Childhood Obesity Evidence Base Project: Methods for Taxonomy Development for Application in Taxonomic Meta-Analysis.

Heather King, Mackenzie Magnus, Larry V Hedges, Chris Cyr, Deborah Young-Hyman, Laura Kettel Khan, Lori A J Scott-Sheldon, Jason A Saul, Sonia Arteaga, John Cawley, Christina D Economos, Debra Haire-Joshu, Christine M Hunter, Bruce Y Lee, Shiriki K Kumanyika, Lorrene D Ritchie, Thomas N Robinson, Marlene B Schwartz

Journal: Childhood obesity (Print) 2021;16(S2):S27-S220

PMID: 32936039

Abstract

Meta-analysis has been used to examine the effectiveness of childhood obesity prevention efforts, yet traditional conventional meta-analytic methods restrict the kinds of studies included, and either narrowly define mechanisms and agents of change, or examine the effectiveness of whole interventions as opposed to the specific actions that comprise interventions. Taxonomic meta-analytic methods widen the aperture of what can be included in a meta-analysis data set, allowing for inclusion of many types of interventions and study designs. The National Collaborative on Childhood Obesity Research Childhood Obesity Evidence Base (COEB) project focuses on interventions intended to prevent childhood obesity in children 2-5 years old who have an outcome measure of BMI. The COEB created taxonomies, anchored in the Social Ecological Model, which catalog specific outcomes, intervention components, intended recipients, and contexts of policies, initiatives, and interventions conducted at the individual, interpersonal, organizational, community, and societal level. Taxonomies were created by discovery from the literature itself using grounded theory. This article describes the process used for a novel taxonomic meta-analysis of childhood obesity prevention studies between the years 2010 and 2019. This method can be applied to other areas of research, including obesity prevention in additional populations.

Address: Impact Genome Project, Mission Measurement, Chicago, IL, USA.; Department of Statistics, Northwestern University, Evanston, IL, USA.; Office of Behavioral and Social Sciences, Office of the Director, National Institutes of Health, Bethesda, MD, USA.; Division of Nutrition, Physical Activity, and Obesity, Centers for Disease Control and Prevention, Atlanta, GA, USA.; Centers for Behavioral and Preventive Medicine, The Miriam Hospital, Providence, RI, USA.; Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Providence, RI, USA.; Center for Impact Sciences, Harris School of Public Policy, University of Chicago, Chicago, IL, USA.; Office of the Director, National Institutes of Health, Bethesda, MD, USA.; Department of Policy Analysis and Management and Cornell University, Ithaca, NY, USA.; Department of Economics, Cornell University, Ithaca, NY, USA.; Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA.; Center for Obesity Prevention and Policy Research, Brown School Washington University, Saint Louis, MO, USA.; CUNY Graduate School of Public Health and Policy, New York, NY, USA.; Department of Community Health and Prevention, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA.; Nutrition Policy Institute, University of California Agriculture and Natural Resources, Berkeley, CA, USA.; Stanford Solutions Science Lab, Stanford University, Stanford, CA, USA.; Department of Human Development and Family Studies, University of Connecticut, Hartford, CT, USA.
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