Year: 2025
Type: article
Study design: Observational Study
Abstract: Recent studies have addressed the problem of the complex classification and discovery of multimorbidity patterns; however, to date there are still many doubts about the conceptualization of multimorbidity and its adequate measurement due to the need to work with very large samples and longitudinal designs that allow us to study the dynamics of multimorbidity patterns and the social contexts from which they emerge. The present study makes use of a sample of 341,343 patients over 50 years of age residing in southern Spain with the aim of analysing the trajectories of multimorbidity patterns that are linked to different socioeconomic areas. Employing Hidden Markov Models for the study of changes in the latent states of multimorbidity profiles, our analysis demonstrates significant associations between multimorbidity patterns and the socioeconomic gradient of residential areas. Moreover, we provide additional evidence that enables a characterisation of transitions from initial disease patterns to multisystemic profiles of chronicity (or complex multimorbidity) that offer a worse prognosis of health and quality of life for the patient. Our study adds relevant and contextualized information on the evolution of multimorbidity patterns that can serve as a basis for further research and policies aimed at the prevention and control of multimorbidity from an early age. As people age, many develop multiple chronic diseases at once, known as multimorbidity. This study examined how these disease patterns change over time and whether they differ by socioeconomic status. Using health records from 341,343 adults aged 50+ in Southern Spain, we identified common clusters of diseases (e.g., heart conditions, mental health issues) and tracked how they progressed over 10 years. We found that people in poorer areas often developed more complex and severe disease combinations earlier in life. Mental health problems in women and substance use disorder related diseases in men were key drivers of worsening health. These findings highlight the need for early, targeted healthcare—especially in disadvantaged areas—to prevent multimorbidity from becoming severe. Our results can help policymakers design better prevention strategies. Carretero-Bravo et al. analyze multimorbidity patterns in 341,343 individuals aged 50+ in Southern Spain, revealing associations between socioeconomic status and disease trajectories. Hidden Markov Models identify transitions to complex multimorbidity, highlighting disparities by sex and area deprivation.
Source: Communications Medicine
Institutions: Universidad Loyola Andalucía, Universidad de Cádiz
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,690
Awards: G114353912, G1940243671
OpenAlex ID: W4415350090