ORIGINAL RESEARCH
Using a novel data resource to explore heart rate during
mountain and road running
Andrew Best1
& Barry Braun2
1 Department of Anthropology, University of Massachusetts, Amherst, Massachusetts
2 Department of Health and Exercise Science, Colorado State University, Fort Collins, Colorado
Keywords
Altitude, cardiac drift, hypoxia, Strava.
Correspondence
Andrew Best, Department of Anthropology,
University of Massachusetts, 217 Machmer
Hall, 240 Hicks Way, Amherst, MA.
Tel: +1 (860) 882-3678
Fax: +1 413-577-4217
E-mail: abest@umass.edu
Funding information
No funding information provided.
Received: 2 March 2017; Revised: 23 March
2017; Accepted: 23 March 2017
doi: 10.14814/phy2.13256
Physiol Rep, 5 (8), 2017, e13256,
doi: 10.14814/phy2.13256
Abstract
Online, accessible performance and heart rate data from running competitions
are posted publicly or semi-publicly to social media. We tested the efﬁcacy of
one such data resource- Strava- as a tool in exercise physiology investigations
by exploring heart rate differences in mountain racing and road racing run-
ning events. Heart rate and GPS pace data were gathered from Strava activities
posted by 111 males aged 21–49, from two mountain races (Mt. Washington
Road Race and Pike’s Peak Ascent) and two road race distances (half mara-
thon and marathon). Variables of interest included race ﬁnish time, average
heart rate, time to complete the ﬁrst half (by distance) of the race, time to
complete the second half, average heart rate for both the ﬁrst and second half,
estimated maximal heart rate, and competitiveness (ﬁnish time as percentage
of winning time). Mountain runners on average showed no change in heart
rate in the second versus ﬁrst half of the event, while road racers at the half
marathon and marathon distances showed increased second-half heart rate.
Mountain runners slowed considerably more in the second half than road
runners. Heart rate increases in road races were likely reﬂective of cardiac
drift. Altitude and other demands speciﬁc to mountain racing may explain
why this was not observed in mountain races. Strava presents enormous
untapped opportunity for exercise physiology research, enabling initial inquiry
into physiological questions that may then be followed by targeted laboratory
studies.
Introduction
Heart rate and GPS recording devices have become a
common training tool for endurance athletes. Thousands
post running and cycling activities on social media ser-
vices
such
as
Strava
(www.strava.com),
Movescount
(www.movescount.com), and Training Peaks (www.train
ingpeaks.com). Of these, Strava has the largest cache of
public data (registration not required) and semipublic
data (free registration required). Strava enables access to
in situ data from thousands of athletic competitions that
would require signiﬁcant time and effort to collect
through traditional research approaches. Standard data
posted in Strava activities include pace and elevation, and
sometimes heart rate and age. Some limitations are
inherent: potentially relevant information, such as body
mass, aerobic capacity, and training history are inaccessi-
ble without direct communication with individual ath-
letes, which violates Strava’s terms of use. Despite these
constraints
Strava
represents
an
untapped
“big-data”
source for exercise physiology research. Here, we explore
the efﬁcacy of this novel investigative approach through a
comparative study of heart rate proﬁles of road running
and mountain running competitions, events for which
sufﬁcient data is available on Strava.
Mountain running may be broadly deﬁned as running
or run/hiking over mountainous terrain and differs from
traditional road racing in grade, altitude and terrain. The
Mt. Washington Road Race (Gorham, NH) and the Pike’s
Peak Ascent (Manitou Springs, CO) are analogous in
ª 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of
The Physiological Society and the American Physiological Society.
This is an open access article under the terms of the Creative Commons Attribution License,
which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
2017 | Vol. 5 | Iss. 8 | e13256
Page 1
Physiological Reports ISSN 2051-817X
duration (but not distance) to the half marathon and
marathon, respectively, traditional distances for road run-
ning competitions. Differences in heart rate and perfor-
mance data between these races, gathered from Strava
activities, may provide clues to the physiological demands
unique to these two disciplines. Thus, a secondary goal of
this study is to infer physiological differences between
mountain and road running from studying heart rate
proﬁles during these events. If identiﬁed, effects of differ-
ential biomechanics, cardiovascular physiology, and/or
hypoxia could be studied directly in more targeted experi-
mental studies.
Methods
Mountain races sampled include the Mt. Washington
Road Race (MWRR, 2009–2016) and the Pike’s Peak
Ascent or the ascent split from the Pike’s Peak Marathon
(PP, 2012–2016), held the same weekend over the same
course but with a return downhill run. Candidate road
races were identiﬁed by searching Strava for races with
large samples of posted data. Chosen races included the
Hartford Half Marathon (2011–2015), the Philadelphia
Half Marathon (2011–2015), the Boston Athletic Associa-
tion Half Marathon (2015), and the New York City Mara-
thon (2015). It was necessary to sample from several half
marathons over multiple years to achieve a sufﬁcient sam-
ple size, and each of these races was chosen because these
race courses are not excessively hilly nor is the second
half of the race substantially more difﬁcult than the ﬁrst
half. For any race, data were excluded for years where the
ambient temperature was excessively warm. Also excluded
were Strava activities that showed unrealistic HR proﬁles,
such as precipitous changes, long periods of total stasis,
or rapid ﬂuctuations, all of which suggest heart rate mon-
itor malfunction.
Most data were accessed through fully public or
semipublic Strava pages (those requiring free site member-
ship), but several runners submitted GPX data ﬁles directly
after responding to Facebook requests and completing an
informed consent document. Per Strava’s request, Strava
users were not contacted. Data were anonymized and par-
ticipants were assigned study subject ID’s. Heart rate and
GPS data from 111 males aged 21–49 (mean 34.5  6.4)
were included in this study (see Table 1). Age, race ﬁnish
time, winning time, and status of altitude residence (de-
ﬁned here as living at 3500’ or higher) were determined by
accessing race results posted on race websites. Variables of
interest included: race ﬁnish time, age and residence (ob-
tained from ofﬁcial race results); average heart rate (HR)
throughout the race; time to complete the ﬁrst half (by
distance) of the race; time to complete the second half;
and average HR for both the ﬁrst and second half. HRmax
was estimated using the Tanaka et al. (2001) equation for
endurance trained men, 205—(0.6 x age). From these data
other measures were calculated, including percentage of
winning time (a measure of competitiveness), time differ-
ence to complete the ﬁrst versus second half, heart rate
difference in beats per minute (bpm) for the ﬁrst versus
second half, heart rate difference as a percentage of HRmax
for the ﬁrst versus second half, and overall heart rate as a
percentage of HRmax. Data were analyzed using SPSS sta-
tistical software v. 22 (IBM). T-tests were performed for
duration-matched races and ANOVAs were used to exam-
ine differences between all test groups. Linear regressions
were used to explore relationships between variables of
interest. Finally, three additional MWRR competitors for
whom heart rate data were not available were included to
create a subgroup of four altitude-acclimatized MWRR
runners. All study protocol were reviewed and endorsed
by the University of Massachusetts Human Subjects
Review Board.
Table 1. Characteristics of participants in each race, mean  SD.
All
MWRR
½ Marathon
Pikes Peak
Marathon
MWRR altitude
subgroup
N
111
19
21
21
50
4
Age (years)
34.5  6.4
35.0  5.4
32.9  6.7
37.0  7.5
33.9  5.9
31.8  5.2
Race duration
(hr:min:sec)
–
1:23:45  0:08:20
1:25:42  0:04:52
2:59:33  0:11:47
2:54:43  0:07:20
1:05:31  0:10:073
% of winning
time
136.1  9.5
142.8  13.81,2
138.2  10.1
133.1  8.81
133.9  5.62
111.3  16.63
1Signiﬁcant difference (P < 0.01) between MWRR and Pikes Peak.
2Signiﬁcant difference (P < 0.01) between MWRR and the Marathon. Runners in the shorter races, considered together, were slightly less com-
petitive than those in longer races (P < 0.01). MWRR and the ½ marathon were signiﬁcantly shorter in duration than Pikes Peak and the mara-
thon (P < 0.0001).
3MWRR altitude subgroup had signiﬁcantly lower % of winning time and race duration than all other groups (P < 0.01).
2017 | Vol. 5 | Iss. 8 | e13256
Page 2
ª 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of
The Physiological Society and the American Physiological Society.
Heart Rate during Mountain Running
A. Best et al.
There were no signiﬁcant differences in age between test
groups nor signiﬁcant differences in duration for matched
races- MWRR (1:23:45  0:08:20) versus the half mara-
thon (1:25:42  0:04:52), and PP (2:59:33  0:11:47) ver-
sus the marathon (2:54:43  0:07:20). Only one MWRR
participant of 19 lived at altitude (in the initial sample)
while only three of 21 PP runners did not. Runners’ ﬁnish
times ranged from 112% to 174% of the respective race
winning time (mean 136  9.5) and this measure was not
different between duration and matched races. MWRR
runners, however, were less competitive by this measure
than PP and marathon runners (P < 0.01) and sampled
runners in the shorter races considered together (MWRR
and the ½ marathon) were slightly less competitive than
the longer races (PP and the marathon; P < 0.01). Still,
overall the runners in this study can be described as recre-
ationally competitive. For example, most of the marathon-
ers ﬁnished in under 3 h, a common benchmark of
competitiveness, and the fastest ran 2 h 34 min, a perfor-
mance that would earn a top-10 ﬁnish in most American
marathons outside of the major city marathons (Boston,
New York, and Chicago). The subgroup of four MWRR
runners from altitude was markedly more competitive than
the larger study groups: two were race winners and one ﬁn-
ished in second place, giving this subgroup an average ﬁn-
ish time relative to the winner of 111.3%, signiﬁcantly
faster than any test group (P < 0.01).
Results
Heart rate increased over the second half of both road
events: half marathoners saw a 3.7 bpm increase (P < 0.01)
and marathoners a 1.8 bpm increase (P < 0.05). There was
no change in heart rate in the second versus ﬁrst half of
MWRR and HR decreased by 4.4 bpm at PP, though not
quite signiﬁcantly (P = 0.056; see Table 2 and Fig. 1).
These differences are also reﬂected in percentage estimated
HRmax. Heart rate change was highly variable in the PP
sample (SD=9.9 bpm) and there was a dramatic outlier
whose HR dropped 34 bpm over the second half while
slowing about the same as the average PP runner (see
Fig. 2). When both mountain races were compared against
both road races, the former were found to have signiﬁ-
cantly greater slowdown in the second half (P < 0.001) and
a signiﬁcantly different second half HR change (P < 0.01;
see Table 3). This was true in duration-matched pair com-
parisons as well: MWRR had greater second-half slowing
and less of a second-half HR increase than the ½ marathon
(P < 0.05), while PP had greater second-half slowing and a
drop in HR over the second half, as compared with the
marathon where HR increased (P < 0.01). The four accli-
matized runners comprising the MWRR altitude subgroup
had similar second half slowing to other MWRR runners
(15.4%  1.0 vs. 11.5%  4.8), signiﬁcantly more than
half
marathoners
and
marathoners
(P < 0.05)
and
signiﬁcantly less than PP runners (P < 0.001). Runners in
the
shorter
races
(MWRR
and
the
half
marathon)
displayed higher overall HR (bpm and as percentage
estimated HRmax; P < 0.05) and less second-half slowing
(P < 0.01).
Age was positively, though very weakly, correlated with
slowing in the second half when all races were analyzed
together (r2=0.054; P < 0.05). No signiﬁcant relationship
was found in individual races. Percentage of winning time
was positively and weakly correlated with HR for the
marathon (r2=0.085; P < 0.05) and inversely correlated
with HR change in the second half of MWRR, both in
bpm and percent estimated HRmax (r2=0.207; P = 0.05);
that is, less competitive runners had a smaller HR
increase or larger decrease in the second half at these
Table 2. HR and pace results, mean  SD.
MWRR
½ Marathon
Pikes Peak
Marathon
MWRR altitude
subgroup
HR (bpm)
168.9  8.3
171.1  7.7
164.1  9.8
166.5  9.3
–
HR % estimated
max
91.8  4.7
92.4  4.2
89.2  4.7
90.2  5.1
–
Second half %
slower
11.5  4.81
4.3  8.4
51.2  8.82
5.7  5.4
15.4  1.03
HR change bpm
0.4  4.3
3.7  5.44
4.4  9.95
1.8  6.14
–
Change % est. HRmax
0.2  2.3
2.0  2.94
2.4  5.45
1.0  3.3
–
1MWRR slowed more than ½ marathoners (P < 0.01) and marathoners (P = 0.01).
2PP runners slowed more than all other groups (P < 0.0001).
3MWRR altitude runners slowed more than ½ marathoners and marathoners (P < 0.05).
4½ Marathoners’ (P < 0.01) and marathoners’ (P < 0.05) HR increased in the 2nd half.
5PP runners’ HR decrease was signiﬁcantly different from the marathoners’ (P < 0.01) and ½ marathoners’ (P = 0.001) HR increase.
ª 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of
The Physiological Society and the American Physiological Society.
2017 | Vol. 5 | Iss. 8 | e13256
Page 3
A. Best et al.
Heart Rate during Mountain Running
races. Considered all together, runners who slowed more
in the second half of their race had less of a HR increase
or a greater decrease both in bpm and percent estimated
HRmax (r2=0.187 and 0.189, respectively; P < 0.001). This
relationship was signiﬁcant only for MWRR runners
(r2=0.222 and 0.221, P < 0.05) and marathon runners
(r2=0.371 and 0.373, P < 0.001); there was almost no cor-
relation at PP or the half marathon.
Discussion
Our primary objective was to pilot the use of Strava’s
publicly and semi-publicly available data in an exercise
physiology investigation. The primary strength of this
approach is that large quantities of data are available from
a variety of competitions and training activities, enabling
initial inquiry into questions that would otherwise be dif-
ﬁcult to test. Questions dealing with relative performance
will likely be more amenable to this approach than inves-
tigations of the underlying physiology as performance
data are abundant but physiological data from Strava
activities are limited. Indeed, heart rate is the only physi-
ological measurement available; without knowledge of
each subject’s maximal heart rate, VO2-max, blood lactate
values and oxygen consumption during the event, physio-
logical differences can only be inferred. Predictive equa-
tions based on age are routinely used to estimate HRmax,
but even the best of these (speciﬁc to endurance-trained
subjects and as used in this study) explains only 53% of
the variation in HRmax between subjects (Tanaka et al.
2001). We could not control for effects of training history
and runners unaccustomed to the speciﬁc demands of
prolonged uphill running will surely respond and perform
differently than well-prepared competitors, a point that
will be discussed further.
There are several ways in which Strava’s utility to a
researcher could be improved. First, recruiting users to
record and submit heart rate and GPS data speciﬁcally
for study purposes, which is currently against Strava’s
terms of use, could increase sample size and permit col-
lection of additional information, including training char-
acteristics.
However,
this
would
require
extensive
recruitment,
obviating
the
primary
strength
of
the
approach piloted here (easy data access). Second, Strava
or other athletic social media services may choose to
incorporate a running power feature, allowing uploading
of data from running power meters such as Stryd (www.
stryd.com), a relatively new device which estimates power
in watts; if accuracy is validated this could be a useful
measure. Other services dedicated to tracking and analyz-
ing athlete data—such as Movescount or Training Peaks,
mentioned previously-—may provide additional metrics,
but at present these services do not host a public or
semipublic data cache as large as Strava’s. Finally, poten-
tial
physiological
differences
identiﬁed
through
this
approach could be explored further with targeted labora-
tory-based studies where variables such as training his-
tory, climate, and terrain could be controlled and direct
physiological measurements could be collected.
This study is also, to our knowledge, the ﬁrst to demon-
strate heart rate differences between mountain running and
road running events. Compared to duration-matched road
HR difference (bpm)
20
10
0
–10
–20
–30
–40
MWRR
1/2 marathon
Pikes peak
Marathon
Figure 1. HR difference in the second versus ﬁrst half of each race
in beat per minute (bpm). Boxplots show ﬁrst, second, and third
quartiles, minimum and maximum, and outliers.
Second half % slower
80.0
60.0
40.0
20.0
.0
–20.0
HR change (bpm)
20
10
0
–10
–20
–30
–40
Marathon
PP
1/2 marathon
MWRR
Figure 2. Relationship between slowing in the second half and HR
change in the second half. Signiﬁcant negative correlation for
MWRR (r2=0.224, P < 0.05) and the marathon (r2=0.370,
P < 0.0001).
2017 | Vol. 5 | Iss. 8 | e13256
Page 4
ª 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of
The Physiological Society and the American Physiological Society.
Heart Rate during Mountain Running
A. Best et al.
races, participants in mountain races experienced no
increase (MWRR) or a reduction (PP) in HR (both
absolute and as percentage estimated HRmax) and slowing
pace over the second half of the race. The observed
increases in HR in the second versus ﬁrst half of the half
marathon and marathon are not surprising: cardiac drift,
an increase in HR without a concomitant increase in work
output (i.e., running speed), has been demonstrated in
one-hour (Ekelund 1967; Mognoni et al. 1990) and 4-hour
(Dawson et al. 2005) exercise tests and is likely resultant
from lower stroke volume concomitant with reduced
plasma volume (Hamilton et al. 1991) and lower diastolic
function (Dawson et al. 2005). There is little reason to
speculate that these factors do not affect runners at MWRR
and PP— races of similar duration to the half marathon
and marathon, respectively— so maintenance of heart rate
in those events must be attributable to a factor sufﬁciently
robust that it masks the effect of drift. Three potential
explanatory factors, not mutually exclusive, warrant further
consideration.
Altitude
The PP Ascent begins at 2382 m (7814 feet) and ﬁnishes
at 4302 m (14 115 feet) while the Mt. Washington Road
Race starts at 465 m (1526 feet) and ﬁnishes at 1917 m
(6289 feet). The marathon and half marathons included
in this study are held near sea level. Performance and car-
diac function are undoubtedly impacted by the hypoxia
encountered throughout the PP race: acute altitude expo-
sure at simulated 4000 m (13 123 feet) increases heart
rate and cardiac output during submaximal exercise to
compensate for reduced arterial partial pressure of oxygen
(PaO2), but maximal HR is reduced slightly, possibly due
to reduced oxygen delivery to cardiac tissue (Stenberg
et al. 1966) or increased production of epinephrine,
which may have additional performance effects as it
speeds uptake of glucose into muscle cells (Richardson
et al. 1998). Wehrlin and Hallen (2006) found a 1.9 bpm
decrease in maximal HR per 1000 m–in keeping with
Stenberg et al.’s (1966) result at 4000 m– beginning at
least as low as 1000 m, encompassing most of the alti-
tudes encountered at MWRR. Thus, perhaps the lack of
HR increase observed in mountain races does not reﬂect
a reduction in percent HRmax (reduced aerobic effort),
but rather lower HRmax resultant from hypoxia opposes
cardiac drift and attenuates (MWRR) or completely
negates (PP) a rise in heart rate in the second half of the
race. Importantly, most participants in the PP Ascent live
at and are ostensibly acclimatized to altitude, so many of
their physiological responses during the race are not
directly comparable with nonacclimatized runners; how-
ever, some HR effects persist even after acclimatization
(Vogel et al. 1967).
Acclimatization also affords these runners a buffer
against altitude-induced performance decrements and thus
a performance advantage relative to sea-level runners
(Mahe et al. 1974; Fulco et al. 2000). Most participants in
the Mt. Washington Road Race are sea-level residents and
so any hypoxia experienced during the event is novel and
acute. Little work has been done to evaluate HR responses
to altitudes below 4000 m, but Wehrlin and Hallen’s
results (2006) suggest that Mt. Washington’s altitude is
sufﬁcient to decrease maximal HR, as has been observed at
altitudes equivalent to PP. Regardless, Mt. Washington’s
elevation should certainly incur a performance penalty,
especially for non-acclimatized runners. Reductions in
VO2-max have been observed relative to sea level values
beginning at low altitudes: 580 m (Gore et al. 1996, 1997)
and even right from sea level (Wehrlin and Hallen 2006).
Thus, VO2-max decreases linearly up to 3000 m, an
impairment that appears to be more severe for endurance-
trained individuals (Lawler et al. 1988; Koistinen et al.
1995). This effect is not resultant from reduced maximal
exercise intensity achieved in altitude tests: Wehrlin and
Hallen (2006) found that performance, measured as time
to exhaustion in running tests at simulated altitudes with
speed kept constant, followed an observed 6% VO2-max
decrease per 1000 m. As the second half of MWRR
ascends to an altitude 730 meters higher than the ﬁrst half,
Table 3. HR and pace for mountain versus road races and shorter versus longer races.
Mountain races
Road races
Shorter races
Longer races
HR (bpm)
166.4  9.3
167.9  9.0
170.0  8.03
165.8  9.4
HR % estimated max
90.5  4.8
90.9  4.9
92.1  4.43
90.0  4.9
Second half % slower
32.4  21.31
5.2  6.4
7.7  7.83
19.1  21.9
HR change bpm
2.1  8.02
2.4  5.9
2.1  5.1
0.0  7.9
Change % est. HRmax
1.1  4.42
1.3  3.2
1.2  2.8
0.0  4.3
1Mountain races had greater second half slowing than road races (P < 0.0001).
2HR change in bpm and as % est. HRmax was signiﬁcantly different in mountain versus road races (P < 0.001).
3Shorter races were characterized by higher HR (bpm and % est. HRmax; P < 0.05) and less second half slowing (P < 0.01) than longer races.
ª 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of
The Physiological Society and the American Physiological Society.
2017 | Vol. 5 | Iss. 8 | e13256
Page 5
A. Best et al.
Heart Rate during Mountain Running
we may predict a 4.3% VO2-max penalty imposed by alti-
tude in the second half, explaining part of the observed
11.5% slowing.
It is also possible that increasing altitude throughout
both mountain races led to a slowing of pace while effort
remained relatively unchanged. Enormous slowing at PP
(51.2%  8.8) may be explained in part by the more
extreme altitude and the increasing difﬁculty of the footing
on the racecourse. However, as slowing was not associated
with a decrease in HR for PP (r2=0.001), increasing techni-
cal difﬁculty alone is unlikely to explain the vast discrep-
ancy between PP slowing and marathon slowing (5.7%).
MWRR is run on pavement, eliminating terrain as a com-
plicating variable, so a direct comparison with the half
marathon is easier- and indeed MWRR runners slowed far
more than half marathoners (11.5% vs. 4.3%). Slowing
pace at MWRR explains only 22% of the variability in HR
decrease, so other factors must be operative.
Pacing and psychological factors
An alternative or additional explanation for lack of HR
increase together with slowing pace during mountain
races is that runners reduce their effort as the race pro-
gresses due to psychological factors, or perhaps runners
are not as adept at pacing themselves evenly in these
events. This interpretation is supported by a weak but sig-
niﬁcant correlation between second-half slowing and HR
change at MWRR (r2=0.202; P < 0.001): runners who slo-
wed more had a greater decrease, or smaller increase, in
HR compared with those who slowed less. However, 80%
of the variation in HR change is not explained by slowing
pace, and there is almost no correlation at all between
these variables for PP (r2=0.001). Additionally, the four
altitude-acclimatized MWRR athletes- three of whom are
world class mountain runners (one is a world champion)-
slowed just as much as their fellow MWRR competitors.
This may suggest that altitude is not responsible for the
observed slowing (and perhaps HR) effects as altitude
acclimatization afforded no buffering against second-half
slowing. Alternatively, the fact that highly trained and
experienced mountain runners slowed just as much as
everyone else may suggest that pacing and psychological
factors alone cannot account for slowing and HR changes,
as these runners should be expected to be expertly pre-
pared for the physical and psychological demands of
mountain racing. Also, as acclimatization simply mitigates
but does not eliminate altitude-incurred diminishments
in aerobic capacity, and VO2-max declines linearly begin-
ning from sea level, we may not expect acclimatized run-
ners to slow less over the second half but rather to simply
experience less of a performance declination overall rela-
tive to un-acclimatized athletes.
Muscle recruitment and biomechanical
factors
The road races included in this study climb and descend
no more than several hundred feet in total, while MWRR
ascends about 4600’ at an average grade of 12% and the
PP Ascent climbs about 7800’, also averaging 12% in
grade. The biomechanics of uphill running differ signiﬁ-
cantly from level running: less eccentric work is per-
formed by muscles and tendons, and none above 15%
grade (Minetti et al. 1994), contributing to a higher
energy cost. At grades steeper than 15% (which are brieﬂy
encountered at MWRR and PP) slopes of cost of trans-
port for walking and running converge (Minetti et al.
1994), and above 28% grade, walking is more efﬁcient
than running (Giovanelli et al. 2016). Of course, in a
race, efﬁciency is second to the primary goal of covering
the course as quickly as possible. Many participants in
mountain racing events, especially the slower racers,
employ a mix of running and walking. So different are
uphill biomechanics that the traditional deﬁnition of run-
ning gait may need to be modiﬁed to encompass locomo-
tion lacking a true ﬂight phase, but characterized by a
bouncing gait instead of the inverted pendulum motion
of walking. Such a gait has been described as “Groucho
running” in a study of bent-knee running on a level
treadmill (McMahon et al. 1987) and “grounded run-
ning” in a study of ostriches (Rubenson et al. 2004), but
these terms aptly describe the slower ranges of uphill
human running (Giovanelli et al. 2016).
How do the incline-speciﬁc biomechanics encountered
in mountain racing affect physiology? Balducci et al.
(2016) found that ten elite French mountain runners each
achieved the same VO2-max, blood lactate concentrations
and heart rate in maximal tests on level ground, 12.5%
slope, and 25% slope. Further, incline running perfor-
mance was poorly predicted by level running perfor-
mance,
and
there
was
signiﬁcant
inter-individual
variation in energy cost increase from level to uphill run-
ning: moving from 0% to 12.5% incline increased energy
cost 50% for some subjects and 104% for others. These
results inform the present study by suggesting that, in
uphill-trained subjects, (1) uphill racing absent altitude
effects should not be characterized by different heart rate
proﬁles and aerobic capacities; and (2) uphill running
imposes unique challenges and speciﬁc training may have
a strong effect on performance. However, this was a short
test (<16 min) and the physiology of 1- to 3-h mountain
racing may be different; and importantly, the two moun-
tain races we sampled do present altitude challenges. The
observation that even highly trained mountain runners
showed tremendous variation in uphill energy cost sug-
gests that this effect may be even stronger in many of the
2017 | Vol. 5 | Iss. 8 | e13256
Page 6
ª 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of
The Physiological Society and the American Physiological Society.
Heart Rate during Mountain Running
A. Best et al.
athletes included in this study. A runner unaccustomed to
the muscle recruitment patterns speciﬁc to mountain rac-
ing may prematurely exhaust particular muscle groups
resulting in reduced performance relative to what he or
she can achieve in a traditional road race (for which they
are ostensibly better trained). For example, uphill running
activates the vastus muscle group and the soleus to a
greater extent than level running while other muscle
groups are activated less (Gostill et al. 1974; Sloniger
et al. 1997). It is possible that a runner unaccustomed to
the demands of uphill running may exhaust the vastus
and soleus muscles prematurely and be forced to reduce
pace and aerobic effort as the race progresses. However,
substantial second-half slowing observed in this study’s
elite and altitude-acclimatized subgroup—three athletes
trained for the speciﬁc demands of mountain running—
suggests that this effect may be minimal. A larger sample
of elite runners could clarify this point.
Heart rate change in the second half of the marathon is
more strongly
correlated (r2=0.370) with second-half
slowing than at MWRR (again, this correlation was
inconsequential for the half marathon and PP). Here, per-
haps is a good candidate application for the hypothesis of
reduced HR due to reduced aerobic output. The eccentric
muscle damage and diminishing glycogen stores incurred
during a marathon may cause a slowing that is concur-
rent with, and causative of, a reduction in aerobic output.
A moderate and signiﬁcant correlation between slowing
pace and HR decrease supports this explanation. Glyco-
gen depletion should also be expected to pose a challenge
for PP runners, but as HR change was not associated with
changing pace, glycogen depletion can only minimally
explain HR and pace changes.
Other observed signiﬁcant correlations are most likely
specious. Less competitive MWRR runners displayed a
greater reduction or smaller increase in HR over the sec-
ond half, but competitiveness was not correlated with sec-
ond-half slowing at this or any race. The very weak
correlation between age and second-half slowing disap-
peared when examined for individual races. Less competi-
tive marathoners had higher HR, but an r-squared value
of 0.085 and a lack of correlation between competitive-
ness and any other variable suggest this is a false positive.
Finally, the higher HR (as bpm and percentage estimated
HRmax) in the shorter-duration events conﬁrms long-
established observations that relative intensity is inversely
related to exercise duration.
In summary, uphill mountain racing does not appear
to be characterized by the continually increasing heart
rate seen in the half marathon and marathon. Our three
hypotheses for this phenomenon could be investigated
with a laboratory based study with subjects completing
race effort runs on ﬂat and uphill grades. This would
control for terrain, altitude, and variability in interindi-
vidual responses (each subject could complete both ﬂat
and uphill race efforts), and would permit collection of
physiological data (VO2, RER, blood lactate, etc.) and
training history.
Conclusions
Strava’s performance and heart rate data are a useful
and novel resource for exercise science investigations
provided that research questions are carefully articulated
in consideration of the strengths and limitations of this
approach. Competitors in mountain races slowed more
than their counterparts in duration-matched road races.
Mountain racing is characterized by a maintained or
decreased heart rate in the second versus ﬁrst half of the
event, while road racing at the half marathon and mara-
thon distances is characterized by an increasing heart
rate. It is unclear whether or how altitude or demands
speciﬁc to uphill running explain this difference. This
study demonstrates how Strava data can be used in an
inquiry into a physiological or performance question;
results may then be used to inform a targeted labora-
tory-based study.
Acknowledgment
The authors wish to thank the athletes who contributed
data directly or indirectly to make this study possible.
Conﬂict of Interest
The authors declare no conﬂicts of interest.
References
Balducci, P., M. Clemencon, B. Morel, G. Quiniou, D. Saboul,
and C. A. Hautier. 2016. Comparison of level and graded
treadmill tests to evaluate endurance mountain runners. J.
Sports Sci. Med. 15:239–246.
Dawson, E. A., R. Shave, K. George, G. Whyte, D. Ball, D.
Gaze, et al. 2005. Cardiac drift during prolonged exercise
with echocardiographic evidence of reduced diastolic
function of the heart. Eur. J. Appl. Physiol. 94:305–309.
Ekelund, L. G. 1967. Circulatory and respiratory adaptation
during prolonged exercise. Acta Physiol. Scand. Suppl.
292:1.
Fulco, C. S., P. Rock, and A. Cymerman. 2000. Improving
athletic performance: is altitude residence or
altitude training helpful? Aviat. Space Environ. Med.
71:162–171.
Giovanelli, N., A. L. R. Ortiz, K. Henninger, and R. Kram.
2016. Energetics of vertical kilometer foot races; is steeper
cheaper? J. Appl. Physiol. 120:370–375.
ª 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of
The Physiological Society and the American Physiological Society.
2017 | Vol. 5 | Iss. 8 | e13256
Page 7
A. Best et al.
Heart Rate during Mountain Running
Gore, C. J., A. G. Hahn, G. C. Scroop, D. B. Watson, K. I.
Norton, R. J. Wood, et al. 1996. Increased arterial
desaturation in trained cyclists during maximal exercise at
580 m altitude. J. Appl. Physiol. 80:2204–2210.
Gore, C. J., S. C. Little, A. G. Hahn, G. C. Scroop, K. I.
Norton, P. C. Bourdon, et al. 1997. Reduced performance of
male and female athletes at 580 m altitude. Eur. J. Appl.
Physiol. Occup. Physiol. 75:136–143.
Gostill, D. L., E. Jansson, P. D. Gollnick, and B. Saltin. 1974.
Glycogen utilization in leg muscles of men during level and
uphill running. Acta Physiol. Scand. 91:475–481.
Hamilton, M. T., J. Gonzalez-Alonso, S. J. Montain, and E. F.
Coyle. 1991. Fluid replacement and glucose infusion during
exercise prevent cardiovascular drift. J. Appl. Physiol.
71:871–877.
Koistinen, P., T. Takala, V. Martikkala, and J. Lepp€aluoto.
1995. Aerobic ﬁtness inﬂuences the response of maximal
oxygen uptake and lactate threshold in acute hypobaric
hypoxia. Int. J. Sports Med. 16:78–81.
Lawler, J., S. K. Powers, and D. Thompson. 1988. Linear
relationship between VO2-max and VO2-max decrement during
exposure to acute hypoxia. J. Appl. Physiol. 64:1486–1492.
Mahe, J. T., L. G. Jones, and L. H. Hartley. 1974. Effects of
high-altitude exposure on submaximal endurance capacity
of men. J. Appl. Physiol. 37:895–898.
McMahon, T. A., G. Valian, and E. C. Frederick. 1987.
Groucho running. J. Appl. Physiol. 62:2326–2337.
Minetti, A. E., L. P. Ardigo, and F. Saibene. 1994. Mechanical
determinants of the minimum energy cost of gradient
running in humans. J. Exp. Biol. 195:211–225.
Mognoni, P., M. D. Sirtori, F. Lorenzelli, and P. Cerretelli.
1990. Physiological responses during prolonged exercise at
the power output corresponding to the blood
lactate threshold. Eur. J. Appl. Physiol. Occup. Physiol.
60:239–243.
Richardson, R. S., E. A. Noyszewski, J. S. Leigh, and P. D.
Wagner. 1998. Lactate efﬂux from exercising human
skeletal muscle: role of intracellular. J. Appl. Physiol.
85:627–634.
Rubenson, J., D. Heliams, D. G. Lloyd, and P. A. Fournier.
2004. Gait selection in the ostrich: mechanical and
metabolic characteristics of walking and running with and
without an aerial phase. Proc. R. Soc. Lond. B Biol. Sci.
271:1091–1099.
Sloniger, M. A., K. J. Cureto, B. M. Prior, and E. M. Evans.
1997. Lower extremity muscle activation during horizontal
and uphill running. J. Appl. Physiol. 83:2073–2079.
Stenberg, J., B. Ekblom, and R. Messin. 1966. Hemodynamic
response to work at simulated altitude, 4000 m. J. Appl.
Physiol. 21:1589–1594.
Tanaka, H., K. D. Monahan, and D. R. Seals. 2001. Age-
predicted maximal heart rate revisited. J. Am. Coll. Cardiol.
37:153–156.
Vogel, J. A., J. E. Hansen, and C. W. Harris.
1967. Cardiovascular responses in man during exhaustive
work at sea level and high altitude. J. Appl. Physiol. 23:531–
539.
Wehrlin, J. P., and J. Hallen. 2006. Linear decrease in VO2-
max and performance with increasing altitude in endurance
athletes. Eur. J. Appl. Physiol. 96:404–412.
2017 | Vol. 5 | Iss. 8 | e13256
Page 8
ª 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of
The Physiological Society and the American Physiological Society.
Heart Rate during Mountain Running
A. Best et al.

Using a novel data resource to explore heart rate during mountain and road running.
Best, Andrew,Braun, Barry