About
Aims: Our research project aims to investigate the relationship between serum markers, lifestyle factors, and the risk of cardiovascular and cerebrovascular diseases, as well as all-cause mortality. We also aim to explore the genetic contributions to these health outcomes. By understanding these associations, we hope to identify potential risk factors and improve our understanding of the underlying mechanisms.
Scientific Rationale: Cardiovascular and cerebrovascular diseases, such as heart disease and stroke, are leading causes of death worldwide. Lifestyle factors and serum markers, which are measurable substances in the blood, have been linked to the development of these diseases. By studying a large cohort from the UK Biobank database, we can explore how lifestyle choices and serum markers influence disease risk and mortality. Additionally, we will investigate the genetic components that may contribute to these outcomes.
Project Duration: The research project is expected to be conducted over 3 years. The exact timeline will be determined based on the complexity of the research questions and the availability of the required data.
Public Health Impact: The findings of this study have the potential to significantly impact public health. By identifying specific lifestyle factors and serum markers associated with cardiovascular and cerebrovascular diseases, we can develop targeted interventions and strategies for disease prevention and management. Furthermore, understanding the genetic contributions to these health outcomes can lead to the development of personalized approaches to healthcare, enabling individuals to make informed decisions about their health based on their genetic risk profiles.
Overall, our research project aims to shed light on the associations between serum markers, lifestyle factors, cardiovascular and cerebrovascular diseases, and all-cause mortality. By leveraging the UK Biobank database, we hope to uncover valuable insights that can inform public health policies, improve risk prediction models, and ultimately contribute to reducing the burden of these diseases in the population.