Multimorbidity patterns and mortality in older adults: a two-cohort pooled analysis

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 multi-morbid 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: hypercholesterolemia; metabolic, depression and cancer; cardiometabolic and respiratory; gastrointestinal, genitourinary and depression; respiratory; unspecific (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 cardiometabolic and respiratory pattern showed the highest mortality (pooled HR 2.62, 95% CI 2.15-3.10), followed by unspecific (pooled HR 1.45, 95% CI 1.21-1.68), respiratory (pooled HR 1.33, 95% CI 1.01-1.64) and gastrointestinal, genitourinary and depression (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.