Embedding the MapMe intervention into the English National Child Measurement Programme: a within-trial cost utility analysis - Tomos Robinson; Sedighe Hosseini Jebeli; João Paulo de Aguiar Greca; Letitia Sermin-Reed; Maddey Patterson; Angela R Jones; Laura Basterfield; Lorraine McSweeney; Vera Araújo Soares; Elizabeth H Evans; Alison Gahagan; Mohadeseh Shojaei Shahrokhabadi; et al. (Health Economics Review, 2026)
Abstract Childhood obesity is a major health concern and a public health priority. Parents play a key role in addressing childhood obesity, and one possible solution could be directly informing parents about their child’s weight status, encouraging them to change behaviour. The MapMe intervention has been developed as a tool to improve parental acknowledgement and understanding of childhood obesity. A three-arm cluster randomised trial was delivered within England’s mandatory National Child Measurement Programme as part of the MapMe2 study. Building on the original MapMe trial, it assessed the effect of two versions MapMe intervention on weight in children aged 4–5 and 10–11 years. The aim of this study was to conduct a within-trial cost-utility analysis (CUA) using the MapMe2 trial data to estimate the potential cost-effectiveness of two versions of the MapMe intervention (a ‘Web Only’ version and a ‘Web Boost’ version) compared to a control group. The CUA was carried out from an NHS perspective over a one-year time horizon. In the base case, the primary outcome was child health-related quality of life measured by the CHU-9D. The inclusion of out-of-pocket costs and an alternative measure of health-related quality of life (the WAItE) were conducted as sensitivity analyses. Results were expressed as incremental cost per Quality Adjusted Life Year (QALY) gained. The results indicated that the ‘Web Only’ and ‘Web Boost’ intervention versions were more likely to be cost-effective than the control. This conclusion held true even when including parental out-of-pocket expenses for weight management and physical activity, and when using a condition-specific health-related quality of life measure. However, given the small sample size in the sub-study, the results from this study should be treated with a high degree of caution. Future analysis should focus on estimating the cost-effectiveness of public health interventions such as MapMe over a longer time horizon, given that full costs and benefits are unlikely to be captured in the short time frame of trials such as MapMe2.