On longitudinal study of chronic diseases multimorbidity patterns at older ages

In high-income countries, when healthcare systems are transitioning from being centered around single disease to multimorbidity approach, understanding the structure of multimorbidity across time is important to assess the population health burden. Precise and flexible identification of the multimorbidity situation allows sound measures to prevent adverse health outcomes and better allocate healthcare resources. Compared to standard practice like factorial and cluster analysis, combining the probabilistic approach of graphical model and the intuitive visibility of network analysis is emerging as powerful tool to explore the richness of administrative health data and provide a framework with predictability. By applying these methods on reliable longitudinal data of individuals aged 50+ residing in Emilia-Romagna region (northern Italy) in 2011 and followed up to 2019 (N = 1,010,610), we study the multimorbidity patterns across time and their impact on mortality at older ages.