Effects of Age and Locomotor Demand on Foot Mechanics During Walking

Abstract

Older adults exhibit reductions in push-off power that are often attributed to deficits in plantarflexor force-generating capacity. However, growing evidence suggests that the foot may also contribute to push-off power during walking. Thus, age-related changes in foot structure and function may contribute to altered foot mechanics and ultimately reduced push-off power. The purpose of this paper was to quantify age-related differences in foot mechanical work during walking across a range of speeds and, at a single fixed speed with varied demands for push-off power. 9 young and 10 older adults walked at 1.0, 1.2, and 1.4 m/s, and at 1.2 m/s with an aiding or impeding horizontal pulling force equal to 5% BW. We calculated foot work in Visual3D using a unified deformable foot model, accounting for contributions of structures distal to the hindfoot’s center-of-mass. Older adults walked while performing less positive foot work and more negative net foot work (p<0.05). Further, we found that the effect of age on mechanical work performed by the foot and the ankle-foot complex increased with increased locomotor demand (p<0.05). Our findings suggest that during walking, age-related differences in foot mechanics may contribute to reduced push-off intensity via greater energy loss from distal foot structures, particularly during walking tasks with a greater demand for foot power generation. These findings are the first step in understanding the role of the foot in push-off power deficits in older adults and may serve as a roadmap for developing future low-cost mobility interventions.

Introduction

Older adults often exhibit a substantial reduction in mechanical power during the push-off phase of walking that is freuqently attributed to deficits in mechanical power output from muscle-tendon units spanning the ankle (Cofre et al., 2011; DeVita and Hortobagyi, 2000; Kerrigan et al., 1998). Yet, interventions designed to strengthen the plantarflexor muscles, while effective at increasing their force-generating capacity, have been generally unsuccessful at improving habitual push-off power (Beijersbergen et al., 2013). Those disappointing translational outcomes suggest that age-related declines in plantarflexor mechanical output are not the sole factor contributing to reduced push-off power during walking. Growing evidence alludes to the critical role of the foot as both a stiff lever for push-off and an elastic energy storage and return system for economical locomotion (Farris et al., 2019; Ray and Takahashi, 2020; Takahashi et al., 2017; Zelik and Honert, 2018). Unfortunately, many studies comparing gait biomechanics between young and older adults model the foot as a single rigid segment, neglecting potentially deleterious changes in mechanical contributions from the foot. As we elaborate in more detail below, we suspect that age-related differences in foot mechanical power during the stance phase of walking contribute to reductions in push-off power in older adults. Addressing this gap will advance our mechanistic understanding of age-related reductions in push-off power during walking toward innovative opportunities to preserve and/or restore walking ability in our aging population.

Effective transmission of plantarflexor force during walking is governed by the instantaneous position of the ground reaction force under the foot (Carrier et al., 1994; Cunningham et al., 2010). The human foot acts as a variable lever arm during walking that can modify ankle mechanical advantage as the ground reaction force propagates from heel to toe during each step. Artificially increasing foot stiffness in young adults (by augmenting insole stiffness) can improve mechanical advantage at the ankle, which in turn may reduce fascicle shortening speed and enhance plantarflexor force generation (Ray and Takahashi, 2020; Takahashi et al., 2016). Moreover, there is evidence of structural connections between the Achilles tendon and plantar aponeurosis (Snow et al., 1995; Stecco et al., 2013) that may facilitate active force transmission between these structures (Carlson et al., 2000). Recent evidence also suggests that the plantar intrinsic foot muscles are instrumental in tensioning the plantar surface of the foot (Farris et al., 2020). Accordingly, foot structural properties, such as plantar aponeurosis stiffness and/or plantar intrinsic muscle activation, may influence plantarflexor force transmission with significant implications for walking performance.

In addition to augmenting function of the plantarflexor muscle-tendon units, the foot may contribute independently to push-off power during walking. Mid-tarsal push-off power is substantial during late stance (Bruening et al., 2012; Farris et al., 2020), and increases in response to the demand for push-off power, such as when walking up stairs (DiLiberto et al., 2018), or walking at fast speeds (Eerdekens et al., 2019). Mid-tarsal push-off power may be the result of contributions from plantar intrinsic muscle activation (Farris et al., 2020; Farris et al., 2019), plantar aponeurosis stiffness (Hicks, 1954), and transverse arch morphology (Venkadesan et al., 2020). Mid-tarsal power generation is offset by power absorption at the metatarsalphalangeal (MTP) joints; as the MTP joints extend in late stance, the plantar aponeurosis is stretched, creating a flexor moment and ultimately, net negative foot work. Thus, reduced stiffness and/or an inability to regulate stiffness of foot joints with task demand may result in greater mechanical energy loss via the foot. We note that here and throughout the manuscript when we refer to foot “stiffness” we are describing the aggregate result of passive and active elements in the foot – namely, foot quasi-stiffness. Ultimately, greater energy loss via the foot may require greater ankle mechanical output to maintain the overall mechanical function of the ankle-foot complex.

Age-related changes in foot structure and function are well-documented and may contribute to altered foot mechanics during walking. For example, older adults exhibit reduced non-weight bearing MTP range of motion (Scott et al., 2007) and lower transverse arch height (Carvalho et al., 2015) compared to young adults. Further, age-related reductions in plantar intrinsic muscle strength (Endo et al., 2002; Menz et al., 2006; Mickle et al., 2016) may contribute to reduced foot stiffness during the stance phase of walking, leading to a greater loss of energy via larger foot deformation (Kelly et al., 2018). A recent study by da Silva et al. (2020) found that older adults performed slightly more negative work at faster speeds compared to young adults. However, the foot was modeled as a rigid segment which may not provide a complete characterization of foot power. To our knowledge, there have been no other investigations of age-related changes in patterns of foot or ankle foot power generation during walking. Thus, our current understanding of age-related differences in foot mechanics, and the role of the foot in age-related reductions in ankle push-off power, is incomplete.

The purpose of this study was to quantify age-related differences in foot mechanical power and work performed during walking across a range of speeds and, at a single fixed speed, with varied demands for push-off power – the later via the application of horizontal aiding and impeding forces. The inclusion of horizontal aiding and impeding forces was intended as a targeted approach to manipulate the push-off demands of walking. Indeed, changes in walking speed influence not only the demands for forward propulsion but also those for vertical support. Given the evidence of age-related changes in foot structure and function, we hypothesized that older adults would exhibit less positive foot work and more negative net foot work compared to young adults. By logical extension, we further hypothesized that older adults would display less positive and/or more negative net work performed by the ankle-foot complex compared to young adults. Finally, due to the speed- and task-dependent nature of age-related deficits in push-off work (Cofre et al., 2011; Kerrigan et al., 1998), we hypothesized that the effects of age on foot mechanical work and ankle-foot mechanical work would increase with increasing locomotor demand. To fully characterize the mechanisms responsible for age-related differences in push-off power, we also report associations between foot and ankle mechanical work.

Methods

Participants

9 young (24±3 yrs, 72.1±9.8 kg, 1.8±0.1 m, 5M/4F) and 10 older adults (73±4 yrs, 67.17±6.1 kg, 1.7±0.1 m, 6M/4F) participated in this study. An a priori power analysis suggested that eight participants per age group would have 80% power to detect a 33% reduction in peak ankle power output during walking due to age (DeVita and Hortobagyi, 2000). Prior to participation, subjects were screened and excluded if they reported injury or fracture to the lower-extremity within the previous six months, neurological disorders affecting the lower-extremity, or were currently taking medications that cause dizziness. All subjects provided written informed consent according to the University of North Carolina Biomedical Sciences Institutional Review Board.

Experimental Protocol

We first determined subjects’ self-selected walking speed as the average of three times taken to walk the middle 2 m of a 10 m walkway. Subjects then walked barefoot on an instrumented treadmill (Bertec, Columbus, OH) for five minutes at their self-selected walking speed to acclimate to treadmill walking. Following the acclimation period, subjects walked on the treadmill for one minute each at 1.0 m/s, 1.2 m/s, and 1.4 m/s. Subjects also walked at 1.2 m/s while wearing a waistbelt connected to a motor that prescribed constant aiding or impeding horizontal pulling forces equal to 5% body weight via a custom LabVIEW script. The details of this system and experimental paradigm are summarized in detail previously (Conway and Franz, 2020). Briefly, the aiding and impeding pulling forces are biomechanically similar to walking downhill or uphill, respectively. Conditions were block randomized such that the first block included speeds ≤ 1.2 m/s (to include walking at 1.2 m/s with aiding or impeding forces), and the second block included speeds > 1.2 m/s. Ground reaction forces were measured at 1000 Hz, and 3D positions of 39 retroreflective markers (detailed below) were recorded at 100 Hz using a 16-camera motion capture system (Motion Analysis, Santa Rosa, CA).

Data Processing

Marker position and ground reaction force data were exported to Visual 3D (C-Motion, Germantown, MD) and filtered using a 4^th order low-pass Butterworth filter with cutoff frequencies of 6 Hz and 100 Hz, respectively. A linked-segment model was created for each subject using marker positions from a static standing trial. The ankle joint center was defined as the midpoint between the medial and lateral malleoli markers. Markers placed on the foot included the calcaneus, cuboid bone, navicular bone, and the first and fifth metatarsal heads. Of these, the hindfoot segment was defined using markers on the calcaneus, cuboid, and navicular bones.

Joint angles were calculated using 6DOF pose estimation and a Cardan XYZ rotation sequence (Wu and Cavanagh, 1995). 6DOF iterative Newton-Euler inverse dynamics were used to calculate ankle joint power (Buczek et al., 1994). We calculated foot power using a unified deformable foot model that accounted for contributions of structures distal to the hindfoot’s center of mass (Takahashi and Stanhope, 2013; Takahashi et al., 2017). We calculated ankle-foot power as the sum of ankle power and foot power (Takahashi et al., 2017). Ankle work, foot work, and ankle-foot work were then calculated as the time integral of the respective power curves across the entire stance phase. We also include a supplementary secondary analysis in which we performed these integrations over time periods corresponding to push-off, single support, and collision phases of gait, using individual leg GRF data. The push-off phase was defined by the period of double limb support in early stance, single support was defined by the period when only the right foot was on the groud in midstance, and collision was defined by the period of double limb support in late stance. Supplemental document 1 includes details of the statistical analysis, results, and figures.

Statistical Analysis

These data were part of a larger study that placed ultrasound probes on the right calf and ankle. As such, we included outcomes derived only from the unencumbered left leg for our analyses. Eight strides from the left leg were averaged to produce one representative stride for each subject per condition. SPSS was used for statistical analysis. There were no missing data points. Assumption of normality for primary outcome variables was tested and met using using a combination of the Shapiro-Wilk test, and skewness and kurtosis statistics. In cases in which the assumption of normality was not met using results of the Shapiro-Wilk test, we examined the skewness and kurtosis data to confirm that normality was a reasonable assumption for these variables. Two mixed factor ANOVAs tested for significant effects of and interactions between age and either: (i) speed (W1.0, W1.2, W1.4 m/s) or (ii) horizontal pulling force (W1.2, aiding, impeding) on foot work, ankle work, and ankle-foot work. When a significant main effect or interaction was found, Fisher’s least squares difference (LSD) post hoc t-tests compared differences due to age at each speed or horizontal pulling force. Pearson’s correlation coefficients were used to determine the associations between net foot and ankle work in each condition. We defined significance using an alpha level of 0.05 for all comparisons. Partial eta squared (${\eta }_P^2$) determined the magnitude of the interaction and main effect sizes and Hedge’s g determined effect sizes for pairwise comparisons (Fritz et al., 2012). Values of g>0.20, 0.50, and 0.80 indicated small, moderate, and large effects, respectively (Cohen, 1988).

Results

Age×Speed interactions over the stance phase

We found an age×speed interaction for positive foot work (F_2,34=3.66, p=0.04, ${\eta }_P^2$=0.18) and net (F_2,34=4.97, p=0.01, ${\eta }_P^2$=0.23), with significant main effects of age (Positive: F_1,17=7.24, p=0.02, ${\eta }_P^2$=0.30; Net: F_1,17=8.27, p=0.01, ${\eta }_P^2$=0.33) and speed (Positive: F_2,34=18.20, p<0.001, ${\eta }_P^2$=0.52; Net: F_2,34=6.98, p=0.003, ${\eta }_P^2$=0.29). We did not observe an age×speed interaction (F_2,34=2.77, p=0.07, ${\eta }_P^2$=0.14) or a significant main effect of age (F_1,17=4.06, p=0.06, ${\eta }_P^2$=0.19) on ankle-foot work, but we did observe a significant main effect of speed (F_2,34=7.35, p=0.002, ${\eta }_P^2$=0.30). Older adults performed less positive foot work than young adults for the W1.0 and W1.4 conditions. Compared to young adults, older adults also performed more negative net foot work at all walking speeds and more negative net ankle-foot work for the W1.4 condition. Young and older adults performed similar positive and net ankle work across all speeds (Table 1, Fig. 1).

Table 1.

Summary statistics and effect sizes for pairwise comparisons of joint work across speeds

		Ankle work (J/kg)		Foot Work (J/Kg)			Ankle-Foot Work (J/kg)
		Pos	Net	Pos	Neg	Net	Net
W1.0	Young	0.196 ± 0.045*	0.093 ± 0.076*	0.080 ± 0.159*	−0.141 ± 0.029*	−0.061 ± 0.037	−0.002 ± 0.049*
	Older	0.218 ± 0.078	0.060 ± 0.052	0.060 ± 0.230*	−0.183 ± 0.050*	−0.123 ± 0.057	−0.030 ± 0.060
	p (g)	0.454(0.34)	0.278(0.51)	0.046(0.10)	0.040(1.01)	0.013(1.28)	0.283(0.51)
Aid	Young	0.167 ± 0.029*	−0.054 ± 0.047*	0.089 ± 0.019	−0.204 ± 0.037*	−0.115 ± 0.046*	−0.169 ± 0.068*
	Older	0.165 ± 0.061*	−0.028 ± 0.074*	0.064 ± 0.014*	−0.233 ± 0.071	−0.170 ± 0.076	−0.198 ± 0.059*
	p (g)	0.937(0.04)	0.364(0.41)	0.006(1.51)	0.275(0.50)	0.074(0.86)	0.344(0.46)
W1.2	Young	0.236 ± 0.056	0.101 ± 0.057	0.100 ± 0.280	−0.176 ± 0.037	−0.076 ± 0.050	0.025 ± 0.044
	Older	0.247 ± 0.062	0.117 ± 0.058	0.080 ± 0.029	−0.212 ± 0.057	−0.133 ± 0.057	−0.016 ± 0.059
	p (g)	0.668(0.19)	0.547(0.28)	0.137(0.10)	0.113(0.74)	0.034(1.06)	0.105(0.78)
Impede	Young	0.363 ± 0.059*	0.277 ± 0.068*	0.135 ± 0.031*	−0.157 ± 0.052	−0.023 ± 0.065*	0.255 ± 0.042*
	Older	0.293 ± 0.084	0.206 ± 0.085*	0.080 ± 0.037	−0.169 ± 0.048*	−0.089 ± 0.067*	0.117 ± 0.077*
	p (g)	0.051(0.95)	0.059(0.92)	0.003(1.60)	0.063(0.24)	0.043(1.00)	<0.001(2.19)
W1.4	Young	0.276 ± 0.071	0.130 ± 0.078	0.122 ± 0.031*	−0.194 ± 0.061	−0.071 ± 0.079	0.059 ± 0.057
	Older	0.299 ± 0.080*	0.166 ± 0.090*	0.078 ± 0.026	−0.259 ± 0.064*	−0.181 ± 0.079*	−0.015 ± 0.067
	p (g)	0.530(0.30)	0.365(0.43)	0.004(1.55)	0.036(1.04)	0.008(1.39)	0.020(1.18)

Summary statistics shown are mean ± SD, significant age group differences are shown in bold (p < 0.05)

^*indicates a within-group speed/horizontal pulling force difference compared to W1.2 (p <0.05).

Figure 1.

A) Group mean sagittal plane ankle (top), foot (middle), and ankle-foot (bottom) power for young (black) and older (gray) adults walking at 1.0 m/s (W1.0), 1.2 m/s (W1.2), and 1.4 m/s (W1.4). The stride begins and ends at heel strike. Positive values indicate power generation or positive work and negative values indicate power absorption or negative work. B) Box and whisker plots of net ankle (top), net foot (middle), and net ankle-foot (bottom) joint work in young and older adults. The horizontal line within the box indicates the median, the boundaries of the box indicate the 25th and 75th percentiles, the whiskers indicate the highest and lowest values, and a + indicates an outlier value. *indicates significant pairwise comparison of age (p<0.05)

Age×Horizontal Pulling Force interactions over the stance phase

We found an age×horizontal pulling force interaction for positive foot work (F_2,34=5.08, p=0.012, ${\eta }_P^2$=0.23) and ankle-foot work (F_2,34=7.64, p=0.002, ${\eta }_P^2$=0.31), with significant main effects of age (Foot: F_1,17=9.73, p=0.006, ${\eta }_P^2$=0.36; Ankle-Foot: F_1,17=10.64, p=0.005, ${\eta }_P^2$=0.39) and horizontal pulling force (Foot: F_2,34=14.20, p<0.001, ${\eta }_P^2$=0.46; Ankle-Foot: F_2,34=292.73, p<0.001, ${\eta }_P^2$=0.95). We did not find an age×horizontal pulling force interaction for net foot work (F_2,34=0.188, p=0.829, ${\eta }_P^2$=0.01). However, we did find significant main effects of age (F_1,17=5.27, p=0.035, ${\eta }_P^2$=0.24) and horizontal pulling force (F_2,34=37.64, p<0.001, ${\eta }_P^2$=0.69) on net foot work. Compared to young adults, older adults performed less positive foot work for the aiding and impeding force conditions, accompanied by more negative net foot and ankle-foot work for the impeding force condition (Table 1, Fig. 2). Young and older adults did not exhibit differences in positive or net ankle work across any pulling force conditions (Table 1, Fig. 2).

Figure 2.

A) Group mean sagittal plane ankle (top), foot (middle), and ankle-foot (bottom) power for young (black) and older (gray) adults walking at 1.2 m/s with an aiding horizontal pulling force, no pulling force, and impeding horizontal pulling force. The stride begins and ends at heel strike. Positive values indicate power generation or positive work and negative values indicate power absorption or negative work. B) Box and whisker plots of net ankle (top), net foot (middle), and net ankle-foot (bottom) joint work in young and older adults. The horizontal line within the box indicates the median, the boundaries of the box indicate the 25th and 75th percentiles, the whiskers indicate the highest and lowest values, and a + indicates an outlier value. *indicates significant pairwise comparison of age (p<0.05)

Correlations between foot and ankle mechanical work

Older adults displayed significant negative correlations between net foot work and net ankle work for the aiding (r=−0.692, p=0.027) and W1.4 conditions (r=−0.697, p=0.025) (Fig. 3). Young adults displayed significant negative correlations between net foot and net ankle work for the W1.2 (r=−0.674, p=0.047), impeding (r=−0.798, p=0.010), and W1.4 (r=−0.737, p=0.024) conditions (Fig. 3).

Figure 3.

Scatterplots and Pearsons correlation coefficients (r) between net foot work and net ankle work in young (black circles) and older (gray circles) adults walking at 1.0 m/s, 1.2 m/s, and 1.4 m/s, and walking at 1.2 m/s with aiding or impeding horizontal pulling forces. * indicates a significant correlation (p<0.05)

Discussion

The purpose of this study was to quantify age-related differences in foot mechanical work during walking at a range of speeds and with varied demands for push-off power. Given the evidence of age-related changes in the structure and function of the foot and ankle, we anticipated that older adults would exhibit less positive foot work and more negative net foot work compared to young adults. Consistent with our first hypothesis, we found that older adults walked while performing less positive foot work and more negative net foot work compared to young adults. By logical extension, we further anticipated that older adults would exhibit less positive and/or more negative net work performed by the ankle-foot complex compared to young adults. As hypothesized, older adults exhibited more negative net ankle-foot work than young adults, although these effects were task-dependent. Finally, consistent with our third hypothesis, we found that the effect of age on mechanical work performed by the foot and the ankle-foot complex increased with increased locomotor demand. In combination, these findings suggest that age-related differences in foot mechanics may contribute to reduced push-off intensity, a hallmark feature of older adult gait and common target in mobility interventions. As we describe below, these reductions in push-off intensity may occur via greater energy loss from distal foot structures, and may be larger during walking tasks that require greater push-off power output such as walking faster or walking uphill.

Our findings support emerging evidence to suggest the foot facilitates push-off power during walking (Arch and Fylstra, 2016; Takahashi and Stanhope, 2013; Takahashi et al., 2017; Zelik and Honert, 2018), and challenge the idea that the ankle plantarflexor muscles are the sole contributors to reduced push-off power in older adults. Based on prior literature, we were surprised to find that young and older adults did not exhibit differences in ankle work during walking (Table 1, Figs. 1 and 2). Effect sizes for pairwise comparisons of positive ankle work ranged from g=0.04 when walking with a horizontal aiding force, to g=0.95 when walking with a horizontal impeding force. Indeed, older adults usually walk with hallmark reductions in mechanical output from muscle-tendon units spanning the ankle (Cofre et al., 2011; DeVita and Hortobagyi, 2000; Kerrigan et al., 1998). The absence of age-related differences in ankle mechanical output has been reported previously when young and older adults walk at relatively slow speeds (Buddhadev and Martin, 2016), or in very fit and active older adults (e.g. endurance runners) (Karamanidis and Arampatzis, 2007; Krupenevich and Miller, 2020). The participants in our study did not have a history of habitual endurance running but were nonetheless healthy and active. Alternatively, these findings could be artifacts of methodological differences in ankle power computation. Traditionally, ankle power is calculated using a 3DOF model, but in the present study we calculated 6DOF ankle joint power, which may have contributed to our contrasting results (Buczek et al., 1994). Additionally, ankle power calculated from rigid segment models may include contributions from the mid-tarsal joints which i) may overestimate the contribution of the ankle plantarflexors to push-off power (Zelik and Honert, 2018), and ii) may mis-attribute age-related reductions in push-off power to the plantarflexor muscles. The deformable foot segment used here may indicate that age-related differences in foot mechanical power precede differences in ankle mechanical output.

Older adults in our study consistently performed less positive foot work and more negative net foot work during stance. These age-related differences in positive and net work were largest for walking conditions with the highest demands for push-off power output. Consequently, older adults performed more negative net work via the ankle-foot complex when walking at a faster speed or with an impeding force. Functionally, these findings may translate to disproportionate difficulties for older adults walking uphill or at faster speeds. Our findings are partially consistent with those of da Silva et al. (2020) who found that older adults performed more negative foot work at faster walking speeds, but similar positive foot work across a range of walking speeds. However, da Silva et al. (2020) modeled the foot as a single rigid segment which may provide an incomplete characterization of foot power and limits their interpretation of functional differences attributed to the foot. Alternatively, it is possible that the observed age-related difference in negative net work is partially due to age-related changes in the viscoelastic properties of the heel fat pad with age (Hsu et al., 1998). Future studies utilizing musculoskeletal models may be ideal for understanding the contributions of age-related changes in elastic soft tissues to foot work during walking.

Notably, during the push-off phase of walking, older adults performed net negative foot work across all walking conditions, while young adults performed net positive foot work (Supplemental Figs. 1 and 2). These stark differences in push-off work were not accompanied by age-related differences in positive foot work, indicating that net negative push-off work in older adults is the result of a greater loss of mechanical energy via distal foot structures. Although we did not measure foot stiffness in this study, we posit that this energy loss may be due to a reduced ability to regulate foot mechanical stiffness, which may disrupt the foot-ankle interaction. Indeed, Arch and Fylstra (2016) found that reduced energy loss at the foot resulted in less positive ankle work, but similar ankle-foot work, indicating an important interaction between energy generated at the ankle and lost at the foot. We note, however, that Arch and Fylstra (2016) modeled the foot as a single rigid segment which, as noted earlier, may mischaracterize the ankle-foot interaction. We interpret our results such that age-related differences in foot mechanical power manifested as a deficit in total push-off work when the propulsive demands of walking were greatest. Older adults who are unable to increase ankle mechanical output may then succumb to slower walking speeds.

Our findings have translational implications for the preservation and maintenance of mobility in older adults. For example, low-cost assistive devices, such as carbon fiber shoe insoles or ankle-foot orthoses may effectively reduce the amount energy lost via the foot. It is still an open question as to how assistive devices augment ankle and/or foot power during walking. However, Cigoja et al. (2019) found that during running, increased midsole bending stiffness resulted in less negative and more positive work at the MTP joint. Such assistive devices or orthotic interventions may themselves need active impedance control to meet the task-specific response of the foot during walking (e.g. Blaya and Herr, 2004). Our findings also highlight the need for future studies to investigate age-related differences in foot structures such as the plantar aponeurosis, elastic soft tissues (e.g. heel fat pad), and plantar intrinsic muscles to determine their contribution to age-related differences in foot mechanics.

This study provides new insights for the clinical management of age-related mobility impairments, but there are several limitations. First, the older adults in this study did not display the characteristic age-related reduction in ankle push-off power. Our older adult subjects were healthy and active; our inclusion and exclusion criteria were selected to minimize the effects of potentially confounding variables such as chronic disease or past injury. Therefore, these results may underestimate the extent of age-related differences in foot and ankle-foot mechanical work in older adults who are less mobile. We screened and excluded participants who reported any lower-extremity injuries within the past 6 months. However, fractures and other injuries may have long-lasting effects on foot mechanics that we did not account for here. The foot model used in this study did not quantify individual joint kinematics (e.g., mid-tarsal, and MTP) and thus is unable to describe age-related differences in kinematics between these joints. Additionally, our foot model may alter hindfoot angular velocity and power estimates. Future studies using musculoskeletal modeling approaches may be able to tease out active vs. passive contributions to the age-related differences in foot and ankle work reported here. Finally, our sample sizes were relatively small, increasing the chance of false negative findings. However, we provide effect sizes for all pairwise comparisons to aid in interpreting the meaningfulness of reported differences and suggest that these results are interpreted conservatively.

Conclusion

Our findings suggest that during walking, age-related differences in foot mechanics may contribute to reduced push-off intensity via greater energy loss from distal foot structures. These age effects may be larger during walking tasks with a greater demand for foot power generation, such as walking faster or walking uphill and may predispose older adults to slower walking speeds. These findings are the first step in understanding the role of the foot in older adults during walking and may serve as a roadmap for developing future low-cost mobility interventions.