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Dynamic prediction of childhood high blood pressure in a population-based birth cohort: a model development study
  1. Marleen Hamoen1,2,
  2. Yvonne Vergouwe1,
  3. Alet H Wijga3,
  4. Martijn W Heymans4,
  5. Vincent W V Jaddoe2,
  6. Jos W R Twisk4,
  7. Hein Raat1,
  8. Marlou L A de Kroon1,5
  1. 1 Department of Public Health, Erasmus University Medical Center, Rotterdam, Netherlands
  2. 2 Erasmus University Medical Center, The Generation R Study Group, Rotterdam, Netherlands
  3. 3 National Institute for Public Health and the Environment, Center for Nutrition, Prevention and Health Services, Bilthoven, Netherlands
  4. 4 Department of Epidemiology and Biostatistics, Amsterdam Public Health research institute, VU University Medical Center, Amsterdam, Netherlands
  5. 5 Department of Health Sciences, University Medical Center Groningen, Groningen, Netherlands
  1. Correspondence to Marleen Hamoen; m.hamoen{at}erasmusmc.nl

Abstract

Objectives To develop a dynamic prediction model for high blood pressure at the age of 9–10 years that could be applied at any age between birth and the age of 6 years in community-based child healthcare.

Design, setting and participants Data were used from 5359 children in a population-based prospective cohort study in Rotterdam, the Netherlands.

Outcome measure High blood pressure was defined as systolic and/or diastolic blood pressure ≥95th percentile for gender, age and height. Using multivariable pooled logistic regression, the predictive value of characteristics at birth, and of longitudinal information on the body mass index (BMI) of the child until the age of 6 years, was assessed. Internal validation was performed using bootstrapping.

Results 227 children (4.2%) had high blood pressure at the age of 9–10 years. Final predictors were maternal hypertensive disease during pregnancy, maternal educational level, maternal prepregnancy BMI, child ethnicity, birth weight SD score (SDS) and the most recent BMI SDS. After internal validation, the area under the receiver operating characteristic curve ranged from 0.65 (prediction at age 3 years) to 0.73 (prediction at age 5–6 years).

Conclusions This prediction model may help to monitor the risk of developing high blood pressure in childhood which may allow for early targeted primordial prevention of cardiovascular disease.

  • high blood pressure
  • children
  • birth cohort
  • prediction model
  • risk assessment

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

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Footnotes

  • Contributors MLAdK and AHW conceived the project. MLAdK obtained funds for the ProCOR project, and is project coordinator. MH performed the analysis, supervised by YV, MWH and JWRT. MH drafted the first version of the manuscript, with help from MLAdK and YV. VWVJ contributed to the conception of the cohort. VWVJ and HR contributed to the design of the cohort. The final manuscript was critically revised and approved by all authors.

  • Funding This study is part of larger project aiming to develop prediction and decision tools for childhood overweight and cardiometabolic risk factors, funded by The Netherlands Organization for Health Research and Development (ZonMw grant no. 200500006). Generation R is financially supported by the Erasmus MC University Medical Center, the Netherlands Organization for Health Research and Development, and the Ministry of Health, Welfare and Sport. Generation R also received funding from the European Union’s Horizon 2020 Research and Innovation Programme (grant no. 733206, LifeCycle). Vincent Jaddoe received an additional grant from the Netherlands Organization for Scientific Research (NWO-VIDI 016.136.361) and a Consolidator Grant from the European Research Council (ERC-2014-CoG-648916).

  • Competing interests None declared.

  • Patient consent Obtained.

  • Ethics approval Medical Ethics Committee of the Erasmus University Medical Center, Rotterdam.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement The datasets generated and/or analysed during the current study are not publicly available due to privacy of the participants, but are available from the corresponding author on reasonable request.

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