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© Nofer Institute of Occupational Medicine, Łódź, Poland
International Journal of Occupational Medicine and Environmental Health 2007;20(1):1 – 8
DOI 10.2478/v10001-007-0005-5
EFFECT OF AEROBIC FITNESS ON
THE PHYSIOLOGICAL STRESS RESPONSES
AT WORK
TIINA RITVANEN¹, VEIKKO LOUHEVAARA1, PERTTI HELIN1, TOIVO HALONEN2, and OSMO HÄNNINEN¹
¹ Department of Physiology
University of Kuopio, Finland
² Department of Clinical Chemistry
Kuopio University Hospital
Kuopio, Finland
Abstract
Objectives: The aim of the present study was to examine the effects of aerobic fitness on physiological stress responses
experienced by teachers during working hours. Materials and Methods: Twenty six healthy female and male teachers aged
33–62 years, participated in the study. The ratings of perceived stress visual analogue scale (VAS), and the measurement of
physiological responses (norepinephrine, epinephrine, cortisol, diastolic and systolic blood pressure, heart rate (HR) and
trapezius muscle activity by electromyography (EMG) were determined. Predicted maximal oxygen uptake (VO2max) was
measured using the submaximal bicycle ergometer test. The predicted VO2max was standardized for age using residuals
of linear regression analyses. Results: Static EMG activity, HR and VAS were associated with aerobic fitness in teachers.
Conclusions: The results suggest that a higher level of aerobic fitness may reduce muscle tension, HR and perceived work
stress in teachers.
Key words:
Stress, Aerobic fitness, Muscle tension, Heart rate, Teachers
INTRODUCTION
Regular physical activity has positive effects on the prevention and rehabilitation of illnesses, such as heart disease, hypertension, osteoporosis, cancer, pulmonary diseases, and diabetes[1,2]. Physical activity has been shown
to alleviate state and trait anxiety and to improve physical
self-perception and mental well-being [3,4]. In addition,
physical activity exhibited marked positive associations
with good work capacity and healthy lifestyle [5]. Aldana
et al. [6] indicated that employees showing physical moderate activity had about half the rate of perceived stress
compared with more passive individuals. On the other
hand, Sorensen et al. [7] reported non-significant correlations between physical activity and work ability or per-
ceived physical or mental job stress in police officers during a 15-year follow-up.
The benefits of good aerobic capacity are associated with
low blood pressure and heart rate at rest and during submaximal exercise [8,9]. This suggests that aerobically fit
individuals require less sympathetic activation to perform
the same absolute physical workload than unfit individuals. However, there is no consensus that aerobic power can
protect against the kind of stress that is related to lifestyle
or occupation [10,11]. Several studies have attempted to
investigate the effects of physical fitness on physiological
stress responses in simulated mentally demanding tasks in
the laboratory [12–16], but only a few have been performed
under field conditions [17,18]. Aerobic fitness seems to
Received: October 30, 2006. Accepted: January 24,2007.
Address reprint requests to Tiina Ritvanen, PhD, Department of Physiology, University of Kuopio, P.O. Box 1627, 70211 Kuopio, Finland
(e-mail: tiina.ritvanen@uku.fi).
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moderate stress responses and improve an individual’s
capacity for stress coping [13,15,19]. Rejeski et al.[20] reported that physical exercise acutely reduces the reactivity
of the blood pressure to psychosocial stress. Boutcher and
Nugent [12] reported that the absolute response of heart
rate (HR) during and after repeated exposures to psychological stress factors is lower in aerobically fit than in unfit
individuals. In the study of Szapo et al. [14], the reactivity
of heart rate in the mental arithmetic task was independent of the level of aerobic fitness.
Aerobic fitness may also modulate responses of the autonomic nervous system in a real life mentally demanding
occupation. Consequently, the aim of the present study
was to examine whether aerobic fitness had any effect on
physiological stress responses in the work of teachers.
MATERIALS AND METHODS
Study population
The study population comprised 26 healthy high school
teachers, 17 women (age range, 35–61 years; mean, 50;
SD 8) and 9 men (age range, 33–62 years; mean, 47; SD 6)
(Table 1). Two of them smoked, occasionally. The teachers provided their informed consent to participate in the
study, and the study protocol was approved by the Ethics
Committee of the Kuopio University Hospital.
Aerobic fitness
Maximal oxygen uptake (VO2max) was estimated according to the submaximal cycle-ergometer test in the laboratory [21]. The target HR was set at the level of 220-age
beats/min minus 15% [22]. HR was recorded with the cardiac monitor of Polar Accurex Plus (Polar Electro Ltd.,
Finland). An Ergoline 900 Cycle ergometer (Ergoline
GmbH &Co. KG, Germany) was used in the test. The initial workload was 40 W for the women and 50 W for the
men with a pedalling speed of 60–70 revolutions/min. The
workload was increased by 10 W for the females and 20 W
for the males every minute until the target HR was reached.
HR data and workload were analyzed and VO2max was
estimated with the FitWare software (FitWare Ltd., Vantaa, Finland). The rating of perceived exertion (RPE) was
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Table 1. Anthropometric data, estimated maximal oxygen uptake
(VO2max) and physiological stress responses of the female and male
teachers. The values are expressed as means and standard deviation (SD)
Women
n = 17 (SD)
Variable
Men
n = 9 (SD)
Age (years)
50 (8)
47 (6)
Height (cm)
163 (5)
177 (6)
Weight (kg)
65 (11)
70 (6)
Body mass index (BMI)
24 (4)
22 (2)
Work experience (years)
21 (9)
17 (10)
VO2max (ml/min/kg)
38 (8)
52 (9)
Cortisol (mmol/l)
500 (120)
524 (126)
Epinephrine (μmol/24h)
0.03 (0.01)
0.06 (0.03)
Norepinephrine (μmol/24h)
0.23 (0.08)
0.26 (0.7)
VAS (mm)
52 (22)
45 (32)
DBP (mmHg)
84 (11)
80 (5)
SBP (mmHg)
137 (20)
134 (9)
HR (beats/min)
73 (8)
71 (9)
Static EMG (%)
5 (2)
4 (1)
VAS – visual analogue scale; DBP – diastolic blood pressure;
SBP – systolic blood pressure; HR – heart rate; EMG – electromyography.
inquired with the scale of 6–20 at intervals of 2 min during
the test [23]. Exercise tests were performed in the morning
between 8:00 and 10:00 am one day after biochemical
tests, and muscle activity, blood pressure, HR, and perceived stress were recorded in all subjects.
Physiological stress response
Catecholamine and cortisol exertion
Neuroendocrine reactivity was assessed following the diurnal urine excretion of epinephrine and norepinephrine
in a 24-h urine collection. Urine samples were collected in
polyethylene containers with 10 ml of 6 mol/L HCl as a preservative and stored in a refrigerator (5oC ± 3oC) during
the collection. The volume of 24-h urine was measured and
60 ml of the aliquot was frozen at –70oC until analyzed.
The chromatographic system consisted of the Shimadzu
LC-10A pump (Shimadzu, Japan), Waters 717 Autosampler (Waters Inst., USA), ESA, Chromsystems HPLC column for urinary catecholamines (# 6100) (Chromsystems
Instruments and Chemicals GmbH, Munich, Germany),
ESA, Coulochem II detector equipped with Guard Cell
(Model 5020), and Analytical Cell (Model 5011) (ESA,
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Bedford, MA, USA). The data were analyzed with a HP
Kayak XA computer (Hewlett Packard, USA) equipped
with the HP ChemStation chromatography program.
An aliquot of sample, standard or control (3.0 ml), was
transferred to the vessel, followed by the addition of 100 ml
of internal standard and 6.0 ml of dilution buffer. The diluted urine was applied to prepared clean-up columns. The
effluent was discarded. Thereafter, the clean-up columns
were rinsed once with one column volume of distilled water. Finally, catecholamines were eluted out of the clean-up
columns with 6 ml of elution buffer. An aliquot of 20 ml was
injected for the HPLC system. The absolute recovery of
catecholamines was 81–87%, analytical recovery 89–102%,
linear range of the method 0.06–6 nmol/l, intra-assay variation 3–5%, and inter-assay variation 5–7%.
Venous blood samples were taken from the forearm between 8:00 and 9:00 am for cortisol analyses. The blood
samples were aliquoted into appropriate prechilled vacutainer tubes and centrifuged within 1 h. The plasma fractions were frozen and stored at –80oC until the assays were
performed. The Immulite 2000 Cortisol method based on
the EIA principle with chemiluminescense detection was
used to quantitate cortisol levels (Diagnostic Products
Corporation, Los Angeles, CA, USA).
Muscle tension
Muscle tension was assessed by electromyography, which
was recorded bilaterally from the surface of the trapezius
muscle (trapezius pars descendes) by a portable ME3000P
device. EMG was analyzed by using ME300P software
(Mega Electronics Ltd., Kuopio, Finland). The ME3000P
device enables the muscle activity to be monitored as averaged fully rectified signals from 15 to 500 Hz with the
averaging period of 1 s to give the root-mean-square
(RMS) values [24]. The skin was cleaned with an alcohol
swab before pairs of disposable surface electrodes were
affixed (Ag/AgCI, type M-00-S, N-00-S Medicotest, Ölstykke, Denmark). The electrodes were attached bilaterally to the upper rim of the trapezius muscle with a 2 cm
inter-electrode spacing about 2 cm lateral of the midpoint
between C7 and acromion. The reference electrodes were
attached to the skin approximately 9 cm laterally from
ORIGINAL PAPERS
the recording electrodes. The positions of the electrodes
were defined according to the recommendations of Zipp
[25]. EMG was measured during the entire working day
(8 h). The RMS values were normalized with a reference
voluntary electrical activity obtained during a static submaximal reference voluntary contraction. The achieved
normalization values corresponded with about 10–15%
of the maximal voluntary contraction (MVC) of the trapezius muscle [26]. EMG levels were analyzed according
to the amplitude probability distribution function (APDF)
introduced by Jonsson et al. [27]. From a cumulative frequency distribution, the 10th percentile was defined as the
static load level.
Blood pressure and heart rate
The measurement of systolic and diastolic blood pressure and
HR were carried out at 8:00–9:00 am and 15:00–16:00 pm
using an automatic digital device (Omron M4, Matsusaka
Co., Ltd., Japan). The measurements were taken in the sitting position after a 10-min rest period and the result represented the mean of three measurements completed at
intervals of 1 min. Afternoon BP and HR values were used
in the analyses.
Perceived stress
The perceived psychophysiological stress was assessed using a visual analogue scale. The results of each VAS were
expressed in millimetres (scale 0–100 mm, with the end
points of “no stress” and “extreme stress”) [28].
Statistical analysis
SPSS package 11.0 for Windows was used for statistical
analysis. Differences between gender were calculated by
t-test. VO2max is highly age-dependent [21], therefore,
VO2max was standardized for age using residuals of linear
regression analyses, labeled by suffix “(res)”. The associations between VO2maxres and physiological stress responses were determined by linear regression analyses with the
calculation of the Pearson product correlation coefficient
separately for the male and female teachers. Covariance
analyses of ANOVA were used to calculate the effects of
predicted VO2maxres and relevant confounders (body mass
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index – working experience, gender) on physiological
stress responses and perceived stress. P values below 0.05
were considered significant.
RESULTS
There was, a significant negative correlation between static EMG activity, HR and VAS and aerobic fitness in the
female teachers (r = –0.61, p < 0.01; r = –0.56, p < 0.05;
r = –0.63, p < 0.01, respectively). In the male teachers,
the corresponding correlations were negative, but did not
reach the level of significance (Figs. 1,2,3).
The covariance analysis revealed the significant (p < 0.01)
effect of the estimated VO2maxres on HR significant. BMI
approached the level of significance (p = 0.064), but neither gender nor work experience exerted its effect on HR.
The model, which included VO2maxres, BMI, work experience and gender, predicted 39% of HR variance (F = 4.18;
p = 0.01) (Table 2).
Fig. 1. Relationship between the static electromyography (EMG)
and the age-standardized estimated maximal oxygen consumption
(VO2maxres) in the women (n = 17) and men (n = 9).
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Fig. 2. Relationship between heart rate (HR) and the age-standardized estimated maximal oxygen consumption (VO2maxres) in the
women (n = 17) and men (n = 9).
Fig. 3. Relationship between perceived stress, visual analogue scale
(VAS) and the age-standardized estimated maximal oxygen intake
(VO2maxres) in the woman (n = 17) and men (n = 9).
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Table 2. The effects of covariates related to heart rate (HR), static electromyography (EMG) and perceived stress according to the visual analogue
scale (VAS) at work (n = 26)
Variable
F
P
Covariates
F
P
HR
4.18
0.006
VO2maxres
8.99
0.007
Adjusted R
Static EMG
6.51
Adjusted R
VAS
2
4.07
Adjusted R
0.064
0.04
NS
Gender
0.15
NS
VO2maxres
5.59
0.028
BMI
0.68
NS
Work experience
0.09
NS
Gender
0.13
NS
VO2maxres
4.72
0.042
0.37
0.013
2
3.81
0.39
0.003
2
BMI
Work experience
BMI
0.55
NS
Work experience
0.34
NS
Gender
0.23
NS
0.33
F – variance ratio; P – level of significance; VO2maxres – age-standardized estimated maximal oxygen uptake; BMI – body mass index; VAS – visual analogue scale; NS – not significant.
With respect to the static EMG activity, the model predicted 37% of the variance (F = 6.51; p = 0.003). The effect of VO2maxres was significant (p < 0.05), but no effects
of BMI, gender or work experience on the static EMG
activity were found (Table 2).
The model for VAS predicted 33% of the variance (F =
4.07; p = 0.013). The effects of VO2maxres were significant
(F = 4.7; p = 0.05), but no other variables made any significant contribution to VAS (Table 2).
The variance analysis showed no significant predictive
power of VO2maxres with respect to SBP and DBP or
catecholamine and cortisol excretion. The male teachers
showed higher epinephrine levels than the female teachers (F = 4.47; p = 0.048).
DISCUSSION
An interesting observation was the significant association
between estimated aerobic fitness and static EMG activity.
This finding may indicate that the higher aerobic fitness
alleviates muscle tension during work, exerting a positive
buffering effect on stress, and thus may reduce musculoskeletal problems, such as tight muscles. Augustine [29] also
suggested that physical activity may reduce the tightness
of muscles and help to ease stress. Brandon et al. [19] also
found a negative relationship between the levels of frontalis EMG and aerobic fitness in subtraction tasks. Several
studies have revealed that stress can contribute to static
EMG activity at work [30–33].
Another interesting observation was the significant negative association between estimated aerobic fitness and
HR. In the analysis of covariance, the significant association still survived, but the model showed that the effect of
BMI approached the level of significance. This observation supports previous findings that in general physically
active individuals have lower resting and submaximal HR
than more passive individuals [8,9], and also suggests that
BP is lower in physically fit individuals. The subjects in the
present study were normotensive with a narrow BP range,
and thus it was not possible to duplicate the above observation. In addition, Georgiades et al. [34] suggested that
physical exercise, especially when combined with a weight
loss program, may lower BP and HR levels at rest and during conditions of mental stress.
Although the hypothalamic-pituitary-adrenal (HPA) axis
is responsive to stress [35–37], no significant links between
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cortisol and work stress have been established [38]. An
increased basal activity of the HPA axis with higher urinary, plasma or salivary cortisol levels was reported, but
no evidence was found for a low HPA activity in chronically stressed individuals [39–41]. Kirschbaum et al. [42]
suggested that the opposite regulation of the HPA axis
related to chronic stress could be due to the adaptational
and coping processes of individuals. In this study, only the
morning cortisol levels were assessed, since the increase
in the morning cortisol excretion were shown to be associated with prolonged psychological stress [43,44]. However,
no significant associations between aerobic fitness and the
levels of morning cortisol excretion were found. There are
many confounders, which may affect the morning cortisol
level, such as quality of sleep at the previous night and
individual activities before blood sampling in the morning.
In the future, statistical weighing of the HPA axis status
should be assessed.
Gender affected the epinephrine excretion. The higher
catecholamine excretion of the male teachers may be explained by the greater body size of men, which has been
reported to influence catecholamine output [45]. In the
present study, the estimated aerobic fitness was not associated with diurnal catecholamine excretion. Moyna et al.
[46] reported that norepinephrine increased in the speech
task, but the neuroendocrine response to psychological
stressor factors was independent of the level of aerobic
fitness.
There was a significant, negative association between aerobic fitness and perceived stress, indicating that a higher
aerobic fitness may affect self-confidence and personal appearance. The significant association survived in the analysis of covariance. In the present study, perceived stress was
assessed by the simple VAS method, which is widely used
to measure the intensity of pain [47], but it has also been
used to measure satisfaction and acutely perceived stress
[48]. Methodological and terminological differences with
regard to the definition of the physical fitness and stress
complicate the comparison of reports on the hypothesized
relationship between aerobic fitness and stress. As the
subjects of the present study were middle-aged, the assessment of VO2max was carried out in the laboratory. The
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submaximal assessment of VO2max has been shown to be
an appropriate method to be used in middle-aged or older
individuals [49]. In addition, there are few non-laboratory
studies of this issue and thus it is difficult to find similar
previous studies to compare our results.
There are certain limitations to the present study related
to its relatively small sample size. The cross-sectional design reduces its power to establish causal relationships. In
spite of these limitations, the higher aerobic fitness seems
to lower muscle tension and HR in the work of teachers.
On the other hand in this study, HR was measured only in
the resting condition. In future studies, long-term ambulatory HR monitoring during work and leisure time should
be undertaken. Proactive strategies for coping with stress,
including physical activity, may play an important role before the basic causes of stress can be tackled. Certainly,
physiological and psychological benefits associated with
the increased physical fitness have major public health
implications. Probably the combination of ergonomic and
individual measures has the best effect on the promotion
of health and work ability of teachers.
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