(45) The Influence of Age on the Load Velocity Profile in Females

Purpose: In order to combat age-related declines in muscular strength, a Load Velocity (LV) relationship can be generated based on how much load an individual can lift and how fast they can lift that load. The purpose of this study was to examine the influence of age on the load-velocity profile (LVP) in females.

Methods: Twenty-seven female participants (19-78 y) volunteered to complete a load-velocity assessment on the belt squat machine. Participants were instructed to move as fast as possible during the concentric phase of the movement after briefly pausing at the bottom of the squat. Three trials at each load were completed with each load increasing by 20% of the participant’s body weight (BW) after the initial load of the empty belt squat machine (31 lbs) until maximal load was reached when the participant fell below a movement velocity of 0.3 m/s. A two-minute rest break was given in between sets. Participants’ strength was measured by assessing one repetition maximum (1RM) belt squat. Relative strength (1RM_REL) was calculated as the 1RM/BW to normalize strength for comparison across individuals. Maximal movement speed (MMS; m/s) was determined as the highest mean velocity achieved when lifting the empty belt squat rack. The highest mean velocity trial from each set was used to create a linear regression equation. The slope of the linear regression equation (LV_SLOPE) was calculated to allow for the assessment of belt squat performance as it relates to the interaction between load and velocity. The area under the LV regression line (LV_AUC) was calculated using the trapezoidal method. LV_SLOPE and LV_AUC were normalized to body (SLOPE_REL and AUC_REL). A one-way ANOVA was run to examine group differences between Young Females (YF:19-39 y), Middle Females (MF: 40-60 y), and Older Females (OF: 60+ y). Hedges’ g was used to estimate effect size.

Results: Significant group differences were revealed in LV_AUC (F= 11.93, p= < 0.001), AUC_REL (F= 10.42, p=< 0.001), Maximal Strength (F= 11.54, p=< 0.001), 1RM_REL (F= 11.50, p=< 0.001), and MMS (F= 5.92, p= 0.008). Post-hoc analysis revealed significant differences in LV_AUC between YF and OF (YF: -95.20 ± 15.40 kg·m/s·BW, OF: -40.50 ± 22.63 kg·m/s·BW, p≤0.001, g = -5.70), as well as significant differences in AUC_REL between YF and OF (YF: -1.40 ± 0.22 kg/BW/m/s, MF: -0.91 ± 0.33 kg·m/s·BW, p= 0.019, g = -3.55; YF: -1.40 ± 0.22 kg/BW/m/s, OF: -0.61 ± 0.35 kg·m/s·BW, p≤0.001, g = -5.22, respectively). Post-hoc analysis revealed significant differences in 1RM_REL between YF and OF (YF: 3.12 ± 0.45 kg/BW, OF: 2.21 ± 0.38 kg/BW, p≤0.001, g = 4.43) and MMS (YF: 0.92 ± 0.14 m/s, OF: 0.67 ± 0.15 m/s, p= 0.007, g = 3.46). Post-hoc analysis showed significant differences in 1RM_REL between YF and MF (YF: 3.12 ± 0.45 kg/BW, MF: 2.49 ± 0.32 kg/BW, p= 0.017, g =3.22 ).

Conclusion: These data suggest that there are significant differences in 1RM, 1RM_REL, MMS, LV_AUC, and AUC_REL in females across the age span. These data also suggest, due to the small effect sizes and no significant differences in LV_SLOPE and SLOPE_REL across the age span, LV_AUC and AUC_REL might be a better indicator for differences in females across the age span in regards to the LV relationship. Practical Applications: These data provide practitioners, clinicians, strength and conditioning coaches, as well as health care providers, with additional information when prescribing evidence-based exercise programs to females of any age.

Acknowledgements: We would like to thank Dr. Ferlic for providing funding for this project. We would not be able to complete this work without his generous support.