Child health in the UK is getting worse, and the gap between rich and poor children is widening—yet policymakers lack the hard evidence needed to fix it. This research builds a large-scale data platform to answer a practical question: which combinations of welfare, education, and public health policies will actually reduce child health inequalities, and how quickly will the savings arrive? Current policies are failing because they are not tested against real-world causal pathways—for example, how poor parental mental health or low family income drives worse outcomes in children’s own mental health. The project links population datasets from Denmark, Wales, northwest England, and across Europe to simulate trials of policies that have not yet been tried, and to calculate the return on investment over different time horizons. If successful, the work will give national and local decision-makers—including the NHS, the WHO, and UNICEF—a rigorous, costed menu of policy options. Instead of guessing which interventions work, governments could know, for example, whether investing in early childhood support saves more money in teenage mental health services than a later school-based programme. The platform itself will remain as a reusable tool for future policy evaluation, turning child health inequality from a political talking point into a measurable, solvable problem.
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Background Addressing health inequalities and improving child health are UK government priorities, but current policies are failing. The UK continues to slip down international rankings for child health in high-income countries. Large and persistent health inequalities, increasing pre-COVID-19, have worsened during the pandemic. Of particular concern are rising mental health problems amongst children and young people. Successful strategies to mitigate these harms will require combinations of public health, welfare, and education interventions. Yet there is insufficient evidence to inform crucial real-world policy changes that can work for all children, equitably. Critical evidence gaps include understanding the best times and targets for policies; which combination of policies will be most cost-effective in a financially constrained system; and the time horizons over which benefits and cost savings will accrue. Research aims: To develop an interventional epidemiology platform to address these evidence gaps. To translate this evidence into policy and practice, informing whole systems change to reduce socioeconomic inequalities in child health. Research questions To what extent do key exposures, for example poor parental mental health and low family income, mediate the association between parental disadvantage and important child health outcomes such as mental health? To what extent do interventions that target these causal pathways from parental disadvantage to child health outcomes improve child health and reduce inequalities? In the context of finite resources, how and when in the life-course should resources be allocated across these causal pathways to reduce inequalities in health, and what are the likely time horizons over which benefits and cost savings will accrue? What are the best ways to embed this evidence into practice sustainably? Methods 1) Causal mediation analysis in longitudinal data; 2) Simulation of trials of interventions and natural policy experiments; 3) Economic evaluation. Work package (WP) 1 will link world leading datasets and cohorts capturing population level data across Europe to develop an agile, efficient research platform for policy evaluation. These include the DANLIFE whole population linked datasets in Denmark (DANLIFE), Wales (SAIL) and NW England (CIPHA), and the EU Child Cohort Network of population based prospective cohort studies. WP2 will assess causal pathways to inequalities in child health and model the effect of different policy scenarios on inequalities in health at the population level, with an initial focus on child mental health. In WP3, I will collaborate with leading economists to apply a dynamic microsimulation model for childhood policy analysis to assess timescales for the return on investment of policies to address child health inequalities. WP4 will translate evidence into policy and practice transformation internationally, working with policymakers and children, young people and families. Anticipated impact and dissemination Scientifically robust evidence to drive more effective policies will generate significant population health, economic and social impacts. Working with the WHO, UNICEF and national/local decision-makers, including the Cheshire and Merseyside Integrated Care System, this evidence will be used to design and implement better policies for children. Inequalities are an international problem; solutions will be globally relevant.
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