Introduction: Noise is one of the factors that can seriously disturb sleep, and sound volume is an important factor in this context. One strategy involves avoiding exposure to sounds in the night, while entail the minimization of background noise in a bedroom. The goal of this study was to investigate the effect of systematic sound attenuation on nocturnal sleep by influencing sound volume and reverberation within the context of room acoustics. Materials and Methods: On this basis, we designed a randomized, controlled crossover trial investigating 24 healthy sleepers (15 men and 9 women, aged 24.9 ± 4.1 years) with a body mass index (BMI) of 21.9 ± 1.6 kg/m2. Each participant slept for three consecutive nights at three different locations: (a) at our sleep lab, (b) at the participant’s home, and (c) at an acoustically isolated room. In addition to conduct of polysomnography (PSG), subjective sleep quality and nocturnal noise level were measured at each location. We likewise measured room temperature and relative humidity. Results: Under conditions of equal sleep efficiency, a significant increase in deep sleep, by 16–34 min, was determined in an acoustically isolated room in comparison to the two other sleep locations. Fewer arousal events and an increase in rapid eye movement (REM) latency became evident in an acoustically isolated environment. Sleep in a domestic environment was subjectively better than sleep under the two test conditions. Discussion: For healthy sleepers, room acoustics influence the microstructure of sleep, without subjective morning benefit. Reduction of noise level and of reverberation leads to an increase in the amount of deep sleep and to reduction of nocturnal arousal events, which is especially important for poor sleepers.
Keywords: Noise, reverberation, sleep quality, sound isolation, sound reduction
|How to cite this article:|
Fietze I, Barthe C, Hölzl M, Glos M, Zimmermann S, Bauer-Diefenbach R, Penzel T. The effect of room acoustics on the sleep quality of healthy sleepers. Noise Health 2016;18:240-6
|How to cite this URL:|
Fietze I, Barthe C, Hölzl M, Glos M, Zimmermann S, Bauer-Diefenbach R, Penzel T. The effect of room acoustics on the sleep quality of healthy sleepers. Noise Health [serial online] 2016 [cited 2022 Jan 27];18:240-6. Available from: https://www.noiseandhealth.org/text.asp?2016/18/84/240/192480
| Introduction|| |
Approximately 20% of the population of the European Union suffers from noise levels that are considered unacceptable by scientists and health experts. As a result, noise-abatement measures play an increasingly important role. Here, attention, has been focused on minimization of traffic, aircraft, and railway noise − as well as on disturbances caused by commercial and industrial noise. Sleepers are particularly sensitive to noise during the early morning hours, when most of the sleep pressure has dissipated and sleep is characterized by more superficial sleep stages (stages 1 and 2) and by rapid eye movement (REM) sleep. During sleep, noise can cause arousal, which leads to fragmentation of sleep and, in turn, to shortening of the deep-sleep phase.
As a result of the great significance accorded to restorative sleep and to its importance for health and quality of life, we consider sleep disturbance to be the most harmful consequence of noise pollution. A review from 2011 summarizes increased cardiovascular risk, higher cortisol levels, and sleep disturbance such as awakenings and shallower sleep stages as the most severe health effects of noise on sleep studied. The World Health Organization (WHO) accordingly recommends the following:
The mean outdoor sound level should not exceed 50 dB(A) during the hours of the day (LAeq = 16 h) “… in order to prevent moderate disturbance ….” The mean outdoor sound level should be lower during the evening hours and should be 5–10 dB(A) lower during the hours of the night (LAeq = 8 h) than during daytime hours. These recommendations include the guideline that the mean sound level prevailing in bedrooms should not exceed 30 dB(A).
In the cities of Germany, 9% of the population is subjected to a mean sound level of 55 dB(A) or more. A review of studies conducted over 20 years on this topic extensively reveals not only the effects of noise produced by traffic or industry on sleep, but also ambient sources of sounds such as leisure activities and neighboring noise have an apparently disturbing effect on sleep.
Measures toward reducing noise − in addition to sound isolation, prevention of the emission of noise, and reduction of the noise level − also include measures concerning room acoustics. There are many different qualities involved in a room acoustic environment. One example is modulation of sound decay, which can be studied by measuring reverberation time. A variety of background noise measures exist that examine aspects such as sound pressure level (a measure of the sound volume), spectral quality, and temporal pattern. This study focused on two measures: reverberation time and sound pressure level.
In this study, we investigated sleep in an acoustically isolated room, one with appreciably reduced reverberation and a low noise level. The purpose of this study was to determine whether noise abatement beyond the usually attempted extent provides an optimal condition for restful sleep among those with unimpaired hearing. The study compared sleep in a noise-reduced environment with sleep in a sleep lab, and with sleep at home. Our hypothesis was that sleep quality in an extremely quiet environment is better, even for healthy sleepers.
| Materials and Methods|| |
Study cohort: Inclusion and exclusion criteria
In our study, we included n = 24 participants (m = 15, f = 9) with a mean age of 24.9 ± 4.1 years and a mean Body Mass Index (BMI) of 21.9 ± 1.6 kg/m2. All participants were healthy sleepers with unimpaired hearing. The participants took no medication of any kind (except contraceptives), none suffered from an acute disorder, none had a clinically relevant chronic disease, and none had a known drug or alcohol problem. During the study period, participants were not allowed to consume caffeinated products or chocolate after 2:00 p.m., to smoke more than five cigarettes a day, or to consume alcohol. No consumption of medication was allowed. Histories of previous disorders and questionnaires filled out before our study − and based on the Epworth Sleepiness Scale (ESS), the Insomnia Severity Index (ISI), and the Pittsburgh Sleep Quality Index (PSQI) − precluded existing sleep disorders. Unimpaired hearing was confirmed by a tone audiogram recorded for every participant. Moreover, the presence of sleep apnea or periodic limb movement disorders was precluded by including only participants with an Apnea–Hypopnea Index (AHI) and periodic limb movement index of less than 10 per hour. All participants signed an informed consent form before participating in the study, and the local Ethics Committee of the university hospital center provided written approval for the study.
Course of the study
Each participant spent three study nights at three different locations on three consecutive days, each of which was followed by a workday. In exceptional cases, we allowed interposition of a maximum of one nonstudy night between two study nights. The scheduled time for the participants to retire to bed was between 11:00 p.m. and 12:30 a.m. and was designed to remain unchanged for all three study nights. The specific bedtime of each participant was oriented to the participant’s accustomed bedtimes, on the basis of bedtime average taken from the days immediately prior to the study, and as a result of evaluation of an interview. We randomized the sequence of study locations and balanced the number of participants following the same sequence scheme − i.e., four participants in each of the six different groups. Accordingly, we did not modify analysis of variance (ANOVA). We included only those participants who slept under all three conditions and therefore did not consider Mixed Model ANOVA. To compensate for the first-night effect, the night sessions took place consecutively in randomized order.
To assure identical environmental conditions, all participants slept in a sleep-lab room that faced a rear courtyard. We used two adjacent rooms, adjacent to each other, for testing. Virtually all features of the rooms as the following were identical: window size, bed, and location within the sleep-lab facility. We did, however, note minor differences in acoustic reverberation characteristics. In the normally furnished room, the reverberation time − measured and averaged over a frequency range of 100 Hz to 5 kHz − was Tm = 0.42 s [Figure 1]. The mean background noise level in the empty room of the sleep lab was LAeq = 24.9 dB(A). We conducted daytime measurements to define the basic conditions provided by the empty rooms themselves, without any distracting sounds produced by the sleeper. In all further statistical calculations, we applied the sound levels measured during the actual study nights, including the sounds produced by the study participants.
|Figure 1: Comparison between measured reverberation times in a sleep-lab bedroom and in the acoustically isolated room|
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Acoustically isolated room
A single bed was set up in an audiometry booth, 10 m2 in size, originally intended to conduct hearing tests. We set up the bed every study night and used the same type of mattress as in the sleep lab to ensure comparable comfort. During the study nights, we switched off all electrical devices and shut down all sockets in the audiometry booth to minimize possible noise sources. In this highly sound-absorbing room, we measured the reverberation time and averaged the readings throughout a frequency range of 100 Hz to 5 kHz, and arrived at the mean of Tm = 0.12 s [Figure 1]. The background noise level in the empty audiometry booth was LAeq = 19 dB(A). A highly sound-absorbing audiometry booth attenuated the background noise level of its space by absorption. Reduction of the reverberation time in this room lowered the sound pressure level by approximately 3 dB(A), which partially accounted for the difference in overall noise level between the sleep lab and the acoustically isolated room.
Participant’s home environment
We conducted nonattended recording of sleep by polysomnography (PSG) in the participant’s usual home bedroom. We did not measure the background noise or reverberation time in the empty bedroom. The participants were requested to sleep in their accustomed environment at home. If they normally shared the bed with their partner during sleep, they were asked not to change this arrangement for the study. Five of our participants slept in one bed with their partner. None of the participants had children at home. During study nights at home, lights were turned off and documentation was recorded by the director of studies, who was present at all evenings prior to the nights of PSG. PSG equipment was installed during the night, and participants were awakened the next morning by the director of studies.
We conducted the following sleep polygraphic measurements: electroencephalography (EEG: C3-A2 and C4-A1), electrooculography (EOG), electromyography of the chin (EMG of chin), EMG of the legs (EMG-Tib), electrocardiography (ECG), nasal flow, thoracic and abdominal movements, pulse, and oxygen content of the blood (pulse oximetry). Signals and settings were in accordance with standard recording conditions. The same biocalibration procedure was applied before each recording night, independent of the PSG equipment. We employed the following systems: In the sleep lab, we employed the system EMBLA N7000 (Embla Inc., Broomfield, CO, USA) for recording the signals. In the participant’s home environment site as well as in the acoustically isolated room, we used a mobile sleep recording system Somnocheck R&K (Weinmann Medizingeräte GmbH, Hamburg, Germany), which offers fewer options but still suffices for sleep recording. This system was validated for PSG recording by the supplier. For visual analysis of the data, we applied the software SOMNOlab 2.19 for the Somnocheck system and Somnologica 3.3 for the Embla system. Sleep stages were scored visually in 30-s segments according to American Academy of Sleep Medicine (AASM) criteria. On this basis, we calculated time in bed (TIB), total sleep time (TST), sleep efficacy (SE = TST/TIB), sleep latency, latency to sleep stages N1, N2, N3, and REM − as well as the percentage of TST for sleep stages N1, N2, N3, and REM. We evaluated arousal episodes according to AASM criteria.
Questionnaire for participants’ rating of the quality of sleep (VIS-M)
On the morning following PSG, we applied the questionnaire VIS-M in the sleep lab, at the home bedroom, and in the acoustically isolated room. For this study, we analyzed only the responses from the first item of the questionnaire. On the morning after sleep, we asked the participants to rate the quality of sleep for the preceding night by using a scale of 0 (“terribly tiredly and half-heartedly”) to 100 (“marvelous freshly and energetically”).
Measurements of noise, humidity, and temperature
We measured the noise with an audio and acoustic analyzer (XL2, NTi Audio AG, Schaan, Liechtenstein) equipped with a class II microphone from the same manufacturer (M4260; sensitivity: 32.6 mV/Pa; linear range 35 dB(A) … 144 dB). The sound-level value analyzed by us was a moving time-averaged level (LAeq60′), with 60 min of sliding time included in the calculation. Other measured values such as L95% and L5% were cumulative probability levels (L95% is the level achieved or exceeded during 95% of the measuring interval) that were measured by the XL2 system, but which we did not evaluate. L5% corresponds to the peak level.
We set up the analysis system approximately 1 m from the bed. LAeq was detected every second during nocturnal measurement, independent of the study location. All sound measurements referred to indoor sound pressure levels. Background sound in the rooms was mainly noise from outside and sound produced by the patients themselves. In the sleep lab and the acoustic isolated room, sound pressure level was measured twice: the first measurement was done one time at setup in the empty study locations to compare the two base conditions of the different rooms, and the second measurement took place during actual nocturnal recording while volunteers were asleep. The data of the nocturnal measurements were used in statistical analysis. We employed a digital thermometer and a hygrometer to measure room temperature and room humidity.
We used the program Statistical Package for the Social Sciences (SPSS) version 20.0 to analyze the collected data. We tested measurement differences for significance by using the t-test for connected samples and variance analysis with measurement repetition.
For all procedures used, we set the significance level at α = 0.05 and the level of the confidence interval to 95%. We rounded off all results to the second decimal place, and rounded down in cases of doubt. Results in minutes and seconds were rounded to the nearest minute.
| Results|| |
Sleep parameters from polysomnography
[Table 1] shows the distribution of variables from sleep evaluation. Sleep efficiency (SE) did not vary among the three rooms.
|Table 1: Sleep efficacy, percentage of sleep stages, sleep latency, latency to sleep stages, and arousal rate for the three study sites|
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The average percentage of sleep stages N3 on TST measured in the acoustically isolated room was 7.5% greater than the N3 amount measured in the sleep lab (P = 0.001). With the average TST of 6 h and 34 min, this amounts to a difference of approximately 30 min. In comparison to sleep in the participant’s home environment, this amounted to approximately 16 min more (P = 0.026) [Table 1].
No difference among the three study locations became apparent in the percentage of sleep stages N1 and N2. The percentage of REM sleep was 14.2 ± 5.1% in the acoustically isolated room, which was 4.5% (18 min) less than in the sleep lab (P = 0.001). In the participant’s home environment, the REM sleep percentage was 15.8 ± 5.5% [Table 1].
In the acoustically isolated room, REM latency was 132 ± 49 min, which was more than 50 min longer than in the sleep lab (P < 0.001) and 20 min longer than in the participant’s home environment (n.s.). In variance analysis, the sleep location had significant influence on REM latency (P = 0.004) [Table 1].
In the acoustically isolated room, the number of arousals per hour of sleep was 11.9 ± 5.0, which was significantly fewer than at the participant’s home (15.1 ± 8.8, P = 0.023) and at the sleep lab (15.5 ± 7.9, P = 0.011) [Table 1].
Subjective sleep quality rating by VIS-M
On a scale of 0 (worst quality) to 100 (best), the quality of sleep as perceived after the night at the participant’s home was 62.0 ± 15.0; after the night in the acoustically isolated room, it was 58.4 ±16.1; and after the night in the sleep lab, it was 51.2 ± 20.7. The night in the bedroom at the participant’s home was subjectively better than in the sleep lab (P = 0.028). The night in the acoustically isolated room did not differ in sleep quality from the other two nights.
Sound level, temperature, and humidity during sleep
The mean of the 60-min moving time-averaged sound level (LAeq60′) at the three study sites were different (P < 0.0001). Noise level of LAeq60′, 33.8 ± 2.8 dB(A), measured in the acoustically isolated room was significantly lower in comparison to a LAeq60′ of 39.6 ± 5.4 dB(A) at the sleep lab (P = 0.0001) and also in comparison to a LAeq60′ of 40.5 ± 7.1 dB(A) at the participant’s home (P = 0.0001).
The mean of the 5th percentile of the sound level (LAF5%) at the three study sites were different (P = 0.042). Noise level of LAF5%, 34.2 ± 6.1 dB(A), measured in the acoustically isolated room was lower compared to a LAF5% of 40.7 ± 7.1 dB(A) at the participant’s home (P = 0.046) but not different to LAF5% of 36.1 ± 4.6 dB(A) at the sleep lab (P = 0.847).
The mean of the 95th percentile of the sound level (LAF95%) at the three study sites were not different (P = 0.123).
The mean of the maximum sound level (LAFmax_dt) at the three study sites were not different (P = 0.681).
The mean temperature in the three rooms differed by a maximum of 2.6°C (P = 0.0001), and the humidity by a maximum of 7.8% (P = 0.001). The average temperature/humidity was 22.8 ± 1.9°C/40.7 ± 4.6% in the sleep lab, 22.5 ± 1.8°C/38.6 ± 6.1% in the acoustically isolated room, and 20.2 ± 2.1°C/46.4 ± 6.4% at the participant’s home.
| Discussion|| |
In this study, we show that room acoustics − defined by noise level and reverberation − has no influence on sleep efficiency, but that it indeed influences sleep structure. Although, in subjective terms, the best sleep is in a familiar domestic environment, in objective terms, it is best in a quiet environment with attenuation of sound and noise. The subjective perception of sleep quality was assessed by a standardized morning questionnaire. The results showed a nonsignificant trend that the participants felt most refreshed after the night in their own bedrooms. This was a surprising finding for us, because we studied healthy sleepers for whom we would not have necessarily assumed an improvement in sleep structure. Present studies concerning the influence of room acoustics on sleep quality are rare. The only relevant study that investigated differences in sleep parameters compared two nights under conditions of different reverberation (using a three-bed room that was equipped with sound-absorbing ceiling tiles in the comparing night), and was conducted in Sweden in 2001 by Berg During the test nights, they used loudspeakers to emit a sound-stimulus scheme with sound levels varying from 27 to 58 dB(A). In contrast to our results, no change in distribution of the sleep stages was found between the nights of different reverberation times, but a significant reduction in arousal responses to the sound stimuli was determined in the night under absorbing ceiling tiles. These researchers conclude that reduced reverberation time results in decreased sleep fragmentation caused by sound stimuli. The results of our study support the assumption that reduced nocturnal reverberation time results in a decreased arousal rate. In addition, we evidence that it is possible to optimize sleep, even among healthy sleepers, by improving room acoustics − although our findings suggest that reverberation time must be severely reduced to achieve these results (the reduced reverberation time of the Swedish study approximately corresponds to the time measured in our sleep lab).
Although the standardized facilities of a sleep lab include not only the possibility of darkening the rooms, but also of providing noise abatement, we are not able to achieve household comfort there − which is evidently the reason for the superiority of subjectively assessed sleep in a home bedroom. Objectively seen, however, there are virtually no differences between sleep quality in a sleep lab and in domestic environments. The results of our subjective questionnaire survey, however, are based only on one question and not on a standardized morning protocol. For intraindividual comparison of the three study nights, nevertheless, this one question still has certain significance.
During interpretation of our results, sleep duration during the three study nights is not an influencing variable, because the participants – when they slept at home – were woken at the same time as in the sleep lab and in the acoustically isolated room.
The duration of deep-sleep phase increased in an isolated environment, which is the essential finding of our study. The fact that noise can impair deep-sleep phase is well known, but it had not been determined that noise reduction beyond that prevailing in a quiet sleep lab can lengthen the duration of deep sleep. Loud nocturnal noise disturbance – both repeated as well as continuing in nature – leads to shortening of the deep-sleep phase, i.e., beginning at a level of LAeq = 36 dB(A) for continuous noise disturbance and LAmax = 45 dB(A) for intermittent noise. Basner and Samel have examined nocturnal noise levels between 45 and 80 dB(A) (e.g., by intermittent aircraft noise) and have also revealed a reduction in slow-wave sleep (SWS) under such disturbance. In that study, the participants slept in a sleep lab in which a noise level of 30 dB prevailed under conditions of rest. Reverberation was not investigated.
It is already known that a reduction in nocturnal noise levels helps to mitigate an existing deficit in deep sleep. In a study by Wilkinson and Campbell in which the participants were exposed to nocturnal traffic noise, average noise reduction by only 5.6 dB(A) resulted in longer deep sleep and enhancement of subjectively experienced sleep quality. A review has confirmed the negative correlation between nocturnal noise (in this case, aircraft noise) and deep sleep. Studies have also disclosed a dose–effect relationship between the number and the volume of noise events, and lengthening or shortening of the deep-sleep phase. In our investigation as well, the noise level varied only by 5–10 dB(A) among the various study locations, which shows, or confirms, that even slight changes in sound volume have effects on sleep. This supports our results, because changes in the distribution of sleep stages could already be found with differences in sound volume of approximately 5–7 dB(A).
Arousals may well represent an influencing factor for the extent of deep sleep. We recorded fewer arousals in our acoustically isolated room, which explains the lengthening of deep sleep. Because intermittent noise beginning at a level of LAmax 45 dB(A) already induces waking reactions, we may assume that the low average sound level of 34.01 dB(A) – in combination with the reduced brightness in the acoustically isolated room – was responsible for the reduced number of waking reactions, although noise-induced awakenings may be provoked by sound levels beginning at 30–40 dB(A). Nocturnal waking reactions interrupt the sleep structure and must be considered harmful to health when they occur frequently.
Sleep efficiency did not significantly vary among the three sleep sites. As a result, we must conclude that acoustic optimization of sleep environment can enhance some, but not all, parameters of sleep macrostructure and microstructure in healthy sleepers, i.e., neither the length of sleep nor the effective sleep time during TIB changed. Other studies have extensively described a reduction in sleep efficiency under the influence of nocturnal traffic noise. Saletu et al. studied healthy participants from various age groups (mean age in group 1 = 25 years; group 2 = 62 years) who were subjected to simulated nighttime traffic noise (intensity = 68–83 dB(A); LAeq = 75.6 dB(A)). They also revealed diminished sleep efficiency. Sleep efficiency was greater under quieter conditions. This study approach does not, however, justify the conclusion that noise attenuation according to standards enables enhancement of sleep efficiency, as our study disclosed.
Other studies have revealed enhancement of sleep quality [sleep-onset latency (SOL), wake after sleep onset (WASO), percent sleep stages, and TST] with the use of earplugs in nocturnal environments with intensive noise (90 dB). The use of earplugs has also proven to be an inexpensive and sleep-enhancing measure for patients in intensive-care wards. Conventional earplugs available in drugstores reduce surrounding noise levels by 30–35 dB(A). With a surrounding noise level of 95 dB(A) – as investigated by Li et al. this would still represent noise disturbance of 60–65 dB(A), i.e., an environmental sound level still distinctly higher than that in our acoustically isolated study room. In addition, the use of earplugs is not comparable to active attenuation of reverberation and sound volume. It is also not realistic to compare the sleep of young and healthy participants with patients in a hospital intensive-care ward. The former have abnormal circadian rhythms, shortened REM and deep-sleep phases, and a higher waking index.
In our study, in addition to the reduction of arousals in the acoustically isolated room, we likewise revealed a reduction in the REM sleep phase. A study published in 1999 reported that maintenance of REM sleep duration requires a quiet environment. In this context, continuous nocturnal noise disturbance (e.g., actual, simulated continuous, or transient traffic noise) leads to shortening of the REM sleep phase beginning with LAeq = 45 dB(A). This study also revealed that the noise threshold that leads to departure from the REM sleep phase is higher than the threshold that results in abnormal deep sleep and sleep phase 2. Hecht and Maschke also disclosed a shortening of REM sleep as early as with continuous noise over 35 dB(A). Traffic noise has a general negative effect on REM sleep, as has been confirmed for various noise events, various noise levels, and varying quantitative extent.
One explanation for REM reduction in our study is the greater deep-sleep share and the defined getting-up time. An indication for the role of deep sleep is also lengthened REM latency. Under conditions of longer morning sleep times – which were not possible in our study, because we had limited the length of sleep – an increase in REM sleep is also to be expected.
The other environmental parameters such as room temperature and humidity showed no influence on sleep quality. We only recorded these parameters and did not modulate them; they were similar in all three study locations. This is essential, because a correlation between temperature and sleep is well known.
There are some limitations in our study. Firstly, we did not have the opportunity to measure sound levels in the empty bedrooms at the participants’ home. Secondly, for enhanced comparability, we decided to use sound levels measured during the night − including sounds produced by the patient at all three locations – and not the daytime sound characteristics.
Another limitation is the use of two different PSG systems, which was necessary to enable recordings outside the sleep lab. Within the sleep lab, the Embla system is installed in all sleeping rooms. We used Somnocheck R&K as the portable system, which allowed recording of validated PSG with fewer electrophysiological signals, but which still represented a feasible compromise regarding portability. To eliminate the chances of reduced comparability, we ensured that identical EEG and EOG channels were used and that all hardware settings such as filter and sampling rates were accordingly made.
The audio and acoustic analyzer was equipped by a class II microphone only. However, because we intended to conduct only a comparative investigation and did not intend to define new standards, a possible discrepancy here should not prove relevant.
There are currently no studies in which reduction in usual or normal environmental sounds during sleep has led to impairment of sleep quality. On the contrary, our study has led to the conclusion that acoustic reduction in sound volume and in reverberation can objectively optimize sleep − even among healthy sleepers. For subjective sleep quality, sleeping comfort in familiar surroundings is apparently a significant additional quality factor.
Sensitive sleepers and insomniacs should therefore pay attention not only to the sleeping comfort and the temperature of their bedrooms, but also and especially to room acoustics. They should particularly avoid loud and reverberating sleeping environments. For future investigations, we suggest further research on the possibly positive effects on sleep quality of other aspects of room acoustics, in addition to reverberation time and sound pressure level.
Financial support and sponsorship
This study was solely funded by Charite University funds.
Conflicts of interest
There are no conflicts of interest.
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Charité − Universitätsmedizin Berlin, CCM-CC11, Centre for Sleep Medicine, Charitéplatz 1, Berlin - 10117
Source of Support: None, Conflict of Interest: None