Walking is a fundamental part of everyday life and depends on balance, joint motion, endurance, and muscle strength.1 Several studies have shown that walking is the most common physical activity among older people,2,3 and it is practiced more regularly than more vigorous activities.4
Measuring walking speed is easy and can tell much about older adults living in a home care setting.5 Compared with other mobility tests such as chair stand, stair climbing, and Timed Up and Go, walking speed is the most frequently used method.6 Walking speed gives information about a person's physical performance. Also, the difference between habitual walking speed and maximal walking speed (fast walking) provides information about a person's functional reserve capacity.7 Both habitual and maximal walking speeds are influenced by age, sex, height, muscle strength in the lower extremities, and body composition.8,9 The difference between habitual and maximal walking speed can be explained by an increase in cadence, step length, and stride length in maximal walking speed compared to habitual speed.10 Walking speed can be useful as a measurement for screening older people who may need a detailed physical therapy evaluation and intervention.11,12 The method is easy to execute in a clinical setting, is inexpensive, and does not require any special equipment. It is also easy to administer.11,13 There are many different descriptions of how to perform the test. Different distances have been reported in the literature, primarily 4, 6, or 10 m, but longer distances have also been used. Differences in test distances make test comparisons difficult.1
Both habitual and maximal walking speeds are highly valid measurements in terms of both concurrent and discriminative validity.14 Walking speed can also predict fracture, cognitive decline, cardiovascular diseases, hospitalization, institutionalization, and mortality.6,15 A systematic review showed that several different cutoffs have been reported in the literature, but they vary depending on whether the target group is a healthy or frail population. The cutoff scores have been evaluated in relation to prediction of health-related outcomes, fear of falling, and fall risk. The most common value reported is 1 m/s.14 This cutoff has also been suggested in screening for sarcopenia in older people, and those who score below the cutoff should be transferred for body composition assessment.16 Habitual walking speed has been shown to be reliable in older people, but no studies have evaluated the reliability of maximal walking speed in older people with different medical diagnoses.14
Many older people living in various types of assisted living have several diagnoses and poor physical performance. These conditions may also result in the development of additional risk factors and a greater fall risk.17 It is very important to analyze and estimate physical limitations in these people to prevent falls and further physical decline. Exercise programs have been shown to reduce the risk of falling as well as physical decline.18,19 Walking speed can also be used as an outcome measure for evaluating a physical exercise program,20 but to do so, relative and absolute reliability need to be established. Therefore, the aim of this study was to investigate the reliability of maximal walking speed using test-retest in older people living in a residential care unit.
A sample of older people living in a residential care unit was invited to participate in the study. Both verbal and written information about the purpose of the study was given in accordance with the Helsinki declaration. Subjects who agreed to participate in the study gave written informed consent.
Inclusion criteria were people who could walk with or without walking aids and who could understand and follow given instructions. Exclusion criteria were people with infections or people who had recently had infections that affected their physical performance, people with psychiatric diagnoses such as depression, as well as stroke in the last 12 months and myocardial infarction in the last 6 months.
The number of and the most common diagnoses were retrieved from the patient's medical journals and listed. The subjects were also asked about their dependency in activities of daily living according to the Katz index.21
Data were collected twice for each individual with a 1-week interval. The subjects walked with or without walking aids. They performed one trial to get familiarized with the test and were then allowed a 5-minute rest before starting the test. After a week, the second test was performed under the same circumstances and at the same time of day. The subjects were not allowed to exercise between the test occasions beyond their normal exercise activities. The same comfortable footwear and walking aids were used on both occasions.
Maximal walking speed was measured for a distance of 10 m with an acceleration and deceleration phase of 2 m each. The subjects were instructed to walk to the first line and increase to maximum speed when crossing the first line until they crossed the second line. The evaluator walked beside the participant, began timing with a digital stopwatch when the subject's first foot crossed the starting line, and stopped the timing when the first foot crossed the second line.22,23
Intraclass correlation coefficient (ICC) (1,1),24 as well as Bland and Altman's 95% limits of agreement25,26 were analyzed using JMP 6.0 (SAS Institute, Cary, NC) and Excel 2007 (Microsoft, Redmond, WA). The 95% limits of agreement were introduced by Bland and Altman as an alternative and complement to the correlation coefficient for method comparison studies. Two methods may be highly correlated, yielding a high value for the correlation coefficient, although the agreement is low. The coefficient of the variation was calculated to express standard error as a percentage.27 “Line of equality” was used to obtain a visual estimate of the correlation between the two measurements.25 A paired t test was used to analyze whether there was a systematic difference between test occasions 1 and 2.
Of the 35 participants who were enrolled in the study, 4 dropped out at the first test occasion due to fatigue, so 31 subjects participated on both test occasions. The mean age was 89 years (74–100 years); 25 women and 6 men participated and 24 subjects used a walker. Fifteen subjects were dependent in personal activities of daily living, whereas 11 were dependent in daily bath or shower (Table 1). The most common diagnoses were cardiovascular diseases, joint diseases, impaired vision and/or hearing, and osteoporosis (Table 2).
The results of the test at occasions 1 and 2 are shown in Figure 1. The analysis showed an ICC (1,1) of 0.86 between the 2 tests. The mean value of the first occasion was 0.97 m/s (SD = 0.30 m/s), and the mean value of the second occasion was 0.95 m/s (SD = 0.29 m/s). The mean difference was −0.03 m/s (SD = 0.16 m/s), and the Bland and Altman's 95% limits of agreement for the mean difference were −0.33 to + 0.27 m/s (Figure 2). Calculation with the paired t test showed that there was no systematic difference between measurements (P = .3742). The coefficient of variation was 11.4%.
The result of the study showed a high correlation between tests with a mean difference of 0.03 m/s. To our knowledge, no studies have evaluated test-retest reliability for maximal walking speed in this target group. According to previous studies, ICC values for similar target groups vary between 0.79 and 0.94 for habitual walking speed.28,29 One study has evaluated the reliability of maximal walking speed on a GaitRite showing an ICC of 0.97; the tests were, however, performed during the same day.30 Taken together, the difference in measurement, distance, and speed limits comparability.
ICC is a relative measure of variation within subject in relation to the variation between subjects and takes into account the systematic error and is the recommended choice in these types of analyses.24 Absolute reliability has been suggested to be measured with standard error of measurement31 or Bland and Altman's “95% limits of agreement25,32 because it shows the difference between the 2 measurements. The advantage with Bland and Altman's method is that it also calculates the standard deviation of the difference between measurements. In this study, the Bland and Altman's analyses showed variance of −0.33 to +0.27 m/s. This may seem elevated, but the frail subjects' day-to-day variability must be considered. In addition, the performance of maximal walking speed has been shown to be related to several factors such as age, gender, leg extensor power, standing balance, and physical activity.33
Another explanation of the difference between the 2 measurements could be due to the instructions from the test leader. When the test leader encouraged the subject to walk as fast as possible an initial reduction of walking speed was in some cases observed, but maximum speed was soon reached. This effect should be considered when performing the test. Also, the subjects included in this study were frail with several diagnoses and many of them were dependent on personal activities of daily living. This might influence each subject's daily condition and thus also the differences between the 2 test occasions. Similar findings have been reported in a study evaluating the reliability of Timed Up and Go. The study showed that the slower the subjects performed the test, the more the variance increased.34 Another explanation of the difference between tests 1 and 2 could be the instructor's tone of voice, body language, and feedback.
In health care and rehabilitation settings, knowledge of an older person's physical performance is of utmost importance to deliver appropriate care. The emphasis on individual targeted exercise programs for frail older people19 requires valid and reliable instruments. The variance of −0.33/+0.27 m/s needs therefore to be taken into account if the test is used to evaluate, for example, a physical exercise program. A change within the limits cannot be regarded as a true change. This is of importance both in a clinical setting as well as in randomized controlled trials. Another clinical implication is that walking speed has been suggested to be used as a functional “vital sign” to determine outcomes such as functional capacity, discharge location, and the need for rehabilitation.35
The major limitation of the study is the rather small sample size in relation to the analyses of 95% limits of agreement. According to Altman,36 the sample size should be large enough to allow the limits of agreement to be estimated well; otherwise, there might be a risk of too much variance in ranges. Thus a sample size of at least 50 but preferably larger is desirable.36 This might also explain the results of this study.
Maximum walking speed tests in institution-dwelling people aged 74 years and older, with several different diagnoses, shows high reliability. The method is easy to perform in a clinical setting at a minimal cost. The method can be recommended for use in this group before and after a training period. However, the mean difference −0.03 m/s and Bland and Altman's 95% limits of agreement of −0.33 to +0.27 m/s needs to be taken into account when evaluating the effect of a training period.
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Keywords:Copyright © 2013 the Section on Geriatrics of the American Physical Therapy Association
evaluation; physical function; physical performance; test-retest; screening