Center for Biostatistics, 12306The Ohio State University, USA.
Department of Health Policy and Management, College of Public Health, 12215University of Arkansas for Medical Sciences, USA.
Nutr Health. 2021 Jun;27(2):273-281. doi: 10.1177/0260106020975571. Epub 2020 Dec 17.
We report the design, protocol and statistical analysis plan for the Arkansas Active Kids (AAK) Study. The study investigates the complex relationships between factors that contribute to metabolic health and obesity status in prepubertal school-age children in the state of Arkansas.
We aim to identify modifiable behavioral and environmental factors and phenotypes related to metabolic health that are associated with obesity status that, if addressed effectively, can aid in designing effective intervention strategies to improve fitness and reduce obesity in children.
We analyzed dietary and physical activity data from two national surveys (National Survey of Children's Health and Youth Risk Behavior Surveillance System). We then conducted detailed surveys to collect dietary, physical activity, socio-demographic, and environmental data from a sample of 226 prepubertal Arkansas children. In the same sample of prepubertal children, we also collected extensive physiologic data to further study associations between physical activity and metabolic health.
All study visits included detailed measures of vital signs, energy expenditure, components of physical fitness, body composition and the collection of biological samples for determination of metabolic analytes.
The observational, environmental and physiological results will be used to craft multivariate statistical models to identify which variables define 'phenotype signatures' that associate with fitness level and obesity status.
我们报告了阿肯色州积极儿童(AAK)研究的设计、方案和统计分析计划。该研究调查了导致代谢健康和肥胖状态的因素之间的复杂关系,这些因素与阿肯色州学龄前期儿童有关。
我们旨在确定与肥胖状态相关的与代谢健康相关的可改变行为和环境因素及表型,这些因素如果得到有效解决,可以帮助设计有效的干预策略,以提高儿童的健康水平和减少肥胖。
我们分析了两项全国性调查(全国儿童健康调查和青少年风险行为监测系统)的饮食和体力活动数据。然后,我们对 226 名阿肯色州学龄前期儿童进行了详细的调查,以收集饮食、体力活动、社会人口统计学和环境数据。在同一批学龄前期儿童中,我们还收集了广泛的生理数据,以进一步研究体力活动与代谢健康之间的关联。
所有研究访问都包括详细的生命体征、能量消耗、身体素质成分、身体成分和生物样本采集,以确定代谢分析物。
观察、环境和生理结果将用于制定多元统计模型,以确定哪些变量定义与健康水平和肥胖状态相关的“表型特征”。