Modeling the relation between obesity and sleep parameters in children referred for dietary weight reduction intervention.

ABSTRACT

OBJECTIVES: Cross-sectional and longitudinal studies have demonstrated that short sleep periods increase the likelihood of obesity in children. This study was designed to identify other less-clearly defined sleep and behavioral patterns associated with changes in body mass index (BMI) in obese children referred for interventions. METHODS: We retrospectively reviewed the clinic records of children with obesity and children at risk for developing obesity who were referred for counseling and weight loss. Information on sleep habits, pediatric quality of life, pediatric sleep questionnaire (PSQ), and the pediatric daytime sleepiness scale were analyzed, and children were distributed into three behavior groups using cluster analysis. RESULTS: Our sample contained 48 girls and 29 boys with an age range of 2.7 to 16.8 years. The mean BMI was 33.08 ± 7.37 kg/m(2), and mean sleep duration was 9.09 ± 1.09 hours. Multivariate analysis revealed a significant interaction between sleep duration and age when the child was older than 12 years. A 1-hour increase in sleep in older children was associated with a decrease in BMI of 1.263 kg/m(2). Higher (more abnormal) pediatric quality-of-life school scores, higher PSQ1 and PSQ2 scores, and higher pediatric daytime sleepiness scale scores were associated with an increased BMI in univariate analyses but not in the multivariate analysis using the behavior group as an independent predictor. Children who shared a bedroom had a lower BMI in univariate analysis but not in the multivariate analysis. CONCLUSIONS: Longer sleep periods are associated with a decreased BMI, even in children who already meet the criteria for obesity. These children have poor-quality sleep, diurnal behavioral problems, and increased diurnal sleepiness. This study suggests that studies in obese children using questionnaires about sleep habits and quality of life provide useful information that could lead to better weight loss intervention studies.