Early antenatal prediction of gestational diabetes in obese women: Development of prediction tools for targeted intervention

Sara L. White, Debbie A. Lawlor, Annette L. Briley, Keith M. Godfrey, Scott M. Nelson, Eugene Oteng-Ntim, Stephen C. Robson, Naveed Sattar, Paul T. Seed, Matias C. Vieira, Paul Welsh, Melissa Whitworth, Lucilla Poston, Dharmintra Pasupathy, UPBEAT Consortium, Lucilla Poston, Andrew Shennan, Annette Briley, Claire Singh, Paul T. SeedJane Sandall, Thomas Sanders, Nashita Patel, Angela Flynn, Shirlene Badger, Suzanne Barr, Bridget Holmes, Louise Goff, Clare Hunt, Judy Filmer, Jeni Fetherstone, Laura Scholtz, Hayley Tarft, Anna Lucas, Tsigerada Tekletdadik, Deborah Ricketts, Carolyn Gill, Alex Seroge Ignatian, Catherine Boylen, Funso Adegoke, Elodie Lawley, James Butler, Rahat Maitland, Matias C. Vieira, Dharmintra Pasupathy, Eugene Oteng-Ntim, Nina Khazaezadeh, Jill Demilew, Sile O'Connor, Yvonne Evans, Susan O'Donnell, Ari De La Llera, Georgina Gutzwiller, Linda Hagg, Stephen C. Robson, Ruth Bell, Louise Hayes, Tarja Kinnunen, Catherine McParlin, Nicola Miller, Alison Kimber, Jill Riches, Carly Allen, Claire Boag, Fiona Campbell, Andrea Fenn, Sarah Ritson, Alison Rennie, Robin Durkin, Gayle Gills, Roger Carr, Scott Nelson, Naveed Sattar, Therese McSorley, Hilary Alba, Kirsteen Paterson, Janet Johnston, Suzanne Clements, Maxine Fernon, Savannah Bett, Laura Rooney, Sinead Miller, Paul Welsh, Lynn Cherry, Melissa K. Whitworth, Natalie Patterson, Sarah Lee, Rachel Grimshaw, Christine Hughes, Jay Brown, Kim Hinshaw, Gillian Campbell, Joanne Knight, Diane Farrar, Vicky Jones, Gillian Butterfield, Jennifer Syson, Jennifer Eadle, Dawn Wood, Merane Todd, Asma Khalil, Deborah Brown, Paola Fernandez, Emma Cousins, Melody Smith, Jane Wardle, Helen Croker, Laura Broomfield, Keith Godfrey, Sian Robinson, Sarah Canadine, Lynne Greenwood, Catherine Nelson-Piercy, Stephanie Amiel, Gail Goldberg, Daghni Rajasingham, Penny Jackson, Sara Kenyon, Patrick Catalano

Research output: Contribution to journalArticlepeer-review

30 Citations (Scopus)

Abstract

All obese women are categorised as being of equally high risk of gestational diabetes (GDM) whereas the majority do not develop the disorder. Lifestyle and pharmacological interventions in unselected obese pregnant women have been unsuccessful in preventing GDM. Our aim was to develop a prediction tool for early identification of obese women at high risk of GDM to facilitate targeted interventions in those most likely to benefit. Clinical and anthropometric data and non-fasting blood samples were obtained at 1518 weeks' gestation in 1303 obese pregnant women from UPBEAT, a randomised controlled trial of a behavioural intervention. Twenty one candidate biomarkers associated with insulin resistance, and a targeted nuclear magnetic resonance (NMR) metabolome were measured. Prediction models were constructed using stepwise logistic regression. Twenty six percent of women (n = 337) developed GDM (International Association of Diabetes and Pregnancy Study Groups criteria). A model based on clinical and anthropometric variables (age, previous GDM, family history of type 2 diabetes, systolic blood pressure, sum of skinfold thicknesses, waist:height and neck:thigh ratios) provided an area under the curve of 0.71 (95% CI 0.68-0.74). This increased to 0.77 (95%CI 0.73-0.80) with addition of candidate biomarkers (random glucose, haemoglobin A1c (HbA1c), fructosamine, adiponectin, sex hormone binding globulin, triglycerides), but was not improved by addition of NMR metabolites (0.77; 95%CI 0.74-0.81). Clinically translatable models for GDM prediction including readily measurable variables e.g. mid-arm circumference, age, systolic blood pressure, HbA1c and adiponectin are described. Using a ≥35% risk threshold, all models identified a group of high risk obese women of whom approximately 50% (positive predictive value) later developed GDM, with a negative predictive value of 80%. Tools for early pregnancy identification of obese women at risk of GDM are described which could enable targeted interventions for GDM prevention in women who will benefit the most.

Original languageEnglish
Article numbere0167846
Number of pages17
JournalPLoS One
Volume11
Issue number12
DOIs
Publication statusPublished - 8 Dec 2016
Externally publishedYes

Keywords

  • Gestational Diabetes
  • obese women
  • Targeted interventions
  • Randomised controlled trial
  • anthropometric measures

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