A Comparison between Alpine Skiing, Cross-Country Skiing and Indoor Cycling on Cardiorespiratory and Metabolic Response

Abstract

Since physical inactivity especially prevails during winter months, we set out to identify outdoor alternatives to indoor cycling (IC) by comparing the metabolic and cardiorespiratory responses during alpine skiing (AS), cross-country skiing (XCS) and IC and analyse the effects of sex, age and fitness level in this comparison. Twenty one healthy subjects performed alpine skiing (AS), cross-country skiing (XCS), and IC. Oxygen uptake (VO2), total energy expenditure (EE), heart rate (HR), lactate, blood glucose and rate of perceived exertion (RPE) were determined during three 4-min stages of low, moderate and high intensity. During XCS and IC VO2max and EE were higher than during AS. At least 2½ hours of AS are necessary to reach the same EE as during one hour of XCS or IC. HR, VO2, lactate, and RPEarms were highest during XCS, whereas RPEwhole-body was similar and RPElegs lower than during AS and IC, respectively. Weight adjusted VO2 and EE were higher in men than in women while fitness level had no effect. Male, fit and young participants were able to increase their EE and VO2 values more pronounced. Both AS and XCS can be individually tailored to serve as alternatives to IC and may thus help to overcome the winter activity deficit. XCS was found to be the most effective activity for generating a high EE and VO2 while AS was the most demanding activity for the legs.

Full text

©Journal of Sports Science and Medicine (2016) 15, 184-195
http://www.jssm.org
Received: 10 December 2015 / Accepted: 27 January 2016 / Published (online): 01 March 2016
A Comparison between Alpine Skiing, Cross-Country Skiing and Indoor Cy-
cling on Cardiorespiratory and Metabolic Response
Thomas Stöggl 1

, Christoph Schwarzl 1,2, Edith E. Müller 2,3, Masaru Nagasaki 4, Julia Stöggl 1, Pe-
ter Scheiber 1, Martin Schönfelder 2,3 and Josef Niebauer 2,3
1Department of Sport Science and Kinesiology, University of Salzburg, Hallein/Rif, Austria; 2 University Institute of
Sports Medicine, Prevention and Rehabilitation, Paracelsus Medical University, Salzburg, Austria; 3 Research Institute
of Molecular Sports Medicine and Rehabilitation, Paracelsus Medical University, Salzburg, Austria; 4 Department of
Health Science, Faculty of Psychological and Physical Science, Aichi Gakuin University, Nisshin, Aichi, Japan
Abstract
Since physical inactivity especially prevails during winter
months, we set out to identify outdoor alternatives to indoor
cycling (IC) by comparing the metabolic and cardiorespiratory
responses during alpine skiing (AS), cross-country skiing (XCS)
and IC and analyse the effects of sex, age and fitness level in
this comparison. Twenty one healthy subjects performed alpine
skiing (AS), cross-country skiing (XCS), and IC. Oxygen uptake
(VO2), total energy expenditure (EE), heart rate (HR), lactate,
blood glucose and rate of perceived exertion (RPE) were deter-
mined during three 4-min stages of low, moderate and high
intensity. During XCS and IC VO2max and EE were higher than
during AS. At least 2½ hours of AS are necessary to reach the
same EE as during one hour of XCS or IC. HR, VO2, lactate,
and RPEarms were highest during XCS, whereas RPEwhole-body was
similar and RPElegs lower than during AS and IC, respectively.
Weight adjusted VO2 and EE were higher in men than in women
while fitness level had no effect. Male, fit and young partici-
pants were able to increase their EE and VO2 values more pro-
nounced. Both AS and XCS can be individually tailored to serve
as alternatives to IC and may thus help to overcome the winter
activity deficit. XCS was found to be the most effective activity
for generating a high EE and VO2 while AS was the most de-
manding activity for the legs.
Key words: Borg, blood lactate, cross-country skiing, cycling,
energy expenditure, fitness level, oxygen uptake, gender.
Introduction
During the winter season the frequency of participating in
physical activity and the total daily energy expenditure
has been shown to be reduced when compared with the
summer months (Dannenberg et al., 1989, Merchant et al.,
2007). Furthermore, blood pressure, cholesterol and body
mass index tend to increase in all age groups and both
sexes during winter months, leading to an increasing risk
of chronic coronary disease and cardiac events (Ulmer et
al., 2004). Physical inactivity is one of the main modifia-
ble risk factors of cardiovascular diseases and has been
reported to be as deleterious as tobacco smoking (Mendis
et al., 2011). Therefore, there is a need to identify modes
of exercise and sports that are attractive to the wider pop-
ulation with the potential to maintain if not even increase
physical fitness during winter.
Indoor cycling (IC) might be regarded as the gold
standard for physical training with no seasonal limitations
and its feasibility for different target groups, i.e. those
without access to mountains and snow or injuries and
chronic disease that preclude them from participation in
winter sports. Alpine and Nordic sports have a long stand-
ing tradition in alpine and Scandinavian countries. More
than one third of all Austrians (~7.6 Million in the year
1986) think that alpine skiing (AS) is the best way to
experience nature and freedom in the winter months
(Bachleitner, 1998). AS has become the most popular
winter sport world-wide, with more than eight million
skiers visiting Austria each year (Burtscher et al., 2000).
Alpine skiing is a leisure sport where gravity is the driv-
ing force and the work needed to raise the potential ener-
gy for the next downhill is provided by the chairlift not
the skier as i.e. during alpine touring skiing or cross-
country skiing (XCS). It is open to debate whether AS
might provide sufficient cardiovascular and metabolic
stimuli to achieve fitness gains. In the past few years,
recent investigations have shown that AS is a suitable and
safe recreational sport for an elderly and sedentary popu-
lation (Kahn et al., 1993; Krautgasser et al., 2011; Müller
et al., 2011; Pötzelsberger et al., 2015; Scheiber et al.,
2009; 2012). However, Karlsson et al. (1978) listed some
limitations for recreational skiers not being able to reach
high intensities during skiing due to poor technique and
strength when compared with professional skiers. While
there are several studies that discuss the physiological
response during XCS in general (e.g. Mygind et al., 1991,
Mognoni et al., 2001, Welde et al., 2003, Larsson and
Henriksson-Larsen, 2008), research about the effects of
fitness level on physiological response during XCS or IC
is missing.
Cross-country skiing can be regarded as the gold
standard winter time aerobic exercise mode, with a high
percentage of muscles in the whole body being activated
(Rusko, 2008, Björklund et al., 2015, Stöggl et al., 2013,
Björklund et al., 2010), and the highest VO2max values
among all sports being measured in world class XCS
athletes (Holmberg et al., 2007, Rusko, 2008, Saltin and
Astrand, 1967). It is not known if AS can be used as an
alternative to XCS and/or IC to fill the winter gap of
physical activity and provide an alternative to indoor
training.
There are many studies that have analyzed the
physiological responses of AS, XCS and IC separately
Research article

Stöggl et al.
185
(e.g., Bergh, 1982; Hoffman, 1992; Holmberg, 2005;
Impellizzeri and Marcora, 2007; Mujika and Padilla,
2001; Kahn et al., 1993; Krautgasser et al., 2011; Müller
et al., 2011; Pötzelsberger et al., 2015; Scheiber et al.,
2009; Vogt et al., 2005). However to the best of our
knowledge, no direct comparisons within the same sub-
jects were done while performing AS, XCS as well as IC.
In addition, most of the previous studies included well-
trained if not elite athletes, which is not representative of
the common population. Furthermore, data about energy
expenditure (EE) and MET values during AS are solely
provided during the downhill phase (Ainsworth et al.,
2011, Vogt et al., 2005) representing not a measure with
sufficient external validity based on recovery periods
while standing in line, taking a lift and short breaks dur-
ing skiing of up to 67% of total skiing time (Müller et al.,
2011). And lastly, sex, fitness and age aspects were large-
ly neglected; and interactions of the above mentioned
factors with exercise intensity and exercise mode (here IC
vs. XCS vs. AS) are missing. Recently we have provided
a first outline about the cardiorespiratory and metabolic
response with AS, XCS and IC (Stöggl et al., 2015), how-
ever the detailed effects of exercise intensity, sex, age,
fitness level and its interactions are open to be discussed.
Therefore, in the current study we set out to 1) compare
the metabolic and cardiorespiratory responses as well as
rates of perceived exertion during AS to XCS and IC, 2)
analyze the effects of gender, age and fitness level and its
interaction with exercise intensity and exercise mode in
this comparison, and 3) translate the duration of an AS
session into isocaloric training sessions of XCS and IC.
Methods
Participants
Twenty-one volunteers were selected and included in this
study according to the following criteria: written informed
consent; >30 years; no abnormalities in the electrocardio-
gram (ECG); non-smoker for at least one year; proficien-
cy in AS and XCS (>10 days of AS and XCS per season);
no medical conditions which would conflict with partici-
pation in maximal indoor and outdoor exercise tests; no
intake of anticoagulants including aspirin; no alcohol or
drug abuse; and no severe obesity (BMI>40). Partici-
pants’ characteristics are presented in Table 1. Partici-
pants were stratified according to age (two age groups
delineated by the median in age; Young: n = 11, age = 38
± 4 yrs; Old: n = 10, age = 60 ± 6 yrs), fitness level (two
levels according to relative VO2max; Fit: n = 11, age = 40
± 7 yrs, VO2ma x = 49.2 ± 10.8 ml∙kg-1∙min-1; Unfit: n = 10,
age = 54 ± 12 yrs, VO2max = 29.3 ± 7.8 ml∙kg-1∙min-1) and
sex. The study received approval from the Ethical Com-
mittee and was conducted in accordance with the Declara-
tion of Helsinki. This study is registered and published at
ClinicalTrials.gov: NCT02082106.
Overall design
The study was carried out during the winter months from
January to March. Following the recruiting process every
participant underwent a complete medical examination
and a cycle ergometry ramp protocol until volitional ex-
haustion, all completed by a physician. Those who met all
inclusion criteria performed an AS, XCS, and IC session
in randomized order on three separate days with a mini-
mum of 48 hours in between. During each session oxygen
uptake (VO2), heart rate (HR), blood lactate, rating of
perceived exertion (RPE, BORG scale: 6-20) for the
whole body (RPEwhole-body), legs only (RPEle gs) and arms
only (RPEa rms), and kinematic data of skiing (velocities,
altitude meters, covered distances) were recorded. Each
session commenced with a 10-min rest period, followed
by 5 min of warm-up, three 4-min stages of low (LOW),
moderate (MOD) and high (HIGH) intensity and a 10-min
resting period at the end of HIGH for determination of
excess post exercise O2 consumption (EPOC). For stand-
ardization purposes food intake was not permitted 4 h
prior to testing, and participants were instructed not to
change their diet and amount of physical activity through-
out the examination period.
Baseline medical examination and VO2max ramp test
Baseline examinations (see Table 1) included completion
of two questionnaires about physical activity (IPAQ) and
training/competition history, routine blood analysis in a
fasting state, determination of body mass, lung function
testing (EasyOne, Medizintechnik, Switzerland), and an
incremental cycling ergometry to volitional exhaustion
(Ergoselect 200, Ergoline GmbH, Bitz, Germany) to as-
sess maximal power output (Pmax), VO2max , HRmax and
peak lactate. The testing protocol was adapted to sex and
estimated physical fitness: for females, start: 50 W; in-
crement: 15 W every 1 min; for unfit males, start: 50 W;
increment: 20 W every 1 min; and for fit males, start: 50
W; increment: 25 W every 1 min (categorization for fit or
unfit was based on the questionnaire data). HR (12-lead-
ECG stress test system; Amedtec, Aue, Germany) and
breath-by-breath spirometric data (MasterScreen CPX,
Carl Reiner GmbH, Wien, Austria) were recorded contin-
uously. The flow of the turbine was measured with the
integrated automatic volume calibration program of the
ergospirometry system. Gas calibration was performed
with the automatic gas analyzer calibration procedure
using standardized oxygen (16.00 vol %) and carbon
dioxide (5.01 vol %) concentrations (rest volume: nitro-
gen). Both calibration procedures were performed directly
before each test. A 15 s moving average was used for all
cardiorespiratory data. Lactate as well as blood pressure
was measured every two minutes, as well as three and
five minutes after the completion of the test. For lactate
analysis, a 20 µl blood sample from the earlobe was col-
lected immediately after each second increment and quan-
tified amperometric-enzymatically (Biosen S-Line Lab+,
EKF-diagnostic GmbH, Magdeburg, Germany). The
lactate sensor was calibrated before each test using a
lactate standard sample of 12 mmol∙L-1. Results within a
range of ±0.1 mmol∙L-1 were accepted.
Outdoor trials
Participants’ HR and GPS data (distance, skiing speed
and altitude) were recorded by telemetry (Suunto Ambit
2.0, Helsinki, Finland) sampling at 1-s intervals. For alti-
tude calculations automated barometric measurements

Alpine skiing counteracts activity deficit
186
and GPS data were used. VO2 was continuously recorded
by a portable breath-by-breath spirometer (K4b2, Cos-
med, Rome, Italy). For determination of lactate and blood
glucose (see above) a sample was collected immediately
after each intensity stage, as well as three, five and 10
minutes after the completion of the HIGH intensity stage
during the EPOC phase.
Alpine skiing trials
Alpine skiing trials were performed on a slope with suffi-
cient width (~50 m) and homogenous grade, allowing
steady skiing of 4 min (~1.6 km with ~490 m altitude
change, 17-18° grade). Each intensity trial was done in
one separate descent. For LOW, the parallel ski steering
(PSS) technique was used which is characterized by slid-
ing on the ski-edges during each swing while skis are
being kept in parallel position. For MOD, carving with
long radii (CLR) was performed where the skier carves on
the ski-edges avoiding skidding, trying to ski a full 180°
curve each swing. HIGH was done using short turn skiing
(ST) which is characterized by short but highly frequent
turns at low skiing radii and using high dynamic whole
body motion (up- down motion of the center of mass
partly leading to a jump in between swings). For standard-
ization all downhill trials were instructor paced, by a
board certified Austrian alpine skiing instructor who
adapted the skiing speeds to the skill level of the partici-
pant (Figure 1A).
XCS trials
XCS sessions were performed on a 450 m-loop with a
total altitude change of 6 m. All participants used the
classical technique (mainly the diagonal stride in the
skiers with lower fitness level, and according to the track
topography a mix of diagonal stride, kick double poling
and double poling in the fit skiers) and their own equip-
ment. Following a 5-min warm-up at 60% HRmax, 4-min
stages with LOW (70% HRma x), MOD (80% HRmax) and
HIGH (90% HRmax) intensity with 2-min of active recov-
ery at 60% HRmax in between stages were performed.
Heart rate was monitored by a Suunto Ambit 2.0 monitor
in paired fashion (i.e. HR belt worn by participant; HR
monitors worn both by the participant and examiner) and
verbally communicated by the examiner who was skiing
right next to the participant (Figure 1B).
Indoor cycling ergometry sessions
Indoor cycling sessions were conducted on indoor cycle
ergometers (Ergoselect 200, Ergoline GmbH, Bitz, Ger-
many) following the same protocol as in XCS regarding
stage duration and HR controlled exercise intensity.
Parameter calculations
During the ramp test Pmax was calculated by linear inter-
polation using the formula: Pmax = Pf + ((t/60)·ΔP), where
Pf was the power output during the last workload com-
pleted, t the duration of this last workload (s) and ΔP the
difference in power output during the last two workloads
(Kuipers et al., 1985). The breath-by-breath values of the
VO2 measurements were converted into a 1 Hz signal by
linear interpolation. Furthermore, all cardiorespiratory
data were smoothed by application of a 15 s moving aver-
age. Based on this smoothed data the mean and peak
values over the single 4-min stages were calculated. The
steady state values were based on the mean over 30 s
prior to the end of each stage. The EPOC phase after
HIGH consisted of 2 min low intensity activity (cycling at
60% HRmax, or walking to the shelter with a seat during
AS and XCS) and 8 min sitting in an upright position with
no talking being allowed. Energy expenditure (EE) was
determined for each 4-min stage and also estimated for a
1-hr session based on the steady state values. The formula
of Weir (1949) EE (kcal∙day-1) = [(3.9·VO2 + 1.1·VCO2) ·
1440], approximating a caloric equivalent of 21.1 kJ per L
O2 was used. To get the EE values for the 4-min stages,
the 1 Hz values (kcal∙day-1) were converted to kcal∙s-1 and
then integrated over the 4-min. All these calculations
were performed using the Ikemaster Software (IKE-
Software Solutions, Salzburg, Austria).
Statistical analysis
All data exhibited a Gaussian distribution verified by the
Shapiro-Wilk’s test and, accordingly, the values are pre-
sented as means (± SE). Repeated-measures ANOVAs
(with 3 exercise modes and 3 intensities as repeated
measures, and 2 sex; 2 fitness level, 2 age groups as
Figure 1. Illustration of the A) AS trials with the participant following the alpine skiing instructor and B) XCS trials where
the examiner skies right next to the participant, monitoring and verbally communicating the participant’s HR (HR monitors
worn both by the participant and examiner) for intensity control.

Stöggl et al.
187
Table 1. Characteristics of participants without dropouts at baseline examination. Data are means (±SE).
Overall (n = 19)
Male (n = 12)
Female (n = 7)
Age (years)
47.6 (12.4)
46.9 (12.0)
48.9 (13.9)
Weight (kg)
80.9 (14.5)
85.3 (12.4)
73.2 (15.6)
Height (m)
1.76 (.09)
1.80 (.07)
1.68 (.08)
BMI (kg∙m-²)
26.2 (4.5)
26.3 (3.5)
26.1 (6.2)
Pmax (W)
252.5 (93.7)
299.3 (82.9)
172.3 (43.1)
relPmax (W∙kg-1)
3.2 (1.2)
3.6 (1.2)
2.5 (.9)
HRmax (bpm)
172 (17)
171 (18)
173 (16)
VO2max (ml∙kg-1∙min-1)
39.5 (12.9)
44.2 (12.3)
31.5 (10.3)
FEV1 (L)
3.7 (.9)
4.2 (.5)
2.9 (.8)
FEV1/FVC (%)
76.7 (6.3)
78.7 (5.3)
73.4 (6.9)
HDL (mg∙dL-1)
75.4 (22.7)
67.2 (19.7)
89.6 (21.5)
LDL (mg∙dL-1)
118.2 (31.0)
122.3 (24.8)
111.0 (40.8)
CHOL (mg∙dL-1)
218.2 (40.7)
218.6 (22.8)
217.6 (63.5)
CK (U∙L-1)
157.3 (105.8)
175.8 (106.1)
125.4 (105.2)
BMI, body mass index; HRmax, maximal heart rate; Pmax, maximal power output; relPmax, relative maximal
power output (per kg body weight); VO2max, relative maximal oxygen consumption (per kg body weight);
FEV1, forced expiratory volume in the first second; CHOL, cholesterin; CK, creatinekinase; FVC, forced
vital capacity; L/HDL, low/high density lipoprotein.
independent measures) were performed to test for main
effects of sex, fitness level, age, exercise modes (IC, AS,
XCS) and intensities (LOW, MOD, HIGH) as well as
interactions between these factors. Following the identifi-
cation of a significant main effect and/or interaction effect
for exercise mode or intensity a one-way repeated-
measures ANOVA with Bonferroni post hoc analysis
were applied. An alpha value of < 0.05 was considered
significant. The Statistical Package for the Social Scienc-
es (Version 22.0; SPSS Inc., Chicago, IL, USA) and Of-
fice Excel 2010 (Microsoft Corporation, Redmond, WA,
USA) were used.
Results
Patient characteristics (Table 1)
Of the 21 screened volunteers two had to be excluded
during the initial medical examination, one due to uncon-
trolled type 2 diabetes mellitus and one because of signs
of myocardial ischemia during exercise stress testing (n =
19).
Characterization of AS and XCS trials
During AS 4-min trials at LOW, MOD and HIGH intensi-
ty participants skied a distance of 1.57 ± 0.07, 1.60 ±
0.10 and 1.26 ± 0.05 km (F2,17 = 35, p < 0.001), with an
altitude change of 384 ± 20, 380 ± 29 and 350 ± 19 m
(F2,17 = 9.0, p = 0.002), a vertical speed of 96 ± 5, 95 ± 7
and 87 ± 5 m∙min-1 (F2,17 = 8.6, p = 0.003), a mean skiing
speed of 24.0 ± 1.0, 27.7 ± 1.7 and 21.1 ± 0.8 km∙h-1 (F2,17
= 25, p < 0.001) and a peak skiing speed of 33.7 ± 1.6,
38.4 ± 2.0 and 28.5 ± 1.0 km∙h-1 (F2,17 = 34, p < 0.001).
Skiing time for each ride including skiing from the top of
the chairlift to the start of the measuring site, and from the
end of the 4-min stage to the bottom of the chairlift was
7:02 ± 1:46 min. Mean time for waiting in line and sitting
on the chairlift was 8:57 ± 1:46 min. Active skiing time
was 44 ± 5%. For XCS during the 4-min trials at LOW,
MOD and HIGH intensity participants skied a distance of
0.55 ± 0.05, 0.63 ± 0.06 and 0.73 ± 0.07 km (F2,17 = 45, p
< 0.001), with an altitude change of 11 ± 1, 12 ± 1 and 13
± 2 m (F2,17 = 0.2, p = 0.814) and a mean skiing speed of
8.3 ± 0.8, 9.6 ± 0.9 and 11.0 ± 1.0 km∙h-1 (F2,17 = 37, p <
0.001). Break time in between trials was 2:15 ± 0:10 min.
Main effects exercise mode (Table 2)
When data for LOW, MOD, and HIGH were pooled with-
in each mode of exercise (i.e. AS, XCS, and IC), with the
exception of RPEwhole-body and relative lactate (% peak
lactate) all variables demonstrated significant differences
between AS, XCS and IC (Table 2). For the absolute VO2
values, AS resulted in lower values compared with XCS
(all p < 0.001) and IC (p = 0.047 to 0.006), with no differ-
ence between XCS and IC. VO2peak in percent of VO2max
demonstrated lowest values for AS (XCS: p < 0.001; IC:
p = 0.070), followed by IC (XCS: p = 0.027), and XCS.
Mean respiratory exchange ratio (RER) was higher in
XCS compared with IC (p = 0.005) and AS (p = 0.001).
Regarding HR parameters (peak and %HRmax), IC
demonstrated lower values compared with XCS (p <
0.001) and AS (p = 0.031 to p = 0.029). RPEwhole-body was
not different between exercise modes, while RPEarms was
higher in XCS compared with both IC and AS (both p <
0.001). RPElegs was greatest in AS followed by IC (p = 0
.023) and XCS (p < 0.001 to both). EE was lower in AS
compared with IC (p = 0.011 to 0.006) and XCS (p <
0.001) with no difference between the latter two. In AS,
when considering the time for standing in line and sitting
on the chair lift, the value would decrease to 279 ± 16
kcal∙h-1. An AS duration of approximately 2:37, respec-
tively 2:25 hrs, would be necessary to achieve comparable
EE of 1 h of XCS or IC (Figure 2). There was a trend
towards lower lactate values during AS compared with
XCS (p = 0.072), while no difference was found when
compared with IC. EPOC expressed in liter O2 or energy
expenditure in kcal was lower in AS compared with XCS
(p = 0.017 or < 0.001) and IC (p = 0.004 or p = 0.001)
with no difference between the two latter.
During each mode of exercise, all measured meta-
bolic and cardiorespiratory parameters increased with
intensity (blood glucose: p = 0.006, all other parameters p
< 0.001). Blood glucose was unchanged between LOW
and MOD (4.74 ± 0.08 vs. 4.74 ± 0.10 mmol∙L-1) but was

Alpine skiing counteracts activity deficit
188
Table 2. Cardiorespiratory and metabolic parameters for the pooled data during alpine skiing (AS), cross-country skiing
(XCS) and indoor cycling (IC) (n = 19). Data are means (±SE).
Exercise Mode
ANOVA
AS
XCS
IC
(F-value, p-value)
HRpeak (bpm)
151 (3)
153 (2)
143 (3) *
F2,11=13, p=.001
Rel. HRpeak (% HRma x)
87 (2)
88 (1)
82 (1) *
F2,11=11, p=.003
Blood lactate (mmol∙L-1)
3.2 (.2)
4.2 (.5)
3.7 (.3)
F2,11=4.0, p=.049
Rel. lactate (% peak lactate)
39 (3)
48 (6)
44 (4)
NS
Blood glucose (mmol∙L-1)
4.7 (.1)
5.0 (.1)
4.7 (.1)
NS
RERmean
.98 (.02)
1.07 (.03) *
.95 (.01)
F2,8=14, p=.003
VO2peak (ml∙kg-1∙min-1)
28.2 (.9) *
34.5 (1.2) *
31.8 (.9) *
F2,8=13, p=.003
VO2steadystate (ml∙kg-1∙min-1)
24.1 (.7) *
29.6 (1.1)
28.4 (.8)
F2,8=11, p=.005
Rel. VO2p eak (%VO2max)
74 (3)
89 (3) *
82 (4)
F2,8=21, p=.001
EEsteady state (kcal∙h-1)
584 (25) *
729 (30)
679 (31)
F2,8=10, p=.006
EE4 min (kcal)
35.8 (1.4) *
45.6 (1.8)
43.0 (2.0)
F2,8=13, p=.003
RPEwhole-body
12.4 (.5)
12.2 (.3)
12.8 (.3)
NS
RPEarms
9.3 (.5)
11.6 (.5) *
9.3 (.5)
F2,11=17, p<.001
RPElegs
15.1 (.5) *
10.7 (.4) *
13.4 (.2) *
F2,11=37, p<.001
EPOC (L O2 ∙10 min-1)
3.6 (.3) *
5.3 (.3)
5.8 (.2)
F2,11=13, p=.001
EPOC EE (kcal ∙10 min-1)
32.8(1.5) *
44.4 (1.7)
45.2 (1.4)
F2,11=11, p=.003
HR, heart rate; RER, respiratory exchange ratio; VO2, oxygen uptake; EE, energy expenditure; EEsteady_state, estimated energy expenditure
over one hour based on the EE during the last minute of each intensity stage; EE4min , exact energy expenditure during each of the 4-min
stages; EPOC, excess post exercise oxygen consumption; *, different to all other exercise modes; NS, not significant.
Figure 2. Estimated skiing time needed with alpine skiing
(AS) to be isocaloric towards 1 hr cross-country skiing
(XCS) or indoor cycling (IC) at low intensity (LOW), mod-
erate intensity (MOD) and high intensity (HIGH).
increased at HIGH (4.91 ± 0.11 mmol∙L-1) compared with
LOW (p = 0.012) and MOD (p = 0.010) (Table 3).
Effects of sex, age and fitness level (Table 4)
Pooled data for all three intensities and three exercise
modes for sex, age and fitness level are presented in Table
4. Male participants revealed higher VO2, EE and EPOC
(all p < 0.001). Both absolute and relative HR were lower
in men (p < 0.05). No sex differences were found for
relative VO2 (% VO2max), RER, RPE, lactate and blood
glucose (all p > 0.05). The younger participants demon-
strated higher absolute VO2 (p < 0.01), absolute HR (p <
0.01), EE (p < 0.05) and EPOC (p < 0.05) than the older
participants with no further differences in the other meas-
ured parameters. Compared to the unfit, the fit partici-
pants had higher absolute VO2 (p < 0.001) and RPElegs (p
= 0.022). Additionally, relative HR (%HRmax) and relative
lactate (%peak lactate) were reduced in the fit group (all p
< 0.05).
Interaction effects
The interaction between exercise mode x fitness level was
significant for RPEwhole-body (p = 0.004), RPEarms (p =
0.030) and RPElegs (p = 0.015). For both RPEwhole-body and
RPElegs equal values for fit and unfit were found for IC
while during XCS and AS the fit had higher values. For
RPEarms equal levels between fit and unfit were found
during IC and AS while the fit revealed increased values
during XCS.
Interaction effects between fitness level x exercise
intensity, sex x exercise intensity and age x exercise in-
tensity were found for absolute VO2 (p = 0.002 to 0.026),
and EE (p = 0.004 to 0.025) demonstrating a more pro-
nounced increase in the fit, respectively male and young
participants when intensity was increased when compared
with the unfit, respectively female and older participants
(see Figure 3A-C).
Among all measured parameters, interactions be-
tween exercise mode x exercise intensity were found only
for blood glucose (p = 0.029, Figure 3D), lactate (p =
0.033) and RER (p = 0.020) demonstrating a more pro-
nounced increase with a greater exercise increase during
XCS compared with IC and AS.
Discussion
The main findings of our study are: 1) XCS and IC are
generally more demanding for the cardiorespiratory sys-
tem than AS, i.e. VO2 and EE are higher; 2) This might be
partially due to the high levels of RPElegs during AS,
which might result in an attenuated increase in cardi-
orespiratory output based on muscular limitations as
compared to XCS and IC; 3) with XCS, even though VO2,
HR and lactate were higher compared to both or at least
one of the exercise modes IC and AS, RPEwhole-body was
equal and RPElegs lower compared with AS and IC; 4)
RPEarms was only high during XCS and was also paral-
leled by increased blood glucose and lactate levels during
the high intensity trial compared with the other exercises;
5) absolute and relative (% body weight) values of VO2,
EE and EPOC were higher in men; 6) unfit had higher
relative lactate levels (% peak lactate), lower VO2 but

Stöggle et al. 189
Table 3. Cardiorespiratory and metabolic parameters during alpine skiing (AS), cross-country skiing (XCS) and indoor cycling (IC) at low (70%HRmax), moderate (80% HRmax) and high
(90% HRmax) intensity (n =19). Data are means (±SE).
AS
XCS
IC
ANOVA (F-value, p-value)
Low
Mod
High
Low
Mod
High
Low
Mod
High
Modea
Intensityb
HRpeak (bpm)
138 (4)*
154 (4)
162 (3)
137 (2)*
152 (2)
170 (2)
124 (3)*
142 (3)
161 (3)
F2,11=13, p=.001
F2,11=262, p <.001
Rel. HRpeak (% HRma x)
79 (2)*
88 (2)
93 (2)
79 (1)*
87 (1)
98 (1)
71 (1)*
82 (1)
92 (1)
F2,11=11, p=.003
F2,11=240, p<.001
Blood lactate (mmol∙L-1)
1.8 (.2)*
3.3 (.2)
4.6 (.5)
2.4 (.3)*
3.5 (.5)
6.6 (.6)
1.9 (.2)*
3.3 (.3)
6.0 (.5)
F2,11=4.0, p=.049
F2,11=51, p<.001
Rel. lactate (% peak lactate)
23 (3)*
37 (2)
57 (7)
28 (4)*
40 (7)
76 (7)
22 (3)*
39 (4)
71 (8)
NS
F2,11=50, p<.001
Blood glucose (mmol∙L-1)
4.8 (.1)
4.8 (.1)
5.3 (.2)
4.6 (.1)
4.7 (.1)
4.8 (.1)*
4.8 (.1)
4.7 (.2)
4.6 (.2)
NS
F2,11=14, p=.006
RERmean
.91 (.02)*
.95 (.01)
.98 (.02)
1.02 (.03)
1.05 (.03)
1.14 (.03)*
.92 (.02)
1.00 (.03)
1.00 (.03)
F2,8=14, p=.003
F2,8=14, P=.001
VO2peak (ml∙kg-1∙min-1)
23.7 (.9)*
28.6 (1.1)
32.4 (1.2)
32.4 (1.1)*
34.6 (1.4)
36.4 (1.5)
27.1 (.8*)
31.7 (.9)
36.7 (1.3)
F2,8=13, p=.003
F2,8=47, p<.001
VO2steadystate (ml∙kg-1∙min-1)
19.0 (.5)*
24.1 (.9)
29.1 (1.1)
26.6 (1.0)*
29.8 (1.1)
32.4 (1.2)
23.7 (.8)*
28.3 (.8)
33.1 (1.0)
F2,8=11, p=.005
F2,8=67, p<.001
Rel. VO2pea k %VO2max
64 (3)*
74 (4)
84 (4)
84 (4)*
89 (3)
94 (3)
70 (4)*
82 (4)
94 (3)
F2,8=21, p=.001
F2,8=42, p<.001
EEsteady state (kcal∙h-1)
448 (21)*
590 (32)
713 (32)
644 (29)*
731 (29)
813 (33)
558 (28)*
677 (30)
803 (37)
F2,8=10, p=.006
F2,8=71, p<.001
EE4 min (kcal)
27.9 (1.1)*
35.6 (1.8)
44.0 (1.8)
40.3 (2.0)*
45.6 (1.7)
51.0 (2.0)
36.2 (1.8)*
42.8 (2.0)
50.1 (2.3)
F2,8=13, p=.003
F2,8=86, p<.001
RPEwhole-body
9.8 (.6)*
12.3 (.6)
14.9 (.6)
9.3 (.4)*
11.7 (.4)
15.6 (.4)
10.5 (.5)*
13.0 (.2)
15.0 (.4)
NS
F2,11=93, p<.001
RPEarms
7.9 (.5)*
9.4 (.5)
10.5 (.8)
9.2 (.4)*
11.1 (.6)
14.4 (.6)
7.9 (.6)*
9.0 (.5)
11.0 (.8)
F2,11=17, p<.001
F2,11=44, p<.001
RPElegs
12.6 (.5)*
16.1 (.6)
16.8 (.6)
8.8 (.4)*
10.2 (.5)
13.0 (.5)
11.1 (.3)*
13.6 (.3)
15.5 (.5)
F2,11=37, p<.001
F2,11=106, p<.001
HR, heart rate; RER, respiratory exchange ratio; VO2, oxygen uptake; EE, energy expenditure; EEsteady_state, estimated energy expenditure over one hour based on the EE during the last minute of each intensity stage; EE4min,
exact energy expenditure during each of the 4-min stages; RPE, rate of perceived exertion.
a main effect of exercise mode. b main effect of intensity. *significantly different to the two other intensities in the same exercise mode. NS, not significant.
Table 4. Cardiorespiratory and metabolic parameters for the pooled data during alpine skiing (AS), cross-country skiing (XCS) and indoor cycling (IC) for male (n=12) vs. fe-
male (n=7), young (n=10) vs. old (n=9), and fit (n=10) vs. unfit (n=9). Data are means (±SE).
Gender
Age
Fitness Level
ANOVA (p-value)
Male
Female
Young
Old
Fit
Unfit
Gender
Age
Fitness
HRpeak (bpm)
145 (3)
155 (4)
156 (3)
139 (3)
149 (3)
149 (3)
p=.042
p=.002
NS
Rel. HRpeak (% HRma x)
84 (1)
88 (1)
85 (1)
87 (1)
83 (1)
87 (1)
p=.023
NS
p=.021
Blood lactate (mmol∙L-1)
4.2 (.3)
3.1 (.5)
3.7 (.4)
3.7 (.4)
3.2 (.4)
4.1 (.4)
NS
NS
NS
Rel. lactate (% peak lactate)
45 (4)
42 (6)
38 (5)
51 (5)
32 (5)
52 (5)
NS
NS
p=.015
RERmean
1.00 (.02)
.99 (.02)
.97 (.02)
1.02 (.02)
.97 (.02)
1.03 (.02)
NS
NS
NS
VO2peak (ml∙kg-1∙min-1)
34.3 (1.1)
25.9 (1.3)
34.3 (1.1)
28.7 (1.2)
36.0 (1.3)
27.0 (1.0)
p=.001
p=.009
p<.001
VO2steadystate (ml∙kg-1∙min-1)
29.8 (.9)
22.4 (1.1)
29.8 (.9)
22.4 (1.1)
29.8 (.9)
22.4 (1.1)
p<.001
p<.001
p<.001
Rel. VO2p eak %VO2max
80 (4)
86 (5)
85 (4)
79 (4)
79 (5)
84 (4)
NS
NS
NS
EEsteady state (kcal∙h-1)
758 (30)
477 (39)
717 (32)
611 (35)
695 (38)
634 (29)
p<.001
NS
NS
EE4 min (kcal)
51.5 (2.2)
35.1 (3.3)
44.8 (2.0)
38.2 (2.1)
43.4 (2.3)
39.5 (1.8)
p=.002
p=.049
NS
RPEwhole-body
12.9 (.3)
11.9 (.5)
12.2 (.4)
12.8 (.4)
13.0 (.4)
12.1 (.4)
NS
NS
NS
RPEarms
10.5 (.5)
9.4 (.7)
9.5 (.6)
10.8 (.6)
10.4 (.6)
9.8 (.6)
NS
NS
NS
RPElegs
13.5 (.3)
12.5 (.4)
13.0 (.4)
13.2 (.3)
13.8 (.3)
12.5 (.4)
NS
NS
p=.022
HR, heart rate; RER, respiratory exchange ratio; VO2, oxygen uptake; EE, energy expenditure; EEsteady_state, estimated energy expenditure over one hour based on the EE dur-
ing the last minute of each intensity stage; EE4min, exact energy expenditure during each of the 4-min stages; NS, not significant.

190 Alpine skiing counteracts activity deficit
Figure 3. Interaction between A) fitness level and exercise intensity, B) sex and exercise intensity, C) age and exercise intensi-
ty and D) exercise mode (XCS, cross-country skiing; IC, indoor cycling; AS, alpine skiing) and exercise intensity [low intensi-
ty (LOW), moderate intensity (MOD) and high intensity (HIGH)] with regards to energy expenditure during the 4-min trials.
equal EE values, 7) younger participants demonstrated
higher VO2, HR, EE and EPOC at similar relative HR (%
HRmax), and 8) young, fit and male participants were able
to increase their EE and VO2 more pronounced compared
with their old, unfit and female counterparts.
Energy expenditure and cardiorespiratory parameters
In the current study, VO2 and EE were similar during
XCS and IC, but significantly higher than during AS.
Also, VO2 and EE during AS-HIGH compared well to
XCS-MOD and IC-MOD, while AS-MOD was compara-
ble to XCS-LOW and IC-LOW. However, this calculation
is just valid when estimating the EE per hr based on the 4-
min active skiing interval and neglecting the recovery
period while standing in line or taking a lift. Müller et al.
(2011) demonstrated that this systematic change from
relatively high load (~73% HRmax ~7 min) followed by a
pronounced recovery (~59% HRmax, ~13 min) happens
between 9-10 times during a ski day. Therefore, a 3.5 hrs
ski day consists of 68 min skiing (33%), 120 min recov-
ery time (56%) and 23 min rest or extended recovery
(11%). In this study, active skiing time was slightly high-
er with 44 ± 5%. Based on this data, to achieve equal EE
at the three different intensities during AS compared with
one hour of XCS or IC, AS (including both active and
recovery time) has to be performed 2:37 and 2:25 hrs,
respectively.
In the literature, there is little data available on EE
during AS, XCS and IC in elite athletes, let alone leisure
time skiers. Jeukendrup and Gleeson (2010) reported
estimated energy cost for AS in relation to body weight
(50 - 90 kg) of 270 – 500 kcal∙h-1 for low intensity down-
hill skiing and 440 - 828 kcal∙h-1 for high intensity down-
hill skiing. Therefore, based on the current studies results,
by using a skiing style like CLR and ST continuously
over 4 min, EE values comparable or even higher as dur-
ing racing might be achieved.
In our study, relative HR (%HRmax) during AS
were 79%, 88% and 93% for PSS, CLR and ST, and thus
higher than those also documented in elderly skiers by
Scheiber et al. (2009) and Müller et al. (2011). Müller et
al. (2011) reported mean HR values during the active
skiing time of 73% HRmax and Scheiber et al. (2009) val-
ues of 62-68% and 69-75% during PSS and CLR on be-
ginner slopes, and 70-76% and 80-81% during PSS and
CLR on steeper slopes. Furthermore, in the study by
Scheiber et al. (2009) mean VO2 values ranged from
approximately 13-19 ml∙kg-1∙min-1 across all analyzed
skiing situations with significantly higher values for CLR
(13-17 ml∙kg-1∙min-1) compared to PSS (16-19 ml∙ kg-
1∙min-1). Those values compare well with the current
study demonstrating increased VO2 values with CLR
compared with PSS (23.7 vs. 28.6 ml∙kg-1∙min-1). In addi-
tion, it was demonstrated that by skiing with ST even a
further increase in VO2 up to 32.4 ml∙kg-1∙min-1 was pos-
sible. As with HR values, %VO2 max of 64-84% were dis-
tinctly higher compared to the study by Scheiber et al.
(2009) who demonstrated values of 38-42% and 45-49 %

Stöggl et al.
191
for PSS and CLR on beginner slopes, and 42-46% and 50-
52% during PSS and CLR on steeper slopes. Therefore, in
the current study, continuous skiing over 4 min with dif-
ferent intensities posed a greater physiological challenge.
This might be attributed to the more dynamic skiing dur-
ing CLR and ST and the younger participants (47.6 vs.
62.2 yrs) compared with the study by Scheiber et al.
(2009). Also, during AS racing, %VO2 max were docu-
mented to be between 68-88% (Vogt et al., 2005,
Karlsson et al., 1978). Therefore, ST constitutes compa-
rable loading as compared with AS racing.
In contrast to AS, XCS and IC are typical endur-
ance sports with constant or varying loads and a high
demand on the cardio-respiratory and musculoskeletal
system. A high percentage of the whole body musculature
is activated during XCS (Rusko, 2008). Jeukendrup and
Gleeson (2010) reported weight dependent (50 – 90 kg)
values of 530 - 950 kcal∙h-1 during XCS and for cycling
200 - 360 kcal∙h-1 at 9 km∙h-1 h, 260 - 570 kcal∙h-1 at 15
km∙h-1 and 530 - 950 kcal∙h-1 during racing. Based on
measurements of carbohydrate and fat utilization during
XCS, Van Hall et al. (2003) reported EE of approximately
1220 kcal∙h-1 during whole body (diagonal stride), and
287 kcal∙h-1 during arm work (double poling), which
compared well with the data measured in our study. Inter-
estingly, the relative VO2 values in the current study (94%
VO2max) during both IC and XCS were similar to those in
previous studies during XCS racing (Stöggl et al., 2007).
The EPOC was lower in AS compared with XCS
and IC which might be mainly attributed towards the
greater physiological loading during the latter two. To the
best of our knowledge no comparable data about EPOC in
these exercise modes is available. Vogt et al. (2005) dis-
tinguished between active phase and EPOC phase during
slalom racing, but no separate data was presented in the
results.
Rating of perceived exertion
Whole body RPE was similar between the three exercise
modes, however XCS was the only exercise mode where
participants reported exertion of the upper body, and AS
was the mode of exercise with the greatest subjective
exertion for the legs, which was followed by IC and XCS.
The former finding is associated with the whole body
involvement during XCS, where a greater part of the
upper body, lower body and trunk muscles are engaged
(Rusko, 2008, Holmberg et al., 2005). Interestingly, even
though HR, VO2 and lactate were slightly higher in XCS,
especially when compared with AS, this was not reflected
in the whole-body and leg RPE values. Therefore, during
XCS high metabolic and respiratory loading can be
achieved at a comparatively moderate level of exertion.
Already during low intensity XCS (e.g. slow walking on
skis in some of the participants) EE was as high as 644
kcal∙h-1. The fact that RPElegs was greatest during AS can
be explained by the mix of static and dynamic muscle
activity of the lower extremities (Müller and
Schwameder, 2003, Kröll et al., 2010) with both moderate
to high concentric and eccentric loading (Tesch, 1995) in
contrast to mainly dynamic and cyclic muscle loading
during XCS and IC. This type of muscle loading during
AS might be associated with the attenuated increase in
cardiorespiratory output based on muscular limitations as
compared to XCS and IC.
Effects of intensity and its interaction with exercise
mode
It is well known that an increase in exercise intensity
leads to an increase in metabolic and cardiorespiratory
parameters alike. Whereas during XCS and IC the exer-
cise intensity can easily be modified by altering the slope
gradient or changing the speed of travel, during AS this
cannot so easily be done. Previous investigations demon-
strated that skiing styles and steepness of the terrain play
important roles on the physiologic response of older rec-
reational skiers (Scheiber et al., 2009). The current study
demonstrates that an increase in the physiological re-
sponses can be induced by choosing different skiing
styles, i.e. PSS, CLR and ST without relevant changes in
skiing speed (vertical speeds: 96, 95, and 87 m∙min-1;
mean skiing speed: 24, 28 and 21 km∙h-1). Since ST in-
duced a pronounced physiological response (91% HRmax
and 84% VO2max) and participants were able to maintain
skiing at such high intensity for 4 min, it might lend itself
to high intensity interval training during AS.
During XCS, blood lactate and glucose were in-
creased more pronounced with an increase in exercise
intensity when compared with IC and AS, where especial-
ly blood glucose values remained stable across intensities
(Fig. 3D). This increase might be explained by the greater
involvement of total muscle mass—especially in the up-
per body and trunk—during XCS compared with the other
two exercise modes. In this context, Van Hall et al. (2003)
demonstrated that when using the double poling tech-
nique—which puts large emphasis on upper body mus-
cles—arterial lactate was 2.5 fold greater when compared
with the whole body exercise diagonal stride. In addition,
Richter et al. (1988) have shown that the net glucose
uptake into the muscle decreases with an increase of ac-
tive muscle mass. This decrease in uptake may depend on
the catecholamine stimulation of glycolysis. This glucose
sparing effect could also be triggered by increasing lactate
levels. Similar results of a post-exercise hyperglycemia
were described after long-distance XCS races (Ronsen et
al., 2004) as well as for type-I diabetics (Adolfsson et al.,
2011, Turner et al., 2015). The question here arises if
exercise induced increases in blood glucose level might
be seen as positive or negative especially when consider-
ing risk groups (e.g. diabetic patients). Nonetheless, in-
creased blood glucose values during XCS at HIGH inten-
sity in this group of healthy participants were still in a
normal range when comparing to diabetic reference val-
ues of normal fasting blood glucose <5.5 mmol∙L-1
(Alberti and Zimmet, 1998). Additionally, Hawley and
Gibala (2009) postulated in their review that high intensi-
ty exercise is possibly more efficient in reducing diabetic
long-term markers such as HbA1c.
Effects of gender
Even though male participants demonstrated lower HR
and similar relative VO2 (% VO2ma x) values compared
with females, men exercised at ~33% higher absolute

Alpine skiing counteracts activity deficit
192
VO2, with 47-59% greater EE and 56-87% higher EPOC.
Therefore, in one hour of steady activity men would have
burned almost 300 kcal∙h-1 more than women. Even when
values were adjusted for body weight, men expended
significantly greater amounts of energy compared to
women (9.5 vs. 7.0 kcal∙h-1∙kg-1), which could be ex-
plained by the generally greater percentage of body fat
and lesser muscle mass in relation to body size in women
as compared to men (Katch et al., 2011).
Effects of fitness level
It is known that EE is related to exercise intensity, body
weight (Jeukendrup and Gleeson, 2010, Katch et al.,
2011), sex, and age (Katch et al., 2011). However, there is
paucity of data about the effects of fitness level on EE. In
the current study, even though VO2 was higher in the fit
group, no differences were found in EE and EPOC be-
tween fit and unfit. This might be based on the trend (p <
0.1) towards a higher RER during exercise in the unfit
group when compared with the fit. Furthermore, the unfit
were loaded at a greater % of their peak lactate. There-
fore, unfit participants demonstrated lower economy for
performing the same task as the fit. These data refer to an
augmented glycolytic energy turn-over during exercise at
similar %HRmax in the unfit. However, based on this data
no matter if fitness level is high or low, equal EE and
EPOC is possible independent of the exercise mode.
Interestingly, the fit participants were – independ-
ent from exercise mode - able to increase their EE and
VO2 more pronounced when exercise intensity was in-
creased compared with the unfit. This is in part in contrast
to previous investigations during AS demonstrating that
fitness level does not play an important role on the physi-
ologic response of older recreational skiers (Scheiber et
al., 2009). However, our finding is supported by Karlsson
et al. (1978) describing As an effective recreational winter
sport with performance enhancing effects, however with
some limitations for recreational skiers compared to pro-
fessional skiers (Karlsson et al., 1978). Those authors
stated that professional skiers normally have high strength
and coordinative capacities, which enables them to ski in
a very active and exhausting skiing style, while recrea-
tional skiers often have limited strength and coordinative
skills. Therefore, low level skiers might not reach high
intensities during skiing – which may be necessary for
training adaptations especially for the cardiopulmonary
system – due to poor technique and strength. Based on the
exercise independent interaction, this finding might be
transferred also to XCS and IC.
During both IC and AS the fitness level had no ef-
fect on the subjective loading of the arms, however during
XCS, the fitter participants reported greater RPEarms com-
pared with the unfit. This might point again towards a
greater technical skill level, coupled with a greater appli-
cation of the upper body and possibly also a greater
amount of double poling during the XCS trials in the fit
group. For the subjective demand on the whole body and
the legs there was no difference between fit and unfit
during IC, however during both XCS and AS the fit
demonstrated greater levels. Therefore, in the more tech-
nical demanding exercises AS and XCS a higher fitness
level leads to an increased possibility to greater exert the
body. This might again be related to the aspects about
technical skills mentioned above, but also on the possibly
higher skiing velocities, a greater number of more dynam-
ic turns and consequently greater muscle loads.
Effect of age
Recent investigations have shown that AS is a suitable
and a safe recreational sport for an elderly and a sedentary
population (Krautgasser et al., 2011, Müller et al., 2011,
Scheiber et al., 2009, Scheiber et al., 2012, Kahn et al.,
1993, Pötzelsberger et al., 2015). However, a direct com-
parison between the physiological loading of young and
elderly participants during winter sports is lacking. In the
current study the younger participants demonstrated
~19% greater absolute VO2, ~13% greater absolute HR
values, 17-27% greater EE, and 15-18% greater EPOC
values compared with the older participants. This goes in
line with the documented decline in basal metabolic rate
(Katch et al., 2011) and aerobic fitness (Jackson et al.,
2009) with increase in age. Special attention should be
paid upon the great discrepancy between absolute and
relative HR values between young and elderly, especially
when trying to control intensity during guided ski-
ing/training. The older the participants the earlier the
limits of HR will be reached.
Finally, male, fit and young participants were able
to increase their EE and VO2 more pronounced with an
increase in intensity compared with their counterparts
(See Figures 3A-C). This might be based on the ability of
this group to push themselves harder when exercise inten-
sity is increased, a lower fear level (e.g. when skiing
speed and dynamics are increasing), a greater reserve to
their maximal effort based on higher work economy (less
anaerobic contribution as discussed above) and again a
higher skill level and therefore less technical limitations
when exercise intensity and speed gets high.
Limitations
Possible limitations of the study can be seen in the mis-
match between men (n = 12) and women (n = 7) and the
effects of wearing the equipment and the mask, which
might have led to augmented subjective loading and
might have influenced the sight especially during AS.
Furthermore, the physiological responses between XCS
and IC are comparable based on the defined exercise
intensities, while during AS intensity was based on appli-
cation of specific skiing techniques. This was done based
on security reasons, due to that the participant had to
focus on the slope conditions, the instructors pace and
also other skiers in the measurement zone and not on the
HR monitor.
Conclusion
There were greater demands on the cardiorespiratory
system at all three intensities during XCS and IC com-
pared to AS. However, by applying the skiing modes
parallel ski steering, carving long radii and short turn
skiing a significant increase in metabolic and cardi-
orespiratory response was achievable, allowing even high

Stöggl et al.
193
intensity training (i.e. HR > 90% HRmax) of adequately
long duration without relevant changes in skiing speed.
EE during AS can be maximized by using only short or
no breaks during the downhill phases and by choosing a
more dynamic skiing mode, i.e. carving or short turn
skiing. Since the active skiing time was approximately
44%, an AS duration of more than 2:30 h is needed to
equalize EE of one hour of XCS or IC. Therefore, when
applying distinct skiing modes and the terrain allows
steady skiing over a longer period, AS might provide
sufficient stimulus for the cardiologic and metabolic sys-
tem to enhance fitness and reduce cardiovascular risk.
Consequently, besides a popular leisure activity to experi-
ence nature and freedom in the winter months, AS might
also serve as a fitness workout (e.g. “cardio-skiing”).
Furthermore, XCS was found to be the most effective
activity for generating a high EE and VO2 while AS was
the most demanding activity for the legs. This aspect
should be considered when choosing an activity for main-
ly leg training purposes.
Acknowledgements
We would like to thank Manuel Hirner, Kathrin Hirner, Stephanie
Feuchter and Markus Förmer for their assistance during the measure-
ments, the participants for their enthusiasm and cooperation and the ski
resorts of Saalbach Hinterglemm and Flachau Winkel for granting us
free access. The current study complies with Austrian ethical standards
and laws. This study was supported in part by an unrestricted grant of
the State of Salzburg
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Key points
• During cross-
country skiing and indoor cycling
VO2max and energy expenditure were higher than
during alpine skiing
• Approximately 2½ hours of alpine skiing are nec-
essary to reach the same energy expenditure of one
hour of cross-country skiing or indoor cycling.
• Alpine skiing and cross-country skiing can be indi-
vidually tailored to serve as sports alternatives in
winter to activity deficit.
• By applying different skiing modes as parallel ski
steering, carving long radii and short turn skiing,
metabol
ic and cardiorespiratory response can be
increased during alpine skiing.
• Male, fit and young participants were able to in-
crease their energy expenditure and VO2 more pro-
nounced with an increase in intensity compared
with their counterparts
AUTHOR BIOGRAPHY
Thomas STÖGGL
Employment
Associate Professor at the Department
of Sport Science and Kinesiology,
University of Salzburg.
Degree
Assoc. Prof. Mag. Dr.
Research interests
Biomechanics and physiology of winter
sports in elite athletes and sedentary
people;
training intensity distribution
among elite endurance athletes; Exer-
cise Physiology.
E-mail: thomas.stoeggl@sbg.ac.at
Christoph SCHWARZL
Employment
Sports Physiotherapist
Degree
Msc
Research interests
Elite Sports; Sports injury
Edith E. MÜLLER
Employment
Research associate
Degree
Dr.
Research interests
exercise intervention; cardiovascular
risk
Masaru NAGASAKI
Employment
Associate Professor at the Department
of Health Science, Faculty of Psycho-
logical and Physical Science, Aichi
Gakuin University
Degree
Associate Professor, PhD
Research interests
Physiology of alpine skiing; Exercise
physiology; Diabetes

Stöggl et al.
195
Julia STÖGGL
Employment
Strength and Conditioning Coach
Degree
Msc
Research interests
Performance diagnostics
; exercise
physiology.
Peter SCHEIBER
Employment
University of Salzburg, Department of
Sport Science and Kinesiology
Degree
Dr.
Research interests
Biomechanics and Physiology in Alpine
Skiing
Martin SCHÖNFELDER
Employment
Scientific assistant
Degree
SD, Dr. rer. Nat.
Research interests
exercise physiology, sports science,
molecular sports biology
E-mail:martin.schoenfelder@tum.de
Josef NIEBAUER
Employment
Full professor and chair; University
Institute of Sports Medicine, Prevention
and Rehabilitation, Paracelsus Medical
University, Salzburg, Austria
Degree
MD PhD MBA
Research interests
A
ntiatherogenic effects of exercise
training; endothelial function; sports
cardiology; pre-participation examina-
tion
E-mail: j.niebauer@salk.at

Assoc. Prof. Mag. Dr. Thomas Stöggl
Department of Sport Science and Kinesiology, University of
Salzburg, Schlossallee 49, 5400 Hallein/Rif, Austria