Risk factor and causal association detection in common diseases

Common diseases including severe or acute diseases, chronic diseases, and cancers, which remain high all over the world, increase the family economic burden, consume public medical resources excessively and cause life quality decreasing. This project mainly focuses on some diseases with increasing significance for the public, including cardiovascular diseases, dementia, breast cancer and lung cancer etc. Risk factor detection research can still be urgent and significant for public health. Due to limitations of some real-world data, some factors were not collected and considered at the same time.
It is important to detect potential risk factors and causal associations prospectively based on this large-scale dataset and provide necessary preventive evidence. This project aims to involve all the necessary subjects from UK Biobank to conduct relative analysis. The effects of sole or combined factors like demographic variables, personal behaviors, medical records, diet models, social test results, metabolic biomarkers, and genetic indications will be considered at the same time. During the detection progress, some important bias-adjustment methods and prediction models will be applied, including parametric and non-parametric regression models.
Since the variable spectrum can be very broad, all the cohort data will be used. The project duration is 3 years. This project is expected to provide more convincing evidence for the underlying mechanism investigation, diagnosis, prevention, and treatment of common diseases. This may help the society to identify some high-risk groups who are more vulnerable to some diseases or some unhealthy conditions. In a world, it is expected to be beneficial to public health care, and decrease the morbidity and mortality of common diseases.