Children in the UK have poor health compared to other Western European countries, and there are large and increasing inequalities in child health, including for mental health and obesity. Over the last 20 years numerous reviews of evidence and policy have repeatedly emphasised the need to provide better support early in children’s lives if we are to have any chance of significantly reducing the inequalities in life chances experienced by people in the UK. The Due North report outlined two essential components that need to be in place to significantly influence child health inequalities at a population level. These included reducing social disadvantage and neighbourhood delivery of universal child health support with more intensive intervention for those who need it most, to break the link between social disadvantage and adverse outcomes. Giving every child the best start in life is a government priority, yet we currently lack validated measures to evaluate how health systems to support children at a neighbourhood level currently operate, are distributed and are changing over time.
To address these challenges, we propose a programme of work with a focus on harnessing data to evaluate systems-based approaches for improving children and young people’s (CYP) outcomes. We will assess the changing inputs and outputs for CYP health at a local level, in order to explain inequalities in child health outcomes. We aim to identify the components of local system-wide approaches that promote cost-effective, equitable local policies, practice and early interventions for child health. The focus of this proposed work is on developing a data platforms, methods and hard outcome measures to evaluate the effectiveness and equity of local public health systems for CYP. Consistent with the SPHR principles, the programme addresses a major public health challenge drawing on the expertise across the collaboration.
Linking to the other work packages in the CYP programme, this work package therefore aims to:
1. Identify areas that have better child health despite adverse trends in determinants such as child poverty.
2. Develop longitudinal datasets for use in evaluation of systems change, and natural experiments.
3. Develop key quality indicators of public health measures relevant to children.