Evaluation of the Pittsburgh Sleep Quality Index in a Group of Orthodontic Patients With Different Sagittal Skeletal Relationships

Evaluation of the Pittsburgh Sleep Quality Index in a Group of Orthodontic Patients With Different Sagittal Skeletal Relationships | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Evaluation of the Pittsburgh Sleep Quality Index in a Group of Orthodontic Patients With Different Sagittal Skeletal Relationships Chanistha Sirichan, Narissaporn Chaiprakit, Siripatra Patchanee This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8098939/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background This study aimed to evaluate and compare the subjective sleep quality of Thai orthodontic patients classified into skeletal class I (Sk-I), class II (Sk-II), and class III (Sk-III) groups using the Thai-Pittsburgh Sleep Quality Index (Thai-PSQI). Methods A total of 93 orthodontic patients undergoing treatment were included in the study. Cephalometric analysis using Dolphin Imaging software classified participants into Sk-I, Sk-II, and Sk-III groups. Sleep quality was assessed using the Thai-PSQI. Data normality was tested using the Shapiro-Wilk test. The Kruskal-Wallis test was used to compare Pittsburgh Sleep Quality Index (PSQI) scores among skeletal groups. Demographic characteristics and differences in sleep-related parameters (sex, age, and body mass index) between good and poor sleepers were analyzed using the Chi-square test and Mann-Whitney U test (α = 0.05). Results The Sk-II group had the highest PSQI scores, followed by the Sk-I and Sk-III groups (6.68 ± 3.39, 6.42 ± 2.71, and 6.26 ± 2.46, respectively), indicating poor quality across all groups. However, no statistically significant differences were observed in PSQI scores among the skeletal groups (p > 0.05). Similarly, the distribution of good and poor sleepers was not significantly different among the Sk-I, Sk-II, and Sk-III groups (p > 0.05). In addition, there was no significant difference in sleep-related parameters between good and poor sleepers (p > 0.05). Conclusions Sleep quality is not influenced by sagittal skeletal patterns. Therefore, incorporating sleep quality assessments into orthodontic treatment planning may be beneficial. Skeletal relationships Skeletal patterns Sleep quality Pittsburgh Sleep Quality Index PSQI Introduction Sleep is an essential component of the human daily routine. Restorative sleep is associated with improved physical, cognitive, and mental health. In contrast, poor or disordered sleep is associated with possible cognitive and psychological problems as well as a deterioration in physical health ( 1 ). The Pittsburgh Sleep Quality Index (PSQI) is a widely used, standardized, self-administered questionnaire that assesses sleep quality over a one-month period ( 2 ). It is employed across clinical and non-clinical populations, including individuals with and without medical or psychological conditions ( 3 , 4 ). PSQI is used in the medical practice as a screening tool for sleep dysfunction ( 3 , 4 ) or to assess sleep quality in healthcare professionals ( 5 ), among other applications. The PSQI was designed to establish a reliable and valid measure of sleep quality, differentiate between “good” and “poor” sleepers, and provide a simple, clinically useful assessment of various sleep problems ( 2 ). The PSQI has been translated into multiple languages, including Thai. The Thai Pittsburgh Sleep Quality Index (Thai-PSQI) is equivalent to the original English version when utilized with Thai-speaking patients and has good sensitivity and specificity for identifying good and poor sleepers ( 6 ). Skeletal relationships are commonly evaluated using cephalometric analysis to assess maxillomandibular discrepancies by orthodontists before treatment ( 7 ). The ANB angle ( 8 ) and the Wits appraisal ( 9 ) are widely used to identify a skeletal sagittal discrepancy, which classifies the skeletal relationships into 3 types: skeletal class I (Sk-I), class II (Sk-II), and class III (Sk-III) ( 8 – 10 ). The mandible's and maxilla's anteroposterior positions, which together form the facial skeletal pattern, influenced upper airway dimensions ( 11 – 13 ). Since the pharyngeal musculature is closely tied to the bone structure, these atypical facial skeletal patterns may be related to the abnormalities of the airway ( 14 ). Orthodontists have also shown interest in the airway, as it plays a vital role in craniofacial development and is relevant to diagnosing and managing conditions such as mouth breathing and sleep disorders ( 15 ). In addition, current evidence indicates that breathing disorders such as obstructive sleep apnea are associated with diminished upper airway dimensions. The previous studies revealed that posterior airway space, which is the most constricted area at the base of the tongue, and oropharyngeal volume were reduced in Sk-III, Sk-I, and Sk-II, respectively ( 16 , 17 ). The nasal passage volume was found to be reduced in Sk-I, Sk-III, and Sk-II, in that order ( 16 ). Moreover, a previous study found that micrognathia and skeletal class II relationships were the most common characteristics in retropalatal and retroglossal obstruction patients, but the retropalatal obstruction group had fewer ( 18 ). Additionally, the oropharyngeal area was found to be significantly related to the ANB angle, with the ANB angle increasing as the oropharynx area decreased ( 17 , 19 ). Narrowing of the pharyngeal structure may increase the tendency of pharyngeal collapse during sleep when the pharyngeal dilator muscles fail to generate sufficient force to resist the negative inspiratory pressure in the pharynx ( 20 – 22 ), which may impair sleep quality. According to previous studies, the skeletal pattern influences the dimensions of the upper airway, and as the ANB angle increases, the area of the oropharynx significantly decreases, potentially leading to breathing disorders ( 17 , 19 , 23 ). Thus, this study aims to evaluate and compare the sleep quality in Thai orthodontic patients with different skeletal patterns using the Thai-PSQI. Materials and Methods Study Design and Participants This study was approved by the Human Research Ethics Committee of Thammasat University (Science), Thailand. The study included 93 Thai orthodontic patients aged 18–50 (34 males and 59 females) who were undergoing orthodontic treatment at the Orthodontic Department in the Faculty of Dentistry at Thammasat University, and all participants provided written informed consent prior to their inclusion in the study. All participants had reached cervical vertebral maturation (CVM) stage CS6 and were proficient in reading, writing, speaking, and listening in Thai. The patients who were excluded from the study were those with obesity (body mass index > 30) or clinical overweight, night shift work, a history of orthognathic surgery or orthopedic treatments in the craniofacial region, chronic respiratory disease, previous tonsillectomy and/or adenoidectomy, craniofacial trauma or pathology in the study area, a history of head and neck radiation therapy, mental or psychiatric disorders, and doctor-diagnosed obstructive sleep apnea. Measures Lateral cephalometric radiographs were taken with subjects in an upright position with the x-ray tube perpendicular to the sagittal plane and all subjects in the Frankfort horizontal plane parallel to the floor. During head stabilization throughout exposure, ear rods are inserted into the external auditory meatus. Participants were instructed to bite in maximum intercuspation and inhale through the nose during image capture ( 24 , 25 ). Cephalometric analyses were conducted using "Dolphin Imaging Version 11.95.08.50 Premium" (Dolphin Imaging and Management Solution, Los Angeles, California, USA) to classify participants into Sk-I, Sk-II, and Sk-III groups using the Thai norm of ANB Angle (2.8 o ± 2.3 o ) ( 26 ). To classify the sagittal skeletal pattern, SNA, SNB, and ANB angles were measured: Sk-I, 0.5 o ≤ ANB ≤ 5.1 o ; Sk-II, ANB > 5.1 o ; Sk-III, ANB < 0.5 o . All patients have been checked for normal SN length (males, 70.2 ± 4.6 mm; females, 63.4 ± 3.1 mm) and SN-FH angle (6.9 o ± 3.1 o ) ( 26 ). If a patient's SN length or SN-FH angle is not within the Thai norm, the skeletal classification is confirmed by the Thai norm of Wits appraisal (males, -0.6 ± 3.1 mm; females, -1.8 ± 2.6 mm) ( 26 ). The Wits appraisal value in Thai norm indicates Sk-I; a greater positive Wits appraisal indicates Sk-II; and a negative Wits appraisal indicates Sk-III. Nineteen cephalometric radiographs (20% of the total sample) were randomly selected and re-measured two weeks after the initial assessment. The Intraclass Correlation Coefficient (ICC) was used to evaluate the reliability of the measurements between the first and second assessments. In this study, ICC greater than 0.90 is considered excellent reliability ( 27 ), so the first set of measurements was utilized. All subjects were assessed for sleep quality using the Thai-PSQI ( 6 ). Nineteen questions are self-scored, and five are roommate or bed partner scored. The last five questions are used for clinical information only and are not included in PSQI scoring. These nineteen questions are scored equally on a 0–3 scale for subjective sleep quality (SQ), sleep latency (SL), sleep duration (SD), habitual sleep efficiency (HSE), sleep disturbances (SDI), sleep medication use (SM), and daytime dysfunction (DD). The total of the seven component scores results in a global PSQI score ranging from 0 to 21. A total global PSQI score ≤ 5 indicates good sleep quality, while > 5 indicates poor sleep quality. Higher global PSQI scores indicate poorer sleep ( 2 ). Statistical Analysis All statistical analyses were conducted using IBM SPSS Software Version 26 (IBM Corporation, Armonk, NY, USA). The statistics showed that the measurement was not normally distributed according to the Shapiro–Wilk test. The PSQI scores were compared among the groups using the Kruskal-Wallis test. A comparison of PSQI scores in each sleep-related parameter (sex, age, and body mass index [BMI]) was conducted using the Mann-Whitney U test and the Kruskal-Wallis test. The Chi-square test and Mann-Whitney U test were used to analyze the demographics and differences in sleep-related parameters between good and poor sleepers. Statistical significance was set at α = 0.05. Results Demographic characteristics This study included 93 orthodontic patients (32 males, 61 females) with a mean age of 23.68 ± 5.80 years, and a mean BMI of 21.09 ± 3.44 kg/m². Participants were categorized into three groups based on their skeletal patterns: Skeletal Class I (Sk-I): 8 males, 23 females (mean age: 22.94 ± 4.37 years; BMI: 20.25 ± 2.63 kg/m 2 ; ANB: 3.41 o ± 0.95 o ) Skeletal Class II (Sk-II): 10 males, 21 females (mean age: 24.55 ± 7.26 years; BMI: 21.69 ± 3.72 kg/m 2 ; ANB: 6.37 o ± 0.89 o ) Skeletal Class III (Sk-III): 14 males, 17 females (mean age: 23.55 ± 5.49 years; BMI: 21.34 ± 3.80 kg/m 2 ; ANB: -2.25 o ± 2.22 o ). No statistically significant differences were observed in sex, age, or BMI among groups (p > 0.05). Additionally, the Sk-I, Sk-II, and Sk-III groups of this study are only different in the anteroposterior position of the mandible (SNB) and not different in the anteroposterior position of the maxilla (SNA) (Table 1). Table 1: Sample characteristics (N=93) Variables Sk I (n=31) Sk II (n=31) Sk III (n=31) Total (n=93) p value‡ Sex Male (%): Female (%) 8(25.8) : 23(74.2) 10(32.3) : 21(67.7) 14(45.2) : 17(54.8) 32(34.4) : 61(65.6) 0.263 ғ Age (yr) 22.94 ± 4.37 24.55 ± 7.26 23.55 ± 5.49 23.68 ± 5.80 0.913 Weight (kg) 54.23 ± 10.44 58.84 ± 11.62 59.26 ± 12.89 57.44 ± 11.79 0.153 Height (m) 1.63 ± 0.09 1.65 ± 0.07 1.66 ± 0.09 1.65 ± 0.08 0.352 BMI (kg/m 2 ) 20.25 ± 2.63 21.69 ± 3.72 21.34 ± 3.80 21.09 ± 3.44 0.393 SNA ( o ) 84.05 ± 2.67 85.48 ± 3.12 83.61 ± 4.33 84.38 ± 3.50 0.088† SNB ( o ) 80.63 ± 2.68 79.17 ± 3.35 86.18 ± 5.18 81.99 ± 4.89 *0.000 ANB ( o ) 3.41 ± 0.95 6.37 ± 0.89 -2.25 ± 2.22 2.51 ± 3.88 *0.000 SN (mm) Male Female 63.82 ± 2.62 66.01 ± 2.86 63.05 ± 2.10 65.01 ± 3.50 68.63 ± 2.69 63.29 ± 2.33 66.30 ± 6.11 70.00 ±2.69 63.25 ± 4.05 65.04 ± 4.41 68.58 ± 4.79 63.19 ± 2.80 0.152 0.146 0.926 SN-FH ( o ) 8.63 ± 1.56 8.33 ± 2.37 8.53 ± 3.08 8.49 ± 2.39 0.835 AO-BO (mm) Male Female 0.19 ± 2.55 0.9 ± 2.33 -0.57 ± 2.56 3.12 ± 2.36 4.62 ± 2.94 2.41 ± 1.69 -7.57 ± 4.30 -9.45 ±5.33 -6.02 ± 2.43 -1.55 ± 5.49 -2.47 ± 7.54 -1.06 ± 4.03 *0.000 *0.000 *0.000 ғ Chi-square test; data are presented as frequencies (percentages), † One-way ANOVA and ‡ A Kruskal-Wallis test were performed for intergroup differences in skeletal class I, II, and III groups; data are presented as mean ± standard (*p < 0.05). The PSQI scores and sagittal skeletal patterns The mean PSQI score for all participants was 6.45 ± 2.85, exceeding the cutoff of 5, indicating poor sleep quality. In total, 55.9% of the participants were categorized as individuals with poor sleep quality. The average PSQI scores for patients in the Sk-I, Sk-II, and Sk-III groups were 6.42 ± 2.71, 6.68 ± 3.39, and 6.26 ± 2.46, respectively. The highest PSQI scores was observed in the Sk-II group, followed by the Sk-I group, and then the Sk-III group. The highest subcomponent score in the Sk-I group is subjective sleep quality scores (1.39 ± 0.62), while in the Sk-II group, it is the daytime dysfunction scores (1.32 ± 0.91), and in the Sk-III group, it is sleep onset latency scores (1.52 ± 0.93). Interestingly, using sleep medication resulted in the lowest subcomponent score among all classifications (Sk-I: 0.16 ± 0.58, Sk-II: 0.13 ± 0.56, Sk-III: 0.00 ± 0.00) (Table 2). There were no significant differences in the total PSQI score, sleep duration (DURAT), sleep disturbances (DISTB), sleep latency (LATEN), daytime dysfunction (DAYDYS), habitual sleep efficiency (HSE), sleep quality (SLPQUAL), or sleep medication (MEDS) among the Sk-I, Sk-II, and Sk-III groups (p-values > 0.05) (Table 2). Table 2: A comparison of PSQI scores and subcomponent scores Variable s Sk-I (n=31) Sk-II (n=31) Sk-III (n=31) Total Kruskal-Wallis H p value Mean ± SD Median (IQR) Mean rank Mean ± SD Median (IQR) Mean rank Mean ± SD Median (IQR) Mean rank 1 DURAT 0.77± 0.76 1 (1) 49.48 0.87 ± 1.06 0(2) 48.61 0.61 ± 0.84 0 (1) 42.90 0.75 ± 0.89 1.286 0.526 2 DISTB 1.16 ± 0.45 1(0) 41.76 1.29 ± 0.46 1 (1) 47.21 1.39 ± 0.56 1(1) 52.03 1.28 ± 0.50 3.397 0.183 3 LATEN 1.26 ± 0.77 1 (1) 44.44 1.26 ± 0.82 1 (1) 44.66 1.52 ± 0.93 1 (1) 51.90 1.34 ± 0.84 1.773 0.412 4 DAYDYS 1.35 ± 0.84 1 (1) 49.89 1.32 ± 0.91 1 (1) 48.35 1.10 ± 0.83 1 (2) 42.76 1.26 ± 0.86 1.370 0.504 5 HSE 0.32 ± 0.79 0 (0) 43.26 0.52 ± 0.77 0 (1) 51.82 0.35 ± 0.71 0 (1) 45.92 0.40 ± 0.75 2.648 0.266 6 SLPQUAL 1.39 ± 0.62 1 (1) 50.34 1.29 ± 0.74 1 (1) 45.13 1.29 ± 0.64 1 (1) 45.53 1.32 ± 0.66 0.908 0.635 7 MEDS 0.16 ± 0.58 0 (0) 48.98 0.13 ± 0.56 0 (0) 47.52 0.00 ± 0.00 0 (0) 44.50 0.10 ± 0.47 2.912 0.233 Total PSQI scores 6.42 ± 2.71 6 (3) 47.31 6.68 ± 3.39 5 (5) 46.39 6.26 ± 2.46 6 (4) 47.31 6.45 ± 2.85 0.024 0.988 Total PSQI score s , sleep duration (DURAT), sleep disturbances (DISTB), sleep latency (LATEN), daytime dysfunction (DAYDYS), habitual sleep efficiency (HSE), sleep quality (SLPQUAL), and sleep medication (MEDS) in sagittal skeletal classifications I, II, and III was done using the Kruskal-Wallis test at p < 0.05; data are presented as mean ± standard deviation, median (interquartile range) and mean rank. The PSQI scores and sleep-related parameters A comparison of PSQI scores for differences in sleep-related parameters revealed no significant differences between groups based on sex (male and female), age groups (under 30 years and 30-50 years), and BMI categories (under 18.5, 18.5-24.9, and 25-30 kg/m 2 ) (Table 3). Table 3: A comparison of PSQI scores for differences in sleep-related parameters Variables n (%) PSQI p value Mean ± SD Median (IQR) Mean rank Sex Male Female 32 (34.4) 61 (65.6) 6.00 ± 2.27 6.69 ± 3.11 5.50 (3.00) 6.00 (4.00) 42.86 49.17 0.279 a Age < 30 yr 30 – 50 yr 82 (88.2) 11 (11.8) 6.51 ± 2.87 6.00 ± 2.83 6.00 (3.00) 5.00 (5.00) 47.67 42.00 0.509 a BMI < 18.5 kg/m 2 18.5 – 24.9 kg/m 2 25.0 – 30.0 kg/m 2 24 (25.8) 55 (59.1) 14 (15.1) 6.42 ± 3.03 6.60 ± 2.99 5.93 ± 1.94 6.00 (3.75) 6.00 (4.00) 5.50 (3.25) 47.21 47.94 42.96 0.824 b a p value derived from the Mann-Whitney U test (p < 0.05), b p value derived from the Kruskal-Wallis test (p < 0.05); data are presented as mean ± standard deviation, median (interquartile range) and mean rank. Good and poor sleepers’ demographics and differences in sleep related parameters The Sk-I group has 13 good sleepers (41.9%) and 18 poor sleepers (58.1%); the Sk-II group has 16 good sleepers (51.6%) and 15 poor sleepers (48.4%); and the Sk-III group has 12 good sleepers (38.7%) and 19 poor sleepers (61.3%). The frequency of good and poor sleepers did not significantly differ among the skeletal groups (p values > 0.05) (Table 4). After classifying the sample into good and poor sleeper groups, we found that there were no significant differences in the frequency of the good and poor sleepers in sex distribution, age, BMI, and ANB (p > 0.05) (Table 4). Table 4: Good and poor sleepers’ demographics and differences in sleep related parameters Variables Good sleeper PSQI ≤ 5 Poor sleeper PSQI > 5 p value Sex (n(%)) Male Female 17 (53.1) 24 (39.3) 15 (46.9) 37 (60.7) 0.204 a Age (yr) Mean±SD Median (IQR) Mean rank 23.83 ± 5.74 22.00 (5.00) 48.43 23.56 ± 5.91 22.00 (5.00) 45.88 0.649 b BMI (kg/m 2 ) Mean±SD Median Mean rank 21.32 ± 3.67 20.81 (5.13) 48.62 20.92 ± 3.28 20.31 (4.71) 45.72 0.607 b ANB ( o ) Mean±SD Median Mean rank 3.05 ± 3.61 3.70 (6.05) 50.66 2.08 ± 4.07 3.10 (6.50) 44.12 0.246 b Skeletal pattern (n(%)) Sk-I Sk-II Sk-III 13 (41.9) 16 (51.6) 12 (38.7) 18 (58.1) 15 (48.4) 19 (61.3) 0.567 a Total (n(%)) 41 (44.1) 52 (55.9) a p value derived from χ 2 test (p ≤ 0.05); data are presented as frequencies (percentages), b p value derived from Mann-Whitney U test (p < 0.05); data are presented as mean ± standard deviation, median (interquartile range), and mean rank. Discussion This study evaluated the mean PSQI scores and the variations in PSQI scores among Sk-I, Sk-II, and Sk-III groups. Our methodology demonstrated that there were no significant differences in baseline demographic characteristics (sex, age, BMI) among the three groups, which minimized the effect of confounding factors on the results. Regarding sex, prior research has reported that young adult females experience poorer sleep quality than males, as assessed by the PSQI ( 28 ). In our study, we observed that although females exhibited higher PSQI scores compared to males, the difference was not statistically significant. The previous study found that obesity (BMI ≥ 27.8 kg/m²) was associated with increased daytime sleepiness, high wake time after onset of sleep, total wake time, and low sleep time ( 29 ). We found no significant differences in sleep quality among patients with a BMI of 18.5, 18.5–24.9, and 25–30 kg/m² groups in our study. This might be due to the fact that obesity was defined as a BMI of ≥ 30 kg/m² and was excluded from the study ( 30 ). According to the previous studies, many young adults report poor sleep quality. The lifestyle of young adults, which is characterized by the lack of a normal sleeping schedule, leads to irregular sleep-wake patterns. As a result, their nightly sleep falls short of meeting their body's needs. Research had shown that undergraduate students experience insufficient amounts of sleep due to academic and social obligations ( 31 , 32 ). Our study participants consisted of 88.2% young adults (aged < 30 years) and found that all three skeletal groups exhibited poor sleep quality. In the Sk-I group, the highest subcomponent score was subjective sleep quality, while in the Sk-II group it was daytime dysfunction. Furthermore, the Sk-III group exhibited the highest subcomponent score in sleep onset latency. In another study, the PSQI in younger participants (18–29 years) also showed worse subjective sleep quality, longer sleep latency, and more daytime dysfunction ( 33 ). However, due to their mild sleep problems, they rarely use prescription sleep aids, and sleep medication requires a doctor's prescription ( 31 , 32 ). This corresponds with our research results, as we noticed the lowest levels of sleep medication usage in every skeletal group. Our study conducted a subgroup analysis to compare patients under 30 years of age with those aged 30–50 years. The results also showed that the younger group had higher PSQI scores, but no significant difference was observed. Similarly, in the previous study, it was found that 18–29-year-olds had the highest PSQI among participants aged 18–70 but observed no statistically significant variance between different age groups ( 33 ). In this study, the mean PSQI scores for the Sk-I, Sk-II, and Sk-III indicated poor sleep quality (PSQI > 5). Sk-II group exhibited the highest PSQI score (mean 6.68 ± 3.39), followed by Sk-I (6.42 ± 2.71), and Sk-III (6.26 ± 2.46). The observed differences in airway dimensions among individuals with different sagittal skeletal patterns may be the underlying cause. Prior research has determined that different sagittal skeletal patterns are associated with varying upper airway dimensions ( 17 , 19 ). The oropharynx is the most common site for airway obstruction ( 16 , 34 ). El H. and Palomo JM.'s studies found that oropharyngeal volume was reduced for Class III with mandibular protrusion, Class III maxillary retrusion, Class I, Class II maxillary protrusion, and Class II mandibular retrusion, in order ( 16 ). Pornsuksiri's research also showed a significant reduction in the dimensions of the oropharyngeal and hypopharyngeal airways in Class III, I, and II, respectively ( 17 ). Furthermore, the oropharyngeal area exhibited significant correlation with the ANB angle, declining as the ANB angle increased ( 17 , 19 ). However, statistical analysis in this study revealed no significant differences in PSQI scores among Sk-I, Sk-II, and Sk-III groups (p > 0.05). Furthermore, when classifying patients into good and poor sleeper groups, we found no statistically significant differences in sex distribution, age, BMI, ANB, or in the Sk-I, Sk-II, and Sk-III distribution (p > 0.05). Similarly, a previous study on sagittal skeletal patterns, specifically focusing on Sk-I and Sk-II, found no significant correlation between the sagittal skeletal patterns and PSQI scores ( 35 ). Thus, the PSQI scores did not show any statistically significant differences in sagittal skeletal patterns. This suggests that only the sagittal skeletal pattern is insufficient to accurately predict sleep quality. Sleep quality is influenced by numerous factors. The size of the upper airway can affect the ability to breathe properly during sleep, which is one of the interesting factors. Consequently, future research should aim to quantify the upper airway dimension to ascertain its potential correlation with sleep quality. Conclusions The findings of this study indicate that sleep quality does not significantly differ among skeletal class I (Sk-I), class II (Sk-II), and class III (Sk-III) orthodontic patients. Additionally, there are no significant differences in the frequency of good and poor sleepers across the sagittal skeletal classifications. Therefore, for comprehensive orthodontic treatment planning, we recommend incorporating sleep quality assessments, such as the PSQI, into routine orthodontic evaluations. Abbreviations Sk-I, II and III Skeletal class I, II and III PSQI Pittsburgh Sleep Quality Index ANB angle Subspinale (A point) – Nasion – Supramentale (B point) angle BMI Body Mass Index CVM Cervical Vertebral Maturation DURAT Sleep duration DISTB Sleep disturbances LATEN Sleep latency DAYDYS Daytime dysfunction HSE Habitual sleep efficiency SLPQUAL Sleep quality MEDS Sleep medication Declarations Ethics approval and consent to participate : This study was conducted in accordance with the Declaration of Helsinki, the Belmont report, CIOMS guidelines and the international practice (ICH-GCP) and approved by The Human Research Ethics Committee of Thammasat University (Science), Thailand (project code: 66DE020, approved on 9 June 2023). Informed consent was obtained from all subjects involved in the study. Informed consent was obtained from all subjects involved in the study. Consent for publication : All authors have approved the manuscript, and any participants involved have given explicit consent for their data to be published. Availability of data and materials : The data are only available on request due to privacy restrictions. Competing interests : The authors declare that they have no competing interests Funding: This study was supported by Thammasat University Research Fund, Contract No. TUFT 042/2568 Author contributions: Conceptualization, C.S., N.C. and S.P.; Data curation C.S.; Formal analysis, C.S., and S.P.; Investigation, C.S.; Methodology, C.S., N.C. and S.P.; Project administration, N.C. and S.P.; Resources, C.S., N.C. and S.P.; Software, C.S.; Supervision N.C. and S.P.; Validation, C.S., N.C. and S.P.; Visualization, C.S., and S.P.; Writing – original draft, C.S.; Writing – review and editing, C.S., N.C. and S.P. 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Angle Orthod. 2002;72(2):124–34. Ceylan I, Oktay H. A study on the pharyngeal size in different skeletal patterns. Am J Orthod Dentofac Orthop. 1995;108(1):69–75. Stauffer JL, Zwillich CW, Cadieux RJ, Bixler EO, Kales A, Varano LA, et al. Pharyngeal size and resistance in obstructive sleep apnea. Am Rev Respir Dis. 1987;136(3):623–7. Anch AM, Remmers JE, Bunce H. 3rd. Supraglottic airway resistance in normal subjects and patients with occlusive sleep apnea. J Appl Physiol Respir Environ Exerc Physiol. 1982;53(5):1158–63. Remmers JE, deGroot WJ, Sauerland EK, Anch AM. Pathogenesis of upper airway occlusion during sleep. J Appl Physiol Respir Environ Exerc Physiol. 1978;44(6):931–8. Karakoc O, Akcam T, Gerek M, Genc H, Ozgen F. The upper airway evaluation of habitual snorers and obstructive sleep apnea patients. ORL J Otorhinolaryngol Relat Spec. 2012;74(3):136–40. Endo S, Mataki S, Kurosaki N. Cephalometric evaluation of craniofacial and upper airway structures in Japanese patients with obstructive sleep apnea. J Med Dent Sci. 2003;50(1):109–20. Tripuwabhrut K, Sonsuwan N, Lampang S, Jotikasthira D. Efficacy of Non-adjustable Magnetic Mandibular Advancement Appliances (2M2A) in Patients with Mild Obstructive Sleep Apnea: a Preliminary Short-term Study: Original articles. CM Dent J [Internet]. 2019;40(3):55–66. Sutthiprapaporn P, Manosudprasit A, Pisek A, Manosudprasit M, Pisek P, Phaoseree N, et al. Establishing Esthetic Lateral Cephalometric Values for Thai Adults after Orthodontic Treatment. Khon Kaen Dent J. 2020;23(2):31–41. Koo TK, Li MY. A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. J Chiropr Med. 2016;15(2):155–63. Fatima Y, Doi SA, Najman JM, Mamun AA. Exploring Gender Difference in Sleep Quality of Young Adults: Findings from a Large Population Study. Clin Med Res. 2016;14(3–4):138–44. Vgontzas AN, Bixler EO, Tan TL, Kantner D, Martin LF, Kales A. Obesity without sleep apnea is associated with daytime sleepiness. Arch Intern Med. 1998;158(12):1333–7. Wosu AC, Vélez JC, Barbosa C, Andrade A, Frye M, Chen X, et al. The Relationship between High Risk for Obstructive Sleep Apnea and General and Central Obesity: Findings from a Sample of Chilean College Students. ISRN Obes. 2014;2014:871681. Pensuksan WC, Lertmaharit S, Lohsoonthorn V, Rattananupong T, Sonkprasert T, Gelaye B, et al. Relationship between Poor Sleep Quality and Psychological Problems among Undergraduate Students in the Southern Thailand. Walailak J Sci Technol. 2016;13(4):235–42. Chanamanee P, Taboonpong S, Intanon T. Sleep quality and related factors among university students in southern Thailand. J Health Sci Med Res. 2006;24:163–73. Tsaava M, Oniani N, Eliozishvili M, Sakhelashvili I, Tkemaladze N, Aladashvili T, Basishvili T, Darchia N. Age-Based Differences in Sleep Quality, Pre-Sleep Arousal, and Psychosocial Factors during the Second Wave Lockdown of the COVID-19 Pandemic in Georgia—A Higher Vulnerability of Younger People. Int J Environ Res Public Health. 2022;19(23):16221. 10.3390/ijerph192316221 . Schwab RJ, Gefter WB, Hoffman EA, Gupta KB, Pack AI. Dynamic upper airway imaging during awake respiration in normal subjects and patients with sleep disordered breathing. Am Rev Respir Dis. 1993;148(5):1385–400. Vejwarakul W, Ko EW, Lin CH. Evaluation of pharyngeal airway space after orthodontic extraction treatment in class II malocclusion integrating with the subjective sleep quality assessment. Sci Rep. 2023;13(1):9210. Additional Declarations No competing interests reported. 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Thammasat University","correspondingAuthor":false,"prefix":"","firstName":"Narissaporn","middleName":"","lastName":"Chaiprakit","suffix":""},{"id":559467065,"identity":"0f3437fd-a44d-45a4-9966-5492defa8f51","order_by":2,"name":"Siripatra Patchanee","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIiWNgGAWjYDACZgaGA1Am42OICHMDMVoMwExjMIOZkYAWCABrYZOGMAhokW/nfXi4oOZPPn8D77Hqgoo/0fztQC0/KrbhNv4wu8HhGccMLGcc4Eu7PeOMQe6Mw4wNjD1nbuPWwszGcJiHzcCA4QCP2W3eNoPcBqAWZsY23Frkm0Fa/hkYyAO1FIO0zCekheEwUAtQpYEBUAszSMsGQloMQFpm9hkbGB7mS5bmOWOcuxGo5SA+v8j3H2P+XPBNzkDueO/BzzwVcrnzzh8++OBHBR6HMYBjE0TyIEQO4FUP18LAg1/VKBgFo2AUjFwAADWBULkY6TMSAAAAAElFTkSuQmCC","orcid":"","institution":"Faculty of Dentistry, Thammasat University","correspondingAuthor":true,"prefix":"","firstName":"Siripatra","middleName":"","lastName":"Patchanee","suffix":""}],"badges":[],"createdAt":"2025-11-12 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18:21:24","extension":"html","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":153196,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8098939/v1/200257f99e28a9a428f2062a.html"},{"id":98774780,"identity":"f1743b4f-10d0-4ea5-9b44-5cbc14401ae4","added_by":"auto","created_at":"2025-12-22 12:14:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":852889,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8098939/v1/ca5ea995-d328-4e11-b4f1-72b928e05c71.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eEvaluation of the Pittsburgh Sleep Quality Index in a Group of Orthodontic Patients With Different Sagittal Skeletal Relationships\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSleep is an essential component of the human daily routine. Restorative sleep is associated with improved physical, cognitive, and mental health. In contrast, poor or disordered sleep is associated with possible cognitive and psychological problems as well as a deterioration in physical health (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The Pittsburgh Sleep Quality Index (PSQI) is a widely used, standardized, self-administered questionnaire that assesses sleep quality over a one-month period (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). It is employed across clinical and non-clinical populations, including individuals with and without medical or psychological conditions (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). PSQI is used in the medical practice as a screening tool for sleep dysfunction (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) or to assess sleep quality in healthcare professionals (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), among other applications. The PSQI was designed to establish a reliable and valid measure of sleep quality, differentiate between \u0026ldquo;good\u0026rdquo; and \u0026ldquo;poor\u0026rdquo; sleepers, and provide a simple, clinically useful assessment of various sleep problems (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). The PSQI has been translated into multiple languages, including Thai. The Thai Pittsburgh Sleep Quality Index (Thai-PSQI) is equivalent to the original English version when utilized with Thai-speaking patients and has good sensitivity and specificity for identifying good and poor sleepers (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSkeletal relationships are commonly evaluated using cephalometric analysis to assess maxillomandibular discrepancies by orthodontists before treatment (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The ANB angle (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) and the Wits appraisal (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) are widely used to identify a skeletal sagittal discrepancy, which classifies the skeletal relationships into 3 types: skeletal class I (Sk-I), class II (Sk-II), and class III (Sk-III) (\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). The mandible's and maxilla's anteroposterior positions, which together form the facial skeletal pattern, influenced upper airway dimensions (\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Since the pharyngeal musculature is closely tied to the bone structure, these atypical facial skeletal patterns may be related to the abnormalities of the airway (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOrthodontists have also shown interest in the airway, as it plays a vital role in craniofacial development and is relevant to diagnosing and managing conditions such as mouth breathing and sleep disorders (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). In addition, current evidence indicates that breathing disorders such as obstructive sleep apnea are associated with diminished upper airway dimensions. The previous studies revealed that posterior airway space, which is the most constricted area at the base of the tongue, and oropharyngeal volume were reduced in Sk-III, Sk-I, and Sk-II, respectively (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). The nasal passage volume was found to be reduced in Sk-I, Sk-III, and Sk-II, in that order (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Moreover, a previous study found that micrognathia and skeletal class II relationships were the most common characteristics in retropalatal and retroglossal obstruction patients, but the retropalatal obstruction group had fewer (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Additionally, the oropharyngeal area was found to be significantly related to the ANB angle, with the ANB angle increasing as the oropharynx area decreased (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Narrowing of the pharyngeal structure may increase the tendency of pharyngeal collapse during sleep when the pharyngeal dilator muscles fail to generate sufficient force to resist the negative inspiratory pressure in the pharynx (\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), which may impair sleep quality.\u003c/p\u003e \u003cp\u003eAccording to previous studies, the skeletal pattern influences the dimensions of the upper airway, and as the ANB angle increases, the area of the oropharynx significantly decreases, potentially leading to breathing disorders (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Thus, this study aims to evaluate and compare the sleep quality in Thai orthodontic patients with different skeletal patterns using the Thai-PSQI.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Participants\u003c/h2\u003e \u003cp\u003e This study was approved by the Human Research Ethics Committee of Thammasat University (Science), Thailand. The study included 93 Thai orthodontic patients aged 18\u0026ndash;50 (34 males and 59 females) who were undergoing orthodontic treatment at the Orthodontic Department in the Faculty of Dentistry at Thammasat University, and all participants provided written informed consent prior to their inclusion in the study. All participants had reached cervical vertebral maturation (CVM) stage CS6 and were proficient in reading, writing, speaking, and listening in Thai. The patients who were excluded from the study were those with obesity (body mass index\u0026thinsp;\u0026gt;\u0026thinsp;30) or clinical overweight, night shift work, a history of orthognathic surgery or orthopedic treatments in the craniofacial region, chronic respiratory disease, previous tonsillectomy and/or adenoidectomy, craniofacial trauma or pathology in the study area, a history of head and neck radiation therapy, mental or psychiatric disorders, and doctor-diagnosed obstructive sleep apnea.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cp\u003eLateral cephalometric radiographs were taken with subjects in an upright position with the x-ray tube perpendicular to the sagittal plane and all subjects in the Frankfort horizontal plane parallel to the floor. During head stabilization throughout exposure, ear rods are inserted into the external auditory meatus. Participants were instructed to bite in maximum intercuspation and inhale through the nose during image capture (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCephalometric analyses were conducted using \"Dolphin Imaging Version 11.95.08.50 Premium\" (Dolphin Imaging and Management Solution, Los Angeles, California, USA) to classify participants into Sk-I, Sk-II, and Sk-III groups using the Thai norm of ANB Angle (2.8\u003csup\u003eo\u003c/sup\u003e\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003csup\u003eo\u003c/sup\u003e) (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). To classify the sagittal skeletal pattern, SNA, SNB, and ANB angles were measured: Sk-I, 0.5\u003csup\u003eo\u003c/sup\u003e\u0026thinsp;\u0026le;\u0026thinsp;ANB\u0026thinsp;\u0026le;\u0026thinsp;5.1 \u003csup\u003eo\u003c/sup\u003e; Sk-II, ANB\u0026thinsp;\u0026gt;\u0026thinsp;5.1 \u003csup\u003eo\u003c/sup\u003e; Sk-III, ANB\u0026thinsp;\u0026lt;\u0026thinsp;0.5\u003csup\u003eo\u003c/sup\u003e. All patients have been checked for normal SN length (males, 70.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6 mm; females, 63.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1 mm) and SN-FH angle (6.9 \u003csup\u003eo\u003c/sup\u003e \u0026plusmn; 3.1\u003csup\u003eo\u003c/sup\u003e) (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). If a patient's SN length or SN-FH angle is not within the Thai norm, the skeletal classification is confirmed by the Thai norm of Wits appraisal (males, -0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1 mm; females, -1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6 mm) (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). The Wits appraisal value in Thai norm indicates Sk-I; a greater positive Wits appraisal indicates Sk-II; and a negative Wits appraisal indicates Sk-III.\u003c/p\u003e \u003cp\u003eNineteen cephalometric radiographs (20% of the total sample) were randomly selected and re-measured two weeks after the initial assessment. The Intraclass Correlation Coefficient (ICC) was used to evaluate the reliability of the measurements between the first and second assessments. In this study, ICC greater than 0.90 is considered excellent reliability (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), so the first set of measurements was utilized.\u003c/p\u003e \u003cp\u003eAll subjects were assessed for sleep quality using the Thai-PSQI (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Nineteen questions are self-scored, and five are roommate or bed partner scored. The last five questions are used for clinical information only and are not included in PSQI scoring. These nineteen questions are scored equally on a 0\u0026ndash;3 scale for subjective sleep quality (SQ), sleep latency (SL), sleep duration (SD), habitual sleep efficiency (HSE), sleep disturbances (SDI), sleep medication use (SM), and daytime dysfunction (DD). The total of the seven component scores results in a global PSQI score ranging from 0 to 21. A total global PSQI score\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;5 indicates good sleep quality, while\u0026thinsp;\u0026gt;\u0026thinsp;5 indicates poor sleep quality. Higher global PSQI scores indicate poorer sleep (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were conducted using IBM SPSS Software Version 26 (IBM Corporation, Armonk, NY, USA). The statistics showed that the measurement was not normally distributed according to the Shapiro\u0026ndash;Wilk test. The PSQI scores were compared among the groups using the Kruskal-Wallis test. A comparison of PSQI scores in each sleep-related parameter (sex, age, and body mass index [BMI]) was conducted using the Mann-Whitney U test and the Kruskal-Wallis test. The Chi-square test and Mann-Whitney U test were used to analyze the demographics and differences in sleep-related parameters between good and poor sleepers. Statistical significance was set at α\u0026thinsp;=\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003e\u003cu\u003eDemographic characteristics\u0026nbsp;\u003c/u\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study included 93 orthodontic patients (32 males, 61 females) with a mean age of 23.68 \u0026plusmn; 5.80 years, and a mean BMI of 21.09 \u0026plusmn; 3.44 kg/m\u0026sup2;. Participants were categorized into three groups based on their skeletal patterns:\u0026nbsp;\u003c/p\u003e\n\u003cul class=\"decimal_type\"\u003e\n \u003cli\u003eSkeletal Class I (Sk-I): 8 males, 23 females (mean age: 22.94 \u0026plusmn; 4.37 years; BMI: 20.25 \u0026plusmn; 2.63 kg/m\u003csup\u003e2\u003c/sup\u003e; ANB: 3.41\u003csup\u003eo\u003c/sup\u003e \u0026plusmn; 0.95\u003csup\u003eo\u003c/sup\u003e)\u003c/li\u003e\n \u003cli\u003eSkeletal Class II (Sk-II): 10 males, 21 females (mean age: 24.55 \u0026plusmn; 7.26 years; BMI: 21.69 \u0026plusmn; 3.72 kg/m\u003csup\u003e2\u003c/sup\u003e; ANB: 6.37\u003csup\u003eo\u003c/sup\u003e \u0026plusmn; 0.89\u003csup\u003eo\u003c/sup\u003e)\u003c/li\u003e\n \u003cli\u003eSkeletal Class III (Sk-III): 14 males, 17 females (mean age: 23.55 \u0026plusmn; 5.49 years; BMI: 21.34 \u0026plusmn; 3.80 kg/m\u003csup\u003e2\u003c/sup\u003e; ANB: -2.25\u003csup\u003eo\u003c/sup\u003e \u0026plusmn; 2.22\u003csup\u003eo\u003c/sup\u003e).\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eNo statistically significant differences were observed in sex, age, or BMI among groups (p \u0026gt; 0.05). Additionally, the Sk-I, Sk-II, and Sk-III groups of this study are only different in the anteroposterior position of the mandible (SNB) and not different in the anteroposterior position of the maxilla (SNA) (Table 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e1:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;Sample characteristics (N=93)\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"553\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSk I (n=31)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSk II \u0026nbsp;(n=31)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSk III \u0026nbsp;(n=31)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal (n=93)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u0026Dagger;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003eSex\u003cbr\u003e\u0026nbsp;Male (%): Female (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cbr\u003e\u0026nbsp;8(25.8) : 23(74.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cbr\u003e\u0026nbsp;10(32.3) : 21(67.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cbr\u003e\u0026nbsp;14(45.2) : 17(54.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cbr\u003e\u0026nbsp;32(34.4) : 61(65.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cbr\u003e\u0026nbsp;0.263 ғ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003eAge (yr)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e22.94 \u0026plusmn; 4.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e24.55 \u0026plusmn; 7.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e23.55 \u0026plusmn; 5.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e23.68 \u0026plusmn; 5.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e0.913\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003eWeight (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e54.23 \u0026plusmn; 10.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e58.84 \u0026plusmn; 11.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e59.26 \u0026plusmn; 12.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e57.44 \u0026plusmn; 11.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e0.153\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003eHeight (m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e1.63 \u0026plusmn; 0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e1.65 \u0026plusmn; 0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e1.66 \u0026plusmn; 0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e1.65 \u0026plusmn; 0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e0.352\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e20.25 \u0026plusmn; 2.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e21.69 \u0026plusmn; 3.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e21.34 \u0026plusmn; 3.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e21.09 \u0026plusmn; 3.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e0.393\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003eSNA (\u003csup\u003eo\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e84.05 \u0026plusmn; 2.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e85.48 \u0026plusmn; 3.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e83.61 \u0026plusmn; 4.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e84.38 \u0026plusmn; 3.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e0.088\u0026dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003eSNB (\u003csup\u003eo\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e80.63 \u0026plusmn; 2.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e79.17 \u0026plusmn; 3.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e86.18 \u0026plusmn; 5.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e81.99 \u0026plusmn; 4.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e*0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003eANB (\u003csup\u003eo\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e3.41 \u0026plusmn; 0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e6.37 \u0026plusmn; 0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e-2.25 \u0026plusmn; 2.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e2.51 \u0026plusmn; 3.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e*0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003eSN (mm)\u003cbr\u003e\u0026nbsp;Male\u0026nbsp;\u003cbr\u003e\u0026nbsp;Female\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e63.82 \u0026plusmn; 2.62\u003cbr\u003e\u0026nbsp;66.01 \u0026plusmn; 2.86\u003cbr\u003e\u0026nbsp;63.05 \u0026plusmn; 2.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e65.01 \u0026plusmn; 3.50\u003cbr\u003e\u0026nbsp;68.63 \u0026plusmn; 2.69\u003cbr\u003e\u0026nbsp;63.29 \u0026plusmn; 2.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e66.30 \u0026plusmn; 6.11\u003cbr\u003e\u0026nbsp;70.00 \u0026plusmn;2.69\u003cbr\u003e\u0026nbsp;63.25 \u0026plusmn; 4.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e65.04 \u0026plusmn; 4.41\u003cbr\u003e\u0026nbsp;68.58 \u0026plusmn; 4.79\u003cbr\u003e\u0026nbsp;63.19 \u0026plusmn; 2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e0.152\u003cbr\u003e\u0026nbsp;0.146\u003cbr\u003e\u0026nbsp;0.926\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003eSN-FH (\u003csup\u003eo\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e8.63 \u0026plusmn; 1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e8.33 \u0026plusmn; 2.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e8.53 \u0026plusmn; 3.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e8.49 \u0026plusmn; 2.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e0.835\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003eAO-BO (mm)\u003cbr\u003e\u0026nbsp;Male\u0026nbsp;\u003cbr\u003e\u0026nbsp;Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e0.19 \u0026plusmn; 2.55\u003cbr\u003e\u0026nbsp;0.9 \u0026plusmn; 2.33\u003cbr\u003e\u0026nbsp;-0.57 \u0026plusmn; 2.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e3.12 \u0026plusmn; 2.36\u003cbr\u003e\u0026nbsp;4.62 \u0026plusmn; 2.94\u003cbr\u003e\u0026nbsp;2.41 \u0026plusmn; 1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e-7.57 \u0026plusmn; 4.30\u003cbr\u003e\u0026nbsp;-9.45 \u0026plusmn;5.33\u003cbr\u003e\u0026nbsp;-6.02 \u0026plusmn; 2.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e-1.55 \u0026plusmn; 5.49\u003cbr\u003e\u0026nbsp;-2.47 \u0026plusmn; 7.54\u003cbr\u003e\u0026nbsp;-1.06 \u0026plusmn; 4.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e*0.000\u003cbr\u003e\u0026nbsp;*0.000\u003cbr\u003e\u0026nbsp;*0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003e\u003csup\u003eғ\u003c/sup\u003e\u003c/em\u003e\u003cem\u003e\u0026nbsp;Chi-square test; data are presented as frequencies (percentages), \u003csup\u003e\u0026dagger;\u003c/sup\u003e One-way ANOVA and \u003csup\u003e\u0026Dagger;\u0026nbsp;\u003c/sup\u003eA Kruskal-Wallis test were performed for intergroup differences in skeletal class I, II, and III groups; data are presented as mean \u0026plusmn; standard (*p\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u003cu\u003e\u0026lt;\u003c/u\u003e\u003c/em\u003e\u003cem\u003e\u0026nbsp;0.05).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cu\u003eThe PSQI scores and sagittal skeletal patterns\u003c/u\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe mean PSQI score for all participants was 6.45 \u0026plusmn; 2.85, exceeding the cutoff of 5, indicating poor sleep quality. In total, 55.9% of the participants were categorized as individuals with poor sleep quality. The average PSQI scores for patients in the Sk-I, Sk-II, and Sk-III groups were 6.42 \u0026plusmn; 2.71, 6.68 \u0026plusmn; 3.39, and 6.26 \u0026plusmn; 2.46, respectively. The highest PSQI scores was observed in the Sk-II group, followed by the Sk-I group, and then the Sk-III group.\u0026nbsp;The highest subcomponent score in the Sk-I group is subjective sleep quality scores (1.39 \u0026plusmn; 0.62), while in the Sk-II group, it is the daytime dysfunction scores (1.32 \u0026plusmn; 0.91), and in the Sk-III group, it is sleep onset latency scores (1.52 \u0026plusmn; 0.93). Interestingly, using sleep medication resulted in the lowest subcomponent score among all classifications (Sk-I: 0.16 \u0026plusmn; 0.58, Sk-II: 0.13 \u0026plusmn; 0.56, Sk-III: 0.00 \u0026plusmn; 0.00) (Table 2).\u003c/p\u003e\n\u003cp\u003eThere were no significant differences in the total PSQI score, sleep duration (DURAT), sleep disturbances (DISTB), sleep latency (LATEN), daytime dysfunction (DAYDYS), habitual sleep efficiency (HSE), sleep quality (SLPQUAL), or sleep medication (MEDS) among the Sk-I, Sk-II, and Sk-III groups (p-values \u0026gt; 0.05) (Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable 2:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;A comparison of PSQI scores and\u0026nbsp;\u003c/em\u003e\u003cem\u003esubcomponent scores\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"left\" width=\"662\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003cstrong\u003es\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSk-I (n=31)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSk-II (n=31)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSk-III (n=31)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKruskal-Wallis H\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ep value \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u0026nbsp;\u003c/strong\u003e\u0026plusmn; \u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean rank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u0026nbsp;\u003c/strong\u003e\u0026plusmn; \u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean rank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u0026nbsp;\u003c/strong\u003e\u0026plusmn; \u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean rank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e1 DURAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.77\u0026plusmn; 0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e49.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.87 \u0026plusmn; 1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0(2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e48.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.61 \u0026plusmn; 0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e42.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.75 \u0026plusmn; 0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.526\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e2 DISTB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e1.16 \u0026plusmn; 0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e41.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.29 \u0026plusmn; 0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e47.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.39 \u0026plusmn; 0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e52.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.28 \u0026plusmn; 0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e3.397\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.183\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e3 LATEN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e1.26 \u0026plusmn; 0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e44.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.26 \u0026plusmn; 0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e44.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.52 \u0026plusmn; 0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e51.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.34 \u0026plusmn; 0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.773\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.412\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e4 DAYDYS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e1.35 \u0026plusmn; 0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e49.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.32 \u0026plusmn; 0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e48.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.10 \u0026plusmn; 0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e42.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.26 \u0026plusmn; 0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.504\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e5 HSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.32 \u0026plusmn; 0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e43.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.52 \u0026plusmn; 0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e51.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.35 \u0026plusmn; 0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e45.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.40 \u0026plusmn; 0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e2.648\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.266\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e6 SLPQUAL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e1.39 \u0026plusmn; 0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e50.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.29 \u0026plusmn; 0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e45.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.29 \u0026plusmn; 0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e45.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.32 \u0026plusmn; 0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.908\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.635\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e7 MEDS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.16 \u0026plusmn; 0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e48.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.13 \u0026plusmn; 0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e47.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.00 \u0026plusmn; 0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e44.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.10 \u0026plusmn; 0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e2.912\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.233\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003eTotal PSQI scores\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e6.42 \u0026plusmn; 2.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e6 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e47.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e6.68 \u0026plusmn; 3.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e5 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e46.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e6.26 \u0026plusmn; 2.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e6 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e47.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e6.45 \u0026plusmn; 2.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.988\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cem\u003eTotal PSQI score\u003c/em\u003e\u003cem\u003es\u003c/em\u003e\u003cem\u003e,\u0026nbsp;\u003c/em\u003e\u003cem\u003esleep duration (DURAT), sleep disturbances (DISTB), sleep latency (LATEN), daytime dysfunction (DAYDYS), habitual sleep efficiency (HSE), sleep quality (SLPQUAL), and sleep medication (MEDS) in sagittal skeletal classifications I, II, and III was done using the Kruskal-Wallis test at p \u003cu\u003e\u0026lt;\u003c/u\u003e 0.05; data are presented as mean \u0026plusmn; standard deviation, median (interquartile range) and mean rank.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cu\u003eThe PSQI scores and sleep-related parameters\u003c/u\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA comparison of PSQI scores for differences in sleep-related parameters revealed no significant differences between groups based on sex (male and female), age groups (under 30 years and 30-50 years), and BMI categories (under 18.5, 18.5-24.9, and 25-30 kg/m\u003csup\u003e2\u003c/sup\u003e) (Table 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable 3:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cem\u003eA comparison of PSQI scores for differences in sleep-related parameters\u003c/em\u003e\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePSQI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean \u0026plusmn; SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean rank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Male \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Female \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e32 (34.4)\u003c/p\u003e\n \u003cp\u003e61 (65.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6.00 \u0026plusmn; 2.27\u003c/p\u003e\n \u003cp\u003e6.69 \u0026plusmn; 3.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5.50 (3.00)\u003c/p\u003e\n \u003cp\u003e6.00 (4.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e42.86\u003c/p\u003e\n \u003cp\u003e49.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0.279\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026lt; 30 yr\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;30 \u0026ndash; 50 yr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e82 (88.2)\u003c/p\u003e\n \u003cp\u003e11 (11.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6.51 \u0026plusmn; 2.87\u003c/p\u003e\n \u003cp\u003e6.00 \u0026plusmn; 2.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6.00 (3.00)\u003c/p\u003e\n \u003cp\u003e5.00 (5.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e47.67\u003c/p\u003e\n \u003cp\u003e42.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0.509\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026lt; 18.5 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;18.5 \u0026ndash; 24.9 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;25.0 \u0026ndash; 30.0 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e24 (25.8)\u003c/p\u003e\n \u003cp\u003e55 (59.1)\u003c/p\u003e\n \u003cp\u003e14 (15.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6.42 \u0026plusmn; 3.03\u003c/p\u003e\n \u003cp\u003e6.60 \u0026plusmn; 2.99\u003c/p\u003e\n \u003cp\u003e5.93 \u0026plusmn; 1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6.00 (3.75)\u003c/p\u003e\n \u003cp\u003e6.00 (4.00)\u003c/p\u003e\n \u003cp\u003e5.50 (3.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e47.21\u003c/p\u003e\n \u003cp\u003e47.94\u003c/p\u003e\n \u003cp\u003e42.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0.824\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cem\u003e\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/em\u003e\u003cem\u003e\u0026nbsp;p value derived from the\u0026nbsp;\u003c/em\u003e\u003cem\u003eMann-Whitney U test\u0026nbsp;\u003c/em\u003e\u003cem\u003e(p \u003cu\u003e\u0026lt;\u003c/u\u003e 0.05), \u003csup\u003eb\u0026nbsp;\u003c/sup\u003ep value derived from the Kruskal-Wallis test (p \u003cu\u003e\u0026lt;\u003c/u\u003e 0.05); data are presented as mean \u0026plusmn; standard deviation, median (interquartile range) and mean rank.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cu\u003eGood and poor sleepers\u0026rsquo; demographics and differences in sleep related parameters\u003c/u\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe Sk-I group has 13 good sleepers (41.9%) and 18 poor sleepers (58.1%); the Sk-II group has 16 good sleepers (51.6%) and 15 poor sleepers (48.4%); and the Sk-III group has 12 good sleepers (38.7%) and 19 poor sleepers (61.3%). The frequency of good and poor sleepers did not significantly differ among the skeletal groups (p values \u0026gt; 0.05) (Table 4).\u003c/p\u003e\n\u003cp\u003eAfter classifying the sample into good and poor sleeper groups, we found that there were no significant differences in the frequency of the good and poor sleepers in sex distribution, age, BMI, and ANB (p \u0026gt; 0.05) (Table 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable 4:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;Good and poor sleepers\u0026rsquo; demographics and differences in sleep related parameters\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"553\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGood sleeper\u0026nbsp;\u003cbr\u003e\u0026nbsp;PSQI \u0026le; 5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePoor sleeper\u0026nbsp;\u003cbr\u003e\u0026nbsp;PSQI \u0026gt; 5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex (n(%))\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Male \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Female \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e17 (53.1)\u003c/p\u003e\n \u003cp\u003e24 (39.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e15 (46.9)\u003c/p\u003e\n \u003cp\u003e37 (60.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0.204\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (yr)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Mean\u0026plusmn;SD\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Median (IQR)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Mean rank\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e23.83 \u0026plusmn; 5.74\u003c/p\u003e\n \u003cp\u003e22.00 (5.00)\u003c/p\u003e\n \u003cp\u003e48.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e23.56 \u0026plusmn; 5.91\u003c/p\u003e\n \u003cp\u003e22.00 (5.00)\u003c/p\u003e\n \u003cp\u003e45.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0.649\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Mean\u0026plusmn;SD\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Median\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Mean rank\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e21.32 \u0026plusmn; 3.67\u003c/p\u003e\n \u003cp\u003e20.81 (5.13)\u003c/p\u003e\n \u003cp\u003e48.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e20.92 \u0026plusmn; 3.28\u003c/p\u003e\n \u003cp\u003e20.31 (4.71)\u003c/p\u003e\n \u003cp\u003e45.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0.607\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eANB (\u003csup\u003eo\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Mean\u0026plusmn;SD\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Median\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Mean rank\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.05 \u0026plusmn; 3.61\u003c/p\u003e\n \u003cp\u003e3.70 (6.05)\u003c/p\u003e\n \u003cp\u003e50.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.08 \u0026plusmn; 4.07\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.10 (6.50)\u003c/p\u003e\n \u003cp\u003e44.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0.246\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSkeletal pattern (n(%))\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Sk-I\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Sk-II\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Sk-III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e13 (41.9)\u003c/p\u003e\n \u003cp\u003e16 (51.6)\u003c/p\u003e\n \u003cp\u003e12 (38.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e18 (58.1)\u003c/p\u003e\n \u003cp\u003e15 (48.4)\u003c/p\u003e\n \u003cp\u003e19 (61.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0.567\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal \u0026nbsp;(n(%))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e41 (44.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e52 (55.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/em\u003e\u003cem\u003e\u0026nbsp;p value derived from \u0026chi;\u003csup\u003e2\u003c/sup\u003e test (p\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026le;\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003e0.05); data are presented as frequencies (percentages), \u003csup\u003eb\u003c/sup\u003e p value derived from\u0026nbsp;\u003c/em\u003e\u003cem\u003eMann-Whitney\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eU\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003etest\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003e(p \u003cu\u003e\u0026lt;\u003c/u\u003e 0.05); data are presented as mean \u0026plusmn; standard deviation, median (interquartile range), and mean rank.\u003c/em\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study evaluated the mean PSQI scores and the variations in PSQI scores among Sk-I, Sk-II, and Sk-III groups. Our methodology demonstrated that there were no significant differences in baseline demographic characteristics (sex, age, BMI) among the three groups, which minimized the effect of confounding factors on the results.\u003c/p\u003e \u003cp\u003eRegarding sex, prior research has reported that young adult females experience poorer sleep quality than males, as assessed by the PSQI (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). In our study, we observed that although females exhibited higher PSQI scores compared to males, the difference was not statistically significant.\u003c/p\u003e \u003cp\u003eThe previous study found that obesity (BMI\u0026thinsp;\u0026ge;\u0026thinsp;27.8 kg/m\u0026sup2;) was associated with increased daytime sleepiness, high wake time after onset of sleep, total wake time, and low sleep time (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). We found no significant differences in sleep quality among patients with a BMI of 18.5, 18.5\u0026ndash;24.9, and 25\u0026ndash;30 kg/m\u0026sup2; groups in our study. This might be due to the fact that obesity was defined as a BMI of \u0026ge;\u0026thinsp;30 kg/m\u0026sup2; and was excluded from the study (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAccording to the previous studies, many young adults report poor sleep quality. The lifestyle of young adults, which is characterized by the lack of a normal sleeping schedule, leads to irregular sleep-wake patterns. As a result, their nightly sleep falls short of meeting their body's needs. Research had shown that undergraduate students experience insufficient amounts of sleep due to academic and social obligations (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Our study participants consisted of 88.2% young adults (aged\u0026thinsp;\u0026lt;\u0026thinsp;30 years) and found that all three skeletal groups exhibited poor sleep quality. In the Sk-I group, the highest subcomponent score was subjective sleep quality, while in the Sk-II group it was daytime dysfunction. Furthermore, the Sk-III group exhibited the highest subcomponent score in sleep onset latency. In another study, the PSQI in younger participants (18\u0026ndash;29 years) also showed worse subjective sleep quality, longer sleep latency, and more daytime dysfunction (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). However, due to their mild sleep problems, they rarely use prescription sleep aids, and sleep medication requires a doctor's prescription (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). This corresponds with our research results, as we noticed the lowest levels of sleep medication usage in every skeletal group. Our study conducted a subgroup analysis to compare patients under 30 years of age with those aged 30\u0026ndash;50 years. The results also showed that the younger group had higher PSQI scores, but no significant difference was observed. Similarly, in the previous study, it was found that 18\u0026ndash;29-year-olds had the highest PSQI among participants aged 18\u0026ndash;70 but observed no statistically significant variance between different age groups (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, the mean PSQI scores for the Sk-I, Sk-II, and Sk-III indicated poor sleep quality (PSQI\u0026thinsp;\u0026gt;\u0026thinsp;5). Sk-II group exhibited the highest PSQI score (mean 6.68\u0026thinsp;\u0026plusmn;\u0026thinsp;3.39), followed by Sk-I (6.42\u0026thinsp;\u0026plusmn;\u0026thinsp;2.71), and Sk-III (6.26\u0026thinsp;\u0026plusmn;\u0026thinsp;2.46). The observed differences in airway dimensions among individuals with different sagittal skeletal patterns may be the underlying cause. Prior research has determined that different sagittal skeletal patterns are associated with varying upper airway dimensions (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). The oropharynx is the most common site for airway obstruction (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). El H. and Palomo JM.'s studies found that oropharyngeal volume was reduced for Class III with mandibular protrusion, Class III maxillary retrusion, Class I, Class II maxillary protrusion, and Class II mandibular retrusion, in order (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Pornsuksiri's research also showed a significant reduction in the dimensions of the oropharyngeal and hypopharyngeal airways in Class III, I, and II, respectively (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Furthermore, the oropharyngeal area exhibited significant correlation with the ANB angle, declining as the ANB angle increased (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). However, statistical analysis in this study revealed no significant differences in PSQI scores among Sk-I, Sk-II, and Sk-III groups (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Furthermore, when classifying patients into good and poor sleeper groups, we found no statistically significant differences in sex distribution, age, BMI, ANB, or in the Sk-I, Sk-II, and Sk-III distribution (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Similarly, a previous study on sagittal skeletal patterns, specifically focusing on Sk-I and Sk-II, found no significant correlation between the sagittal skeletal patterns and PSQI scores (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThus, the PSQI scores did not show any statistically significant differences in sagittal skeletal patterns. This suggests that only the sagittal skeletal pattern is insufficient to accurately predict sleep quality. Sleep quality is influenced by numerous factors. The size of the upper airway can affect the ability to breathe properly during sleep, which is one of the interesting factors. Consequently, future research should aim to quantify the upper airway dimension to ascertain its potential correlation with sleep quality.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe findings of this study indicate that sleep quality does not significantly differ among skeletal class I (Sk-I), class II (Sk-II), and class III (Sk-III) orthodontic patients. Additionally, there are no significant differences in the frequency of good and poor sleepers across the sagittal skeletal classifications. Therefore, for comprehensive orthodontic treatment planning, we recommend incorporating sleep quality assessments, such as the PSQI, into routine orthodontic evaluations.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eSk-I, II and III\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Skeletal class I, II and III\u003c/p\u003e\n\u003cp\u003ePSQI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Pittsburgh Sleep Quality Index\u003c/p\u003e\n\u003cp\u003eANB angle\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Subspinale (A point)\u0026nbsp;–\u0026nbsp;Nasion\u0026nbsp;–\u0026nbsp;Supramentale\u0026nbsp;(B\u0026nbsp;point) angle\u003c/p\u003e\n\u003cp\u003eBMI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Body Mass Index\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCVM \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Cervical Vertebral Maturation\u003c/p\u003e\n\u003cp\u003eDURAT Sleep duration\u003c/p\u003e\n\u003cp\u003eDISTB \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Sleep disturbances\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLATEN \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Sleep latency\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDAYDYS \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Daytime dysfunction \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHSE \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Habitual sleep efficiency\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSLPQUAL \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Sleep quality \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMEDS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Sleep medication\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cu\u003eEthics approval and consent to participate\u003c/u\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cu\u003e:\u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the Declaration of Helsinki, the Belmont report, CIOMS guidelines and the international practice (ICH-GCP) and approved by The Human Research Ethics Committee of Thammasat University (Science), Thailand (project code: 66DE020, approved on 9 June 2023).\u0026nbsp;Informed consent was obtained from all subjects involved in the study.\u0026nbsp;Informed consent was obtained from all subjects involved in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eConsent for publication\u003c/u\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cu\u003e:\u003c/u\u003e\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll authors have approved the manuscript, and any participants involved have given explicit consent for their data to be published.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eAvailability of data and materials\u003c/u\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cu\u003e:\u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data are only available on request due to privacy restrictions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eCompeting interests\u003c/u\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cu\u003e:\u003c/u\u003e\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eFunding:\u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by Thammasat University Research Fund, Contract No. TUFT 042/2568\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eAuthor contributions:\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, C.S., N.C. and S.P.; Data curation\u0026nbsp;C.S.;\u0026nbsp;Formal analysis, C.S.,\u0026nbsp;and S.P.; Investigation, C.S.; Methodology, C.S., N.C. and S.P.; Project administration, N.C. and S.P.; Resources, C.S., N.C. and S.P.; Software,\u0026nbsp;C.S.; Supervision N.C. and S.P.; Validation, C.S., N.C. and S.P.; Visualization, C.S.,\u0026nbsp;and S.P.; Writing – original draft, C.S.; Writing – review and editing, C.S., N.C. and S.P.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eAcknowledgements:\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by Thammasat University Research Fund, Contract No. TUFT 042/2568\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCrivello A, Barsocchi P, Girolami M, Palumbo F. 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Int J Environ Res Public Health. 2022;19(23):16221. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijerph192316221\u003c/span\u003e\u003cspan address=\"10.3390/ijerph192316221\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchwab RJ, Gefter WB, Hoffman EA, Gupta KB, Pack AI. Dynamic upper airway imaging during awake respiration in normal subjects and patients with sleep disordered breathing. Am Rev Respir Dis. 1993;148(5):1385\u0026ndash;400.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVejwarakul W, Ko EW, Lin CH. Evaluation of pharyngeal airway space after orthodontic extraction treatment in class II malocclusion integrating with the subjective sleep quality assessment. Sci Rep. 2023;13(1):9210.\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-oral-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ohea","sideBox":"Learn more about [BMC Oral Health](http://bmcoralhealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ohea/default.aspx","title":"BMC Oral Health","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Skeletal relationships, Skeletal patterns, Sleep quality, Pittsburgh Sleep Quality Index, PSQI","lastPublishedDoi":"10.21203/rs.3.rs-8098939/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8098939/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThis study aimed to evaluate and compare the subjective sleep quality of Thai orthodontic patients classified into skeletal class I (Sk-I), class II (Sk-II), and class III (Sk-III) groups using the Thai-Pittsburgh Sleep Quality Index (Thai-PSQI).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA total of 93 orthodontic patients undergoing treatment were included in the study. Cephalometric analysis using Dolphin Imaging software classified participants into Sk-I, Sk-II, and Sk-III groups. Sleep quality was assessed using the Thai-PSQI. Data normality was tested using the Shapiro-Wilk test. The Kruskal-Wallis test was used to compare Pittsburgh Sleep Quality Index (PSQI) scores among skeletal groups. Demographic characteristics and differences in sleep-related parameters (sex, age, and body mass index) between good and poor sleepers were analyzed using the Chi-square test and Mann-Whitney U test (α\u0026thinsp;=\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e The Sk-II group had the highest PSQI scores, followed by the Sk-I and Sk-III groups (6.68\u0026thinsp;\u0026plusmn;\u0026thinsp;3.39, 6.42\u0026thinsp;\u0026plusmn;\u0026thinsp;2.71, and 6.26\u0026thinsp;\u0026plusmn;\u0026thinsp;2.46, respectively), indicating poor quality across all groups. However, no statistically significant differences were observed in PSQI scores among the skeletal groups (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Similarly, the distribution of good and poor sleepers was not significantly different among the Sk-I, Sk-II, and Sk-III groups (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). In addition, there was no significant difference in sleep-related parameters between good and poor sleepers (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eSleep quality is not influenced by sagittal skeletal patterns. Therefore, incorporating sleep quality assessments into orthodontic treatment planning may be beneficial.\u003c/p\u003e","manuscriptTitle":"Evaluation of the Pittsburgh Sleep Quality Index in a Group of Orthodontic Patients With Different Sagittal Skeletal Relationships","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-18 18:21:20","doi":"10.21203/rs.3.rs-8098939/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-12-31T16:56:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"234620949203492355398172367278060432688","date":"2025-12-23T03:04:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-12T14:47:02+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-14T13:18:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-13T08:20:15+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-13T08:19:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Oral Health","date":"2025-11-12T17:55:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-oral-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ohea","sideBox":"Learn more about [BMC Oral Health](http://bmcoralhealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ohea/default.aspx","title":"BMC Oral Health","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7dd4a868-9460-4ade-9b59-31d0498e36b2","owner":[],"postedDate":"December 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-12-18T18:21:20+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-18 18:21:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8098939","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8098939","identity":"rs-8098939","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}