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Original Research

Unilateral Isometric Squat: Test Reliability, Interlimb Asymmetries, and Relationships With Limb Dominance

Bishop, Chris1; Read, Paul2; Lake, Jason3; Loturco, Irineu4; Dawes, Jay5; Madruga, Marc6; Romero-Rodrigues, Daniel6; Chavda, Shyam1; Turner, Anthony1

Author Information
Journal of Strength and Conditioning Research: February 2021 - Volume 35 - Issue - p S144-S151
doi: 10.1519/JSC.0000000000003079
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Abstract

Introduction

Numerous methods exist when assessing an athlete's strength capabilities such as isokinetic dynamometry to measure torque (12,30), 1-repetition maximum (1RM) testing during the back-squat exercise (16,31), and isometric tests assessing maximal force production through the isometric midthigh pull (IMTP) or squat (9,14,18). Isokinetic dynamometry may offer useful insight into interlimb and intralimb differences for the quadriceps and hamstring muscles at different contraction velocities. However, such methods are typically confined to a laboratory setting, thus, may not always be viable for practitioners in a team-sport environment (7). The back squat is a commonly programmed exercise during strength programs and often suggested as a means of assessing lower-body strength (16,21,31). Although the importance of this exercise is not being disputed, it has been suggested that high levels of mobility are required for optimal technique, which becomes especially important if using maximal loads (7). In addition, assuming that optimal technique can be adhered to for this exercise, 1RM protocols (which are often suggested) can be time-consuming, potentially reducing their usability with large groups of athletes (25). With recent literature highlighting strength as a critical physical quality to develop for both performance (33,34) and injury risk reduction (24), alternative methods of strength assessment may need to be considered.

The IMTP or isometric squat offers practitioners with a useful indication of athletes' force production capabilities and has been suggested to be more time-efficient than isokinetic dynamometry and 1RM back-squat testing (7). Further to this, isometric strength testing permits the generation of force-time curves, which enables practitioners to examine rapid force production characteristics over specific time intervals (13,18,35). In turn, this may provide practitioners with some insight into athletes' force production capacity during athletic tasks underpinned by strength such as sprinting, jumping, and changing direction (36). Previous investigations have compared these 2 tests and reported acceptable reliability for peak force (PF: intraclass correlation coefficient [ICC] ≥0.86, coefficient of variation [CV] ≤9.4%) (9). Results of this study highlighted significantly greater PF values for the isometric squat; thus, it was suggested that if practitioners wish to establish athletes' true lower-body maximal force production capabilities, the isometric squat might be the preferred choice. However, this was conducted during bilateral testing, and the literature pertaining to a unilateral version of this test is limited (18,19).

Spiteri et al. (32) investigated the effect of strength (using the unilateral isometric squat test) on foot kinetics and kinematics during a change of direction speed (CODS) task. Results showed that greater lower-body force production capabilities were associated with greater magnitude plant foot kinetics and, thus, faster CODS performance. In addition, although not the primary focus of their study, both limbs reported strong reliability for PF (ICC = 0.97; CV = 5.5–7.0%). However, this was the only metric to report reliability statistics. Hart et al. (18) assessed the reliability of PF and rate of force development (RFD) during the unilateral isometric squat on dominant (D) and nondominant (ND) limbs and reported acceptable reliability (ICC ≥ 0.83) for both measures with the exception of RFD on the ND limb (ICC = 0.36). This test was also used to establish interlimb strength asymmetries in 31 Australian rules football athletes (19), where players were required to kick a ball to a target 20 m away. For the purpose of data analysis, the sample was divided into accurate (n = 15) and inaccurate (n = 16) kickers and showed that the accurate group were almost perfectly symmetrical (1% asymmetry). By contrast, the inaccurate group showed an 8% asymmetry with the nonkicking limb (required to stabilize during the action of kicking) demonstrating weaker PF values. With limited literature on the unilateral isometric squat to date, further research is warranted to establish its ability to detect interlimb asymmetries and its associations with strength capacity (i.e., do larger asymmetry scores relate to reduced force production on a given limb), given previous literature has highlighted that strength imbalances may be detrimental to physical and sporting performance (5).

Therefore, the aims of this study were 3-fold: (a) establish the reliability of the unilateral isometric squat for multiple metrics when tested on a force platform, (b) quantify interlimb asymmetries for these associated metrics, and (c) establish the relationship between interlimb asymmetries and force-time characteristics for each limb. It was hypothesized that significant negative relationships would exist between asymmetries and isometric squat performance.

Methods

Experimental Approach to the Problem

A familiarization session provided subjects with the opportunity to practice test procedures as many times as required after all relevant test instructions had been given, thus, reducing any potential learning effects from the exercise. One week later, subjects attended a single-test session and performed 3 trials of the unilateral isometric squat on each limb. This test was chosen for 2 reasons: (a) recent research has shown that the isometric squat may be better at depicting isometric force production than the isometric IMTP, albeit bilaterally (9), and (b) recent research has investigated the unilateral IMTP (14,35); thus, it was decided that comparable research was needed on the isometric squat test. Procedures were conducted on a single force platform (PASPORT force plate, PASCO Scientific, CA, USA) sampling at 1,000 Hz. A standardized dynamic warm-up consisting of dynamic stretches to the lower body (multiplanar lunges, inchworms, and “world's greatest stretch”) was conducted before data collection, followed by 3 practice trials on each limb at approximately 60, 80, and 100% perceived effort for the isometric squat test. Three minutes of rest was provided after the final warm-up trial and the first data collection trial.

Subjects

Twenty-eight male recreational sport athletes with a background in soccer and rugby (age = 27.29 ± 4.6 years; mass = 80.72 ± 9.26 kg; height = 1.81 ± 0.06 m; ± SD) volunteered to take part in this study. A minimum of 27 participants was determined from a priori power analysis using G*Power (Version 3.1, University of Dusseldorf, Germany) implementing statistical power of 0.8 and a type 1 alpha level of 0.05, which has been used in comparable literature (13). Inclusion criteria required all subjects to have a minimum of 1 year resistance training experience, with any subject excluded from the study if they had any lower-body injury at the time of testing. Subjects were required to complete written informed consent forms to demonstrate that they were willing and able to undertake all testing protocols. Ethical approval was granted from the London Sport Institute's research and ethics committee, Middlesex University, UK.

Procedures

Unilateral Isometric Squat Test

A custom-built “ISO rig” (Absolute Performance, Cardiff, United Kingdom) was used for this test protocol (Figure 1). A goniometer was used to measure approximately 140° of hip and knee flexion for each participant (7,18), with full extension of the knee joint equaling 180°. To determine knee angle, the fulcrum of the goniometer was positioned on the lateral epicondyle of the femur. The stabilization arm was lined up along the line of the fibula (in the direction of the lateral malleolus), and the movement arm was lined up with the femur (pointing toward the greater trochanter at the hip). To determine hip angle, the fulcrum of the goniometer was positioned on the greater trochanter of the femur. The stabilization arm was lined up along the line of the femur (in the direction of the knee joint), and the movement arm was lined up along the line of the torso (pointing toward the shoulder joint). The nonstance limb was required to hover next to the working limb, so as to try and keep the hip levels during the isometric squat action, thus, aiding balance and stability.

F1
Figure 1.:
A and B) Example positioning during the unilateral isometric squat test.

To determine body mass, subjects were required to remain motionless on the force plate for 2 seconds. Once in position, each trial was then initiated by a “3, 2, 1, Go” countdown, and subjects were instructed to try and extend their knees and hips by driving up as “fast and hard as possible” against the bar for 5 seconds (14). The force plate was subsequently “zeroed” after each trial before subjects stepped on to the force plate for subsequent trials. Recorded metrics included PF; RFD from 0 to 0.1 seconds, 0.1–0.2 seconds, 0.2–0.3 seconds; and impulse from 0 to 0.1 seconds, 0.1–0.2 seconds, and 0.2–0.3 seconds. The first meaningful change in force was established when values surpassed 5 SDs of each subject's body mass (14,29). Peak force was defined as the maximum force generated during the test. Rate of force development was defined as the rate of change in force (epoch) after the first meaningful onset was recorded at the start of each specified time point (28), whereas impulse was defined as the net force multiplied by the time taken to produce it at each specified time point, i.e., the area under the force-time curve (14). Limb dominance was defined as the limb with the greatest score between the 2 and subsequently used in this way for the calculation of interlimb asymmetries. Each participant conducted testing on their left leg first and then alternated between limbs until 3 trials were conducted for each limb. The trial with the greatest PF was used for subsequent analysis to ensure that RFD and impulse time integrals were being analyzed from the same trial.

Statistical Analyses

Initially, all force-time data were saved as text files and analyzed unfiltered (13) in a custom-built spreadsheet in Microsoft Excel in line with recent suggestions from Chavda et al. (11). All data were expressed as mean values and SDs and later transferred into SPSS (V.24, Chicago, IL, USA) for additional analyses. Reliability was quantified for each metric using the CV and ICC. However, given that it is highly plausible that one of these methods may report strong reliability while the other shows unacceptable variability, results were interpreted in line with previous suggestions from Bradshaw et al. (8). When considered together, average reliability was considered “good” if ICC > 0.67 and CV < 10%, “moderate” if ICC < 0.67 or CV > 10%, or “poor” if ICC < 0.67 and CV > 10% (8). Interlimb asymmetries were quantified as the percentage difference between limbs using the formula proposed by Bishop et al. (3,4): (100/[maximum value] × [minimum value] × −1 + 100). Given that the desired goal for all metrics in this study was to demonstrate the highest value possible, the authors suggest that this equation (which uses the maximum value as a reference value) is a valid means of quantifying interlimb differences for unilateral tests (3). Pearson's r correlations were conducted to determine the relationships between the asymmetry score and test scores for D and ND limbs, respectively. Statistical significance for these relationships was set at p ≤ 0.05. Finally, the magnitude of change was quantified between limbs using Cohen's d effect sizes: (MeanD − MeanND)/SDPooled. These were interpreted in line with a suggested scale by Hopkins et al. (22) where <0.2 = trivial; 0.2–0.6 = small; 0.6–1.2 = moderate; 1.2–2.0 = large; 2.0–4.0 = very large; and >4.0 = near perfect.

Results

Mean scores, effect sizes, and test reliability data are presented in Table 1. Most metrics demonstrated moderate reliability, with the exception of PF on both limbs and RFD on the ND limb (0.2–0.3 seconds), which showed good reliability, and impulse on the ND limb (0–0.1 seconds), which showed poor reliability. When determining magnitude of change between limbs, effect sizes were small (0.32–0.56) for all metrics. For asymmetry (Figure 2), the smallest differences were seen for PF (8.36%), and a noticeable trend was evident for these interlimb differences when RFD and impulse were viewed. Asymmetries were largest during the first timeframe (0–0.1 seconds) and continued to decrease from 0.1–0.2 and 0.2–0.3 seconds, respectively. Finally, relationships between asymmetry scores and limb dominance are presented in Table 2. Of note, all significant relationships (p < 0.05) were negative indicating that larger asymmetries were indicative of reduced force outputs. Three significant negative relationships were shown with the D limb (r range = −0.43 to −0.47), whereas 31 negative correlations (of a possible 49) were reported with the ND limb (r range = −0.42 to −0.71).

Table 1. - Mean ± SD, effect size (between D and ND limbs) and reliability data for the unilateral isometric squat test.*
Test variable Mean ± SD Effect size CV (%) ICC (95% CI) Reliability descriptor
Peak force (D) 1,661.80 ± 408.67 0.32 5.70 0.93 (0.87–0.96) Good
Peak force (ND) 1,530.35 ± 417.79 5.44 0.94 (0.88–0.97) Good
RFD 0–0.1 s (D) 5,676.94 ± 2,503.34 0.48 18.57 0.87 (0.77–0.93) Moderate
RFD 0–0.1 s (ND) 4,458.20 ± 2,565.73 25.98 0.78 (0.64–0.88) Moderate
RFD 0.1–0.2 s (D) 4,625.61 ± 1,651.47 0.36 12.37 0.92 (0.86–0.96) Moderate
RFD 0.1–0.2 s (ND) 4,023.74 ± 1,652.79 13.10 0.92 (0.85–0.96) Moderate
RFD 0.2–0.3 s (D) 3,615.60 ± 1,137.48 0.32 10.37 0.89 (0.81–0.94) Moderate
RFD 0.2–0.3 s (ND) 3,251.05 ± 1,135.98 9.20 0.91 (0.85–0.96) Good
Impulse 0–0.1 s (D) 31.46 ± 12.48 0.56 23.48 0.77 (0.61–0.87) Moderate
Impulse 0–0.1 s (ND) 24.21 ± 13.18 32.12 0.60 (0.39–0.77) Poor
Impulse 0.1–0.2 s (D) 109.68 ± 42.13 0.47 14.59 0.90 (0.82–0.95) Moderate
Impulse 0.1–0.2 s (ND) 89.21 ± 44.04 20.26 0.83 (0.70–0.91) Moderate
Impulse 0.2–0.3 s (D) 211.50 ± 72.72 0.42 12.14 0.92 (0.85–0.96) Moderate
Impulse 0.2–0.3 s (ND) 180.96 ± 73.39 13.71 0.89 (0.80–0.94) Moderate
*D = dominant; ND = nondominant; CV = coefficient of variation; ICC = intraclass correlation coefficient; CI = confidence interval; RFD = rate of force development; s = seconds.
Peak force measured in Newton, RFD measured in Newton per second, and impulse measured in Newton seconds.

F2
Figure 2.:
Interlimb asymmetry values and SDs (error bars) for each metric in the unilateral isometric squat test. RFD = rate of force development.
Table 2. - Correlations between interlimb asymmetries and performance on the dominant and nondominant limbs.*
Asymmetry variable (%) Peak force RFD, 0–0.1 RFD, 0.1–0.2 RFD, 0.2–0.3 Impulse, 0–0.1 Impulse, 0.1–0.2 Impulse, 0.2–0.3
D ND D ND D ND D ND D ND D ND D ND
Peak force −0.28 −0.49 −0.38 −0.36 −0.43 −0.45 −0.39 −0.46 −0.30 −0.27 −0.37 −0.42 −0.40 −0.48
RFD 0–0.1 0.08 0.02 −0.17 −0.57§ −0.17 −0.34 −0.06 −0.16 −0.24 −0.54 −0.19 −0.52 −0.19 −0.40
RFD 0.1–0.2 0.01 −0.08 −0.38 −0.56§ −0.27 −0.52 −0.21 −0.32 −0.47 −0.61§ −0.37 −0.59§ −0.32 −0.54
RFD 0.2–0.3 −0.21 −0.31 −0.41 −0.50 −0.38 −0.47 −0.27 −0.50 −0.43 −0.41 −0.40 −0.47 −0.40 −0.48
Impulse 0–0.1 0.06 −0.01 −0.29 −0.58§ −0.17 −0.34 −0.07 −0.13 −0.32 −0.71§ −0.28 −0.57§ −0.22 −0.42
Impulse 0.1–0.2 0.01 −0.10 −0.20 −0.54 −0.20 −0.40 −0.13 −0.22 −0.25 −0.55§ −0.22 −0.59§ −0.21 −0.49
Impulse 0.2–0.3 −0.06 −0.18 −0.26 −0.51 −0.25 −0.46 −0.19 −0.28 −0.33 0.55§ −0.29 −0.60§ −0.27 −0.55§
*RFD = rate of force development; D = dominant; ND = nondominant.
N.B: peak force is measured in Newton; RFD is measured in Newton per second; and impulse is measured in Newton seconds.
Significant at p < 0.05.
§Significant at p < 0.01.

Discussion

The aims of this study were to establish the reliability of the unilateral isometric squat across a range of metrics and quantify their associated interlimb asymmetries. A further aim was to establish the relationships between the asymmetry scores and performance on the D and ND limbs. Most metrics reported moderate reliability, with the exception of PF and RFD on the ND limb (0.2–0.3 seconds), which was good and impulse from 0 to 0.1 seconds, which was poor on the ND limb. Interlimb asymmetries varied across metrics highlighting their task-specific nature, and relationships between asymmetry scores and limb dominance highlighted multiple negative associations, most of which were with the ND limb.

Table 1 shows the reliability of metrics during the unilateral isometric squat test. The only metric to report good reliability on both limbs was PF, which is in line with previous research (18,32), suggesting that this is a reliable metric during this unilateral test. To the authors' knowledge, only 2 studies have reported reliability data on the unilateral isometric squat test. Spiteri et al. (32) reported near-perfect relative reliability (ICC = 0.97) and acceptable variability (CV = 5.5–7.0%) for PF. No other metrics were investigated because of the aims being associated with investigating the effects of strength on kinetics and kinematics of a CODS task. Hart et al. (18) showed that RFD from 0 to 0.3 seconds was only reliable on the D limb, with the ND limb reporting ICC of 0.36 and CV of 46%. By contrast, this study showed good reliability on the ND limb for RFD between 0.2 and 0.3 seconds and moderate reliability between 0–0.1 and 0.1–0.2 seconds time points (which Hart et al. (18) did not report). It is worth noting, however, that Hart et al. (18) used a portable device when investigating test reliability, which allowed some aspect of “sway,” and, therefore, instability. In this study, the platform for testing was stable (Figure 1), which may have contributed to the improved reliability data on the ND limb. In addition, RFD was calculated differently in this study compared with Hart et al. (18), which may have also contributed to different reliability statistics. Impulse showed a similar trend in results with each time point showing moderate reliability with the exception of the ND limb between 0 and 0.1 seconds (which was poor). In addition, although RFD and impulse showed moderate reliability at the earlier time intervals, CV values were noticeably higher than 10% indicating that practitioners should be cautious when using these metrics at those time points. As such, if practitioners want to quantify data from the unilateral isometric squat, PF may be the only truly reliable metric to use if the current time intervals are used for RFD and impulse analysis.

However, given the paucity of reliability data for the unilateral isometric squat, it is worth highlighting that comparable results have been reported for the unilateral IMTP (35). Dos'Santos et al. (14) reported better within-session reliability data than this study but used different time intervals in the analysis. Impulse was analyzed from 0 to 0.1 seconds (ICC = 0.83–0.87; CV = 9.3–9.5%), 0–0.2 seconds (ICC = 0.82–0.86; CV = 10.3–10.8%), and 0–0.3 seconds (ICC = 0.82–0.88; CV = 10.5–11.6%), noting here that a range is provided because separate data exists for each limb. However, PF was comparable with this study with ICC of 0.94 on both limbs and CV values of 4.7–5.0%. Similarly, Thomas et al. (35) reported between-session reliability data for the unilateral IMTP. Again, comparable data were reported for PF (ICC = 0.95–0.97; CV = 4.15–4.91%), and the same time intervals as used by Dos'Santos et al. (14) were used to analyze impulse. Between-session reliability data for impulse at 0–0.1 seconds (ICC = 0.88–0.94; CV = 7.08–8.30%), 0–0.2 seconds (ICC = 0.85–0.95; CV = 6.16–9.24%), and 0–0.3 seconds (ICC = 0.92–0.95; CV = 6.27–7.43%) again showed notably better findings than this study. Thus, it is plausible that the reliability data for impulse in this study would have been improved if analyzed in line with the methods of Dos'Santos et al. (14) and Thomas et al. (35), and that consecutive 0.1-second time intervals are not suitable, which has been previously suggested (26). However, further research is warranted to compare the 2 methods of analysis during unilateral isometric strength testing.

Figure 2 shows the interlimb asymmetry scores for each metric. Previous research has highlighted how task-specific asymmetries can be (4,20,24,27,29); however, this concept can now also be applied to different metrics within the same test. Figure 2 clearly shows substantially different asymmetries for PF, RFD, and impulse metrics, in addition to large SDs (as represented by the error bars). The PF asymmetry values are in agreement with those reported by Hart et al. (19) who used the same test to determine PF asymmetries (also 8%) in Australian rules football athletes. Where RFD and impulse are concerned, there was a noticeable trend for asymmetries to reduce as time increased; however, the concept of test variability must also be considered. Previous research has highlighted that asymmetries may not be “real” unless they are greater than the CV value (2,3,15). Therefore, despite the large asymmetry values seen for RFD between 0 and 0.1 seconds and impulse between 0–0.1 and 0.1–0.2 seconds, the accompanying CV values at these time points were larger (Table 1). Thus, with the test variability score (CV) being greater than the interlimb difference, practitioners should be mindful about using such data as part of an athlete profiling report. With that in mind, meaningful asymmetry scores are evident for PF, RFD between 0–0.1 and 0.1–0.2 s, and impulse between 0.2 and 0.3 seconds. Furthermore, with previous research highlighting that PF asymmetries of 8% can have a detrimental effect on sporting performance (19), and 10% being a possible threshold for heightened injury risk in quadriceps strength (23), the present values of 8.36–15.45% could be a strong consideration for practitioners when planning subsequent training interventions.

Table 2 shows the correlations between all asymmetry scores and the performance on D and ND limbs for each metric. The first point to consider is that, regardless of statistical significance, nearly all correlations are negative, suggesting that the larger an asymmetry is, the less force or RFD occurs. For the D limb, 3 of 49 individual correlations were significant, suggesting that asymmetries do not affect the performance on the D limb for the most part. Given only 3 metrics showed significance on the D limb, these findings can likely be considered random anomalies. However, the ND limb showed 31 of 49 negative correlations, suggesting that being asymmetrical is detrimental to the strength performance on the ND limb. Noting that many sporting actions occur unilaterally (such as sprinting and changing direction), and that many of these are underpinned by strength (36), it seems logical to suggest that the correction of these imbalances and strengthening for the ND limb could be advantageous. Furthermore, a recent critical review of the effects of asymmetry on athletic performance highlighted that the reduction of imbalances could be seen from a “windows of opportunity” perspective (27). In essence, with additional focus being provided to the weaker limb, this may assist in reducing any existing side-to-side differences and enhance overall force output bilaterally. Given the volume of negative relationships reported on the ND limb in this study, this may be a viable option for practitioners to consider whether similar results are found with their athletes. Previous research has suggested that unilateral training is most likely a favorable method for reducing interlimb asymmetries (6,10,17). In this context, it may be suggested that exercises such as split squats, step-ups, and lunges might be appropriate for reducing strength imbalances, thus, improving the performance of the ND limb in a task such as the unilateral isometric squat.

This study was not without some limitations. First, it only investigated within-session reliability data; thus, further research should aim to establish between-session reliability data for the chosen metrics. This between-session analysis should also be computed for asymmetry data as well, noting that we alluded to the task-specific nature of asymmetry earlier. In addition, these findings can only be attributed to recreational sport athletes. Given the importance of strength for athletic development (33,34), future research should also aim to establish reliability data in elite athlete populations for unilateral isometric tasks.

In summary, PF may be the only truly reliable metric when analyzing force-time curves from the unilateral isometric squat test. With real interlimb asymmetries of 8.36–15.45% and multiple relationships with reduced force characteristics on the ND limb, it is suggested that the reduction of between-limb differences in strength may be warranted.

Practical Applications

The findings of this study show that if practitioners wish to use the unilateral isometric squat to assess force production capabilities of each limb, PF may be the only metric to interpret with real confidence given its strong reliability. Asymmetries in strength as small as 6.6% have been shown to correlate with reduced jump performance (1); therefore, the interlimb differences reported in this study can be considered quite large. When their effects on the force production capability of the ND limb are considered as well, the results indicate that practitioners should be mindful of such large imbalances, and it seems logical to suggest that practitioners may wish to consider reducing these imbalances. If said imbalances are viewed as “windows of opportunity,” the addition of unilateral strength exercises such as split squats, lunges, and step-ups in conjunction with bilateral lifts may help to reduce asymmetries. The relevance here being that many sporting actions occur unilaterally for team-sport athletes (such as sprinting and changing direction), many of which are underpinned by strength. Thus, the reduction of strength asymmetries seems like a logical suggestion for athlete populations.

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Keywords:

strength assessment; side-to-side differences; peak force

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