RT Journal Article
SR Electronic
T1 Study of How Adiposity in Pregnancy has an Effect on outcomeS (SHAPES): protocol for a prospective cohort study
JF BMJ Open
JO BMJ Open
FD British Medical Journal Publishing Group
SP e073545
DO 10.1136/bmjopen-2023-073545
VO 13
IS 9
A1 Heslehurst, Nicola
A1 Vinogradov, Raya
A1 Nguyen, Giang T
A1 Bigirumurame, Theophile
A1 Teare, Dawn
A1 Hayes, Louise
A1 Lennie, Susan C
A1 Murtha, Victoria
A1 Tothill, Rebecca
A1 Smith, Janine
A1 Allotey, John
A1 Vale, Luke
YR 2023
UL http://bmjopen.bmj.com/content/13/9/e073545.abstract
AB 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 researchTrial registration number ISRCTN82185177.