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

Abstract

AbstractBackgroundObstructive 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.MethodChildren 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.ResultsIn 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.InterpretationBMI, NHR, and age are easily obtained in a clinical setting and can be utilized to identify children at high risk for OSA.