Prediction of adolescent and adult adiposity outcomes from early life anthropometrics. (30th October 2014)

• Record Type: Journal Article
• Authors: Graversen, Lise; Sørensen, Thorkild I.A.; Gerds, Thomas A.; Petersen, Liselotte; Sovio, Ulla; Kaakinen, Marika; Sandbaek, Annelli; Laitinen, Jaana; Taanila, Anja; Pouta, Anneli; Järvelin, Marjo‐Riitta; Obel, Carsten
• Is Part Of: Obesity. Volume 23:Number 1(2015:Jan.)
• Page Start: 162
• Page End: 169
• Publication Date: 2014-10-30
• Subjects: Obesity -- Periodicals; 616.398005
• DOI: 10.1002/oby.20921
• Languages: English
• ISSNs: 1930-7381

Abstract

<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <sec id="oby20921-sec-0001" sec-type="section"> <title>Objectives</title> <p>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.</p> </sec> <sec id="oby20921-sec-0002" sec-type="section"> <title>Methods</title> <p>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).</p> </sec> <sec id="oby20921-sec-0003" sec-type="section"> <title>Results</title> <p>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.</p> </sec> <sec id="oby20921-sec-0004" sec-type="section"> <title>Conclusions</title> <p>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.</p> </sec> </abstract>