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©Journal of Sports Science and Medicine (2017) 16, 53-59
http://www.jssm.org
Received: 08 November 2016 / Accepted: 09 January 2017 / Published (online): 01 March 2017
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Retrospective Injury Epidemiology and Risk Factors for Injury in CrossFit
Alicia M. Montalvo 1
, Hilary Shaefer 1, Belinda Rodriguez 1, Tan Li 1, Katrina Epnere 1 and Grego-
ry D. Myer 2
1 Florida International University, Miami, FL, USA
2 Cincinnati Children's Hospital Medical Center in Cincinnati, OH., USA
Abstract
The objective of the study is to examine injury epidemiology
and risk factors for injury in CrossFit athletes. A survey was
administered to athletes at four owner-operated facilities in
South Florida. Respondents reported number, location of injury,
and training exposure from the preceding six months and an-
swered questions regarding potential risk factors for injury. Fifty
out of 191 athletes sustained 62 injuries during CrossFit partici-
pation in the preceding six months. The most frequently injured
locations were the shoulder, knee, and lower back. Injury inci-
dence was 2.3/1000 athlete training hours. Competitors were
more likely to be injured (40% v 19%, p = 0.002) and had great-
er weekly athlete training hours (7.3 ± 7.0 v 4.9 ± 2.9, p <
0.001) than non-competitors. Athletes who reported injury also
reported significantly higher values for the following risk fac-
tors: years of participation (2.7 ± 1.8 v 1.8 ± 1.5, p = 0.001),
weekly athlete training hours (7.3 ± 3.8 v 4.9 ± 2.1, p = 0.020),
weekly athlete-exposures (6.4 ± 3.8 v 4.7 ± 2.1, p = 0.003),
height (1.72 ± 0.09 m v 1.68 ± 0.01 m, p = 0.011), and body
mass (78.24 ± 16.86 kg v 72.91 ± 14.77 kg, p = 0.037). Injury
rates during CrossFit and location of injuries were similar to
those previously reported. Injury incidence was similar to relat-
ed sports, including gymnastics and powerlifting. While being a
competitor was related to injury, increased exposure and length
of participation in CrossFit likely underlied this association.
Specifically, increased exposure to training in the form of great-
er weekly athlete training hours and weekly participations may
contribute to injury. Increased height and body mass were also
related to injury which is likely reflective of increased load
utilized during training. Further research is warranted to deter-
mine if biomechanical factors associated with greater height and
ability to lift greater loads are modifiable factors that can be
adapted to reduce the increase risk of injury during CrossFit.
Key words: Incidence, prevalence, exercise, weight training.
Introduction
CrossFit is a strength and conditioning program that em-
phasizes functional and constantly varied exercise per-
formed at a relatively high intensity. A key characterizing
feature of CrossFit exercise is scalability. Scalability
refers not only to progressions in load, but to modifica-
tions to movements that involve greater skill and/or flexi-
bility. Through the use of these modifications, individuals
of varying fitness levels ranging from beginner to ad-
vanced can participate in a similar training regimen, or the
“workout of the day” (WOD). The issue of scalability is
particularly important in group settings because of the
types of WODs that are typically programmed. WODs are
usually completed for time, sometimes with a time cap, or
as many rounds of the exercise are completed as possible
within a given period of time. Scaling of high skill
movements, such as muscle-ups and toes-to-bar, allows
less skilled athletes to both participate in the WOD in a
manner similar to how it was prescribed and to build
towards achieving the strength and skill necessary to
execute the prescribed movement. Scalability enables
another feature of CrossFit: community. Athletes of vary-
ing skill levels can share the experience of a WOD to-
gether.
While some CrossFit athletes complete WODs in-
dividually or informally, many CrossFit athletes belong to
CrossFit affiliates, or independently operated facilities,
where they may participate in individual or group-based
CrossFit. Many affiliates promote another key feature of
CrossFit which is the purported reason for CrossFit’s
effectiveness – a sense of community. CrossFit affiliate
members reported experiencing significantly greater
bonding (friendship development) and community be-
longingness compared to traditional gym members
(Whiteman-Sandland et al., 2016). Research indicates that
cohesion contributes to exercise adherence, which may
explain this belief related to CrossFit’s effectiveness
(Burke et al., 2008).
CrossFit’s popularity has increased substantially
since 2005. With the rapid increase in participation and
limited associated literature on injury epidemiology,
CrossFit has been questioned for its safety. CrossFit
WODs combine traditional cardiovascular exercises, such
as running, biking, and rowing, with elements from
Olympic weightlifting, powerlifting, strongman, and
gymnastics. The elements from other sports include, but
are not limited to, the clean, jerk, and snatch from Olym-
pic weightlifting, the squat and deadlift from powerlifting,
the farmer walk, tire flip, and yoke from strongman, and
the handstand walk and muscle-up from gymnastics.
While it borrows elements from these sports, CrossFit is
different from them in distinct ways. Olympic weightlift-
ing and powerlifting have events that occur in a specific
order. For example, in Olympic weightlifting the snatch
always precedes the clean and jerk. The goals of these
sports is to lift the greatest loads. CrossFit is more similar
to strongman in the sense that events within a competition
vary. Strongman, as the name implies, has a greater em-
phasis on feats of strength whereas CrossFit utilizes
WODs that test cardiovascular and muscular power,
strength, and endurance. WODs typically mix aerobic and
anaerobic exercises with high skill movements, including
Research article
CrossFit injury epidemiology
54
jerks, snatches and muscle-ups, which are performed
under cardiovascular and muscular fatigue conditions.
This is in contrast to traditional training principles that
promote the execution of multi-joint power movements
first in order to maximize load and preserve technique
(Baechle and Earle, 2008). Furthermore, traditional train-
ing principles emphasize technical competence, especially
with multi-joint power movements. Fatigue associated
with high intensity anaerobic exercise may result in the
deterioration of concentration and skill. This fatigue is
believed to put athletes at greater risk of injury. The unor-
thodox combination and order of exercises and decreased
focus on technical competence compared to related sports
have contributed to the concerns about CrossFit’s safety.
As a result, newspapers and media outlets have noted the
potential danger of CrossFit participation (Cooperman,
2005; Diamond, 2015; Robertson, 2013).
Despite the safety concerns, little evidence exists
to either support or refute safety-related claims for Cross-
Fit athletes. Existing research on CrossFit injury epidemi-
ology utilizes methods that may not result in representa-
tive findings as sampling techniques did not address par-
ticipant self-selection. Hak et al. (2013) utilized online
CrossFit forums to collect data on CrossFit injury epide-
miology using a retrospective survey, but were unable to
determine how many individuals viewed the survey and
opted not to take it. Weisenthal et al. (2014) sent their
retrospective injury epidemiology survey to specific affil-
iates and made it available on the main CrossFit website.
They also were unable to determine how many individu-
als viewed the survey and opted not to take it. In addi-
tion, there is a dearth of research that uses advanced sta-
tistical techniques to identify risk factors that may lead to
injury in CrossFit athletes. Therefore, the purpose of this
research was to examine injury epidemiology and risk
factors for injury in CrossFit. Results of this research may
be used to determine relative safety of the sport and to
identify potential factors that put athletes at greater risk of
injury.
Methods
Subjects
Fourteen CrossFit affiliates in South Florida were asked
to participate in the research. Only four affiliates agreed
to participate. All participating affiliates were owner-
operated facilities, or facilities owned and managed by the
same individual. A total of 255 athletes from participating
affiliates were asked to participate in the research. Of
those athletes who were asked, 191 completed the survey.
CrossFit athletes were eligible for participation if they
were members at the facilities and were present the day of
data collection. There were no exclusion criteria. The
research was approved by the university’s Institutional
Review Board. Consent was implied upon submission of
each survey.
Instrumentation
The purpose of this investigation was to examine the
location, severity, and number of injuries, and potential
risk factors for injury in the preceding six months. The
survey was developed and used to collect data on these
variables. In addition to original questions, the survey
contained questions similar to those posed by Winwood et
al. (2014) in a retrospective injury survey for strongman
athletes. Content validity was established via review by a
Level I certified CrossFit coach, two Division I collegiate
athletic trainers, and an exercise science professional. The
survey was modified based on suggestions to improve
clarity. Next, the survey was piloted at one CrossFit affil-
iate and changes were made to questions based on feed-
back from pilot participants.
The survey was composed of three sections. Sec-
tion one pertained to the athletes’ participation. These
questions were related to athletes’ participation in Cross-
Fit, including length of participation in CrossFit (years),
frequency of participation in CrossFit (weekly athlete
training days, weekly athlete training hours, and weekly
athlete-exposures), and whether or not athletes incorpo-
rated warm-ups and cool-downs. Section two pertained to
CrossFit injury history within the preceding six months.
Injury was defined as any physical damage to a body part
that caused them to miss or modify one or more training
sessions or hindered activities of daily living. If the ath-
lete had an injury, they were asked to mark with an “X”
the exact location of injury on an illustrated representation
of an anatomical figure (Figure 1). Because the injury
history portion only allowed participants to report one
injury at a time additional injuries were reported on sepa-
rate forms. Questions targeting type of injury were used to
determine mechanism (acute versus chronic onset). Ques-
tions targeting severity of injury focused on the changes
athletes had to make to training because of injury and
treatment that athletes received following injury. Section
three pertained to the athletes’ background. The questions
asked about fitness level before beginning CrossFit, moti-
vation for CrossFit participation, physical activity outside
of CrossFit, and participation in CrossFit competitions.
This section also addressed demographic and biometric
information. All measurements were self-reported and
injuries were not confirmed via diagnosis from a medical
professional.
Figure 1. Anatomical diagram used to detail location of
injury.
Procedures
Researchers spent one day at each of the four CrossFit
facilities administering surveys. Upon entering the facili-
Montalvo et al.
55
ty, CrossFit athletes were asked to participate in the sur-
vey and each coach encouraged participation at the end of
each WOD. Athletes were given the survey, which in-
cluded instructions for each section. If the subjects had
any questions, researchers were available for answers.
Each survey was reviewed for completion upon submis-
sion. The number of responses and refusals were tallied in
order to calculate a response rate.
Data were coded and entered into a spreadsheet.
For location of injury, body parts from the figure were
classified using the National Athletic Injury/Illness Re-
porting System by a licensed and certified athletic trainer
(Buckley, 1982; Clarke and Miller Jr, 1974). For open-
ended questions where responses were uninterpretable,
data were excluded from final analyses.
Injury rates
Injury rates were calculated by estimating the number of
athlete training hours in the preceding six months. The
question that asked, “In the last week, how much time in
hours did you spend doing CrossFit WODs”, was used in
the estimate. Total weekly athlete training hours reported
were multiplied by 26, the number of weeks in six
months. Rate was then converted to number of inju-
ries/1000 athlete training hours.
Statistical procedures
Descriptive statistics were calculated for each variable.
Chi-Square or Fisher’s Exact Tests were used to test the
unadjusted association of categorical variables and inde-
pendent t-tests were used on continuous variables to com-
pare athletes with and without injury in the preceding six
months. Multiple logistic regression was used to evaluate
adjusted associations. To select the final logistic regres-
sion model, forward, backward and stepwise model selec-
tion procedures were considered. To avoid multicollinear-
ity, the variation inflation factor was examined before
entering the variables into the regression model. For the
covariates that were included in the final logistic regres-
sion model, adjusted odds ratios (AOR) and 95% confi-
dence intervals (CI) were estimated. A p-value of 0.05
was used to determine statistical significance. All statisti-
cal procedures were performed using the SPSS software,
version 17.0 (IBM Corporation, NY, USA) and Statistical
Analysis System (SAS) 9.4 for Windows (SAS Institute
Inc., Cary, NC, USA).
Results
Risk factors for injury
One hundred ninety-one CrossFit athletes were surveyed
(94 males, 97 females) from four owner-operated facili-
ties in South Florida. The response rate was 75%
(191/255). Participant characteristics are presented in
Table 1 (Total). Fifty out of 191 athletes sustained a total
of 62 injuries during CrossFit participation in the preced-
ing six months. The reported incidence rate of injury
equated to 2.3 injuries/1000 hours of participation. With
regard to risk factors, injured athletes differed from unin-
jured athletes for several characteristics (Table 1). Years
of participation in CrossFit, weekly athlete training hours,
weekly athlete-exposures, height, and body mass differed
between injured and uninjured athletes (p < 0.05). Injured
athletes did not differ from uninjured athletes with regard
to weekly athlete-days, class size, coach number, years
completing structured physical activity, or age in unad-
justed analyses. In addition, males and females had simi-
lar injury prevalence (31.91% v 20.62%, p = 0.076).
In unadjusted models, participation in CrossFit
competition was significantly associated with injury (Ta-
ble 2). Forty percent of competitors were injured in the
preceding six months while only 19.05% of non-
competitors were injured; however, competitors reported
significantly greater athlete training hours than non-
competitors (7.1 v 4.7, p = 0.008). In addition, physical
activity outside of CrossFit was significantly associated
with injury. Over 30% of those who participated in out-
side physical activity reported injury in the preceding six
months while only 15% of those who did not engage in
outside physical activity reported injury. Gender, inclu-
sion of warm-ups and cool-downs, and participation in
CrossFit for fitness were not related to injury
Greater length of participation in CrossFit in-
creased the odds of being injured (AOR = 1.252, CI:
1.002-1.564; Table 3). Competitors had 93.7% (AOR =
1.937, CI: 0.873-4.298) higher odds of being injured
compared to non-competitors; however, participation in
CrossFit competitions was not significant in the adjusted
model (p = 0.1041). The odds of being injured for those
athletes who engaged in physical activity outside of
CrossFit were 2.3 (AOR: 2.311, CI: 1.1011, 5.283) times
the odds of being injured while not engaging in outside
physical activity. Higher weekly athlete-exposures
Table 1. Means and standard deviations and results for independent t-tests comparing uninjured and injured CrossFit par-
ticipants with regard to potential risk factors (unadjusted).
Variable
Injury status
p-value
Total (n = 191)
Uninjured (n=141)
Injured (n=50)
Mean
SD
Mean
SD
Mean
SD
Years of participation in CrossFit
2.04
1.65
1.80
1.52
2.71
1.82
0.001
Weekly athlete training hours
5.49
4.48
4.85
2.94
7.30
6.98
0.020
Weekly athlete training days
4.39
1.31
4.29
1.26
4.68
1.42
0.069
Weekly athlete-exposures
5.12
2.78
4.65
2.14
6.41
3.80
0.003
CrossFit class size
9.24
4.76
9.40
4.73
8.79
4.89
0.438
Number of coaches per CrossFit class
1.48
0.64
1.48
0.63
1.48
0.67
0.946
Years of physical activity
17.74
29.64
16.25
28.46
21.94
32.69
0.114
Age
31.69
9.40
31.78
9.78
31.42
8.34
0.817
Height (m)
1.68
0.10
1.68
0.10
1.72
0.09
0.011
Body mass (kg)
74.32
15.49
72.91
14.77
78.24
16.86
0.037
CrossFit injury epidemiology
56
Table 2. Means and percentages and results for Chi-Square/Fisher’s Exact Tests comparing uninjured and in-
jured CrossFit participants with regard to potential risk factors (unadjusted).
Variable
Injury status
Total (n = 191)
Uninjured (n = 141) Injured (n = 50)
n
%
n
%
n
%
sig.
Participation in CrossFit competitions
**
Non-competitor
126
66.0
102
81.0
24
19.1
Competitor
65
34.0
39
60.0
26
40.0
Fitness level before CrossFit
Not fit at all
32
16.8
24
75.0
8
25.0
Not very fit
33
17.3
26
78.8
7
21.2
Average fitness
88
46.1
64
72.7
24
27.3
Very fit
30
15.7
21
70.0
9
30.0
Extremely fit
8
4.2
6
75.0
2
25.0
Warm up included in CrossFit workouts
$
Yes
187
97.9
137
73.3
50
26.7
No
4
2.1
4
100.0
0
0.0
Cool down included in CrossFit workouts
Yes
144
75.4
106
73.6
38
26.4
No
47
24.6
35
74.5
12
25.5
Physical Activity outside CrossFit
*
Yes
123
64.4
84
68.3
39
31.7
No
67
35.1
57
85.1
10
15.0
CrossFit for Fitness
Yes
180
94.2
134
74.4
46
25.6
$
No
11
5.8
7
63.6
4
36.4
Gender
Male
94
49.2
64
68.1
30
31.9
Female
97
50.8
77
79.4
20
20.6
* Significant at 0.05 **Significant at 0.01 **Significant at 0.001. $ Fisher’s Exact test instead of Chi-Square (expected
counts less than 5).
Table 3. Multivariable logistic regression analysis of risk factors associated with status of injury
for CrossFit participants.
Variable
AOR
95% CI
p-value
Years of participation in CrossFit
1.25
1.00
1.56
0.048
Participation in CrossFit competitions
0.104
Competitor
1.94
0.87
4.30
Non-Competitor
Ref
Physical activity outside CrossFit
0.047
Yes
2.31
1.01
5.28
No
Ref
Weekly athlete exposures
1.17
1.00
1.37
0.048
Height
1.12
1.01
1.24
0.029
AOR=adjusted odds ratio, CI=confidence interval, Ref=reference category.
increased the odds of injury (AOR =1.172, CI: 1.002-
1.371). Taller CrossFit athletes had increased odds of
being injured (AOR = 1.124, CI: 1.013-1.247).
Injury epidemiology
Of the 50 respondents who reported injury in the preced-
ing six months, 12 respondents reported more than one
injury over the surveillance period. The most frequent
injured locations were the shoulder (14/62), knee (10/62),
and lower back (8/62). Table 4 presents the frequency of
all injury sites and incidence at each site. Eleven out of 62
injuries were pre-existing or re-injuries and 47/62 were
primary injuries that occurred as a direct result of Cross-
Fit participation. Most of the injuries occurred acutely
(34/62), whereas a smaller proportion were chronic in
onset (22/62). Twenty-four percent of the athletes indicat-
ed that their injury did not affect their training while 50%
indicated that their reported injury caused them to change
their performance of an exercise/training regimen. Nearly
20% of the athletes reported that the injury caused Cross-
Fit cessation and another 20% of the athletes reported that
the injury caused cessation of specific exercises. Over
half of the athletes reported that their injuries required
attention from a medical professional. However, some
injuries were resolved using self-administered care. Three
injuries did not require treatment or alterations to training
program.
Discussion
The overall incidence of injury in CrossFit athletes was
2.3/1000 athlete training hours, with 26% of athletes
reporting injury. This rate was similar to those previously
reported. Hak et al. (2013) distributed a survey on online
CrossFit forums and reported a rate 3.1 injuries/1000
hours of CrossFit participation. Weisenthal et al. (2014)
Montalvo et al.
57
conducted an internet survey on CrossFit injury epidemi-
ology and found that 19.4% (75/386) of athletes reported
injury. Sprey et al. (2016) found that 31% of CrossFit
athletes who completed their survey experienced injury
during CrossFit participation. Additionally, in a survey
investigating only shoulder injuries in CrossFit athletes
Summit et al. (2016) found that incidence of new shoulder
injuries was 1.18/1000 athlete training hours. This was
more than double the incidence we reported. However,
Summit et al. (2016) specifically targeted CrossFit ath-
letes with shoulder injury.
Table 4. Frequency, percentage, and incidence rate of in-
jured body parts (n = 62).
Body part Frequency Percent
Incidence/1000
athlete training hours
Shoulder
14
22.6
0.51
Knee
10
16.1
0.37
Lower back
8
12.9
0.29
Wrist
7
11.3
0.26
Hand
4
6.5
0.15
Upper arm
3
4.8
0.11
Upper back
3
4.8
0.11
Elbow
2
3.2
0.07
Ankle
2
3.2
0.07
Shin
2
3.2
0.07
Calf
1
1.6
0.04
Cervical spine
1
1.6
0.04
Foot
1
1.6
0.04
Hip
1
1.6
0.04
Rib
1
1.6
0.04
Systemic
1
1.6
0.04
Thigh
1
1.6
0.04
In addition to other CrossFit-specific reports, the
rate of injury fell within the range of injury incidence in
related sports. The rate of injury in powerlifters has been
reported to be between 1.0-5.8 injuries/1000 hours
(Brown and Kimball, 1983; Haykowsky et al., 1999;
Keogh et al., 2006; Raske and Norlin, 2002; Siewe et al.,
2011). The rate of injury in Olympic weightlifters has
been reported to be between 2.4-3.3 injuries/1000 hours
(Calhoon and Fry, 1999; Raske and Norlin, 2002). Injury
incidence in CrossFit was similar to injury incidence in
both Olympic weightlifting and powerlifting which sug-
gests that movements from these sports are possibly con-
tributing to a majority of injuries in CrossFit. This finding
is supported by Weisenthal et al. (2014) who found that
powerlifting and Olympic lifting movements accounted
for 40% of injuries. Kolt and Kirkby (1999) reported a
rate of 2.63 injuries/1000 hours in elite gymnasts and a
rate of 4.63 injuries/1000 hours in subelite gymnasts. The
higher incidence of injury in subelite gymnasts indicates
that lack of gymnastics skill may be related to injury. The
fact that our rate was more similar to that of elite gym-
nasts suggests that CrossFit athletes performing gymnas-
tics movements are likely skilled and that CrossFit ath-
letes who are less skilled are likely not performing gym-
nastics movements. Regardless, Weisenthal et al. (2014)
reported that gymnastics movements accounted for 20%
of all injuries. Finally, the rate of injury in CrossFit was
lower than that reported by Winwood et al. (2014) in
competitive strongmen (5.5 injuries/1000 hours). This
finding is of interest because our results suggested that
taller and heavier athletes were more likely to experience
injury. In their study, Winwood et al. (2014) reported that
the average height and mass of their strongman respond-
ents were 1.83 ± 0.07m and 113 ± 20kg, respectively.
Their respondents were considerably larger than our re-
spondents who reported injury (1.72 ± 0.09 m, 78.2 ±
16.9kg). Moreover, Winwood et al (2014) suggest that it
is the nature of the movements that may result in the
higher rate of injury in strongman athletes. While Cross-
Fit does incorporate elements from strongman, they may
not be the elements that put athletes at the greatest risk of
injury. These elements include stones, tire flip, and log
press, among others (Winwood et al., 2011). Overall, we
found that injury incidence in CrossFit athletes was simi-
lar to related sports.
With regard to location of injury, our results indi-
cated that the shoulder, knee, and lower back were the
most frequently injured locations. This was similar to
findings from both Hak et al. (2013) and Weisenthal et al
(2014). Hak et al. (2013) identified the shoulder and spine
as the most frequently reported locations of injury and
Weisenthal et al. (2014) identified the shoulder, lower
back, and knee as the most frequently injured locations. In
their review, Keogh and Winwood (2016) found that
Olympic weightlifters most frequently injured the knee,
lower back, and shoulder, powerlifters most frequently
injured the shoulder, lower back, and knee, and strong-
men most frequently injured the lower back, shoulder, and
bicep. CrossFit athletes most closely resembled power-
lifters in this sense. This finding was surprising consider-
ing the rate of injury in CrossFit athletes most closely
resembled that of Olympic weightlifters and because
Weisenthal et al. (2014) found that powerlifting move-
ments resulted in more injuries than Olympic weightlift-
ing movements (23% vs 17%). One possible explanation
for this finding may be that Olympic weightlifters are
more accustomed to lifting weight overhead than power-
lifters and CrossFit athletes. As such, they may have in-
creased skill, strength, and flexibility relative to other
lifting athletes. Keogh et al. (2006) found that elite Olym-
pic weightlifters had lower injury incidence than non-elite
Olympic weightlifters, indicating that greater skill,
strength, and flexibility are related to lower injury inci-
dence. All of these findings combined suggest that Cross-
Fit athletes who aim to reduce their risk of shoulder injury
should improve skill, strength, and felexibility in over-
head gymnastics and Olympic lifting activities.
With regard to potential risk factors for CrossFit
participation, injured athletes had significantly greater
training exposure than uninjured athletes. Greater expo-
sure equates to more chances in which injury can occur.
As such, this finding is expected. As previously men-
tioned, injured athletes were significantly taller and
weighed significantly more than uninjured athletes. Simi-
larly, heavyweight strongmen (>105kg) reported signifi-
cantly greater incidence than lightweight strongmen
(<105kg) (Winwood et al., 2014). Greater height may be
associated with greater biomechanical moments. In addi-
tion, athletes who are larger are likely training with in-
creased load and placing their musculoskeletal systems at
CrossFit injury epidemiology
58
increased risk of injury. We speculate that increased risk
of injury may actually be associated with strength and not
with anthropometrics. Finally, injured athletes had signif-
icantly greater length of participation/experience in
CrossFit than uninjured athletes. This finding may be
partially explained by skill level and, again, the relative
loads utilized, which were not measured in this research.
As skill level and strength improve, CrossFit athletes
scale to more difficult movements and heavier loads. By
scaling to make exercise more challenging, it is possible
that athletes are performing movements or lifting loads
that may increase their risk of injury. Further research is
needed to identify specific movements that resulted in
injury to CrossFit athletes and to investigate the effect of
load on injury.
With regard to injury severity, most injuries were
acute (34/62), caused the athlete to stop performing an
exercise or cease activity completely (19/62), and most
required medical attention (26/62). Hak et al. (2013) also
reported that most injuries in CrossFit athletes were acute.
However, they found that most injuries were mild. Con-
versely, Weisenthal et al. (2014) found that 73.5% of
CrossFit athletes reported injury that prevented them from
working, training, or competing and that 7% of athletes
required surgery for the injury. However, neither Hak et
al. (2013) nor Weisenthal et al. (2014) had systematic
sampling or reported response rate. Results of this re-
search indicate that injury severity is consistent with what
has previously been reported.
Because of the greater skill level assumed to ac-
company competition, it was hypothesized that competi-
tors would be at greater risk of injury. However, competi-
tors only had a slightly increased risk of injury relative to
non-competitors in unadjusted models. This association
was not significant in adjusted models. Additionally,
while competitors had a significantly greater injury inci-
dence than non-competitors, they also had significantly
greater exposure. As previously mentioned, greater expo-
sure allows for more chances for injury to occur. It is
likely that time spent participating in CrossFit was a con-
founding factor for the greater incidence of injury ob-
served in competitors. This association was likely further
confounded by length of participation in CrossFit. Rather
than competition being a risk factor for injury, it is likely
that the increased skill level and strength that accompany
greater and longer participation increased injury inci-
dence.
This research was not without its limitations. Only
four facilities chose to allow the survey to be adminis-
tered to patrons and all facilities were owner-operated.
These findings may not be generalizable to other types of
facilities, such as individual facilities or groups of facili-
ties owned by investors. Specifically the results of the
current study may be biased to facilities that follow the
safest CrossFit practices. In addition, we were unable to
capture information from athletes who were not present
for data collection due to injury or who no longer partici-
pate in CrossFit due to injury. Finally, exposure was esti-
mated by using the preceding six months. This method
may have resulted in an inaccurate estimate of exposure.
Furthermore, athletes may have completed the survey
under fatigued conditions which could have influenced
their ability to recall the preceding six months correctly.
However, the injury incidence rate was similar to those of
previous research and related sports. This indicates that
we likely experienced similar bias to previous research
despite efforts to achieve less bias. Future research on
injury epidemiology in CrossFit should focus on maxim-
izing external validity and on capturing the true popula-
tion. Additionally, to overcome recall bias, future investi-
gations into CrossFit injury epidemiology should be pro-
spective as recommended by Keogh and Winwood
(2016). To reduce the risk of injury in CrossFit future
research should identify which exercises, conditions, or
modifiable factors result in injury, especially to the shoul-
der, lower back, and knee.
Conclusion
Currently, only 20% of American adults meet physical
activity guidelines set forth by the US government and
69% of adults are overweight or obese.(Prevention; Pre-
vention) The US government recommends that adults
perform 75 minutes of vigorous intensity physical activity
and two days of moderate or high intensity muscle
strengthening two days per week.(Promotion). CrossFit
offers a solution to achieving vigorous physical activity
and weight training recommendations with the added
benefit of cohesion, which may improve exercise adher-
ence. While the rate of injury in CrossFit is similar to
other forms of exercise, some injured respondents report-
ed the need to cease physical activity or seek medical
attention. Individuals interested in pursuing CrossFit for
fitness, competition, or both should weigh the risks and
benefits of participation.
Acknowledgements
The authors declare no conflict of interests regarding the publication of
this manuscript.
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Key points
• The overall rate of injury in CrossFit athletes was
2.3/1000 athlete training hours.
•
The shoulder, knee, and lower back were the most
frequently reported locations of injury.
• In adjusted models, length of participation in Cross-
Fit, physical activity outside of CrossFit, weekly ath-
lete-exposures to CrossFit, and height were associat-
ed with injury in CrossFit athletes.
AUTHOR BIOGRAPHY
Alicia MONTALVO
Employment
Assistant Professor of Athletic Training at Florida Interna-
tional University in Miami, FL.
Degree
PhD
Research interests
Injury epidemiology; injury prevention; epigenetics; preci-
sion medicine
E-mail: amontal@fiu.edu
Hilary SHAEFER
Employment
Certified and licensed athletic trainer at Immaculata-La Salle
High School in Miami, Florida.
Degree
MSc
Research interests
Injury epidemiology
E-mail: Hshae002@fiu.edu
Belinda RODRIGUEZ
Employment
Certified and licensed athletic trainer at Lourdes Academy in
Miami, Florida.
Degree
MSc
Research interests
Injury epidemiology
E-mail: Brodr037@fiu.edu
Tan LI
Employment
Assistant professor of Biostatistics and Deputy Director of
the Integrated Biostatistics & Data Management Center at
Florida International University in Miami, FL.
Degree
PhD
Research interests
Item response t
heory for ordinal data analysis; multilevel
regression modeling; logic regression modeling
E-mail: tanli@fiu.edu
Katrina Epnere
Employment
G
raduate student of Biostatistics at Florida International
University in Miami, FL.
Degree
BSc
Research interests
Item response t
heory for ordinal data analysis; multilevel
regression modeling; logic regression modeling
E-mail: Kepne001@fiu.edu
Gregory D. MYER
Employment
Director of Research and The Human Performance Laborato-
ry in the
Division of Sports Medicine at Cincinnati Children's Hospital
Medical Center in Cincinnati, OH.
Degree
PhD
Research interests
Injury biomechanics; human performance; pediatric exercise
science; preventative medicine; sensorimotor neuroscience
E-mail: Greg.myer@cchmc.org
Alicia Montalvo, PhD, LAT, ATC, CSCS
Assistant Professor, Athletic Training Program, Nicole
Wertheim College of Nursing and Health Sciences, Florida
International University, AHC 3-331, Miami, FL, USA 33199
