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Associations of sleep patterns with metabolic syndrome indices, body composition, and energy intake in children and adolescents
Author(s) -
Mi Sarah J.,
Kelly Nichole R.,
Brychta Robert J.,
Grammer Anne Claire,
Jaramillo Manuela,
Chen Kong Y.,
Fletcher Laura A.,
Bernstein Shanna B.,
Courville Amber B.,
Shank Lisa M.,
Pomeroy Jeremy J.,
Brady Sheila M.,
Broadney Miranda M.,
TanofskyKraff Marian,
Yanovski Jack A.
Publication year - 2019
Publication title -
pediatric obesity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.226
H-Index - 69
eISSN - 2047-6310
pISSN - 2047-6302
DOI - 10.1111/ijpo.12507
Subject(s) - medicine , bedtime , waist , blood pressure , body mass index , obesity , metabolic syndrome
Summary Background Self‐reported short sleep duration is associated with greater risk for metabolic syndrome (MetS), obesity, and higher energy intake (EI). However, studies of these associations in children using objective methods are sparse. Objectives The study aims to determine the associations for sleep patterns with MetS indices, body composition, and EI using objective measures in children. Methods Free‐living sleep and physical activity were measured in 125 children (aged 8‐17 years, BMI z = 0.57 ± 1.0, 55% female) using wrist‐worn actigraphs for 14 nights. Blood pressure, fasting blood levels of lipids, insulin, glucose, waist circumference, and body composition (dual‐energy X‐ray absorptiometry [DXA]) were obtained during outpatient visits. EI was assessed during an ad libitum buffet meal. Results Later weekday and weekend bedtimes were associated with higher systolic blood pressure ( P s < 0.05). Sleep duration and bedtime were not significantly associated with other components of MetS, body composition, or EI. Short sleepers (duration less than 7 hours) consumed a greater percentage of carbohydrates than those with adequate (greater than or equal to 7 hours) sleep ( P < 0.05). Conclusion Indicators of sleep duration were variably associated with children's eating patterns and risk for chronic disease. Prospective data are needed to determine whether these indicators of sleep quality represent unique or shared risk factors for poor health outcomes.