Race and Financial Strain are Independent Correlates of Sleep in Midlife Women: The SWAN Sleep Study

Study Objectives:

To examine racial differences in sleep in a large cohort of midlife women and to evaluate whether indices of socioeconomic status (SES) are associated with racial differences in sleep.

Design:

Cross-sectional study.

Setting:

Participants'' homes.

Participants:

Caucasian (n = 171), African American (n = 138) and Chinese women (n = 59).

Interventions:

None.

Measurements:

Sleep quality was assessed with the Pittsburgh Sleep Quality Index. Polysomnographically assessed sleep duration, continuity, architecture, and NREM electroencephalograhic (EEG) power were calculated over multiple nights. Sleep disordered breathing and periodic leg movements were measured on a separate night. Linear regression analysis was used to model the independent and synergistic effects of race and SES on sleep after adjusting for other factors that impact sleep in midlife women. Indices of SES were self-reported educational attainment and financial strain.

Results:

Sleep was worse in African American women than Caucasian participants as measured by self-report, visual sleep stage scoring, and NREM EEG power. Slow wave sleep differences were also observed between Chinese and Caucasian participants. Racial differences persisted after adjustment for indices of SES. Although educational attainment was unrelated to sleep, financial strain was associated with decreased sleep quality and lower sleep efficiency. Financial strain-by-race interactions were not statistically significant, suggesting that financial strain has additive effects on sleep, independent of race.

Conclusions:

Independent relationships between race and financial strain with sleep were observed despite statistical adjustment for other factors that might account for these relationships. Results do not suggest that assessed indices of SES moderate the race-sleep relationship, perhaps due to too few women of low SES in the study.

Citation:

Hall MH; Matthews KA; Kravitz HM; Gold EB; Buysse DJ; Bromberger JT; Owens JF; Sowers M. Race and financial strain are independent correlates of sleep in midlife women: the SWAN sleep study. SLEEP 2009;32(1):73-82.     

Sleep during menopausal transition: a 10-year follow-up

Study ObjectivesA 10-year observational follow-up study to evaluate the changes in sleep architecture during the menopausal transition.MethodsFifty-seven premenopausal women (mean age 46 years, SD 0.9) were studied at baseline and after a 10-year follow-up. At both time points, polysomnography (PSG) was performed, and the serum follicle-stimulating hormone (S-FSH) concentration was measured. Linear regression models were used to study the effects of aging and menopause (assessed as change in S-FSH) on sleep.ResultsAfter controlling for body mass index, vasomotor, and depressive symptoms, higher S-FSH level was associated with longer sleep latency (B 0.45, 95% confidence interval [CI]: 0.07 to 0.83). Aging of 10 years was associated with shorter sleep latency (B −46.8, 95% CI: −77.2 to −16.4), shorter latency to stage 2 sleep (B −50.6, 95% CI: −85.3 to −15.9), decreased stage 2 sleep (B −12.4, 95% CI: −21.4 to −3.4), and increased slow-wave sleep (B 12.8, 95% CI: 2.32 to 23.3) after controlling for confounding factors.ConclusionsThis study suggests that PSG measured sleep of middle-aged women does not worsen over a 10-year time span due to the menopausal transition. The observed changes seem to be rather age- than menopause-dependent.     

Predictors of sleep quality in women in the menopausal transition

STUDY OBJECTIVES: To determine associations between menopausal status, reproductive hormone levels, menopausal symptoms, and poor sleep quality. DESIGN: The present study examines subjective sleep quality over an 8-year period in participants in an ongoing longitudinal study of ovarian aging in a randomly identified cohort of African American and Caucasian women. PARTICIPANTS: The Penn Ovarian Aging Study, a population-based cohort of 436 women from Philadelphia County who were 35 to 47 years of age and had regular menstrual cycles at enrollment. INTERVENTIONS: N/A. MEASUREMENTS AND RESULTS: The primary outcome measure was the Sleep Quality factor score, derived from the St. Mary's Hospital Sleep Questionnaire, which was adapted for this population and collected at each assessment period over the 8-year follow-up. Associations between menopausal status, reproductive hormone levels, menopausal symptoms, sleep quality, age, and race were examined in multivariable linear mixed regression models for repeated measures. Menopausal status was not significantly associated with sleep quality (P = 0.12). In the adjusted model, independent predictors of sleep quality were hot flashes (P < 0.0001), Center for Epidemiological Studies Depression Scale scores (P < 0.0001) and levels of the reproductive hormone inhibin B (P = 0.05). CONCLUSIONS: Sleep quality was predicted by hormone levels and symptoms that occur in the menopausal transition but did not worsen with advancing menopausal status alone. Lower inhibin B levels, hot flashes, and symptoms of depression were all strong and independent predictors of difficulty sleeping. Race was not a significant contributor to sleep quality. Together, the findings demonstrate that women who experience other perimenopausal symptoms are likely to experience sleep problems during the menopausal transition.     

Age affects sleep microstructure more than sleep macrostructure

It is well known that the quantity and quality of physiological sleep changes across age. However, so far the effect of age on sleep microstructure has been mostly addressed in small samples. The current study examines the effect of age on several measures of sleep macro‐ and microstructure in 211 women (22–71 years old) of the ‘Sleep and Health in Women’ study for whom ambulatory polysomnography was registered. Older age was associated with significantly lower fast spindle (effect size f² = 0.32) and K‐complex density (f² = 0.19) during N2 sleep, as well as slow‐wave activity (log) in N3 sleep (f² = 0.21). Moreover, total sleep time (f² = 0.10), N3 sleep (min) (f² = 0.10), rapid eye movement sleep (min) (f² = 0.11) and sigma (log) (f² = 0.05) and slow‐wave activity (log) during non‐rapid eye movement sleep (f² = 0.09) were reduced, and N1 sleep (f² = 0.03) was increased in older age. No significant effects of age were observed on slow spindle density, rapid eye movement density and beta power (log) during non‐rapid eye movement sleep. In conclusion, effect sizes indicate that traditional sleep stage scoring may underestimate age‐related changes in sleep.     

Changes in sleepiness and body temperature precede nocturnal sleep onset: Evidence from a polysomnographic study in young men

Recent research has shown a close temporal relationship between the nocturnal decrease in rectal core temperature and the initiation of sleep. However, there is not yet a clear temporal relationship between changes in peripheral and core temperatures and nocturnal sleep onset. We recorded body temperatures in 14 adult males (age±SEM=22.1±0.6 y), who attended the sleep laboratory for an adaptation night and two counterbalanced experimental sessions. Subjects self-selected lights-out on one experimental night (the Habitual Sleep condition). To determine the relationship between body temperature changes and sleep onset, lights out was delayed until after 01.00 hours on the other experimental night (Delayed Sleep condition). Individual datasets in both conditions were expressed relative to the time of sleep onset in the Habitual Sleep condition only, so that they were aligned at identical clock times. Saliva samples confirmed that mean dim light melatonin onset (DLMO) occurred at 00.10±00.16 hours in the Delayed Sleep condition, which was after habitual sleep onset at 23.44±00.08 hours. Rectal core temperature (Tc) decreased significantly over time only in the Habitual Sleep condition ( P < 0.01). For the 20 min before habitual sleep onset, Delayed Sleep Tc was on average 0.1°C higher than Tc in the Habitual Sleep condition ( P < 0.01). The greater decline in Habitual Sleep Tc was associated with significantly increased peripheral hand and foot skin temperatures before sleep (both P < 0.05). Subjective sleepiness measures were higher in the Habitual Sleep onset condition from 150 min prior until sleep onset ( P < 0.01). From these results it is reasonable to infer that a sequence of thermoregulatory and sleep propensity changes occur before, but are associated with habitual sleep onset, as the changes are significantly attenuated if sleep is delayed.     

Associations between longitudinal trajectories of insomnia symptoms and sleep duration with objective physical function in postmenopausal women: the Study of Women’s Health Across the Nation

Study ObjectivesExamine the association between trajectories of self-reported insomnia symptoms and sleep duration over 13 years with objective physical function.MethodsWe utilized data from 1,627 Study of Women’s Health Across the Nation participants, aged 61.9 ± 2.7 years at the end of the 13-year follow-up. Latent class growth models identified trajectories of insomnia symptoms (trouble falling asleep, frequent night-time awakenings, and/or early morning awakening) and sleep duration over 13 years. Physical function tests were performed at the end of the 13-year period: 40-ft walk, 4-m walk, repeated chair stand, grip strength, and balance. Multivariable regression analyses examined each physical function measure according to the insomnia symptom or sleep duration trajectory group.ResultsFive insomnia symptom trajectories and two sleep duration trajectories were identified. Women with a consistently high likelihood of insomnia symptoms and women with a decreased likelihood of insomnia symptoms (i.e. improving) had slower gait speed (3.5% slower 40-ft walk [consistently high], 3.7% slower 4-m walk [improving]; each p ≤ .05) than those with a consistently low likelihood of insomnia symptoms. In contrast, women with a steep increase in the likelihood of insomnia symptoms over time and women with persistent insufficient sleep duration had lower odds of having a balance problem (odds ratio [OR] = 0.36 and OR = 0.61, respectively; each p < .02) compared to those with a consistently low likelihood of insomnia symptoms and those with persistent sufficient sleep duration, respectively.ConclusionThese results suggest that women’s sleep during midlife has important implications for maintaining physical function during the transition into older adulthood.     

(Not so) Smart sleep tracking through the phone: Findings from a polysomnography study testing the reliability of four sleep applications

An increasing number of sleep applications are currently available and are being widely used for in‐home sleep tracking. The present study assessed four smartphone applications (Sleep Cycle‐Accelerometer, SCa; Sleep Cycle‐Microphone, SCm; Sense, Se; Smart Alarm, SA) designed for sleep?wake detection through sound and movement sensors, by comparing their performance with polysomnography. Twenty‐one healthy participants (six males, 15 females) used the four sleep applications running on iPhone (provided by the experimenter) simultaneously with portable polysomnography recording at home, while sleeping alone for two consecutive nights. Whereas all apps showed a significant correlation with polysomnography‐time in bed, only SA offered significant correlations for sleep efficacy. Furthermore, SA seemed to be quite effective in reliable detection of total sleep time and also light sleep; however, it underestimated wake and partially overestimated deep sleep. None of the apps resulted capable of detecting and scoring rapid eye movement sleep. To sum up, SC (functioning through both accelerometer and microphone) and Se did not result sufficiently reliable in sleep?wake detection compared with polysomnography. SA, the only application offering the possibility of an epoch‐by‐epoch analysis, showed higher accuracy than the other apps in comparison with polysomnography, but it still shows some limitations, particularly regarding wake and deep sleep detection. Developing scoring algorithms specific for smartphone sleep detection and adding external sensors to record other physiological parameters may overcome the present limits of sleep tracking through smart phone apps.     

Period-amplitude analysis and power spectral analysis: a comparison based on all-night sleep EEG recordings

Both period-amplitude analysis (PAA) and power spectral analysis (PSA) were performed on all-night human sleep EEG recordings obtained from 11 subjects. The comparison of the two methods was based on the PAA variables time in band (a wave incidence measure) and rectified amplitude, and on the PSA variables spectral power density and spectral amplitude (the square root of power). The mean time course of these variables was determined for the first 4 nonREM-REM sleep cycles. Spectral power density and spectral amplitude in the delta range were high in nonREM sleep and low in REM sleep, and showed a declining trend over consecutive nonREM sleep episodes. In the frequency range below 2 Hz, rectified amplitude was highly correlated with both time in band and spectral amplitude, and there was no evidence for a dissociation between wave amplitude and wave incidence measures. However, in frequencies above 2 Hz, the modulation of time in band was a mirror image of that below 2 Hz. This result does not reflect a property of the data, but is inherent to the methodology applied. The reversal point of modulation was merely shifted when the high-pass filter settings were changed. It is concluded that band-pass filtering is necessary prior to PAA even for the analysis of the lowest frequency range, and that the indiscriminate use of PAA may give rise to spurious results.     

Modeling women's health during the menopausal transition: a longitudinal analysis

OBJECTIVE: There has been controversy about the relative effects on various health outcomes of hormonal, psychosocial, and lifestyle changes during the menopausal transition. In previous studies the risk factors for one particular health endpoint have been analyzed separately. Separate analyses do not provide an overall view of the relationships between all the variables or the relative importance of different factors. Thus, the objective of this study was to provide an overall analysis of the influence of hormonal changes during the menopausal transition on a range of health outcomes while simultaneously considering all the available predictors and all the endpoints and to test the hypothesis that prior health status predicts current health status. DESIGN: This was a 9-year prospective observational study of 438 Australian-born women, who at baseline were aged 45 to 55 years and had menstruated in the prior 3 months. Interviews were conducted and fasting blood and physical measurements were performed annually. RESULTS: Main outcome measures were hormone levels, sociodemographic variables, attitudes and lifestyle variables, self-rated health and well-being, bothersome symptoms, coronary heart disease risk, bone mineral density, and sexuality. Data from 336 women, 77% of the original sample, were analyzed. Statistical modeling using structural equations showed that for all health endpoints, the prior level of that variable was the most important predictor. Declining levels of estradiol during the menopausal transition affected certain health outcomes: bone mineral density, coronary heart disease risk, vasomotor symptoms, vaginal dryness, and sexual response. Well-being is negatively affected by symptoms, hassles, and stress. Exercise has beneficial effects on hot flushes, well-being, body mass index, and coronary heart disease risk. Relationship factors and mood affect sexual response. CONCLUSIONS: This observational study provides a conceptual data-based framework for understanding changes in women's health during the natural menopausal transition.     

Sleep changes following statin therapy: a systematic review and meta-analysis of randomized placebo-controlled polysomnographic trials

Introduction

Statin use might be associated with an increased risk of sleep disturbances including insomnia, but the evidence regarding sleep changes following statin therapy has not been conclusive. Therefore we assessed the impact of statin therapy on sleep changes through a systematic review and meta-analysis of available randomized controlled trials (RCTs).

Material and methods

We searched MEDLINE and SCOPUS up to October 1, 2014 to identify placebo-controlled RCTs investigating the effect of statin therapy on sleep changes. A meta-analysis was performed using either a fixed-effects or a random-effect model according to the I2 statistic. Effect size was expressed as weighted mean difference (WMD) and 95% confidence interval (CI).

Results

Overall, the impact of statin therapy on polysomnography (PSG) indices of sleep was reported in 5 trials comprising 9 treatment arms. Overall, statin therapy had no significant effect on total sleep duration (WMD: –7.75 min, 95% CI: –18.98, 3.48, p = 0.176), sleep efficiency (WMD: 0.09%, 95% CI: –2.27, 2.46, p = 0.940), entries to stage I (WMD: 0.36, 95% CI: –0.91, 1.63, p = 0.580), or latency to stage I (WMD: –1.92 min, 95% CI: –4.74, 0.89, p = 0.181). In contrast, statin therapy significantly reduced wake time (WMD: –4.43 min, 95% CI: –7.77, –0.88, p = 0.014) and number of awakenings (WMD: –0.40, 95% CI: –0.46, –0.33, p < 0.001). Meta-regression did not suggest any correlation between changes in wake time and awakening episodes with duration of treatment and LDL-lowering effect of statins.

Conclusions

The results indicated that statins have no significant adverse effect on sleep duration and efficiency, entry to stage I, or latency to stage I sleep, but significantly reduce wake time and number of awakenings.     

The value of one hour daytime sleep recording in the diagnosis of the sleep apnoea syndrome

In this study we investigated whether the diagnosis of sleep apnoea syndrome (SAS), based on night-time polysomnography (NPSG), can be predicted or excluded by a one-hour daytime polysomnography (DPSG). The results of 306 NPSGs were compared with DPSGs, which were performed the day before. Treated patients were excluded. In the 89 patients with SAS (Apnoea index (AI)>/=5) 59 showed apnoeas during the DPSG and 30 did not. In the 217 without SAS 25 showed apnoeas daring DPSG and 192 did not. Sensitivity for detecting SAS was 66%, the specificity was 88%, the positive predictive value (PPV) 70% and the negative predictive value (NPV) 86%. For relevant SAS (AI>/=10) the NPV would be 95%. We conclude that the one-hour DPSG is not sufficient for diagnosing or excluding SAS with certainty. It can be used to make the presence of relevant SAS unlikely.     

Distinguishing sleep from wake with a radar sensor: a contact-free real-time sleep monitor

This work aimed to evaluate whether a radar sensor can distinguish sleep from wakefulness in real time. The sensor detects body movements without direct physical contact with the subject and can be embedded in the roof of a hospital room for completely unobtrusive monitoring. We conducted simultaneous recordings with polysomnography, actigraphy, and radar on two groups: healthy young adults (n = 12, four nights per participant) and patients referred to a sleep examination (n = 28, one night per participant). We developed models for sleep/wake classification based on principles commonly used by actigraphy, including real-time models, and tested them on both datasets. We estimated a set of commonly reported sleep parameters from these data, including total-sleep-time, sleep-onset-latency, sleep-efficiency, and wake-after-sleep-onset, and evaluated the inter-method reliability of these estimates. Classification results were on-par with, or exceeding, those often seen for actigraphy. For real-time models in healthy young adults, accuracies were above 92%, sensitivities above 95%, specificities above 83%, and all Cohen''s kappa values were above 0.81 compared to polysomnography. For patients referred to a sleep examination, accuracies were above 81%, sensitivities about 89%, specificities above 53%, and Cohen''s kappa values above 0.44. Sleep variable estimates showed no significant intermethod bias, but the limits of agreement were quite wide for the group of patients referred to a sleep examination. Our results indicate that the radar has the potential to offer the benefits of contact-free real-time monitoring of sleep, both for in-patients and for ambulatory home monitoring.     

Searching for a marker of REM sleep behavior disorder: submentalis muscle EMG amplitude analysis during sleep in patients with narcolepsy/cataplexy

STUDY OBJECTIVES: To evaluate the amplitude of submentalis muscle EMG activity during sleep in patients with narcolepsy/cataplexy with or without REM sleep behavior disorder (RBD). DESIGN: Observational study with consecutive recruitment. SETTINGS: Sleep laboratory. PATIENTS: Thirty-four patients with narcolepsy/cataplexy and 35 age-matched normal controls. MEASUREMENTS AND RESULTS: Half the patients (17 subjects) had a clinical and video polysomnographic diagnosis of RBD. The average amplitude of the rectified submentalis muscle EMG signal was used to assess muscle atonia, and the new REM sleep Atonia Index was computed. Chin muscle activations were detected and their duration and interval analyzed. REM sleep Atonia Index was lower in both patient groups (with narcolepsy patients with RBD showing the lowest values) with respect to controls, and it did not correlate with age as it did in controls. The total number of chin EMG activations was significantly higher in both patient groups than controls. No significant differences were found between the two groups of patients, although more chin EMG activations were noted in narcolepsy patients with RBD than those without. CONCLUSIONS: Elevated muscle activity during REM sleep is the only polysomnographic marker of RBD. This study shows that polysomnographically evident RBD is present in many patients with narcolepsy/ cataplexy. This condition might be specific to narcolepsy/cataplexy, reflecting a peculiar form of REM sleep related motor dyscontrol (i.e., status dissociatus), paving the way to enacting dream behaviors, and correlated with the specific neurochemical and neuropathological substrate of narcolepsy/cataplexy.     

Discrepancy between wrist‐actigraph and polysomnographic measures of sleep in patients with stable heart failure and a novel approach to evaluating discrepancy

Wrist‐actigraphy is often used to measure sleep characteristics in a variety of populations, but discrepancies between actigraphic and polysomnographic measures have been noted in populations experiencing poor sleep quality. The purpose of this study is to examine the discrepancy between these measures and risk factors for discrepancy in people with heart failure using a novel index. We used sleep measures simultaneously recorded by actigraphy and polysomnography, and clinical data from a cross‐sectional study of 155 patients with heart failure (age = 60.5 [16.1] years; 65.2% male) recruited from evidence‐based heart failure disease management programmes. The discrepancy and consistency between the two measures were evaluated using Bland–Altman plots, intra‐class correlations and a newly developed index that represents activity counts in wake episodes. Overall, participants had short total sleep time (327.7 [95.9] min) and poor sleep efficiency (71.3 [16.0]%) on polysomnography. The discrepancies between sleep measures were small in patients less than 60 years old, and there was excellent consistency (intra‐class correlation = 0.81) compared with older patients who had poorer consistency (intra‐class correlation = 0.53) on total sleep time. Higher daytime motor activity, poor sleep quality and more severe insomnia were associated with smaller discrepancies in older, but not younger, patients, and associations were more sensitively detected by the new index. These findings suggest the importance of aging, disability and co‐morbidity that may influence motor activity from which sleep estimates are scored with actigraphy. The new index may be useful in identifying factors associated with the correspondence between actigraphy and polysomnography.     

Zolpidem and sleep deprivation: different effect on EEG power spectra

To study the role of GABA-ergic mechanisms in sleep regulation, the combined action of 40 h sleep deprivation and either 20 mg zolpidem or placebo on the sleep electroencephalogram (EEG) were investigated by quantitative EEG analysis in eight young men who participated in a positron emission tomography study. Compared with baseline, sleep deprivation increased low-frequency (1.25-7.0 Hz) EEG power in non-rapid eye movement (NREM) sleep in the placebo night. After administration of zolpidem, power in the 3.75-10.0 Hz range and 14. 25-16.0 Hz band was reduced. The largest decrease was observed in the theta band. Comparison with placebo revealed that zolpidem attenuated power in the entire 1.75-11.0 Hz range. The plasma concentration of zolpidem at 4.5 h after intake showed a positive correlation with the drug-induced difference in power from placebo in the 14.25-16.0 Hz band. Regional EEG analysis based on bipolar derivations along the antero-posterior axis disclosed, for NREM sleep, a drug-induced posterior shift of power in the frequency range of 7.75-9.75 Hz. Zolpidem did not affect rapid eye movemnt sleep spectra. We conclude that sleep deprivation and agonistic modulation of GABAA receptors have separate and additive effects on power spectra and that their effects are mediated by different neurophysiological mechanisms.     

Body image during the menopausal transition: a systematic scoping review

This scoping review aimed to examine women's body image during the menopausal transition systematically. A systematic search strategy and exclusion criteria were applied to ensure that only relevant research was included in the review. A total of 15 studies in 17 papers were included highlighting an equivocal relationship between body image and the menopausal transition. The menopausal transition is complex and individual, and should not be examined as a simple positive or negative transition. There is a sense of confusion for women experiencing the menopausal transition due to contradicting medical advice and societal expectations of body image. Currently, the research consists of exploratory-based studies that highlight the importance of researching this field further to aid adaptive coping and self-management across this transition.     

Women sleep objectively better than men and the sleep of young women is more resilient to external stressors: effects of age and menopause

The aims of this study were to: (i) assess gender differences of objective sleep patterns in a general population sample; (ii) evaluate the effects of menopause and hormone treatment (HT) on the sleep of the same cohort; and (iii) examine gender differences in sleep resilience towards external stressors. The participants were (i) 1324 subjects without sleep complaints, recruited from the general population of Central Pennsylvania that spent one night in the sleep laboratory and (ii) 66 young, healthy volunteers whose sleep was disturbed during night four by an external stressor, i.e. 24-h blood drawing (average of nights 2 and 3 versus night 4). Women compared with men in the general population sample had significantly higher percentage of sleep time, lower percentage of stage 1, and higher percentage of slow wave sleep. Also, menopause, in the absence of HT, was associated with prolonged sleep latency and decreased deep sleep. Finally, young, healthy women compared with men experienced less sleep disturbance because of blood draws as indicated by a significantly smaller change in per cent sleep time, and percentage of stage 1 sleep. These findings suggest that women without sleep complaints sleep objectively better across age than men and the sleep of young women is more resistant to external stressors. Also, gonadal hormones exert a beneficial effect on women's sleep. This gender dimorphism in sleep regulation may have been to protect women from the demands of infant and child care, and in part, might contribute to women's lower cardiovascular risks and greater longevity.     

Motor disturbances during non-REM and REM sleep in narcolepsy-cataplexy: a video-polysomnographic analysis

Motor events during sleep can be frequently observed in patients with narcolepsy-cataplexy. We hypothesized that increased motor events and related arousals contribute to sleep fragmentation in this disease. We aimed to perform a detailed whole-night video-polysomnographic analysis of all motor events during non-rapid eye movement and rapid eye movement sleep in a group of narcolepsy-cataplexy patients and matched controls, and to assess the association with arousals. Video-polysomnographic registrations of six narcolepsy-cataplexy patients and six sex- and age-matched controls were analysed. Each motor event in the video was classified according to topography, number of involved body parts, duration and its association with arousals. The mean motor activity index was 59.9 ± 23.0 h(-1) in patients with narcolepsy-cataplexy compared with 15.4 ± 9.2 h(-1) in controls (P = 0.004). Distribution of motor events was similar in non-rapid eye movement and rapid eye movement sleep in the patient group (P = 0.219). In narcolepsy-cataplexy, motor events involved significantly more body parts (≥ 2 body regions: 38.2 ± 15.6 versus 14.9 ± 10.0; P = 0.011). In addition, the proportion of motor events lasting longer than 1 s was higher in patients than controls (88% versus 44.4%; P < 0.001). Both total and motor activity-related arousal indices were increased in narcolepsy-cataplexy (total arousal index: 21.6 ± 9.0 versus 8.7 ± 3.5; P = 0.004; motor activity-related arousal index: 17.6 ± 9.8 versus 5.9 ± 2.3; P = 0.002). Motor activity and motor activity-related arousal indices are increased in both non-rapid eye movement and rapid eye movement sleep in narcolepsy-cataplexy compared with controls. This supports the concept of a general sleep motor dysregulation in narcolepsy-cataplexy, which potentially contributes to or even underlies sleep fragmentation in this disease.