Association Between Double-Leg Squat and Single-Leg Squat Performance and Injury Incidence Among Incoming NCAA Division I Athletes: A Prospective Cohort Study

Research Review: Association Between Double-Leg Squat and Single-Leg Squat Performance and Injury Incidence Among Incoming NCAA Division I Athletes: A Prospective Cohort Study

By William Chancey Sumner, PTA, MS, CES, CAFS, HMS, FRCms, c-PT

Edited by Brent Brookbush, DPT, PT, COMT, MS, PES, CES, CSCS, ACSM H/FS

Original Citation: Eckard, T., Padua, D., Mauntel, T., Frank, B., Pietrosimone, L., Begalle, R., Goto, S., Clark, M., Kucera, K. (2018). Association between double-leg squat and single-leg squat performance and injury incidence among incoming NCAA Division I athletes: A prospective cohort study. Physical Therapy in Sport, 34, 192 – 200. ABSTRACT

Introduction:

Research has investigated several movement screens and assessments intended to highlight impairments that may result in injury, but most have shown little, if any efficacy (1-4). Research has demonstrated correlation between specific impairments and future injury risk (5 - 11); however, further research is needed to determine a practical and reliable assessment that will highlight those impairments. This 2018 prospective study by American researchers demonstrates that more identified movement faults (e.g. knee valgus, hip drop, forward lean) on the double-leg squat (DLS) and single-leg squat (SLS) tests were correlated with a greater incidence of lower extremity injury in collegiate athletes. Human movement professionals should consider integrating the DLS and SLS into practice, and addressing noted impairments with the intent of reducing the risk of future lower extremity injury.

Overhead Squat Assessment (Image: courtesy of www.BrentBrookbush.com)

Study Summary

Study Design	Prospective study
Level of Evidence	III Evidence from non-experimental descriptive studies, such as comparative studies, correlation studies and case-control studies
Participant Characteristics	Demographics Number of participants: 115 NCAA Division I collegiate athletes enrolled in the study 64 males 51 females Data from 111 participants were used for the analysis Participants were first-year NCAA Division I student athletes at the university (freshmen or transfer students) 5 varsity male sports Football, soccer, cross country, track and field, and lacrosse 5 varsity female sports Field hockey, soccer, cross country, track and field, and lacrosse Inclusion Criteria: Injury free collegiate athletes Exclusion Criteria: Inability to perform the double-leg squat (DLS) or SLS due to a current injury. Injury history included a grade III sprain or strain, a lower-extremity fracture requiring surgery, and/or any lower extremity (LE) injury resulting in at least 6-months of missed sport participation
Methodology	A standardized questionnaire was completed during first semester of enrollment that included: Demographics Injury history Respective sport Participant assessments were completed and tests included: DLS SLS Jump-landing task Single-leg triple hop Lower extremity range of motion testing Upper extremity range of motion testing Push-up task Lower extremity manual muscle testing DLS: Scored as either poor or non-poor and a single observer assessed for movement errors. Possible scores could range from 0-15. Errors are scored as “1”. Number of errors are summed to yield a score. DLS was performed with the following guidelines: Feet hip-width apart Toes straight ahead Arms above their head Errors for the DLS include: foot turns out, foot flattens, knee valgus/varus, forward lean, low back arch/round, arm forward, heel lift-off, weight-shift. DLS was assessed from the anterior, lateral and posterior views Single-leg squat (SLS): Single observer rated participants poor or non-poor on performance. During the SLS, participants alternated leg with each repetition to avoid fatigue. The score for each lower extremity was from 0-9. Errors are scored as “1”. Number of errors are summed to yield a score. The SLS was performed with the following guidelines: Weight bearing foot pointed straight forward Non-weight bearing knee flexed to 90° and hip flexed to 45° Hands on iliac crest Errors for the SLS include: foot flattens, knee valgus/varus, forward lean, balance loss, knee flexion <60 degrees, low back round, trunk flexion/rotation/side-bend, and hip drop/hike. SLS was assessed from the anterior and lateral views Same 5 assessors were utilized throughout testing and were certified athletic trainers or physical therapists with at least 2 years of experience Lower extremity injury data was collected from each participant’s from the universities electronic medical record (EMR). There were no previously established thresholds for determining poor movers based on DLS and SLS scores. DLS and SLS scores were grouped into tertiles, quartiles, quintiles for analysis, and injury rates were correlated. Participants were observed for incidence of lower extremity (LE) injury over one calendar year. The occurrence of LE injuries were tracked by university clinical medical staff.
Data Collection and Analysis	Descriptive statistics were calculated for demographics, movement quality, and injury data. Incidence rate ratios were calculated for the 4 potential covariates: LE injury history – dichotomized to yes/no Sport cutting load – dichotomized to moderate/high and low/no cutting BMI (Body Mass Index) – continuous variable Sex – dichotomized to male/female Multi-variate Poisson regression analysis Compare the incidence of LE injuries in poor versus non-poor movers on the DLS and SLS, with potential covariates included as part of the analysis. Regression modeling was performed by SAS software (version 9.4; SAS Institute Inc, Cary, NC, USA) Receiver operating characteristic curve analysis was completed by SPSS Statistical software (version 24; IBM Corporation, Armonk, NY)
Outcome Measures	Incidence of lower extremity injuries Acetabulum/hip joint, thigh, leg, foot, and all associated joints were included. Time loss and non-time loss LE injuries Acute and chronic LE injuries Days at risk Athlete’s participation status was listed as “full”, “limited”, or “out” Days at risk were calculated as days “out” subtracted from 365 days in a calendar year Potential covariates Four covariates were included to assess possible confounding variables: LE injury history, sport cutting load, sex and body mass index (BMI)
Results	Largest number of participants participated in men's football (29.6%, n=34), women’s soccer (17.4%, n=20) and men’s lacrosse (17.4%, n=20). 50 participants (43.9%) reported history of LE injuries. 110 LE (65.5%, n=72) injuries occurred during the study and the majority were acute in nature Ankle/foot (30%, n=33), thigh (23.6%, n=26) and knee (18.2%, n=20) were the most frequently injured areas of the LEs Most common injuries were strains (34.5%, n=38) and sprains (29.1%, n=32) 3 most common diagnoses were: ankle sprain (12.7%, n=14), hamstring strain (8.2%, n=9) and adductor strain (4.5%, n=5) Most LE injuries were non-time loss (NTL) (54.5%, n=60) Time loss (TL) injuries accounted for 45.5% of LE injuries (n=50) Mean days at risk among participants was 33.23 ± 66.57 person-days Double-leg squat (DLS) test: Mean score was 4.19 ± 2.43 (range 0-10) Most common errors were: forward lean (57.9%, n=66), foot turns out (56.1%, n=64) and weight shift (54.4%, n=62) Poor movement was ranked as the highest quartile, which equated to ≥5 errors on the DLS (24.6%, n=28) Unadjusted LE injury incidence rate was 3.26 (95% CI: 2.15, 4.94) per 1000 person-days in the DLS poor mover group The crude incidence rate ratio (IRR) for poor versus non-poor mover group on DLS was 1.22 (95% CI: 0.76, 2.00) Sex was not found to be an effect modifier on DLS poor mover-LE injury association (p=0.83) In multivariate analyses a change of ≥10% was not shown when any covariate was removed (sex 8.5%, LE injury history <0.10%, cutting load 1.29%, BMI <0.10%) The final DLS model was adjusted for sex and LE injury history and yielded an IRR of 1.33 (95% CI: 0.80, 2.22) for being a poor versus non-poor mover on DLS Using the threshold of ≥5 errors on the DLS, the sensitivity was 0.22, specificity was 0.86, and the area under the curve (AUC) was 0.54 (95% CI: 0.36, 0.72) Single-leg squat (SLS) test: Mean score was 7.16 ± 3.31 (range 1-13) Most common errors were: trunk/hip shift (82.5%, n=94), knee valgus (70.2%, n=80) and hip drop/hike (60.5%, n= 69) Poor movement was ranked as highest quartile, which equated to ≥10 errors on the right and left LE combined (21.1%, n=24) Unadjusted LE injury incidence rate was 3.98 per 1000 person-days (95% CI: 2.64, 6.01) in the SLS poor mover group and 2.51 per 1000 person-days (95% CI: 1.93, 3.27) in SLS non-poor mover group The crude IRR for poor versus non-poor movers on SLS was 1.58 (95% CI: 0.97, 2.58) Sex was not found to be an effect modifier on SLS poor mover-LE injury association (p=0.45) In multivariate analyses a change of ≥10% was not shown when any covariate was removed (sex 4.84%, LE injury history 2.68%, cutting load 0.19%, BMI 0.41%) The final SLS model was adjusted for sex and LE injury history and yielded an IRR of 1.62 (95% CI: 0.98, 2.66) for being a poor versus non-poor mover on SLS Using the cutpoint of ≥10 errors on the SLS the sensitivity was 0.17, specificity was 0.71, and the area under the curve (AUC) was 0.55 (95% CI: 0.37, 0.72) 16 subjects scored poor on both the DLS and SLS tests
Our Conclusions	The findings of this study show that more errors on the DLS and SLS may be associated with an increased risk of LE injury in collegiate athletes. The DLS and SLS should be considered for integration into a comprehensive movement assessment or athletic screen. Further research is needed to investigate interventions based on
Researchers' Conclusions	Collegiate athletes with more errors on the DLS or SLS demonstrated greater incidence of LE injuries than those with less errors. The majority of LE injuries in this study were acute and did not result in time lost from competition.

Caption: Power training has been shown to improve the cross-sectional area of type II muscle fibers. Image courtesy of www.BrentBrookbush.com

Hop Down to Single-Leg Landing and Balance (Image courtesy of www.BrentBrookbush.com)

How this study contributes to the body of research:

This study adds to a growing body of research investigating assessments with the intent of identifying impairments that may be predictive of future injury (1 - 3, 13 - 16). Previous research has demonstrated moderate to good inter- and intra-rater reliability using the double-leg squat (DLS ) and single-leg squat (SLS), but no data was available regarding the ability of the test to highlight impairments associated with increased risk. This prospective study addressed this gap, demonstrating that a lower score and/or certain movement discrepancies were correlated with higher risk in college athletes.

How the Findings Apply to Practice:

The findings of this study demonstrate a correlation between poor performance on the DLS /SLS and an increased risk of lower extremity (LE) injury. Human movement professionals should consider integration of the DLS /SLS into their assessment protocol, and potentially consider using these tests as a screen for preventative care programs. Future research should investigate the ability of interventions based on assessment findings, to reduce the risk of injury.

This study had many methodical strengths, including:

Prospective studies are relatively rare in human movement science. This study demonstrated the efficacy of the DLS /SLS as screens for impairments that may increase the risk of injury.
Multiple sports were included in data collection which aids in the studies generalizability to other college sports.
Sex, BMI, LE injury history and sport cutting load were also analyzed as potential confounding variables. No correlation was noted.

Weaknesses and limitations that should be noted prior to clinical integration of the findings include:

LE injury data was obtained from the university’s electronic medical record, which relies on self-reported injury to initiate treatment; this may have resulted in underestimated injury rates.
All subjects were incoming NCAA Division I athletes; results may not be generalizable to recreational athletes and other populations.
A small cohort was included in this study and a larger cohort may identify if the SLS or DLS scores are a significant indicator of LE injury risk.

How the study relates to Brookbush Institute Content?

The Brookbush Institute (BI) has developed predictive models of postural dysfunction based on evidence of common tissue changes (muscle, joint, fascia and nerve) to aid human movement professionals in selecting optimal assessments, manual interventions and exercise. This study uses the same assessments recommended by the BI, with the intent of identifying common tissue changes. The findings of this study demonstrate that the identification of movement impairments is predictive of future injury risk. The BI will continue to pursue optimal practice by refining predictive models of postural dysfunction , using aggregated results of all available evidence.

The following videos illustrate common assessment techniques for LED and assessment techniques:

Overhead Squat Assessment: Introduction

Overhead Squat Assessment: Feet Turn Out

Overhead Squat Assessment: Asymmetrical Weight Shift

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Association Between Double-Leg Squat and Single-Leg Squat Performance and Injury Incidence Among Incoming NCAA Division I Athletes: A Prospective Cohort Study

Research Review: Association Between Double-Leg Squat and Single-Leg Squat Performance and Injury Incidence Among Incoming NCAA Division I Athletes: A Prospective Cohort Study

Introduction:

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