ABSTRACT
Snoring and obstructive sleep apnoea (OSA) affect a significant percentage of children. Recent studies have suggested that altered craniofacial morphology may contribute to the multifactorial pathophysiology of OSA. This study aims to determine the prevalence of craniofacial abnormalities and malocclusion in children referred for polysomnography due to OSA suspicion. This is a multicentre prevalence study completed across four Canadian sites. Otherwise, healthy children (≥ 4 years old) who were seen at the sleep clinic were recruited. Upon arrival for their hospital‐based overnight sleep recording, a clinical orthodontic assessment and a series of paediatric sleep questionnaires were completed for each participant. Data from 315 children (age 9.37 ± 3.70) revealed significant risk factors associated with the presence of OSA, including male sex, presence of snoring, endomorph body type, and hypertrophic tonsils. The intra‐oral and facial morphologic characteristics were not significantly different between children with (AHI 9.51 ± 10.94) and without (AHI 0.84 ± 0.50) PSG‐verified OSA. Factors such as maxillary constriction/posterior crossbite and a retrognathic mandible showed similar (p > 0.05) prevalence between groups. Hierarchical regression analysis showed no statistically significant facial and dental variables in predicting AHI. In conclusion, a multidisciplinary approach involving dental professionals with expertise in growth and development is crucial for the assessment of possible craniofacial abnormalities in children with OSA. Craniofacial morphology may play a limited role in the pathophysiology of OSA in most children, as no differences in the prevalence of these variables in children with and without OSA were found in this large, multicentre study.
Keywords: children, craniofacial morphology, malocclusion, obstructive sleep apnoea
1. Introduction
Breathing problems during sleep are a recognised chronic disorder affecting both children and adolescents. Approximately 3%–27% of them snore and 1%–10% have obstructive sleep apnoea (OSA) (Bixler et al. 2009; Brunetti et al. 2001; Canadian‐Lung‐Association 2011; Gozal and O'Brien 2004; Lumeng and Chervin 2008; Magnusdottir and Hill 2024; Miano et al. 2010; Public‐Health‐Agency‐of‐Canada 2009; Schutz et al. 2011). Recently, OSA prevalence in children has been estimated at 2%–3% in Canada (Canadian‐Lung‐Association 2011; Public‐Health‐Agency‐of‐Canada 2009).
OSA has a dramatic impact on the health of children and adolescents, including delayed growth, metabolic syndromes, increased cardio‐pulmonary risk, learning disabilities, and behavioural problems (Di Sessa et al. 2022; Gozal and O'Brien 2004; Smith and Amin 2019; Yoshioka et al. 2024). OSA and fragmented sleep are often underdiagnosed in children and youth, especially when their primary complaint is a behavioural problem.
Tonsil and adenoid hypertrophy, as well as obesity, are major risk factors for paediatric OSA. Soft tissue surgery and/or continuous positive airway pressure (CPAP) devices are the treatments of choice but are not suitable for all children and, in some instances, may only partially improve the problem. These incomplete or modest cure rates are perhaps not surprising considering the more recently understood multifactorial nature of OSA (Eckert 2018). While initially proposed for adults with OSA, the concept of different underlying disease endotypes beyond simply a small airway has been extended to the paediatric population (Nicolau et al. 2024; Siriwardhana et al. 2020). Dentofacial morphology has not typically been characterised in prospective clinical trials assessing treatment options in children, and thus the role of anatomy in both OSA aetiology and treatment outcomes has been underexplored.
Historically, it has been the long‐narrow face with a constricted maxilla and retruded mandible of the ‘adenoid facies’ that has been associated with sleep disordered breathing in children. Consequently, orthodontic therapy to address these anatomical differences has been advocated as an alternative treatment option for the management of paediatric OSA. However, this association with altered facial morphology has often been based on small retrospective studies, with subjective reporting of the presence of OSA in patients recruited from dental clinics. Modern assessments from medical settings have either found that the prevalence of malocclusion is not greater than what has been reported for the general population (Pliska et al. 2017), or, as reported in a recent meta‐analysis, with mandibular retrognathia, greater mandibular plane angle and overjet observed in children with OSA (Liu et al. 2023).
Studies from uncontrolled trials have suggested that orthodontic treatments, such as maxillary expansion or mandibular advancement with functional appliances in patients with craniofacial abnormalities, may be effective in improving paediatric snoring and OSA (Guilleminault et al. 2011; Marino et al. 2012; Pirelli et al. 2010, 2004; Villa et al. 2007, 2011). It has been reported that between 15% and 47% of children remain stable or worsen following rapid maxillary expansion, in addition to 57% of children presenting residual OSA (Marino et al. 2012; Villa et al. 2015) suggesting that for many this should not be used as a stand‐alone treatment for OSA but rather as one component of a broader therapeutic strategy. Though the strength of the evidence for widespread adoption of orthodontic therapy in the management of paediatric OSA has been challenged, there is a clear need for further research to better define the relationship between facial form and OSA (Fernández‐Barriales et al. 2022).
Therefore, the objective of this study is to determine the prevalence of craniofacial abnormalities and malocclusion (abnormal bite) in children referred to a hospital‐based sleep clinic for suspicion of OSA. This would then provide insight from the broader clinical setting of children referred to sleep clinics on the proportion of children who may be eligible for and benefit from orthodontic screening and therapy. In addition, this would inform on need for a multidisciplinary approach to paediatric OSA, from suspicion to disease management.
2. Methods
2.1. Study Design and Settings
This is a multicentre prevalence study that was completed across hospital‐based paediatric sleep clinics of four Canadian sites: CHU Sainte Justine (Université de Montréal), BC Children's Hospital (University of British Columbia), Alberta Children's Hospital (University of Calgary) and the Hospital for Sick Children (SickKids) (University of Toronto). The project was approved by the research ethics boards of all four contributing institutions. We have complied with the STROBE protocol on cross‐sectional studies.
2.2. Participants
Children at least 4 years of age who were seen at the participating sleep clinics and scheduled to undergo in‐hospital sleep studies were recruited. Children who had any craniofacial abnormality related to genetic syndromes, who were currently treated with positive airway pressure therapy and who had a history of orthodontic treatment or adeno/tonsillectomy were excluded from the final analysis.
2.3. Procedures
During each child's visit for their sleep test at the hospital, participants were invited to complete the only study visit, which consisted of a clinical dental examination and a brief paediatric sleep questionnaire completed by a parent while waiting (Spruyt and Gozal 2012). The dental assessment, conducted by calibrated dentists, lasted approximately 15 min and included an intra‐oral dental exam and extra‐oral evaluation of facial form.
In‐hospital polysomnography data was used to confirm the diagnosis of sleep apnoea on the basis of AHI. Qualified sleep technicians at each site used a standardised assessment method. The events of sleep and breathing were visually assessed according to the parameters established by the American Academy of Sleep Medicine (Berry et al. 2012). All studies were interpreted by sleep physicians at their respective centres.
2.4. Outcomes
From the dental assessment, the following data of dentofacial morphology was collected by a trained dentist, who was trained on standardised forms: (1) extra‐oral variables (vertical facial type, facial profile, skeletal anterior–posterior classification, subjective breathing mode); (2) intra‐oral variables (overjet, overbite, stage of dentition, maxillary inter‐molar and inter‐canine distance, presence of openbite and crossbite, and dental crowding of at least 4 mm). The Index of Orthodontic Treatment Need (IOTN), a validated assessment of the overall severity of malocclusion, was also scored (Brook and Shaw 1989). Moreover, tonsil size was assessed using the Friedman grading scale. A global score was calculated from the brief paediatric questionnaire of Spruyt and Gozal (2012), where the previously established cutoff value of > 2.72 was used for OSA risk. Based on Question 6 in the questionnaire, children were divided into snorers (snoring three or more nights per week) or non‐snorers (two or less nights per week) (Marcus et al. 2013). From the result of the polysomnography study, children who have an AHI ≥ 2 event/h were considered to have OSA, and children with an AHI ≥ 5 were considered to have moderate to severe OSA (Marcus et al. 2013). Children with an AHI < 2 were considered in the non‐OSA group. All study data were collected and managed using REDCap (Research Electronic Data Capture) tools hosted at the Université de Montréal.
3. Statistical Analyses
Data were presented as mean ± standard deviation or median ± interquartile range for continuous data and as count and percentage for categorical data. Univariate analyses were used to compare all outcome variables between both OSA and non‐OSA groups, where independent t‐tests or ANOVA tests were used for continuous variables and chi‐square tests for categorical variables. For non‐normally distributed continuous variables, the Mann–Whitney U‐test or Kruskal–Wallis test was used. Statistical analyses were done using SPSS 26.0 software.
Hierarchical regression was used to examine the relationship between AHI and craniofacial and dental variables after controlling for children's demographic characteristics (gender, age, and BMI) and questionnaire score. In Step 1, demographic characteristics and questionnaire score were added to the model. Then, in Step 2, we ran a series of models for each of the following variables individually: body type, tongue size, tonsil size, history of mouth breathing, face profile, maxillary and mandibular position, vertical facial type, lower facial height, overbite, overjet, anterior openbite, posterior crossbite, inter‐molar and inter‐canine distance and dental arch shape. The dentofacial variables with associations that were significant (p < 0.05) would be included in a ‘final’ multivariate model.
4. Results
A total of 436 participants were recruited into the study, with 121 excluded from the final analysis due to medical history or missing data (Figure 1). Thus, the analyses were carried out on the available data of 315 participants, which were separated into OSA (n = 160) and non‐OSA (n = 155) groups (Table 1). There was diverse recruitment across Canada, with 111 (35.2%) subjects from the BC Children's Hospital, 114 (36.2%) from the CHU Sainte Justine, 83 (26.3%) from SickKids and 7 (2.2%) from Alberta Children's Hospital, with a similar ratio of OSA/non‐OSA groups in each site (chi‐square test, p = 0.203). Both groups were similar in age, with a mean age of 9.49 ± 3.56 years old for the non‐OSA group and 9.26 ± 3.83 years old for the OSA group. The male/female ratio was different between groups (p < 0.01), with 1.3/1 for the non‐OSA group and 2.5/1 for the OSA group. The BMI percentile and BMI z‐score were not different between groups. However, body type was different between groups (p = 0.033), with more endomorph body type in the OSA group. In the OSA group, all OSA severity categories were represented, with 50.0% (n = 80 of 160) having mild OSA (2 ≤ AHI < 5), 22.5% (n = 36) having moderate OSA (5 ≤ AHI < 10) and 27.5% (n = 44) having severe OSA (10 ≤ AHI). There were 41% of children in the non‐OSA group who were non‐snoring and 23% in the OSA group who were considered non‐snoring.
FIGURE 1.
Study enrolment.
TABLE 1.
Patient demographic and clinical characteristics (n = 315) grouped by AHI and BMI.
| Non‐OSA vs. OSA | Non‐obese vs. Obese | |||||
|---|---|---|---|---|---|---|
| Non‐OSA (n = 155) | OSA (n = 160) | p | Non‐obese (n = 136) | Obese (n = 179) | p | |
| Age (years) | 9.49 ± 3.56 | 9.26 ± 3.83 | 0.578 | 7.98 ± 3.14 | 10.43 ± 3.75 | 0.000** |
| Sex | 0.007** | 0.227 | ||||
| Female | 66 (42.6) | 45 (28.1) | 53 (39.0) | 58 (32.4) | ||
| Male | 89 (57.4) | 115 (71.9) | 83 (61.0) | 121 (67.6) | ||
| BMI | 22.34 ± 8.30 | 24.20 ± 10.29 | 0.079 | 16.12 ± 2.07 | 28.73 ± 9.14 | 0.000** |
| BMI percentile (%) | 74.47 ± 29.58 | 75.17 ± 31.38 | 0.839 | 46.21 ± 26.17 | 96.56 ± 4.08 | 0.000** |
| Questionnaire score | 1.94 ± 0.97 | 2.38 ± 1.01 | 0.000** | 2.09 ± 1.01 | 2.22 ± 1.01 | 0.224 |
| Snoring | 0.000** | 0.788 | ||||
| Present (≥ 3 nights per week) | 80 (58.8) | 112 (77.2) | 83 (67.5) | 109 (69.0) | ||
| Not present (≤ 2 nights per week) | 56 (41.2) | 33 (22.8) | 40 (32.5) | 49 (31.0) | ||
| AHI | 0.84 ± 0.50 | 9.51 ± 10.94 | 0.000** | 3.09 ± 4.24 | 6.89 ± 10.98 | 0.000** |
| ODI | 0.60 ± 1.00 | 2.08 ± 7.50 | 0.000** | 1.00 ± 2.13 | 1.45 ± 4.50 | 0.04* |
| Body type | 0.033* | 0.000** | ||||
| Ectomorph | 27 (17.5) | 18 (11.3) | 37 (27.2) | 8 (4.5) | ||
| Mesomorph | 87 (56.5) | 79 (49.7) | 96 (70.6) | 70 (39.1) | ||
| Endomorph | 40 (26.0) | 62 (39.0) | 3 (2.2) | 99 (55.3) | ||
| Stage of dentition | 0.334 | 0.000** | ||||
| Primary | 23 (14.8) | 34 (21.3) | 38 (27.9) | 19 (10.6) | ||
| Mixed | 80 (51.6) | 77 (48.1) | 77 (56.6) | 80 (44.7) | ||
| Permanent | 52 (33.5) | 49 (30.6) | 21 (15.4) | 80 (44.7) | ||
| Tongue size | 0.217 | 0.000** | ||||
| Normal | 124 (84.9) | 124 (80.0) | 119 (91.5) | 129 (75.4) | ||
| Microglossia (relative) | 1 (0.7) | 0 (0.0) | 1 (0.8) | 0 (0.0) | ||
| Macroglossia (relative) | 21 (14.4) | 31 (20.0) | 10 (7.7) | 42 (24.6) | ||
| Tonsils | 0.019* | 0.076 | ||||
| +1 and +2 | 124 (80.0) | 108 (68.4) | 94 (69.1) | 138 (78.0) | ||
| +3 and +4 | 31 (20.0) | 50 (31.6) | 42 (30.9) | 39 (22.0) | ||
| History of mouth breathing | 0.164 | 0.890 | ||||
| Present | 107 (69.9) | 123 (76.9) | 99 (73.9) | 131 (73.2) | ||
| Not present | 46 (30.1) | 37 (23.1) | 35 (26.1) | 48 (26.8) | ||
| History of oral habits | 0.055 | 0.660 | ||||
| Present | 85 (55.2) | 71 (44.4) | 69 (51.1) | 87 (48.6) | ||
| Not present | 69 (44.8) | 89 (55.6) | 66 (48.9) | 92 (51.4) | ||
Note: OSA was diagnosed by the critical value of AHI > 2.0. Obesity was defined by the critical value of BMI percentile > 85.0%. Continuous variables were expressed as mean ± SD, and compared using independent t‐sample test. Categorical variables were expressed as N (%), and compared using chi‐square test. ODI was not normally distributed, thus was expressed as median ± interquartile range. For this variable, Mann–Whitney U‐test was used.
P < 0.05.
p < 0.01.
In the non‐OSA group, 80.0% had small tonsils (Friedman Grade 1 and 2), and 20.0% had large tonsils (Friedman Grades 3 and 4), while in the OSA group, 68.4% had small tonsils and 31.6% had large tonsils. A chi‐square test was done to assess the relation between Friedman grade and groups, with subjects with OSA being significantly more likely to have larger tonsils (p = 0.019). Self‐reported oral habits were assessed, such as nail biting, lip/cheek biting, bruxism, or thumb/finger sucking. No difference was found between groups.
All intra‐oral and extra‐oral variables assessed from the dental examination, including the presence of open bite and crossbite, overbite, overjet, inter‐canine and inter‐molar distance, presence of dental crowding, facial type, lower facial height, profile and prevalence of mandibular retrognathia, were not significantly different between the OSA and non‐OSA groups (Table 2).
TABLE 2.
Patient facial and dental characteristics (n = 315) grouped by AHI and BMI.
| Non‐OSA vs. OSA | Non‐obese vs. Obese | |||||
|---|---|---|---|---|---|---|
| Non‐OSA (n = 155) | OSA (n = 160) | p | Non‐obese (n = 136) | Obese (n = 179) | p | |
| Overjet (mm) | 3.06 ± 2.06 | 2.85 ± 1.80 | 0.315 | 2.88 ± 1.78 | 3.01 ± 2.04 | 0.584 |
| Overbite (%) | 38.04 ± 33.67 | 45.26 ± 36.75 | 0.071 | 46.06 ± 35.40 | 38.46 ± 35.15 | 0.060 |
| Upper inter‐molar distance (mm) | 37.27 ± 5.74 | 37.11 ± 7.03 | 0.821 | 36.15 ± 6.49 | 37.98 ± 6.28 | 0.013* |
| Upper inter‐canine distance (mm) | 32.03 ± 3.96 | 31.63 ± 4.44 | 0.401 | 30.48 ± 4.15 | 32.84 ± 3.97 | 0.000** |
| Score of IOTN | 3.40 ± 2.25 | 3.42 ± 2.44 | 0.939 | 3.37 ± 2.26 | 3.44 ± 2.42 | 0.820 |
| Facial type | 0.998 | 0.000** | ||||
| Mesocephalic | 108 (69.7) | 111 (69.4) | 92 (67.6) | 127 (70.9) | ||
| Brachycephalic | 24 (15.5) | 25 (15.6) | 13 (9.6) | 36 (20.1) | ||
| Dolichocephalic | 23 (14.8) | 24 (15.0) | 31 (22.8) | 16 (8.9) | ||
| Lower facial height | 0.252 | 0.376 | ||||
| Normal | 106 (68.4) | 106 (66.3) | 96 (70.6) | 116 (64.8) | ||
| Increased | 38 (24.5) | 34 (21.3) | 30 (22.1) | 42 (23.5) | ||
| Decreased | 11 (7.1) | 20 (12.5) | 10 (7.4) | 21 (11.7) | ||
| Face profile | 0.177 | 0.057 | ||||
| Straight | 70 (45.2) | 88 (55.0) | 60 (44.1) | 98 (54.7) | ||
| Concave | 10 (6.5) | 11 (6.9) | 7 (5.1) | 14 (7.8) | ||
| Convex | 75 (48.4) | 61 (38.1) | 69 (50.7) | 67 (37.4) | ||
| Maxillary profile | 0.617 | 0.995 | ||||
| Retrognathic | 15 (9.7) | 11 (6.9) | 11 (8.1) | 15 (8.4) | ||
| Orthognathic | 133 (85.8) | 140 (87.5) | 118 (86.8) | 155 (86.8) | ||
| Prognathic | 7 (4.5) | 9 (5.6) | 7 (5.1) | 9 (5.0) | ||
| Mandibular profile | 0.828 | 0.088 | ||||
| Retrognathic | 68 (43.9) | 66 (41.5) | 66 (48.9) | 68 (38.0) | ||
| Orthognathic | 82 (52.9) | 89 (56.0) | 67 (49.6) | 104 (58.1) | ||
| Prognathic | 5 (3.2) | 4 (2.5) | 2 (1.5) | 7 (3.9) | ||
| Anterior open‐bite | 0.930 | 0.063 | ||||
| Present | 9 (6.2) | 9 (5.9) | 4 (3.1) | 14 (8.3) | ||
| Not present | 137 (93.8) | 143 (94.1) | 125 (96.9) | 155 (91.7) | ||
| Posterior crossbite | 0.193 | 0.312 | ||||
| Present | 20 (12.9) | 29 (18.2) | 18 (13.2) | 31 (17.3) | ||
| Not present | 135 (87.1) | 130 (81.8) | 118 (86.8) | 147 (82.1) | ||
| Dental crowding | 0.378 | 0.113 | ||||
| Present | 106 (68.4) | 112 (70.0) | 95 (69.9) | 123 (68.7) | ||
| Not present | 49 (31.6) | 48 (30.0) | 41 (30.1) | 56 (31.3) | ||
| Upper arch shape | 0.858 | 0.766 | ||||
| U‐Shape | 132 (85.7) | 136 (85.0) | 117 (86.0) | 151 (84.8) | ||
| V‐Shape | 22 (14.3) | 24 (15.0) | 19 (14.0) | 27 (15.2) | ||
| Lower arch shape | 0.111 | 0.100 | ||||
| U‐Shape | 151 (97.4) | 149 (93.7) | 126 (92.6) | 174 (97.2) | ||
| V‐Shape | 4 (2.6) | 10 (6.3) | 9 (6.6) | 5 (2.8) | ||
Note: OSA was diagnosed by the critical value of AHI > 2.0. Obesity was defined by the critical value of BMI percentile > 85.0%. Continuous variables were expressed as mean ± SD, and compared using independent t‐sample test. Categorical variables were expressed as N (%), and compared using chi‐square test.
Abbreviation: IOTN, Index of Orthodontic Treatment Need.
P < 0.05.
P < 0.01.
When children were grouped based on the presence of overweight and obesity (BMI percentile ≥ 85%), several differences in anthropometric dentofacial characteristics emerged (Tables 1 and 2). The obese children were, on average, almost 2.5 years older (10.43 ± 3.75 vs. 7.98 ± 3.14), and as a group had higher OSA severity (6.89 ± 10.98 vs. 3.09 ± 4.24 AHI). As would be expected by age and BMI, the obese subjects also had a greater prevalence of the endomorph body type and were more likely to be in the permanent dentition. Dentally, the obese subjects were observed to have greater inter‐canine and inter‐molar distances and were significantly less likely to present with a dolichocephalic facial type.
Differences between non‐OSA subjects and those with either mild or moderate/severe OSA were also assessed (Table 3). Subjects with moderate/severe OSA were observed to have significantly higher BMI percentile (82.38 ± 27.30 vs. 67.95 ± 33.63) and a higher prevalence of bigger tonsil size than those with mild OSA. Moderate to severe OSA patients were more likely to present with frequent snoring. The moderate/severe group was also found to have a higher prevalence of both a straight profile and relative macroglossia.
TABLE 3.
Patient demographic, clinical and dental characteristics (n = 315) grouped by OSA severity.
| Non OSA (n = 155) | Mild OSA (n = 80) | Moderate to severe OSA (n = 80) | p | Post hoc p | |||
|---|---|---|---|---|---|---|---|
| 1–2 | 1–3 | 2–3 | |||||
| Age (years) | 9.49 ± 3.56 | 9.04 ± 3.63 | 9.48 ± 4.04 | 0.643 | |||
| Sex | 0.027** | ||||||
| Female | 66 (42.6) | 23 (28.8) | 22 (27.5) | ||||
| Male | 89 (54.7) | 57 (71.3) | 58 (72.5) | ||||
| BMI | 22.34 ± 8.30 | 21.68 ± 8.49 | 26.71 ± 11.32 | 0.001** | 0.600 | 0.001** | 0.001** |
| BMI percentile (%) | 74.47 ± 29.58 | 67.95 ± 33.63 | 82.38 ± 27.30 | 0.011* | 0.117 | 0.057 | 0.003** |
| Questionnaire score | 1.94 ± 0.97 | 2.16 ± 0.98 | 2.60 ± 0.99 | 0.000** | 0.109 | 0.000** | 0.006** |
| Snoring | 0.000** | ||||||
| Present (≥ 3 nights per week) | 80 (58.8) | 50 (71.4) | 62 (82.7) | ||||
| Not present (≤ 2 nights per week) | 56 (41.2) | 20 (28.6) | 13 (17.3) | ||||
| AHI | 0.85 ± 0.50 | 3.15 ± 0.88 | 15.87 ± 12.58 | 0.000** | 0.009** | 0.000** | 0.000** |
| ODI | 0.60 ± 1.00 | 1.75 ± 2.00 | 7.2 ± 14.20 | 0.000** | 0.000** | 0.000** | 0.000** |
| Body type | 0.003** | ||||||
| Ectomorph | 27 (17.5) | 11 (13.9) | 7 (8.8) | ||||
| Mesomorph | 87 (56.5) | 46 (58.2) | 33 (41.3) | ||||
| Endomorph | 40 (26.0) | 22 (27.8) | 40 (50.0) | ||||
| Stage of dentition | 0.642 | ||||||
| Primary | 23 (14.8) | 18 (22.5) | 16 (20.0) | ||||
| Mixed | 80 (51.6) | 39 (48.18) | 38 (47.5) | ||||
| Permanent | 52 (33.5) | 23 (28.8) | 26 (32.5) | ||||
| Tongue size | 0.036* | ||||||
| Normal | 124 (84.9) | 69 (88.5) | 55 (71.4) | ||||
| Microglossia (relative) | 1 (0.7) | 0 (0.0) | 0 (0.0) | ||||
| Macroglossia (relative) | 21 (14.4) | 9 (11.5) | 22 (28.6) | ||||
| Tonsils | 0.061 | ||||||
| +1 and +2 | 124 (80.0) | 54 (67.5) | 54 (69.2) | ||||
| +3 and +4 | 31 (20.0) | 26 (32.5) | 24 (30.8) | ||||
| History of mouth breathing | 0.374 | ||||||
| Present | 107 (69.7) | 62 (77.5) | 61 (76.3) | ||||
| Not present | 46 (30.3) | 18 (22.5) | 19 (23.8) | ||||
| History of oral habits | 0.157 | ||||||
| Present | 85 (55.2) | 36 (45.0) | 35 (43.8) | ||||
| Not present | 69 (44.8) | 44 (55.0) | 45 (56.3) | ||||
| Overjet (mm) | 3.06 ± 2.06 | 2.99 ± 1.71 | 2.70 ± 1.89 | 0.394 | |||
| Overbite (%) | 38.04 ± 33.67 | 45.84 ± 34.08 | 44.70 ± 39.42 | 0.194 | |||
| Upper inter‐molar distance (mm) | 37.27 ± 5.74 | 36.82 ± 7.56 | 37.40 ± 6.50 | 0.830 | |||
| Upper inter‐canine distance (mm) | 32.03 ± 3.96 | 31.34 ± 4.59 | 31.93 ± 4.29 | 0.472 | |||
| Score of IOTN | 3.40 ± 2.25 | 3.31 ± 2.38 | 3.53 ± 2.51 | 0.836 | |||
| Facial type | 0.777 | ||||||
| Mesocephalic | 108 (69.7) | 53 (66.3) | 58 (72.5) | ||||
| Brachycephalic | 24 (15.5) | 12 (15.0) | 13 (16.3) | ||||
| Dolichocephalic | 23 (14.8) | 15 (18.8) | 9 (11.3) | ||||
| Lower facial height | 0.436 | ||||||
| Normal | 106 (68.4) | 56 (70.0) | 50 (62.5) | ||||
| Increased | 38 (24.5) | 15 (18.8) | 19 (23.8) | ||||
| Decreased | 11 (7.1) | 9 (11.3) | 11 (13.8) | ||||
| Face profile | 0.027* | ||||||
| Straight | 70 (45.2) | 37 (46.3) | 51 (63.8) | ||||
| Concave | 10 (6.5) | 4 (5.0) | 7 (8.8) | ||||
| Convex | 75 (48.4) | 39 (48.8) | 22 (27.5) | ||||
| Maxillary profile | 0.879 | ||||||
| Retrognathic | 15 (9.7) | 6 (7.5) | 5 (6.3) | ||||
| Orthognathic | 133 (85.8) | 69 (86.3) | 71 (88.8) | ||||
| Prognathic | 7 (4.5) | 5 (6.3) | 4 (5.0) | ||||
| Mandibular profile | 0.416 | ||||||
| Retrognathic | 68 (43.9) | 39 (48.8) | 27 (34.2) | ||||
| Orthognathic | 82 (52.9) | 39 (48.8) | 50 (63.3) | ||||
| Prognathic | 5 (3.2) | 2 (2.5) | 2 (2.5) | ||||
| Anterior open‐bite | 0.531 | ||||||
| Present | 9 (6.2) | 6 (8.1) | 3 (3.8) | ||||
| Not present | 137 (93.8) | 68 (91.9) | 75 (96.2) | ||||
| Posterior crossbite | 0.354 | ||||||
| Present | 20 (12.9) | 16 (20.0) | 13 (16.5) | ||||
| Not present | 135 (87.1) | 64 (80.0) | 66 (83.5) | ||||
| Dental crowding | 0.717 | ||||||
| Present | 106 (68.4) | 56 (70.0) | 56 (70.0) | ||||
| Not present | 49 (31.6) | 24 (30.0) | 24 (30.0) | ||||
| Upper arch shape | 0.400 | ||||||
| U‐Shape | 132 (85.7) | 65 (81.3) | 71 (88.8) | ||||
| V‐Shape | 22 (14.3) | 15 (18.8) | 9 (11.3) | ||||
| Lower arch shape | 0.215 | ||||||
| U‐Shape | 151 (97.4) | 73 (92.4) | 76 (95.0) | ||||
| V‐Shape | 4 (2.6) | 6 (7.6) | 4 (5.0) | ||||
Note: Mild OSA was diagnosed by the critical value of AHI > 2.0. Moderate and severe OSA was diagnosed by the critical value of AHI > 5.0. Continuous variables were expressed as Mean ± SD, and compared using ANOVA and post hoc (LSD) test. Categorical variables were expressed as N (%), and compared using chi‐square test. ODI was not normally distributed, thus was expressed as median ± interquartile range. For this variable, independent sample Kruskal–Wallis test was used.
P < 0.05.
P < 0.01.
The results of hierarchical regression analysis predicting AHI are shown in Table 4. The result of Step 1 indicated that the variance in AHI accounted for (R 2) by demographic variables, including age, gender, BMI and questionnaire score, was equal to 0.176 (p < 0.001). Seventeen selected facial and dental variables were added to a series of models in Step 2. None of these variables contributed a statistically significant increase in explaining AHI variance (ΔR 2) compared to Step 1. Therefore, the final equation of regression analysis did not include any dentofacial characteristics.
TABLE 4.
Hierarchical regression analysis, with demographic variables and questionnaire score in Step 1 and each of the orthodontic variables individually in Step 2, used to predict AHI (n = 301).
| Variables in regression | Significant predictor | Model R 2 | ΔR 2 | p | |
|---|---|---|---|---|---|
| (Standardised coefficient (beta), p) | |||||
| Step 1 | Age, Gender, BMI, Questionnaire Score | Age (−0.160, 0.024) | 0.176 (P < 0.001) | / | / |
| Gender (0.117, 0.028) | |||||
| BMI (0.333, < 0.001) | |||||
| Questionnaire Score (0.271, < 0.001) | |||||
| Step 2 | |||||
| Model 1 | Age, Gender, BMI, Questionnaire Score, Body type | Age (−0.144, 0.044) | 0.189 | 0.013 | 0.053 |
| Gender (0.118, 0.026) | |||||
| BMI (0.223, 0.014) | |||||
| Questionnaire Score (0.274, < 0.001) | |||||
| Model 2 | Age, Gender, BMI, Questionnaire Score, Tonsil size | Age (−0.156, 0.030) | 0.176 | 0.000 | 0.726 |
| Gender (0.120, 0.027) | |||||
| BMI (0.334, < 0.000) | |||||
| Questionnaire Score (0.266, < 0.001) | |||||
| Model 3 | Age, Gender, BMI, Questionnaire Score, Mouth breathing | Age (−0.159, 0.026) | 0.177 | 0.001 | 0.565 |
| Gender (0.117, 0.029) | |||||
| BMI (0.335, < 0.001) | |||||
| Questionnaire Score (0.262, < 0.001) | |||||
| Model 4 | Age, Gender, BMI, Questionnaire Score, Tongue size | Age (−0.164, 0.021) | 0.196 | 0.006 | 0.147 |
| Gender (0.118, 0.029) | |||||
| BMI (0.322, < 0.011) | |||||
| Questionnaire Score (0.282, < 0.001) | |||||
| Model 5 | Age, Gender, BMI, Questionnaire Score, Face profile | Age (−0.150, 0.035) | 0.184 | 0.008 | 0.090 |
| Gender (0.115, 0.031) | |||||
| BMI (0.314, < 0.001) | |||||
| Questionnaire Score (0.270, < 0.001) | |||||
| Model 6 | Age, Gender, BMI, Questionnaire Score, Maxilla sagittal position | Age (−0.159, 0.025) | 0.178 | 0.002 | 0.465 |
| Gender (0.119, 0.026) | |||||
| BMI (0.337, < 0.001) | |||||
| Questionnaire Score (0.271, < 0.001) | |||||
| Model 7 | Age, Gender, BMI, Questionnaire Score, Mandible sagittal position | Age (−0.160, 0.025) | 0.177 | 0.001 | 0.935 |
| Gender (0.116, 0.030) | |||||
| BMI (0.334, < 0.001) | |||||
| Questionnaire Score (0.271, < 0.001) | |||||
| Model 8 | Age, Gender, BMI, Questionnaire Score, Vertical facial type | Age (−0.161, 0.025) | 0.176 | 0.000 | 0.892 |
| Gender (0.118, 0.028) | |||||
| BMI (0.334, < 0.001) | |||||
| Questionnaire Score (0.271, < 0.001) | |||||
| Model 9 | Age, Gender, BMI, Questionnaire Score, Lower facial height | Age (−0.158, 0.026) | 0.179 | 0.003 | 0.322 |
| Gender (0.121, 0.024) | |||||
| BMI (0.323, < 0.001) | |||||
| Questionnaire Score (0.268, < 0.001) | |||||
| Model 10 | Age, Gender, BMI, Questionnaire Score, Overjet | Age (−0.153, 0.035) | 0.178 | 0.002 | 0.735 |
| Gender (0.119, 0.026) | |||||
| BMI (0.327, < 0.001) | |||||
| Questionnaire Score (0.273, < 0.001) | |||||
| Model 11 | Age, Gender, BMI, Questionnaire Score, Overbite | Age (−0.161, 0.024) | 0.178 | 0.002 | 0.601 |
| Gender (0.118, 0.028) | |||||
| BMI (0.338, < 0.001) | |||||
| Questionnaire Score (0.271, < 0.001) | |||||
| Model 12 | Age, Gender, BMI, Questionnaire Score, Anterior openbite | Age (−0.169, 0.019) | 0.190 | 0.014 | 0.164 |
| Gender (0.115, 0.036) | |||||
| BMI (0.343, < 0.001) | |||||
| Questionnaire Score (0.287, < 0.001) | |||||
| Model 13 | Age, Gender, BMI, Questionnaire Score, Posterior crossbite | Age (−0.158, 0.026) | 0.179 | 0.003 | 0.348 |
| Gender (0.117, 0.027) | |||||
| BMI (0.340, < 0.001) | |||||
| Questionnaire Score (0.272, < 0.001) | |||||
| Model 14 | Age, Gender, BMI, Questionnaire Score, Intermolar distance | Age (−0.177, 0.019) | 0.178 | 0.002 | 0.575 |
| Gender (0.111, 0.040) | |||||
| BMI (0.332, < 0.001) | |||||
| Questionnaire Score (0.273, < 0.001) | |||||
| Model 15 | Age, Gender, BMI, Questionnaire Score, Intercanine distance | Age (−0.190, 0.016) | 0.178 | 0.002 | 0.400 |
| BMI (0.331, < 0.001) | |||||
| Questionnaire Score (0.275, < 0.001) | |||||
| Model 16 | Age, Gender, BMI, Questionnaire Score, Upper arch shape | Age (−0.155, 0.029) | 0.185 | 0.009 | 0.071 |
| Gender (0.115, 0.030) | |||||
| BMI (0.339, < 0.001) | |||||
| Questionnaire Score (0.276, < 0.001) | |||||
| Model 17 | Age, Gender, BMI, Questionnaire Score, Lower arch shape | Age (−0.160, 0.025) | 0.176 | 0.000 | 0.998 |
| Gender (0.118, 0.027) | |||||
| BMI (0.332, < 0.001) | |||||
| Questionnaire Score (0.272, < 0.001) |
5. Discussion
In this large multicentre study, there were no identifying dental or craniofacial morphological risk factors for OSA observed in a population of children who underwent polysomnography at a hospital‐based sleep centre. The presence of dentofacial characteristics typically associated with sleep‐disordered breathing, such as anterior open bite and maxillary constriction, was not statistically significant between children objectively diagnosed with or without OSA.
The pathophysiology of OSA is complex and involves a number of interactive factors that either reduce the structural size of the airway or increase its susceptibility to collapse. Adenotonsillar hypertrophy and obesity are well‐characterised risk factors for OSA in children; however, neuromuscular deficiencies, altered ventilatory control (Bokov et al. 2022) and systemic inflammation (Gaines et al. 2017) have also been recently implicated in the aetiology of the disease. It has been speculated and assumed that deficiencies in dentofacial anatomy, such as mandibular retroposition or retrognathia (Xu et al. 2023; Yuen et al. 2023), also contribute to decreased airway size, but the exact degree to which this occurs in the non‐syndromic paediatric population is unclear. In an effort to identify paediatric phenotypes of OSA, a recent study did not find distinct phenotypes based on soft tissue facial nor on craniofacial features alone; rather, their affects are modulated by other clinical features such as age and obesity (Fernandes Fagundes et al. 2023). It should be noted that most children diagnosed with OSA in the present study did not present with any notable morphologic differences in dentofacial anatomy.
Based on the CHAT and PAT studies, children were classified as snorers and non‐snorers, based on the frequency of nights when the children do snore. It is important to understand that 23% of children with OSA did not snore and could have been dismissed from sleep clinics and not received proper treatment. In the non‐OSA group, there were 41% of children without snore, which allows us to state that this group could not be classified as primary snorers or sleep‐disordered breathing.
The association between dentofacial morphology and OSA has often been based on retrospective studies, with small sample sizes or subjective assessments of OSA. More recently, systematic reviews and meta‐analyses of the cephalometric measurements or dental characteristics of children with PSG‐diagnosed OSA have failed to find a strong relationship between craniofacial morphology and the disease. The most frequently reported cephalometric differences between children with OSA and healthy controls are in the measures of mandibular retrusion (SNB°) and a downward rotated chin (mandibular plane angle). While reported as statistically significant, these differences are in the order of only a few degrees and relatively small when compared to the ranges and large standard deviations of these measures observed in the general population (Fagundes et al. 2022). Similarly, smaller intermolar widths (approximately 1– 2 mm) may have little clinical relevance (Liu et al. 2023), and lack discriminative value as a screening tool, especially as no differences are noted between different degrees of OSA severity (Flores‐Mir 2016).
The classic phenotype of ‘adenoid facies’, with an increased lower face height, retrusive mandible, and narrow maxilla, has been associated with nasal obstruction and sleep‐disordered breathing in children. This is likely an oversimplification and overestimation of the relationship. The often‐quoted works of Woodside et al. (1991) have documented changes in the direction of facial growth following surgical removal of adenoids; however, it is frequently overlooked that this change occurred in only roughly half of the original sample. When changes did occur, they were small and with wide amounts of individual variation, leading to the inference that changes in facial growth as a response to nasopharyngeal obstruction may only actually occur in a subset of affected patients. It may be that there is a subset of children with OSA who will have a significant alteration to their facial form; however, most children with OSA will appear within normal limits.
Craniofacial growth is predominantly influenced by genetic inheritance (Löfstrand‐Tideström and Hultcrantz 2010) and a smaller maxilla and/or mandible may predispose children to OSA. Although natural growth can resolve snoring and OSA in some children, others are probably more vulnerable to OSA (Li et al. 2013; Marcus et al. 1998). From the Penn State Child Cohort, an 8‐year longitudinal study showed that prepubertal OSA resolved with growth in 52.9% of individuals as the child transitioned into adolescence (Bixler et al. 2016). Although none of these studies on the natural history of snoring and OSA assessed the craniofacial morphology nor the non‐anatomical risk factors, the risk factors for those who are more vulnerable to OSA are to be male, obese and have soft tissue hypertrophy (Bixler et al. 2016; Li et al. 2013; Marcus et al. 1998) factors which confirm the current study findings with little impact of craniofacial morphology. Down syndrome and Pierre Robin Sequence are some of the craniofacial syndromes associated with OSA. This association can be attributed to neuromotor deficits that impair the ability to maintain a patent upper airway and also due to relatively large and obvious alterations in craniofacial morphology (Alsaeed et al. 2023). Children with neurodevelopmental disorders have well‐known neuromuscular abnormalities. In these populations, there is indeed a high prevalence of malocclusion, but to believe the craniofacial alone is the cause of OSA and healthy children with similar but less prominent characteristics is often incorrect.
In a similar setting of a paediatric hospital‐based sleep clinic, an Italian study that screened 260 OSA patients who underwent polysomnography only found 35 (13.46%) children who were eligible for orthodontic treatment due to a narrow high arch palate (Villa et al. 2007). In a more recent study that assessed 279 children with suspected OSA who underwent a sleep study at the paediatric hospital‐based sleep clinic, 31% had a narrow palate (Villa et al. 2013). This present study observed a posterior crossbite in 18.2% of children with OSA and 12.9% of children without OSA, a non‐significant difference. We may conclude that approximately 1 in 5 children with OSA could be candidates for orthodontic treatment with maxillary expansion. This treatment has been shown to benefit some (Guilleminault et al. 2011; Marino et al. 2012; Pirelli et al. 2010, 2004; Villa et al. 2007, 2011) but there is a sub‐group of non‐responders comprising 15%–46.7% who do not improve their AHI following maxillary expansion (Marino et al. 2012; Villa et al. 2015). Moreover, a study reported that 57.5% of maxillary expansion‐treated children had residual OSA (Villa et al. 2015), and the data available on the effects of maxillary expansion on paediatric OSA are severely limited, with only one study comparing expansion to watchful waiting, which found no difference between groups (Fernández‐Barriales et al. 2022).
This study had a few limitations; the clinical assessment was partly subjective. To standardise these measurements, training cases were created, and all dentists under orthodontic training were instructed and calibrated based on the measurements. Also, there is a potential selection bias, which means that the results cannot be completely applicable to a general population, especially for the non‐OSA group. Indeed, participants were recruited from hospital‐based paediatric sleep clinics across Canada and were not compared to a control sample from the general population. However, the main objective of the study was to assess a population selected from paediatric sleep centres. In our study, we used an AHI > 2 to identify OSA. The AASM recommends the use of polysomnography, and despite its limitations, there is a need for careful diagnosis and patient assessment to avoid overtreatment of OSA. It brings to discussion the importance of identifying other possible factors which could impact a child's sleep. Recent literature focuses on the amount of sleep required in children and adolescents. The AASM has developed a consensus statement on the amount of sleep, and they concluded that sleeping the number of recommended hours on a regular basis is associated with better health outcomes, including improved attention, behaviour, learning, memory, emotional regulation, quality of life, and mental and physical health (Paruthi et al. 2016). Studies on treatment for snoring and mild OSA should always have a watchful waiting group, as well as an assessment of sleep hours to assess possible confounders of improved sleep.
This is the largest study to include patients evaluated by a dentist in a sleep clinic with full polysomnography. This current cross‐sectional study could not identify craniofacial differences between children with or without OSA, questioning the efficacy and need for orthodontic treatment for most children with OSA.
6. Conclusion
Although craniofacial morphology may play a limited role in the pathophysiology of OSA, our study could not find a difference in the prevalence of these variables between OSA and non‐OSA children. Future multidisciplinary studies involving dental professionals with expertise in growth and development are required to understand the role of mild to severe craniofacial abnormalities in the pathophysiology of OSA and also on which children should be referred for orthodontic treatment.
Author Contributions
Nelly Huynh: conceptualization, investigation, funding acquisition, writing – original draft, methodology, validation, writing – review and editing, project administration, formal analysis. Jingjing Zhang: writing – original draft, writing – review and editing, formal analysis. Benjamin Pliska: writing – review and editing, supervision, validation. Reshma Amin: conceptualization, writing – review and editing, investigation, supervision. Indra Narang: conceptualization, writing – review and editing, investigation, supervision. Neil Chadha: writing – review and editing, methodology. Marie‐Claude Cholette: investigation, methodology, writing – review and editing, data curation. Val Kirk: supervision, writing – review and editing, methodology. Andrée Montpetit: methodology, writing – review and editing, supervision. Kevin Vezina: methodology, writing – review and editing, supervision. Sheila Jacob: methodology, writing – review and editing, supervision. Sophie Laberge: methodology, writing – review and editing, supervision. Mona Hamoda: data curation, writing – review and editing, investigation. Fernanda Almeida: conceptualization, investigation, funding acquisition, writing – original draft, methodology, validation, writing – review and editing, formal analysis, project administration, supervision, resources.
Conflicts of Interest
The authors declare no conflicts of interest.
Acknowledgements
We would like to express our deep gratitude and appreciation to all individuals and organisations who have contributed to the successful completion of this study. They include but are not limited to the following: (1) participants and their families for their time and interest; and (2) healthcare professionals involved in this study for their time and expertise, including the respiratory technologists (Sylvie Laporte) and the orthodontics residents (Jeremie Abikhezer, Julia Cohen‐Lévy, Mathieu Laramée, Evan Ayers and Kevin Lee).
Huynh, N. , Zhang J., Pliska B., et al. 2025. “Prevalence of Altered Craniofacial Morphology in Children With OSA .” Journal of Sleep Research 34, no. 5: e70060. 10.1111/jsr.70060.
Funding: This work was supported by Canadian Institutes of Health Research (NI14‐012).
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.