Sequential Patterns and Transition Timelines of Chronic Disease Comorbidities in Obesity: Evidence from the ELSA database

Objective : To characterize the sequential patterns and transition timelines of chronic disease comorbidities in population with obesity. Methods : We analyzed population with obese from the English Longitudinal Study of Ageing, including 22,355 independent participants for using association rule mining (ARM) to identify comorbidity patterns and 92,092 person-observations to analyze disease progression pathways and transition probability by multi-stage Markov chain (MMC). Health burden was compared between different onset disease. Results : ARM identified cardiovascular (CVD), metabolic (MTD), and skeletal-muscular disease (SMD) as the most prevalent disease trio. MMC revealed 40% of obese individual will develop a chronic disease within 5 years, and nearly 30% with MTD or CVD will develop to the trio within 10 years. Progression times to the trio differed significantly based on initial disease type ( p < 0.003), with MTD onset being the fastest progression (3.89 years). SMD onset was associated with the most adverse health burden profile, including the highest depression rate (6.3%), poorest sleep quality (77.0%), and substantial work limitations (74.0%). Conclusions : These findings establish quantifiable transition probabilities and timelines for chronic disease progression, emphasizing the important role of onset disease and contributing empirical evidence for the sequential nature of multimorbidity development.