Recommendations for future research
Synthesis of patient level data by individual patient data meta-analysis is needed to assess any differential effect of the benefits observed with interventions in various groups based on BMI, age, ethnicity, socioeconomic status, parity, and risk status in pregnancy. Availability of the raw data will substantially increase the power to detect baseline factors that truly modify the intervention effect98 and will enable intervention effects to be quantified for clinically relevant groups.99 In addition, individual patient data meta-analysis will be able to assess whether the improvement in clinical outcomes is related to reduction in gestational weight gain alone or if there is any added benefit from the type of intervention resulting in weight change. It will also allow the magnitude of benefit from weight change in pregnancy to be quantified for both the mother and baby. This will allow us to implement those weight management interventions that show clear benefit with specific weight gain targets in pregnancy. This approach will also provide adequate power to generate valid, reliable answers and to populate the model for decision analytic modelling for health economic evaluation. The paucity of descriptive information on the intensity and duration of intervention, means of provision, and patient compliance are factors that could potentially facilitate or hinder implementation. These gaps identify issues for further research. There is a need for good quality large prospective studies for the important clinical outcomes identified including long term effects on the mother and fetus.