Mouth Breathing and Its Impact on Sleep Breathing Disorders in Children: A Cross-Sectional Study in Bandung, Indonesia
Bibliographic record
Abstract
Risti Saptarini Primarti,* Aliannisya Fatma,* Claudia Nur Rizky Jayanti,* Iwan Ahmad Musnamirwan,* Arlette Suzy Setiawan* Department of Pediatric Dentistry, Faculty of Dentistry, Universitas Padjadjaran, Bandung, Indonesia*These authors contributed equally to this workCorrespondence: Risti Saptarini Primarti, Department of Pediatric Dentistry, Faculty of Dentistry, Universitas Padjadjaran, Jl. Sekeloa No. 1, Bandung, West Java, Indonesia, Email risti.saptarini@unpad.ac.idPurpose: Mouth breathing is an associated or characteristic feature of sleep-disordered breathing (SDB), not a direct cause. This study aims to investigate whether mouth-breathing children in Indonesia have a higher risk of SDB, as assessed by the Pediatric Sleep Questionnaire (PSQ) questionnaire.Patients and Methods: A cross-sectional study was conducted in three public elementary schools in Bandung (SDN 001 Merdeka, SDN 062 Ciujung, and SDN 054 Tikukur), involving 343 children aged 8– 9 years (193 boys, 150 girls). Clinical examinations were performed to identify mouth breathing habits, followed by administration of the PSQ questionnaire completed by parents. Prior to questionnaire completion, parents received standardized guidance via standardized online briefing sessions.Results: Mouth breathing was observed in 95 children (27.7%). PSQ scores were significantly higher in mouth breathers compared to non-mouth breathers (mean: 25.45% vs 7.93%; median: 19.05% vs 4.54%; range: 4.54– 58.82 vs 0.0– 45.46; p < 0.001). Furthermore, 41.1% of mouth-breathing children were identified as having SDB, in contrast to 9.7% of non-mouth breathers. The relative risk (RR) for SDB in mouth breathers was 4.24 (95% CI: 2.70– 6.65; p < 0.001).Conclusion: Mouth breathing in school-aged children is significantly associated with a higher risk of developing sleep-disordered breathing. These findings highlight the importance of early screening and timely intervention to prevent adverse health outcomes linked to SDB.Keywords: mouth breathing, sleep-disordered breathing, children, pediatric sleep questionnaire
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".