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Article Abstract

Background: Different multimorbidity patterns can affect health trajectories and influence survival.

Aims: We investigated their association with mortality in two population-based cohorts of older adults.

Methods: Two Italian cohorts of randomly selected individuals (60–79 years old) from general population: CUORE (baseline 2008–2012) and Moli-sani (baseline 2005–2010). Latent Class Analysis used to identify homogeneous groups of multimorbid individuals (≥ 2 diseases) with similar underlying disease patterns. Cox regression models used to assess the association of multimorbidity patterns and all-cause mortality (end of follow-up 12/31/2019). Results pooled in a random-effects meta-analysis.

Results: Total samples of 3,695 individuals in CUORE (48% male, mean age 68.8 years [SD 5.6]) and 7,801 in Moli-sani (51% male, mean age 68.2 years [SD 5.4]). In both cohorts, six multimorbidity patterns were identified and named after their overexpressed diseases: ,, (i.e., no diseases overexpressed). Overall mortality rates were 1.66 per 100 person/years in CUORE and 1.85 per 100 person/years in Moli-sani. Compared to the multimorbidity-free group (< 2 diseases), individuals displaying a pattern showed the highest mortality (pooled HR 2.62, 95% CI 2.15–3.10), followed by (pooled HR 1.45, 95% CI 1.21–1.68), (pooled HR 1.33, 95% CI 1.01–1.64) and , (pooled HR 1.33, 95% CI 1.06–1.60).

Discussion: Multimorbidity patterns in older adults are differentially associated to shorter survival.

Conclusions: Their identification may help optimize clinical management by improving risk stratification, allowing for more targeted prevention and intervention strategies.

Supplementary Information: The online version contains supplementary material available at 10.1007/s40520-025-03150-0.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12367807PMC
http://dx.doi.org/10.1007/s40520-025-03150-0DOI Listing

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