Osteoarthritis (OA) is a leading cause of disability worldwide, often coexisting with obesity and cardiometabolic diseases. Physical activity is known to influence both OA risk and its comorbidities, yet most prior studies relied on self-reported data and failed to capture the complexity of real-world movement behaviors. This project aims to investigate the relationships between objectively measured physical activity patterns and osteoarthritis outcomes, and to explore how these associations are modified by individual physiological characteristics such as body mass index, fat distribution, and muscle strength.
Using the UK Biobank cohort, we will analyze accelerometer-derived metrics of physical activity intensity in relation to incident and prevalent hip and knee OA identified through hospital and primary care records. We will further examine the potential effect modification by body composition (e.g., fat mass, fat-free mass, waist-hip ratio) and muscle strength (grip strength, leg strength) to understand whether physical activity confers different benefits across metabolic phenotypes.
A secondary objective is to assess the prospective association between activity patterns among individuals with OA and their subsequent risk of developing cardiovascular and cerebrovascular diseases. This will provide insight into whether specific behavioral profiles could mitigate the high cardiometabolic burden observed in OA populations.
This project leverages UK Biobank’s accelerometer data, anthropometry, body composition, and longitudinal health records to generate a comprehensive picture of how movement behaviors interact with physiological traits to influence musculoskeletal and cardiometabolic health. Findings may inform personalized lifestyle recommendations for OA prevention and management.
