Recent empirical work suggests the prevalence of eating disorders may be raised in autistic individuals, however, questions remain as to whether the co-occurrence of autism and eating disorders could be due to selective samples and/or difficulties disentangling symptoms of autism as compared to symptoms of eating disorders. An alternative explanation is that autism, or high levels of autistic traits, in childhood, may causally increases risk for eating disorders later in development. In addition, autistic children often experience high level of anxiety, and might use overeating or binge eaitng as a coping strategy to sooth and calm themselves down, which might put them on increased risk for later eating disorders. Further research into the pathways and potential mediators of the link between autism, anxiety,and eating disorders is needed to illuminate underpinning mechanisms, which in turn will highlight targets for prevention/intervention.

Breastfeeding is sustainable, the biological norm, and potentially life-saving, particularly for premature babies. Evidence-based strategies to support breastfeeding have been successful, but inequalities in breastfeeding rates are proving difficult to reduce, affecting the most vulnerable of mothers and babies. Successfully establishing and sustaining breastfeeding can be facilitated by both removing structural and cultural barriers, and overcoming individual challenges. Common factors such as obesity and depression/anxiety could play an important part in explaining some of the variability (and inequality) in breastfeeding duration. Conversely, maternal factors reflecting good mental and physical health could increase resilience to contexts with low systemic and cultural support for breastfeeding, such as the UK. However, the evidence on the individual determinants causally influencing successful and sustained breastfeeding is of poor quality. The identification of causal determinants of early cessation will improve breastfeeding support activities.

Depression is the leading cause of disability worldwide and is a major contributor to the overall global burden of disease, with more than 350 million people of all ages suffering from depression. Especially when recurrent and with moderate or severe intensity, depression may become a serious health condition. Further, we now know that many young people suffer from clinical depression. In fact, major depression is one of the most common mental health disorders in children and adolescents, with an estimated one year prevalence of 4-5% in mid-late adolescence and 5.6% in young people of 13-18 year old. Depression in young people is a precursor of adult depressive disorder which is strongly linked to poor physical health outcomes, lower income and increased unemployment, with half of those with lifelong recurrent depression starting to develop their symptoms before the age of 15 years. Thus, to recognize and treat depression in young ages is crucial. To sum up, depression is a substantial and largely unrecognized problem among young people that warrants an increased need and opportunity for identification and intervention. Understanding how specific factors might prevent and/od be effective in the treatment of depression in young people is crucial for the development of early intervention and treatment of depression among youths.
Depression results from a complex interaction of social, psychological, and biological factors. Recent attempts have been made by the Wellcome Trust to investigate the evidence for different active ingredients (i.e. those aspects of an intervention that drive clinical effect, are conceptually well defined, and link to specific hypothesised mechanisms of action) deemed to help prevent, treat, and manage depression in young people globally, including behaviours and activities, beliefs and knowledge, brain/body functions, cognitive and attentional skills, human connections, and socioeconomic factors. However, what is still unknown is which of these potential active ingredients and/or which combination of these active ingredients constitute a more accurate predictor for different groups of young people with depression, including those with high levels of depression.
A number of important issues need further investigation to aid early intervention in depression. First, most studies in young people with depression have focused on single time points, while very few studies have investigated the different trajectories of depression across adolescence and young adulthood, including young people with persistent high levels of depression. In addition, despite the recent attempt to identify specific active ingredients of effective interventions for depression, it is still unclear which of these active ingredients (and their combinations/interactions) are the most relevant to prevent depression across childhood and adolescence. For this reason, new statistical approaches, including predictive modelling are required and will help advance the field of early intervention in depression.
Therefore, the main purpose of this research proposal will be to characterize the most relevant active ingredients (and their combination) that prevent the development of persistent high levels of depression across adolescence and young adulthood. More specifically, we will aim to answer to the following main research questions: "What combination/s of active ingredients prevent the development of persistent high levels of depression across adolescence and young adulthood?"
To do this, we will use the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort, which is a longitudinal birth cohort study, set in the UK, examining the determinants of development, health and disease during childhood and beyond.

This project will examine whether adolescent physical activity is related to heart function in adulthood. This will be investigated by comparing physical activity levels and measurements of heart structure and function as collected in the Avon Longitudinal Cohort Study of Parents and Children.

The mental health of university students is a growing public health concern (1). Findings from population-based studies in the USA, UK and Norway point to a significant increase in mental distress among students over the last decade (2-5). Around 5% of young people in the UK have a diagnosis of either anxiety or depression, and the rate of people attending university has doubled in the past twenty years (6). For many the transition to university coincides with a developmentally high-risk period for the emergence of mental health concerns (7-9). This risk may be made worse by the need to adjust to a new social and academic environment whilst at the same time becoming financially independent (8, 10). This period could be particularly risky for students who have faced adversity, are socially disadvantaged (11), or for people who find it harder adjust to new social groups (8, 9). Few long-term studies have looked at these issues (12). While some evidence has shown how many students are likely to experience a mental disorder and use a mental health service at university (13); we do not currently know how much mental health need occurs prior to university attendance. By understanding this and any risk factors for the emergence and development of mental health need at this transition we could inform support-based prevention for students. This study aims to use data collected in ALSPAC to understand the risk university attendance poses on mental health and service use for a mental health reason among young people.

1. Barkham M, Broglia E, Dufour G, Fudge M, Knowles L, Percy A, et al. Towards an evidence-base for student wellbeing and mental health: Definitions, developmental transitions and data sets. Counselling and Psychotherapy Research. 2019;19(4):351-7.
2. Knapstad M, Sivertsen B, Knudsen AK, Smith ORF, Aarø LE, Lønning KJ, et al. Trends in self-reported psychological distress among college and university students from 2010 to 2018. Psychological Medicine. 2021;51(3):470-8.
3. Lipson SK, Lattie EG, Eisenberg D. Increased Rates of Mental Health Service Utilization by U.S. College Students: 10-Year Population-Level Trends (2007-2017). Psychiatric services (Washington, DC). 2019;70(1):60-3.
4. McManus S, Gunnell D. Trends in mental health, non‐suicidal self‐harm and suicide attempts in 16–24-year old students and non-students in England, 2000–2014. Social Psychiatry and Psychiatric Epidemiology. 2020;55(1):125-8.
5. Tabor E, Patalay P, Bann D. Mental health in higher education students and non-students: evidence from a nationally representative panel study. Social Psychiatry and Psychiatric Epidemiology. 2021;56(5):879-82.
6. Boero G, Nathwani, T., Naylor, R., Smith, J. Graduate Earnings Premia in the UK: Decline or Fall. Higher Education Statistics Agency (HESA): HESA; 2021.
7. Kessler RC, Amminger GP, Aguilar-Gaxiola S, Alonso J, Lee S, Ustün TB. Age of onset of mental disorders: a review of recent literature. Curr Opin Psychiatry. 2007;20(4):359-64.
8. Lei J, Brosnan M, Ashwin C, Russell A. Evaluating the Role of Autistic Traits, Social Anxiety, and Social Network Changes During Transition to First Year of University in Typically Developing Students and Students on the Autism Spectrum. Journal of Autism and Developmental Disorders. 2020;50(8):2832-51.
9. Adams KL, Saunders KE, Keown-Stoneman CDG, Duffy AC. Mental health trajectories in undergraduate students over the first year of university: a longitudinal cohort study. BMJ Open. 2021;11(12):e047393.
10. McCloud T, Bann D. Financial stress and mental health among higher education students in the UK up to 2018: rapid review of evidence. Journal of Epidemiology and Community Health. 2019;73(10):977-84.
11. Cullinan J, Walsh S, Flannery D. Socioeconomic Disparities in Unmet Need for Student Mental Health Services in Higher Education. Applied Health Economics and Health Policy. 2020;18(2):223-35.
12. Lewis GM, T. Callender, C. Higher Education and Mental Health: Analyses of the LSYPE cohorts: research reports. In: Education. Do, editor. 2021.
13. Eisenberg D, Hunt J, Speer N. Help seeking for mental health on college campuses: review of evidence and next steps for research and practice. Harvard review of psychiatry. 2012;20(4):222-32.

Non-heterosexual (bisexual, lesbian, gay, and asexual) adolescents are at greater risk of common mental health disorders compared to heterosexual adolescents. The dominant theoretical framework used to explain the elevated rates of mental disorders among non-heterosexuals is minority stress theory. However, this model cannot fully explain sexual orientation disparities in mental health outcomes. Thus, other mechanisms or explanations, may help explain the sexual orientation disparities in mental health outcomes should be further explored. In addition, many adult mental health problems begin in childhood or adolescence. Non-heterosexual adolescents may be at greater risk of poorer mental health even in early childhood compared with heterosexual adolescents, which cannot be explained by the minority stress theory since when sexual identity development is nascent. However, the underlying mechanisms remained under-explored. Thus, this project aims to further test the psychosocial and biological influences on the sexual orientation disparities in mental health outcomes, especially in childhood, early adolescence, and the developmental trajectories from childhood to adolescence.

Cardiovascular disease (CVD) is the primary cause of premature morbidity and mortality in type 1 diabetes, with this effect particularly pronounced in those diagnosed at a younger age. The magnitude of this problem has recently been starkly highlighted by findings from the Swedish National Diabetes Register, where patients diagnosed with diabetes between 1 and 10 years of age were found to have a 10× higher risk of future acute myocardial infarction compared to those diagnosed between the ages of 26 and 30 years, and over a 30× higher risk than the general population. These and other data suggest that adolescence may be a particularly crucial time in the development of future CVD complications in type 1 diabetes, and that effective intervention at this age may offer long-lasting benefits for cardiovascular health.

While compromised glycaemic control represents the major risk factor for CVD complications in type 1 diabetes, individuals living with the disease are also exposed to many other well-established and potentially modifiable risk factors faced by the population at-large. Obesity is a well-established causal driver of subclinical disease in the young, is known to track into adulthood, and therefore represents one of the major risk factors in early-life for future risk of CVD. Although individuals with type 1 diabetes have traditionally been considered to be a relatively lean population, recent evidence has shown that obesity rates in this group are now similar or possibly even higher than in the general population, with an alarmingly high prevalence in children and adolescents.

For the last 14 years, our group have tracked, genotyped, and extensively phenotyped a cohort of adolescents with type 1 diabetes; first as part of a randomised clinical trial (The Adolescent type 1 Diabetes cardio-renal Intervention Trial - AdDIT), and then as part of a long-term epidemiological study (AdDIT Follow-Up). We now wish to use this data alongside that collected over the same timespan in ALSPAC to address the following aims and objectives:

Evidence has accumulated that the parents of children with intellectual disabilities are at increased risk of adverse mental health outcomes including depression and anxiety. Research in the field is currently attempting to explore the nature of this association, trying to identify which parents are most at risk and to what extent is the association confounded by the family environment, genetics and prior episodes of adverse mental health. The ALSPAC cohort has not been used to explore this research question so far and has substantial information on the family environment, parental mental health before and after the development of an intellectual disability in the child, maternal genetics and child behaviours. Such information may be useful for identifying modifiable targets for intervention or exploring which parents are most at risk.

Increased adiposity and Type 2 diabetes (T2D) have both been associated with increased risk of developing certain cancers and are both becoming increasingly prevalent globally. Although adiposity, T2D and cancer share many risk factors, the biological pathways linking adiposity and T2D to cancer remain poorly understood.

Chronic low-grade inflammation, characterised by abnormal cytokine production, is associated with both adiposity and T2D. Observational studies have suggested that increased adiposity and hyperglycaemia associated with diabetes induce the production of pro-inflammatory cytokines such as tumour necrosis factor-alpha and interleukin-6 which have key roles in cancer. This observation has led to the hypothesis that chronic inflammation might be a potential mechanism linking adiposity and T2D to cancer. However, due to the inherent limitations of observational research such as reverse causation and confounding, findings from observational studies need to be interpreted with caution. Furthermore, previous studies have used a single ‘baseline’ measurement of adiposity, T2D and inflammation and cannot fully account for the time-dependent variability in these measurements which may lead to a biased estimation.

Mendelian randomization is an analytical approach where genetic variants reliably associated with risk factors of interest are used as proxy measures to re-estimate the associations between an exposure and an outcome where some of the limitations of observational epidemiology are reduced. In this investigation, we would like to use genetic variants associated with adiposity, T2D and related glycaemic traits to investigate the estimated causal association between adiposity and T2D with inflammatory proteins (measured using the Olink inflammatory panel). We will also use longitudinal measures of inflammatory proteins to investigate whether the relationship between BMI/T2D with inflammation changes over time (across childhood and young adulthood) and potentially identify patterns in the relationship between BMI/T2D and inflammation which may be relevant to cancer development.