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Risk factors for obstructive sleep apnoea in obese children: a systematic review and meta-analysis
Catharina Tao1, Mary Fortune2, Emma A Webb3
1Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, United Kingdom.
Paediatric Respiratory Reviews
|January 9, 2026
Summary
Obstructive sleep apnoea (OSA) in obese children is multifactorial, linked to higher BMI, neck/waist circumference, and adenotonsillar hypertrophy. Early identification of these risk factors is crucial for effective intervention.
Area of Science:
- Pediatric Pulmonology
- Sleep Medicine
- Obesity Research
Background:
- Obstructive sleep apnoea (OSA) is common in obese children, contributing to significant long-term health issues.
- Identifying risk factors for OSA in this population is critical for early diagnosis and management.
Purpose of the Study:
- To systematically review and meta-analyze risk factors for obstructive sleep apnoea (OSA) in overweight and obese children aged 0-18.
- To synthesize evidence on the association between various factors and OSA prevalence in pediatric obesity.
Main Methods:
- Systematic review and meta-analysis of 47 studies.
- Searched PubMed and Embase databases.
- Applied random-effects models to analyze risk factors including adiposity, adenotonsillar hypertrophy, sex, ethnicity, and airway neuromuscular tone.
Main Results:
- Children with OSA exhibited higher BMI z-scores, neck circumference, and waist circumference compared to obese children without OSA.
- Adenotonsillar hypertrophy and male sex were significantly associated with increased odds of OSA.
- Preliminary evidence suggests airway neuromuscular tone and non-Caucasian ethnicity as potential risk factors, requiring further investigation.
Conclusions:
- Obstructive sleep apnoea in obese children is a complex condition influenced by multiple factors.
- Comprehensive assessment considering diverse risk factors can enhance screening accuracy.
- Targeted interventions for this high-risk pediatric population can be guided by a multifactorial approach.
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