107_115_Pichot_CAR_251 29.03.2005 13:17 Uhr Seite 107
Clin Auton Res (2005) 15 : 107–115
DOI 10.1007/s10286-005-0251-1
Vincent Pichot
Frédéric Roche
Christian Denis
Martin Garet
David Duverney
Frédéric Costes
Jean-Claude Barthélémy
■ Abstract Aims Autonomic nervous system activity decreases continuously with age and appears to
be a powerful predictor of disease
and death. Attempts are thus made
to reactivate autonomic drive with
the intent of improving health.
Methods We assessed maximal oxygen consumption (VO2max), autoReceived: 10 September 2002
Accepted: 18 November 2004
V. Pichot · F. Roche · Ch. Denis ·
M. Garet · D. Duverney · F. Costes ·
J.-C. Barthélémy
Laboratoire de Physiologie
GIP E2S, Université de Saint-Etienne
Saint-Etienne, France
V. Pichot ()
Laboratoire de Physiologie
CHU Nord – Niveau 6
42055 Saint-Etienne, Cedex 2, France
Tel.: +33-47/7828-300
Fax: +33-47/7828-447
E-Mail: [email protected]
RESEARCH ARTICLE
Interval training in elderly men
increases both heart rate variability
and baroreflex activity
nomic nervous system activity by
heart rate variability (HRV) analysis and spontaneous cardiac
baroreflex activity (SBR) in eleven
elderly men (73.5 ± 4.2 years) before and after a 14-week program
of intensive cycloergometer interval training. The standard HRV indices were calculated using time
domain (mean RR, PNN50,
RMSSD, SDNN, SDANN and
SDNNIDX), and Fourier transform
(total power, ULF, VLF, LF, LFnu,
HF, HFnu and LF/HF) analyses of
24-hour, daytime and nighttime
Holter recordings. The SBR was
calculated from 15-minute recordings of spontaneous blood pressure
and RR interval variations using
the sequence (slope, slSBR) and
cross-spectral (αSBRHF and
αSBRLF) methods. Results After the
training period, VO2max increased
by 18.6 % (26.8 ± 4.4 to
31.8 ± 5.2 ml · kg–1 · min–1, p < 0.01).
Introduction
■ Key words aging · exercise ·
baroreflex · autonomic nervous
system activity · heart rate
variability
higher heart rate variability indices than age-matched
sedentary controls [9, 10]. Interestingly enough, most of
the longitudinal studies concerning elderly people reported an increase in heart rate variability with endurance training, essentially in the parasympathetic indices [14, 24]. However, some discrepancies in the results
of these studies may depend upon various factors such
as the duration and intensity of training, the indices under scrutiny [29] or the average population age. Ultracentenarians present higher parasympathetic heart rate
variability indices than 81- to 100-year-old people [19],
suggesting precise autonomic control is of importance
CAR 251
The capacity of the autonomic nervous system to regulate homeostasis can be evaluated by analyzing heart
rate variability [1, 30] and baroreflex activity [16, 18, 26].
These indices decrease with age [10, 13–15] and some of
them constitute to date the most powerful predictors of
death from any cause [6, 12]. Cross-sectional studies
have demonstrated a positive linear relationship between VO2max and parasympathetic activity [11].
It has been shown that elderly active runners have
The nocturnal parasympathetic indices of HRV increased (PNN50:
3.05 ± 2.21 to 5.00 ± 2.87 %, RMSSD:
29.1 ± 7.6 to 38.8 ± 10.9 ms, HF:
117 ± 54 to 194 ± 116 ms2/Hz, all
p < 0.05) as did the SBR indices
(slSBR: 7.0 ± 1.8 to 9.8 ± 2.1
ms · mmHg–1, p < 0.01; αSBRHF:
6.9 ± 2.2 to 10.5 ± 3.7 ms · mmHg–1,
p < 0.05; αSBRLF: 5.3 ± 2.3 to
6.9 ± 3.1 ms · mmHg–1, p = 0.22).
Conclusion Intensive endurance
training in elderly men enhanced
parasympathetic parameters of
HRV and, interestingly, of SBR.
Physiological mechanisms and
long-term clinical effects on health
status should be further investigated.
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for longevity. Thus, systematic endurance training programs might be beneficial by compensating for the agerelated decline of autonomic regulation. Baroreflex activity is also an important indicator of health status [12].
Baroreflex activity represents an integrated sympathetic
and parasympathetic autonomic reflex [18]. To date, no
longitudinal studies have shown any significant increase
in baroreflex activity in response to endurance training
in healthy older adults [4, 25], while one study has shown
a decrease [27]. Conversely, one cross-sectional study
demonstrated evidence of increased baroreflex in elderly endurance-trained athletes compared with agematched sedentary subjects [3]. These controversial results concerning the effects of training on baroreflex
activity may be explained by the limited duration of the
training protocols [4], the intensity of the training sessions [4], and, more specifically, by differences in the
methods used to measure the baroreflex [4, 21, 27].
Thus, the goal of the present study was to evaluate the
changes in autonomic regulation occurring in response
to endurance-interval training in a cohort of eleven
healthy elderly subjects aged 73.5 ± 4.2 years. We chose
to measure baroreflex activity by analyzing the simultaneous spontaneous variations of heart rate and systolic
blood pressure, a non-invasive method that reflects a
global measure of baroreflex activity [21, 26]. The subjects participated in a fourteen-week endurance-interval training program with intermittent bouts of 65 %
and 85 % VO2max exercise.
Material and methods
■ Subjects
Eleven healthy, active, normotensive elderly men participated in the
study (age 73.5 ± 4.2 years, weight 81.8 ± 12.0 kg, BMI 28.4 ± 4.0
kg · m–2, mean ± sd). They were free of any known cardiac abnormalities and none of them were taking cardioactive medication. The participants had been moderately trained cyclists in the past. All were
volunteers and provided written informed consent. The protocol was
approved by the university hospital ethics committee.
■ Maximal aerobic parameters
Maximal power output,VO2max, and the corresponding maximal heart
rate (HRmax) of the subjects were measured with a stepwise incremental maximal cycle ergometer (Monark, Sweden) protocol performed as follows. After proper calibration of the metabolic cart
(CPXD, MedGraphics, MN), data were collected during a 3-minute period at rest on the cycloergometer. The subjects started cycling for 2
minutes at a range of 15 to 25 Watts, depending on their presumed initial level. Then, the power was incremented by 15 to 25 Watts every 2
minutes until exhaustion. Validation criteria for a maximal test were:
lack of increase in VO2 with an increase in workload, heart rate close
to the theoretical maximal value, respiratory exchange ratio above 1.1
and blood lactate concentration above 9 mmol · l–1.
■ Heart rate variability
Heart rate variability was measured from 24-hour Holter monitoring
(Vista, Novacor, Rueil-Malmaison, France). Each RR interval was
manually validated before analysis. Heart rate variability indices were
calculated from the entire 24-hour period and separately for daytime
and nighttime periods.Variations arising from differences in the subject’s daily environment were avoided by analyzing heart rate variability over the nighttime periods. We calculated mean RR, mean
heart rate, time domain indices and frequency indices (Fourier transform) for the three periods (24h, daytime, nighttime).
Before performing the Fourier analysis, the RR signal was re-sampled at 4 Hz [30]. For the indices calculated over the entire 24-hour
recordings, all the RR intervals were simultaneously analyzed; for the
day and night indices, they were calculated as the mean of the values
calculated on 256 successive RR intervals (approximately 5 minutes)
according to the standards previously described in the literature [30].
All the calculated indices are recognized to provide a good estimation of autonomic nervous system activity. Some variables arising
from the time domain analysis are mainly under the control of
parasympathetic activity (PNN50, RMSSD) or reflect the global autonomic activity (SDNN, SDANN) [30]. Concerning the physiological
interpretation of Fourier analysis, the total power of the spectrum
(Ptot) is an estimation of the global activity of the autonomic nervous
system. The indices corresponding to the very low frequency of the
spectrum (VLF) contain partially parasympathetic activity, low frequency indices (LF and LFnu) contain both sympathetic and
parasympathetic activities, high frequency indices (HF and HFnu)
represent vagal activity, and the LF/HF ratio has been proposed as a
marker for autonomic nervous system balance [1, 30].
■ Baroreflex activity
Spontaneous cardiac baroreflex activity was calculated using the sequence method [18] and the cross-spectral analysis method [16]. A
15-minute simultaneous recording of electrocardiogram, blood pressure and ventilation was performed at rest in the supine position. The
electrocardiographic lead with the greatest R wave amplitude and
greatest signal-to-noise ratio was continuously monitored by means
of an oscillographic monitor. Finger arterial blood pressure was measured by the volume-clamp method by means of a noninvasive continuous blood pressure monitor (Finapress 2300, Ohmeda®). The
plethysmographic cuff was placed around the middle phalanx of the
finger and the cuff pressure was modulated to maintain transmural
pressure at effective zero. All recordings were continuously digitized
at a sampling rate of 500 Hz after appropriate calibration, stored
through Labview® files and transferred off-line to a Macintosh computer. Then, MatLab® software was used to detect the R wave peaks,
and the RR intervals were calculated after removal of any non-sinusal
beats or artifacts. Each RR interval was paired with the corresponding systolic pressure wave. For the calculation of the spontaneous cardiac baroreflex activity using the sequence method, the software
listed all sequences of at least three or more successive heart beats in
which there were concordant increases or decreases in systolic blood
pressure and RR interval. For each sequence, the linear regression
slope was calculated. Then, the spontaneous cardiac baroreflex activity (slSBR, expressed in ms · mmHg–1) was calculated as the mean of
the slopes of all the sequences. Although the vasoactive drug bolus
technique seems to be widely used, the spontaneous method provides
a reliable noninvasive assessment of human vagal cardiac baroreflex
activity [18].
Cross-spectral analysis was applied on the same recordings. The
baroreflex activity cross-spectral indices were calculated as the ratio
between the transfer function moduli of arterial blood pressure and
heart rate variability, for the frequencies between 0.04 and 0.15 Hz reflecting parasympathetic activity (αSBRLF) and between 0.15 and 0.40
Hz reflecting both parasympathetic and sympathetic activities
(αSBRHF) [16]. The values were validated when the coherence be-
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tween arterial blood pressure and heart rate variability was greater
than 0.5.
81.2 ± 12.3 kg before and after the training program respectively, NS).
■ Blood pressure
Systolic arterial blood pressure (SBP), diastolic arterial blood pressure (DBP) and mean arterial blood pressure (MBP) were measured
over a 15-minute noninvasive continuous recording period as described in the previous section.
■ Training protocol
Measurements of VO2max, baroreflex activity and heart rate variability
were made one week before the beginning of the training period and
one week after its end, on a resting day. The VO2max tests were done on
a separate day from the other measurements. The training period
lasted 14 weeks with 4 sessions per week. All the training sessions
were performed on a cycloergometer (Monark, Sweden) at the laboratory. Exercise intensity was assessed by monitoring heart rate during each training session. Each 45-minute training session consisted
of 9 repeated adjacent consecutive 5-minute bouts of cycling, each
bout being composed of 4 minutes at 65 % HRmax followed by 1 minute
at 85 % HRmax allowing to target a nearly constant relative training
load.
■ Statistics
Data were calculated and analyzed with MatLab® and StatView® software on a Macintosh computer. Variables were compared using a
paired t-test and p-values less than 0.05 were considered significant.
Results
■ Subjects
All the subjects reached the end of the protocol. Their
weight did not show any variation (81.8 ± 12.0 versus
Fig. 1 VO2max and HRmax in eleven
healthy elderly subjects before and after
fourteen weeks of aerobic exercise training
■ VO2max and HRmax
Ten of the eleven subjects increased their VO2max with
the training program while one subject showed a slight
decrease (Figs. 1a and b). Overall, VO2max increased
significantly by 18.6 %, from 2185 ± 400 to
2547 ± 302 ml · min–1, or, when expressed in relative
value, from 26.84 ± 4.38 to 31.82 ± 5.15 ml · kg–1 · min–1
(both p < 0.01). The corresponding maximum heart rate
measured during VO2max (HRmax) demonstrated a slight
but significant decrease from 155.8 ± 13.3 to 152.6 ± 13.6
bpm (p < 0.05) (Fig. 1c).
■ Heart rate and heart rate variability
There was an increase of the mean RR interval, reaching
statistical significance when measured during the day as
well as over the 24-hour recordings (11.5 %, p < 0.001,
and 7.7 %, p < 0.001, respectively) (Table 1, Fig. 2 lower
panel). When measured during the 24-hour recordings,
the SDNN and SDANN decreased (SDNN 24 hours:
–15.4 %, p < 0.05; SDANN 24 hours: –21.0 %, p < 0.01) but
remained unchanged when measured separately during
the day and night periods. The RMSSD and PNN50 increased significantly (PNN50 night: 63.9 %, p < 0.01;
RMSSD night: 33.3 %, p < 0.01; RMSSD day: 13 %,
p < 0.05) as well as the SDNNIDX (SDNNIDX 24 hours:
11.8 %, p < 0.001; SDNNIDX day: 11.3 %, both p < 0.05).
The main result concerning Fourier analysis con-
VȮ2max (ml · min–1 · kg–1)
VȮ2max (l · min–1)
HRmax (bpm)
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110
Table 1 Time domain indices of heart rate variability before and after the training period
Before training (Mean ± SD)
Mean HR
RR
PNN50
SDNN
RMSSD
SDANN
SDNNIDX
bpm
ms
%
ms
ms
ms
ms
After training (Mean ± SD)
24 hours
Day
Night
24 hours
Day
night
71.9±9.9
847±100
3.52±2.53
149±45
30.3±7.5
138±42
47.4±14.9
78.9±8.6
768±77
3.79±3.15
102±28
30.8±8.7
90.5±27.7
44.0±14.8
62.0±12.6c
997±163c
3.05±2.21
78.2±26.7
29.1±7.6
65.2±15.4b
52.2±17.6b
67.2±11.4***
912±133***
4.41±2.79
126±40**
36.4±8.8**
109±37***
53.0±15.9***
71.4±10.6***
856±115***
4.13±3.10
100±29
34.8±8.9*
82.2±24.0
49.0±15.1**
60.9±13.1c
1019±180c
5.00±2.87**
77.2±22.0a
38.8±10.9***, a
61.2±11.3c
58.5±19.4*, b
* P < 0.05; ** P < 0.01; *** P < 0.001, before vs. after training; a P < 0.05; b P < 0.01; c P < 0.001, day vs. night period
Fig. 2 Heart rate variability indices in
healthy elderly subjects before and after
fourteen weeks of aerobic exercise training
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sisted of an increase in the high and low frequencies of
heart rate variability after the 14 weeks of aerobic training (Table 2, Fig. 2 upper panel). These indices increased
significantly when measured during the night period
(LF: up to 37.4 %; HF: up to 65.8 %, both p < 0.01). The
LF/HF ratio demonstrated a moderate decrease for each
measured period, reaching significance for the day period (–19.1 %, p < 0.05).
Before training, there were no significant differences
in short-term HRV indices between daytime and nighttime. After the training protocol, there was a restoration
of this difference for most subjects (RMSSD, pNN50,
p < 0.05; borderline significant for HF). This is shown in
Fig. 3.
Globally, the training period mainly yielded a
marked increase of the indices representing parasympathetic activity.
Table 2 Fourier transform indices of
heart rate variability before and after the
training period
■ Arterial blood pressure
The resting systolic, diastolic, and mean arterial blood
pressure were unchanged (all NS) when measured before and after the training period (Table 3).
Table 3 Arterial blood pressure before and after the training period
SBP
DBP
MBP
mmHg
mmHg
mmHg
24 hours
Ptot
ULF
VLF
LF
HF
LF/HF
LFnu
HFnu
ms2/Hz
ms2/Hz
ms2/Hz
ms2/Hz
%
%
4520±2591
3416±2271
715±575
221±208
103±54
–
–
–
After training
(Mean ± SD)
111.6±13.9
59.5±16.9
76.9±14.9
111.1±13.3
61.3±13.5
77.9±12.3
All NS
Before training (Mean ± SD)
ms2/Hz
Before training
(Mean ± SD)
After training (Mean ± SD)
Day
Night
24 hours
Day
Night
1125±770
–
653±492
239±232
112±69
2.93±1.35
62.4±9.5
37.6±9.5
1681±932a
4683±2307
3521±1963
704±526*
233±159
149±89**
–
–
–
1259±684
–
776±539*
226±133
139±72
2.37±1.10*
58.6±11.4*
41.4±11.4*
1873±936a
–
1281±707a
338±203**
194±116**
2.46±1.31
57.3±13.0
42.7±13.0
–
1290±772a
246±166
117±54
2.87±1.71
60.4±14.0
39.6±14.0
* P < 0.05; ** P < 0.01, before vs. after training; a P < 0.001, day vs. night period
Fig. 3 Day:night difference of shortterm heart rate variability in healthy elderly subjects before and after fourteen
weeks of aerobic exercise training
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■ Baroreflex activity
A main finding of our study was the improvement of
cardiac baroreflex activity with physical exercise in elderly subjects. Using the sequence method, the baroreflex activity increased significantly from 7.0 ± 1.8 to
9.8 ± 2.1 ms/mmHg (slSBR: 40 %, p < 0.01) (Fig. 4a). Interestingly, 10 subjects demonstrated an increase and
only 1 subject showed a decrease of this parameter. Despite the decrease in baroreflex activity, this subject
showed beneficial effects of exercise training in all other
measures.
For the calculation using the spectral method, the
data of one subject were eliminated because of poor coherence between arterial blood pressure and heart rate
variability spectra. Thus, the results presented in Figs. 4b
and 4c concern only 10 subjects. In that group, the αSBRHF increased significantly from 6.9 ± 2.2 to 10.5 ± 3.7
ms · mmHg–1 (52.5 %, p < 0.05) with 8 subjects demonstrating an increase in the baroreflex activity and 2 subjects showing a decrease. Concerning the αSBRLF, only 4
subjects demonstrated a clear increase of this parameter, and the statistical analysis did not reach significance
(from 5.3 ± 2.3 to 6.9 ± 3.1 ms · mmHg–1, p = 0.22).
Discussion
The present study demonstrated a major increase in
parasympathetic activity measured by spontaneous cardiac baroreflex sensitivity and heart rate variability, in
response to 14 weeks of aerobic interval training in an
elderly male population.
Fig. 4 Baroreflex activity indices in
healthy elderly subjects before and after
fourteen weeks of aerobic exercise training
sISBR
(ms · mmHg–1)
Heart rate variability analysis demonstrated an increase of the parasympathetic activity. Our results confirm the previous longitudinal studies that have also
demonstrated a significant increase in autonomic nervous system activity with aerobic exercise training in
populations aged up to 68 years [14, 24, 29]. Aging does
not appear to be a limitation to autonomic nervous system adaptations since we obtained the same gain in a
population with a mean age of 73 years.
A main issue of our study lies in the improvement of
cardiac baroreflex activity with physical exercise in elderly subjects. Our results are in accordance with the
cross-sectional study that has reported higher baroreflex activity in elderly active subjects compared with
age-matched sedentary people [3]. On the contrary, in
similar populations, some previous longitudinal studies
have demonstrated a lack of increase [4, 25] or even a decrease [27] in baroreflex activity in response to physical
training. Differences in the methods of measurement
may explain some discrepancies. Most studies have relied on the pharmacological method [25, 27] or the neck
suction method but the only previous study analyzing,
as we did, spontaneous baroreflex activity [4] was unable to demonstrate any increase in baroreflex activity
induced by physical training in spite of a 24 % increase
in maximal oxygen consumption. This discrepancy
could be due to differences in the design of the training
program (interval training program, higher intensity
and longer duration). It could be that a longer training
period may be needed to obtain a baroreflex adaptation
than an increase in metabolic adaptations.
Several mechanisms could be involved in baroreflex
enhancement. Bradycardia, a direct consequence of
αSBRHF
(ms · mmHg–1)
αSBRLF
(ms · mmHg–1)
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training, is known to elicit an improved baroreflex response [5]. Also, following a training period, autonomic
equilibrium shifts towards greater parasympathetic predominance that, again, increases baroreflex activity,
mainly due to a decrease in vascular tone as demonstrated by physiological responses to low body negative
pressure [5]. Physical exercise training decreases the
level of plasmatic renin activity, inducing a decrease in
the renin-angiotensin system that probably plays a role
in baroreflex activity enhancement. Measuring the
spontaneous baroreflex integrates both the receptors
and the central command. From our results, we cannot
identify how they are specifically involved in the adaptation.
Our training protocol consisted of repeated consecutive bouts of 4 minutes of easy cycling followed by 1
minute of intensive cycling with a heart rate above 85 %
of the maximal heart rate (HRmax) leading to a progressive increase in workload as the protocol proceeded.
Other studies examining the effect of a single training
level of variable intensity (60 % to 80 % HRmax) [4, 25, 27,
29] have been unable to demonstrate increased baroreflex indices. Repetition of high and low intensity periods
during the same session could be a stronger stimulus of
the autonomic nervous system activity than constantload training. Indeed, interval training is widely used in
most aerobic training programs since it allows a higher
intensity training load for athletes. Exercise intensity
thresholds below which no improvement in autonomic
regulations appears have been described [17].A possible
explanation for the increased baroreflex after aerobic
training could be that it is easier to reactivate the regulatory system in detrained subjects than to activate it in
untrained subjects [3]. Our subjects were moderately
trained cyclists in the past, while at the time of the protocol, they were relatively detrained. This could also explain the low arterial blood pressure values recorded in
our population. The results might not have been the
same with strictly sedentary people. In any case, the increase in baroreflex activity demonstrated in this study
is coherent with the increase in heart rate variability in
response to aerobic exercise training since they are both
dependent on increased parasympathetic activity [1, 18,
30].
As demonstrated earlier [7, 20], high intensity training can cause a transient decrease in heart rate variability, from 24 hours after a single bout of exercise, to several days (or weeks) after a 3- to 4-week intensive
training program. To be sure that the ultimate heart rate
variability measurement actually reflects the new autonomic regulation level, the final recovery recording
should be performed after at least two or three days of
rest after the end of the training program. In our protocol, heart rate variability was measured one week after
the last training session, allowing the autonomic nervous system enough time to reach its new equilibrium.
Parasympathetic activity is known to progressively
decline with age and has been shown to be a strong
predictor of death of any cause [6]. Moreover cross-sectional studies have demonstrated preserved parasympathetic indices of heart rate variability in ultracentenarians [19]. Physical exercise is able to ameliorate the
age-related trend of decreased heart rate variability.
However, a direct relationship between the gain in heart
rate variability and/or in spontaneous baroreflex activity due to exercise and a gain in life duration has not yet
been demonstrated in humans. Conversely, a considerable protective effect of exercise against sudden death,
through increased parasympathetic activity, has been
demonstrated in dogs [8].
In the present study, SDNN and SDANN indices measured on 24-hour RR recordings decreased after the
training protocol while they did not show any variation
when measured separately on the day and night periods.
The decrease of these 24-hour indices, representing the
global heart rate variability, is not consistent with the
Fourier Ptot index, which did not show any variation.
Moreover, a decrease in SDNN and SDANN is usually associated with mortality. An explanation of this sole controversial result could be that the subjects were especially sedentary on the day of the second test or they
were still in a fatigued state due to insufficient recovery.
Also, some heart rate variability indices may present intra-individual variations and, thus, results have to be interpreted considering all the indices of the analysis.
Three subjects presented with high values of SDNN before the training period, with a decrease to a more normal range after the training (Fig. 2). These high values
could be related to the presence of obstructive sleep apnea syndrome, which has been demonstrated to increase
a specific band in the very low frequency of the heart
rate variability spectrum [23]. Interestingly, we observed that their power at this specific band was abnormally high before training and decreased significantly
after the training period, explaining the initial high
SDNN values. After exclusion of these three outlier subjects, the decline in SDNN and SDANN with exercise
training was not seen, and there were no significant differences in pre-to-post training values. Another heart
rate variability result that might be also discussed is the
lack of day-to-night difference in parasympathetic indices (pNN50, RMSSD, HF) in the pre-training condition. This observation, in 73-year-old subjects, is consistent with previous studies that have shown an inverse
relationship between the day-to-night difference and
age, and no difference for people older than 60 to 70
years [2]. Notably, in our study, there is a re-appearance
of this day-to-night difference after the 14 weeks of
physical training, which supports the hypothesis that
physical activity can ameliorate the aged-related trend
of heart rate variability.
A limitation of the present study is the number of
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subjects and the fact that all of the subjects were males.
Results may not be generalizable to women [28]. Indeed,
our results showed a significant increase in VO2max,
baroreflex and parasympathetic activity but also disclosed that some subjects appear to respond better to
physical training than others. A larger group of subjects
would undoubtedly have confirmed the significant increases found here, but might also have provided some
physiological explanation for such differences between
subjects. For example, the initial level of VO2max, baroreflex activity or heart rate variability could be determinant in a subject’s ability to increase autonomic activity
after physical training. No such significant relationships
were found in the present study.
In conclusion, physical training in 73-year-old men
significantly increases the two major indices of autonomic nervous system activity, heart rate variability and
spontaneous baroreflex, and, thus, should “fuel the
brain” [22]. A longitudinal survey on the protective effects of physical exercise on these parameters still needs
to be done and would undoubtedly provide insight concerning the cardiovascular, and more particularly the
cerebrovascular status of elderly subjects.
■ Acknowledgments This work was supported by a grant from the
Région Rhône-Alpes called Programme Fédératif de Recherche “Exercice et Maîtrise du vieillissement humain”.
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