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Childhood obesity: how long should we wait to predict weight?
Better Start Natl Sci Challenge, Auckland, New Zealand.;Univ Auckland, Liggins Inst, Private Bag 92019, Auckland, New Zealand..
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Women's and Children's Health. Better Start Natl Sci Challenge, Auckland, New Zealand.; Univ Auckland, Liggins Inst, Auckland, New Zealand..ORCID iD: 0000-0003-1226-1956
Better Start Natl Sci Challenge, Dunedin, New Zealand.;Univ Otago, Dunedin Sch Med, Dunedin, New Zealand..
Better Start Natl Sci Challenge, Auckland, New Zealand.;Univ Auckland, Liggins Inst, Private Bag 92019, Auckland, New Zealand..
2018 (English)In: Journal of Pediatric Endocrinology & Metabolism (JPEM), ISSN 0334-018X, E-ISSN 2191-0251, Vol. 31, no 5, p. 497-501Article, review/survey (Refereed) Published
Abstract [en]

Obesity is highly prevalent in children under the age of 5 years, although its identification in infants under 2 years remains difficult. Several clinical prediction models have been developed for obesity risk in early childhood, using a number of different predictors. The predictive capacity (sensitivity and specificity) of these models varies greatly, and there is no agreed risk threshold for the prediction of early childhood obesity. Of the existing models, only two have been practically utilized, but neither have been particularly successful. This commentary suggests how future research may successfully utilize existing early childhood obesity prediction models for intervention. We also consider the need for such models, and how targeted obesity intervention may be more effective than population-based intervention.

Place, publisher, year, edition, pages
2018. Vol. 31, no 5, p. 497-501
Keywords [en]
intervention, model, obese, overweight, prediction, prevention, risk
National Category
Pediatrics
Identifiers
URN: urn:nbn:se:uu:diva-357655DOI: 10.1515/jpem-2018-0110ISI: 000431124900002PubMedID: 29668465OAI: oai:DiVA.org:uu-357655DiVA, id: diva2:1242564
Available from: 2018-08-28 Created: 2018-08-28 Last updated: 2018-08-28Bibliographically approved

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