Title: Adiposity risk in pregnancy: identifying cost effective risk prediction measures that can be implemented at scale within NHS maternity services
Funder: Department of Health and Social Care

Abstract: Background: Half of pregnant women in England are overweight (BMI 25-29.9kg/m2) or obese (BMI30kg/m2). Guidelines use obese BMI to allocate high-risk antenatal care. However, 49% of obese women (~87,000/year) have uncomplicated pregnancies and don't require high-risk care, whereas 42% of overweight women (~103,000/year) develop complications despite not being judged as high-risk. This is little better than deciding risk by tossing a coin. Ineffective risk-prediction wastes NHS resources and harms women/offspring. Extensive research demonstrates BMI poorly predicts risk compared with adiposity measures of body-fat distribution. Prognostic risk-prediction improves outcomes and cost-effectiveness. Simple prognostic measures are more feasible to implement than complex multivariable prognostic models.Experts at the 2017 World Obesity Federation Obesity in Pregnancy Hot Topic Conference universally agreed the big unanswered question is how to predict risk. There is an urgent need to identify adiposity measures with greater sensitivity and specificity than BMI for targeted high-risk care to improve health of women/offspring and reduce NHS resource waste.Aim: To identify the prognostic performance of single-variable adiposity measures and multivariable models to predict which pregnant women require high-risk NHS maternity care, and cost-effectiveness of implementation at scale.WP1: Prognostic measure/model development (Years 1-2) Aim: to identify the prognostic performance of single-variable adiposity measures and multivariable models to estimate risk of adverse pregnancy outcomes.I carried out a systematic review which identified 58 studies reporting early-pregnancy adiposity measures (n=82,185 births). Individual patient data (IPD) meta-analysis will be used to develop and internally validate prognostic adiposity measures and models to predict maternal/offspring health outcomes. Analysis of prognostic performance will involve calibration, discrimination and internal validation.WP2: External validation (Years 2-4) Aim: to validate the prognostic performance of adiposity measures/models in a new population.Generalisability of prognostic measures/models requires evaluation in a new setting before use in clinical practice. Pregnant women (n=1,400) will be recruited from Newcastle NHS Trust to provide early-pregnancy adiposity measures. These will be linked to routine data on clinical outcomes. The prognostic measures/models from WP1 will be applied to the external population data to assess generalisability.WP3: Cost-effectiveness of implementation (Year 5) Aim: to determine the clinical cost-effectiveness of implementing the validated prognostic measures/models to target high-risk maternity care.Economic modelling will be used to estimate cost-effectiveness of using adiposity measures/models to predict risks. The model will describe the pathways of NHS care initiated based on predicted risk from WP2. Costs and consequences include measurement costs (adiposity measurement) and treatment costs (high-risk care). The output will be cumulative costs, probability of event occurring for each prognostic measure/model considered, and incremental cost per event avoided. Deterministic and probabilistic sensitivity analyses will explore the effect of uncertainty surrounding estimates of cost-effectiveness.Anticipated impact and dissemination NHS/patient impact: Scalable implementation of cost-effective risk stratification. Prevention of adverse outcomes for women/offspring. Reduction of resource waste. Career impact: support my transition to being a prominent research leader in my field. Dissemination/impact strategy target audiences: academia; health professionals/organisations; pregnant women/families; maternity managers/commissioners; national/international policy makers; public/media; third sector. Future research: HTA funding for implementation trial.

Lay abstract: Background: Current guidelines use body mass index (BMI) to predict which women have increased risk of developing pregnancy complications and require additional care. BMI is an inaccurate measure to predict risk and leads to many women receiving inappropriate care, makes health outcomes worse and wastes NHS resources.Being overweight (BMI between 25 and 29) or obese (BMI 30 or above) is associated with pregnancy complications including diabetes, preterm birth, and death of mother or baby. Guidelines recommend that obese women receive costly high-risk care including additional referrals, tests and closer monitoring. This is unnecessary for half of obese women who don't develop pregnancy complications, approximately 87,000 women/year in England. Almost half of overweight women do develop complications, approximately 103,000 women/year. Using obese BMI in guidelines wastes resources and increases anxiety for obese women inaccurately labelled as high-risk, and overlooks many overweight women who do require additional care.BMI does not assess where body fat is stored. When fat is stored in the upper-body there is an increased risk of developing certain diseases. Someone with a 'healthy' BMI who stores fat around their waist can have a higher risk than someone with obesity who stores fat on their hips. Alternative measures can identify where body fat is stored (e.g. waist size, ultrasound examination). These are called adiposity measures.Aim: This research will look at whether adiposity measures can predict which women will develop complications in pregnancy to help the NHS target care to women who really need it.Design and methods: Risk-prediction research is used to identify who is likely to develop complications before they occur. This research will explore whether adiposity measures are more accurate than BMI at predicting risk, either on their own (e.g. waist size) or combined with other measures (e.g. waist size plus ultrasound scan and mothers age). Combined measures are called models.This research has three stages:I will use existing data collected for other research studies to explore how useful different adiposity measures and models are at predicting which women develop pregnancy complications. This stage will involve combining the existing data and using statistical analysis to compare the accuracy of different adiposity measures and BMI at predicting which women develop pregnancy complications.I will collect data from pregnant women to test the results from stage 1 in a new population. Women will be invited to have adiposity and BMI measurements in early pregnancy. We will then wait until after pregnancy and link these measurements with the women's maternity records which have data on pregnancy outcomes. Statistical analysis will explore if results are similar to stage 1. I will compare the cost of using the measures in routine maternity care, with the benefits for improving health outcomes. This can help the NHS make decisions about which adiposity measures/models would be the best use of resources to improve the health outcomes for women and their babies. Patient and public involvement: Parents and pregnant women (including overweight and obese women) have been involved in the research development. They will continue to be involved in the research steering group and in regular coffee-morning discussions to develop information resources, inform the research methods (e.g. recruitment) and develop the dissemination strategy.Dissemination: The purpose of the research is to improve NHS maternity care, health outcomes, and reduce resource waste. Target audiences for dissemination include pregnant women and their families, public, health professionals, maternity managers, policy makers, charities and researchers. Dissemination will be appropriate to target audiences (e.g. policy briefs for policy makers, media/social-media coverage for public, journals and conferences for researchers). Future research funding will explore how to improve maternity care.

Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: REPRODUCTIVE HEALTH AND CHILDBIRTH