Identification of obstructive sleep apnea in children with obesity: A cluster analysis approach.

Background: Obstructive sleep apnea (OSA) is a heterogeneous disorder with a prevalence of 25%-60% in children with obesity. There is a lack of diagnostic tools to identify those at high risk for OSA.

Method: Children with obesity, aged 8-19 years old, were enrolled into an ongoing multicenter, prospective cohort study related to OSA. We performed k-means cluster analysis to identify clinical variables which could help identify obesity related OSA.

Results: In this study, 118 participants were included in the analysis; 40.7% were diagnosed with OSA, 46.6% were female and the mean (SD) body mass index (BMI) and age were 39.7 (9.6) Kg/m², and 14.4 (2.6) years, respectively. The mean (SD) obstructive apnea-hypopnea index (OAHI) was 11.0 (21.1) events/h. We identified two distinct clusters based on three clustering variables (age, BMI z-score, and neck-height ratio [NHR]). The prevalence of OSA in clusters 1 and 2, were 22.4% and 58.3% (p = 0.001), respectively. Children in cluster 2, in comparison to cluster 1, had higher BMI z-score (4.7 (1.1) versus 3.2 (0.7), p < 0.001), higher NHR (0.3 (0.02) versus 0.2 (0.01), p < 0.001) and were older (15.0 (2.2) versus 13.7 (2.9) years, p = 0.09), respectively. However, there were no significant differences in sex and OSA symptoms between the clusters. The results from hierarchical clustering were similar to k-means analysis suggesting that the resulting OSA clusters were stable to different analysis approaches.

Interpretation: BMI, NHR, and age are easily obtained in a clinical setting and can be utilized to identify children at high risk for OSA.