Clinical relevance and validity of tools to predict infant, childhood and adulthood obesity: a systematic review.

Public Health Nutr

1School of Human Movement and Nutrition Sciences, Faculty of Health and Behavioural Sciences, The University of Queensland,Brisbane,QLD4072,Australia.

Published: December 2018

Objective: To determine the global availability of a multicomponent tool predicting overweight/obesity in infancy, childhood, adolescence or adulthood; and to compare their predictive validity and clinical relevance.Design/SettingThe PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed. The databases PubMed, EMBASE, CINAHL, Web of Science and PsycINFO were searched. Additional articles were identified via reference lists of included articles. Risk of bias was assessed using the Academy of Nutrition and Dietetics' Quality Criteria Checklist. The National Health and Medical Research Council's Levels of Evidence hierarchy was used to assess quality of evidence. Predictive performance was evaluated using the ABCD framework.

Subjects: Eligible studies: tool could be administered at any life stage; quantified the risk of overweight/obesity onset; used more than one predictor variable; and reported appropriate prediction statistical outcomes.

Results: Of the initial 4490 articles identified, twelve articles (describing twelve tools) were included. Most tools aimed to predict overweight and/or obesity within childhood (age 2-12 years). Predictive accuracy of tools was consistently adequate; however, the predictive validity of most tools was questioned secondary to poor methodology and statistical reporting. Globally, five tools were developed for dissemination into clinical practice, but no tools were tested within a clinical setting.

Conclusions: To our knowledge, a clinically relevant and highly predictive overweight/obesity prediction tool is yet to be developed. Clinicians can, however, act now to identify the strongest predictors of future overweight/obesity. Further research is necessary to optimise the predictive strength and clinical applicability of such a tool.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10260762PMC
http://dx.doi.org/10.1017/S1368980018001684DOI Listing

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