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Abstract

BACKGROUND:

Although it is known that isokinetic knee extensor strength and balance ability are important, valid and reliable parameters, they have not been used hitherto to predict the performance of junior weightlifters.

OBJECTIVE:

To investigate the relationship among body composition, isokinetic knee extensor strength, balance, and weightlifting performance and to determine whether these factors predict competition performance in junior men weightlifters.

METHODS:

Fifty-one male junior weightlifters (age: 15.9 $\pm$ 1.2 years, height: 161.9 $\pm$ 7.7 cm, body mass: 62.7 $\pm$ 11.3 kg) participated in this study. Participants performed isokinetic knee extensor strength tests in concentric mode (at 60 and 180 ${}^{\circ}$ /s) and balance tests (static and dynamic). Competition performance was calculated according to the Sinclair equation, which was used as the dependent variable in the statistical analysis. The extent to which the independent variables predicted competition performance was determined by bivariate correlations and multiple linear regression analysis.

RESULTS:

Significant correlations were found between the Sinclair score and the independent variables ( $r=$ 0.496–0.804, $p<$ 0.05). Three models were fitted by hierarchical linear regression analysis. Body fat percentage was determined as a control variable in step one, isokinetic knee extensor strength at 180 ${}^{\circ}$ /s was included in step two, and static balance was included in step three, with all three contributing to the models significantly ( $p=$ 0.0001, $p=$ 0.0001, and $p=$ 0.003, respectively). The variance of competition performance was explained by approximately 65% in step one, approximately 78% in step two, and approximately 82% in step three.

CONCLUSIONS:

The results of this study suggest that isokinetic knee extensor strength, static balance, and body fat percentage are effective for predicting competition performance in junior weightlifters.

Keywords

Olympic weightlifting knee extensor Sinclair snatch clean and jerk

1. Introduction

Olympic weightlifting (OW) is a sport that requires both dynamic strength and power to perform multi-joint whole body movements [1, 12, 13]. Therefore, OW requires a unique physiological profile consisting of a combination of muscle power and strength, flexibility, balance, kinesthetic awareness, and lifting technique [7, 14]. During the weightlifting techniques of “snatch” and “clean and jerk,” athletes must generate extremely high peak forces and contractile impulses to lift the largest weight [12]. When applying these techniques, athletes first perform a quick transition from full extension position to squat position to go underneath the barbell and then move back from squat position to full extension with the barbell, exhibiting slower and more balanced movement [5]. It has been demonstrated that the lower body’s contribution to power development in weightlifters is very important [1]. In addition, OW performance has been shown to be correlated with several biomechanical patterns in the pull phases of snatch and clean and jerk techniques. Greater involvement of the knee extensor muscles during the second pull is related to greater lift mass. Although with a small knee extensor moment during the first pull for heavy loads more extension moments during the second pull and the initial knee flexion-extension moments of the second pull are highly correlated with weightlifting performance. These results highlight the importance of the rapid employment of the knee extensor muscles during the second pull in relation to performance [2].

Strength and power discriminate the best weightlifters from the others and are a combination of morphological and neural factors that include muscle cross-sectional area and architecture, musculotendinous stiffness, motor unit recruitment, motor unit synchronization, and neuromuscular inhibition [15]. Balance is generally defined as the ability to maintain the body’s center of gravity within its base of support and is a complementary component that helps strength reflect success in weightlifters [16, 17, 18]. The central nervous system maintains balance mechanisms while performing physical movements using data coming from vestibular, somatosensory, and visual systems [18, 19]. During OW techniques, after the first pull is completed and the carrying of the load by the body is started it is necessary to stabilize the bar and maintain this stabilization for a certain period of time in different directions: the forward-backward direction in both techniques, and the right-left direction, especially in the snatch technique [3, 4, 5, 6]. Hence, maximum force development and maximum stability are required when lifting a barbell with heavy plate.

Functional tests that require strength, power, and postural stability are preferred when evaluating the effectiveness of training, monitoring performance development, or identifying weightlifters’ profiles [14, 20]. It has been reported that knee extensor muscles provide a major driving force that is transferred through the kinetic chain during dynamic movements [21]. Isokinetic dynamometry can evaluate both the function and the strength of the joint at different angular velocities [22], however, previous studies have mostly focused on the variables based on anthropometric measurements, somatotype, and body composition when predicting the performance of weightlifters. To date, there have been limited findings regarding the relationship between weightlifting performance and isokinetic knee extension tests. In addition, although there is a widespread belief that balance ability is required in addition to physical and somatotype properties, speed, and power characteristics to be successful in weightlifting [17, 20, 23, 24, 25] we could not trace research relating to prediction of weightlifting performance via balance ability. Previous studies have emphasized that the body fat percentage (BF%) is one of the main variables that determines performance in weightlifters [7, 8, 9]. Since weightlifting is grouped according to body weight, it is inevitable that having a low BF% and a high muscle mass will be a great advantage. Therefore, when the factors such as technique, strategy, flexibility, and balance are kept constant, it is a basic assumption that athletes who have the same weight, but more muscle mass will produce higher strength than others. For this reason, this study aimed to investigate the relationship between isokinetic strength, balance, body fat percentage, and weightlifting performance and to determine whether these factors can predict competition performance in junior weightlifters. We hypothesized that isokinetic knee extensor strength and balance in addition to body composition would be good predictors for weightlifting performance.

2. Methods

2.1 Participants

Fifty-one male junior weightlifters (age: 15.9 $\pm$ 1.2 years, height: 161.9 $\pm$ 7.7 cm, body mass: 62.7 $\pm$ 11.3 kg) who competed at the National Weightlifting Championships participated in this study. The inclusion criteria were as follows: must be at least 15 years of age; must have at least two years of training experience with a coach registered with the National Federation; and must have no current injury or disease. The exclusion criteria were as follows: a current orthopedic problem, pain in the hamstring or quadriceps, missing a testing session during the data collection period, and using an ergogenic aid that would affect the isokinetic test [10]. All participants and their families were informed about any possible risks and provided written informed consent. The research protocol was approved by our central university ethics committee.

2.2 Procedures

All data were collected from two different weightlifting clubs during the pre-National Championship camp. Weightlifting performance was based on the National Weightlifting Championships conducted two weeks after the measurements. During the data collection process, isokinetic knee extension strength tests, static and dynamic balance tests were applied in random order in two sessions at 48-hour intervals, after a familiarization session. The same investigator performed all tests to avoid test-retest errors. The athletes were asked to maintain their normal daily meal routines, not to use any stimulant or supplement, and not to perform any exhaustive activities during the test period. The participants were verbally encouraged to maximize their performance during the tests.

2.3 Olympic weightlifting performance

OW performance was calculated using the Sinclair equation according to the total weight lifted (“snatch” and “clean and jerk”) in the National Championships conducted two week after the measurements. The Sinclair equation, which is presented by the International Weightlifting Federation, is a polynomial equation that allows the comparison of a weightlifter’s competition performance to that of other athletes in different weight categories. This equation is based on current Olympic records and is updated every four years (www.iwf.net). For the current Olympic cycle, the Sinclair formula for men is as follows:

$\textit{Sinclair total}=\textit{Unadjusted total}\cdot 10^{\textit{AX2}}$ , where $X=\log_{10}$ (BM $\cdot$ 175.508 ${}^{1}$ ) and $A=$ 0.751945030.

2.4 Body Composition

Skinfold thickness measurements were performed using a skinfold caliper device (Holtain Ltd., Crymych, UK). The generalized skinfold equation of Jackson and Pollock (measuring seven body regions) was used to calculate body density (g-mhO) [26] and relative fat levels were determined using the Siri equation [27].

2.5 Anthropometric measures

The height of the participants was measured with a portable stadiometer according to standard procedures (Holtain Ltd., Pembrokeshire, UK). Body weight was measured using a Tanita weighing scale (BC-310; Tanita Corp., Tokyo, Japan).

2.6 Isokinetic strength test

The isokinetic knee extensor strength test comprised of concentric phases at of 60 ${}^{\circ}$ /s with five repetitions, then 180 ${}^{\circ}$ /s with 15 repetitions using a Cybex HUMAC Norm (CSMi, Stoughton, MA, USA). Before starting the tests, the descriptive information regarding the participants (name, age, sex, body weight, height, and dominant leg) was recorded in the software program. Before the tests, the isokinetic dynamometer was calibrated in accordance with the manufacturer’s guidelines. The participants completed a standardized five-minute warm-up on a cycle ergometer at 60–70 W.

The tests were started after the seat, dynamometer, stabilization, isolation, gravity correction, and range of motion were adjusted according to the angular velocity and following the manufacturer’s instructions. Participants were secured in a seated position with approximately 90 ${}^{\circ}$ of hip flexion. The knee joint rotation axis coincided with the rotation axis of the dynamometer. An angular range of motion from 90 ${}^{\circ}$ to 0 ${}^{\circ}$ was used. During the testing, the participants were fixed to the chair in optimum position, with stabilization straps at the trunk, hips, and thigh while holding their arms across their chest. For each angular velocity and contraction type, participants performed three maximal contractions through their full range of movement to adapt them to the device before the test. The absolute peak moment and relative (BM.kg ${}^{-1}$ ) peak moment specific to both angular velocities were determined for the dominant leg. In the isokinetic tests, two trials were performed in concentric mode, and the highest value was accepted as valid. ICC (95% CI) values were calculated as follows: for 60 ${}^{\circ}$ /s, 0.94 (0.91–0.96); for 180 ${}^{\circ}$ /s, 0.93 (0.91–0.95). During the test, there was a three-minute rest interval between trials and a five-minute rest interval between the two angular velocities.

Table 1
Descriptive and performance characteristics of participants ( $N=$ 51)

Descriptive characteristics		Weightlifting performance
Age (years)	15.9 $\pm$ 1.2		Absolute	Relative (BM.kg ${}^{-1}$ )
Height (cm)	161.9 $\pm$ 7.7	Clean & Jerk (kg)	105.69 $\pm$ 28.74	1.68 $\pm$ 0.30
Body mass (kg)	62.7 $\pm$ 11.3	Snatch (kg)	88.17 $\pm$ 25.24	1.40 $\pm$ 0.28
Body fat (%)	16.1 $\pm$ 5.7	Total (kg)	195.79 $\pm$ 60.20	3.12 $\pm$ 0.72
Competition performance		Isokinetic knee extensor strength
Sinclair	268.26 $\pm$ 63.57		Absolute	Relative (BM.kg ${}^{-1}$ )
		E-60 (Nm)	169.33 $\pm$ 50.57	2.67 $\pm$ 0.55
Balance		E-180 (Nm)	138.45 $\pm$ 54.31	2.19 $\pm$ 0.51
Static balance	6.1 $\pm$ 2.6
Dynamic balance	20.1 $\pm$ 8.1

E-60 $=$ Isokinetic knee extensor strength at 60 ${}^{{\circ}}$ /s, E-180 $=$ Isokinetic knee extensor strength at 180 ${}^{{\circ}}$ /s.

2.7 Static and dynamic balance test

Static and dynamic balance measurements were made using an balance system measuring device (CSMI-TecnoBody PK-252, Dalmine, Italy) with a 20-Hz sampling rate and sensitivity of 0.1 ${}^{\circ}$ . Both tests were conducted on the fixed platform in a bipedal stance with eyes open. Participants placed their bare feet on the balance platform shoulder-width apart and equidistant from the origin point with reference to the lines on the x- and y-axis. To measure static balance scores, the participants were asked to keep their position for 30 seconds during the test and were allowed to observe their status information on a screen. The participants looked at a fixed spot in front of them and after reaching balance, the test was initiated manually and automatically terminated by the computer. The static balance test score was calculated by summing the units of the medial-lateral and backward-forward deviations from the center point.

To measure dynamic balance, the pressure level was set to a difficulty level of five (out of 50). The test was completed by rotating the platform clockwise five times during 60 seconds to track the circular trajectory on the screen. The average track error values were calculated as the percentage of the deviation from the center point and were used as a dynamic balance score. Therefore, higher values indicated poor balance and lower values indicated good balance in both tests [28, 29]. The descriptive data of the participants were entered before each test and the device was calibrated. Both the dynamic and static balance tests were repeated twice and the better test score was used in the analysis. ICC (95% CI) values were calculated as follows: for static balance, 0.93 (0.89–0.97); for dynamic balance, 0.91 (0.88–0.94).

2.8 Statistical analyses

The normality of the data was confirmed using the Shapiro-Wilk test. Simple Pearson correlations were used to determine the relationship among competition performance, body composition, and performance test results. The main analysis involved a three-step multiple hierarchical regression with competition performance as the dependent variable. BF% was entered as a control variable in step one, isokinetic knee extension strength variables were entered in step two, and static and dynamic balance values were entered in step three. Statistical analyses were performed using Statistica version 12.0 (Statsoft Inc, Tulsa, OK, USA), and a $p$ value $<$ 0.05 was accepted as significant.

3. Results

All the correlations between the Sinclair score (dependent variable) and the independent variables were significant ( $r=$ 0.496–0.804, $p<$ 0.05; see Table 2). The results of the multiple hierarchical linear regression indicated the best predictors of competition performance (Table 3). According to the regression analysis, the most optimal three models were fitted which includes the performance predictors. BF% was included as a control variable and contributed significantly to the step one model. E-180 was included in step two and SB was included in step three and both contributed to the models significantly ( $p=$ 0.0001 and $p=$ 0.003, respectively). The variance of competition performance was explained by approximately 65% in step one, approximately 78% in step two, and approximately 82% in step three.

Table 2
Pearson moment correlation coefficients between different variables ( $N=$ 51)

	Sinclair	BF%	E-60	E-180	SB	DB
Sinclair	–	$-$ 0.804 ${}^{*}$	0.667 ${}^{*}$	0.759 ${}^{*}$	$-$ 0.656 ${}^{*}$	$-$ 0.496 ${}^{*}$
BF%	$-$ 0.804 ${}^{*}$	–	$-$ 0.706 ${}^{*}$	$-$ 0.717 ${}^{*}$	0.478 ${}^{*}$	0.381 ${}^{*}$
E-60	0.667 ${}^{*}$	$-$ 0.706 ${}^{*}$	–	0.924 ${}^{*}$	$-$ 0.496 ${}^{*}$	$-$ 0.223
E-180	0.759 ${}^{*}$	$-$ 0.717 ${}^{*}$	0.924 ${}^{*}$	–	$-$ 0.501 ${}^{*}$	$-$ 0.320 ${}^{*}$
SB	$-$ 0.656 ${}^{*}$	0.478 ${}^{*}$	$-$ 0.496 ${}^{*}$	$-$ 0.501 ${}^{*}$	–	0.532 ${}^{*}$
DB	$-$ 0.496 ${}^{*}$	0.381 ${}^{*}$	$-$ 0.223	$-$ 0.320 ${}^{*}$	0.532 ${}^{*}$	–

${}^{*}p<$ 0.05, BF% $=$ Body fat, E-60 $=$ Isokinetic knee extensor strength at 60 ${}^{{\circ}}$ /s, E-180 $=$ Isokinetic knee extensor strength at 180 ${}^{{\circ}}$ /s, SB $=$ Static balance, DB $=$ Dynamic balance.

Table 3

The estimation model of the competition performance (Sinclair) on the basis of the tests and body composition ( $N=$ 51)

Model	B	Std. Error	Beta	CR	R	R ${}^{2}$	F Change	Sig. F Change
Step one
BF%	$-$ 8.92	0.94	$-$ 0.80	100%	0.804	0.65	89.64	0.0001
(Constant)	411.96	16.09
Step two
BF%	$-$ 6.10	0.92	$-$ 0.550	60%	0.883	0.78	29.04	0.0001
E-180	0.624	0.116	0.445	40%
(Constant)	280.14	27.62
Step three
BF%	$-$ 5.40	0.87	0.487	56%	0.904	0.82	9.80	0.003
E-180	0.50	0.11	0.357	29%
SB	$-$ 5.80	1.85	$-$ 0.237	15%
(Constant)	321.58	28.64

BF $=$ Body fat, E-180 $=$ Isokinetic knee extensor strength, SB $=$ Static balance, CR $=$ Contribution rate.

4. Discussion

In the present study, the relationship among body composition, isokinetic knee strength, and static and dynamic balance and competition performance (Sinclair score) was investigated in junior men weightlifters. The Sinclair score, which eliminates the effect of body weight category, was the preferred indicator of competition performance and was used as a dependent variable in the analysis. The main finding of the present study indicated that BF% significantly explained competition performance (Sinclair score) in junior weightlifters. Weightlifting is categorized according to body weight; therefore, it is clear that having a low BF% and a high muscle mass will be of great advantage. It is a basic assumption that athletes who compete at the same weight category and have more muscle mass will produce higher strength than others, when the effect of factors such as technique, strategy, flexibility, and balance are controlled [1, 6, 15]. Therefore, BF% was used as a control variable in this study. Garcia-Pallares et al. [30] indicated that elite Olympic weightlifters had lower BF% than amateurs and Ebada [31] found a significant correlation between body mass index (BMI) and weightlifting performance. Similarly, Siahkouhian and Hedayatneja [9] found that both the “snatch” and the “clean and jerk” techniques were significantly correlated with BMI, shoulder and chest circumference, waist-to-hip ratio, and BF% in weightlifters. Furthermore, Copic et al. [32] reported that body composition was a valid predictor for movements based on lower extremity. In summary, previous studies have reported that BF% is a valid predictor in tests that require strength and power output, which is in line with the findings of the present study.

Weightlifting is a sport that requires high biomechanical demands on the lower joints. Therefore, the main extensor muscle groups of the lower extremities, especially the knees, play a major role during the lifting techniques [20]. Studies on weightlifters have generally focused on physical measurements such as anthropometric data, assessment of body dimensions, or body composition. Some researchers thought that physical measurements are insufficient compared with modern laboratory measurements [18, 33, 34, 35]. Isokinetic evaluation as a laboratory test is a highly valid and reliable assessment method for measuring the lower extremity strength of weightlifters. Although many studies have revealed the strong relationship between jumping ability and weightlifting performance in weightlifters [14, 36, 37, 38], few have investigated the relationship between isokinetic knee strength and weightlifting performance. Moreover, these studies presented the isokinetic knee strength of the weightlifters as a descriptor [17, 39]. The results of this study showed that E-180 was a valid predictor of competition performance in junior weightlifters. A previous study reported that the best output of weightlifters occurs at a slow speed (60 ${}^{\circ}$ /s) compared to other sports and this is thought to be due to the training program of these athletes consisting of low speed exercises that require more strength [11]. On the other hand, a systematic review reported that the angular speed for peak moment and muscle work in concentric and eccentric contraction was 60 ${}^{\circ}$ /s in isokinetic evaluations and 180 ${}^{\circ}$ /s for muscle power [40]. In this context, E-180 may be a better predictor because the power output associated with the second pull is very important. OW is not only a strength sport [41], it is also influenced by technical factors and is therefore better defined as a strength-speed sport which the ability to produce very high peak power is the main factor that determines success [42]. For a successful lift in the “snatch” and “clean and jerk” techniques, the bar must have sufficient height in the second pull stage. Therefore, this is the most critical factor for producing the power output needed to lift the bar to a sufficient height [43]. Power can be defined as work/time (or force $\times$ speed). Peak (instantaneous) power represents the maximum power generated in a given movement for a short period of time under a given condition [44] and is produced when both force and speed are at optimum values [45]. Therefore, it seems reasonable that E-180 shown in this study predicts weightlifting performance.

The present study also indicated that SB was a valid predictor of competition performance in junior weightlifters. Although it is frequently emphasized that balance is an important factor in OW, there have been no studies on whether it predicts actual OW performance. During the snatch and clean and jerk, the first pull is completed, and then it is necessary to stabilize the bar and maintain this stabilization for a certain period of time in different directions: forward-backwards or right-left. Therefore, it is very important for weightlifters to be able to hold their bodies around a center, evenly balanced on their feet [43]. Hamilton et al. [46] found no significant relationship between balance and isokinetic knee extension at angular velocities of 60 and 180 ${}^{\circ}$ /s in college athletes and we also found that the relationship between isokinetic knee extensor strength and balance was minimal. According to our findings, however, although balance did not have a strong correlation with isokinetic knee extensor strength, it was significant when predicting weightlifting performance. Similarly, the results of this study indicated that static balance was associated with competition performance and that static balance was a significant predictor of competition performance.

4.1 Limitations

This study has several limitations. It consisted only of athletes of a specific age category (categorized as junior in OW). In line with current research on weightlifting, we could not reach enough women weightlifters. Similarly, it may not be possible to generalize the results of the study to senior weightlifters, and it may not be useful for novice weightlifters. Another limitation is the determination of the competition performance based on the scores of a national championship. Weightlifting is not just a strength-power sport. As well as being influenced by technical factors, psychological factors and tactical errors due to poor coaching may also affect competition performance. Weightlifting performance could be measured through a simulated competition. However, there may not be enough motivation for athletes to perform at the highest level in this simulated competition. Other psychological and physiological reasons may also influence the outcome. For these reasons, we suggest that there are limitations inherent in determining OW performance.

5. Conclusions

It is clear that the lower body extensor muscles are very important in weightlifting. In addition, these muscles must be strong enough to lift the maximum weight and the body must be extremely balanced during both weightlifting techniques. The present study highlights the relationship among weightlifting competition performance, body fat percentage, isokinetic knee extensor strength, and static and dynamic balance.

Moreover, the results suggest that isokinetic knee extension strength at 180 ${}^{\circ}$ /s and static balance can be used to predict competition performance, assess readiness, and control training efficiency. These factors can provide coaches with valuable information about weightlifting training and competition potential. Fluctuations that may be accompanied by periodic training can be monitored and changes can be made to the training program if necessary. In addition, the findings of this study may help monitor long-term athlete development and control the training efficiency.

Footnotes

Acknowledgments

There has been no financial support for this work that could have influenced its outcome. The authors would like to thank the athletes for their participation in the study.

Conflict of interest

The authors wish to confirm that there is no conflict of interest associated with this publication.

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Body composition isokinetic knee extensor strength and balance as predictors of competition performance in junior weightlifters

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSIONS:

Keywords

1. Introduction

2. Methods

2.1 Participants

2.2 Procedures

2.3 Olympic weightlifting performance

2.4 Body Composition

2.5 Anthropometric measures

2.6 Isokinetic strength test

Table 1 Descriptive and performance characteristics of participants ( N = 51)

2.8 Statistical analyses

3. Results

Table 2 Pearson moment correlation coefficients between different variables ( N = 51)

4.1 Limitations

5. Conclusions

Footnotes

Acknowledgments

Conflict of interest

References

Table 1
Descriptive and performance characteristics of participants ( $N=$ 51)

Table 2
Pearson moment correlation coefficients between different variables ( $N=$ 51)