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dc.contributor.authorTrude, Angela Cristina Bizzotto
dc.contributor.authorArmstrong, Bridget
dc.contributor.authorKramer Fiala Machado, Adriana
dc.contributor.authorWickwire, Emerson M
dc.contributor.authorCovington, Lauren B
dc.contributor.authorWang, Yan
dc.contributor.authorHager, Erin
dc.contributor.authorBlack, Maureen M
dc.date.accessioned2022-02-21T14:53:59Z
dc.date.available2022-02-21T14:53:59Z
dc.date.issued2022-02-10
dc.identifier.urihttp://hdl.handle.net/10713/18045
dc.description.abstractObjective: To identify longitudinal bidirectional associations between unique sleep trajectories and obesity and hypertension among Black, adolescent girls. Design, setting, and participants: Longitudinal data were from a randomized controlled trial (2009-2013) implemented in schools serving low-income communities aimed at preventing obesity among adolescent girls (mean age = 12.2 years (standard deviation ± 0.72). Measures: Nocturnal sleep data were extracted from accelerometers at T1 (enrollment, n = 470), T2 (6-month, n = 348), and T3 (18-month follow-up, n = 277); height and weight were measured at T1-T3; and systolic/diastolic blood pressure at T1 and T3 using an oscillometric monitor. Multilevel models examined longitudinal associations. Finite mixture models identified sleep trajectory groups. Structural equation models examined whether T1 chronic disease risk predicted sleep profiles, and conversely, if sleep trajectories predicted T3 chronic disease risk. Data were analyzed in 2021. Results: For each additional hour of sleep and 1% increase in efficiency there was a 7% lower risk of overweight/obesity at T1 and 6% lower risk at T2, but not at T3. Four sleep trajectories emerged: Worsened, Irregular, Improved, and Regular, with no demographic or metabolic differences between the trajectories. Improved sleep trajectory predicted lower diastolic percentile at T3 (b = −8.81 [95% confidence interval −16.23, −1.40]). Conclusions: Group-based trajectories of sleep duration and quality provide information on modifiable factors that can be targeted in interventions to evaluate their impact on reducing chronic diseases and addressing disparities. Additional research is needed on samples beyond those recruited in the context of an intervention study. © 2022 The Authorsen_US
dc.description.urihttps://doi.org/10.1016/j.sleh.2021.12.001en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofSleep Healthen_US
dc.rightsCopyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.en_US
dc.subjectAdolescenten_US
dc.subjectBlood pressureen_US
dc.subjectLongitudinal designen_US
dc.subjectMultigroup trajectoryen_US
dc.subjectObesityen_US
dc.subjectPovertyen_US
dc.subjectSleepen_US
dc.titleWaking up to sleep's role in obesity and blood pressure among Black adolescent girls in low-income, US urban communities: A longitudinal analysis.en_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.sleh.2021.12.001
dc.identifier.pmid35153168
dc.source.journaltitleSleep health
dc.source.countryUnited States


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