Multimorbidity is the presence of multiple long-term health conditions. People with multimorbidity tend to have worse quality of life, and to be high users of the health service. Mental-physical multimorbidity (MPMM) is a specific form of multimorbidity, typically defined as the presence of at least one mental health condition and at least one physical health condition. People who experience MPMM have more complex health needs than people with only physical health problems or only mental health problems. Each set of health problems may make the challenges of the other set worse, leading to worse quality of life for these patients. Poverty and other measures of deprivation are strongly linked to MPMM, making it a key driver of health inequality.

Research on MPMM is limited, but most studies that do exist focus on adults. However, data from primary care records suggest that 2.5% of 10-19 year olds and 11.1% of 20-29 year olds have MPMM. The true level of MPMM in children and young people will be much higher than this, as many health conditions, particularly mental health conditions, are poorly recorded in health records. Children and young people who already have MPMM are likely to go on to experience complex health needs across their life course, and represent a challenging group for the health service. Understanding who comprises this group, and the determinants and consequences (both for the health service and for the young people themselves) is crucial to identify potential intervention points to reduce the incidence of MPMM and to mitigate its adverse consequences.

In this project, we use birth-cohort data from three studies in the UK and Brazil to explore how and when MPMM occurs in children and young people, estimating the prevalence of overall MPMM and of specific combinations of health conditions. We will also examine the causal determinants of MPMM, and the consequences for young people (including education, employment, pain, health-risk behaviours, and wellbeing) and the health service. Studying both causes and consequences will allow us to reach conclusions about potential intervention targets both for preventing MPMM and for mitigating its adverse effects, and to quantify the potential gains from interventions to prevent MPMM or supporting young people with MPMM. Using data from both a high income country and a middle income country allows us to explore setting-specific patterns, causes, and consequences of MPMM – essential for understanding how tailored interventions must be to the local setting. Using birth cohort data allows us to circumvent the problems of under ascertainment of health conditions in administrative health records; linked health data in the UK cohorts will allow us to quantify this problem.