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Department of Kinesiology, Louisiana State University, Baton Rouge, Louisiana 70813
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ABSTRACT |
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 TOP
 ABSTRACT
 INTRODUCTION
METHODS
PROCEDURES
RESULTS
DISCUSSION
REFERENCES
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Blood pressure and continuous electrocardiogram recordings were obtained from 12 participants during spontaneous breathing (SB1), dynamic handgrip exercise at 20% (HG20) of maximal voluntary contraction (MVC), and spontaneous breathing (SB2) and dynamic handgrip exercise at 60% (HG60) of MVC. Repeated-measures ANOVAs were used to examine the effects of the exercise conditions on mean arterial pressure (MAP), on mean standard deviation (SDNN), and on the coefficient of variation of R-R intervals. The mean R-R interval responded to exercise in an intensity-dependent manner. SDNN decreased with exercise but was not intensity dependent. Coefficient of variation decreased during HG20, and MAP increased following HG60. These data are consistent with the notion that changes in cardiovascular function with low-intensity exercise are primarily mediated by parasympathetic withdrawal, and as exercise intensity increases, additional cardiovascular reactivity is mediated by increased sympathetic outflow. The change in the coefficient of variation from rest to exercise was unique in comparison to the changes in SDNN, and this merits further investigation.
heart rate variability; autonomic; hemodynamic
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INTRODUCTION |
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TOP
ABSTRACT
INTRODUCTION
METHODS
PROCEDURES
RESULTS
DISCUSSION
REFERENCES
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NUMEROUS METHODS have been employed to evaluate autonomic responses to physical activity (2, 6, 8, 9, 10, 12). One model that has been frequently used in humans is that of dynamic handgrip exercise. With the use of this model, autonomic activity has been inferred from changes in heart rate, mean arterial pressure (MAP), and vascular resistance in the nonworking arm (11, 14, 15). Recently, microneurography has been employed as a technique for describing sympathetic motor nerve activity during dynamic handgrip exercise (11, 14, 15). Using this technique, Victor and Seals (14) suggested that dynamic handgrip exercise at 60% of maximal voluntary contraction (MVC) would result in significant sympathetic activation, but that exercise at 20% of MVC would not significantly augment sympathetic activity. Despite the apparent usefulness of this technique, inferences are limited to sympathetic responses to activity, whereas little information is available concerning parasympathetic mediated responses.
Heart rate variability (HRV) has recently emerged as a useful noninvasive tool for describing autonomic modulation of the heart. Studies employing vagotomy, vagal nerve stimulation, and pharmacological blockade strongly support the premise that alterations in HRV reflect changes in parasympathetic modulation of the heart (3, 4). One of the limitations of HRV, however, is that none of the presently accepted measures of this parameter can account for the multicollinearity of the mean of R-R intervals. That is to say that a change in HRV during exercise, for example, may to some degree occur as a function of exercise-induced shortening of the R-R intervals themselves. This problem has been addressed in other disciplines (e.g., biomechanics/motor control) by using the coefficient of variation to quantify variability (see Ref. 16 for a review). Yet surprisingly, this expression of variability has not been used to quantify HRV.
The purpose of this study was to determine the effect of low- and high-intensity dynamic handgrip exercise on autonomic modulation of the heart and central hemodynamics. Furthermore, the unique aspects of this study were the use of HRV as an index of parasympathetic responses to exercise and the examination of the behavior of the coefficient of variation of the R-R intervals. Only one investigation has utilized HRV during handgrip exercise (7). These authors investigated HRV during isometric handgrip at an intensity of 30% MVC. The findings of this study were consistent with decreased parasympathetic activity with low-intensity activity, a phenomenon that is generally well accepted. However, no studies have evaluated HRV during incremental dynamic handgrip exercise. The hypothesis of this investigation was that indexes of sympathetic activity would appear augmented at high work intensities, and that HRV would decrease during low-intensity handgrip exercise but would not continue to drop with increased exercise intensity.
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METHODS |
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TOP
ABSTRACT
INTRODUCTION
METHODS
PROCEDURES
RESULTS
DISCUSSION
REFERENCES
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Participants
Twelve college-aged (21 ± 1 yr) participants completed all aspects of this study. These participants were free of known disease and were not using any medication known to affect cardiovascular function. The maximal oxygen consumption (
O2 max) of
each participant was determined, as described in Maximal
O2 consumption, and is reported as an
index of cardiovascular fitness. The
O2 max for this study
group was 34.4 ± 5.9 ml · kg
1 · min1.
Additional descriptive characteristics (weight and maximal handgrip strength) are presented in Table 1.
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Instruments
Health status questionnaire. A version of the Health Status Questionnaire (5) was used to screen for the presence of disease and/or the use of medications (prescriptive or otherwise).
Handgrip dynamometry. A handgrip dynamometer (Lafayette Instrument, Lafayette, IN) was used to determine maximal handgrip strength and was employed in the exercise protocols.
Heart rate variability. A Biopac MP100 and its companion software Acqknowledge (model MP100A, Biopac, Santa Barbara, CA) were used to collect and analyze electrocardiogram (ECG) data for mean heart period and beat-to-beat variation in heart period.
Maximal O2 consumption.
O2 max was determined
by means of collecting breath gases in Douglas bags and subjecting them
to gas analysis via an AMETEK gas analyzer (model S-3A/1, Thermox
Instruments Division, Pittsburgh, PA). Minute ventilation was
determined using a Collins 120 L chain compensated gasometer (Warren E. Collins, Brain-tree, MA).
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PROCEDURES |
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TOP
ABSTRACT
INTRODUCTION
METHODS
PROCEDURES
RESULTS
DISCUSSION
REFERENCES
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Participants reported to the laboratory on two occasions no more than
10 days apart. Time of day was held constant for both visits. The first
visit was for the purpose of familiarizing the participant with the
testing environment; therefore, the data described herein are those
collected during the second visit only. Health status and
O2 max were examined
during the second visit only. The following procedures were performed
on each occasion.
Hemodynamic Studies
Upon arriving at the laboratory, participants were asked some general questions about their health history to assess for the presence of any disease, condition, or medical therapy that might affect cardiovascular function. Participants were then instructed to lie supine and were fitted with a blood pressure cuff on the upper aspect of the nondominant arm. A three-lead ECG was applied, and ECG data were continuously collected throughout the protocol (using the Biopac MP100 system). MVC was obtained via a one-repetition maximum on a handgrip dynamometer.Participants performed dynamic handgrip exercise at 20% of MVC (HG20) and 60% of MVC (HG60) at ~60 contractions/min for a maximum of 5 min (14). Each exercise period was preceded by a 5-min quiet rest interval where the subject breathed spontaneously (SB1 and SB2, respectively). Blood pressure readings were obtained from the nonworking arm during minutes 3 and 5 of the spontaneous breathing conditions, and during minute 3 and immediately after each handgrip exercise condition.
O2 max
Data Treatment
MAP was calculated using the equation MAP = (SBP
DBP)/3 + DBP,
where SBP and DBP are systolic and diastolic blood pressure, respectively. The ECG data were analyzed using the
Acqknowledge 3.0 software. The ECG data were visually inspected for
nonsinus beats and converted to a tachogram of the R-R period. None of the participants demonstrated nonsinus activity. The mean heart period
(mean R-R) and standard deviation of normal R-R intervals (SDNN) over
90 s of steady-state exercise (see Fig. 1)
are reported. We did not report frequency domain data for the following
two reasons: 1) the tachogram of heart rate during exercise is
not a stationary signal, and 2) the comparison of HRV values
under different conditions, where R-R periods are also different,
appears to be of limited value. However, in an effort to control for
differences between resting and exercise heart periods, we used the
coefficient of variation (SDNN/RR) as an expression of HRV. To our
knowledge, HRV has never been reported using this technique.
Nonetheless, there may be some potential to glean unique information
from expressing HRV relative to the underlying mean chronotropic
activity of the heart.
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Statistical Analysis
A repeated measures ANOVA with preplanned contrasts was used to determine differences in MAP, mean R-R, SDNN, and coefficient of variation, among the four test conditions. Alpha was set at 0.05.| |
RESULTS |
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TOP
ABSTRACT
INTRODUCTION
METHODS
PROCEDURES
RESULTS
DISCUSSION
REFERENCES
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Descriptive statistics for the participants can be found in Table 1.
Figure 2 is a representative sample of a
heart rate tachogram during one spontaneous breathing condition, with
HG20 and HG60. Results of the ANOVA indicate a
main effect of the test condition on all variables (P < 0.05). The effect was such that MAP was significantly higher during
HG60 than all other conditions, and that MAP during SB1,
SB2, and HG20 were not different from one another (see Fig.
3). Mean R-R interval and SDNN dropped
significantly during both exercise conditions. The lower SDNN values
observed during HG20 and HG60 were not
different from one another (see Fig.
4B), whereas the mean R-R during
HG60 was significantly lower than that observed during
HG20 (see Fig. 4A). The condition effect on the
coefficient of variation was unique in that the values for this
variable were significantly lower during HG20 than in all
other conditions, and HG60 was not different from SB1 and SB2. (see Fig. 4C).
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DISCUSSION |
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TOP
ABSTRACT
INTRODUCTION
METHODS
PROCEDURES
RESULTS
DISCUSSION
REFERENCES
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The purpose of this investigation was to determine the effect of low- and high-intensity dynamic handgrip exercise on autonomic modulation of the heart and central hemodynamics in young, apparently healthy adults. The participant characteristics and study protocol were similar to those of Victor and Seals (14) but also included HRV as a measure of parasympathetic modulation of the heart.
The findings of the present investigation support previous studies that suggest an intensity-dependent increase in sympathetic responses to dynamic handgrip exercise (11, 14, 15). MAP, an index of sympathetic activation, increased as a consequence of dynamic handgrip at 60% MVC, but not at 20% MVC. This finding is in agreement with Saito et al. (11), who reported no change in MAP with dynamic handgrip exercise at 10% of MVC. In contrast, Victor and Seals (14) reported a 7% increase in MAP with 20% MVC. However, the mean resting MAP of Victor and Seals's sample was significantly higher than that observed in this study (97 mmHg vs. 81 mmHg, respectively). Although both values are within the expected range of normal blood pressures, the apparently lower resting MAP reported herein may have been a consequence of the acclimatization period. Nonetheless, the results of the present investigation are in agreement with those of Victor and Seals (14). These authors observed an increase in MAP with 60% MVC that was of a greater magnitude than that observed during 20% MVC. Therefore, there is agreement that sympathetic excitation, as a consequence of dynamic handgrip exercise, is intensity dependent.
Measures for R-R interval and SDNN were derived from 90-s segments of ECG data during each test condition. These datasets reflect chronotropic activity during steady state (i.e., stable heart rate). The heart rate response to the exercise protocols was such that steady state was attained by 90 s into the exercise period. This observation is in agreement with that of Fagraeus and Linnarsson (3), who reported time to steady-state heart rate during leg exercise to be 60-90 s.
With respect to the chronotropic activity of the heart, the findings of this study suggest an intensity-dependent decrease in heart period (increase in heart rate) and a significant decrease in SDNN with exercise at 20% MVC, but no further decrease with 60% MVC. The observation of an intensity-dependent drop in mean R-R interval with HG20 and HG60 is in agreement with Victor and Seals (14). The unique aspect of this study is the inclusion of SDNN in this model. This parameter was chosen as a method for characterizing HRV in accordance with the Task Force of the European Society of Cardiology (13). These recommendations suggest that SDNN is a sensitive measure of HRV when data are analyzed over an extremely short time period (90 s), and that this measure would primarily reflect parasympathetic mediated activity. In contrast to the intensity-dependent changes in MAP and R-R interval, SDNN did not drop in an intensity-dependent manner. Rather, the changes in SDNN are consistent with parasympathetic withdrawal at low intensity (20% MVC) but no further change in parasympathetic modulation of the heart at higher (60% MVC) workloads. These findings are in agreement with those of Fagraeus and Linnarsson (3), who reported that initial changes in heart rate during exercise were primarily due to parasympathetic withdrawal. Additionally Hollander and Bouman (4) demonstrated, using pharmacological blockade, that the decrease in R-R interval during low-intensity exercise was mediated by vagus nerve activity without an increase in sympathetic drive. Furthermore, these findings are consistent with the observations of Kurita et al. (7), who examined HRV during isometric handgrip.
Thus the exercise-induced changes in SDNN and MAP are consistent with the notion that changes in central CV function with low-intensity exercise are primarily mediated by vagal withdrawal, and that as exercise intensity increases, additional cardiovascular reactivity is mediated by increased sympathetic outflow. The agreement between the response of SDNN during the incremental handgrip exercise and our understanding of vagal control of the heart suggests some degree of construct validity for using SDNN to quantify changes in parasympathetic modulation of the heart during dynamic handgrip exercise. The inclusion of HRV in this model may prove to be of particular importance in evaluating autonomic function in various pathological conditions such as heart failure, hypertension, and diabetes mellitus.
One of the criticisms of comparing HRV values collected under different conditions is that the variability of the heart rate may be dependent on the heart rate itself (1). A unique aspect of this study was the expression of HRV as the coefficient of variation of R-R intervals. Whereas this method of characterizing variability relative to the mean behavior of the system is rather simple and straightforward, to our knowledge HRV has not been expressed in this fashion. The data from this investigation suggest that coefficient of variation provides some unique information about cardiac chronotropic control. That is to say that the exercise-induced changes in the coefficient of variation of R-R intervals were different from the changes in mean R-R intervals and SDNN. Similarly to SDNN, the coefficient of variation dropped with 20% MVC but did not drop below resting values during 60% MVC. From these findings one could hypothesize that a change in the coefficient of variation reflects parasympathetic withdrawal without an increase in sympathetic activation. However, the meaningfulness of this parameter is not at all clear. Rather, we report these findings in the context of recommending that future efforts determine the physiological correlates and the predictive validity of the coefficient of variation of R-R intervals.
In summary, the findings of this study support the use of HRV as an index of parasympathetic modulation of the heart during dynamic handgrip exercise. Furthermore, this study suggests that the coefficient of variation of R-R intervals provides a unique method of characterizing cardiac chronotropic activity.
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FOOTNOTES |
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The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. §1734 solely to indicate this fact.
Address for reprint requests and other correspondence: H. A. Kluess, 112 HPL Field House, Department of Kinesiology, Louisiana State University, Baton Rouge, LA 70813 (E-mail: hklues1{at}lsu.edu).
Received 22 July 1999; accepted in final form 15 November 1999.
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TOP
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METHODS
PROCEDURES
RESULTS
DISCUSSION
REFERENCES
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