Modified Functional Walking Categories and participation in people with multiple sclerosis

Multiple Sclerosis and Related Disorders 26 (2018) 11–18

Contents lists available at ScienceDirect

Multiple Sclerosis and Related Disorders journal homepage: www.elsevier.com/locate/msard

Modified Functional Walking Categories and participation in people with multiple sclerosis

T

⁎

Rita Bertonia, , Johanna Jonsdottira, Peter Feysb, Ilse Lamersb, Davide Cattaneoa a b

IRCCS Fondazione Don Carlo Gnocchi, Italy REVAL Rehabilitation Research Center, Hasselt University, Diepenbeek, Belgium

A R T I C LE I N FO

A B S T R A C T

Keywords: Multiple sclerosis Walking Community integration Participation Walking aid Gait speed

Background: Gait velocity influences the ability of a person to move in different outdoor or indoor contexts and has accordingly been classified through the Modified Functional Walking Categories (MFWC). Community ambulation in persons with multiple sclerosis (PwMS) may give information on their social and productive participation, as well as independence in household activities. Objectives: To investigate factors associated with walking and mobility restrictions as classified by the Modified Functional Walking Categories (MFWC) and analyze the influence of disease characteristics, demographical and walking factors on participation in PwMS. Methods: 155 PwMS attending two rehabilitation center were evaluated. Community ambulation was classified with the MFWC; participation was measured with the Community Integration Questionnaire (CIQ). MFWC and statistically significant variables associated with CIQ score were entered in a multivariate logistic model to assess the multiple relationships. Results: PwMS with a secondary progressive type of disease, longer disease duration and using walking aids were classified in the worse MFWC. Participation restrictions were more frequent in Limited Household (72.3%) and in Physiological Walkers (93.7%). The final multivariate model (p < 0.0001) showed that the use of a walking aid (OR = 2.59), being male (OR = 2.94) and older (OR = 1.06) increased the likelihood of having participation restrictions. The same variables predicted home participation; MFWC and age predicted productive participation while only age influenced social participation. Conclusions: Modified Functional Walking Categories were associated with type of disease, disease duration, disability level and type of walking aid. The best clinical predictor of participation restriction was walking aid while walking categories only predicted productive participation.

1. Introduction Community ambulation has been defined as locomotion outdoors encompassing activities such as visits to the supermarket, shopping mall and bank, leisure activities, (Lord et al., 2004) all activities that are important for independence in daily life. Reduction in mobility for persons with Multiple Sclerosis (PwMS) can profoundly impact on independence and community integration (Kister et al., 2013; LaRocca, 2011). Various studies have reported on how walking impairments in PwMS lead to a reduced ability to participate in community activities, including home-based activities, social activities, and work (Cattaneo et al., 2017; Kierkegaard et al., 2012). Participation, as involvement in life situations or community integration, is a complex construct composed of several dimensions

⁎

influenced by personal and environmental factors, health conditions, body function and activities (World Health Organization, 2001). The Community Integration Questionnaire (CIQ) (Willer et al., 1994) was found to be a valid and reliable instrument, able to detect changes at participation level in a cohort of PwMS (Negahban et al., 2013; Taheri et al., 2016). There are indications that symptoms related to cognition and mobility may impact on community participation as measured by CIQ (Cattaneo et al., 2017; Hughes et al., 2015; Kratz et al., 2016; Cameron et al., 2014). Walking has already been stated as a factor influencing participation in PwMS (Cattaneo et al., 2017). Kwiatkowski et al. (2014) reported moderate to strong correlations of social participation with disability status as measured by the Expanded Disability Status Score (EDSS); Kierkegaard et al. (2012) similarly noted that walking speed

Corresponding author at: Don C. Gnocchi Foundation, Via Capecelatro 66, Milan 20148, Italy. E-mail address: [email protected] (R. Bertoni).

https://doi.org/10.1016/j.msard.2018.08.031 Received 27 April 2018; Received in revised form 27 August 2018; Accepted 30 August 2018 2211-0348/ © 2018 Elsevier B.V. All rights reserved.

Multiple Sclerosis and Related Disorders 26 (2018) 11–18

R. Bertoni et al.

1) 2) 3) 4) 5)

was a good predictor of activity/participation. Paltamaa et al. (2008) in a cohort of PwMS identified gait velocity and domestic life participation as the most responsive measures to deterioration due to MS. Categorization of community walking performance according to walking speed and self reported ability to move in different environments has been explored in MS in order to go beyond the description of symptoms and disability when describing participation (Feys et al., 2014). Perry et al. (1995) exploring walking speed and self reported ability to move in different environments classified walking capacity in six functional walking categories, the Modified Walking Functional Categories (MFWC). A successive study by Kempen et al. (2011) further defined the gait speed thresholds for each category of the MFWC in a cohort of PwMS at the time of definite diagnosis. To date the relationship with categorization of functional community ambulation or the effect of the use of a walking aid with respect to participation has not been explored. Community ambulation is supposed to be bound to participation but at present no studies have examined the relationship between MFWC and a measure of participation in PwMS. The first aim of the present study was to investigate factors associated with walking and mobility restrictions as classified by the Modified Functional Walking Categories; the second aim was to analyze the influence of functional walking category, use of a walking aid and EDSS on community participation in a convenient sample of PwMS attending a rehabilitation center. We hypothesized that MFWC would be a better predictor of participation restrictions than the use of a walking aid or disability level as classified by EDSS.

Unlimited/Least-limited community walker (≥1.35 m/s) Most-Limited community walker (<1.35 m/s) Unlimited household walker (<1.04 m/s) Limited household walker (<0.48 m/s) Physiological Walker and non ambulant PwMS (<0.10 m/s)

Physiological walkers were all wheelchair bound people unable to walk with aid or that had a gait velocity lower than 0.10 m/s. The examinations were performed by experienced physiotherapists. To ensure standardization between centers, an instruction booklet was created and practice sessions were held to minimize the differences between the assessors. 2.1. Data analysis To ensure a sufficient sample size for statistical analysis, Leastlimited and Unlimited community walkers categories were collapsed in one, hereafter named Unlimited Community walkers. Likewise MS type was analyzed as progressive or non-progressive, due to the insufficient primary progressive sample size. Box-plot analysis was used to detect outliers, then between categories differences for demographical and clinical characteristics were calculated using Kruskal-Wallis (K-W) test or Chi square (χ2) test when appropriate; post-hoc tests (Bonferroni correction) were applied to investigate differences between categories. On the basis of published total CIQ cut-off scores subjects were then divided into having (≤17 points) or not having (>17 points) participation restrictions (Cattaneo et al., 2017). Further, for each subscale the relative cut off score was used (Cattaneo et al., 2017). Univariate logistic models were used to assess associations between being restricted or not restricted in participation according to the CIQ total score and clinical variables, MFWC, walking aid and EDSS. According to the Hosmer and Lemershow approach for two-step modeling (Hosmer and Lemeshow, 2000) statistically significant variables (p < 0.05) associated with the CIQ score were entered in a multivariate logistic regression analysis to identify factors predicting the having or not having participation restrictions with a stepwise approach and the resultant significant factors were then entered in a final reduced predictive logistic model. The same procedure was used for the three CIQ subscales. Models were checked for distribution of residuals and presence of influential points.

2. Material and methods One hundred and sixty PwMS were screened among people attending two different rehabilitation centres in Milan, IRCCS Fondazione Don Carlo Gnocchi (Italy) and Hasselt, REVAL Rehabilitation Research Institute (Belgium) for rehabilitation or routine medical examinations. Inclusion criteria were confirmed MS diagnosis and age ≥18 years; people with cognitive impairment leading to inability to follow testing instructions or having other neurological or orthopaedic co-morbidities that could interfere with the execution of the assessment protocol were excluded. All participants received full information about the study and signed an informed consent form; the study was approved by the local ethics committee. For each participant age, gender, EDSS, disease duration, type of MS and employment status were registered. All data were collected at the same occasion for each participants. The Community Integration Questionnaire (CIQ) (Willer et al., 1994) inquires on participation in three different domains: home, social and productive activities. For each domain maximum scores are, respectively, 10 (home); 12 (social) and 7 (productive) points while maximum total score of 29 points is indicative of a good level of participation. Scores for each item are based on self-reported independency or frequency of the community activity inquired upon. The following cut off scores differentiating between normal and abnormal CIQ scores have been established for a sample of healthy subjects: 17 out of 29 points for Total participation score; 3 out of 10, 8 out of 12 and 2 points out of 7 respectively for Home, Social and Productive participation subscores. (Cattaneo et al., 2017) Walking speed for ambulant PwMS was measured with the Timed 25 Foot Walk (T25FW) (Fischer et al., 1999). Subjects were asked to walk twice at fast but safe walking speed, and mean velocity of the two trials in m/s was calculated. Usual walking aid was permitted during the T25FW and recorded for further analyses. Mean velocity for PwMS unable to walk even with aid for 25 ft was recorded as 0 m/s. Subjects' mean velocity was used to categorize the whole sample in 5 categories based on the Modified Functional Walking Categories provided by Kempen et al. (2011) for PwMS to assess the influence of walking speed on participation:

3. Results Preliminary statistical analysis revealed that out of the 155 PwMS matching inclusion criteria six were outliers and were thus excluded from the analyses. Demographic (age, gender, EDSS, type of MS and disease duration) and clinical characteristics for the whole sample and MFWC are reported in Table 1. Comparisons among MFWCs are reported in Table 2. We found an overall statistically significant age difference between MFWCs. Post hoc analysis revealed differences only for Physiological walkers compared to Unlimited Community category, with the Physiological walkers being older. EDSS scores increased through walking categories, presenting statistical differences among all groups except between Unlimited Household and Most-Limited Community categories where EDSS values tend to overlap. Statistical differences were found between MFWCs also in disease duration; at post-hoc analysis, Physiological walkers had a longer disease duration compared to Most-Limited and Unlimited Community categories; also Unlimited Household showed a longer disease duration with respect to Unlimited Community categories. Proportion of PwMS with RR and progressive type of MS varied according to MFWC. At post hoc analysis there were statistically significant differences between all groups except between Most-Limited Community and Household categories and between Limited Household 12

Multiple Sclerosis and Related Disorders 26 (2018) 11–18

R. Bertoni et al.

Table 1 Demographical and clinical characteristics of the whole sample and for each Modified Functional Walking Category.

Gender, n (F/M) Age, mean ± SD (years) EDSS, median (IQR) Type of MS n (%) RR PP SP Disease duration, mean ± SD (years) Walking aid, n (%) None Unilateral Bilateral Wheelchair CIQ Total, median (IQR) Home, median (IQR) Social, median (IQR) Productive, median (IQR)

Total

MFWC

N = 149

Unlimited Community n = 20 (13%)

M-Limited Community n = 25 (17%)

Unlimited Household n = 33 (22%)

Limited Household n = 39 (26%)

Physiological walkers n = 32 (22%)

94/55 52.8 ± 11 6.5 (5.5/6.5)

13/7 46.8 ± 9.7 3.5 (3.0/4.75)

14/11 50.0 ± 10 5.0 (4.5/6)

22/11 53.1 ± 10 6.0 (5.5/6.5)

29/10 54.9 ± 10.4 6.5 (6.5/6.5)

16/16 55.9 ± 12.7 7.75 (7.5/8)

63 21 65 17.3 ± 10.4

17 (27) 1 (5) 2 (3) 10.4 ± 8.0

11 (18) 5 (24) 9 (14) 13.0 ± 9.2

19 (30) 3 (14) 11 (17) 18.2 ± 8.9

12 (19) 7 (33) 20 (31) 18.0 ± 9.6

4 (6) 5 (24) 23 (35) 23.1 ± 11.5

50 22 45 32 14 (11/19) 4 (2/6) 7 (5/9) 2 (1/5)

19 (38) 1 (5) 0 (0) 0 (0) 17.5 (15/20.5) 6 (4.5/7.5) 8 (6/10) 4.5 (2/6)

16 (32) 7 (32) 2 (5) 0 (0) 14 (12/19) 5 (4/6) 7 (6/8) 2 (2/6)

13 (26) 9 (41) 11 (24) 0 (0) 18 (14/21) 5 (3/7) 8 (7/10) 5 (2/6)

2 (4) 5 (23) 32 (71) 0 (0) 12 (8/16) 4 (1/5) 7 (5/9) 2 (1/2)

0 (0) 0 (0) 0 (0) 32 (100) 11 (8/13.5) 2 (0.5/3) 7 (5/9) 1.5 (1/3)

MFWC: Modified Functional Walking Category; M-Limited Community: Most-Limited Community; F: female; M: male; SD: standard deviation; EDSS: Expanded Disability Status Scale; MS: multiple sclerosis; RR: relapsing-remitting; PP: primary progressive; SP: secondary progressive; CIQ: Community Integration Questionnaire; IQR: Interquartile range 1st −3rd quartile.

4. Discussions

and Physiological walkers. Statistically significant differences (Table 2) were found between groups in walking aid and post-hoc analysis confirmed statistical differences between all categories except between Community walking categories and between Most-Limited Community walkers and Unlimited Household walkers. Use of walking aid is depicted in Fig. 1, as walking gets slower the need of a walking aid becomes greater, progressively shifting from the employment of unilateral aid to a bilateral support. Participation as measured by the CIQ is represented in Fig. 2. Statistically significant differences in total score were found between MFWCs; at post-hoc analysis statistically significant differences were found between all groups except between Physiological walkers and Limited Household, Limited Household and Most-Limited Community, Most-Limited Community and Unlimited Community categories. The CIQ subscale for home participation showed statistical differences between groups; at post hoc analysis Physiological walkers category registered a statistically significantly lower score in comparison with all other categories, while Limited Household category showed a statistically significant difference only with respect to the Unlimited Community category. No differences were found between categories on the social participation subscale. Instead, statistical differences were found between categories for productive subscale; at post-hoc analysis, Physiological walkers and Limited Household categories both showed statistically significant reduction in productive participation with respect to Unlimited Household and Unlimited Community walkers. Univariate logistic analysis, reported in Table 3, suggested that both clinical and demographical characteristics play some role in defining participation level of PwMS. Only disease duration did not show statistically significant association and was excluded in the multivariate analysis. The final multivariate model (Table 4) showed that older age, being male and using a walking aid are risk factors for participation restrictions. Fig. 3 depicts the probability of having participation restrictions of a male and female person with MS aged 53 years old (mean age of the observed group) depending on walking aid. In all three participation subsections age had a significant, although small, influence. MFWC played a role only in productive activities while walking aid and gender influenced home participation.

This study describes factors associated to walking impairments using the MFWC and the influence of walking category, use of a walking aid and clinical characteristics of the disease on participation in a sample of PwMS.

4.1. Characteristics of PwMS classified by MFWC More than two thirds of the sample had a relevant walking disorder with only 30% of them walking in the community while almost 70% of the sample belonged to the last three walking categories and so was limited to moving about the house. Twenty % of those were physiological walkers and so used a wheelchair, thus the present study expands on results by Kempen et al. (2011) including PwMS with moderate to high disease severity. Two thirds of the sample had a progressive course of MS. Having a progressive course and a longer disease duration was associated with a worse outcome in terms of MFWC. The association of disease type and duration confirms findings by Confavreux and Vukusic (2006) and Kister et al. (2013) reporting that subjects with RR and shorter disease duration have less mobility restrictions. In addition, a strong association was found between MFWCs and use of a walking aid. Of all community walkers 17% used a unilateral support and only 5% used a bilateral support. In agreement with Goldman et al. (2013), Unlimited Household walkers used a large variety of different walking aids and the vast majority of Limited Household had a bilateral support. Future studies are needed to verify if the association between walking aid and walking dysfunction is primarily due to balance disorders and/or fatigue rather than deficits in gait parameters. Finally, in agreement with Kempen et al., we observed a clear relationship between EDSS and the MFWC only in the better community walking categories (Kempen et al., 2011). This suggests EDSS may not provide a reliable picture of the ability of subjects’ in the Most-Limited Community walkers and the Unlimited Household categories to move around. PwMS with EDSS levels between 5.5 and 6 tended to be classified in these two walking categories suggesting that in this phase of the disease categorizing for velocity may discriminate better between limitations in walking in home and community. 13

Multiple Sclerosis and Related Disorders 26 (2018) 11–18

R. Bertoni et al.

Sixty-three percent of PwMS revealed participation restrictions based on the total CIQ results with a non linear relationship between walking and participation. Participation restrictions were less severe in the first three walking categories becoming more frequent in Limited Household and in Physiological walkers. Most-Limited Community walkers show limitation in participation due to avoidance of crowded places and assistance to get to local stores (Perry et al., 1995). Unlimited Household categories did not show strong differences compared to the former group in participation restrictions (Table 1). The lack of difference between these two groups is probably due to coping strategies used by the Unlimited Household group including rearrangement of their daily activities and use of walking aids (Table 1) to maintain the same level of participation. In support of these findings, Goldman et al. (2013) did not find any differences in amount of community ambulation between Most-Limited Community walkers and Unlimited Household walkers except that the more impaired group had a bigger percentage of people using walking aid and had a higher energy consumption during walking. Limited Household walkers instead represent the walking category where people cannot walk outside and may have trouble going out without another person's assistance. Accordingly, two thirds of PwMS in this category had participation restrictions. This figure increases to 95% for the category Physiological walker, people using their wheelchair for bedroom and bathroom mobility. In these two categories participation restrictions are high since their getting out of the house and being in the community most likely depends on the presence of caregivers, the use of wheelchairs and the presence of environmental barriers. 4.3. Predictors of participation restrictions Functional walking categories, walking aid, EDSS, gender, age and MS type were all found to be univariate predictors of participation restrictions. However, when these variables were entered into a multivariate analysis only age, gender and the presence of walking aid remained independent predictors. Older male subjects using a bilateral support or a wheelchair were more likely to have participation restrictions (see Fig. 3), a finding that corroborates results of Goldman et al that highlighted the importance of walking aid for functional mobility and benchmark disability levels in PwMS (Goldman et al., 2013). The role of walking aid in maintaining independence, was well described in the work of Finlayson and van Denend (2003) in which PwMS reported that the use of walking aid is primarily directed to retain the ability to complete activities of daily living related to personal mobility inside and outside the house. In addition walking aids represent a way to prevent falls and injurious falls that have been found to impact on participation (Cattaneo et al., 2017; Finlayson and van Denend, 2003; Nilsagård et al., 2009). The provision of appropriate mobility device agreeable to the subject is thus important for preserving a level of independence, even though the use of these aids may initially be perceived as surrendering to the disease or marking them as disabled persons in the community (Finlayson and van Denend, 2003). On the other hand, mobility rehabilitation that increases physical ability and thus potentially reduces the reliance on walking aids could increase participation. This ambiguity should be further investigated in controlled studies. 4.4. Predictors of home, social and productive participation restrictions The predictors of participation restriction in the sub-domain of home activities were age, gender and walking aid. These results are in accordance with Yorkston et al. (2008) and Kratz et al. (2016) stating that limitations in mobility are correlated to self-efficacy in home activities and with LaRocca (2011) who found that 83% of PwMS

⁎

Δ

0.002Δ 0.004Δ 1.00 1.00

Kruskall Wallis Test; Chi-square Test; M-Limited Community: Most-Limited Community; EDSS: Expanded Disability Status Scale; MS: multiple sclerosis; CIQ: Community Integration Questionnaire; Significant p value at Bonferroni Post Hoc Test; Significant p value < 0.005 (Bonferroni correction). b

a

0.001Δ 0.075 0.152

1.00 <0.001Δ

1.00 0.007Δ 1.00 0.070 <0.001* <0.001Δ 0.082 0.408 <0.001Δ 0.002 0.013 <0.001* 0.002Δ <0.001Δ 0.756 <0.001Δ 0.482 0.458 <0.001* 0.278 0.359 1.00 0.071 0.454 0.414 0.122 1.00 1.00 0.031Δ <0.001Δ <0.001Δ <0.001* <0.001* <0.001Δ <0.001Δ 0.384 <0.001Δ 0.049Δ 0.110 <0.001* 1.00 1.00

0.264 0.020 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.195 <0.001 Gender Age EDSS Disease duration Type of MS Walking aid CIQ Total Home Social Productive

5.24b 11.65a 109.47a 22.53a 33.95b 234.06b 37.96a 41.47a 6.05a 27.55a

1.00 <0.001Δ 1.00 0.019 0.099 1.00 1.00

0.061 <0.001Δ 0.050 <0.001* <0.001* 0.003Δ 0.016Δ

1.00

1.00 <0.001Δ 0.449 <0.001* <0.001* <0.001Δ <0.001Δ Limited Household Limited Household Unlimited Household M-Limited Community

Limited Household

Unlimited Community vs Physiological Walkers Unlimited Community vs Unlimited Community vs Unlimited Community vs

Post-hoc p-values Overall p-value K-Wa o χ2b

Table 2 Comparisons of demographical and clinical variables between Modified Functional Walking Categories.

M-Limited Community vs Unlimited Household

M-Limited Community vs

M-Limited Community vs Physiological Walkers

Unlimited Household vs

Unlimited Household vs Physiological Walkers

1.00 <0.001Δ 0.289 0.143 <0.001* 0.508 0.013Δ

Limited Household vs Physiological Walkers

4.2. MFWC and participation restrictions

14

Multiple Sclerosis and Related Disorders 26 (2018) 11–18

R. Bertoni et al.

Fig. 1. Percentages of type of walking aid in the Modified Functional Walking Categories.

In our sample social participation was only slightly reduced with respect to healthy subjects and was influenced only by age. This is in contrast with findings by Kwiatkowski and colleagues that found reduced social participation in persons with EDSS levels equal or above 6 and Mikula and colleagues that found an association between social participation and the physical components of the SF-12 (Kwiatkowski et al., 2014; Mikula et al., 2017). It is possible that the presence of age in the model obscured the role of walking abilities in predicting social participation since it is known that older people tend to have a more advanced disease level and worse mobility disorders. We can also speculate that mobile communication may have an impact on how social participation is perceived. Through use of technology and social media even people with high mobility restrictions but cognitively sufficiently preserved may in part retain social relationships

reporting walking impairment required assistance to fulfill household responsibilities. In a similar vein Goldman et al. (2013) speculated that subjects walking slower than 0.95 m/s may be unable to do household activities (house cleaning, laundry, cooking) due to energetic cost of walking and emphasized that below this walking speed PwMS usually walk with a walker. Regarding the impact of gender, the probability of having participations restrictions was 11 times higher for males than females and this gender gap was increased for older PwMS. This may be due to cultural and social factors since women are more often in charge of household activities. Further studies are however necessary to better understand the interaction of gender and age and factors, such as cognitive disorders and upper limb impairment previously found to be associated with participation restrictions at home (Cattaneo et al., 2017).

Fig. 2. Community integration questionnaire total score for each modified walking functional category. 15

Multiple Sclerosis and Related Disorders 26 (2018) 11–18

R. Bertoni et al.

Table 3 Univariate logistic analysis for factors influencing participation restrictions (measured by total CIQ score). Participation Variable

Unrestricted CIQ > 17 n = 55 (37%)

Restricted CIQ ≤ 17 n = 94 (63%)

Age, mean, years ( ± SD) Disease duration, mean, years ( ± SD) Gender, n (%) F M Type of MS, n (%) RR PP SP EDSS, median (IQR) MFWC, n (%) Unlimited Community Most-Limited Community Unlimimited Household Limited Household Physiological Walkers Walking Aid, n (%) None Unilateral Bilateral Wheelchair

48.75 15.20

( ± 9.3) ( ± 8.82)

55.21 18.49

( ± 11.27) ( ± 11.06)

41 14

(75) (25)

53 41

(56) (44)

35 7 13 6.0

(64) (13) (23) (4.5/6.5)

28 14 52 6.5

(30) (15) (55) (5.5/7.5)

13 12 18 10 2

(23) (22) (33) (18) (4)

7 13 15 29 30

(7) (14) (16) (31) (32)

32 10 11 2

(58) (18) (20) (4)

18 12 34 30

(19) (13) (36) (32)

Wald's χ2

Odds ratio

CI

11.300* 3.428 4.809*

1.06 1.03 0.44

1.02 – 1.10 0.21 – 0.92

8.848*

2.24

1.31 – 3.83

14.600* 14.923*

1.60 0.51

1.26 – 2.06 0.36 – 0.72

27.903*

2.63

1.83 – 3.78

CI: Confidence Interval; CIQ: Community Integration Questionnaire; SD: standard deviation; F: female; M: male; MS: multiple sclerosis; RR: relapsing-remitting; PP: primary progressive; SP: secondary progressive; MFWC: Modified Functional Walking Category; ⁎ p-level < 0.05.

Some limitations should be noted. A larger sample size for each walking category could have decreased the variability and provided more conclusive results. In the predictive model the presence of a caregiver, cognitive impairments and fatigue were not accounted for. Also the impact of number of mobility devices used by the individual was not considered, while it is known that PwMS usually own various mobility devices for indoor and/or outdoor activities (Iezzoni et al., 2009). The entangled relationship between walking aids, EDSS and gait velocity should also be further investigated. Results for social and productive participation may be controversial due to low levels of internal consistency and dimensionality that has been reported for these subscales (Hirsh et al., 2011). Further, this is a cross sectional study while a longitudinal study might be indicated to better understand the impact individually tailored walking aids may have on participation and whether rehabilitation to increase gait velocity impacts on productive participation. Finally, the

(Yorkston et al., 2005). Concerning participation in productive activities, two thirds of the PwMS were employed at the time of evaluation, a percentage similar to those reported by other studies (Tinghög et al., 2013; Raggi et al., 2016; Krause et al., 2013). Only in this subcategory of the CIQ lower levels of the MFWC were predictive of restrictions in participation, along with age. This is not surprising since problems with mobility have been associated to work-related difficulties, such as reduced working hours, working less or even not working at all (Raggi et al., 2016; Wickström et al., 2014). This emphasizes the importance of augmenting or maintaining mobility performance through rehabilitation and physical activity in PwMS since it has also been shown that improvement in walking capacity predicts reduction of sick leave (Wickström et al., 2014). Other factors, such as early retirement policies, cognitive impairments and fatigue that were not included in our model may also have impacted on productive participation (Schiavolin et al., 2013).

Table 4 Final predictive logistic model of factors influencing participation measured by Community Integration Questionnaire. CIQ Total

Home

Social

Productive

Coefficient (B) Constant Age Gender[ref. female] Walking Aid Max Likelihood Final Constant Age Gender [ref. female] Walking Aid Max Likelihood Final Constant Age Max Likelihood Final Constant Age MFWC Max Likelihood Final

−2.828 0.056 −1.080 0.953 Loss: 73.99; χ2 −4.886 0.065 −2.273 1.045 Loss: 58.91; χ2 −2.662 0.053 Loss: 97.07; χ2 −6.500 0.074 0.613 Loss: 71.49; χ2

Standard Error

1.077 0.020 0.446 0.195 (3 )= 48.250 1.268 0.022 0.506 0.238 (3 )= 61.235 0.877 0.016 (1 )= 11.599 1.286 0.021 0.186 (2 )= 34.241

Wald χ2

p Value

Odds Ratio

95% CI

6.895 7.709 5.865 23.851

0.008 0.005 0.016 <0.001

1.05 0.34 2.59

1.02 0.14 1.76

– – –

1.10 0.82 3.82

14.836 8.577 20.182 19.236

<0.001 0.003 <0.001 <0.001

1.07 0.10 2.84

1.02 0.04 1.78

– – –

1.12 0.28 4.55

9.216 10.601

0.002 0.001

1.05

1.02

–

1.09

25.558 11.942 10.835

<0.001 <0.001 <0.001

1.07 1.85

1.03 1.28

– –

1.12 2.70

CIQ: Community Integration Questionnaire; 95% CI: 95% Confidence Interval; MFWC: Modified Functional Walking Category. Ref: restricted. 16

Multiple Sclerosis and Related Disorders 26 (2018) 11–18

R. Bertoni et al.

Fig. 3. Probability of having participation restrictions for male and female by walking aid. Note: probability has been calculated for a supposed person with MS of 53 years old (mean age of the observed group).

population that uses a wheelchair and is restricted to the limited household and physiological walker categories may require separate controlled studies inquiring on non-walking related factors.

Goldman, M.D., Motl, R.W., Scagnelli, J., Pula, J.H., Sosnoff, J.J., Cadavid, D., 2013. Clinically meaningful performance benchmarks in MS: timed 25-foot walk and the real world. Neurology 81 (November(21)), 1856–1863. Hirsh, A.T., Braden, A.L., Craggs, J.G., Jensen, M.P., 2011 Oct. Psychometric properties of the community integration questionnaire in a heterogeneous sample of adults with physical disability. Arch. Phys. Med. Rehabil. 92 (October(10)), 1602–1610. Hosmer, D.W., Lemeshow, S., 2000. Applied Logistic Regression. Wiley, New York. Hughes, A.J., Hartoonian, N., Parmenter, B., Haselkorn, J.K., Lovera, J.F., Bourdette, D., Turner, A.P., 2015 Nov. Cognitive Impairment and community integration outcomes in individuals living with multiple sclerosis. Arch. Phys. Med. Rehabil. 96 (November (11)), 1973–1979. Iezzoni, L.I., Rao, S.R., Kinkel, R.P., 2009 Apr. Patterns of mobility aid use among working-age persons with multiple sclerosis living in the community in the United States. Disabil Health J. 2 (April(2)), 67–76. Kempen, J.C., de Groot, V., Knol, D.L., Polman, C.H., Lankhorst, G.J., Beckerman, H., 2011 Aug. Community walking can be assessed using a 10-metre timed walk test. Mult. Scler. 17 (August(8)), 980–990. Kierkegaard, M., Einarsson, U., Gottberg, K., von Koch, L., Holmqvist, L.W., 2012 May. The relationship between walking, manual dexterity, cognition and activity/participation in persons with multiple sclerosis. Mult. Scler. 18 (May(5)), 639–646. Kister, I., Bacon, T.E., Chamot, E., Salter, A.R., Cutter, G.R., Kalina, J.T., Herbert, J., 2013. Natural history of multiple sclerosis symptoms. Int. J. MS Care 15 (3), 146–158 Fall. Kratz, A.L., Ehde, D.M., Hanley, M.A., Jensen, M.P., Osborne, T.L., Kraft, G.H., 2016 Mar. Cross-sectional examination of the associations between symptoms, community integration, and mental health in multiple sclerosis. Arch. Phys. Med. Rehabil. 97 (March(3)), 386–394. Krause, I., Kern, S., Horntrich, A., Ziemssen, T., 2013 Nov. Employment status in multiple sclerosis: impact of disease-specific and non-disease-specific factors. Mult. Scler. 19 (November(13)), 1792–1799. Kwiatkowski, A., Marissal, J.P., Pouyfaucon, M., Vermersch, P., Hautecoeur, P., Dervaux, B., 2014. Social participation in patients with multiple sclerosis: correlations between disability and economic burden. BMC Neurol. 14 (May), 115. LaRocca, N.G., 2011. Impact of walking impairment in multiple sclerosis: perspectives of patients and care partners. Patient 4 (3), 189–201. Lord, S.E., McPherson, K., McNaughton, H.K., Rochester, L., Weatherall, M., 2004 Feb. Community ambulation after stroke: how important and obtainable is it and what measures appear predictive. Arch. Phys. Med. Rehabil. 85 (February(2)), 234–239. Mikula, P., Nagyova, I., Krokavcova, M., Vitkova, M., Rosenberger, J., Szilasiova, J., Gdovinova, Z., Stewart, R.E., Groothoff, J.W., van Dijk, J.P., 2017 Jul. Self-esteem, social participation, and quality of life in patients with multiple sclerosis. J. Health Psychol. 22 (July(8)), 984–992. Negahban, H., Fattahizadeh, P., Ghasemzadeh, R., Salehi, R., Majdinasab, N., Mazaheri, M., 2013 Aug. The Persian version of community integration questionnaire in persons with multiple sclerosis: translation, reliability, validity, and factor analysis. Disabil. Rehabil. 35 (August(17)), 1453–1459. Nilsagård, Y., Lundholm, C., Denison, E., Gunnarsson, L.G., 2009 Mar. Predicting accidental falls in people with multiple sclerosis - a longitudinal study. Clin. Rehabil. 23 (March(3)), 259–269. Paltamaa, J., Sarasoja, T., Leskinen, E., Wikström, J., Mälkiä, E., 2008 Feb. Measuring deterioration in international classification of functioning domains of people with multiple sclerosis who are ambulatory. Phys. Ther. 88 (February(2)), 176–190. Perry, J., Garrett, M., Gronley, J.K., Mulroy, S.J., 1995 Jun. Classification of walking handicap in the stroke population. Stroke 26 (June(6)), 982–989. Raggi, A., Covelli, V., Schiavolin, S., Scaratti, C., Leonardi, M., Willems, M., 2016. Work-

5. Conclusion Most PwMS are restricted in community integration. Their participation was associated with walking categories, progressive type of MS, disease level and duration, as well as, the use of a walking aid. Walking categories and walking aid are related concepts when describing mobility, however our results show that walking aid may be a better predictor of overall participation in PwMS. This indicates the importance of considering benefits and minuses of walking aids within rehabilitation aimed at increasing mobility and participation. Conflict of interest None. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. References Cameron, M.H., Fitzpatrick, M., Overs, S., Murchison, C., Manning, J., Whitham, R., 2014 May. Dalfampridine improves walking speed, walking endurance, and community participation in veterans with multiple sclerosis: a longitudinal cohort study. Mult. Scler. 20 (May(6)), 733–738. Cattaneo, D., Lamers, I., Bertoni, R., Feys, P., Jonsdottir, J., 2017. Participation restriction in people with multiple sclerosis: prevalence and correlations with cognitive, walking, balance, and upper limb impairments. Arch. Phys. Med. Rehabil. 98 (July (7)), 1308–1315. Confavreux, C., Vukusic, S., 2006 Mar. Natural history of multiple sclerosis: a unifying concept. Brain 129 (March(Pt 3)), 606–616. Feys, P., Bibby, B., Romberg, A., Santoyo, C., Gebara, B., de Noordhout, B.M., Knuts, K., Bethoux, F., Skjerbæk, A., Jensen, E., Baert, I., Vaney, C., de Groot, V., Dalgas, U., 2014. Within-day variability on short and long walking tests in persons with multiple sclerosis. J. Neurol. Sci. 338 (March(1-2)), 183–187. Finlayson, M., van Denend, T., 2003. Experiencing the loss of mobility: perspectives of older adults with MS. Disabil. Rehabil. 25 (October(20)), 1168–1180. Fischer, J.S., Rudick, R.A., Cutter, G.R., Reingold, S.C., 1999 Aug. The multiple sclerosis functional composite measure (MSFC): an integrated approach to MS clinical outcome assessment. National MS society clinical outcomes assessment task force. Mult. Scler. 5 (August(4)), 244–250.

17

Multiple Sclerosis and Related Disorders 26 (2018) 11–18

R. Bertoni et al.

multiple sclerosis after one year of natalizumab treatment. A prospective ad hoc analysis of the TYNERGY trial. Mult. Scler. 20 (July(8)), 1095–1101. Willer, B., Ottenbacher, K.J., Coad, M.L., 1994 Apr. The community integration questionnaire. A comparative examination. Am. J. Phys. Med. Rehabil. 73 (April(2)), 103–111. World Health Organization, 2001. International Classification of Functioning, Disability and Health (ICF). World Health Organization, Geneva. Yorkston, K.M., Johnson, K.L., Klasner, E.R., 2005 May. Taking part in life: enhancing participation in multiple sclerosis. Phys. Med. Rehabil. Clin. North Am. 16 (May(2)), 583–594 Review. Yorkston, K.M., Kuehn, C.M., Johnson, K.L., Ehde, D.M., Jensen, M.P., Amtmann, D., 2008. Measuring participation in people living with multiple sclerosis: a comparison of self-reported frequency, importance and self-efficacy. Disabil. Rehabil. 30 (2), 88–97.

related problems in multiple sclerosis: a literature review on its associates and determinants. Disabil. Rehabil. 38 (10), 936–944. Schiavolin, S., Leonardi, M., Giovannetti, A.M., Antozzi, C., Brambilla, L., Confalonieri, P., Mantegazza, R., Raggi, A., 2013 Jun. Factors related to difficulties with employment in patients with multiple sclerosis: a review of 2002-2011 literature. Int. J. Rehabil. Res. 36 (June(2)), 105–111. Taheri, M., Negahban, H., Mostafaee, N., Salehi, R., Tabesh, H., 2016. Responsiveness of selected outcome measures of participation restriction and quality of life in patients with multiple sclerosis. Disabil. Rehabil. 38 (5), 482–486. Tinghög, P., Hillert, J., Kjeldgård, L., Wiberg, M., Glaser, A., Alexanderson, K., 2013 Dec. High prevalence of sickness absence and disability pension among multiple sclerosis patients: a nationwide population-based study. Mult. Scler. 19 (December(14)), 1923–1930. Wickström, A., Dahle, C., Vrethem, M., Svenningsson, A., 2014 Jul. Reduced sick leave in

18