Abstract
Study Objectives:
Subjectively assessed snoring and sleepiness are known to be related. However, no evidence supporting the usefulness of snoring measurements exists. We examined whether the objectively measured snoring intensity was correlated with sleepiness.
Methods:
The records of 515 patients who underwent polysomnography for suspected obstructive sleep apnea were retrospectively reviewed. Subjective sleepiness was assessed using the Epworth sleepiness scale (ESS). Snoring intensity was assessed using the highest one percentile ambient sound pressure level (L1) attained while asleep during polysomnography.
Results:
L1 was correlated with ESS in apneic patients with an apnea-hypopnea index (AHI) ≥15 (r = 0.38, p < 0.0001), but not in other patients. The correlation in the apneic patients was preserved after adjustments for various confounding factors, including the AHI. A stepwise multiple regression in the apneic patients adopted desaturation time, L1, daily sleep time, subjective snoring, and nasal obstruction symptoms as determinants for the ESS. L1 was correlated with the mean pulse rate during polysomnography but not with sleep fragmentation variables after adjustment for the AHI.
Conclusions:
The measured snoring intensity was independently related to sleepiness in apneics. Snoring intensity may explain part of sleepiness that cannot be fully explained by ordinary polysomnographic variables.
Citation:
Nakano H; Furukawa T; Nishima S. Relationship between snoring sound intensity and sleepiness in patients with obstructive sleep apnea. J Clin Sleep Med 2008;4(6):551-556.
Keywords: Snoring, sleep apnea, sleepiness, sound intensity
BACKGROUND
Snoring is the most common manifestation of obstructive sleep apnea (OSA) and has been used as a surrogate parameter for OSA in many epidemiological studies. These studies have demonstrated relationships between snoring and cardiovascular disease1–4 and snoring and sleepiness.5 Although the relationship between snoring and sleepiness is thought to depend on the relationship between snoring and OSA, snoring itself may be related to sleepiness as a result of its detrimental effect on sleep. A large-scale population-based study has demonstrated a relationship between snoring and sleepiness that was independent of OSA.6 However, most studies have used snoring frequency or intensity determined by a questionnaire. Wilson et al. measured the intensity of snoring sounds during polysomnography (PSG) and reported that it was related to the severity of OSA as well as various clinical factors.7 However, they did not examine the independent relationship between snoring intensity and the clinical factors. Recently, Hunsaker et al. reported that sleepiness depended on both the intensity of the snoring sound and the apnea–hypopnea index, suggesting a relationship between sleepiness and snoring sound intensity independent of OSA.8 However, their results were considered inconclusive because their study was conducted using a portable monitor without measuring sleep. Thus, evidence supporting an independent relationship between objectively measured snoring and sleepiness remains insufficient. Although sleepiness is the most important symptom of OSA, the correlation between the degree of sleepiness and the severity of OSA has been reported to be relatively weak in many studies. If objectively measured snoring is related to sleepiness independent of OSA, such a relationship would imply that quantitative measurements of snoring are desirable in ordinary sleep studies. To clarify this point, we examined the relationship between objective measures of snoring and subjective sleepiness using a retrospective sample of polysomnographic records.
METHODS
Patients
The records of 515 patients who were referred for suspected OSA and who underwent diagnostic PSG with the measurement of ambient sound intensity between September 2002 and January 2005 were reviewed. Their presenting features included habitual snoring (n = 422), daytime sleepiness (n = 371), witnessed apnea (n = 385), and nocturnal choking (n = 130). At the time of their first visit to the hospital, all the patients were asked to answer a questionnaire on their sleep habits and related symptoms that included the Epworth Sleepiness Scale (ESS),9 daily sleep time, snoring frequency and quality, and nocturnal nasal obstruction symptoms. The questionnaire asked about snoring frequency (1: < 1/month; 2: < 1/week; 3: 1–2 x/week; 4: 3–5 x/week; 5: almost daily) and snoring intensity (1: no snoring; 2: regular and weak; 3: regular and loud; 4: regular and very loud; 5: very loud and intermittent); these questions were similar to those included in the Basic Nordic Sleep Questionnaire.10 Subjective nasal obstruction during sleep time was classified into 4 degrees (1: none; 2: rarely; 3: sometimes; 4: always). Seven patients were excluded from the analysis because they did not respond to the ESS questionnaire. In addition, one of the patients was diagnosed with narcolepsy and was excluded. Accordingly, the records of 507 patients were used for subsequent analysis.
Polysomnography
PSG was recorded using a polygraph system (EEG7414; Nihon Kohden, Japan). EEG (C3-A2, C4-A1), bilateral EOG, submental EMG, ECG, and bilateral anterior tibial EMG were recorded. Oronasal airflow was monitored using a thermistor. Thoracic and abdominal respiratory movements were monitored using respiratory inductive plethysmography (RIP) (Respitrace; Ambulatory Monitoring Inc., USA). Oxyhemoglobin saturation and pulse rate were monitored using pulse oximetry with a finger probe (OLV-3100; Nihon Kohden, Japan). All the signals were digitized and stored on a personal computer (PC). Sleep stages were scored manually according to the standard criteria of Rechtschaffen and Kales.11 As a parameter for sleep fragmentation, we calculated the sleep fragmentation index (SFI), which is the total number of awakenings/shifts to stage 1 (from deeper NREM or REM sleep) divided by the total sleep time in hours.12 Apnea was defined as an episode of complete airflow cessation lasting more than 10 s. Hypopnea was defined by ≥ 30% reduction in amplitude of the RIP sum signal lasting more than 10 s with ≥ 4% oxygen desaturation.13 The AHI was calculated as the number of apneic + hypopneic episodes per sleep hour. To assess the severity of hypoxemia, we calculated the duration of oxygen saturation below 90%, which was expressed as a percentage of the total examination time (CT90).
Measurement of Tracheal Sounds
Tracheal sounds were recorded using an air-coupled microphone (ECM140; SONY, Japan) attached to the neck over the trachea. The recording system for tracheal sounds was calibrated using a reference sound pressure (94 dB). Tracheal sounds were analyzed using a PC-based compressed sound spectrograph system that we previously developed for analyzing snoring. We defined the snoring time as the absolute time when the power spectral density exceeded a threshold value and expressed the snoring time as a percentage of the total sleep time. Details of our analytical method have been described elsewhere.14 Although this method can yield parameters for analyzing snoring sound intensity, we decided not to use these parameters in the present analyses because the variables derived from the tracheal sounds for snoring intensity were found to suffer a ceiling effect in patients with extremely loud snoring, and this effect might have obscured possible intersubject differences in snoring sound intensity.
Measurement of Ambient Sound Intensity
To evaluate snoring sound intensity, ambient sound pressure was recorded using a sound level meter (LA1200; Ono Sokki, Yokohama, Japan). The microphone of the sound level meter was suspended 1.2 m above the surface of the patient's bed. The same room was used for the ambient sound measurement during the study period. The ambient sound intensity was measured as an A-weighted sound pressure level with a time constant of 125 ms. The mean background noise level was 40.8 dB (SD 2.8 dB), caused primarily by noise generated by the air conditioner in the room. The measured sound pressure level was inputted to the polygraph system as an analogue signal and digitized simultaneously with the other PSG signals. The sampling frequency for the sound pressure level was 10 Hz. The measurement system was calibrated using a reference sound pressure (94 dB). After manually scoring the sleep stages, we calculated the distribution of the sound pressure level during the examination time excluding all full-awake time using a computer program. In this analysis, we included epochs adjoining sleep epochs even when they were scored as stage awake, because we thought these epochs could contain significant snoring sounds. We determined 3 levels of ambient sound pressure: L1, L5, and L10, corresponding to the highest 1, 5, and 10 percentile sound pressure levels,7 respectively. In addition, we calculated the mean sound pressure level (Leq). The ambient sound measurements were not used to determine the duration of snoring because we thought that the tracheal sound spectrograph recordings, which can identify snoring sounds regardless of the intensity, would be more appropriate for this purpose than the ambient sound pressure levels recorded using the sound level meter.
Statistical Analysis
The relationships between variables of snoring sound intensity and subjective sleepiness (ESS) were evaluated using Pearson correlation coefficients and scatter plots. The relationships between snoring sound intensity and other variables were assessed using Pearson correlation coefficients (r) or Spearman rank relation coefficients (rs), depending on the normality of the distribution. Differences in characteristics among snoring intensity quartile groups as well as AHI quartile groups were determined using a one-way analysis of variance (ANOVA) and Bonferroni post hoc test, with p < 0.05 considered significant. A multivariate regression analysis was used to elucidate the independent relationship between snoring sound intensity and the ESS after adjustments for AHI and other possible confounders. A stepwise multivariate regression analysis was used to determine the contribution of the snoring sound intensity to the ESS in a best-fit statistical model.
RESULTS
Patient Characteristics
Patient characteristics are presented in Table 1. As the median AHI was 15.6, we classified the subjects into a non-to-mild OSA group (AHI < 15; n = 246) and a moderate-to-severe OSA group (AHI ≥ 15; n = 261) to elucidate the effect of OSA severity on the relationship between snoring intensity and sleepiness in subsequent analyses. There were no patients with central sleep apnea.
Table 1.
Patient Characteristics
| All | AHI < 15 | AHI ≥ 15 | |
|---|---|---|---|
| N | 507 | 246 | 261 |
| Male, % | 93 | 88 | 97 |
| Age, years | 45.4 (13.2) | 43.4 (13.3) | 47.2 (12.8) |
| BMI, kg/m2 | 26.2 (4.3) | 24.6 (3.2) | 27.8 (4.6) |
| ESS | 10.6 (5.3) | 10.4 (5.2) | 10.8 (5.5) |
| Sleep efficiency, % | 0.82 | 0.85 | 0.80 |
| [0.71,0.90] | [0.73,0.91] | [0.70,0.89] | |
| AHI, /h | 15.6 | 5.2 | 38.3 |
| [5.5, 40.2] | [1.5,9.4] | [25.0,61.0] | |
| SFI | 15.0 (8.2) | 11.3 (5.2) | 18.5 (8.9) |
| Snoring time (%TST) | 15.2 (9.0) | 12.0 (8.4) | 18.2 (8.6) |
| Ambient sound | |||
| Leq, dB | 45.6 (4.5) | 43.2 (2.9) | 47.9 (4.6) |
| L10, dB | 46.1 (4.7) | 43.8 (3.1) | 48.2 (4.9) |
| L5, dB | 48.4 (5.8) | 45.2 (3.7) | 51.4 (5.8) |
| L1, dB | 53.2 (7.3) | 48.7 (4.7) | 57.3 (6.8) |
| %Time SPL > 50dB | 1.9 | 0.4 | 5.5 |
| [0.3,7.1] | [0.1,1.4] | [2.1,10.6] | |
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Abbreviations: BMI, body mass index; ESS, Epworth Sleepiness Scale; AHI, apnea-hypopnea index; SFI, sleep fragmentation index; TST, total sleep time; Leq, mean sound pressure level; L10, L5, L1, the highest 10, 5, 1 percentile ambient sound pressure levels, respectively; SPL, sound pressure level. Data are expressed as mean (SD) for normally distributed variables, otherwise as median [interquartile range].
Correlation Between Snoring Sound Intensity and ESS
No relationship between snoring time and ESS was observed. However, all the variables of snoring intensity were weakly, but significantly, correlated with ESS in the overall patient population (Table 2). When this relationship was further examined in the non-to-mild and moderate-to-severe OSA groups, the correlation completely disappeared in the non-to-mild OSA group, whereas the correlation became even stronger in the moderate-to-severe OSA group (Table 2). The correlation coefficients between the 5 snoring variables and ESS were similar. We then performed various analyses in the moderate-to-severe OSA group using L1, which of all the snoring parameters had the highest correlation with the subjective intensity of snoring in the questionnaire (rs = 0.37), as the measure of snoring. The scatter plots for L1 and AHI vs. ESS in the moderate-to-severe OSA group are shown in Figure 1.
Table 2.
Correlation Coefficient Between Variables of Snoring and the Epworth Sleepiness Scale
| All | AHI <15 | AHI ≥15 | ||||
|---|---|---|---|---|---|---|
| R | p | R | p | R | p | |
| AHI | 0.175 | 0.0001 | −0.164 | 0.0098 | 0.333 | < 0.0001 |
| snoring time | 0.020 | > 0.2 | −0.060 | > 0.2 | 0.076 | > 0.2 |
| Leq | 0.203 | < 0.0001 | −0.070 | > 0.2 | 0.385 | < 0.0001 |
| L10 | 0.193 | < 0.0001 | −0.074 | > 0.2 | 0.354 | < 0.0001 |
| L5 | 0.199 | < 0.0001 | −0.065 | > 0.2 | 0.375 | < 0.0001 |
| L1 | 0.190 | < 0.0001 | −0.063 | > 0.2 | 0.383 | < 0.0001 |
| %Time SPL > 50dB | 0.236 | < 0.0001 | 0.027 | > 0.2 | 0.358 | < 0.0001 |
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Abbreviations: AHI, apnea-hypopnea index; Leq, mean sound pressure level; L10, L5, L1, the highest 10, 5, 1 percentile ambient sound pressure levels, respectively; SPL, ambient sound pressure level
Figure 1.
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The patient characteristics and ESS data according to the L1 quartiles as well as the AHI quartiles are given in Table 3. The ESS, as well as the BMI and AHI, were higher in the higher L1 quartiles. The ESS, BMI, and L1 also tended to be higher in the highest AHI quartile than in the lower AHI quartiles.
Table 3.
Subject Characteristics and ESS Data for L1 and AHI Quartiles
| AHI Quartile | 1:15.1–24.8 | 2:25–38.2 | 3:38.3–60.7 | 4:60.8–119.5 | ||||
|---|---|---|---|---|---|---|---|---|
| Mean | SD | Mean | SD | Mean | SD | Mean | SD | |
| Age, y | 48.7 | 12.9 | 48.4 | 12.8 | 49.1 | 13.0 | 42.6*,1,2,3 | 11.6 |
| BMI, kg/m2 | 26.5 | 3.8 | 26.2 | 3.3 | 27.2 | 4.0 | 31.3*,1,2,3 | 5.2 |
| AHI, /h | 19.1 | 2.9 | 30.9 | 3.7 | 48.9 | 6.2 | 78.7 | 14.1 |
| L1, dB | 52.8 | 4.8 | 54.6 | 4.3 | 57.3*,1,2 | 5.1 | 64.5*,1,2,3 | 6.1 |
| ESS | 9.7 | 4.9 | 9.7 | 5.0 | 10.6 | 5.3 | 13.1*,1,2,3 | 6.0 |
| Snoring (L1) Quartile | 1:43.4–52.2 | 2:52.3–56.3 | 3:56.3–61 | 4:61.2–76.7 | ||||
| Mean | SD | Mean | SD | Mean | SD | Mean | SD | |
| Age, y | 50.6 | 12.7 | 50.4 | 14.0 | 46.4 | 11.9 | 41.5*,1,2 | 10.2 |
| BMI, kg/m2 | 25.3 | 2.9 | 26.5 | 4.0 | 28.2*,1,2 | 3.8 | 31.1*,1,2,3 | 5.2 |
| AHI, /h | 27.3 | 11.1 | 37.1*,1 | 18.0 | 46.1*,1,2 | 20.9 | 67.4*,1,2,3 | 23.1 |
| L1, dB | 49.6 | 2.0 | 54.4 | 1.2 | 58.5 | 1.4 | 66.7 | 3.9 |
| ESS | 8.8 | 5.0 | 9.3 | 4.9 | 11.7*,1,2 | 5.0 | 13.3*,1,2 | 5.6 |
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Abbreviations: AHI, apnea–hypopnea index; BMI, body mass index; L1, the highest 1 percentile ambient sound pressure level; ESS, Epworth Sleepiness Scale.
*
Statistically different from the 1st (*1), 2nd (*2), or 3rd quartiles (*3)
Correlation between Snoring Sound Intensity and Possible Confounders
We examined the correlation between L1 and possible confounders of the relationship between snoring and ESS in the moderate-to-severe OSA group. L1 was significantly correlated (p < 0.0001) with age (r = −0.29), body mass index (BMI; r = 0.52), AHI (r = 0.68), and CT90 (square root transformed; r = 0.71). We considered insufficient sleep in daily life, which may enhance both snoring intensity and sleepiness, to be another possible confounder. However, L1 was not significantly correlated (p > 0.05) with daily sleep time (r = 0.03) or sleep efficiency (rs = 0.11).
Independent Correlation between Snoring Sound Intensity and Sleepiness
A multiple regression analysis was used to analyze the relationship between L1 and ESS after adjustments for possible confounders in the moderate-to-severe OSA group (Table 4). The severity of OSA was considered to be the most influential confounder. Therefore, we performed a multiple regression analysis using ESS as the dependent variable and AHI and L1 as independent variables. As a result, L1 was shown to be related to ESS in an independent manner. Similar results were obtained when age, BMI, and CT90—in addition to AHI and L1—were used as independent variables. In addition, to exclude the possibility that the relationship was caused by the selection of the AHI cutoff value, the same analyses were repeated for subjects with mild-to-severe OSA (AHI ≥ 5). As a result, the relationships between L1 and ESS were almost the same as above (β = 0.212, p = 0.00005 when adjusted for AHI; β = 0.140, p = 0.018 when adjusted for age, BMI, CT90, and AHI).
Table 4.
Multiple Regression Analysis for the Epworth Sleepiness Scale in Patients with Obstructive Sleep Apnea (AHI ≥ 15)
| Variables | β | SE | p | R2 | Adjusted R2 |
|---|---|---|---|---|---|
| Model 1 | |||||
| AHI | 0.0310 | 0.0177 | 0.0817 | 0.157 | 0.150 |
| L1 | 0.235 | 0.063 | 0.0002 | ||
| Model 2 | |||||
| Age | −0.0788 | 0.0263 | 0.0030 | 0.194 | 0.178 |
| BMI | −0.121 | 0.084 | 0.1521 | ||
| AHI | 0.0121 | 0.0214 | 0.5732 | ||
| CT90 | 0.459 | 0.263 | 0.0826 | ||
| L1 | 0.182 | 0.069 | 0.0093 | ||
| Model 3 | |||||
| Daily sleep time | −0.711 | 0.286 | 0.0134 | 0.239 | 0.222 |
| Snoring frequency | 0.679 | 0.227 | 0.0030 | ||
| Nasal obstruction | 0.891 | 0.297 | 0.0029 | ||
| CT90 | 0.495 | 0.219 | 0.0244 | ||
| L1 | 0.165 | 0.066 | 0.0133 | ||
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Definition of abbreviations: AHI, apnea–hypopnea index; L1, the highest 1 percentile ambient sound pressure level; BMI, body mass index; ESS, Epworth Sleepiness Scale; CT90, cumulative time while SpO2 < 90% expressed as a percentage of the total examination time; β, regression coefficient; SE, standard error for the regression coefficient
Snoring Sound Intensity and Sleep Architecture
L1 was significantly correlated with the percentages of stage 1 sleep time (r = 0.238, p = 0.0001), stage 2 sleep time (r = −0.181, p = 0.0034), and REM sleep time (r = −0.225, p = 0.0002) in the moderate-to-severe OSA group. However, the correlations disappeared after adjustment for AHI. L1 was not significantly correlated with the percentage of slow wave sleep (SWS; stage 3 + stage 4) time or SFI. In contrast, AHI was more strongly correlated with all these variables (% stage 1: r = 0.467, % stage 2: r = −0.382, % REM: r = −0.388, % SWS: r = −0.154, SFI: r = 0.322).
Snoring Sound Intensity and Pulse Rate
L1 was significantly correlated with the mean value (r = 0.424, p < 0.0001) and the coefficient of variation (CV; r = 0.263, p < 0.0001) of the pulse rate during PSG. The correlation between L1 and the mean pulse rate persisted after adjustments for confounding variables including sex, age, BMI, and AHI, whereas that between L1 and CV was lost after adjustments were made. Moreover, AHI was correlated with the mean pulse rate (r = 0.347, p < 0.0001) and the CV (r = 0.285, p < 0.0001). However, both correlations became insignificant after adjustments for confounding variables including sex, age, BMI, and L1.
Stepwise Multiple Regression Analysis
Various possible determinants of sleepiness were entered into a forward stepwise multiple regression analysis using the ESS score as the dependent variable (Table 4). The variables entered included sex, age, BMI, AHI, CT90 (square root transformed), SFI, pulse rate (mean, CV), L1, daily sleep time, subjective frequency of snoring, and degree of nasal obstruction symptoms. The number of the patients used for the analysis was 223. As a result, CT90, L1, frequency of snoring, degree of nasal obstruction symptoms and daily sleep time were adopted as significant determinants. The partial coefficients of determination (partial R2) were 9.0%, 6.1%, 5.0%, 2.6%, and 1.3% for CT90, L1, frequency of snoring, degree of nasal obstruction symptoms, and daily sleep time, respectively.
DISCUSSION
The main finding of this study is that the sound intensity of objectively measured snoring was independently correlated with subjective sleepiness, as measured by ESS, in patients with OSA. Subjective sleepiness was better explained by snoring intensity than by AHI. To our knowledge, this is the first study to show an independent relationship between the intensity of snoring sounds and sleepiness using PSG with sound measurements.
Earlier studies showed a correlation between the AHI and subjective sleepiness, as measured by the ESS,9,15 as well as objective sleepiness, as measured by the multiple sleep latency test.16–18 However, this correlation was reported to be relatively weak (r2 = 0.11) in a large-scale study in a clinical population17 and insignificant in other studies.19,20 Thus, AHI can explain only a small part of the variance in sleepiness in patients with OSA. Other variables related to OSA severity, including nocturnal hypoxemia and sleep fragmentation, are also known to be determinants of sleepiness.18,21,22 In the present study, snoring intensity and AHI together could explain the variance of the ESS by 15%. Furthermore, a multivariate model determined using a stepwise multiple regression analysis, which included snoring intensity, desaturation severity, daily sleep time, and subjective snoring frequency and nasal obstruction symptom as independent variables, explained 22% of the variance of the ESS. These facts indicate that not only OSA severity, but also snoring intensity contribute to sleepiness and that subjectively measured sleep time and frequency of snoring are important as the determinants of dozing propensity in daily life.
Although snoring intensity was related to sleepiness in the moderate-to-severe OSA group, snoring intensity and sleepiness were not correlated in the non-to-mild OSA group. Several possible reasons for this may be considered. The most likely explanation is a referral bias of the patients. The patients were not a sample from the general population, but patients with symptoms. Therefore, patients in the non-to-mild OSA group, some of whom may have a trait susceptible to sleep loss and/or suffer from short sleep time, tended to have sleepiness regardless of the severity of their breathing abnormality during sleep. Another possible reason is that snoring intensity is related to sleepiness only when considerable apnea/hypopnea coexists. To elucidate this issue, the relationship between snoring sound intensity and sleepiness in the general population should be examined.
One of the potential mechanisms underlying the relationship between snoring sound intensity and sleepiness is sleep fragmentation caused by increased upper airway resistance during high-intensity snoring. However, L1 was not correlated with a parameter of sleep fragmentation (SFI), and the correlations between L1 and parameters of sleep architecture were lost after adjusting for the AHI. Moreover, all the variables of sleep fragmentation and sleep architecture were more strongly correlated with the AHI, which seemed to be less correlated with the ESS than the L1. Thus, we do not think that sleep fragmentation is a major cause of sleepiness related to snoring. Another possible mechanism is the high intrathoracic negative pressure during inspiration that generates intense snoring, since the intensity of snoring is reported to be positively correlated with the amplitude of intraesophageal pressure swings.23 Zamagni et al. has reported that the respiratory effort during apnea is correlated with sleepiness but not with parameters of sleep fragmentation.24 Another study by Pelin et al. also showed that respiratory efforts during apnea were most strongly correlated with the ESS among the various variables of PSG in patients with OSA.25 An interesting finding in the current study is the relationship between L1 and the pulse rate during PSG. The mean pulse rate was correlated with L1 even after adjustments for confounding variables, whereas the correlation between the AHI and the mean pulse rate was weak and lost after adjustments for confounding variables. A recent study by Sumi et al. has shown that the mean heart rate was correlated with the severity of OSA and decreased after treatment with nasal continuous positive airway pressure. This suggests that the mean heart rate is related to the pathophysiology of OSA.26 Although we cannot clearly explain the implications of the relationship between L1 and the mean pulse rate, we think that the increased work of breathing during sleep, which could increase the pulse rate, is a possible cause of daytime sleepiness.
This study has a few limitations that should be addressed. The most important limitation is that this study was performed using a clinic sample, and the results, therefore, cannot be extended to the general population. This study cannot answer the important question of whether intense snoring without apnea/hypopnea is related to sleepiness. The snoring measurements may represent another possible limitation. No standard method of quantifying snoring intensity exists. We selected L1, which was defined as the top one percentile ambient sound pressure level during sleep, as the parameter used to evaluate snoring sound intensity in this study. Although L1 is considered to reflect snoring sound intensity in most cases, it is possible that L1 may reflect sounds other than snoring, such as bruxism, coughing, and talking in one's sleep. Finally, we used the ESS as a subjective measure of sleepiness. Untreated, sleepy patients with OSA are known to have a tendency to underestimate their subjective sleepiness.27 Therefore, the relationship between snoring intensity and objective sleepiness could be different from the result of the current study.
In conclusion, we demonstrated that objectively measured snoring intensity was correlated with subjective sleepiness independently of the AHI. The relationship was demonstrated only in patients with moderate to severe OSA. Further studies of the general population are needed to elucidate the exact relationship between snoring and sleepiness.
DISCLOSURE STATEMENT
This was not an industry supported study. The authors have indicated no financial conflicts of interest.
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