afford the possibility of testing people who are overweight or obese, which is inadvisable in the case of running tests.

5. Conclusions

Our study identified a group of factors that compound the negative health impacts of the COVID-19 pandemic on young males. Factors significantly correlated with COVID-19 and its more serious complications (i.e., those requiring hospitalization) include low PA, low motor fitness, and high body fat. University students with these characteristics were more likely to develop COVID-19 and attained lower HRmax values compared with non-infected men. Investigations involving measurements of the body composition and motor fitness characteristics of students with an in-depth analysis of their HRmax values should be carried out in the form of longitudinal research in each year of academic studies. Observation of transformations triggered by the onset of modern civilization and intergenerational changes provides researchers with a great deal of valuable information on the health status of successive generations. They make it possible to implement appropriate recovery programs, although no effective “healthy school” program has been developed so far.

Author Contributions

Conceptualization, R.P.; methodology, R.P.; software, K.B.; validation, K.B. and R.P.; formal analysis, K.B.; investigation, R.P. and J.W.; resources, R.P.; data curation, R.P.; writing—original draft preparation, R.P., K.B. and J.W.; writing—review and editing, R.P., J.W. and K.B.; visualization, R.P.; supervision, R.P.; project administration, R.P.; funding acquisition, R.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted upon the prior consent of the Ethics Committee of the University of Warmia and Mazury in Olsztyn (decision No. 37/2011), Poland.

Informed Consent Statement

The study involved volunteers who signed an informed consent statement.

Data Availability Statement

The access to Excel data generated during this study has been restricted by the Ethics Committee of the UWM in Olsztyn to protect the participants’ privacy. Researchers who meet the criteria for access to confidential data can submit a data request by email to podstawskirobert@gmail.com.

Acknowledgments

The authors would like to thank the male students who participated in the study.

Conflicts of Interest

The authors declare no conflicts of interest.

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Table 1. Descriptive statistics for the entire test group.
Table 1. Descriptive statistics for the entire test group.
CharacteristicMeanSDMin.Max.As *
PA and Anthropometric Characteristics
Age [years]19.931.6617.424.00.694
PA [METs/min/week]1975.33429.48750.03100.0−0.379
Body height [cm]179.755.69168.0191.0−0.178
Body mass [kg]77.1010.9655.9111.00.551
TBW [kg]46.465.6332.957.8−0.054
Proteins [kg]12.611.538.915.7−0.046
Minerals [kg]4.380.593.25.70.094
BFM [kg]13.646.164.031.80.908
FFM [kg]63.467.7545.079.2−0.046
SMM [kg]36.044.6524.745.5−0.073
BMI [kg/m2]23.832.9619.232.40.851
PBF [%]17.296.026.030.60.391
Target weight [kg]74.927.4162.193.20.379
Weight control [kg]−2.185.76−17.87.9−0.767
BFM control [kg]−3.145.18−17.84.9−1.082
FFM control [kg]0.962.020.09.12.407
BMR [Kcal]1740.70167.321342.02082.0−0.044
WHR0.850.070.71.00.529
Visceral Fat Level5.082.911.014.00.846
Physiological characteristics
Distance [m]2412.61377.161769.03115.00.007
Power [W]112.0550.7842.0227.00.407
Calories [kcal]135.7334.9487.0215.00.398
S/M [strokes/min]27.203.2320.034.0−0.203
Pace/500 m [s]150.7425.51104.0203.00.229
HRavg [bpm]166.5017.24109.0197.0−0.81
HRmax [bpm]186.7013.47144.0219.0−0.570
Intensity of effort [s]
Zone 1: 90–108 [bpm]17.8265.030.0429.05.365
Zone 2: 108–125 [bpm]52.97105.850.0474.02.932
Zone 3: 126–144 [bpm]128.96174.440.0607.01.606
Zone 4: 145–162 [bpm]149.83164.250.0603.01.154
Zone 5: >162 [bpm]370.42286.310.0715.0−0.189
Note: * AS—skewness coefficient.
Table 2. Descriptive and comparative analysis of the investigated parameters in the three analyzed groups.
Table 2. Descriptive and comparative analysis of the investigated parameters in the three analyzed groups.
ParameterGroup *Difference
G1 (n = 33)G2 (n = 22)G3 (n = 11)
MeanSDMeanSDMeanSDFp
PA and Anthropometric Characteristics
PA [METs/min/week]2116.27 3341.222013.41 3324.171476.36 1,2512.9012.60<0.001
Body height [cm]178.975.61180.436.42180.734.380.62ns
Body mass [kg]73.31 38.9976.07 38.9690.53 1,210.2714.68<0.001
TBW [kg]45.08 35.5646.455.0650.64 15.314.430.016
Proteins [kg]12.23 31.5212.591.3413.77 11.454.630.013
Minerals [kg]4.23 30.574.390.584.81 10.554.360.017
BFM [kg]11.76 34.2512.63 35.5821.29 1,26.7414.62<0.001
FFM [kg]61.55 37.6463.446.9669.24 17.284.500.015
SMM [kg]34.90 34.6563.446.9669.24 17.284.690.013
BMI [kg/m2]22.85 32.2523.34 32.2827.74 1,23.0617.69<0.001
PBF [%]15.93 34.8816.35 35.8823.25 1,26.317.86<0.001
Target weight [kg]73.10 36.5174.24 36.9081.74 1,27.606.770.002
Weight control [kg]−0.21 34.03−1.84 35.20−8.79 1,26.7412.49<0.001
BFM control [kg]−1.57 33.42−2.41 34.76−9.31 1,26.2113.05<0.001
FFM control [kg]1.362.540.581.270.521.181.32ns
BMR [Kcal]1699.39 3165.071740.27150.171865.46 1157.104.500.015
WHR0.84 30.060.83 30.060.91 1,20.088.05<0.001
Visceral Fat Level4.27 32.074.50 32.608.64 1,23.2013.91<0.001
Physiological characteristics
Distance [m]2648.67 2,3315.012304.96 1,3230.531919.73 1,2137.4833.51<0.001
Power [W]144.58 2,346.2092.36 1,328.5553.82 1,212.1229.27<0.001
Calories [Kcal]157.88 2,331.99123.09 1,318.8994.55 1,28.5829.49<0.001
S/M [strokes/min]28.52 2,32.6725.95 13.2725.73 13.296.460.003
Pace/500 m [s]136.30 2,319.69155.82 1,318.89183.91 1,216.8827.06<0.001
HRavg [bpm]174.21 2,313.53159.82 118.27156.73 115.658.22<0.001
HRmax [bpm]191.82 312.28184.3611.60176.00 113.767.410.001
Intensity of effort [s]
Zone 1: 90–108 [bpm]6.6119.9227.3690.7232.3689.931.00ns
Zone 2: 108–125 [bpm]22.12 234.2596.73 1150.2858.00119.463.550.034
Zone 3: 126–144 [bpm]123.18195.02113.50132.78177.18189.350.52ns
Zone 4: 145–162 [bpm]87.27 3107.75184.18180.59268.82 1196.546.780.002
Zone 5: >162 [bpm]480.82 3250.33298.73299.97183.64 1230.796.410.003
Note: * G1—COVID-19-free subjects, G2—non-hospitalized COVID-19 sufferers, G3—hospitalized COVID-19 sufferers, ns – not significant difference. Different superscript numbers represent Significant differences between the groups.
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Podstawski, R.; Borysławski, K.; Wąsik, J. COVID-19 as a Factor Influencing Maximal Heart Rates among Male University Students. Appl. Sci. 2024, 14, 6146. https://doi.org/10.3390/app14146146

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Podstawski R, Borysławski K, Wąsik J. COVID-19 as a Factor Influencing Maximal Heart Rates among Male University Students. Applied Sciences. 2024; 14(14):6146. https://doi.org/10.3390/app14146146

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Podstawski, Robert, Krzysztof Borysławski, and Jacek Wąsik. 2024. "COVID-19 as a Factor Influencing Maximal Heart Rates among Male University Students" Applied Sciences 14, no. 14: 6146. https://doi.org/10.3390/app14146146

APA Style

Podstawski, R., Borysławski, K., & Wąsik, J. (2024). COVID-19 as a Factor Influencing Maximal Heart Rates among Male University Students. Applied Sciences, 14(14), 6146. https://doi.org/10.3390/app14146146

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