Abstract
ABSTRACT Objective To assess sleep quality and its association with metabolic syndrome and its components. Methods This cross-sectional study was conducted from June 2011 to March 2012 at the Childhood Obesity Center, Campina Grande, Paraíba , Brazil, with 135 overweight or obese children and adolescents. Sleep quality was assessed by the Pittsburgh Sleep Quality Index. Metabolic syndrome diagnosis was based on abdominal circumference, blood pressure, glycemia, high density lipoprotein-cholesterol, and triglycerides. The data were treated by the software Statistical Package for the Social Sciences version 22.0 at a significance level of 5%. Results The prevalence of poor sleep quality or sleep disorder according to the Pittsburgh Sleep Quality Index was 40.7%, and females had higher mean global Pittsburgh Sleep Quality Index score. Metabolic syndrome prevalence was 63.0%. Females also had higher daytime dysfunction. Poor sleep quality was associated with high diastolic blood pressure (OR=2.6; p =0.015) and waist circumference (OR=3.17; p =0.024) after adjusting for sex and age. Conclusion Girls had higher global Pittsburgh Sleep Quality Index score, which was associated with daytime dysfunction. Poor sleep quality was a predictor of high diastolic blood pressure in the study sample.
Highlights
Sleep is a vital necessity and its periodicity, quality, and constancy characterize very important variables in the development of children and adolescents1
The prevalence of poor sleep quality or sleep disorder according to the Pittsburgh Sleep Quality Index was 40.7%, and females had higher mean global Pittsburgh Sleep Quality Index score
Girls had higher global Pittsburgh Sleep Quality Index score, which was associated with daytime dysfunction
Summary
This cross-sectional study was conducted from June 2011 to March 2012 at the Childhood Obesity Center, Campina Grande, Paraíba, Brazil, with 135 overweight or obese children and adolescents. Sleep quality was assessed by the Pittsburgh Sleep Quality Index. Metabolic syndrome diagnosis was based on abdominal circumference, blood pressure, glycemia, high density lipoprotein-cholesterol, and triglycerides. The data were treated by the software Statistical Package for the Social Sciences version 22.0 at a significance level of 5%.
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