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Early Antenatal Prediction of Gestational Diabetes in Obese Women: Development of Prediction Tools for Targeted Intervention

Lookup NU author(s): Professor Steve RobsonORCiD



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


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 15(+0)-18(+6) 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.

Publication metadata

Author(s): White SL, Lawlor DA, Briley AL, Godfrey KM, Nelson SM, Oteng-Ntim E, Robson SC, Sattar N, Seed PT, Vieira MC, Welsh P, Whitworth M, Poston L, Pasupathy D, UPBEAT Consortium

Publication type: Article

Publication status: Published

Journal: PLoS One

Year: 2016

Volume: 11

Issue: 12

Online publication date: 08/12/2016

Acceptance date: 16/11/2016

Date deposited: 01/02/2017

ISSN (electronic): 1932-6203

Publisher: Public Library of Science


DOI: 10.1371/journal.pone.0167846


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Funder referenceFunder name
Diabetes UK Sir George Alberti Research Training Fellowship
NIHR Biomedical Research Centre at Guy's and St Thomas' NHS Foundation Trust and King's College London
1060508Guys and St Thomas' Charity
CZB/A/680Chief Scientist Office Scottish Government Health Directorates (Edinburgh)
MR/L002477/1Medical Research Council UK
RP-PG-0407-10452UK's National Institute for Health Research
RP-PG-0407-10452UK's National Institute for Health Research
SC039280Tommy's Charity