The Arkansas Active Kids Study: Identifying contributing factors to metabolic health and obesity status in prepubertal school-age children. Issue 2 (June 2021)

• Record Type: Journal Article
• Authors: Bai, Shasha; Goudie, Anthony; Børsheim, Elisabet; Weber, Judith L
• Is Part Of: Nutrition and health. Volume 27:Issue 2(2021)
• Page Start: 273
• Page End: 281
• Publication Date: 2021-06
• Subjects: Obesity -- children -- metabolic health -- physical activity -- physical fitness; Nutrition -- Periodicals; Diet -- Periodicals; Diet therapy -- Periodicals; 613.205
• DOI: 10.1177/0260106020975571
• Languages: English
• ISSNs: 0260-1060

Abstract

Background: 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. Aim: 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. Methods: 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. Results: 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. Conclusion: 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.