Psychotic experiences, such as hallucinations or delusions, are associated with numerous negative health outcomes. Previous work suggests a potential relationship between psychotic experiences and religious beliefs and behaviours, which may moderate or mediate associations between psychotic experiences and negative health outcomes, yet findings are contradictory and high-quality studies are rare. We therefore plan to use ALSPAC data to explore these relationships in more detail.

Led by Universities of Bristol, Edinburgh and University College London, and in collaboration with academic, industry and government partners from across the UK, the Centre aims to dramatically improve understanding of health and wellbeing by revolutionising how researchers can use and access data.

The rise of the internet and digital technologies such as mobile phones and wearable technology like smart watches over the last few decades has meant that more data than ever before has been collected about us. This data can reveal important information about who we are and what we do. These types of data are called Smart Data. Historically, much of the data used by researchers into how our actions and behaviours might affect our health and wellbeing has been collected through studies called Longitudinal Population Studies (LPSs). These studies typically run for many decades, and follow the same individuals through the course of their lives which can show how behaviours and health change over a long period of time. The methods for collecting information in LPSs do not normally use Smart Data, and most major studies of this type began before it was available. Both Smart Data and LPS data can provide different types of vital information about how our actions can affect our health, but these two types of data are not often joined up. Our Centre aims to integrate Smart Data into LPSs and will enable researchers to understand and answer questions about health and wellbeing that were previously unattainable through separate efforts.

The Centre will support bringing together Smart Data derived from our everyday interactions with digital services—such as shopping records, wearable sensors, environmental data, banking, and apps—together with the rich Longitudinal Population Studies’ data linked to health and other administrative data in the UK Longitudinal Linkage Collaboration (UK LLC) Trusted Research Environment, supporting cutting edge research for public good. Our ultimate objective is to seamlessly integrate Smart Data into the UK's Longitudinal Population Studies (LPS, or Studies) and make it available to researchers with other key datasets, thereby establishing a pioneering Centre for Longitudinal Smart Data. Through this innovative approach, we will create a platform that will allow scientists to uncover fresh perspectives on lifelong health and wellbeing, enriching our comprehension of people’s health, behaviours and how they change over time. This novel approach holds the potential to transform how we understand and address societal and health challenges.

Our initiative tackles various challenges concerning participant acceptance, ethical considerations, legal frameworks, and beyond. With participants' consent as a cornerstone, the Centre for Longitudinal Smart Data is designed to offer secure access to a diverse range of research-ready Smart Data for authorised researchers. Through close collaboration with study participant advisory groups, we ensure that the use of Smart Data aligns with the preferences and priorities of the participants themselves. This approach prioritises transparency, accountability, and respect for individual choices, fostering a culture of responsible data usage and research ethics.

The Centre establishes a Community of Practice, bringing together experts to tackle the hurdles linked to individual-level Smart Data within the UK's Longitudinal Population Studies. It will strive to foster opportunities for studies across various domains, including wellbeing, health, sustainability, productivity, and digital society.

The fetal and developmental origins of disease hypothesis suggests that pre-conception (maternal and paternal) and intrauterine (maternal) prenatal factors can influence postnatal health, including growth and adiposity. Birth weight is a marker of intrauterine growth and has been associated with risk of overweight and obesity, as have preterm birth, and small and large for gestational age. To the best of our knowledge, no study has investigated the association between continuous birthweight (for gestational age) centiles beyond the traditional thresholds for small or large for gestational age and longitudinal growth throughout infancy and childhood. This study will address this evidence gap.

Infertility affects 1 in 6 couples. With increasing numbers of assisted reproductive technology (ART) conceptions, understanding the effects of ART on maternal and offspring health has been designated a major research priority. Research to date has been highlighted as having limited quality and lacking methodological transparency. In ART-HEALTH we use a robust, systematic approach of triangulating different sources of evidence to address this.

We try to understand intergenerational inequalities in education. Unraveling the process of human capital transmission over generations is fundamental to uncover the sources of inequality. Understanding the sources of inequality in turn is crucial to design and justify redistribution policies.

The process of human capital transmission is a widely researched topic in economics and social sciences. Given that parents transmit their genes to their children and expose these children to a particular environment at the same time, it is incredibly challenging to disentangle the pathways through which human capital transmission takes place. With the recent advances of social science genetics we can now have a direct measure of one’s genetic predisposition for a certain trait. In particular, we want to exploit the fact that ALSPAC contains a) genetic information on the child’s mother and father; b) detailed information on educational achievement of the child and parents; c) detailed information of the parental and peer behavior towards the child; c) educational aspirations and social network data.

Jointly, we hope to answer the question to what extent intergenerational inequality is due to genetic transmission, and environmental transmission including the educational aspirations of parents, children and their peers.

Developing good self-regulation skills is one of the most important tasks for a child to accomplish. Earliest signs of difficulties in self-regulation include excessive crying, sleeping, or feeding difficulties, which are labelled as ‘regulatory problems’. Increasing evidence has shown that regulatory problems in infancy/toddlerhood increase the risk of several negative outcomes such as attention problems, emotional and behavioral dysregulation in childhood, and depressive symptoms in adolescence. However, it remains unknown if regulatory problems in infancy/toddlerhood are also associated with adverse health and social outcomes in adolescence.

The current study aims to investigate whether regulatory problems in infancy/toddlerhood increase the risk of following adverse a) health outcomes in adolescence: harmful drinking, smoking, cannabis use, illicit drug use, problem gambling, unwanted pregnancy, obesity, excessive screen time, and self-harm at 18 years, and b) social outcomes in adolescence: getting into trouble with police, not being in education, employment or training (NEET), low peer social support, low closeness in romantic relationships and relationship with parents.

Multimorbidity (MM) happens when two or more different diseases are present at the same time in an individual. This is common between physical and psychiatric diseases with almost half of people with a psychiatric disease also having a physical disease. As well as about a third of people with a physical disease also having a psychiatric disease. These patients have worse quality of life than those with a single disease, they often struggle to get the best care and are at risk of living less long. A common and serious type of MM is between internalizing diseases (depression and anxiety) and cardiovascular disease (ICV-MM). Still, very little is understood as to how ICV-MM develops and why it happens. We do know however that both internalizing disease and cardiovascular risk (e.g., obesity, cholesterol) tend to begin before adulthood.

To really understand how ICV risk develops, we need large studies of people of all ages whose health has been followed over time. Studies of children are crucial because they can tell us about early risks for development of ICV-MM later in life. This is important for developing better plans to prevent at-risk children developing ICV-MM. We also know that certain conditions that start early in life (neurodevelopmental conditions) such as intellectual disability, autism and ADHD increase risk of developing ICV MM later. Children's environments can also increase this risk, for example, stressful experiences such as poverty and physical or sexual abuse. But how exactly neurodevelopmental conditions and early environmental risks influence the development of ICV-MM over the lifespan is still not understood. Certain groups are known to be at increased risk of ICV-MM, such as people of South Asian heritage and women, but we don't know why this is. Better understanding of how ICV-MM develops in different groups in society will help doctors give patients care that is matched to their specific needs. It will also help doctors, governments and schools prevent ICV-MM in at-risk children in ways that work best for them.

To really understand the complexities of ICV-MM development, a team of researchers with a wide range of expertise is needed who together understand physical and psychiatric diseases as well as how neurodevelopmental conditions and the environments people live in influence them throughout their lives. The PhD student will benefit from working within our LIfespaN multimorbidity research Collaborative (LINC), which combines wide-ranging medical and research expertise in physical and psychiatric diseases. LINC has brought together five very large studies (of which the student will access two – ALSPAC and UK Biobank) in which the health of many people has been followed over time. Rich medical data is available, including from medical records. Important information has been collected such as on people's living environments, life events and lifestyles. These studies follow the health over time of children, adolescents and adults. We can therefore study how internalizing and cardiovascular disease happen together in adulthood. Importantly we can then also study early risk factors in the children before they develop these conditions. Because our child and adult samples differ in ethnicity and economic situation, we can also study how the development of ICV-MM differs for different groups in society. The student’s studies will further LINC’s efforts in understanding how ICV-MM develops and which circumstances influence this. What we learn will be important for the prevention of ICV-MM in children who are at risk because of their sex, or ethnic or economic reasons. The student will disseminate their research to Welsh government, patient and public involvement groups and charities to develop specific health advice in order to reduce ICV-MM in at risk groups in the future.

Attention-Deficit/Hyperactivity Disorder (ADHD) is a common diagnosis. It affects around 3% of the population. ADHD has symptoms of hyperactivity, inattention, or both. Although ADHD is usually seen in childhood, it is now accepted that for many, ADHD persists into adulthood. Adults with ADHD are more likely to also have symptoms of depression and anxiety. Without effective management, this can make life more difficult for someone with ADHD.

Both children and adults with ADHD also often report sleep problems. Getting good quality sleep is crucial to someone's health. Sleep problems are also a key aspect of mental health conditions, including anxiety and depression. In this proposal, we set out how we aim to investigate what role sleep disturbance plays in both ADHD and mental health.

This project will use existing measures collected from consenting ALSPAC participants. In particular, we will use measures of ADHD symptoms, sleep, anxiety, and depression. Through statistical analysis, we will explore whether ADHD influences someone's sleep quality. We will build on this by exploring whether a relationship between ADHD and sleep goes on to impact someone's mental health.

Our findings may have consequences for how we view the importance of sleep for someone with ADHD. Crucially, sleep is a modifiable behaviour. Our results may help promote clinical recommendations that consider sleep as a key component of ADHD management.

This proposal will use the dataset for B4541 only. No new data is required.

Social inequality is the unequal distribution of socio-economic (SES) resources which affects people’s standards of living. Typically, individuals from lower SES backgrounds have a higher risk of poor physical and mental health, and children, have an increased likelihood of developing emotional and behavioural difficulties. Multiple factors such as family stress or genetics can influence this relationship between SES position and mental health difficulties. For example, low family income can contribute to difficulty in affording needs and parental distress, which in turn may lead to harsher parenting or family conflict which affect child development. Some of the exposures associated with low SES position can lead to heritable changes in gene expression without altering the DNA sequence which could then affect mental health outcomes. These changes are known as epigenetics, and DNA methylation (DNAm) is the most common epigenetic mechanism through which social inequality can affect gene expression. Low SES position has been previously associated with more alterations to DNAm profiles compared to higher SES positions. DNA methylation occurring in some gene regions have also been observed to associate with child mental health difficulties. Therefore, in this study we propose to investigate the relationship between SES position and child mental health difficulties, and whether this relationship can be explained by epigenetic changes and family functioning. We will make use of multiple methods, most notably structural equation modelling (SEM) for longitudinal analysis of participant data from the Avon Longitudinal Study of Parents and Children (ALSPAC).