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Abstract Many studies have documented the association between mechanical deviations from normal and the presence or risk of injury. Some runners attempt to change mechanics by increasing running cadence. Previous work documented that increasing running cadence reduces deviations in mechanics tied to injury. The long-term effect of a cadence retraining intervention on running mechanics and energy expenditure is unknown. This study aimed to determine if increasing running cadence by 10% decreases running efficiency and changes kinematics and kinetics to make them less similar to those associated with injury. Additionally, this study aimed to determine if, after 6 weeks of cadence retraining, there would be carryover in kinematic and kinetic changes from an increased cadence state to a runner's preferred running cadence without decreased running efficiency. We measured oxygen uptake, kinematic and kinetic data on six uninjured participants before and after a 6-week intervention. Increasing cadence did not result in decreased running efficiency but did result in decreases in stride length, hip adduction angle and hip abductor moment. Carryover was observed in runners' post-intervention preferred running form as decreased hip adduction angle and vertical loading rate.
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The effect of a cadence retraining protocol on running
biomechanics and efficiency: a pilot study
Jocelyn F. Haferab, Allison M. Brownc, Polly deMilled, Howard J. Hillstromb & Carol Ewing
Garbere
a Kinesiology, University of Massachusetts Amherst, Amherst, MA, USA
b Hospital for Special Surgery, Leon Root, MD Motion Analysis Laboratory, New York, NY, USA
c Department of Rehabilitation and Movement Science, Rutgers Biomedical and Health
Sciences, Newark, NJ, USA
d Sports Rehabilitation and Performance Center, Hospital for Special Surgery, New York, NY,
USA
e Department of Biobehavioral Sciences, Teachers College, Columbia University, New York,
NY, USA
Published online: 04 Nov 2014.
To cite this article: Jocelyn F. Hafer, Allison M. Brown, Polly deMille, Howard J. Hillstrom & Carol Ewing Garber (2015) The
effect of a cadence retraining protocol on running biomechanics and efficiency: a pilot study, Journal of Sports Sciences,
33:7, 724-731, DOI: 10.1080/02640414.2014.962573
To link to this article: http://dx.doi.org/10.1080/02640414.2014.962573
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The effect of a cadence retraining protocol on running biomechanics
and efciency: a pilot study
JOCELYN F. HAFER
1,2
*, ALLISON M. BROWN
3
, POLLY DEMILLE
4
,
HOWARD J. HILLSTROM
2
& CAROL EWING GARBER
5
1
Kinesiology, University of Massachusetts Amherst, Amherst, MA, USA,
2
Hospital for Special Surgery, Leon Root, MD
Motion Analysis Laboratory, New York, NY, USA,
3
Department of Rehabilitation and Movement Science, Rutgers
Biomedical and Health Sciences, Newark, NJ, USA,
4
Sports Rehabilitation and Performance Center, Hospital for Special
Surgery, New York, NY, USA and
5
Department of Biobehavioral Sciences, Teachers College, Columbia University,
New York, NY, USA
(Accepted 1 September 2014)
Abstract
Many studies have documented the association between mechanical deviations from normal and the presence or risk of
injury. Some runners attempt to change mechanics by increasing running cadence. Previous work documented that
increasing running cadence reduces deviations in mechanics tied to injury. The long-term effect of a cadence retraining
intervention on running mechanics and energy expenditure is unknown. This study aimed to determine if increasing
running cadence by 10% decreases running efciency and changes kinematics and kinetics to make them less similar to
those associated with injury. Additionally, this study aimed to determine if, after 6 weeks of cadence retraining, there would
be carryover in kinematic and kinetic changes from an increased cadence state to a runners preferred running cadence
without decreased running efciency. We measured oxygen uptake, kinematic and kinetic data on six uninjured participants
before and after a 6-week intervention. Increasing cadence did not result in decreased running efciency but did result in
decreases in stride length, hip adduction angle and hip abductor moment. Carryover was observed in runnerspost-
intervention preferred running form as decreased hip adduction angle and vertical loading rate.
Keywords: step rate, training intervention, running mechanics, running injury, stride frequency
1. Introduction
Running is a popular activity as evidenced by the
almost 14 million road race nishers in the United
States in 2011 (Running USA: Statistics, 2013).
While many enjoy the health benets of this form
of exercise, 2465% of runners sustain an injury
annually (Macera et al., 1989). Most of these injuries
are categorised as overuse injuries, with patellofe-
moral pain syndrome, iliotibial band syndrome and
tibial stress fractures being three of the most com-
mon running injuries (Taunton et al., 2002).
Previous studies have tied these injuries to particular
alterations in kinematics and kinetics. These three
injuries have been associated with increased peak hip
adduction angle (Noehren, Davis, & Hamill, 2007;
Noehren, Pohl, Sanchez, Cunningham, &
Lattermann, 2012; Pohl, Mullineaux, Milner,
Hamill, & Davis, 2008; Willson & Davis, 2008),
and tibial stress fractures have also been associated
with increased tibial acceleration and vertical loading
rate (Milner, Ferber, Pollard, Hamill, & Davis,
2006). These variables may be affected by interven-
tions aimed at altering running form. An interven-
tion that may be effective at modifying running
mechanics associated with injury is to increase run-
ning cadence.
Previous studies have shown that increasing
cadence at a constant speed (or implementing an
intervention that leads to this) reduced the magni-
tude of loading variables that have been associated
with stress fractures (Derrick, 2004; Derrick,
Hamill, & Caldwell, 1998; Edwards, Taylor,
Rudolphi, Gillette, & Derrick, 2009; Hamill,
Derrick, & Holt, 1995; Heiderscheit, Chumanov,
Michalski, Wille, & Ryan, 2011; Hobara, Sato,
Sakaguchi, Sato, & Nakazawa, 2012). A study by
Heiderscheit et al. found that increasing cadence
resulted in decreased heel strike distance (a correlate
of stride length), decreased peak vertical ground
reaction force and decreased peak hip adduction,
*Correspondence: Jocelyn F. Hafer, Kinesiology, University of Massachusetts Amherst, Amherst MA, USA. E-mail: jocelynfhafer@gmail.com
Journal of Sports Sciences, 2015
Vol. 33, No. 7, 724731, http://dx.doi.org/10.1080/02640414.2014.962573
© 2014 Taylor & Francis
Downloaded by [173.70.46.240] at 06:22 06 May 2015
hip exion and knee exion angles as well as an
increase in knee exion angle at initial contact
(Heiderscheit et al., 2011). It is notable that these
changes are in the opposite direction of the aberrant
mechanics associated with patellofemoral pain syn-
drome (Willson & Davis, 2008), iliotibial band syn-
drome (Noehren et al., 2007) and tibial stress
fractures (Pohl et al., 2008). An acute intervention
by Giandolini et al. found that increasing cadence
resulted in decreased centre of mass vertical displa-
cement, but found no differences between normal
and increased cadence running in peak vertical
ground reaction force or vertical loading rate
(Giandolini et al., 2013). While it has been shown
that an acute trial of increased cadence can poten-
tially decrease injurious kinematics and kinetics such
as abnormal hip adduction, impact force and knee
exion at initial contact (Heiderscheit et al., 2011;
Hobara et al., 2012), it is unknown if runners will
maintain these biomechanical changes over the
course of an extended intervention. Additionally, it
is not known what effect increased cadence has on
running efciency in the long term.
Previous multi-week gait retraining intervention
studies have demonstrated the feasibility of improv-
ing potentially injurious running biomechanics.
Potentially benecial mechanical alterations have
been observed after employing feedback interven-
tions and Pose Method running techniques includ-
ing decreases in loading rate, impact peak, peak
positive acceleration (Crowell, Milner, Hamill, &
Davis, 2010; Giandolini et al., 2013), hip adduction,
hip internal rotation (Noehren, Scholz, & Davis,
2011), stride length and vertical oscillation
(Dallam, Wilber, Jadelis, Fletcher, & Romanov,
2005). However, where oxygen uptake has been
measured in interventions, the results have been
conicting, with some studies showing no change
in efciency and others reduced efciency
(Cavanagh & Williams, 1982; Dallam et al., 2005;
Messier & Cirillo, 1989). Furthermore, the retrain-
ing methods in these studies required feedback
mechanisms that are not available to the average
runner (e.g. accelerometers, visual feedback, Pose
Method instructor).
Increasing running cadence is an intervention
which runners can implement easily and, because
of the mechanical changes caused by increased run-
ning cadence, it has the potential to be a successful
intervention for recovering from and preventing
overuse running injuries. Moreover, if a cadence
intervention can reduce potentially injurious biome-
chanics without adverse effects on running ef-
ciency, runners will more likely adopt these gait
alterations as a long-term injuryprevention strategy.
Therefore, the aim of this study was to determine if a
retraining protocol employing increased cadence
results in a decrease in potentially injurious kinetics
and kinematics while maintaining running efciency
in a group of healthy runners. The purpose of this
pilot study was to test the potential effectiveness of
an un-coached, runner-motivated intervention that,
if successful, could be extended to larger populations
of injured or previously injured runners in future
work. We hypothesized that an acute increase in
running cadence will lead to running mechanics
that are less similar to those tied to injury, speci-
cally increased knee exion angle at initial contact,
decreased ankle exion (dorsiexion) angle at initial
contact, decreased heel strike distance and peak hip
adduction angle, decreased peak hip extensor and
abductor moments, decreased knee extensor
moment, increased peak ankle plantar-exor
moment and decreased vertical loading rate while
leading to decreased running efciency (dened
here as increased oxygen uptake at a set running
speed). Additionally, we hypothesised that after 6
weeks of a cadence retraining protocol, runners will
have incorporated kinematic and kinetic changes
into their preferred running form with no decrease
in running efciency.
2. Methods
The study protocol was approved by the institutional
review board for human participants research.
2.1. Participants
Participants were recruited through contact with
local running coaches, running clubs, yers posted
in gyms and by word of mouth. Inclusion criteria
included the following: no musculoskeletal injuries
in the previous 12 months, currently running at least
15 miles/week, being a rear-foot striker as conrmed
by investigator observation and having a preferred
running cadence of 7585 strides/min. This cadence
range was set to select for runners with what clini-
cians and running coaches would describe as low
cadence. Before enrolment, all runners were
screened for preferred running pace and cadence.
To determine preferred pace and cadence, run-
ners were asked to run on a treadmill at a pace
they would select for a typical comfortable run.
Runners with a cadence between 75 and 85 strides/
min were invited to participate. A runners cadence
at enrolment was used as the preferred cadence from
which the retraining cadence was determined, and
pace at screening was used as the pace for all data
capture sessions. Participants provided informed
consent upon enrolling in the study.
Effects of cadence retraining 725
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2.2. Procedure
Data were captured at two time points: before and
immediately after a 6-week cadence retraining inter-
vention. All participants completed a questionnaire
at the initial visit to document current training
volume and regimen, race history and injury history.
A physical therapist performed a basic biomechani-
cal evaluation on all participants at the rst visit to
rule out structural or functional abnormalities. This
evaluation included lower extremity joint passive
range of motion, strength as assessed by manual
muscle testing and specic tests for iliotibial band
and hip exor tightness. A brief evaluation was also
performed at the follow-up visit to determine if there
were any clinically relevant changes. Motion capture
and metabolic data were captured at both visits.
2.2.1. Variables of interest. Variables of interest were
selected because of their documented association
with overuse injuries (Crowell et al., 2010;
Edwards et al., 2009; Noehren et al., 2007; Willson
& Davis, 2008). Kinematic outcome variables
included centre of mass vertical displacement, heel
strike distance (the horizontal distance between the
centre of the pelvis and the ankle at initial contact
(Figure 1)), stride length, knee exion angle at initial
contact, ankle dorsiexion at initial contact and peak
hip adduction angle. Kinetic outcome variables
included internally referenced peak hip abductor
moment, peak hip and knee extensor moments and
ankle plantar-exor moment, and vertical loading
rate (Figure 2; as calculated by Milner et al. (2006)).
2.2.2. Motion capture protocol. During both of the
laboratory visits, kinematic and kinetic data were
collected while the participant ran over ground
across a 30 m runway at self-selected pace and
cadence (as determined at enrolment screening).
Pace was monitored using a Photogate system
(SenSource, Youngstown, OH, USA). Trials were
collected until a total of ve complete strides per side
of kinematic and kinetic data were captured.
Acceptable trials were ±5% of the participants pre-
ferred running pace from enrolment screening. To
acclimate to increasing their running cadence, parti-
cipants then ran on a treadmill for 35 min while
listening to and matching a metronome set at 10%
greater than their preferred cadence. Following this,
overground trials were collected at the +10%
cadence until a total of ve complete strides per
side of kinematic and kinetic data were captured
while runners listened to and matched a metronome.
Speed was monitored and controlled to match the
original self-selected pace.
Kinematic data were captured at 120 Hz using a
twelve-camera motion capture system (Motion
Analysis Corporation, Santa Rosa, CA, USA) and
passive retroreective markers. Lower extremity
kinematics were calculated based on a 54 marker,
six degree of freedom markerset (Figure 3). A static
calibration trial was used to calculate segment char-
acteristics and joint centres. Hip joint centres were
calculated by a regression equation based on the
inter-anterior superior iliac spine distance (as recom-
mended in OrthoTrak software, Motion Analysis
Corporation, Santa Rosa, CA, USA), and knee
joint centres were calculated as the midpoint
Figure 1. X depicts HSD, the horizontal distance between the
centre of the pelvis and the ankle at initial contact.
0.1 0.15
Seconds
0.2 0.250
0
0.05
1
1.5
Times body weight (BW)
2
2.5
3
0.5
Figure 2. Example of vertical ground reaction force prole. The
average vertical loading rate was calculated as the slope of the
curve between 20% and 80% of the time until impact peak
(shown as dashed section) (Milner et al., 2006).
726 J. F. Hafer et al.
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between the medial and lateral femoral epicondyles.
Anatomical markers dened the trunk (right and left
acromioclavicular joints and sacro-lumbar joint),
pelvis (left and right anterior superior iliac spine
and sacro-lumbar joint), thigh (hip joint centre and
medial and lateral femoral epicondyles), shank
(medial and lateral femoral epicondyles, tibial tuber-
osity, and medial and lateral malleoli) and foot (heel
and rst and fth metatarsal heads). Between-day
marker placement reliability has previously been
reported to be acceptable, with the lowest ICC for
the variables examined in this study being reported
as 0.69 for peak hip adduction angle (Ferber,
Noehren, Hamill, & Davis, 2010). In this study,
between-day marker placement variation was also
minimised by having the same, trained investigator
place markers on all participants at both visits. To
ensure consistent shoe conditions within each parti-
cipant before and after 6 weeks of training, all
motion data were captured while participants ran
with laboratory-provided neutral running shoes
(New Balance 1062, Boston, MA, USA). Kinetic
data were captured concurrently at 4800 Hz using
four force plates (Bertec Corp., Columbus, OH
USA and AMTI, Watertown, MA, USA).
2.2.3. Motion capture data processing. Motion cap-
ture data were processed with a custom code written
in LabView (National Instruments, Austin, TX,
USA) and Visual 3D (C-Motion, Inc., Rockville,
MD, USA). Kinematic and kinetic variables were
smoothed using low pass fourth-order Butterworth
lters at 8 Hz and 50 Hz, respectively. Kinematic
and kinetic measures were calculated from ve
acceptable trials for each limb.
2.2.4. Metabolic Data Capture Protocol. After the
motion capture protocol, participants completed
metabolic energy expenditure testing to determine
running efciency. All measures were captured dur-
ing treadmill running at the same pace that partici-
pants ran at during motion capture data collection.
Oxygen uptake (VO2) was rst measured during a
participants self-selected cadence and then at a
cadence 10% higher than the participants self-
selected cadence. A metabolic cart (ParvoMedics,
Sandy, UT, USA) was used to collect oxygen uptake
data. Participants ran for 8 min or until they had
completed 5 min in a steady state for each condition
(self-selected and +10% cadence). Energy expendi-
ture tests were conducted consecutively with no
break between tests. Data for the second phase of
the test were reported once steady state was reached
after the participants change in cadence. Running
efciency was taken as the average oxygen uptake per
minute from the last 5 min of steady-state data.
2.2.5. Cadence retraining protocol. Upon completion
of the initial visit, participants were given instruc-
tions for the cadence retraining period. The cadence
retraining protocol was designed to mimic an infor-
mal intervention that a runner might undertake
themselves. Participants received a 6-week training
log to complete with their +10% cadence recorded
on the log. Participants were informed about and
given access to metronomes, music playlists consist-
ing of songs with tempos at their +10% cadence and
free-access phone and computer applications that
provided these services. Each participant could use
whichever tool they preferred for their training. To
complete their training, runners were instructed to
listen to and match the tempo of the audible tool
they were using. None of the tools the participants
used provided feedback on how well each participant
was matching their prescribed cadence.
Participants were instructed to complete at least
50% of their weekly mileage at their +10% cadence
and to record all training in the training log.
Training could be completed during overground or
treadmill running, whichever the participant pre-
ferred. A study investigator contacted each partici-
pant on a weekly basis to provide encouragement,
monitor participants for injury and ensure adherence
to the training protocol. Training logs were collected
at the second visit.
2.2.6. Visit 2 protocol. The same procedures were
followed for data collection at the second visit.
Pace and +10% cadence were matched to the pace
and +10% cadence selected at visit 1. Preferred
Figure 3. Marker set used for 3D motion analysis.
Effects of cadence retraining 727
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cadence was not constrained at visit 2 to allow for
observation of whether a runners preferred cadence
had changed from visit 1 to 2 as a result of the
retraining period.
2.2.7. Statistics. As one participant dropped out
during the retraining period due to a non-running-
related injury, outcome variables were compared
across two conditions (visit 1 only) for six partici-
pants and across four conditions (visits 1 and 2) for
ve participants.
Outcome variables were calculated for four condi-
tions: visit 1 preferred cadence, visit 1 +10%
cadence, visit 2 preferred cadence and visit 2 +10%
cadence. Effect size was calculated for all variables
for clinically relevant comparisons (visit 1 preferred
versus +10% cadence, visit 1 +10% cadence versus
visit 2 +10% cadence and visit 1 preferred versus
visit 2 preferred cadence). Variables were compared
using generalized estimating equations, including
average values of each variable for each limb of all
participants. For variables not associated with a limb
(VO2, centre of mass vertical displacement, stride
length), repeated measures ANOVAs were used to
compare between conditions. Because of participant
dropout, two sets of statistical analyses were run.
The rst set compares visit 1 preferred cadence to
visit 1 +10% cadence for six participants. The sec-
ond set compares all four conditions for the ve
participants who completed the study. Signicance
was set a priori at P0.05 for all analyses. Post hoc
analyses with Bonferroni corrections to P0.017
were run for variables identied as signicant.
3. Results
Twenty-six runners responded to recruitment
attempts. Most were not eligible for inclusion due
to running cadence over 85 strides/min or an injury
in the last year. Eight runners met inclusion criteria.
Of these eight runners, one became injured and one
moved out of state before they could participate in
visit 1 of the study. Six runners (age 31.0 ± 5.5 years,
1.76 ± 0.1 m, 70.7 ± 13.6 kg) enrolled in the study.
Four participants were female. One participant did
not complete the post-intervention visit due to a
non-running-related injury. All participants were
recreational runners training an average of
18.5 miles/week (s= 5.16). No runners reported
running-related injuries during the retraining period.
At the initial visit, the six participantsoverground
cadence averaged 80.83 (s= 3.13) strides/min and
88.67 (s= 3.50) strides/min for preferred and +10%
conditions, respectively. For the ve participants
who completed the study, visit 1 cadences were
82.88 (s= 4.01) strides/min and 89.91 (s= 1.84)
strides/min for preferred and +10% conditions,
respectively. At visit 2, these ve participants
cadence averaged 84.87 (s= 6.24) strides/min and
91.00 (s= 2.13) strides/min for preferred and +10%
conditions, respectively. This demonstrates a signi-
cant increase in preferred cadence from visits 1 to 2
(P< 0.001, effect size 0.39). Through analysis of
training logs, all participants reported completing at
least 50% of their weekly mileage at their assigned
+10% cadence (average: 61%, range: 5080%).
3.1. Visit 1, preferred cadence versus ±10% cadence
An increase in running cadence resulted in changes
in mechanics in the expected direction without a
change in oxygen consumption. Running efciency
was not signicantly different between conditions.
Centre of mass vertical displacement, heel strike
distance, stride length, ankle dorsiexion angle at
initial contact, hip adduction angle, peak hip abduc-
tor moment, peak knee extensor moment and peak
ankle plantar-exor moment were signicantly
decreased at the +10% cadence condition (Table I).
3.2. Visit 1 versus visit 2
After 6 weeks of a cadence retraining intervention,
runners had a small but signicant increase in pre-
ferred running cadence. This small increase in pre-
ferred cadence translated into decreases in ankle
dorsiexion at initial contact, peak hip adduction
angle and vertical loading rate. Running efciency
was not signicantly different between any condi-
tions. Differences seen between preferred and
+10% conditions were similar to the visit 1 compar-
ison for all variables, with the exception of peak hip
abductor moment (Table II).
4. Discussion
The purpose of this study was twofold: (1) to deter-
mine if changes in mechanics with increased running
cadence come at the cost of running efciency and
(2) to examine if acute adaptations to increased run-
ning cadence are assimilated into a runners pre-
ferred running form after 6 weeks of a simple
intervention with little outside feedback. Our aim
was to determine if an intervention that mimics the
self-imposed and self-monitored interventions many
recreational runners undertake has the potential to
modify potentially injurious mechanics, and if typical
runners are able to adopt these changes in mechanics
without a cost to efciency. The results of this pilot
study support the hypothesis that, after 6 weeks of
cadence retraining, runners alter their preferred run-
ning form in a manner that would potentially
decrease the risk of overuse injury without decreas-
ing their running efciency.
728 J. F. Hafer et al.
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Overall, this pilot study supports the limited litera-
ture documenting that increased running cadence
reduces kinematics and kinetics that have been tied
to overuse running injuries (Heiderscheit et al.,
2011). Additionally, this study demonstrates the
ability of healthy runners to adhere to an uncoached
cadence retraining intervention and that runners can
modify their preferred running mechanics within 6
weeks. The acute (visit 1) differences seen with
increased cadence are similar to mechanical changes
seen with earlier cadence and barefoot running inter-
ventions (Chumanov, Wille, Michalski, &
Heiderscheit, 2012; Giandolini et al., 2013;
Heiderscheit et al., 2011; Squadrone & Gallozzi,
2009). In this group of experienced but not highly
trained runners, increasing cadence by 10% did not
decrease running efciency. Previous studies of
either highly trained (Cavanagh & Williams, 1982)
or novice (Messier & Cirillo, 1989) runners found
little to no change in running efciency with changes
in running cadence or form. This study supports
those works in showing that the running efciency
of recreational runners may not be decreased by
small changes in running form.
The initial changes seen in running mechanics
support our hypothesis that increased cadence
Table II. Final efciency, kinematic and kinetic results for ve participants; post hoc: a = visit 1 preferred cadence different from visit
1 +10% cadence, b = visit 1 +10% cadence different from visit 2 preferred cadence, c = visit 2 preferred cadence different from visit 2 +10%
cadence, d = visit 1 preferred cadence different from visit 2 +10% cadence, e = visit 1 +10% cadence different from visit 2 +10% cadence,
f = visit 1 preferred cadence different from visit 2 preferred cadence.
Visit 1 Preferred
cadence
Visit 1 +10%
cadence
Visit 2 Preferred
cadence
Visit 2 +10%
cadence Effect Size
Average sAverage sAverage sAverage sP-value post-hoc a e f
VO2 (mL/kg*min) 36.4 3.7 36.8 4.1 36.7 4.1 36.8 4.1 0.952^ 0.11 0.00 0.07
CVD (m) 0.11 0.01 0.10 0.00 0.11 0.02 0.09 0.00 0.002^ a,d 1.63 2.82 0.00
HSD (m) 0.23 0.04 0.21 0.04 0.22 0.04 0.20 0.03 <0.001 a,b,c,d 0.50 0.29 0.25
SL (m) 2.29 0.33 2.07 0.21 2.20 0.33 2.05 0.24 0.002^ a,c,d 0.81 0.09 0.27
KFIC (°) 4.3 2.2 6.1 3.5 3.4 4.6 4.8 5.3 <0.001 a,b,c 0.65 0.31 0.26
AFIC (°) 12.6 4.0 11.5 4.1 10.8 3.1 9.7 3.1 <0.001 a,d,e,f 0.28 0.49 0.52
HA (°) 12.3 1.7 10.5 1.8 11.3 1.4 10.2 1.9 <0.001 a,b,c,d,f 1.06 0.16 0.65
HAM (Nm/kg) 1.8 0.2 1.8 0.3 1.7 0.1 1.7 0.2 0.257 0.32 0.41 0.63
HEM (Nm/kg) 1.5 0.5 1.7 0.3 1.3 0.3 1.4 0.4 0.195 0.39 0.71 0.48
KEM (Nm/kg) 2.4 0.5 2.0 0.3 2.3 0.6 2.2 0.5 <0.001 a,c 1.06 0.50 0.07
APM (Nm/kg) 2.7 0.1 2.6 0.1 2.6 0.2 2.6 0.2 0.048 a,d 0.67 0.07 0.39
VLR (BW/sec) 48.0 17.7 46.1 14.7 44.1 16.6 46.2 13.7 <0.001 f 0.12 0.01 0.23
Notes: Effect size reported for clinically relevant comparisons. ^indicates repeated measures comparison. Bold values indicate statistically
signicant difference.
Table I. Running energy expenditure, kinematics and kinetics at baseline for six participants.
Visit 1 preferred cadence Visit 1 +10% cadence
Average sAverage sP-value Effect size
VO2 (mL/kg*min) 38.1 4.7 38.4 5.3 0.259^ 0.07
CVD (m) 0.12 0.01 0.10 0.00 0.004^ 4.00
HSD (m) 0.24 0.06 0.23 0.06 0.002 0.17
SL (m) 2.44 0.47 2.19 0.34 0.009^ 0.62
KFIC (°) 6.0 4.6 7.1 3.9 0.222 0.26
AFIC (°) 13.3 3.9 11.4 3.7 0.021 0.49
HA (°) 12.0 1.7 10.4 1.6 <0.001 0.96
HAM (Nm/kg) 1.8 0.3 1.7 0.3 0.018 0.30
HEM (Nm/kg) 1.7 0.7 1.8 0.5 0.409 0.17
KEM (Nm/kg) 2.5 0.5 2.1 0.5 <0.001 0.79
APM (Nm/kg) 2.7 0.2 2.6 0.1 0.003 0.65
VLR (BW/s) 49.8 16.6 47.7 13.9 0.305 0.14
Notes: CVD: centre of mass vertical displacement; HSD: heel strike distance; SL: stride length; KFIC: knee exion at initial contact; AFIC:
ankle dorsiexion at initial contact; HA: peak hip adduction angle; HAM: peak hip abductor moment; HEM: peak hip extensor moment;
KEM: peak knee extensor moment; APM: peak ankle plantar-exor moment; VLR: vertical loading rate.
^indicates repeated measures comparison.
Bold values indicate statistically signicant difference.
Effects of cadence retraining 729
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would result in decreases in potentially injurious
running mechanics. Decreases in centre of mass
vertical displacement and stride length are thought
to result in increased attenuation of impact forces in
the body, while decreases in heel strike distance and
ankle dorsiexion at initial contact can place the leg
in a more spring-like landing posture (e.g. more
exed knee and possible neutral or plantar-exed
ankle at initial contact), leading to better distribution
of impact through the lower extremity. Longer stride
lengths (Edwards et al., 2009) and a more extended
knee at initial contact (Derrick, 2004) can lead to
greater forces transmitted to the tibia and, presum-
ably, a greater risk of tibial stress fractures. An
increase in peak hip adduction is thought to contri-
bute to more strain on tissues that cross the hip
laterally (e.g. the iliotibial band) either because of
greater magnitude of loading, higher loading rate
(Hamill, Miller, Noehren, & Davis, 2008)ora
longer time spent in a strained alignment.
Decreased knee extensor moments correspond to
decreased forces being transmitted across the knee
and, in combination with changes in knee kine-
matics, may reduce patellofemoral contact forces
(Lenhart, Thelen, Wille, Chumanov, &
Heiderscheit, 2014) and the chance of patellofe-
moral pain.
Supporting our initial hypothesis, several changes
that were seen between preferred and +10% cadence
conditions in visit 1 carried over to preferred
cadence in visit 2. Most promising are the signicant
decreases in peak hip adduction angle and vertical
loading rate, because higher than average values of
these variables have been measured in runners at risk
for iliotibial band syndrome (Ferber et al., 2010;
Noehren et al., 2007), with patellofemoral pain
(Noehren et al., 2012; Willson & Davis, 2008) and
with a history of tibial stress fractures (Milner et al.,
2006; Pohl et al., 2008). While changes between pre-
and post-intervention preferred running mechanics
are not as numerous as those between preferred and
+10% conditions, the average change in preferred
cadence was only +2.4% for the entire group. This
suggests that signicant benets may be possible
with only a small change in running cadence.
While these results are derived from a small sam-
ple, the consistency and direction of the improve-
ments in the kinematic and kinetic parameters across
conditions are promising and support the need for
future research. Several variables (heel strike dis-
tance, stride length, hip, knee and ankle moments)
showed differences between the preferred and +10%
cadence conditions at both visits 1 and 2 and also
decreased modestly when comparing visits 1 and 2
preferred cadence conditions, but these differences
did not reach statistical signicance due to low
power. Some variables also showed slight decreases
from visit 1 +10% cadence to visit 2 +10% cadence,
demonstrating that runners continue to adapt to
intervention-imposed constraints past the acute
stage. These trends suggest that longer or more
structured interventions may lead to additional
changes in running mechanics.
While this study demonstrates that recreational
runners are able to adopt the potentially benecial
mechanics of a simple cadence retraining interven-
tion through a minimally monitored program, none
of the runners in this study had a recent history of
overuse injuries and therefore may have responded
differently than runners who have symptoms of an
overuse injury or who have a history of overuse
injury. However, it is promising that healthy runners
were able to complete this intervention without alter-
ing their training volume or sustaining running inju-
ries, supporting the potential clinical effectiveness of
this interventional approach. From some prospective
studies, it may be inferred that historically uninjured
runners possess mechanics that are closer to optimal
compared with runners who will go on to be injured
(Noehren et al., 2007). The presence of potentially
injurious mechanics may leave these runners with
more room for positive alterations in their running
form, but this question would have to be answered
by future studies. The ndings of a reduction in
potentially injurious mechanics in healthy runners
preferred running form without a decrease in run-
ning efciency support investigation of cadence
retraining interventionseffects on runners with or
at risk of overuse injury.
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... Increasing the step rate has been shown to decrease peak ground reaction forces and loading rates, which may require less energy absorption from the lower extremity musculature and joints [17][18][19][20][21]. Increasing step rate effectively draws the foot closer to the body center of mass at ground contact, reducing vertical oscillation of the center of mass, thereby reducing the energy absorbed by the lower limbs, and altering joint kinematics [20,21]. For example, increasing step rate has been shown to decrease peak hip adduction [20,[22][23][24], peak knee abduction [25], and peak rearfoot eversion [2], all of which have been implicated in the development of specific RRIs [10,15,26]. ...
... Some authors have suggested that tibial internal rotation could also be caused by more proximal mechanisms, such as changes at the hip [39]. Increasing step rate has been shown to affect motion at the hip [2,20,23,25], adding support for hip compensation to impact these changes seen in tibial rotation early in stance. This period of significance in the first 30% of stance did not include peak tibial internal rotation; however, significant differences were observed when the discrete values were compared between conditions. ...
... This study also only tested the acute effects of increased step rate on measures of rearfoot kinematics and ground reaction forces. Previous investigations implementing at-home or in-lab gait retraining sessions over the course of multiple weeks or months have shown that participants are able to effectively alter their step rate [19,22,23,[44][45][46][47]. However, the longitudinal effects on rearfoot motion, and whether the modifications in rearfoot angles and ground reaction forces would still be observed after implementing a longer-term gait retraining protocol, remain unknown. ...
Article
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Relatively high frontal and transverse plane motion in the lower limbs during running have been thought to play a role in the development of some running-related injuries (RRIs). Increasing step rate has been shown to significantly alter lower limb kinematics and kinetics during running. The purpose of this study was to evaluate the effects of increasing step rate on rearfoot kinematics, and to confirm how ground reaction forces (GRFs) are adjusted with increased step rate. Twenty runners ran on a force instrumented treadmill while marker position data were collected under three conditions. Participants ran at their preferred pace and step rate, then +5% and +10% of their preferred step rate while being cued by a metronome for three minutes each. Sagittal and frontal plane angles for the rearfoot segment, tibial rotation, and GRFs were calculated during the stance phase of running. Significant decreases were observed in sagittal and frontal plane rearfoot angles, tibial rotation, vertical GRF, and anteroposterior GRF with increased step rate compared with the preferred step rate. Increasing step rate significantly decreased peak sagittal and frontal plane rearfoot and tibial rotation angles. These findings may have implications for some RRIs and gait retraining.
... Adopting a forefoot strike pattern has been shown to reduce impact loading (Cheung & Davis, 2011) and tibiofemoral joint loading (Bowersock et al., 2017). Increased step rate has been shown to reduce impact loading (Hafer et al., 2015) and to lower mechanical energy absorbed by the hip and knee joints (Heiderscheit et al., 2011). Running softer can lead to decreased impact loading (Crowell et al., 2010) and anterior trunk lean has been suggested as a gait modification to soften footfalls (Arendse et al., 2004). ...
... To eliminate speed and footwear effects, the same running speed and shoes were used for all subsequent trials. Participants then performed three specifically trained gait modification trials in a randomised order: forefoot strike pattern, increased step rate (10% increased Bowersock et al., 2017;Hafer et al., 2015) and anterior trunk lean posture (10-degree increased trunk flexion Teng & Powers, 2014). Each trial lasted 5 min, and participants rested for 5 min or longer if requested between trials. ...
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Impact loading has been associated with running-related injuries, and gait retraining has been suggested as a means of reducing impact loading and lowering the risk of injury. However, gait retraining can lead to increased perceived awkwardness and effort. The influence of specifically trained and self-selected running gait modifications on acute impact loading, perceived awkwardness and effort is currently unclear. Sixteen habitual rearfoot/midfoot runners performed forefoot strike pattern, increased step rate, anterior trunk lean and self-selected running gait modifications on an instrumented treadmill based on real-time biofeedback. Impact loading, perceived awkwardness and effort scores were compared among the four gait retraining conditions. Self-selected gait modification reduced vertical average loading rate (VALR) by 25.3%, vertical instantaneous loading rate (VILR) by 27.0%, vertical impact peak (VIP) by 16.8% as compared with baseline. Forefoot strike pattern reduced VALR, VILR and peak tibial acceleration. Increased step rate reduced VALR. Anterior trunk lean did not reduce any impact loading. Self-selected gait modification was perceived as less awkward and require less effort than the specifically trained gait modification (p < 0.05). These findings suggest that self-selected gait modification could be a more natural and less effortful strategy than specifically trained gait modification to reduce acute impact loading, while the clinical significance remains unknown.
... Step frequency manipulation is one of the fundamental locomotor strategies, and there should be an optimum step frequency to minimize GRFs on the intact limb. It has been reported that able-bodied individuals can be trained to vary step frequency at a given running speed resulting in changing GRFs [31,32]. Thus, retraining of step frequency in individuals with amputation should also be viable [29,30]. ...
Article
Full-text available
Background: Individuals with unilateral transfemoral amputation are prone to developing health conditions such as knee osteoarthritis, caused by additional loading on the intact limb. Such individuals who can run again may be at higher risk due to higher ground reaction forces (GRFs) as well as asymmetric gait patterns. The two aims of this study were to investigate manipulating step frequency as a method to reduce GRFs and its effect on asymmetric gait patterns in individuals with unilateral transfemoral amputation while running. Methods: This is a cross-sectional study. Nine experienced track and field athletes with unilateral transfemoral amputation were recruited for this study. After calculation of each participant's preferred step frequency, each individual ran on an instrumented treadmill for 20 s at nine different metronome frequencies ranging from - 20% to + 20% of the preferred frequency in increments of 5% with the help of a metronome. From the data collected, spatiotemporal parameters, three components of peak GRFs, and the components of GRF impulses were computed. The asymmetry ratio of all parameters was also calculated. Statistical analyses of all data were conducted with appropriate tools based on normality analysis to investigate the main effects of step frequency. For parameters with significant main effects, linear regression analyses were further conducted for each limb. Results: Significant main effects of step frequency were found in multiple parameters (P < 0.01). Both peak GRF and GRF impulse parameters that demonstrated significant main effects tended towards decreasing magnitude with increasing step frequency. Peak vertical GRF in particular demonstrated the most symmetric values between the limbs from - 5% to 0% metronome frequency. All parameters that demonstrated significant effects in asymmetry ratio became more asymmetric with increasing step frequency. Conclusions: For runners with a unilateral transfemoral amputation, increasing step frequency is a viable method to decrease the magnitude of GRFs. However, with the increase of step frequency, further asymmetry in gait is observed. The relationships between step frequency, GRFs, and the asymmetry ratio in gait may provide insight into the training of runners with unilateral transfemoral amputation for the prevention of injury.
... If not provided, the analyzed distance was calculated from the reported speed. If only the number of steps or insufficient information was reported for determining the analyzed distance, equivalences between 200 m, 60 s, and 150 steps/min were used-200 m in 60 s corresponds with a speed of 3.33 m/s, which is a common intermediate running speed [9,10], and 150 steps/min is on the low end of preferred running cadence [11][12][13][14], representing a low threshold of number of steps that equates to 200 m. ...
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... 8 Gait retraining uses feedback strategies, such as real-time visual feedback of impact loading 11,12 or joint kinematics, 43,53 verbal feedback from a therapist, 19 or audible feedback from an external device (eg, metronome). 23 Biomechanical changes in response to feedback may facilitate a more efficient running technique 13,21 and reduce running-related injuries. 8 In 2015, there was limited evidence of the effects of gait retraining on clinical outcomes and an absence of randomized controlled trials (RCTs). ...
Article
Objective: To evaluate the effectiveness of running gait retraining on kinematics, kinetics, performance, pain, and injury in distance runners. Design: Intervention systematic review with meta-analysis. Literature search: Seven electronic databases from inception to March 2021. Study selection criteria: Randomised controlled trials that (i) evaluated running gait retraining compared to no intervention, usual training, placebo, or standard care, and (ii) reported biomechanical, physiological, performance, or clinical outcomes. Data synthesis: Random-effects meta-analyses were completed, and the certainty of evidence was judged using the GRADE criteria. We categorised interventions into step-rate, non-rearfoot footstrike, impact, ground contact time, and multi-parameter subgroups. Results: We included 19 trials (673 participants). Moderate certainty evidence indicated step rate gait retraining increased step rate (SMD 1.03 [95% CI: 0.63, 1.44]; number of trials (N): 4; I2: 0%) and reduced average vertical loading rate (SMD -0.57 [95% CI: -1.05, -0.09], N: 3; I2: 0%). Low certainty evidence indicated non-rearfoot footstrike retraining increased knee flexion at initial contact (SMD 0.74 [95% CI: 0.11, 1.37]; N: 2; I2: 0%), but did not alter running economy (SMD 0.21 [95% CI: -1.11, 1.52]; N: 3; I2: 19%).). Low certainty evidence indicated multi-parameter retraining did not alter running economy (SMD 0.32 [-0.39, 1.02]; N: 3; I2: 19%) or performance (SMD 0.14 [95% CI: -4.87, 4.58]; N: 2; I2: 18%). Insufficient trials reported on pain outcomes. Two trials demonstrated reduced 1 year injury incidence following gait retraining. Conclusions: Gait retraining interventions altered step rate and knee kinematics, lowered vertical loading rates, and did not affect running performance. J Orthop Sports Phys Ther, Epub 5 Feb 2022. doi:10.2519/jospt.2022.10585.
... Runners have successfully increased step rate up to 18 steps/min following a few weeks of training sessions involving cueing and feedback. 30,36,37 However, this magnitude of change may not be necessary to reduce injury risk. Runners may experience meaningful reductions in BSI risk with subtle, attainable increases in step rate. ...
Article
Objectives To determine if running biomechanics and bone mineral density (BMD) were independently associated with bone stress injury (BSI) in a cohort of National Collegiate Athletic Association Division I cross country runners. Methods This was a prospective, observational study of 54 healthy collegiate cross country runners over three consecutive seasons. Whole body kinematics, ground reaction forces (GRFs) and BMD measures were collected during the preseason over 3 years via motion capture on an instrumented treadmill and total body densitometer scans. All medically diagnosed BSIs up to 12 months following preseason data collection were recorded. Generalised estimating equations were used to identify independent risk factors of BSI. Results Univariably, step rate, centre of mass vertical excursion, peak vertical GRF and vertical GRF impulse were associated with BSI incidence. After adjusting for history of BSI and sex in a multivariable model, a higher step rate was independently associated with a decreased risk of BSI. BSI risk decreased by 5% (relative risk (RR): 0.95; 95% CI 0.91 to 0.98) with each one step/min increase in step rate. BMD z-score was not a statistically significant risk predictor in the final multivariable model (RR: 0.93, 95% CI 0.85 to 1.03). No other biomechanical variables were found to be associated with BSI risk. Conclusion Low step rate is an important risk factor for BSI among collegiate cross country runners and should be considered when developing comprehensive programmes to mitigate BSI risk in distance runners.
... In previous studies, explicit instructions about running technique have been given to participants with the intention of reducing impact 29,30 . In these studies [30][31][32][33][34][35][36] groups of shod runners were asked to substantially increase their running cadence (i.e., steps per minute) or to change to an anterior foot strike pattern 9-31. . Besides explicitly imposing a particular change in running technique, a more personalized approach is to let the runner discover his or her own motor strategy of lower impact running with the use of biofeedback as in 10,16 . ...
Article
Full-text available
Methods to reduce impact in distance runners have been proposed based on real-time auditory feedback of tibial acceleration. These methods were developed using treadmill running. In this study, we extend these methods to a more natural environment with a proof-of-concept. We selected ten runners with high tibial shock. They used a music-based biofeedback system with headphones in a running session on an athletic track. The feedback consisted of music superimposed with noise coupled to tibial shock. The music was automatically synchronized to the running cadence. The level of noise could be reduced by reducing the momentary level of tibial shock, thereby providing a more pleasant listening experience. The running speed was controlled between the condition without biofeedback and the condition of biofeedback. The results show that tibial shock decreased by 27% or 2.96 g without guided instructions on gait modification in the biofeedback condition. The reduction in tibial shock did not result in a clear increase in the running cadence. The results indicate that a wearable biofeedback system aids in shock reduction during over-ground running. This paves the way to evaluate and retrain runners in over-ground running programs that target running with less impact through instantaneous auditory feedback on tibial shock.
Thesis
Running is a gross-motor skill and a popular physical activity, though it comes with a risk of injury. Gait retraining is performed with the intent on managing the risk of running injury. The peak tibial acceleration may be linked with running injuries and is suitable as input for biofeedback. So far, retraining programs with the use of biofeedback on peak tibial acceleration have been bound to a treadmill. Therefore, the objective of this doctoral thesis was to evaluate the effectiveness of a novel music-based biofeedback system on peak tibial acceleration in the context of gait retraining in a training environment. This system is wearable and has lightweight sensors to attach to the lower leg. The sensor first records the tibial acceleration. Then, a processing unit detects the acceleration spike for direct auditory biofeedback. Studies 1 to 5 covered the measurement of peak tibial accelerations, the design of the music-based feedback, and the effectiveness evaluation of the biofeedback system for impact reduction in a training center. In study 1 the peak tibial acceleration of a group of distance runners was reliable in the same test and repeatable in a re-test. The peak tibial accelerations increased with running speed and were correlated with the maximum vertical loading rate of the ground reaction force, which is an impact characteristic derived in the biomechanics laboratory. The developed peak detection algorithm identified the peak tibial acceleration in real-time. The music-based feedback was developed in study 2. The music was superimposed with perceptible pink noise. The noise intensity could be linked to a biological parameter such as the peak acceleration tibial. The tempo of the music synchronized with the cadence of the runner to motivate the runner and allowed for a user-induced change in cadence in response to the biofeedback. Studies 3 to 5 examined the effectiveness of music-based biofeedback on the peak tibial peak in a training environment. We demonstrated that smaller peak values are achievable with the aid of the validated biofeedback system. In study 3, ten runners with high peak tibial acceleration were subjected to biofeedback on the momentary peak tibial acceleration. The group was able to reduce their peak tibial acceleration by 27% or 3 g in the biofeedback condition. Study 4 evaluated the initial learning effect within a single session at ~11.5 km/h. The main change in peak acceleration occurred after approximately 8 minutes of biofeedback. However, there was substantial between-subject variation in time which ranged from 4 to 1329 gait cycles. Study 5 confirmed the effectiveness of the biofeedback in a quasi-randomized study with control group. The experimental group received the biofeedback in a 3-week retraining program comprising of biofeedback faded in time. The control group received tempo-synchronized music as placebo. A running speed of approximately 10 km/h was maintained session after session via speed feedback. All runners completed the running program consisting of 6 sessions. The peak acceleration decreased by 26% or 3 g in the experimental group. The smaller peak values in studies 3-5 must have resulted from a movement alteration, although there was no significant change in running cadence at the group level. Studies 6 to 9 give insight into possible strategies for low(er) peak tibial acceleration in level running. In study 6, we discovered that peak tibial accelerations depend on the manner of heel striking. Specifically, a more pronounced heel landing was correlated with smaller axial (1D) and resultant (3D) peak tibial accelerations. The multicenter results of study 7 showed greater resultant peak acceleration in non-rearfoot strikes compared with heel strikes. This greater acceleration was due to an abrupt horizontal deceleration of the lower leg. In study 8, we described and compared the running mechanics of a successful long-distance runner with low (impact) load and a high load capacity. A pronounced heel strike in conjunction with long stance and short flight phases characterized a low-impact runner who successfully completed 100 marathons in 100 days. Study 9 documented adaptations post-biofeedback in a lab center. There was no clear relationship between the changes in peak tibial acceleration and in running cadence, which confirmed the results of the data captured in the training center. Casuistry showed visually detectable changes in the curve of the vertical ground reaction force. A runner with high peak tibial acceleration peaks changed to a more pronounced rearfoot strike or changed to a non-rearfoot strike pattern to reduce the axial peak tibial acceleration. These results suggest the existence of different distal strategies for impact reduction elicited by biofeedback. Our experiments opened the possibility of impact reduction with the use real-time auditory biofeedback that is perceptible and motivating. Two motor strategies were discovered to run with less peak tibial acceleration. We hope these findings offer encouragement for runners, coaches and clinicians who wish to target a form of low(er) impact running. The biofeedback system effectively modified the running form and has great ecological value due to the portable hardware and energy source for outdoor usage. User-oriented biofeedback systems should become available for the consumer and the patient if proven useful for respectively injury reduction and injury management. Overall, this doctoral thesis contributed to a better understanding of impact severity in distance running and its reduction in a gait retraining context with the use of real-time music-based biofeedback.
Article
Full-text available
Background Increasing cadence in running has been advocated as a means to improve performance and reduce impact forces. Although acoustic pacing can be used for this purpose, it might by itself lead to an increased impact force, which would counteract the decrease in impact force that is being pursued by increasing the cadence with acoustic pacing and thus have a counterproductive effect. Research question What are the effects of acoustic pacing and cadence on peak impact force and loading rate during running? Methods Unpublished data from a previous study, in which 16 participants ran on an instrumented treadmill with various forms of acoustic pacing, were analyzed to address the research question. Peak impact force and loading rate while running with and without pacing, at three different cadences were extracted from the ground reaction force data and compared statistically between these two main conditions. In addition, we compared step-based and stride-based pacing, and paced and unpaced steps within stride-based pacing conditions. Results As expected, increasing the cadence was accompanied by a significant reduction in peak impact force and instantaneous vertical loading rate, whereas acoustic pacing had no significant effect on the impact forces compared to unpaced running with similar cadence, both before and after pacing. There were also no significant differences in this regard between step- and stride-based pacing. Significance Acoustic pacing does not adversely affect impact force when used to increase cadence in running with the aim of reducing the impact force and can thus be used for this purpose without introducing a counterproductive effect.
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• This prospective study of 583 habitual runners used baseline information to examine the relationship of several suspected risk factors to the occurrence of running-related injuries of the lower extremities that were severe enough to affect running habits, cause a visit to a health professional, or require use of medication. During the 12-month follow-up period, 252 men (52%) and 48 women (49%) reported at least one such injury. The multiple logistic regression results identified that running 64.0 km (40 miles) or more per week was the most important predictor of injury for men during the follow-up period (odds ratio=2.9). Risk also was associated with having had a previous injury in the past year (odds ratio = 2.7) and with having been a runner for less than 3 years (odds ratio=2.2). These results suggest that the incidence of lower-extremity injuries is high for habitual runners, and that for those new to running or those who have been previously injured, reducing weekly distance is a reasonable preventive behavior.(Arch Intern Med. 1989;149:2565-2568)
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