The Snoring Spectrum: ConclusionFrom our study sample, two other important anatomical determinants were associated with higher snoring sound intensity levels: a higher BMI and narrow pharyngeal passages.
We hypothesized that snoring sound intensity would have a negative association with sleep quality. Our data partially supports this hypothesis. Varying degrees of snoring sound intensity levels resulted in significant differences in the polysom-nographic markers of sleep quality. Specifically, the percentages of SWS were significantly lower in patients with peak L1 or L5 values of a 55 dBA, compared to patients with L1 or L5 values of < 55 dBA. Sleep latency was significantly lower in patients with L1, L5, and Leq values a 55 dBA, compared to patients with L1, L5, and Leq values of < 55 dBA. Read the rest of this entry »

We have shown that women do not snore as loudly as men. The difference between the mean Leq value for men and women was 3.0 dBA, which translates into a substantially higher sound intensity perception for the listener. This gender effect on snoring sound during sleep was independent of the severity of sleep-disordered breathing and body mass. Women also had lower peak intensity values. For example, men presented L1 values that were 2.7 dBA louder than those for women. This finding stands in contrast to data from Metes et al, who reported that there was no difference in the maximal snoring sound intensity levels between 77 women and 293 men who were studied prospectively during sleep. It is not clear what accounts for this difference in results. Clearly, there were differences in the methods used to measure snoring sound intensity. Our data were based on the complete distribution of sound intensity over time, and Metes et al used the maximal snoring sound intensity reported during the recording period. Read the rest of this entry »

The Snoring Spectrum: DiscussionThe same equipment was used to measure and record snoring sound intervals for all study patients. While each recording was made, technicians subjectively verified that the noisy breathing sounds being recorded were made by snoring. The acoustic analyses of the snoring sound intensity data were performed using methods that are used by OSHA to determine the intensity of noise pollution in the workplace, and by other governmental agencies, including the MPCA, to monitor environmental noise. These methods had not been used previously for sleep study purposes. Government and industrial hearing conservation programs based on OSHA standards recommend that hearing protection be used if the average sound intensity reaches 85 dBA for > 8 h, and mandate that hearing protection be used at levels of > 90 dBA for > 8 h. Read the rest of this entry »

Multivariate Logistic Regression Analyses
Multivariate logistic regression analyses measured the relative strength of the associations among the RDI categories (an RDI of > 10 or < 10), the snoring sound intensity levels, and a variety of demographic and clinical factors (Table 5). Independent variables were selected for the model based on their univariate relationship with the RDI categories, the dependent variable. Independent variables with strong colinearity with other independent variables were taken out of the model. Regression results show that among the factors included in the model, snoring sound intensity levels, obesity status, and gender had the strongest associations with the RDI categories. Read the rest of this entry »

The Snoring Spectrum: Snoring Sounding Intensity During Sleep and Clinical FactorsSnoring Sounding Intensity During Sleep and Clinical Factors
The clinical information regarding the chief complaint was available for 682 of the study participants (Table 1). Table 4 shows the sound intensity levels for three chief complaint categories: snoring, hypersomnolence, and breathing stoppage. Patients with breathing stoppage had significantly higher snoring sound intensity levels than patients with snoring or hypersomnolence (p < 0.001). Patients with snoring or hypersomnolence had similar Leq, L1, and L5 values (p > 0.283). Read the rest of this entry »

The relationships between snoring sound intensity and demographic factors, the BMI, gender, and age were examined. Univariate analyses revealed that the BMI and gender were significantly related to all sound intensity levels (Table 2). The BMI had a positive association with snoring sound intensity levels, with a Pearson correlation coefficient for the Leq, L1, L5, and L10 values, respectively, of 0.30, 0.29, 0.28, and 0.24 (p < 0.0001). Men were significantly louder snorers than women. The relationship between snoring sound intensity levels and the BMI remained statistically significant after controlling for gender (p < 0.001). No correlation was found between snoring sound intensity levels and age for the Leq, L1, L5, and L10 values, respectively: 0.08, 0.05, 0.01 and 0.06. Read the rest of this entry »

The Snoring Spectrum: Statistical AnalysisStatistical Analysis: The results were expressed as percentages and means (± SD) or 95% confidence intervals (CIs). Hypothesis tests were used to evaluate the presence of statistical significance among the groups. The likelihood ratio x2 test and the proportion Z test were used for categorical data analysis. Nonparametric testing was used for continuous variables with a nongaussian distribution. Multivariate logistic regression analysis and partial correlation coefficients were used to determine the independent effects of selected variables on the dependent variables. A p value of < 0.05 was considered statistically significant. Read the rest of this entry »

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