This study investigates how physical activity, sociodemographic factors, chronic diseases, psychological and physiological factors, and blood biomarkers influence cognitive function and related conditions (e.g., sarcopenia, frailty). Key questions: 1) How do physical activity and biomarkers (e.g., CRP, lipids, HbA1c) impact cognitive function and disease risk? 2) Do these relationships vary by demographic or clinical subgroups? Objectives: Quantify associations, identify mediating pathways, and develop predictive models using deep learning and statistical methods to inform targeted interventions. Scientific rationale: Physical activity may enhance cognitive and physical health via neuroplasticity, reduced inflammation, and improved vascular health. However, interactions with sociodemographic factors (e.g., education), chronic diseases (e.g., diabetes), psychological factors (e.g., depression), and biomarkers are underexplored. UK Biobank’s existing data, including physical activity (self-reported and accelerometer), cognitive tests, brain imaging, blood biomarkers (e.g., CRP, HbA1c), and health records for ~500,000 participants, provide a unique resource to address these gaps. Using UKB-RAP, we will analyze data with Python, R, and Spark SQL, supporting public health strategies to reduce dementia and frailty burden.
