Effect of Ankle Mobility and Segment Ratios on Trunk Lean in the Barbell Back Squat

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Abstract

Fuglsang, EI, Telling, AS, and Sørensen, H. Effect of ankle mobility and segment ratios on trunk lean in the barbell back squat. J Strength Cond Res 31(11): 3024–3033, 2017—The barbell back squat is a popular exercise used for both performance enhancing and rehabilitation purposes. However, injuries are common, and people with a history of lower back pain are especially vulnerable. Past studies have shown that higher trunk angles (less forward lean) generate less stress on the lower back; thus, it seems appropriate to investigate the factors presumed to influence the trunk angle. Therefore, the aim of this study was to investigate how ankle mobility and the segment ratios between the thoracic spine, thighs, and shanks influence the trunk angle in the back squat. While recorded with motion capture, 11 male subjects performed 3 repetitions at approximately 75% of 1 repetition maximum in the squat to a parallel position (thighs horizontal) or lower. Furthermore, subjects performed a weight bearing lunge test to determine maximal range of motion (ROM) of the ankle joint. Segment angles of the shank, thigh, and trunk segments as well as ankle joint angles were calculated by 2-dimensional kinematic analysis. Simple linear and multiple regressions were used to test the correlation between the lower extremity angles, segment ratios, and the trunk angle. On average, subjects had an 11.4 ± 4.4° deficit in dorsiflexion ROM between maximal ROM and ROM in the parallel squat (PS) which was independent of maximal ROM. Ankle mobility showed to significantly negatively correlate with trunk angle, thereby showing that a subject with greater ankle ROM had a more upright torso in the PS position. This study was unable to find a significant correlation between the segment ratios and trunk angle. Furthermore, when combined, no significant relationship between ankle mobility, segment length ratios, and trunk angle were found, although it was noticed that this more complex model showed the greatest R2 value.

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