What question did this study set out to answer?

The study aimed to estimate the prevalence of sleep-disordered breathing risk in children and identify associated craniofacial and occlusal patterns.

April 19, 2026Open Access

Craniofacial and occlusal phenotypes associated with questionnaire-defined risk of sleep-disordered breathing in children: a cross-sectional study

Puntos clave

The study aimed to estimate the prevalence of sleep-disordered breathing risk in children and identify associated craniofacial and occlusal patterns.
Conducted a cross-sectional study in Shanghai, China
Utilized randomized cluster sampling among children aged 3–11 years
Performed clinical examinations for craniofacial morphology and dental occlusion
Collected data via PSQ-22 and OSA-18 questionnaires
Applied a two-step cluster analysis to classify children into subgroups
Identified 14.78% of children as screen-positive for SDB risk
Discovered three distinct clusters of phenotypic profiles for preschool and school-age children
High-risk profiles included specific facial features and medical histories
Significant differences in questionnaire scores and positivity rates across clusters

Resumen

The prevalence of sleep-disordered breathing (SDB) among urban children aged 3 to 11 years remains insufficiently characterized. In addition, population-based screening lacks well-defined risk profiles, particularly in East Asian populations. This study aimed to estimate the prevalence of questionnaire-defined risk of SDB across pediatric age groups and to identify associated craniofacial and occlusal phenotypic patterns. A cross-sectional study was conducted in Shanghai, China, using a randomized cluster sampling approach among children aged 3–11 years. Clinical examinations by dental professionals assessed craniofacial morphology, dental occlusion, and tonsillar size. Additional data were collected on sociodemographic characteristics, medical history, and parent-reported responses to the PSQ-22 and OSA-18 sleep questionnaires. A two-step cluster analysis was performed to automatically classify participants into subgroups based on shared clinical and demographic features. A total of 1,624 children from 31 schools were included in the analysis, with 14.78% identified as screen-positive for SDB risk. Three distinct clusters were identified for both preschool and school-age children, based on combinations of demographic variables, craniofacial features, dental occlusion, and tonsil size. Significant differences in questionnaire scores and positivity rates were observed across clusters. Key high-risk phenotypic profiles included: (1) preschool children with convex facial profiles, distal occlusion, increased overbite, and increased overjet; and (2) school-age children with relevant medical histories (adenotonsillar hypertrophy, chronic rhinitis), pronounced dental crowding, straight or convex profiles, Angle Class II/III molar relationship, increased overbite, and increased overjet. Using cluster analysis of craniofacial and occlusal characteristics, this study identified age-specific phenotypic profiles associated with questionnaire-defined risk of sleep-disordered breathing (SDB) in children. These results highlight the potential utility of phenotype-based screening approaches in epidemiological settings and may aid in the early identification of children at increased risk.

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