This study aims to use the UK Biobank (UKB) database to explore the effects of diet, drugs, lifestyle, metabolism and other factors on cardiovascular and cerebrovascular diseases. Diet, drugs, lifestyle habits, metabolism and other factors may affect a variety of diseases, and are also the pathogenesis of many chronic diseases. Existing studies have shown that it can affect the human body in a variety of ways, leading to cell damage, gene mutations, chronic inflammation, hormone secretion disorders, and metabolic disorders. Demographic information (age, sex, race, place of residence, etc.) and health information (diagnosis records of hypertension, coronary heart disease, cerebral infarction, diabetes, etc.) were obtained from the UKB database. Environmental exposure data: alcohol consumption, smoking, coffee, tea, exercise, etc. The collected data were cleaned, integrated and standardized to ensure data quality and consistency. Machine learning method was used to rank the influencing factors according to their importance, and Cox proportional hazards regression model was used to analyze the effect of exposure group on the risk of cardiovascular and cerebrovascular diseases. A multivariate logistic regression model was used to analyze the effects of pollution exposure level, individual characteristics and socioeconomic factors on the risk of cardiovascular and cerebrovascular diseases. This study will clarify the impact of diet, medicine, lifestyle, metabolism and other factors on cardiovascular and cerebrovascular diseases, and provide evidence for the development of effective prevention and treatment measures.
