Prospective epidemiological studies support the belief that a physically active lifestyle can lower the risk of developing various chronic diseases such as coronary artery disease, Type 2 diabetes mellitus, hypertension, and obesity (1). With an emphasis on promoting a physically active lifestyle, numerous studies have examined the practicality and feasibility of using the pedometer as a tool for measuring physical activity levels (10,11,17,22,23,28,29). Pedometers are devices that are typically worn at the waist and are capable of counting steps. Some models also calculate distance and estimate energy expenditure. Pedometers are a means of objectively measuring ubiquitous, ambulatory activity as well as many types of structured physical activities (24).
The three main areas in which pedometer models may differ are cost, mechanism, and sensitivity of the device. There is considerable variation in the cost of a pedometer, which can range anywhere from $10 to $200. Given the wide range of costs of various pedometers, a less expensive pedometer becomes an attractive option for those wanting to do large-scale studies. Thus, it would be of interest to determine whether some of the less expensive pedometers are as accurate as some of the more costly versions. The internal mechanism is also a distinguishing point among the various brands and models of pedometers. There are three primary mechanisms by which pedometers function. The first type uses a spring-suspended horizontal lever arm that moves up and down in response to the hip’s vertical accelerations. This movement opens and closes an electrical circuit; the lever arm makes an electrical contact (metal-on-metal contact) and a step is registered. The second type of mechanism is a magnetic reed proximity switch. With this mechanism, a magnet connected to a spring-suspended horizontal lever arm within the pedometer moves up and down with each vertical acceleration of the hip. The magnetic field triggers a proximity switch encased in a glass cylinder and a step is counted. The third type uses an accelerometer-type mechanism consisting of a horizontal beam and a piezoelectric crystal. Pedometers using this particular mechanism can distinguish between differing intensities of exercise when estimating caloric expenditure. Finally, pedometers may also differ in their sensitivity, which is a function of the vertical acceleration “threshold” needed to trigger a step. Although this issue is related to the mechanism, the sensitivity of the internal mechanisms of different pedometers can vary as can the quality of the mechanism itself.
In general, pedometers are most accurate in counting steps, less accurate in calculating distance, and even less accurate at estimating energy expenditure (2,4). Because steps are the most direct expression of what the pedometer actually measures (25), most researchers recommend reporting pedometer data as steps (4,25). A previous study conducted by Bassett et al. (2) assessed the accuracy of five electronic pedometers in measuring distance walked and steps taken on a sidewalk course and found that pedometers varied significantly in the pedometer-calculated distance over 4.88 km. Due to the potential for such inaccuracies between pedometer models, it is essential that pedometers be tested for accuracy.
In addition to the variation that exists between models, it is possible for discrepancies to exist within a particular pedometer model (intramodel reliability). Given the potential for differences in manufacturing tolerances and design specifications, it is conceivable for devices of the same model to differ significantly in steps counted. Thus, it is evident that the reliability of pedometers within a particular model should be assessed.
Considering the fact that a great number of pedometer models have been introduced in recent years and that variability exists not only in the cost but also in the mechanism and sensitivity among pedometers, it would be beneficial to determine the accuracy of a variety of pedometers. In addition, the only multibrand comparison was carried out in 1996 (2), and none of the pedometers that were assessed at that time are currently available. Therefore, the purpose of this study was to determine the accuracy and reliability of 10 electronic pedometers for counting steps.
METHODS
Pedometers.
Ten models of commercially available electronic pedometers were assessed in this study: Freestyle Pacer Pro (FR), Kenz Lifecorder (KZ), New Lifestyles NL-2000 (NL), Omron HJ-105 (OM), Oregon Scientific PE316CA (OR), Sportline 330 (SL330) and 345 (SL345), Walk4Life LS 2525 (WL), Yamax Skeletone EM-180 (SK), and the Yamax Digi-Walker SW-701 (DW). Pedometer characteristics are presented in Table 1.
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TABLE 1:
Pedometer characteristics.
Subjects.
Ten male and 10 female adults (22–69 yr of age) volunteered to participate in the study. The procedures were reviewed and approved by the Institutional Review Board at the University of Tennessee. Each subject completed a Physical Activity Readiness Questionnaire (PAR-Q) and signed a written informed consent before participating in the study. Height was measured without shoes using a stadiometer and weight was also assessed without shoes in light clothing using a calibrated physician’s scale. In addition, each subject’s stride length was determined before participation in the study. To determine stride length, subjects were asked to take 20 strides at their normal walking pace on an outdoor track. The total distance was divided by 20, to calculate average stride length. Physical characteristics of the subjects are presented in Table 2.
TABLE 2:
Physical characteristics of subjects.
The subjects then took part in a series of walks around a 400-m outdoor track. Pedometer placement was standardized by placing it on the belt or waistband, in the mid-line of the thigh, consistent with the manufacturers’ recommendations. Pedometers with a variable sensitivity switch (OM, OR) were always placed in the middle setting. Devices of the same model were worn on both the right and left sides of the body while the subject walked a lap around the 400-m track. Then, two other devices of the same model were tested during a subsequent lap around the track to determine intramodel reliability. This procedure was repeated until four pedometers representing each of the 10 models were tested. The actual steps taken were determined by a researcher using a hand-tally counter. The researcher walked behind the subject to avoid influencing the subject’s pace. Each subject walked at his/her own normal walking speed, and the amount of time it took to complete the lap was measured to calculate walking speed. The testing took place over the course of 1–4 d, and the subjects wore the same pair of shoes for all trials.
Statistical analyses.
All analyses were performed using SPSS 11.0.1 for Windows (SPSS Inc., Chicago IL). For all analyses, an alpha of 0.05 was used to denote statistical significance. A two-way repeated measures ANOVA (model × side) was used to assess differences between pedometers worn on the right and left sides of the body and to determine whether significant differences existed between pedometer models. Paired t-tests were used to determine whether the pedometer-estimated steps were significantly different from the actual steps taken. Cronbach’s alpha was used to assess the intramodel reliability among pedometers of the same model. An alpha value of 0.80 was used to denote statistically significant intramodel reliability (12).
Bland-Altman (5) plots were constructed to show the dispersion of the individual pedometer error scores around zero. This is a widely accepted technique to show the accuracy of biomedical devices (27). In this manner, the mean error score can be illustrated, and the 95% prediction interval (i.e., 95% confidence interval for the individual observations) can also be shown. Individual error scores that have a tight prediction interval around zero signify a more accurate device.
RESULTS
The average self-selected walking speed was 96.5 m·min−1 and ranged from 77.3 to 114.9 m·min−1. There was no significant difference (P > 0.05) between pedometers worn on the right and left sides of the body. However, there was a significant difference (P < 0.05) among the 10 pedometer models. To determine accuracy, an error score (actual steps minus pedometer steps) was computed and compared with zero. Individual error scores of zero would indicate that there was no difference between the estimated and actual steps taken, whereas negative scores represent overestimations and positive scores represent underestimations. Figure 1 displays the mean error scores between the actual steps taken and the pedometer-measured steps. The OR significantly overestimated the actual number of steps taken (P < 0.05). The SL330 significantly underestimated the actual number of steps (P < 0.05). The remaining pedometers had mean values that neither over- nor underestimated the true number of steps taken. However, as we will show, three models (NL, DW, and KZ) were clearly more accurate than the other models.
FIGURE 1:
Mean error scores (actual − pedometer) ± SE in number of steps during a 400-m track walk at self-selected speeds. *P < 0.05.
Table 3 displays the mean error scores and the 95% prediction intervals. Figure 2 shows the Bland-Altman plots for various pedometer models. For convenience, the y-axes are standardized to highlight the differences in accuracy between pedometers. The NL, DW, and KZ models were exceptionally accurate, having 95% prediction intervals that were within ±17 steps (of an average of 513) from zero. The WL, SK, SL345, FR, and OR were moderately accurate, having 95% prediction intervals that were within ±100 steps from zero. Finally, the OM and SL330 were the least accurate, having 95% prediction intervals that were within ±188 steps from zero.
TABLE 3:
Error scores (actual − pedometer) in number of steps during a 400-m track walk at self-selected speeds.
FIGURE 2:
Representative Bland-Altman plots for three pedometers with varying accuracy. The Yamax Digi-Walker SW-701 (DW) was one of the three most accurate pedometers, the Oregon Scientific PE316CA (OR) was among the four moderately accurate pedometers, and Sportline 330 (SL330) was one of the two least accurate pedometers. Solid horizontal line, mean error score; dashed lines, 95% prediction intervals (i.e., 95% confidence intervals of the individual observations).
As shown in Table 4, the intramodel reliability (among four pedometers of a single model) was >0.80 in all pedometers with the exception of the SL330. The intramodel reliability was exceptionally high (>0.99) in the KZ, OM, NL, and the DW. However, despite high reliability, the OM had poor accuracy.
TABLE 4:
Intramodel reliability for each of the 10 different pedometer models.
Table 5 displays the mean difference in actual distance walked and the pedometer-calculated distance. Negative scores represent overestimations and positive scores indicate underestimations by the pedometer. There were significant differences (P < 0.05) in five of the six pedometers that calculated distance, with the SL345 approximating distance more closely than all other models. To determine accuracy in calculating distance, the estimated distance from the pedometer was subtracted from the actual distance walked, and this difference score was compared with zero.
TABLE 5:
Error scores (actual − pedometer) in distance (m) during a 400-m track walk at self-selected speeds.
DISCUSSION
In the current study, 8 of the 10 pedometers tested yielded mean values that were not significantly different from the actual steps taken at self-selected walking speeds. However, the KZ, NL, and DW were the only pedometers accurate to within ±3% of the actual steps taken, 95% of the time. These three pedometers differed from the actual steps taken by less than 17 steps during a 400-m walk (totaling about 513 steps). Interestingly, these pedometers are all made in Japan, and they all met the Japanese Industrial Standard set by the Ministry of Industry and Trading regulations (7), which requires less than a 3% margin of error (3 steps of 100). The intramodel reliability for the KZ, NL, and DW was also very high (>0.99), suggesting adequate quality control and tight manufacturing tolerances. These pedometers would appear to be suitable for use in research studies.
Four of the other pedometers (WL, SK, SL345, and FR) had moderate accuracy. They displayed values that were within ±20% of the actual steps taken, 95% of the time. These four models predicted the actual steps to within ±100 steps during a 400-m walk.
Three pedometer models were judged to be unacceptable under the conditions in which they were tested. The OR consistently tended to overestimate the actual number of steps, possibly due to a high sensitivity for recording steps. As a result, the OR significantly overestimated the mean number of steps (P < 0.05). The SL330 and OM were the least accurate pedometers; they displayed values that were within ±37% of the actual steps taken, 95% of the time. These two models predicted the actual steps to within ±188 steps during a 400-m walk. Only the SL330 significantly underestimated the mean number of steps taken. However, in both of these pedometers, there was a tendency to grossly underestimate steps, particularly in obese subjects (BMI ≥ 30 kg·m−2). Thus, these pedometers would be poor choices for use with obese individuals.
There have been conflicting results regarding pedometer accuracy in obese individuals (BMI ≥ 30 kg·m−2). Shephard et al. (18) reported that the Sportline pedometer was less accurate in obese subjects compared with nonobese subjects as evidenced by greater mean absolute error scores in the obese. However, Swartz et al. (19) demonstrated that the Yamax SW-200 pedometer was accurate in lean, overweight, and obese subjects. Their results are consistent with those in the current study in showing that the Yamax SW-701 was accurate over a wide range of BMI (18.6–33.6 kg·m−2). (These two models use the same internal mechanism for recording steps; they differ only in the functions that are displayed.) Some other pedometers (OM and SL330) grossly underestimated steps taken by obese subjects. It should be noted, however, that the OM was accurate in individuals with both normal BMI (18–24.9 kg·m−2) and those classified as overweight (25–29.9 kg·m−2). It is possible that in obese individuals, especially those with a significant amount of abdominal fat, the angle of the pedometer when clipped to the belt or waistband compromises its ability to count steps accurately.
Although the accuracy of pedometers for assessing distance was also examined, the results should be interpreted with caution. To calculate distance, the following formula is used:EQUATION
Pedometer models differ in the precision with which stride length can be entered. For example, some pedometers allow the operator to input stride length to the nearest inch, whereas others only allow stride length to be input to the nearest 0.25 ft. Furthermore, only one stride length can be programmed into a pedometer, so if a subject changes his/her stride length after the calibration procedure, the distance estimated will be inaccurate. For most pedometers, distance was underestimated because the subjects had longer strides (and thus took fewer steps) during the 400-m track walk than in the 20-step calibration procedure. The SL345 was the only pedometer that did not significantly underestimate distance. However, this is because the SL345 overestimated the number of steps taken. Because most researchers choose to report pedometer data as steps, it would be inappropriate to conclude that the SL345 is the most accurate pedometer.
Recent U.S. physical activity recommendations have encouraged Americans to accumulate at least 30 min of moderate physical activity on most, preferably all, days of the week (14,26). Dr. Hatano of Japan has proposed an alternative recommendation. He believes that taking 10,000 step·d−1 would be effective for cardiovascular disease prevention (7). Hatano (8) has found that increased ambulatory activity is associated with lower levels of blood pressure and subcutaneous fat. Hatano also estimated that a 60-kg Japanese male would expend at least 333 kcal·d−1 in walking 10,000 step·d−1. Previous research indicates that this amount (>2000 kcal·wk−1) appears to be protective against heart attacks (13). In addition, longitudinal studies have demonstrated that walking 10,000 step·d−1 results in improvements in cardiovascular disease risk factors in sedentary, at-risk populations (11,20).
Electronic pedometers have gained widespread acceptance among physical activity researchers over the past decade (4), and the use of pedometers has become increasingly popular with the continued publicity of the 10,000 step·d−1 recommendation (9,15). Thus, it is essential that the pedometer display accurate results. Wilde et al. (28) showed that by adding a 30-min walk to their daily routine, subjects increased their step counts from 7,220 to 10,030 step·d−1. This study indicates that for sedentary women including a daily 30-min walk in their schedule will generally allow them to meet both physical activity recommendations, suggesting that the two are roughly equivalent. However, pedometer accuracy can have a significant impact on the number of steps counted over the course of a day. A study conducted by Tudor-Locke et al. (21) compared the Yamax SW-200 with the CSA model 7164 Actigraph (a research grade accelerometer) and showed an 1800 step·d−1difference between the two types of step counters. It was suggested that this difference is due to variations in the sensitivity of the two devices. Thus, because 1800 steps may represent a relatively large portion of a person’s daily step count and because it is possible for two step-counters to differ by this amount, it is essential that the pedometer accurately report steps taken.
The electronic pedometer has limitations as a research tool (6) including its inability to provide information related to nonambulatory activity (i.e., cycling, weight training, and swimming). Nevertheless, it does have some distinguishing characteristics that make it useful as a motivational tool for promoting physical activity. First, the pedometer continuously monitors physical activity whether it is incidental or intentional. Studies have shown recall of ubiquitous, moderate activities (e.g., walking) is less accurate than recall of structured, vigorous activities (3,16). Thus, a device that is capable of continuously monitoring ambulatory activity would be beneficial for those interested in the assessment of physical activity. Second, the pedometer can serve as a feedback tool, providing immediate information on accumulated ambulatory activity and serving as a reminder to be physically active. Although earlier criticisms of pedometers included their inability to store data (6), two of the pedometers assessed in this study, the NL and KZ pedometers are capable of storing up to 7 and 42 d worth of data, respectively, in 1-d epochs. This makes these pedometers an appealing option for researchers who want to eliminate the potential bias of subjects recording their own data.
This study is in agreement with the study conducted by Bassett et al. (2) in demonstrating that considerable variation in accuracy exists among pedometers. Likewise, both studies indicated that a Yamax brand pedometer (DW-500 or SW-701) was one of the best in regard to its accuracy and reliability. However, other pedometers that were unavailable at the time of the previous study have been shown to very accurate and reliable as well (NL and KZ). An ideal objective instrument is one that is low in cost, easy to administer to large groups, unobtrusive to the subject, and accurate (6). Although most pedometers displayed mean step scores that were not significantly different from the actual steps taken at self-selected walking speeds, some were distinctly better than others as indicated by individual error scores that had a tight prediction interval around zero. Due to the variation that exists among pedometers in regard to the manufacturing specifications, mechanism and sensitivity of each device, not all pedometers count steps accurately. Thus, it is important for researchers who use pedometers to assess physical activity to know the accuracy and reliability of their instruments.
The authors would like to thank Cary Springer of the UT statistical consulting services for performing the data analyses in this study.
No financial support was received from the pedometer manufacturers, importers, or retailers.
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