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Shape Information in Repeated Glucose Curves during Pregnancy Provided Significant Physiological Information for Neonatal Outcomes

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  • Kathrine Frey Frøslie
  • Jo Røislien
  • Elisabeth Qvigstad
  • Kristin Godang
  • Jens Bollerslev
  • Tore Henriksen
  • Marit B Veierød

Abstract

Objective: To use multilevel functional principal component analysis to exploit the information inherent in the shape of longitudinally sampled glucose curves during pregnancy, and to analyse the impact of glucose curve characteristics on neonatal birth weight, percentage fat and cord blood C-peptide. Study Design and Setting: A cohort study of healthy, pregnant women (n = 884). They underwent two oral glucose tolerance tests (gestational weeks 14–16 and 30–32), which gave two glucose curves per woman. Results: Glucose values were higher, and peaked later in third trimester than in early pregnancy. The curve characteristic “general glucose level” accounted for 91% of the variation across visits, and 72% within visits. The curve characteristics “timing of postprandial peak”, and “oscillating glucose levels” accounted for a larger part of the variation within visits (15% and 8%), than across visits (7% and

Suggested Citation

  • Kathrine Frey Frøslie & Jo Røislien & Elisabeth Qvigstad & Kristin Godang & Jens Bollerslev & Tore Henriksen & Marit B Veierød, 2014. "Shape Information in Repeated Glucose Curves during Pregnancy Provided Significant Physiological Information for Neonatal Outcomes," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-10, March.
    • Handle: RePEc:plo:pone00:0090798
    DOI: 10.1371/journal.pone.0090798
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    References listed on IDEAS

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    1. Crainiceanu, Ciprian M. & Goldsmith, A. Jeffrey, 2010. "Bayesian Functional Data Analysis Using WinBUGS," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 32(i11).
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