Effects of COVID-19 Lockdown on Body Composition and Fitness Performance among Football Players in Negro African Environment

Moulongo Jean Georges André¹, Makosso Vheiye Georges¹, Loubelo Prosper², Mouanda Konde Dorel¹, Massamba Miabaou Didace³, Mabiala Babela Jean Robert⁴, Massamba Alphonse^1*

¹Sport Biosciences Laboratory, Higher Institute of Physical and Sports Education, Marien Ngouabi University, Brazzaville, Congo.
²Nutrition and Motor Performance Laboratory, Faculty of Sports Sciences and Physical Education, Lille 2 University, Lille, France.
³Department of Digestive Surgery, University Hospital Center, Faculty of Health Sciences, Marien Ngouabi University, Brazzaville, Congo.
⁴Department of Pediatrics, University Hospital Center, Faculty of Health Sciences, Marien Ngouabi University, Brazzaville, Congo.

DOI: 10.4236/health.2022.144036                

Abstract

Context and Objective: The nutritional and sports dimension of the lockdown implemented during the COVID-19 pandemic is unexplored in the African environment. The purpose of this study was to assess the effects of COVID-19 lockdown on body composition and fitness performance in Congolese football players. Methods: This was an observational study carried out in Brazzaville between February 9 and October 30, 2020. It included 16 male players among Congolese senior national team and 11 male football players of first division Brazzaville clubs. Two types of measurements were carried out: anthropometric measures (height, body mass, total fat percent, lean body mass); physical capacities [30 m sprint, repeated sprint, aerobic endurance (Yo-Yo Intermittent Recovery test), vertical jump (Squat Jump test, Countermovement test)]. The measurements were realized at 4 times: before lockdown (month of february, T0), 1^st week of june (T1), 1^st week of september (T2), 1^st week of october (T3). Data were compared using Student t test, Sokal S test, Anova, Newman-Keuls test (multiple contrasts) and correlation analysis. Results: A significant increase in body mass (p < 0.05), body mass index (p < 0.02) was observed in all subjects, compared to a less marked increase in muscle mass. Significant reductions in performance in the 30 m sprint, the 6-sprint series, the endurance event and the vertical jumps were noted. However, a significant effect of “practice level” on the changes in performance on Squat Jump and Countermovement Jump was only found, the maximum differences throughout experimental period being found among senior football players of Congolese national team. Conclusion: The present data suggest that COVID-19 lockdown promotes weight gain and decreased physical ability in football players.

Keywords

COVID-19 Lockdown, Football, Body Composition, Physical Capacities, Congo-Brazzaville

1. Introduction

The COVID-19 pandemic that is hitting planet Earth is an event in the full sense of the term, an unforeseen upsurge that upsets our daily lives, even in our sports practices and therefore our motor performance. The Severe Acute Respiratory Syndrom Coronavirus-2 (SARS-CoV-2) or Corona virus Disease (COVID-19) pandemic began in December 2019 in the city of Wuhan, China [1], then reached the African continent, including the Republic Congo in early March 2020. In Congo-Brazzaville, 4642 cases of COVID-19 have been confirmed with 120 deaths from March 19, 2020 to March 1, 2021 [2]. Among the health restriction measures taken by the government to stem the spread of the pandemic are physical distancing and the closure of sports practice spaces (public and private gymnasiums, and playgrounds). However, these strategies can have unintended consequences for the health and fitness of athletes.

Indeed, studies carried out around the worldwide show that the COVID-19 pandemic and the health measures to contain it are accompanied in individuals by a radical change in daily activities and life routines, with numerous consequences. These include the significant disruption of biological rhythms [3]. Indeed, sleep-wake rhythms depend on a number of environmental parameters (“Zeitgeber” or time givers) to be able to function well, including: exposure to daylight [4], by far the most important synchronizer; but also the daily physical activity (PA) and especially in the morning; eating meals at regular times, and social interactions [5]. In a situation of lockdown, the majority of these synchronizers (light, physical activity, food, social interactions) are greatly modified or even suppressed—as a result, sleep disorders and sleep-wake rhythms may appear. In addition, the exposure of these Zeitgeber can also be done at the wrong time of the day (for example, exposure to television screens and microcomputers late at night and in particular to blue light). It is in this context that some recent studies report an impact of COVID-19 reduction strategies on the eating behavior and fitness of subjects [6] [7]. As far as athletes are concerned, the data relating thereto is fragmentary.

Indeed, football, which is banned in the public environment during lockdown, is an intermittent and high-intensity sports activity that requires excellent fitness to perform in its competitive practice. High-level football players cover a distance of 587 ± 333 meters on the pitch at a fast speed v of running (19.8 - 25.2 km/h) and 184 ± 87 meters of sprinting (v > 25.2 km/h) [8]. The total distance covered at high intensity during a match depends on the position occupied by the player, the stake of the match and the rank occupied by the team during the championship (or competition) [9]. Thus, fitness is an important factor in getting a victory for a football team. Several studies have shown that intense training improves the fitness performance of players, through the development of abilities such as sprinting, strength and endurance [10] [11]. The organization of the physical preparation schedule for football varies according to the periodization of training, variations in volume and intensity of work load. These variations help to optimize the physical condition of the players and to minimize injuries [12]. Thus, the physical preparation takes place 4 - 5 months before the start of the competition. Therefore, a prolonged rest period for football players such as that relating to COVID-19 lockdown has an impact on their physical condition. Indeed, it emerges from the review of the literature that a long period of rest after the end of a sports season leads to the partial or complete loss of physiological adaptations and performance induced by training, which is called “detraining” in the specialized literature [13]. The magnitude of this loss depends on the fitness level of the subjects and the duration of cessation of training [14]. Regarding COVID-19 lockdown-induced detraining, a few Western studies report a significant loss in motor performance [4] [15]. However, these effects of detraining are not well documented and in sub-Saharan Africa no data have been identified in the literature. Hence the aim of this study was to determine and analyze the impact of COVID-19 lockdown on body composition and fitness performance in Congolese football players. The interest of this study is to raise awareness among athletes and sports actors in black African communities on the health of the athlete during the COVID-19 pandemic and its consequences on the determinants of performance.

2. Methods

2.1. Type, Period and Setting of the Study

The observational and longitudinal study was carried out from February 9 to October 30, 2020, i.e. 8 months 9 days, in Brazzaville, Republic of Congo. It concerned football players pre-selected to participate in the African Nations Championship (CHAN) in Cameroon in January 2021 and other football players playing in the first division teams of the Brazzaville league during the 2019-2020 sports season.

2.2. Participants

The target population was made up of 22 senior male football players at the continental level of practice (total squad for CHAN) and football players playing in the senior men’s teams of the Brazzaville first division, an estimated number of 253 players according to data from the technical staff of the Brazzaville football league during the 2019-2020 sporting season.

The inclusion criteria were: 1) having at least 2 years of competitive football practice in top division football competitions and tournaments for players no selected for CHAN 2021; 2) be regular in training and competitions before lockdown for all players; 3) be shortlisted to participate in the African Nations Championship in Yaoundé in January 2021; 4) having a health status deemed normal before each physical test event after a sports medical examination.

The informed consent, written or oral, of the subjects was required and constituted a prerequisite, as well as the authorization of the technical direction of the senior national football team. Ultimately, after approval of the study by the Ethics Committee for Research in Health Sciences, General Delegation for Scientific and Technical Research of the Republic of Congo, 16 senior male football players selected to participe at CHAN 2021 (group 1) and 11 senior male football players no selected (group 2) participated in the experiment.

2.3. Experimental Procedures

During the study period, all assessments were conducted between 8:00 a.m. and 10:00 a.m., three hours before breakfast. Four (04) evaluation moments were selected for carrying out the tests: one month before lockdown [Pre-lockdown (T0)]; first week of June [lockdown (T1)]; first week of September [lockdown (T2)]; first week of October and resumption of training [Post-lockdown (T3)].

The experiment was carried out in the following order: 1) anthropometric measurements (height, weight, fat percent, lean body mass); 2) blood pressure [systolic blood pressure (SBP), diastolic blood pressure (DBP)]; 3) motor performance (30 m sprint test, RSSA test, Yo-Yo IR1 test, Squat jump test, Countermovement test).

During the study period, the subjects restricted the practice of exercises at home to games of skill and ball control, muscle flexibility exercises due to health measures related to the COVID-19 pandemic and the smallness of the accommodation (sharing of the courtyard with other tenants in the plot).

2.4. Anthropometric and Blood Pressure Measurements

All protocols for measuring height and body mass were based on the recommendations issued by the French Society of Sports Medicine on fitness performance [16]. Body mass and total fat percent (PCTG) were measured by impedancemetry, using a scale fitted with an OMRON brand body composition monitor, type BF511 on renewable batteries (manufacturer: OMRON HEALTH CARE Co Ltd, Kyoto, Japan). The body mass index (BMI) reported in the tables of the National Institute of Health and Medical Research (INSERM) of France was calculated from the formula:

$\text{BMI}\left(\text{kg}/{\text{m}}^{\text{2}}\right)=\text{Weight}\left(\text{kg}\right)/{\left[\text{Height}\left(\text{m}\right)\right]}^{\text{2}}$

The nutritional status of the subject was assessed using the BMI assessment scale of the World Health Organization [17]. Lean body mass (LBM) was calculated using the Forsyth and Sinning equation [18]:

$\text{LBM}\left(\text{kg}\right)=\text{bodymass}-\left[\text{PCTG}\left(\%\right)\frac{\text{Bodymass}}{100}\right]$

Blood pressure was measured on the left arm of each subject using an AutoTensio^® brand electronic blood pressure monitor (SPENGLER, Issoudun, France).

2.5. Fitness Performance Testing

Field tests used in this study are those likely to be implemented easily and not requiring too elaborate and expensive materials.

Sprint ability. The test consisted of 30 m sprint run on a 250 m long tartan athletic track. It is a running event on 2 × 30 m with a 2 min rest between each sprint. The running time at the end of each 30 meters was recorded using a 1/100^th stopwatch, and the best time taken by the subject was retained for data analysis.

Repeated-sprint ability. The ability to repeat sprints was determined using the repeated sprint running test (RSSA). This ability is a physical quality that takes on its full meaning in team sports, especially in football where players may be required to repeat movements at maximum speed, very intense game actions with short recovery periods between two actions. This is how the RSSA test is used to assess this ability in football players. This test includes rapid changes of direction, which represent a series of football-specific movements. After a 15-minute warm-up, each subject performed 6 sprints over a distance of 40 m each, spaced out by 20 s of passive rest. The race times were recorded using a stopwatch to 1/100_th and the best time (T_best) is retained. The average time taken during the 6 sprints is:

$T_{mean}=\left(\sum t_i\right)/6\text{where}\sum t_i=t_1+t_2+\cdot \cdot \cdot +t_6$

The decrease in race times, from the first to the sixth series, is described by the performance decrement [19]:

$T_{dec}\left(in\%\right)=\left[\left(T_{mean}/T_{best}\right)\times 100\right]-100$

Specific aerobic fitness. The Yo-Yo Intermittent Recovery Level 1 (Yo-YoIR1) test, which took place on a tartan handball court, was used to assess high endurance performance [20]. Cones were placed on two horizontal lines 20 m apart and 5 m behind the starting line. Players completed a 2 × 20 m run at the beep, with the two runs separated by a 10 s active recovery time of running across a 2 × 5 m course. The duration of the beeps was shorter and shorter with each step and the subjects continued to run at increasing speed until they were no longer able to maintain the required pace between two beeps. Players had to place 1 foot on or behind the 20 m line at the end of each shuttle. If a player did not reach the line in time, they were asked to do so in the next round. The final stage (km/h) reached and the total distances traveled (m) were recorded.

Vertical jump abilities. The squat Jump (SJ) test was performed by the subject starting from the static semi-squat position, with the two segments (legs-thighs) of the pelvic limb forming an angle of approximately 90˚. After a short rest (~1 s), the subject executed a vertical jump with the highest possible maximal effort.

Regarding the Countermovement Jump (CMJ), the subject, starting from a standing position, performed an explosive vertical relaxation according to a slow cycle of muscle shortening-stretching-relaxation for a 90% inclination with respect to the knee. All subjects performed on the same handball court the two vertical jump tests in the same order, i.e. SJ followed by the CMJ test with akimbo hands. Each subject performed 3 jumps for each test, with an interval of 60 s between each jump. The mean of the two best performances was retained for the data analysis [21].

2.6. Course of the Tests

The subjects performed the tests in the following order: 30 m sprint, Yo-Yo IR1 test, RSSA test, Squat Jump, Countermovement Jump. These tests were carried out after 2 days for each group of players: first day, Sprint on 30 m, Yo-Yo intermittent Recovery 1; second day, RSSA test, Squat Jump, Countermovement Jump. The consumption of alcohol or caffeine was prohibited 24 hours before the tests. One hour before the first series of tests, the subjects arrived at the experimental site for the anthropometric measurements.

2.7. Operational Definitions

The COVID-19 pre-lockdown period has been defined as the period prior to the date of declaration of containment for the populations of Brazzaville and Pointe-Noire, March 24, 2020. The COVID-19 lockdown period has been defined as that from March 24 to September 18, 2020, and characterized by two extensions. The date of January 17, 2021, following the declaration of the President of the Republic of Congo on the post-lockdown, was retained as that of the real start of training for the national football team.

2.8. Variables of the Study

These were: 1) body mass; 2) body mass index; 3) fat percent; 4) lean body mass; 5) time spent in the 30 meter running test; 6) the performance achieved (in meters) in the Yo-YoIR1 event; 7) the performance achieved (in seconds) in the RSSA running event; 8) the performance achieved (in cm) in the Squat Jump event; 9) the performance achieved (in cm) in the CMJ test.

2.9. Statistical Analysis

Results are expressed as mean ± standard deviation. All statistical tests were implemented using Sigma Stat 3.5 software (Systat Inc, USA). The normal distribution of the data was checked from the Kolmogorov-Smirnov test and was confirmed. Student’s paired t test was used to compare all the parameters measured before lockdown and when training resumed for each group of players. This was the unpaired t test for comparing the values deduced from the measurements taken at a given time t between the football players of groups 1 and 2. The use of a one-way, 4-factor analysis of variance (ANOVA) made it possible to detect the differences observed between the values measured at times T(0), T(1), T(2) and T(3) at the level of each group of players. In case of statistical significance, the determination of the level at which these differences are located used the post-hoc test of multiple contrasts of Newman-Keuls. The relationships between some parameters of body composition and those associated with physical condition were also investigated using the correlation coefficients r of Pearson moment products. The level of correlation was defined according to the Hopkins scale [22]: trivial if r < 0.1; low if r is between 0.1 and 0.3; moderate if r > 0.5 - 0.7; narrow if r > 0.7 - 0.9; very narrow if r > 0.9; almost perfect if r > 0.9 - 1; and perfect if r = 1. Finally, the “group” effects were evaluated from the values of the “square partial eta” coefficient, η²_p, which is defined as: trivial if ${\eta }_p^2$ <0.1, low for ${\eta }_p^2$ between 0.1 and 0.3, moderate for 0.3 - 0.5 and broad if ${\eta }_p^2$ > 0.5 [22]. Statistical significance threshold was set at 5% for all tests.

3. Results

3.1. Sociodemographic and Clinical Characteristics

The sociodemographic and clinical characteristics of the subjects are recorded in Table 1.

Table 1 shows that the age of the subjects in the two groups was comparable, with a mean age of 25 years (range: 19 - 27 years). If these football players did not smoke, all consumed alcohol. About 4/5 of the subjects had completed secondary education and none of them was illiterate. Overall, there were more single people (85.1%).

Table 1. Sociodemographic and clinical characteristics of the subjects

3.2. Variations in Body Composition

The evolution of the players’ body composition data during the experimental period and their changes is reported in Table 2 and Table 3.

Before the start of lockdown and the start of the experiment, Table 2 shows that no statistical difference was found between the football players of groups 1 and 2 in terms of body mass (Δ = 0.4%), BMI (Δ = 2.6%), total fat percent (Δ = 1.1%) and lean body mass (Δ = 0.3%). However, the values showed a significant increase throughout the study period (Table 2 and Table 3): the differences noted between the times T(0) and T(3) (Pre-lockdown versus Post-lockdown) were +5.3% in group 1 and +6.5% in group 2 for body mass, +5.1% in group 1 versus +6.5% in group 2 for BMI, +9.7% in group 1 against +12.1% in group 2 for total fat percent, and +4.2% in group 1 and +5.1% in the group 2 for mean body mass. The maximum differences between football players of two groups were found at the resumption of training.

3.3. Evolution of Specific Fitness Performance

The evolution of performance in fitness tests among football players in groups 1 and 2 is shown in Figures 1-5.

Table 2. Evolution of body mass, body mass index, total fat percent and lean body mass of football players in groups 1 and 2 before lockdown, at 3 and 6 months during lockdown, and at resumption of training.

BMI, body mass index; Pre-Lockdown (T0), pre-Lockdown at T0; Lockdown. (T1), Lockdown at T1; Lockdown. (T2), Lockdown at T2; Post-Lockdown, Post-lockdown and resumption of training.

Table 3. Variations observed in the body composition of football players in groups 1 and 2 between the start of lockdown and resumption of training.

BMI, body mass index; LBM, lean body mass.

Abbreviations: *p < 0.05, significant difference compared to the values noted in pre-lockdown.

Figure 1. Evolution of performance (in seconds) in the 30-meter sprint test among football players in groups 1 and 2 during the study period.

Abbreviations: **p < 0.01, significant difference compared to the values noted in pre-lockdown; ***p < 0.001, significant difference compared to the values noted in pre-lockdown

Figure 2. Evolution of performance (in seconds) in the RSSA test in groups 1 and 2 during the study period.

Figure 3. Evolution of performance (in meters) in the Yo-Yo IR2 test among football players in groups 1 and 2 during the study period.

Abbreviations: **p < 0.05, significant difference compared to the values noted in pre-lockdown; #, significant intergroup difference at p < 0.05.

Figure 4. Evolution of performance (in centimeters) in the Squat Jump test among football players in groups 1 and 2 during the study period.

The sprinting times had lengthened throughout the experimental period (Figure 1), with respective differences between T0 and T3 of +5.3% (p<0.05) in the group 1 (4.1% ± 0.07 s versus 4.39 ± 0.11 s) and +2.6% (4.15 ± 0.02 s versus 4.26 ± 0.04 s) in group 2 No difference between groups of players was observed (η²_p = 0.177; p = 0.157).

During the RSSA event (Figure 2), there was a significant increase in repeating-sprint times throughout the COVID-19 lockdown; the maximum durations were found at the end of the experiment in comparison with the times noted at the start of the study: 8.58 ± 0.21 s vs 8.18 ± 0.17 s in group 1. In addition, there

Abbreviations: *p < 0.05, significant difference compared to the values noted in pre-lockdown; **p < 0.01, significant difference compared to the values noted in pre-lockdown; #, significant intergroup difference at p < 0.05.

Figure 5. Evolution of performance (in centimeters) in the Countermovement Jump test among football players in groups 1 and 2 during the study period.

was no significant difference in performance achieved between the two groups regardless of the moment of evaluation ( ${\eta }_p^2$ = 0.144; p = 0.203), particularly at the third evaluation T(2): 8.58 ± 0.21s in group 1 versus 8.43 ± 0.12 s in group 2 (t value of Student test = 0.83; p > 0.05) and at T(3): 8.42 ± 0.09 s for group 1 versus 8.25 ± 0.10 s for group 2 (t value of Student test = 1.81; p > 0.05). The average decrease in running times between the first and sixth series of running, before and after follow-up, was respectively: −6.3% in group 1 versus −11.8% in group 3 before follow-up, −4.7% in group 1 vs −10.6% in group 2 after follow-up.

With regard to the performances achieved in the Yo-Yo IR1 test (Figure 3), a regular drop in the established scores was noted between the start and the end of the experiment, but no significant difference: 2503 ± 182 m versus 221 ± 154 m for group 1; 2498 ± 203 m against 1812 ± 195 m for the group.

As for performance in the Squat Jump (Figure 4) and Countermovement (Figure), no-significant decreases were found until the 3rd evaluation T(2) compared to the values recorded at T(0): Squat Jump, 36, 72 ± 0.53 cm at T(0) vs 35.24 ± 0.71 cm at T(2) in group 1, 36.46 ± 0.31 cm at T(0) 35.18 ± 0.62 cm at T(2) in group 2; Countermovement Jump, 38.62 ± 0.45 cm at T(0) vs 37.61 ± 0.32 cm at T(2) in group 1, 38.30 ± 0.32 cm at T(0) vs 37.41 ± 0.26 cm at T(2) in group 2.

The differences were further increased from the T(2) to T(3) assessment and a significant difference between groups 1 and 2 was found in the two tests at T(3): Squat Jump, 35.13 ± 0, 52 cm in group 1 against 34.43 ± 0.26 cm in group 2; Countermovement Jump, 37.25 ± 0.34 cm in group 1 against 36.48 cm ± 0.31 cm in group 2.

3.4. Impact of Body Composition Changes on Fitness Performance

The values of the correlation coefficients r between the variations of some body composition parameters and the performances achieved in the physical fitness tests are recorded in Table 4.

Table 4 shows that negative and significant correlations between the changes in body mass, BMI and total fat percent between T0 and T3 and those of performance in the Yo-Yo IR1 test and the SJ test were found.

However, these correlations were positive and no significant for in lean body mass changes. As regards the relationships between the RSSA test and the body composition parameters, they were positive and significant, except for Δ (% total fat) where it was negative (r = −0.54; p = 0.042) and Δ (muscle mass) where the relationship, although positive, was no significant (r = +0.33; p = 0.075).

4. Discussion

This study assessed the changes in body composition and fitness performance in Congolese football players during the COVID-19 lockdown. The main findings highlight: 1) a significant increase in body mass (p < 0.05), body mass index (p < 0.001), total fat percent (p < 0.02), unlike lean body mass (p > 0.05) in football players in groups 1 and 2; 2) a significant decrease of performance during the 30 m sprint, the series of 6 repeated sprints, the endurance Yo-Yo IR1 test and the vertical jumps (Squat Jump and Countermovement Jump); 3) a “level of practice” effect (intergroup difference) on the variations observed in the performances achieved during the final evaluations of the vertical jumps tests, the maximum differences between pre-lockdown and the resumption of training being found in the group 1.

The variations in body mass, BMI and fat mass throughout our study which are significant, reflected in a steady increase. This can be explained by the disruption of the food system as observed by Makosso Vheiye et al. [23] in their study on the dietary profile of Congolese adults in Brazzaville during the first 6 months of the COVID-19 lockdown. These authors noted lipid intakes of 43.27%

Table 4. Relations (Pearson correlation coefficients) between variations in body mass, body mass index, percentage of total fat, lean body mass and those of some fitness parameters.

BMI, Body mass index; LBM, lean body mass; Δ, deviation.

of daily caloric intake during the study, a higher percent than the recommended standards for a balanced diet: 30% of caloric intake. Even if we do not have data showing the absence of self-regulation between the ingestion of lipids and the oxidation of lipids in the compartment of energy reserve within the organism, these eating habits are found in the most average and low-income Brazzaville households, which constitute 94.7% of the social strata [24]. Therefore, the high lipid intake has undoubtedly induced an imbalance between ingestions and their oxidation; which is accompanied by net fat storage and an increase in body mass.

No pathological case of sleep disorder was found in our subjects during the study, other major factors are also thought to explain players’ weight gain. First, it is the increased frequency of snacking during the COVID-19 lockdown and the reversal of the food rhythm, which clearly contributes to the increase in body mass and total fat [25]. Added to this is the time spent in front of television and computer screens, as reported in the study by the study of Dietz and Gortmaker carried out on football players during a 4-month period of detraining [26]: in subjects aged 20 to 27, body mass would increase by 1.5% for 30 hours spent in front of the small screen. In addition, the establishment of the curfew has led to the overconsumption of food taken outside the home in a limited time, a phenomenon comparable to food compulsion or “binge eating” of the Anglo-Saxons which often leads to weight gain [27].

Third, the stress induced by the COVID-19 lockdown prolonged by the curfew until now may be incriminated in the weight gain in our subjects. This could lead to eating disorders (snacking, food compulsions) which pass through biological relays. Among these biological agents, we find monoamines (including catecholamines), peptides (including CRF) and other substrates at work in the central control of food intake [28] and through the effects of some of them. them on peripheral metabolism, although there are still uncertainties in the intricate nature of their various interactions. Finally, the weight gain observed in all our subjects can be explained by the decrease in daily physical activity. Indeed, lockdown and the curfew are accompanied by a reduction in daily activities, the adoption of several physically passive behaviors (watching television, playing on the console, working on the computer, telephoning while seated, etc.) and by movements or movements of low intensity; all of these are weight gain factors.

The significant decrease observed in BMI (p = 0.001) during the 8 months of experimental study in both groups of football players, parallel to that of the percentage of total fat (p = 0.05 in group 1 and p = 0.02 in group 2) is found in the literature; it confirms the fact that the predominance of sedentary occupations promotes an increase in BMI or adiposity. In a longitudinal study by Gallagher et al. [29] relating to 286 adults aged 20 - 25 years at inclusion, the physical activity assessed is inversely associated with changes in BMI and body fat at the age of 25 - 30 years. The harmful effect of sedentary occupations is observed in adults who are less active or have a diet higher in fat; these observations agree with ours. Thus, the assertion that the time spent in front of the television reflects a lack of PA is consolidated; but other unfavorable factors such as nibbling behaviors also intervene. However, only the evaluation of plasma insulin levels, plasma concentrations of triglycerides (TG) and high density lipoproteins (HDL) can better objectify these assertions.

The results relating to the significant drop in physical performance are in agreement with numerous studies on populations of football players. This deterioration in the physical abilities of the players studied partly explains the defeat of the Congolese team during the quarter-finals at CHAN 2021, Yaoundé (Cameroon), insofar as our players from group 1 formed the backbone of the national selection during this African competition; this is in line with the observations of the technical staff at the end of this competition. With regard to the data from the Yo-Yo IR1 test (endurance test), a decrease in the distances traveled by the subjects was noted from the 3rd month of COVID-19 lockdown (FigureIII.3). Our observations agree with those of Thomassen et al. [10], Christensen et al. [30] who also highlight, after 2 weeks of detraining, a drop in performance in this test in top football players. In addition, a study conducted in the laboratory reports that a prolonged period of detraining induces an 8% decline in maximal oxygen consumption [31], in close correlation with the distance traveled in the Yo-Yo IR1 test [32]. The degree of fitness deterioration during the detraining period after a competitive season is closely related to the fitness level of athletes prior to detraining [33]. Thus, in this work, the decrease in performance in the Yo-Yo IR1 test from the third month of COVID-19 lockdown can be explained. These decreases in performance may have a muscular origin. Indeed, it is known that several weeks of detraining lead to a return of muscle capillarization to the basic level in athletes (~3 weeks for elite footballers according to the literature [34], but not evaluated in our study) and to a 25% - 45% drop in enzymatic oxidative activities, a result of the reduced production of ATP mitochondria in skeletal muscle [35]. This decrease in fitness is for Noon et al. [36], Olivier et al. [37], in connection with a few factors of well-being and quality of life of the subjects such as motivation, appetite, fatigue and stress.

As for the performance achieved in the Squat Jump (Figure 4) and Countermovement Jump (Figure 5) significant drops were observed throughout the COVID-19 lockdown (Figures 1-5). This decrease in anaerobic performance is reported in the literature in high-level soccer players, after a short period of detraining after a competitive season [38]. Thus, the cessation of training beyond 2 weeks could affect the expression of the Na+-K+ pump, translated by: a reduction in the signal AB FXYD1 ser 68; a 17% decrease in the level of pyruvate dehydrogenase; 12% in the activity of citrate synthase and 18% in 3-hydroxyacyl CoA. In addition, the performances achieved during the SJ test and CMJ test also showed a respective drop of 5.95% and 6.4%. Kooundourakis et al. [39], examining the effect of detraining on exercise performance, noted that a 6-week period of detraining significantly decreased maximal oxygen consumption (VO_2max) and performance achieved in sprint tests (10 m, 20 m), SJ and CMJ. These variations can be related to changes in skeletal muscle morphology, reflected in a reduction in mitochondrial enzymatic section [40].

Furthermore, following the COVID-19 lockdown measures characterized among other things by a notable increase in physical inactivity, the decrease in contractile activity of the muscle may explain this drop in performance in the Yo-Yo IR1, CMJ and Squat events. Jump. Indeed, significant muscle atrophy (1% - 4% decrease) has been reported after just 14 days of reduced physical activity in young and older adults [41]. According to Arc-Chagnaud et al. [42], skeletal muscle adapts to prolonged physical inactivity by decreasing not only muscle fiber size (atrophy) but also muscle function and quality. Additionally, mechanosensing proteins such as costamers, titin, filamin-C, and bag 3 are known to enable muscle fibers to transform electrical excitation into mechanical forces [43]. Their activation during muscle contraction regulates protein turnover through the interaction between the rapamycin 1 complex (mTORC1) and the main proteolytic pathways (autophagic systems of lysosomes and ubiquitous proteases) [44]. However, research on rats shows that the immobilization of muscle during a 2 - 3 weeks period of drastically reduces the quantity and quality of mitochondria due to the decrease in the regulation of mitochondrial biogenesis, the increase in the regulation of proteases ubiquities and increased expression of mitophagic genes [45] [46]. Indeed, mitochondria, conventionally considered as sources of muscular energy production, play an important role, not only by controlling the proliferation and production of new organelles (biogenesis of mitochondria) but also by regulating the elimination of the dysfunction of mitochondria via mitophagy and morphological dynamics through fusion and fission [45] [46]. This deterioration of mitochondrial homeostasis during the COVID-19 lockdown then undoubtedly leads to a decline in muscle function, and therefore in specific-fitness performance such as suggested in this study.

However, some precautions should be taken into consideration when interpreting the results presented. First, these are the small size of our sample of the subjects in group 2, 11 out of 253 first division football players; this does not authorize the generalization of the conclusions obtained to the entire population of football players. Second, the morbid antecedents and lifestyle of the subjects during the experimental period were based only on their declarations, without rigorous verification. Third, we should have strictly controlled the diet of our subjects and made it uniform in both groups. However, the socioeconomic crisis due to the COVID-19 pandemic has resulted in Brazzaville households losing purchasing power, and therefore the disruption of eating habits, as reported by Makosso Vheiye et al [23]. Fourth, the study would also have assessed the recovery process of players throughout the lockdown. Although a measure of recovery was planned, the large number of missing data did not allow these analyzes to be carried out. However, these limitations mentioned do not completely affect the power of the observations. This study nevertheless has the merit of having addressed the monitoring of body composition and physical condition parameters in athletes during COVID-19 lockdown, a topic not yet addressed in recent African scientific literature. In addition, our experimental work followed protocols similar to other previous studies on detraining [47] [48] [49] [50]. In these studies, subjects like those in our series were assessed four times and considered as their own control. Another strength of our work lies in the simplicity and speed of the fitness tests used; these did not require any sustained learning, while guaranteeing the repeated follow-up of the subjects. They therefore remain particularly suitable for our study.

5. Conclusion

This study, while presenting certain limitations, made it possible to identify the interesting results of the impact of 8 months of prolonged COVID-19 lockdown on the body composition and some physical abilities in senior football players from Brazzaville. The body mass and fat percentage of the subjects are increased. The physical condition of the players is altered, reflected in a significant decrease in performance in sprint, endurance and relaxation. This is why, in the current socio-economic and health crisis, it is necessary to at least limit the damage by authorizing the controlled resumption of sports training. For this, it is desirable to improve the sports management of the current health crisis to meet the needs of the populations for the maintenance of physical condition and the maintenance of body shape.

Author Contributions

Conceptualization: Massamba, A.

Formal analysis: Massamba, A., Makosso-Vheiye, G., Moulongo J.G.A.

Investigation: Makosso-Vheiye, G., Loubelo, P., Mouanda Konde, D.

Methodology: Makosso Vheiye, G., Moulongo, J.G.A., Massamba Miabaou, D., Mabiala Babela, J.R.

Data processing: Massamba, A., Moulongo, J.G.A., Makosso-Vheiye, G.

Writing of the draft: Makosso-Vheiye, G.

Corrections and revision of the draft: Massamba, A, Moulongo, J.G.A., Massamba Miabaou, D., Mabiala Babela, J.R.

Analysis of the final text: All authors.

Conflicts of Interest

The authors declare no conflicts of interest regarding the publication of this paper.

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