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dc.contributor.authorWelten, Marieke
dc.contributor.authorWijga, Alet H
dc.contributor.authorHamoen, Marleen
dc.contributor.authorGehring, Ulrike
dc.contributor.authorKoppelman, Gerard H
dc.contributor.authorTwisk, Jos W R
dc.contributor.authorRaat, Hein
dc.contributor.authorHeymans, Martijn W
dc.contributor.authorde Kroon, Marlou L A
dc.date.accessioned2020-05-25T19:34:09Z
dc.date.available2020-05-25T19:34:09Z
dc.date.issued2020-05-13
dc.identifier.issn2047-6310
dc.identifier.pmid32400070
dc.identifier.doi10.1111/ijpo.12647
dc.identifier.urihttp://hdl.handle.net/10029/623812
dc.description.abstractAfter backward selection in a Generalized Estimating Equations analysis, the prediction model included the baseline predictors maternal BMI, paternal BMI, paternal education, birthweight, sex, ethnicity and indoor smoke exposure; and the longitudinal predictors BMI SDS, and the linear and quadratic terms of the growth curve describing a child's BMI SDS development over time, as well as the longitudinal predictors' interactions with age. The area under the curve of the model after internal validation was 0.845 and Nagelkerke R2 was 0.351.en_US
dc.language.isoenen_US
dc.subjectcohort studyen_US
dc.subjectdynamic prediction modelen_US
dc.subjectfuture overweighten_US
dc.subjectgeneral populationen_US
dc.subjectprimordial preventionen_US
dc.subjectyoung childrenen_US
dc.titleDynamic prediction model to identify young children at high risk of future overweight: Development and internal validation in a cohort study.en_US
dc.typeArticleen_US
dc.identifier.journalPediatr Obes 2020; 13:e12647en_US
dc.source.journaltitlePediatric obesity


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