Protocol of the Snuggle Bug/Acurrucadito Study: a longitudinal study investigating the influences of sleep-wake patterns and gut microbiome development in infancy on rapid weight gain, an early risk factor for obesity
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Author
Petrov, M.E.Jiao, N.
Panchanathan, S.S.
Reifsnider, E.
Coonrod, D.V.
Liu, L.
Krajmalnik-Brown, R.
Gu, H.
Davidson, L.A.
Chapkin, R.S.
Whisner, C.M.
Affiliation
College of Medicine Phoenix, University of ArizonaIssue Date
2021Keywords
Actigraphychild overweight
time varying effect models
circadian rhythm
Gastrointestinal microbiota
infant sleep
Rapid weight gain
sleep-wake pattern
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BioMed Central LtdCitation
Petrov, M. E., Jiao, N., Panchanathan, S. S., Reifsnider, E., Coonrod, D. V., Liu, L., Krajmalnik-Brown, R., Gu, H., Davidson, L. A., Chapkin, R. S., & Whisner, C. M. (2021). Protocol of the Snuggle Bug/Acurrucadito Study: A longitudinal study investigating the influences of sleep-wake patterns and gut microbiome development in infancy on rapid weight gain, an early risk factor for obesity. BMC Pediatrics, 21(1).Journal
BMC PediatricsRights
Copyright © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Background: Overweight, obesity, and associated comorbidities are a pressing global issue among children of all ages, particularly among low-income populations. Rapid weight gain (RWG) in the first 6 months of infancy contributes to childhood obesity. Suboptimal sleep-wake patterns and gut microbiota (GM) have also been associated with childhood obesity, but little is known about their influences on early infant RWG. Sleep may alter the GM and infant metabolism, and ultimately impact obesity; however, data on the interaction between sleep-wake patterns and GM development on infant growth are scarce. In this study, we aim to investigate associations of infant sleep-wake patterns and GM development with RWG at 6 months and weight gain at 12 months. We also aim to evaluate whether temporal interactions exist between infant sleep-wake patterns and GM, and if these relations influence RWG. Methods: The Snuggle Bug/ Acurrucadito study is an observational, longitudinal study investigating whether 24-h, actigraphy-assessed, sleep-wake patterns and GM development are associated with RWG among infants in their first year. Based on the Ecological Model of Growth, we propose a novel conceptual framework to incorporate sleep-wake patterns and the GM as metabolic contributors for RWG in the context of maternal-infant interactions, and familial and socio-physical environments. In total, 192 mother-infant pairs will be recruited, and sleep-wake patterns and GM development assessed at 3 and 8 weeks, and 3, 6, 9, and 12 months postpartum. Covariates including maternal and child characteristics, family and environmental factors, feeding practices and dietary intake of infants and mothers, and stool-derived metabolome and exfoliome data will be assessed. The study will apply machine learning techniques combined with logistic time-varying effect models to capture infant growth and aid in elucidating the dynamic associations between study variables and RWG. Discussion: Repeated, valid, and objective assessment at clinically and developmentally meaningful intervals will provide robust measures of longitudinal sleep, GM, and growth. Project findings will provide evidence for future interventions to prevent RWG in infancy and subsequent obesity. The work also may spur the development of evidence-based guidelines to address modifiable factors that influence sleep-wake and GM development and prevent childhood obesity. © 2021, The Author(s).Note
Open access journalISSN
1471-2431Version
Final published versionae974a485f413a2113503eed53cd6c53
10.1186/s12887-021-02832-8
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Except where otherwise noted, this item's license is described as Copyright © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License.