- Email: [email protected]
Steps Per Day Among Persons With Multiple Sclerosis: Variation by Demographic, Clinical, and Device Characteristics
Archives of Physical Medicine and Rehabilitation journal homepage: www.archives-pmr.org Archives of Physical Medicine and Rehabilitation 2013;94:1534-9
ORIGINAL ARTICLE
Steps Per Day Among Persons With Multiple Sclerosis: Variation by Demographic, Clinical, and Device Characteristics Deirdre Dlugonski, BSc, Lara A. Pilutti, PhD, Brian M. Sandroff, MS, Yoojin Suh, MS, Swathi Balantrapu, BSc, Robert W. Motl, PhD From the Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL.
Abstract Objectives: To identify steps per day in a large sample of persons with multiple sclerosis (MS) and to describe variation by demographic and clinical characteristics and device type. Design: Cross-sectional design. Setting: General community. Participants: Convenience sample of persons with multiple sclerosis (NZ645) recruited from the general community who were ambulatory and relapse free for 30 days. Mean age SD of the participants was 46.310.6 years old. Participants were mostly women (85%), white (93%), and employed (64%). Interventions: Not applicable. Main Outcome Measure: Step counts measured by a motion sensor during a 7-day period. Results: The average value for the entire sample was 59033185 steps per day. This value varied by demographic and clinical characteristics, but not device type, and indicated that men, participants who were unemployed, had a high school education or less, progressive MS, a longer disease duration, and higher disability were less physically active based on the metric of steps per day. Conclusions: This study provides an expected value for average steps per day among persons with MS. Such an expected value for this population is an important first step to help researchers and clinicians interested in improving the overall health of persons with MS through physical activity promotion. Archives of Physical Medicine and Rehabilitation 2013;94:1534-9 ª 2013 by the American Congress of Rehabilitation Medicine
There is increasing evidence for the health benefits of physical activity in persons with multiple sclerosis (MS),1,2 thereby prompting recommendations for the promotion of this behavior.3 Such efforts are particularly salient given that persons with MS are less physically active than the general population of adults without a chronic disease,4,5 and therefore are less likely to accrue the associated health benefits. Nevertheless, there is limited information that guides the surveillance, screening, recommendation, and evaluation of physical activity levels in those with MS. One approach, which has been adopted for addressing the aforementioned needs in the general population of adults, is the
Supported by the National Multiple Sclerosis Society Pilot (grant no. PP 1695). No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit on the authors or on any organization with which the authors are associated.
provision of expected values for steps per day from motion sensors (ie, accelerometers and pedometers).6,7 Such expected values are benchmarks, which provide estimates of central tendency and variability to facilitate research and program planning (eg, designing interventions to increase physical activity based on daily movement counts). These expected values may be useful for researchers as a referent value for comparing the physical activity level of future samples of person with MS.8 Based on the available literature, researchers have proposed a hierarchical, 5-level index for the classification of physical activity levels in the general population: inactive (<5000 steps per day); low active (5000e7499 steps per day); somewhat active (7500e9999 steps per day); active (10,000e12,499 steps per day); and highly active (12,500 steps per day).9 One recent review highlighted the paucity, yet critical need, of research on the expected value of steps per day that could then inform a similar classification system for special populations.10
0003-9993/13/$36 - see front matter ª 2013 by the American Congress of Rehabilitation Medicine http://dx.doi.org/10.1016/j.apmr.2012.12.014
Steps per day among persons with multiple sclerosis The present study identified average steps per day in a large sample of persons with MS and described variation in steps per day by demographic and clinical characteristics and device type. Such information will (1) provide a reference value for researchers examining physical activity levels of persons with MS; (2) generate a benchmark for clinicians who are interested in monitoring and promoting physical activity among patients; and (3) establish the physical activity level of persons with MS compared with the general population using a simple, universal metric of steps per day.
Methods Participants Participants were recruited from throughout the United States by multiple sources including print and e-mail flyers and an online advertisement on the National Multiple Sclerosis Society website for research on physical activity in persons with MS. The inclusion criteria included a self-reported diagnosis of MS, relapse free in the previous 30 days, and willingness to wear a motion sensor. Persons not satisfying those criteria were excluded from participation. We screened 1041 persons with MS, and 669 (64.3%) of them volunteered for participation and satisfied inclusion criteria. There were 24 participants who did not comply with the study protocol and had less than 2 valid days of wear time for the motion sensors, and these persons were excluded from the analysis, resulting in a final sample of 645 participants.
Devices Steps per day were measured with Yamax SW-200a pedometers or ActiGraph accelerometers (models 7164 or GT3X).b The available pool of devices for data collection included 50 SW-200 pedometers, model 7164 accelerometers, and model GT3X accelerometers. All devices were checked for accurately measuring 500 steps taken while walking on a treadmill at 4.8kph and 0% grade by laboratory staff members prior to use in this project in order to minimize variation among and between devices. Multiple types of devices were included, because there was an insufficient quantity of any 1 device for systematically capturing the physical activity levels of all participants. This further facilitated a comparison of steps per day between pedometer and accelerometer devices. The Yamax SW-200 pedometer is a simple device that is easy to use and measures steps using a spring-loaded lever arm. The ActiGraph accelerometers (models 7164 and GT3X) measure steps using a piezoelectric bender element or solid state accelerometer that produces an electric signal proportionate to the force acting on it during movement. The steps were recorded over 1-minute intervals, stored in the accelerometer’s memory, and then downloaded by the research team using ActiLife softwareb onto a personal computer. Steps per 1-minute interval were later
List of abbreviations: ANCOVA CI EDSS MS PDDS
analysis of covariance confidence interval Expanded Disability Status Scale multiple sclerosis Patient Determined Disease Steps
www.archives-pmr.org
1535 summed over the course of the day. Accelerometer data were checked against participant recorded wear times from the log sheet, and only valid days (10h of wear time without periods of continuous zeros exceeding 60min) were included in the analysis.
Measures We included a standard scale developed in our laboratory to measure all demographic and clinical characteristics reported in this study, with the exception of disability. The Patient Determined Disease Steps (PDDS) scale11 was used for capturing information on self-reported disability status. Participants were asked to choose 1 item on the PDDS scale that best reflected their level of disability from 0 (normative) through 8 (bedridden). This scale focuses mainly on walking ability and is strongly associated with physician-administered Expanded Disability Status Scale (EDSS) scores (rZ.93).11
Procedure The study and procedure were approved by a university institutional review board, and all participants provided written informed consent. This study was conducted during all seasons of a multiyear period in order to limit seasonality effects, and included participants from throughout the United States. After telephone screening for inclusion and provision of a signed informed consent document, participants were mailed a pedometer or accelerometer, a log sheet, instructions for wearing the device, and a packet containing a demographic scale along with the PDDS scale. Participants were instructed to wear the pedometer or accelerometer on a belt around the waist over the nondominant hip during all waking hours of a 7-day period, except when swimming, bathing, or showering. Waking hours were defined for participants as the moment of getting out of bed in the morning until the moment of getting into bed in the evening. During this 1-week period, participants were asked to maintain normative routines and usual levels of physical activity. Participants were provided with a log sheet to record the time of day that the unit was worn and any times throughout the day that the unit was not worn. Participants who received pedometers further recorded steps per day on the log before resetting the unit. After completion, participants returned the study materials in a prestamped and preaddressed envelope. Participants received $15 remuneration for completion of the study procedures.
Data analysis Descriptive and inferential statistics were performed in PASW 18.0.c Descriptive statistics are presented in the text and tables as mean SD along with 95% confidence interval (CI), unless otherwise noted (eg, median, range, and SE). Inferential statistics involved independent samples t tests to compare steps per day with demographic and clinical characteristics and device type. Analysis of covariance (ANCOVA) was used to determine differences between groups in the presence of significant covariates. We further provide effect size estimates based on Cohen’s d (ie, difference between mean scores for 2 groups divided by the pooled SD) and interpreted the values as small, moderate, and large based on criteria of 0.2, 0.5, and 0.8, respectively.12 Finally, we conducted a multiple linear regression
1536 with direct entry of variables as an exploratory analysis to determine predictors of steps per day.
Results Participants were primarily women (nZ550; 85%), employed (nZ415; 64%), and white (nZ599; 93%) with an average age SD of 46.310.6 years. The median PDDS score was 2.0 (range, 0e6). This indicated that the sample overall was characterized by moderate disability (ie, no limitations in walking but significant problems because of MS, which limit daily activity in other ways) with a range between normative and 2-point assistance (eg, rollator or frame). The average duration SD of MS was 9.37.8 years, with nearly 89% of the sample (nZ575) reporting a diagnosis of relapsing-remitting MS. All 645 participants included in the analysis had at least 2 days of valid accelerometer data or provided 2 or more days of pedometer data.13 There were 24 participants with <2 valid days of accelerometer and/or pedometer data who were excluded for noncompliance, as previously described in the Participants section. Of these 24 participants, 2 wore pedometers and 22 wore accelerometers, resulting in 1% and around 6% noncompliance rates by device type, respectively. To our knowledge, there were no device malfunctions that occurred during this study. The percentages of participants with 7, 6, 5, 4, 3, and 2 days of usable data, respectively, were 76.5, 14.1, 6.1, 1.4, 1.3, and 0.6. The average value for the entire sample (NZ645) was 59033185 steps per day (95% CI, 5657e6149) with a range of 419 to 19,473 steps per day. The value of steps per day varied by sex, disease type, disease duration, self-reported disability, employment, and education, but not by race or device type. Descriptive statistics for group differences based on the original analysis are provided in table 1. Independent samples t tests indicated that participants who were women (t643Z2.03, PZ.043, dZ.23), employed (t641Z9.09, PZ.001, dZ.75), and college educated (t642Z3.4, PZ.001, dZ.38) had higher steps per day than participants who were men, unemployed, and had earned a high school education or less, respectively. There was a small but statistically significant correlation between sex and disability (rZ.14, PZ.003). ANCOVA results indicated that when controlling for disability, there was no longer a significant difference in steps per day by sex (F1,445Z1.48, PZ.23). There were no statistically significant correlations between sex and education or employment. There were no statistically significant differences between steps per day of white and nonwhite participants (t643Z1.44, PZ149, dZ.22). Participants who had a relapsing-remitting MS disease course (t636Z5.38, PZ.001, dZ.71), shorter disease duration (t643Z3.28, PZ.001, dZ.26), and a lower PDDS score (t447Z10.79, PZ.001, dZ1.03) had higher steps per day than participants who had a progressive disease course, a disease duration >10 years, and a PDDS score of 3 (ie, moderate disability). There was a statistically significant correlation between age and disease duration (rZ.36, PZ.001), and ANCOVA results indicated that there was no longer a statistically significant difference in steps per day by disease duration when controlling for age (F1,642Z1.01, PZ.32). There was not a statistically significant difference between steps per day measured by pedometers and accelerometers (t643Z.71, PZ.476, dZ.06). The effect sizes for differences in step counts between groups were
D. Dlugonski et al small for sex, education, and disease duration, but large for employment, disease type, and self-reported disability. In the final analysis, we regressed average steps per day on education, sex, employment, disability, disease duration, and type of MS. The model was statistically significant (F6,435Z26.94, PZ.001) and accounted for 26% of the variance in daily step counts (adjusted R2Z.26). There were statistically significant effects for disability (bZ .347), employment (bZ.20), and education (bZ.094), indicating that moderate impairment, unemployment, and lower education level were associated with lower average steps per day. Complete regression results are included in table 2.
Discussion The current study provides novel information regarding an overall expected value for steps per day from a large sample of persons with MS and variation of the expected value based on demographic and clinical characteristics and device type. Overall, the sample had an average daily step count of 5903, and this would be described as low active based on guidelines for adults without a chronic disease condition.9 Using the physical activity classifications suggested for the general population,9 the percent of the sample classified as inactive, low active, somewhat active, active, and highly active was 45, 28, 16, 7, and 4, respectively. The value for steps per day varied by demographic and clinical characteristics, but not device type, and indicated that those who were unemployed, had a high school education or less, progressive MS, and higher disability were less physically active based on the metric of steps per day. Such information provides critical information for guiding the surveillance, screening, recommendation, and evaluation of physical activity levels in persons with MS. As expected, the average daily step count for the current sample (59033185 steps) was considerably less than the step count averages from previous studies of healthy adults in the United States (96761079)7 and Finland (74992908).6 This finding further supports previous research indicating that persons with MS engage in less physical activity when compared with the general population.4,5 The daily step count average for persons with MS from the current sample is consistent with the wide range of expected values for special populations (1200e8800 steps) reported by previous researchers,10 and is similar to the daily step count average of persons with neuromuscular diseases (5769 steps) from a recent review.8 This indicates that persons with MS are less active than healthy adults but similarly active compared with persons with other chronic diseases and conditions. Analyses of demographic characteristics indicated that participants who were employed and had at least a college education took more steps per day compared with those who were unemployed and participants with no more than a high school education. The magnitude of difference in step counts, based on effect sizes, was small for education and large for employment. When considering level of disability, we found no difference in average daily step counts between men and women. Previous research in samples of healthy U.S.7 and Finnish6 adults found differences between the average daily step counts for men and women. However, it seems that in the presence of disability, sex differences are attenuated in MS. Significant differences by employment status and education were in the expected direction based on www.archives-pmr.org
Steps per day among persons with multiple sclerosis Table 1
1537
Average daily step counts by demographic and clinical characteristics
Characteristic Sex Female Male Clinical course Relapsing remitting MS Progressive MS Disease duration <10y 10y Disability status PDDS scale score 2 PDDS scale score 3 Employment status Employed Unemployed Education High school or less At least some college Race White Nonwhite Device type Spring-loaded pedometer Accelerometer
n (%)
Mean SD
Mean 95% CI
550 (85) 95 (15)
60083205 52923016
5740e6276 4685e5898
2.03
0.23
716.5
575 (89) 63 (10)
61373196 39032403
5876e6398 3310e4497
5.38
0.71
2233.8
1418.9 to 3048.7
395 (61) 250 (39)
62273268 53902986
5905e6550 5020e5760
3.28
0.26
837.5
335.8 to 1339.2
255 (40) 194 (30)
71673004 42572584
6799e7536 3893e4620
10.79
1.03
2910.6
2380.6 to 3440.6
415 (64) 228 (35)
67023231 44492539
6394e7010 4120e4779
9.09
0.75
2252.2
1766.0 to 2738.5
94 (15) 550 (85)
48762856 60763202
4298e5453 5806e6346
3.40
0.38
1200.4
507.5 to 1893.3
599 (93) 46 (7)
59533230 52502476
5694e6211 4534e5965
1.44
0.22
703.3
252.9 to 1659.4
273 (42) 372 (58)
60073277 58263118
5618e6396 5496e6157
0.71
0.06
180.9
317.7 to 679.6
t
Cohen’s d
Mean Difference
Mean Difference 95% CI 23.3 to 1409.8
NOTE. The sample sizes and percentages for each characteristic differ because of missing data per characteristic.
previous studies of pedometer-determined physical activity in adults.9,14 We did not find a statistically significant difference by race in the present study, inconsistent with previous research,9 and this may be because of the relatively small number of nonwhite participants in this study and in those who have MS in general. As expected, participants with a relapsing-remitting disease course and less disability had higher steps per day than those who had progressive MS and higher levels of gait disability. Effect sizes indicated that the magnitude of difference in step counts was moderate-to-large for disease type and large for disability status. These results are supported by data from a recent study indicating that higher levels of disability, as measured by the EDSS, are associated with lower levels of physical activity in a sample of persons with MS.15 In another study of adverse health behaviors among persons with MS, physical activity intensity was negatively associated with level of disability,16 further supporting the current findings. Table 2 Summary of direct entry regression analysis for variables predicting steps per day in 645 persons with MS Variable
B SE
Sex Employment Education Disease course Duration Disability
346.11369.57 1370.80302.80 904.41405.46 805.14473.56 18.7517.07 2229.67288.05
* P<.05.
www.archives-pmr.org
b .04 .20* .09* .07 .05 .35*
We did not find any significant differences because of device type, and this was expected given the strong correlation (rZ.93) between output from accelerometers and pedometers reported in a previous study of persons with MS.17 We further note that published data support the comparability of step counts from the same brands of pedometers and accelerometers in a large sample of older adults.18 To that end, either device might be acceptable for monitoring steps per day in clinical and research applications involving persons with MS. The findings from this study provide a description of average daily step counts in persons with MS, which may be useful for researchers and clinicians who are interested in the surveillance, screening, evaluation, and promotion of physical activity in this population. This information is important given the low levels of physical activity in persons with MS, as reported by previous researchers,4,5 and the potential for improving health through increasing physical activity. We provide reference values for average daily step counts by demographic and clinical characteristics and device type, which researchers might use as benchmarks for future samples of persons with MS. Researchers might further use this information as a first step toward creating recommendations about steps per day needed to meet public health guidelines specific to this population, similar to guidelines that have been provided for older adults.10 Steps per day may be a useful and meaningful metric based on the frequency of walking behavior among persons with MS19,20 and the potential for increasing physical activity by encouraging walking in the context of a behavioral intervention using pedometers and simple behavior change strategies.21,22 Clinicians might use the data presented herein as a benchmark when trying to better understand, monitor, and promote physical activity among patients. Using step counting devices in clinical
1538 settings presents an opportunity to improve the health of patients by monitoring physical activity and setting realistic goals for increasing step counts in the context of daily activities.
Study limitations This study had several noteworthy limitations. The participants in the current study were mostly white, women, employed, and educated, with a relapsing-remitting disease course. We did not measure other contextual variables, such as geographic (eg, urban or rural dwellers) or cultural factors (eg, religious beliefs), which may influence physical activity. This is important, because these characteristics may limit generalizations broadly among the larger population of persons with MS, but provide important information for those interested in the physical activity of these particular groups of persons with MS. Another limitation was the reliance on self-reported information regarding the definite diagnosis of MS as well as disease type. Our experience from previous research has resulted in a 100% agreement between self-reported and physician confirmed diagnoses of MS, but we may still lack specificity of diagnosis and disease course in the current study. We further recognize that there was substantial individual variation in the values of steps per day based on the SDs presented in this article, even when characterized by demographic and clinical characteristics, although the 95% CIs around the point estimates were fairly tight. For that reason, the step count values presented herein should not serve as absolute reference points or goals for individuals with MS without considering other important contextual factors related to physical activity. Finally, there were several limitations related to the use of motion sensors in the present study. These limitations included the use of 3 types of motion sensors, which may have introduced additional variability in steps per day, reactivity to wearing a motion sensor, and the lack of face-to-face instructions for wearing the pedometer or accelerometer. We reduced the potential threat of variability by type of device, because the units were all checked for accuracy before initiating data collection; our results indicated that there were no differences by device type. Future studies might replicate the results using a single device, longer sampling periods to reduce the novelty of wearing a motion sensor, and face-to-face directions for wearing the pedometer or accelerometer.
Conclusions Participation in physical activity has important and meaningful consequences for persons with MS. This study provided evidence for the average daily step counts of persons with MS from a large sample using pedometers and accelerometers as objective measures of physical activity. Such a reference value for average daily step counts overall, and by demographic and clinical characteristics for this population, is a first step toward generating recommendations for meeting public health guidelines through increased walking, which has the potential to improve the overall health of persons with MS.
Suppliers a. Yamax Corp, Yamasa Tokei Keiki Co, 1-5-7, Chuo-cho, Meguro-ku, Tokyo 152-8691, Japan. b. ActiGraph Corp, 49 E Chase St, Pensacola, FL 32502. c. SPSS Inc, 233 S Wacker Dr, 11th Fl, Chicago, IL 60606.
D. Dlugonski et al
Keywords Health; Multiple sclerosis; Rehabilitation; Walking
Corresponding author Robert W. Motl, PhD, Department of Kinesiology and Community Health, University of Illinois, 233 Freer Hall, Urbana, IL 61801. E-mail address: [email protected].
References 1. Garrett M, Coote S. Multiple sclerosis and exercise in people with minimal gait impairment: a review. Phys Ther Rev 2009;14: 169-80. 2. White LJ, Castellano V. Exercise and brain healtheimplications for multiple sclerosis: Part 1eneuronal growth factors. Sports Med 2008; 38:91-100. 3. Motl RW. Physical activity and its measurement and determinants in multiple sclerosis. Minerva Med 2008;99:157-65. 4. Motl RW, McAuley E, Snook EM. Physical activity and multiple sclerosis: a meta-analysis. Mult Scler 2005;1:459-63. 5. Sandroff BM, Dlugonski D, Weikert M, Suh Y, Balantrapu S, Motl RW. Physical activity and multiple sclerosis: new insights regarding inactivity. Acta Neurol Scand 2012;126:256-62. 6. Hirvensalo M, Telama R, Schmidt MD, et al. Daily steps among Finnish adults: variation by age, sex, and socioeconomic position. Scand J Public Healt 2011;39:669-77. 7. Tudor-Locke C, Johnson WD, Katzmarzyk PT. Accelerometerdetermined steps per day in US adults. Med Sci Sports Exer 2009; 41:1384-91. 8. Tudor-Locke C, Washington TL, Hart TL. Expected values for steps/day in special populations. Prev Med 2009;49:3-11. 9. Tudor-Locke C, Bassett DR. How many steps/day are enough? Preliminary pedometer indices for public health. Sports Med 2004;34: 1-8. 10. Tudor-Locke C, Craig CL, Aoyagi Y, et al. How many steps/day are enough? For older adults and special populations. Int J Behav Nutr Phys Act 2011;8:80-98. 11. Hadjimichael O, Kerns RD, Rizzo MA, Cutter G, Vollmer T. Persistent pain and uncomfortable sensations in persons with multiple sclerosis. Pain 2007;127:35-41. 12. Cohen J. A power primer. Psychol Bull 1992;112:155-9. 13. Motl RW, Zhu W, Park Y, McAuley E, Scott J, Snook E. Reliability of scores from physical activity monitors in adults with multiple sclerosis. Adapt Phys Act Q 2007;24:245-53. 14. De Cocker K, Cardon G, De Bourdeaudhuij I. Pedometer-determined physical activity and its comparison with the International Physical Activity Questionnaire in a sample of Belgian adults. Res Q Exer Sport 2007;78:429-37. 15. Beckerman H, de Groot V, Scholten MA, Kempen JCE, Lankhorst GJ. Physical activity behavior of people with multiple sclerosis: understanding how they can become more physically active. Phys Ther 2010;90:1001-13. 16. Marrie RA, Horwitz R, Cutter G, Tyry T, Campagnolo D, Vollmer T. High frequency of adverse health behaviors in multiple sclerosis. Mult Scler 2009;15:105-13. 17. Motl RW, McAuley E, Snook EM, Scott JA. Validity of physical activity measures in ambulatory individuals with multiple sclerosis. Disabil Rehabil 2006;28:1151-6. 18. Harris TJ, Owen CG, Victor CR, Adams R, Ekelund U, Cook DG. A comparison of questionnaire, accelerometer, and pedometer: measures in older people. Med Sci Sport Exer 2009; 41:1392-402.
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Steps per day among persons with multiple sclerosis 19. Weikert MW, Dlugonski D, Balantrapu S, Motl RW. Most common types of physical activity self-selected by persons with multiple sclerosis. Int J MS Care 2011;13:16-20. 20. Rietberg MB, van Wegen EE, Uitdehaag BM, de Vet HC, Kwakkel G. How reproducible is home-based 24-hour ambulatory monitoring of motor activity in patients with multiple sclerosis? Arch Phys Med Rehabil 2010;91:1537-41.
www.archives-pmr.org
1539 21. Motl RW, Dlugonski D, Wo´jcicki TR, McAuley E, Mohr DC. Internet intervention for increasing physical activity in persons with multiple sclerosis. Mult Scler 2011;17:116-28. 22. Dlugonski D, Motl RW, Mohr DC, Sandroff BM. Internet-delivered behavioral intervention to increase physical activity in persons with multiple sclerosis: sustainability and secondary outcomes. Psychol Health Med 2012;17:636-51.
ORIGINAL ARTICLE
Steps Per Day Among Persons With Multiple Sclerosis: Variation by Demographic, Clinical, and Device Characteristics Deirdre Dlugonski, BSc, Lara A. Pilutti, PhD, Brian M. Sandroff, MS, Yoojin Suh, MS, Swathi Balantrapu, BSc, Robert W. Motl, PhD From the Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL.
Abstract Objectives: To identify steps per day in a large sample of persons with multiple sclerosis (MS) and to describe variation by demographic and clinical characteristics and device type. Design: Cross-sectional design. Setting: General community. Participants: Convenience sample of persons with multiple sclerosis (NZ645) recruited from the general community who were ambulatory and relapse free for 30 days. Mean age SD of the participants was 46.310.6 years old. Participants were mostly women (85%), white (93%), and employed (64%). Interventions: Not applicable. Main Outcome Measure: Step counts measured by a motion sensor during a 7-day period. Results: The average value for the entire sample was 59033185 steps per day. This value varied by demographic and clinical characteristics, but not device type, and indicated that men, participants who were unemployed, had a high school education or less, progressive MS, a longer disease duration, and higher disability were less physically active based on the metric of steps per day. Conclusions: This study provides an expected value for average steps per day among persons with MS. Such an expected value for this population is an important first step to help researchers and clinicians interested in improving the overall health of persons with MS through physical activity promotion. Archives of Physical Medicine and Rehabilitation 2013;94:1534-9 ª 2013 by the American Congress of Rehabilitation Medicine
There is increasing evidence for the health benefits of physical activity in persons with multiple sclerosis (MS),1,2 thereby prompting recommendations for the promotion of this behavior.3 Such efforts are particularly salient given that persons with MS are less physically active than the general population of adults without a chronic disease,4,5 and therefore are less likely to accrue the associated health benefits. Nevertheless, there is limited information that guides the surveillance, screening, recommendation, and evaluation of physical activity levels in those with MS. One approach, which has been adopted for addressing the aforementioned needs in the general population of adults, is the
Supported by the National Multiple Sclerosis Society Pilot (grant no. PP 1695). No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit on the authors or on any organization with which the authors are associated.
provision of expected values for steps per day from motion sensors (ie, accelerometers and pedometers).6,7 Such expected values are benchmarks, which provide estimates of central tendency and variability to facilitate research and program planning (eg, designing interventions to increase physical activity based on daily movement counts). These expected values may be useful for researchers as a referent value for comparing the physical activity level of future samples of person with MS.8 Based on the available literature, researchers have proposed a hierarchical, 5-level index for the classification of physical activity levels in the general population: inactive (<5000 steps per day); low active (5000e7499 steps per day); somewhat active (7500e9999 steps per day); active (10,000e12,499 steps per day); and highly active (12,500 steps per day).9 One recent review highlighted the paucity, yet critical need, of research on the expected value of steps per day that could then inform a similar classification system for special populations.10
0003-9993/13/$36 - see front matter ª 2013 by the American Congress of Rehabilitation Medicine http://dx.doi.org/10.1016/j.apmr.2012.12.014
Steps per day among persons with multiple sclerosis The present study identified average steps per day in a large sample of persons with MS and described variation in steps per day by demographic and clinical characteristics and device type. Such information will (1) provide a reference value for researchers examining physical activity levels of persons with MS; (2) generate a benchmark for clinicians who are interested in monitoring and promoting physical activity among patients; and (3) establish the physical activity level of persons with MS compared with the general population using a simple, universal metric of steps per day.
Methods Participants Participants were recruited from throughout the United States by multiple sources including print and e-mail flyers and an online advertisement on the National Multiple Sclerosis Society website for research on physical activity in persons with MS. The inclusion criteria included a self-reported diagnosis of MS, relapse free in the previous 30 days, and willingness to wear a motion sensor. Persons not satisfying those criteria were excluded from participation. We screened 1041 persons with MS, and 669 (64.3%) of them volunteered for participation and satisfied inclusion criteria. There were 24 participants who did not comply with the study protocol and had less than 2 valid days of wear time for the motion sensors, and these persons were excluded from the analysis, resulting in a final sample of 645 participants.
Devices Steps per day were measured with Yamax SW-200a pedometers or ActiGraph accelerometers (models 7164 or GT3X).b The available pool of devices for data collection included 50 SW-200 pedometers, model 7164 accelerometers, and model GT3X accelerometers. All devices were checked for accurately measuring 500 steps taken while walking on a treadmill at 4.8kph and 0% grade by laboratory staff members prior to use in this project in order to minimize variation among and between devices. Multiple types of devices were included, because there was an insufficient quantity of any 1 device for systematically capturing the physical activity levels of all participants. This further facilitated a comparison of steps per day between pedometer and accelerometer devices. The Yamax SW-200 pedometer is a simple device that is easy to use and measures steps using a spring-loaded lever arm. The ActiGraph accelerometers (models 7164 and GT3X) measure steps using a piezoelectric bender element or solid state accelerometer that produces an electric signal proportionate to the force acting on it during movement. The steps were recorded over 1-minute intervals, stored in the accelerometer’s memory, and then downloaded by the research team using ActiLife softwareb onto a personal computer. Steps per 1-minute interval were later
List of abbreviations: ANCOVA CI EDSS MS PDDS
analysis of covariance confidence interval Expanded Disability Status Scale multiple sclerosis Patient Determined Disease Steps
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1535 summed over the course of the day. Accelerometer data were checked against participant recorded wear times from the log sheet, and only valid days (10h of wear time without periods of continuous zeros exceeding 60min) were included in the analysis.
Measures We included a standard scale developed in our laboratory to measure all demographic and clinical characteristics reported in this study, with the exception of disability. The Patient Determined Disease Steps (PDDS) scale11 was used for capturing information on self-reported disability status. Participants were asked to choose 1 item on the PDDS scale that best reflected their level of disability from 0 (normative) through 8 (bedridden). This scale focuses mainly on walking ability and is strongly associated with physician-administered Expanded Disability Status Scale (EDSS) scores (rZ.93).11
Procedure The study and procedure were approved by a university institutional review board, and all participants provided written informed consent. This study was conducted during all seasons of a multiyear period in order to limit seasonality effects, and included participants from throughout the United States. After telephone screening for inclusion and provision of a signed informed consent document, participants were mailed a pedometer or accelerometer, a log sheet, instructions for wearing the device, and a packet containing a demographic scale along with the PDDS scale. Participants were instructed to wear the pedometer or accelerometer on a belt around the waist over the nondominant hip during all waking hours of a 7-day period, except when swimming, bathing, or showering. Waking hours were defined for participants as the moment of getting out of bed in the morning until the moment of getting into bed in the evening. During this 1-week period, participants were asked to maintain normative routines and usual levels of physical activity. Participants were provided with a log sheet to record the time of day that the unit was worn and any times throughout the day that the unit was not worn. Participants who received pedometers further recorded steps per day on the log before resetting the unit. After completion, participants returned the study materials in a prestamped and preaddressed envelope. Participants received $15 remuneration for completion of the study procedures.
Data analysis Descriptive and inferential statistics were performed in PASW 18.0.c Descriptive statistics are presented in the text and tables as mean SD along with 95% confidence interval (CI), unless otherwise noted (eg, median, range, and SE). Inferential statistics involved independent samples t tests to compare steps per day with demographic and clinical characteristics and device type. Analysis of covariance (ANCOVA) was used to determine differences between groups in the presence of significant covariates. We further provide effect size estimates based on Cohen’s d (ie, difference between mean scores for 2 groups divided by the pooled SD) and interpreted the values as small, moderate, and large based on criteria of 0.2, 0.5, and 0.8, respectively.12 Finally, we conducted a multiple linear regression
1536 with direct entry of variables as an exploratory analysis to determine predictors of steps per day.
Results Participants were primarily women (nZ550; 85%), employed (nZ415; 64%), and white (nZ599; 93%) with an average age SD of 46.310.6 years. The median PDDS score was 2.0 (range, 0e6). This indicated that the sample overall was characterized by moderate disability (ie, no limitations in walking but significant problems because of MS, which limit daily activity in other ways) with a range between normative and 2-point assistance (eg, rollator or frame). The average duration SD of MS was 9.37.8 years, with nearly 89% of the sample (nZ575) reporting a diagnosis of relapsing-remitting MS. All 645 participants included in the analysis had at least 2 days of valid accelerometer data or provided 2 or more days of pedometer data.13 There were 24 participants with <2 valid days of accelerometer and/or pedometer data who were excluded for noncompliance, as previously described in the Participants section. Of these 24 participants, 2 wore pedometers and 22 wore accelerometers, resulting in 1% and around 6% noncompliance rates by device type, respectively. To our knowledge, there were no device malfunctions that occurred during this study. The percentages of participants with 7, 6, 5, 4, 3, and 2 days of usable data, respectively, were 76.5, 14.1, 6.1, 1.4, 1.3, and 0.6. The average value for the entire sample (NZ645) was 59033185 steps per day (95% CI, 5657e6149) with a range of 419 to 19,473 steps per day. The value of steps per day varied by sex, disease type, disease duration, self-reported disability, employment, and education, but not by race or device type. Descriptive statistics for group differences based on the original analysis are provided in table 1. Independent samples t tests indicated that participants who were women (t643Z2.03, PZ.043, dZ.23), employed (t641Z9.09, PZ.001, dZ.75), and college educated (t642Z3.4, PZ.001, dZ.38) had higher steps per day than participants who were men, unemployed, and had earned a high school education or less, respectively. There was a small but statistically significant correlation between sex and disability (rZ.14, PZ.003). ANCOVA results indicated that when controlling for disability, there was no longer a significant difference in steps per day by sex (F1,445Z1.48, PZ.23). There were no statistically significant correlations between sex and education or employment. There were no statistically significant differences between steps per day of white and nonwhite participants (t643Z1.44, PZ149, dZ.22). Participants who had a relapsing-remitting MS disease course (t636Z5.38, PZ.001, dZ.71), shorter disease duration (t643Z3.28, PZ.001, dZ.26), and a lower PDDS score (t447Z10.79, PZ.001, dZ1.03) had higher steps per day than participants who had a progressive disease course, a disease duration >10 years, and a PDDS score of 3 (ie, moderate disability). There was a statistically significant correlation between age and disease duration (rZ.36, PZ.001), and ANCOVA results indicated that there was no longer a statistically significant difference in steps per day by disease duration when controlling for age (F1,642Z1.01, PZ.32). There was not a statistically significant difference between steps per day measured by pedometers and accelerometers (t643Z.71, PZ.476, dZ.06). The effect sizes for differences in step counts between groups were
D. Dlugonski et al small for sex, education, and disease duration, but large for employment, disease type, and self-reported disability. In the final analysis, we regressed average steps per day on education, sex, employment, disability, disease duration, and type of MS. The model was statistically significant (F6,435Z26.94, PZ.001) and accounted for 26% of the variance in daily step counts (adjusted R2Z.26). There were statistically significant effects for disability (bZ .347), employment (bZ.20), and education (bZ.094), indicating that moderate impairment, unemployment, and lower education level were associated with lower average steps per day. Complete regression results are included in table 2.
Discussion The current study provides novel information regarding an overall expected value for steps per day from a large sample of persons with MS and variation of the expected value based on demographic and clinical characteristics and device type. Overall, the sample had an average daily step count of 5903, and this would be described as low active based on guidelines for adults without a chronic disease condition.9 Using the physical activity classifications suggested for the general population,9 the percent of the sample classified as inactive, low active, somewhat active, active, and highly active was 45, 28, 16, 7, and 4, respectively. The value for steps per day varied by demographic and clinical characteristics, but not device type, and indicated that those who were unemployed, had a high school education or less, progressive MS, and higher disability were less physically active based on the metric of steps per day. Such information provides critical information for guiding the surveillance, screening, recommendation, and evaluation of physical activity levels in persons with MS. As expected, the average daily step count for the current sample (59033185 steps) was considerably less than the step count averages from previous studies of healthy adults in the United States (96761079)7 and Finland (74992908).6 This finding further supports previous research indicating that persons with MS engage in less physical activity when compared with the general population.4,5 The daily step count average for persons with MS from the current sample is consistent with the wide range of expected values for special populations (1200e8800 steps) reported by previous researchers,10 and is similar to the daily step count average of persons with neuromuscular diseases (5769 steps) from a recent review.8 This indicates that persons with MS are less active than healthy adults but similarly active compared with persons with other chronic diseases and conditions. Analyses of demographic characteristics indicated that participants who were employed and had at least a college education took more steps per day compared with those who were unemployed and participants with no more than a high school education. The magnitude of difference in step counts, based on effect sizes, was small for education and large for employment. When considering level of disability, we found no difference in average daily step counts between men and women. Previous research in samples of healthy U.S.7 and Finnish6 adults found differences between the average daily step counts for men and women. However, it seems that in the presence of disability, sex differences are attenuated in MS. Significant differences by employment status and education were in the expected direction based on www.archives-pmr.org
Steps per day among persons with multiple sclerosis Table 1
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Average daily step counts by demographic and clinical characteristics
Characteristic Sex Female Male Clinical course Relapsing remitting MS Progressive MS Disease duration <10y 10y Disability status PDDS scale score 2 PDDS scale score 3 Employment status Employed Unemployed Education High school or less At least some college Race White Nonwhite Device type Spring-loaded pedometer Accelerometer
n (%)
Mean SD
Mean 95% CI
550 (85) 95 (15)
60083205 52923016
5740e6276 4685e5898
2.03
0.23
716.5
575 (89) 63 (10)
61373196 39032403
5876e6398 3310e4497
5.38
0.71
2233.8
1418.9 to 3048.7
395 (61) 250 (39)
62273268 53902986
5905e6550 5020e5760
3.28
0.26
837.5
335.8 to 1339.2
255 (40) 194 (30)
71673004 42572584
6799e7536 3893e4620
10.79
1.03
2910.6
2380.6 to 3440.6
415 (64) 228 (35)
67023231 44492539
6394e7010 4120e4779
9.09
0.75
2252.2
1766.0 to 2738.5
94 (15) 550 (85)
48762856 60763202
4298e5453 5806e6346
3.40
0.38
1200.4
507.5 to 1893.3
599 (93) 46 (7)
59533230 52502476
5694e6211 4534e5965
1.44
0.22
703.3
252.9 to 1659.4
273 (42) 372 (58)
60073277 58263118
5618e6396 5496e6157
0.71
0.06
180.9
317.7 to 679.6
t
Cohen’s d
Mean Difference
Mean Difference 95% CI 23.3 to 1409.8
NOTE. The sample sizes and percentages for each characteristic differ because of missing data per characteristic.
previous studies of pedometer-determined physical activity in adults.9,14 We did not find a statistically significant difference by race in the present study, inconsistent with previous research,9 and this may be because of the relatively small number of nonwhite participants in this study and in those who have MS in general. As expected, participants with a relapsing-remitting disease course and less disability had higher steps per day than those who had progressive MS and higher levels of gait disability. Effect sizes indicated that the magnitude of difference in step counts was moderate-to-large for disease type and large for disability status. These results are supported by data from a recent study indicating that higher levels of disability, as measured by the EDSS, are associated with lower levels of physical activity in a sample of persons with MS.15 In another study of adverse health behaviors among persons with MS, physical activity intensity was negatively associated with level of disability,16 further supporting the current findings. Table 2 Summary of direct entry regression analysis for variables predicting steps per day in 645 persons with MS Variable
B SE
Sex Employment Education Disease course Duration Disability
346.11369.57 1370.80302.80 904.41405.46 805.14473.56 18.7517.07 2229.67288.05
* P<.05.
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b .04 .20* .09* .07 .05 .35*
We did not find any significant differences because of device type, and this was expected given the strong correlation (rZ.93) between output from accelerometers and pedometers reported in a previous study of persons with MS.17 We further note that published data support the comparability of step counts from the same brands of pedometers and accelerometers in a large sample of older adults.18 To that end, either device might be acceptable for monitoring steps per day in clinical and research applications involving persons with MS. The findings from this study provide a description of average daily step counts in persons with MS, which may be useful for researchers and clinicians who are interested in the surveillance, screening, evaluation, and promotion of physical activity in this population. This information is important given the low levels of physical activity in persons with MS, as reported by previous researchers,4,5 and the potential for improving health through increasing physical activity. We provide reference values for average daily step counts by demographic and clinical characteristics and device type, which researchers might use as benchmarks for future samples of persons with MS. Researchers might further use this information as a first step toward creating recommendations about steps per day needed to meet public health guidelines specific to this population, similar to guidelines that have been provided for older adults.10 Steps per day may be a useful and meaningful metric based on the frequency of walking behavior among persons with MS19,20 and the potential for increasing physical activity by encouraging walking in the context of a behavioral intervention using pedometers and simple behavior change strategies.21,22 Clinicians might use the data presented herein as a benchmark when trying to better understand, monitor, and promote physical activity among patients. Using step counting devices in clinical
1538 settings presents an opportunity to improve the health of patients by monitoring physical activity and setting realistic goals for increasing step counts in the context of daily activities.
Study limitations This study had several noteworthy limitations. The participants in the current study were mostly white, women, employed, and educated, with a relapsing-remitting disease course. We did not measure other contextual variables, such as geographic (eg, urban or rural dwellers) or cultural factors (eg, religious beliefs), which may influence physical activity. This is important, because these characteristics may limit generalizations broadly among the larger population of persons with MS, but provide important information for those interested in the physical activity of these particular groups of persons with MS. Another limitation was the reliance on self-reported information regarding the definite diagnosis of MS as well as disease type. Our experience from previous research has resulted in a 100% agreement between self-reported and physician confirmed diagnoses of MS, but we may still lack specificity of diagnosis and disease course in the current study. We further recognize that there was substantial individual variation in the values of steps per day based on the SDs presented in this article, even when characterized by demographic and clinical characteristics, although the 95% CIs around the point estimates were fairly tight. For that reason, the step count values presented herein should not serve as absolute reference points or goals for individuals with MS without considering other important contextual factors related to physical activity. Finally, there were several limitations related to the use of motion sensors in the present study. These limitations included the use of 3 types of motion sensors, which may have introduced additional variability in steps per day, reactivity to wearing a motion sensor, and the lack of face-to-face instructions for wearing the pedometer or accelerometer. We reduced the potential threat of variability by type of device, because the units were all checked for accuracy before initiating data collection; our results indicated that there were no differences by device type. Future studies might replicate the results using a single device, longer sampling periods to reduce the novelty of wearing a motion sensor, and face-to-face directions for wearing the pedometer or accelerometer.
Conclusions Participation in physical activity has important and meaningful consequences for persons with MS. This study provided evidence for the average daily step counts of persons with MS from a large sample using pedometers and accelerometers as objective measures of physical activity. Such a reference value for average daily step counts overall, and by demographic and clinical characteristics for this population, is a first step toward generating recommendations for meeting public health guidelines through increased walking, which has the potential to improve the overall health of persons with MS.
Suppliers a. Yamax Corp, Yamasa Tokei Keiki Co, 1-5-7, Chuo-cho, Meguro-ku, Tokyo 152-8691, Japan. b. ActiGraph Corp, 49 E Chase St, Pensacola, FL 32502. c. SPSS Inc, 233 S Wacker Dr, 11th Fl, Chicago, IL 60606.
D. Dlugonski et al
Keywords Health; Multiple sclerosis; Rehabilitation; Walking
Corresponding author Robert W. Motl, PhD, Department of Kinesiology and Community Health, University of Illinois, 233 Freer Hall, Urbana, IL 61801. E-mail address: [email protected].
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Steps per day among persons with multiple sclerosis 19. Weikert MW, Dlugonski D, Balantrapu S, Motl RW. Most common types of physical activity self-selected by persons with multiple sclerosis. Int J MS Care 2011;13:16-20. 20. Rietberg MB, van Wegen EE, Uitdehaag BM, de Vet HC, Kwakkel G. How reproducible is home-based 24-hour ambulatory monitoring of motor activity in patients with multiple sclerosis? Arch Phys Med Rehabil 2010;91:1537-41.
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1539 21. Motl RW, Dlugonski D, Wo´jcicki TR, McAuley E, Mohr DC. Internet intervention for increasing physical activity in persons with multiple sclerosis. Mult Scler 2011;17:116-28. 22. Dlugonski D, Motl RW, Mohr DC, Sandroff BM. Internet-delivered behavioral intervention to increase physical activity in persons with multiple sclerosis: sustainability and secondary outcomes. Psychol Health Med 2012;17:636-51.