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Falls in People With Multiple Sclerosis Who Use a Walking Aid: Prevalence, Factors, and Effect of Strength and Balance Interventions
Archives of Physical Medicine and Rehabilitation journal homepage: www.archives-pmr.org Archives of Physical Medicine and Rehabilitation 2013;94:616-21
ORIGINAL ARTICLE
Falls in People With Multiple Sclerosis Who Use a Walking Aid: Prevalence, Factors, and Effect of Strength and Balance Interventions Susan Coote, PhD, Neasa Hogan, PhD, Sue Franklin, PhD From the Department of Clinical Therapies & Centre for Physical Activity and Health Research, University of Limerick, Limerick, Ireland.
Abstract Objectives: To investigate falls prevalence, factors associated with falling, and the effects of balance and strengthening interventions on falls in persons with multiple sclerosis (MS). Design: Baseline and posttreatment data from a randomized controlled trial. Setting: Community. Participants: People with MS (NZ111) who use bilateral support for gait. Interventions: Group and one-on-one physiotherapy. Main Outcome Measures: Falls prevalence was assessed using retrospective recall. Demographic information was collected, impairments of body function were assessed, and results from the Berg Balance Scale, 6-minute walk test (6MWT), Multiple Sclerosis Impact Scale-29 version 2 physical and psychological scores, and the Modified Fatigue Impact Scale (MFIS) were obtained. Results: The prevalence of falls in a 3-month period was 50.5% among participants with MS, of whom 28% had more than 1 fall. Fallers had a greater physical (mean difference, 3.9; PZ.048) and psychological (median difference, 4.5; PZ.001) impact of MS and a greater impact of fatigue (mean difference, 9.4; PZ.002). A logistic regression analysis found that the MFIS score made a unique, significant contribution to the model (odds ratioZ1.04; 95% confidence interval, 1.018e1.079), correctly identifying 68% of fallers. A 10-week group physiotherapy intervention significantly reduced both the number of fallers (58.3% before to 22.9% after intervention, PZ.005) and the number of falls (63 before to 25 after intervention, PZ.001). Conclusions: The prevalence of falls is high in this population of persons with MS, and the impact of MS and of fatigue is greater in fallers. Development and evaluation of interventions to reduce falls risk and the transition to faller or multiple faller status are required. Archives of Physical Medicine and Rehabilitation 2013;94:616-21 ª 2013 by the American Congress of Rehabilitation Medicine
Falls are a significant problem for both the person who falls and the health care system. At a personal level, falls can lead to pain, injury, or fracture. This can lead to increased reliance on others for assistance, fear of falling, and activity curtailment. At a societal level, the medical costs of falls and fractures are great, as are the costs incurred because of loss of income and increased care needs. For people with multiple sclerosis (MS), the prevalence of falls is estimated to be between 52% and 55% in retrospective Presented to the European Committee for Treatment and Research in Multiple Sclerosis, October 13–16, 2010, Gothenburg, Sweden. Supported by Multiple Sclerosis Ireland through the Getting the Balance Right Project. 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. Clinical Trial Registration Number: ISRCTN77610415.
studies1-3 considering self-reported falls in the last 2 to 12 months. Prospective reports suggest similar proportions, with between 48%4 and 63%5 of people falling. This is significantly greater than the prevalence in elderly populations where a large epidemiologic6 study suggested that 15.9% of elderly people fell in a 3-month period. In addition to a higher incidence of falling, people with MS have an increased fracture risk because of a reduction in bone mineral density as a result of decreased mobility, vitamin D deficiency, and the use of glucocorticoids and antidepressants.7 Recent studies in the United Kingdom8 and the Netherlands9 found that the risk of hip fracture in people with MS was higher than in the general population, and that people with MS with a history of falling had double the risk of osteoporotic fracture.8 The incidence of falls was significantly greater in people with
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Falls in people with multiple sclerosis who use a walking aid MS10 than in healthy controls, even in those in the early course of MS. The risk of an injurious fall was 3 times higher for women veterans with MS than for women veterans without MS after controlling for age and number of clinic visits.11 Several studies have investigated the factors relating to falls in people with MS. The factors that are most common are deficits of balance (7 studies),1,2,4,12-15 walking aid use and lower mobility status (6 studies2,5,12,14,16,17), and a higher Expanded Disability Status Score (6 studies4,5,10,13,14,17). Other authors have found that impairments of muscle tone and proprioception,5 continence,1 brainstem and middle cerebellar peduncal lesions,13 and increasing numbers of symptoms16 are associated with falls. Fear of falling and activity curtailment,18 and cognitive deficits17 are also associated with falls in people with MS. There are a variety of symptoms that predict falling. The fact that these symptoms can occur in various combinations highlights the complexity of this problem and its management. Despite the increased prevalence of falls and related injuries, and the ever-increasing body of work to investigate the factors associated with falls in people with MS, there are very few studies with the aim of reducing fall risk or that evaluate falls as an outcome. Although several studies19-21 have reported positive outcomes on balance, only 2 studies were found that have considered number of falls as an outcome. Cattaneo et al19 evaluated balance programs based on sensory and motor strategies, and motor strategies alone and found a significant difference between groups in the number of falls that was not present preintervention. Esnouf et al22 found that those people using a drop-foot stimulator had significantly fewer falls than those participating in an exercise program focusing on core stability. While both studies suggest positive outcomes on number of falls, the small number of studies highlights the need for development and evaluation of interventions to reduce both fall risk and the number of falls. The aim of this article is to present the falls data for a cohort of people with MS who were assessed as part of a randomized controlled trial of interventions for people with MS who use bilateral assistance to walk outdoors. The article presents data on falls prevalence over a 3-month period before intervention, the factors associated with falls, and the effect of 2 physiotherapy interventions and yoga on number of fallers and number of falls in the sample.
Methods These data were part of the baseline assessments of 1 arm of an exercise trial, the methods of which have been published previously.23 Participants were stratified according to their mobility, and these data include people with MS who scored 3 or 4 on the Guys Neurological Disability Rating Scale (GNDS) mobility section (indicating use of bilateral aids for gait and/or occasional wheelchair use for longer distances). Ethical approval was obtained for all the testing sites, and patients gave written informed consent.
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Measures A fall was defined as “an unexpected contact of any part of the body with the ground.” Falls status was established by asking 2 questions: (1) Have you ever fallen? and (2) Have you fallen in the last 3 months? If participants responded yes to the second question, they were asked how many times they had fallen in the last 3 months. Participants were asked retrospectively about the number of falls in the 3 months before the baseline assessment. They then received the interventions for a 10-week period and were reassessed at week 12, during which they were asked about the number of falls in the 3 months before that assessment. At impairment level, lower limb sensation was evaluated using a simple verbal numerical rating scale, with 0 indicating no feeling at all and 10 indicating normal sensation. Three areas of the lower limb were tested bilaterally; thus a total of 60 indicated normal sensation. Proprioception was assessed by placing participants’ big toe in an “up” or “down” position and asking participants to identify where their toe was. It was scored as either normal or abnormal. At activities level, balance was assessed using the Berg Balance Scale (BBS), a 14-item clinical scale that evaluates balance in sitting and standing and rates performance from 0 (cannot perform) to 4 (normal performance). It has been demonstrated to have good reliability24 and validity25 for people with MS. Walking endurance was measured using the 6-minute walk test (6MWT). This measures walking distance over a 6-minute period and is a good predictor of habitual walking.26 Studies have suggested that it is valid27 and reliable28 for people with MS. Subjects were instructed to walk “as fast and as safely as possible.”29 At participation level, the Multiple Sclerosis Impact Scale-29 version 230 (MSIS-29v2) physical and psychological components were used. The impact of fatigue was measured using the Modified Fatigue Impact Scale31 (MFIS). The data from the baseline assessments in week 1 were used in this analysis.
Interventions Participants were randomly assigned to take part in group physiotherapy, one-to-one physiotherapy, or yoga. All interventions were for 1 hour per week for 10 weeks. The median number of sessions attended was 8, 9, and 8 for group physiotherapy, one-toone physiotherapy, and yoga, respectively. The group physiotherapy intervention focused on a standardized program of 6 exercises designed to target both balance and strength, and is outlined in the study protocol.23 One-to-one physiotherapy was at the discretion of the treating therapist, but data gathered from the treating therapists revealed that they also focused on exercises to improve balance and strength. Data from the yoga instructors suggested that they focused on relaxation exercises, meditation, breathing techniques, stretching, and maintaining different yogic postures and poses.
List of abbreviations: BBS GNDS MFIS MS MSIS-29v2 6MWT
Berg Balance Scale Guys Neurological Disability Rating Scale Modified Fatigue Impact Scale multiple sclerosis Multiple Sclerosis Impact Scale-29 version 2 6-minute walk test
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Analysis Data were coded and entered into an Excela spreadsheet and imported into SPSSb for analysis. Descriptive statistics were used to identify the prevalence of falls in the cohort. To assess any significant differences between fallers and nonfallers for the
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potential risk factors, independent t tests were used for continuous data that were normally distributed, Mann-Whitney U tests were performed on data that were abnormally distributed, and chisquare tests for independence were used for categorical data. Based on the existing literature for falls prediction, the hypothesis was that sex, age, time since diagnosis, lower limb sensation, proprioception, BBS score, GNDS score (disability), and 6MWT distance (mobility) would predict falling. Based on the finding that Multiple Sclerosis Impact Scale-29 version 2 (MSIS-29v2) and MFIS scores were greater for fallers, the impact of fatigue (MFIS) and impact of MS (MSIS-29v2 physical and psychological scores) were also added to the model. The dependent variable for the analysis was the number of falls in the last 3 months, coded as 0 for no falls or 1 for one or more falls. Given the dichotomous nature of the variable, a bivariate logistic regression was used. To ensure that multicollinearity was not an issue, variables with a Spearman correlation coefficient greater than 0.6 were omitted from the model. On this basis, the MSIS-29v2-psychological component was omitted because it was significantly correlated with both the MSIS-29v2-physical (.60, P<.001) and MFIS (.64, P<.001) variables. Model selection was performed on the final set of 10 potential covariates by using 3 different model selection methods: enter, backward conditional, and forward conditional. For all models, a P value of .05 was used for both entry into and remaining in the model. The models obtained from the 3 methods were then compared to assess whether there were discrepancies. To assess the effect of the intervention on the proportion of fallers (people who reported 1 or more falls in the last 3 months), the McNemar test was used to analyze the data. The Wilcoxon signed-rank test was used to analyze the difference in number of falls pre- and postintervention.
reporting more than 1 fall in the previous 3 months (nZ31) made up 27.9% of the total sample. The number of falls in the previous 3 months ranged from 1 to 18, with a mean of 3 falls per faller during that time. When considering only those participants with more than 1 fall, they had a mean of 4.5 falls each in the previous 3 months. Table 1 presents the differences between fallers and nonfallers for a number of symptoms and outcome measures. Fallers reported a significantly greater physical and psychological impact of MS and a significantly greater impact of fatigue. There was agreement in all 3 regression models in terms of the significant variables in the model. The forward and backward conditional models concurred and were significant (P<.001, c21Z11.762, nZ94), indicating the model was able to distinguish between fallers and nonfallers. The model as a whole explained between 11.8% (Cox & Snell r2) and 15.7% (Nagelkerke r2) of the variance in fall status, correctly classifying 68.1% of fallers. Only 1 variable made a unique, statistically significant contribution to the model. A higher MFIS score (PZ.002), indicating greater impact of fatigue, recorded an odds ratio of 1.048 (95% confidence interval, 1.018e1.079). The P value for the Hosmer and Lemeshow goodness-of-fit test suggested no evidence of lack of fit (PZ.400). Table 2 presents the number and percent of fallers and number of falls in each group before and after the interventions. There was a significant reduction in both the number of fallers and the number of falls after the group physiotherapy intervention.
Discussion The results indicate that 50.5% of participants reported a fall in the last 3 months. This suggests a similar prevalence to population studies in the United States that also found prevalences of 52% to 55%.1,3 Because our sample considered only those who use walking aids, and since walking aid use in itself has been found to be associated with falls in previous studies,2,5,14 this prevalence is somewhat lower than expected. It is possible that the shorter period in the falls question (3mo in this study as opposed to 6 or 12mo in previous studies) may account for this. We found that
Results Of the 111 participants assessed at baseline, 81.1% (nZ90) answered yes to the question “have you ever fallen,” and 50.5% (nZ56) reported 1 or more falls in the last 3 months. Those
Table 1
Differences between participants who reported a fall in the last 3 months and those who did not at baseline
Characteristic
Fallers (nZ56)
Nonfallers (nZ55)
Mean Difference (95% CI)
P
Age (y) Sex (M/F) GNDS mobility score 3/4 Time since diagnosis (y) LL sensation (normal/abnormal) Proprioception (normal/abnormal) MSIS-29v2ephysical MSIS-29v2epsychological BBS 6MWT distance (m) MFIS
55.610.4 17/38 33/23 16.65 27/25 34/20 549.5 19.5 (5.5)x 28.210 78 (41.5)x 46.714.1
54.711.1 23/32 33/21 14.13 31/23 37/15 50.310.8 15 (4)x 29.511 92.5 (49.5)x 3816.9
1.1 (5.1 to 2.9)
.586* .116y .858y .561* .452y .551y .048*{ .001z{ .879* .174z .002*{
3.9 (7.8 to 0.3) 4.5jj 1.2 (3.9 to 4.5) 14.5jj 9.4 (15.5 to 3.5)
NOTE. Values are mean SD, n, or as otherwise indicated. Abbreviations: CI, confidence interval; F, female; LL, lower limb; M, male. * Independent t tests. y c2 test for independence. z Mann-Whitney U test. x Median (interquartile range). jj Median difference. { Statistically significant.
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Falls in people with multiple sclerosis who use a walking aid Table 2
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Number of fallers and falls pre- and postintervention
Intervention
Fallers Preintervention
Fallers Postintervention
P*
Total No. of Falls Preintervention
Total No. of Falls Postintervention
Py
Group physiotherapy (nZ48) 1-to-1 Physiotherapy (nZ35) Yoga (nZ13) Control (nZ15)
28 16 7 5
11 9 3 2
.005* .118 .125 .375
63 61 25 14
25 21 8 2
.001z .088 .091 .131
(58.3) (45.7) (53.8) (33.3)
(22.9) (25.7) (23.1) (13.3)
NOTE. Values are n (%) or as otherwise indicated. * McNemar test. y Wilcoxon signed-rank test. z Statistically significant.
28% of the sample, which equates to 56% of fallers, reported more than 1 fall in the last 3 months; this is similar to other studies which reported that 45%15 of fallers reported multiple falls. These data confirm that falls are a significant problem for people with MS. The fall prevalence for this population (50%)2,3 is much greater than that for the aging population (15%),6 which has been the focus of a great deal of research to date. Given the increased risk of fracture for people with MS,8 it is essential that greater efforts are made to develop and evaluate falls prevention programs for this population. Of note is that fallers had a greater physical and psychological impact of MS, represented by significantly higher scores on both subsections of the MSIS-29v2. This finding provides further compelling evidence for the need to address this issue, to improve the quality of life for people with MS. Interestingly, the BBS scores were not different between fallers and nonfallers. This finding is in conflict with that of Cattaneo et al,12 who found a significant difference between fallers and nonfallers on this variable. While their mean BBS scores were 44 and 52, respectively, our population had much lower scores (28 and 29, respectively), and all used walking aids. It is possible that walking aid use in itself is the predictor of falls, and that other domains not measured in this study are more greatly associated with fall status for this more disabled subgroup of people with MS. These data also suggest that fallers had a greater impact of fatigue and that fatigue is the only significant predictor of falls status among the variables considered in this study. Previously, only Finlayson et al1 have considered fatigue as a variable and found a difference between fallers and nonfallers in self-reported fatigue, but fatigue did not remain in the final regression model of falls status. The variables in this analysis considered demographics (sex, age, time since diagnosis), impairments of body functions (proprioceptive deficit, sensory deficit), activity (balance, walking endurance), disability (GNDS mobility score), and participation (impact of MS and impact of fatigue) measures. Despite the fact that variables such as age,1,14 balance,2,4 walking aid use,2,14 and disability4,10 have been found to be significantly associated with fallers in other studies, the only variable to emerge as a unique and significant predictor of falls is the MFIS score. The data suggest that for every 10-point increase in MFIS score, there is a 10-fold increased likelihood of reporting a fall, and that 68% of fallers can be predicted by their MFIS score alone. This new finding suggests that fatigue management strategies may be an important element of falls prevention programs for people with MS who use walking aids. The cause or effect relationship between fatigue and falls requires further evaluation. Is a history of falls and activity curtailment because of a fear of falling contributing www.archives-pmr.org
to a lack of fitness and weakness caused by inactivity and hence contributing to fatigue impact? Or is the “peripheral” element of fatigue that affects muscle latencies and muscle endurance properties preventing normal balance responses and causing falls? These complex relationships require further investigation. These preliminary data from our exercise trial suggest that a 10-week group physiotherapy intervention consisting of exercises to improve balance and strength can significantly reduce both the proportion of fallers and the number of falls. This concurs with the findings of Cattaneo,19 who also found reductions in falls status after their balance interventions. Interestingly, and similar to the findings of Cattaneo,19 the control group also demonstrated a reduction (though nonsignificant in both studies) in falls. The simple act of asking about falls may have made the participants more aware that they were falling and led to a change in behavior as a result. Matsuda et al15 found that only 50% of fallers talked to a health care professional about falls. It may be important, therefore, to educate health care professionals about the need to ask about falls in people with MS. After a comprehensive search of the literature, only 2 studies that considered the number of falls as an outcome for people with MS were found. This is in contrast to the 111 studies included in a Cochrane review of falls interventions in the elderly population, whose falls prevalence is far less than that for persons with MS. Studies with the primary aim of falls prevention for people with MS, and with larger sample sizes and matched control groups are urgently required.
Study limitations Our data were obtained from people who volunteered for a clinical trial of exercise interventions, rather than from a population study, as is the case in the aforementioned studies. It is therefore possible that our relatively small sample is biased toward those more predisposed to exercise, possibly excluding those with significant activity curtailment because of falls. Additionally, falls status was collected using retrospective methods relying on patient recall over a 3-month period rather than the more common 6-month time interval. Prospective, diary-based methods with a minimum of monthly reporting as recommended by the PROFANE network32 are recommended for future studies. Furthermore, we did not consider all the factors that have been associated with fall statusdthere was no measure of strength, spasticity, or of fear of falling, which may be important. Nonetheless, the MFIS score alone correctly identified 68% of fallers. While group intervention reduced the number of falls and fallers, it must be noted that our yoga and control groups had
620 low numbers because some participants were not treated as randomized. Participants expressed a need for “physiotherapy” and refused to be in the yoga or control groups. They were subsequently randomly assigned to either group or one-to-one physiotherapy. This introduces selection bias to the study, and it is therefore important that this finding be confirmed by a larger study with a matched control group. Additionally, a longer follow-up of the effect of intervention on falls status is required.
Conclusions Data from this study confirm the high prevalence of falls among people with MS. Fallers report a significantly greater impact of MS on their lives than nonfallers, reinforcing the importance of addressing this complex issue. When considering the factors associated with falls status, the impact of fatigue (MFIS score) was the only variable in the final model correctly classifying 68% of fallers. The odds ratios suggest that for every 10-point increase in the MFIS score, there is a 10-fold increase in the likelihood of reporting a fall for this population of people with MS who have significant disability and use bilateral assistance to walk. The relationship between fatigue and falls status warrants further investigation. Preliminary data suggest that a group physiotherapy intervention consisting of a 10-week balance and strengthening exercise program can significantly reduce the number of fallers and falls. This finding needs to be confirmed in studies with a larger sample size powered to detect a reduction in falls, and with a matched control group. There is an urgent need for intervention trials that have the primary aim of reducing falls, falls risk, and the transition to becoming a faller. To appropriately design and evaluate programs, it is essential that we fully understand the relationships between the many factors that contribute to falls. To do this, prospective studies incorporating a wide range of measures are required. Interventions should then be developed based on those key factors and using the perspectives of people with MS, clinicians, and health care providers.
Suppliers a. Microsoft Excel; Microsoft, One Microsoft Way, Redmond, WA 98052. b. SPSS Inc, 233 S Wacker Dr, 11th Fl, Chicago, IL 60606.
Keywords Accidental falls; Clinical trial; Multiple sclerosis; Prevalence; Rehabilitation
Corresponding author Susan Coote, PhD, Health Sciences Bldg, University of Limerick, Castletroy, Limerick, Ireland. E-mail address: [email protected].
Acknowledgments We thank the Multiple Sclerosis Society of Ireland for their support in recruiting subjects for the study.
S. Coote et al
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621 28. Paltamaa J, West H, Sarasoja T, Wikstro¨m J, Ma¨lkia¨ E. Reliability of physical functioning measures in ambulatory subjects with MS. Physiother Res Int 2005;10:93-109. 29. Fry DK, Pfalzer LA. Reliability of four functional tests and rating of perceived exertion in persons with multiple sclerosis. Physiother Can 2006;58:212-20. 30. Hobart J, Cano S. Improving the evaluation of therapeutic interventions in multiple sclerosis: the role of new psychometric methods. Health Technol Assess 2009;13(12):1-200. 31. Fisk JD, Ritvo PG, Ross L, Haase DA, Marrie TJ, Schlech WF. Measuring the functional impact of fatigue: initial validation of the Fatigue Impact Scale. Clin Infect Dis 1994;18(Suppl 1): S79-83. 32. Lamb SE, Jorstad-Stein EC, Hauer K, Becker C. Development of a common outcome data set for fall injury prevention trials: the Prevention of Falls Network Europe consensus. J Am Geriatr Soc 2005;53:1618-22.
ORIGINAL ARTICLE
Falls in People With Multiple Sclerosis Who Use a Walking Aid: Prevalence, Factors, and Effect of Strength and Balance Interventions Susan Coote, PhD, Neasa Hogan, PhD, Sue Franklin, PhD From the Department of Clinical Therapies & Centre for Physical Activity and Health Research, University of Limerick, Limerick, Ireland.
Abstract Objectives: To investigate falls prevalence, factors associated with falling, and the effects of balance and strengthening interventions on falls in persons with multiple sclerosis (MS). Design: Baseline and posttreatment data from a randomized controlled trial. Setting: Community. Participants: People with MS (NZ111) who use bilateral support for gait. Interventions: Group and one-on-one physiotherapy. Main Outcome Measures: Falls prevalence was assessed using retrospective recall. Demographic information was collected, impairments of body function were assessed, and results from the Berg Balance Scale, 6-minute walk test (6MWT), Multiple Sclerosis Impact Scale-29 version 2 physical and psychological scores, and the Modified Fatigue Impact Scale (MFIS) were obtained. Results: The prevalence of falls in a 3-month period was 50.5% among participants with MS, of whom 28% had more than 1 fall. Fallers had a greater physical (mean difference, 3.9; PZ.048) and psychological (median difference, 4.5; PZ.001) impact of MS and a greater impact of fatigue (mean difference, 9.4; PZ.002). A logistic regression analysis found that the MFIS score made a unique, significant contribution to the model (odds ratioZ1.04; 95% confidence interval, 1.018e1.079), correctly identifying 68% of fallers. A 10-week group physiotherapy intervention significantly reduced both the number of fallers (58.3% before to 22.9% after intervention, PZ.005) and the number of falls (63 before to 25 after intervention, PZ.001). Conclusions: The prevalence of falls is high in this population of persons with MS, and the impact of MS and of fatigue is greater in fallers. Development and evaluation of interventions to reduce falls risk and the transition to faller or multiple faller status are required. Archives of Physical Medicine and Rehabilitation 2013;94:616-21 ª 2013 by the American Congress of Rehabilitation Medicine
Falls are a significant problem for both the person who falls and the health care system. At a personal level, falls can lead to pain, injury, or fracture. This can lead to increased reliance on others for assistance, fear of falling, and activity curtailment. At a societal level, the medical costs of falls and fractures are great, as are the costs incurred because of loss of income and increased care needs. For people with multiple sclerosis (MS), the prevalence of falls is estimated to be between 52% and 55% in retrospective Presented to the European Committee for Treatment and Research in Multiple Sclerosis, October 13–16, 2010, Gothenburg, Sweden. Supported by Multiple Sclerosis Ireland through the Getting the Balance Right Project. 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. Clinical Trial Registration Number: ISRCTN77610415.
studies1-3 considering self-reported falls in the last 2 to 12 months. Prospective reports suggest similar proportions, with between 48%4 and 63%5 of people falling. This is significantly greater than the prevalence in elderly populations where a large epidemiologic6 study suggested that 15.9% of elderly people fell in a 3-month period. In addition to a higher incidence of falling, people with MS have an increased fracture risk because of a reduction in bone mineral density as a result of decreased mobility, vitamin D deficiency, and the use of glucocorticoids and antidepressants.7 Recent studies in the United Kingdom8 and the Netherlands9 found that the risk of hip fracture in people with MS was higher than in the general population, and that people with MS with a history of falling had double the risk of osteoporotic fracture.8 The incidence of falls was significantly greater in people with
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Falls in people with multiple sclerosis who use a walking aid MS10 than in healthy controls, even in those in the early course of MS. The risk of an injurious fall was 3 times higher for women veterans with MS than for women veterans without MS after controlling for age and number of clinic visits.11 Several studies have investigated the factors relating to falls in people with MS. The factors that are most common are deficits of balance (7 studies),1,2,4,12-15 walking aid use and lower mobility status (6 studies2,5,12,14,16,17), and a higher Expanded Disability Status Score (6 studies4,5,10,13,14,17). Other authors have found that impairments of muscle tone and proprioception,5 continence,1 brainstem and middle cerebellar peduncal lesions,13 and increasing numbers of symptoms16 are associated with falls. Fear of falling and activity curtailment,18 and cognitive deficits17 are also associated with falls in people with MS. There are a variety of symptoms that predict falling. The fact that these symptoms can occur in various combinations highlights the complexity of this problem and its management. Despite the increased prevalence of falls and related injuries, and the ever-increasing body of work to investigate the factors associated with falls in people with MS, there are very few studies with the aim of reducing fall risk or that evaluate falls as an outcome. Although several studies19-21 have reported positive outcomes on balance, only 2 studies were found that have considered number of falls as an outcome. Cattaneo et al19 evaluated balance programs based on sensory and motor strategies, and motor strategies alone and found a significant difference between groups in the number of falls that was not present preintervention. Esnouf et al22 found that those people using a drop-foot stimulator had significantly fewer falls than those participating in an exercise program focusing on core stability. While both studies suggest positive outcomes on number of falls, the small number of studies highlights the need for development and evaluation of interventions to reduce both fall risk and the number of falls. The aim of this article is to present the falls data for a cohort of people with MS who were assessed as part of a randomized controlled trial of interventions for people with MS who use bilateral assistance to walk outdoors. The article presents data on falls prevalence over a 3-month period before intervention, the factors associated with falls, and the effect of 2 physiotherapy interventions and yoga on number of fallers and number of falls in the sample.
Methods These data were part of the baseline assessments of 1 arm of an exercise trial, the methods of which have been published previously.23 Participants were stratified according to their mobility, and these data include people with MS who scored 3 or 4 on the Guys Neurological Disability Rating Scale (GNDS) mobility section (indicating use of bilateral aids for gait and/or occasional wheelchair use for longer distances). Ethical approval was obtained for all the testing sites, and patients gave written informed consent.
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Measures A fall was defined as “an unexpected contact of any part of the body with the ground.” Falls status was established by asking 2 questions: (1) Have you ever fallen? and (2) Have you fallen in the last 3 months? If participants responded yes to the second question, they were asked how many times they had fallen in the last 3 months. Participants were asked retrospectively about the number of falls in the 3 months before the baseline assessment. They then received the interventions for a 10-week period and were reassessed at week 12, during which they were asked about the number of falls in the 3 months before that assessment. At impairment level, lower limb sensation was evaluated using a simple verbal numerical rating scale, with 0 indicating no feeling at all and 10 indicating normal sensation. Three areas of the lower limb were tested bilaterally; thus a total of 60 indicated normal sensation. Proprioception was assessed by placing participants’ big toe in an “up” or “down” position and asking participants to identify where their toe was. It was scored as either normal or abnormal. At activities level, balance was assessed using the Berg Balance Scale (BBS), a 14-item clinical scale that evaluates balance in sitting and standing and rates performance from 0 (cannot perform) to 4 (normal performance). It has been demonstrated to have good reliability24 and validity25 for people with MS. Walking endurance was measured using the 6-minute walk test (6MWT). This measures walking distance over a 6-minute period and is a good predictor of habitual walking.26 Studies have suggested that it is valid27 and reliable28 for people with MS. Subjects were instructed to walk “as fast and as safely as possible.”29 At participation level, the Multiple Sclerosis Impact Scale-29 version 230 (MSIS-29v2) physical and psychological components were used. The impact of fatigue was measured using the Modified Fatigue Impact Scale31 (MFIS). The data from the baseline assessments in week 1 were used in this analysis.
Interventions Participants were randomly assigned to take part in group physiotherapy, one-to-one physiotherapy, or yoga. All interventions were for 1 hour per week for 10 weeks. The median number of sessions attended was 8, 9, and 8 for group physiotherapy, one-toone physiotherapy, and yoga, respectively. The group physiotherapy intervention focused on a standardized program of 6 exercises designed to target both balance and strength, and is outlined in the study protocol.23 One-to-one physiotherapy was at the discretion of the treating therapist, but data gathered from the treating therapists revealed that they also focused on exercises to improve balance and strength. Data from the yoga instructors suggested that they focused on relaxation exercises, meditation, breathing techniques, stretching, and maintaining different yogic postures and poses.
List of abbreviations: BBS GNDS MFIS MS MSIS-29v2 6MWT
Berg Balance Scale Guys Neurological Disability Rating Scale Modified Fatigue Impact Scale multiple sclerosis Multiple Sclerosis Impact Scale-29 version 2 6-minute walk test
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Analysis Data were coded and entered into an Excela spreadsheet and imported into SPSSb for analysis. Descriptive statistics were used to identify the prevalence of falls in the cohort. To assess any significant differences between fallers and nonfallers for the
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potential risk factors, independent t tests were used for continuous data that were normally distributed, Mann-Whitney U tests were performed on data that were abnormally distributed, and chisquare tests for independence were used for categorical data. Based on the existing literature for falls prediction, the hypothesis was that sex, age, time since diagnosis, lower limb sensation, proprioception, BBS score, GNDS score (disability), and 6MWT distance (mobility) would predict falling. Based on the finding that Multiple Sclerosis Impact Scale-29 version 2 (MSIS-29v2) and MFIS scores were greater for fallers, the impact of fatigue (MFIS) and impact of MS (MSIS-29v2 physical and psychological scores) were also added to the model. The dependent variable for the analysis was the number of falls in the last 3 months, coded as 0 for no falls or 1 for one or more falls. Given the dichotomous nature of the variable, a bivariate logistic regression was used. To ensure that multicollinearity was not an issue, variables with a Spearman correlation coefficient greater than 0.6 were omitted from the model. On this basis, the MSIS-29v2-psychological component was omitted because it was significantly correlated with both the MSIS-29v2-physical (.60, P<.001) and MFIS (.64, P<.001) variables. Model selection was performed on the final set of 10 potential covariates by using 3 different model selection methods: enter, backward conditional, and forward conditional. For all models, a P value of .05 was used for both entry into and remaining in the model. The models obtained from the 3 methods were then compared to assess whether there were discrepancies. To assess the effect of the intervention on the proportion of fallers (people who reported 1 or more falls in the last 3 months), the McNemar test was used to analyze the data. The Wilcoxon signed-rank test was used to analyze the difference in number of falls pre- and postintervention.
reporting more than 1 fall in the previous 3 months (nZ31) made up 27.9% of the total sample. The number of falls in the previous 3 months ranged from 1 to 18, with a mean of 3 falls per faller during that time. When considering only those participants with more than 1 fall, they had a mean of 4.5 falls each in the previous 3 months. Table 1 presents the differences between fallers and nonfallers for a number of symptoms and outcome measures. Fallers reported a significantly greater physical and psychological impact of MS and a significantly greater impact of fatigue. There was agreement in all 3 regression models in terms of the significant variables in the model. The forward and backward conditional models concurred and were significant (P<.001, c21Z11.762, nZ94), indicating the model was able to distinguish between fallers and nonfallers. The model as a whole explained between 11.8% (Cox & Snell r2) and 15.7% (Nagelkerke r2) of the variance in fall status, correctly classifying 68.1% of fallers. Only 1 variable made a unique, statistically significant contribution to the model. A higher MFIS score (PZ.002), indicating greater impact of fatigue, recorded an odds ratio of 1.048 (95% confidence interval, 1.018e1.079). The P value for the Hosmer and Lemeshow goodness-of-fit test suggested no evidence of lack of fit (PZ.400). Table 2 presents the number and percent of fallers and number of falls in each group before and after the interventions. There was a significant reduction in both the number of fallers and the number of falls after the group physiotherapy intervention.
Discussion The results indicate that 50.5% of participants reported a fall in the last 3 months. This suggests a similar prevalence to population studies in the United States that also found prevalences of 52% to 55%.1,3 Because our sample considered only those who use walking aids, and since walking aid use in itself has been found to be associated with falls in previous studies,2,5,14 this prevalence is somewhat lower than expected. It is possible that the shorter period in the falls question (3mo in this study as opposed to 6 or 12mo in previous studies) may account for this. We found that
Results Of the 111 participants assessed at baseline, 81.1% (nZ90) answered yes to the question “have you ever fallen,” and 50.5% (nZ56) reported 1 or more falls in the last 3 months. Those
Table 1
Differences between participants who reported a fall in the last 3 months and those who did not at baseline
Characteristic
Fallers (nZ56)
Nonfallers (nZ55)
Mean Difference (95% CI)
P
Age (y) Sex (M/F) GNDS mobility score 3/4 Time since diagnosis (y) LL sensation (normal/abnormal) Proprioception (normal/abnormal) MSIS-29v2ephysical MSIS-29v2epsychological BBS 6MWT distance (m) MFIS
55.610.4 17/38 33/23 16.65 27/25 34/20 549.5 19.5 (5.5)x 28.210 78 (41.5)x 46.714.1
54.711.1 23/32 33/21 14.13 31/23 37/15 50.310.8 15 (4)x 29.511 92.5 (49.5)x 3816.9
1.1 (5.1 to 2.9)
.586* .116y .858y .561* .452y .551y .048*{ .001z{ .879* .174z .002*{
3.9 (7.8 to 0.3) 4.5jj 1.2 (3.9 to 4.5) 14.5jj 9.4 (15.5 to 3.5)
NOTE. Values are mean SD, n, or as otherwise indicated. Abbreviations: CI, confidence interval; F, female; LL, lower limb; M, male. * Independent t tests. y c2 test for independence. z Mann-Whitney U test. x Median (interquartile range). jj Median difference. { Statistically significant.
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Falls in people with multiple sclerosis who use a walking aid Table 2
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Number of fallers and falls pre- and postintervention
Intervention
Fallers Preintervention
Fallers Postintervention
P*
Total No. of Falls Preintervention
Total No. of Falls Postintervention
Py
Group physiotherapy (nZ48) 1-to-1 Physiotherapy (nZ35) Yoga (nZ13) Control (nZ15)
28 16 7 5
11 9 3 2
.005* .118 .125 .375
63 61 25 14
25 21 8 2
.001z .088 .091 .131
(58.3) (45.7) (53.8) (33.3)
(22.9) (25.7) (23.1) (13.3)
NOTE. Values are n (%) or as otherwise indicated. * McNemar test. y Wilcoxon signed-rank test. z Statistically significant.
28% of the sample, which equates to 56% of fallers, reported more than 1 fall in the last 3 months; this is similar to other studies which reported that 45%15 of fallers reported multiple falls. These data confirm that falls are a significant problem for people with MS. The fall prevalence for this population (50%)2,3 is much greater than that for the aging population (15%),6 which has been the focus of a great deal of research to date. Given the increased risk of fracture for people with MS,8 it is essential that greater efforts are made to develop and evaluate falls prevention programs for this population. Of note is that fallers had a greater physical and psychological impact of MS, represented by significantly higher scores on both subsections of the MSIS-29v2. This finding provides further compelling evidence for the need to address this issue, to improve the quality of life for people with MS. Interestingly, the BBS scores were not different between fallers and nonfallers. This finding is in conflict with that of Cattaneo et al,12 who found a significant difference between fallers and nonfallers on this variable. While their mean BBS scores were 44 and 52, respectively, our population had much lower scores (28 and 29, respectively), and all used walking aids. It is possible that walking aid use in itself is the predictor of falls, and that other domains not measured in this study are more greatly associated with fall status for this more disabled subgroup of people with MS. These data also suggest that fallers had a greater impact of fatigue and that fatigue is the only significant predictor of falls status among the variables considered in this study. Previously, only Finlayson et al1 have considered fatigue as a variable and found a difference between fallers and nonfallers in self-reported fatigue, but fatigue did not remain in the final regression model of falls status. The variables in this analysis considered demographics (sex, age, time since diagnosis), impairments of body functions (proprioceptive deficit, sensory deficit), activity (balance, walking endurance), disability (GNDS mobility score), and participation (impact of MS and impact of fatigue) measures. Despite the fact that variables such as age,1,14 balance,2,4 walking aid use,2,14 and disability4,10 have been found to be significantly associated with fallers in other studies, the only variable to emerge as a unique and significant predictor of falls is the MFIS score. The data suggest that for every 10-point increase in MFIS score, there is a 10-fold increased likelihood of reporting a fall, and that 68% of fallers can be predicted by their MFIS score alone. This new finding suggests that fatigue management strategies may be an important element of falls prevention programs for people with MS who use walking aids. The cause or effect relationship between fatigue and falls requires further evaluation. Is a history of falls and activity curtailment because of a fear of falling contributing www.archives-pmr.org
to a lack of fitness and weakness caused by inactivity and hence contributing to fatigue impact? Or is the “peripheral” element of fatigue that affects muscle latencies and muscle endurance properties preventing normal balance responses and causing falls? These complex relationships require further investigation. These preliminary data from our exercise trial suggest that a 10-week group physiotherapy intervention consisting of exercises to improve balance and strength can significantly reduce both the proportion of fallers and the number of falls. This concurs with the findings of Cattaneo,19 who also found reductions in falls status after their balance interventions. Interestingly, and similar to the findings of Cattaneo,19 the control group also demonstrated a reduction (though nonsignificant in both studies) in falls. The simple act of asking about falls may have made the participants more aware that they were falling and led to a change in behavior as a result. Matsuda et al15 found that only 50% of fallers talked to a health care professional about falls. It may be important, therefore, to educate health care professionals about the need to ask about falls in people with MS. After a comprehensive search of the literature, only 2 studies that considered the number of falls as an outcome for people with MS were found. This is in contrast to the 111 studies included in a Cochrane review of falls interventions in the elderly population, whose falls prevalence is far less than that for persons with MS. Studies with the primary aim of falls prevention for people with MS, and with larger sample sizes and matched control groups are urgently required.
Study limitations Our data were obtained from people who volunteered for a clinical trial of exercise interventions, rather than from a population study, as is the case in the aforementioned studies. It is therefore possible that our relatively small sample is biased toward those more predisposed to exercise, possibly excluding those with significant activity curtailment because of falls. Additionally, falls status was collected using retrospective methods relying on patient recall over a 3-month period rather than the more common 6-month time interval. Prospective, diary-based methods with a minimum of monthly reporting as recommended by the PROFANE network32 are recommended for future studies. Furthermore, we did not consider all the factors that have been associated with fall statusdthere was no measure of strength, spasticity, or of fear of falling, which may be important. Nonetheless, the MFIS score alone correctly identified 68% of fallers. While group intervention reduced the number of falls and fallers, it must be noted that our yoga and control groups had
620 low numbers because some participants were not treated as randomized. Participants expressed a need for “physiotherapy” and refused to be in the yoga or control groups. They were subsequently randomly assigned to either group or one-to-one physiotherapy. This introduces selection bias to the study, and it is therefore important that this finding be confirmed by a larger study with a matched control group. Additionally, a longer follow-up of the effect of intervention on falls status is required.
Conclusions Data from this study confirm the high prevalence of falls among people with MS. Fallers report a significantly greater impact of MS on their lives than nonfallers, reinforcing the importance of addressing this complex issue. When considering the factors associated with falls status, the impact of fatigue (MFIS score) was the only variable in the final model correctly classifying 68% of fallers. The odds ratios suggest that for every 10-point increase in the MFIS score, there is a 10-fold increase in the likelihood of reporting a fall for this population of people with MS who have significant disability and use bilateral assistance to walk. The relationship between fatigue and falls status warrants further investigation. Preliminary data suggest that a group physiotherapy intervention consisting of a 10-week balance and strengthening exercise program can significantly reduce the number of fallers and falls. This finding needs to be confirmed in studies with a larger sample size powered to detect a reduction in falls, and with a matched control group. There is an urgent need for intervention trials that have the primary aim of reducing falls, falls risk, and the transition to becoming a faller. To appropriately design and evaluate programs, it is essential that we fully understand the relationships between the many factors that contribute to falls. To do this, prospective studies incorporating a wide range of measures are required. Interventions should then be developed based on those key factors and using the perspectives of people with MS, clinicians, and health care providers.
Suppliers a. Microsoft Excel; Microsoft, One Microsoft Way, Redmond, WA 98052. b. SPSS Inc, 233 S Wacker Dr, 11th Fl, Chicago, IL 60606.
Keywords Accidental falls; Clinical trial; Multiple sclerosis; Prevalence; Rehabilitation
Corresponding author Susan Coote, PhD, Health Sciences Bldg, University of Limerick, Castletroy, Limerick, Ireland. E-mail address: [email protected].
Acknowledgments We thank the Multiple Sclerosis Society of Ireland for their support in recruiting subjects for the study.
S. Coote et al
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