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Journal of Exercise Physiologyonline
August 2013
Volume 16 Number 4
Editor-in-Chief
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Official Research Journal
of the American Society of
Exercise Physiologists
ISSN 1097-9751
JEPonline
Pacing Strategy and Heart Rate on the Influence of
Circadian Rhythms
Ramon Cruz¹, Bruno P. Melo², Francisco A. Manoel³, Phelipe H.C.
Castro4, Sandro F. da Silva5
1Postgraduation
student in Physical Education, Federal University of
Juiz de Fora, Juiz de Fora/MG Brasil, ²Graduated in Physical
Education, Federal University of Lavras, Lavras/MG Brasil,
³Graduated in Physical Education, Federal University of Lavras,
Lavras/MG Brasil, 4Masters degree student in Physical Education,
Federal University of Juiz de Fora, Juiz de Fora/MG Brasil, 5Adjunct
Professor at Federal University of Lavras, Lavras/MG Brasil
ABSTRACT
Cruz R, Melo, BP, Manoel FA, Castro PHC, Da Silva SF. Pacing
Strategy and Heart Rate on the Influence of Circadian Rhythms.
JEPonline 2013;16(4):24-31. Circadian rhythms (CR) control several
important human physiological activities such as the sleep-wake cycle,
heart rate (HR), body temperature, and hormone secretion. Although
CR can directly influence athletes’ physical performance, no other
study has indicated the influence of this biological control on HR and
pacing in 3000 m and 5000 m races. Eight physically active adults
(average age 26.62  7.79 yrs) participated in this study. The races
were held in a 400 m track in the morning, afternoon, and evening. In
order to evaluate pacing strategy, time and HR were registered in each
lap. The data were analyzed using descriptive statistics, Shapiro-Wilk
W-test, Two-Way ANOVA with Tuckey’s Post-Hoc test. Correlation
coefficient between HR and the time of each lap was determined
according to the Pearson correlation test (P<0.05). There was no
statistical difference in HR and time in each lap of the 3000 m and
5000 m races during the three periods of the day. Results indicate that
the morning period was the one in which the higher physical wear was
observed in each lap, and that the circadian rhythms did not influence
pacing strategy of physically active adults.
Key Words: Circadian, Running, Physical Exertion, Exercise
Physiology
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INTRODUCTION
Biological control of circadian rhythms (CR) is done by the suprachiasmatic nucleus, which located in
the anterior hypothalamus. In a review by Weipeng and colleagues (19), they claimed that this
autonomous control regulates the sleep-wake cycle and the biological response to light/dark cycle.
Cruz and Silva (7) argued that the best activity period was the one in which the participants were
under the influence of the sleep period, working shifts, and usual time for practicing sports. Reilly and
Waterhouse (15) demonstrated that lifestyle is also an important factor in optimizing physical exercise
and performance.
Biological rhythms refer to cyclical changes that regularly repeat in a certain time that are related to
physiological processes and responses (14). These rhythms may be named circadian (i.e., relating to
solar day (24 ± 4 hrs), ultradian (cycles with less than 24 hrs), or infradian (cycles with more than 28
hrs) (11). According to Reilly (13), circadian rhythms control several human physiological activities
including the sleep-wake cycle, heart rate, body temperature, and hormone secretions. Each of these
activities is known to directly influence the athletes’ physical performance (12).
Among the different forms of controlling effort intensity and training prescription, heart rate (HR) is
well recognized as the primary variable to monitor (5). In fact, in a progressive test, it is possible to
identify a change in the linearity of heart rate behavior. The change is referred to as transition points.
The first transition point is referred to as the HR point of inflection. The second transition point is
called the HR point of deflection (8), which is used as a non-invasive indication of the second lactate
threshold and as an intensity approach to the maximum lactate steady state (3,4,8). Thus, from using
the subject’s HR data, it is possible to estimate the behavior of other physiological and metabolic
variables that influence sports performance.
Pacing strategy (1,10) is referred to as the constant adjustments of running speed in order to reach
the subject’s best performance. This concept has been especially important in determining a subject’s
readiness for medium and long-term races. For the distances of 3000 m and 5000 m, the most
important race strategy is that which allows the subject to increase in speed in the end. (1). In a study
that involved 10,000 m runners, Billat and colleagues (2) claimed that HR and oxygen consumption
(VO2) are the primary regulators of the athlete’s pacing strategy.
Although Carmo and colleages. (6) classified the athlete’s pacing strategy into four types (steady,
decreasing, increasing, and variable), Abbiss (1) and Lima-Silva (10) suggested that despite the
chosen pacing strategy there is an increase in speed (a phenomenon known as final spurt) at the end
of the race. Yet, interestingly, even though these studies suggest a relationship between pacing and
HR, none of the studies have demonstrated that CR influences HR and pacing in 3000 m and 5000 m
races. Thus, the purpose of this study was to verify whether CR has an influence on HR and pacing
strategy during 3000 m and 5000 m races. A secondary purpose was to correlate the runners’ pacing
strategy with their HR during each lap in both distances.
METHODS
Subjects
Eight physically active subjects participated in this study. All subjects signed the Free and Informed
Consent Form that was approved by the Ethics Committee of the University of Itaúna under protocol
n. 002/09. The sample characteristics are presented in Table 1.
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Table 1. Descriptive Data of the Subjects.
N
Age (yrs)
Body Mass (Kg)
8
26.62 ± 7.79
69.23 ± 7.65
Height (cm)
175.5 ± 3.15
%G
16.95 ± 1.67
Procedures
The subjects performed a 3000 m and a 5000 m race in the morning (between 8 and 10 am), in the
afternoon (between 2 and 4 pm), and in the evening (between 6 and 8 pm). The three races were
randomly performed on different days using a 400 m running track paved with clay. The subjects
were asked to run the distances in the shortest time possible. None of the subjects reported
discomfort or muscular pain that could have influenced the tests results. Heart rate was monitored
during the entire test using a Polar® Rx 880i cardiofrequencimeter. Every 400 m, the subjects
indicated the HR value that was displayed on their watch; all values were immediately recorded.
Statistical Analyses
Descriptive statistics with comparison through mean and standard deviation was used. For the
sample distribution, Shapiro-Wilk W-test was applied followed by a Two-Way ANOVA with Tuckey’s
Post-Hoc test in order to identify significant differences among the three race periods. To obtain the
correlation coefficient between HR and the time of each lap, a two-sided Pearson correlation was
applied. In all analyses, the SPSS 20.0 statistic software was used. Statistical significance was set at
an alpha level of P<0.05.
RESULTS
The behavior of the subjects’ HR is presented for each lap during the 3000 m (Figure 1a) and the
5000 m (Figure 1b) tests during the morning, afternoon, and evening periods.
1 (a)
190
FC (bpm)
180
170
Morning
Afternon
160
Night
150
0
200
600
1000
1400
1800
Distance (m)
2200
2600
3000
27
1 (b)
190
FC (bpm)
180
170
Morning
Afternon
Night
160
150
0 200
600 1000 1400 1800 2200 2600 3000 3400 3800 4200 4600 5000
Distance (m)
Figure 2 and Figure 3 indicate the average time in each lap of the 3000 m and the 5000 m races,
respectively, in the three periods during which the tests were performed.
24a
(a
1:50
1:40
Time (min)
1:30
1:20
1:10
1:00
0:50
Morning
0:40
Afternon
0:30
Night
0 200
600
1000 1400 1800 2200 2600 3000
Distance (m)
3
5
2:00 1:50
1:40
Time (min)
1:30
1:20
1:10
1:00
Morning
0:50
Afternon
0:40
Night
0:30
0.00
0 200
600 1000 1400 1800 2200 2600 3000 3400 3800 4200 4600 5000
Distance (m)
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Table 2 indicates the duration of the 3000 m race and the 5000 m race in each of the three periods.
Table 2. Mean and Standard Deviation of Total Time of the Races during Each Period.
Time 3000 m (min)
Time 5000 m (min)
Morning
14:29 ± 02:08
22:20 ± 03:43
Afternoon
12:46 ± 01:53
22:37 ± 03:36
Evening
12:38 ± 01:40
22:09 ± 03:15
Period
The HR comparisons for each lap with the three periods (morning, afternoon, and evening) did not
show statistically significant differences. Correlations between the pacing strategy in each lap and its
respective HR are described in Table 3. All results were found statistically significant.
Table 3. Correlation between HR and Time in Each Lap.
Distance
Morning
Afternoon
Evening
3000 m
0.905*
0.790*
0.810*
5000 m
0.811*
0.757*
0.657*
* Significant correlation (Pearson Correlation Test).
DISCUSSION
The subjects’ HR responses in both 3000 m and the 5000 m races were similar. There was an initial
increase followed by gradual increases, except during the afternoon 5000 m race in which a decrease
was observed at 3800 m. It is likely that this finding can be explained by the higher physical exertion
at the beginning of this race. Higher HR values were observed, which appear to have been caused by
an increase in the runners’ cumulative fatigue that allowed for a physiological readjustment at that
point (16).
Every race in every period had strong and positive correlations that were statistically significant, with
a special focus on the 3000 m race and the 5000 m race in the morning period. Also, according to
the runners’ HR values, it is apparent that the physiological stress was higher in the morning races.
Lower correlations were found for the 3000 m race during the afternoon period and the 5000 m race
during the evening period. This finding appears to favor the afternoon and early evening periods,
which is in agreement with the physiological responses considered ideal for sports performance
(19,20). The time of each lap responded in a similar manner. The subjects in this study adopted a Ushaped tactic of running, in which we observed an initial speed increase, decrease and maintenance
29
and, then, in the end the phenomenon called “final spurt” was observed in which the runners
increased their speed in search of a better result (1,10).
With regards to the three periods of the day, CR did not show a statistically significant difference
between the comparison of HR and time in each lap on the 3000 m and the 5000 m races. However,
the evening period was the period during which the runners demonstrated their best performance in
both distances. The evening race began at 6 pm (given that there is a peak of physiological variables
that influence performance. In particular, VO2, body temperature, and HR have been reviewed by
Weipeng et al. (19) and Winget et al. (20). In another review, Reilly and Waterhouse (15) indicated
that there are three primary factors essential to the study of CR and athletic performance. These
factors are exogenous factors (environment), endogenous factors (physiological responses), and
lifestyle (habits).
CONCLUSIONS
There were no statistical differences between the comparisons of HR and pacing strategy in the 3000
m and 5000 m races during the three designated periods of the day. However, the results indicate
that a higher correlation between HR behavior and time in each lap. The greater the time in each lap
of both races, the higher the heart rate.
ACKNOWLEDGMENTS
Financial Support - FAPEMIG- Fundação de Amparo a Pesquisa de Minas Gerais – Scientific
Initiation Scholarship.
Address for correspondence: Sandro Fernandes da Silva, PhD. NEMOH - Nucleus of Studies of
Human Movement - Department of Physical Education - University of Lavras - University Campus,
PO Box 3037, ZIP Code 37200-000. Lavras/MG. Brasil. 00 55 (35) 3829-5132- sandrofs@def.ufla.br
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