To send content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about sending content to .
To send content items to your Kindle, first ensure email@example.com
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about sending to your Kindle.
Note you can select to send to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
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.
The 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.
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.
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.
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.