Inequalities in developing multimorbidity over time: a population-based cohort study using Multistate Markov Chain Models
Social inequalities accelerate the development of multimorbidity, yet the mechanisms which drive multimorbidity trajectories remain unclear. Previous studies assume that disease trajectories are in a progressive state, and do not account for disease recovery. We aimed to examine whether social inequalities affect the evolution of multimorbidity, taking the sequence of diseases into consideration.
We used a retrospective cohort of adults aged 18 years and over, registered at any point between April 2005 to May 2020 in general practices in one inner London borough (n=826,936). The development and resolution of 32 long term conditions (LTCs) were examined through the application of Markov chains.
Participants were followed up for a mean of 5.7 years (sd = 4.8); 77% entered the study with no LTCs, 14% with 1 LTC, 5% with 2 LTCs, and 4% with 3 or more LTCs. At the end of follow-up, 24% gained 1 or more LTCs, while 12% had resolved LTCs and 3% died. In multistate models, deprivation (hazard ratio [HR] 1.37 – 1.71), female sex (HR 1.09 – 1.14), and Black ethnicity (HR [vs White] 1.22 – 1.30) were associated with an increased risk of transition from healthy state to multimorbidity or death, and less time spent in a healthy state. The results of first order Markov chains show patterns such as musculoskeletal diseases followed by psychological diseases; alcohol and substance dependency followed by HIV, viral hepatitis, and liver disease; and morbid obesity followed by diabetes, hypertension, osteoarthritis and chronic pain.
We examined the relations among 32 conditions, taking the order of disease occurrence into consideration. Distinctive patterns for the development and accumulation of multimorbidity have emerged, with increased risk of transitioning from a healthy state to multimorbidity related to ethnicity, deprivation and gender.