An individual participant data meta-analysis of going-to-sleep position and risk of late pregnancy stillbirth

Duration: Two years

Leader: Professor Lesley McCowan

Team: Professor Edwin Mitchell; Associate Professor John Thompson; Associate Professor Lisa Askie; Dr Adrienne Gordon; Dr Camille Raynes-Greenow; Dr Alexander Heazell; Dr Tomasina Stacey; Dr Minglan Li; Victoria Bowring

Institute: University of Auckland

This project is co-funded by Red Nose (Australia) and Cure Kids (New Zealand).

Late stillbirth (the death of a baby in the womb after 28 weeks of pregnancy) is a tragic loss with long term effects for families. It affects 2.5 – 3 per 1,000 pregnant women in Australia and New Zealand each year, or the annual loss of approximately 1,000 babies. Identification of modifiable risk factors for stillbirth has potential to significantly reduce these unexpected deaths. Four published studies of risk factors for stillbirth have reported that when women in the last 3 months of pregnancy go to sleep lying on their back, there is a 2.5 – 6 fold increase in the risk of late stillbirth.

Maternal going to sleep position is a risk factor that could be changed. There is an urgent need, therefore, to assess the combined evidence from these studies to inform public health messages for pregnant women and health professionals regarding going to sleep position. In particular, there is a need for further detailed information as to whether right sided going to sleep position is a risk factor and whether there are groups of women (e.g. those who smoke, carry excess weight or have babies who are small) who are at elevated risk.

This project will combine the individual data from the existing case-control studies (two New Zealand, one Australian and one UK study identified to date) that have included information about maternal sleep practices and stillbirth risk. Individual participant data meta-analysis is a specialised statistical technique to combine information from separate studies to allow greater power to answer the main question as well as the ability to look in closer detail at how risk factors may interact with each other.

This Trans-Tasman collaboration will enable cost-effective use of existing data to create high quality evidence on which to base appropriate educational messages that are likely to reduce late stillbirth.