Sex-Specific Differences in Running Injuries: A Systematic Review with Meta-Analysis and Meta-Regression

Abstract

Background
Running is a popular sport with high injury rates. Although risk factors have intensively been investigated, synthesized knowledge about the differences in injury rates of female and male runners is scarce.

Objective
To systematically investigate the differences in injury rates and characteristics between female and male runners.

Methods
Database searches (PubMed, Web of Science, PEDro, SPORTDiscus) were conducted according to PRISMA guidelines using the keywords “running AND injur*”. Prospective studies reporting running related injury rates for both sexes were included. A random-effects meta-analysis was used to pool the risk ratios (RR) for the occurrence of injuries in female vs. male runners. Potential moderators (effect modifiers) were analysed using meta-regression.

Results
After removal of duplicates, 12,215 articles were screened. Thirty-eight studies were included and the OR of 31 could be pooled in the quantitative analysis. The overall injury rate was 20.8 (95% CI 19.9–21.7) injuries per 100 female runners and 20.4 (95% CI 19.7–21.1) injuries per 100 male runners. Meta-analysis revealed no differences between sexes for overall injuries reported per 100 runners (RR 0.99, 95% CI 0.90–1.10, n = 24) and per hours or athlete exposure (RR 0.94, 95% CI 0.69–1.27, n = 6). Female sex was associated with a more frequent occurrence of bone stress injury (RR (for males) 0.52, 95% CI 0.36–0.76, n = 5) while male runners had higher risk for Achilles tendinopathies (RR 1. 86, 95% CI 1.25–2.79, n = 2). Meta-regression showed an association between a higher injury risk and competition distances of 10 km and shorter in female runners (RR 1.08, 95% CI 1.00–1.69).

Conclusion
Differences between female and male runners in specific injury diagnoses should be considered in the development of individualised and sex-specific prevention and rehabilitation strategies to manage running-related injuries.

Full text

Vol.:(0123456789)
Sports Medicine (2021) 51:1011–1039
https://doi.org/10.1007/s40279-020-01412-7
SYSTEMATIC REVIEW
Sex‑Specific Differences inRunning Injuries: ASystematic Review
withMeta‑Analysis andMeta‑Regression
KarstenHollander1,2 · AnnaLinaRahlf3 · JanWilke4 · ChristopherEdler5 · SimonSteib6 · AstridJunge1,7 ·
AstridZech3
Accepted: 10 December 2020 / Published online: 12 January 2021
© The Author(s) 2021
Abstract
Background Running is a popular sport with high injury rates. Although risk factors have intensively been investigated,
synthesized knowledge about the differences in injury rates of female and male runners is scarce.
Objective To systematically investigate the differences in injury rates and characteristics between female and male runners.
Methods Database searches (PubMed, Web of Science, PEDro, SPORTDiscus) were conducted according to PRISMA
guidelines using the keywords “running AND injur*”. Prospective studies reporting running related injury rates for both
sexes were included. A random-effects meta-analysis was used to pool the risk ratios (RR) for the occurrence of injuries in
female vs. male runners. Potential moderators (effect modifiers) were analysed using meta-regression.
Results After removal of duplicates, 12,215 articles were screened. Thirty-eight studies were included and the OR of 31
could be pooled in the quantitative analysis. The overall injury rate was 20.8 (95% CI 19.9–21.7) injuries per 100 female
runners and 20.4 (95% CI 19.7–21.1) injuries per 100 male runners. Meta-analysis revealed no differences between sexes for
overall injuries reported per 100 runners (RR 0.99, 95% CI 0.90–1.10, n = 24) and per hours or athlete exposure (RR 0.94,
95% CI 0.69–1.27, n = 6). Female sex was associated with a more frequent occurrence of bone stress injury (RR (for males)
0.52, 95% CI 0.36–0.76, n = 5) while male runners had higher risk for Achilles tendinopathies (RR 1. 86, 95% CI 1.25–2.79,
n = 2). Meta-regression showed an association between a higher injury risk and competition distances of 10km and shorter
in female runners (RR 1.08, 95% CI 1.00–1.69).
Conclusion Differences between female and male runners in specific injury diagnoses should be considered in the develop-
ment of individualised and sex-specific prevention and rehabilitation strategies to manage running-related injuries.
Supplementary Information The online version contains
supplementary material available at https ://doi.org/10.1007/s4027
9-020-01412 -7.
* Karsten Hollander
karsten.hollander@medicalschool-hamburg.de
Extended author information available on the last page of the article
Key Points
There were no differences between female and male run-
ners in overall injury rates.
Female runners had more bone stress injuries.
Male runners had more Achilles tendon injuries.
Shorter competition distances increase the risk of injury
for female runners.
1 Introduction
Running is a very popular sport practiced all over the world.
While regular physical activity and sports such as running
are beneficial for prevention and rehabilitation of many
health complaints (“exercise is medicine”) [1, 2], running
is frequently associated with high injury prevalence and
incidence rates [3–5].
For injury prevention, risk factors need to be well
understood [6]. Risk factors for running are manifold
and consist of training load, biomechanical, anatomical
and anthropometrical variables [7–12]. While some previ-
ous studies exclusively investigated either male [9, 13] or
female [14–16] runners, sex has been suggested to be a
risk factor for specific injury patterns in running, as well
as for overall injury risk [7, 17, 18]. This is supported by
a study investigating injury rates for female and male elite
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1012 K.Hollander et al.
running athletes [19]. Analysing data collected during 14
international athletics championships, Edouard etal. [19]
showed that male elite athletes had lower injury incidence
rates for bone stress injuries (BSI) than female counter-
parts. However, injury risks differed between sexes for
running disciplines (from middle distances upwards)
although only with a small to trivial relative risk (1.5
for middle distances, 0.9 for long distances and 1.3 for
marathon running) [19].
Including and investigating both sexes in running injury
research is in line with evidence for the different risks
between female and male athletes for specific types of inju-
ries such as anterior cruciate ligament ruptures or concus-
sions in different team sports as well as ankle sprains in all
sports [20–22]. However, considering the current literature,
it is difficult to derive conclusive summaries about differ-
ences in overall or specific injury epidemiology for both
sexes in specific sports [18]. To develop and optimize indi-
vidualized prevention and treatment options for running
injuries, it is crucial to understand if and to what extent
injury epidemiology differs between the sexes. Therefore,
the aim of this systematic review was to evaluate the differ-
ences in injury rates and characteristics between male and
female runners using meta-analytical techniques. First, dif-
ferences in overall injury rates were compared between both
sexes. Secondly, depending on the availability of sufficient
data, specific injury diagnoses were analysed regarding their
occurrence in female and male runners.
2 Methods
This study was conducted and presented according to
the PRISMA guidelines for reporting systematic reviews
and meta-analysis [23]. Prior to the start of the study, the
review protocol was registered in the PROSPERO database
(CRD4201911883).
2.1 Search Strategy andInclusion Criteria
Two independent investigators (K.H. and C.E.) conducted a
systematic literature search including articles from inception
till April 2020. Prospective cohort studies and randomized
controlled trials investigating healthy runners from differ-
ent age groups were included. The search was restricted to
articles from peer-reviewed journals published in English,
German, or Spanish languages. Furthermore, studies had to
report rates of running-related injuries for both sexes. Over-
all injury rates and injury rates for specific locations, diagno-
ses or injury mechanisms were considered. Included running
disciplines were middle distance and long-distance track as
well as cross-country, trail and road running. There was no
restriction to a specific injury definition. Reviews, systematic
reviews, commentaries, case studies, case series, cross-sec-
tional studies, retrospective studies and interventional arms
of randomised controlled trials (RCT) were excluded. For
RCTs, only untreated control groups were considered.
The search strategy using specific keywords (running
AND injur*) was applied to four different databases (Pub-
Med, Web of Science, PEDro, SPORTDiscus). All databases
were searched to identify relevant studies based on keywords,
title and abstract. Two independent investigators (C.E. and
K.H.) extracted relevant studies based on the inclusion cri-
teria first by readingthe title, the abstract and the full text, if
available. A third reviewer (A.Z.) was available for consensus
decisions. The bibliographical information of included arti-
cles was examined for further relevant references (backward
search). A forward search was done via citation tracking using
Web of Science® (Thomson Reuters).
2.2 Data Extraction
Study characteristics (design, running discipline, population,
age and number of participants) as well as prevalence and inci-
dence rates for both sexes were extracted. For prevalence rates,
number of injuries or number of injured runners were related to
the number of runners investigated. For incidence rates, number
of injuries and specific exposures (in hours, kilometres or ath-
lete exposure) were used. An athlete exposure (AE) is defined
as one athlete participating in one practice or competition [24].
When it was not possible to extract the data from an article
for specific running distances (e.g., pooling of overall injuries
for track disciplines), corresponding authors were contacted
by email to obtain the data. If specific data were not able to be
obtained, the respective study was included in the systematic
review but not in subsequent analyses.
2.3 Study Quality Assessment
Due to insufficient study quality assessment tools in sports
injury epidemiology, a new tool was developed by consensus
of K.H., A.J., A.L.R., A.Z. and S.S. on the basis of previ-
ously used tools [20, 22, 25, 26]. The modification ensured
that all relevant points regarding the quality of the study
design and important content-related information would be
considered—e.g., differences in methodological approaches
such as competition or season, or the type of data collection.
This tool consisted of 15 items on recruitment, reporting,
injury and exposure collection, injury definition and drop-
out (Table1).
The identified quality score was used to determine a high
(above the median) or low (below the median) study qual-
ity of the studies investigated (median score was 18). Two
independent reviewers (K.H., A.J.) with a third reviewer
(A.L.R.) for consensus assessed the study quality of the
included studies.
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1013
Sex-Specific Differences in Running Injuries
Publication bias was checked by visual inspection of fun-
nel plots (log risk ratio against standard errors) and regres-
sion test for funnel plot asymmetry.
2.4 Data Synthesis andStatistics
To compare injury risk between male and female runners,
risk ratios (RR) with 95% confidence intervals (CI) were
computed for each study. Meta-analytic pooling was done
using a random-effects model (DerSimonian and Laird
method [27]). Between-study heterogeneity was estimated
using Cochran’s Q and I2 statistics. To reveal potential publi-
cation biases, funnel plots were constructed if more than ten
studies were available [28]. Besides visually checking their
symmetry, Egger’s regression test was applied.
Following the calculation of pooled RRs, we used a
mixed-effects meta-regression model to identify variables
potentially affecting the outcome of the meta-analysis
[27]. The choice of tested moderators (effect modifiers)
was based on three criteria: (1) a plausible impact on the
tested variables, (2) reporting in the included studies, (3)
sufficient variation of the moderators’ values [29]. The
following moderators were submitted into the meta-regres-
sion model: performance/expertise level (recreational: no
competitions, competitive: participating in local competi-
tions, elite: qualifying for national or international com-
petitions); age (youth: < 18, adult: ≥ 18) competition dis-
tance (≤ 10km, > 10km); study quality (low: study quality
score < 18, high: study quality score ≥ 18), training dura-
tion (low: < 7.5h or high: ≥ 7.5h/week), training mileage
(low: < 64km/week, high: ≥ 64/week). Moderator analyses
were performed if ten or more studies were available [28].
If a significant moderator was detected, a subgroup analy-
sis comparing the respective values of the moderator was
performed using the meta-analytic procedures described
above.
All calculations were performed using algorithms of
the metaphor package embedded in R (R Foundations for
Statistical Computing, Vienna, Austria) as well as the soft-
ware JAMOVI [30] and OpenMeta [Analyst] software (OS
X version 10.12 obtained from http://www.cebm.brown
.edu/openm eta/).
3 Results
3.1 Search Results
The search returned 15,914 studies and 29 additional stud-
ies were identified through other sources. After removing
3699 duplicates and applying inclusion criteria, a total
of 38 studies were considered eligible [7, 19, 24, 31–65].
Thirty-one of them could be included in the quantitative
analysis. Seven studies reported on the same data sets as
other included studies and were excluded from the quan-
titative analysis [19, 31–33, 39, 40, 65]. The full literature
search process is displayed in Fig.1.
Table 1 Risk of bias assessment tool
Question Rating
Are the sources and methods of participant recruitment clearly
described?
Yes (1), no (0)
Are the relevant characteristics (n, age, sex, sport, level of competition)
of the study population reported?
Yes (1), no (0)
Does the study cover season and/or tournaments/championships? Season (2), tournaments (1), not reported (0)
Are exposure data recorded? Yes (1), no (0)
Is the frequency of data collection reported? Yes (1), no (0)
If yes: ≥ Daily (3), ≥ weekly (2), ≥ monthly (1), not reported (0)
Is a clear injury definition provided? Yes (1), no (0)
If yes: Medical attention (3), time loss (2), other (1), no clear definition (0)
Is the method for assessing exposure described? Yes (1), no (0)
If yes: Individual data collection (2), exposure estimated (1), not reported (0)
Is the method for assessing injury reported? Yes (1), no (0)
If yes: Briefed medical personnel (3), medical personnel (2), coach, self-
report, media reports (1), not reported (0)
Are characteristics of injury reported (location, type, mechanism, sever-
ity, recurrent)?
Yes (1), no (0)
If yes: Complete (2), partly (1), no (0)
Is the drop out < 30% drop out? Yes (1), no (0)
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1014 K.Hollander et al.
3.2 Characteristics ofIncluded Studies
Of the included studies, 36 reported injury data from 35,689
participants (40.8% female). Two studies reporting on inju-
ries from the National Collegiate Athletic Association
(NCAA) database did not state the number of athletes but
did report the athlete exposure (242,244 athlete exposures
with 46.7% females [24] and 276,207 athlete exposures with
50.7% females [59]). Most studies were prospective cohort
studies (n = 37), while the control group (not receiving any
intervention) from one randomised controlled study met the
inclusion criteria [42]. Twenty-three studies investigated
road runners, 11 track runners (middle and long distance),
10 cross-country runners and 3 studies reported on trail
running/orienteering (Table2). Studies from major competi-
tions (European or World Championships) reported concur-
rently on track and road running (half or full marathon) [19,
31–33, 41]. Regarding competition level, 18 studies reported
on novice and recreational runners, 11 on competitive and 9
on elite runners. Study characteristics of all included studies
are summarized in Table2.
3.3 Study Quality
The two independent reviewers evaluating study quality
agreed on 441 of 570 evaluated items (agreement = 77.4%).
The scores for study quality ranged between 9 and 23 out of
24 points with a median of 18 and a mean ± SD of 16.8 ± 4.1.
Fig. 1 Flow diagram displaying the literature search
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1015
Sex-Specific Differences in Running Injuries
Table 2 Study characteristics
Study Sport Cohort/
populations,
(Country)
Level Number of
participants
(female/male)
Age (years) Duration of data
collection
Injury defini-
tion
Exposure
measurement
Injury rates
(overall)
Injury rates
(female/male)
Risk
of bias
score
Nicholl etal.
[54]
Marathon Sheffield
Marathon
(1982) par-
ticipants
Recreational 53/2236 over 18 1day Contact with
medical staff
at first-aid
posts
One full
marathon
18 injured
runners
per 100
marathon
runners
Female: 32
injured run-
ners per 100
marathon
runners;
Male: 17.5
injured run-
ners per 100
marathon
runners
14
Hughes etal.
[47]
Road racing Chicago Dis-
tance Clas-
sic (20km)
Recreational 188/1071 32.3 (range
9—75)
1day Self-reported
specific
orthopaedic
problems
20km race 28.4 injured
runners per
100 runners
Female: 54.3
injured run-
ners per 100
runners;
Male: 31.6
injured run-
ners per 100
runners
11
Johansson
[49]
Orienteers College stu-
dents
Elite 33/56 17.5 ± 1.5 1year Time loss
training or
competition
injuries
Daily train-
ing logs,
monthly
reports of
training
3 injuries per
1000h;
74 injuries
per 100 run-
ners
Female: 72.7
injuries per
100 runners;
Male: 75.0
injuries per
100 runners
20
de Loes and
Goldie [38]
Road/Trail Population
based (Swe-
den)
Recreational 2505/3530 15–59 1year Medically
diagnosed:
injury reg-
istry from
hospitals
and sports
medicine
physician.
Validated by
telephone
interview
Data were col-
lected from
representa-
tive sample
via question-
naire, then
extrapola-
tion to
whole
population
0.7 injuries
per 1000h
Female: 0.7
injuries per
1000h;
Male: 0.7
injuries per
1000h
14
McLain and
Reynolds
[52]
Cross-country High school
students
Competitive
(high school)
40/54 NA 1year Athletic
trainer: Any
time loss
incident
resulting
from athletic
participation
NA 10.7 injuries
per 100 run-
ners
Female: 7
injured run-
ners per 100
runners;
Male: 13
injured run-
ners per 100
runners
11
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1016 K.Hollander et al.
Table 2 (continued)
Study Sport Cohort/
populations,
(Country)
Level Number of
participants
(female/male)
Age (years) Duration of data
collection
Injury defini-
tion
Exposure
measurement
Injury rates
(overall)
Injury rates
(female/male)
Risk
of bias
score
Walter etal.
[63]
Road runners
(10 Miles)
Community
running
events
(4–22.4km)
in Ontario
Recreational 301/980 over 14 52weeks Injuries severe
enough to
reduce the
number
of miles
run, take
medicine, or
see a health
professional
NA 48.4 injured
runners per
100 runners
Female: 45.5
injured run-
ners per 100
runners;
Male: 49.3
injured run-
ners per 100
runners
13
Bennell etal.
[35]
Track Victoria ath-
letics
Competitive
(college)
26/28 17–26 48weeks Stress frac-
ture: medi-
cal imaging
after clinical
evaluation
Structured
interview:
hours per
week, weeks
without run-
ning,
0.7 stress
fractures per
1000h
25.9 runners
with stress
fractures per
100 runners
Female: 30.8
runners
with stress
fractures per
100 runners;
Male: 21.4
runners
with stress
fractures per
100 runners
21
Beachy etal.
[34]
Cross-country High school
students
(Punahou,
Hawai)
Competitive
(high school)
787/501 NA 8years Any athlete
complaint
that required
the attention
of the ath-
letic trainer,
regardless
of the time
lost from
activity
NA 65 injuries
per 100 run-
ners
Female: 65
injuries per
100 girls;
Male: 66
injuries per
100 boys
14
Colbert etal.
[36]
Road running Patients from
Cooper
Clinic
Recreational 220/1771 NA 8years Clinical visit NA 26.3 injured
runners per
100 runners
Female: 25.0
injured run-
ners per 100
runners;
Male: 26.4
injured run-
ners per 100
runners
9
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1017
Sex-Specific Differences in Running Injuries
Table 2 (continued)
Study Sport Cohort/
populations,
(Country)
Level Number of
participants
(female/male)
Age (years) Duration of data
collection
Injury defini-
tion
Exposure
measurement
Injury rates
(overall)
Injury rates
(female/male)
Risk
of bias
score
Rauh etal.
[58]
Cross country High school
students
(Washington
state)
Competitive
(high school)
1202/2031 NA 15years An injury was
defined as
a medical
problem
resulting
from athletic
participation
that required
an athlete to
be removed
from a
practice or
competi-
tive event
or to miss a
subsequent
practice or
competitive
event
An AE was
defined as
any practice
or meet
(competi-
tion) in
which there
was the
possibility
of sustaining
an athletic
injury
13.1 injuries
per 1000
AEs
Female: 16.7
injuries per
1000 AEs;
Male: 10.9
injuries per
1000 AEs
18
Steinacker
etal. [61]
Marathon Berlin
Marathon
participants
Recreational 22/36 44.5 24weeks Self-reported
orthopaedic
problems
(Survey)
NA 46.6 injured
runners per
100 runner
Female: 41.6
injured run-
ners per 100
runners;
Male: 54.5
injured run-
ners per 100
runners
11
Taunton etal.
[62]
Road race
(10km)
Vancouver
Sun Run
(10km)
Recreational 635/205 NA 13weeks Self-reported
pain (Sur-
vey) with
medical
confirmation
NA 29.5 injured
runners per
100 runner
Female: 30.2
injured run-
ners per 100
runners;
Male: 28.3
injured run-
ners per 100
runners
14
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1018 K.Hollander et al.
Table 2 (continued)
Study Sport Cohort/
populations,
(Country)
Level Number of
participants
(female/male)
Age (years) Duration of data
collection
Injury defini-
tion
Exposure
measurement
Injury rates
(overall)
Injury rates
(female/male)
Risk
of bias
score
Dane etal.
[37]
Road running College stu-
dents
Competitive
(college)
47/45 17–28 One season
(12weeks)
Medically
diagnosed:
contusions,
bleeding,
wounds, and
fractures,
except small
bruises,
were clas-
sified as
injuries
NA 57.1 injured
runners per
100 runners
Female: 52
injured run-
ners per 100
runners;
Male: 60
injured run-
ners per 100
runners
10
Rauh etal.
[57]
Cross country College
students
(Seattle)
Competitive
(college)
186/235 NA One season Muscle, joint,
or bone
problem/
injuries of
the back
or lower
extremity
requiring
the runner to
be removed
from a prac-
tice or meet
or to miss a
subsequent
one
An AE was
any practice
or competi-
tive event
where a
runner was
at risk of
sustaining
an injury
17.0 injuries
per 1000
AEs
Female: 19.6
injuries per
1000 AEs;
Male: 15.0
injuries per
1000 AEs
20
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1019
Sex-Specific Differences in Running Injuries
Table 2 (continued)
Study Sport Cohort/
populations,
(Country)
Level Number of
participants
(female/male)
Age (years) Duration of data
collection
Injury defini-
tion
Exposure
measurement
Injury rates
(overall)
Injury rates
(female/male)
Risk
of bias
score
Plisky etal.
[56]
Cross country High school
students
(Wisconsin)
Competitive
(college)
46/59 NA 13weeks Medial
tibial stress
fracture:
pain in the
tibial region,
exacerbated
with repeti-
tive weight-
bearing
activity, and
localized
pain with
pal- pation
along the
distal two
thirds of the
posterior-
medial tibia
AE: any
practice or
competitive
event
2.8 stress
fractures per
1000 AEs
Female:
4.3 stress
fractures per
1000 AEs;
Male: 1.7
stress
fractures per
1000 AEs
21
Alonso etal.
[32]
Track + Mara-
thon
2007 IAAF
World cham-
pionships
(Osaka)
participants
Elite 249/267 17–37 9days All mus-
culoskel-
etal injuries
regardless
of the conse-
quences
with respect
to the
athlete’s
absence
from compe-
tition or
training
Number of
competing
athletes
150 competi-
tion injuries
per 1000
athletes
Time-loss
injuries
per 1000
registered
athletes
- Female:
800m: 22,
1500m:
26, 3000m
SC: 48,
5000m: 38,
10000m:
158, mara-
thon 61;
- Male:
800m: 43,
1500m:
24, 3000m
SC: 79,
10000m:
91, mara-
thon: 118
22
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1020 K.Hollander et al.
Table 2 (continued)
Study Sport Cohort/
populations,
(Country)
Level Number of
participants
(female/male)
Age (years) Duration of data
collection
Injury defini-
tion
Exposure
measurement
Injury rates
(overall)
Injury rates
(female/male)
Risk
of bias
score
Alonso etal.
[33]
Track + Mara-
thon
2009 IAAF
World cham-
pionships
(Berlin)
participants
Elite 244/312 NA 9days All time-loss
muscu-
loskel-
etal injuries
(traumatic
and overuse)
regardless
of the conse-
quences
with respect
to the
athlete’s
absence
from compe-
tition or
training
The number
of compet-
ing athletes
was defined
as all
athletes who
started at
least once in
a discipline
MD: 173.3
injuries
per 1000
registered
athlete
LD: 151.1
injuries
per 1000
registered
athletes
Injuries
per 1000
registered
athletes
- Female:
800m 46.5
1500m 71.4
3000m SC:
48.8
5000m 43.5
10000m 90.9
Marathon 0
- Male:
800m 0
1500m 37.0
3000m SC:
26.5 5000m
102.6
10000m 32.3
Marathon
30.6
22
Buist etal. [7] Road racing
(4 Miles)
Groningen 4
mile
Recreational 422/207 43.7 ± 9.5 8weeks Any time loss
running-
related
musculo-
skeletal pain
at the lower
extremity or
back
Exposure as
given by
training
programme
25.9 injured
runner per
100 runners;
30.1 injuries
per 1000h
Injury inci-
dence rate
per 1000h -
Female: 27.5,
Male: 35.0
Mean Preva-
lence -
Female: 23.4
injured run-
ners per 100
runners
Male: 31.4
injured run-
ners per 100
runners
18
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1021
Sex-Specific Differences in Running Injuries
Table 2 (continued)
Study Sport Cohort/
populations,
(Country)
Level Number of
participants
(female/male)
Age (years) Duration of data
collection
Injury defini-
tion
Exposure
measurement
Injury rates
(overall)
Injury rates
(female/male)
Risk
of bias
score
Alonso etal.
[31]
Track + Mara-
thon
2011 IAAF
World cham-
pionship
(Daegue)
participants
Elite 208/268 17–42 9days All mus-
culoskel-
etal injuries
regardless
of the conse-
quences
with respect
to the
athlete’s
absence
from compe-
tition or
training
Number of
competing
athletes
MD: 176.1
injuries
per 1000
registered
athletes
LD: 187.8
injuries
per 1000
registered
athletes
Time-loss
injuries
per 1000
registered
athletes
- Female:
800m: 55.6,
1500m:
57.1,
3000m SC:
0, 5000m:
125 injuries,
10000m:
52.6,, mara-
thon 53.6;
- Male:
800m: 22.7,
1500m:
76.9,
3000m SC:
0, 5000m:
122 injuries,
10000m:
47.6 injuries
marathon:
220.6
22
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1022 K.Hollander et al.
Table 2 (continued)
Study Sport Cohort/
populations,
(Country)
Level Number of
participants
(female/male)
Age (years) Duration of data
collection
Injury defini-
tion
Exposure
measurement
Injury rates
(overall)
Injury rates
(female/male)
Risk
of bias
score
Jacobsson
etal. [48]
Track
(MD + LD)
Swedish
national
team
Elite 54/55 17–37 52weeks Self-reported
musculo-
skeletal
pain, sore-
ness or
injury with
time loss
or changes
in normal
training/
competition
Self-reported
athletic
training par-
ticipation
83 injured
runners per
100 runners
Adults:
Female: 74
injured run-
ners per 100
runners;
Male: 81
injured run-
ners per 100
runners
Youth:
Female: 57
injured run-
ners per 100
runners;
Male: 58
injured run-
ners per 100
runners
19
Edouard etal.
[40]
Track (MD) European Ath-
letics indoor
champion-
ships Paris
2011 partici-
pants
Elite 125/75 NA 3days Any muscu-
loskeletal
complaint
and concus-
sion that
received
medical
attention
regardless of
time loss
Athletes’
exposure in
competition
MD: 53
injuries
per 1000
registered
athletes
Injuries
per 1000
registered
athletes –
Female:
800m: 47.6
3000m 150.0
- Male:
800m: 107.1
3000m 34.5
21
Nielsen etal.
[55]
Road racing DANO-RUN
study
Novice runners 441/432 37.2 ± 10.3 1year Any muscu-
loskeletal
complaint
of the lower
extremity
or back
caused by
running that
restricted
the amount
of running
for at least
1week
Online diary:
GPS or
manually
kilometers
23.1 injured
runner per
100 runners
Female: 21.8
injured run-
ners per 100
runners;
Male: 24.5
injured run-
ners per 100
runners
23
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1023
Sex-Specific Differences in Running Injuries
Table 2 (continued)
Study Sport Cohort/
populations,
(Country)
Level Number of
participants
(female/male)
Age (years) Duration of data
collection
Injury defini-
tion
Exposure
measurement
Injury rates
(overall)
Injury rates
(female/male)
Risk
of bias
score
Edouard etal.
[39]
Track (MD) European
Athletics
champion-
ships Hel-
sinki 2012
participants
Elite 66/164 NA 3days Any muscu-
loskeletal
complaint
and concus-
sion that
received
medical
attention
regardless of
time loss
Athletes’
exposure in
competition
MD: 53
injuries
per 1000
registered
athletes
Injuries
per 1000
registered
athletes
-Female:
800m: 41.7
1500m: 30.3
3000m: 142.9
5000m: 347.8
10000m:
176.5
- Male:
800m: 69.8,
1500m:
171.4,
3000m: 275.9
5000m: 71.4
10000m
103.4
21
Changstrom
etal. [24]
Cross-country National High
School
Sports-
Related
Injury
Surveillance
System
(2011–
2012),
(USA)
Competitive
(high school)
NA 13–19 2years (Stress)
fractures,
concussions
and dental
injuries with
or without
time loss.
All injuries
with time
loss requir-
ing medical
attention
Athlete expo-
sure (AE)
7.8 stress
fractures
per 100,000
AEs
Female:
10.6 stress
fractures
per 100,000
AEs; Male:
5.4 stress
fractures
per 100,000
AEs
19
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1024 K.Hollander et al.
Table 2 (continued)
Study Sport Cohort/
populations,
(Country)
Level Number of
participants
(female/male)
Age (years) Duration of data
collection
Injury defini-
tion
Exposure
measurement
Injury rates
(overall)
Injury rates
(female/male)
Risk
of bias
score
Edouard etal.
[19]
Track + Mara-
thon
All athletic
world cham-
pionships
(2007–2014)
Elite 1302/1573 NA (3–9days per
championship)
All mus-
culoskel-
etal injuries
(traumatic
and overuse)
and concus-
sion newly
incurred
during
competition
or training
regardless
of the conse-
quences
with respect
to the
athlete’s
absence
from compe-
tition or
training
Total number
of registered
athletes
N/A Injuries
per 1000
registered
athletes
- Female:
MD 94.6
LD 155.3
Marathon
153.3
- Male:
MD 108.5
LD 141.4
Marathon
195.5
21
Kluitenberg
etal. [50]
Road racing NLstart2run Novice runners 1332/364 43.3 6weeks A muscu-
loskeletal
complaint
of the lower
extremity
or back that
hampered
running
ability
for three
consecutive
training ses-
sions
Weekly
running
frequency
and running
exposure (in
minutes) for
each training
session
27.5 injuries
per 1000h
Female: 10.4
injured run-
ners per 100
runners;
Male: 12.6
injured run-
ners per 100
runners
17
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1025
Sex-Specific Differences in Running Injuries
Table 2 (continued)
Study Sport Cohort/
populations,
(Country)
Level Number of
participants
(female/male)
Age (years) Duration of data
collection
Injury defini-
tion
Exposure
measurement
Injury rates
(overall)
Injury rates
(female/male)
Risk
of bias
score
Hespanhol
Junior etal.
[45]
Road racing
(10 Miles)
Tilburg Ten
Miles
Recreational 31/22 44.1 18weeks OSTRC: All
running-
related
injuries
Online ques-
tionnaires
completed
every fort-
night
Mean preva-
lence: 30.8
injured run-
ners per 100
runners and
cumulative
prevalence
60.4 injured
runners per
100 runners
Mean preva-
lence
Female:
11.5%
injured run-
ners per 100
runners
Male: 19.3
injured run-
ners per 100
runners
18
Hespanhol
Junior etal.
[44]
Trailrunning Dutch trail
runners
Recreational 57/171 43.4 6months OSTRC: All
running-
related
injuries
Online ques-
tionnaires
completed
every fort-
night
10.7 injuries
per 1000h;
mean
prevalence
22.4%
Injury inci-
dence rate
per 1000h -
Female 9.1
Male: 11.3
Mean Preva-
lence:
Female:
20.7%;
Male: 23.0%
17
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1026 K.Hollander et al.
Table 2 (continued)
Study Sport Cohort/
populations,
(Country)
Level Number of
participants
(female/male)
Age (years) Duration of data
collection
Injury defini-
tion
Exposure
measurement
Injury rates
(overall)
Injury rates
(female/male)
Risk
of bias
score
Rizzone etal.
[59]
Cross country NCAA
(2004–2014)
Competitive
(college)
NA NA 9years Time loss
stress
fractures
that required
medical
attention:
(1) occurred
due to
participation
in a school-
sanctioned
practice or
competition,
(2) required
attention
from an AT
or physician,
(3) resulted
in at least
24h of time
missed from
participa-
tion, and
(4) had a
reported
diagnosis
of stress
fracture
AE: 1 student-
athlete
participating
in 1 NCAA-
sanctioned
practice or
competition
22.4 stress
fractures
per 100,000
AEs
Female:
28.6 stress
fractures
per 100,000
AEs;
Male: 16.1
stress
fractures
per 100,000
AEs
18
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1027
Sex-Specific Differences in Running Injuries
Table 2 (continued)
Study Sport Cohort/
populations,
(Country)
Level Number of
participants
(female/male)
Age (years) Duration of data
collection
Injury defini-
tion
Exposure
measurement
Injury rates
(overall)
Injury rates
(female/male)
Risk
of bias
score
Messier etal.
[53]
Road racing TRAILS study Recreational 128/172 Range 18—60 104weeks Overuse
running
injuries:
grade 1,
maintained
full activity
in spite of
symptoms;
grade 2,
reduced
weekly
mileage;
and grade 3,
interrupted
all training
for at least
2weeks
NA 66 injured
runners per
100 runners
Female: 73
injured run-
ners per 100
runners;
Male: 62
injured run-
ners per 100
runners
15
Winter etal.
[64]
Road running Runners from
local run-
ning club
Recrea-
tional + Com-
petitive
35/57 18—65 52weeks Pain prevent-
ing the
runner from
performing
or complet-
ing at least
one training
session
Training
diary with
information
on running
sessions
per week,
distance and
duration of
runs
51.3 injured
runners per
100 runners
Female: 54.8
injured run-
ners per 100
runners;
Male: 48.9
injured run-
ners per 100
runners
20
Fokkema
etal. [42]
Road racing INSPIRE
trial (NN
City Pier
City The
Hague, NN
Marathon
Rotterdam,
Ladies Run
Rotterdam)
Recreational 553/629
(Control
group)
41.4 ± 12 4.5 ± 1.6months Injuries of the
lower back
or lower
extremities
caused by
running
with change
of training
for at least
1week, a
medical visit
or medica-
tion
NA 36.7 injured
runners per
100 runners
Female: 35.8
injured run-
ners per 100
runners;
Male: 38.3
injured run-
ners per 100
runners
15
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1028 K.Hollander et al.
Table 2 (continued)
Study Sport Cohort/
populations,
(Country)
Level Number of
participants
(female/male)
Age (years) Duration of data
collection
Injury defini-
tion
Exposure
measurement
Injury rates
(overall)
Injury rates
(female/male)
Risk
of bias
score
Hayes etal.
[43]
Cross-country NCAA (Ivy
League &
New Eng-
land Small
College
Athletics)
Competitive
(college)
57/10 17–21 1 US-cross-
country season
Self-reported
Injuries that
were not
present dur-
ing adminis-
tration of the
pre-season
survey
Average and
maximum
weekly
mileage in
increments
of 10 miles
(e.g. 31–40
miles per
week)
53 injured
runners per
100 runners
(over one
season)
Female: 51
injured run-
ners per 100
runners;
Male: 55
injured run-
ners per 100
runners
12
Lagas etal.
[51]
Road racing INSPIRE
trial (NN
City Pier
City The
Hague, NN
Marathon
Rotterdam,
Ladies Run
Rotterdam)
Recreational 909/1020 41.9 ± 12.1 20.5 ± 7weeks Self-reported
Achilles
tendinopa-
thy caused
by running
with change
of training
for at least
1week, a
medical visit
or medica-
tion
NA 5.2 injured
runners per
100 runners
Female: 3.6
injured run-
ners per 100
runners;
Male: 6.6
injured run-
ners per 100
runners
12
Ruffe etal.
[60]
Cross-country High school
students
(California)
Competitive
(high school)
80/68 15.6 1 US-cross-
country season
Muscle, bone,
or joint
problem/
injury of the
low back
or lower
extremity
requiring
removal
from
training/
competitions
or leading
to missed
subsequent
training/
competitions
Runners’ daily
participation
in prac-
tices and
competitive
events
33.1 injured
runners per
100 runners
(over one
season)
Female: 38.8
injured run-
ners per 100
runners;
Male: 26.5
injured run-
ners per 100
runners
16
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1029
Sex-Specific Differences in Running Injuries
Table 2 (continued)
Study Sport Cohort/
populations,
(Country)
Level Number of
participants
(female/male)
Age (years) Duration of data
collection
Injury defini-
tion
Exposure
measurement
Injury rates
(overall)
Injury rates
(female/male)
Risk
of bias
score
Winter etal.
[65]
Road running Runners from
local run-
ning club
Recrea-
tional + Com-
petitive
35/57 18—65 52weeks Pain prevent-
ing the
runner from
performing
or complet-
ing at least
one training
session
assessed by
an experi-
enced health
or medical
professional
Average kilo-
meters per
week; aver-
age duration
(minutes)
per week;
average
frequency
per week
51.3 injured
runners per
100 runners
Female: 54.8
injured run-
ners per 100
runners;
Male: 48.9
injured run-
ners per 100
runners
21
Edouard etal.
[41]
Track + Mara-
thon
IAAF World
and Euro-
pean Cham-
pionships
participants
Elite MD: 742/943;
LD 656/793;
Marathon
464/550
NA 78days
(3–9days per
championship)
All mus-
culoskel-
etal injuries
(traumatic
and overuse)
and concus-
sion newly
incurred
during
competition
or training
regardless
of the conse-
quences
with respect
to the
athlete’s
absence
from compe-
tition or
training
Total number
of registered
athletes
Injuries
per 1000
registered
athletes—
MD: 97
LD: 126
Marathon:
139
Injuries
per 1000
registered
athletes
- Female:
MD 84.9
LD 128
Marathon
118.5
Male:
MD 106
LD 123.6
Marathon
156.4
19
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1030 K.Hollander et al.
Most studies (> 90%) reported recruitment procedures,
injury assessment and documented injury characteristics.
Fewer studies achieved maximal points due to not record-
ing individual exposure data (50.0% of maximal points) or
exposure data at all (57.9% of maximal points) as well as
not using a medical attention definition (56.1% of maximal
points). The results of the study quality assessment are pre-
sented in Electronic Supplementary Material TableS1.
Except for one outlier [47], visual inspection of the funnel
plot (Fig.2) showed a symmetrical distribution of the log
risk ratios and the regression test for funnel plot asymmetry
(− 0.150; p= 0.881) suggested no indication of publication
bias.
3.4 Overall Injury Rates
The overall injury rate was 20.4 (95% CI 19.7–21.1) injuries
per 100 male runners and20.8 (95% CI 19.9–21.7) injuries
per 100 female runners. Meta-analytic pooling did not reveal
differences between female and male runners’ injury rates
per runner (n = 21; RR 0.99, 95% CI 0.90–1.10; p = 0.84;
I2 = 72.31) or per specific exposures (n = 6; RR 0.94, 95%
CI 0.69–1.27; p = 0.669; I2 = 85.93) (Figs.3 and 4). Due to
the small number (n = 6) of studies reporting injuries per
exposure (athlete exposures (n = 2) or hours (n = 4)), no
aggregation of overall injury rates per specific exposures
was performed.
3.5 Meta‑Regression
Moderator analyses of injury RR rates per runner revealed
an association of a higher injury risk in men and compe-
tition distances exceeding distances of 10km (p = 0.002)
(Table3). Specifically, the subgroup meta-analysis of com-
petition distance showed a significantly higher RR of 1.08
(95% CI: 1.04–1.39) for female runners with competition
Table 2 (continued)
Study Sport Cohort/
populations,
(Country)
Level Number of
participants
(female/male)
Age (years) Duration of data
collection
Injury defini-
tion
Exposure
measurement
Injury rates
(overall)
Injury rates
(female/male)
Risk
of bias
score
Hofstede etal.
[46]
Half- + Mara-
thon
SUMMUM
study
(Utrecht
Marathon)
Recreational 71/90 40.7 ± 11.7 16weeks OSTRC ques-
tionnaire,
injuries with
a moderate
to severe
reduction in
training or
competition
or time loss
NA 44.1 substan-
tial injuries
per 100
runners
Female: 52.1
substantial
injuries per
100 runners;
Male: 37.8
substantial
injuries per
100 runners
14
NA not available, 3000m SC 3000m steeplechase, AE athlete exposure, MD middle distance, LD long distance, IAAF International Amateur Athletics Federation, GPS global positioning sys-
tem, NCAA National Collegiate Athletic Association, OSTRC Oslo Sports Trauma Research Center
Fig. 2 Funnel plot of the overall differences between injury rate of
female and male runners (log risk ratios against standard error)
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1031
Sex-Specific Differences in Running Injuries
distances ≤ 10km. For competition distances > 10 km, the
comparison approached but failed to reach significance
although the RR of 0.77 (95% CI: 0.58–1.02) was sugges-
tive of a lower probability of injury in male runners (Fig.5).
No meta-regression was performed for specific injuries and
moderators training duration or training mileage due to
absence of more than ten studies reporting these variables
[28].
3.6 Specific Injury Rates
Data for two specific running-related injuries were available
for synthesis.
3.6.1 Bone Stress Injuries
Four studies reported on bone stress injuries with a pooled
decreased probability for male runners (estimated RR
0.52, 95% CI 0.36–0.76, p < 0.001; I2 = 0) (Fig.6).
3.6.2 Achilles Tendinopathy
Furthermore, data pooling for two studies reporting injury
rates for Achilles tendinopathy revealed an increased
chance for male runners to have an Achilles tendon injury
(estimated RR 1.86, 95% CI 1.25–2.79, p = 0.022; I2 = 0%)
(Fig.7).
Fig. 3 Forest plot depicting the meta-analytical results comparing risk ratios for male and female runners regarding injuries per 100 runners
Fig. 4 Forest plot depicting the meta-analytical results comparing risk ratios for male and female runners regarding injuries per exposure (hours
or athlete exposures)
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1032 K.Hollander et al.
4 Discussion
The aim of this analysis was to systematically ana-
lyse the literature to reveal sex-related differences in
running-related injury rates and characteristics. While no
differences between sexes were found for overall running-
related injuries, female runners were more likely to sustain
bone stress injuries while male runner were more prone to
Achilles tendinopathies. Meta-regression showed that for
Table 3 Results of the
moderator analysis for injury
risk ratio rates per 100 female
or male runners
95% CI 95% confidence interval
Moderator No of com-
parisons (k)
Z p Risk ratio estimate (95% CI) Tau2/Q
Risk of bias 22 0.0299/68.1
Intercept − 0.88 0.378 − 0.051 (− 0.167 to 0.063)
Moderator 1.42 0.156 0.151 (− 0.058 to 0.359)
Level 20 0.0385/63.1
Intercept 0.68 0.495 0.044 (− 0.083 to 0.171)
Moderator 1.05 0.293 0.110 (− 0.095 to 0.316)
Age 15 0.0224/27.3
Intercept 0.87 0.387 0.116 (− 0.146 to 0.378)
Moderator − 0.81 0.419 − 0.119 (− 0.407 to 0.170)
Competition distance 14 0.0311/44.7
Intercept 1.71 0.088 0.144 (− 0.021 to 0.309)
Moderator − 3.05 0.002 − 0.387 (− 0.636 to − 0.138)
Fig. 5 Forest plot depicting the meta-analytical results for sub-anal-
ysis (competition distance) of risk ratios for male and female runners
regarding injuries per 100 runners. Subgroup 1 (a) represents studies
investigating runners competing in distances below or equal to 10km
and subgroup 2 (b) in distances above 10km
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1033
Sex-Specific Differences in Running Injuries
competition distances of10kmand shorter, female runners
had higher risk for injuries than malerunners.
4.1 No Differences inOverall Injury Rates
betweenFemale andMale Runners
Despite pooling data from all available epidemiological stud-
ies, no differences in overall injury rates between female and
male runners were found in this systematic review. This was
the case for both studies reporting injuries per runner and inju-
ries per specific exposures. The injury rates of 20.4 (male) and
20.8 (female) per 100 runners are in accordance with summa-
ries of injury rates from the last three decades [4]. Nonethe-
less, these rates are at the lower spectrum of published injury
rates that were reported to be up to 79.3% [66].
4.2 Shorter Competition Distances Increase theRisk
ofInjury forFemale Runners
Injury rates depend on several factors that need to be taken
into consideration, such as systematic factors (age, BMI),
running-/training-related factors (training frequency, train-
ing and racing distance, experience, level of running, foot-
wear, biomechanics), health factors (injury history) and
lifestyle factors (drinking, smoking) [66–70].
Not all of these factors were reported in each study and
may vary between investigated populations. Therefore, the
moderator analysis was incorporated into this study. Only
competition distance was a statistically significant modera-
tor for an increased risk of female runners compared to male
runners when running competition distances of 10km and
shorter. Furthermore, the subanalysis revealed a tendency of
increased injury risk for male runners for longer distances
than 10km. This is in accordance with the finding that male
runners had a higher risk of sustaining injuries compared to
female runners when running high mileages (> 64km/week)
[18]. While running higher mileages are associated with
longer competition distances, this can only be used as an
estimate for this discussion. Unfortunately, there was insuf-
ficient reporting of training load (time or mileage) in the
included studies. For future studies reporting data on injury
epidemiology or risk factors, it is strongly recommended to
report the training load [71, 72].
4.3 Bone Stress Injuries Occur Twice asOften
inFemale thaninMale Runners
Female runners had twofold higher risk of having a bone
stress injury compared to male runners in this review. A
bone stress injury is an injury pattern with known sex dif-
ferences for epidemiology and risk factors [73]. Bone stress
injuries are common running-related overuse injuries due
to cumulative microtrauma to the bone [74]. Especially in
younger ages, females seem to have a higher risk for bone
stress injuries compared to male runners. For example,
Changstrom etal. [24] reported a twofold risk and Plisky
etal. [56] a 2.5-fold risk for female high school runners
of sustaining a bone stress injury compared to male high
school runnersin cross-country. In older collegiate ath-
letes, female cross-country runners were found to have
28.6 injuries per 100,000 athlete exposures (AE) compared
to 16.4 injuries per 100,000 AE in males, representing a
Fig. 6 Forest plot depicting the meta-analytical results comparing risk ratios for male and female runners regarding bone stress injuries
Fig. 7 Forest plot depicting the meta-analytical results comparing risk ratios for male and female runners regarding Achilles tendinopathy
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

1034 K.Hollander et al.
statistically significant rate ratio of 1.8 [59]. In outdoor
track (100m–1500m), this difference was even higher (22.3
injuries/100,000AE for females and 7.2 injuries/100,000AE
for males, risk ratio of 3.1) [59]. One possible explanation
that has been discussed was the association of bone stress
injuries with the female athlete triad (low energy availabil-
ity, menstrual disturbance and low bone mineral density)
to explain the higher risk for bone stress injuries in female
runners [35, 75, 76]. However, while the term female athlete
triad is used only for female athletes, the more current and
more detailed concept of relative energy deficiency of sports
(RED-S) has also been described for male athletes [77–79].
Despite using the same initial treatment (activity modifica-
tion, protected or non-weight bearing) of bone stress injuries
for both sexes, the further treatment differs between female
and male runners, depending on specific risk factors, such as
elevated RED-S risk, biomechanics (load rates, hip adduc-
tion, rearfoot eversion), altered hormonal status or calcium
and vitamin D intake [14, 15, 73, 80]. In summary, bone
stress injuries are more prevalent in female runners and
treatment/rehabilitation strategies should incorporate sex
as an important variable. Nonetheless, in the prevention of
bone stress injuries consideration of the sex would probably
benefit from awareness of RED-S, including screening for
low energy availability and low mineral bone density.
4.4 Achilles Tendinopathies Occur Twice asOften
inMale Compared toFemale Runners
Data from two studies showed that male runners had almost
twice the risk of having an Achilles tendinopathy as female
runners [49, 51]. This is in accordance with a systematic
review on the pathogenesis of Achilles tendinopathy [81].
The Achilles tendon transmits the generated forces from
the gastrocnemius-soleus muscle complex and, thus, is an
important tendon for propulsion during running. However,
the Achilles tendon has a poor blood supply and, therefore,
is prone to overuse injuries, such as a tendinopathy [81]. The
lifetime prevalence has been reported as high as 40–50%
in runners [13, 82] and a recent 1-year prospective study
determined the incidence rate in a cohort of recreational
runners to be 5.2% [51]. While the amount of loading is the
key factor in the etiology of Achilles tendinopathy, there
are several intrinsic (age, stress, genes, biomechanics, body
composition) and extrinsic factors (footwear) modulating the
risk for this injury [83]. Recent studies found biomechanical
(footstrike pattern, ankle dorsiflexion moments) and train-
ing-related parameters (changes in training, cold weather,
footwear, use of compression socks, mileage) as possible
risk factors [10, 51, 84–86]. This summary of (possible) risk
factors does not directly explain the increased probability
for male runners to have an Achilles tendinopathy. There-
fore, we can only speculate about the possible mechanisms.
One recently published study discusses the mechanism of
the lifetime cumulated load (together with running years)
which might be higher in male runners than in female run-
ners [87]. Chronic loading needs to be taken into account
when evaluating the risk for Achilles tendinopathies.
Another explanation might be found in the hormonal dif-
ferences between women and men. For example, estrogen is
associated with collagen synthesis and could therefore influ-
ence tendon healing capacity [88, 89]. Furthermore, estro-
gen deficiency has been reported to negatively affect tendon
metabolism and healing [90]. Hormonal fluctuations that are
typical for the menstrual cycle have not been associated with
modifications of tendon function [90, 91]. A review summa-
rizes that high or low levels of sexual hormones (estrogen,
progesterone and testosterone) are not directly causing ten-
dinopathies but may play a role in tendon pathologies [92].
Therefore, individual hormonal status should be taken into
account for injury risk of female and male runners as well
as for their therapies and prevention [92].
4.5 Results oftheCurrent Review inContrast
withandinAddition toOther Systematic
Reviews
This was the first systematic review on sex-specific differ-
ences in running injuries incorporating a meta-regression
analysis to determine moderating variables and shall be
discussed in light of other systematic reviews on this topic.
This systematic review contrasts the findings of the
systematic review by van der Worp etal. [18], who found
female runners at a lower overall risk of sustaining an injury
than male runners. This finding was particularly found in
men under 40years. However, when assessing the evidence
level the authors called for caution in the interpretation of
their findings since these were based on only five high-
quality and one low-quality studies. In contrast, our review
included epidemiological studies reporting injury rates
separately for both sexes. With this approach, 26 studies
were included and meta-analyses showed no sex differences
for overall running injuries when calculated per runner or
per exposure (hours or AE). Furthermore, we were able to
conduct a meta-regression analysis showing ahigher injury
risk for female runners in competition distances of10 km
and shorter as well as atendency for a higher injury risk for
male runners in competition distances longer than 10km.
This is a new finding and in line with the increased risk for
male runners with a high weekly mileage (> 64km), which
is typically needed for longer competition distances [18].
The systematic review by Wright etal. [93] found female
sex to be a primary risk factor for lower extremity bone
stress injuries despite conflicting evidence using an explora-
tory meta-analysis incorporating three etiological studies [6,
94, 95]. The meta-analysis found a similar 2.3-fold increased
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

1035
Sex-Specific Differences in Running Injuries
probability for female runners. Our meta-analysis supports
these findings and underlines the evidence for female run-
ners to be more prone to bone stress injuries based on five
included prospective studies [24, 35, 49, 56, 59]. Female
sex as a risk factor for medial tibial stress syndrome has also
been described by a meta-analysis in active individuals (not
exclusively runners [96]).
4.6 Limitations andMethodological Considerations
ofCurrent Research
This systematic review summarised data from 38 prospec-
tive studies representing more than 35,689 participants
(from 36 studies) and 518,000 athlete exposures (from 2
studies). While the distribution between female and male
runners (40.8–50.7% females) was similar and no overall
differences were found, breakdown of injury data regarding
sex and according to location or diagnosis was only possible
in six studies. Consequently, the available literature included
in this systematic review did not allow conclusions on the
sex-dependent epidemiology of pathologies other than bone
stress injuries and Achilles tendinopathies.
The meta-regression approach of this study included
several potential moderators. However, considering the
multifactorial aetiology of running-related injuries, other
confounding bias such as biomechanical or psychologi-
cal variables may have influenced the injury risk. Another
limitation was the moderate to high heterogeneity of studies
included in the overall injury meta-analyses, emphasizing
the need for further studies with a clear injury definition and
uniform data collection methods [71, 97].
Regarding quality, future studies would benefit from doc-
umenting exposure data and using medical attention injury
definitions. Furthermore, moderator analysis was only pos-
sible for 1 outcome (overall injuries per 100 runners) due to
missing descriptive information on study populations (such
as mileage, training duration, competition distances). As
seen in Table2, there are several different data collection
methods applied and injury definitions used to determine a
running injury. In accordance with recent consensus state-
ments in injury epidemiology [71] and a Delphi consensus
on running injuries [98], we encourage future running injury
research to follow these guidelines to improve the homo-
geneity of studies. From this, future meta-analyses would
benefit from comparing rates of injuriesbetween studies
[97, 99].
5 Conclusion
Sex does not seem to represent a specific risk factor when
considering the overall occurrence of injuries in running.
However, female runners more frequently sustain bone stress
injuries, while male runners have higher risk of developing
Achilles tendinopathies. Preventive measures targeting these
diagnoses may therefore be more effective when account-
ing for sex-specific aspects such as hormonal changes or
biomechanical characteristics. Regarding moderators, there
is a paucity of evidence although meta-regression identi-
fied running competition distance (cut-off 10km) as a factor
associated with higher injury rates in male runners.
Declarations
Funding Open Access funding enabled and organised by Projekt
DEAL. The research fellowship of Karsten Hollander wasfunded by
the German Research Foundation (Grant Number HO 6214/2-1). No
sources of funding were used to assist in the preparation of this article.
Conflict of Interest Karsten Hollander, Anna Rahlf, Jan Wilke, Chris-
topher Edler, Simon Steib, Astrid Junge and Astrid Zech have no con-
flicts of interest relevant to the content of this review.
Ethics approval Not applicable.
Consent to participate Not applicable.
Consent for publication Not applicable.
Data Availability Statement The data from the current study are pre-
sented in the article/electronic supplementary material and are avail-
able from the corresponding author upon request.
Code availability Not applicable.
Author Contributions KH: conceptualization, methodology, litera-
ture search, study quality assessment, formal analysis, writing (origi-
nal draft preparation). ALR: conceptualization, methodology, study
quality assessment, writing (review and editing). JW: formal analysis,
visualization, writing (review and editing). CE: literature search, writ-
ing (review and editing). SS: conceptualization, methodology, writing
(review and editing). AJ: conceptualization, methodology, study quality
assessment, writing (review and editing). AZ: conceptualization, meth-
odology, literature search, writing (review and editing), supervision.
All authors read and approved the final manuscript.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article’s Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http://creat iveco mmons .org/licen ses/by/4.0/.
References
1. Pedersen BK, Saltin B. Exercise as medicine - evidence for pre-
scribing exercise as therapy in 26 different chronic diseases. Scand
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

1036 K.Hollander et al.
J Med Sci Sports. 2015;25(Suppl 3):1–72. https ://doi.org/10.1111/
sms.12581 .
2. Pedisic Z, Shrestha N, Kovalchik S, Stamatakis E, Liangruenrom
N, Grgic J, etal. Is running associated with a lower risk of all-
cause, cardiovascular and cancer mortality, and is the more the
better? A systematic review and meta-analysis. Br J Sports Med.
2020;54(15):898–905. https ://doi.org/10.1136/bjspo rts-2018-
10049 3.
3. Van Middelkoop M, Kolkman J, Van Ochten J, Bierma-
Zeinstra SM, Koes B. Prevalence and incidence of lower
extremity injuries in male marathon runners. Scand J
Med Sci Sports. 2008;18(2):140–4. https ://doi.org/10.111
1/j.1600-0838.2007.00683 .x.
4. Nigg BM, Baltich J, Hoerzer S, Enders H. Running shoes and run-
ning injuries: mythbusting and a proposal for two new paradigms:
“preferred movement path” and “comfort filter.” Br J Sports Med.
2015;49(20):1290–4. https ://doi.org/10.1136/bjspo rts-2015-09505
4.
5. Hollander K, Baumann A, Zech A, Verhagen E. Prospective
monitoring of health problems among recreational runners
preparing for a half marathon. BMJ Open Sport Exerc Med.
2018;4(1):e000308. https ://doi.org/10.1136/bmjse m-2017-00030
8.
6. van Mechelen W, Hlobil H, Kemper HC. Incidence, severity, aeti-
ology and prevention of sports injuries. A review of concepts.
Sports Med. 1992;14(2):82–99. https ://doi.org/10.2165/00007
256-19921 4020-00002 .
7. Buist I, Bredeweg SW, Bessem B, van Mechelen W, Lemmink
KA, Diercks RL. Incidence and risk factors of running-related
injuries during preparation for a 4-mile recreational running event.
Br J Sports Med. 2010;44(8):598–604. https ://doi.org/10.1136/
bjsm.2007.04467 7.
8. Ceyssens L, Vanelderen R, Barton C, Malliaras P, Dingenen B.
Biomechanical risk factors associated with running-related inju-
ries: A systematic review. Sports Med. 2019;49(7):1095–115.
https ://doi.org/10.1007/s4027 9-019-01110 -z.
9. Van Middelkoop M, Kolkman J, Van Ochten J, Bierma-Zeinstra
SM, Koes BW. Risk factors for lower extremity injuries among
male marathon runners. Scand J Med Sci Sports. 2008;18(6):691–
7. https ://doi.org/10.1111/j.1600-0838.2007.00768 .x.
10. Hollander K, Johnson CD, Outerleys J, Davis IS. Multifactorial
determinants of running injury locations in 550 injured recrea-
tional runners. Med Sci Sports Exerc. 2021;53(1):103–7. https
://doi.org/10.1249/MSS.00000 00000 00245 5 (accepted for
publication).
11. Hoenig T, Rolvien T, Hollander K. Footstrike patterns in runners:
concepts, classifications, techniques, and implicationsfor running-
related injuries. Dtsch Z Sportmed. 2020;71(3):55–61. https ://doi.
org/10.5960/dzsm.2020.424.
12. Vannatta CN, Heinert BL, Kernozek TW. Biomechanical risk
factors for running-related injury differ by sample population:
a systematic review and meta-analysis. Clin Biomech (Bristol,
Avon). 2020;75:104991. https ://doi.org/10.1016/j.clinb iomec
h.2020.10499 1.
13. Kujala UM, Sarna S, Kaprio J. Cumulative incidence of achilles
tendon rupture and tendinopathy in male former elite athletes.
Clin J Sport Med. 2005;15(3):133–5. https ://doi.org/10.1097/01.
jsm.00001 65347 .55638 .23.
14. Davis IS, Bowser BJ, Mullineaux DR. Greater vertical impact
loading in female runners with medically diagnosed injuries: a
prospective investigation. Br J Sports Med. 2016;50(14):887–92.
https ://doi.org/10.1136/bjspo rts-2015-09457 9.
15. Milner CE, Hamill J, Davis IS. Distinct hip and rearfoot kin-
ematics in female runners with a history of tibial stress frac-
ture. J Orthop Sports Phys Ther. 2010;40(2):59–66. https ://doi.
org/10.2519/jospt .2010.3024.
16. Duckham RL, Brooke-Wavell K, Summers GD, Cameron N,
Peirce N. Stress fracture injury in female endurance athletes
in the United Kingdom: a 12-month prospective study. Scand
J Med Sci Sports. 2015;25(6):854–9. https ://doi.org/10.1111/
sms.12453 .
17. McKean KA, Manson NA, Stanish WD. Musculoskeletal injury in
the masters runners. Clin J Sport Med. 2006;16(2):149–54. https
://doi.org/10.1097/00042 752-20060 3000-00011 .
18. van der Worp MP, ten Haaf DS, van Cingel R, de Wijer A,
Nijhuis-van der Sanden MW, Staal JB. Injuries in runners; a sys-
tematic review on risk factors and sex differences. PLoS ONE.
2015;10(2):e0114937. https ://doi.org/10.1371/journ al.pone.01149
37.
19. Edouard P, Feddermann-Demont N, Alonso JM, Branco P, Junge
A. Sex differences in injury during top-level international athletics
championships: surveillance data from 14 championships between
2007 and 2014. Br J Sports Med. 2015;49(7):472–7. https ://doi.
org/10.1136/bjspo rts-2014-09431 6.
20. Prien A, Grafe A, Rossler R, Junge A, Verhagen E. Epidemiology
of head injuries focusing on concussions in team contact sports:
a systematic review. Sports Med. 2018;48(4):953–69. https ://doi.
org/10.1007/s4027 9-017-0854-4.
21. Hewett TE, Myer GD, Ford KR. Anterior cruciate ligament inju-
ries in female athletes: Part 1, mechanisms and risk factors. Am J
Sports Med. 2006;34(2):299–311. https ://doi.org/10.1177/03635
46505 28418 3.
22. Doherty C, Delahunt E, Caulfield B, Hertel J, Ryan J, Bleakley C.
The incidence and prevalence of ankle sprain injury: a systematic
review and meta-analysis of prospective epidemiological studies.
Sports Med. 2014;44(1):123–40. https ://doi.org/10.1007/s4027
9-013-0102-5.
23. Moher D, Liberati A, Tetzlaff J, Altman DG, Group P. Preferred
reporting items for systematic reviews and meta-analyses: the
PRISMA statement. PLoS Med. 2009;6(7):e1000097. https ://doi.
org/10.1371/journ al.pmed.10000 97.
24. Changstrom BG, Brou L, Khodaee M, Braund C, Comstock RD.
Epidemiology of stress fracture injuries among US high school
athletes, 2005–2006 through 2012–2013. Am J Sports Med.
2015;43(1):26–33. https ://doi.org/10.1177/03635 46514 56273 9.
25. Downs SH, Black N. The feasibility of creating a checklist for the
assessment of the methodological quality both of randomised and
non-randomised studies of health care interventions. J Epidemiol
Community Health. 1998;52(6):377–84.
26. Hollander K, Zech A, Rahlf AL, Orendurff MS, Stebbins J, Heidt
C. The relationship between static and dynamic foot posture and
running biomechanics: a systematic review and meta-analysis.
Gait Posture. 2019;72:109–22. https ://doi.org/10.1016/j.gaitp
ost.2019.05.031.
27. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control
Clin Trials. 1986;7(3):177–88. https ://doi.org/10.1016/0197-
2456(86)90046 -2.
28. Higgins J, Thomas J, Chandler J, Cumpston M, Li T, Page M,
etal. Cochrane handbook for systematic reviews of interventions
version 6.0 (updated July 2019). 2nd ed. Chichester: Wiley; 2019.
29. Wilke J, Muller AL, Giesche F, Power G, Ahmedi H, Behm DG.
Acute effects of foam rolling on range of motion in healthy adults:
a systematic review with multilevel meta-analysis. Sports Med.
2020;50(2):387–402. https ://doi.org/10.1007/s4027 9-019-01205
-7.
30. Şahin M, Aybek E. Jamovi: an easy to use statistical software for
the social scientists. Int J Assess Tools Educ. 2019. https ://doi.
org/10.21449 /ijate .66180 3.
31. Alonso JM, Edouard P, Fischetto G, Adams B, Depiesse F, Mount-
joy M. Determination of future prevention strategies in elite track
and field: analysis of Daegu 2011 IAAF Championships injuries
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

1037
Sex-Specific Differences in Running Injuries
and illnesses surveillance. Br J Sports Med. 2012;46(7):505–14.
https ://doi.org/10.1136/bjspo rts-2012-09100 8.
32. Alonso JM, Junge A, Renstrom P, Engebretsen L, Mount-
joy M, Dvorak J. Sports injuries surveillance during the 2007
IAAF World Athletics Championships. Clin J Sport Med.
2009;19(1):26–32. https ://doi.org/10.1097/JSM.0b013 e3181
91c8e 7.
33. Alonso JM, Tscholl PM, Engebretsen L, Mountjoy M, Dvorak
J, Junge A. Occurrence of injuries and illnesses during the
2009 IAAF World Athletics Championships. Br J Sports Med.
2010;44(15):1100–5. https ://doi.org/10.1136/bjsm.2010.07803 0.
34. Beachy G, Akau CK, Martinson M, Olderr TF. High school
sports injuries. A longitudinal study at Punahou School: 1988
to 1996. Am J Sports Med. 1997;25(5):675–81. https ://doi.
org/10.1177/03635 46597 02500 515.
35. Bennell KL, Malcolm SA, Thomas SA, Wark JD, Brukner PD.
The incidence and distribution of stress fractures in competitive
track and field athletes. A twelve-month prospective study. Am
J Sports Med. 1996;24(2):211–7. https ://doi.org/10.1177/03635
46596 02400 217.
36. Colbert LH, Hootman JM, Macera CA. Physical activity-related
injuries in walkers and runners in the aerobics center longitu-
dinal study. Clin J Sport Med. 2000;10(4):259–63. https ://doi.
org/10.1097/00042 752-20001 0000-00006 .
37. Dane S, Can S, Gursoy R, Ezirmik N. Sport injuries: rela-
tions to sex, sport, injured body region. Percept Mot Skills.
2004;98(2):519–24. https ://doi.org/10.2466/pms.98.2.519-524.
38. de Loes M, Goldie I. Incidence rate of injuries during sport activ-
ity and physical exercise in a rural Swedish municipality: inci-
dence rates in 17 sports. Int J Sports Med. 1988;9(6):461–7. https
://doi.org/10.1055/s-2007-10250 52.
39. Edouard P, Depiesse F, Branco P, Alonso JM. Analyses of Hel-
sinki 2012 European Athletics Championships injury and illness
surveillance to discuss elite athletes risk factors. Clin J Sport Med.
2014;24(5):409–15. https ://doi.org/10.1097/JSM.00000 00000
00005 2.
40. Edouard P, Depiesse F, Hertert P, Branco P, Alonso JM. Injuries
and illnesses during the 2011 Paris European Athletics Indoor
Championships. Scand J Med Sci Sports. 2013;23(4):e213–8.
https ://doi.org/10.1111/sms.12027 .
41. Edouard P, Navarro L, Branco P, Gremeaux V, Timpka T, Junge
A. Injury frequency and characteristics (location, type, cause and
severity) differed significantly among athletics (’track and field’)
disciplines during 14 international championships (2007–2018):
implications for medical service planning. Br J Sports Med.
2020;54(3):159–67. https ://doi.org/10.1136/bjspo rts-2019-10071
7.
42. Fokkema T, de Vos RJ, van Ochten JM, Verhaar JAN, Davis IS,
Bindels PJE, etal. Online multifactorial prevention programme
has no effect on the number of running-related injuries: a ran-
domised controlled trial. Br J Sports Med. 2019;53(23):1479–85.
https ://doi.org/10.1136/bjspo rts-2018-09974 4.
43. Hayes LE, Boulos A, Cruz AI Jr. Risk factors for in-season injury
in varsity collegiate cross-country athletes: an analysis of one sea-
son in 97 athletes. J Sports Med Phys Fitness. 2019;59(9):1536–
43. https ://doi.org/10.23736 /S0022 -4707.19.09221 -1.
44. Hespanhol Junior LC, van Mechelen W, Verhagen E. Health and
economic burden of running-related injuries in Dutch trailrunners:
a prospective cohort study. Sports Med. 2017;47(2):367–77. https
://doi.org/10.1007/s4027 9-016-0551-8.
45. Hespanhol Junior LC, van Mechelen W, Postuma E, Verhagen
E. Health and economic burden of running-related injuries in
runners training for an event: a prospective cohort study. Scand
J Med Sci Sports. 2016;26(9):1091–9. https ://doi.org/10.1111/
sms.12541 .
46. Hofstede H, Franke TPC, van Eijk RPA, Backx FJG, Kemler E,
Huisstede BMA. In training for a marathon: runners and running-
related injury prevention. Phys Ther Sport. 2020;41:80–6. https ://
doi.org/10.1016/j.ptsp.2019.11.006.
47. Hughes WA, Noble HB, Porter M. Distance race injuries: an anal-
ysis of runners’ perceptions. Phys Sportsmed. 1985;13(11):43–58.
https ://doi.org/10.1080/00913 847.1985.11708 924.
48. Jacobsson J, Timpka T, Kowalski J, Nilsson S, Ekberg J, Dahl-
strom O, etal. Injury patterns in Swedish elite athletics: annual
incidence, injury types and risk factors. Br J Sports Med.
2013;47(15):941–52. https ://doi.org/10.1136/bjspo rts-2012-09165
1.
49. Johansson C. Injuries in elite orienteers. Am J Sports Med.
1986;14(5):410–5. https ://doi.org/10.1177/03635 46586 01400 515.
50. Kluitenberg B, van Middelkoop M, Smits DW, Verhagen E, Hart-
gens F, Diercks R, etal. The NLstart2run study: Incidence and
risk factors of running-related injuries in novice runners. Scand
J Med Sci Sports. 2015;25(5):e515–23. https ://doi.org/10.1111/
sms.12346 .
51. Lagas IF, Fokkema T, Verhaar JAN, Bierma-Zeinstra SMA, van
Middelkoop M, de Vos RJ. Incidence of Achilles tendinopathy and
associated risk factors in recreational runners: a large prospective
cohort study. J Sci Med Sport. 2020;23(5):448–52. https ://doi.
org/10.1016/j.jsams .2019.12.013.
52. McLain LG, Reynolds S. Sports injuries in a high school. Pediat-
rics. 1989;84(3):446–50.
53. Messier SP, Martin DF, Mihalko SL, Ip E, DeVita P, Cannon
DW, etal. A 2-year prospective cohort study of overuse running
injuries: the runners and injury longitudinal study (TRAILS). Am
J Sports Med. 2018;46(9):2211–21. https ://doi.org/10.1177/03635
46518 77375 5.
54. Nicholl JP, Williams BT. Injuries sustained by runners during a
popular marathon. Br J Sports Med. 1983;17(1):10–5. https ://doi.
org/10.1136/bjsm.17.1.10.
55. Nielsen RO, Parner ET, Nohr EA, Sorensen H, Lind M, Rasmus-
sen S. Excessive progression in weekly running distance and risk
of running-related injuries: an association which varies according
to type of injury. J Orthop Sports Phys Ther. 2014;44(10):739–47.
https ://doi.org/10.2519/jospt .2014.5164.
56. Plisky MS, Rauh MJ, Heiderscheit B, Underwood FB, Tank
RT. Medial tibial stress syndrome in high school cross-country
runners: incidence and risk factors. J Orthop Sports Phys Ther.
2007;37(2):40–7. https ://doi.org/10.2519/jospt .2007.2343.
57. Rauh MJ, Koepsell TD, Rivara FP, Margherita AJ, Rice SG. Epi-
demiology of musculoskeletal injuries among high school cross-
country runners. Am J Epidemiol. 2006;163(2):151–9. https ://doi.
org/10.1093/aje/kwj02 2.
58. Rauh MJ, Margherita AJ, Rice SG, Koepsell TD, Rivara FP. High
school cross country running injuries: a longitudinal study. Clin
J Sport Med. 2000;10(2):110–6. https ://doi.org/10.1097/00042
752-20000 4000-00005 .
59. Rizzone KH, Ackerman KE, Roos KG, Dompier TP, Kerr ZY.
The epidemiology of stress fractures in collegiate student-athletes,
2004–2005 through 2013–2014 academic years. J Athl Train.
2017;52(10):966–75. https ://doi.org/10.4085/1062-6050-52.8.01.
60. Ruffe NJ, Sorce SR, Rosenthal MD, Rauh MJ. Lower quarter- and
upper quarter Y balance tests as predictors of running-related inju-
ries in high school cross-country runners. Int J Sports Phys Ther.
2019;14(5):695–706.
61. Steinacker T, Steuer M, Holtke V. Orthopedic problems in older
marathon runners. Sportverletz Sportschaden. 2001;15(1):12–5.
https ://doi.org/10.1055/s-2001-11962 .
62. Lynam DR, Whiteside S, Jones S. Self-reported psychopathy: a
validation study. J Pers Assess. 1999;73(1):110–32. https ://doi.
org/10.1207/S1532 7752J PA730 108.
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

1038 K.Hollander et al.
63. Walter SD, Hart LE, McIntosh JM, Sutton JR. The Ontario
cohort study of running-related injuries. Arch Intern Med.
1989;149(11):2561–4.
64. Winter SC, Gordon S, Brice SM, Lindsay D, Barrs S. Overuse
injuries in runners of different abilities-a one-year prospective
study. Res Sports Med. 2019. https ://doi.org/10.1080/15438
627.2019.16165 48.
65. Winter SC, Gordon S, Brice SM, Lindsay D, Barrs S. A mul-
tifactorial approach to overuse running injuries: a 1-year pro-
spective study. Sports Health. 2020;12(3):296–303. https ://doi.
org/10.1177/19417 38119 88850 4.
66. van Gent RN, Siem D, van Middelkoop M, van Os AG, Bierma-
Zeinstra SM, Koes BW. Incidence and determinants of lower
extremity running injuries in long distance runners: a system-
atic review. Br J Sports Med. 2007;41(8):469–80. https ://doi.
org/10.1136/bjsm.2006.03354 8.
67. van Poppel D, de Koning J, Verhagen AP, Scholten-Peeters GG.
Risk factors for lower extremity injuries among half marathon
and marathon runners of the Lage Landen Marathon Eindhoven
2012: a prospective cohort study in the Netherlands. Scand J
Med Sci Sports. 2016;26(2):226–34. https ://doi.org/10.1111/
sms.12424 .
68. Malisoux L, Delattre N, Urhausen A, Theisen D. Shoe cushioning
influences the running injury risk according to body mass: a ran-
domized controlled trial involving 848 recreational runners. Am
J Sports Med. 2020;48(2):473–80. https ://doi.org/10.1177/03635
46519 89257 8.
69. Hollander K, Heidt C, Babette CVDZ, Braumann KM, Zech A.
Long-term effects of habitual barefoot running and walking: a
systematic review. Med Sci Sports Exerc. 2017;49(4):752–62.
https ://doi.org/10.1249/MSS.00000 00000 00114 1.
70. Krabak BJ, Roberts WO, Tenforde AS, Ackerman KE, Adami PE,
Baggish AL, etal. Youth running consensus statement: minimis-
ing risk of injury and illness in youth runners. Br J Sports Med.
2020. https ://doi.org/10.1136/bjspo rts-2020-10251 8.
71. Bahr R, Clarsen B, Derman W, Dvorak J, Emery CA, Finch CF,
etal. International Olympic Committee consensus statement:
methods for recording and reporting of epidemiological data on
injury and illness in sport 2020 (including STROBE Extension
for Sport Injury and Illness Surveillance (STROBE-SIIS)). Br
J Sports Med. 2020;54(7):372–89. https ://doi.org/10.1136/bjspo
rts-2019-10196 9.
72. Soligard T, Schwellnus M, Alonso JM, Bahr R, Clarsen B, Dijk-
stra HP, etal. How much is too much? (Part 1) International
Olympic Committee consensus statement on load in sport and
risk of injury. Br J Sports Med. 2016;50(17):1030–41. https ://doi.
org/10.1136/bjspo rts-2016-09658 1.
73. Lin CY, Casey E, Herman DC, Katz N, Tenforde AS. Sex differ-
ences in common sports injuries. PM R. 2018;10(10):1073–82.
https ://doi.org/10.1016/j.pmrj.2018.03.008.
74. Hoenig T, Tenforde A, Strahl A, Rolvien T, Hollander K. Does
MRI grading correlate with return to sports following bone stress
injuries? A systematic review and meta-analysis. Am J Sports
Med. 2021; (accepted for publication).
75. Rauh MJ, Barrack M, Nichols JF. Associations between the female
athlete triad and injury among high school runners. Int J Sports
Phys Ther. 2014;9(7):948–58.
76. Tenforde AS, Carlson JL, Chang A, Sainani KL, Shultz R, Kim
JH, etal. Association of the female athlete triad risk assessment
stratification to the development of bone stress injuries in colle-
giate athletes. Am J Sports Med. 2017;45(2):302–10. https ://doi.
org/10.1177/03635 46516 67626 2.
77. Mountjoy M, Sundgot-Borgen J, Burke L, Ackerman KE, Blau-
wet C, Constantini N, etal. International Olympic Committee
(IOC) consensus statement on Relative Energy Deficiency in
Sport (RED-S): 2018 update. Int J Sport Nutr Exerc Metab.
2018;28(4):316–31. https ://doi.org/10.1123/ijsne m.2018-0136.
78. Tenforde AS, Parziale AL, Popp KL, Ackerman KE. Low bone
mineral density in male athletes is associated with bone stress
injuries at anatomic sites with greater trabecular composition. Am
J Sports Med. 2018;46(1):30–6. https ://doi.org/10.1177/03635
46517 73058 4.
79. Tenforde AS, Beauchesne AR, Borg-Stein J, Hollander K, McIn-
nis K, Kotler D, etal. Awareness and comfort treating the female
athlete triad and relative energy deficency in sport among health-
care p-roviders. Dtsch Z Sportmed. 2020;71(3):76–80. https ://doi.
org/10.5960/dzsm.2020.422.
80. Bredeweg SW, Kluitenberg B, Bessem B, Buist I. Differences in
kinetic variables between injured and noninjured novice runners:
a prospective cohort study. J Sci Med Sport. 2013;16(3):205–10.
https ://doi.org/10.1016/j.jsams .2012.08.002.
81. Magnan B, Bondi M, Pierantoni S, Samaila E. The pathogenesis
of Achilles tendinopathy: a systematic review. Foot Ankle Surg.
2014;20(3):154–9. https ://doi.org/10.1016/j.fas.2014.02.010.
82. Lopes AD, Hespanhol Junior LC, Yeung SS, Costa LO. What
are the main running-related musculoskeletal injuries? A sys-
tematic review. Sports Med. 2012;42(10):891–905. https
://doi.org/10.2165/11631 170-00000 0000-00000 (10.1007/
BF03262301).
83. Cook JL, Purdam CR. Is tendon pathology a continuum? A pathol-
ogy model to explain the clinical presentation of load-induced
tendinopathy. Br J Sports Med. 2009;43(6):409–16. https ://doi.
org/10.1136/bjsm.2008.05119 3.
84. Kernozek TW, Knaus A, Rademaker T, Almonroeder TG. The
effects of habitual foot strike patterns on Achilles tendon load-
ing in female runners. Gait Posture. 2018;66:283–7. https ://doi.
org/10.1016/j.gaitp ost.2018.09.016.
85. Asplund CA, Best TM. Achilles tendon disorders. BMJ.
2013;346:f1262. https ://doi.org/10.1136/bmj.f1262 .
86. Wearing SC, Davis IS, Brauner T, Hooper SL, Horstmann T. Do
habitual foot-strike patterns in running influence functional Achil-
les tendon properties during gait? J Sports Sci. 2019;37(23):2735–
43. https ://doi.org/10.1080/02640 414.2019.16636 56.
87. Lieberthal K, Paterson KL, Cook J, Kiss Z, Girdwood M, Brad-
shaw EJ. Prevalence and factors associated with asymptomatic
Achilles tendon pathology in male distance runners. Phys Ther
Sport. 2019;39:64–8. https ://doi.org/10.1016/j.ptsp.2019.06.006.
88. Bryant AL, Clark RA, Bartold S, Murphy A, Bennell KL, Hohm-
ann E, etal. Effects of estrogen on the mechanical behavior
of the human Achilles tendon invivo. J Appl Physiol (1985).
2008;105(4):1035–43. https ://doi.org/10.1152/jappl physi ol.01281
.2007.
89. Leblanc DR, Schneider M, Angele P, Vollmer G, Docheva D. The
effect of estrogen on tendon and ligament metabolism and func-
tion. J Steroid Biochem Mol Biol. 2017;172:106–16. https ://doi.
org/10.1016/j.jsbmb .2017.06.008.
90. Oliva F, Piccirilli E, Berardi AC, Frizziero A, Tarantino U, Maf-
fulli N. Hormones and tendinopathies: the current evidence. Br
Med Bull. 2016;117(1):39–58. https ://doi.org/10.1093/bmb/ldv05
4.
91. Kubo K, Miyamoto M, Tanaka S, Maki A, Tsunoda N, Kanehisa H.
Muscle and tendon properties during menstrual cycle. Int J Sports
Med. 2009;30(2):139–43. https ://doi.org/10.1055/s-0028-11045
73.
92. Abate M, Guelfi M, Pantalone A, Vanni D, Schiavone C, Andia I,
etal. Therapeutic use of hormones on tendinopathies: a narrative
review. Muscles Ligaments Tendons J. 2016;6(4):445–52. https
://doi.org/10.11138 /mltj/2016.6.4.445.
93. Wright AA, Taylor JB, Ford KR, Siska L, Smoliga JM. Risk
factors associated with lower extremity stress fractures in run-
ners: a systematic review with meta-analysis. Br J Sports Med.
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

1039
Sex-Specific Differences in Running Injuries
2015;49(23):1517–23. https ://doi.org/10.1136/bjspo rts-2015-
09482 8.
94. Tenforde AS, Sayres LC, McCurdy ML, Sainani KL, Frederic-
son M. Identifying sex-specific risk factors for stress fractures in
adolescent runners. Med Sci Sports Exerc. 2013;45(10):1843–51.
https ://doi.org/10.1249/MSS.0b013 e3182 963d7 5.
95. Yagi S, Muneta T, Sekiya I. Incidence and risk factors for medial
tibial stress syndrome and tibial stress fracture in high school run-
ners. Knee Surg Sports Traumatol Arthrosc. 2013;21(3):556–63.
https ://doi.org/10.1007/s0016 7-012-2160-x.
96. Reinking MF, Austin TM, Richter RR, Krieger MM. Medial Tibial
stress syndrome in active individuals: a systematic review and
meta-analysis of risk factors. Sports Health. 2017;9(3):252–61.
https ://doi.org/10.1177/19417 38116 67329 9.
97. Timpka T, Alonso JM, Jacobsson J, Junge A, Branco P, Clarsen B,
etal. Injury and illness definitions and data collection procedures
for use in epidemiological studies in Athletics (track and field):
consensus statement. Br J Sports Med. 2014;48(7):483–90. https
://doi.org/10.1136/bjspo rts-2013-09324 1.
98. Yamato TP, Saragiotto BT, Lopes AD. A consensus definition of
running-related injury in recreational runners: a modified Delphi
approach. J Orthop Sports Phys Ther. 2015;45(5):375–80. https
://doi.org/10.2519/jospt .2015.5741.
99. Yamato TP, Saragiotto BT, Hespanhol Junior LC, Yeung SS,
Lopes AD. Descriptors used to define running-related musculo-
skeletal injury: a systematic review. J Orthop Sports Phys Ther.
2015;45(5):366–74. https ://doi.org/10.2519/jospt .2015.5750.
Aliations
KarstenHollander1,2 · AnnaLinaRahlf3 · JanWilke4 · ChristopherEdler5 · SimonSteib6 · AstridJunge1,7 ·
AstridZech3
1 Medical School Hamburg, Hamburg, Germany
2 Department ofPhysical Medicine andRehabilitation,
Spaulding National Running Center, Harvard Medical
School, Cambridge, MA, USA
3 Department ofHuman Movement Science andExercise
Physiology, Institute ofSport Science, Friedrich Schiller
University Jena, Jena, Germany
4 Department ofSports Medicine andExercise Physiology,
Goethe University Frankfurt, Frankfurt, Germany
5 Prevention, Rehabilitation andInterdisciplinary Sports
Medicine, BG Trauma Hospital ofHamburg, Hamburg,
Germany
6 Department ofHuman Movement, Training andActive
Aging, Institute ofSports andSports Science, Heidelberg
University, Heidelberg, Germany
7 Swiss Concussion Center, Schulthess Klinik, Zürich,
Switzerland
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

1.
2.
3.
4.
5.
6.
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