It has been well documented that maximal short-term performances fluctuate with time of day, with morning nadirs and afternoon maximum values (23,25,26,28). These daily variations have been found to range from 3 to 21.2%, depending on the population tested, the muscle groups, and the experimental design (20).
The diurnal variations in short-term maximal exercises (≤1 minute) mainly involving anaerobic metabolism can be influenced by several factors such as sleep deprivation (29), warm-up duration (26), and time of day of the training (22-24,27). Based on previous literature, training in the morning can (a) improve typically poor morning anaerobic performance to the same or an even higher level as their normal daily peak typically observed in the late afternoon and (b) decrease the amplitude of the diurnal variations (22-24,27). However, training in the evening hours can increase the amplitude of the daily variations of neuromuscular performances (27). Souissi et al. (27) and Sedliak et al. (22-24) demonstrated that greater improvements in anaerobic performances occurred at the time of the day at which resistance training was regularly performed. However, Souissi et al. (27) found stronger temporal specificity of the morning group than did Sedliak et al. (22-24). Moreover, Sedliak et al. (22-24) reported no significant time of day–specific adaptations after training in the evening hours. Recently, Blonc et al. (4) failed to show any time-of-day effects on either performance or training benefits. The discrepancies in the findings between these studies might be partly because of an accumulated neuromuscular fatigue or to a detraining phase, which may impair the performance in the posttraining test sessions. In fact, in the Sedliak et al. studies (22-24), the posttraining test sessions were performed after an intensive resistance training phase, which could induce accumulated neuromuscular fatigue (9,14). However, in the Souissi et al. study (27), the posttraining test sessions were performed after 2 weeks of training cessation, which can lead to reduced adaptation levels and then performances (9,14).
To reach peak performance and to avoid neuromuscular fatigue, coaches and researchers with an interest in resistance training have attempted to identify the proper handling of program variables (e.g., intensity, frequency, and volume) (16). It is believed that the short-term reduction of the training volume while the intensity is kept high is a well-known practice used to maximize performance after an intense training period (10,11,14,17,19). This process, known as taper, can have a major influence on the athlete's performance level (14,17). A recent meta-analysis suggests that tapering can reduce accumulated fatigue after a training period (8,17) and improve performances by 0.5–6% (18). Regarding anaerobic performances, Gibala et al. (9) examined the effects of 10 days of tapering after 3 weeks of resistance training and reported significant increases in isometric peak torque and low-velocity isokinetic strength performance of the elbow flexors. Recently, Izquierdo et al. (14) found that 4 weeks of tapering resulted in further increases in maximal strength and muscle power after 16 weeks of periodized resistance training. Thus, the incorporation of a short-term tapering period after a resistance training program may allow physical and mental recovery and seems to be effective in avoiding the negative impact of training stimuli before the start of new testing sessions or before a major competition in athletic performance.
In light of these observations, along with the fact that there is a conflict in the literature with regard to the impact of training at the same time of day, we hypothesized that, by using a taper period and controlling other variables such as training intensity and volume, we could advance knowledge in the area of the temporal specificity of resistance training and tapering. The question then arises to determine if tapering period scheduled at a particular time of day can (a) induce further time-of-day–specific adaptation and (b) lead to similar or different improvements in anaerobic performances (i.e., difference between training in the morning or in the evening hours). It is critical, therefore, for athletes interested in maximal performance, and coaches and researchers, to determine the role of a taper period scheduled in the morning or the evening hours to optimize training adaptability (strength and power gains) and to avoid overreaching or overtraining.
In view of the above considerations, the purpose of this study was twofold: (a) to determine the effect of 12 weeks of resistance training and 2 weeks of tapering scheduled in the morning or in the evening on the diurnal variations of short-term maximal performances and (b) to investigate the effect of time of day of tapering on the improvements of these performances. We hypothesized that a tapering period scheduled in the morning or in the evening may induce time-of-day–specific adaptations and increases in short-term maximal performances. However, to the authors' knowledge, there are no studies to support this hypothesis.
Experimental Approach to the Problem
There is a conflict in the literature with regard to the influence of training at the same time of day on short-term maximal performances. Therefore, by comparing 2 resistance training programs, one scheduled in the morning and the other in the evening, we sought to investigate the importance of time of day of training and tapering on the diurnal variation and the improvements of anaerobic performances. To achieve this, the subjects performed maximal brief squat jumps (SJ), countermovement jumps (CMJ), maximal voluntary contraction (MVC), and the Wingate tests before (T0) and after 12 weeks of resistance training (T1) and after 2 weeks of tapering (T2). They were randomly assigned to either a morning training group (MTG, who trained between 0700 and 0800 hours, n = 10), evening training group (ETG, who trained between 1700 and 1800 hours, n = 11), or a control group (CG, did not train but participated in all the tests, n = 10). They performed the evaluation tests at 0700 and 1700 hours. These time points were chosen because they correspond to the minimum and maximum day-time levels of anaerobic performances (20). The dependent variable included the core temperature values and the SJ, CMJ, MVC, and the Wingate test's performances (peak [Ppeak] and mean [Pmean] powers and fatigue index [FI]). The independent variables included groups, periods, and time of day. The test sessions were conducted from January to May 2010.
Thirty-one healthy male physical education students (age: 23.1 ± 1.98 years; height: 176.06 ± 6.28 cm; and weight: 74.92 ± 10.88 kg) volunteered to participate in this study. The characteristics of each group's participants (mean ± SD) are shown in Table 1. Initially, all the participants had exactly the same time schedule at the university from sunrise to sunset under the control of the experimental team. The subjects had taken part in various recreational low-intensity physical activities such as walking, jogging, or aerobics in our university, but none of them had any background in regular resistance training (i.e., during the 6 months before the study). Medications, which are expected to affect physical performance, are prohibited. Before participation, all the subjects were informed about the experimental procedures, the possible risks, and discomforts associated with the study and signed a written informed consent. The study was conducted according to the Declaration of Helsinki, and the protocol was fully approved by the Clinical Research Ethics Committee and the Ethic Committee of the National Center of Medicine and Science of Sports of Tunis before the commencement of the assessments. The subjects were categorized either as “moderately morning type” (n = 10) or as “neither type” (n = 21) on the basis of their answers to the Horne and Östberg's (13) self-assessment questionnaire, which assesses morningness eveningness.
One week before the actual measurements, the subjects were familiarized with the experimental testing procedures on a control day. Anthropometrical measurements and resistance load verifications for the experimental exercises were also determined for each subject at this time. Thereafter, the subjects were tested on 6 different occasions in a randomized order using identical protocols (SJ, CMJ, MVC, and Wingate test, with a recovery period of at least 15 minutes between 2 successive tests): before training (T0), after training (T1), and after tapering (T2) in the morning and in the evening. The test sessions were performed on separate days with only 1 test session a day, allowing a recovery period ≥36 hours. Three sessions were conducted in the morning (0700 hours) and 3 in the evening (1700 hours) (Figure 1). The MTG trained only in the morning and performed tests at 0700 and 1700 hours. However, the ETG trained only in the evening and were also tested at both 0700 and 1700 hours. The morning and evening tests were scheduled at the same time of day as the training sessions. Additionally, the subjects were dismissed if they were absent for >3 consecutive bouts. The average number of training sessions completed was 37.33 ± 1.55, with all the subjects completing ≥35 sessions.
To minimize confounding factors, instructions related to sleep and diet were given to the subjects before the experiment. On the night preceding each test session, the subjects were asked to keep their usual sleeping habits, with a minimum of 6 hours sleep. During the period of investigation, they were prohibited from consuming any known stimuli (e.g., caffeine) or depressants (e.g., alcohol) that could possibly enhance or compromise wakefulness. Moreover, the participants were requested to maintain their habitual physical activity and to avoid strenuous activity in the day before testing throughout the study. The actimetry (Actiwatch®; Cambridge Neurotechnology Ltd., Cambridge, United Kingdom; Mini Mitter, Respironics Inc., Bend, OR, USA) allowed us to check that their sleep duration was not <6 hours and that they did not engage in any fatiguing exercise during the testing period. Before the morning test sessions, the subjects were asked to come to the laboratory at 06:00 hours in a fasting state. Only 1 glass (150–200 ml) of water was allowed, to avoid the postprandial thermogenesis effects. Before the evening test sessions, they had the same standard isocaloric meal at 12:00 hours. The overall daily energy intake goal was set at 10.5 MJ (2,500 kcal) per capita per day. After lunch, only water was allowed ad libitum. During the entire experimental period, the mean ambient temperature and relative humidity of the laboratory were kept stable (20.9 ± 1.2°C and 37.5 ± 7.3%, respectively).
Subjects' oral temperature was recorded using a digital clinical thermometer (Omron®, Paris, France; accuracy ± 0.05°C) in the beginning of each testing session after they lay in a supine position for 15 minutes to reduce the effect of prior activity.
Both groups (MTG and ETG) trained the knee extensors and flexors muscles of both legs 3 times per week for 12 weeks (from T0 to T1). Subsequently, the subjects participated in a 2 weeks' period of tapering (from T1 to T2). The training program (designed to enhance muscle size and strength) was similar so that the MTG and the ETG trained in an identical manner throughout the study (e.g., performed the same exercises, repetitions, number of sets). During the course of the 12 weeks' training period, the training sessions were standardized to consist of 3 sets of 4 exercises (Squat, Leg press, Leg extension, and Leg curl). Training intensity was established as 10 repetitions to failure per set (10 repetition maximum [10RM]: weight was assessed as that which could just be lifted 10 times) and adjusted as performance improved to stay within the desired RM training zone. Two minutes recovery was allowed between sets. During all the training sessions, if the load happened to become slightly too heavy, as it did in some cases, the subject was assisted slightly during the last l–3 repetitions of the set. The training volumes presented by multiplication of load, sets, and repetitions (sets × repetitions × load) over 1 training session and the weekly training volume were 3,185.71 and 9,557.14 kg, respectively. Each training session lasted approximately 1 hour. It was preceded by 10 minutes of warm-up and concluded with 10 minutes of cool-down. The warm-up included 8–10 repetitions using light weights for all exercises. Additionally, all resistance training sessions were supervised by one of the investigators during the span of investigation.
After the resistance training period, the subjects were assigned to 2 weeks of tapering period conducted 2 days per week. Tapering consisted of a period of decreased training volume (i.e., ≈ 20% over 1 training session and ≈50% over 1 week) with increased intensity (i.e., from 10RM to 8RM). During this phase, the subjects performed 3 sets of the same exercises (Squat, Leg press, Leg extension, and Leg curl) with 3-minute rest periods between sets and exercises. All the exercises were performed with the maximum load possible to achieve 8 repetitions (8RM) in each set. During this tapering phase, the training volume (sets × repetitions × load) over 1 training session and the weekly training volume was 2,565.71 and 5,131.42 kg, respectively.
The Wingate test was conducted on a friction-loaded cycle ergometer (Monark 894E, Stockholm, Sweden) interfaced with a microcomputer. The cycle was equipped with toe clips to prevent the subject's feet from slipping. The seat height and handlebars were adjusted to each subject's satisfaction. The Wingate test consisted of a 30-second maximal sprint against a constant resistance related to body mass (0.087 kg· kg−1 body mass) as proposed by Bar-Or (1). The test began from a rolling start, at 60 rpm against minimal resistance (weight basket supported). When a constant pedal rate of 60 rpm was achieved, a countdown of “3–2-1-go!” was given by the experimenter. At the start signal, the test resistance was applied, and the subjects were instructed to pedal as fast as they could during 30 seconds. During the test, the subjects had to remain seated and were strongly encouraged to reach the maximal pedaling rate as quickly as possible. Every second, the power output was calculated by the computer and stored. The highest power output over 1 second (Ppeak) and the mean power (Pmean), corresponding to the ratio between total work done and time to completion (e.g., 30 seconds), were recorded at the end of the test. The FI (e.g., the percentage of decrease in power output) was equal to the difference between the highest (Ppeak) and lowest power (Plow) divided by the highest power:
Squat Jump and Countermovement Jump Tests
The subjects were asked to perform a maximal vertical SJ and CMJ without any load on an infrared jump system (Optojump, Microgate, Bolzano, Italy) interfaced with a microcomputer. This system is developed to measure with 10−3-second precision all flying and ground contact times. Then, the calculations of the jump height are made. The Optojump photocells placed 6 mm from the ground were triggered by the feet of the participant at the instant of take-off and were stopped at the instant of contact upon landing. The subjects stood between two 1-m infrared sensor bars to perform the SJ and the CMJ.
In the SJ, the subjects lower themselves into a squat position (90°) and after a brief pause, jump upward as quickly and as high as possible. No downward motion is allowed immediately before jumping upward. In contrast, in the CMJ subjects initiated the jump from an extended leg position, descended to 90° knee flexion, and immediately performed an explosive concentric action for maximal height.
In these jumping conditions, the subjects were instructed to keep their hands on the hips and to minimize lateral and horizontal displacements throughout the entire jump. Jumping height was calculated from the flight time. The subjects performed 3 maximal trials of each jump test interspersed with 15 seconds of rest, and the peak value was used for further analysis.
Maximal Voluntary Contraction
The subjects performed three 5-second MVC of the knee extensors (120° knee flexion) of the dominant leg. They were strongly encouraged while visual feedback was provided to reach maximal level. The subjects were secured to a sitting position in a knee extension device (Leg extension machine, PANATTA SPORT®, Italia). The torso was fixed with 2 horizontal safety belts in the chest and waist area, and the upper extremities were placed next to the body holding handgrips. Moreover, both thighs were strapped. The force generated during the muscle contraction was measured by a strain gauge (Globus Italia, Codogne, Italy) properly mounted on the leg extension machine with chains attached to the sliding axis of the seat. The signal from the strain gauge was sampled at 100 Hz and stored on a computer for later analysis with commercially available software (TCS-SUITE 400, Globus Italia).
The MVC was determined as the highest torque over the 5-second duration. Three trials were performed in each condition, separated by 2-minute rest, and the highest values were retained for subsequent analyses.
All statistical tests were processed using STATISTICA Software (StatSoft, France). Mean, SD and standard error (SE) were calculated for the selected variables. The Shapiro-Wilk W-test of normality revealed that the data were normally distributed. Once the assumption of normality was confirmed, parametric tests were performed. The effects of group, time of day and training were verified by a 3-way analysis of variance with repeated measures. As the CG was included to determine whether the increase of performance is because of our training and tapering program or the physical activity at the university, data of this group were analyzed separately using a 2-way analysis of variance with repeated measures (3 [periods] × 2 [time of day]). The data of the MTG and ETG were analyzed using a 3-way analysis of variance with repeated measures (2 [groups] × 3 [periods] × 2 [time of day]) using absolute values. To determine the difference between the MTG and the ETG, the average of each independent variable recorded in the morning and in the evening was calculated. Then, a 2-way analysis of variance with repeated measures (2 [groups] × 3 [periods]) was used to determine significant differences among the 3 periods. When appropriate, significant differences between means were assessed using Tukey's honestly significant difference (HSD) test procedure. Moreover, unpaired t-tests were used to compare relative changes (delta change values) from T0 to T1 and T1 to T2 between the MTG and ETG. Effect sizes were calculated as partial eta-squared ηp2 to assess the practical significance of our findings. Test-retest reliability was assessed by means of intraclass correlation coefficients (ICCs) and standard error of measurement (SEM). The statistical significance for all analyses was set at p ≤ 0.05.
A significant main effect for time of day (F(1.9) = 2023.9, p < 0.001) demonstrated that the oral temperature improved significantly from morning to evening measures (p < 0.001, Figure 2) with an amplitude (peak to trough) of approximately 2.33 ± 0.1%. There were no significant main effects for groups (F(2.18) = 0.40, p > 0.05) or periods (F(2.18) = 0.63, p > 0.05). Neither was there a significant groups × periods × time-of-day interaction (F(4.36) = 0.61, p > 0.05), indicating that the time-of-day effects for all periods (T0, T1, and T2) did not change with training or tapering at the same time of day.
Mechanical parameters recorded during the Wingate test at T0, T1, and T2, in the morning and in the evening for all the groups are given in Table 2.
The ICC and SEM for Ppeak showed high reliability (ICC >0.86 and absolute SEM < 0.4 W·kg−1). Concerning the CG, there was a significant main effect for time of day (F(1.9) = 23.06, p < 0.001, ηp2 = 0.81) indicating that Ppeak was significantly higher in the evening than in the morning during T0, T1, and T2 (p < 0.05). In contrast, there was no main effect for periods (F(2.18) = 0.97, p > 0.05, ηp2 = 0.04) and periods × time-of-day interaction (F(2.18) = 0.94, p > 0.05, ηp2 = 0.08).
Concerning the 2 training groups, there was a significant main effect for time of day (F(1.9) = 14.54, p < 0.01, ηp2 = 0.67) and periods (F(2.18) = 8.61, p < 0.01, ηp2 = 0.62). However, there was no main effect for groups (F(1.9) = 0.32, p > 0.05, ηp2 = 0.12) and groups × periods × time-of-day interaction (F(2.18) = 0.55, p > 0.05, ηp2 = 0.09). In T0, the post hoc revealed that, for the MTG and ETG, Ppeak improved between the morning and the evening (p < 0.01 for MTG and p < 0.001 for ETG). These diurnal variations persisted in the ETG (p < 0.001) and disappeared in the MTG (p > 0.05) in T1 and T2. Data related to the amplitude of these diurnal variations are presented in Table 4.
When we consider the effect of training and tapering, there was a significant main effect for periods (F(1.9) = 8.61, p < 0.01, ηp2 = 0.75). The post hoc analysis showed that Ppeak was significantly higher in T1 than in T0 (p < 0.01) and in T2 than in T0 (p < 0.001) in the MTG and ETG (Table 5). However, there was no significant difference in the relative increase between the MTG and the ETG at T1 (t = 0.38, p > 0.05) and T2 (t = 0.18, p > 0.05) (Table 6).
The ICC and SEM for Pmean showed high reliability (ICC >0.81 and absolute SEM < 0.3 W·kg−1). For the CG, there was a significant main effect for time of day (F(1.9) = 15.05, p < 0.01, ηp2 = 0.49) indicating that Pmean improved significantly from morning to evening during the 3 periods (p < 0.01 in T0 and p < 0.05 in T1 and T2). However, the main effect for periods (F(2.18) = 1.5, p > 0.05, ηp2 = 0.05) and the periods × time-of-day interaction (F(2.18) = 0.16, p > 0.05, ηp2 = 0.07) were not significant.
For the 2 training groups, the main effect for time of day (F(1.9) = 17.74, p < 0.01, ηp2 = 0.78) and periods (F(2.18) = 5.04, p < 0.05, ηp2 = 0.38) were significant. However, the main effects for groups (F(1.9) = 0.72, p > 0.05, ηp2 = 0.03) and the groups × periods × time-of-day interaction (F(2.18) = 0.36, p > 0.05, ηp2 = 0.07) were not significant. In T0, Pmean was significantly higher in the evening than in the morning (p < 0.001). This daily variation disappeared in the MTG and persisted in the ETG (p < 0.001) in T1 and T2. Data related to the ranges of the diurnal gains are presented in Table 4.
In T1 and T2, there was a significant main effect for periods (F(1.9) = 5.06, p < 0.01, ηp2 = 0.62) with post hoc analysis showed that Pmean was significantly higher in T1 than T0 (p < 0.05) only in the ETG and in T2 than in T0 (p < 0.05) in the MTG and ETG (Table 5). However, there was no significant difference in the relative increase between the MTG and the ETG at T1 (t = 0.4, p > 0.05) and T2 (t = 0.1, p > 0.05) (Table 6).
For the FI, the main effects for groups (F(2.18) = 1.03, p > 0.05), periods (F(2.18) = 1.82, p > 0.05) and time of day (F(1.9) = 1.67, p > 0.05) were not significant. Moreover, the groups × periods × time-of-day interaction (F(4.36) = 0.42, p > 0.05) was not significant.
Maximal Voluntary Contraction
The ICC and SEM showed very high reliability (ICC > 0.95 and absolute SEM < 42.12 N). For the CG, there was a significant main effect for time of day (F(1.9) = 11.73, p < 0.01, ηp2 = 0.7) indicating a significant diurnal variation of MVC with higher values observed in the evening during T0, T1, and T2 (p < 0.01) (Figure 3). In contrast, there was no main effect for periods (F(2.18) = 0.12, p > 0.05, ηp2 = 0.07) and periods × time-of-day interaction (F(2.18) = 0.1, p > 0.05, ηp2 = 0.03).
For the MTG and ETG, the main effects for time of day (F(1.9) = 31.35, p < 0.001, ηp2 = 0.87) and periods (F(2.18) = 23.97, p < 0.001, ηp2 = 0.84) and the groups × periods × time-of-day interaction (F(2.18) = 13.31, p < 0.001, ηp2 = 0.53) were significant. However, there was no main effect for groups (F(1.9) = 0.1, p > 0.05, ηp2 = 0.04). In T0, MVC values were significantly higher at 1700 than 0700 hours (p < 0.001 and p < 0.01 for MTG and ETG, respectively). In T1 and T2, the post hoc analysis revealed that these diurnal fluctuations persisted in the ETG (Figure 4) (p < 0.001). However, the daily variations on MVC disappeared with training in the morning hours (Figure 5). The amplitudes of these diurnal variations are presented in Table 4.
Regarding the effect of training and tapering, there was a significant main effect for periods (F(1.9) = 23.97, p < 0.001, ηp2 = 0.85). The post hoc analysis showed that MVC values improved significantly from T0 to T1 and from T0 to T2 (p < 0.001) (Table 5). However, there was no significant difference in the relative increase between the MTG and the ETG at T1 (t = 0.14, p > 0.05) and T2 (t = 1.8, p > 0.05) (Table 6).
Table 3 presents the SJ and CMJ results calculated in the morning and in the evening, in T0, T1, and T2, for all groups.
The ICC and SEM showed high reliability (ICC > 0.86 and absolute SEM < 1.66 cm). Concerning the CG, there was a significant main effect for time of day (F(1.9) = 9.62, p < 0.05, ηp2 = 0.73) indicating that SJ was significantly higher in the evening than in the morning during the 3 periods (p < 0.05). Nonetheless, there was no main effect for periods (F(2.18) = 0.1, p > 0.05, ηp2 = 0.08) and periods × time-of-day interaction (F(2.18) = 0.08, p > 0.05, ηp2 = 0.05).
Concerning the MTG and ETG, there were significant main effects for time of day (F(1.9) = 10.57, p < 0.01, ηp2 = 0.66) and periods (F(2.18) = 17.32, p < 0.001, ηp2 = 0.69). In contrast, there was no main effect for groups (F(1.9) = 0.07, p > 0.05, ηp2 = 0.06) and groups × periods × time-of-day interaction (F(2.18) = 2.89, p > 0.05, ηp2 = 0.08). In T0, the post hoc analysis showed that SJ values recorded at 1700 hours were higher than those recorded at 0700 hours (p < 0.05). In T1 and T2, these diurnal fluctuations persisted in the ETG (p < 0.01 and p < 0.001, respectively) and disappeared in the MTG. Data related to the amplitudes are shown in Table 4.
Regarding the effect of training and tapering, there was a significant main effect for periods (F(1.9) = 17.23, p < 0.001, ηp2 = 0.59) with post hoc analysis showed that SJ improved significantly from T0 to T1 (p < 0.01 for the MTG and p < 0.05 for the ETG) and from T0 to T2 (p < 0.01) (Table 5). However, the relative increases between the MTG and the ETG at T1 (t = 0.5, p > 0.05) and T2 (t = 0.05, p > 0.05) were not significant (Table 6).
The ICC and SEM for CMJ showed very high reliability (ICC > 0.96 and absolute SEM < 1.06 cm). For the CG, there was a significant main effect for time of day (F(1.9) = 10.41, p < 0.05, ηp2 = 0.41) indicating that CMJ was improved significantly from morning to evening during T0, T1, and T2 (p < 0.01). However, there was no main effect for periods (F(2.18) = 0.1, p > 0.05, ηp2 = 0.04) and periods × time-of-day interaction (F(2.18) = 0.04, p > 0.05, ηp2 = 0.03).
For the 2 training groups, significant main effects for time of day (F(1.9) = 59.87, p < 0.001, ηp2 = 0.78) and periods (F(2.18) = 31.2, p < 0.001, ηp2 = 0.8) were evident. However, the groups effect (F(1.9) = 1.07, p > 0.05, ηp2 = 0.05) and the groups × periods × time-of-day interaction (F(2.18) = 0.58, p > 0.05, ηp2 = 0.04) were not significant. In T0, the post hoc revealed that the 2 training groups behaved similarly; CMJ augmented between the morning and evening (p < 0.05 and p < 0.01 for the MTG and ETG, respectively). In T1 and T2, these diurnal variations persisted in the ETG and disappeared in the MTG. The amplitudes of the diurnal rhythm are shown in Table 4.
After training and tapering, there was a significant main effect for periods (F(1.9) = 32.1, p < 0.001, ηp2 = 0.68). The post hoc analysis showed that CMJ was significantly higher in T1 and T2 than in T0 (p < 0.05 and p < 0.001, respectively) in the MTG and ETG (Table 5). However, there was no significant difference in the relative increase between the MTG and the ETG at T1 (t = 0.33, p > 0.05) and T2 (t = 1.7, p > 0.05) (Table 6).
The aim of this study was to (a) examine the effect of 12 weeks of resistance training and 2 weeks of tapering on the diurnal patterns of short-term maximal performances and (b) to assess the effect of time of day of tapering on the improvement of these anaerobic performances. The major result of this study was that 12 weeks of resistance training and 2 weeks of tapering performed either in the morning or in the evening hours resulted in significant increases in anaerobic performances. However, the magnitude of gains was similar after training and tapering in the morning or in the evening hours.
In T0, short-term maximal performances (i.e., Wingate test, SJ, CMJ, and MVC) were significantly higher in the evening (1700–1800 hours) compared with that in the morning test sessions (0700–0800 hours), with amplitudes amounting to between 3.01 ± 2.24 and 14.6 ± 7.68%. These results confirm those obtained by others (2,15,20,23-28), who observed a significant diurnal variation during various short duration tasks. Moreover, the gains observed in this study are in accordance with the amplitude (peak-to-trough variation) found in other studies (3–21.2%) (20). The exact underlying mechanisms are still not known, but some authors (2,15) have hypothesized a causal link between the temporal fluctuation in core temperature and the diurnal variation in muscular strength and power. In agreement with this, the present results showed a significant diurnal variation in oral temperature. The higher body temperature may enhance metabolic reactions, increase the extensibility of connective tissue, reduce muscle viscosity, and increase the conduction velocity of action potentials (28). However, in our study, the amplitude of variation in oral temperature observed over the day was low (∼2%), and this seems insufficient to entirely explain the changes observed in the muscle contraction properties (e.g., differences between 3 and 41% in short duration exercise performances). Thus, the diurnal difference in core temperature is not the only explanation of the time-of-day effects on anaerobic performances. Recent findings have suggested that the diurnal variation in short-term anaerobic performances has been linked to variation in both central (neural input to the muscles) and peripheral (contractile state of the muscle) mechanisms across the day (7). Moreover, to explain the diurnal variations in muscular power, Souissi et al. (25) have suggested that the daily variations during the Wingate test is mainly because of a higher aerobic contribution in energy production (26), faster O2 kinetics, and better net efficiency (relationship between work performed and energy expended above that at rest) in the evening than in the morning (6).
The major result of this study was that 12 weeks of resistance training modified the diurnal variations of anaerobic performances with a greater improvement of these performances at the time of day at which training was conducted. Moreover, the 2 weeks of tapering resulted in further time-of-day–specific adaptations and increased short-term anaerobic performances. In fact, after these 2 periods, the typical diurnal pattern of anaerobic performances was blunted in the MTG and persisted with higher amplitudes in the ETG.
Although Blonc et al. (4) reported no significant training at a specific hour effect on SJ and CMJ performances after 5 weeks of training (i.e., sprints, jumps, and others exercises), the present findings are consistent, in part, with those of Souissi et al. (27) and Sedliak et al. (22-24). Souissi et al. (27) showed that 6 weeks of resistance training enhanced short-term anaerobic performances and induced a significant time-of-day–specific adaptation. Recently, Sedliak et al. (22-24) showed that diurnal variations during anaerobic tasks decreased after 10 weeks of resistance training in the MTG but not in the ETG and CG. However, the adaptations to resistance training of the MTG in this study were comparable with the results of Sedliak et al. (22-24) and somewhat less pronounced than those of Souissi et al. (27) after 12 weeks of training. After 2 weeks of the tapering phase, the present results were somewhat comparable with the results of Souissi et al. (27). In our opinion, it is possible that the 10 weeks training period (especially the intensive phase performed during the last 5 weeks) in the Sedliak et al. studies (22-24) may have induced accumulated neuromuscular fatigue and could have even led to reduced performances in the posttraining test sessions (19). Regarding training in the evening hours, the present results are in line with those of Sedliak et al. (22-24) who observed that the ETG improved their anaerobic performances in the morning and in the evening. In contrast, Souissi et al. (27) showed that the ETG enhanced their performances only in the evening. The discrepancies between the present findings and those of Souissi et al. (27) might be because of the enhancement of performances during this study tapering program and a decreased performance after training cessation in Souissi et al.'s study. In fact, to avoid detraining and maintain or improve training adaptations and performances before a new test sessions or a major competition, it is important to reduce the training load (i.e., especially by a reduction in the training volume) (14,16-18). Moreover, Gibala et al. (9) showed that only 10 days of detraining resulted in a significant decrease in anaerobic performances (∼8%).
The present results underscore the importance of the temporal specificity of training and tapering. However, the mechanisms responsible for the purported time-of-day–specific adaptations remain elusive. It appears that performances during anaerobic tasks are dependent on a number of time-dependent factors such as neuromuscular and hormonal systems. Testosterone and cortisol have repeatedly been linked with resistance training adaptations, and higher concentrations appear preferential (12). Bird and Tarpenning (3) showed higher testosterone and cortisol levels were obtained after evening than after morning resistance training sessions. These results suggest that optimal adaptations to resistance training seem to occur in the evening (12). However, Sedliak et al. (24) showed that only cortisol concentrations decreased significantly in the MTG, whereas training in the morning or evening hours had no effect on resting serum testosterone concentrations. These authors suggested that this reduction in serum cortisol may presumably be because of a decreased anticipatory psychological stress before the morning test sessions. Another possible explanation may stem from neuromuscular adaptations to resistance training. However, Sedliak et al. (23) failed to show any adaptation to resistance training scheduled repeatedly at a particular time of the day, on the electromyography activity of the knee extensors during unilateral isometric knee extension peak torque. Thus, the authors suggested that peripheral rather than neural adaptations are the main source of temporal specificity in resistance training. More recently, Sedliak et al. (22) observed that the magnitude of muscular hypertrophy (quadriceps femoris cross-sectional areas and volume) did not differ after training in the morning or in the evening hours.
Regarding the adaptations to the tapering phase after intense training, the present results showed significant improvement in short-term performances. These findings are consistent with those of some previous research reporting significant increases in isometric peak torque and low-velocity isokinetic strength performance of the elbow flexors (9) and on maximal strength (10,11) and muscle power (14) after 3–16 weeks of resistance training. Moreover, although there is a tendency to be higher in the evening than in the morning (e.g., 1.9 vs. 2.2% for the SJ, 2.8 vs. 5.3% for the CMJ, and 4.8 vs. 8.4% for MVC in the morning and in the evening, respectively), our results showed that the improvements of performances after the tapering period were similar (no statistical significant difference) after training in the morning or in the evening hours. Because this is the first study examining the effect of tapering at different time of the day on short-term maximal performance, it is difficult to compare the present results referring to the literature. Although speculative, it is possible that the lack of difference between morning and evening tapering may be explained in part by this study' choice of the step taper type (i.e., a sudden, standardized reduction). In fact, although it has been well established that performance improvement after a tapering phase was more sensitive to reductions in training volume than to manipulation of other training variables (5,21), some researchers consider that a fast decay of training volume during this phase is more likely to enhance subsequent performance than a slow decay or step taper (21). Moreover, most experimental and observation research on tapering in the scientific literature has been conducted with individual sports and events (aerobic exercises). Individual sports wherein taper has been examined include running, swimming, cycling, and triathlon (21). However, there is little information available on the prescription of the key elements of the taper (e.g., volume, intensity) after a resistance training period. Thus, a comparative study using different types of taper would be necessary to understand the true importance of tapering in the morning or in the evening hours. Moreover, further research is required to identify the mechanisms by which taper may improve short-term performances after evening or morning training. In this context, hormonal markers such as plasma levels of testosterone and cortisol have been proposed as physiological markers to evaluate the tissue remodeling process and other related mechanisms involved for adaptations during a strength training period (14) and should be measured in such studies.
In summary, the findings of this study suggest that resistance training and tapering at the same time of day have the potential to alter normal diurnal variation in muscle strength and power. Indeed, adaptation to resistance training and tapering is greater at the time of the day at which training is performed than at other times. Moreover, resistance training and tapering performed in the morning hours can improve typically poor morning performances to the same or even higher level as their normal daily peaks typically observed in the evening. Moreover, the present results indicated that the increase of short-term performances after a tapering phase was unaffected by the time of the day of training. Thus, strength and power athletes required to compete at a certain time of day (i.e., when the time of competition is known) may be advised to coincide training and tapering hours with the time of day at which one's critical performance is planned. Moreover, if the time of competition in not known, a tapering phase after a resistance training program could be performed at any time of day with the same benefits.
The authors thank all the subjects for their voluntary participation in this study. The authors have no conflicts of interest that are directly relevant to the contents of this manuscript. This study was financially supported by the Ministry of Scientific Research, Tunisia.
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Keywords:© 2012 National Strength and Conditioning Association
circadian rhythm; muscle power; muscle strength; time-of-day-specific training; taper