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Updated: Dec 8, 2025

Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Childhood Obesity Evidence Base Project: Building Translational Capacity through Meta-Analytic Methods
Deborah Young-Hyman1, Laura Kettel Khan2
1Office of Behavioral and Social Sciences, Office of the Director, National Institutes of Health, Bethesda, MD, USA.
Abstract:
The purpose of this article is to demonstrate the need for and utility of using a taxonomic approach for evidence aggregation and meta-analyses, with focus on prevention and reduction of childhood obesity in very young children. As evidence has been generated through heterogeneous efforts, it is important that the field makes use of all available evidence to learn what works, for who, and in what circumstances. The Childhood Obesity Evidence Base (COEB) project conducted a taxonomic meta-analysis, using Grounded Theory to code elements present in reports of existing studies and initiatives, of diverse design and evaluation approaches, which were then mapped onto the levels of the socio-ecologic model. This article is the fourth in a series that describes the COEB project overall. It discusses both generally and specifically how taxonomies contribute to traditional meta-analytic methods, what questions can and cannot be answered, the method's contribution to translational (implementation) capacity, and ability to inform future efforts. The COEB project illustrates how the taxonomic meta-analytic approach broadens the evidence base, increases translational capacity for effective intervention components, and evaluates the influence of contextual elements to inform future initiatives. How the method is used to establish associations between varying intervention components, contextual elements, and outcomes is discussed. Taxonomies generated through this process can be used for meta-analysis, serving to generate topic-specific questions associated with intervention approaches and outcomes in context, which is adjunctive to traditional meta-analytic methods and can inform public health approaches.
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