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Identifying young children without overweight at high risk for adult overweight: The Terneuzen Birth Cohort

Authors

  • MARLOU L. A. de KROON,

    Corresponding author
    1. Department of Public and Occupational Health, EMGO-Institute for Health and Care Research, VU University Medical Centre, Amsterdam, the Netherlands
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  • CARRY M. RENDERS,

    1. Section of Prevention and Public Health, Department of Health Sciences and EMGO Institute for Health and Care Research, VU University Amsterdam, Amsterdam
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  • JACOBUS P. VAN WOUWE,

    1. Netherlands Organisation for Applied Scientific Research, TNO Quality of Life, Prevention and Health Care, Leiden, the Netherlands
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  • REMY A. HIRASING,

    1. Department of Public and Occupational Health, EMGO-Institute for Health and Care Research, VU University Medical Centre, Amsterdam, the Netherlands
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  • STEF VAN BUUREN

    1. Netherlands Organisation for Applied Scientific Research, TNO Quality of Life, Prevention and Health Care, Leiden, the Netherlands
    2. Dept of Methodology and Statistics, FSS, University of Utrecht, the Netherlands
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Department of Public and Occupational Health, Institute for Research in Extramural Medicine (room no. C574), VU University Medical Centre, Van der Boechorststraat 7, 1081 BT Amsterdam, the Netherlands. Fax 31 204 448 387. E-mail: top@fms.demon.nl

Abstract

Objective. To develop a tool to identify children with high risk of adult overweight (AO), especially before developing overweight, based on body mass index (BMI) standard deviation score(s) (SDS) changes between 2–6 years (y) of age. Methods. We fitted a linear spline model to BMI SDS of 762 young Caucasian adults from the Terneuzen Birth Cohort at fixed ages between birth and 18 y. By linear regression analysis, we assessed the increase in explained variance of the adult BMI SDS by adding the BMI SDS at 2 y to the models including the BMI SDS at 4 y, 6 y and both 4 y and 6 y. AO risk was modelled by logistic regression. The internal validity was estimated using bootstrap techniques. Risk models were represented as risk score diagrams by gender for the age intervals 2–4 y and 2–6 y. Results. In addition to the BMI SDS at certain ages, the previous BMI SDS during childhood is positively related to adult weight. Receiver Operating Curves analysis provides insight into sensible cut-offs (AUC varied from 0.76 to 0.83). The sensitivity and specificity for 2–6 y at the cut-off of 0.25 and 0.5 are respectively, 0.76 and 0.74, and 0.36 and 0.93, whereas the PPV is 0.52 and 0.67, respectively. Conclusions. The risk score diagrams can serve as a tool for young children for primary prevention of adult overweight. To avoid wrongly designating children at risk for AO, we propose a cut-off with a high specificity at the risk of approximately 0.5. After external validation, wider adoption of this tool might enhance primary AO prevention.

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