首页> 外文期刊>BMC Pediatrics >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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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

机译:Snuggle Bug / Acurrucadito研究的协议:纵向研究调查睡眠模式和肠道微生物组发育在快速体重增加上的影响,肥胖的早期危险因素

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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. 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. 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.
机译:超重,肥胖和相关的合并症是所有年龄段的儿童的紧迫全球问题,特别是在低收入人口中。在前6个?婴儿期的快速增长(RWG)有助于儿童肥胖。次优睡眠唤醒模式和肠道微生物瘤(GM)也与儿童肥胖有关,但对他们对早期婴儿RWG的影响很少。睡眠可能会改变GM和婴儿新陈代谢,最终影响肥胖;然而,关于睡眠模式和通用婴儿生长的互动和通用汽车发展之间的数据稀缺。在这项研究中,我们的目标是调查婴幼儿睡眠模式和转基因发展的协会,RWG在6?月份和12个月的体重增加。我们还旨在评估婴幼儿睡眠模式和通用汽车之间是否存在时间互动,以及这些关系影响RWG。依偎虫/ Acurrucadito研究是一个观察到的纵向研究,调查了24-H,激光评估,睡眠模式和转基因发展在第一年的婴儿中的RWG相关。基于生态模型的增长,我们提出了一种新颖的概念框架,将睡眠唤醒模式和通用汽车作为RWG的代谢贡献者在母婴互动和家庭和社会物理环境的背景下。总共招募了192对母婴对,并在3和8周内评估的睡眠模式和转基因开发评估,3,6,9和12个月。将评估包括孕产妇和儿童特征,家庭和环境因素,喂养实践和婴儿和母亲的膳食摄入以及粪便衍生的代谢物和去聚集数据的协调因素。该研究将应用机器学习技术与物流时变效果模型相结合,以捕捉婴儿生长并有助于阐明研究变量与RWG之间的动态关联。在临床和发育有意义的间隔内重复,有效和客观评估将提供纵向睡眠,通用术语和生长的强大措施。项目调查结果将提供未来干预措施,以防止婴儿期和随后的肥胖中的rwg。这项工作也可能促进发展基于证据的准则,以解决影响睡眠唤醒和通用汽车发展和防止儿童肥胖的可修改因素。

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