Due to the aging population, cognitive decline has become prevalent in many countries worldwide. However, there is a lack of understanding regarding the reasons whether and why healthy daily activities may be associated with delayed cognitive decline. Consequently, our study aims to investigate the factors that contribute to cognitive decline. Moreover, we are interested in exploring how health, daily activities, and biomarkers are related to cognitive decline across different age groups throughout an individual’s lifespan. Furthermore, we seek to examine the potential moderating effects on the relationships. These moderating factors may include age, personality traits, economic status, family dynamics, employment status, biomarkers, and social policies. To achieve our objectives, we will utilize advanced data analysis techniques and machine learning techniques to identify the most significant moderators and develop a predictive model based on existing data to understand the relationship between daily activities and cognitive decline across adulthood.
