Authors: Susan L. Kasser, PhD Jesse V. Jacobs, PhD Benjamin Littenberg, MD John T. Foley, PhD Bradley J. Cardinal, PhD Gianni F. Maddalozzo, PhD
Multiple Sclerosis
ORIGINAL RESEARCH ARTICLE
Affiliations: From the Department of Rehabilitation and Movement Science (SLK, JVJ) and Department of Medicine (BL), University of Vermont, Burlington, Vermont; Department of Physical Education, State University of New York at Cortland, Cortland, New York (JTF); and School of Biological and Population Health Sciences, Oregon State University, Corvallis, Oregon (BJC, GFM).
Exploring Physical Activity in Women with Multiple Sclerosis Associations with Fear of Falling and Underlying Impairments
Correspondence:
ABSTRACT
All correspondence and requests for reprints should be addressed to: Susan L. Kasser, PhD, Department of Rehabilitation and Movement Science, University of Vermont, 306 Rowell Bldg, 106 Carrigan Dr, Burlington, VT 05405.
Kasser SL, Jacobs JV, Littenberg B, Foley JT, Cardinal BJ, Maddalozzo GF: Exploring physical activity in women with multiple sclerosis: associations with fear of falling and underlying impairments. Am J Phys Med Rehabil 2014; 93:461Y469.
Disclosures: Supported by the National Multiple Sclerosis Society (grant no. PP0848) and the John C. Erkkila, M.D., Endowment for Health and Human Performance, Good Samaritan Hospital Foundation, Corvallis, OR. Financial disclosure statements have been obtained, and no conflicts of interest have been reported by the authors or by any individuals in control of the content of this article.
0894-9115/14/9306-0461 American Journal of Physical Medicine & Rehabilitation Copyright * 2014 by Lippincott Williams & Wilkins DOI: 10.1097/PHM.0000000000000049
Objective: The aim of this study was to conduct an exploratory analysis of fear of falling (FoF), balance, gait, and strength impairments and future physical activity in women with multiple sclerosis. Design: This prospective study followed a convenience sample of 99 women with multiple sclerosis for 1 yr. The participants were assessed on FoF and perceived mental health by questionnaire. Objective measures included Limits of Stability, the Sensory Organization Test, and the Functional Ambulation Profile. Strength was quantified by knee extensor power asymmetry. Activity-specific metabolic equivalent values were used to determine minutes per week of moderate and vigorous physical activity.
Results: Future physical activity most strongly associated with baseline FoF (R 2 = 0.09, P G 0.01), and baseline FoF associated with limits of stability and lower extremity strength asymmetry (R 2 = 0.21, P G 0.001). Follow-up FoF is best predicted by initial levels of FoF independent of intervening falls (A = 3.26, P G 0.001).
Conclusions: Future physical activity of women with multiple sclerosis was best predicted by FoF independent of physical and mental functioning. Increased FoF was associated with greater lower extremity strength asymmetry and decreased limits of stability rather than with the experience of falls. Key Words:
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Physical Activity, Balance, Prospective Design, Psychology
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I
ndividuals with multiple sclerosis (MS) experience broad and variable symptoms that pose substantial challenges to daily functioning, mobility, and community participation.1,2 Cumulative evidence suggests that physical activity can be beneficial for symptom management and functional improvements.3 It has also been proposed that increased activity may reduce neurologic impairment and slow disease progression.3Y5 Nonetheless, individuals with MS engage in less physical activity and at lower intensity levels than do other populations.6Y8 This is particularly important for women with MS because the incidence of MS for women is twice that for men9 and women are at high risk for osteoporosis and osteoporotic fractures.10,11 In addition, activity limitations are important to understand because these associate with disability progression12,13 as well as poorer perceived mental health and health-related quality of life.14Y18 Although the importance of physical activity is apparent, it is less clear what factors drive this behavior in individuals with MS. Substantial research has focused on examining a range of physical, environmental, and behavioral correlates of physical activity among those with the disease. Such correlates include the frequency and the severity of MS symptoms,19Y21 self-efficacy and social cognitive constructs,22Y24 as well as health beliefs.25Y27 In addition, restricted activity has been associated with falls and fear of falling (FoF) in this group.28,29 However, the relative associations among falls, FoF, balance impairment, and physical activity remain unclear because FoF and activity curtailment have been observed in individuals with and without a history of falls.28Y30 Whereas the role played by FoF in activity participation has been investigated, little attention has been directed to examining specific factors underlying this increased fear. In the published studies associating FoF and physical activity, researchers have noted mobility difficulties, imbalance, and lowered mental health as correlates of FoF.28,29 However, while specific mechanisms related to poor balance and mobility have been examined in relation to falls,31,32 the extent to which these underlying impairments influence FoF, and ultimately physical activity, has yet to be explored. Moreover, the research to date has primarily been cross-sectional and limited by retrospective accounts of falling and activity restriction. The degree to which individuals with MS can realize the benefits of an active lifestyle requires a stronger understanding of the determinants of physical activity behavior in this population. Exploring how specific impairments intersect with FoF and prospec-
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tively influence future physical activity may provide this clarity. Therefore, the analytic goal of this study was to identify the best independent and modifiable predictors of future physical activity from baseline measures of FoF and physical impairments of balance, gait, and strength and then to identify the correlates of these baseline predictors. In doing so, researchers and practitioners may be better able to deliver targeted interventions to decrease FoF, increase physical activity, and optimize long-term health and functioning among those with MS.
METHODS Participants Participants included a convenience sample of 99 ambulatory women, aged 30Y74 yrs (mean age, 50.5 yrs; SD, 8.4 yrs), with physician-diagnosed MS (Table 1). To be included in the study, the women had to report no exacerbation of symptoms within the 3 mos before enrollment. The participants also had to provide a signed release from their physician indicating that they were independent (i.e., could drive themselves to the testing facility, did not require assistance to perform activities of daily living) and to have sufficient cognitive ability to comprehend and answer all questionnaires and to successfully complete assessments. Approval for this study was obtained from the institutional review boards of the authors’ respective institutions, and all participants gave written informed consent before participation.
Procedures Before initial testing, demographic and clinical characteristics of each participant were collected. The participants completed questionnaires on FoF and perceived health status. They were also evaluated on physical assessments of balance, gait, and lower extremity strength at the start of the study. The order of baseline testing was randomized except for the strength measure, which was conducted last to minimize localized muscle fatigue. The participants were provided rest periods between assessments as needed. In the following year, each participant kept a daily falls log and, at 12 mos, was assessed on FoF and level of physical activity.
Fear of Falling The Survey of Activities and Fear of Falling in the Elderly33 was used to assess each participant’s FoF while engaged in 11 activities of daily living associated with social and recreational activities. On the measure, participants are asked whether they do each activity and, if so, how worried they are that they
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TABLE 1 Subject characteristics and assessments
Characteristics Expanded Disability Status score Age, yrs BMI Baseline SF-36 mental component summary Sensory Orientation equilibrium score FAP FoF LOS maximum excursion Knee extension asymmetry Follow-up Falls FoF Moderate/vigorous physical activity, mins per week
N
Mean
SD
52 67 67
2.97 50.5 25.8
1.3 8.38 4.89
67 67 67 67 67 67
42.7 72.4 89.2 0.735 78.6 18.9
7.85 14 11.4 0.65 11.6 15.2
60 65 67
1.62 0.714 207
2.97 0.642 283
Minimum
Median
0 29.9 17.6
3 49.7 25.4
25.5 0 48.5 0 37.5 0.215
43.2 77 91.8 0.545 81.8 17.4
0 0 0
0 0.545 100
Maximum 5.5 73.7 42.1 60.1 87 100 2.2 96.3 62.6 16 2.27 1230
SF-36, Short-Form 36 Health Survey.
might fall (0, not at all worried; 1, a little worried; 2, somewhat worried; and 3, very worried). The fear score is obtained by averaging the worry scores across the number of activities performed by the participant. Scores range from 0 to 3, with higher scores indicating greater fear. The reliability and the validity of the Survey of Activities and Fear of Falling in the Elderly have been established in the elderly34 and other patient populations.35
Mental and Emotional Functioning Mental and emotional functioning were assessed using the Short-Form 36 Health Survey mental component summary score.36 The mental component summary score was derived according to published scoring guidelines from four of the survey’s subscales: vitality, social functioning, role emotional, and mental health. Scores are standardized to a range of 0 to 100 and norm based with a mean of 50. There is excellent evidence for the reliability and the validity of the Short-Form 36 Health Survey in a variety of populations including those with MS.37
Physical Activity The participants completed the Aerobics Center Longitudinal Study Physical Activity Questionnaire,38 reporting the frequency and duration of various activities such as stair climbing, walking, bicycling, swimming, aerobic dance, sport-related activities, weight training, household activities, and lawn work or gardening. For some activities, pace or distance was also requested to provide an estimate of the intensity of the activity. Intensity of each activity was determined using published activity-specific metabolic equivalent values.39 Metabolic equivalent values of less than 3 www.ajpmr.com
indicate light activity, values of 3Y6 indicate moderate activity, and values of greater than 6 indicate vigorous activity. For each participant, minutes per week of light, moderate, and vigorous physical activity were calculated on the basis of the determined metabolic equivalent values for each reported activity. Minutes per week of moderate and vigorous activity levels were then combined to better align with published guidelines for health-promoting levels of physical activity40 and used in the analysis. Although the psychometric properties of the Aerobics Center Longitudinal Study Physical Activity Questionnaire have not been established for individuals with MS, it has been validated for both younger and older adults and used in other MS research involving physical activity assessment.41
Balance Multiple dimensions of balance were assessed using the Smart Balance Master (NeuroCom, Clackamas, OR). This computerized system was used to quantify standing balance via estimations of center-of-gravity displacements derived from measured ground reaction forces under a participant’s feet during standing sway or voluntary standing leans.42 Computerized dynamic posturography has been extensively used in balance research and shown to associate with disability level43,44 and fall status45 in people with MS. Organization of sensory information during stance was evaluated with the Sensory Organization Test.42 By controlling the usefulness of the sensory information through sway referencing and/or eyesopen versus eyes-closed conditions, the Sensory Organization Test identifies the relative contributions of the visual, somatosensory, and vestibular systems used Physical Activity in Women with MS
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to control standing posture. Differences in the amount of body sway under six different sensory conditions determine a participant’s ability to organize and select the appropriate sensory information to maintain postural control. For the Sensory Organization Test, an equilibrium score quantifies the center of gravity’s displacement for three trials for each of the six sensory conditions. The weighted average of the scores across all sensory conditions is then used to calculate a composite equilibrium score, which characterizes the overall level of performance. A score of 100 represents no sway, whereas a score of zero indicates sway that exceeds the limits of stability and results in a loss of balance. The Sensory Organization Test protocol has been found to be important in predicting future falls in women with MS.32 The Limits of Stability (LOS) test was used to quantify the maximum distance one can volitionally lean toward predetermined targets in eight different directions without losing balance, stepping, or reaching for assistance.42 Each target is positioned at 100% of the individual’s maximum theoretical stability limits or the maximum range in which the center of body mass can be moved safely without changing the base of support. The maximum center-of-gravity excursion achieved while leaning is averaged across the eight targets. The LOS test has been shown to be a reliable measure in people with a fall history46 and important in determining fall risk in people with MS.32
Gait The GAITRite walkway system (CIR Systems, United States) was used to measure the temporalspatial parameters of gait. The system entails a 3.66-m long by 0.61-m wide walkway with electronic sensors arranged in a grid to identify footfall contacts. Data were sampled at a frequency of 80 Hz. The spatial and temporal characteristics of gait were processed and stored using GAITRite GOLD, version 3.2b software. The participants were instructed to start walking 4 m before reaching the walkway and continue walking 4 m beyond the walkway to ensure that all gait parameters were collected in steady-state walking. The participants performed four walking trials while barefoot or in their stocking feet at a requested Beveryday walking pace.[ Data from the recorded gait variables of four trials were averaged into a composite Functional Ambulation Profile (FAP), a quantitative index of gait quality. The FAP score is based on the step length/leg length ratio, step time, normalized velocity, and dynamic base of support.47 The basis of the FAP score is the linear relationship between step length/leg length ratio to
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step time when velocity is normalized to leg length. As with the balance measures, the participants were assessed in accordance with protocols recommended by the manufacturers and previously published research examining gait impairments in MS.48Y50
Strength The Biodex Multipoint System 3 (Biodex Medical Systems, Inc, Shirley, NY) was used to assess strength through measures of peak power produced by activating the knee extensors on each leg. The strength assessment protocol was programmed into the dynamometer to set the start and stop angles as well as the speed of contraction to standardize testing and ensure consistency. All tests were conducted at a speed of 30 degrees per second and were gravity corrected. Range of motion for the knee extensors was 90 to 160Y170 degrees. Each participant warmed up with 10 submaximal trials followed by three trials at maximal effort. Each maximal effort was separated by approximately 1 min of rest. Asymmetry scores were determined for peak isometric power of the knee extensors. The asymmetry score is equal to 1 minus the value of the weaker limb divided by the value of the stronger limb. Zero percent asymmetry indicates even distribution of power across limbs, and 100% indicates maximal asymmetry. Strength asymmetry, rather than the unilateral strength of each leg, was used in this study for two reasons. Although bilateral strength loss has been observed in this group, individuals with MS often report unilateral muscle weakness.51 In addition, Chung et al.52 not only found bilateral power deficits and asymmetry of the knee extensor muscles of women with MS but also showed that the extent of bilateral strength asymmetry in knee extensors was significantly associated with variability in center-of-pressure displacements and postural instability in those with the disease.
Falls After initial testing, each day for 12 mos the participants were asked to document whether they had fallen and to record a description of the fall. The participants were instructed that a Bfall[ was any unexpected loss of balance that resulted in wholebody contact with the ground.53 Research assistants telephoned each participant every 6 wks, on average, to follow up on the individual’s fall reporting during that period.
Analysis The analytic goal was to identify the best independent predictors of future physical activity from measures of FoF as well as physical impairments
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TABLE 2 Backward stepwise logistic regression of physical activity at follow-up Final Model Independent Variables Baseline FoF Constant R2 P N
A
P
j1.18 0.88
0.007 0.028 0.09 0.003 67
A = regression coefficient. Although all modifiable baseline variables were included in the model (BMI, FoF, sensory organization equilibrium score, LOS maximum excursion, FAP, mental component score, and knee extension power asymmetry), only the significant predictor is shown here.
of balance, gait, and strength and then to identify the correlates of these baseline predictors. Because the distributions of the outcome variables (and their linear transforms) were not normally distributed, they were transformed into binary variables by dichotomizing at their median values. For instance, activity at follow-up was declared to be Bhigh[ if the participant’s value was in the top half of all reported values and Blow[ otherwise. These binary variables were modeled as the logistic function of linear combinations of the candidate predictors. The model started with an Ball-in[ approach, in which all candidate predictors were included and then repeated in the analysis with the least significant predictor systematically removed one at a time in a Bbackward stepwise[ fashion until remaining predictors were significant with P G 0.05. Because these could not be interpreted clinically as modifiable factors, no interaction terms were included in the models. Some of the 99 participants did not complete every assessment because they either could not or chose not to complete the test. The models were built on the subset of 67 participants with complete data and then repeated with the larger set of participants with incomplete data. There were no significant differences in the models when these partially complete records were added. Nonetheless, the authors report the models with those participants who successfully completed all assessments (Table 1). The initial analysis sought to identify modifiable baseline predictors of future activity. The second analysis sought to identify modifiable predictors of the characteristics identified in the first analysis. Given the known association between body mass index (BMI) and physical activity, BMI was included in the models as a control variable to assess the correlates of physical activity independent of BMI. www.ajpmr.com
Finally, as a secondary analysis, the effect of FoF at baseline and the number of actual falls reported between baseline and follow-up, and their interaction, were modeled with FoF at follow-up. In addition, the effect of baseline FoF and the number of intervening falls, and their interaction, were modeled on future physical activity. All analyses were done in Stata 11.2 (StataCorp LP, College Station, TX).
RESULTS The participants varied greatly in weekly minutes of moderate to vigorous physical activity at follow-up (Table 1). At this time, 33 (50%) of 67 participants reported at least 100 mins per week. In addition, 35 participants (58%) experienced at least one fall during the 12 mos, with a total of 100 falls reported for the sample. Most of the participants (93%) were on some type of disease-modifying therapy, and all were taking medications for MSrelated symptom management. Ten of the women (14%) reported having an exacerbation of symptoms during the 1-yr period. When considering the combined levels of moderate and vigorous physical activity, the regression analysis identified baseline FoF as the only significant independent predictor of future physical activity (R 2 = 0.09, P G 0.01) (Table 2). On the basis of this finding, a subsequent regression analysis with remaining baseline variables resulted in limits of stability and knee extension asymmetry being the only significant independent predictors of current FoF (R 2 = 0.21, P G 0.001) (Table 3). After controlling for FoF at baseline, the number of falls was not significantly associated with future FoF (A = 3.26; P G 0.001). Falls did, however, independently predict future physical
TABLE 3 Backward stepwise logistic regression of baseline FoF Final Model Independent Variables (Baseline) LOS Knee extension asymmetry Constant R2 P N
A j0.06 0.07 2.87
P 0.04 0.001 0.18 0.21 G0.001 67
A = regression coefficient. Although all modifiable baseline variables were included in the model (BMI, sensory organization equilibrium score, LOS maximum excursion, FAP, mental component score, and knee extension power asymmetry), only the significant predictors are shown here.
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activity when considered with initial levels of fear (A = j0.34; P G 0.01).
DISCUSSION The primary aim of this study was to better understand modifiable mechanisms underlying future physical activity considering both FoF as well as physical impairments of strength, balance, and gait in women with MS. The lowered physical activity levels of the women in this study are commensurate with that found in other MS research.6Y8 Although some individuals achieved activity levels sufficient to promote health, most failed to meet recommended guidelines of at least 30 mins on 5 days per week.40 In this study, future physical activity was best predicted by FoF independent of physical and mental functioning. Finally, increased FoF was associated with more strength asymmetry and decreased limits of stability. The finding that FoF represented the only significant independent predictor of physical activity is consistent with Peterson et al.,28 who demonstrated in a cross-sectional design that nearly 83% of individuals with MS who report an FoF also report reduced physical activity. These researchers further demonstrated that activity curtailment associated with needing assistance during walking and activities of daily living. The results of this study provide additional insight, demonstrating that although physical activity associates with impaired balance, gait, and strength, these associated impairments offered no additional predictive ability to identify physical activity levels beyond that provided by FoF alone. FoF would certainly be an important contributor to a person’s willingness or perceived ability to engage in physical activity. FoF may be of greater influence than actual impairments in objectively recorded balance, gait, and strength, at least partially, because the sample was primarily composed of younger participants with milder MS. FoF and its subsequent activity curtailment may thus represent preventive strategies to mitigate fall risk rather than in response to a fall, especially in light of the increased number of Bnear falls[ common in MS.31 The current study also offers some evidence to support previously identified associations between falls and physical activity.28,29 Unlike the findings of Sosnoff and colleagues,30 who suggested that fall history has little impact on physical activity levels, the findings from the present study showed that falls, irrespective of baseline FoF, did indeed predict future activity. One reason for this difference could be attributed to the timing of fall reports. The present study prospectively measured falls and
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physical activity, whereas in the previous study, participants retrospectively recalled their fall history. It is possible that retrospective accounts may have led to inaccuracies or underreporting of falls. Another reason for the discrepant findings may be related to the nature and the type of physical activity. In the earlier study, physical activity was quantified as steps per day. In this study, physical activity was measured, albeit by self-report, as minutes per day of moderate to vigorous physical activity. Although speculative, it may be possible that falls have a differential effect on the type and the intensity of physical activity. Individuals who have fallen may remain active by accumulating a large number of steps, but these steps may be amassed from light activity rather than activity intense enough to derive significant health benefit. Nonetheless, further empirical study exploring the role FoF and falls play in relation to physical activity of varying intensities remains necessary. Although FoF was found to be the best predictor of physical activity in this study, it accounted for only a small part of the variability observed (R2 = 0.09). Because none of the other assessed impairments (i.e., strength, balance, gait, or mental health) significantly improved predictions of physical activity beyond that provided by FoF, other personal and environmental factors likely exist to influence activity participation in this group. It seems that physical activity behavior is more complex and must be examined more broadly than with considerations of only balance, strength, gait, and FoF. Future research should explore a range of physical, social, and cognitive factors that may contribute to physical activity involvement for persons with MS.54 This study suggests that limits of stability and strength asymmetry of the lower extremities provide better predictors of FoF than do gait quality and sensory organization. It remains unclear whether FoF influenced the participants’ willingness to lean to their limits of stability and to engage a maximum knee extensor contraction or whether these impairments limit balance confidence and thus physical activity. Although the direction of effect must first be clarified, these findings suggest an opportunity to impact FoF by intervening on strength and limits of stability.
Study Limitations Although this study offers a prospective evaluation of physical activity in people with MS, the findings should be considered in light of potential study limitations. Levels of physical activity were obtained though self-report, which may not be accurate, sensitive enough to detect differences in activity levels or
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may differentially correlate with objective measures of physical activity depending on the specific selfreport measure used.55Y57 Further, the physical activity instrument used for this study has not been validated specifically for research on participants with MS. However, the instrument did include a range of activities (i.e., walking, bicycling, swimming, floor exercises, household chores, and lawn work) commensurate with the functional levels of the participants in the present study, and metabolic equivalent values obtained for the sample seemed comparable with other MS research. Although the Survey of Activities and Fear of Falling in the Elderly instrument incorporates a range of activities appropriate for individuals with MS, the instrument has not been validated for this population and, as well, may be limited by ceiling effects.34 Other instruments of FoF may provide more dispersed score distributions and, therefore, may provide more sensitive correlates to physical activity. Nonetheless, the symptoms between older adults and those with MS are similar, and the Survey of Activities and Fear of Falling in the Elderly scale has demonstrated strong validity when selfadministered.34 The study sample was restricted to women with MS who were relatively young and ambulatory and had mild to moderate disability. Differences in age, disability phenotype and status, pharmaceutical treatments, and functional capacity between the participants in this study and those in other MS research may limit generalizability and comparability. Moreover, this study did not use a control group of healthy participants. As such, definitive conclusions regarding the magnitude of physical activity restriction in women with MS compared with an agematched healthy population cannot be offered. This study assessed only a few predictors of activity. Other factors such as cardiovascular conditioning, symptoms of fatigue and depression, comorbidities, self-efficacy, or exercise outcome expectations also associate with physical activity.12,19,58,59 Future research should include a broader range of disease-specific and psychosocial factors when exploring physical activity participation in people with MS.
CONCLUSIONS The potential benefits of physical activity combined with the typically low levels of physical activity in people with MS suggests a strong need for intervention, especially in light of speculations that physical activity might slow disease progression.4,5,60 This study_s findings indicate that physical www.ajpmr.com
activity is associated more with FoF than with physical impairments of balance, strength, and gait and that FoF associates with specific deficits in balance and strength rather than with the experience of falls. These deficits may represent opportunities to intervene and increase physical activity and general health in this population. REFERENCES 1. Ploughman M, Austin MW, Murdoch M, et al: Factors influencing healthy aging with multiple sclerosis: A qualitative study. Disabil Rehabil 2011;34:26Y33 2. Crawford A, Hollingsworth HH, Morgan K, et al: People with mobility impairments: Physical activity and quality of participation. Disabil Health J 2008;1:7Y13 3. Doring A, Pfueller C, Paul F, et al: Exercise in multiple sclerosisVAn integral component of disease management. EPMA J 2012;3:1Y13 4. Dalgas U, Stenager E: Exercise and disease progression in multiple sclerosis: Can exercise slow down the progression of multiple sclerosis? Ther Adv Neurol Disord 2012;5:81Y95 5. Motl RW, Dlugonski D, Pilutti L, et al: Premorbid physical activity predicts disability progression in relapsing-remitting multiple sclerosis. J Neurol Sci 2012;323:123Y7 6. Sandroff BM, Dlugnski D, Weikert M, et al: Physical activity and multiple sclerosis: New insights regarding inactivity. Acta Neurol Scand 2012;126:256Y62 7. Motl RW, McAuley E, Snook EM: Physical activity and multiple sclerosis: A meta-analysis. Mult Scler 2005;11:459Y63 8. Beckerman H, Groot V, Scho¨lten MA, et al: Physical activity behavior of people with multiple sclerosis: Understanding how they can become more physically active. Phys Ther 2010;90:1001Y13 9. Koch-Henriksen N, SLrensen PS: The changing demographic pattern of multiple sclerosis epidemiology. Lancet Neurol 2010;9:520Y32 10. Marrie RA, Cutter G, Tyry T, et al: A cross-sectional study of bone health in multiple sclerosis. Neurol 2009; 73:1394Y8 11. Gibson JC, Summers GD: Bone health in multiple sclerosis. Osteoporos Int 2011;22:2935Y49 12. Marrie RA, Horwitz RI: Emerging effects of comorbidities on multiple sclerosis. Lancet Neurol 2010;9:820Y8 13. Motl R, McAuley E: Association between change in physical activity and short-term disability progression in multiple sclerosis. J Rehabil Med 2011;43:305Y10 14. Benito-Leon J, Morales JM, Rivera-Navarro J, et al: A review about the impact of multiple sclerosis on health-related quality of life. Disabil Rehabil 2003;25: 1291Y303 15. Mitchell AJ, Benito-Leon J, Gonzalez JM, et al: Quality of life and its assessment in multiple sclerosis: Integrating physical and psychological components of well-being. Lancet Neurol 2005;4:556Y66
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32. Kasser SL, Jacobs JV, Foley JT, et al: A prospective evaluation of balance, gait, and strength to predict falling in women with multiple sclerosis. Arch Phys Med Rehabil 2011;92:1840Y6 33. Lachman ME, Howland J, Tennstedt S, et al: Fear of falling and activity restriction: The Survey of Activities and Fear of Falling in the Elderly (SAFE). J Gerontol Psychol Sci 1998;53B:43Y50 34. Talley KMC, Wyman JF, Gross CR: Psychometric properties of the activities-specific balance confidence scale and the survey of activities and fear of falling in older women. J Am Geriatr Soc 2008;56:328Y33 35. Nilsson MH, Drake AM, Hagell P: Assessment of fall-related self-efficacy and activity avoidance in people with Parkinson’s disease. BMC Geriatrics 2010; 10:78 36. Ware JE, Kosinski M, Gandel B: SFY36 Health Survey: Manual and interpretation guide. Lincoln, RI, QualityMetric, 2003 37. Vickrey BG, Hays RD, Harooni R, et al: A healthrelated quality of life measure for multiple sclerosis. Qual Life Res 1995;4:187Y206 38. Blair SN: The Aerobics Center Longitudinal Study Physical Activity questionnaire. Med Sci Sports Exerc 1997;29:S10Y4 39. Ainsworth BE, Haskell WL, Whitt MC, et al: Compendium of physical activities: An update of activity codes and MET intensities. Med Sci Sport Exerc 2000;32:S498Y516 40. Haskell WL, Lee I-M, Pate RP, et al: Physical activity and public health: Updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc 2007;39:1423Y34 41. Trojan DA, Arnold D, Collet JP, et al: Fatigue in multiple sclerosis: Association with disease-related, behavioural and psychosocial factors. Mult Scler 2007;13:985Y95 42. NeuroCom International, Inc: Balance Masters operators manual. Clackamus, OR, NeuroCom International Inc, 1999 43. Boes MK, Sosnoff JJ, Socie MJ, et al: Postural control in multiple sclerosis: Effects of disability status and dual task. J Neurol Sci 2012;315:44Y8 44. Caoa H, Peyrodiea L, Boudeta S, et al: Expanded Disability Status Scale (EDSS) estimation in multiple sclerosis from posturographic data. Gait Posture 2012;37:242Y5 45. Prosperini L, Fortuna D, Giannı` C, et al: The diagnostic accuracy of static posturography in predicting accidental falls in people with multiple sclerosis. Neurorehabil Neural Repair 2013;27:45Y52 46. Clark S, Rose DJ: Evaluation of dynamic balance among community-dwelling older adult fallers: A generalizability study of the limits of stability. Arch Phys Med Rehabil 2001;82:468Y74 47. Nelson AJ: Functional Ambulation Profile. Phys Ther 1974;54:1059Y65 48. Givon U, Zeilig G, Achiron A: Gait analysis in multiple sclerosis: Characterization of temporal-spatial
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parameters using GAITRite functional ambulation system. Gait Posture 2009;29:138Y42 49. Sosnoff JJ, Weikert M, Dlugonski D, et al: Quantifying gait impairment in multiple sclerosis using GAITRite technology. Gait Posture 2011;34:145Y7 50. Sosnoff JJ, Sandroff BM, Motl RW: Quantifying gait abnormal in persons with multiple sclerosis with minimal disability. Gait Posture 2012;36:154Y6 51. Lambert CP, Archer RL, Evans WJ: Muscle strength and fatigue during isokinetic exercise in individuals with multiple sclerosis. Med Sci Sports Exerc 2001; 33:1613Y9 52. Chung LH, Remelius JG, Van Emmerik RE, et al: Leg power asymmetry and postural control in women with multiple sclerosis. Med Sci Sports Exerc 2008;40:1717Y24
55. Motl RW, Sandroff BM: Objective monitoring of physical activity behavior in multiple sclerosis. Phys Ther Rev 2010;15:204Y11 56. Motl RW, McAuley E, Snook EM, et al: Validity of physical activity measures in ambulatory individuals with multiple sclerosis. Disabil Rehabil 2006;28: 1151Y6 57. Gosney JL, Scott JA, Snook EM, et al: Physical activity and multiple sclerosis: Validity of self-report and objective measures. Fam Community Health 2007;30:144Y50 58. Motl RW, Snook EM, McAuley E, et al: Symptoms, self-efficacy, and physical activity among individuals with multiple sclerosis. Res Nurs Health 2006;29: 597Y606
53. Nevitt MC, Cummings Sr, Kidd S, et al: Risk factors for recurrent nonsyncopal falls: A prospective study. JAMA 1989;261:2663Y8
59. Ferrier S, Dunlop N, Blanchard C: The role of outcome expectations and self-efficacy in explaining physical activity behaviors of individuals with multiple sclerosis. Behav Med 2010;36:7Y11
54. Levy SS, Li K-K, Cardinal BJ, et al: Transitional shifts in exercise behavior among women with multiple sclerosis. Disabil Health J 2009;2:216Y23
60. Benito-Leo´n J: Physical activity in multiple sclerosis: The missing prescription. Neuroepidemiol 2011;36: 192Y3
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Multiple Sclerosis
ORIGINAL RESEARCH ARTICLE
Affiliations: From the Department of Rehabilitation and Movement Science (SLK, JVJ) and Department of Medicine (BL), University of Vermont, Burlington, Vermont; Department of Physical Education, State University of New York at Cortland, Cortland, New York (JTF); and School of Biological and Population Health Sciences, Oregon State University, Corvallis, Oregon (BJC, GFM).
Exploring Physical Activity in Women with Multiple Sclerosis Associations with Fear of Falling and Underlying Impairments
Correspondence:
ABSTRACT
All correspondence and requests for reprints should be addressed to: Susan L. Kasser, PhD, Department of Rehabilitation and Movement Science, University of Vermont, 306 Rowell Bldg, 106 Carrigan Dr, Burlington, VT 05405.
Kasser SL, Jacobs JV, Littenberg B, Foley JT, Cardinal BJ, Maddalozzo GF: Exploring physical activity in women with multiple sclerosis: associations with fear of falling and underlying impairments. Am J Phys Med Rehabil 2014; 93:461Y469.
Disclosures: Supported by the National Multiple Sclerosis Society (grant no. PP0848) and the John C. Erkkila, M.D., Endowment for Health and Human Performance, Good Samaritan Hospital Foundation, Corvallis, OR. Financial disclosure statements have been obtained, and no conflicts of interest have been reported by the authors or by any individuals in control of the content of this article.
0894-9115/14/9306-0461 American Journal of Physical Medicine & Rehabilitation Copyright * 2014 by Lippincott Williams & Wilkins DOI: 10.1097/PHM.0000000000000049
Objective: The aim of this study was to conduct an exploratory analysis of fear of falling (FoF), balance, gait, and strength impairments and future physical activity in women with multiple sclerosis. Design: This prospective study followed a convenience sample of 99 women with multiple sclerosis for 1 yr. The participants were assessed on FoF and perceived mental health by questionnaire. Objective measures included Limits of Stability, the Sensory Organization Test, and the Functional Ambulation Profile. Strength was quantified by knee extensor power asymmetry. Activity-specific metabolic equivalent values were used to determine minutes per week of moderate and vigorous physical activity.
Results: Future physical activity most strongly associated with baseline FoF (R 2 = 0.09, P G 0.01), and baseline FoF associated with limits of stability and lower extremity strength asymmetry (R 2 = 0.21, P G 0.001). Follow-up FoF is best predicted by initial levels of FoF independent of intervening falls (A = 3.26, P G 0.001).
Conclusions: Future physical activity of women with multiple sclerosis was best predicted by FoF independent of physical and mental functioning. Increased FoF was associated with greater lower extremity strength asymmetry and decreased limits of stability rather than with the experience of falls. Key Words:
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Physical Activity, Balance, Prospective Design, Psychology
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I
ndividuals with multiple sclerosis (MS) experience broad and variable symptoms that pose substantial challenges to daily functioning, mobility, and community participation.1,2 Cumulative evidence suggests that physical activity can be beneficial for symptom management and functional improvements.3 It has also been proposed that increased activity may reduce neurologic impairment and slow disease progression.3Y5 Nonetheless, individuals with MS engage in less physical activity and at lower intensity levels than do other populations.6Y8 This is particularly important for women with MS because the incidence of MS for women is twice that for men9 and women are at high risk for osteoporosis and osteoporotic fractures.10,11 In addition, activity limitations are important to understand because these associate with disability progression12,13 as well as poorer perceived mental health and health-related quality of life.14Y18 Although the importance of physical activity is apparent, it is less clear what factors drive this behavior in individuals with MS. Substantial research has focused on examining a range of physical, environmental, and behavioral correlates of physical activity among those with the disease. Such correlates include the frequency and the severity of MS symptoms,19Y21 self-efficacy and social cognitive constructs,22Y24 as well as health beliefs.25Y27 In addition, restricted activity has been associated with falls and fear of falling (FoF) in this group.28,29 However, the relative associations among falls, FoF, balance impairment, and physical activity remain unclear because FoF and activity curtailment have been observed in individuals with and without a history of falls.28Y30 Whereas the role played by FoF in activity participation has been investigated, little attention has been directed to examining specific factors underlying this increased fear. In the published studies associating FoF and physical activity, researchers have noted mobility difficulties, imbalance, and lowered mental health as correlates of FoF.28,29 However, while specific mechanisms related to poor balance and mobility have been examined in relation to falls,31,32 the extent to which these underlying impairments influence FoF, and ultimately physical activity, has yet to be explored. Moreover, the research to date has primarily been cross-sectional and limited by retrospective accounts of falling and activity restriction. The degree to which individuals with MS can realize the benefits of an active lifestyle requires a stronger understanding of the determinants of physical activity behavior in this population. Exploring how specific impairments intersect with FoF and prospec-
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tively influence future physical activity may provide this clarity. Therefore, the analytic goal of this study was to identify the best independent and modifiable predictors of future physical activity from baseline measures of FoF and physical impairments of balance, gait, and strength and then to identify the correlates of these baseline predictors. In doing so, researchers and practitioners may be better able to deliver targeted interventions to decrease FoF, increase physical activity, and optimize long-term health and functioning among those with MS.
METHODS Participants Participants included a convenience sample of 99 ambulatory women, aged 30Y74 yrs (mean age, 50.5 yrs; SD, 8.4 yrs), with physician-diagnosed MS (Table 1). To be included in the study, the women had to report no exacerbation of symptoms within the 3 mos before enrollment. The participants also had to provide a signed release from their physician indicating that they were independent (i.e., could drive themselves to the testing facility, did not require assistance to perform activities of daily living) and to have sufficient cognitive ability to comprehend and answer all questionnaires and to successfully complete assessments. Approval for this study was obtained from the institutional review boards of the authors’ respective institutions, and all participants gave written informed consent before participation.
Procedures Before initial testing, demographic and clinical characteristics of each participant were collected. The participants completed questionnaires on FoF and perceived health status. They were also evaluated on physical assessments of balance, gait, and lower extremity strength at the start of the study. The order of baseline testing was randomized except for the strength measure, which was conducted last to minimize localized muscle fatigue. The participants were provided rest periods between assessments as needed. In the following year, each participant kept a daily falls log and, at 12 mos, was assessed on FoF and level of physical activity.
Fear of Falling The Survey of Activities and Fear of Falling in the Elderly33 was used to assess each participant’s FoF while engaged in 11 activities of daily living associated with social and recreational activities. On the measure, participants are asked whether they do each activity and, if so, how worried they are that they
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TABLE 1 Subject characteristics and assessments
Characteristics Expanded Disability Status score Age, yrs BMI Baseline SF-36 mental component summary Sensory Orientation equilibrium score FAP FoF LOS maximum excursion Knee extension asymmetry Follow-up Falls FoF Moderate/vigorous physical activity, mins per week
N
Mean
SD
52 67 67
2.97 50.5 25.8
1.3 8.38 4.89
67 67 67 67 67 67
42.7 72.4 89.2 0.735 78.6 18.9
7.85 14 11.4 0.65 11.6 15.2
60 65 67
1.62 0.714 207
2.97 0.642 283
Minimum
Median
0 29.9 17.6
3 49.7 25.4
25.5 0 48.5 0 37.5 0.215
43.2 77 91.8 0.545 81.8 17.4
0 0 0
0 0.545 100
Maximum 5.5 73.7 42.1 60.1 87 100 2.2 96.3 62.6 16 2.27 1230
SF-36, Short-Form 36 Health Survey.
might fall (0, not at all worried; 1, a little worried; 2, somewhat worried; and 3, very worried). The fear score is obtained by averaging the worry scores across the number of activities performed by the participant. Scores range from 0 to 3, with higher scores indicating greater fear. The reliability and the validity of the Survey of Activities and Fear of Falling in the Elderly have been established in the elderly34 and other patient populations.35
Mental and Emotional Functioning Mental and emotional functioning were assessed using the Short-Form 36 Health Survey mental component summary score.36 The mental component summary score was derived according to published scoring guidelines from four of the survey’s subscales: vitality, social functioning, role emotional, and mental health. Scores are standardized to a range of 0 to 100 and norm based with a mean of 50. There is excellent evidence for the reliability and the validity of the Short-Form 36 Health Survey in a variety of populations including those with MS.37
Physical Activity The participants completed the Aerobics Center Longitudinal Study Physical Activity Questionnaire,38 reporting the frequency and duration of various activities such as stair climbing, walking, bicycling, swimming, aerobic dance, sport-related activities, weight training, household activities, and lawn work or gardening. For some activities, pace or distance was also requested to provide an estimate of the intensity of the activity. Intensity of each activity was determined using published activity-specific metabolic equivalent values.39 Metabolic equivalent values of less than 3 www.ajpmr.com
indicate light activity, values of 3Y6 indicate moderate activity, and values of greater than 6 indicate vigorous activity. For each participant, minutes per week of light, moderate, and vigorous physical activity were calculated on the basis of the determined metabolic equivalent values for each reported activity. Minutes per week of moderate and vigorous activity levels were then combined to better align with published guidelines for health-promoting levels of physical activity40 and used in the analysis. Although the psychometric properties of the Aerobics Center Longitudinal Study Physical Activity Questionnaire have not been established for individuals with MS, it has been validated for both younger and older adults and used in other MS research involving physical activity assessment.41
Balance Multiple dimensions of balance were assessed using the Smart Balance Master (NeuroCom, Clackamas, OR). This computerized system was used to quantify standing balance via estimations of center-of-gravity displacements derived from measured ground reaction forces under a participant’s feet during standing sway or voluntary standing leans.42 Computerized dynamic posturography has been extensively used in balance research and shown to associate with disability level43,44 and fall status45 in people with MS. Organization of sensory information during stance was evaluated with the Sensory Organization Test.42 By controlling the usefulness of the sensory information through sway referencing and/or eyesopen versus eyes-closed conditions, the Sensory Organization Test identifies the relative contributions of the visual, somatosensory, and vestibular systems used Physical Activity in Women with MS
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to control standing posture. Differences in the amount of body sway under six different sensory conditions determine a participant’s ability to organize and select the appropriate sensory information to maintain postural control. For the Sensory Organization Test, an equilibrium score quantifies the center of gravity’s displacement for three trials for each of the six sensory conditions. The weighted average of the scores across all sensory conditions is then used to calculate a composite equilibrium score, which characterizes the overall level of performance. A score of 100 represents no sway, whereas a score of zero indicates sway that exceeds the limits of stability and results in a loss of balance. The Sensory Organization Test protocol has been found to be important in predicting future falls in women with MS.32 The Limits of Stability (LOS) test was used to quantify the maximum distance one can volitionally lean toward predetermined targets in eight different directions without losing balance, stepping, or reaching for assistance.42 Each target is positioned at 100% of the individual’s maximum theoretical stability limits or the maximum range in which the center of body mass can be moved safely without changing the base of support. The maximum center-of-gravity excursion achieved while leaning is averaged across the eight targets. The LOS test has been shown to be a reliable measure in people with a fall history46 and important in determining fall risk in people with MS.32
Gait The GAITRite walkway system (CIR Systems, United States) was used to measure the temporalspatial parameters of gait. The system entails a 3.66-m long by 0.61-m wide walkway with electronic sensors arranged in a grid to identify footfall contacts. Data were sampled at a frequency of 80 Hz. The spatial and temporal characteristics of gait were processed and stored using GAITRite GOLD, version 3.2b software. The participants were instructed to start walking 4 m before reaching the walkway and continue walking 4 m beyond the walkway to ensure that all gait parameters were collected in steady-state walking. The participants performed four walking trials while barefoot or in their stocking feet at a requested Beveryday walking pace.[ Data from the recorded gait variables of four trials were averaged into a composite Functional Ambulation Profile (FAP), a quantitative index of gait quality. The FAP score is based on the step length/leg length ratio, step time, normalized velocity, and dynamic base of support.47 The basis of the FAP score is the linear relationship between step length/leg length ratio to
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step time when velocity is normalized to leg length. As with the balance measures, the participants were assessed in accordance with protocols recommended by the manufacturers and previously published research examining gait impairments in MS.48Y50
Strength The Biodex Multipoint System 3 (Biodex Medical Systems, Inc, Shirley, NY) was used to assess strength through measures of peak power produced by activating the knee extensors on each leg. The strength assessment protocol was programmed into the dynamometer to set the start and stop angles as well as the speed of contraction to standardize testing and ensure consistency. All tests were conducted at a speed of 30 degrees per second and were gravity corrected. Range of motion for the knee extensors was 90 to 160Y170 degrees. Each participant warmed up with 10 submaximal trials followed by three trials at maximal effort. Each maximal effort was separated by approximately 1 min of rest. Asymmetry scores were determined for peak isometric power of the knee extensors. The asymmetry score is equal to 1 minus the value of the weaker limb divided by the value of the stronger limb. Zero percent asymmetry indicates even distribution of power across limbs, and 100% indicates maximal asymmetry. Strength asymmetry, rather than the unilateral strength of each leg, was used in this study for two reasons. Although bilateral strength loss has been observed in this group, individuals with MS often report unilateral muscle weakness.51 In addition, Chung et al.52 not only found bilateral power deficits and asymmetry of the knee extensor muscles of women with MS but also showed that the extent of bilateral strength asymmetry in knee extensors was significantly associated with variability in center-of-pressure displacements and postural instability in those with the disease.
Falls After initial testing, each day for 12 mos the participants were asked to document whether they had fallen and to record a description of the fall. The participants were instructed that a Bfall[ was any unexpected loss of balance that resulted in wholebody contact with the ground.53 Research assistants telephoned each participant every 6 wks, on average, to follow up on the individual’s fall reporting during that period.
Analysis The analytic goal was to identify the best independent predictors of future physical activity from measures of FoF as well as physical impairments
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TABLE 2 Backward stepwise logistic regression of physical activity at follow-up Final Model Independent Variables Baseline FoF Constant R2 P N
A
P
j1.18 0.88
0.007 0.028 0.09 0.003 67
A = regression coefficient. Although all modifiable baseline variables were included in the model (BMI, FoF, sensory organization equilibrium score, LOS maximum excursion, FAP, mental component score, and knee extension power asymmetry), only the significant predictor is shown here.
of balance, gait, and strength and then to identify the correlates of these baseline predictors. Because the distributions of the outcome variables (and their linear transforms) were not normally distributed, they were transformed into binary variables by dichotomizing at their median values. For instance, activity at follow-up was declared to be Bhigh[ if the participant’s value was in the top half of all reported values and Blow[ otherwise. These binary variables were modeled as the logistic function of linear combinations of the candidate predictors. The model started with an Ball-in[ approach, in which all candidate predictors were included and then repeated in the analysis with the least significant predictor systematically removed one at a time in a Bbackward stepwise[ fashion until remaining predictors were significant with P G 0.05. Because these could not be interpreted clinically as modifiable factors, no interaction terms were included in the models. Some of the 99 participants did not complete every assessment because they either could not or chose not to complete the test. The models were built on the subset of 67 participants with complete data and then repeated with the larger set of participants with incomplete data. There were no significant differences in the models when these partially complete records were added. Nonetheless, the authors report the models with those participants who successfully completed all assessments (Table 1). The initial analysis sought to identify modifiable baseline predictors of future activity. The second analysis sought to identify modifiable predictors of the characteristics identified in the first analysis. Given the known association between body mass index (BMI) and physical activity, BMI was included in the models as a control variable to assess the correlates of physical activity independent of BMI. www.ajpmr.com
Finally, as a secondary analysis, the effect of FoF at baseline and the number of actual falls reported between baseline and follow-up, and their interaction, were modeled with FoF at follow-up. In addition, the effect of baseline FoF and the number of intervening falls, and their interaction, were modeled on future physical activity. All analyses were done in Stata 11.2 (StataCorp LP, College Station, TX).
RESULTS The participants varied greatly in weekly minutes of moderate to vigorous physical activity at follow-up (Table 1). At this time, 33 (50%) of 67 participants reported at least 100 mins per week. In addition, 35 participants (58%) experienced at least one fall during the 12 mos, with a total of 100 falls reported for the sample. Most of the participants (93%) were on some type of disease-modifying therapy, and all were taking medications for MSrelated symptom management. Ten of the women (14%) reported having an exacerbation of symptoms during the 1-yr period. When considering the combined levels of moderate and vigorous physical activity, the regression analysis identified baseline FoF as the only significant independent predictor of future physical activity (R 2 = 0.09, P G 0.01) (Table 2). On the basis of this finding, a subsequent regression analysis with remaining baseline variables resulted in limits of stability and knee extension asymmetry being the only significant independent predictors of current FoF (R 2 = 0.21, P G 0.001) (Table 3). After controlling for FoF at baseline, the number of falls was not significantly associated with future FoF (A = 3.26; P G 0.001). Falls did, however, independently predict future physical
TABLE 3 Backward stepwise logistic regression of baseline FoF Final Model Independent Variables (Baseline) LOS Knee extension asymmetry Constant R2 P N
A j0.06 0.07 2.87
P 0.04 0.001 0.18 0.21 G0.001 67
A = regression coefficient. Although all modifiable baseline variables were included in the model (BMI, sensory organization equilibrium score, LOS maximum excursion, FAP, mental component score, and knee extension power asymmetry), only the significant predictors are shown here.
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activity when considered with initial levels of fear (A = j0.34; P G 0.01).
DISCUSSION The primary aim of this study was to better understand modifiable mechanisms underlying future physical activity considering both FoF as well as physical impairments of strength, balance, and gait in women with MS. The lowered physical activity levels of the women in this study are commensurate with that found in other MS research.6Y8 Although some individuals achieved activity levels sufficient to promote health, most failed to meet recommended guidelines of at least 30 mins on 5 days per week.40 In this study, future physical activity was best predicted by FoF independent of physical and mental functioning. Finally, increased FoF was associated with more strength asymmetry and decreased limits of stability. The finding that FoF represented the only significant independent predictor of physical activity is consistent with Peterson et al.,28 who demonstrated in a cross-sectional design that nearly 83% of individuals with MS who report an FoF also report reduced physical activity. These researchers further demonstrated that activity curtailment associated with needing assistance during walking and activities of daily living. The results of this study provide additional insight, demonstrating that although physical activity associates with impaired balance, gait, and strength, these associated impairments offered no additional predictive ability to identify physical activity levels beyond that provided by FoF alone. FoF would certainly be an important contributor to a person’s willingness or perceived ability to engage in physical activity. FoF may be of greater influence than actual impairments in objectively recorded balance, gait, and strength, at least partially, because the sample was primarily composed of younger participants with milder MS. FoF and its subsequent activity curtailment may thus represent preventive strategies to mitigate fall risk rather than in response to a fall, especially in light of the increased number of Bnear falls[ common in MS.31 The current study also offers some evidence to support previously identified associations between falls and physical activity.28,29 Unlike the findings of Sosnoff and colleagues,30 who suggested that fall history has little impact on physical activity levels, the findings from the present study showed that falls, irrespective of baseline FoF, did indeed predict future activity. One reason for this difference could be attributed to the timing of fall reports. The present study prospectively measured falls and
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physical activity, whereas in the previous study, participants retrospectively recalled their fall history. It is possible that retrospective accounts may have led to inaccuracies or underreporting of falls. Another reason for the discrepant findings may be related to the nature and the type of physical activity. In the earlier study, physical activity was quantified as steps per day. In this study, physical activity was measured, albeit by self-report, as minutes per day of moderate to vigorous physical activity. Although speculative, it may be possible that falls have a differential effect on the type and the intensity of physical activity. Individuals who have fallen may remain active by accumulating a large number of steps, but these steps may be amassed from light activity rather than activity intense enough to derive significant health benefit. Nonetheless, further empirical study exploring the role FoF and falls play in relation to physical activity of varying intensities remains necessary. Although FoF was found to be the best predictor of physical activity in this study, it accounted for only a small part of the variability observed (R2 = 0.09). Because none of the other assessed impairments (i.e., strength, balance, gait, or mental health) significantly improved predictions of physical activity beyond that provided by FoF, other personal and environmental factors likely exist to influence activity participation in this group. It seems that physical activity behavior is more complex and must be examined more broadly than with considerations of only balance, strength, gait, and FoF. Future research should explore a range of physical, social, and cognitive factors that may contribute to physical activity involvement for persons with MS.54 This study suggests that limits of stability and strength asymmetry of the lower extremities provide better predictors of FoF than do gait quality and sensory organization. It remains unclear whether FoF influenced the participants’ willingness to lean to their limits of stability and to engage a maximum knee extensor contraction or whether these impairments limit balance confidence and thus physical activity. Although the direction of effect must first be clarified, these findings suggest an opportunity to impact FoF by intervening on strength and limits of stability.
Study Limitations Although this study offers a prospective evaluation of physical activity in people with MS, the findings should be considered in light of potential study limitations. Levels of physical activity were obtained though self-report, which may not be accurate, sensitive enough to detect differences in activity levels or
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may differentially correlate with objective measures of physical activity depending on the specific selfreport measure used.55Y57 Further, the physical activity instrument used for this study has not been validated specifically for research on participants with MS. However, the instrument did include a range of activities (i.e., walking, bicycling, swimming, floor exercises, household chores, and lawn work) commensurate with the functional levels of the participants in the present study, and metabolic equivalent values obtained for the sample seemed comparable with other MS research. Although the Survey of Activities and Fear of Falling in the Elderly instrument incorporates a range of activities appropriate for individuals with MS, the instrument has not been validated for this population and, as well, may be limited by ceiling effects.34 Other instruments of FoF may provide more dispersed score distributions and, therefore, may provide more sensitive correlates to physical activity. Nonetheless, the symptoms between older adults and those with MS are similar, and the Survey of Activities and Fear of Falling in the Elderly scale has demonstrated strong validity when selfadministered.34 The study sample was restricted to women with MS who were relatively young and ambulatory and had mild to moderate disability. Differences in age, disability phenotype and status, pharmaceutical treatments, and functional capacity between the participants in this study and those in other MS research may limit generalizability and comparability. Moreover, this study did not use a control group of healthy participants. As such, definitive conclusions regarding the magnitude of physical activity restriction in women with MS compared with an agematched healthy population cannot be offered. This study assessed only a few predictors of activity. Other factors such as cardiovascular conditioning, symptoms of fatigue and depression, comorbidities, self-efficacy, or exercise outcome expectations also associate with physical activity.12,19,58,59 Future research should include a broader range of disease-specific and psychosocial factors when exploring physical activity participation in people with MS.
CONCLUSIONS The potential benefits of physical activity combined with the typically low levels of physical activity in people with MS suggests a strong need for intervention, especially in light of speculations that physical activity might slow disease progression.4,5,60 This study_s findings indicate that physical www.ajpmr.com
activity is associated more with FoF than with physical impairments of balance, strength, and gait and that FoF associates with specific deficits in balance and strength rather than with the experience of falls. These deficits may represent opportunities to intervene and increase physical activity and general health in this population. REFERENCES 1. Ploughman M, Austin MW, Murdoch M, et al: Factors influencing healthy aging with multiple sclerosis: A qualitative study. Disabil Rehabil 2011;34:26Y33 2. Crawford A, Hollingsworth HH, Morgan K, et al: People with mobility impairments: Physical activity and quality of participation. Disabil Health J 2008;1:7Y13 3. Doring A, Pfueller C, Paul F, et al: Exercise in multiple sclerosisVAn integral component of disease management. EPMA J 2012;3:1Y13 4. Dalgas U, Stenager E: Exercise and disease progression in multiple sclerosis: Can exercise slow down the progression of multiple sclerosis? Ther Adv Neurol Disord 2012;5:81Y95 5. Motl RW, Dlugonski D, Pilutti L, et al: Premorbid physical activity predicts disability progression in relapsing-remitting multiple sclerosis. J Neurol Sci 2012;323:123Y7 6. Sandroff BM, Dlugnski D, Weikert M, et al: Physical activity and multiple sclerosis: New insights regarding inactivity. Acta Neurol Scand 2012;126:256Y62 7. Motl RW, McAuley E, Snook EM: Physical activity and multiple sclerosis: A meta-analysis. Mult Scler 2005;11:459Y63 8. Beckerman H, Groot V, Scho¨lten MA, et al: Physical activity behavior of people with multiple sclerosis: Understanding how they can become more physically active. Phys Ther 2010;90:1001Y13 9. Koch-Henriksen N, SLrensen PS: The changing demographic pattern of multiple sclerosis epidemiology. Lancet Neurol 2010;9:520Y32 10. Marrie RA, Cutter G, Tyry T, et al: A cross-sectional study of bone health in multiple sclerosis. Neurol 2009; 73:1394Y8 11. Gibson JC, Summers GD: Bone health in multiple sclerosis. Osteoporos Int 2011;22:2935Y49 12. Marrie RA, Horwitz RI: Emerging effects of comorbidities on multiple sclerosis. Lancet Neurol 2010;9:820Y8 13. Motl R, McAuley E: Association between change in physical activity and short-term disability progression in multiple sclerosis. J Rehabil Med 2011;43:305Y10 14. Benito-Leon J, Morales JM, Rivera-Navarro J, et al: A review about the impact of multiple sclerosis on health-related quality of life. Disabil Rehabil 2003;25: 1291Y303 15. Mitchell AJ, Benito-Leon J, Gonzalez JM, et al: Quality of life and its assessment in multiple sclerosis: Integrating physical and psychological components of well-being. Lancet Neurol 2005;4:556Y66
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