Prediction of gestational diabetes in pregnant women with BMI>30

  • Research type

    Research Study

  • Full title

    Development of first trimester biomarkers to better predict gestational diabetes in obese pregnant women.

  • IRAS ID

    245296

  • Contact name

    SS Huda

  • Contact email

    shahzya.huda@nhs.net

  • Sponsor organisation

    NHS Forth Valley

  • Duration of Study in the UK

    1 years, 0 months, 1 days

  • Research summary

    The rates of maternal obesity are alarmingly high: around 1 in 4 pregnant women in Scotland is obese. If you are obese you are 3-9 times more likely to develop diabetes in pregnancy (gestational diabetes or GDM) with associated pregnancy complications of high blood pressure, large babies, problems at birth including caesarean section and birth injury. Worryingly, diabetes in pregnancy has a long-term negative impact on offspring heart health and rates of obesity, extending into adolescence and early adulthood. Large trials have shown that identifying and even treating mild gestational diabetes can have a positive effect on pregnancy outcome.

    Although BMI is a low cost screening tool, it is not discriminatory and will only identify 1 in 3 women who will go on to develop pregnancy complications. This is partially attributable to the fact that BMI is a proxy marker of total body adiposity (fat) which cannot distinguish between individuals who store fat in subcutaneous fat tissue (SAT) stores in a healthy “benign” way (pears), and those individuals who store fat around abdominal organs or visceral fat tissue (VAT) stores (apples) which leads to abnormal blood fats or lipids, diabetes, inflammation and heart disease.

    We need a better more discriminatory screening tool to more effectively and efficiently target intervention in this high risk pregnant group.

    We plan to measure a hormone in the blood called adiponectin in the first trimester which has previously been shown to moderately good at predicting GDM together with a simple measure of visceral fat (VAT). This is achieved by the use of bioimpedence which provides a quick safe effective tool for estimating VAT. We will assess whether bioimpedence improves prediction of GDM over and above adiponectin alone with the ultimate aim to facilitate better stratification of high risk obese women who would benefit from increased intervention.

  • REC name

    London - Bloomsbury Research Ethics Committee

  • REC reference

    18/LO/1117

  • Date of REC Opinion

    27 Jun 2018

  • REC opinion

    Favourable Opinion