Different multimorbidity patterns can influence health outcomes. We investigated their association with the risk of cardiovascular events in CUORE (baseline 2008–2012), an Italian cohort of randomly selected individuals from general population aged 35–69 years. Latent Class Analysis was used to identify homogeneous groups of multimorbid individuals (≥2 diseases) with similar underlying disease patterns. Cardiovascular disease (CVD) risk scores were estimated for each pattern, separately for men and women, and the one-way Anova test was used to evaluate significant differences between classes. Final sample consisted of 6,614 individuals (50% male, mean age 52 [SD 9.9]). Four multimorbidity patterns were identified and named after their overexpressed diseases: unspecific; inflammatory and metabolic; respiratory, cancer and anemia; obesity. We observed significant differences in cardiovascular risk scores between patterns, both in males and females; the unspecific and obesity patterns showed the highest mean cardiovascular risk scores. Multimorbidity patterns are differentially associated with CVD risk and their identification may provide prognostic information to improve prevention strategies.

Multimorbidity Patterns and the Risk of Cardiovascular Event: Results from an Italian Population-Based Study / Damiano, Cecilia; Marcozzi, Benedetta; Donfrancesco, Chiara; Palmieri, Luigi; Lo Noce, Cinzia; Onder, Graziano; Vetrano Liborio, Davide. - (2025). (Intervento presentato al convegno SIS 2025 – Statistics for Innovation tenutosi a Genova).

Multimorbidity Patterns and the Risk of Cardiovascular Event: Results from an Italian Population-Based Study

Benedetta Marcozzi;
2025

Abstract

Different multimorbidity patterns can influence health outcomes. We investigated their association with the risk of cardiovascular events in CUORE (baseline 2008–2012), an Italian cohort of randomly selected individuals from general population aged 35–69 years. Latent Class Analysis was used to identify homogeneous groups of multimorbid individuals (≥2 diseases) with similar underlying disease patterns. Cardiovascular disease (CVD) risk scores were estimated for each pattern, separately for men and women, and the one-way Anova test was used to evaluate significant differences between classes. Final sample consisted of 6,614 individuals (50% male, mean age 52 [SD 9.9]). Four multimorbidity patterns were identified and named after their overexpressed diseases: unspecific; inflammatory and metabolic; respiratory, cancer and anemia; obesity. We observed significant differences in cardiovascular risk scores between patterns, both in males and females; the unspecific and obesity patterns showed the highest mean cardiovascular risk scores. Multimorbidity patterns are differentially associated with CVD risk and their identification may provide prognostic information to improve prevention strategies.
2025
SIS 2025 – Statistics for Innovation
Multimorbidity, Population-based Study
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Multimorbidity Patterns and the Risk of Cardiovascular Event: Results from an Italian Population-Based Study / Damiano, Cecilia; Marcozzi, Benedetta; Donfrancesco, Chiara; Palmieri, Luigi; Lo Noce, Cinzia; Onder, Graziano; Vetrano Liborio, Davide. - (2025). (Intervento presentato al convegno SIS 2025 – Statistics for Innovation tenutosi a Genova).
File allegati a questo prodotto
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1753513
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact