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38World Medical & Health Games& INTERNATIONAL SPORT MEDECINE SYMPOSIUM

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Examination of related some morphometric parameters of forearm and hand with hand-

grip strength

Serpil Çilingiroğlu Anlı1, Rahmi Ertan Anlı2

1Kırıkkale University School of Medicine, Department of Anatomy, Kırıkkale, TURKEY 2Ankara University Faculty of Sport Sciences, Ankara, TURKEY

INTRODUCTION•  Handgrip strength may be an indicator of

muscular strength of an individual (1,2). Because

of its close association with the neural and

musculoskeletal systems, grip strength is

routinely utilized in wide range of clinical settings

including evaluation of individuals with

pathologies affecting the upper limb function (3).

INTRODUCTION

•  Grip strength refers to the ability of the fingers and

hand to generate muscle power and force. In

athletes, grip strength is an important component of

participating in many sports, including rock

climbing, judo, weight lifting, baseball, martial arts,

racquets sports etc. (4).

INTRODUCTION

•  If the forearm muscles have been overused, the

resulting decrease in grip strength or fatigue of

the forearm muscles may result in the muscles

not being able to maintain force output. This

would result in decreasing the overall

effectiveness of an athlete’s sports ability (5).

INTRODUCTION

•  Kickboxing and Muay Thai are two very popular

striking combat sports that have similar

characteristics as the operating principles, as

punching and kicking techniques are used[6,7].

PURPOSE•  Specific anthropometric characteristics play an important

role for the perfect performance of the players in sportive

activites.

•  Especially, hand is a very complex structure capable of

motor function and handgrip strength is also very

important for the maximal performance for the players.

•  The purpose of this study was performed to evaluate

forearm and hand anthropometric characteristics and

handgrip strength in kickbox athletes.

METHOD

The present study were based on 60

healthy male licensed kickboks atlethes,

between the age of 17 to 25, attached to

Turkish Kickboxing Federation.

METHOD

Anthropometric characteristics were

measured on each subject following

standard techniques.*

*Lohmann TG, Roche AF, Martorell R. Anthropometric Standardization Reference Manual. Champaign, IL: Human Kinetics Books.1988

METHOD

A digital caliper (Asimeto, Resolution:

0.0005 inch/0.01mm) and a medical tape

measure was used for morphometric

measurement of some morphometric

parameters of upper extremity.

METHOD

A digital hand dynamometer (Takei) was

used for hand-grip strength measurement.

Athletes were tested for grip strength,

which is an indication of upper extremity

strength.

METHOD •  The hand dynamometer was set according

to the athlete hand measurement. •  The athletes held the dynamometer on the

side of their bodies, without bending their elbows and making an angle of 10-15 degrees from their shoulders.

•  It was demanded from the athletes to tighten the dynamometer by applying as much force as possible.

Figure 1: The hand dynamometer

METHOD

•  After 2 attempts with both hands, the best

performance was determined in kilograms.

•  The best performance to evaluate was

taken.

METHOD These obtained data were analyzed by

response surface methodology (RSM). (It was performed using Stat-Ease Design Expert 7.0.0 software

Stat-Ease Inc., Minneapolis, USA).

METHOD

Response Surface Methodology (RSM)

was used to determine the optimal

conditions for the upper extremity

morphology and handgrip strength in the

present study.

METHOD•  Response surface methodology (RSM) is a

collection of mathematical and statistical techniques for empirical model building.

•  By careful design of experiments, the objective is to optimize a response (output variable) which is influenced by several independent variables (input variables).

METHOD

An experiment is a series of tests, called

runs, in which changes are made in the

input variables in order to identify the

reasons for changes in the output

response.

METHOD

Re la t i ve mode l equa t ions were

established with independent variables of

morphometric parameters,

Right wrist circumference (RWC), Right hand lenght (RHL), Right hand width (RHW), Right forearm lenght (RFL),

METHOD

Left wrist circumference (LWC), Left hand lenght (LHL), Left hand width (LHW), Left forearm lenght (LFL),

METHOD

Other upper extremity morphometric parameters:

Shoulder width (SW), Right arm lenght (RAL), Left arm lenght (LAL) Right arm lenght (elbow flexion-900)(RALEF).

METHOD

The model equation was found by establishing the relationship matrix with age, height, weight and body fat ratio independent variables and the right handgrip strength dependent variable. The dependent variable was revealed by 54.40% by independent variables (R2 = 0.5440).

1-Right handgrip strength & Age, height, weight and body fat ratio

RESULTS

Right handgrip strength & Age, height, weight and body fat ratio

•  Results of ANOVA showed that the model was significant with low P-value of 0.0003 for right handgrip strength.

•  Age, height, weight and body fat ratio parameters was found insignificant for right handgrip strength.

•  The model was demonstrated as significant (p<0.05).

The model equation was found by establishing the relationship matrix with age, height, weight and body fat ratio independent variables and the left handgrip strength dependent variable. The dependent variable was revealed by 55,62% by independent variables (R2= 0,5562).

2-Left handgrip strength & Age, height, weight and body fat ratio

•  Results of ANOVA showed that the model was significant with low P-value of 0.0002 for right handgrip strength.

•  Age, height, weight and body fat ratio parameters was found insignificant for left handgrip strength.

Left handgrip strength & Age, height, weight and body fat ratio

The model equation was found by establishing the relationship matrix with RWC, RHL, RHW and RFL independent variables and the right handgrip strength dependent variable. The dependent variable was revealed by 57,60% by independent variables (R2= 0,5760).

3-Right handgrip strength & RWC, RHL, RHW and RFL

Right handgrip strength & RWC, RHL, RHW and RFL

•  Results of ANOVA showed that the model was highly significant with low P-value of 0.0001 for right handgrip strength.

•  The model was found significant. For the left handgrip strength; LWC parameter was shown significant, but LHL, LHW and LFL parameters was found insignificant.

The model equation was found by establishing the relationship matrix with RAL, RFL and SW independent variables and the right handgrip strength dependent variable. The dependent variable was revealed by 53,48% by independent variables (R2= 0,5348).

4-Right handgrip strength & RAL, RFL and SW

Right handgrip strength & RAL, RFL and SW •  Results of ANOVA showed that the model was

highly significant with low P-value of 0.0245 for right handgrip strength.

•  The model was found significant. RAL, SW and the dual interaction of RAL-RFL was determined as significant model parameter. While RFL parameter is not significant for the right handgrip strength.

Optimum point: RAL: 35.60, RFL: 28.40, SW: 46.60, Right Handgrip Strength: 45.3008

The model equation was found by establishing the relationship matrix with RAL, RAL-EF and SW independent variables and the right handgrip strength dependent variable. The dependent variable was revealed by 53,69% by independent variables (R2= 0,5369).

5-Right handgrip strength & RAL, RALEF and SW

•  Results of ANOVA showed that the model was highly significant with P-value of 0.0238 for right handgrip strength.

•  The model was found significant. The dual interaction

of RAL-SW and RALEF-SW was determined as significant model parameter.

Right handgrip strength & RAL, RALEF and SW

Optimum point: RAL: 35.00, RALEF: 33.80,

The model equation was found by establishing the relationship matrix with LWC, LHL, LHW and LFL independent variables and the left handgrip strength dependent variable. The dependent variable was revealed by 51,04% by independent variables (R2= 0,5104).

6-Left handgrip strength & LWC, LHL, LHW and LFL

Left handgrip strength & LWC, LHL, LHW and LFL

•  Results of ANOVA showed that the model was significant with low P-value of 0.0019 for left handgrip strength.

•  The model was found significant. For the left

handgrip strength; LWC parameter was shown significant, but LHL, LHW and LFL parameters was found insignificant.

The model equation was found by establishing the relationship matrix with LAL, LALEF, LFL and SW independent variables and the left handgrip strength dependent variable. The dependent variable was revealed by 51,14% by independent variables (R2= 0,5414).

7-Left handgrip strength & LAL, LALEF, LFL and SW

Left handgrip strength & LAL, LALEF, LFL and SW

•  Results of ANOVA showed that the model was significant with P-value of 0.0091 for left handgrip strength.

•  The model was found significant. For the left handgrip strength; The intrinsic interaction of LFL parameter was shown significant.

The model equation was found by establishing the relationship matrix with LAL, LFL and SW independent variables and the left handgrip strength dependent variable. The dependent variable was revealed by 51,11% by independent variables (R2= 0,5111).

8-Left handgrip strength & LAL, LFL and SW

Left handgrip strength & LAL, LALEF, LFL and SW

•  Results of ANOVA showed that the model was significant with P-value of 0.0426 for left handgrip strength.

•  The model was found significant and SW parameters

was found significant.

SUMMARY Hand-grip strength selected as dependent variable

•  RFL, p-value:0.0051 •  LWC, p-value:0.0230 •  SW, p-value:0.0362 •  RAL-RFL, p-value:0.0129 •  LFL, p-value:0.0159

was determined as the significant model parameter. Moreover, the dual interaction of RALEF-SW was

determinedas significant model parameter (p-value:0.0478).

CONCLUSION

Consequently, the different anthropometric

variables of forearm and hand are

posit ively correlated with handgrip

strength.

REFERENCES•  (1)LingCH,TaekemaD,deCraenAJ,GusseklooJ,WestendorpRG,Maier

AB. Handgrip strength and mortality in the oldest old populaDon: theLeiden85-plusstudy.CMAJ.2010;182(5):429–435.

•  (2) Foo LH, ZhangQ, ZhuK,MaG,GreenfieldH, FraserDR. Influenceofbody composiDon, muscle strength, diet and physical acDvity on totalbody and forearm bone mass in Chinese adolescent girls. Br J Nutr.2007;98(6):1281–1287.

•  (3) Abaraogu, UO, Ezema,CI , Ofodile, UN Igwe , SE. AssociaDon of gripstrength with anthropometric measures: Height, forearm diameter, andmiddlefinger length inyoungadults.PolishAnal.OfMedicine.ArDcle inPress.2017;hep//dx.doi.org/10.1006/pomed2016.11.008.

•  (4) Mathiowetz, V., Kashman, N., Volland, G., Weber, K., Dowe, M., &Rogers, S. (1985). Grip and pinch strength: normaDve data for adults.ArchivesofPhysicalMedicineandRehabilitaDon,66,69e74

REFERENCES

•  (5)Chang,H-Y,Kun-Yu,K-Y,Lin,J-J,Lin,J-F,Wang,C-H. Immediateeffectofforearm Kinesio taping on maximal grip strength and force sense inhealthycollegiateathletes.PhysicalTherapyinSport11(2010)122e127.

•  (6) Silva JJR, Del Vecchio FB, Picanc¸o LM, TakitoMY, FranchiniE. Time-moDon analysis in Muay Thai and kickboxing amateurmatches. J HumSportExerc2011;6(3):490-496.

•  [7]SlimaniM,ChaabeneH,MiarkaB,ChamariK.TheacDvityprofileofelitelow-kick kickboxing compeDDon. Int J SportsPhysiol Perform 2016 [inpress].

HAND IN HAND TO KEEP THE BLUE ALIVE…

THANKS J

& INTERNATIONAL SPORT MEDECINE SYMPOSIUM · • Grip strength refers to the ability of the fingers...

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