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  5. Prediction of adolescent and adult adiposity outcomes from early life anthropometrics

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Article
en
2014

Prediction of adolescent and adult adiposity outcomes from early life anthropometrics

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en
2014
Vol 23 (1)
Vol. 23
DOI: 10.1002/oby.20921

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Paul M Ridker
Paul M Ridker

Harvard University

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Lise Graversen
Thorkild I. A. Sørensen
Thomas Alexander Gerds
+9 more

Abstract

OBJECTIVES: Maternal body mass index (BMI), birth weight, and preschool BMI may help identify children at high risk of overweight as they are (1) similarly linked to adolescent overweight at different stages of the obesity epidemic, (2) linked to adult obesity and metabolic alterations, and (3) easily obtainable in health examinations in young children. The aim was to develop early childhood prediction models of adolescent overweight, adult overweight, and adult obesity. METHODS: Prediction models at various ages in the Northern Finland Birth Cohort born in 1966 (NFBC1966) were developed. Internal validation was tested using a bootstrap design, and external validation was tested for the model predicting adolescent overweight using the Northern Finland Birth Cohort born in 1986 (NFBC1986). RESULTS: A prediction model developed in the NFBC1966 to predict adolescent overweight, applied to the NFBC1986, and aimed at labelling 10% as "at risk" on the basis of anthropometric information collected until 5 years of age showed that half of those at risk in fact did become overweight. This group constituted one-third of all who became overweight. CONCLUSIONS: Our prediction model identified a subgroup of children at very high risk of becoming overweight, which may be valuable in public health settings dealing with obesity prevention.

How to cite this publication

Lise Graversen, Thorkild I. A. Sørensen, Thomas Alexander Gerds, Liselotte Petersen, Ulla Sovio, Marika Kaakinen, Annelli Sandbæk, Jaana Laitinen, Anja Taanila, Anneli Pouta, Paul M Ridker, Carsten Obel (2014). Prediction of adolescent and adult adiposity outcomes from early life anthropometrics. , 23(1), DOI: https://doi.org/10.1002/oby.20921.

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Publication Details

Type

Article

Year

2014

Authors

12

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1002/oby.20921

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