Purpose: To evaluate the effect of maturity status on the autonomic nervous system at rest and recovery after short-term, high-intensity exercise in adolescents.
Methods: A biological maturity age was estimated in 27 males by calculating the years from peak height velocity (PHV) using a multiple regression equation. Subjects were divided into two groups: pre-PHV (years from PHV < 0.49), N = 14, mean age = 12.29 ± 0.91 yr; post-PHV (years from PHV > 0.5, N = 13, mean age = 15.12 ± 0.76 yr). HR variability was used to evaluate autonomic function. ECG tracings were collected during 5 min at rest and recovery after a Wingate test and were analyzed in the frequency domain (low-frequency (LF), high-frequency (HF), LF/HF, total power (TP)). Data are presented as natural logarithms (LN).
Results: Changes in HR from HRpeak during exercise to HR measured at minute 4 after exercise (ΔHR4) were significantly greater in the pre-PHV group (84.31 ± 17.58 bpm) compared with the post-PHV group (69.42 ± 17.63 bpm). There were no significant differences in resting HR variability between pre- and post-PHV groups (P > 0.05). Significant group × time interactions were found for LFLN (ms2) and TPLN (ms2) measured during recovery (P < 0.05). Post hoc tests showed that the pre-PHV group had significantly higher postexercise LFLN (5.02 ± 0.97 vs 4.19 ± 0.79) and TPLN (6.36 ± 1.02 vs 5.62 ± 0.65) compared with the post-PHV group. When postexercise LFLN (ms2) was normalized for TPLN (ms2), there were no significant differences between groups (P > 0.05).
Conclusion: The pre-PHV group had higher total HR variability than the post-PHV group after a Wingate test, suggesting that maturity status significantly affects total HR variability during recovery after high-intensity exercise.
1Department of Exercise Science, Syracuse University, NY; 2Department of Kinesiology, University of Illinois, Champaign, IL; 3College of Kinesiology, University of Saskatchewan, SK, CANADA; and 4Sport Department, Liverpool Hope University, Liverpool, UNITED KINGDOM
Address for correspondence: Styliani Goulopoulou, M.S., 820 Comstock Avenue, Room 201, Syracuse, NY 13244-5040; E-mail: email@example.com.
Submitted for publication July 2005.
Accepted for publication November 2005.
Significant differences in the rate of HR recovery after exercise have been demonstrated among children of varying size (27) and between children and adults (1,12,22). Changes in HR from maximum to HR measured during recovery after maximal aerobic exercise (ΔHR) have been demonstrated to be greater in smaller children (body surface area < 1.0 m2, age: 7 yr) compared with larger children (body surface area > 1.2 m2, age: 12 yr) (27). It has also been found that children exhibit greater ΔHR compared with adults after exercise of various intensities. Baraldi et al. (1) showed that these differences were more pronounced after high-intensity exercise compared with exercise of a lower intensity. These findings were further confirmed by Hebestreit et al. (12), who found faster HR recovery kinetics and lower net HR (postexercise HR minus resting HR) in children compared with adults after a short-term, high-intensity exercise (Wingate test). More recently, Zafeiridis et al. (28) showed HR after high-intensity, intermittent anaerobic exercise recovered faster in prepubertal compared with pubertal boys.
It has been speculated that developmental changes in the sympathetic and parasympathetic autonomic nervous systems might be responsible for the faster rate of HR recovery after exercise in children compared with adolescents and adults (1,12,22). Autonomic function can be estimated using assessment of HR variability, which is a noninvasive method of measuring variations in R-R intervals and assessing the contribution of sympathetic and parasympathetic nervous systems to HR modulation. Cross-sectional HR variability studies in infants (19), children (8,9), and adolescents at rest (24) suggest a progressive maturation of the autonomic nervous system from childhood to adulthood. In particular, it has been shown that total HR variability increases up to the age of 6 and decreases toward adolescence (10,18). The changes, however, in autonomic function that occur during the adolescent period remain unclear (9,24).
There is limited research assessing the contribution of the autonomic nervous system to HR regulation during recovery from exercise in children and adolescents. Ohuchi et al. (22) demonstrated a significant relationship between changes in HR during recovery after exercise at two different exercise intensities (maximal exercise and a constant load at the anaerobic threshold) and HR variability in individuals with a history of Kawasaki disease. These authors, however, only investigated the relationship between changes in HR recovery and HR variability variables measured at rest. Research in adults has shown recovery HR may be better explained when HR variability is measured during recovery after exercise (16).
Finley et al. (9) speculated that differences in the rate of maturational progress might be responsible for the large variation noted in resting HR variability in children and adolescents. Others have shown a significantly positive relationship between maturity status, using secondary sex characteristics and long-term HR variability in adolescents (7). One of the problems with using secondary sex characteristics is the invasive nature of the assessment. Also, the timing of secondary sex characteristic events varies greatly between individuals of the same sex and makes the use of secondary sex staging problematic. The most commonly used somatic milestone in longitudinal studies of childhood growth is the age at peak height velocity (PHV). Once age at PHV is identified, individuals are aligned around this biological maturity age to adjust for the confounding effects of maturation. Although previously serial data were required for its assessment, age at PHV can now be estimated using gender-specific multiple regression equations. These equations are based on segmental growth patterns that predict the maturity offset age parameter (21).
The purposes of this study were 1) to compare sympathetic and parasympathetic modulation of HR between males who had not yet reached PHV (pre-PHV) with males who had reached PHV (post-PHV), at rest and during recovery after short-term, high-intensity exercise; and 2) to evaluate the relationship between change in HR (ΔHR = HRpeak − HRrecovery) during recovery from short-term, high-intensity exercise and sympathetic and parasympathetic nervous system activity in males 12-16 yr of age. We hypothesized that the pre-PHV group would exhibit greater changes in HR after exercise accompanied by higher postexercise parasympathetic activity and lower sympathetic activity compared with the post-PHV group. We also hypothesized that ΔHR during recovery would be significantly correlated with postexercise sympathetic (negative correlation) and parasympathetic (positive correlation) nervous system activities.
Twenty-seven healthy adolescent males aged 12-16 yr (13.68 ± 1.69 yr) volunteered to participate in this study. Exclusion criteria included known cardiac problems, hypertension, metabolic-endocrine disorders, and orthopedic conditions. A physical activity questionnaire modified from Bar-Or was used to obtain subjects' physical activity level for descriptive purposes (2). None of the subjects were participating in endurance training > 3 h·wk−1. Subjects' physical characteristics are summarized in Table 1. Written informed consent from the parents/guardians and verbal assent from the children were obtained prior to the start of the study. The study was approved by the institutional review board at Syracuse University.
All subjects were familiarized with all testing procedures prior to datacollection; these included paced breathing (15 breaths per minute) determinedby a metronome (MR-800 Quartz Metronome, Korea), and several trial sprints(3- to 5-s duration) to represent the Wingate test on an electronically braked cycle ergometer (Excalibur, Lode, Netherlands). The familiarization session lasted approximately 20 min. Anthropometric measurements were obtained including stretch standing and sitting height and body mass. HR variability measurements were conducted in the supine position for 5 min preexercise after 10 min of quiet rest and immediately after a 30-s Wingate test. All subjects completed a pretest questionnaire to verify that they were in a postprandial state (~3h) and had refrained from vigorous exercise 12 h before the testing and caffeinated products (i.e., soft drinks, tea, chocolate) 3 h prior to the tests.
All subjects were asked to repeat the HR variability measurements and the Wingate test on an additional visit. This visit was optional, and its purpose was to assess reproducibility of the HR variability measurements after a Wingate test. It was performed 48 h (minimum) to 14 d (maximum) after the first testing session, and all tests were conducted at the same time of day as the first day to control for circadian variation in HR variability measurements (20).
Body mass, stretch height, sitting height, and leg length measurements were conducted following the International Standards for Anthropometric Assessment (17). Body mass was measured in kilograms on a calibrated electronic scale (BodPod, Life Measurement Instruments, Concord, CA). The subjects were weighed with their shoes removed and wearing swimming trunks. Body mass to nearest 0.1 kg was recorded. Stretch height was measured in centimeters using a wall-mounted stadiometer. The subjects removed their shoes and stood with back, buttocks, and heels against the wall and faced directly forward. The investigator placed his/her hands along the line of the subjects' jaw to ensure that the head was in the proper position. The subjects were instructed to take and hold a deep breath. A headboard was placed firmly down on the subjects' vertex, depressing the hair as much as possible. Measurements at the end of the subjects' deep inward breath to the nearest 0.1 cm were recorded. Sitting height was measured in centimeters using a measuring box (height: 86.3 cm) attached to a wall-mounted stadiometer. The subjects sat on the measuring box with their hands resting on their lap. The stretch height protocol was used to measure the sitting height. Two measurements were taken for both sitting and stretch height. If the two measurements differed by more than 0.4 cm, a third trial was conducted. If two measures were obtained, the average value was used, whereas if three measurements were taken, the median value was recorded. Sitting height was calculated as the maximum distance from the vertex to the base of the sitting surface. Leg length (cm) was calculated by subtracting the sitting height from the stretch height. Test-retest reliability was calculated for stretch height (R = 0.999, P < 0.05) and sitting height (R = 0.990, P < 0.05) using intraclass correlation coefficients. Body mass index (BMI) was calculated as body mass divided by height squared(kg·m−2).
Years from PHV were calculated using anthropometric variables (leg length, body mass, sitting and standing height) and chronological age as dependent variables in the following equation. This equation estimates maturity offset (years from PHV) within an error of ± 1 yr, 95% of the time (21): Years from PHV = −9.3236 + [0.0002708 × (leg length × sitting height)] + [(−0.001663) × (chronological age × leg length)] + [0.007216 × (chronological age × sitting height)] + [0.02292 × (body mass/standing height) × 100)]. Based on years from PHV, subjects (N = 27) were divided into two maturity groups: 1) pre-PHV (maturity offset < 0.49 yr, N = 14), and 2) post-PHV (maturity offset > 0.5 yr, N = 13).
HR variability measurements.
Following a 10-min quiet rest in the supine position, R-R intervals were recorded for 5 min by continuous HR measurements with a modified CM5ECG lead, interfaced with data collection and interpretation software (Biopac Systems, CA). The R-R intervals were collected at a sample rate of 1000 Hz. After the exercise test, subjects were assisted to immediately lie down in the supine position, and HR variability measurements were repeated for 10 min as previously described. All subjects were asked to breathe at a rate of 15 breaths per minute (0.25 Hz) during the HR variability measurements at both rest and recovery. The rate of paced breathing was set for the subjects using a metronome (MR-800 Quartz Metronome, Korea).
ECG data was filtered through visual and automatic editing to eliminate undesirable noise or premature beats. HR variability was not quantified during the first 5 min of recovery due to time series nonstationarity. Thus, HR variability analysis was performed only during the second 5-min segment of ECG data. The filtering and analysis of the R-R intervals were conducted according to procedures described by Huikuri et al. (15). Any R-R interval that deviated more than 30% from the previous interval was considered premature. Recordings in which more than 2% of beats were filtered were excluded from the HR variability analysis. Specifically designed software (HEARTS™, Finland) was used to calculate power spectrum densities of HR variability (frequency domain analysis). An autoregressive approach (fixed model order of 10) was used to determine low-frequency (LF; 0.04-0.14 Hz) and high-frequency (HF; 0.15-0.40 Hz) power as previously described by Tulppo et al. (26). Total power (TP) and LF/HF were calculated. The HF was used as an index of parasympathetic nervous system activity, whereas the LF primarily reflects sympathetic nervous system activity (4). The LF/HFratio was also used as an index of sympathetic modulation (4). It has been suggested that when alterations in total variability (TP) occur (e.g., with an exercise stimulus), LF and HF should be expressed relative to TP (4). Thus, HF and LF power spectral densities were calculated in both absolute and normalized units (normalized to total spectral power) following standard procedures recommended by the Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology (4).
All subjects performed a Wingate test on an electronically braked cycle ergometer (Excalibur, Lode, Netherlands). Prior to the exercise test, seat height was adjusted to accommodate the subject's stature, such that the knee would be slightly bent at maximal leg extension. Toe clips were used and the subject was instructed to adjust the handlebars to a comfortable position. Subjects performed a 3-min warm-up pedaling at a cadence of 80 rpm at a constant power output set at 50 W. The warm-up included two to three brief (3-5s) sprinting bouts to maximal cycling speed (120 rpm) at higher power output. The intensity of the warm-up was chosen to increase HR to approximately 140-150bpm (3). After a 1-minrest, subjects were instructed to pedal at full speed with the cycle ergometer unloaded for 5-8 s. At this stage, the full braking force [(0.7 N·kg−1 bodymass) × (subject's body mass (kg)] was applied and a 30-s countstarted (6). Researchers verbally encouraged the subjects throughout the test. Peak power (PP) was measured as the highest power achieved at any 5-s stage of the test and was expressed in both watts and watts per kilogram of body mass.
Data were not normally distributed and, consequently, logarithmic transformation of the HR variability variables was performed so that parametric statistics could be used. HR variability data are presented as natural logarithms (LN); LFLN, HFLN, LFLN/HFLN, TPLN. Two-way ANOVA (2 × 2 ANOVA) with repeated measures (group (pre-PHV vs post-PHV) × time (preexercise, recovery)) was conducted to determine any significant differences between the two maturity groups with respect to LFLN (ms2) and (nu), HFLN (ms2) and (nu), LF/HF, and TP (ms2). When significant F values were obtained, pairwise comparisons were carried out using a modified Bonferroni correction for the number of pairwise comparisons to control for Type I error by dividing α < 0.05 by the number of comparisons in that ANOVA analysis to obtain the "critical value" against which each P value was compared 14).
Differences between groups in HRpeak were assessed using an independent t-test. Differences between groups in HR changes from HRpeak to HR measured at minutes 1, 2, 3, and 4 after the Wingate test were evaluated using 2 × 4 ANOVA with repeated measures. Pearson product-moment correlations were used to assess the relationship between the LFLN (nu), HFLN (nu), and the changes in HR at minute 4 (ΔHR4). Partial correlation was used to examine the above-mentionedb relationships controlling for HRpeak.
The threshold of significance in all statistical tests was set at α = 0.05. All values are presented as mean ± SD. Statistical analysis was performed with SPSS for Windows, version 12.0 (SPSS, Inc., Chicago).
A power calculation was conducted to provide an estimate of the minimum sample size in our 2 (time) × 2 (groups) experimental design, necessary to provide adequate statistical power. Changes in HR (mean ± SD) from a research study conducted by Ohuchi et al. (22) were used for the power analysis. Based on the power calculation, a sample size of 10 in each group would have 80% power to detect, at the end of the study, a change of 80% in HR and HR variability variables (α = 0.05). This study had a minimum of 13 subjects in each group.
Subject characteristics are shown in Table 1. Age (yr), body mass (kg), height (cm), body mass index (kg·m−2), and peak power (W) were significantly higher in the post-PHV group compared with the pre-PHV group (P < 0.05). When PP was expressed relative to body mass (W·kg−1), there were no significant differences between groups.
HR responses after the Wingate test.
Figure 1 illustrates the HR responses at rest, at the end of exercise (HRpeak), and 10 min after the Wingate test. There were no significant differences in preexercise HR between the pre-PHV and post-PHV groups (P > 0.05). HRpeak was significantly higher in the pre-PHV compared with post-PHV subjects (pre-PHV: 180 ± 16 vs post-PHV: 167 ± 13, P < 0.05). There were no significant differences between groups at any time point after the Wingate test (P > 0.05). Moreover, there was no significant group × time interaction (P > 0.05).The changes in HR measured at minutes 2, 3, and 4 during recovery weresignificantly larger in the pre-PHV group compared with the post-PHV group(Table 2) (P < 0.05).
HR variability at rest and during recovery.
The comparison of HR variability measured preexercise and during recovery after the Wingate test between the pre- and post-PHV group is shown in Table 3. As can be seen, there was a significant time effect for all the HR variability variables (LFLN (ms2,nu), HFLN (ms2, nu), LF/HFLN, TPLN (ms2)). HFLN (ms2, nu) was significantly lower during recovery compared with baseline in both groups (P < 0.05). Similarly, LFLN (ms2) and TPLN (ms2) were significantly reduced during recovery compared with the resting values (P < 0.05). When LFLN was expressed in normalized units, the postexercise values were significantly higher than the resting values in both groups (P < 0.05). The LF/HFLN ratio was also significantly higher during recovery compared with baseline in both maturity groups (P < 0.05). There was no significant group effect on HR variability variables either atrest or during recovery (P > 0.05). A significant group (pre-PHV vs post-PHV) × time (rest, recovery) interaction was found for LFLN power (ms2) and TPLN (ms2) (P < 0.05). Post hoc analysis showed that the pre-PHV group had significantly higher postexercise LFLN (5.02 ± 0.97 vs 4.19 ± 0.79) and TPLN (6.36 ± 1.02 vs 5.62 ± 0.65) compared with the post-PHV group. When postexercise LFLN (ms2)was normalized for TPLN (ms2), there were no significant differences between groups (P > 0.05). Figure 2 illustrates the time × group interaction for LFLN (ms2) and TPLN (ms2).
Correlations between HR variability and changes in HR.
There were no significant correlations amongst preexercise LFLN (nu) power, HFLN (nu) power, and ΔHR4 (P > 0.05). Postexercise LFLN (nu) and HFLN (nu) were moderately correlated with ΔHR4. Correlation coefficients were 0.475 (P = 0.019) and −0.469 (P = 0.021) for HFLN (nu) and LFLN (nu), respectively. When the correlations were controlled for HRpeak, correlation coefficients were 0.714 (P = 0.00) and −0.646 (P = 0.001) for HFLN (nu) and LFLN (nu), respectively.
Reproducibility of HR variability measurements during recovery.
Seven subjects repeated the experiment (HR variability measurements and Wingate test) on a separate occasion. Reproducibility of HR variability measurements during recovery after the Wingate test was evaluated, and intraclass correlation coefficients were 0.964 and 0.933 (P < 0.05) for LFLN (ms2) and HFLN (ms2), respectively.
The present study demonstrated that there were no significant differences in any of the resting HR variability variables between pre- and post-PHV adolescent males, whereas postexercise TPLN and absolute LFLN power of HR variability were significantly higher in the pre-PHV group compared with the post-PHV group. Furthermore, moderate correlations were found between the changes in HR immediately after the Wingate test and normalized LFLN, HFLN power of HR variability.
Previous cross-sectional studies have demonstrated that total HR variability decreases with increasing chronological age (18). Studies in children and adolescents, however, have revealed conflicting results. Tanaka et al. (24) reported that resting parasympathetic nervous system activity (HF power) was significantly higher in adolescents 12-16 yr old compared with children aged 6-11 yr. Conversely, Finley et al. (9) found that resting parasympathetic activity (HF power) was not significantly different between children aged 5-7 and 10-12 yr, whereas resting sympathetic nervous system activity (LF power, LF/HF) was significantly higher in the youngest group compared with the oldest group. In a subsequent study, the same investigators reported a gradual increase in LF, HF, and TP from 0 to 6 yr followed by an increase to 24 yr, suggesting an increase in parasympathetic nervous system from infancy to early childhood followed by a reduction to adulthood (8). No adolescent group was included in this study. Pakkujamsa et al. (23) confirmed these findings and also reported that children 6-15 yr old had higher TP, LF, and HF compared with children younger than 6 yr. Finley et al. (8,9) suggested that variation in maturity status might be responsible for the high variation in the HR variability findings noted within each age group. None of the above-mentioned studies measured HR variability with respect to maturity status.
Faulkner et al. (7) assessed the relationship between maturity status and long-term HR variability measured in the time domains in adolescents aged 13-18 yr. They found a significant relationship (r = 0.29) between secondary sex characteristic stages for development of pubic hair and the SD of R-R intervals, which is an index of circadian variation of HR variability. The authors concluded that circadian variation of HR variability might be affected by maturation over the pubertal years. However, because this relationship was weak and there were no significant relationships between sexual maturity and the rest of the time domain variables, it was suggested that maturity status was not significantly related with the HR variability measurements. Our study aimed to further examine the effect of maturity status on short-term HR variability, comparing adolescents of different maturity status using age at PHV as a maturity index. Because we found no significant differences in resting HR variability between the two groups, we suggest that maturity status does not significantly affect resting HR variability during the adolescent period. This indicates that the function of the autonomic nervous system at rest might not be maturity dependent. These findings were further supported by the absence of significant differences in resting HR between the two groups.
Although HR and HR variability at rest were not significantly different between the two maturity groups, there were significant differences in HR and HR variability during recovery. The changes in HR from HRpeak to HR measured at minutes 2, 3, and 4 of recovery were significantly greater in the pre-PHV group compared with the post-PHV group, suggesting that the changes in HR after the Wingate test were maturity status related. Our findings are in agreement with those of previous investigations that demonstrated that the HR of prepubertal children recovered faster than that of pubertal children and adults after short-term, high-intensity exercise (28). Comparing the HR variability responses to recovery after the Wingate test, we found that TPLN and absolute LFLN power were significantly higher in the pre-PHV group compared with the post-PHV group. Both variables were significantly lower during recovery compared with rest in both groups. These findings suggested that TPLN and absolute LFLN returned to baseline values faster in the pre-PHV group compared with the post-PHV group. It is possible to speculate that the Wingate test might provoke a greater decrease in TPLN and absolute LFLN during exercise in the post-PHV group compared with the pre-PHV group. It has been suggested that HR variability measurements during exercise should be made at steady state, and thus we did not measure HR variability during the Wingate test. Therefore, it is not possible to state with certainty whether the differences in HR variability variables between groups were due to a faster recovery in autonomic nervous system in the pre-PHV group or a differential HR variability response to the Wingate test between the two maturity groups. The higher LFLN noted in the pre-PHV group was not accompanied by a higher normalized LFLN or a higher LF/HFLN, which are better indicators of sympathetic nervous system activity; therefore, these findings should be treated with caution. TP of HR variability reflects total variability in HR, which is primarily determined by the parasympathetic nervous system activity. Therefore, we can speculate that parasympathetic nervous system activity was significantly higher in the pre-PHV group compared with the post-PHV group after the Wingate test. This could further explain their faster HR recovery.
There were significant differences in HRpeak between the two maturity groups, with the pre-PHV group having higher HRpeak compared with the post-PHV group. This indicates that HRpeak in response to the Wingate test is maturity status related. To the best of our knowledge, no previous studies have evaluated HRpeak in response to the Wingate test with respect to maturity status. Based on previously published data, possible mechanisms responsible for these differences might include maturity-related differences in heart size (mass and volume) (5,13) and muscle pump function between advanced and late maturers. The present study did not assess the subjects' cardiac volume and function of muscle pump. Nevertheless, differences in these variables between groups could result in differences in venous return, and thus individuals of different maturity status could experience different responses of right atrium receptors. Consequently, this would result in different autonomic influences on the sinoatrial node.
To determine the association between changes in HR during recovery and HR variability variables, we evaluated the correlations between changes in HR at 4 min after the Wingate test and normalized HFLN power and LFLN power. HFLN power is a valid measure of parasympathetic nervous system, whereas LFLN power is influenced by both the parasympathetic and sympathetic nervous systems. Our findings demonstrated a negative correlation between ΔHR4 and LFLN (nu) and a positive correlation between ΔHR4 and HFLN (nu), indicating that withdrawal of sympathetic activity and activation of parasympathetic activity are significantly related to decreases in HR during recovery after the Wingate test. There were no significant relationships between ΔHR4 and resting parasympathetic and sympathetic nervous system activity. Our findings are in contrast with those of Ohuchi et al. (22), who demonstrated that changes in HR during recovery after maximal aerobic exercise were significantly associated with resting HF power (r = −0.56) and LF/HF (r = 0.69) in children (9-12 yr) and young adults (17-21 yr). However, these investigators did not measure HR variability during recovery, and thus they did not evaluate the relationship between changes in HR and autonomic nervous system measured at recovery. Similar to the present study, previous research has demonstrated that changes in HR after exercise were associated with the postexercise rather than the resting HR variability (16). The moderate relationships found between changes in HR and the autonomic nervous system were improved when the correlations were controlled for differences in HRpeak between groups. This indicates that the differences in HR responses to exercise were associated with the differences in changes in HR during recovery.
The results of the present study also demonstrated that HR variability was not fully restored 10 min after a 30-s supramaximal exercise test, irrespective of maturity status. The HFLN (nu) was significantly suppressed 10 min after exercise, whereas the LFLN (nu) and LF/HFLN were significantly higher during recovery compared with preexercise values in both maturity groups. Our findings suggest that parasympathetic nervous system activity was suppressed, whereas sympathetic activity was enhanced compared with preexercise 10 min after a 30-s supramaximal exercise (4). This finding is in agreement with previous studies in adults. Hayashi et al. (11) found that HF, which reflects parasympathetic nervous system activity, was still suppressed 10 min after a maximal aerobic exercise test. In addition, Terziotti et al. (25) reported that 15 min after a 20-min steady-state exercise test at 80% of anaerobic threshold, sympathetic nervous system activity was still enhanced and approximately 1 h was needed for complete restoration of autonomic control. To the best of our knowledge, no previous study has reported evidence regarding the time course of the recovery of the autonomic nervous system after high-intensity exercise in children.
In conclusion, the findings of this study show that even though there were no significant differences in resting HR variability between advanced and late maturers, postexercise HR variability was higher in late maturers, indicating higher cardiac parasympathetic nervous system activity immediately after exercise in this group. These findings suggest that maturity status should be taken into account when HR variability measurements are conducted. Furthermore, maturity status may also need to be considered when selecting the appropriate time interval for recovery from high-intensity exercise in adolescents.
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Keywords:©2006The American College of Sports Medicine
MATURATION; PARASYMPATHETIC; SYMPATHETIC; EXERCISE