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. Seed; Jane 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

doi:10.1371/journal.pone.0167846

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

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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 language	English
Article number	e0167846
Number of pages	17
Journal	PLoS One
Volume	11
Issue number	12
DOIs	https://doi.org/10.1371/journal.pone.0167846
Publication status	Published - 8 Dec 2016
Externally published	Yes

Keywords

Gestational Diabetes
obese women
Targeted interventions
Randomised controlled trial
anthropometric measures

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1371/journal.pone.0167846Licence: CC BY

Published versionFinal published version, 1.02 MBLicence: CC BY

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White, S. L., Lawlor, D. A., Briley, A. L., Godfrey, K. M., Nelson, S. M., Oteng-Ntim, E., Robson, S. C., Sattar, N., Seed, P. T., Vieira, M. C., Welsh, P., Whitworth, M., Poston, L., Pasupathy, D., UPBEAT Consortium, Poston, L., Shennan, A., Briley, A., Singh, C., ... Catalano, P. (2016). Early antenatal prediction of gestational diabetes in obese women: Development of prediction tools for targeted intervention. PLoS One, 11(12), Article e0167846. https://doi.org/10.1371/journal.pone.0167846

@article{52164fab8b27410c9e7499ad3631900b,

title = "Early antenatal prediction of gestational diabetes in obese women: Development of prediction tools for targeted intervention",

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.",

keywords = "Gestational Diabetes, obese women, Targeted interventions, Randomised controlled trial, anthropometric measures",

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

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doi = "10.1371/journal.pone.0167846",

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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, Poston, L, Shennan, A, Briley, A, Singh, C, Seed, PT, Sandall, J, Sanders, T, Patel, N, Flynn, A, Badger, S, Barr, S, Holmes, B, Goff, L, Hunt, C, Filmer, J, Fetherstone, J, Scholtz, L, Tarft, H, Lucas, A, Tekletdadik, T, Ricketts, D, Gill, C, Ignatian, AS, Boylen, C, Adegoke, F, Lawley, E, Butler, J, Maitland, R, Vieira, MC, Pasupathy, D, Oteng-Ntim, E, Khazaezadeh, N, Demilew, J, O'Connor, S, Evans, Y, O'Donnell, S, De La Llera, A, Gutzwiller, G, Hagg, L, Robson, SC, Bell, R, Hayes, L, Kinnunen, T, McParlin, C, Miller, N, Kimber, A, Riches, J, Allen, C, Boag, C, Campbell, F, Fenn, A, Ritson, S, Rennie, A, Durkin, R, Gills, G, Carr, R, Nelson, S, Sattar, N, McSorley, T, Alba, H, Paterson, K, Johnston, J, Clements, S, Fernon, M, Bett, S, Rooney, L, Miller, S, Welsh, P, Cherry, L, Whitworth, MK, Patterson, N, Lee, S, Grimshaw, R, Hughes, C, Brown, J, Hinshaw, K, Campbell, G, Knight, J, Farrar, D, Jones, V, Butterfield, G, Syson, J, Eadle, J, Wood, D, Todd, M, Khalil, A, Brown, D, Fernandez, P, Cousins, E, Smith, M, Wardle, J, Croker, H, Broomfield, L, Godfrey, K, Robinson, S, Canadine, S, Greenwood, L, Nelson-Piercy, C, Amiel, S, Goldberg, G, Rajasingham, D, Jackson, P, Kenyon, S & Catalano, P 2016, 'Early antenatal prediction of gestational diabetes in obese women: Development of prediction tools for targeted intervention', PLoS One, vol. 11, no. 12, e0167846. https://doi.org/10.1371/journal.pone.0167846

TY - JOUR

T1 - Early antenatal prediction of gestational diabetes in obese women

T2 - Development of prediction tools for targeted intervention

AU - White, Sara L.

AU - Lawlor, Debbie A.

AU - Briley, Annette L.

AU - Godfrey, Keith M.

AU - Nelson, Scott M.

AU - Oteng-Ntim, Eugene

AU - Robson, Stephen C.

AU - Sattar, Naveed

AU - Seed, Paul T.

AU - Vieira, Matias C.

AU - Welsh, Paul

AU - Whitworth, Melissa

AU - Poston, Lucilla

AU - Pasupathy, Dharmintra

AU - UPBEAT Consortium

AU - Poston, Lucilla

AU - Shennan, Andrew

AU - Briley, Annette

AU - Singh, Claire

AU - Seed, Paul T.

AU - Sandall, Jane

AU - Sanders, Thomas

AU - Patel, Nashita

AU - Flynn, Angela

AU - Badger, Shirlene

AU - Barr, Suzanne

AU - Holmes, Bridget

AU - Goff, Louise

AU - Hunt, Clare

AU - Filmer, Judy

AU - Fetherstone, Jeni

AU - Scholtz, Laura

AU - Tarft, Hayley

AU - Lucas, Anna

AU - Tekletdadik, Tsigerada

AU - Ricketts, Deborah

AU - Gill, Carolyn

AU - Ignatian, Alex Seroge

AU - Boylen, Catherine

AU - Adegoke, Funso

AU - Lawley, Elodie

AU - Butler, James

AU - Maitland, Rahat

AU - Vieira, Matias C.

AU - Pasupathy, Dharmintra

AU - Oteng-Ntim, Eugene

AU - Khazaezadeh, Nina

AU - Demilew, Jill

AU - O'Connor, Sile

AU - Evans, Yvonne

AU - O'Donnell, Susan

AU - De La Llera, Ari

AU - Gutzwiller, Georgina

AU - Hagg, Linda

AU - Robson, Stephen C.

AU - Bell, Ruth

AU - Hayes, Louise

AU - Kinnunen, Tarja

AU - McParlin, Catherine

AU - Miller, Nicola

AU - Kimber, Alison

AU - Riches, Jill

AU - Allen, Carly

AU - Boag, Claire

AU - Campbell, Fiona

AU - Fenn, Andrea

AU - Ritson, Sarah

AU - Rennie, Alison

AU - Durkin, Robin

AU - Gills, Gayle

AU - Carr, Roger

AU - Nelson, Scott

AU - Sattar, Naveed

AU - McSorley, Therese

AU - Alba, Hilary

AU - Paterson, Kirsteen

AU - Johnston, Janet

AU - Clements, Suzanne

AU - Fernon, Maxine

AU - Bett, Savannah

AU - Rooney, Laura

AU - Miller, Sinead

AU - Welsh, Paul

AU - Cherry, Lynn

AU - Whitworth, Melissa K.

AU - Patterson, Natalie

AU - Lee, Sarah

AU - Grimshaw, Rachel

AU - Hughes, Christine

AU - Brown, Jay

AU - Hinshaw, Kim

AU - Campbell, Gillian

AU - Knight, Joanne

AU - Farrar, Diane

AU - Jones, Vicky

AU - Butterfield, Gillian

AU - Syson, Jennifer

AU - Eadle, Jennifer

AU - Wood, Dawn

AU - Todd, Merane

AU - Khalil, Asma

AU - Brown, Deborah

AU - Fernandez, Paola

AU - Cousins, Emma

AU - Smith, Melody

AU - Wardle, Jane

AU - Croker, Helen

AU - Broomfield, Laura

AU - Godfrey, Keith

AU - Robinson, Sian

AU - Canadine, Sarah

AU - Greenwood, Lynne

AU - Nelson-Piercy, Catherine

AU - Amiel, Stephanie

AU - Goldberg, Gail

AU - Rajasingham, Daghni

AU - Jackson, Penny

AU - Kenyon, Sara

AU - Catalano, Patrick

PY - 2016/12/8

Y1 - 2016/12/8

N2 - 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.

AB - 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.

KW - Gestational Diabetes

KW - obese women

KW - Targeted interventions

KW - Randomised controlled trial

KW - anthropometric measures

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U2 - 10.1371/journal.pone.0167846

DO - 10.1371/journal.pone.0167846

M3 - Article

C2 - 27930697

AN - SCOPUS:85002679571

SN - 1932-6203

VL - 11

JO - PLoS One

JF - PLoS One

IS - 12

M1 - e0167846

ER -

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

Abstract

Keywords

UN SDGs

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