BACKGROUND

Although the relationships among physical disability, mood disorders, and pain are well described in multiple sclerosis (MS), little is known about whether those symptoms are associated with sleep disturbances.

METHODS

Forty-six patients with MS experiencing pain participated. Sleep was indirectly measured by assessing rest-activity rhythm via actigraphy: interdaily stability, intradaily variability, and relative amplitude. Pain was assessed using visual and verbal analog scales, mood by the Beck Depression Inventory and Symptom Checklist-90, and physical disability by the Expanded Disability Status Scale.

RESULTS

Incorporating mood, pain, and physical disability into 1 regression model resulted in a significant association with interdaily stability.

CONCLUSIONS

Compared with intradaily variability and relative amplitude, interdaily stability seems to be the most vulnerable actigraphy variable for mood disturbances, pain, and physical disabilities.

Major symptoms of multiple sclerosis (MS) include motor dysfunction, cognitive impairment, mood disturbances, and pain.1  The relationships between those symptoms have been extensively examined, more specifically those between physical disability and pain,2  between pain and mood (anxiety, depression),3  and between mood and cognition.4 

Sleep disturbances are also highly prevalent (42%–65%) in patients with MS.5  In one study,6  49% of participants reported insomnia, characterized by problems such as difficulty falling asleep or getting up in the morning and nighttime awakenings. In another study,7  32.7% of participants complained of sleep-related movement disorders such as restless legs syndrome. Sleep-related breathing disorders, such as obstructive sleep apnea, have similarly been observed, reported by 37.8% of participants in 1 study.8 

Considering the close relationship between pain, mood, and physical disability in patients with MS, how do each of these comorbidities contribute to sleep problems in MS? It is known that pain and mood disorders, ie, depression and anxiety, may cause sleep disturbances.8,9  One study observed an association between pain and sleep in patients with MS, but pain was not included as an independent variable in a regression analysis.10  Consequently, there was no information about how much of the sleep variance was explained by pain. In the same study, pain had a significant relationship with mood when sleep was assessed by means of the Pittsburgh Sleep Quality Index (PSQI), a self-report covering sleep-related issues and daytime functioning. In another study,11  patients with MS who self-reported sleep disturbances had significantly higher scores on anxiety and depression than those who indicated sleeping well. Sarraf and colleagues12  observed a relationship between physical disability, measured by the Expanded Disability Status Scale (EDSS), and sleep, assessed by the PSQI. Vitkova et al13  suggested that such a relationship might also be indirect, mediated by depression. They also assessed sleep by means of the PSQI.

Although the studies noted previously herein, and many more, use the PSQI, a more objective method to assess sleep is actigraphy. Actigraphy assesses the rest-activity rhythm, an indirect measure of the sleep-wake rhythm.14  Actigraphy facilitates insight into 3 clinically relevant variables: interdaily stability (IS), intradaily variability (IV), and relative amplitude (RA) (for further details, see the Methods section). One study found no differences in those 3 variables between patients with MS (n = 16) and controls (n = 16).15  In another study, 3 of 15 patients with MS had a circadian rhythm disturbance: Two patients had a delayed sleep phase and 1 patient displayed an irregular sleep phase.16  These findings might suggest that circadian rhythm disturbances are not a clinical hallmark of MS. On the other hand, the number of participants in each study is relatively small and, overall, there is a dearth of studies assessing the rest-activity rhythm in MS. Moreover, the 3 actigraphy variables–IS, IV, and RA–have not been examined in relation to pain, mood disturbances, or physical disability in MS. The goal of the present cross-sectional study is to investigate whether there is a positive relationship between pain, mood, physical disability, and the rest-activity rhythm—IS, IV, and RA—in patients with MS.

Participants

The original total sample consisted of 61 patients with MS, 26 men and 35 women. Twenty-eight patients lived in a center that specialized in MS and other neurodegenerative disorders (ie, Nieuw Unicum, Zandvoort, the Netherlands), and 33 patients lived in their own homes. Of these 61 patients with MS, 46 (17 men, 29 women) experienced pain and 15 (9 men, 6 women) did not. Of the 46 patients with pain, 19 were from Nieuw Unicum and 27 were still living in their own homes. For each patient, a diagnosis of MS and the specific subtype, according to the criteria of either Poser et al17  or McDonald et al,18  was made by an MS neurologist. The Mini-Mental State Examination (MMSE)19  was used to assess patients’ global cognitive functioning (maximum score = 30). Level of education was scored as follows20 : elementary school not finished (score = 1), elementary school finished (score = 2), more than 6 classes elementary school (score = 3), education but did not complete secondary school (score = 4), secondary school (score = 5), higher secondary school (score = 6), higher vocational training for age 18 years and older/university (score = 7).

From the medical records, we registered chronic comorbidities that existed in the 6 months before the time of assessment and actual comorbidities that existed at the assessment. Conditions causing pain for the cohort were, among others, arthrosis/rheumatoid arthritis, musculoskeletal disorders (eg, neck-shoulder pain), osteoporosis, and peripheral neuropathy.

We listed the following analgesics in the study: baclofen, paracetamol, diclofenac, naproxen, ibuprofen, and cannabis. Medication that could be prescribed for sleep enhancement was registered.

Patients were excluded from the study if they had a history of neoplasms, cerebral traumata, alcoholism, normal pressure hydrocephalus, and/or psychiatric and neurologic disorders with an etiology other than MS.

The local medical ethics committee approved the present study. After being extensively informed about the study’s processes and goals, the patients were asked to provide oral and written consent. We emphasized that the patient was completely free to withdraw from the study at any point.

Rest-Activity Rhythm Assessment

Rest-activity rhythm was assessed by means of actigraphy. Participants wore an Actiwatch (Cambridge Neurotechnology Ltd) around their wrist like a watch. The Actiwatch objectively records the intensity, amount, and duration of arm movements in episodes of 1 minute, during at least 5 consecutive days and nights, ie, at least 120 hours. The total time that participants wore the Actiwatch ranged from 141 to 193 hours.

The following dependent variables were assessed: (1) IV, which measures the fragmentation of the rhythm within 24 hours, ie, the transitions between periods of activity and rest continuity; a high value means an unstable rhythm within a single day; (2) IS, which assesses the (in)stability of the rhythm between days; the higher the value the more the stability between the days; and (3) RA, which assesses the relative difference between a participant’s maximal rest (normally at night) and maximal activity (normally during the day).

Pain Assessment

During testing, various scales were used to assess pain according to 4 domains: pain intensity, pain affect, mood, and physical disability.

Pain Intensity

Color analog scale.21  The color analog scale (CAS) was used to assess pain intensity (CAS Intensity) and the affective aspects of pain (CAS Affect) (0 = no pain, 10 = severe pain).

Faces Pain Scale.22  The Faces Pain Scale is composed of 7 faces expressing different levels of pain, ranging from no pain (score 0) to severe pain (score 7). The scores of the 2 scales were converted to z scores. This resulted in a Cronbach α of 0.79. Subsequently, we added the z scores and to create a pain intensity domain.

Pain Affect

CAS Affect.21  See above.

Number of Words Chosen-Affective.23  The McGill Pain Questionnaire (Dutch version) also encompasses an affective pain scale, reflected in 5 groups of words that appeal to the affective aspects of pain (0 = no suffering, 15 = high suffering). The scores of the 2 scales were converted to z scores. This resulted in a Cronbach α of 0.68. Subsequently, we added the z scores to create a pain affect domain.

Mood

The Beck Depression Inventory (BDI)24,25  was administered to assess depression (minimum score = 0, maximum score = 63), and the Symptom Checklist-90 (SCL-90) was used to assess anxiety (minimum score = 0, maximum score = 40)26  and depression (minimum score = 0, maximum score = 52).27  The scores of these 3 subscales were converted to z scores. This resulted in a Cronbach α of 0.87. Subsequently, we added the z scores to create a mood domain.

Physical Disability

Physical disability was assessed using the EDSS.28  The EDSS score ranges from 0 (no disability) to 10 (death due to MS).29  The EDSS addresses physical disabilities and is not a suitable tool for assessing cognitive functioning.30,31 

Procedure

The principal investigator (R.J.S.) taught 2 students the study protocol and trained them to administer the EDSS, the BDI, and the pain scales and to use the Actiwatch.

Data Analyses

IBM SPSS-PC Statistics, version 26.0 (IBM Corp) was used for data analysis. Because only 1 group of patients with MS was studied, we compared the mean MMSE, education, pain, depressive symptom, and EDSS scores with the maximum score of each scale. Pain medication use is presented as a percentage, and the relationship between pain and pain medication as a correlation (partial r).

The main research question, ie, the relationships among pain, motor abilities, mood, and the rest-activity rhythm, was analyzed by 4 hierarchical regression analyses. The dependent variables were IS, IV, and RA. Four models were applied: mood (model 1), pain intensity (model 2), pain affect (model 3), and EDSS (model 4). The level of significance was set at P < .05.

Demographics

Of 61 patients with MS (26 men, 35 women) who participated in the study, 6 had relapsing-remitting diagnoses, 25 had primary progressive diagnoses, 28 had secondary progressive diagnoses, and 2 had undetermined courses. The mean ± SD age of the participants was 55.54 ± 9.33 years, with the range from 29 to 71 years. The mean ± SD MMSE score of the patients was 27.15 ± 3.24 (range, 16–30), and the mean ± SD level of education was 5.41 ± 0.97 (range, 2–7).

We listed comorbidities that were present in the 6 months before the assessment (chronic) (TABLE S1, available online at IJMSC.org) and at the assessment (actual). At the time of assessment, 1 patient had a urinary tract infection and 1 patient had a pressure ulcer.

The cohort’s mean ± SD scores on the various pain scales are presented in TABLE 2 The mean scores on each of the separate pain scales suggest that the patients with MS had mild pain (TABLE S2). The number and percentage of the group using analgesics are presented in TABLE S3. After controlling for mood, the relationship between total pain (adding the z scores of all separate pain scales) and total pain medication (adding all pain medications) was not significant (partial r = 0.15, P = .32). Concerning the relationship between separate pain medications and pain, a significant positive relationship was observed between total pain and cannabis, once controlled for mood (partial r = 0.32, P = .037).

TABLE 2.

Predicting Interdaily Stability With Mood, Pain Intensity, Pain Affect, and Motor Activity in Patients With Pain

Predicting Interdaily Stability With Mood, Pain Intensity, Pain Affect, and Motor Activity in Patients With Pain
Predicting Interdaily Stability With Mood, Pain Intensity, Pain Affect, and Motor Activity in Patients With Pain

One patient each used temazepam (a benzodiazepine) combined with melatonin, temazepam combined with modafinil (treatment for narcolepsy), zopiclone, and zopiclone combined with melatonin.

The cohort had mean ± SD mood scores of 10.26 ± 6.60 (range, 1–29) on the BDI, 13.07 ± 3.97 (range, 10–26) on the SCL-90 Anxiety, and 24.82 ± 9.13 (range, 14–51) on the SCL-90 Depression; the mean ± SD EDSS score was 7.00 ± 1.23, with a range from 3 to 9 (maximum score = 10). The 3 main variables (IS, IV, RA) had mean ± SD values as follows: IS, 0.67 ± 0.25 (range, 0.08–0.95); IV, 0.58 ± 0.31 (range, 0.10–1.60); and RA, 0.71 ± 0.20 (range, 0.04–1.00).

Relationship Between Pain, Motor Abilities, Mood, and Rest-Activity Rhythm

Interdaily Stability

The percentage of explained variance of the scores on IS by model 4, including mood, pain intensity, pain affect, and the EDSS as predictors, was 12% and showed a trend (P = .06). None of the separate predictors significantly contributed to the explained variance of 12% (TABLE 1).

TABLE 1.

Predicting Interdaily Stability With Mood, Pain Intensity, Pain Affect, and Motor Activity

Predicting Interdaily Stability With Mood, Pain Intensity, Pain Affect, and Motor Activity
Predicting Interdaily Stability With Mood, Pain Intensity, Pain Affect, and Motor Activity

Intradaily Variability

None of the models significantly explained variance of the scores on IV (TABLE S4).

Relative Amplitude

None of the models significantly explained variance of the scores on RA (TABLE S5).

Subgroup Analysis Including Only Patients With MS With Pain

Considering that only the whole-group IS data (including 15 patients without pain) showed a trend (P = .06), we reanalyzed the data on IS exclusively with patients with MS who were in pain (n = 46).

The data analysis shows that model 4, including mood, pain intensity, pain affect, and the EDSS as predictors, explained 19% of the variance of the IS. Similar to the whole-group analysis, none of the separate predictors contributed significantly to the explained variance of 19% (TABLE 2).

The cohort experienced mild pain (see mean scores), a finding similar to another study.32  In contrast, Ayache and colleagues33  observed that their cohort of patients with MS with neuropathic pain had a mean score of approximately 50 on a visual analog scale (scores range from 0 to 100). In comparison, in the present study the CAS Affect mean score was 2.63 and the CAS Intensity mean score was 3.09. Even higher visual analog scale scores (>70) were observed in patients with MS with “pain” (not further specified) in another study.34  An explanation for this discrepancy is that 3 of the 4 scales used were unidimensional visual analog pain scales. It has been argued that this type of pain scale is more appropriate for acute pain.35  Assessment of complex chronic pain, characteristic of MS, requires multidimensional pain scales.36  We applied only 1 multidimensional pain scale, the Number of Words Chosen-Affective.36 

Because the present cohort experienced mild pain, analgesics were not prescribed for each patient, which explains the lack of a significant relationship between pain and pain medication in general. The only significant relationship was between pain and the use of cannabis. Although prescribing cannabis for chronic pain in MS is becoming increasingly popular, firm conclusions about its analgesic effectiveness warrant further longitudinal studies of high quality, eg, the dosage of cannabis should become more standardized.37 

Only a few patients used sleep medication. The limited prescription of sleep medication reflects the relatively preserved rest-activity rhythm of the present group of patients.

The mean scores on the BDI and the SCL-90 suggest that the cohort had a minimal to mild level of depression and anxiety. The mean scores on the BDI and the SCL-90 agree with those in other studies.4,25 

The present participants had a mean ± SD EDSS score of 7.07 ± 1.23 (range, 3–9). In comparison, the cohort of patients with MS with neuropathic pain described by Heitmann et al38  had a mean EDSS score of 3.3.

One might expect the mean values of all 3 actigraphy variables of patients with MS to deviate from the mean values of persons without MS.5  Such a deviation would imply lower mean values for IS and RA and a higher mean value for IV. Of note is that IS has a negative relationship with IV, ie, the higher the IS, the lower the IV. Remarkably, the present patients show a higher IS/lower IV (mean = 0.66 and 0.59, respectively) than persons without MS (age >50 years): mean IS, 0.57; mean IV, 0.81.39  Similar findings were observed in another study that included adults (mean age, 52 years) living in their own homes: mean IS, 0.53; mean IV, 0.89.40  Compared with the previously mentioned studies, in the present study, the actigraphy variables IS and IV had the highest and lowest values, respectively, indicating a more stable rest-activity rhythm between days and a lower fragmentation of the rhythm with each 24 hours.

A possible explanation is related to the physical condition of the patients. The decline in physical abilities might limit the amount and variation of the daily activities of people with MS. The more severe the decline in physical abilities, the more care might be needed. It has been suggested that the more intensive the care patients need, the more stable the rest-activity rhythm.39  The mean EDSS score of 7.07 in the present patients with MS indicates serious physical disabilities, irrespective of housing (home and/or institution; data not shown). Consequently, the rest-activity rhythm within each day (IV) and between several days (IS) has become more similar over the course of the disease. This suggestion has also been made by researchers investigating the rest-activity rhythm of Korean patients with dementia.41 

In the present study, the mean RA of the cohort of patients with MS (0.73) was lower than that of persons without MS (0.9239  and 0.7840 ). Because RA reflects the difference between maximal physical activity and maximal rest, it seems quite logical that due to patients’ physical disability, the difference between maximal physical activity and maximal rest has become smaller.

The main research question of the present study concerned the relationship between pain, motor abilities, mood, and the rest-activity rhythm. The first main finding of the present study was that the 12% of the variance of the IS scores of the whole group (patients with MS with and without pain) was explained by only a combination of mood, pain intensity, pain affect, and the EDSS as predictors in model 4 (a trend; P = .06) (Table 1). In that model, pain intensity and EDSS were the strongest predictors; both showed a trend (P =.06).

Next, we reanalyzed the relationship between pain, motor abilities, mood, and the rest-activity rhythm in only patients with MS experiencing pain. Data analyses showed that model 4 significantly explained 19% of the variance in IS scores and that pain intensity and EDSS in model 4 became significant predictors (Table 2). In other words, the combination of pain intensity and motor dysfunctions explained 19% of the variance.

How can we understand these findings? First, the finding that the prediction of IS by model 4 over the whole group (including those without pain) showed a trend (P = .06), whereas the prediction by model 4 was significant (P = .04) over the smaller “only pain” group. An explanation might be as follows. We hypothesized that pain would be one of the variables that might disturb the rest-activity rhythm. By adding a relatively large group (n=15) of MS patients without pain to a whole group analysis, it is quite logical that the prediction of IS by model 4 became somewhat less strong (P = .06).

Concerning pain, only pain intensity is the (nearly) significant predictor in model 4 in both groups. Subsequently, we analyzed only the data of the CAS Intensity scale, not the Faces Pain Scale, because this scale has a pain score ranging from 0 to 10, enabling us to make pain subgroups, ie, no pain (score = 0), mild pain (score = 1–3), moderate pain (score = 4–7), and severe pain (score = 8–10). As presented in TABLE S6, a nonlinear association between pain and the rest-activity was indeed observed for IS. The mean IS scores of those without pain and those with the most severe pain were the highest (0.70 and 0.79, respectively). More pain might imply more care, and, as mentioned previously herein, more care might result in a more stable rhythm between various days (ie, IS).39  In addition, compared with IV and RA, IS seems to be a strong indicator for the 24-hour rest-activity rhythm and can be affected by neurologic disorders and lifestyle.42  More specifi-cally, physical functioning (Functional Assessment Staging Scale, Reisberg),43  mood (Cornell Scale for Depression in Dementia),44  and activities of daily living (Nurse Informant Index of Activities of Daily Living)45  were most strongly and positively related to IS compared with IV and RA.46  Participants in the study by Carvalho-Bos46  were institutionalized older persons with dementia. Compared with IV and RA, IS also seems to have a stronger relationship with pain intensity in patients with spinal cord injury47  and with neuropathy in patients with diabetes.16 

A limitation of the present study might be that the group of patients with MS lived both in their own homes and in an institution. This difference in housing might imply a difference in variables that were included in the main research question of the present study: mood disturbances, pain intensity, pain affect, and the EDSS. Except for mood disturbances, which were significantly higher in those who lived in their own homes, the 2 groups did not differ significantly in pain intensity, pain affect, IS, IV, RA, or total comorbidity (data not shown). The similarity between the groups is also reflected in the fact that those who still lived in their own homes received professional care from the institution that housed the other members of the cohort. Another limitation is that the level of disability was high in the present patients, limiting the generalizability of the results.

In conclusion, the present findings suggest that to effectively treat sleep disturbances in patients with MS, clinicians should pay attention to the combination of mood disturbances, pain, and physical disability. A positive relationship between mood, pain, and the rest-activity rhythm might imply that a more adequate treatment of, eg, pain and/or mood disturbances, might regulate the sleep-wake rhythm of patients and consequently improve their quality of life.48 

PRACTICE POINTS
  • Mood disturbances, pain, and physical disability affect rest-activity rhythm (ie, interdaily stability) in people with multiple sclerosis.

  • To effectively treat sleep disturbances in people with multiple sclerosis, clinicians should pay attention to the trio.

The authors are most grateful to all the study participants and to the team at Nieuw Unicum, Zandvoort, the Netherlands.

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FINANCIAL DISCLOSURES: The authors declare no conflicts of interest.

FUNDING/SUPPORT: None.

Author notes

Note: Supplementary material for this article is available at IJMSC.org

Supplementary Material