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Physical activity, functional capacity, and step variability during walking in people with lower-limb amputation
Gait & Posture 40 (2014) 140–144
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Gait & Posture journal homepage: www.elsevier.com/locate/gaitpost
Physical activity, functional capacity, and step variability during walking in people with lower-limb amputation Suh-Jen Lin *, Katie D. Winston, Jill Mitchell, Jacob Girlinghouse, Karleigh Crochet School of Physical Therapy, Institute of Health Sciences – Dallas, Texas Woman’s University, TX, United States
A R T I C L E I N F O
A B S T R A C T
Article history: Received 19 July 2013 Received in revised form 4 March 2014 Accepted 8 March 2014
Physical activity is important for general health. For an individual with amputation to sustain physical activity, certain functional capacity might be needed. Gait variability is related to the incidence of falls. This study explored the relationship between physical activity and a few common performance measures (six-minute walk test, step length variability, step width variability, and comfortable walking speed) in individuals with unilateral lower-limb amputation. Twenty individuals completed the study (age: 50 11 yrs). Twelve of them had transtibial amputation, seven had transfemoral amputation, and one had through-knee amputation. Gait data was collected by the GaitRite instrumented walkway while participants performed a 3-min comfortable walking trial followed by a six-minute walk test. Physical activity was indicated by the mean of 7-day step counts via a pedometer. Gait variability was calculated by the coefficient of variation. Pearson correlation analysis was conducted between physical activity level and the 4 performance measures. Significance level was set at 0.05. Physical activity correlates strongly to comfortable walking speed (r = 0.76), six-minute walk distance (r = 0.67), and correlates fairly to step width variability (r = 0.44). On the contrary, physical activity is inversely related to step length variability of the prosthetic leg (r = 0.46) and of the sound leg (r = 0.47). Having better functional capacity and lateral stability might enable an individual with lower-limb amputation to engage in a higher physical activity level, or vise versa. However, our conclusions are only preliminary as limited by the small sample size. ß 2014 Elsevier B.V. All rights reserved.
Keywords: Amputation Gait variability Walk test Physical activity Functional capacity
1. Introduction Studies have consistently showed a positive association between physical activity and health-related quality of life and a reduction of all-cause mortality [1]. Current guidelines recommend that adults engage in moderate-intensity physical activity 5 days a week or vigorous-intensity activity 30 min a day for at least 3 days a week [2]. Physical activity can be estimated by a selfreported questionnaire, an accelerometer, or a pedometer [1,3]. A pedometer recording step counts is inexpensive, reliable, and correlates well with an accelerometer [4]. To sustain optimal physical activity a person may require a certain degree of aerobic capacity, muscle strength, and balance abilities. Most people with a lower-limb amputation are less active. Ten thousand steps per day is the recommended activity level for adults [2], whereas a sedentary lifestyle is generally defined as
* Corresponding author at: TWU Institute of Health Science – Dallas, 5500 Southwestern Medical Avenue, Dallas, TX 75235, United States. Tel.: +214 689 7718; fax: +214 689 7703. E-mail address: [email protected] (S.-J. Lin). http://dx.doi.org/10.1016/j.gaitpost.2014.03.012 0966-6362/ß 2014 Elsevier B.V. All rights reserved.
fewer than 5000 steps per day [5]. Daily step counts in individuals with lower-limb amputation range from 2500 to 8500 steps depending on age, reason of amputation (vascular vs. traumatic) [6,7], level of amputation, comorbidity [8], and types of prosthetic foot [9]. For individuals with lower-limb amputation, a higher physical activity level was associated with a better perceived quality of life [10]. Therefore, promoting physical activity is important in this population. A person’s self-selected walking speed (SSWV) is very close to speeds with the least energy consumption per distance traveled [11]. It is a reliable measure and a strong predictor of disability [12]. In general, It ranges from 1.27 m/s to 1.46 m/s in normal adults and decreases with age [13]. In individuals with transtibial amputation, it ranges from 1.12 m/s to 1.18 m/s [9], which is just slightly faster than the speed required for community ambulation [14]. A person with a higher physical activity level is shown to have a faster SSWV [15]. However, we do not know whether this is also true for individuals with lower-limb amputation. Determining exercise capacity is challenging for people with disabilities, and standard equipment may not be applicable such as treadmill, upright cycle ergometer, and stair stepper machine. Field exercise tests, such as walk tests, provide an alternative. The
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six-minute walk test measures the maximal distance a person can cover in 6 min (distance of the six-minute walk test, or 6MWD). It is easy to administer, relates to day-to-day activity, and physiological responses can be monitored. In addition, it demonstrates good test-retest reliability [16], and is strongly related to a person’s peak oxygen consumption [17]. A 6MWD of less than 300 m predicts an increased likelihood of death within 6 months in patients with heart failure [17]. Relationship between physical activity and 6MWD has not been reported in individuals with amputation. During walking, the anterior/posterior stepping motion control is passive in nature or only requires a low level of control; whereas lateral stability requires more active control through adjusting step width continuously [18,19]. At normal walking speed, the preferred step width is about 12 cm, which is the most energy efficient [20]. During running, the step width is near zero, in order to enhance step-to-step transition. People with lower-limb amputation often adapt a larger base of support for compensation of impaired sensation due to limb loss [21]. If an amputee can narrow the step width of walking to be close to that of nonamputees, then he/she must have a better control of lateral stability and could walk faster. At normal walking speed, mechanical efficiency is known to inversely relate to step length variability [11]. Gait variability is often expressed as the standard deviation, or coefficient of variation, of a series of steps. Increased step length variability or reduced step width variability is associated with increased risk of falls [22,23]. Exploring the relationship between physical activity and gait variability may shed light on the effects of promoting physical activity on gait performance in amputees. The purpose of this study was to explore the associations between physical activity level and physical performance measures (self-selected walking velocity, 6MWD, step length variability, and step width variability) in individuals with lowerlimb amputation. We hypothesized that a higher physical activity level, as indicated by daily step count, would be associated with a faster self-selected walking velocity, a higher functional capacity, a smaller step length variability, and a larger step width variability during comfortable walking in persons with lowerlimb amputation.
2. Materials and methods 2.1. Subjects An appropriate sample size was estimated based on the finding that 6MWD was a strong predictor of step count and step rate, accounting for 38–54% of the variance [15,24]. Assuming the standardized effect size for Pearson’s correlation of 0.62, to achieve a statistical power of 80% at an a2 level of 0.05, we estimated that about 18 subjects were needed. Subjects were recruited from local amputee support groups in a metropolitan area. The inclusion criteria were: (1) independent walking with a prosthesis, (2) experience with prosthesis use over 6 months, (3) intact skin condition of the residual limb, and (4) well controlled medical conditions. Thirty-five people with lower-limb amputation were recruited. Thirteen individuals were excluded due to the following reasons: 2 required a walking aid, 2 were having their prostheses adjusted, 1 had an ankle fusion, 1 had a bilateral amputation, 2 had health issues, and 5 decided not to participate due to commuting or scheduling conflicts. Therefore, a total of 22 subjects were enrolled and informed consent was obtained. This study was approved by the Institutional Review Board of our institution.
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2.2. Protocol Each subject came in for a one-hour session consisting of a history interview for demographic data and measurement of selfselected walking velocity and 6MWD. Each subject was instructed to walk at his/her comfortable speed for three minutes back and forth across a 13.41 m (44 ft) segment of a hallway with a 4-m GAITRite1 instrumented mat placed at the middle of the segment. The GAITRite system was shown to have good test-retest reliability and concurrent validity [25]. Step length is defined as the distance from the heel center of the current footprint to the heel center of the previous footprint on the opposite foot along the line of progression. Step width is defined as the mediolateral distance from the midline midpoint of one footprint to the line formed by the midline midpoint of two footprints of the opposite foot. Step variability is expressed as the coefficient of variation of a series of steps (i.e. (standard deviation/mean) 100%). For the six-minute walk test, each participant was instructed to walk as far as they could for 6 min along a 150 ft segment of a hallway. Vital signs were obtained before and after the test, including heart rate, blood pressure, and perceived exertion [26]. Subjects were instructed to stop immediately if signs and symptoms of exercise intolerance were experienced or observed [16]. After testing, each subject was given a pedometer2 to wear at the waist level and to attempt walking for a short distance to make sure the pedometer was functioning properly. Then they were instructed to wear the pedometer for the next 7 days from the time they woke up until they went to bed, except when they took a shower, and to continue their normal routine. They recorded the number of steps each day, then either emailed, called, or texted our research team their daily step counts. The reliability of the pedometer was previously tested on a few healthy individuals in our lab (Appendix 1). 2.3. Data analysis Descriptive statistics were used for demographic data. Gait data were exported to Excel for initial analysis. Pearson’s Product Moment Correlation analysis was conducted with SPSS 15.0 for Windows3 to examine the relationships between physical activity and the following performance measures: self-selected walking velocity, distance of the six-minute walk test, step length variability of the sound leg, step length variability of the amputated leg, and step width variability. We used the mean of 7-day step count to represent physical activity level since daily step count is a common measure of physical activity. To account for possible variation in the day to day step counts, we also examined the correlation between the mean of 7-day step counts and the total 7-day step counts. In view of the small sample size, regression analysis was not applicable. Therefore, we examined the correlations between physical activity level and anthropometric characteristics to identify potential co-variables. We also examined the relationship between step width and step width variability, and between step width and physical activity level to help us better understand the trend of step width variability. Statistical significance level was set at 0.05. 3. Results Two subjects dropped out from the study. One individual had back pain. The other individual developed redness in the residual limb and required prosthesis adjustment, so they stopped 1 2 3
CIR Systems, Inc., 60 Garlor Dr., Havertown, PA 19083, USA. Impulse, model B-1, Deer Park, NY 11729, USA. IBM Corporation, 1 New Orchard Rd., Armonk, NY 10504, USA.
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142 Table 1 Characteristics of subjects with lower-limb amputation. Mean SD
Total (n = 20) AK (n = 8)
BK (n = 12)
Age (years) Height (m) Weight (kg) BMI (kg/m2) Gender Women/men Prosthesis use (years) Cause of amputation Traumatic/vascular Other K Functional level K3/K2 With comorbidity No/yes Types and frequency of comorbidity Hypertension Diabetes Peripheral vascular dx Coronary artery dx Obesity Pain (back, phantom) hx of cancer Physical activity (steps per day)
50.6 10.6 1.75 0.08 90.5 22.5 29.3 7.0
45.8 8 1.74 0.07 86.5 19.7 28.2 5.7
53.7 10.9 1.76 0.09 93.2 24.7 30.1 7.8
5/15 12.4 13.2
3/5 10.2 12.8
2/10 13.9 13.8
12/7 1
4/1 3
8/2 2
16/4
6/2
10/2
4/16
1/7
3/9
4 3 3 2 7 3 3 4785 1868
1 2 2 1 3 2 2 3985 1246
3 1 1 1 4 1 1 5318 2066
SD: standard deviation; BMI: body mass index; AK: above-knee amputation; BK: below-knee amputation; TK: through-knee amputation.
Table 2 Characteristics of step length and step width variability in subjects with lower-limb amputation. Total (n = 20)
Mean (SD)
Sound leg Step length (cm) Step length variability Step length variability Prosthetic leg Step length (cm) Step length variability Step length variability Total (n = 20) Step width Step width Step width AK (n = 8) Step width Step width Step width BK (n = 12) Step width Step width Step width
Range
(SD) (cm) (cv) (%)
67.46 (9.69) 2.36 (1.05) 4% (2%)
55.33–85.11 1.26–5.32 1.8–8.1%
(SD) (cm) (cv) (%)
69.12 (12.31) 2.01 (0.78) 3% (2%)
40.10–92.22 0.93–4.67 1.44–8.88%
(cm) variability (SD) (cm) variability (cv) (%) (cm) variability (SD) (cm) variability (cv) (%) (cm) variability (SD) (cm) variability (cv) (%)
17.01 (5.84) 2.76 (1.18) 18.34% (11.14%) 19.66 (4.67) 2.23 (1.10) 12% (6%) 15.29 (5.79) 3.1 (1.08) 22.56% (11.32%)
7.03–29.62 0.36–5.09 5.7–48.4% 15.24–30.02 0.36–3.8 2.33–20.69% 7.03–29.6 1.68–4.64 10.97–48.41%
SD: standard deviation; cv: coefficient of variation; AK: above-knee amputation; BK: below-knee amputation.
recording their steps. Therefore, final data analysis was conducted on twenty subjects. Twelve of them had below-knee amputation and eight had above-knee amputation, including one with through-knee amputation. The subject characteristics, types of comorbidity, and step counts are shown in Table 1. There are no statistically significant differences between the above-knee subgroup and the below-knee subgroup in the anthropometric characteristics, including age, height, body weight, body mass index, and years of prosthesis use (p > 0.05). Most of our subjects emailed or called the research team their step counts each day with good compliance. Only three subjects required the research team to call them for the step counts. The correlation between the mean of 7-day step counts and the total 7day step counts is very strong (r = 0.99, p < 0.001). There are no significant correlations between physical activity level indicated by the mean of 7-day step counts and anthropometric data such as age, weight, body mass index, or years of prosthesis use (p > 0.05), except for body height which is of borderline significance (r = 0.443, p = 0.05). However, there are no significant relationships between body height and any of the gait parameters of interest (p > 0.05). The overall mean self-selected walking velocity is 1.12 m/s (SD = 0.24 m/s). The above-knee amputation subgroup has a mean speed of 1.11 (SD = 2.39 m/s), which is slower than the below-knee group’s (mean 1.27 m/s, SD = 2.29 m/s). All subjects completed the six-minute walk test without adverse physiologic responses. The overall mean 6MWD is 478.84 m (SD = 125.94 m). For the aboveknee subgroup, it is 427.16 m (SD = 91.89 m), which is shorter than that of the below-knee group (mean 513.29 m, SD = 137.05 m). The data on step length, step width, step length variability, step width variability are presented in Table 2. The variability is expressed by standard deviation and coefficient of variation. In general, the step length variability is much smaller than the step width variability. The mean step width for the above-knee group is much wider than that of the below-knee group. The Pearson correlation coefficients between physical activity level and performance measures are listed in Table 3. The trends of these correlations are similar for the group as a whole versus for separate subgroups (above-knee or below-knee amputation). In addition, a higher physical activity level is associated with a shorter step width (Fig. 1, r = 0.46, r < 0.05), and there is an inverse relationship between step width and step width variability (Fig. 2, r = 0.573, p < 0.05). 4. Discussion It is well known that physical activity has lots of health-related benefits and can reduce mortality rate from all causes [1]. The results of this study confirm our hypotheses that physical activity in people with lower-limb amputation is associated with their functional capacity and gait control as evidenced by the outcome
Table 3 Pearson correlation coefficients between physical activity and performance measures in subjects with lower-limb amputation. Physical activity (mean 7-day step count) Total (n = 20) SSWV (m/s) 6MWD (m) step length variability (cv in %) (sound leg) step length variability (cv in %) (amputated leg) step width variability (cv in %)
0.763** 0.67** 0.468* 0.465* 0.445*
Above-knee (n = 8) 0.575 0.523 0.561 0.371 0.258
cv: coefficient of variation; SSWV: self-selected walking velocity; 6MWD: distance of the six-minute walking test. * p < 0.05 (2-tailed). ** p < 0.01 (2-tailed).
Below-knee (n = 12) 0.826** 0.65* 0.304 0.511 0.341
[(Fig._1)TD$IG] Physical Activity (daily step count)
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12000 10000 8000 6000 4000 2000 0 0
10
20
30
40
Step Width (cm)
[(Fig._2)TD$IG]
Fig. 1. Relationship between step width and physical activity.
step width variability (%)
60% 50% ( r = - 0.573)
40% 30% 20% 10% 0% 0
5
10
15
20
25
30
35
step width (cm) Fig. 2. Relationship between step width and step width variability (in terms of coefficient of variation).
parameters of 6MWD, self-selected walking velocity (SSWV), step length variability and step width variability at SSWV. Therefore, the collaborative efforts from health care professionals in improving prostheses, balance control, and gait in amputees are vital, which could enhance amputees’ ability to engage in physical activities and harvest health benefits. For the correlation between physical activity and SSWV, with the sample size of twenty and the Pearson correlation coefficient (r) of 0.76, we have a statistical power of 99.4%. Though there is still a 0.6% possibility of a type II error, this correlation is quite strong. The range of SSWV is from 0.76 m/s to 1.77 m/s, which is broader than those reported in amputees [9] and in healthy individuals [13]; therefore, our sample might be quite representative of community-dwelling individuals with amputation. Other than physical activity level, a number of factors could also contribute to the wide range of SSWV, such as age, height, type of amputation, type of prosthesis, experience in prosthesis use, and existing comorbidities. But, the correlations between these anthropometric factors and SSWV are not significant. Those with above knee amputation walked slower than those with below-knee amputation, but the differences are not significant (p > 0.05). So, we thought that the correlation between physical activity and SSWV is not influenced by the above anthropometric characteristics. In addition, thirteen subjects had a SSWV of lower than 1.22 m/s – the typical speed required for crossing a signalized intersection safely [27]. Seven of them had SSWV of even slower than 1.1 m/s, which
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would seriously affect their safety functioning in a community and involvement in regular physical activity. Therefore, screening for SSWV in this population may help the early detection on the deterioration of their exercise capacity and overall physical health. Second, we confirmed that the physical activity level is positively related to cardiovascular capacity in individuals with lower-limb amputation, similar to those observed in individuals with stroke or COPD [15,24]. Our finding implies that aerobic capacity may be important in this population, in order to sustain the energy demand of regular physical activity. However, no causeeffect relationship could be established since this is a correlation type of study. Future experimental studies would be needed. In addition, the range of our 6MWD was large, from 279 m to 733 m, with three values of 279 m, 309 m, and 320 m much lower than those typically reported in non-amputees, i.e., 400–700 m [28]. One subject had above-knee amputation and a history of sarcoma, and the other two subjects had below-knee amputation and poor circulation of the legs due to diabetes. It seemed that their much reduced functional capacity was not only related to the amputation but also due to their cardiovascular comorbidities. Patients with chronic heart failure and a functional capacity less than 300 m on the 6MWD were suggested for medical intervention [17]. Maybe there is a critical functional capacity for patients with lower-limb amputation as well. Future studies with a larger sample size using regression analysis might be able to identify such a critical level of functional capacity, or physical activity level, in individuals with lower-limb amputation who may warrant medical attention. Third, we confirmed that a higher physical activity level is associated with a lower step length variability when walking at self-selected walking velocity. People with a higher physical activity level may have a better mechanical efficiency, thus less variance in step length is needed when speed is relatively constant as step length is a passive pendulum-like movement requiring not much energy and muscular control [18,19]. The large step width variability during step-to-step transition indicates that maintaining lateral stability remains a big challenge for amputees. In addition, the step width variability expressed in standard deviation did not seem much different between the above-knee and the below-knee groups in Table 2. But when expressed in terms of coefficient of variation, it clearly showed the above-knee group had much larger step width variability than those in the below-knee group. Previous studies often reported gait variability in terms of standard deviation [22,29,30], which does not take into account of the difference between the means. The use of coefficient of variation as an indicator of variability may be a better approach when comparing between studies. Next, there is an interesting finding that the physical activity is positively associated with step width variability when walking at self-selected walking velocity. In amputees, the ability to balance is highly related to their walking ability [31] and lateral stability requires continuously active control from both legs [18,19]. Therefore, with good muscular strength of the legs and balance, amputees could vary their step width from wider to narrower, or vice versa, in response to various perturbations during step-to-step transition. This may further enable them to engage in more physical activity, since they might have better adapted to their sensory and neuromuscular impairment than those with wide step width and less variability. For those with a lower physical activity level, they probably had more muscle weakness, locomotor control problems, and sensory impairments [18,19,22,29], such that they did not walk as much. If they did, they had to constantly adopt a wider step width in order to prevent falls as reflected in Fig. 2. Furthermore, we did not find any associations between physical activity and the anthropometric data (age, height, weight, and years of prosthesis use). Therefore, the influence of these potential confounding factors on physical activity is likely negligible.
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There are some limitations to the present study. The small sample size limits the generalization of our results. Our subjects were recruited from the community by convenience, rather than from out-patient prosthetic clinics or rehabilitation centers, so most of them probably did not have a functional or medical issue. Our subjects may have been more physically active to begin with, since they voluntarily responded to our advertisement. In addition, step count recorded by a pedometer could not differentiate between dynamic activities in as much detail as an accelerometrybased activity monitor. Hence, we could not determine whether our subjects were involved in dynamic transfer activities (e.g., sit to stand), walking, or stair-climbing. Future studies are warranted to elucidate these issues. Acknowledgements This study was supported by the Small Grants Program of the Texas Woman’s University. The authors would like to thank Fabian Bizama, Sloane Jammer, and Jackie Simmons for their assistance in data collection, and John Maddoux for his assistance in statistics. Conflict of interest: There is no conflict of interest of any author of the paper. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.gaitpost.2014. 03.012. References [1] Bize R, Johnson JA, Plotnikoff RC. Physical activity level and health-related quality of life in the general adult population: a systematic review. Prev Med 2007;456:401–15. [2] Haskell WL, Lee IM, Pate RR, Powell KE, Blair SN, Franklin BA, et al. American College of Sports Medicine, American Heart Association Physical activity and public health: updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Circulation 2007;1169:1081–93. [3] Balboa-Castillo T, Leon-Munoz LM, Graciani A, Rodriguez-Artalejo F, GuallarCastillon P. Longitudinal association of physical activity and sedentary behavior during leisure time with health-related quality of life in communitydwelling older adults. Health Qual Life Outcomes 2011;9:47. [4] Tudor-Locke C, Ainsworth BE, Thompson RW, Matthews CE. Comparison of pedometer and accelerometer measures of free-living physical activity. Med Sci Sports Exerc 2002;3412:2045–51. [5] Tudor-Locke C, Bassett Jr DR. How many steps/day are enough? Preliminary pedometer indices for public health. Sports Med 2004;341:1–8. [6] Bussmann JB, Grootscholten EA, Stam HJ. Daily physical activity and heart rate response in people with a unilateral transtibial amputation for vascular disease. Arch Phys Med Rehabil 2004;852:240–4. [7] Bussmann JB, Schrauwen HJ, Stam HJ. Daily physical activity and heart rate response in people with a unilateral traumatic transtibial amputation. Arch Phys Med Rehabil 2008;893:430–4.
[8] van den Berg-Emons RJ, Bussmann JB, Stam HJ. Accelerometry-based activity spectrum in persons with chronic physical conditions. Arch Phys Med Rehabil 2010;9112:1856–61. [9] Hsu MJ, Nielsen DH, Lin-Chan SJ, Shurr D. The effects of prosthetic foot design on physiologic measurements, self-selected walking velocity, and physical activity in people with transtibial amputation. Arch Phys Med Rehabil 2006;871:123–9. [10] Deans SA, McFadyen AK, Rowe PJ. Physical activity and quality of life: a study of a lower-limb amputee population. Prosthet Orthot Int 2008;322:186–200. [11] Zarrugh MY, Radcliffe CW. Predicting metabolic cost of level walking. Eur J Appl Physiol Occup Physiol 1978;383:215–23. [12] Studenski S, Perera S, Patel K, Rosano C, Faulkner K, Inzitari M, et al. Gait speed and survival in older adults. JAMA – J Am Med Assoc 2011;3051:50–8. [13] Bohannon RW. Comfortable and maximum walking speed of adults aged 20– 79 years: reference values and determinants. Age Ageing 1997;261:15–9. [14] US Department of Transportation. Federal highway administration. Signalized intersections – information guide. Chapter 2 – road user needs. In: Anonymous. FHWA-HRT-04-091. 2004;p. 17–31. [15] Mudge S, Stott NS. Timed walking tests correlate with daily step activity in persons with stroke. Arch Phys Med Rehabil 2009;902:296–301. [16] Lin SJ, Bose NH. Six-minute walk test in persons with transtibial amputation. Arch Phys Med Rehabil 2008;8912:2354–9. [17] Cahalin LP, Mathier MA, Semigran MJ, Dec GW, DiSalvo TG. The six-minute walk test predicts peak oxygen uptake and survival in patients with advanced heart failure. Chest 1996;1102:325–32. [18] Bauby CE, Kuo AD. Active control of lateral balance in human walking. J Biomech 2000;3311:1433–40. [19] Kuo AD, Donelan JM. Dynamic principles of gait and their clinical implications. Phys Ther 2010;902:157–74. [20] Donelan JM, Kram R, Kuo AD. Mechanical and metabolic determinants of the preferred step width in human walking. Proc Biol Sci 2001;2681480: 1985–92. [21] Sagawa Jr Y, Turcot K, Armand S, Thevenon A, Vuillerme N, Watelain E. Biomechanics and physiological parameters during gait in lower-limb amputees: a systematic review. Gait Posture 2011;334:511–26. [22] Brach JS, Berlin JE, VanSwearingen JM, Newman AB, Studenski SA. Too much or too little step width variability is associated with a fall history in older persons who walk at or near normal gait speed. J Neuroeng Rehabil 2005;2:21. [23] Vanicek N, Strike S, McNaughton L, Polman R. Gait patterns in transtibial amputee fallers vs non-fallers: biomechanical differences during level walking. Gait Posture 2009;293:415–20. [24] Moy ML, Danilack VA, Weston NA, Garshick E. Daily step counts in a US cohort with COPD. Respir Med 2012;1067:962–9. [25] Bilney B, Morris M, Webster K. Concurrent related validity of the GAITRite walkway system for quantification of the spatial and temporal parameters of gait. Gait Posture 2003;171:68–74. [26] Borg GA. Psychophysical bases of perceived exertion. Med Sci Sports Exerc 1982;145:377–81. [27] Langlois JA, Keyl PM, Guralnik JM, Foley DJ, Marottoli RA, Wallace RB. Characteristics of older pedestrians who have difficulty crossing the street. Am J Public Health 1997;873:393–7. [28] ATS Committee on Proficiency Standards for Clinical Pulmonary Function Laboratories. ATS statement: guidelines for the six-minute walk test. Am J Respir Crit Care Med 2002;1661:111–7. [29] Brach JS, Studenski S, Perera S, VanSwearingen JM, Newman AB. Stance time and step width variability have unique contributing impairments in older persons. Gait Posture 2008;273:431–9. [30] Richardson JK, Thies SB, DeMott TK, Ashton-Miller JA. Gait analysis in a challenging environment differentiates between fallers and nonfallers among older patients with peripheral neuropathy. Arch Phys Med Rehabil 2005;868:1539–44. [31] van Velzen JM, van Bennekom CA, Polomski W, Slootman JR, van der Woude LH, Houdijk H. Physical capacity and walking ability after lower limb amputation: a systematic review. Clin Rehabil 2006;2011:999–1016.
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Gait & Posture journal homepage: www.elsevier.com/locate/gaitpost
Physical activity, functional capacity, and step variability during walking in people with lower-limb amputation Suh-Jen Lin *, Katie D. Winston, Jill Mitchell, Jacob Girlinghouse, Karleigh Crochet School of Physical Therapy, Institute of Health Sciences – Dallas, Texas Woman’s University, TX, United States
A R T I C L E I N F O
A B S T R A C T
Article history: Received 19 July 2013 Received in revised form 4 March 2014 Accepted 8 March 2014
Physical activity is important for general health. For an individual with amputation to sustain physical activity, certain functional capacity might be needed. Gait variability is related to the incidence of falls. This study explored the relationship between physical activity and a few common performance measures (six-minute walk test, step length variability, step width variability, and comfortable walking speed) in individuals with unilateral lower-limb amputation. Twenty individuals completed the study (age: 50 11 yrs). Twelve of them had transtibial amputation, seven had transfemoral amputation, and one had through-knee amputation. Gait data was collected by the GaitRite instrumented walkway while participants performed a 3-min comfortable walking trial followed by a six-minute walk test. Physical activity was indicated by the mean of 7-day step counts via a pedometer. Gait variability was calculated by the coefficient of variation. Pearson correlation analysis was conducted between physical activity level and the 4 performance measures. Significance level was set at 0.05. Physical activity correlates strongly to comfortable walking speed (r = 0.76), six-minute walk distance (r = 0.67), and correlates fairly to step width variability (r = 0.44). On the contrary, physical activity is inversely related to step length variability of the prosthetic leg (r = 0.46) and of the sound leg (r = 0.47). Having better functional capacity and lateral stability might enable an individual with lower-limb amputation to engage in a higher physical activity level, or vise versa. However, our conclusions are only preliminary as limited by the small sample size. ß 2014 Elsevier B.V. All rights reserved.
Keywords: Amputation Gait variability Walk test Physical activity Functional capacity
1. Introduction Studies have consistently showed a positive association between physical activity and health-related quality of life and a reduction of all-cause mortality [1]. Current guidelines recommend that adults engage in moderate-intensity physical activity 5 days a week or vigorous-intensity activity 30 min a day for at least 3 days a week [2]. Physical activity can be estimated by a selfreported questionnaire, an accelerometer, or a pedometer [1,3]. A pedometer recording step counts is inexpensive, reliable, and correlates well with an accelerometer [4]. To sustain optimal physical activity a person may require a certain degree of aerobic capacity, muscle strength, and balance abilities. Most people with a lower-limb amputation are less active. Ten thousand steps per day is the recommended activity level for adults [2], whereas a sedentary lifestyle is generally defined as
* Corresponding author at: TWU Institute of Health Science – Dallas, 5500 Southwestern Medical Avenue, Dallas, TX 75235, United States. Tel.: +214 689 7718; fax: +214 689 7703. E-mail address: [email protected] (S.-J. Lin). http://dx.doi.org/10.1016/j.gaitpost.2014.03.012 0966-6362/ß 2014 Elsevier B.V. All rights reserved.
fewer than 5000 steps per day [5]. Daily step counts in individuals with lower-limb amputation range from 2500 to 8500 steps depending on age, reason of amputation (vascular vs. traumatic) [6,7], level of amputation, comorbidity [8], and types of prosthetic foot [9]. For individuals with lower-limb amputation, a higher physical activity level was associated with a better perceived quality of life [10]. Therefore, promoting physical activity is important in this population. A person’s self-selected walking speed (SSWV) is very close to speeds with the least energy consumption per distance traveled [11]. It is a reliable measure and a strong predictor of disability [12]. In general, It ranges from 1.27 m/s to 1.46 m/s in normal adults and decreases with age [13]. In individuals with transtibial amputation, it ranges from 1.12 m/s to 1.18 m/s [9], which is just slightly faster than the speed required for community ambulation [14]. A person with a higher physical activity level is shown to have a faster SSWV [15]. However, we do not know whether this is also true for individuals with lower-limb amputation. Determining exercise capacity is challenging for people with disabilities, and standard equipment may not be applicable such as treadmill, upright cycle ergometer, and stair stepper machine. Field exercise tests, such as walk tests, provide an alternative. The
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six-minute walk test measures the maximal distance a person can cover in 6 min (distance of the six-minute walk test, or 6MWD). It is easy to administer, relates to day-to-day activity, and physiological responses can be monitored. In addition, it demonstrates good test-retest reliability [16], and is strongly related to a person’s peak oxygen consumption [17]. A 6MWD of less than 300 m predicts an increased likelihood of death within 6 months in patients with heart failure [17]. Relationship between physical activity and 6MWD has not been reported in individuals with amputation. During walking, the anterior/posterior stepping motion control is passive in nature or only requires a low level of control; whereas lateral stability requires more active control through adjusting step width continuously [18,19]. At normal walking speed, the preferred step width is about 12 cm, which is the most energy efficient [20]. During running, the step width is near zero, in order to enhance step-to-step transition. People with lower-limb amputation often adapt a larger base of support for compensation of impaired sensation due to limb loss [21]. If an amputee can narrow the step width of walking to be close to that of nonamputees, then he/she must have a better control of lateral stability and could walk faster. At normal walking speed, mechanical efficiency is known to inversely relate to step length variability [11]. Gait variability is often expressed as the standard deviation, or coefficient of variation, of a series of steps. Increased step length variability or reduced step width variability is associated with increased risk of falls [22,23]. Exploring the relationship between physical activity and gait variability may shed light on the effects of promoting physical activity on gait performance in amputees. The purpose of this study was to explore the associations between physical activity level and physical performance measures (self-selected walking velocity, 6MWD, step length variability, and step width variability) in individuals with lowerlimb amputation. We hypothesized that a higher physical activity level, as indicated by daily step count, would be associated with a faster self-selected walking velocity, a higher functional capacity, a smaller step length variability, and a larger step width variability during comfortable walking in persons with lowerlimb amputation.
2. Materials and methods 2.1. Subjects An appropriate sample size was estimated based on the finding that 6MWD was a strong predictor of step count and step rate, accounting for 38–54% of the variance [15,24]. Assuming the standardized effect size for Pearson’s correlation of 0.62, to achieve a statistical power of 80% at an a2 level of 0.05, we estimated that about 18 subjects were needed. Subjects were recruited from local amputee support groups in a metropolitan area. The inclusion criteria were: (1) independent walking with a prosthesis, (2) experience with prosthesis use over 6 months, (3) intact skin condition of the residual limb, and (4) well controlled medical conditions. Thirty-five people with lower-limb amputation were recruited. Thirteen individuals were excluded due to the following reasons: 2 required a walking aid, 2 were having their prostheses adjusted, 1 had an ankle fusion, 1 had a bilateral amputation, 2 had health issues, and 5 decided not to participate due to commuting or scheduling conflicts. Therefore, a total of 22 subjects were enrolled and informed consent was obtained. This study was approved by the Institutional Review Board of our institution.
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2.2. Protocol Each subject came in for a one-hour session consisting of a history interview for demographic data and measurement of selfselected walking velocity and 6MWD. Each subject was instructed to walk at his/her comfortable speed for three minutes back and forth across a 13.41 m (44 ft) segment of a hallway with a 4-m GAITRite1 instrumented mat placed at the middle of the segment. The GAITRite system was shown to have good test-retest reliability and concurrent validity [25]. Step length is defined as the distance from the heel center of the current footprint to the heel center of the previous footprint on the opposite foot along the line of progression. Step width is defined as the mediolateral distance from the midline midpoint of one footprint to the line formed by the midline midpoint of two footprints of the opposite foot. Step variability is expressed as the coefficient of variation of a series of steps (i.e. (standard deviation/mean) 100%). For the six-minute walk test, each participant was instructed to walk as far as they could for 6 min along a 150 ft segment of a hallway. Vital signs were obtained before and after the test, including heart rate, blood pressure, and perceived exertion [26]. Subjects were instructed to stop immediately if signs and symptoms of exercise intolerance were experienced or observed [16]. After testing, each subject was given a pedometer2 to wear at the waist level and to attempt walking for a short distance to make sure the pedometer was functioning properly. Then they were instructed to wear the pedometer for the next 7 days from the time they woke up until they went to bed, except when they took a shower, and to continue their normal routine. They recorded the number of steps each day, then either emailed, called, or texted our research team their daily step counts. The reliability of the pedometer was previously tested on a few healthy individuals in our lab (Appendix 1). 2.3. Data analysis Descriptive statistics were used for demographic data. Gait data were exported to Excel for initial analysis. Pearson’s Product Moment Correlation analysis was conducted with SPSS 15.0 for Windows3 to examine the relationships between physical activity and the following performance measures: self-selected walking velocity, distance of the six-minute walk test, step length variability of the sound leg, step length variability of the amputated leg, and step width variability. We used the mean of 7-day step count to represent physical activity level since daily step count is a common measure of physical activity. To account for possible variation in the day to day step counts, we also examined the correlation between the mean of 7-day step counts and the total 7-day step counts. In view of the small sample size, regression analysis was not applicable. Therefore, we examined the correlations between physical activity level and anthropometric characteristics to identify potential co-variables. We also examined the relationship between step width and step width variability, and between step width and physical activity level to help us better understand the trend of step width variability. Statistical significance level was set at 0.05. 3. Results Two subjects dropped out from the study. One individual had back pain. The other individual developed redness in the residual limb and required prosthesis adjustment, so they stopped 1 2 3
CIR Systems, Inc., 60 Garlor Dr., Havertown, PA 19083, USA. Impulse, model B-1, Deer Park, NY 11729, USA. IBM Corporation, 1 New Orchard Rd., Armonk, NY 10504, USA.
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142 Table 1 Characteristics of subjects with lower-limb amputation. Mean SD
Total (n = 20) AK (n = 8)
BK (n = 12)
Age (years) Height (m) Weight (kg) BMI (kg/m2) Gender Women/men Prosthesis use (years) Cause of amputation Traumatic/vascular Other K Functional level K3/K2 With comorbidity No/yes Types and frequency of comorbidity Hypertension Diabetes Peripheral vascular dx Coronary artery dx Obesity Pain (back, phantom) hx of cancer Physical activity (steps per day)
50.6 10.6 1.75 0.08 90.5 22.5 29.3 7.0
45.8 8 1.74 0.07 86.5 19.7 28.2 5.7
53.7 10.9 1.76 0.09 93.2 24.7 30.1 7.8
5/15 12.4 13.2
3/5 10.2 12.8
2/10 13.9 13.8
12/7 1
4/1 3
8/2 2
16/4
6/2
10/2
4/16
1/7
3/9
4 3 3 2 7 3 3 4785 1868
1 2 2 1 3 2 2 3985 1246
3 1 1 1 4 1 1 5318 2066
SD: standard deviation; BMI: body mass index; AK: above-knee amputation; BK: below-knee amputation; TK: through-knee amputation.
Table 2 Characteristics of step length and step width variability in subjects with lower-limb amputation. Total (n = 20)
Mean (SD)
Sound leg Step length (cm) Step length variability Step length variability Prosthetic leg Step length (cm) Step length variability Step length variability Total (n = 20) Step width Step width Step width AK (n = 8) Step width Step width Step width BK (n = 12) Step width Step width Step width
Range
(SD) (cm) (cv) (%)
67.46 (9.69) 2.36 (1.05) 4% (2%)
55.33–85.11 1.26–5.32 1.8–8.1%
(SD) (cm) (cv) (%)
69.12 (12.31) 2.01 (0.78) 3% (2%)
40.10–92.22 0.93–4.67 1.44–8.88%
(cm) variability (SD) (cm) variability (cv) (%) (cm) variability (SD) (cm) variability (cv) (%) (cm) variability (SD) (cm) variability (cv) (%)
17.01 (5.84) 2.76 (1.18) 18.34% (11.14%) 19.66 (4.67) 2.23 (1.10) 12% (6%) 15.29 (5.79) 3.1 (1.08) 22.56% (11.32%)
7.03–29.62 0.36–5.09 5.7–48.4% 15.24–30.02 0.36–3.8 2.33–20.69% 7.03–29.6 1.68–4.64 10.97–48.41%
SD: standard deviation; cv: coefficient of variation; AK: above-knee amputation; BK: below-knee amputation.
recording their steps. Therefore, final data analysis was conducted on twenty subjects. Twelve of them had below-knee amputation and eight had above-knee amputation, including one with through-knee amputation. The subject characteristics, types of comorbidity, and step counts are shown in Table 1. There are no statistically significant differences between the above-knee subgroup and the below-knee subgroup in the anthropometric characteristics, including age, height, body weight, body mass index, and years of prosthesis use (p > 0.05). Most of our subjects emailed or called the research team their step counts each day with good compliance. Only three subjects required the research team to call them for the step counts. The correlation between the mean of 7-day step counts and the total 7day step counts is very strong (r = 0.99, p < 0.001). There are no significant correlations between physical activity level indicated by the mean of 7-day step counts and anthropometric data such as age, weight, body mass index, or years of prosthesis use (p > 0.05), except for body height which is of borderline significance (r = 0.443, p = 0.05). However, there are no significant relationships between body height and any of the gait parameters of interest (p > 0.05). The overall mean self-selected walking velocity is 1.12 m/s (SD = 0.24 m/s). The above-knee amputation subgroup has a mean speed of 1.11 (SD = 2.39 m/s), which is slower than the below-knee group’s (mean 1.27 m/s, SD = 2.29 m/s). All subjects completed the six-minute walk test without adverse physiologic responses. The overall mean 6MWD is 478.84 m (SD = 125.94 m). For the aboveknee subgroup, it is 427.16 m (SD = 91.89 m), which is shorter than that of the below-knee group (mean 513.29 m, SD = 137.05 m). The data on step length, step width, step length variability, step width variability are presented in Table 2. The variability is expressed by standard deviation and coefficient of variation. In general, the step length variability is much smaller than the step width variability. The mean step width for the above-knee group is much wider than that of the below-knee group. The Pearson correlation coefficients between physical activity level and performance measures are listed in Table 3. The trends of these correlations are similar for the group as a whole versus for separate subgroups (above-knee or below-knee amputation). In addition, a higher physical activity level is associated with a shorter step width (Fig. 1, r = 0.46, r < 0.05), and there is an inverse relationship between step width and step width variability (Fig. 2, r = 0.573, p < 0.05). 4. Discussion It is well known that physical activity has lots of health-related benefits and can reduce mortality rate from all causes [1]. The results of this study confirm our hypotheses that physical activity in people with lower-limb amputation is associated with their functional capacity and gait control as evidenced by the outcome
Table 3 Pearson correlation coefficients between physical activity and performance measures in subjects with lower-limb amputation. Physical activity (mean 7-day step count) Total (n = 20) SSWV (m/s) 6MWD (m) step length variability (cv in %) (sound leg) step length variability (cv in %) (amputated leg) step width variability (cv in %)
0.763** 0.67** 0.468* 0.465* 0.445*
Above-knee (n = 8) 0.575 0.523 0.561 0.371 0.258
cv: coefficient of variation; SSWV: self-selected walking velocity; 6MWD: distance of the six-minute walking test. * p < 0.05 (2-tailed). ** p < 0.01 (2-tailed).
Below-knee (n = 12) 0.826** 0.65* 0.304 0.511 0.341
[(Fig._1)TD$IG] Physical Activity (daily step count)
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12000 10000 8000 6000 4000 2000 0 0
10
20
30
40
Step Width (cm)
[(Fig._2)TD$IG]
Fig. 1. Relationship between step width and physical activity.
step width variability (%)
60% 50% ( r = - 0.573)
40% 30% 20% 10% 0% 0
5
10
15
20
25
30
35
step width (cm) Fig. 2. Relationship between step width and step width variability (in terms of coefficient of variation).
parameters of 6MWD, self-selected walking velocity (SSWV), step length variability and step width variability at SSWV. Therefore, the collaborative efforts from health care professionals in improving prostheses, balance control, and gait in amputees are vital, which could enhance amputees’ ability to engage in physical activities and harvest health benefits. For the correlation between physical activity and SSWV, with the sample size of twenty and the Pearson correlation coefficient (r) of 0.76, we have a statistical power of 99.4%. Though there is still a 0.6% possibility of a type II error, this correlation is quite strong. The range of SSWV is from 0.76 m/s to 1.77 m/s, which is broader than those reported in amputees [9] and in healthy individuals [13]; therefore, our sample might be quite representative of community-dwelling individuals with amputation. Other than physical activity level, a number of factors could also contribute to the wide range of SSWV, such as age, height, type of amputation, type of prosthesis, experience in prosthesis use, and existing comorbidities. But, the correlations between these anthropometric factors and SSWV are not significant. Those with above knee amputation walked slower than those with below-knee amputation, but the differences are not significant (p > 0.05). So, we thought that the correlation between physical activity and SSWV is not influenced by the above anthropometric characteristics. In addition, thirteen subjects had a SSWV of lower than 1.22 m/s – the typical speed required for crossing a signalized intersection safely [27]. Seven of them had SSWV of even slower than 1.1 m/s, which
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would seriously affect their safety functioning in a community and involvement in regular physical activity. Therefore, screening for SSWV in this population may help the early detection on the deterioration of their exercise capacity and overall physical health. Second, we confirmed that the physical activity level is positively related to cardiovascular capacity in individuals with lower-limb amputation, similar to those observed in individuals with stroke or COPD [15,24]. Our finding implies that aerobic capacity may be important in this population, in order to sustain the energy demand of regular physical activity. However, no causeeffect relationship could be established since this is a correlation type of study. Future experimental studies would be needed. In addition, the range of our 6MWD was large, from 279 m to 733 m, with three values of 279 m, 309 m, and 320 m much lower than those typically reported in non-amputees, i.e., 400–700 m [28]. One subject had above-knee amputation and a history of sarcoma, and the other two subjects had below-knee amputation and poor circulation of the legs due to diabetes. It seemed that their much reduced functional capacity was not only related to the amputation but also due to their cardiovascular comorbidities. Patients with chronic heart failure and a functional capacity less than 300 m on the 6MWD were suggested for medical intervention [17]. Maybe there is a critical functional capacity for patients with lower-limb amputation as well. Future studies with a larger sample size using regression analysis might be able to identify such a critical level of functional capacity, or physical activity level, in individuals with lower-limb amputation who may warrant medical attention. Third, we confirmed that a higher physical activity level is associated with a lower step length variability when walking at self-selected walking velocity. People with a higher physical activity level may have a better mechanical efficiency, thus less variance in step length is needed when speed is relatively constant as step length is a passive pendulum-like movement requiring not much energy and muscular control [18,19]. The large step width variability during step-to-step transition indicates that maintaining lateral stability remains a big challenge for amputees. In addition, the step width variability expressed in standard deviation did not seem much different between the above-knee and the below-knee groups in Table 2. But when expressed in terms of coefficient of variation, it clearly showed the above-knee group had much larger step width variability than those in the below-knee group. Previous studies often reported gait variability in terms of standard deviation [22,29,30], which does not take into account of the difference between the means. The use of coefficient of variation as an indicator of variability may be a better approach when comparing between studies. Next, there is an interesting finding that the physical activity is positively associated with step width variability when walking at self-selected walking velocity. In amputees, the ability to balance is highly related to their walking ability [31] and lateral stability requires continuously active control from both legs [18,19]. Therefore, with good muscular strength of the legs and balance, amputees could vary their step width from wider to narrower, or vice versa, in response to various perturbations during step-to-step transition. This may further enable them to engage in more physical activity, since they might have better adapted to their sensory and neuromuscular impairment than those with wide step width and less variability. For those with a lower physical activity level, they probably had more muscle weakness, locomotor control problems, and sensory impairments [18,19,22,29], such that they did not walk as much. If they did, they had to constantly adopt a wider step width in order to prevent falls as reflected in Fig. 2. Furthermore, we did not find any associations between physical activity and the anthropometric data (age, height, weight, and years of prosthesis use). Therefore, the influence of these potential confounding factors on physical activity is likely negligible.
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There are some limitations to the present study. The small sample size limits the generalization of our results. Our subjects were recruited from the community by convenience, rather than from out-patient prosthetic clinics or rehabilitation centers, so most of them probably did not have a functional or medical issue. Our subjects may have been more physically active to begin with, since they voluntarily responded to our advertisement. In addition, step count recorded by a pedometer could not differentiate between dynamic activities in as much detail as an accelerometrybased activity monitor. Hence, we could not determine whether our subjects were involved in dynamic transfer activities (e.g., sit to stand), walking, or stair-climbing. Future studies are warranted to elucidate these issues. Acknowledgements This study was supported by the Small Grants Program of the Texas Woman’s University. The authors would like to thank Fabian Bizama, Sloane Jammer, and Jackie Simmons for their assistance in data collection, and John Maddoux for his assistance in statistics. Conflict of interest: There is no conflict of interest of any author of the paper. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.gaitpost.2014. 03.012. References [1] Bize R, Johnson JA, Plotnikoff RC. Physical activity level and health-related quality of life in the general adult population: a systematic review. Prev Med 2007;456:401–15. [2] Haskell WL, Lee IM, Pate RR, Powell KE, Blair SN, Franklin BA, et al. American College of Sports Medicine, American Heart Association Physical activity and public health: updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Circulation 2007;1169:1081–93. [3] Balboa-Castillo T, Leon-Munoz LM, Graciani A, Rodriguez-Artalejo F, GuallarCastillon P. Longitudinal association of physical activity and sedentary behavior during leisure time with health-related quality of life in communitydwelling older adults. Health Qual Life Outcomes 2011;9:47. [4] Tudor-Locke C, Ainsworth BE, Thompson RW, Matthews CE. Comparison of pedometer and accelerometer measures of free-living physical activity. Med Sci Sports Exerc 2002;3412:2045–51. [5] Tudor-Locke C, Bassett Jr DR. How many steps/day are enough? Preliminary pedometer indices for public health. Sports Med 2004;341:1–8. [6] Bussmann JB, Grootscholten EA, Stam HJ. Daily physical activity and heart rate response in people with a unilateral transtibial amputation for vascular disease. Arch Phys Med Rehabil 2004;852:240–4. [7] Bussmann JB, Schrauwen HJ, Stam HJ. Daily physical activity and heart rate response in people with a unilateral traumatic transtibial amputation. Arch Phys Med Rehabil 2008;893:430–4.
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