title: Shape information in repeated glucose curves during pregnancy provided significant physiological information for neonatal outcomes.
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.
  
  
  METHODS
  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 <2%). A late postprandial peak during pregnancy, and high general glucose levels in third trimester had significant, positive effects on birth weight (p<0.05). Generally high glucose levels during pregnancy had a significant, positive impact on neonatal percentage fat (p = 0.04). High general glucose level in third trimester had a significant, positive impact on cord blood C-peptide (p = 0.004).
  
  
  CONCLUSIONS
  Shape information in entire OGTT curves provides significant physiological information of importance for several outcomes, and may contribute to the understanding of the metabolic changes during pregnancy.
authors.affiliation: Department of Biostatistics, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway; Norwegian Resource Centre for Women's Health, Division of Obstetrics and Gynaecology, Oslo University Hospital Rikshospitalet, Oslo, Norway.
authors.forename: Kathrine Frey
authors.initials: KF
authors.lastname: Frøslie
authors.affiliation: Department of Biostatistics, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.
authors.forename: Jo
authors.initials: J
authors.lastname: Røislien
authors.affiliation: Section of Specialised Endocrinology, Department of Medicine, Oslo University Hospital, Oslo, Norway.
authors.forename: Elisabeth
authors.initials: E
authors.lastname: Qvigstad
authors.affiliation: Section of Specialised Endocrinology, Department of Medicine, Oslo University Hospital, Oslo, Norway.
authors.forename: Kristin
authors.initials: K
authors.lastname: Godang
authors.affiliation: Section of Specialised Endocrinology, Department of Medicine, Oslo University Hospital, Oslo, Norway; Faculty of Clinical Medicine, University of Oslo, Oslo, Norway.
authors.forename: Jens
authors.initials: J
authors.lastname: Bollerslev
authors.affiliation: Faculty of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Obstetrics and Gynaecology, Oslo University Hospital Rikshospitalet, Oslo, Norway.
authors.forename: Tore
authors.initials: T
authors.lastname: Henriksen
authors.affiliation: Department of Biostatistics, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.
authors.forename: Marit B
authors.initials: MB
authors.lastname: Veierød
mesh_terms: D000328:Adult; D001724:Birth Weight; D001786:Blood Glucose; D002096:C-Peptide / Q000097:blood; D005260:Female; D005312:Fetal Blood / Q000378:metabolism; D006801:Humans; D007231:Infant, Newborn; D011247:Pregnancy; D012044:Regression Analysis; D012307:Risk Factors; D055815:Young Adult
chemical_list: D001786:Blood Glucose; D002096:C-Peptide