Is Physical Behavior Affected in Fatigued Persons With Multiple Sclerosis?
Presented as a poster and oral presentation to the Rehabilitation in Multiple Sclerosis Conference, June 6–7, 2014, Brighton, UK.
Published Online: September 17, 2014
Highlights
- •Fatigued persons with multiple sclerosis are less physically active than healthy controls during the whole day.
- •Persons with multiple sclerosis are especially less active in the morning and evening.
- •Persons with multiple sclerosis spend more time sedentary and less time at higher-intensity physical activity than healthy controls.
- •Persons with multiple sclerosis have longer sedentary periods and shorter high-intensity periods.
- •Detailed measures may provide more insight into how multiple sclerosis affects physical behavior.
Abstract
Objective
To study physical behavior in detail in fatigued persons with multiple sclerosis (MS).
Design
Case-control explorative study.
Setting
Outpatient rehabilitation department and participants' daily environment.
Participants
Fatigued persons with MS (n=23) were selected from a randomized controlled trial. Cases were matched by age and sex to healthy, nonfatigued controls (n=23). Eligible persons with MS were severely fatigued (Checklist Individual Strength fatigue domain mean score, 43.2±6.6) and ambulatory (Expanded Disability Status Scale mean score, 2.5±1.5).
Interventions
Not applicable.
Main Outcome Measures
Measurements were performed using an accelerometer over 7 days. Outcomes included the following: amount of physical activity expressed in counts per day, counts per minute (CPM), and counts per day period (morning, afternoon, evening); duration of activity intensity categories (sedentary, light physical activity, moderate-to-vigorous physical activity [MVPA]); and distribution of MVPA and sedentary periods over the day.
Results
Persons with MS had fewer counts per day (mean difference, −156×103; 95% confidence interval [CI], −273×103 to −39×103; P=.010), had fewer CPM (mean difference, −135; 95% CI, −256 to −14; P=.030), and were less physically active in the morning (mean difference, −200; 95% CI, −389 to −11; P=.039) and evening (mean difference, −175; 95% CI, −336 to −14; P=.034) than controls. Persons with MS spent a higher percentage of their time sedentary (mean difference, 5.6; 95% CI, .1–11.1; P=.045) and spent less time at the higher MVPA intensity (mean difference, −2.4; 95% CI, −4.7 to −0.09; P=.042). They had fewer MVPA periods (mean difference, 29; 95% CI, −56.2 to −2.6; P=.032) and a different distribution of sedentary (mean difference, .033; 95% CI, .002 to .064; P=.039) and MVPA periods (mean difference, −.08; 95% CI, −.15 to −.01; P=.023).
Conclusions
Detailed analyses of physical behavior showed that ambulatory fatigued persons with MS do differ from healthy controls not only in physical activity level, but also in other physical behavior dimensions (eg, day patterns, intensity, distribution).
List of abbreviations:
CI (confidence interval), CPM (counts per minute), MS (multiple sclerosis), MVPA (moderate-to-vigorous physical activity)
Multiple sclerosis (MS) is a chronic progressive neurologic disease leading to limitations in activities and participation.1, 2,3 Limitations may result from 2 prevalent consequences of MS: fatigue and changes to the condition of the patient's posture, patient's movement, patient's activities of daily life (physical behavior).4 Fatigue affects 80% of persons with MS,5and studies show that MS-related fatigue severely limits daily activities and restricts participation.6, 7
Thus far, the effects of MS and MS-related fatigue on physical behavior have been studied primarily from the perspective of physical activity levels (eg, total number of activity counts, number of steps). Literature in this area shows that persons with MS are generally less physically active than healthy persons.8, 9, 10, 11, 12 However, it is important to recognize that physical activity level is just one of the dimensions of physical behavior. For example, MS rehabilitation interventions (eg, energy conservation management)13 do not usually focus on the total amount of activity, but on issues such as balancing day patterns, frequency and intensity of activities, and distribution of activity and rest. Therefore, it is questionable whether physical activity level, as determined by total activity counts, is the most clinically relevant indicator of physical behavior in MS.
The relevance of other physical behavior dimensions is increasingly recognized,4 and technologic developments increasingly allow objective measurement of these dimensions. Studies of other patient populations show that more detailed information about physical behavior provides additional insight into the consequences of disease and treatment effects. For example, Evering et al14 showed that patients with chronic fatigue syndrome differed in afternoon and evening day patterns compared with healthy people, but they did not differ over the course of the whole day. Other studies show that similar total activity counts may result from prolonged periods of low-intensity activity or short periods of high-intensity activity.14, 15, 16 Similarly, studies show that patients (eg, those with Parkinson disease or chronic fatigue syndrome) differ from healthy people in the distribution of sedentary periods17, 18; however, they do not differ in the total amount of time spent sedentary.
For persons with MS, research providing detailed analyses of physical behavior is scarce. Rietberg et al,19 who studied the physical activity day patterns for specific postures and movements over a 24-hour period, found that persons with MS had lower physical activity levels in the morning, which persisted throughout the day. Klaren et al20 found that persons with MS spent less time in moderate and vigorous physical activity compared with healthy controls. Neither study included fatigued persons with MS, described >1 dimension of physical behavior, or based their results on long measurement periods. Therefore, the research question of the present explorative study is as follows: Do fatigued persons with MS show different physical behavior compared with matched controls on detailed outcomes (eg, day patterns, intensity of activities, distribution of activities)?
Methods
Participants
This case-control study is part of the multicenter research program Treating Fatigue in MS with Aerobic Training, Cognitive Behavioral Therapy and Energy Conservation Management.21 The research program evaluates the effectiveness of rehabilitation interventions on fatigue and participation in persons with MS. The inclusion criteria are as follows: definite diagnosis of MS; severe fatigue as indicated by a score of ≥35 on the fatigue domain of the Checklist Individual Strength; ambulatory status (ie, Expanded Disability Status Scale score ≤6); no diagnosis of depression (ie, Hospital Anxiety and Depression Scale score <11); no initiation or change to pharmacologic treatment for fatigue during the previous 3 months; and aged 18 to 70 years.
The present study was based on available accelerometer baseline data (n=67) from the Treating Fatigue in MS with Aerobic Training, Cognitive Behavioral Therapy and Energy Conservation Management, a Randomized Controlled Trial Study. For the present study, an additional inclusion criterion was that baseline measurements were performed during the same time period (April–September) in which the control subjects were planned to be measured. This criterion resulted in a subpopulation of 29 persons with MS who were eligible for inclusion. Each person with MS in this subpopulation was asked to recruit a maximum of 5 control subjects of similar age (±5y) and sex from their social environment who were potentially willing to participate. The recruited control subjects were contacted and informed of their selection for inclusion by a research student. The control subjects completed a form with demographic and personal characteristics and the Checklist Individual Strength and Hospital Anxiety and Depression Scale questionnaires. Control subjects were eligible if they scored Checklist Individual Strength fatigue scores <35, Hospital Anxiety and Depression Scale scores <11, and had no mobility limitations that affected their physical activity. Included control subjects were matched for age and sex with the patients with MS. Demographic and personal characteristics were recorded for both groups.
The protocol for this study was approved by the Medical Ethics Committee of the VU University Medical Center, Amsterdam, The Netherlands. All participants provided written informed consent.
Measurements
Physical behavior assessment was performed using 3-dimensional accelerometry (ActiGraph GT3X+ modela; 4.6×3.3×1.5cm; 19g). This device has demonstrated validity and reliability in measuring physical behavior in persons with MS and healthy adults.22, 23 Participants wore the accelerometer on an elastic belt that was positioned at the waist. To ensure that the accelerometer was worn correctly, participants were shown how to wear the accelerometer and were given detailed written instructions. All participants wore the activity monitor during waking hours for 7 days, except while showering or swimming. The measurements were performed in the daily environment of the participants; participants were instructed to behave naturally. Accelerometer signals were sampled with 30Hz and analyzed with Actilife version 6.6.2 software.a For all 3 axes, activity counts were calculated for 10-second epochs. From this, the vector magnitude was calculated. In the Actilife software, the low-frequency extension option was enabled. A 180-minute (or longer) period of continuous zero counts was defined as a nonwear period and was excluded from further analyses. Days with at least 660 minutes of wear time were considered valid. For data to be included in the analysis, at least 5 valid measurement days were required. Additional calculations were performed using Microsoft Excelb and MATLAB.c
Outcome measures
Physical behavior outcomes were analyzed per individual. They were calculated as group means for valid days of the total measurement period and were averaged for the number of days. To describe day patterns, we only included weekdays because including weekend days may confound the day pattern data.24
For the dimensions of physical behavior, the first dimension included length of the day: the wear time per day (min). The second dimension was the amount of physical activity, including total counts per day and counts per minute (CPM). Additionally, for weekdays, CPM were calculated for each hour and summarized for 3 periods of the day14, 24: morning (5:00 am–12:00 m), afternoon (12:00 m–6:00 pm), and evening (6:00 pm–12:00 am). For data to be included in these analyses, the minimal wear time per hour was set at 30 minutes. Finally, the time spent in intensity categories was included as a dimension. Based on counts and valid default vector magnitude cutpoints,25, 26, 27 each minute was categorized as sedentary (0–150 counts), light (151–2690 counts), and moderate-to-vigorous physical activity (MVPA) (>2691 counts). The time spent in each category was expressed as a percentage of the wear time per day.
Distribution of the duration of periods
The distribution of the duration of periods (bout length) of sedentary and MVPA behavior was assessed according to the method described by Chastin et al.17, 18 A sedentary bout was defined as at least 1 minute of CPM ≤150, and an MVPA bout was defined as at least 1 minute of CPM ≥2691. Bout detection was performed with Actilife, and bout time series were exported to MATLAB for further analysis. The following bout parameters were calculated per day. First, the number of bouts was calculated. Second, the mean bout length (min) was calculated: because the length of bouts was lognormally distributed, the natural log of the data was taken. The mean of the log data was calculated and backtransformed to the original scale. The third parameter was the variation of bout length (coefficient of variation). This outcome was obtained after dividing the SD by the mean bout length (min) from the lognormal transformed data. It indicates whether the bout length shows much (high value) or little (lower value) within-subject variability. The fourth parameter was the fragmentation of bouts.16, 28 This variable was calculated as the number of bouts divided by the summed duration (min) of all bouts. A higher fragmentation index indicates that time spent sedentary or active is more fragmented with shorter bouts. The final parameter was the Gini index. The Gini index reflects the pattern of accumulation of bouts and was calculated separately for sedentary and MVPA behavior. The Gini index varies from 0 to 1, where a Gini index score near 1 indicates that the summed bout time is composed of longer bouts rather than short bouts. A lower Gini index score indicates that there are a larger number of periods of different lengths, with a dominance of short bouts.17, 18, 29
Statistical analysis
SPSS version 21d was used for data analysis. Descriptive data are presented as mean ± SD or as otherwise indicated. The significance level was set at P<.05 for all analyses. Differences between groups were examined using independent ttests. Effect size estimates based on Cohen d (ie, difference between mean scores for 2 groups divided by the pooled SD) were calculated for all outcomes.
Results
Of the 29 persons with MS, 4 had invalid data and 2 could not be matched with control subjects. The persons with MS recruited 57 control subjects, of which 2 were excluded because of mobility limitations, 4 were excluded because of fatigue or depression, 2 could not be contacted, and 26 were redundant or could not be matched to a person with MS. Finally, data were obtained from 23 persons with MS and 23 matched control subjects. The characteristics of both groups are shown in table 1. Persons with MS were severely fatigued and had low Expanded Disability Status Scale scores, showing minimal neurologic impairments; 87% had relapsing-remitting MS. The matched controls had a more favorable work status (ie, more were employed) (P=.04).
NOTE. Values are mean ± SD (range), n, or as otherwise indicated.
Abbreviations: BMI, body mass index; CIS, Checklist Individual Strength; EDSS, Expanded Disability Status Scale; F, female; FSS, Fatigue Severity Scale; M, male; NA, not applicable; RR, relapsing remitting; SP, secondary progressive.
∗Value is median (interquartile range).
†Groups differed significantly.
The results for physical behavior of persons with MS and controls are shown in table 2. Persons with MS had significantly lower amounts of physical activity levels per day and for all day periods, except for the afternoon. The CPM results per day for weekdays are shown in figure 1. Day pattern outcomes were based on weekdays because as we previously stated weekend days may confound the day patterns. Therefore, we did an additional analysis to compare the groups on weekend days: no differences between the groups on CPM day patterns (morning, afternoon, evening) were found, indicating that day patterns indeed differ for weekdays and weekend days. For the other physical behavior outcomes, the results were not different for weekdays or weekend days, except for length of day: both persons with MS (mean difference, 57min; P<.001) and controls (mean difference, 35min; P=.006) had shorter days on weekends.
NOTE. Values are in mean ± SD or as otherwise indicated.
Abbreviations: CoVSed or MVPA, variation of sedentary or MVPA bout length; CPD, counts per day; FSed or MVPA, fragmentation of sedentary or MVPA bouts; PB, physical behavior.
∗Groups differed significantly.
Fig 1
Amount of physical activity per period of the weekday. Expressed in mean CPM per hour with the SEM.
Figure 2 shows the relative time spent in each physical behavior intensity category. Persons with MS spent more time in sedentary behavior (P=.045) and less time in MVPA (P=.042) than controls.
Fig 2
Relative time spent in intensity categories. Categories expressed in mean percentages with the SEM. *Significant differences between persons with MS and matched control subjects.
The distribution analyses of sedentary periods showed a significantly different accumulation of sedentary periods between groups. Persons with MS had a higher sedentary Gini index, meaning that they had longer sedentary bouts and fewer short bouts than controls; other measures of sedentary behavior did not differ. Additionally, there was a tendency for persons with MS to have a less fragmented pattern of sedentary behavior and more variability in bout length. The MVPA period distribution analysis showed that persons with MS had a significantly lower number of MVPA bouts than controls. Also, the accumulation of MVPA bouts differed between the 2 groups, indicating that persons with MS build up their MPVA time with more short bouts and fewer long bouts.
Discussion
The aim of the present study was to elucidate which dimensions (eg, day patterns, intensity of activities, distribution of activities) of physical behavior are affected in fatigued persons with MS compared with age- and sex-matched control subjects. In general, fatigued persons with MS had lower physical activity levels. The effects on other aspects of physical behavior were variable, but every dimension analyzed (ie, day patterns, intensity categories, distribution of the duration of different aspects of physical behavior) revealed ≥1 significant difference between groups.
The finding that persons with MS had lower amounts of daily physical activity levels is consistent with other studies,9, 10, 30,31, 32 despite the differences in devices and settings used. Lower amounts of daily physical activity may result from a shorter day or less activity per minute or hour. Our results indicate that the latter explanation is more likely: we found a nonsignificant mean difference of −36 minutes (95% confidence interval [CI], −77 to 5) in length of day between groups, whereas CPM differed significantly (mean difference, −135; 95% CI, −256 to −14).
We also studied other dimensions of physical behavior, including day patterns, intensity of activities, and distribution of the duration of periods of sedentary and MVPA behavior. It was shown that persons with MS were less active during the morning and evening, but not during the afternoon (although there was a trend toward less activity). We cannot explain the lack of difference between groups during the afternoon. Rietberg19 recently studied day patterns in persons with MS compared with controls based on a 24-hour measurement period; lower amounts of PA levels were observed throughout the day and during all 3 day periods compared with healthy controls. The difference in findings with respect to afternoon data between studies may reflect patient population differences: fatigue was not an inclusion or exclusion criterion for the Rietberg study. Another difference between the studies is that Rietberg focused on specific postures or activities (walking) and expressed these as durations, whereas we included all activities and expressed them as amounts of activity per minute (CPM).
Physical behavior intensity was another detailed outcome examined in our study. Categories of sedentary behavior, light activity, and higher activity (MVPA) were defined by preset cutpoints of counts. The results indicate that persons with MS spent more time in the sedentary category and less time in the higher-intensity (MVPA) category. Klaren20 also showed that persons with MS spent less time in MVPA than matched controls. To our knowledge, time spent sedentary in persons with MS has not been studied previously. However, the literature shows that the amount of sedentary behavior is an independent determinant of health.33, 34 Although significant, the differences we detected in time spent in the sedentary category between groups were small (5.6%; 95% CI, 0.1–11.1; P=.045).
Distribution outcomes (eg, fragmentation, Gini index) are related to the duration and pattern of periods of sedentary and higher activity (MVPA) behavior. The most comprehensive outcome, the Gini index, gives information about how sedentary and MVPA periods are distributed over time. Results of the Gini index suggest that persons with MS accumulate sedentary time in longer sedentary periods, with a trend toward less fragmented sedentary patterns and more variable lengths of sedentary periods. Furthermore, persons with MS had fewer higher activity (MVPA) periods, and these were of shorter duration. For fatigued persons with MS, the distribution of different physical behavior over the day may depend on adaptation strategies used to reduce perceived fatigue. It may be more efficient to have more fragmented activity and rest periods; longer periods of sedentary behavior may indicate overload or deconditioning behavior. Chastin17, 18 found similar results for accumulation of sedentary periods in patients with Parkinson disease17 and chronic fatigue syndrome.18However, their Gini index values were higher, meaning that their total measured sedentary behavior consisted of more long sedentary periods. This difference may be because of their inclusion of night as sedentary time, which results in overall longer sedentary period measurements.
The focus of our study was to conduct a detailed analysis of several dimensions of physical behavior of fatigued persons with MS. It was assumed that MS affects not only the total amount of physical activity, but other dimensions of physical behavior as well. Our results support this assumption: effects on the total amount of physical activity and most detailed outcomes were noted. This study showed how detailed measures provide more insight into how MS affects physical behavior. These outcomes can be used by clinicians and therapists for the development and evaluation of rehabilitation interventions, such as energy conservation management,13 which emphasizes balancing rest and active behavior to decrease fatigue levels and increase participation.
Study limitations
Employment may be a determinant of several physical behavior outcomes. In our study, persons in the control group were more often employed. However, it can be assumed that differences in employment result from the disease and therefore should not be considered as a confounder. To examine the potential effect of employment, we compared weekdays and weekend days to show that persons with MS and controls had comparable physical behavior dimensions; therefore, employment seemed to be a nonsignificant influence.
Another limitation is the small sample size. The small sample size affected our power to detect statistically significant differences. Therefore, it might be that some outcomes that were nonsignificant in our study would have been significant in a larger sample. An additional limitation is that this study evaluates only ambulatory persons with MS and fatigue; therefore, results may not be generalizable to all persons with MS. Furthermore, small group sizes prevented us from performing subgroup analysis by fatigue level.
Conclusions
Our study shows that ambulatory fatigued persons with MS are less physically active per day, especially in the morning and evening, and more time is spent sedentary and less time is spent at higher-intensity (MVPA) activity compared with age- and sex-matched controls. The results suggest that physical behavior of fatigued persons with MS consists of relatively longer sedentary periods and fewer and relatively shorter higher-intensity periods. Overall, it can be concluded that detailed analysis provides more insight into how physical behavior is affected in fatigued persons with MS. The results of this exploratory study should be confirmed in prospective studies.
Suppliers
- a.ActiGraph, 48 E Chase St, Pensacola, FL 32502.
- b.Microsoft Corp, 1 Microsoft Way, Redmond, WA 98052-6399.
- c.MathWorks, 3 Apple Hill Dr, Natick, MA 01760-2098.
- d.SPSS Inc, 233 S Wacker Dr, 11th Fl, Chicago, IL 60606-6307.
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