Non-communicable chronic diseases (NCDs) (e.g., diabetes, Alzheimer’s disease, fatty liver disease, and cancer) are leading causes of global morbidity and mortality. Development of NCDs is determined by a constellation of factors, including but not limited to diet, genetic, social, and environmental factors. Adherence to healthy dietary patterns (e.g., Mediterranean diet) has been shown to mitigate incident NCDs, whereas intake of an unhealthy diet (e.g., ultra-processed foods) exacerbates it. However, current dietary guidelines seemly adopt a “one size fits all” approach, without accounting for individual variability in genetic predisposition, social determinants, or environmental exposures. Genetic susceptibility plays a crucial role in NCDs risk, yet its interaction with diet and environmental exposures remains poorly understood. Social determinants of health (e.g., income, education) significantly influence dietary behaviors and access to healthy food options, compounding health disparities. In addition, environmental pollutants (e.g., PM2.5) contribute to systemic inflammation and metabolic dysfunction, further increasing NCDs risk. However, these factors seldom occur alone, yet their joint impact on NCDs and the underlying mechanisms are insufficiently explored. A more comprehensive understanding of how these factors independently and collectively contribute to NCDs or subclinical markers will better inform public health planning and clinical strategies. Further improvements in prediction models for NCDs are needed for timely detection and early intervention.
By using UK Biobank comprehensive dataset, we aim: (1) to examine individual and joint associations of dietary quality/componets, genetic susceptibility, social factors, and air pollutants with incident NCDs; (2) to explore biological mechanisms underlying these associations; (3) to identify predictive markers of NCDs and further improve the performance of the prediction models of NCDs.