Quantitative electroencephalography Spectral Power and Emotional Disturbances in Children with Sleep Disordered Breathing

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This study aimed to establish associations of quantitative electroencephalography (qEEG) alterations during different sleep stages with depression and anxiety in children with SDB. Methods A total of 147 children aged 3–12 years with SDB were included in the study. They were divided into two groups: primary snoring (n = 88, 44% female) and obstructive sleep apnea (n = 59, 34% female). Children underwent whole-night polysomnography (PSG) at the hospital, during which quantitative electroencephalography (qEEG) data were acquired. Prior to the test, parents of SDB children completed the Obstructive Sleep Apnea Questionnaire-18 (OSA-18), the Spence Children’s Anxiety Scale–Parent version (SCAS-P) or the Preschool Anxiety Scale (PAS), and the Children's Depression Inventory (CDI). Results Compared to the PS group, the OSA group had lower mean SpO2, sleep duration and efficiency. Sleep efficiency mediated the association between the OSA/PS exposure and the OSA-18 outcome, with the negative estimate of -1.514 (95% CI: -3.658, -0.01; p < .01). OSA children exhibited higher CDI scores compared to the PS children of the same age. Notably, the NREM3 EEG slowing ratio was negatively correlated with anxiety levels, and the NREM2 EEG slowing ratio was negatively correlated with depressive symptoms. Conclusions QEEG alterations during different sleep stages are linked to emotional disturbances of children suffering from SDB. The EEG slowing ratio in NREM sleep may be a useful indicator for the nocturnal electrophysiology in children with SDB, potentially linked to emotional disturbances. sleep disordered breathing child polysomnography anxiety depression Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Highlights Decreased EEG slowing ratio during different sleep stages was associated with emotional disturbances in children with sleep disordered breathing. Sleep efficiency mediated the association between obstructive sleep apnea and the quality of life in childhood. Our findings highlight early detection of emotional disturbances in children with sleep disordered breathing, ultimately enhancing the quality of life for children. 1. Introduction Sleep disordered breathing (SDB) is common in children, characterized by alterations in breathing during sleep [ 1 ] . In children, SDB is described as a spectrum [ 2 ] , regardless of the disease severity, children with SDB face an elevated risk of psychological comorbidities [ 3 ] , most commonly anxiety and depression, which are believed to be the consequence of the repeated cycles of hypoxia followed by reperfusion, hypercarbia, and sleep fragmentation [ 4 ] . In addition, studies in children with OSA have shown that the longer the duration of the OSA course and hypoxia, the greater the impact on symptoms of anxiety and depression, and the higher the risk of anxiety and depression occurring in adulthood, which can cause serious impairments of social interaction, work abilities, health condition and other adult functions [ 5 – 7 ] . Remarkably, some scholars have found that adenotonsillectomy (AT) significantly assuages the emotional symptoms and has a positive impact on the overall quality of life of OSA children [ 6 , 8 , 9 ] . Thus, clinicians need to pay more attention to emotional disturbances of children with SDB and to treat promptly in order to reduce the occurrence of psychological comorbidities and avoid non-reversible deficits. The evaluation of OSA children’s mental health has historically relied on subjective questionnaires which is limited by its dependence on parents’ accurate memory and correct attribution of ambiguous symptoms [ 10 ] . Therefore, objective methods are needed to more accurately evaluate mental disturbances. Polysomnography (PSG) is the gold standard for the diagnosis of SDB. Quantitative electroencephalogram (qEEG), employing mathematical algorithms to compute numerical features from specific EEG components, can meticulously and distinctly reveal the underlying neurobiological mechanisms of emotional disturbances [ 11 – 16 ] . QEEG is especially useful for detecting subtle brain activity changes that traditional methods may miss [ 17 ] . Sleep is divided into rapid eye movement (REM) sleep and non-rapid eye movement (NREM) sleep, with NREM sleep further subdivided into N1, N2, and N3 stages. Each stage is crucial for children’s growth, metabolism, memory, and mental health. Studies have shown that sleep spindles, the characteristic EEG signatures of N2 sleep, mediate memory consolidation [ 18 ] , while another study revealed that children with PS exhibited significantly reduced sleep spindle activity across all NREM stages [ 19 ] . Further evidence showed that the global theta/beta ratio during the NREM period in the first sleep cycle of SDB children was positively correlated with inattention score, emphasizing the link between EEG alterations and cognitive impairments [ 20 ] . While numerous studies have investigated correlation between EEG characteristics and cognitive dysfunctions in patients with SDB, a notable gap exists in the current research landscape. Specifically, the majority of current research focus on adult patients, behavioral deficits, and cognitive impairments, with relatively fewer studies paying attention to the emotional disturbances of children with SDB. Therefore, our research aimed to explore the relationship between emotional disturbances and qEEG alterations during different sleep stages in SDB children with varying degrees of disease severity. We hypothesized that emotional disturbances, sleep architecture, and SDB metrics will exhibit variances among different severities of SDB. Additionally, we hypothesize that qEEG parameters, such as EEG slowing ratio and the power of frequency bands, are related to emotional disturbances in children with SDB. 2. Methods 2.1 Participants and procedures In this cross-sectional study, children presenting with symptoms of SDB from December 2020 to May 2024 at the Otolaryngology Department of Shanghai Children’s Medical Center were enrolled. After the preliminary evaluation by specialists, these children conducted a whole-night PSG at hospital. Prior to PSG, the caregivers and their children fulfilled three questionnaires concerning children’s depression, anxiety, and SDB symptoms with the instruction of a professional researcher. We split the cohort in two subgroups based on AHI common cutoffs: PS (AHI<1 event/h, N = 88), and OSA (AHI ≥ 1 event/h, N = 59). Inclusion criteria required having SDB symptoms or signs and completing PSG and all questionnaires. The exclusion criteria were as follows: (ⅰ) history of surgery or medication treatment for SDB; (ⅱ) cardiac diseases; (ⅲ) acute infection phase of respiratory diseases; (ⅳ) psychiatric or psychological disorders; (ⅴ) age either over 12 or below 3 years; (ⅵ) significant artifacts in EEG data. Informed consent was obtained from all caregivers before inclusion in the study. This study was performed following the principle of the Declaration of Helsinki, and the protocol had been approved by the Institutional Review Board of Shanghai Children’s Medical Center, Shanghai Jiao Tong University School of Medicine (SCMCIRB-K2023105-1). 2.2 Polysomnography All participants underwent one overnight PSG at the hospital using the SOMNOtouch RESP (SOMNO medics Corporation, Germany), a 13-channel device. All sleep architecture variables and sleep stages were recorded and assessed by a certified technician according to the standard criteria of the American Academy of Sleep Medicine. Sleep related parameters were calculated and reported. The sleep stages were divided into the wake stages, NREM (N1, N2, and N3) sleep and REM sleep. Given the special characteristics of children’s sleep structure, we have chosen to mainly focus on N2, N3 and REM sleep stages. 2.3 EEG pre-processing and feature extraction We obtain two-channel EEG data (Fp1, Fp2) from PSG recordings, sampled at a rate of 256 Hz. MATLAB software (R2024a) was used for processing and extraction of EEG features from the entire night’s EEG data. We imported EEG data in European data format (EDF) to MATLAB and band-pass filtered it within 0.2–35 Hz. The transitions between sleep stages were converted into plain text format and subsequently matched with EEG recordings. Artifact removal was conducted independently by two experienced technicians. Independent component analysis and average re-reference were performed. Eventually, we utilized a fast Fourier transform with a Hann windows (30-second epochs) to extract the absolute power of each EEG wave. Subsequently, we calculated the relative power ,the EEG slowing ratio, theta/beta ratio (TBR) and theta/alpha ratio (TAR) [ 21 ] . Specifically, every band frequency was defined as follows: δ (delta, 0.5-4 Hz); θ (theta, 4–8 Hz); α (alpha, 8–12 Hz); σ (sigma, 12–14 Hz); and β (beta, 14–30 Hz). 2.4 Questionnaires 2.4.1 Children’s Depression Inventory (CDI) The Children’s Depression Inventory (CDI) assess depression in children and adolescents through 27 items across five subscales: anhedonia, ineffectiveness, interpersonal problems, negative mood, and negative self-esteem [ 22 ] . Each item is rated from 0 to 2, with total scores ranging from 0 to 54. A cutoff score of 16 has been proved to offer optimal sensitivity and specificity for screening depression [ 22 ] . The Chinese version has high validity and reliability, with Cronbach’s alpha values ranging from 0.85 to 0.89 [ 23 ] . The CDI in our study had a Cronbach alpha of 0.93. 2.4.2 The Spence Children’s Anxiety Scale-Parent version (SCAS-P) & Preschool Anxiety Scale (PAS) The Spence Children’s Anxiety Scale-Parent version (SCAS-P) assesses anxiety severity in children across six domains, including panic attack and agoraphobia, separation anxiety, physical injury fears, social phobia, obsessive compulsive disorder, and generalized anxiety disorder. Caregivers rated their children’s anxiety symptoms on a 4-point scale from 0 (never) to 3 (always), with a maximum score of 114. In addition, scholars have proved that the SCAS is suitable for assessing anxiety in Chinese children [ 24 ] , with a cutoff score of 18. The Cronbach’s alpha of current survey was 0.95. Preschool Anxiety Scale (PAS) specifically assesses anxiety symptoms in preschool children (≤ 6 years) [ 25 ] . Caregivers rate responses on a 5-point scale ranging from 0 (not at all true) to 4 (very often true). The maximum possible score is 112, with a cutoff of 48 [ 25 ] . In our test, PAS had a Cronbach’s alpha of 0.94. 2.4.3 The Obstructive Sleep Apnea Questionnaire-18 (OSA-18) The Obstructive Sleep Apnea Questionnaire-18 (OSA-18) is used to evaluate pediatric SDB in 5 domains: sleep disturbance, physical suffering, emotional distress, daytime problems, and caregiver concerns. Each item is rated from 1 (None of the time) to 7 (All of the time), with scores over 60 showing a moderate or large impact on health-related quality of life (HRQL). The Chinese version is reliable for early detection of SDB symptoms in children [ 26 ] , and in this study, the Cronbach’s alpha was 0.90. 2.5 Statistical analysis Analysis was performed using R version 4.2.1. Exploratory descriptive statistics identify the data distribution and bivariate relationship. Frequency and proportions tables were implemented to measure the distribution of individuals among all variables of the study interest and identify any missing entries. As variables were non-normally distributed, the non-parametric Wilcoxon rank-sum test was used, reporting medians and IQR. Chi-square significance test of independence and homogeneity was performed for categorical variables. Simple linear regression was conducted to analyze the unadjusted association between the primary exposure of OSAS or PS assignment and the outcome of CDI, PASsum and/or SCAS-P sum, and OSA-18. A partial F-test was conducted to assess the model fit by comparing the fully adjusted and nested/reduced models. Multiple linear regression (MLR) was implemented to analyze the association through the inclusion of independent predictors and the exclusion of collinear terms to build optimal predictive models. 3. Results 3.1 Demographics and PSG No missing values were found in the data (Table 1 ). The median ages and sex proportions did not differ significantly between OSA and PS groups. However, mean SpO2, sleep duration, and efficiency were significantly higher in the PS group compared to OSAS (Table 1 ; Fig. 1 ). Spearman correlation matrices (Figs. 2 a-b) indicated positive correlations between REM and NREM characteristics and sleep efficiency/duration (p<0.05). Due to multicollinearity, REM and NREM characteristics were excluded from the regression models, and sleep efficiency was used as the sole sleep characteristic. Table 1 Demographic, Polysomnographic Characteristics and Questionnaire Score of All the Participants Variable N OSAS, N = 59 1 PS, N = 88 1 p-value 2 Demographics Age 47 6.00 (4.00, 7.00) 5.00 (4.00, 6.25) 0.4 Age group 47 0.8 ≤ 6 years 43 (73%) 66 (75%) > 6 years 16 (27%) 22 (25%) Sex 47 0.2 Male 39 (66%) 49 (56%) Female 20 (34%) 39 (44%) Polysomnographic Characteristics Mean SpO2 (%) 47 99.00 (98.00, 99.00) 99.00 (99.00, 99.00) 0.011 Sleep duration (min) 47 495 (432, 535) 521 (473, 561) 0.017 Sleep efficiency (%) 47 91 (85, 95) 94 (88, 97) 0.014 REM incubation period (min) 47 80 (59, 119) 72 (49, 97) 0.053 REM sustaining time (min) 47 80 (60, 90) 82 (70, 95) 0.073 REM period (%) 47 15.7 (13.6, 17.4) 15.9 (14.0, 18.2) 0.4 NREM sustaining time (min) 47 417 (358, 456) 429 (392, 468) 0.049 NREM period (%) 47 84.3 (82.7, 86.5) 84.2 (81.8, 86.0) 0.4 Relative Spectral Power and Frequency Band Ratios NREM2 relative theta (4–8 Hz) 147 0.084 (0.065, 0.101) 0.086 (0.065,0.105) 0.7 relative delta (1–4 Hz) 147 0.86 (0.82, 0.88) 0.85 (0.82, 0.89) 0.7 relative alpha (8–12 Hz) 147 0.030 (0.022, 0.041) 0.027 (0.020, 0.038) 0.3 relative beta (15–20 Hz) 147 0.018 (0.015, 0.022) 0.019 (0.015, 0.023) 0.6 relative sigma (12–15 Hz) 147 0.006 (0.005, 0.009) 0.006 (0.005, 0.007) 0.2 TAR 147 2.70 (2.15, 3.75) 3.06 (2.25, 3.93) 0.2 TBR 147 4.00 (3.24, 6.30) 4.53 (3.55, 5.78) 0.3 EEG slowing 147 17 (13, 21) 17 (14, 24) 0.2 NREM3 relative theta 147 0.064 (0.049, 0.076) 0.063 (0.054, 0.076) 0.7 relative delta 147 0.914 (0.900, 0.936) 0.917 (0.899, 0.930) 0.7 relative alpha 147 0.011 (0.008, 0.015) 0.011 (0.008, 0.016) > 0.9 relative beta 147 0.0039 (0.0028, 0.0055) 0.0041 (0.0032, 0.0053) 0.6 relative sigma 147 0.0018 (0.0013, 0.0025) 0.0018 (0.0014, 0.0024) > 0.9 TAR 147 5.99 (3.90, 7.51) 5.68 (4.14, 7.59) 0.9 TBR 147 16 (12, 21) 16 (12, 20) 0.9 EEG slowing 147 60 (43, 75) 56 (44, 73) > 0.9 REM relative theta 147 0.043 (0.037, 0.061) 0.046 (0.036, 0.063) > 0.9 relative delta 147 0.92 (0.91, 0.94) 0.93 (0.91, 0.95) 0.7 relative alpha 147 0.010 (0.008, 0.016) 0.010 (0.008, 0.014) 0.5 relative beta 147 0.008 (0.006, 0.011) 0.008 (0.006, 0.012) 0.7 relative sigma 147 0.0021 (0.0017, 0.0037) 0.0024 (0.0016, 0.0030) 0.9 TAR 147 4.49 (3.77, 5.27) 4.71 (3.90, 5.45) 0.4 TBR 147 4.94 (3.85, 7.55) 5.34 (4.24, 7.60) 0.3 EEG slowing 147 50 (30, 59) 46 (35, 65) 0.5 Total Sleep relative theta 147 0.057 (0.049, 0.071) 0.066 (0.054, 0.080) 0.073 relative delta 147 0.910 (0.894, 0.926) 0.904 (0.877, 0.919) 0.2 relative alpha 147 0.015 (0.012, 0.021) 0.015 (0.011, 0.020) 0.4 relative beta 147 0.0094 (0.0078, 0.0115) 0.0094 (0.0073, 0.0110) 0.5 relative sigma 147 0.0035 (0.0024, 0.0043) 0.0031 (0.0024, 0.0040) 0.4 TAR 147 3.81 (2.57, 4.94) 3.88 (2.95, 5.14) 0.3 TBR 147 6.18 (5.08, 7.89) 6.85 (5.25, 8.77) 0.1 EEG slowing 147 34 (27, 41) 32 (25, 43) 0.8 Outcome metrics score OSA-18 total score 147 60 (46, 74) 62 (48, 72) 0.9 OSA-18 binary 147 0.6 No 30 (51%) 41 (47%) Yes 29 (49%) 47 (53%) CDI total score 147 6.0 (1.0, 12.0) 3.0 (2.0, 7.0) 0.078 CDI binary 147 0.025 No 50 (85%) 84 (95%) Yes 9 (15%) 4 (4.5%) SPENCE total score 147 21 (12, 28) 19 (11, 28) > 0.9 1Median (IQR); n (%) 2Wilcoxon rank sum test; Pearson's Chi-squared test 3.2 Analysis on Sleep Efficiency Mediating the Impact of SDB on OSA-18 Cumulative incidence differences for OSA-18 from the linear regression adjusted for sex and age resulted in non-significant OSAS/PS results. Adjusting for sleep efficiency significantly altered the effect estimates for sex (-9.54, p < .001) and sleep efficiency (0.45, p < .01) (Table 2 ). Partial F-test results showed that the full model with sleep efficiency had a statistically lower SSE than the reduced model (p < .01) (Table 2 ). Incorporating mean SpO2 and EEG slowing ratios at different sleep stages did not yield significant effect estimates. The interaction between sleep efficiency and OSA/PS was also insignificant (p = 0.318) (Table 2 ). None of the interactions involving sex, age, and OSA/PS improved model fit or predictive power when adjusted further (Table 2 ). Table 2 OSA/PS-OSA-18 model (reduced and full adjusted for the additional sleep efficiency) Dependent variable: OSA-18 total score Reduced Adjusted for sleep efficiency Adjusted for sleep efficiency as an effect modifier Female -9.18*** -9.544*** -9.684*** (2.90) (2.825) (2.825) Age 0.18 0.232 0.232 (0.76) (0.740) (0.740) OSA group 0.23 1.739 1.739 (2.92) (2.891) (2.891) Sleep efficiency 0.453*** 0.453*** (0.156) (0.156) OSAS: Sleep efficiency 0.319 (0.319) Constant 62.92*** 21.372 38.193* (4.53) (14.990) (22.502) Observations 147 147 147 R2 0.07 0.119 0.125 Adjusted R2 0.05 0.094 0.094 Residual Std. Error 17.09 (df = 143) 16.663 (df = 142) 16.662 (df = 141) F Statistic 3.42** (df = 3; 143) 4.801*** (df = 4; 142) 4.042*** (df = 5; 141) Note: *p < 0.1; **p < 0.05; ***p < 0.01 Sleep efficiency was hypothesized as a mediator between OSA/PS treatments and childhood outcome metrics. Mediation analysis with sleep efficiency as the mediator revealed a significant average causal mediation effect between OSA/PS exposure and OSA-18 outcome (-1.514, 95% CI: -3.658, -0.01; p < .01) (Table 3 ), suggesting sleep efficiency mediated the relationship between OSA and OSA-18. Diagnostic plots confirmed no violations of assumptions (Fig. 3 ). Table 3 Bootstrapped mediation analysis between OSA/PS and OSA-18 with sleep efficiency as the mediator Nonparametric Bootstrap Confidence Intervals with the Percentile Method Effect Estimate 95% CI Lower 95% CI Upper p-value ACME -1.51* -3.66 -0.01 0.044 ADE 1.74 -4.30 7.84 0.536 Total Effect 0.23 -5.56 6.31 0.874 Prop. Mediated -6.73 -11.31 5.90 0.882 Sample Size Used: 147 Simulations: 1000 Significance codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘’ 1 Abbreviations: ACME, average causal mediation effect; ADE, average direct effect 3.3 Significant Interaction between Age and OSA/PS on CDI Scoring In the OSA/PS-CDI model, age was a significant interaction term (p < .05) alongside sex adjustment, yielding a significantly lower SSE (p < .05) (Table 4 ). The interaction showed that increasing age was associated with higher CDI risks in OSA children compared to PS (Table 4 ). OSA was linked to reduced CDI risks, but this was not significant (-3.65 units; p = 0.240) (Table 4 ). Adding sleep efficiency, mean SpO2, and EEG ratios resulted in non-significant models. The assumptions of the final model were met in diagnostic plots (Fig. 4 ). Table 4 OSA/PS-CDI model (reduced and full adjusted for the additional interaction term of group*age) CDI total score Reduced Adjusted for age as the effect modifier Female -1.254 -1.799* (0.982) (1.004) Age 1.089*** 0.493 (0.257) (0.381) OSA group 2.513 -3.649 (0.989) (3.092) Age: OSAS 1.109** (0.528) Constant -0.378 3.013 (1.537) (2.217) Observations 147 147 R2 0.171 0.196 Adjusted R2 0.154 0.174 Residual Std. Error 5.796 (df = 143) 5.728 (df = 142) F Statistic 9.855*** (df = 3; 143) 8.671*** (df = 4; 142) Note: *p < 0.1; **p < 0.05; ***p < 0.01 3.4 Correlation Analysis of EEG Slowing Ratio and Emotional Symptoms In the final model with OSAS*age interaction and NREM Stage 3 EEG slowing ratio, an antagonistic interaction occurred, with a combined effect of OSAS*age being less negative than expected (Table 5 ). The sum of expected effects was − 1.83, while the observed effect was − 1.54, suggesting age-related decline in OSA was mitigated (Table 5 ). Subgroup analysis showed that increasing age posed a higher risk for OSA children (Table 5 ). Mediation modeling with NREM EEG slowing ratio as the mediator was statistically insignificant. Nonetheless, the NREM3 EEG slowing ratio was significantly negatively correlated with PAS/SCAS-P sum (spearman’s rho = -0.68; p < .001), and NREM2 was negatively correlated with CDI (spearman’s rho = -0.59; p < .01) (Fig. 2 b). However, no significant differences in EEG slowing ratios were found between OSA and PS groups. Simple linear regression models did not demonstrate significant relationships between OSA/PS assignments and EEG slowing ratios. Table 5 OSA/PS-PASsum and/or SCAS-P sum model (reduced and full) and OSA/PS-stratified subgroup analyses (both unadjusted for the age as the effect modifier) SPENCE total score Reduced non-adjusted for N3EEG slowing Adjusted for N3EEG slowing PS subgroup analysis OSA subgroup analysis Female -4.053* -3.437 -3.978 -2.523 (2.235) (2.185) (2.788) (3.585) Age -2.172** -2.291*** -2.306*** 0.714 (0.848) (0.826) (0.850) (0.784) OSA group -17.729** -17.382** (6.880) (6.697) N3EEG Slowing -0.115 -0.102* -0.131** (0.038) (0.052) (0.057) Age: OSAS 3.110*** 3.087*** (1.175) (1.143) Constant 34.374*** 41.814*** 41.334*** 25.629*** (4.932) (5.409) (6.084) (5.966) Observations 147 147 88 59 R2 0.061 0.117 0.124 0.110 Adjusted R2 0.035 0.086 0.092 0.061 Residual Std. Error 12.747 (df = 142) 12.406 (df = 141) 12.663 (df = 84) 12.209 (df = 55) F Statistic 2.326* (df = 4; 142) 3.746*** (df = 5; 141) 3.952** (df = 3; 84) 2.260* (df = 3; 55) Note: *p < 0.1; **p < 0.05; ***p < 0.01 4. Discussion This study analyzed the qEEG power during different sleep stages and its correlation with emotional disturbances of children with varying SDB severity. Our findings on sleep architecture showed that the mean SpO2, sleep duration and efficiency in PS group were significantly higher compared to the OSA group. We found that increasing age is associated with higher risks of depression and anxiety in the OSA children compared to the PS children. Specifically, a higher level of depression among OSA children was noted compared to the PS ones at the same age. Significantly, our study reveals that sleep efficiency mediated the association between OSA and the quality of life in childhood. Notably, the NREM3 EEG slowing ratio was negatively correlated with anxious symptoms, and the NREM2 EEG slowing ratio was negatively correlated with depressive symptoms. SDB is one of the most common causes of poor-quality sleep among children, with both PS and OSA affecting children’s normal sleep architecture [ 27 ] . Depression is another significant factor negatively affecting sleep quality, and poor sleep quality, in turn, aggravates depressive moods, leading to a vicious cycle. Our study found that, compared to the children with PS, children with OSA exhibited significantly shorter sleep duration and lower sleep efficiency. In addition, we observed that children with OSA had lower mean SpO2 compared to the PS children. Intermittent hypoxia and sleep fragmentation could potentially lead to the apoptotic neuronal cell death, inflammation and intracellular edema, all of which are associated with neurocognitive impairments and alteration of brain structure [ 28 – 30 ] . Sleep problems in childhood can not only predict the emergence of emotional problems, but are also related to the future risk of depression in adulthood [ 31 ] . In this study, slightly higher risks are observed in the OSA group compared to the PS group as age increases, consistent with the previous study that longer OSA and hypoxia worsen anxiety level and depressive symptoms [ 6 ] . Preschool children’s emotions are less affected by SDB, which may be related to their limited cognitive development and difficulty in expressing complex emotions. In this study, the sleep efficiency of OSA children was lower than that of PS children, which can negatively impact children’s daily life and academic performance, manifesting symptoms such as lower mood and excessive daytime sleepiness, potentially aggravating the depressive symptoms in the long term. However, a previous study found a negative correlation between depression, anxiety and the severity of sleep apnea, indicating that patients with more severe OSA are at lower risk of developing depressive symptoms [ 32 ] . It is possible that continuous exposure to IH cycles protect emotional development by reducing the rate of neuronal death and inducing neuronal branching on surviving neurons [ 33 , 34 ] . However, the observed discrepancy may be due to the limited classification of OSA severity and the small proportion of children with severe OSA. Despite the severity of PS is generally milder than OSA, our study extends previous research by emphasizing the potential negative impact of SDB duration on children’s mental status, and serves as a reminder to physicians, caretakers, and parents not to overlook PS in children. A large -sample survey in China on children with OSA pointed out that the negative emotions interfere with various aspects of the affected children’s lives, leading to a decline in their quality of life [ 6 ] . Consequently, the quality of family life also decreases [ 35 ] . However, the severity of sleep apnea, assessed using AHI, may have a protective role against emotional disorders [ 33 ] . With observational empirical and clinical evidence underscoring the potential protective effects of OSA on life quality, we can conclude that the effects were further mediated by the lower sleep efficiency which is regarded as new findings. There is a mutually reciprocal influential relationship between life quality and OSA, with each condition exacerbating the symptoms of the other [ 36 ] . Since we are conducting a cross-sectional design, we do not have justifiable and reliable means to establish the absence of the reverse causation or association in the exposure-response relationship, unlike the fully concurrent or retrospective cohort designs at the individual level Our study found a moderate negative correlation between the EEG slowing ratio during N3 sleep and anxiety levels, and between the EEG slowing ratio during N2 sleep and depressive symptoms. N3 EEG slowing ratio is a negative predictor of children’s anxiety levels for both preschool and during school age in modelling the association between OSA(/PS) and risks to child anxiety. During the investigation of OSA, slow EEG activity is often interpreted as a sign of arousal. In F. Morisson’s study, the author attributed the elevated ratio of slow to fast activity in OSA patients to the increased delta activity [ 37 ] . Compared to the previous studies, our research focuses on a narrow yet crucial age range of children, exploring the association between qEEG alterations and mental disturbances in children with SDB. More importantly, children are more likely to experience shorter N2, N3, and REM sleep episodes and durations compared to their adult counterparts [ 38 ] , in which their sleep characteristics may not be representative and generalizable of the typical non-REM and REM sleep. The results indicate that EEG slowing ratio during NREM sleep may serve as a valuable indicator for assessing anxiety levels and depressive symptoms. We acknowledged several limitations in our study. Firstly, due to the cross-sectional design in our study, we are unable to discern the temporal sequence of events, which prevents us from directly establishing causality between the variables. Secondly, the OSA group is predominantly comprised of mild OSA, with limited sample of moderate-to-severe cases, which may dilute effect size estimates. Lastly, due to the limitations of PSG devices, we were only able to assess EEG power in the frontal brain region. Therefore, future research should encompass multiple brain regions, investigating the intricate relationship between EEG power and emotional disturbances exhibited by SDB children. 5. Conclusion In summary, our research establishes an association among OAHI-OSA, qEEG power and emotional disturbances in children with SDB. These findings not only deepen our understanding of the pathophysiology of SDB, but also provide scientific evidence for timely intervention in emotional disturbances of SDB children. Clinical practice should strengthen mental health assessments and prompt application of psychological counseling to improve emotional well-being for children. Abbreviations TAR theta/alpha ratio TBR theta/beta ratio EEG slowing (delta + theta)/(alpha + beta + sigma) Declarations Author Contribution Xiaojing Chen contributed to the design, methodology, data collection, EEG processing, the original draft of the manuscript, and revision of the manuscript. Yanbo Li was involved in formal analysis, visualization, and writing of the original draft. Feng Zhai (the principal investigator PI) was responsible for resources, design, funding, and also revised the manuscript. All authors contributed to and have approved the final version of the manuscript.To note, Xiaojing Chen and Yanbo Li held co-first authorship of the manuscript and contributed equally to the manuscript. Data Availability Data is provided within the manuscript. References GOKDEMIR Y, ERSU R. Sleep disordered breathing in childhood [J]. Eur Respiratory Rev. 2016;25(139):48–53. BIGGS S N, NIXON G M, HORNE R S. The conundrum of primary snoring in children: what are we missing in regards to cognitive and behavioural morbidity? [J]. Sleep Med Rev. 2014;18(6):463–75. CSáBI E, GAáL V, HALLGATó E, et al. Increased behavioral problems in children with sleep-disordered breathing [J]. Ital J Pediatr. 2022;48(1):173. KANG J, TIAN Z. Changes in insular cortex metabolites in patients with obstructive sleep apnea syndrome [J]. NeuroReport. 2018;29(12):981–6. OTTO M W, POLLACK M H, MAKI K M, et al. Childhood history of anxiety disorders among adults with social phobia: rates, correlates, and comparisons with patients with panic disorder [J]. Depress Anxiety. 2001;14(4):209–13. HAI Y, KOU W, GU Z, et al. Obstructive sleep apnea affects the psychological and behavioural development of children–a case–control study [J]. J Sleep Res. 2023;33(1):e13924. LOPARO D, FONSECA A C, MATOS A P M, et al. Anxiety and Depression from Childhood to Young Adulthood: Trajectories and Risk Factors [J]. Volume 55. Child Psychiatry & Human Development; 2022. pp. 127–36. 1. CAIXETA J A S, SAMPAIO J C S, COSTA V V, et al. Long-term Impact of Adenotonsillectomy on the Quality of Life of Children with Sleep-disordered breathing [J]. Int Archives Otorhinolaryngol. 2020;25(01):e123–8. TORRETTA S, ROSAZZA C, PACE M E, et al. Impact of adenotonsillectomy on pediatric quality of life: review of the literature [J]. Ital J Pediatr. 2017;43(1):107. HABERER JE, TRABIN T. Furthering the reliable and valid measurement of mental health screening, diagnoses, treatment and outcomes through health information technology [J]. Gen Hosp Psychiatry. 2013;35(4):349–53. UMEMOTO A, PANIER L Y X, COLE S L, et al. Resting posterior alpha power and adolescent major depressive disorder [J]. J Psychiatr Res. 2021;141:233–40. MA H Y, XU Y F QIAOD, et al. Abnormal sleep features in adolescent MDD and its potential in diagnosis and prediction of early efficacy [J]. Sleep Med. 2023;106:116–22. SOLELHAC G, BERGER M, STRIPPOLI M F, et al. Objective polysomnography-based sleep features and major depressive disorder subtypes in the general population [J]. Psychiatry Res. 2023;324:115213. CHANG J, CHOI Y. Depression diagnosis based on electroencephalography power ratios [J]. Brain Behav. 2023;13(8):e3173. SCHMIDT L A, POOLE K L, HASSAN R, et al. Frontal EEG alpha-delta ratio and social anxiety across early adolescence [J]. Int J Psychophysiol. 2022;175:1–7. POOLE K L, HASSAN R, SCHMIDT LA. Temperamental Shyness, Frontal EEG Theta/Beta Ratio, and Social Anxiety in Children [J]. Child Dev. 2021;92(5):2006–19. PUSKAS S, KOZAK N. Quantitative EEG in obstructive sleep apnea syndrome: a review of the literature [J]. Rev Neurosci. 2017;28(3):265–70. MANOACH DS. Abnormal Sleep Spindles, Memory Consolidation, and Schizophrenia [J]. Annu Rev Clin Psychol. 2019;15:451–79. BROCKMANN PE, BRUNI O, KHEIRANDISH-GOZAL L, et al. Reduced sleep spindle activity in children with primary snoring [J]. Sleep Med. 2020;65:142–6. MA D, WU Y, WANG C, et al. Characteristics of ADHD Symptoms and EEG Theta/Beta Ratio in Children With Sleep Disordered Breathing [J]. Clin EEG Neurosci. 2024;55(4):417–25. LI J, YOU J, YIN G, et al. Electroencephalography Theta/Beta Ratio Decreases in Patients with Severe Obstructive Sleep Apnea [J]. Nat Sci Sleep. 2022;14:1021–30. TIMBREMONT B, BRAET C. Assessing Depression in Youth: Relation Between the Children's Depression Inventory and a Structured Interview [J]. J Clin Child Adolesc Psychol. 2004;33(1):149–57. YU D, LI X. Preliminary Use of the Children's Depression Inventory in China [J]. Chin Mental Health J. 2000;14(4):225–7. ZHAO J, XING X. Psychometric properties of the Spence Children's Anxiety Scale (SCAS) in Mainland Chinese children and adolescents [J]. J Anxiety Disord. 2012;26(7):728–36. WANG M. Anxiety Disorder Symptoms in Chinese Preschool Children [J]. Child Psychiatry Hum Dev. 2014;46(1):158–66. HUANG Y S, HWANG F M, LIN C H, et al. Clinical manifestations of pediatric obstructive sleep apnea syndrome: Clinical utility of the Chinese-version Obstructive Sleep Apnea Questionaire‐18 [J]. J Neuropsychiatry Clin Neurosci. 2015;69(12):752–62. RAMAMURTHY M B JAYAPRAKASHS. Introduction to Pediatric Sleep Medicine [J]. Indian J Pediatr. 2023;90(9):927–33. PUECH C, BADRAN M, RUNION A R, et al. Cognitive Impairments, Neuroinflammation and Blood–Brain Barrier Permeability in Mice Exposed to Chronic Sleep Fragmentation during the Daylight Period [J]. Int J Mol Sci. 2023;24(12):9880. LEE M-H SINS, LEE S, et al. Cortical thickness and hippocampal volume in adolescent children with obstructive sleep apnea [J]. Sleep. 2023;46(3):zsac201. BURTSCHER J, MALLET R T, BURTSCHER M, et al. Hypoxia and brain aging: Neurodegeneration or neuroprotection? [J]. Ageing Res Rev. 2021;68:101343. GREENE G, GREGORY A M, FONE D, et al. Childhood sleeping difficulties and depression in adulthood: the 1970 British Cohort Study [J]. J Sleep Res. 2014;24(1):19–23. LEE S-A, IM K, SEO JY, et al. Association between sleep apnea severity and symptoms of depression and anxiety among individuals with obstructive sleep apnea [J]. Sleep Med. 2023;101:11–8. ZHU X-H, YAN H-C ZHANGJ, et al. Intermittent Hypoxia Promotes Hippocampal Neurogenesis and Produces Antidepressant-Like Effects in Adult Rats [J]. J Neurosci. 2010;30(38):12653–63. AVILES-REYES R X, ANGELO M F, VILLARREAL A, et al. Intermittent hypoxia during sleep induces reactive gliosis and limited neuronal death in rats: implications for sleep apnea [J]. J Neurochem. 2010;112(4):854–69. JACKMAN A R, BIGGS S N WALTERLM, et al. Sleep Disordered Breathing in Early Childhood: Quality of Life for Children and Families [J]. Sleep. 2013;36(11):1639–46. URBANO G L, TABLIZO B J, MOUFARREJ Y, et al. The Link between Pediatric Obstructive Sleep Apnea (OSA) and Attention Deficit Hyperactivity Disorder (ADHD) [J]. Children. 2021;8(9):824. MORISSON F, LAVIGNE G. Spectral analysis of wakefulness and REM sleep EEG in patients with sleep apnoea syndrome [J]. Eur Respir J. 1998;11(5):1135–40. ZHANG C, WANG Y, LI D, et al. EEG Power Spectral Density in NREM Sleep is Associated with the Degree of Hypoxia in Patients with Obstructive Sleep Apnea [J]. Nat Sci Sleep. 2023;15:979–92. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 19 Mar, 2026 Reviews received at journal 10 Aug, 2025 Reviews received at journal 08 Aug, 2025 Reviews received at journal 05 Aug, 2025 Reviewers agreed at journal 02 Aug, 2025 Reviewers agreed at journal 31 Jul, 2025 Reviewers agreed at journal 28 Jul, 2025 Reviewers invited by journal 18 Jul, 2025 Editor assigned by journal 16 Jul, 2025 Editor invited by journal 26 Jun, 2025 Submission checks completed at journal 25 Jun, 2025 First submitted to journal 25 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6908921","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":488174897,"identity":"90d6479e-88e6-42f9-ad90-ecbb906b618b","order_by":0,"name":"Xiaojing Chen","email":"","orcid":"","institution":"Shanghai Jiao Tong University","correspondingAuthor":false,"prefix":"","firstName":"Xiaojing","middleName":"","lastName":"Chen","suffix":""},{"id":488174898,"identity":"d8b32626-f968-40be-8b25-e0c9da014bde","order_by":1,"name":"Yanbo Li","email":"","orcid":"","institution":"University of British Columbia","correspondingAuthor":false,"prefix":"","firstName":"Yanbo","middleName":"","lastName":"Li","suffix":""},{"id":488174901,"identity":"e843615c-82da-4609-8e2d-377416483b2e","order_by":2,"name":"Feng Zhai","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4ElEQVRIie3PsWrCUBTG8SOCkxInOcUhr3Ckq+irJGRwieCYoUNA8RlS9CEEB3X7Lhfsch9AaAdLwTnStYhRcTV3LHj/y1m+33CIXK7/GBMhKa5QFcgTW2KupBaqzFgSupH6q25MLIQ/G38DyVdvxXGORkq+18JjUplvBTCHaJMNF3hZU+d9FjwmVQ5EH6c6kl1BOoYC+SwhNR7kUKcLifcIpxakzrFApbpXEIKyIczxCNjqQMxBVGq4/Bc/GyxzvOm+fEQ/v39J1/faJeRemDavS7abX+qTB/u1y+VyPVdnM6hVG9n87+QAAAAASUVORK5CYII=","orcid":"","institution":"Shanghai Jiao Tong University","correspondingAuthor":true,"prefix":"","firstName":"Feng","middleName":"","lastName":"Zhai","suffix":""}],"badges":[],"createdAt":"2025-06-16 23:53:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6908921/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6908921/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87663923,"identity":"184962b5-17dd-4c02-a086-dac934fd911c","added_by":"auto","created_at":"2025-07-27 10:55:35","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":172274,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplots of variables with statistically significant differences between PS and OSA groups\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6908921/v1/d77ac3eedd5a05a19f8294d8.jpeg"},{"id":87663924,"identity":"7937799e-76bf-4db9-9e44-f1e2770d0737","added_by":"auto","created_at":"2025-07-27 10:55:35","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":176931,"visible":true,"origin":"","legend":"\u003cp\u003ea. Spearman’s correlation coefficient matrix (color-coded correlation gradient/scale) of continuous variables of study interests.\u003c/p\u003e\n\u003cp\u003eb. More detailed spearman’s correlation coefficient matrix (scatterplot) of continuous variables of study interests\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6908921/v1/17917b214e7a6421133aa76b.jpg"},{"id":87662842,"identity":"e75d8e10-adf1-4f83-803c-d3fbe564a242","added_by":"auto","created_at":"2025-07-27 10:47:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":17809,"visible":true,"origin":"","legend":"\u003cp\u003eDiagnostic plots for assessing model assumptions of the mediation outcome model (lm (`OSA-18 total score` ~ Sex+Age+group+`sleep efficiency`))\u003c/p\u003e","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6908921/v1/b97d9ecd0cf915e8675d83f9.png"},{"id":87662847,"identity":"2a4930b8-35f1-49bf-8233-874c6439692a","added_by":"auto","created_at":"2025-07-27 10:47:36","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":72537,"visible":true,"origin":"","legend":"\u003cp\u003eDiagnostic plots for assessing model assumptions of the outcome model (lm(`CDI total score`~Sex+Age*group))\u003c/p\u003e","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6908921/v1/f6ded28cc70ae4522063e07a.png"},{"id":87662852,"identity":"f794cc01-0514-4e31-b86b-85d0c1e1a6b2","added_by":"auto","created_at":"2025-07-27 10:47:36","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":17105,"visible":true,"origin":"","legend":"\u003cp\u003eDiagnostic plots for assessing model assumptions of the outcome model (lm (`SPENCE total score `~Sex+Age+group+group*Age+N3EEGslowing))\u003c/p\u003e","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-6908921/v1/28f9f65c7134e6e9350f8a03.png"},{"id":87665436,"identity":"ea187c34-88af-4ca7-b486-bd63e19bf4d2","added_by":"auto","created_at":"2025-07-27 11:03:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1664811,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6908921/v1/785ff7ab-1c47-406a-acd1-297dd88d59b8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Quantitative electroencephalography Spectral Power and Emotional Disturbances in Children with Sleep Disordered Breathing","fulltext":[{"header":"Highlights","content":"\u003cul start=\"50\"\u003e\n \u003cli\u003eDecreased EEG slowing ratio during different sleep stages was associated with emotional disturbances in children with sleep disordered breathing.\u003c/li\u003e\n \u003cli\u003eSleep efficiency mediated the association between obstructive sleep apnea and the quality of life in childhood.\u003c/li\u003e\n \u003cli\u003eOur findings highlight early detection of emotional disturbances in children with sleep disordered breathing, ultimately enhancing the quality of life for children. \u003c/li\u003e\n\u003c/ul\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eSleep disordered breathing (SDB) is common in children, characterized by alterations in breathing during sleep\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. In children, SDB is described as a spectrum\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e, regardless of the disease severity, children with SDB face an elevated risk of psychological comorbidities\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e, most commonly anxiety and depression, which are believed to be the consequence of the repeated cycles of hypoxia followed by reperfusion, hypercarbia, and sleep fragmentation\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. In addition, studies in children with OSA have shown that the longer the duration of the OSA course and hypoxia, the greater the impact on symptoms of anxiety and depression, and the higher the risk of anxiety and depression occurring in adulthood, which can cause serious impairments of social interaction, work abilities, health condition and other adult functions\u003csup\u003e[\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Remarkably, some scholars have found that adenotonsillectomy (AT) significantly assuages the emotional symptoms and has a positive impact on the overall quality of life of OSA children\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Thus, clinicians need to pay more attention to emotional disturbances of children with SDB and to treat promptly in order to reduce the occurrence of psychological comorbidities and avoid non-reversible deficits.\u003c/p\u003e\u003cp\u003eThe evaluation of OSA children\u0026rsquo;s mental health has historically relied on subjective questionnaires which is limited by its dependence on parents\u0026rsquo; accurate memory and correct attribution of ambiguous symptoms\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Therefore, objective methods are needed to more accurately evaluate mental disturbances. Polysomnography (PSG) is the gold standard for the diagnosis of SDB. Quantitative electroencephalogram (qEEG), employing mathematical algorithms to compute numerical features from specific EEG components, can meticulously and distinctly reveal the underlying neurobiological mechanisms of emotional disturbances\u003csup\u003e[\u003cspan additionalcitationids=\"CR12 CR13 CR14 CR15\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. QEEG is especially useful for detecting subtle brain activity changes that traditional methods may miss\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eSleep is divided into rapid eye movement (REM) sleep and non-rapid eye movement (NREM) sleep, with NREM sleep further subdivided into N1, N2, and N3 stages. Each stage is crucial for children\u0026rsquo;s growth, metabolism, memory, and mental health. Studies have shown that sleep spindles, the characteristic EEG signatures of N2 sleep, mediate memory consolidation\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e, while another study revealed that children with PS exhibited significantly reduced sleep spindle activity across all NREM stages \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. Further evidence showed that the global theta/beta ratio during the NREM period in the first sleep cycle of SDB children was positively correlated with inattention score, emphasizing the link between EEG alterations and cognitive impairments\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. While numerous studies have investigated correlation between EEG characteristics and cognitive dysfunctions in patients with SDB, a notable gap exists in the current research landscape. Specifically, the majority of current research focus on adult patients, behavioral deficits, and cognitive impairments, with relatively fewer studies paying attention to the emotional disturbances of children with SDB.\u003c/p\u003e\u003cp\u003eTherefore, our research aimed to explore the relationship between emotional disturbances and qEEG alterations during different sleep stages in SDB children with varying degrees of disease severity. We hypothesized that emotional disturbances, sleep architecture, and SDB metrics will exhibit variances among different severities of SDB. Additionally, we hypothesize that qEEG parameters, such as EEG slowing ratio and the power of frequency bands, are related to emotional disturbances in children with SDB.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Participants and procedures\u003c/h2\u003e\u003cp\u003eIn this cross-sectional study, children presenting with symptoms of SDB from December 2020 to May 2024 at the Otolaryngology Department of Shanghai Children\u0026rsquo;s Medical Center were enrolled. After the preliminary evaluation by specialists, these children conducted a whole-night PSG at hospital. Prior to PSG, the caregivers and their children fulfilled three questionnaires concerning children\u0026rsquo;s depression, anxiety, and SDB symptoms with the instruction of a professional researcher. We split the cohort in two subgroups based on AHI common cutoffs: PS (AHI\u0026lt;1 event/h, N\u0026thinsp;=\u0026thinsp;88), and OSA (AHI\u0026thinsp;\u0026ge;\u0026thinsp;1 event/h, N\u0026thinsp;=\u0026thinsp;59). Inclusion criteria required having SDB symptoms or signs and completing PSG and all questionnaires. The exclusion criteria were as follows: (ⅰ) history of surgery or medication treatment for SDB; (ⅱ) cardiac diseases; (ⅲ) acute infection phase of respiratory diseases; (ⅳ) psychiatric or psychological disorders; (ⅴ) age either over 12 or below 3 years; (ⅵ) significant artifacts in EEG data. Informed consent was obtained from all caregivers before inclusion in the study. This study was performed following the principle of the Declaration of Helsinki, and the protocol had been approved by the Institutional Review Board of Shanghai Children\u0026rsquo;s Medical Center, Shanghai Jiao Tong University School of Medicine (SCMCIRB-K2023105-1).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Polysomnography\u003c/h2\u003e\u003cp\u003eAll participants underwent one overnight PSG at the hospital using the SOMNOtouch RESP (SOMNO medics Corporation, Germany), a 13-channel device. All sleep architecture variables and sleep stages were recorded and assessed by a certified technician according to the standard criteria of the American Academy of Sleep Medicine. Sleep related parameters were calculated and reported. The sleep stages were divided into the wake stages, NREM (N1, N2, and N3) sleep and REM sleep. Given the special characteristics of children\u0026rsquo;s sleep structure, we have chosen to mainly focus on N2, N3 and REM sleep stages.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 EEG pre-processing and feature extraction\u003c/h2\u003e\u003cp\u003eWe obtain two-channel EEG data (Fp1, Fp2) from PSG recordings, sampled at a rate of 256 Hz. MATLAB software (R2024a) was used for processing and extraction of EEG features from the entire night\u0026rsquo;s EEG data. We imported EEG data in European data format (EDF) to MATLAB and band-pass filtered it within 0.2\u0026ndash;35 Hz. The transitions between sleep stages were converted into plain text format and subsequently matched with EEG recordings. Artifact removal was conducted independently by two experienced technicians. Independent component analysis and average re-reference were performed. Eventually, we utilized a fast Fourier transform with a Hann windows (30-second epochs) to extract the absolute power of each EEG wave. Subsequently, we calculated the relative power ,the EEG slowing ratio, theta/beta ratio (TBR) and theta/alpha ratio (TAR)\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. Specifically, every band frequency was defined as follows: δ (delta, 0.5-4 Hz); θ (theta, 4\u0026ndash;8 Hz); α (alpha, 8\u0026ndash;12 Hz); σ (sigma, 12\u0026ndash;14 Hz); and β (beta, 14\u0026ndash;30 Hz).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Questionnaires\u003c/h2\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.4.1 Children\u0026rsquo;s Depression Inventory (CDI)\u003c/h2\u003e\u003cp\u003eThe Children\u0026rsquo;s Depression Inventory (CDI) assess depression in children and adolescents through 27 items across five subscales: anhedonia, ineffectiveness, interpersonal problems, negative mood, and negative self-esteem\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. Each item is rated from 0 to 2, with total scores ranging from 0 to 54. A cutoff score of 16 has been proved to offer optimal sensitivity and specificity for screening depression\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. The Chinese version has high validity and reliability, with Cronbach\u0026rsquo;s alpha values ranging from 0.85 to 0.89\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. The CDI in our study had a Cronbach alpha of 0.93.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e2.4.2 The Spence Children\u0026rsquo;s Anxiety Scale-Parent version (SCAS-P) \u0026amp; Preschool Anxiety Scale (PAS)\u003c/h2\u003e\u003cp\u003eThe Spence Children\u0026rsquo;s Anxiety Scale-Parent version (SCAS-P) assesses anxiety severity in children across six domains, including panic attack and agoraphobia, separation anxiety, physical injury fears, social phobia, obsessive compulsive disorder, and generalized anxiety disorder. Caregivers rated their children\u0026rsquo;s anxiety symptoms on a 4-point scale from 0 (never) to 3 (always), with a maximum score of 114. In addition, scholars have proved that the SCAS is suitable for assessing anxiety in Chinese children \u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e, with a cutoff score of 18. The Cronbach\u0026rsquo;s alpha of current survey was 0.95.\u003c/p\u003e\u003cp\u003ePreschool Anxiety Scale (PAS) specifically assesses anxiety symptoms in preschool children (\u0026le;\u0026thinsp;6 years) \u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. Caregivers rate responses on a 5-point scale ranging from 0 (not at all true) to 4 (very often true). The maximum possible score is 112, with a cutoff of 48\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. In our test, PAS had a Cronbach\u0026rsquo;s alpha of 0.94.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e2.4.3 The Obstructive Sleep Apnea Questionnaire-18 (OSA-18)\u003c/h2\u003e\u003cp\u003eThe Obstructive Sleep Apnea Questionnaire-18 (OSA-18) is used to evaluate pediatric SDB in 5 domains: sleep disturbance, physical suffering, emotional distress, daytime problems, and caregiver concerns. Each item is rated from 1 (None of the time) to 7 (All of the time), with scores over 60 showing a moderate or large impact on health-related quality of life (HRQL). The Chinese version is reliable for early detection of SDB symptoms in children\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e, and in this study, the Cronbach\u0026rsquo;s alpha was 0.90.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Statistical analysis\u003c/h2\u003e\u003cp\u003eAnalysis was performed using R version 4.2.1. Exploratory descriptive statistics identify the data distribution and bivariate relationship. Frequency and proportions tables were implemented to measure the distribution of individuals among all variables of the study interest and identify any missing entries. As variables were non-normally distributed, the non-parametric Wilcoxon rank-sum test was used, reporting medians and IQR. Chi-square significance test of independence and homogeneity was performed for categorical variables. Simple linear regression was conducted to analyze the unadjusted association between the primary exposure of OSAS or PS assignment and the outcome of CDI, PASsum and/or SCAS-P sum, and OSA-18. A partial F-test was conducted to assess the model fit by comparing the fully adjusted and nested/reduced models. Multiple linear regression (MLR) was implemented to analyze the association through the inclusion of independent predictors and the exclusion of collinear terms to build optimal predictive models.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Demographics and PSG\u003c/h2\u003e\u003cp\u003eNo missing values were found in the data (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The median ages and sex proportions did not differ significantly between OSA and PS groups. However, mean SpO2, sleep duration, and efficiency were significantly higher in the PS group compared to OSAS (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Spearman correlation matrices (Figs.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e2\u003c/span\u003ea-b) indicated positive correlations between REM and NREM characteristics and sleep efficiency/duration (p\u0026lt;0.05). Due to multicollinearity, REM and NREM characteristics were excluded from the regression models, and sleep efficiency was used as the sole sleep characteristic.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDemographic, Polysomnographic Characteristics and Questionnaire Score of All the Participants\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOSAS, N\u0026thinsp;=\u0026thinsp;59\u003csup\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePS, N\u0026thinsp;=\u0026thinsp;88\u003csup\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDemographics\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.00 (4.00, 7.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.00 (4.00, 6.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;6 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e43 (73%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e66 (75%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;6 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 (27%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22 (25%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39 (66%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e49 (56%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20 (34%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39 (44%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePolysomnographic Characteristics\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean SpO2 (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e99.00 (98.00, 99.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99.00 (99.00, 99.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.011\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSleep duration (min)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e495 (432, 535)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e521 (473, 561)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.017\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSleep efficiency (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e91 (85, 95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e94 (88, 97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eREM incubation period (min)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e80 (59, 119)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e72 (49, 97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.053\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eREM sustaining time (min)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e80 (60, 90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e82 (70, 95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.073\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eREM period (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.7 (13.6, 17.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15.9 (14.0, 18.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNREM sustaining time (min)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e417 (358, 456)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e429 (392, 468)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.049\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNREM period (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e84.3 (82.7, 86.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e84.2 (81.8, 86.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRelative Spectral Power and Frequency Band Ratios\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNREM2\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003erelative theta (4\u0026ndash;8 Hz)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.084 (0.065, 0.101)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.086 (0.065,0.105)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003erelative delta (1\u0026ndash;4 Hz)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.86 (0.82, 0.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.85 (0.82, 0.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003erelative alpha (8\u0026ndash;12 Hz)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.030 (0.022, 0.041)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.027 (0.020, 0.038)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003erelative beta (15\u0026ndash;20 Hz)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.018 (0.015, 0.022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.019 (0.015, 0.023)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003erelative sigma (12\u0026ndash;15 Hz)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.006 (0.005, 0.009)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.006 (0.005, 0.007)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTAR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.70 (2.15, 3.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.06 (2.25, 3.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.00 (3.24, 6.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.53 (3.55, 5.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEEG slowing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17 (13, 21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17 (14, 24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNREM3\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003erelative theta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.064 (0.049, 0.076)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.063 (0.054, 0.076)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003erelative delta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.914 (0.900, 0.936)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.917 (0.899, 0.930)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003erelative alpha\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.011 (0.008, 0.015)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.011 (0.008, 0.016)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003erelative beta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0039 (0.0028, 0.0055)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0041 (0.0032, 0.0053)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003erelative sigma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0018 (0.0013, 0.0025)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0018 (0.0014, 0.0024)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTAR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.99 (3.90, 7.51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.68 (4.14, 7.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 (12, 21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16 (12, 20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEEG slowing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60 (43, 75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e56 (44, 73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eREM\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003erelative theta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.043 (0.037, 0.061)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.046 (0.036, 0.063)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003erelative delta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.92 (0.91, 0.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.93 (0.91, 0.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003erelative alpha\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.010 (0.008, 0.016)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.010 (0.008, 0.014)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003erelative beta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.008 (0.006, 0.011)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.008 (0.006, 0.012)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003erelative sigma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0021 (0.0017, 0.0037)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0024 (0.0016, 0.0030)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTAR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.49 (3.77, 5.27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.71 (3.90, 5.45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.94 (3.85, 7.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.34 (4.24, 7.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEEG slowing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50 (30, 59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e46 (35, 65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal Sleep\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003erelative theta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.057 (0.049, 0.071)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.066 (0.054, 0.080)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.073\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003erelative delta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.910 (0.894, 0.926)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.904 (0.877, 0.919)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003erelative alpha\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.015 (0.012, 0.021)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.015 (0.011, 0.020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003erelative beta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0094 (0.0078, 0.0115)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0094 (0.0073, 0.0110)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003erelative sigma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0035 (0.0024, 0.0043)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0031 (0.0024, 0.0040)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTAR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.81 (2.57, 4.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.88 (2.95, 5.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.18 (5.08, 7.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.85 (5.25, 8.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEEG slowing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34 (27, 41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32 (25, 43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOutcome metrics score\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOSA-18 total score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60 (46, 74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e62 (48, 72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOSA-18 binary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30 (51%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41 (47%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29 (49%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e47 (53%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCDI total score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.0 (1.0, 12.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.0 (2.0, 7.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.078\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCDI binary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50 (85%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e84 (95%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9 (15%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (4.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSPENCE total score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21 (12, 28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19 (11, 28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e1Median (IQR); n (%)\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e2Wilcoxon rank sum test; Pearson's Chi-squared test\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e3.2 Analysis on Sleep Efficiency Mediating the Impact of SDB on OSA-18\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eCumulative incidence differences for OSA-18 from the linear regression adjusted for sex and age resulted in non-significant OSAS/PS results. Adjusting for sleep efficiency significantly altered the effect estimates for sex (-9.54, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) and sleep efficiency (0.45, p\u0026thinsp;\u0026lt;\u0026thinsp;.01) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Partial F-test results showed that the full model with sleep efficiency had a statistically lower SSE than the reduced model (p\u0026thinsp;\u0026lt;\u0026thinsp;.01) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Incorporating mean SpO2 and EEG slowing ratios at different sleep stages did not yield significant effect estimates. The interaction between sleep efficiency and OSA/PS was also insignificant (p\u0026thinsp;=\u0026thinsp;0.318) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). None of the interactions involving sex, age, and OSA/PS improved model fit or predictive power when adjusted further (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eOSA/PS-OSA-18 model (reduced and full adjusted for the additional sleep efficiency)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eDependent variable:\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eOSA-18 total score\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eReduced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAdjusted for sleep efficiency\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eAdjusted for sleep efficiency as an effect modifier\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e-9.18***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-9.544***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-9.684***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e(2.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(2.825)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(2.825)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.232\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.232\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e(0.76)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.740)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0.740)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOSA group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e0.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.739\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.739\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e(2.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(2.891)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(2.891)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSleep efficiency\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.453***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.453***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.156)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0.156)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOSAS: Sleep efficiency\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.319\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0.319)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e62.92***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21.372\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e38.193*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e(4.53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(14.990)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(22.502)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eObservations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.125\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdjusted R2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.094\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.094\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eResidual Std. Error\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e17.09\u003c/p\u003e\u003cp\u003e(df\u0026thinsp;=\u0026thinsp;143)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16.663\u003c/p\u003e\u003cp\u003e(df\u0026thinsp;=\u0026thinsp;142)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16.662\u003c/p\u003e\u003cp\u003e(df\u0026thinsp;=\u0026thinsp;141)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eF Statistic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e3.42**\u003c/p\u003e\u003cp\u003e(df\u0026thinsp;=\u0026thinsp;3; 143)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.801***\u003c/p\u003e\u003cp\u003e(df\u0026thinsp;=\u0026thinsp;4; 142)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.042***\u003c/p\u003e\u003cp\u003e(df\u0026thinsp;=\u0026thinsp;5; 141)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNote:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;0.1; **p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eSleep efficiency was hypothesized as a mediator between OSA/PS treatments and childhood outcome metrics. Mediation analysis with sleep efficiency as the mediator revealed a significant average causal mediation effect between OSA/PS exposure and OSA-18 outcome (-1.514, 95% CI: -3.658, -0.01; p\u0026thinsp;\u0026lt;\u0026thinsp;.01) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), suggesting sleep efficiency mediated the relationship between OSA and OSA-18. Diagnostic plots confirmed no violations of assumptions (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBootstrapped mediation analysis between OSA/PS and OSA-18 with sleep efficiency as the mediator Nonparametric Bootstrap Confidence Intervals with the Percentile Method\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEffect\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEstimate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95% CI Lower\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e95% CI Upper\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eACME\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1.51*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-3.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.044\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eADE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-4.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.536\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal Effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-5.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.874\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProp. Mediated\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-6.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-11.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.882\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eSample Size Used: 147\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eSimulations: 1000\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eSignificance codes: 0 \u0026lsquo;***\u0026rsquo; 0.001 \u0026lsquo;**\u0026rsquo; 0.01 \u0026lsquo;*\u0026rsquo; 0.05 \u0026lsquo;.\u0026rsquo; 0.1 \u0026lsquo;\u0026rsquo; 1\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eAbbreviations: ACME, average causal mediation effect; ADE, average direct effect\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Significant Interaction between Age and OSA/PS on CDI Scoring\u003c/h2\u003e\u003cp\u003eIn the OSA/PS-CDI model, age was a significant interaction term (p\u0026thinsp;\u0026lt;\u0026thinsp;.05) alongside sex adjustment, yielding a significantly lower SSE (p\u0026thinsp;\u0026lt;\u0026thinsp;.05) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The interaction showed that increasing age was associated with higher CDI risks in OSA children compared to PS (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). OSA was linked to reduced CDI risks, but this was not significant (-3.65 units; p\u0026thinsp;=\u0026thinsp;0.240) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Adding sleep efficiency, mean SpO2, and EEG ratios resulted in non-significant models. The assumptions of the final model were met in diagnostic plots (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eOSA/PS-CDI model (reduced and full adjusted for the additional interaction term of group*age)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eCDI total score\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReduced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAdjusted for age as the effect modifier\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1.254\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.799*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(0.982)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.004)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.089***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.493\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(0.257)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0.381)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOSA group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.513\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-3.649\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(0.989)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(3.092)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge: OSAS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.109**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0.528)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.378\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.013\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(1.537)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2.217)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eObservations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.171\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.196\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdjusted R2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.154\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.174\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eResidual Std. Error\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.796 (df\u0026thinsp;=\u0026thinsp;143)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.728 (df\u0026thinsp;=\u0026thinsp;142)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eF Statistic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.855*** (df\u0026thinsp;=\u0026thinsp;3; 143)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.671*** (df\u0026thinsp;=\u0026thinsp;4; 142)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNote:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;0.1; **p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Correlation Analysis of EEG Slowing Ratio and Emotional Symptoms\u003c/h2\u003e\u003cp\u003eIn the final model with OSAS*age interaction and NREM Stage 3 EEG slowing ratio, an antagonistic interaction occurred, with a combined effect of OSAS*age being less negative than expected (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The sum of expected effects was \u0026minus;\u0026thinsp;1.83, while the observed effect was \u0026minus;\u0026thinsp;1.54, suggesting age-related decline in OSA was mitigated (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Subgroup analysis showed that increasing age posed a higher risk for OSA children (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Mediation modeling with NREM EEG slowing ratio as the mediator was statistically insignificant. Nonetheless, the NREM3 EEG slowing ratio was significantly negatively correlated with PAS/SCAS-P sum (spearman\u0026rsquo;s rho = -0.68; p\u0026thinsp;\u0026lt;\u0026thinsp;.001), and NREM2 was negatively correlated with CDI (spearman\u0026rsquo;s rho = -0.59; p\u0026thinsp;\u0026lt;\u0026thinsp;.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). However, no significant differences in EEG slowing ratios were found between OSA and PS groups. Simple linear regression models did not demonstrate significant relationships between OSA/PS assignments and EEG slowing ratios.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eOSA/PS-PASsum and/or SCAS-P sum model (reduced and full) and OSA/PS-stratified subgroup analyses (both unadjusted for the age as the effect modifier)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eSPENCE total score\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReduced non-adjusted for N3EEG slowing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAdjusted for N3EEG slowing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePS subgroup analysis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOSA subgroup analysis\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-4.053*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-3.437\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-3.978\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.523\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(2.235)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2.185)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(2.788)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(3.585)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-2.172**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2.291***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-2.306***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.714\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(0.848)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0.826)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.850)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0.784)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOSA group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-17.729**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-17.382**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(6.880)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(6.697)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN3EEG Slowing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.102*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.131**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0.038)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.052)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0.057)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge: OSAS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.110***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.087***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(1.175)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.143)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34.374***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41.814***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41.334***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e25.629***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(4.932)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(5.409)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(6.084)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(5.966)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eObservations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e59\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.061\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.117\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.124\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.110\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdjusted R2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.086\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.092\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.061\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eResidual Std. Error\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.747\u003c/p\u003e\u003cp\u003e(df\u0026thinsp;=\u0026thinsp;142)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.406\u003c/p\u003e\u003cp\u003e(df\u0026thinsp;=\u0026thinsp;141)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12.663\u003c/p\u003e\u003cp\u003e(df\u0026thinsp;=\u0026thinsp;84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12.209\u003c/p\u003e\u003cp\u003e(df\u0026thinsp;=\u0026thinsp;55)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eF Statistic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.326*\u003c/p\u003e\u003cp\u003e(df\u0026thinsp;=\u0026thinsp;4; 142)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.746***\u003c/p\u003e\u003cp\u003e(df\u0026thinsp;=\u0026thinsp;5; 141)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.952**\u003c/p\u003e\u003cp\u003e(df\u0026thinsp;=\u0026thinsp;3; 84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.260*\u003c/p\u003e\u003cp\u003e(df\u0026thinsp;=\u0026thinsp;3; 55)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNote:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;0.1; **p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study analyzed the qEEG power during different sleep stages and its correlation with emotional disturbances of children with varying SDB severity. Our findings on sleep architecture showed that the mean SpO2, sleep duration and efficiency in PS group were significantly higher compared to the OSA group. We found that increasing age is associated with higher risks of depression and anxiety in the OSA children compared to the PS children. Specifically, a higher level of depression among OSA children was noted compared to the PS ones at the same age. Significantly, our study reveals that sleep efficiency mediated the association between OSA and the quality of life in childhood. Notably, the NREM3 EEG slowing ratio was negatively correlated with anxious symptoms, and the NREM2 EEG slowing ratio was negatively correlated with depressive symptoms.\u003c/p\u003e\u003cp\u003eSDB is one of the most common causes of poor-quality sleep among children, with both PS and OSA affecting children\u0026rsquo;s normal sleep architecture\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. Depression is another significant factor negatively affecting sleep quality, and poor sleep quality, in turn, aggravates depressive moods, leading to a vicious cycle. Our study found that, compared to the children with PS, children with OSA exhibited significantly shorter sleep duration and lower sleep efficiency. In addition, we observed that children with OSA had lower mean SpO2 compared to the PS children. Intermittent hypoxia and sleep fragmentation could potentially lead to the apoptotic neuronal cell death, inflammation and intracellular edema, all of which are associated with neurocognitive impairments and alteration of brain structure\u003csup\u003e[\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eSleep problems in childhood can not only predict the emergence of emotional problems, but are also related to the future risk of depression in adulthood\u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. In this study, slightly higher risks are observed in the OSA group compared to the PS group as age increases, consistent with the previous study that longer OSA and hypoxia worsen anxiety level and depressive symptoms\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Preschool children\u0026rsquo;s emotions are less affected by SDB, which may be related to their limited cognitive development and difficulty in expressing complex emotions. In this study, the sleep efficiency of OSA children was lower than that of PS children, which can negatively impact children\u0026rsquo;s daily life and academic performance, manifesting symptoms such as lower mood and excessive daytime sleepiness, potentially aggravating the depressive symptoms in the long term. However, a previous study found a negative correlation between depression, anxiety and the severity of sleep apnea, indicating that patients with more severe OSA are at lower risk of developing depressive symptoms\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. It is possible that continuous exposure to IH cycles protect emotional development by reducing the rate of neuronal death and inducing neuronal branching on surviving neurons\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e. However, the observed discrepancy may be due to the limited classification of OSA severity and the small proportion of children with severe OSA. Despite the severity of PS is generally milder than OSA, our study extends previous research by emphasizing the potential negative impact of SDB duration on children\u0026rsquo;s mental status, and serves as a reminder to physicians, caretakers, and parents not to overlook PS in children.\u003c/p\u003e\u003cp\u003eA large -sample survey in China on children with OSA pointed out that the negative emotions interfere with various aspects of the affected children\u0026rsquo;s lives, leading to a decline in their quality of life\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Consequently, the quality of family life also decreases\u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e. However, the severity of sleep apnea, assessed using AHI, may have a protective role against emotional disorders\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e. With observational empirical and clinical evidence underscoring the potential protective effects of OSA on life quality, we can conclude that the effects were further mediated by the lower sleep efficiency which is regarded as new findings. There is a mutually reciprocal influential relationship between life quality and OSA, with each condition exacerbating the symptoms of the other\u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e. Since we are conducting a cross-sectional design, we do not have justifiable and reliable means to establish the absence of the reverse causation or association in the exposure-response relationship, unlike the fully concurrent or retrospective cohort designs at the individual level\u003c/p\u003e\u003cp\u003eOur study found a moderate negative correlation between the EEG slowing ratio during N3 sleep and anxiety levels, and between the EEG slowing ratio during N2 sleep and depressive symptoms. N3 EEG slowing ratio is a negative predictor of children\u0026rsquo;s anxiety levels for both preschool and during school age in modelling the association between OSA(/PS) and risks to child anxiety. During the investigation of OSA, slow EEG activity is often interpreted as a sign of arousal. In F. Morisson\u0026rsquo;s study, the author attributed the elevated ratio of slow to fast activity in OSA patients to the increased delta activity\u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e. Compared to the previous studies, our research focuses on a narrow yet crucial age range of children, exploring the association between qEEG alterations and mental disturbances in children with SDB. More importantly, children are more likely to experience shorter N2, N3, and REM sleep episodes and durations compared to their adult counterparts\u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e, in which their sleep characteristics may not be representative and generalizable of the typical non-REM and REM sleep. The results indicate that EEG slowing ratio during NREM sleep may serve as a valuable indicator for assessing anxiety levels and depressive symptoms.\u003c/p\u003e\u003cp\u003eWe acknowledged several limitations in our study. Firstly, due to the cross-sectional design in our study, we are unable to discern the temporal sequence of events, which prevents us from directly establishing causality between the variables. Secondly, the OSA group is predominantly comprised of mild OSA, with limited sample of moderate-to-severe cases, which may dilute effect size estimates. Lastly, due to the limitations of PSG devices, we were only able to assess EEG power in the frontal brain region. Therefore, future research should encompass multiple brain regions, investigating the intricate relationship between EEG power and emotional disturbances exhibited by SDB children.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn summary, our research establishes an association among OAHI-OSA, qEEG power and emotional disturbances in children with SDB. These findings not only deepen our understanding of the pathophysiology of SDB, but also provide scientific evidence for timely intervention in emotional disturbances of SDB children. Clinical practice should strengthen mental health assessments and prompt application of psychological counseling to improve emotional well-being for children.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTAR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003etheta/alpha ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTBR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003etheta/beta ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eEEG slowing\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003e(delta\u0026thinsp;+\u0026thinsp;theta)/(alpha\u0026thinsp;+\u0026thinsp;beta\u0026thinsp;+\u0026thinsp;sigma)\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eXiaojing Chen contributed to the design, methodology, data collection, EEG processing, the original draft of the manuscript, and revision of the manuscript. Yanbo Li was involved in formal analysis, visualization, and writing of the original draft. Feng Zhai (the principal investigator PI) was responsible for resources, design, funding, and also revised the manuscript. All authors contributed to and have approved the final version of the manuscript.To note, Xiaojing Chen and Yanbo Li held co-first authorship of the manuscript and contributed equally to the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData is provided within the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGOKDEMIR Y, ERSU R. Sleep disordered breathing in childhood [J]. Eur Respiratory Rev. 2016;25(139):48\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBIGGS S N, NIXON G M, HORNE R S. The conundrum of primary snoring in children: what are we missing in regards to cognitive and behavioural morbidity? [J]. 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Nat Sci Sleep. 2022;14:1021\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTIMBREMONT B, BRAET C. Assessing Depression in Youth: Relation Between the Children's Depression Inventory and a Structured Interview [J]. J Clin Child Adolesc Psychol. 2004;33(1):149\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYU D, LI X. Preliminary Use of the Children's Depression Inventory in China [J]. Chin Mental Health J. 2000;14(4):225\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZHAO J, XING X. Psychometric properties of the Spence Children's Anxiety Scale (SCAS) in Mainland Chinese children and adolescents [J]. J Anxiety Disord. 2012;26(7):728\u0026ndash;36.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWANG M. Anxiety Disorder Symptoms in Chinese Preschool Children [J]. Child Psychiatry Hum Dev. 2014;46(1):158\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHUANG Y S, HWANG F M, LIN C H, et al. Clinical manifestations of pediatric obstructive sleep apnea syndrome: Clinical utility of the Chinese-version Obstructive Sleep Apnea Questionaire‐18 [J]. J Neuropsychiatry Clin Neurosci. 2015;69(12):752\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRAMAMURTHY M B JAYAPRAKASHS. Introduction to Pediatric Sleep Medicine [J]. Indian J Pediatr. 2023;90(9):927\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePUECH C, BADRAN M, RUNION A R, et al. Cognitive Impairments, Neuroinflammation and Blood\u0026ndash;Brain Barrier Permeability in Mice Exposed to Chronic Sleep Fragmentation during the Daylight Period [J]. Int J Mol Sci. 2023;24(12):9880.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLEE M-H SINS, LEE S, et al. 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Intermittent Hypoxia Promotes Hippocampal Neurogenesis and Produces Antidepressant-Like Effects in Adult Rats [J]. J Neurosci. 2010;30(38):12653\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAVILES-REYES R X, ANGELO M F, VILLARREAL A, et al. Intermittent hypoxia during sleep induces reactive gliosis and limited neuronal death in rats: implications for sleep apnea [J]. J Neurochem. 2010;112(4):854\u0026ndash;69.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJACKMAN A R, BIGGS S N WALTERLM, et al. Sleep Disordered Breathing in Early Childhood: Quality of Life for Children and Families [J]. Sleep. 2013;36(11):1639\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eURBANO G L, TABLIZO B J, MOUFARREJ Y, et al. The Link between Pediatric Obstructive Sleep Apnea (OSA) and Attention Deficit Hyperactivity Disorder (ADHD) [J]. Children. 2021;8(9):824.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMORISSON F, LAVIGNE G. Spectral analysis of wakefulness and REM sleep EEG in patients with sleep apnoea syndrome [J]. Eur Respir J. 1998;11(5):1135\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZHANG C, WANG Y, LI D, et al. EEG Power Spectral Density in NREM Sleep is Associated with the Degree of Hypoxia in Patients with Obstructive Sleep Apnea [J]. Nat Sci Sleep. 2023;15:979\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"sleep disordered breathing, child, polysomnography, anxiety, depression","lastPublishedDoi":"10.21203/rs.3.rs-6908921/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6908921/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e\u003cp\u003eSleep disordered breathing (SDB) can result in emotional symptoms among children. This study aimed to establish associations of quantitative electroencephalography (qEEG) alterations during different sleep stages with depression and anxiety in children with SDB.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA total of 147 children aged 3\u0026ndash;12 years with SDB were included in the study. They were divided into two groups: primary snoring (n\u0026thinsp;=\u0026thinsp;88, 44% female) and obstructive sleep apnea (n\u0026thinsp;=\u0026thinsp;59, 34% female). Children underwent whole-night polysomnography (PSG) at the hospital, during which quantitative electroencephalography (qEEG) data were acquired. Prior to the test, parents of SDB children completed the Obstructive Sleep Apnea Questionnaire-18 (OSA-18), the Spence Children\u0026rsquo;s Anxiety Scale\u0026ndash;Parent version (SCAS-P) or the Preschool Anxiety Scale (PAS), and the Children's Depression Inventory (CDI).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eCompared to the PS group, the OSA group had lower mean SpO2, sleep duration and efficiency. Sleep efficiency mediated the association between the OSA/PS exposure and the OSA-18 outcome, with the negative estimate of -1.514 (95% CI: -3.658, -0.01; p\u0026thinsp;\u0026lt;\u0026thinsp;.01). OSA children exhibited higher CDI scores compared to the PS children of the same age. Notably, the NREM3 EEG slowing ratio was negatively correlated with anxiety levels, and the NREM2 EEG slowing ratio was negatively correlated with depressive symptoms.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eQEEG alterations during different sleep stages are linked to emotional disturbances of children suffering from SDB. The EEG slowing ratio in NREM sleep may be a useful indicator for the nocturnal electrophysiology in children with SDB, potentially linked to emotional disturbances.\u003c/p\u003e","manuscriptTitle":"Quantitative electroencephalography Spectral Power and Emotional Disturbances in Children with Sleep Disordered Breathing","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-27 10:47:31","doi":"10.21203/rs.3.rs-6908921/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-19T07:47:36+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-11T01:20:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-08T09:01:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-05T20:18:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"70677868433916668981959838180594292534","date":"2025-08-03T01:16:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"5421836214686593903496712971055532924","date":"2025-07-31T16:22:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"286380948265040554047770679265007709257","date":"2025-07-28T12:28:44+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-18T19:01:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-16T05:01:02+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-06-26T06:06:20+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-25T23:44:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pediatrics","date":"2025-06-25T23:41:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ae811dbe-4272-457c-8cd9-1d9d351bf578","owner":[],"postedDate":"July 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-21T08:54:03+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-27 10:47:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6908921","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6908921","identity":"rs-6908921","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}