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.

Research suggests that children with autistic symptoms have an increased risk of experiencing symptoms of eating disorders in adolescence. However, it is still not clear which experiences lead to this increased risk. Previous studies have shown that autistic children are more likely to be bullied and have symptoms of depression. These are also plausible risk factors for eating disorders and could be addressed by interventions, but no research has investigated these pathways yet.

This analysis will examine the gambling behaviour of participants at age 30, including online gambling, betting on esports and using cryptocurrency to gamble. It will compare the findings at age 30 with previous data on gambling collected at ages 17, 20, 24 and 28 to provide a rich longitudinal picture of gambling activity among young people.

This project aims to assess the association between DNA methylation and breastfeeding using data from ALSPAC and other birth cohorts with similar data. Breastfeeding has both short and long term beneficial effects on child health. DNA methylation is a molecular mechanism which might mediate the relationship between breast feeding and beneficial health effects in children but we do not yet have good evidence to show if DNA methylation is associated with breast feeding. This research aims to answer this knowledge gap.

Exposure to air pollution has been associated with poorer cardiovascular health and cardiovascular disease, and inflammation is one of the postulated mechanisms of this relationship. Most studies have investigated the association between air pollution and inflammation using C-reactive protein (CRP), particularly in adulthood. Evidence in younger ages and using other inflammatory markers is limited. This study will explore the association between air pollution and inflammation from childhood to early adulthood using different inflammatory markers.

The Avon Longitudinal Study of Parents and Children (ALSPAC) is a prospective birth cohort, based in and around Bristol, UK. Maintaining data security and participant anonymity and confidentiality are key principles for the study, hence why data access is restricted to bona fide researchers and ALSPAC data are not openly available. Despite these valid reason for restricting data availability, this position is somewhat in conflict with emerging best scientific practices, which encourage making data openly available to facilitate reproducible and replicable open scientific research.

Given the rich nature of the resource, ALSPAC data may also be valuable as a educational tool, such as for teaching methods such as longitudinal modelling or approaches to modelling missing data. To aid these efforts, we want to assess methods for generating and making openly-available synthesised ALSPAC data; these synthesised datasets are modelled on the original ALSPAC data, thus maintaining variable distributions and relations among variables, while at the same time preserving participant anonymity and confidentiality. We will explore how data can be synthesised using the ‘synthpop’ package in the R statistical programming language, and aim to present a list of guidelines which all researchers wishing to release such synthesised ALSPAC data must follow.

Crime in adulthood is a well-established long-term consequence of childhood adversity, but the exact mechanism underlying this process is not well known. One mechanism suggested by research is that childhood adversity results in impaired neurobiology, emotional and executive functioning, and self-regulation. Disrupted emotional processing is linked to behavioural problems such as conduct disorders due to an impaired ability to recognise certain emotions, namely anger and fear, with the latter being linked to increased violence. Impaired executive functioning is hypothesized to lead to decreased inhibitory control and cognitive flexibility, while disrupted self-regulation is linked to increased aggressiveness due to an inability to regulate one’s thoughts, actions, and emotions. These deficiencies and their outcomes have been linked to crime, especially violent crime. However, other factors such as genetics, socioeconomic status and alcohol use can increase the likelihood of experiencing additional adversity while also influencing the nature and extent of these impairments. The resulting differences in cognitive and emotional impairments may result in different types of crimes being committed. We hope that better understanding of the processes mediating adverse childhood experiences (ACEs) in children and crime in adulthood can inform more precise therapy employed by clinicians treating these ACEs, as well as more cost-effective measures for policymakers to target the effects of these ACEs in vulnerable populations.

This project aims to understand growth during and after a pregnancy in which the placenta is faulty and less able to nourish the fetus, and its impact on the key developmental brain function of sleep, via mathematical modelling.

Growth is a crucial part of healthy development. So, it is important to understand what happens when growth is impaired. In some pregnancies, the placenta cannot transfer as much oxygen and sugar to the fetus as required. To deal with this, the fetus prioritises its most important organ - the brain - and directs most oxygen and sugar there. This results in the size of the brain relative to the body being larger than usual.

Sleep is a key developmental brain function, supporting the formation of memories. This is why babies spend up to 97% of their time asleep. Because sleep occurs to help our brain but also the rest of our body, the size of the brain relative to the body explains for how long we need to sleep. We believe that the brain growing too large relative to the body may disorganise sleep, and make it less good at helping to form memories. This could explain why infants who grow like this sometimes have later learning difficulties.

In this project, we are going to collate and collect data which will allow us to mathematically test our theory that faulty growth impairs sleep. The results will help to understand this condition better, and could suggest new ideas for personalised therapies, e.g. that strengthen sleep.

Previous research has found partial evidence for a role of personality traits in mental health outcomes. However, many of these studies do not examine all of the big 5 personality traits simultaneously, examine mental health generally, or a small number of mental health symptoms. These studies also tend to examine participants cross-sectionally, without examining the way in which personality traits may influence mental health longitudinally, after controlling for confounders. This study aims to overcome the previous patchwork coverage of this topic by combining a range of exposure and outcome variables in a prospective cohort study.