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To provide a large reference material on aerobic fitness and exercise physiology data in a healthy population of Norwegian men and women aged 20-90 years. Maximal and sub maximal levels of VO2, heart rate, oxygen pulse, and rating of perceived exertion (Borg scale: 6-20) were measured in 1929 men and 1881 women during treadmill running. The highest VO2max and maximal heart rate among men and women were observed in the youngest age group (20-29 years) and was 54.4±8.4 mL·kg(-1)·min(-1) and 43.0±7.7 mL·kg(-1)·min(-1) (sex differences, p<0.001) and 196±10 beats·min(-1) and 194±9 beats·min(-1) (sex differences, p<0.05), respectively, with a subsequent reduction of approximately 3.5 mL·kg(-1)·min(-1) and 6 beats·min(-1) per decade. The highest oxygen pulses were observed in the 3 youngest age groups (20-29 years, 30-39 years, 40-49 years) among men and women; 22.3 mL·beat(-1)±3.6 and 14.7 mL·beat(-1)±2.7 (sex differences, p<0.001), respectively, with no significant difference between these age groups. After the age of 50 we observed an 8% reduction per decade among both sexes. Borg scores appear to give a good estimate of the relative exercise intensity, although observing a slightly different relationship than reported in previous reference material from small populations. This is the largest European reference material of objectively measured parameters of aerobic fitness and exercise-physiology in healthy men and women aged 20-90 years, forming the basis for an easily accessible, valid and understandable tool for improved training prescription in healthy men and women.
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Aerobic Capacity Reference Data in 3816 Healthy Men
and Women 20–90 Years
Henrik Loe
1,2
, Øivind Rognmo
1
, Bengt Saltin
3
, Ulrik Wisløff
1
*
1 K.G. Jebsen Center of Exercise in Medicine at Department of Circulation and Medical Imaging, NTNU, Trondheim, Norway, 2 Valnesfjord Rehabilitation Center,
Valnesfjord, Norway, 3 Copenhagen Muscle Research Centre, University Hospital, Copenhagen, Denmark
Abstract
Purpose:
To provide a large reference material on aerobic fitness and exercise physiology data in a healthy population of
Norwegian men and women aged 20–90 years.
Methods:
Maximal and sub maximal levels of VO
2
, heart rate, oxygen pulse, and rating of perceived exertion (Borg scale: 6–
20) were measured in 1929 men and 1881 women during treadmill running.
Results:
The highest VO
2max
and maximal heart rate among men and women were observed in the youngest age group
(20–29 years) and was 54.468.4 mL?kg
21
?min
21
and 43.067.7 mL?kg
21
?min
21
(sex differences, p,0.001) and 196610
beats?min
21
and 19469 beats?min
21
(sex differences, p,0.05), respectively, with a subsequent reduction of approximately
3.5 mL?kg
21
?min
21
and 6 beats?min
21
per decade. The highest oxygen pulses were observed in the 3 youngest age groups
(20–29 years, 30–39 years, 40–49 years) among men and women; 22.3 mL?beat
21
63.6 and 14.7 mL? beat
21
62.7 (sex
differences, p,0.001), respectively, with no significant difference between these age groups. After the age of 50 we
observed an 8% reduction per decade among both sexes. Borg scores appear to give a good estimate of the relative
exercise intensity, although observing a slightly different relationship than reported in previous reference material from
small populations.
Conclusion:
This is the largest European reference material of objectively measured parameters of aerobic fitness and
exercise-physiology in healthy men and women aged 20–90 years, forming the basis for an easily accessible, valid and
understandable tool for improved training prescription in healthy men and women.
Citation: Loe H, Rognmo Ø, Saltin B, Wisløff U (2013) Aerobic Capacity Reference Data in 3816 Healthy Men and Women 20–90 Years. PLoS ONE 8(5): e64319.
doi:10.1371/journal.pone.0064319
Editor: Alejandro Lucia, Universidad Europea de Madrid, Spain
Received February 27, 2013; Accepted April 10, 2013; Published May 15, 2013
Copyright: ß 2013 Loe et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted
use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This study was funded by K.G. Jebsen Foundation, The Norwegian Council on Cardiovascular Disease, The Research Council of Norway (funding for
Outstanding Young Investigators (UW) and scholarship (HL)), Foundation for Cardiovascular Research at St. Olav’s Hospital, Norwegian State Railways, Roche
Norway Incorporated and Valnesfjord Rehabilitation Center. There are no disclosures to report or any conflicts of interest. The funders had no role i n study design,
data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors are declaring a commercial funder, Roche Norway Incorporated. This does not alter the authors’ adherence to all the PLOS
ONE policies on sharing data and materials.
* E-mail: ulrik.wisloff@ntnu.no
Introduction
Evidence supports a strong inverse association between cardio-
respiratory fitness and all-cause mortality [1–4]. Therefore, in
order to increase the individual’s fitness level, different types of
exercise training are used both in prevention and treatment of
cardiovascular and life-style related disease [5]. In order to
prescribe a proper prevention- or treatment program either, the
more reliable, individually cardiopulmonary exercise testing is
needed [6,7], or one can rely upon previously established reference
material. Most previous studies measuring cardiorespiratory fitness
tend to use peak oxygen uptake (VO
2peak
), indirect methods,
estimation by equation, selected populations and/or small sample
sizes [8–15]. Previously established variables suitable for exercise
prescription such as oxygen uptake, heart rate, Watts and Borg
scale scores, are mostly based upon small sample sizes or poorly
described populations [6,16–23]. The aim of this study was to
establish a large reference material of empirical cardiorespiratory
fitness and exercise-physiology data in healthy men and women
aged 20–90 years in order to provide an easily accessible, valid and
understandable tool for improved exercise training prescription.
Methods
Participants
The HUNT 3 fitness study is the third wave of the Nord-
Trøndelag Health Studies (www.ntnu.edu/hunt). Data were
collected between October 2006 and June 2008. The entire
population .20 years of age (n = 94194) were invited to
participate, 54% (n = 50821) accepted. The HUNT 3 Fitness
Study was designed to acquire reference material for submaximal
and maximal cardiorespiratory parameters in a healthy popula-
tion. Exclusion criteria were cancer, cardiovascular disease,
obstructive lung disease and use of blood pressure medication.
Participants also had to be cleared in a brief medical interview.
Based upon self-reported information, 30513 candidates presented
as suitable for VO
2max
testing. Out of these, 12609 candidates
PLOS ONE | www.plosone.org 1 May 2013 | Volume 8 | Issue 5 | e64319
resided in the 3 municipals selected for VO
2max
testing, and 5633
of them volunteered to participate. These 3 locations were chosen
due to geographical location to minimize travel distance for
participants. 4621 candidates completed a VO
2max
test, whereas
3816 tests were considered to have reached the true VO
2max
.
Ethics Statement
The study was approved by the Regional committee for medical
research ethics (2012/1228/REK midt), the Norwegian Data
Inspectorate and the National Directorate of Health, and is in
compliance with the Helsinki declaration. Written informed
consent was obtained from all participants.
VO
2max
and Heart Rate
An individualized graded protocol [24] was used for measuring
VO
2max
(Cortex MetaMax II, Cortex, Leipzig, Germany). Prior of
starting the testing procedure several MetaMax II apparatus were
tested against Douglas-bag and iron lung (Cortex, Leipzig,
Germany). Two MetaMax II apparatus were returned to Cortex
due to unstable recordings (both ventilation and carbon dioxide
analysis) and replaced by two new apparatus that were tested and
found both reliable and valid. Hence, all MetaMax apparatus used
in the project were both valid and reliable. Test-retest correlation
of oxygen-uptake for the tested-personnel in the project was 0.99,
p,0.001 and coefficient of variation was 1.8%. Bland-Altman plot
were constructed where differences in two tests of maximal oxygen
uptake (and sub maximal) from each person (test-1 minus test-2)
were plotted against the average of the two tests ((test-1+test-2)/2).
Average difference was 20.04 ml?kg
21
?min
21
and standard
deviation of the difference was 1.0. Therefore one can expect
that 95% of all observations are at the average ((test-1+test-2)/2)
62 standard deviations. Thus, we can expect values to vary
between 20.04 22?1to20.04+2?1 if we test maximal oxygen
uptake twice in the same person within a short time period.
Velocity and inclination of the test treadmills were calibrated prior
to testing.
The MetaMax II was calibrated prior to the first test each day
using a standard two-point gas calibration procedure recom-
mended by the manufacturer. The calibration includes measure-
ments of ambient air and a gas mix of known content (15.03% O
2
and 4.98% CO
2
in N
2
), a calibration of the Triple-V volume
transducer with a calibrated 3 L syringe (Calibration syringe D,
Sensormedics, CareFusion, San Diego, CA, USA), and barometric
pressure control. Volume calibration was implemented every third
test and the two-point gas calibration every fifth. Before each test
the ambient room air was routinely checked. Heart rate was
measured by radio telemetry (Polar S610i, Polar Electro Oy,
Kempele, Finland). Body mass was measured using the weighing
scale Model DS-102 (Arctic Heating AS, Nøtterøy, Norway). All
participants had a treadmill familiarization period of 8–10 minutes
during warm-up. They were instructed to avoid grabbing
handrails if not necessary. The individualized warm-up workload
determined the initial velocity/inclination on the subsequent
treadmill test. Candidates wore a face mask (Hans Rudolph,
Germany) linked to the MetaMax II. When participant main-
tained a stable oxygen uptake .30seconds, velocity (0.5–1.0 kmh-
1) or inclination (1–2%) were increased. Increased workload was
preferably obtained with increased velocity and keeping a fixed
slope angle. If a participant was unable to increase velocity,
inclination was increased. The average velocity and slope during
test protocol were 6.862.2 km?h
21
(range 2–17 km?h
21
) and
10.061.6% (range 2–16%), respectively. Tests were terminated
when candidates were exhausted or reached a VO
2
plateau that
remained stable despite increased work load [25], i.e. VO
2
did not
increase more than 2 mL?kg
21
?min
21
despite increased work
load.
Ventilatory Equivalent
We calculated the ventilatory equivalent (V
E
?VO
2
21
)at
VO
2max
. The ventilatory equivalent describes the fraction of
minute ventilation (V
E
) to oxygen uptake (VO
2
), hence, the higher
the value the more ineffective is the V
E
. At higher levels of
increasingly harder submaximal workloads, a disproportionate
increase in V
E
relative to VO
2
occurs. This heralds an increasingly
more inefficient V
E
.
Questionnaire-based Information
Physical activity index score (PAI) was calculated from replies in
a self-administered questionnaire that consisted of 3 questions.
Question 1: ‘‘How frequently do you exercise?’’ with response
alternatives ‘‘Never’’ (0); ‘‘Less than once a week’’ (0); ‘‘Once a
week’’ (1); ‘‘2–3 times a week’’ (2.5); ‘‘Almost every day’’ (5).
Question 2: ‘‘If you exercise as frequently as once or more times a
week: How hard do you push yourself?’’ with response alternatives
‘‘I take it easy without breaking a sweat or losing my breath’’ (1); ‘‘I
push myself so hard that I lose my breath and break into sweat’’
(2); ‘‘I push myself near exhaustion’’ (3). Question 3: ‘‘How long
does each session last?’’ with the following response options ‘‘Less
than 15 minutes’’ (0.1); ‘‘15–29 minutes’’ (0.38); ‘‘30 minutes to 1
hour’’ (0.75); ‘‘More than 1 hour’’ (1.0). The numbers in brackets,
corresponding to each subject’s response to the 3 questions above,
were multiplied to calculate the physical activity index score. An
index score in the range 0.05–1.50 was considered to signify low
activity, an index score in the range 1.51–3.75 was interpreted as
medium activity and a score in the range 3.76–15.0 signified high
activity. The index score is previously established as valid and
reliable [26].
Borg Scale of Perceive d Exertion and VO
2
at 2 Sub
Maximal and Maximal Workload
Candidates were asked to state their subjective rating of
perceived exertion (Borg scale) at the end of 3 different levels.
Borg scale visualizes work load intensity, denoted by numbers 6–
20 [22], with a proportional relation between increased rating of
perceived exertion and the reported Borg scale number. Level 1:
The individual initial workload for the test was determined during
warm-up. All individuals reached a stable VO
2
and heart rate after
3 minutes at the first submaximal work load. Level 2: Treadmill
gradient was elevated by 2% or velocity increased 1 km?h
21
. After
1–2 minutes at this sub maximal workload steady state was
obtained. The maximum level is described previously.
Watts
Workload in watts was calculated at the 3 described workloads.
Calculations were based on treadmill slope gradient, velocity and
body mass input in Cortex MetaMax II (Cortex, Leipzig,
Germany). Minimum slope gradient was 2% and mean slope
gradient at maximum workload was 10.461.4%.
Statistical Analysis
Parametric analysis was used based on the large sample size.
QQ-plots supported the assumption of normally distributed data.
Descriptive data are presented as arithmetic mean 6 standard
deviation. An Independent-Samples T test was used for establish-
ing level of significance between sexes and age groups. Linear
regression, with 95% confidence interval, was used to illustrate
associations between physiological parameters. All statistical tests
The HUNT 3 Fitness Study
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were two-sided. SPSS 16.0 (Statistical package for Social Sciences,
Chicago; Illinois, USA) and GraphPad Prism 4.01 (GraphPad
Software, San Diego, California, USA) were used to analyze data.
Correlations were done using data from Level 1, Level 2 and Level
3 (maximum) as described above. A p-value of ,0.05 was
considered statistically significant.
Results
Overall VO
2max
was 3.1960.90 L?min
21
or
41.369.2 mL?kg
21
?min
21
(range 18.6–76.5 mL?kg
21
?min
21
,
Table 1). Women had 18.7% (p,0.001) lower VO
2max
than
men (37.067.5 mL?kg
21
?min
21
vs. 45.468.9 mL?kg
21
?min
21
).
Maximal oxygen pulse was 34% lower (p,0.001) in women than
men (14.062.6 mL?beat
21
vs. 21.163.8 mL?beat
21
). Maximal
workload at VO
2max
was 33% lower (p,0.001) in women
compared with men (121624 W vs. 181636 W). There were no
significant sex differences in maximal heart frequencies or Borg
scores at termination of the test (Table 1).
The highest VO
2max
and maximal heart rate for both sexes
were observed in the age group 20–29 years. Among men and
women in this age group VO
2max
were 54.468.4 mL?kg
21
?min
21
and 43.067.7 mL?kg
21
?min
21
(sex differences, p,0.001) with
corresponding heart rates of 196610 beats?min
21
and 19469
beats?min
21
(sex differences, p,0.05). In both sexes VO
2max
and
maximal heart rates were approximately 8%
(<3.5 mL?kg
21
?min
21
) and 3.5% (6 beats?min
21
) lower per
increased decade, respectively. The Physical Activity Index (PAI)
scores were also highest for both sexes in this age group. For men
and women PAI scores were 4.6464.04 and 3.9663.25,
respectively (no significant sex differences), which are considered
to indicate a high physical activity level. All other age groups,
regardless of sex, had PAI scores in the range 2.67–3.70, which are
considered to indicate medium activity [26] (Table 2).
We observed an EqVO
2max
of 33.964.0 and 34.165.3 among
men and women, aged 20–29 years, respectively. Generally no
differences were found between sexes and age groups, except from
a3%(p,0.05) higher EqVO
2max
in females aged 30–39 and 40–
49 years compared to corresponding groups of males. Addition-
ally, EqVO
2max
increased by 3% (p,0.05) between the two most
senior male groups (Table 2).
The highest maximal oxygen pulse was observed in the 3
youngest age groups (20–49 years) for both sexes, with no
significant difference between these age groups. Women in these
age groups had 33% lower (p,0.001) oxygen pulse compared
with men (14.762.7 mL?beat
21
vs. 22.363.6 mL?beat
21
). In
the subsequent age groups an approximately 8% reduction in
oxygen pulse per decade was observed among both sexes
(Table 3).
Rating of Perceived Exertion, %VO
2max
and %maximal
Heart Rate
As can be seen from Table 4, rating of perceived exertion
reported as Borg Score fairly well estimate the relative exercise
intensity expressed as percent of maximal heart rate and percent
of VO
2max
. Data also show that there may be sex differences in
these relationships in the lowest intensities corresponding to
Borg below 16. For example the actual exercise intensity for
men and women that report to exercise at Borg 6–9
corresponds to 75.8% (CI: 74.5–77.1) and 79.1% (CI: 77.6–
80.5) of maximal heart rate, respectively (sex differences,
p,0.05). Furthermore, Borg 13–15 corresponds to a heart rate
of 84.7% (CI: 84.3–85.1) for men and 88.4% (CI: 88.0–88.7)
for women (sex differences, p,0.001). The same discrepancies
apply to %VO
2max
in corresponding Borg range. At Borg Score
above 16 there were no sex or age group differences, with the
exception of an age group difference between the 50–59 years
and the 60–69 years group in both percent of maximal heart
rate (p,0.01) and percent of VO
2max
(p,0.05).
VO
2
, Heart Rate, Watt and Physical Activity Index
Figure 1 displays the relationship between VO
2
and heart rate.
The overall correlation for VO
2
(L?min
21
) and heart rate was
found to be moderate (r = 0.51, p,0.0001). Stratified by sex, this
association became stronger; males r = 0.70 (p,0.0001), female
r = 0.61 (p,0.0001). The association between percent VO
2
and
percent maximal heart rate was strong; all r = 0.89 (p,0.0001),
male r = 0.90 (p,0.0001), female r = 0.87 (p,0.0001).
Figure 2 demonstrates the strong association between VO
2
(L?min
21
) and treadmill workload (Watts), and the correlation
between watts and heart rate; VO
2
vs. Watts: all r = 0.90
(p,0.0001), male r = 0.89 (p,0.0001), female r = 0.84
(p,0.0001). Heart rate vs. Watts: Viewing the full sample size a
moderate correlation was observed between treadmill workload
(Watts) and heart rate (r = 0.55, p,0.0001). Good correlations
were observed when the data was stratified by sex; male r = 0.71
(p,0.0001), female r = 0.66 (p,0.0001).
Figure 3 demonstrates a poor, but statistically strong association
between Physical activity index and VO
2
(mL?kg
21
?min
21
); all
r = 0.24 (p,0.0001), male r = 0.29 (p,0.0001) and female r = 0.27
(p,0.0001).
Figure 4 exhibits a moderate association between VO
2
(both
mL?kg
21
?min
21
and L?min
21
) and age groups, male: r = 0.54
and r = 0.54, respectively; female: r = 0.52 and r = 0.50, respec-
tively.
Table 1. Physical and physiological characteristics of
participants in the HUNT 3 Fitness study.
All Male Female
(n = 3678) (n = 1929) (n = 1881)
Age (years) 46.7613.1 47.5613.1 45.8613.0
Body mass(kg) 77.3613.7 85.3611.1 69.2611.0
Height (cm) 172.969.0 179.566.4 166.165.8
VO
2max
(L?min
21
) 3.1960.90 3.8360.72 2.5360.49
VO
2max
(mL?kg
21
?min
21
)
41.369.2 45.468.9 37.067.5
VO
2max
(mL?kg
20.75
?min
21
)
122.0627.8 137.3625.6 106.2620.2
O
2
pulse
(mL?beat
21
)
17.764.9 21.163.8 14.062.6
R(CO
2
?VO
2
21
) 1.1460.05 1.1460.05 1.1460.05
f
c
(beats?min
21
)181614 182614 181614
Work load (Watts) 151643 181636 121624
Borg 186118611861
Physical activity
index
3.4162.88 3.3162.99 3.5262.76
Data is presented as arithmetic mean 6SD. VO
2max
: maximal oxygen uptake, O
2
pulse: oxygen uptake per heartbeat, CO
2
: Carb on dioxide, R: respiratory
exchange ratio, f
c
: cardiac frequency, workload: treadmill exercise load, BORG:
subjective perception of fatigue (6–20), Physical activity index: A weighted
product score between training- intensity, duration and frequency.
doi:10.1371/journal.pone.0064319.t001
The HUNT 3 Fitness Study
PLOS ONE | www.plosone.org 3 May 2013 | Volume 8 | Issue 5 | e64319
Discussion
This is the largest European reference material of objectively
measured aerobic capacity and exercise-physiology in healthy men
and women aged 20–90 yrs. Our observations are an important
supplement to previously published data that have mostly been
either indirect or based on small, selected, or poorly-described
populations [8–14].
Sex Differences in VO
2max
and Maximal Heart
Frequencies
Despite being generally more physical active than men, women
had a 34% and 18.5% lower absolute (L?min
21
) and relative
(mL?kg
21
?min
21
)VO
2max
, respectively, than men. When applying
Table 2. Physiological variables in the HUNT 3 Fitness study
stratified by sex and age groups.
Male Female
20–29 years
(n = 199) (n = 215)
VO
2max
(L?min
21
) 4.3260.71 2.7860.46
VO
2max
(mL?kg
21
?min
21
)54.468.4 43.067.7
VO
2max
(mL?kg
20.75
?min
21
) 162.1623.7 121.7620.1
EqVO
2max
(V
E
?VO
2max
21
)33.964.0 34.165.3
Body mass (kg) 80.1610.6 65.5610.4
Height (cm) 1816616666
R(CO
2
?VO
2
21
) 1.1560.05 1.1560.05
f
c
(beats?min
21
)196610 19469
Workload (Watts) 200639 128624
BORG 19611861
PAI 4.6464.03 3.9663.25
30–39 years
(n = 324) (n = 359)
VO
2max
(L?min
21
) 4.2260.63 2.7560.48
VO
2max
(mL?kg
21
?min
21
)49.167.5 40.066.8
VO
2max
(mL?kg
20.75
?min
21
) 149.2621.0 114.9618.1
EqVO
2max
(V
E
?VO
2max
21
)33.263.7 34.164.6
Body mass (kg) 86.8612.1 69.7611.5
Height (cm) 1806616865
R(CO
2
?VO
2
21
) 1.1560.05 1.1560.05
f
c
(beats?min
21
)19069.5 188611
Workload (Watts) 197633 128623
BORG 18611861
PAI 3.1563.23 3.3662.73
40–49 years
(n = 526) (n = 493)
VO
2max
(L?min
21
) 4.0360.61 2.6560.44
VO
2max
(mL?kg
21
?min
21
)47.267.7 38.466.9
VO
2max
(mL?kg
20.75
?min
21
) 143.3621.4 110.3618.1
EqVO
2max
(V
E
?VO
2max
21
)33.664.3 34.664.5
Body mass (kg) 86.4611.5 69.9611.2
Height (cm) 1806716766
R(CO
2
?VO
2
21
) 1.1560.05 1.1560.05
f
c
(beats?min
21
)184611 182611
Workload (Watts) 189633 125622
BORG 18611861
PAI 3.0062.73 3.7062.66
50–59 years
(n = 466) (n = 428)
VO
2max
(L?min
21
) 3.6560.59 2.3660.37
VO
2max
(mL?kg
21
?min
21
)42.667.4 34.465.7
VO
2max
(mL?kg
20.75
?min
21
) 129.5621.1 98.7615.0
EqVO
2max
(V
E
?VO
2max
21
)33.964.9 33.964.2
Body mass (kg) 86.4610.3 69.6610.2
Height (cm) 1796616566
R(CO
2
?VO
2
21
) 1.1460.05 1.1460.05
Table 2. Cont.
Male Female
20–29 years
(n = 199) (n = 215)
f
c
(beats?min
21
)177612 176611
Workload (Watts) 173628 117623
BORG 18611861
PAI 3.2462.70 3.5262.80
60–69 years
(n = 300) (n = 240)
VO
2max
(L?min
21
) 3.3060.55 2.1660.33
VO
2max
(mL?kg
21
?min
21
) 39.266.7 31.165.1
VO
2max
(mL?kg
20.75
?min
21
)118.5619.4 89.6613.4
EqVO
2max
(V
E
?VO
2max
21
) 34.965.0 34.164.4
Body mass (kg) 84.769.9 70.4610.9
Height (cm) 17966 16565
R(CO
2
?VO
2
21
) 1.1460.05 1.1260.05
f
c
(beats?min
21
)171613 169612
Workload (Watts) 160633 110623
BORG 17611762
PAI 3.2262.58 3.1962.57
+
70 years
(n = 76) (n = 53)
VO
2max
(L?min
21
) 2.8160.50 1.8560.35
VO
2max
(mL?kg
21
?min
21
) 35.366.5 28.365.2
VO
2max
(mL?kg
20.75
?min
21
)105.3618.5 80.3613.8
EqVO
2max
(V
E
?VO
2max
21
) 36.065.2 34.964.4
Body mass (kg) 80.269.6 66.2611.2
Height (cm) 17666 16266
R(CO
2
?VO
2
21
) 1.1260.05 1.1160.03
f
c
(beats?min
21
)163615 165616
Workload (Watts) 140631 97626
BORG 17611662
PAI 3.4662.92 2.6761.92
Data is presented as arithmetic mean 6 SD. VO
2max
: maximal oxygen uptake,
EqVO
2max
: ventilatory equivalents, R: respiratory exchange ratio, f
c
: cardiac
frequency, Workload: treadmill exercise load, BORG: subjective perception of
fatigue (6– 20), PAI: physical activity index: A weighted product score between
training- intensity, duration and frequency.
doi:10.1371/journal.pone.0064319.t002
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appropriate scaling procedures [27] where differences in body
mass are taken into consideration for a more accurate comparison
[27–29], women had 22.7% lower VO
2max
(mL?kg
20.75
?min
21
)
than men. The higher VO
2max
in men is in accordance with
former studies [5,10–14,30]. We observed higher VO
2max
compared to that reported in American [9,11,13,14], Japanese
populations [8] and a large Brazilian study [31], especially in the
younger age groups. Earlier Scandinavian research supports our
Table 3. O
2
-pulse in the HUNT 3 Fitness study stratified by intensity levels, sex and age groups.
Male Female
Level 1 Level 2 Maximal Level 1 Level 2 Maximal
20–29 years
(n = 121) (n = 106) (n = 199) (n = 131) (n = 111) (n = 215)
O
2
-pulse (mL? beat
21
)17.565.5 18.464.0 22.164.0 11.862.4 12.662.2 14.462.4
VO
2
(mL?kg?min
21
)34.668.0 40.468.1 54.468.4 29.366.2 33.966.5 43.067.7
%VO
2max
63.7612.3 72.7610.6 68.1611.0 76.669.6
%f
cmax
80.768.8 87.865.4 85.068.3 90.766.4
Workload (watts) 109624 126623 200639 78615 91614 128624
30–39 years
(n = 176) (n = 166) (n = 324) (n = 247) (n = 221) (n = 359)
O
2
-pulse (mL? beat
21
)17.562.9 18.362.9 22.363.6 12.262.5 12.962.6 14.762.7
VO
2
(mL?kg?min
21
)29.865.5 34.265.7 49.167.7 27.265.3 31.065.5 40.066.8
%VO
2max
62.1610.4 71.0610.1 68.5610.4 77.769.9
%f
cmax
78.967.4 86.066.4 83.366.9 90.365.8
Workload (watts) 110621 124620 197633 77616 91618 128623
40–49 years
(n = 351) (n = 334) (n = 526) (n = 347) (n = 320) (n = 493)
O
2
-pulse (mL? beat
21
)18.463.9 19.164.0 22.163.6 12.362.5 13.062.54 14.662.6
VO
2
(mL?kg?min
21
)30.766.8 34.867.1 47.267.7 26.565.03 30.265.9 38.466.9
%VO
2max
65.1610.6 73.7610.4 70.1610.4 79.069.8
%f
cmax
78.667.7 85.767.3 83.167.1 90.066.0
Workload (watts) 107621 123622 189633 74615 88616 125622
50–59 years
(n = 343) (n = 314) (n = 466) (n = 354) (n = 311) (n = 428)
O
2
-pulse (mL? beat
21
)17.863.3 18.563.3 20.763.6 11.862.1 12.362.2 13.462.2
VO
2
(mL?kg?min
21
)28.566.0 32.166.1 42.667.4 24.164.0 27.164.3 34.465.7
%VO
2max
67.6610.9 75.6610.6 72.0610.1 80.269.8
%f
cmax
78.367.7 85.267.3 82.267.1 88.466.4
Workload (watts) 99620 117621 173628 67617 79618 117623
60–69 years
(n = 258) (n = 239) (n = 300) (n = 236) (n = 204) (n = 240)
O
2
-pulse (mL? beat
21
)17.163.3 17.563.4 19.363.4 11.762.5 11.962.1 12.962.3
VO
2
(mL?kg?min
21
)26.665.5 29.665.4 39.266.7 22.963.8 25.564.3 31.165.1
%VO
2max
66.4611.0 76.5611.0 74.869.9 81.969.2
%f
cmax
77.968.5 84.668.0 83.868.4 89.367.4
Workload (watts) 88620 104621 160633 57617 70618 110623
+
70 years
(n = 95) (n = 86) (n = 76) (n = 83) (n = 71) (n = 53)
O
2
-pulse (mL? beat
21
)15.363.1 15.863.3 17.263.2 10.162.2 10.662.1 11.462.4
VO
2
(mL?kg?min
21
)24.365.2 26.966.1 35.366.5 20.764.1 22.864.6 28.365.2
%VO
2max
70.7610.9 77.8611.0 74.5610.4 81.869.0
%f
cmax
80.967.7 86.268.0 84.267.2 90.067.7
Workload (watts) 67625 83627 140631 43618 57619 97626
Data is presented as arithmetic mean 6 SD. O
2
-pulse: oxygen pulse, VO
2
: oxygen uptake, %f
cmax
: percent of maximum heart frequency, Workload: treadmill exercise
load.
doi:10.1371/journal.pone.0064319.t003
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VO
2max
levels [25,32,33]. A study of Nomadic Lapps [34], who
were physically active in taking care of their reindeers, observed
VO
2max
values close to our findings, and it is indicated that
Roman legionnaires [35] had a VO
2max
in the range of
50 mL?kg
21
?min
21
. Also contemporary hunter-gatherer societies
display VO
2max
in the range 50–65 mL?kg
21
?min
21
in young
male populations [36]. This supports the assumption that by living
an active life, VO
2max
in the range we display could be expected.
When applying a scaled VO
2max
[27], where differences in body
weight is considered for a more precise comparison [27–29], the
HUNT 3 fitness study still displays a considerable higher VO
2max
(mL?kg
20.75
?min
21
) than North American, German and Asian
studies. Scaled VO
2max
in HUNT 3 was approximate 20% higher,
considering both sexes and all age groups, than North American
[9,10,37] and a German study [38]. However, a North American
study by Jackson and colleagues [14] display only an estimated
10% lower scaled VO
2max
, compared to our findings, among both
sexes in the 20–29 year age group, with diminishing differences
per subsequent decade. A Japanese study [8] displays an average
14% lower scaled VO
2max
than us, among both sexes and all age
groups. The dissimilarities between our and other findings may be
explained by that we measured VO
2max
whereas most others
[8,9,11,14] use VO
2peak
or estimated VO
2max
[13,15], and that
most other populations might also lead a more sedate lifestyle than
that of Scandinavians.
Despite our relatively high mean VO
2max
, 25 men and 9 women
(.50 years) displayed values below 8 METs (28 mL?kg
21
?min
21
)
and 6 METs (21 mL?kg
21
?min
21
), respectively. This is associated
with higher all-cause mortality and cardiovascular events among
healthy men and women [4]. 1% of men 50–59 years displayed
METs associated with increased risk, with 4% and 11%
prevalence of ‘‘increased risk MET’’ with each subsequent decade.
Women displayed approximately half the prevalence over the
same age groups. We report a somewhat higher maximal heart
rate than previous studies, which could be explained by that others
[10–12] measure peak heart rate. In line with former studies [10–
12] there were no significant sex differences in maximal heart rate.
Differences in VO
2max
and Physical Activity Level
Stratified by Age Group and Sex
The highest VO
2max
, in both men and women, were observed in
the age groups 20–29 years. This fits with that both sexes in this age
group had the highest level of physical activity compared to all other
age groups. Between the two youngest age groups of both men and
women (20–29 years and the 30–39 years) there was no difference in
absolute VO
2max
(L?min
21
). However, among the 30–39 years old,
body mass was 8.4% and 6.4% higher, and physical activity level
32.1% and 15.2% lower for men and women, respectively. A lower
physical activity level did not influence the absolute VO
2max
(L?min
21
) but probably contribute to the higher body mass in those
aged 30–39 years. Relative to body mass VO
2max
(mL?kg
21
?min
21
)
was 10% and a 7% lower among men and women aged 30–39 years
compared to those in the 20–29 year age group. Thus, lower relative
VO
2max
in those aged 30–39 years old was caused by a higher body
mass in our study population.
Despite similar body weights and physical activity level, a highly
significant lower absolute (4.4%) and relative (3.8%) VO
2max
was
observed among men and women aged 40–49 years compared to
those aged 30–39 years. In line with our findings, Sanada and
colleagues [8] observed a similar drop in VO
2max
between these
age groups among healthy Japanese men. However, they observed
a considerably larger ‘‘drop’’ in VO
2max
with no change in body
mass among women compared to our observations. Their findings
are in agreement with another study of women by Jackson and
colleagues [9]. A likely explanation for the lower VO
2max
in those
aged 40–49 vs. 30–39 could be a reduced level of physical activity
in the oldest age group. However, our data does not support this.
The Sanada [8] study shows a decrease in skeletal muscle mass
with simultaneous increase in percent body fat. This would
deteriorate demand properties and decrease VO
2max
. We do not
know if this is the case in our study, but the drop in absolute
VO
2max
yields a reduction in supply properties, hence a reduction
in VO
2max
. The reason for different ‘‘drop’’ in VO
2max
among
women in our study, the Sanada [8] and Jackson [9] studies is not
known and warrant further studies.
Over the 3 next decades (40–69 years) the decrease in absolute
and relative VO
2max
had more than doubled (<10% per decade),
Table 4. Relationships between perceived exertion, VO
2max
and f
cmax
in the HUNT 3 fitness study.
All Male Female
Borgscale % f
cmax
95% CI N % f
cmax
95% CI N % f
cmax
95% CI N
6–9 77.3 76.4–78.3 253 75.8 74.5–77.1 136 79.1 77.6–80.5 117
10–12 79.9 79.5–80.3 1475 78.1 77.6–78.6 813 82.2 81.6–82.7 662
13–15 86.6 86.3–86.7 3017 84.7 84.3–85.1 1459 88.4 88.0–88.7 1558
16–18 98.1 97.9–98.3 1775 98.1 97.8–98.4 862 98.2 97.9–98.5 913
19+ 99.9 99.9–100 1216 99.9 99.7–100 560 100 99.98–100 656
Borgscale %VO
2max
95% CI N %VO
2max
95% CI N %VO
2max
95% CI N
6–9 61.9 60.6–63.3 253 60.1 58.2–62.1 136 64.0 62.3–65.7 117
10–12 66.8 66.3–67.3 1475 64.7 64.1–65.4 813 69.3 68.6–70.0 662
13–15 76.7 76.3–77.1 3017 74.4 73.8–75.0 1459 78.8 78.3–79.4 1558
16–18 96.4 96.0–96.8 1775 96.5 96.0–97.1 862 96.3 95.8–96.8 913
19+ 99.9 99.5–100 1216 99.8 99.5–100 560 99.9 99.9–100 656
Borgscale: subjective perception of perceived ex ertion (6–20), CI: confidence interval, %f
cmax
: percent of maximal heart frequency, %VO
2max
: percent of maximal oxygen
uptake.
doi:10.1371/journal.pone.0064319.t004
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in both sexes, compared to that observed between age groups 30–
39 years and 40–49 years. There were no significant differences in
body mass between these age groups, with the exception of a <2%
reduction in males between 50–59 and 60–69 years. The
reduction in VO
2max
per decade is in line with previous studies
[8,11,14]. A significant reduction in physical activity level with
increased age among women was observed in our study, with no
changes in the male group. Thus, reduced physical activity level
may explain reduced VO
2max
with increased age among women
but not among men. Whether this is really an age-related decline
Figure 1. Correlations between oxygen uptake (VO
2)
and heart rate (f
c
).
doi:10.1371/journal.pone.0064319.g001
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or due to that men have a tendency to over-report physical activity
[39] is not known, and future investigations should aim to obtain
objectively measured physical activity levels.
Between the 60–69 years and the +70 year age groups we
observed the largest ‘‘drop’’ in absolute VO
2max
(L?min
21
) in both
sexes (<14.5%). Relatively VO
2max
(mL?kg
21
?min
21
) were 10%
Figure 2. Correlations between workload (Watts) and oxygen uptake (VO
2
) and correlations between Watts and heart rate (f
c
).
doi:10.1371/journal.pone.0064319.g002
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and 11% lower in males and females aged +70 compared to those
aged 60–69 years. The large drop in relative VO
2max
occurred
despite no significant drops in body mass and physical activity
level. This suggests that the drop may be due to ‘‘age-related’’
adaptations in the organism. Our findings for these age groups are
in line with previous studies reporting reductions in relative and
absolute VO
2max
in the range 13–25% and 12–29% [8,10,12,40].
Ventilatory efficiency, EqVO
2max
, remains generally unchanged
throughout the age groups; hence, it is not a factor in explaining
the diminishing VO
2max
with increasing age. However, subsequent
50 years of age O
2
-pulse displayed a steady decrease, which
indirectly indicate a reducing stroke volume, hence this yield a
reduction in VO
2max
.
Differences in Maximum Heart Rate Stratified by Age
Group and Sex
Maximum heart rate has regularly been estimated by an
equation subtracting age from 220 beats?min
21
, which have
limited scientific merit [41]. The highest heart frequencies were
found in the youngest age groups, regardless of sex. Maximal heart
frequencies in men and women were 196610 beats?min
21
and
19469 beats?min
21
, respectively, with a decline of approximately
3.5% (6 beats?min
21
) per decade. Our maximal heart rate decline
Figure 3. Correlations between physical activity index score
and oxygen uptake (VO
2
).
doi:10.1371/journal.pone.0064319.g003
Figure 4. Decline of oxygen uptake (VO
2
) relative to age. Mean
and SD for each age group is presented in Table 2.
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gradient is approximately half that compared to using the 220
beats?min
21
minus age equation, which is consistent with former
research [10,42,43].
Differences in Oxygen Pulse Stratified by Gender and Age
Groups
The highest maximal oxygen pulse was observed in the 3 youngest
age groups among men (22.363.6 mL?beat
21
) and women
(14.762.7 mL?beat
21
), with no significant difference between these
age groups. Previous reference material on oxygen pulse in healthy
populations is based upon case reports [7] or small studies in athletes
[44] [45] making comparison with our data complicated.
Association between VO
2
and Heart Rate
The benchmark studies of the relationship between submaximal
VO
2
and heart frequencies from the 509s and 609s have small
sample size. When comparing our findings with that of A
˚
strand [6]
there are obvious discrepancies. Compared with our observations,
A
˚
strand reports lower heart frequencies at workloads correspond-
ing to VO
2
lower than 3 L?min
21
, and higher heart frequencies at
VO
2
higher than 3 L?min
21
. Since there are no references to
sample size or gender in A
˚
strands data it is difficult to interpret the
discrepancies between the studies. Another study by A
˚
strand [17]
with 86 relatively well trained male and female students, agrees
with our data, for the age group 20–29 years, on VO
2
less than
3L?min
21
. When VO
2
exceed 3.0 L?min
21
for females and
4.0 L?min
21
for males the present study displays lower heart
frequencies than reported in the A
˚
strand study. A study [18] with
44 females, aged 20–65 years, displayed lower heart frequencies
than we observed for VO
2
,1.5 L?min
21
, but higher heart
frequencies for VO
2
.1.5 L?min
21
. The observed association
between percent VO
2max
and percent maximal heart rate is in
agreement with previous studies [16,18,19] on intensities .70% of
VO
2max
. At exercise intensities ,70% of VO
2max
we observed
higher percent heart rate than previous studies. In our study 30%
of VO
2max
corresponded to 60% of maximal heart rate where
others [16,18,19] have reported that this is equal to 50% of
maximal heart rate. However, we use treadmill testing while the
others use bicycle ergometer, which could explain the discrepan-
cies.
Association between Heart Rate and Watts
Comparing our results to a study by A
˚
strand [20] with 84
healthy males, good agreement was found for workloads .150W,
whereas we observed progressively higher heart frequencies than
A
˚
strand at lower workloads. This is also the case when comparing
our results to another study of males by A
˚
strand [6]. Again, the
inconsistency between our and A
˚
strand’s findings could be explain
by treadmill vs. bicycle ergometer.
Association between VO
2
and Watts
We systematically display higher VO
2
(L?min
21
) at any given
watt than that observed in two studies from A
˚
strand [17,21].
Discrepancies seem to be caused by higher initial VO
2
cost
(L?min
21
) in our results, while the slope gradient is in close
proximity with A
˚
strand [17,21]. The differences may be explained
by that we applied treadmill work whereas A
˚
strand used a cycle
ergometer.
Association between Borg Sca le Scores, % VO
2max
and %
Maximal Heart rRate
We observed a mismatch between the Borg study [22] and our
findings. We observed considerably higher percent VO
2max
and
percent maximal heart rate for a given exertion interval than Borg
[22], but differences vanished at the highest Borg-levels.
Relative to VO
2max
and maximal heart rate Borg scale differed
between sexes. In the range 6–15 on Borg scale males worked at a
lower percent (4%) of both VO
2max
and maximal heart rate than
females, i.e. the relative rating of perceived exertion in males were
higher at a given work load. There were no differences between
sexes at Borg16–20. Our data clearly support the notion that Borg-
scale may be used as a robust tool to guide exercise intensity in
healthy men and women, but that one should be aware of sex
differences at the lowest Borg levels.
Association between Physical Activity Index Scores and
VO
2max
There was a poor overall correlation (r = 0.24) between self-
reported physical activity level and VO
2
, which indicates that only
5.7% of differences in VO
2max
can be explained by the physical
activity scores. This is in agreement with prior research [11,46,47].
Physical activity index score (PAI) is a weighted product between
duration, frequency and intensity. Intensity might be weighted to
low, thus it could explain the poor correlation between PAI and
VO
2
.
Limitations
This study may be subject to bias due to self-selection caused by
the low participation rate. However, almost all of those who were
invited to the current Fitness study from the large HUNT study
agreed to participate in the fitness test. Due to limited capacity at
the test sites resulting in long waiting lines, many potential
participants chose to withdraw their participation from the study.
Those who finally participated in the study could thus be healthier
than those who quit or declined participation. However, a
comparison of the participants in the fitness study with a healthy
sample of the total HUNT population (i.e. free from cardiovas-
cular or pulmonary diseases, cancer, or sarcoidosis) confirmed that
the fitness participants did not considerably differ from other
healthy HUNT participants [48]. In future studies physical activity
should be measured objectively rather than being self-reported,
given the large inconsistencies between VO
2max
and self-reported
physical activity.
Conclusions
The discrepancies between this and previous studies highlighted
the need of a large reference material as presented in this study.
The HUNT 3 Fitness study presents the largest Europen reference
material of objectively measured parameters of aerobic capacity
and exercise-physiology in healthy men and women aged 20–90
years. Our data establishes normal values for the key physiological
factors VO
2max
and heart rate, as well as associations between
commonly used exercise parameters. The data forms the basis for
a user-friendly tool for exercise intensity control in healthy men
and women.
Acknowledgments
The HUNT 3 fitness study is a collaboration between The HUNT research
center (Faculty of Medicine, Norwegian University of Science and
Technology, NTNU), Nord-Trøndelag County Council and The Norwe-
gian Institute of public Health, Liaison Committee between the Central
Norway Regional Health Authority (RHA) and the Norwegian University
of Science and Technology (NTNU).
The HUNT 3 Fitness Study
PLOS ONE | www.plosone.org 10 May 2013 | Volume 8 | Issue 5 | e64319
Author Contributions
Conceived and designed the experiments: UW. Performed the experi-
ments: UW OR. Analyzed the data: HL OR BS UW. Contributed
reagents/materials/analysis tools: HL OR BS UW. Wrote the paper: HL
OR BS UW. Conception and design of the work, acquisition of data, or
analysis and interpretation of data: HL OR BS UW. Drafting the article or
revising it critically for important intellectual content: HL OR BS UW.
Final approval of the version to be published: HL OR BS UW.
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The HUNT 3 Fitness Study
PLOS ONE | www.plosone.org 11 May 2013 | Volume 8 | Issue 5 | e64319
... On the other hand, while we acknowledge the existence of other articles with larger sample sizes that provide reference standard values for some of the variables discussed in the present study, these variables are typically stratified by sex and age (Loe et al. 2013;Vainshelboim et al. 2020), but not by training status. Therefore, understanding the reference standard values of these variables according to training status would be valuable for interpreting an individual's fitness level more accurately. ...
... However, exercise protocols with steeper slopes of load increment yield higher workload values at different physiological points (Jamnick et al. 2018). Regarding reference standard values, other studies report data with larger sample sizes, but they classify individuals based on age and sex rather than training status (Loe et al. 2013;Vainshelboim et al. 2020). Although we acknowledge that our study does not provide data from such a large sample size, to the best of our knowledge, it is currently the only study available in the literature that reports reference values considering training status. ...
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Purpose To analyze the influence of training status on the percentage of maximum oxygen consumption, heart rate and velocity (%VO2max, %HRmax and %Vmax) at which ventilatory threshold 1 and ventilatory threshold 2 occur (VT1 and VT2, respectively), in males and females separately considering age, during a ramp incremental treadmill test. Methods 791 males (36.8 ± 9.9 years) and 301 females (33.9 ± 11.0 years) performed a ramp incremental exercise test until fatigue where VT1 and VT2 were determined. Participants were classified as low, medium or high training status combining the oxygen consumption at VT1, VT2 and VO2max by clustering analysis. Results VO2max is poorly correlated with the %VO2max, %HRmax and %Vmax at which VT1 and VT2 occur (r < 0.3), in contrast, there is a positive correlation between oxygen consumption at VT1 and VT2 with the %VO2max, %HRmax and %Vmax at which VT1 and VT2, respectively, occur in males and females (r = 0.203–0.615). Furthermore, we observed the %VO2max, %HRmax and %Vmax at which thresholds occur were greater the higher the training status (all p < 0.003). Conclusion The physiological determinants of the percentage of maximum at which VT1 and VT2 occur are more related to oxygen consumption at VT1 and VT2, respectively, than to VO2max. Moreover, due to the higher percentage of maximum at which VT1 and VT2 occur in individuals with a higher training status, the common strategy consisting of establishing exercise intensity as a fixed percentage of maximum might not be effective to match intensity across individuals with different training status. Clinical trial registration NCT06246760.
... An SPPB summary score of >10, combined with a gait speed of approximately 1.0 m/s and a Physical Activity Index of >=3.4, indicates good functional status [40,41] and a relatively high level of self-reported physical activity in both survivors and controls [42]. Supported by the results of others [26,27], these findings suggest that radical prostate cancer treatment had little impact on long-term physical performance. ...
Article
Background and objective Whether radical prostate cancer treatment affects long-term physical performance and physical activity in older men is not known. We aimed to compare physical performance and self-reported physical activity between relapse-free older prostate cancer survivors and population-based controls. Methods A single-centre, cross-sectional study including 109 men aged ≥70 yr receiving robotic-assisted radical prostatectomy (61.5%) or external beam radiotherapy (38.5%) between 2014 and 2018 was conducted. Population-based matched (age, gender, and education) controls (n = 327) were drawn from the Trøndelag Health Study. The primary (the Short Physical Performance Battery [SPPB] summary score) and secondary (gait speed, grip strength, one-legged balance, and the self-reported Physical Activity Index) outcomes were compared between survivors and controls by adjusted linear mixed models. Key findings and limitations The SPPB score, gait speed, and Physical Activity Index did not differ between survivors (mean age 78.3 yr, mean time since treatment 52.9 mo) and controls (mean age 78.2 yr). Survivors had slightly poorer grip strength (regression coefficient [RC] –5.81, p < 0.001, 95% confidence interval [CI] –7.46; –4.17) and one-legged balance (RC –4.36, p < 0.001, 95% CI –6.72; –2.00; adjusted models), but the clinical significance is uncertain. Small sample size and potential selection of the fittest survivors are limitations that may reduce the generalisability of our findings. Conclusions and clinical implications 3 to 8 yr after radical prostate cancer treatment, older men’s overall physical performance and physical activity level were comparable with those of matched controls. This suggests that the treatment had little impact on functional status. Patient summary In this study, we investigated physical function in older men several years after they had undergone curatively intended treatment for prostate cancer in comparison with men in a general population of the same age and education. We found that physical function was similar, except slightly poorer grip strength and balance on one leg in men treated for prostate cancer. We conclude that the overall physical function was comparable with that of the general population and believe that this indicates that prostate cancer treatment was well tolerated despite older age.
... Although the adopted exercise protocol was not intended to be exhaustive, four patients (two males) were exhausted at different times during the vigorous workload indicating that they had reached their exercise capacity. The male patients achieved only ~40%, while the female only ~67% of their expected VO 2 max and associated workload compared with reference values of healthy people matched for age and sex (Loe et al., 2013). On average, the cirrhotic patients F I G U R E 1 HS blood flow at rest, during mild (10 min), moderate (20 min), and vigorous (30 min) exercise and in the recovery. ...
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In cirrhotic patients, compromised hepatocyte function combined with disturbed hepatic blood flow could affect hepato‐splanchnic substrate and metabolite fluxes and exacerbate fatigue during exercise. Eight cirrhotic patients performed incremental cycling trials (3 × 10 min; at light (28 [19–37] W; median with range), moderate (55 [41–69] W), and vigorous (76 [50–102] W) intensity). Heart rate increased from 68 (62–74) at rest to 95 (90–100), 114 (108–120), and 140 (134–146) beats/min (P < 0.05), respectively. The hepatic blood flow, as determined by constant infusion of indocyanine green with arterial and hepatic venous sampling, declined from 1.01 (0.75–1.27) to 0.69 (0.47–0.91) L/min (P < 0.05). Hepatic glucose output increased from 0.6 (0.5–0.7) to 1.5 (1.3–1.7) mmol/min, while arterial lactate increased from 0.8 (0.7–0.9) to 9.0 (8.1–9.9) mmol/L (P < 0.05) despite a rise in hepatic lactate uptake. Arterial ammonia increased in parallel to lactate from 47.3 (40.1–54.5) to 144.4 (120.5–168.3) μmol/L (P < 0.05), although hepatic ammonia uptake increased from 19.5 (12.4–26.6) to 69.5 (46.5–92.5) μmol/min (P < 0.05). Among the 14 amino acids measured, glutamate was released in the liver, while the uptake of free fatty acids decreased. During exercise at relatively low workloads, arterial lactate and ammonia levels were comparable to those seen in healthy subjects at higher workloads, while euglycemia was maintained due to sufficient hepatic glucose production. The accumulation of lactate and ammonia may contribute to exercise intolerance in patients with cirrhosis.
... In addition, assessing this indicator typically comprises the evaluation of various factors, such as VO 2max strength and maximum metabolic equivalents (METs), which require regular monitoring [2]. Previous studies also reported a significant correlation between low CRF levels and increased susceptibility to potentially fatal diseases [3]. This has led to the development of various training drills by sports practitioners to increase its levels among individuals [4]. ...
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The aim of this study was to assess the use of NEFA for the young population of Indonesia as well as to test its validity and reliability through comparison with laboratory tests. This study was divided into two phases: laboratory testing aimed at measuring VO2max on a treadmill using a velocity-dependent ramp test (INCS) method based on incremental protocols, and the NEFA measurement phase. The two phases were separated by a week. There was a significant correlation between the three variables: NEFA HRrest vs NEFA Non-HRrest (CC = 0.934; p = 0.001), NEFA Non-HRrest vs INCS test (CC = 0.476; p = 0.005), and NEFA HRrest vs INCS test (CC = 0.525; p = 0.002). The equation of NEFA HRrest and NEFA Non-HRrest was not accurate when performed on a young population with moderate physical activity levels (aerobic for 1–3 hours/week).
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Purpose Exercise has been shown to reduce platelet reactivity and increase platelet sensitivity to prostacyclin, an endothelium-derived inhibitor of platelet activation, in middle-aged men and women. It is currently unknown if these beneficial effects can also be observed in young women and the intracellular mechanisms involved have not been identified. In this study, the feasibility of detecting changes in platelet reactivity, prostacyclin sensitivity and cAMP signalling were tested. Methods 10 well-trained and 10 sedentary but healthy young women participated in this study. Responses of washed platelets to thrombin receptor activating peptide 6, the thromboxane A2 receptor agonist U46619, and prostaglandin E1 were measured by light transmission aggregometry. Expression levels of proteins in the cAMP pathway including phosphorylation of the vasodilator-stimulated phosphoprotein were analysed by western blotting. Results There was no evidence of reduced basal reactivity in platelets from the well-trained group (V˙O2max{\dot{\text{V}}\text{O}}_{2\text{max}} = 51.1 ± 3.6 ml/kg/min) compared to the untrained group (V˙O2max{\dot{\text{V}}\text{O}}_{2\text{max}} = 31.1 ± 4.7 ml/kg/min). Platelets from the trained group showed evidence of greater sensitivity to the anti-aggregatory effects of prostaglandin E1. The slope of the aggregation curves indicated an overall faster rate of aggregation in the untrained group. Mean phosphorylation levels of vasodilator-stimulating phosphoprotein were consistently higher in the trained group, indicative of increased protein kinase A activity. Conclusion Platelets from young women may exhibit an exercise-induced increase in sensitivity to prostacyclin leading to stimulation of the cAMP pathway. A larger study is warranted to explore this vasoprotective effect further.
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Background Skeletal muscle mitochondria and capillaries are crucial for aerobic fitness, and suppressed levels are associated with chronic and age-related diseases. Currently, evidence-based exercise training recommendations to enhance these characteristics are limited. It is essential to explore how factors, such as fitness level, age, sex, and disease affect mitochondrial and capillary adaptations to different exercise stimuli. Objectives The main aim of this study was to compare the effects of low- or moderate intensity continuous endurance training (ET), high-intensity interval or continuous training (HIT), and sprint interval training (SIT) on changes in skeletal muscle mitochondrial content and capillarization. Secondarily, the effects on maximal oxygen consumption (VO2max), muscle fiber cross-sectional area, and fiber type proportion were investigated. Methods A systematic literature search was conducted in PubMed, Web of Science, and SPORTDiscus databases, with no data restrictions, up to 2 February 2022. Exercise training intervention studies of ET, HIT, and SIT were included if they had baseline and follow-up measures of at least one marker of mitochondrial content or capillarization. In total, data from 5973 participants in 353 and 131 research articles were included for the mitochondrial and capillary quantitative synthesis of this review, respectively. Additionally, measures of VO2max, muscle fiber cross-sectional area, and fiber type proportion were extracted from these studies. Results After adjusting for relevant covariates, such as training frequency, number of intervention weeks, and initial fitness level, percentage increases in mitochondrial content in response to exercise training increased to a similar extent with ET (23 ± 5%), HIT (27 ± 5%), and SIT (27 ± 7%) (P > 0.138), and were not influenced by age, sex, menopause, disease, or the amount of muscle mass engaged. Higher training frequencies (6 > 4 > 2 sessions/week) were associated with larger increases in mitochondrial content. Per total hour of exercise, SIT was ~ 2.3 times more efficient in increasing mitochondrial content than HIT and ~ 3.9 times more efficient than ET, while HIT was ~ 1.7 times more efficient than ET. Capillaries per fiber increased similarly with ET (15 ± 3%), HIT (13 ± 4%) and SIT (10 ± 11%) (P = 0.556) after adjustments for number of intervention weeks and initial fitness level. Capillaries per mm² only increased after ET (13 ± 3%) and HIT (7 ± 4%), with increases being larger after ET compared with HIT and SIT (P < 0.05). This difference coincided with increases in fiber cross-sectional area after ET (6.5 ± 3.5%), HIT (8.9 ± 4.9%), and SIT (11.9 ± 15.1%). Gains in capillarization occurred primarily in the early stages of training (< 4 weeks) and were only observed in untrained to moderately trained participants. The proportion of type I muscle fibers remained unaltered by exercise training (P > 0.116), but ET and SIT exhibited opposing effects (P = 0.041). VO2max increased similarly with ET, HIT, and SIT, although HIT showed a tendency for greater improvement compared with both ET and SIT (P = 0.082), while SIT displayed the largest increase per hour of exercise. Higher training frequencies (6 > 4 > 2 sessions/week) were associated with larger increases in VO2max. Women displayed greater percentage gains in VO2max compared with men (P = 0.008). Generally, lower initial fitness levels were associated with greater percentage improvements in mitochondrial content, capillarization, and VO2max. SIT was particularly effective in improving mitochondrial content and VO2max in the early stages of training, while ET and HIT showed slower but steady improvements over a greater number of training weeks. Conclusions The magnitude of change in mitochondrial content, capillarization, and VO2max to exercise training is largely determined by the initial fitness level, with greater changes observed in individuals with lower initial fitness. The ability to adapt to exercise training is maintained throughout life, irrespective of sex and presence of disease. While training load (volume × intensity) is a suitable predictor of changes in mitochondrial content and VO2max, this relationship is less clear for capillary adaptations. Graphical Abstract
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Sex as a biological variable is an underappreciated aspect of biomedical research, with its importance emerging in more recent years. This review assesses the current understanding of sex differences in human physical performance. Males outperform females in many physical capacities because they are faster, stronger and more powerful, particularly after male puberty. This review highlights key sex differences in physiological and anatomical systems (generally conferred via sex steroids and puberty) that contribute to these sex differences in human physical performance. Specifically, we address the effects of the primary sex steroids that affect human physical development, discuss insight gained from an observational study of ‘real‐world data’ and elite athletes, and highlight the key physiological mechanisms that contribute to sex differences in several aspects of physical performance. Physiological mechanisms discussed include those for the varying magnitude of the sex differences in performance involving: (1) absolute muscular strength and power; (2) fatigability of limb muscles as a measure of relative performance; and (3) maximal aerobic power and endurance. The profound sex‐based differences in human performance involving strength, power, speed and endurance, and that are largely attributable to the direct and indirect effects of sex‐steroid hormones, sex chromosomes and epigenetics, provide a scientific rationale and framework for policy decisions on sex‐based categories in sports during puberty and adulthood. Finally, we highlight the sex bias and problem in human performance research of insufficient studies and information on females across many areas of biology and physiology, creating knowledge gaps and opportunities for high‐impact studies. image
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Introduction: In human health and performance development, an interdisciplinary team intends to induce an ergogenic performance effect via manipulating intrinsic performance determinants (e.g., biomotoric qualities) while concomitantly reducing the depressive impact of extrinsic ''stressors'' through delivering sociological-supportive supervision. Unambiguous, quantitatively supported information cultivates avenues in the communicative infrastructure for conveying information between professional team members. Hence, the evident conditional significance of interprofessional communication, especially in establishing performance reports, encouraged the research on a quantitative decision-making model. Methods: A narrative literature review evaluated the sociodemographic characteristics of the high-performance facility attendees and quantitative testing prospects. Subsequently, a feasibility analysis using a modified framework investigated these prospects' viability. Results: The narrative review and feasibility research elucidated a quantitative decision-making tree designed as a catalyst, wherein the model utilises pre-screening, quantitative testing and psycho-sociological data to assign suitable specialists who can tailor the consecutive (training-)interventions. Conclusion: Structuring the acquisition of quantitative testing data cultivates a pathway for interdisciplinary teams to diminish communication noise and optimise their services.
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THE SURPRISING HISTORY OF THE "HRmax=220 -age" EQUATION. Robert A. Robergs, Roberto Landwehr. JEPonline. 2002;5(2):1-10. The estimation of maximal heart rate (HRmax) has been a feature of exercise physiology and related applied sciences since the late 1930's. The estimation of HRmax has been largely based on the formula; HRmax=220-age. This equation is often presented in textbooks without explanation or citation to original research. In addition, the formula and related concepts are included in most certification exams within sports medicine, exercise physiology, and fitness. Despite the acceptance of this formula, research spanning more than two decades reveals the large error inherent in the estimation of HRmax (Sxy=7-11 b/min). Ironically, inquiry into the history of this formula reveals that it was not developed from original research, but resulted from observation based on data from approximately 11 references consisting of published research or unpublished scientific compilations. Consequently, the formula HRmax=220 -age has no scientific merit for use in exercise physiology and related fields. A brief review of alternate HRmax prediction formula reveals that the majority of age -based univariate prediction equations also have large prediction errors (>10 b/min). Clearly, more research of HRmax needs to be done using a multivariate model, and equations may need to be developed that are population (fitness, health status, age, exercise mode) specific.
Book
Since publication of its First Edition in 1981, Exercise Physiology has helped more than 350,000 students build a solid foundation of the scientific principles underlying modern exercise physiology. This Seventh Edition has been thoroughly updated with all the most recent findings, guiding you to the latest understanding of nutrition, energy transfer, and exercise training and their relationship to human performance. This Seventh Edition maintains its popular seven-section structure. It begins with an exploration of the origins of exercise physiology and concludes with an examination of the most recent efforts to apply principles of molecular biology. The book provides excellent coverage of exercise physiology, uniting the topics of energy expenditure and capacity, molecular biology, physical conditioning, sports nutrition, body composition, weight control, and more. Every chapter has been fully revised and updated to reflect the latest information in the field. The updated full-color art program adds visual appeal and improves understanding of key topics. A companion website includes over 30 animations of key exercise physiology concepts; the full text online; a quiz bank; references; appendices; information about microscope technologies; a timeline of notable events in genetics; a list of Nobel Prizes in research related to cell and molecular biology; the scientific contributions of thirteen outstanding female scientists; an image bank; a Brownstone test generator; PowerPoint® lecture outlines; and image-only PowerPoint® slides.
Article
Introduction: If the oxygen pulse (PulmaxO2 = VO(2max)/HR(max), mLO(2 ·beat-1) of Mexican atlhetes practicing diverse sports is caused by sportfit adjustment of different proportion, for both maximal O2 uptake (VO(max)) and maximal heart rate (HR(max)), then we should see significant PulmaxO2 differences among sport speciality groups. Material and methods: Voluntaries were non-athletes (n = 31) and athletes: Karate-Do (n = 8), 400 dash meters (dm) (n = 7), 1,500 dm (n = 13), 5,000 dm (n = 15), 10,000 dm (n = 8), marathon (n = 6), 20 km walking (n = 8), soccer (n = 10) and rowing (n = 8). They all accomplished an increasing ergometric (ramp) test of maximum strength while seated on an electronic cycle-ergometer in an open spirometric system and at 2,240 m of altitude. Results: Both the correlation and the linear regression showed positive relationships between PulmaxO2 and absolute VO(2max) between groups, but they also showed negative relationships between PuimaxO2 and HR(max) in 1,500 dm, 5,000 dm, walking and rowing. The post-hoc (Student-Newman-Keuls) analyses showed similar relative VO(2max) in all sports groups. Non-athletes and marathon runners had the smaller and greater PulmaxO2 respectively. PulmaxO2 differences were found within groups, which were more evident after group rearrangement by absolute VO(max) attributed to different degree of sportier resistance adjustment. Conclusions: PulmaxO2 was more closely related to absolute VO(2max) than to HR(max). PulmaxO2 was a noninvasive indicator of complementary evaluation of the cardiorespiratory function.
Chapter
This chapter reviews the historical record distinguishing the major contributors to the knowledge in this area of the oxygen transport system. The ability to study the oxygen transport system in exercising humans depended on many fundamental discoveries. These began with the isolation of oxygen independently in 1774 by Joseph Priestly (1733-1804) in England and Carl Wilhelm Scheele (1742-1786) in Sweden, the latter named this fraction of the air "fireair." Lavoisier made the first attempt to measure pulmonary gas exchange at rest along with the measurements during exercise. Most of the important intellectual concepts and hypotheses in the understanding of the oxygen transport system and its limitations were proposed by A.L. Lavoisier, E. Smith, N. Zuntz, E.G. Benedict, A. Krogh, G. Liljestrand, A.V. Hill, R. Herbst, H.L. Taylor, S. Robinson, and R.O. Astrand. Subsequent discoveries have solidified these positions and provided better quantification of the important factors or links in the process. In order to reach a more fundamental understanding of the molecular and integrative aspects of the movement of oxygen from inspired air to energy-yielding mitochondria, major contributions still are to be made. Contributions may range from identifying the genes of importance for VO2max and their activation to the very subtle and precise interplay between central nervous factors and reflexes to match and distribute the available cardiac output optimally to active muscle and other central organs at maximal exercise. © 2003 American Physiological Society Published by Elsevier Ltd All rights reserved.
Article
We examined leisure-time physical activities (LTPA) and their contribution to peak oxygen consumption (VO2) in healthy men (N = 619) and women (N = 497) aged 18-95 yr (mean 51 +/- 17) who were participants of the Baltimore Longitudinal study of Aging. Calculations of LTPA were based on the average self-reported time spent performing 97 activities and converted into MET-min x 24 h(-1). The activities were divided into three levels of LTPA based on absolute intensity. Peak VO2 was determined from a maximal treadmill exercise test. Total LTPA was inversely related to age in both sexes (r = -0.26, P < 0.0001 in men and r = -0.23, P < 0.0001 in women), mediated primarily by less high-intensity activities in older subjects, with only minor differences in moderate- and low-intensity activities across age. Peak VO2 correlated positively with LTPA; the correlations were strongest for high-intensity LTPA (r = 0.33 in men and 0.27 in women, each P < 0.0001), intermediate for moderate-intensity activity (r = 0.12, P < 0.004 in men and r = 0.17, P < 0.0001 in women) and minimal for low-intensity activity (r = 0.08, P = 0.05 in men and r = 0.06, P = 0.20 in women). On univariate analysis, total LTPA accounted for 12.9% of peak VO2 variance for men and 10.6% for women. By multivariate analysis, LTPA independently accounted for 1.6% of the peak VO2 variance in men and 1.8% in women after controlling for age and body mass index. In healthy adults across a broad age range, LTPA is a relatively minor independent contributor to aerobic capacity.
Article
Article
Physical fitness in terms of aerobic working capacity was measured in nomadic Lapps living in the northern part of the Scandinavian peninsula. Forty-nine men between 10 and 55 years of age and 21 girls were studied. Aerobic capacity was determined by measuring oxygen consumption during exercise on a bicycle ergometer. Two or three submaximal loads were used. The maximal work lasted three to four minutes, during which time the subjects worked as hard as they could. Blood lactate taken after this heavy run showed that the oxygen requirement exceeded oxygen intake, thus indicating that maximal values for oxygen intake were achieved during this type of exercise. The values for maximal oxygen intake of nomadic Lapps increased steadily from the age of 10 up to 18 years, from an average of 1.4 liters/minute to about 3.5 liters/minute. The latter value remained essentially unchanged up to the age of 30 in men. Maximum oxygen consumption then decreased to about 2.5 liters/minute at 50 years of age. No sex differences in maximum oxygen consumption were noted in subjects below 15 years of age. (Author)