Litcius/Paper detail

12-year evolution of multimorbidity patterns among older adults based on Hidden Markov Models

Albert Roso‐Llorach, Davide Liborio Vetrano, Caterina Trevisan, Sergio Fernández, Marina Guisado‐Clavero, Lucía A. Carrasco‐Ribelles, Laura Fratiglioni, Concepción Violán, Amaia Calderón‐Larrañaga

2022Aging20 citationsDOIOpen Access PDF

Abstract

BACKGROUND: The evolution of multimorbidity patterns during aging is still an under-researched area. We lack evidence concerning the time spent by older adults within one same multimorbidity pattern, and their transitional probability across different patterns when further chronic diseases arise. The aim of this study is to fill this gap by exploring multimorbidity patterns across decades of age in older adults, and longitudinal dynamics among these patterns. METHODS: Longitudinal study based on the Swedish National study on Aging and Care in Kungsholmen (SNAC-K) on adults ≥60 years (N=3,363). Hidden Markov Models were applied to model the temporal evolution of both multimorbidity patterns and individuals' transitions over a 12-year follow-up. FINDINGS: pattern (8.9 years). Transition probabilities varied across decades, sexagenarians showing the highest levels of stability. INTERPRETATION: Our findings highlight the dynamism and heterogeneity underlying multimorbidity by quantifying the varying permanence times and transition probabilities across patterns in different decades. With increasing age, older adults experience decreasing stability and progressively shorter permanence time within one same multimorbidity pattern.

Topics & Concepts

MultimorbidityLongitudinal studyDemographyDynamismLongitudinal dataGerontologyPopulationMedicinePhysicsQuantum mechanicsPathologySociologyChronic Disease Management StrategiesMachine Learning in HealthcareHeart Failure Treatment and Management