Abstract
Background:
Soldiers that suffer a service-related knee musculoskeletal injury routinely develop joint osteoarthritis. Knee osteoarthritis is a substantial and costly problem among soldiers, yet it is unknown how body borne load and duration of walking impact knee adduction biomechanics linked to progression and severity of osteoarthritis.
Research Question:
This study determined the adaptations in magnitude and variability of knee adduction joint angle (KAA) and moment (KAM) during prolonged walking with body borne load.
Methods:
Thirteen recreationally active participants had knee biomechanics quantified while walking over-ground for 60-minutes at 1.3 m/s with three body borne loads (0, 15, and 30 kg). Magnitude and variability of KAA and KAM measures were quantified and submitted to a RM ANOVA to test the main effect and interactions between load ( 0, 15 and 30 kg) and time ( 0, 15, 30, 45 and 60 minutes ).
Results:
Body borne load increased peak KAM (p<0.001), whereas time increased peak and range of KAA (both: p<0.001). Specifically, peak KAM increased with each addition of body borne load (all: p<0.025), and peak and range of KAA increased after 30 minutes of walking (both: p<0.040). Neither body borne load, nor time had a significant effect on KAA or KAM variability (both: p>0.05).
Significance:
Prolonged walking with heavy body borne load increased knee adduction biomechanics related to osteoarthritis. Adding heavy body borne load increased in peak KAM whereas duration of walking increased KAA, knee biomechanics that may increase loading of the medial knee joint compartment and risk of OA at the joint.
Keywords: load carriage, Variability, osteoarthritis, injury prevention, musculoskeletal disease
Introduction
Annually, the U.S. Army spends more than $400 million treating the more than 50% of soldiers who suffer a service-related musculoskeletal injury[1]. A majority of service-related musculoskeletal injuries occur at the knee during basic and advanced training[1,2]. During military training, soldiers are required to walk for long periods of time (more than 60 minutes) with heavy body borne loads (routinely greater than 20 kg), which is reported to be a substantial source of musculoskeletal injury risk, particularly at the knee[3]. Considering knee osteoarthritis (OA), a degenerative musculoskeletal disease, is a leading cause of medical discharge and long term disability, it is imperative to understand if walking with heavy body borne load produces knee biomechanics that increase likelihood of suffering the joint injuries that are a precursor to OA development and/or accelerate its progression[4].
Knee OA is characterized by degeneration (i.e., wear and tear) of the joint’s articular surfaces from the repetitive application of abnormal load during weight-bearing activities, such as locomotion[5]. Knee OA is most prevalent in the medial joint compartment, and results from compressive loads during locomotion that are greater on the medial than the lateral joint compartment. The external knee adduction moment (KAM) is a correlate of medial knee joint compartment loading that is related to knee OA severity and progression and indeed patients with radiographically confirmed OA exhibit up to 30% higher peak KAM than healthy controls[5,6]. Each 1% increase in KAM, in fact, results in a six-fold increase in the progression of knee OA[7]. Moreover, external KAM may further push the knee into varus, increasing peak knee adduction angle (KAA). Peak KAA exhibited during locomotion is purported to be up to 4 degrees greater in patients with radiographically confirmed OA than healthy controls[8]. But it is currently unclear whether prolonged walking with body borne load, as commonly done during military training, produces significant increases in knee adduction biomechanics (i.e., KAA and KAM) related to OA development.
During locomotion, the addition of heavy, military-relevant body borne load results in specific lower limb biomechanics that are associated with the presence and progression of OA. Walking with body borne load (between 8 and 32 kg) increases peak vertical ground reaction forces (GRFs) between 10% and 25%[9]. These elevated GRFs are reported to increase knee joint and soft tissue loads (i.e. articular contact forces and bone stresses/strains), potentially placing abnormal loads on the medial knee joint compartment[10]. To compensate for the elevated GRFs, individuals exhibit lower limb biomechanical adaptations, specifically at the knee. When walking with body borne load, individuals increase knee flexion angle during stance[11]. The flexed knee helps the lower limb musculature attenuate the elevated GRFs, but may contribute to significant increases in lower limb joint moments evident when walking with load. In fact, individuals reportedly increase knee flexion moments up to 36% when walking with body borne load[11]. In addition, individuals walking with loads equivalent to 20% body weight reportedly experience elevated peak KAM, however, it is unclear whether walking for extended periods of time with heavy military loads produces similar or additional increases in knee adduction biomechanics[12].
Prolonged walking with body borne load may lead to increases in knee adduction biomechanics. Peak vertical GRFs are reported to increase approximately 2% every 15 minutes throughout a 60-minute walk task with body borne load[13]. This continual rise in vertical GRFs may require ever-increasing muscle forces to provide adequate joint stabilization, accelerating fatigue-related muscular weakness during prolonged loaded walking. The muscle weakness associated with prolonged load walking may limit the lower limb musculature’s ability to attenuate repetitive loading, and present as significant adaptations of knee biomechanics[13]. Specifically, individuals are reported to increase knee flexion range of motion approximately 5% following fatiguing exercise, but did not exhibit similar increases in knee adduction range of motion following the same protocol; and thus, it is currently unclear if increases in knee adduction are evident during prolonged loaded walking[14]. Additionally, fatigue-related muscular weakness may also impact variability of lower limb biomechanics increasing musculoskeletal injury and disease risk. During walking, variability of knee joint biomechanics, in particular frontal plane joint angles, reportedly increase following exercise-induced fatigue, while variability of spatiotemporal gait parameters decrease with the addition of body borne load[15,16]. Alterations in variability of gait measurements in general, and knee adduction motion specifically, may concentrate knee joint forces on specific soft tissues, such as those found in the medial joint compartment, and increase risk of musculoskeletal injury and disease. Yet to date, it is not known whether prolonged walking with heavy body borne load impacts variability of knee adduction biomechanics and risk of musculoskeletal disease.
Considering knee OA is a leading cause of medical discharge for soldiers, it is imperative to determine whether prolonged walking with heavy military relevant body borne loads produces magnitude and variability of KAA and KAM related to OA development[17]. With that in mind, the purpose of this study was to determine the adaptations in knee adduction exhibited during prolonged walking with body borne loads (0, 15 and 30 kg) commonly worn during military training. It was hypothesized that the magnitude of KAA and KAM would increase with the addition of body borne load and duration of walking, while variability of KAA and KAM would decrease with the addition of body borne load and increase with duration of walking.
Methods
We recruited 13 participants (9 male/4 female: 23.8±3.4yrs, 1.8±0.1m, 72.0±12.6kg) because power analysis of KAM data collected when piloting the prolonged walk task indicated that was the minimum number of participants to achieve 80% statistical power with an alpha level of 0.05, at the anticipated effect size of 0.375. Each potential participant was between 18 and 40 years, and self-reported being recreationally active (determined as ≥ 560 on the physical activity readiness questionnaire) and the ability to safely walk with up to 75 pounds (34 kg). Participants were excluded if they reported: (1) history of surgery in the low back or lower extremity (hip, knee and ankle); (2) pain and/or injuries located in the back or lower extremity (hip, knee and ankle) in the last six months; (3) any known neurological disorders; and/or (4) were currently pregnant. Research approval was obtained from the local Institutional Review Board and all participants provided written informed consent prior to testing.
Each participant performed three test sessions. During each test session, participants completed a prolonged walk task with a different body borne load (0 kg, 15 kg, and 30 kg) (Figure 1). For each body borne load, participants wore spandex shorts and shirt, and their own athletic footwear. For the 15 kg and 30 kg loads, participants also wore a weighted vest (V-MAX, WeightVest.com, Rexburg, ID, USA) that was systematically adjusted with 1 kg weights to provide the necessary load for each condition. Prior to testing, each load configuration was weighed and only loads within 2% of the target were accepted. All test sessions were separated by a minimum of 24 hours to minimize fatigue and likelihood of injury. To avoid bias and confounding data, a 3 x 3 Latin square approach was used to randomly assign the test sequence prior to testing.
Figure 1.
Depicts the equipment worn for the 15 kg and 30 kg load conditions. For the 15 kg and 30 kg load conditions, participants wore a weighted vest that was systematically adjusted to apply the necessary load.
During each test session, participants had three-dimensional (3D) lower limb (hip, knee and ankle) biomechanical data recorded during the prolonged walk task. Specifically, GRF data (2400 Hz) was collected from one in-ground force platform (AMTI OR6 Series, Advanced Mechanical Technology Inc., Watertown, MA), while eight high-speed (240 Hz) optical cameras (MXF20, Vicon Motion Systems LTD, Oxford, UK) recorded lower limb motion data.
The prolonged walk task required each participant to walk over-ground at 1.3 m/s continuously for 60 minutes on a 390-meter walking course (included both indoor and outdoor sections) (Appendix A & B). Each participant started indoors and completed one lap of the walk course every five minutes (minutes 0, 5, 10…60). For the indoor portion, participants walked 1.3 m/s ± 5% three times through the motion capture volume. For each walk trial, two sets of infrared timing gates (TracTronix TF100, TracTronix Wireless Timing Systems, Lenexa, KS), placed four meters apart in the capture volume recorded walk speed. Each trial was noted as either successful or unsuccessful. For a successful trial, the participant walked the required speed and contacted the force platform with only his or her dominant limb during a single stride. Additionally, each participant reported their rating of perceived exertion on the Borg scale (6–20) after each walk trial (Appendix C). After completing the three walk trials (indoor portion), participants exited the lab and walked over a small grassy area and footpath (outdoor portion), before reentering the lab to immediately complete another lap of the indoor portion. Throughout the walk task, participants walked continuously at 1.3 m/s, as this a typical march speed, and to help maintain the correct walk speed each participant stepped to a metronome (Planet Waves PW-MT-01, D’Addario, Famingdale, NY) set to their predetermined cadence throughout[18].
During each walk trial, 3D coordinates of 34 retro-reflective markers affixed to bony landmarks, as well as four virtual markers digitized on the trunk were processed to obtain trunk and lower limb biomechanics data. After each marker was secure, participants stood in anatomical position for a static recording that was used to create a kinematic model that consisted of trunk, pelvis and bilateral thigh, shank and foot segments, and 27 degrees of freedom in Visual 3D (v6, C-Motion, Inc, Germantown, MD, USA). Each model segment was assigned a local coordinate system and three orthogonal axes (x, y and z), according to Seymore et al[19].
The synchronous GRF and marker trajectory data recorded during each trial were low pass filtered using a fourth-order Butterworth filter (12 Hz). The filtered marker trajectories were then processed in Visual 3D to calculate knee rotations that were expressed with respect to each participant’s static pose using a joint coordinate systems approach. Standard inverse-dynamics analyses used the filtered kinematic and GRF data to obtain 3D forces and moments at the knee, with segment inertial properties defined according to Dempster et al[20]. Knee joint moments were reported as external and normalized by body mass (kg) and height (m). All biomechanical data was normalized from 0% to 100% of stance phase and resampled to 1% increments (n = 101). Stance phase was identified as heel strike to toe-off and defined as the moment when GRF first exceeded and fell below 10 N, respectively.
Predefined knee biomechanics related to OA development were submitted to statistical analysis. Specifically, the dependent variables included initial contact (IC), peak (between 0%-100% of stance) and range (ROM, peak minus IC) of KAA, and peak KAM (between 0%-100% of stance). Each dependent variable was averaged across two successful trials recorded at each time point (0, 15, 30, 45 and 60 minutes) of the prolonged walk task to create a participant-based mean for each time point. Then, each participant-based mean was submitted to a repeated measures ANOVA to test the main effects of and interaction between load (0, 15 and 30 kg) and time (0, 15, 30, 45 and 60 minutes). Within subject variability (i.e. Coefficient of Variation (CV)) was calculated as the standard deviation of two successful trials divided by the means of those trials (CV= σ/µ *100) for range of KAA and peak KAM, and submitted to a similar repeated measures ANOVA. For analyses where sphericity was significant, the Greenhouse-Geisser correction was applied to the degrees of freedom. Significant interactions were submitted to simple effects analysis and a Bonferroni correction was used for pairwise comparisons. For significant pairwise comparison, effect size was calculated using Cohen’s d[21]. Alpha was set a priori at P<0.05. All statistical analysis was performed using SPSS software (v25 IMB, Armonk, NY, USA).
Results
No significant interactions were observed, and thus only main effects are presented below. Body borne load had a significant effect on peak KAM (p<0.001), but no KAA variable (all: p>0.662) (Figure 2 and Table 1). Peak KAM increased with 30 compared to 15 (p<0.001, d=0.714) and 0 kg (p=0.007, d=1.270) loads, and with the 15 compared to 0 kg load (p=0.025, d=0.493).
Figure 2.
Mean stance phase (0% - 100%) knee adduction angle (A, B) and moment (C, D) quantified with each body borne load (0, 15 and 30 kg) and time point (minute 0, 15, 30, 45 and 60) during the walk task.
Table 1.
Mean (SD) of magnitude and variability for knee adduction angle and moment with each body borne load a minute 0 through 60 of prolonged walk task.
| 0 Min | 15 Min | 30 Min | 45 Min | 60 Min | |||
|---|---|---|---|---|---|---|---|
| Knee Adduction Angle (deg) | IC | 0 kg | −0.78 (0.97) | −0.58 (1.00) | −0.70 (0.88) | −0.67 (0.81) | −0.65 (0.80) |
| 15 kg | −0.69 (0.81) | −0.38 (0.89) | −0.43 (0.90) | −0.17 (1.19) | −0.37 (1.10) | ||
| 30 kg | −0.73 (0.98) | −0.38 (1.06) | −0.47 (1.01) | −0.51 (1.26) | −0.51 (1.02) | ||
| Peak# | 0 kg | 2.87 (1.98) | 3.16 (1.75) | 3.48 (1.87) | 3.54 (2.11) | 3.53 (1.81) | |
| 15 kg | 3.12 (1.92) | 3.64 (2.37) | 3.51 (2.33) | 3.82 (2.40) | 3.62 (2.42) | ||
| 30 kg | 2.96 (1.58) | 3.50 (1.86) | 3.69 (1.85) | 3.68 (1.88) | 3.94 (1.85) | ||
| Range# | 0 kg | 3.64 (2.02) | 3.74 (1.78) | 4.18 (1.85) | 4.21 (2.21) | 4.18 (1.81) | |
| 15 kg | 3.81 (1.52) | 4.02 (2.04) | 3.94 (1.94) | 4.00 (2.06) | 3.69 (1.89) | ||
| 30 kg | 3.69 (1.42) | 3.88 (1.58) | 4.16 (1.65) | 4.18 (1.76) | 4.45 (1.47) | ||
| CV | 0 kg | 12.30 (15.31) | 14.59 (17.48) | 10.45 (7.90) | 9.08 (5.53) | 10.12 (10.51) | |
| 15 kg | 15.10 (15.08) | 7.45 (5.84) | 9.83 (9.34) | 7.56 (6.90) | 8.19 (4.66) | ||
| 30 kg | 8.51 (6.93) | 8.10 (5.98) | 9.57 (7.00) | 9.82 (8.11) | 8.11 (10.59) | ||
| Knee Adduction Moment (N.m/kg.m) | Peak* | 0 kg | −0.35 (0.07) | −0.35 (0.08) | −0.36 (0.08) | −0.36 (0.08) | −0.35 (0.08) |
| 15 kg | −0.40 (0.09) | −0.40 (0.13) | −0.40 (0.10) | −0.41 (0.12) | −0.40 (0.12) | ||
| 30 kg | −0.47 (0.10) | −0.49 (0.12) | −0.48 (0.12) | −0.49 (0.12) | −0.48 (0.13) | ||
| CV | 0 kg | 5.73 (4.41) | 6.28 (7.27) | 6.25 (4.81) | 4.94 (3.45) | 6.02 (4.58) | |
| 15 kg | 10.45 (11.80) | 5.08 (3.05) | 6.83 (3.33) | 4.82 (5.84) | 4.65 (3.60) | ||
| 30 kg | 5.02 (5.01) | 7.20 (8.39) | 4.59 (2.85) | 5.75 (6.20) | 5.34 (2.86) | ||
Denotes a significant (p<0.05) main effect of time.
Denotes a significant (p<0.05) main effect of body borne load.
Time had a significant effect on peak (p<0.001) and range of KAA (p<0.001), but not IC KAA (p=0.083) or peak KAM (p=0.617) (Figure 2 and Table 1). Peak KAA was greater at minutes 30 through 60 compared to minute 0 (all: p<0.005, d>0.301) and at minute 60 compared to minute 15 (p=0.030, d=0.134), while range of KAA was greater at minute 30 (p=0.040, d=0.219) and minute 60 (p=0.020, d=0.237) compared to minute 0.
Neither body borne load, nor time had a significant effect on CV for range KAA (p=0.476; p=0.412) or peak KAM (p=0.645; p=0.485) (Table 1).
Discussion
This study examined whether walking for 60-minutes with military-relevant body borne load (0, 15 and 30 kg) altered magnitude and variability of knee adduction biomechanics related to musculoskeletal injury and disease. Our hypotheses, however, were only partially supported, as magnitude and not variability of knee adduction was impacted by body borne load and walking duration.
Walking with body borne load may produce knee biomechanics that increase the likelihood of developing musculoskeletal injury and disease. In agreement with previous literature, peak KAM increased 0.05 and 0.13 Nm/kgm when walking with the 15 and 30 kg body borne loads compared to the 0 kg load[22]. Increases in the external KAM reportedly load the medial knee joint compartment, and may accelerate the wear and tear of the joint’s articular surfaces that is associated with knee OA. Considering the current participants increased peak KAM approximately 37% with the 30 kg body borne load, which is larger than the 30% increase in peak KAM for patients with radiographically confirmed OA as compared to healthy controls, routine military training activities such as walking with heavy body borne loads, may increase knee biomechanics associated with OA development[6]. Despite large increases in KAM with heavy body borne load, there was not a significant, continual increase in peak KAM throughout the prolonged walk task. Contrary to our hypothesis, the current participants exhibited no significant difference in peak KAM (< 0.01 Nm/kgm) across the walk duration. It may be that military-relevant body borne loads and not walk duration elevate solider risk of knee OA development. Further considering that individuals similarly exhibit no significant difference in peak KAM (0% to 5%) following general fatigue that is typical of prolonged walk tasks, but significant increases in peak KAM following isolated knee extensor fatigue, future research is needed to determine the specific decrements in muscle function that increase knee joint moments related to injury and disease[23,24].
In line with existing literature, walking with body borne load did not significantly increase KAA[22]. The current participants, in fact, exhibited minimal, non-significant increases in IC and peak KAA of up to 0.26º and 0.24º with the 15 kg and 30 kg addition of load respectively.
Yet, in support of our hypothesis, participants exhibited a 24% and 17% increase in peak and range of KAA throughout the prolonged walk task. Substantial increases in KAA are reported to load the medial knee joint compartment and may be implicated in OA development[25]. Individuals with OA reportedly exhibit peak KAA angles between 3º and 7º greater and a range of KAA that is more than 2º greater than healthy controls[26]. Although it was statistically significant, the current participants exhibited minimal 0.5º increases in range of KAA throughout the prolonged walk task, which may be attributed to the concurrent 0.7º increase in peak KAA. Considering the current participants’ peak KAA was approximately 4º towards the end of the 60-minute walk task, which puts their KAA magnitudes in line with radiographically confirmed OA individuals[26], additional research to determine whether longer walk times and/or distances further increase KAA is warranted.
Contrary to our hypothesis, neither body borne load, nor walking duration impacted the variability of knee adduction biomechanics. Sufficient variability of knee biomechanics is essential for adequate joint stability, and considered a mechanism to reduce musculoskeletal injury risk[27]. Although there was no statistical difference, participants decreased the variability in the range of KAA approximately 20% and 30% with the addition of body borne load and walk duration. A reduction in variability may increase OA risk, as patients with OA reportedly decrease knee adduction variability up to 45% in affected limb compared to unaffected limb[28]. Specifically, large decreases in variability may constrain the joint-level response as well as knee neuromuscular function, concentrating joint forces across a small surface area, impairing an individual’s ability to adequately attenuate impact forces and accelerate OA development[29]. As such, future research is needed to determine if either the addition of body borne load and/or walk duration lead to changes in knee biomechanics variability. Considering variability reportedly differs with cadence, current participants may have had natural stride-to-stride variation constrained by stepping to a pre-determined cadence during the walk task[30]. Further study is also warranted to examine whether this impeded knee adduction variability that would have otherwise been present. In addition, as individuals with existing knee injury tend to exhibit greater variability than uninjured controls, it is warranted to determine how deviation from normal variability leads to musculoskeletal injury that is often the precursor to service member knee OA development[17,27].
The chosen prolonged walk task may be a study limitation. Although participants were required to walk 1.3 m/s for 60 minutes (or just shy of three miles), the time and distance may not have been sufficient to induce the muscular weakness routinely encountered during military training. Lidstone et al., however, recently reported substantial increases in GRF and joint angles during similar 60-minute prolonged load carriage task [13], and the current participants’ self-reported perceived exertion was greater with each incremental addition of body borne load and time (Appendix C). Yet, longer walk durations may lead to larger biomechanical changes and warrants further study. Additionally, participants self-reported ability to safely carry 75 pounds, but were not required to have load carriage experience. Participants with load carriage experience may present different knee biomechanics when carrying military-relevant body borne load. Yet, we are currently unaware of differences in lower limb biomechanics for experienced and inexperienced individuals during load carriage. The current body borne load, which was symmetrically applied anteriorly and posteriorly via a weighted vest, and not the asymmetrical distribution of traditional military equipment (e.g. rucksack, body armor, and ammo panel) may be a limitation. Future study is needed to determine if traditional military equipment results in similar knee biomechanics during prolonged walking.
Conclusion
In conclusion, prolonged walking with heavy body borne load altered magnitude, but not variability of knee adduction biomechanics. During the walk task, adding heavy body borne load increased peak KAM, whereas walk duration lead to greater peak and range of KAA. Both the increases in the magnitude of KAM and KAA may increase loading of the medial knee joint compartment, which is associated with greater risk of joint OA.
Supplementary Material
Highlights.
Prolonged walking with heavy loads increase biomechanics related knee osteoarthritis.
Increases in KAM and KAA agree with literature.
Knee adduction variability is not affected by load or walking duration.
Acknowledgements
Funding for this project was provided by MW CTR-IN /NIGMS (Award # 2U54GM104944). We would like to thank Kayla Seymore and Alexis Flock for their assistance with the data processing and design of the testing procedures respectively.
Footnotes
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Conflict of interest statement
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