Title: Tackling child health inequality. An interventional epidemiology platform to inform policy
Funder: Department of Health and Social Care

Abstract: 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 disseminationScientifically 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.

Lay abstract: My professorship aims to bring together data to evaluate the effects of interventions and policies to help reduce child health inequalities in the UK and to inform policy decisions internationally.The UK lags behind other wealthy countries in child health and continues to slip down international rankings. We now have the highest death rate in children under five in western Europe. Poor children are faring particularly badly. A child born in the most disadvantaged tenth of areas of the UK can expect to live around a decade less that a child born in the most advantaged tenth. The difference increases to almost two decades when we consider years lived in good health. These socioeconomic health inequalities are increasing and have been made worse by the pandemic. Of particular concern are rising inequalities in mental health problems amongst children, which have increased dramatically. I have shown how inequalities in childhood go on to influence adult health and risk of death, driving unsustainable pressures on care systems.Tackling such inequalities in child health has been a priority for the UK in recent decades. Crucial to this endeavour is an understanding of drivers of inequalities. Health outcomes for poor children in rich countries depend on a wide range of national policies that influence their development. It is imperative that such policies are evaluated for their health inequalities impacts. This rationale underpins my programme of work. This research seeks to undertake international comparisons to provide a detailed understanding of why children from more disadvantaged backgrounds have worse health, and how policies and interventions work, for whom, and under what circumstances, so informing real-world policy change that will improve health in childhood and in later life. My proposal focuses on child mental health, but will also address inequalities in other important conditions in childhood, including obesity and asthma. I will involve children and young people throughout, empowering them to use research evidence to influence policy for reducing inequalities. I will bring together a rich set of international data sources - some of the largest datasets in the world that follow children over the course of their lives, such as the LifeCycle EU Child Cohort Network, DANLIFE, CIPHA and SAIL. The LifeCycle Consortium has harmonized data on studies across Europe that follow up children from birth, covering more than 250,000 children and their parents. DANLIFE covers the whole Danish population from birth into mid-adulthood, arguably the richest data source in the world for studying the impact of childhood adversity on later health. SAIL is a comparable data source for the population of children in Wales.Using these international datasets, I will quantify the main causes and consequences of inequalities in child health, assessing the extent to which policies that target causal pathways - such as poverty or risk factor reduction - improve child health and reduce inequalities. For example, I will assess how the clustering of poverty and parental mental health problems influences children's mental health, and evaluate the impact of intervening to reduce poverty and improve parental mental health. I will use the findings of these large-scale evaluations to develop new approaches to ensuring that children and their families receive the right support at the right time, testing these approaches in a UK context.I will work with leading health economists to deploy this evidence to inform better decision-making around the funding and prioritisation of services for children. I will work with the World Health Organisation, UNICEF and national decision-makers in the UK to design and implement better policies for children. Child health inequalities are common internationally, so the work will have global impact.

Research activity codes: 1.2 PSYCHOLOGICAL AND SOCIOECONOMIC PROCESSES;8.3 POLICY, ETHICS AND RESEARCH GOVERNANCE
Health categories: GENERIC HEALTH RELEVANCE