- Email: [email protected]
Variability of step kinematics in young and older adults
Gait and Posture 20 (2004) 26–29
Variability of step kinematics in young and older adults Tammy M. Owings a , Mark D. Grabiner a,b,∗ a
Department of Biomedical Engineering, The Cleveland Clinic Foundation, 9500 Euclud Avenue, Cleveland, OH 44195, USA b School of Kinesiology (M/C 194), University of Illinois at Chicago, Chicago, IL 60608, USA Accepted 12 June 2003
Abstract Fall-related injuries are the most common and serious medical problems facing older adults. Recent studies of older adults have focused on the variability of step kinematics and the relationship to falling. The accuracy of step variability estimates is proportional to the number of steps that are collected. The use of an instrumented treadmill allows simultaneous collection of spatial and temporal step kinematics for a large number of continuous steps. The current study was conducted to determine the influence of age, walking velocity and handrail use on the variability of step kinematics using a treadmill protocol. Eighteen young adults (average age: 27.7 ± 3.3 years) and 12 healthy older adults (average age: 73.4 ± 2.3 years) were recruited from the community. Temporal and spatial gait parameters were quantified using custom designed software from measurements collected during treadmill walking. The primary independent variables were the variability of step length, step width, and step time. Step width variability of older adults was significantly larger than that of young adults. Walking velocity did not influence step kinematic variability. Handrail usage influenced the variability of step length and step width, but not of step time. The present results, and those of previous studies, point to a consistent relationship between age and step width variability. Since step width variability has been implicated in falls, further research is warranted. © 2003 Elsevier B.V. All rights reserved. Keywords: Gait; Locomotion; Older adults; Biomechanics; Variability
1. Introduction Fall-related injuries are the most common and serious medical problems facing older adults [1]. Twenty percent of the eight million fall-related emergency department visits in 1994 involved adults who were 65 years of age or older [2]. Falls and fall-related injuries are the second leading cause of injury death among people between the ages of 75 and 84 years, and the leading cause of injury death among people 85 years of age and older [2]. Fewer than 2% of falls by older adults result in a hip fracture. In contrast, more than 90% of hip fractures in older adults result from a fall [1] and most of these fractures result from a fall occurring during locomotion. This underscores the complex relationships between fall initiation, descent, impact, and the biomechanics of the proximal femur. Because most hip fractures involve an impact on or around the greater trochanter, falls to the side are ∗ Corresponding author. Tel.: +1-312-996-2757; fax: +1-312-413-3699. E-mail address: [email protected] (M.D. Grabiner).
0966-6362/$ – see front matter © 2003 Elsevier B.V. All rights reserved. doi:10.1016/S0966-6362(03)00088-2
associated with a particularly high risk of injury. Indeed, the risk for a hip fracture is increased by six-fold when the fall occurs to the side [3]. This highlights the potential value of determining specific gait variables that increase the risk for falls to the side, that is, falls that expose the hip to impact forces. One possible variable is the control of step width. During locomotion, the lateral placement of the foot, which dictates step width, is the dominant contributor to medial–lateral acceleration of the trunk [4]. The lateral placement of the foot is controlled during the preceding swing phase by the hip abductors and adductors, which are also responsible for medial–lateral trunk stability during the stance phase. The importance of step width control raises questions about the relationships between step width control errors, medial–lateral stability, and falls. A common method to analyze motor control errors is movement variability. Two studies have reported on relationships between step kinematic variability and falling behavior in older adults [5,6]. Decreased step width variability, in conjunction with increased step width, prospectively discriminated older adults who fell from those older adults who did not fall [5]. In contrast, increased variability of step time
T.M. Owings, M.D. Grabiner / Gait and Posture 20 (2004) 26–29
prospectively discriminated older adults who had fallen from older adults who had not fallen [6]. This apparent disparity reflects that the directional importance of altered variability cannot be generalized but rather is likely specific to the outcome measurement [7]. Nevertheless, the differences in technologies used and experimental methods used by Maki [5] and Hausdorff et al. [6] preclude resolution via direct comparison. In the present study, we used an instrumented treadmill that allowed simultaneous quantification of both temporal and spatial step kinematics during sustained locomotion, that is, for hundreds of continuous steps. This conferred upon the present study those measurement advantages occurring in the studies of Maki [5] and Hausdorff et al. [6] The purposes of the study were to determine the extent to which age influences the variability of step kinematics and if step kinematic variability is influenced by walking velocity and the use of handrails during treadmill gait.
27
kinematic variability, a subgroup of the subjects (10 young, 5 older) were asked to walk at a velocity 10% slower than their normal walking. To examine the influence of the use of handrails on step kinematic variability, a second subgroup of the subjects (10 young, 9 older) were asked to walk using both hands on the front supports and again using one hand on the side rail. Two older and two young subjects performed all four walking conditions. For each walking condition, older subjects walked for 10 min while young subjects walked for 15 min. There was a 5 min rest between each walking condition. The order of walking conditions was randomly assigned to each subject. 2.4. Analysis
Eighteen young adults (age: 27.7 ± 3.3 years; height: 1.68±0.11 m; mass: 65.9±10.2 kg) and 12 older adults (age: 73.4±2.3 years; height: 1.72±0.13 m; mass: 76.3±15.5 kg) participated in this study. Older adults were allowed to participate if their physician permitted exercise at a moderate level. All subjects gave informed consent prior to participation in the study. Subjects wore their own walking shoes during the protocol.
Spatial and temporal step kinematics were calculated based on the location of the center of pressure at the instant of heel-strike and toe-off of each foot [9]. Heel-strike and toe-off were designated as the time at which vertical ground reaction force rose above, or dropped below, 10% of the subject’s body weight, respectively. Step length, normalized to body height, was calculated as the anterior–posterior distance from heel-strike of one foot to toe-off of the contralateral foot. Step width was determined as the medial–lateral distance between sequential left and right heel-strikes. Step time was calculated as the elapsed time between ipsilateral heel-strikes. Data points were eliminated from the data series for two reasons. The first reason was if, during the double support phase of walking, both feet were simultaneously located on the same forceplate. The second reason was if data points were considered “extreme” values [10]. Extreme values were determined by sorting the data series by magnitude, and calculating the mean and standard deviation of the central 90% of the sorted series. Data points from the original, unsorted series greater than ±3.77 standard deviations from the calculated mean were eliminated. Because the number of accepted steps was expected to vary between subjects due to differences in step frequency and the number of eliminated steps, each subject’s data set was ultimately truncated to match that of the subject having the fewest number of steps. Following truncation, the mean and standard deviation of step length, step width, and step time were determined for each walking condition of each subject. Standard deviation was used to denote kinematic variability.
2.3. Protocol
2.5. Statistics
Subjects determined their normal, self-selected velocity for treadmill walking during a warm-up period. During this warm-up period, subjects became familiar with the walking conditions that they would be asked to perform. To examine the influence of age on step kinematic variability, subjects were asked to walk at their normal, self-selected walking velocity. To examine the influence of walking velocity on step
It was anticipated that there would not be a main effect of left and right variables [9]. If applicable to the present dataset, further comparisons were planned using the average of the left and right variables. For determining the influence of age, independent t-tests were performed on step length variability, step width variability, and step time variability during the normal walking condition.
2. Methods 2.1. Instrumentation The instrumented treadmill and analysis used in this study has been described previously in greater detail [8,9]. The treadmill consists of a Tredex treadmill (Universal Gym Equipment, Cedar Rapids, IA) equipped with two AMTI forceplates (AMTI Inc., Newton, MA). The forceplates are aligned in an anterior–posterior fashion directly beneath the treadmill belt. Ground reaction forces and moments were measured from both forceplates, digitized at 100 Hz, and stored for post-processing. The treadmill was equipped with hand supports in the front and an adjustable handrail on the right side. 2.2. Subjects
28
T.M. Owings, M.D. Grabiner / Gait and Posture 20 (2004) 26–29
For determining the influence of walking velocity, paired t-tests were performed on all variables from the normal walking condition and the condition in which subjects walked at a 90% of their self-selected velocity. For determining the influence of using the handrails, a three-way (handrail assistance) repeated measures ANOVA was performed on all variables from the normal walking condition and the conditions during which the subjects walked with one hand on the side rail, and walked with both hands on the front support conditions. Bonferroni adjusted post-hoc t-tests were performed where indicated.
3. Results To place the results with respect to variability in context, descriptive statistics for step length, step width, and step time were calculated. These values were computed independently for the effect of age (Table 1), the effect of walking velocity (Table 2), and the effect of handrail (Table 3). The differences between the values measured for the left and right legs were not significant for the variability of step length and step time (P = 0.157 and 0.851, respectively). Thus, all reported values represent the average of the left and right sides. Older adults had significantly larger step width variability than the young adults (P = 0.037, Table 1). On average, Table 1 Spatial and temporal step kinematics and kinematic variability for young (n = 18) and older (n = 12) adults during normal walking on a treadmill Young Step Step Step Step Step Step
length (%bh) length variability (%bh) width (cm) width variability (cm) time (s/100) time variability (s/100)
24.8 1.5 9.5 2.1 114.9 2.3
Older (3.5) (0.9) (1.8) (0.5) (9.0) (0.9)
24.3 1.6 10.4 2.5 107.8 2.6
(5.1) (1.1) (3.4) (0.7)∗ (9.2) (1.1)
Values are mean (standard deviation). Walking speed was 3.5 ± 0.6 km/h for young adults and 3.8 ± 1.0 km/h for older adults. %bh: percentage of body height. ∗ Statistically different than young (P < 0.05). Table 2 Spatial and temporal step kinematics and kinematic variability during walking on a treadmill at a normal, self-selected velocity and at a 10% slower than normal velocity (n = 15; 10 young and 5 older adults)
Step Step Step Step Step Step
length (%bh) length variability (%bh) width (cm) width variability (cm) time (s/100) time variability (s/100)
Normal
10% slower
25.6 1.4 9.2 2.0 113.7 1.8
23.6 1.6 9.8 2.0 117.5 2.1
(3.4) (0.8) (2.0) (0.6) (10.8) (0.5)
(5.4) (1.3) (2.1) (0.5) (11.1) (0.7)
Values are mean (standard deviation). Walking speed was 3.9 ± 0.8 km/h for normal walking and 3.5 ± 0.6 km/h for 10% slower. %bh: percentage of body height.
Table 3 Spatial and temporal step kinematics and kinematic variability during walking on a treadmill with no hands on the rails, with one hand on the side rail, and with two hands on the front rail (n = 19; 10 young and 9 older adults) No hands on rail Step length (%bh) Step length variability (%bh) Step width (cm) Step width variability (cm) Step time (s/100) Step time variability (s/100)
24.1 (4.6) 1.6 (1.0)† 10.2 (2.7) 2.4 (0.6)∗,† 110.4 (9.9) 2.7 (1.0)
One hand on rail
Two hands on rail
25.6 (4.4) 1.2 (0.4)
25.8 (3.9) 1.1 (0.4)
8.3 (2.3) 1.6 (0.4)
8.1 (2.2) 1.4 (0.6)
118.2 (15.1) 2.5 (1.5)
119.6 (14.8) 2.7 (1.6)
Values are mean (standard deviation). Walking speed was 3.4 ± 0.8 km/h for all conditions. %bh: percentage of body height. † Significantly different than two hands on rail (P < 0.02). ∗ Significantly different than one hand on rail (P < 0.02).
the step width variability of the older adults was 0.4 cm larger than the young adults. The influences of age on the variability of step length and step time were not significant (P = 0.734 and 0.478, respectively; Table 1). Step kinematic variability was not significantly affected by walking velocity. The variability of the step length, step width and step time qualitatively increased by 14%, 0% and 17% (P = 0.295, 0.232, and 0.059, respectively; Table 2). There was an influence of handrail assistance on the variability of step length and step width (P = 0.008 and <0.001, respectively; Table 3), but not step time variability (P = 0.502; Table 3). Post-hoc paired t-tests on the variability of step length and step width revealed that step kinematic variability was significantly larger for the condition of walking without handrail assistance compared to walking with both hands on the front safety rails (P = 0.018 and <0.001, respectively). Step width variability was significantly larger for walking without handrail assistance compared to walking with one hand on the side rail (P < 0.001) but significant differences in step length variability for this condition did not meet the necessary adjusted P-value (P = 0.048). The difference in step width variability during the condition of walking with one hand on the side rail and walking with both hands on the front safety rails did not meet the necessary adjusted P-value (P = 0.042). There were no significant differences in step length variability between walking with one hand on the side rail and walking with both hands on the front safety rails (P = 0.334).
4. Discussion A prominent finding of the present work is that step width variability increased by nearly 20% in the older subjects compared to the young subjects. This finding is consistent with the findings of Grabiner et al. [11], who reported
T.M. Owings, M.D. Grabiner / Gait and Posture 20 (2004) 26–29
increased step width variability of 35% in older adults during walking over an instrumented surface. Our finding of an absence of left-right differences in step kinematic parameters in healthy older adults has not been previously reported. This should not be assumed in any particular subject group, especially if there are musculoskeletal or neurological diseases that would be expected to influence gait symmetry. In this type of patient, quantifications of left–right differences may have clinical value. For the current study, patients with known neuromuscular diseases were excluded. The finding that step kinematic variability using a single or double handhold position are not statistically different from each other but differ from the hands free position is important. Adults, particularly older adults, may require at least one hand on a safety rail in order to participate in a walking experiment on a treadmill. Step kinematic parameters collected while subjects use handrails should not be pooled, or averaged with step kinematic parameters collected while subjects do not use handrails. However, our findings suggest that subjects requiring handhold assistance can be pooled for one hand and the two-hand conditions. An important finding in the present work is that older adults walked on a treadmill with significantly larger step width variability than their young counterparts. The meaning of increased step width variability from a biomechanical view has yet to be established, but may be part of the adaptive controls that the body uses to maintain posture during a walk. Increased variability may result from decreased motor skill. It may also reflect an accommodation to the aging of the neuromuscular system. The finding by Maki [5] that step width variability is a predictor of falls increases the attractiveness of pursuing further investigation of this parameter. From a clinical standpoint, step kinematic parameters are easy to measure, and the treadmill protocol is easy to administer. While we have confidence in our results for treadmill walking, the influence of over-ground walking with respect to variability of spatial and temporal step kinematics is un-
29
clear. Continued research in this area is justified in order to decrease the morbidity, mortality, and cost of fall-related injuries.
Acknowledgements We gratefully acknowledge Darryl Barnes, MD, Barbara Messinger-Rapport, MD, and Susan Shutte who assisted in the data collection and analysis.
References [1] Hayes WC, Myers ER, Robinovitch SN, et al. Etiology and prevention of age-related hip fractures. Bone 1996;18:77S–86S. [2] Fingerhut L, Warner M. Injury chartbook. Health, United States, 1996–1997. Hyattsville, MD: National Center for Health Statistics; 1997. [3] Greenspan SL, Myers ER, Maitland LA, et al. Fall severity and bone mineral density as risk factors for hip fracture in ambulatory elderly. J Am Med Assoc 1994;271:128–33. [4] Winter DA. Anatomy, biomechanics, and control of balance during standing and walking. Waterloo, Ont., Canada: Waterloo Biomechanics; 1995. p. 51–3. [5] Maki B. Gait changes in older adults: predictors of falls or indicators of fear? J Am Geriatr Soc 1997;45:313–20. [6] Hausdorff JM, Rios DA, Edelberg HK. Gait variability and fall risk in community-living older adults: a 1-year prospective study. Arch Phys Med Rehabil 2001;82:1050–6. [7] Heiderscheit BC. Movement variability as a clinical measure for locomotion. J Appl Biomech 2000;16:419–27. [8] Dingwell JB, Davis BL. A rehabilitation treadmill with software for providing real-time gait analysis and visual feedback. J Biomech Eng 1996;118:253–5. [9] Owings TM, Grabiner MD. Measuring step kinematic variability using an instrumented treadmill: how many steps are enough? J Biomech 2003;36:1215–8. [10] Hausdorff JM, Zemany L, Peng C, et al. Maturation of gait dynamics: stride-to-stride variability and its temporal organization in children. J Appl Physiol 1999;86:1040–7. [11] Grabiner PC, Biswas ST, Grabiner MD. Age-related changes of spatial and temporal gait variables. Arch Phys Med Rehabil 2001;82: 31–5.
Variability of step kinematics in young and older adults Tammy M. Owings a , Mark D. Grabiner a,b,∗ a
Department of Biomedical Engineering, The Cleveland Clinic Foundation, 9500 Euclud Avenue, Cleveland, OH 44195, USA b School of Kinesiology (M/C 194), University of Illinois at Chicago, Chicago, IL 60608, USA Accepted 12 June 2003
Abstract Fall-related injuries are the most common and serious medical problems facing older adults. Recent studies of older adults have focused on the variability of step kinematics and the relationship to falling. The accuracy of step variability estimates is proportional to the number of steps that are collected. The use of an instrumented treadmill allows simultaneous collection of spatial and temporal step kinematics for a large number of continuous steps. The current study was conducted to determine the influence of age, walking velocity and handrail use on the variability of step kinematics using a treadmill protocol. Eighteen young adults (average age: 27.7 ± 3.3 years) and 12 healthy older adults (average age: 73.4 ± 2.3 years) were recruited from the community. Temporal and spatial gait parameters were quantified using custom designed software from measurements collected during treadmill walking. The primary independent variables were the variability of step length, step width, and step time. Step width variability of older adults was significantly larger than that of young adults. Walking velocity did not influence step kinematic variability. Handrail usage influenced the variability of step length and step width, but not of step time. The present results, and those of previous studies, point to a consistent relationship between age and step width variability. Since step width variability has been implicated in falls, further research is warranted. © 2003 Elsevier B.V. All rights reserved. Keywords: Gait; Locomotion; Older adults; Biomechanics; Variability
1. Introduction Fall-related injuries are the most common and serious medical problems facing older adults [1]. Twenty percent of the eight million fall-related emergency department visits in 1994 involved adults who were 65 years of age or older [2]. Falls and fall-related injuries are the second leading cause of injury death among people between the ages of 75 and 84 years, and the leading cause of injury death among people 85 years of age and older [2]. Fewer than 2% of falls by older adults result in a hip fracture. In contrast, more than 90% of hip fractures in older adults result from a fall [1] and most of these fractures result from a fall occurring during locomotion. This underscores the complex relationships between fall initiation, descent, impact, and the biomechanics of the proximal femur. Because most hip fractures involve an impact on or around the greater trochanter, falls to the side are ∗ Corresponding author. Tel.: +1-312-996-2757; fax: +1-312-413-3699. E-mail address: [email protected] (M.D. Grabiner).
0966-6362/$ – see front matter © 2003 Elsevier B.V. All rights reserved. doi:10.1016/S0966-6362(03)00088-2
associated with a particularly high risk of injury. Indeed, the risk for a hip fracture is increased by six-fold when the fall occurs to the side [3]. This highlights the potential value of determining specific gait variables that increase the risk for falls to the side, that is, falls that expose the hip to impact forces. One possible variable is the control of step width. During locomotion, the lateral placement of the foot, which dictates step width, is the dominant contributor to medial–lateral acceleration of the trunk [4]. The lateral placement of the foot is controlled during the preceding swing phase by the hip abductors and adductors, which are also responsible for medial–lateral trunk stability during the stance phase. The importance of step width control raises questions about the relationships between step width control errors, medial–lateral stability, and falls. A common method to analyze motor control errors is movement variability. Two studies have reported on relationships between step kinematic variability and falling behavior in older adults [5,6]. Decreased step width variability, in conjunction with increased step width, prospectively discriminated older adults who fell from those older adults who did not fall [5]. In contrast, increased variability of step time
T.M. Owings, M.D. Grabiner / Gait and Posture 20 (2004) 26–29
prospectively discriminated older adults who had fallen from older adults who had not fallen [6]. This apparent disparity reflects that the directional importance of altered variability cannot be generalized but rather is likely specific to the outcome measurement [7]. Nevertheless, the differences in technologies used and experimental methods used by Maki [5] and Hausdorff et al. [6] preclude resolution via direct comparison. In the present study, we used an instrumented treadmill that allowed simultaneous quantification of both temporal and spatial step kinematics during sustained locomotion, that is, for hundreds of continuous steps. This conferred upon the present study those measurement advantages occurring in the studies of Maki [5] and Hausdorff et al. [6] The purposes of the study were to determine the extent to which age influences the variability of step kinematics and if step kinematic variability is influenced by walking velocity and the use of handrails during treadmill gait.
27
kinematic variability, a subgroup of the subjects (10 young, 5 older) were asked to walk at a velocity 10% slower than their normal walking. To examine the influence of the use of handrails on step kinematic variability, a second subgroup of the subjects (10 young, 9 older) were asked to walk using both hands on the front supports and again using one hand on the side rail. Two older and two young subjects performed all four walking conditions. For each walking condition, older subjects walked for 10 min while young subjects walked for 15 min. There was a 5 min rest between each walking condition. The order of walking conditions was randomly assigned to each subject. 2.4. Analysis
Eighteen young adults (age: 27.7 ± 3.3 years; height: 1.68±0.11 m; mass: 65.9±10.2 kg) and 12 older adults (age: 73.4±2.3 years; height: 1.72±0.13 m; mass: 76.3±15.5 kg) participated in this study. Older adults were allowed to participate if their physician permitted exercise at a moderate level. All subjects gave informed consent prior to participation in the study. Subjects wore their own walking shoes during the protocol.
Spatial and temporal step kinematics were calculated based on the location of the center of pressure at the instant of heel-strike and toe-off of each foot [9]. Heel-strike and toe-off were designated as the time at which vertical ground reaction force rose above, or dropped below, 10% of the subject’s body weight, respectively. Step length, normalized to body height, was calculated as the anterior–posterior distance from heel-strike of one foot to toe-off of the contralateral foot. Step width was determined as the medial–lateral distance between sequential left and right heel-strikes. Step time was calculated as the elapsed time between ipsilateral heel-strikes. Data points were eliminated from the data series for two reasons. The first reason was if, during the double support phase of walking, both feet were simultaneously located on the same forceplate. The second reason was if data points were considered “extreme” values [10]. Extreme values were determined by sorting the data series by magnitude, and calculating the mean and standard deviation of the central 90% of the sorted series. Data points from the original, unsorted series greater than ±3.77 standard deviations from the calculated mean were eliminated. Because the number of accepted steps was expected to vary between subjects due to differences in step frequency and the number of eliminated steps, each subject’s data set was ultimately truncated to match that of the subject having the fewest number of steps. Following truncation, the mean and standard deviation of step length, step width, and step time were determined for each walking condition of each subject. Standard deviation was used to denote kinematic variability.
2.3. Protocol
2.5. Statistics
Subjects determined their normal, self-selected velocity for treadmill walking during a warm-up period. During this warm-up period, subjects became familiar with the walking conditions that they would be asked to perform. To examine the influence of age on step kinematic variability, subjects were asked to walk at their normal, self-selected walking velocity. To examine the influence of walking velocity on step
It was anticipated that there would not be a main effect of left and right variables [9]. If applicable to the present dataset, further comparisons were planned using the average of the left and right variables. For determining the influence of age, independent t-tests were performed on step length variability, step width variability, and step time variability during the normal walking condition.
2. Methods 2.1. Instrumentation The instrumented treadmill and analysis used in this study has been described previously in greater detail [8,9]. The treadmill consists of a Tredex treadmill (Universal Gym Equipment, Cedar Rapids, IA) equipped with two AMTI forceplates (AMTI Inc., Newton, MA). The forceplates are aligned in an anterior–posterior fashion directly beneath the treadmill belt. Ground reaction forces and moments were measured from both forceplates, digitized at 100 Hz, and stored for post-processing. The treadmill was equipped with hand supports in the front and an adjustable handrail on the right side. 2.2. Subjects
28
T.M. Owings, M.D. Grabiner / Gait and Posture 20 (2004) 26–29
For determining the influence of walking velocity, paired t-tests were performed on all variables from the normal walking condition and the condition in which subjects walked at a 90% of their self-selected velocity. For determining the influence of using the handrails, a three-way (handrail assistance) repeated measures ANOVA was performed on all variables from the normal walking condition and the conditions during which the subjects walked with one hand on the side rail, and walked with both hands on the front support conditions. Bonferroni adjusted post-hoc t-tests were performed where indicated.
3. Results To place the results with respect to variability in context, descriptive statistics for step length, step width, and step time were calculated. These values were computed independently for the effect of age (Table 1), the effect of walking velocity (Table 2), and the effect of handrail (Table 3). The differences between the values measured for the left and right legs were not significant for the variability of step length and step time (P = 0.157 and 0.851, respectively). Thus, all reported values represent the average of the left and right sides. Older adults had significantly larger step width variability than the young adults (P = 0.037, Table 1). On average, Table 1 Spatial and temporal step kinematics and kinematic variability for young (n = 18) and older (n = 12) adults during normal walking on a treadmill Young Step Step Step Step Step Step
length (%bh) length variability (%bh) width (cm) width variability (cm) time (s/100) time variability (s/100)
24.8 1.5 9.5 2.1 114.9 2.3
Older (3.5) (0.9) (1.8) (0.5) (9.0) (0.9)
24.3 1.6 10.4 2.5 107.8 2.6
(5.1) (1.1) (3.4) (0.7)∗ (9.2) (1.1)
Values are mean (standard deviation). Walking speed was 3.5 ± 0.6 km/h for young adults and 3.8 ± 1.0 km/h for older adults. %bh: percentage of body height. ∗ Statistically different than young (P < 0.05). Table 2 Spatial and temporal step kinematics and kinematic variability during walking on a treadmill at a normal, self-selected velocity and at a 10% slower than normal velocity (n = 15; 10 young and 5 older adults)
Step Step Step Step Step Step
length (%bh) length variability (%bh) width (cm) width variability (cm) time (s/100) time variability (s/100)
Normal
10% slower
25.6 1.4 9.2 2.0 113.7 1.8
23.6 1.6 9.8 2.0 117.5 2.1
(3.4) (0.8) (2.0) (0.6) (10.8) (0.5)
(5.4) (1.3) (2.1) (0.5) (11.1) (0.7)
Values are mean (standard deviation). Walking speed was 3.9 ± 0.8 km/h for normal walking and 3.5 ± 0.6 km/h for 10% slower. %bh: percentage of body height.
Table 3 Spatial and temporal step kinematics and kinematic variability during walking on a treadmill with no hands on the rails, with one hand on the side rail, and with two hands on the front rail (n = 19; 10 young and 9 older adults) No hands on rail Step length (%bh) Step length variability (%bh) Step width (cm) Step width variability (cm) Step time (s/100) Step time variability (s/100)
24.1 (4.6) 1.6 (1.0)† 10.2 (2.7) 2.4 (0.6)∗,† 110.4 (9.9) 2.7 (1.0)
One hand on rail
Two hands on rail
25.6 (4.4) 1.2 (0.4)
25.8 (3.9) 1.1 (0.4)
8.3 (2.3) 1.6 (0.4)
8.1 (2.2) 1.4 (0.6)
118.2 (15.1) 2.5 (1.5)
119.6 (14.8) 2.7 (1.6)
Values are mean (standard deviation). Walking speed was 3.4 ± 0.8 km/h for all conditions. %bh: percentage of body height. † Significantly different than two hands on rail (P < 0.02). ∗ Significantly different than one hand on rail (P < 0.02).
the step width variability of the older adults was 0.4 cm larger than the young adults. The influences of age on the variability of step length and step time were not significant (P = 0.734 and 0.478, respectively; Table 1). Step kinematic variability was not significantly affected by walking velocity. The variability of the step length, step width and step time qualitatively increased by 14%, 0% and 17% (P = 0.295, 0.232, and 0.059, respectively; Table 2). There was an influence of handrail assistance on the variability of step length and step width (P = 0.008 and <0.001, respectively; Table 3), but not step time variability (P = 0.502; Table 3). Post-hoc paired t-tests on the variability of step length and step width revealed that step kinematic variability was significantly larger for the condition of walking without handrail assistance compared to walking with both hands on the front safety rails (P = 0.018 and <0.001, respectively). Step width variability was significantly larger for walking without handrail assistance compared to walking with one hand on the side rail (P < 0.001) but significant differences in step length variability for this condition did not meet the necessary adjusted P-value (P = 0.048). The difference in step width variability during the condition of walking with one hand on the side rail and walking with both hands on the front safety rails did not meet the necessary adjusted P-value (P = 0.042). There were no significant differences in step length variability between walking with one hand on the side rail and walking with both hands on the front safety rails (P = 0.334).
4. Discussion A prominent finding of the present work is that step width variability increased by nearly 20% in the older subjects compared to the young subjects. This finding is consistent with the findings of Grabiner et al. [11], who reported
T.M. Owings, M.D. Grabiner / Gait and Posture 20 (2004) 26–29
increased step width variability of 35% in older adults during walking over an instrumented surface. Our finding of an absence of left-right differences in step kinematic parameters in healthy older adults has not been previously reported. This should not be assumed in any particular subject group, especially if there are musculoskeletal or neurological diseases that would be expected to influence gait symmetry. In this type of patient, quantifications of left–right differences may have clinical value. For the current study, patients with known neuromuscular diseases were excluded. The finding that step kinematic variability using a single or double handhold position are not statistically different from each other but differ from the hands free position is important. Adults, particularly older adults, may require at least one hand on a safety rail in order to participate in a walking experiment on a treadmill. Step kinematic parameters collected while subjects use handrails should not be pooled, or averaged with step kinematic parameters collected while subjects do not use handrails. However, our findings suggest that subjects requiring handhold assistance can be pooled for one hand and the two-hand conditions. An important finding in the present work is that older adults walked on a treadmill with significantly larger step width variability than their young counterparts. The meaning of increased step width variability from a biomechanical view has yet to be established, but may be part of the adaptive controls that the body uses to maintain posture during a walk. Increased variability may result from decreased motor skill. It may also reflect an accommodation to the aging of the neuromuscular system. The finding by Maki [5] that step width variability is a predictor of falls increases the attractiveness of pursuing further investigation of this parameter. From a clinical standpoint, step kinematic parameters are easy to measure, and the treadmill protocol is easy to administer. While we have confidence in our results for treadmill walking, the influence of over-ground walking with respect to variability of spatial and temporal step kinematics is un-
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clear. Continued research in this area is justified in order to decrease the morbidity, mortality, and cost of fall-related injuries.
Acknowledgements We gratefully acknowledge Darryl Barnes, MD, Barbara Messinger-Rapport, MD, and Susan Shutte who assisted in the data collection and analysis.
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