Ground Reaction Forces Are Predicted With Functional and Clinical Tests in a Healthy Collegiate Population
Rangos School of Health Sciences
Anterior Cruciate Ligament, Dorsiflexion, Fat Free Mass, H:Q Ratio, Margaria Kalmen, Triple Hop
Purpose: This study aimed to generate models predicting Ground Reaction Forces (GRFs), an established predictor of ACL injury incidence, from practical functional and clinical tests. Participants: Forty-two healthy, active college age individuals (21 females, age 20.667Ã‚Â±1.461; 70.702Ã‚Â±2.363cm; 82.202Ã‚Â±7.606kg; 21 males, age 21.571Ã‚Â±1.28; 65.524Ã‚Â±1.874cm; 64.190Ã‚Â±9.059kg) participated.
Methods and Materials: After assuring all participants met inclusion criteria and provided consent, lower extremity (LE) dominance was determined with drop landings. Individuals then had Fat Free Mass [FFM] determined from skinfolds, ankle joint dorsiflexion passive range of motion taken with a standard goniometer [DPROM], and performed the overhead deep squat test [ODS]. A warm-up on a bicycle ergometer then preceded determination of vertical [GRFz] and posterior ground reaction forces [GRFy] with five, signal-averaged LE drop landings from 35cm height onto a forceplate. Participants then performed the following tests in a counterbalanced order: Margaria-Kalamen [MK], Single Leg Triple Hop [SLTH], isometric peak force for lateral hip rotation [HipLR], knee flexion and knee extension. The knee flexion and extension peak force data was used to calculate a flexion:extension peak force ratio [H:Q] while GRFz and GRFy values were normalized to the participantÃ¢â‚¬â„¢s FFM [nGRFz and nGRFy]. Stepwise linear regression models to predict the GRFs were calculated using FFM, DPROM, ODS, MK, SLTH, HipLR, H:Q and sex as the predictors. Alpha levels for all analyses were set a-priori at PÃ¢â€°Â¤ .05.
Results: Step-wise linear regression analysis indicated that a significant nGRFz model occurred utilizing all independent variables (Adjusted R2= .197, P= .048), but was most parsimonious with only SLTH and DPROM as predictor variables (Adjusted R2= .274; P=.001). Use of all eight-predictor variables for nGRFy also resulted in a statistically significant result (P= .001) but the most parsimonious model occurred with only H:Q, FFM and DPROM (Adjusted R2= .476; P< .001).
Conclusions: Two models significantly predicted GRFs from practical clinical measures and functional tests. One model predicted vertical ground reaction force from SLTH and DPROM, while one model predicted nGRFy from H:Q, FFM and DPROM. Clinical Relevance: If validated, a practical method of predicting nGRFy would be available to identify those at elevated ACL injury risk.
Cacolice, P. (2015). Ground Reaction Forces Are Predicted With Functional and Clinical Tests in a Healthy Collegiate Population (Doctoral dissertation, Duquesne University). Retrieved from https://dsc.duq.edu/etd/1519