Vina, Ernest R. MD, MSc*†; Green, Stephanie L.‡; Trivedi, Tarak§; Kwoh, C. Kent MD*†; Utset, Tammy O. MD, MPH‡
Systemic lupus erythematosus (SLE) is a systemic autoimmune disease that has been associated with poor health-related quality of life (HRQoL) outcomes, most commonly measured using the Medical Outcomes Study (MOS) Short Form 36 (SF-36).1–8 Even though the SF-36 and other HRQoL measures can provide insight into the impact of the disease on the physical, mental, and social aspects of patient health and quality of life, these measures do not include aspect or score for such factors as insomnia or other sleep abnormalities.1,6,9 Yet, chronic sleep disruptions may have detrimental effects on life expectancy and health. Shortened and extended sleep times are associated with increased mortality hazard.10 Sleep loss may deregulate immune responses and can lead to increased susceptibility to infections.11 Sleep abnormalities may significantly impact fatigue.12,13 And, sleep disorder is a common complaint in patients with SLE.12–14
Poor sleep quality has been reported in 56% to 60% of lupus patients.13,14 Compared with healthy women, SLE patients have been found to have longer sleep latencies and more frequent sleep disturbances due to pain and vegetative symptoms, such as breathlessness.12,15 Sleep of SLE patients has also been characterized by respiratory disturbance and movement disorders.16 In animal models of lupus, sleep fragmentation and increased microarousals are associated with severe phases of the disease.17 Early studies that addressed sleep in lupus, though, used unstandardized or infrequently used measures.12,15 Others evaluated sleep using polysomnography along with questionnaires in very small cohorts of lupus patients.16,18
Studies of the determinants of sleep quality in lupus have also been conflicting.13,19 When demographic factors, disease characteristics, functional disability, pain, levels of exercise, and depressed mood were regressed on a global sleep quality index (i.e., the Pittsburgh Sleep Quality Index [PSQI]), depressed mood appeared as an independent determinant of sleep quality.13 In a study of similar methodology, though, only disease activity was a significant correlate of sleep quality.19 Yet, correctly identifying the specific modifiable factors associated with sleep quality will allow the development of interventions aimed at improving sleep quality in SLE.
The MOS Sleep Scale is a comprehensive measure that describes 6 pertinent domains of sleep quality. It has been well validated, carries a low administrative burden, and is endorsed by the OMERACT (Outcome Measures in Rheumatology).20 It also has 2 important advantages over the PSQI.21 It has a validated dimension for sleep disturbance alone, a key assessment for patients with pain. It also contains fewer items than the PSQI, which contains questions that request the evaluation of the patient’s roommate or bed partner. The MOS Sleep Scale has been used to assess sleep quality in fibromyalgia,22,23 rheumatoid arthritis,24 and systemic sclerosis25 patients, but not in lupus patients. The objectives of this study are (1) to characterize sleep quality using the MOS Sleep Scale in SLE patients compared with the general population and (2) to determine the clinical and psychological factors associated with the individual MOS Sleep subscale scores as well as the overall sleep quality in SLE patients.
MATERIALS AND METHODS
Patients who received their usual lupus care in the University of Chicago Rheumatology Clinic were recruited during clinic visits from June 2008 through September 2009. Only those who fulfilled the American College of Rheumatology (≥4 of 11) SLE criteria were included. The following were exclusion criteria: age younger than 18 years and inability to fill out a self-administered standardized survey, based on physician-observed cognitive skills. Institutional review board approval and participants’ informed consents were obtained.
In this cross-sectional, observational study, patients were asked to complete self-administered surveys. The following information was obtained:
MOS Sleep Scale
The 12-question MOS Sleep Scale20 is a self-report questionnaire that determines sleep quality and quantity based on patients’ experience during the past 4 weeks. For 10 of the 12 MOS Sleep Scale questions, patients were asked to report how often each particular sleep symptom or problem was applicable to them on a 6-point ordinal scale ranging from “all of the time” to “none of the time.” Question about time to fall asleep used a 5-point categorical response scale ranging from “0 to 15 minutes” to “more than 60 minutes.” Quantity of sleep was the average number of hours of sleep patients reported per night.
Patients’ responses were aggregated into the MOS Sleep subscale scores based on the published scoring algorithm.20 The 6 subscale scores, based on a varying number of items, included sleep disturbance (4 items), sleep adequacy (2 items), daytime somnolence (3 items), snoring (1 item), awakening with shortness of breath (SOB) or with headache (1 item), and quantity of sleep (1 item). The first 5 subscales were scored on a 0-to 100-point possible range, and higher scores indicated more of the concept being measured. For instance, a higher sleep disturbance subscale score indicates more problems initiating or maintaining sleep, whereas a higher sleep adequacy score reflects more adequate sleep. The Sleep Problems Index (SPI) provides a summary measure of the different types of sleep problems, using 5 of the 6 subscales (except sleep quantity), and is scored on a 0- to 100-point possible range. All subscales and the SPI score relate to a poorer HRQoL (except for sleep adequacy, where higher score relates to better HRQoL).
For comparison of our SLE group with the US general population, we used the study of Hays et al.26 This study administered the MOS Sleep measure by telephone to a nationally representative sample of 1011 US adults 18 years or older. The observations were weighted by age, gender, race, education, number of adults, and number of voice/telephone lines in the household to reflect the adult US population.
The following demographic information was collected: age (number of years), gender (female, male), race/ethnicity (African American, White, Hispanic, Asian American, other), and educational attainment (number of years).
A standardized form was used to extract the following data from each patient’s medical record: 10-day SLE Disease Activity Index (SLEDAI),27 Systemic Lupus International Collaborating Clinics (SLICC) Damage Index,28 involvement of specific SLE-related organ systems, daily prednisone dosage at the time of the survey (in milligrams) and body mass index (BMI). Patients were categorized into the following World Health Organization BMI categories: underweight, less than 18.5 kg/m2; normal, 18.5 to less than 25 kg/m2; overweight, 25.0 to less than 30 kg/m2; and obese, 30 kg/m2 or greater. Pain over the past week was determined using a 10-cm visual analog scale (VAS).29
Psychological characteristics and traits were also measured. The Beck Depression Inventory (BDI; range, 0–63)30 is a 21-item self-report questionnaire. Patients were asked to report how much each particular feeling or thought described them in the last 7 days using a 4-point ordinal scale ranging from 0 to 3. Generally, a score of less than 9 indicates no or minimal depression; 10 to 18, mild-to-moderate depression; 19 to 29, moderate-to-severe depression; and greater than 30, severe depression. Each patient’s current State Trait Anxiety Inventory (STAI; range, 20–80)31 score was also measured. The trait anxiety scale, instead of the state anxiety scale, was specifically used for this study. The STAI is a 20-item measure in which patients were asked how often they generally felt with each statement that may describe them. Answers were based on a 4-point ordinal scale ranging from “almost never” to “almost always.” A cutoff point of 39 to 40 is normally used for clinically significant symptoms of a state of anxiety.32,33 Higher BDI and STAI scores indicate more symptoms.
The mean and SD of the MOS Sleep subscale scores for SLE patients and the US general population26 were compared using a 2-sample t test.
Bivariate correlations of each of the 6 MOS Sleep subscale were determined using a Pearson correlation matrix with each of the following variables: age, years in school, BMI, SLEDAI, SLICC Damage Index, involvement of specific SLE-related organ systems, daily prednisone dosage, pain scale score, BDI, and STAI. Effect sizes of correlations were considered small if |r| ≤ 0.29, moderate if 0.30 ≤ |r| ≤ 0.49 and large if |r| ≥ 0.50.34
To determine the sociodemographic (age, race/ethnicity, and gender), clinical (BMI, SLEDAI, SLICC Damage Index, daily prednisone dosage, pain scale score), and psychological variables (BDI and STAI) associated with each MOS Sleep subscale score, linear regression analyses were performed. Variables were chosen based on variables associated with sleep quality in SLE and other rheumatologic diseases in other studies.13,19,25 Final multivariate linear regression models were selected using stepwise forward selection (P < 0.20).
A series of hierarchical multiple regression analyses were also conducted to determine the importance of clinical and psychological factors to overall sleep problems (i.e., SPI) after controlling for demographic factors. Hierarchical multiple regression is the regression strategy of choice when the goal is to determine the importance of a predictor variable(s) once other predictor variables have already been entered into the equation.34 Each hierarchical regression analysis determined whether the variance explained by the specific set (i.e., clinical or psychological) contributed significantly to the total variance in SPI, adjusted for demographic variables. The increment in R2 was tested for statistical significance.35 To be parsimonious, only theoretically relevant variables and variables shown to be significantly correlated to the SPI were included in the models.
P < 0.05 was considered statistically significant. All analyses were performed using Stata version 12.0 (StataCorp LP, College Station, TX).
A total of 192 SLE patients initially consented to participate in the study. One hundred twenty-one returned the self-administered paper surveys that were provided (see online Supplement 1, http://links.lww.com/RHU/A25). Data from 118 patients who completed the MOS Sleep survey were evaluated.
Respondents’ sociodemographic and clinical characteristics are shown in Table 1. Mean age was 45.5 years; 91.5% were women, and 36.4% were white. The majority were either overweight (28.8%) or obese (31.5%), according to World Health Organization criteria. The mean SLEDAI score was 3.9, and the mean daily prednisone dosage was 10.9 mg. Mean BDI and STAI scores were 11.3 and 40.8, respectively.
The representative US population had an average age of 46 years (range, 18–94 years); 51% were female, and 81% were white.26 The Figure shows the comparison of the MOS Sleep subscale scores between SLE patients and the representative US population. Compared with this sample of the US population, SLE patients’ mean (SD) scores were higher with regard to sleep disturbance (45.3 [SD, 28.8] vs 24.5 [SD, 23.5], P < 0.0001), awakening with SOB or headache (21.4 [SD, 29.1] vs 9.5 [SD, 19.2], P < 0.0001), and daytime somnolence (35.8 [SD, 21.5] vs 21.9 [SD, 19.5], P < 0.0001). On the other hand, SLE patients’ scores were lower in the following subscales: sleep adequacy (39.9 [SD, 24.0] vs 60.5 [SD, 30.0], P < 0.0001) and sleep quantity (6.3 [SD, 1.7] vs 6.8 [SD, 1.4], P = 0.0027). Finally, the overall SPI was markedly higher among SLE patients when compared with the general population (44.6 [SD, 20.5] vs. 25.8 [SD, 18.6], P < 0.0001).
FIGURE. Mean MOS Sle...Image Tools
MOS Sleep Subscales: Correlates
Table 2 shows the significant correlations between each of the 6 MOS Sleep subscale and the sociodemographic, clinical, and psychosocial variables of interest.
Number of years in school had a small negative correlation with sleep disturbance and daytime somnolence and a small positive correlation with sleep quantity (r = −0.25, −0.20, 0.21, respectively, all P < 0.05).
Body mass index had a small positive correlation with snoring and awakening with SOB or headache, and a small negative correlation with sleep quantity (r = 0.24, 0.26, −0.23, respectively, all P < 0.05). Systemic Lupus Erythematosus Disease Activity Index did not significantly correlate with any of the specific MOS Sleep domain. Systemic Lupus International Collaborating Clinics Damage Index had a small positive correlation with snoring (r = 0.19, P < 0.05) but did not significantly correlate with the other sleep subscale scores. Pain, measured using a VAS, significantly correlated with all 6 subscales. It had a large correlation with awakening with SOB or headache (r = 0.52, P < 0.0001) and a moderate correlation with sleep disturbance and daytime somnolence (r = 0.40, 0.34, respectively, all P < 0.01).
Most organ manifestations of SLE had no significant correlation to the MOS Sleep subscale scores, but there are a few exceptions. Having serositis had a small positive correlation with awakening with SOB or headache (r = 0.23, P = 0.0141). Having Sjögren syndrome–like symptoms had a small positive correlation with sleep disturbance (r = 0.28, P = 0.0023). Having neurological/psychological disease had a small to moderate positive correlation with sleep disturbance, awakening with SOB or headache, and daytime somnolence (r = 0.34, 0.32, 0.29, all P < 0.01).
Depression (BDI) also had a moderate correlation with 5 of 6 scores: sleep disturbance, snoring, awakening with SOB or headache, sleep adequacy, and daytime somnolence (r = 0.39, 0.32, 0.37, −0.40, and 0.40, respectively, all P < 0.01). Anxiety (STAI) had a significant moderate correlation with 4 subscale scores: sleep disturbance, snoring, awakening with SOB or headache, and daytime somnolence (r = 0.32, 0.38, 0.38, and 0.43, respectively, all P < 0.01).
MOS Sleep Subscales: Regression Models
The most significant variables associated with each MOS Sleep subscale measure, based on multivariate linear regression, are shown in Table 3. Sleep disturbance score was positively associated with the BDI score (β = 0.80, P = 0.017). Snoring was strongly associated with the following variables: anxiety (STAI) score (β = 1.64, P < 0.001) and age (β = 0.81, P = 0.004). Awakening with SOB or headache was positively associated with the pain VAS score (β = 0.45, P < 0.001). Sleep adequacy was negatively associated with depression (BDI) (β = −0.84, P = 0.002) and positively associated with nonwhite race/ethnicity (β = 10.52, P = 0.042). Daytime somnolence was strongly and positively associated with STAI score (β = 0.81, P < 0.001) and daily prednisone dosage (β = 0.54, P < 0.001).
MOS Sleep Problems Index
Each of the following variables had a significant but small correlation with the SPI: years in school and BMI (r = −0.22 and 0.25, respectively, all P < 0.05). Among all organ system manifestations related to SLE, only having a neurological/psychological disease moderately correlated with the SPI (r = 0.41, P < 0.0001). State Trait Anxiety Inventory also had a moderate positive correlation with SPI (r = 0.48, P < 0.0001). Each of the following variables had a significant and large correlation with the SPI: pain VAS and BDI scores (r = 0.49 and 0.53, respectively, all P < 0.0001).
Results of the hierarchical multiple regression analyses with SPI as the dependent variable are shown in Table 4. The first model assessing the contribution of sociodemographic factors to sleep problems was statistically not significant (F3,107 = 2.58, R2 = 0.0675, P = 0.0571). The addition of clinical variables (model 2) resulted in a significant increase in the R2 value (F8,72 = 3.58, R2 = 0.2375, P = 0.0092). The pain VAS score was significantly associated with the SPI score (P = 0.003). The addition of psychological variables (model 3) also contributed to the demographic set (F5,105 = 8.79, R2 = 0.2950, P < 0.0001). In this model, BDI score was significantly associated with higher sleep problems (P = 0.001). Finally, the full model (model 4) with all variables entered is shown in Table 4. Pain VAS trended toward association with the SPI score (P = 0.078), when controlled for demographic, clinical, and psychological variables.
In general, the MOS Sleep subscale scores of SLE patients were substantially poorer than the general population normative scores in the United States. Specifically, SLE patients were more likely to have sleep disturbance, awakening with SOB or headache, and daytime somnolence. They were also less likely to have sleep adequacy and slept less at night. Our study is the very first to evaluate the multiple dimensions of sleep identified by the MOS20 in a diverse group of SLE patients.
More recently, sleep quality was assessed in lupus cohorts using the PSQI.13,14,19,36–39 Similar to our findings, SLE patients were found to have worse sleep quality than comparison groups.13,19,36 Both MOS Sleep Scale and PSQI have documented reliability and validity.20,25,26,40 The MOS Sleep Scale, though, has important advantages over the PSQI.21 The MOS Sleep Scale has unique, psychometrically validated scores for each identified sleep domain.26 The PSQI has multiple domains, but its components appear to measure a particular aspect of the same overall construct, sleep quality.40 It has also been suggested that the PSQI factor structure may actually be best represented by 3 related factors rather than a single global score.41 Finally, the MOS Sleep Scale is shorter and may be less burdensome for patients to fill out than the PSQI.21
The variables associated with the multiple dimensions of the MOS Sleep Scale were found to be multifactorial, and their contributions varied. Comparison of the results of our study and other studies that also examined the factors associated with sleep in SLE is shown in Supplement 2, http://links.lww.com/RHU/A25. Older age weakly but significantly correlated with snoring in lupus patients. Nonwhite race/ethnicity was positively associated with sleep adequacy and trended toward a negative association with snoring. These results are in agreement with previous reports associating older age and white race/ethnicity with snoring.42–44
In comparison, lupus-specific clinical variables mildly contributed to SLE patients’ sleep quality and quantity. Daily prednisone dose was positively associated with daytime somnolence, possibly because of steroid therapy interfering with the normal pattern of diurnal cortisol production.45 Upon further evaluation, we also found a positive dose effect of prednisone dosage on daytime somnolence (data not shown). However, there was no significant relationship between daily prednisone dosage and other MOS Sleep domains, similar to what other studies have found.12–14,16,19 In addition, SLEDAI neither correlated, nor was it significantly associated, with any of the MOS Sleep Subscale measures. In contrast, Systemic Lupus Activity Measure–Revised score has positively correlated with PSQI score in other studies.13,19 As only ambulatory care clinic patients were recruited in our study, there may not have been enough variation in SLEDAI score in our sample to appropriately explain the variation in the sleep subscale scores.
Pain severity in SLE patients significantly correlated with all MOS Sleep subscales and the overall SPI. Similar bivariate relations have been found between pain and PSQI scores.13,14,19 In our multivariate regression models, pain had a significant relationship only with awakening with SOB or headache. Similarly, when controlled for multiple other variables, pain intensity has not been a significant determinant of the global PSQI score.13,19 Yet, Gudbjörnsson and Hetta12 demonstrated that those with SLE, compared with controls, reported more frequent sleep disturbances due to pain and more frequent awakenings due to headache.
Our study also demonstrated the significance of psychosocial variables in determining sleep quality. The mean BDI scores of our respondents were comparable to scores found by others.46,47 Depression moderately and significantly correlated with nearly all MOS Sleep subscale scores. It was also independently associated with sleep adequacy. The relationship between depression and respiratory abnormalities during sleep in SLE has been demonstrated using polysomnography.16 Depressed mood has also been identified as the single most important determinant of the PSQI score in SLE.13 Chandrasekhara et al19 found a correlation between depression and lupus disease activity, but disease activity was the most significant predictor of the PSQI in the authors’ study. Furthermore, depression has been shown to explain a significant amount of the variance of the MOS Sleep scores in a large sample of patients with rheumatoid arthritis48 and in patients with systemic sclerosis.25 Our data, in summary, support depression as a significant mediator of sleep adequacy in SLE.
Anxiety, on the other hand, had a moderate correlation with 4 MOS Sleep subscale measures. It was also significantly related to snoring and daytime somnolence. Considering the cross-sectional study design of our study, it is, however, difficult to determine the directionality of the association between anxiety and these 2 sleep subscale measures. Anxiety may lead to increased sleep disruption, yet poor sleep may also trigger anxiety. Nonetheless, the PSQI overall score has been known to correlate with anxiety in a sample of SLE patients.14 In other study populations, anxiety and prevalence of manic and hypomanic episodes have also been associated with excessive daytime sleepiness.49,50
To some degree, our study is limited by our cross-sectional study design. Certain aspects of sleep may determine pain level, depression, and anxiety trait, rather than the other way around. Longitudinal studies of SLE and sleep quality need to be conducted. We were also able to recruit patients only from a single academic, urban institution, and only nonhospitalized patients were asked to participate. Administration of the MOS Sleep survey to patients in other institutions and clinical settings may contribute to the generalizability of our findings. As gender-, age-, and race/ethnicity-stratified MOS Sleep scores of the general population are not readily available in the literature, we were also not able to compare our study group to a gender-, age-, and race/ethnicity-comparablereference group. However, MOS Sleep subcale scores of this general population sample have been directly compared with sleep scores of patients with fibromyalgia and scleroderma who are predominantly female.22,25
Our study documents a high frequency of sleep disturbance in respondents with SLE. Sociodemographic, clinical, and psychosocial factors that contributed to poor sleep quality in lupus, though, were highly dependent on the sleep characteristic being measured. In particular, psychological variables were found to be strongly and independently related to snoring, sleep adequacy, and daytime somnolence. Interestingly, daily prednisone dosage was also positively associated with daytime somnolence. More studies are necessary to delineate the remaining variables associated with these specific sleep domains and their directionality in relationship to affective symptoms in SLE patients. By doing so, we can better design and establish the interventions necessary to improve sleep quality in SLE.
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