Abstract
ckground: This study determined whether the knee and ankle muscle extensor forces increase when running with a body-borne load and whether these forces differ between the sexes. Methods: Thirty-six (twenty male and sixteen female) adults had the knee and ankle extensor force quanti ed when running 4.0 m/s with four body-borne loads (20, 25, 30, and 35 kg). Peak normalized (BW) and unnormalized (N) extensor muscle force, relative effort, and joint angle and angular velocity at peak muscle force for both the ankle and the knee were submitted to a mixed model ANOVA. Results: Signi cant load by sex interactions for knee unnormalized extensor force (p= 0.025) and relative effort (p= 0.040) were observed, as males exhibited greater knee muscle force and effort than females and increased their muscle force and effort with additional load. Males also exhibited greater ankle normalized and unnormalized extensor force (p= 0.004,p< 0.001) and knee unnormalized force than females (p= 0.005). The load increased the normalized ankle and knee muscle force (p< 0.001,p= 0.030) and relative effort (p< 0.001,p= 0.044) and the unnormalized knee muscle force (p= 0.009). Conclusion: Running with a load requires greater knee and ankle extensor force, but males exhibited greater increases in muscle force, particularly at the knee, than females. Keywords:load carriage;
force than females (p= 0.005). The load increased the normalized ankle and knee muscle force (p< 0.001,p= 0.030) and relative effort (p< 0.001,p= 0.044) and the unnormalized knee muscle force (p= 0.009). Conclusion: Running with a load requires greater knee and ankle extensor force, but males exhibited greater increases in muscle force, particularly at the knee, than females. Keywords:load carriage; musculoskeletal injury; muscle force; sex dimorphism; biomechanics 1. Introduction Running with a body-borne load is a common service member training and operational activity. During these activities, service members routinely run with heavy body-borne loads (often greater than 20 kg) that reportedly alter lower limb biomechanics, increasing the incidence of musculoskeletal injury [1,2]. In fact, approximately 75% of service members sustain an overuse musculoskeletal injury during training or other occupational activi- ties [3]. Most military-related overuse injuries are sustained in the lower limb, with over 80% occurring at the knee or ankle [4]. Treating the bone and/or soft-tissue damage of a knee or ankle musculoskeletal injury is expensive, yet often fails to prevent re-injury and medical discharge for the service member [5,6]. Considering knee and ankle musculoskeletal injury (and likely re-injury) may pose the greatest threat to military readiness, particularly for female service members, who are twice as likely to suffer a musculoskeletal injury than their male counterparts [7], it is imperative to understand the explicit changes in lower limb biomechanics that increase injury risk when running with heavy body-borne load [8]. When running with heavy military body-borne load, individuals reportedly alter the lower limb biomechanics, which may elevate injury risk of the passive knee and ankle structures. To run with loads greater than 20 kg, individuals produce larger, faster vertical ground reaction forces (vGRFs) that require increases in knee and ankle torsional stiffness up to 19% and 6% [9,10]. While these large increases in joint stiffness may be necessary to maintain stability and prevent limb collapse when running with heavy load [11], it may further increase injury risk [12]. A stiffer joint, for instance, may limit exion, lead- ing to decreased energy absorption by the musculature, allowing greater transmission of
ankle torsional stiffness up to 19% and 6% [9,10]. While these large increases in joint stiffness may be necessary to maintain stability and prevent limb collapse when running with heavy load [11], it may further increase injury risk [12]. A stiffer joint, for instance, may limit exion, lead- ing to decreased energy absorption by the musculature, allowing greater transmission of vGRFs to the musculoskeletal system and elevating injury risk [13,14]. Considering Biomechanics2022,2, 421430.
Biomechanics2022,2 422 individuals typically increase lower limb exion moments when running with load, the larger vGRFs may also stem from greater force contributions from the knee and ankle support musculature [15,16]. During locomotion, the knee musculature must generate suf cient force to prevent limb collapse, while the ankle musculature must produce force to propel the center of mass forward [16,17]. However, these muscle force demands may depend on the speed, length, and mode of locomotion [18]. Individuals produce greater knee and ankle ex- tensor muscle force with each incremental increase in walk speed (from 5% to +5% of normal), and the ankle extensors operate at greater relative effort (typically near 100% of maximal capacity) than the knee extensors (between 63% and 72%, respectively) at faster locomotor speeds [1921]. Considering running with body-borne load increases knee and ankle muscular activity and peak joint moments, it may also require greater knee and ankle muscle force to maintain limb stability and forward propulsion [22,23]. Substantial increases in knee and ankle muscle force, however, may increase the likelihood of lower limb musculoskeletal injury by placing extra stress onto the musculoskeletal system [24]. Although running with heavy body-borne load requires greater knee and ankle muscle activity and joint moments, it is currently unknown whether individuals exhibit similar increases in muscle force. Female service members are typically smaller and weaker than their male counterparts, which may lead to larger changes in the lower limb biomechanics and elevated injury risk when running with heavy body-borne load [25,26]. Brown et al., for instance, recently reported females adopted a 15% stiffer knee and used approximately 5% less peak knee exion than the male participants to run with heavy loads [9]. Considering that with each 1 Nm/deg increase in knee stiffness, recreational runners are 18% more likely to suffer musculoskeletal injury, and an extended knee may increase the likelihood of soft- tissue injury, females' knee biomechanics may contribute to their high rate of injury [27,28]. However, it is unclear if females exhibit dimorphism in knee and ankle muscle force to run with heavy, military body-borne loads. Therefore, the purpose of
stiffness, recreational runners are 18% more likely to suffer musculoskeletal injury, and an extended knee may increase the likelihood of soft- tissue injury, females' knee biomechanics may contribute to their high rate of injury [27,28]. However, it is unclear if females exhibit dimorphism in knee and ankle muscle force to run with heavy, military body-borne loads. Therefore, the purpose of this study was to: (1) determine whether relative knee and ankle muscle force increase when running with body-borne load and (2) whether a sex dimorphism in knee and ankle muscle force exists for running with load. We hypothesized that knee, but not ankle, relative effort would signi cantly increase with each incremental addition of a body-borne load, and females would exhibit greater knee and ankle relative muscle force than males. 2. Materials and Methods 2.1. Participants We recruited 36 (16 female and 20 male) adults between 18 and 40 years old to participate (Table). Each potential participant was physically active (determined as 560 on the physical activity readiness questionnaire) and self-reported the ability to carry up to 75 pounds (~34 kg) [29], but participants were excluded if they reported: (1) a neurological disorder; (2) a history of previous back or lower extremity surgery; (3) pain in the back or lower extremity prior to testing; (4) and/or a recent back or lower extremity injury (previous six months). Research approval was obtained from the local IRB, and written informed consent was provided to participate. Table 1.Mean (SD) age, height, and weight for the male and female participants. N Age (Years) Height (m) a Weight (kg) a Males 20 21.5 (2.8) 1.8 (0.1) 82.6 (11.6) Females 16 21.2 (2.8) 1.7 (0.1) 65.0 (11.5) a Denotes a signi cant main effect of sex. 2.2. Load Con gurations Each participant completed an over-ground running task with four different body- borne loads (20, 25, 30, or 35 kg). For all body-borne loads, participants wore spandex top
Load Con gurations Each participant completed an over-ground running task with four different body- borne loads (20, 25, 30, or 35 kg). For all body-borne loads, participants wore spandex top
Biomechanics2022,2 423 and shorts, weighted vest (Box, WeightVest.com, Rexburg, ID, USA), and standard issue military helmet (ACH), as well as carried a mock military weapon (M16) (Figure). Using 1 kg weights, the vest weight was systematically adjusted to apply the load necessary for each condition. The vest was weighed prior to testing to ensure only loads +/ 2% of the target were applied. To minimize the effects of fatigue, testing with each load was separated by at least 24 h. To randomize and counter balance testing, the load testing order was assigned to each participant using a 4 4 Latin Square design prior to data collection.Biomechanics 2022, 3, FOR PEER REVIEW 3 2.2. Load Configurations Each participant completed an over-ground running task with four different body- borne loads (20, 25, 30, or 35 kg). For all body-borne loads, participants wore spandex top and shorts, weighted vest (Box, WeightVest.com, Rexburg, ID, USA), and standard issue military helmet (ACH), as well as carried a mock military weapon (M16) (Figure 1). Using 1 kg weights, the vest weight was systematically adjusted to apply the load necessary for each condition. The vest was weighed prior to testing to ensure only loads +/− 2% of the target were applied. To minimize the effects of fatigue, testing with each load was sepa- rated by at least 24 h. To randomize and counter balance testing, the load testing order was assigned to each participant using a 4 × 4 Latin Square design prior to data collection. Figure 1. Depicts the equipment configuration for each load condition (20 kg, 25 kg, 30 kg, or 35 kg). For each condition, participants were outfitted with a helmet, mock weapon, and weighted vest, which was systematically adjusted to provide the load necessary for each condition. 2.3. Over-Ground Walk Task During data collection, participants had three-dimensional (3D) lower limb joint bio- mechanics data recorded during an over-ground running task. The running task required participants to run approximately 10 m at 4 m/s ± 5% through the motion capture volume. For each run, a single force platform (2400 Hz, OR6, AMTI, Watertown, MA,
necessary for each condition. 2.3. Over-Ground Walk Task During data collection, participants had three-dimensional (3D) lower limb joint bio- mechanics data recorded during an over-ground running task. The running task required participants to run approximately 10 m at 4 m/s ± 5% through the motion capture volume. For each run, a single force platform (2400 Hz, OR6, AMTI, Watertown, MA, USA) and eight high-speed optical cameras (240 Hz, MXF20, Vicon, Oxford, UK) recorded biome- chanics data. During each run, two sets of infrared timing gates (TF100, TracTronix, Lenexa, KS, USA) were used to quantify the running speed. Participants completed three successful trials of the running task. A successful trial required participants to run at the correct speed and only contact the force platform with their dominant limb, which was determined as the foot they prefer to kick a ball with. To minimize the fatigue during testing, participants were given water and provided adequate rest between each trial. 2.4. Biomechanical Analysis For each successful run trial, lower limb biomechanics were quantified from the 3D coordinates of 34 retro-reflective markers using Visual 3D (v6.00, C-Motion, Rockville, MD), in accordance with previous work [30]. For processing, synchronous 3D GRF and marker trajectories were low-pass filtered using a fourth order Butterworth filter (12 Hz). Then, Visual 3D processed the filtered marker trajectories to solve sagittal plane lower Figure 1. Depicts the equipment con guration for each load condition (20 kg, 25 kg, 30 kg, or 35 kg). For each condition, participants were out tted with a helmet, mock weapon, and weighted vest, which was systematically adjusted to provide the load necessary for each condition. 2.3. Over-Ground Walk Task During data collection, participants had three-dimensional (3D) lower limb joint biomechanics data recorded during an over-ground running task. The running task re- quired participants to run approximately 10 m at 4 m/s 5% through the motion capture volume. For each run, a single force platform (2400 Hz, OR6, AMTI, Watertown, MA, USA) and eight high-speed optical cameras (240 Hz, MXF20, Vicon, Oxford, UK) recorded biomechanics data. During each run, two sets of infrared timing gates (TF100,
running task. The running task re- quired participants to run approximately 10 m at 4 m/s 5% through the motion capture volume. For each run, a single force platform (2400 Hz, OR6, AMTI, Watertown, MA, USA) and eight high-speed optical cameras (240 Hz, MXF20, Vicon, Oxford, UK) recorded biomechanics data. During each run, two sets of infrared timing gates (TF100, TracTronix, Lenexa, KS, USA) were used to quantify the running speed. Participants completed three successful trials of the running task. A successful trial required participants to run at the correct speed and only contact the force platform with their dominant limb, which was determined as the foot they prefer to kick a ball with. To minimize the fatigue during testing, participants were given water and provided adequate rest between each trial. 2.4. Biomechanical Analysis For each successful run trial, lower limb biomechanics were quanti ed from the 3D coordinates of 34 retro-re ective markers using Visual 3D (v6.00, C-Motion, Rockville, MD, USA), in accordance with previous work [30]. For processing, synchronous 3D GRF and marker trajectories were low-pass ltered using a fourth order Butterworth lter (12 Hz). Then, Visual 3D processed the ltered marker trajectories to solve sagittal plane lower limb joint rotations using a joint coordinate system approach [31]. To obtain external sagittal plane lower limb joint moments, the ltered kinematic and GRF data were submitted to standard inverse dynamics analyses, with inertial properties established by Dempster [32]. The external joint moments were normalized to subject mass (kg) and
Biomechanics2022,2 424 height (m). All biomechanical data were normalized from 0% to 100% of the stance phase, which was de ned as heel strike to toe-off ( rst instance GRF exceeded and fell below 10 N, respectively). A custom-written MATLAB (Mathworks, Natick, MA) code calculated the muscle force for the ankle and knee extensors, according to a previous work [33,34]. For both the ankle and the knee, sagittal plane joint angle (x ankleand x knee) and net unnormalized joint moments (M ankleand M knee) were submitted to the muscle force analysis. First, at each joint, the effective extensor moment arm (L ankleand L knee) was calculated as a function of the joint exion angle using the nonlinear equation (Equations (1) and (3)), and then, the extensor muscle force (F ankleand F knee) was calculated by dividing the net joint moment by the effective extensor moment arm (Equations (2) and (4)). L ankle= 2.606E 4 x ankle 2 + 0.08297 x ankle 0.5910 (1) F ankle= M ankle/L ankle (2) L knee= 8.0 E 5 x knee 3 0.013 x knee 2 + 0.28 x knee+ 0.046 (3) F knee= M knee/L knee (4) The ankle and knee muscle forces were calculated in Newtons as well as normalized to participant BW. The relative effort of the ankle and the knee extensor musculature was also determined by normalizing the peak ankle and knee extensor muscle force exhibited with each load (20 kg, 25 kg, 30 kg, and 35 kg) to the peak muscle force produced at the respective joint with the 35 kg load condition. 2.5. Statistical Analysis The dependent variables submitted for analysis included normalized (BW) and unnor- malized (N) extensor muscle force, relative effort, and sagittal plane joint angle and angular velocity at peak muscle force for both the ankle and the knee. Each dependent variable was averaged across three successful run trials to create a participant-based mean and then submitted to a mixed model analysis of variance to test the main effects and interaction between the body-borne load (20, 25, 30, and 35 kg) and sex (female and male).
angular velocity at peak muscle force for both the ankle and the knee. Each dependent variable was averaged across three successful run trials to create a participant-based mean and then submitted to a mixed model analysis of variance to test the main effects and interaction between the body-borne load (20, 25, 30, and 35 kg) and sex (female and male). Signi cant interactions were submitted to a simple effects analysis, and a Bonferroni correction was used for multiple comparisons. Independent t-tests were used to compare the demograph- ics between the sexes. All statistical analysis was performed using the SPSS v25 software (IBM, Amonk, NY, USA), with an alpha level of 0.05. 3. Results The males were taller (p< 0.001) and heavier (p< 0.001) but not older (p= 0.690) than females (Table). The ANOVA revealed signi cant load by sex interactions for unnormalized extensor force (p= 0.025) and relative effort (p= 0.040) at the knee (Table). The males increased the knee extensor force and relative effort with the 25 and 30 compared to the 20 kg load (p< 0.023,p< 0.028), while the females exhibited no signi cant difference in the extensor force or relative effort between any loads (p> 0.05). Compared to females, males exhibited greater knee extensor force with the 25, 30, and 35 kg loads (p< 0.048) and knee relative effort with the 30 kg load (p= 0.030). The males exhibited greater ankle normalized and unnormalized extensor force (p= 0.004,p< 0.001) but only greater knee unnormalized force than the females (p= 0.005) (Table). At the peak muscle force, the males exhibited less knee exion (p= 0.002) but greater knee exion angular velocity (p= 0.001) than the females, while the females exhibited greater ankle dorsi exion than the males (p= 0.018) (Table). Sex had no impact on the ankle or knee relative effort (p> 0.05).
Biomechanics2022,2 425 Table 2. Mean (SD) ankle and knee extensor force for male and female participants with each body-borne load (20, 25, 30, and 35 kg). 20 kg 25 kg 30 kg 35 kg Male Female Male Female Male Female Male Female Extensor Force (N) Ankle b 2018.5 (570.1) 1410.6 (327.2) 1999.6 (387.0) 1429.0 (320.5) 2033.9 (427.7) 1454.3 (322.9) 2134.2 (454.8) 1522.6 (291.0) Knee a,b,c 3346.6 (843.8) 2842.7 (625.4) 3736.2 (900.6) 2880.1 (820.8) 3921.2 (888.0) 2912.5 (731.0) 3606.0 (843.4) 3068.4 (691.8) Extensor Force (BW) Ankle b,c 5.46 (0.85) 4.77 (0.69) 5.49 (0.64) 4.84 (0.64) 5.59 (0.69) 4.90 (0.82) 5.88 (0.77) 5.12 (0.81) Knee c 10.66 (1.88) 10.50 (1.16) 11.61 (1.91) 10.53 (1.59) 11.94 (1.39) 10.65 (1.69) 11.18 (1.72) 10.86 (1.30) a Denotes a signi cant load by sex interaction. b Denotes a signi cant main effect of sex. c Denotes a signi cant main effect of load.Biomechanics 2022, 3, FOR PEER REVIEW 5 Figure 2. Mean stance phase (0–100%) ankle (A,C) and knee extensor muscle force (B,D) with each body-borne load (20 kg, 25 kg, 30 kg, and 35 kg). Figure 3. Mean ± SD ankle (A) and knee (B) relative effort (%) for males and females with each body- borne load (20 kg, 25 kg, 30 kg, and 35 kg). Table 2. Mean (SD) ankle and knee extensor force for male and female participants with each body- borne load (20, 25, 30, and 35 kg). 20 kg 25 kg 30 kg 35 kg Male Female Male Female Male Female Male Female Extensor Force (N) Ankle b 2018.5 (570.1) 1410.6 (327.2) 1999.6 (387.0) 1429.0 (320.5) 2033.9 (427.7) 1454.3 (322.9) 2134.2 (454.8) 1522.6 (291.0) Knee a,b,c 3346.6 (843.8) 2842.7 (625.4) 3736.2 (900.6) 2880.1 (820.8) 3921.2 (888.0) 2912.5 (731.0) 3606.0 (843.4) 3068.4 (691.8) Extensor Force (BW) Ankle b,c 5.46 (0.85) 4.77 (0.69) 5.49 (0.64) 4.84 (0.64) 5.59 (0.69) 4.90 (0.82) 5.88 (0.77) 5.12 (0.81) Knee c 10.66 (1.88) 10.50 (1.16) 11.61 (1.91) 10.53 (1.59) 11.94 (1.39) 10.65 (1.69) 11.18 (1.72) 10.86 (1.30) a Denotes a significant load by sex interaction. b Denotes a significant main effect of sex. c Denotes a significant
Description
The study examines the impact of sex on muscle forces during loaded running.