Globally, increasing prevalence of obesity has been observed, not just amongst adults but also in children. Studies have suggested that early development of obesity in childhood is associated with obesity in adulthood and development of chronic illnesses. It is thus important that factors associated with the rising prevalence of obesity amongst children are investigated, so that early interventions can be put in place to address the issue. While the causes contributing to obesity are complex, healthy eating is one of the most important and modifiable risk factors to address this issue. Traditionally, studies have been conducted to understand specific food group or nutrient and the association with obesity. However, in recent decades, food systems have undergone major changes that have led to a rising availability of ultra-processed foods globally. Under the NOVA food processing classification, ultra-processed foods are defined as industrial products made with many ingredients not accessible in domestic kitchen and typically contain a myriad of artificial additives. While there are growing evidence that the consumption of ultra-processed foods are linked to obesity in adults, this has not been examined in children except for few cohort studies with short follow up time. Therefore, this project aims to investigate the link between childhood consumption of ultra-processed foods and the development of overweight and obesity from childhood to early adulthood in the ALSPAC birth cohort. The results of this study will address an important gap in literature and also provide valuable insights to help shape future policies in tackling childhood obesity.

We propose research to advance precision in predicting individual prognostic trajectory and individual response to intervention for three common and debilitating categories of mental disorders in childhood: (1) Depressive Disorders, (2) Anxiety Disorders, and (3) Attention Deficit Hyperactivity Disorder. Our research will advance this precision by elucidating the etiologic heterogeneity of samples of children within these three diagnostic groups and determining clinical signatures corresponding to such heterogeneity. Such signatures will guide the development of a set of assessment and clinical decision-support tools that we will evaluate – integrating behavioral tests/measures – for classifying children with depression, anxiety disorders, and ADHD into sub-groups strongly informing on individual prognosis and probable responsiveness to specific categories of intervention.

Obesity is a significant challenge for individuals, societies, and economies. Whilst behaviours involved in energy balance, such as physical activity and diet, have been a primary focus of obesity research, several psychosocial factors have also shown promising associations. Social connections (such as social support and social networks) are known to be linked to disease and mortality in later life. Research has shown associations between social connections and a reduced risk of obesity, yet there is little known about these associations in earlier life stages including childhood, adolescence, and young adulthood. Taking a lifecourse perspective has the potential to reset health and social trajectories by encouraging a proactive preventative approach, rather than a reactive treatment approach. The specific roles and relative contributions of the different social connection dimensions (structural, functional, and quality) are also unclear, meaning the optimum ways to intervene are unknown.

Understanding the underlying biosocial mechanisms linking social connections to health is important as it can help establish causality and suggest novel interventions. Stress and inflammatory response systems have been individually associated with both social connections and obesity but have not been studied in this relationship. Ultimately, this project aims to provide a comprehensive understanding of the relationship between early life social connections and obesity across the early lifecourse, including the exploration of the potential underlying biological mechanisms.

Problematic alcohol use is a major public health burden. It is important to understand how to best predict individuals most at risk for alcohol problems so they can be targeted for early prevention efforts. This project will explore whether combining polygenic risk scores can enhance the prediction of alcohol problems.

This projects seeks to deepen our understanding of how the timing of puberty affects adult health outcomes, specifically, risk of cardiovascular disease (CVD). The age at which a girl gets her first menstrual period (age at menarche, or AAM) has a peculiar relationship with CVD: both earlier and later AAM are associated with increased risk of CVD in adulthood.

In preliminary work focusing on later AAM, we applied human genetic techniques to distinguish the effects of common genetic changes on AAM from the effects of other, yet-to-be-identified factors. We were surprised to find that the relationship between later AAM and CVD depends on the underlying cause of later AAM. If caused by common genetic changes, later AAM is actually associated with _lower_ risk of cardiovascular disease. In contrast, if caused by other factors, later AAM is associated with _increased_ risk of cardiovascular disease.

The broad goals of this project are 1) to better understand how common genetic changes affect AAM by subgrouping common genetic variants based on their effects on childhood factors known to affect AAM, and 2) to identify factors other than common genetic changes that influence AAM.

Maternal-related diseases affect the development of offspring nervous system. However, there are currently some limitations in the research on this topic, such as small sample sizes, short observation periods, lack of long-term follow-up, unconsidered confounding factors and interactions, etc. To overcome these limitations, our study plans to use the large-scale population cohort data in ALSPAC, adopt advanced statistical methods and causal inference methods, systematically analyze the strength of the association and causal effects of maternal-related diseases between neurodevelopmental disorders in offspring, and explore possible mechanisms and intervention measures.

Most research has found a positive association between religious belief and mental health, but these are often in US samples, which may differ from samples in other countries. We have previously examined childhood and adolescent mental health and parental religious belief, which have found results that differ from much of the previous literature. This study seeks to expand upon our previous studies of childhood and adolescent mental health by examining adult mental health, and whether offspring religious belief is associated with it in a large UK cohort study.

Mental health problems are globally prevalent, and made worse by Covid-19. There is a growing recognition of the roles of economic circumstances in determining mental health, however, it remains unclear how the economic circumstances at various levels (individual and household; local areas; and national) manifest differently on mental health through different channels. Based on ALSPAC data merged with local authority level information, and cutting-edge econometric methods, we will systematically examine the extensive links between mental health and economic circumstances at individual/household, local area, and national policy levels, and map out a complete and comprehensive picture of economic determinants of mental health. Our research will get to the economic roots of mental health and help answer the long-term big-picture question of how to prevent mental illness. Our research is novel on two fronts. First, we bring together economic data at micro, local, and macro levels from multiple sources to study their roles on mental health in one setting; second, we take advantage of rich and long panel data and dynamic panel modelling methods to examine dynamic and long-run effects over the life course.

Trauma is a transdiagnostic risk factor for posttraumatic stress disorder (PTSD), major depressive disorder (MDD), increased alcohol use, and alcohol use disorder. Additionally, these conditions tend to co-occur, and are genetically-influenced. Decades of work has emphasized the importance of count, type, and timing of traumatic events on these mental health outcomes. However, most work has not examined these mental health conditions simultaneously and very few have investigated their effects over the course of development. This proposed study will examine the role of trauma characteristics on these outcomes across childhood into adulthood, via the use of multiple longitudinal datasets--ALSPAC, as well as two others (Add Health, a nationally representative sample, and ABCD, a diverse sample of children aged 9-10 across the US). This study will also use cutting edge genetic methods (genomic structural equation modeling-derived polygenic risk scores/PRSs) to examine the genetic influences on these conditions, as well as investigate potential interactions between genetic risk and trauma characteristics.