The relationship between CrossFit performance and grip strength

Abstract

There is a growing interest in maximizing CrossFit (CF) performance as the sport becomes more economically viable at elite levels. The ability to delineate the physiological demands of the sport of CF allows coaches and athletes to develop more efficacious exercise programming in order to maximize the athlete’s potential for success at the most elite and lucrative levels of competition. There is also a growing interest in increasing health and fitness in the general population as obesity and chronic disease rates continue to rise. Hand grip strength (HGS) is an indicator of total body strength, mortality, morbidity and independence among aging adults. Given that CF is the “Sport of Fitness”, it would be of interest to determine the relationship between HGS and CF performance. The current study examined the relationship between CF performance and hand grip strength (HGS). It was hypothesized that CF performance would have a meaningful significant relationship with HGS. Fifteen (n=15) female CF participants (age 30.9±7.1 years, height 160.3±4.8 cm, body mass 64.5±9.6 kg) of varying experience levels (51.9±30.6 months) were assessed for HGS and CF performance measures. The CF performance measures were assessed via a Workout of the Day (WOD) comprised of 3 rounds of 30 seconds at each of the following stations: fan bike (FB) for maximum calories, air squats (AS) for maximum repetitions, sit-ups (SU) for maximum repetitions, and burpees (BP) for maximum repetitions. Each 30 second work interval was followed by 2 minutes and 30 seconds of rest to ensure full recovery of the phosphagen energy system. Scores were reported as the mean number of repetitions completed across the 3 attempts at each movement station. Individual movements as well as total repetitions were then compared to HGS with Pearson correlation coefficients (r). Sit-up performance demonstrated a positive moderately (r=0.44) significant relationship with mean HGS (p<0.05). Neither total WOD performance nor any other individual movement had a significant relationship with HGS (p>0.05). Within the parameters of this study, CF participants exhibited a moderate relationship between HGS and sit-up scores.

Full text

Turk J Kinesiol 2019; 5(1): 15-21
www.dergipark.gov.tr/turkjkin Original Research
The relationship between CrossFit performance and grip
strength
Emily Haynes ,
Mark DeBeliso
Southern Utah University, Department of Kinesiology and Outdoor Recreation, Cedar City, UT, USA
Abstract. There is a growing interest in maximizing
CrossFit (CF) performance as the sport becomes more
economically viable at elite levels. The ability to delineate
the physiological demands of the sport of CF allows
coaches and athletes to develop more efficacious exercise
programming in order to maximize the athlete’s potential
for success at the most elite and lucrative levels of
competition. There is also a growing interest in increasing
health and fitness in the general population as obesity and
chronic disease rates continue to rise. Hand grip strength
(HGS) is an indicator of total body strength, mortality,
morbidity and independence among aging adults. Given
that CF is the “Sport of Fitness”, it would be of interest to
determine the relationship between HGS and CF
performance. The current study examined the relationship
between CF performance and hand grip strength (HGS). It
was hypothesized that CF performance would have a
meaningful significant relationship with HGS. Fifteen
(n=15) female CF participants (age 30.9±7.1 years, height
160.3±4.8 cm, body mass 64.5±9.6 kg) of varying
experience levels (51.9±30.6 months) were assessed for
HGS and CF performance measures. The CF performance
measures were assessed via a Workout of the Day (WOD)
comprised of 3 rounds of 30 seconds at each of the
following stations: fan bike (FB) for maximum calories, air
squats (AS) for maximum repetitions, sit-ups (SU) for
maximum repetitions, and burpees (BP) for maximum
repetitions. Each 30 second work interval was followed by
2 minutes and 30 seconds of rest to ensure full recovery of
the phosphagen energy system. Scores were reported as
the mean number of repetitions completed across the 3
attempts at each movement station. Individual
movements as well as total repetitions were then
compared to HGS with Pearson correlation coefficients (r).
Sit-up performance demonstrated a positive moderately
(r=0.44) significant relationship with mean HGS (p<0.05).
Neither total WOD performance nor any other individual
movement had a significant relationship with HGS
(p>0.05). Within the parameters of this study, CF
participants exhibited a moderate relationship between
HGS and sit-up scores.
Keywords. CrossFit, dynamometer, grip strength.
Introduction
CrossFit™ (CF) was founded in 2000 by Greg
Glassman in Santa Cruz, California and its
popularity has been increasing exponentially since.
There are now over 13,000 affiliate gyms located
across 142 different countries (Beers, 2014). CF
defines itself as constantly varied functional
movements performed with high intensity over
broad time and modal domains (CrossFit Inc.,
2017a). Some practitioners use CF in order to increase
general physical preparedness and overall health
and fitness. Others practice CF as a performance
sport and attend a growing number of CF
competitions (CrossFit Inc., 2017b). As the
competition side of CF grows, more lucrative
endorsement deals and prize purses are becoming
available, continuing to spur rapid growth and
increased involvement. The male and female
Received: January 21, 2019 - Accepted: February 20, 2019 - Published: March 30, 2019
To cite this article: Haynes E, DeBeliso M. The relationship between CrossFit performance and grip strength. Turk J Kinesiol, 2019; 5(1): 15-21.
M. DeBeliso, e-mail: markdebeliso@suu.edu DOI: 10.31459/turkjkin.515874

CrossFit and grip strength 16
Turk J Kinesiol 2019; 5(1): 15-21
winners of the Reebok CrossFit Games™ each take
home $300,000 (The Reebok CrossFit Games
Competition Rulebook, 2018), and Reebok offers a
minimum of another $400,000 in endorsements
amongst Games athletes of their choosing
(Pyfferoen, 2018). Likewise, Nike and other brands
have also started to endorse CF athletes (Guelde,
2014), as such, becoming an elite CF athlete has
become a viable full time job.
Despite the burgeoning business of competitive
CF, research is still scarce regarding the
physiological demands of the sport. Crossfit aims to
improve fitness across 10 domains: cardiovascular
and respiratory endurance, stamina, strength,
flexibility, power, speed, coordination, agility,
balance, and accuracy (Glassman, 2002).
Comparisons between traditional resistance training
(RT) methods and CF were initially favorable, with
CF ranking equally or more efficacious for
developing strength and power (Barfield, Channell,
Pugh, Tuck, Pendel, 2012; Barfield & Anderson, 2014;
De Sousa et al, 2016; Fernández-Fernández et al.,
2015). However, a recent meta-analysis (Claudino et
al., 2018) determined that of the 10 fitness domains
that CF claims to address, only 5 have been
researched: cardiovascular and respiratory
endurance, stamina, strength, flexibility, and power
(Eather et al., 2016; Murawska-Cialowicz et al., 2015).
The remaining 5 domains (speed, coordination,
agility, balance, and accuracy) have yet to be
examined.
Several studies have examined body composition
(BC) changes due to CF, presumably as a measure of
health, with mixed results. Healthy but sedentary
participants showed no significant changes in BC
after 8 weeks of CF (Heinrich, 2014), but sedentary
cancer survivors showed significant decreases in fat
mass and relative body fat as well as significant
increases in lean body mass after only 5 weeks of CF
training (Heinrich, 2015). Participants who were
already physically active had significant changes in
lean body mass after 12 weeks of CF training, but
only females showed a significant decrease in body
mass index (BMI) and relative body fat (Murawska,
2014). Female teenagers also showed significant
decreases in BMI with 8 weeks of CF Teens training,
but their male counterparts did not (Eather, 2015).
Finally, a recent meta-analysis of CF literature to has
found no significant relationship between CF
training and any assessment of BC. The meta-
analysis also determined that only 6% of included CF
studies had a high level of evidence at a low risk of
bias (Claudino, 2018).
In the sport of CrossFit, it follows that
competitions are a test of the 10 CF domains
(cardiovascular and respiratory endurance, stamina,
strength, flexibility, power, speed, coordination,
agility, balance, and accuracy) (CrossFit Inc., 2017).
Researchers have determined relationships between
exogenous characteristics and performance in many
other sports, but the CF field is relatively unexplored.
Crossfit is, however, unique in that it is comprised of
several other sports - an elite CF athlete must be a
proficient weightlifter, powerlifter, and gymnast, as
well as a sprinter and an endurance athlete. Notably,
researchers have found significant relationships
between hand grip strength (HGS) and performance
amongst weightlifters, raw powerlifters, and
gymnasts. Fry et al. (2006) determined that 84% of
American junior male weightlifters could be
successfully predicted to be elite or non-elite based
on body mass index (BMI), vertical jump, relative fat,
HGS, and torso angle during an overhead squat
(2006). Schoffstall et al. (2010) found that HGS of raw
powerlifters correlated significantly with their squat
(r=0.95), bench press (r=0.98), deadlift (r=0.97), and
total (r=0.97). Powerlifters were also found to have
significantly greater HGS than gymnasts, who, in
turn, had significantly greater HGS than non-
exercisers (Ruprai et al., 2016). Regarding sport
performance, HGS has been documented to be a
covariant of lean muscle mass, sprinting and
jumping ability, and training experience (Cronin,
2017), all of which are likely related to CF
performance. As such, it would seem reasonable to

17 Haynes & DeBeliso, 2019
Turk J Kinesiol 2019; 5(1): 15-21
suspect that there is a meaningful relationship
between CF performance and HGS.
Hand grip strength may also be of particular
interest to CF practitioners with goals of basic health
and fitness, rather than performance. Though HGS
was used in only one of the existing CrossFit studies
(Meier et al., 2015), HGS is widely used as a
predictive measure of several health markers. The
Honolulu Heart Program (Rantanen et al., 1999)
began in 1965 with 6089 Japanese-American healthy
men, then aged 45 to 68 years. At the initiation of the
program maximal HGS was assessed. By the 1991-
1993 follow period, 2259 men had died. Of the
remaining survivors, 3218 men participated in the re-
assessment of HGS. Greater decrements in HGS were
associated with greater functional limitations over
the interceding 25 years. Men who tested in the
lowest third of HGS upon re-testing were at more
than 2 times the risk of self-care disability than those
in the highest third of HGS. In other words, HGS in
men aged 45 to 68 years is highly predictive of their
ability to independently care for themselves 25 years
later.
Other studies have indicated that HGS is a good
predictor of total body strength and functional
ability (DeBeliso et al., 2015a; DeBeliso et al., 2015b),
total muscle strength (Wind et al., 2010), mortality
(Granic et al., 2017), morbidity (Norman et al., 2011),
and cognition (Praetorious et al., 2016) in aging
adults. Among participants at least 85 years old, a
decline in HGS over the subsequent 10 years was
indicative of a 16% greater risk of mortality in men
and a 33% greater risk in women. Those that
improved their HGS decreased their risk of mortality
by 31% (Granic et al., 2017). In elderly pneumonia
patients admitted to a hospital, HGS was highly
predictive of death and/or readmission within 1 year
of discharge (Bohannon et al., 2004). In participants
who completed baseline testing at 80 years of age and
re-testing at 2 year intervals thereafter, decrements in
HGS occurred conjointly with decrements in
cognition. The closer to death the participants
became, the closer the association between the two
measures (Praetorious et al., 2016). Among male and
female participants over the age of 50, those with one
chronic disease had significantly lower HGS values
than those without a chronic condition, and those
suffering from multi-morbidity had significantly
lower values than those with only one disease (Yorke
et al., 2015).
As elderly populations struggle with frailty, loss
of independence, morbidity, and decreased quality
of life, the likelihood of decline in these areas is
accurately associated with diminished HGS. It
would be worthwhile to investigate which particular
exercise protocols are most efficacious in improving
HGS as a marker of overall health and fitness.
Certain programs have already demonstrated the
ability to improve HGS. A 30 day yoga camp
significantly improved HGS in both male and female
adults. Ten days of yoga was enough to significantly
improve the HGS of children, and 15 days
significantly improved HGS in patients with
rheumatoid arthritis (Dash, 2001). In college-aged
adults, right hand HGS improved significantly after
5 weeks of High Intensity Interval Training (HIIT)
with kettlebells and battle ropes. Notably, left hand
HGS showed no significant changes (Meier, 2015).
However, a study that compared light physical
exercise with a health education program for 72- to
84-year-olds found no improvement in HGS related
to either treatment (Santanasto, 2017), indicating that
perhaps a certain level of intensity or frequency of
exercise is required in order to improve HGS and,
accordingly, the associated health benefits.
Further research to determine the parameters of
exercise type, intensity, frequency, and volume
necessary to elicit measurable improvements in HGS
aging and general populations would appear
warranted. Given the growing popularity of CF, its
geographical availability, and its demonstrated high
levels of community, satisfaction, and motivation
(Claudino et al., 2018), CF has the potential to be an
excellent program choice for those seeking to
improve overall health and fitness. It would be of
interest to examine the relationship between CF and

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Turk J Kinesiol 2019; 5(1): 15-21
HGS, as an association between the two would
indicate that CF may lead to measurable
improvements in health that would support the
preservation of independence and full faculties into
senior years. As such, the purpose of the current
study is to examine the relationship between HGS
and CF performance.
Methods
Participants
A convenience sample of 15 female CrossFit athletes
over the age of 18 were recruited from CrossFit 215,
which is housed within Requisite Fitness in
Philadelphia, Pennsylvania. All participants were
healthy, non-pregnant women with 3 to 96 months of
CrossFit experience. Participants were free of any
neuromuscular, orthopedic, or neurological
conditions that might interfere with physical activity.
They were recruited via an email sent out to the
entire membership body, calling for volunteers.
Prior to any testing or assessment, permission
from the Institutional Review Board was obtained.
Each participant was provided with a written
informed consent form to read and sign before they
were included in the study. It was made abundantly
clear to all participants that participation was strictly
voluntary and could be withdrawn at any time for
any reason.
Instruments and apparatus
Hand grip strength was measured using a Camry
hydraulic hand grip dynamometer (EH101; Camry,
Guangdong Province, China) (range 0-90 kg;
accuracy 0.1 kg) (Latorre Román, 2017), loaned from
Subversus Fitness in Philadelphia, PA. Participants
took part in a specially programmed CF
Workout of the Day (WOD) using Assault AirBike
fan bikes, a Rogue AB-2 ab-mat, and bodyweight
movements.
Five separate workout stations were set up with
screens between each so that participants could not
see each other. Each station measured a minimum of
1.8 meters by 1.8 meters and consisted of one fan
bike, one ab-mat, and ample space to complete the
required bodyweight movements. Due to the
potential confusion around actual time at which to
work or rest, each station was equipped with its own
timing sheet, instructing the participant which
movement to execute at which time on the clock. The
workout was timed using a Muscle Driver USA
programmable gym timer (No Limits; MDUSA,
South Carolina, USA).
Figure 1. Assault AirBike and Rogue ab-mat for sit-ups at the Requisite Fitness in Philadelphia, Pennsylvania, US.

CrossFit and grip strength 16
Turk J Kinesiol 2019; 5(1): 15-21
Procedures
The study was administered in three (3) separate one
(1) hour increments, and participants chose which
hour to attend based on preference and availability.
There were 2 sessions on November 3 at 9 a.m. and
10 a.m., and one session on November 6 at 4:30 p.m.
It has been demonstrated that HGS does not vary
throughout the day (Patel, 2004, Young et. al, 1989).
Upon arrival, participants were individually taken to
a private room where their height, weight, dominant
hand, age, and number of months of CF experience
were recorded. Participants were measured without
shoes or excessive clothing.
The Camry dynamometer was then used to assess
HGS using the guidelines set forth by the American
Society of Hand Therapists: the shoulder was
adducted and neutrally rotated, with the elbow at 90°
flexion and a neutral forearm. Participants were
allowed to self-select wrist position to allow for
maximal gripping (Fess, 1981). The standard
instructions given were as follows: “squeeze the
gauge as hard as you possibly can while maintaining
this standard position.” Subjects completed their
trials on their dominant hand, then rested for 1
minute before repeating for a total of 3 trials. Each
HGS trail lasted 3 seconds. A running stopwatch was
visible to both the administrator and participant at
all times. Dynamometer readings were recorded by
hand and later transferred to an electronic database.
The intraclass reliability coefficient (ICC) for the
three trials of HGS scores was calculated as ICC=0.89.
Upon completion of HGS testing, all participants
were brought to the main part of the facility as a
group for a dynamic warm-up. The dynamic warm-
up consisted of two rounds of one minute on the fan
bike, ten Spiderman steps, ten scapula push-ups, and
ten air squats. In each hour increment, there were
five (5) participants. The WOD was then explained to
the group as follows:
“You will complete three (3) rounds of thirty (30)
seconds of work at each of four stations, with two and a
half (2.5) minutes of rest between each station. The four
stations will be fan bike, air squats, sit-ups, and burpees.
Complete as many repetitions at each station as you can.
The fan bike will be measured in calories. Do not concern
yourself with counting your repetitions - I will be
counting for you. I will not count out loud”.
Each movement was demonstrated for the
participants before they were given time to ask
clarifying questions. Air squat standards required
participants to break parallel at the bottom and fully
extend their hips at the top. Sit-up standards
required participants to lower their upper bodies to
the floor, touching the floor with their hands above
their heads, then sit-up to a point at which the
shoulders crossed the vertical line of the hips. Burpee
standards required participants to touch their chest
to the floor then jump and clap with arms fully
extended overhead. No standards were given
regarding the fan bike. Due to previous CF
experience, all participants were familiar with the
movements and standards.
Each participant was led to their randomly
assigned workout station. Participants were not told
their scores at any point during the workout. The
working period at each station began with the
administrator instructing “begin.” At thirty (30)
seconds in, the administrator instructed the
participant to rest. The two minute and thirty second
rest periods were included to ensure full recovery of
the ATP-CP pathway after its dominant role in the
work period (Baechle & Earle, 2008; Martinopoulou
et al., 2011). Each station completed the workout in a
staggered fashion, so that participants were working
while the others were resting at their respective
stations. This was done solely in the name of
expediency. Participants were allowed to bring
water to their station and hydrate at their discretion.
Upon completion of the WOD, participants were
informed that they had permission to use any space
or equipment in the gym in order to cool down for
the subsequent fifteen minutes. Participants were
reminded not to speak with each other or any
incoming new participants about any part of the

17 Haynes & DeBeliso, 2019
Turk J Kinesiol 2019; 5(1): 15-21
testing. All WOD data was recorded by hand and
later transferred to an electronic database.
The WOD was designed in a manner to assess
movements that did not involve the manipulation of
implements in attempt to separate CF performance
in general from barbell or gymnastics-specific
performance.
Design and analysis
The variables assessed in this study included: HGS
(kgs), fan bike (calories), air squats (repetitions), sit-
ups (repetitions), and burpees (repetitions). The
association between HGS and the four exercise
making up the WOD (fan bike, air squats, sit-ups,
and burpees) were conducted with Pearson
correlation coefficients (r). Individual HGS scores
were also compared to normative values as set forth
by Wang et al. (2018). Significance for the study was
set a priori α≤0.05. All statistical analyses were
completed in MS Excel 2013. The data analysis
spread sheet was peer reviewed for accuracy as
described by Al Tarawneh & Thorne (2017).
Results
Fifteen female participants (right-handed=14, left-
handed=1) completed the study without incident
and the demographics are presented in Table 1. The
average age, height, body mass, and CF experience
were: 30.9±7.1 years, 160.3±4.8 cm, 64.5±9.6 kg, and
51.9±30.6 months respectively. The results of the
Pearson correlation coefficients (r) suggested a
moderately significant relationship between HGS
and sit-up performance (p<0.05) (see Table 5). No
significant relationships were found between HGS
and total performance, fan bike performance, air
squat performance, or burpee performance (p>0.05).
The average fan bike performance was 9.9±2.3
calories in 30 seconds. The average air squat
performance was 27.3±3.4 repetitions. The average
sit-up performance was 16.5±2.5 repetitions. The
average burpee performance was 11.5±1.8
repetitions. Ten (10) participants scored at or above
their normative reference value for HGS, presented
in Table 4. The remaining 5 scored below.
Table 1
Participant descriptive information (Mean ± SD).
Age (years)
Height (cm)
Mass (kg)
Experience (months)
Female (n=15)
30.9±7.1
160.3±4.8
64.5±9.6
51.9±30.6
Table 2
Workout of the day (WOD) scores.
Fan Bike
Calories
Air Squats
Repetitions
Sit-ups
Repetitions
Burpees
Repetitions
Total Score
Female (n=15)
9.9±2.3
27.3±3.4
16.5±2.5
11.5±1.8
65.2±7.9
Average across three trials; Mean ± SD
Table 3
HGS trial data (kg).
Trial 1
Trial 2
Trial 3
Trials Total
Trials Mean
Female (n=15)
28.6±4.5
30.1±5.4
30.3±5.6
89.1±14.6
29.7±4.9
Average across three trials; Mean ± SD

CrossFit and grip strength 16
Turk J Kinesiol 2019; 5(1): 15-21
Table 4
Measured HGS compared to reference values and experience.
Participant
Age
Mean HGS (kg)
Normative Percentile
Range (Actual)
CF Experience
(months)
1
31
29.3
25-<50
48
2
45
31.4
50-<75
60
3
43
28.9
25-<50
72
4
32
19.0
0-<10
3
5
32
31.0
50-<75
96
6
31
32.4
50-<75
90
7
31
31.9
50-<75
96
8
25
25.9
25-<50
60
9
40
34.7
75-<90
48
10
33
20.1
0-<10
72
11
27
36.2
75-<90
36
12
25
27.7
25-<50
3
13
18
36.0
75-<90
30
14
26
32.0
50-<75
60
15
24
28.8
50-<75
5
Table 5
Summary of comparison of total performance and mean HGS.
Performance Measure
HGS
r
Significant
at P<0.05
Size
Total fan bike calories
0.43
No
Total air squats
0.15
No
Total sit-ups
0.44
Yes
Moderate
Total burpees
-0.01
No
Total all
0.34
No
Normative reference percentiles were obtained
from Table 1 (Wang et al., 2018) and are based on sex
and age. For example, Participant 1’s HGS measures
between the 25th and 50th percentile of all 30-34 year
old women in the United States. Highlighted rows
indicate HGS below the 50th percentile of normative
reference values.
Discussion
The purpose of this study was to determine if a
meaningful relationship existed between CF
performance and HGS. It was hypothesized that CF
performance would have a significant meaningful
relationship with HGS. The study results
demonstrated that sit-up performance had a
moderately significant relationship with HGS.
However, neither total performance nor the
performance scores of any other movements had a
significant relationship with HGS. The significant
correlation between HGS and sit-ups indicated that
there may be a relationship between HGS and core
strength, though further research is needed to

CrossFit and grip strength 16
Turk J Kinesiol 2019; 5(1): 15-21
determine if the correlation is movement-specific or
if it can be extrapolated more generally to abdominal
strength or endurance. Overall, the data refute the
existence of a meaningful relationship between CF
performance and HGS.
The majority of participants in the current study
(60%) demonstrated HGS above normative reference
50th percentiles (Wang et al., 2018). Two of the
participants had approximately 3 months of CF
experience. If these two participants were removed
from the data set, 77% of the CF participants in the
current study would have demonstrated HGS above
normative reference 50th percentiles (Wang et al.,
2018). Several studies have established correlations
between HGS and barbell athletes as well as
gymnastics athletes (Ruprai et al., 2016; Schoffstall et
al., 2010; Fry et al., 2006). High HGS values could be
expected from this population because of the
significant amount of time spent manipulating
barbells and other weighted implements in their
regular CF training, as well as time spent
manipulating their own bodyweight around bars
and rings.
The current study specifically chose to assess
movements that did not involve the manipulation of
objects in order to separate CF performance in
general from barbell- or gymnastics-specific
performance. Participants with higher HGS scores
could already be presumed to perform better on a
test like 30 seconds of max effort pull-ups or deadlifts
as repeated coupling with a pull-up or Olympic bar
should contribute to the development of HGS.
Bodyweight movements and the minimal amount of
hand-gripping required for the fan bike were
deliberately chosen for the current investigation to
determine if HGS meaningfully correlated with the
general physical fitness required for CF
performance. Another factor in our decision was the
varied experience level of participants - we did not
want to risk injury by asking participants to perform
30 seconds of moderate-weight deadlifts, for
example. Though this may be done in a CF class, it
would be under a coach’s direct supervision and
guidance. We were of the opinion that researchers
should not attempt to wear multiple hats at once - we
chose movements that would release us from the
need for movement correction and allow us to
simply observe the study without undue concern for
safety. A more challenging study that employed a
WOD where participants were performing more
complex exercises would certainly be feasible with
either more experienced athletes or more research
staff. Because the movements that we chose to
measure did not involve gripping objects, the
performance variables became more of a measure of
anaerobic fitness, aerobic fitness, and bodyweight
exercise proficiency.
Previous research has demonstrated that elite and
sub-elite performers can be accurately stratified
using multiple variables to include HGS and
anaerobic capacity in a variety of field sports (James
et al., 2016) and combat sports (Franchini et al., 2005;
Guidetti et al., 2002; Nikooie et al., 2017). However,
to our knowledge no direct relationship between
HGS and anaerobic fitness has yet been established.
It is therefore not surprising that no significant
relationships were determined between HGS and fan
bike, air squat, burpee, or total performance. Though
there is little research regarding HGS and aerobic
endurance, it is generally theorized that endurance
athletes would not exhibit high HGS because of that
population’s generally low body mass. Larger body
mass often correlates with higher HGS (Cronin,
2017).
HGS may be generally related to performance of
core-to-extremity movements that utilize the kinetic
chain, building momentum from the core out toward
the hand(s) (Cronin, 2017). Examples of this type of
movement include throwing an object or swinging a
bat or racket. Because momentum begins at the core
for those movements, it therefore follows that high
performance requires core strength. The significant
relationship between sit-ups and HGS may confirm
this correlation between core strength and HGS. This
theory has yet to be fully explored or developed, but

17 Haynes & DeBeliso, 2019
Turk J Kinesiol 2019; 5(1): 15-21
this study indicates that perhaps future research on
the topic is warranted.
Within the parameters of this study, HGS proved
unrelated to anaerobic fitness or non-gripping
bodyweight movements, with the exception of sit-
ups. We found it surprising that no relationships
(other than sit-ups) were found between HGS and CF
performance. Upon further consideration, it is
possible that relationships remained insignificant
due to lack of diversity in performance measures
and/or inclusion of covariates that could not be
controlled for, such as height, weight, age, and
training experience (Wang, 2018; Cronin, 2017;
Rantanen, 1999; Wadsworth, 1992). A larger, more
varied sample size might allow researchers to control
those variables. It is possible that a correlation
between HGS and performance of the CF variables
assessed in the current study might emerge if these
aforementioned variables could be controlled for.
The comparatively high HGS scores of the current
study participants were likely predictable as they are
consistent with previous research regarding
gymnasts and barbell athletes (Fry et al., 2006;
Schoffstall et al., 2010; Ruprai). This may suggest that
CF is likely a good system for improving HGS, and
therefore useful for general health and fitness. It
supports the claim by CrossFit that CF participation
benefits aging populations and helps them to stay
healthy and independent. Regarding the sport of CF,
it is difficult to compare this study with previous
studies of other sports. CF is, on the whole,
somewhat difficult to study simply because it is an
amalgamation of so many other sports and activities.
In order to determine the importance of HGS to CF
elite performance, it would be necessary to measure
HGS in a sample of CF elite-level athletes, as well as
the CF sub-elite. It is worth noting that the one
participant that could potentially be classified as an
elite-level competitor (5 Regionals appearances,
including 3 top-10 finishes) included in this study
presented HGS above her normative value, but only
in the 70th percentile of normative values and 73rd
percentile of the current study participants.
Obviously more research would be necessary to
determine if HGS is correlated with success in CF as
it is in certain other sports.
Overall, the above 50 percentile norm HGS scores
of 60% of the participants supports the theory that
occupations and hobbies involving manual
manipulation of implements correlates with higher
HGS. Further, as mentioned above, if the participants
with only 3 months of CF experience were removed
from the data set, a total of 77% of the participants
would exhibit above 50 percentile norm HGS. The
sit-up data also supports the less-developed theory
that HGS is related to core-to-extremity proficiency.
This is particularly interesting because CrossFit Inc.
claims core-to-extremity movement as a defining
characteristic of their program. It is the foundational
core-to-extremity principle upon which the use of
compound movements and the gymnastics kip is
based. The significant correlation between sit-up
performance and HGS revealed in the current study
indicates that this principle may be sound.
The most obvious limitation of the current study
is the small sample size. Due to the limited number
of participants, there was a tremendous variety of
height, weight, and experience level. Other sport-
specific studies have determined that these
characteristics are covariates of HGS (Wang, 2018;
Cronin, 2017; Rantanen, 1999; Wadsworth, 1992). If a
sample size could be obtained with more
homogenous height, weight, and experience levels,
correlations between performance and HGS might
prove meaningful and significant. Additionally, the
workout might not have been challenging enough.
Only 3 of 15 participants had less than 6 months of
CF experience. Since the majority of participants
were fairly experienced CF athletes, most were
capable of completing a similar number of
repetitions in each 30 second interval. Because the
WOD was designed to provide adequate rest, those
repetitions were also repeatable over all 3 rounds. A
more challenging workout might have provided a
greater strata of scores, which in turn might identify

CrossFit and grip strength 18
Turk J Kinesiol 2019; 5(1): 15-21
stronger correlations between total WOD
performance and HGS.
Ideally, future research would rectify these issues
in order to provide a broader understanding of the
physiological needs for success in the sport of fitness
known as CrossFit. Future research might also help
to determine which implements most improve HGS
as CF includes a multitude of implements beyond
barbells and rings to include kettlebells, dumbbells,
ropes, and odd objects. For those pursuing CF as
means for general health and fitness, a longitudinal
study in which CF practitioners could be tracked into
their senior years in order to determine their rates of
independence and mortality would be very useful.
If CF is to be used for general fitness as the hedge
against senescence that it claims to be (Glassman,
2017), then it seems likely that it must include
implement work - i.e. barbells, pull-up bars, or
gymnastics rings. Current literature does indicate
that consistently gripping and manipulating
implements likely correlates to improved HGS, and
that improved HGS correlates, whole body strength,
functional ability, longevity, independence, and
decreases in morbidity (Cronin, 2017; Rantanen et al.,
1999; DeBeliso et al., 2015a; DeBeliso et al, 2015b;
Granic et al., 2017; Norman et al., 2011). With regard
to elite CF performance, it appears that additional
HGS training may not be necessary. In order to
qualify for the CF Games, potential competitors
require a requisite amount of physical strength,
aerobic and anaerobic capacity. Further, a potential
competitor should be proficiently skilled with:
manipulating odd objects, the gymnastics rings, and
performing the Olympic lifts. As such, it would be
likely that the nature of CF training would indirectly
lead to the requisite HGS levels required to compete
at an elite CF level.
Within the parameters of this study, HGS is not
correlated with overall CF performance, though
there is a moderately significant correlation between
HGS and sit-up performance. Participants with
greater than 3 months CF experience tended to
exhibit HGS above 50th percentile normative levels,
which indicates that CF may be a useful fitness
regimen for aging populations. Future research
should pursue the identification of better
physiological predictors of CF performance.
Conflict of Interest Declaration
No funding was received for this research. The
authors have no conflict of interest related to this
research. This research has not been previously
published.
References
AlTarawneh G, Thorne S. A pilot study exploring
spreadsheet risk in scientific research. arXiv
preprint arXiv:1703.09785. arvix.org, Ithca, NY,
2017.
Baechle TR, Earle RW. Essentials of strength training and
conditioning. Champaign, IL: Human Kinetics,
2008.
Barfield JP, Anderson A. Effect of CrossFit on health-
related physical fitness: A pilot study. Journal of
Sport and Human Performance, 2014; 2(1): 23-28.
Barfield JP, Channell B, Pugh C, Tuck M, Pendel D. Format
of basic instruction program resistance training
classes: Effect on fitness change in college students.
Physical Educator, 2012; 69(4): 325-341.
Beers E. Virtuosity goes viral. The CrossFit Journal, 2014;
6: 1–10.
Bellace JV, Healy D, Besser MP, Byron T, Hohman L.
Validity of the Dexter Evaluation System's Jamar
dynamometer attachment for assessment of hand
grip strength in a normal population. Journal of
Hand Therapy: Official Journal of the American
Society of Hand Therapists, 2000; 13(1): 46-51.
Bohannon RW, Maljanian R, Ferullo J. Mortality and
readmission of the elderly one year after
hospitalization for pneumonia. Aging Clinical and
Experimental Research, 2004; 16(1): 22-25.
Brown JT, Sobrero GL, Inman C, Stone W, Zagdsuren B,
Arnett SW, Shafer MA, Lyons S, Maples JM,
Crandall J, Callahan Z. Crossfit vs. circuit-trained
individuals. Medicine Science in Sports and

19 Haynes & DeBeliso, 2019
Turk J Kinesiol 2019; 5(1): 15-21
Exercise, 2015; 47: 800.
doi:10.1249/01.mss.0000478923.27125.12
Cadenas-Sanchez C, Sanchez-Delgado G, Martinez-Tellez
B, Mora-Gonzalez J, Löf M, España-Romero V, Ruiz
JR, Ortega FB. Reliability and validity of different
models of TKK hand dynamometers. The American
Journal of Occupational Therapy: Official
Publication of the American Occupational Therapy
Association, 2016; 70(4), 7004300010.
doi:10.5014/ajot.2016.019117
Cronin J, Lawton T, Harris N, Kilding A, McMaster DT. A
brief review of handgrip strength and sport
performance. Journal of Strength and Conditioning
Research, 2017; 31(11): 3187-3217.
doi:10.1519/JSC.0000000000002149
CrossFit Inc. About the Games. Retrieved November 30,
2018, from https://games.crossfit.com/about-the-
games, 2017b.
CrossFit Inc. Level 1 Training Guide (2nd ed.). Santa Cruz,
California, 2017a.
Dash M, Telles S. Improvement in hand grip strength in
normal volunteers and rheumatoid arthritis
patients following yoga training. Indian Journal of
Physiology and Pharmacology, 2001; 45(3): 355-360.
de Sousa AFM, dos Santos G, dos Reis T, Valerino A, Del
Rosso S, Boullosa D. Differences in physical fitness
between recreational CrossFit® and resistance
trained individuals. Journal of Exercise Physiology
Online, 2016; 19(5): 112-122.
DeBeliso M, Boham M, Harris C, Carson C, Berning JM,
Sevene TG, Adams KJ. Grip and body strength
measures in the mature adult: A brief report.
International Journal of Science and Engineering
Investigations, 2015a; 4(37): 83-86.
DeBeliso M, Boham M, Harris C, Carson C, Berning JM,
Sevene TG, Adams KJ, Climstein M. Grip strength
and functional measures in the mature adult: Brief
report II. International Journal of Science and
Engineering Investigations, 2015b; 4(39): 1-4.
Dunwoody L, Tittmar HG. Grip strength and inter-trial
rest. Perceptual & Motor Skills, 1996; 83(1): 275.
Eather N, Morgan P, Lubans D. Improving health-related
fitness in adolescents: The CrossFit teens
randomized controlled trial. Journal of Sports
Sciences, 2015; 34(3): 1-15.
doi:10.1016/j.jsams.2015.12.406
Fernández-Fernández J, Sabido-Solana R, Moya D, Sarabia
JM, Moya M. Acute physiological responses during
CrossFit workouts. European Journal of Human
Movement, 2015; 35: 114-124.
Fess EE, Moran C. Clinical assessment recommendations.
Indianapolis: American Society of Hand Therapists
Monograph; 1981.
Franchini E, Takito M, Bertuzzi R. Morphological,
physiological and technical variables in high-level
college judoists. Science of Martial Arts, 2005; 1: 1-
7.
Fry AC, Ciroslan D, Fry MD, LeRoux CD, Schilling BK,
Chiu LZ. Anthropometric and performance
variables discriminating elite American junior men
weightlifters. Journal of Strength and Conditioning
Research, 2006; 20(4): 861–866.
Glassman G. Foundations. The CrossFit Journal, 2002; 1:
1–8.
Glassman G. The world's most vexing problem. Lecture
presented at CrossFit Level 1 Seminar in California,
Aromas, September 3, 2017. Retrieved April 19,
2018, from https://journal.crossfit.com/article/cfj-
greg-glassman-the-world-s-most-vexing-problem
Granic A, Davies K, Jagger C, Dodds RM, Kirkwood TL,
Sayer AA. Initial level and rate of change in grip
strength predict all-cause mortality in very old
adults. Age and Ageing, 2017; 46(6): 970-976.
doi:10.1093/ageing/afx087
Guelde L. Nike Signs Mat Fraser, Strengthens Elite Fitness
Foothold, December 5, 2014. Retrieved October 21,
2018, from
https://www.floelite.com/articles/5040021-nike-
sign-mat-fraser-strengthens-elite-fitness-foothold
Guidetti L, Musulin A, Baldari C. Physiological factors in
middleweight boxing performance. Journal of
Sports Medicine & Physical Fitness, 2002; 42(3):
309–314.
Haidar SG, Kumar D, Bassi RS, Deshmukh SC. Average
versus maximum grip strength: which is more

CrossFit and grip strength 20
Turk J Kinesiol 2019; 5(1): 15-21
consistent? Journal of Hand Surgery (Edinburgh,
Scotland), 2004; 29(1): 82-84.
Hak PT, Hodzovic E, Hickey B. The nature and prevalence
of injury during CrossFit training. Journal of
Strength and Conditioning Research, Publish
Ahead of Print, 2013.
Heinrich K, Becker C, Carlisle T, Gilmore K, Hauser J, Frye
J, Harms C. High-intensity functional training
improves functional movement and body
composition among cancer survivors: A pilot study.
European Journal of Cancer Care, 2015; 24(6): 812-
817. doi:10.1111/ecc.12338
Heinrich KM, Patel PM, O’Neal JL, Heinrich BS. High-
intensity compared to moderate-intensity training
for exercise initiation, enjoyment, adherence, and
intentions: An intervention study. BMC Public
Health, 2014; 14(1). doi:10.1186/1471-2458-14-789
James R, Thake C, Birch S. Relationships between
measures of physical fitness change when age-
dependent bias is removed in a group of young
male soccer players. Journal of Strength &
Conditioning Research, 2017; 31(8): 2100–2109.
Latorre Román PÁ, López DM, Aguayo BB, Fuentes AR,
García-Pinillos F, Redondo MM. Handgrip strength
is associated with anthropometrics variables and
sex in preschool children: A cross sectional study
providing reference values. Physical Therapy in
Sport, 2017; 26: 1-6.
Martinopoulou K, Argeitaki P, Paradisis G, Katsikas C,
Smirniotou A. The effects of resisted training using
parachute on sprint performance. Biology of
Exercise, 2011; 7(1): 7-23.
Mckenzie MJ. Crossfit improves measures of muscular
strength and power in active young females.
Medicine & Science in Sports & Exercise, 2015; 47:
797. doi:10.1249/01.mss.0000466164.99273.92
Meier J, Quednow J, Sedlak T. The effects of high intensity
interval-based kettlebells and battle rope training
on grip strength and body composition in college-
aged adults. International Journal of Exercise
Science, 2015; 8(2): 124-133.
Murawska-Cialowicz E, Wojna J, Zuwala-Jagiello J.
Crossfit training changes brain-derived
neurotrophic factor and irisin levels at rest, after
wingate and progressive tests, and improves
aerobic capacity and body composition of young
physically active men and women. Journal of
Physiology and Pharmacology, 2015; 66(6): 811–821.
Nikooie R, Cheraghi M, Mohamadipour F. Physiological
determinants of wrestling success in elite Iranian
senior and junior Greco-Roman wrestlers. Journal
of Sports Medicine and Physical Fitness, 2017; 57:
219–226.
Norman K, Stobäus N, Gonzalez MC, Schulzke J, Pirlich
M. Hand grip strength: outcome predictor and
marker of nutritional status. Clinical Nutrition
(Edinburgh, Scotland), 2011; 30(2): 135-142.
doi:10.1016/j.clnu.2010.09.010
Peolsson A, Hedlund R, Oberg B. Intra- and inter-tester
reliability and reference values for hand strength.
Journal of Rehabilitation Medicine, 2001; 33(1): 36-
41.
Praetorius Björk M, Johansson B, Hassing LB. I forgot
when I lost my grip—strong associations between
cognition and grip strength in level of performance
and change across time in relation to impending
death. Neurobiology of Aging, 2016; 38: 68-72.
doi:10.1016/j.neurobiolaging.2015.11.010
Pyfferoen B. 10 Things you didn’t know about the
CrossFit-Reebok partnership. June 20, 2018.
Retrieved October 21, 2018, from
http://thebarbellspin.com/functional-fitness/10-
things-you-didnt-know-about-the-crossfit-reebok-
partnership/
Rantanen T, Guralnik JM, Foley D, Masaki K, Leveille S,
Curb JD, White L. Midlife hand grip strength as a
predictor of old age disability. Journal of the
American Medical Association, 1999; 281(6): 558-
560.
Ruprai R, Tajpuriya S, Mishra N. Handgrip strength as
determinant of upper body strength/physical
fitness: A comparative study among individuals
performing gymnastics (ring athletes) and
gymnasium (powerlifters). International Journal of
Medical Science and Public Health, 2016; 5(6): 1167.
doi:10.5455/ijmsph.2016.09102015176
Santanasto AJ, Glynn NW, Lovato LC, Blair SN, Fielding
RA, Gill TM, Guralnik JM, Hsu FC, King AC,

21 Haynes & DeBeliso, 2019
Turk J Kinesiol 2019; 5(1): 15-21
Strotmeyer ES, Manini TM, Marsh AP, McDermott
MM, Goodpaster BH, Pahor M, Newman AB. Effect
of physical activity versus health education on
physical function, grip strength and mobility.
Journal of the American Geriatrics Society, 2017;
65(7): 1427-1433. doi:10.1111/jgs.14804
Schoffstall J, Morrison SD, Kozlik B, Boswell B. Grip
strength and powerlifting performance. In:
Southeastern Chapter of the American College of
Sports Medicine Regional Conference, February
2010. Abstract retrieved from:
https://www.researchgate.net/publication/2804088
78_Grip_Strength_and_Powerlifting_Performance
Serafini P, Hoffstetter W, Mimms H, Smith M,
Kliszczewicz B, Feito Y. Body composition and
strength changes following 16-weeks of high-
intensity functional training. Medicine & Science in
Sports & Exercise, 2016; 48: 1001.
doi:10.1249/01.mss.0000488009.97613.c7
Smith MM, Sommer AJ, Starkoff BE, Devor ST. Crossfit-
based high-intensity power training improves
maximal aerobic fitness and body composition.
Journal of Strength And Conditioning Research,
2016; 27(11): 3159-3172.
doi:10.1519/JSC.0b013e318289e59f
The Reebok CrossFit Games Competition Rulebook, no. 7,
CrossFit, Inc., Santa Cruz, CA, USA, Jan 8 2018, p.
24. Accessed on: October 21, 2018 [Online].
Available: https://games.crossfit.com/rules/open
Timmons JF, Minnock D, Hone M, Cogan KE, Murphy JC,
Egan B. Comparison of time‐matched aerobic,
resistance, or concurrent exercise training in older
adults. Scandinavian Journal of Medicine & Science
in Sports, 2018; 28(11): 2272–2283.
Trossman P, Li P. The effect of the duration of inter-trial
rest periods on isometric grip strength performance
in young adults. Occupational Therapy Journal of
Research, 1989; 9(6): 362-378.
Wadsworth C, Nielsen DH, Corcoran DS, Phillips CE,
Sannes TL. Interrater reliability of hand-held
dynamometry: effects of rater gender, body weight,
and grip strength. The Journal of Orthopaedic and
Sports Physical Therapy, 1992; 16(2): 74-81.
Wang YC, Sindhu B, Kapellusch J, Bohannon RW,
Xiaoyan L. Hand-grip strength: Normative
reference values and equations for individuals 18 to
85 years of age residing in the United States. Journal
of Orthopaedic & Sports Physical Therapy, 2018;
48(9): 685–693.
Weisenthal BM, Beck CA, Maloney MD, DeHaven KE,
Giordano BD. Injury rate and patterns among
CrossFit athletes. Orthopaedic Journal of Sports
Medicine, 2014; 2(4): 2325967114531177.
doi:10.1177/2325967114531177
Wind AE, Takken T, Helders PM, Engelbert RH. Is grip
strength a predictor for total muscle strength in
healthy children, adolescents, and young adults?
European Journal of Pediatrics, 2010; 169(3): 281-
287. doi:10.1007/s00431-009-1010-4
Yorke AM, Curtis AB, Shoemaker M, Vangsnes E. Grip
strength values stratified by age, gender, and
chronic disease status in adults aged 50 years and
older. Journal of Geriatric Physical Therapy, 2015;
38(3): 115-121.
Young VL, Pin P, Kraemer BA, Gould RB, Nemergut L,
Pellowski M. Fluctuation in grip and pinch strength
among normal subjects. The Journal of Hand
Surgery, 1986; 14(1): 125-129.
Zagdsuren B, Evans GS, Inman C, Stone W, Arnett S,
Schafer M, Lyons S, Maples JM, Crandall J, Callahan
Z. Crossfit vs. circuit-training. Medicine & Science
in Sports & Exercise, 2015; 47: 801.
doi:10.1249/01.mss.0000478926.16823.b9