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Study of How Adiposity in Pregnancy has an Effect on outcomeS (SHAPES): protocol for a prospective cohort study

Lookup NU author(s): Dr Nicola HeslehurstORCiD, Raya Vinogradov, Dr Gina NguyenORCiD, Dr Theophile Bigirumurame, Dr Louise HayesORCiD, Susan Lennie, vicky Murtha, Rebecca Tothill, Dr Janine Smith, Professor Luke ValeORCiD



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


© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. INTRODUCTION: Maternal obesity increases the risk of multiple maternal and infant pregnancy complications, such as gestational diabetes and pre-eclampsia. Current UK guidelines use body mass index (BMI) to identify which women require additional care due to increased risk of complications. However, BMI may not accurately predict which women will develop complications during pregnancy as it does not determine amount and distribution of adipose tissue. Some adiposity measures (eg, waist circumference, ultrasound measures of abdominal visceral fat) can better identify where body fat is stored, which may be useful in predicting those women who need additional care. METHODS AND ANALYSIS: This prospective cohort study (SHAPES, Study of How Adiposity in Pregnancy has an Effect on outcomeS) aims to evaluate the prognostic performance of adiposity measures (either alone or in combination with other adiposity, sociodemographic or clinical measures) to estimate risk of adverse pregnancy outcomes. Pregnant women (n=1400) will be recruited at their first trimester ultrasound scan (11+2-14+1 weeks') at Newcastle upon Tyne National Health Service Foundation Trust, UK. Early pregnancy adiposity measures and clinical and sociodemographic data will be collected. Routine data on maternal and infant pregnancy outcomes will be collected from routine hospital records. Regression methods will be used to compare the different adiposity measures with BMI in terms of their ability to predict pregnancy complications. If no individual measure performs better than BMI, multivariable models will be developed and evaluated to identify the most parsimonious model. The apparent performance of the developed model will be summarised using calibration, discrimination and internal validation analyses. ETHICS AND DISSEMINATION: Ethical favourable opinion has been obtained from the North East: Newcastle & North Tyneside 1 Research Ethics Committee (REC reference: 22/NE/0035). All participants provide informed consent to take part in SHAPES. Planned dissemination includes peer-reviewed publications and additional dissemination appropriate to target audiences, including policy briefs for policymakers, media/social-media coverage for public and conferences for research TRIAL REGISTRATION NUMBER: ISRCTN82185177.

Publication metadata

Author(s): Heslehurst N, Vinogradov R, Nguyen GT, Bigirumurame T, Teare D, Hayes L, Lennie SC, Murtha V, Tothill R, Smith J, Allotey J, Vale L

Publication type: Article

Publication status: Published

Journal: BMJ Open

Year: 2023

Volume: 13

Issue: 9

Online publication date: 12/09/2023

Acceptance date: 17/08/2023

Date deposited: 28/09/2023

ISSN (print): 2044-6055

ISSN (electronic): 2044-6055

Publisher: BMJ Publishing Group


DOI: 10.1136/bmjopen-2023-073545

PubMed id: 37699635


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Funder referenceFunder name
CDF-2018-11-ST2-011National Institute for Health Research (NIHR)
NIHR Applied Research Collaboration North East and North Cumbria