BACKGROUND: People with serious mental illness (SMI) experience higher mortality partially attributable to higher long-term condition (LTC) prevalence. However, little is known about multiple LTCs (MLTCs) clustering in this population. METHODS: People from South London with SMI and two or more existing LTCs aged 18+ at diagnosis were included using linked primary and mental healthcare records, 2012-2020. Latent class analysis (LCA) determined MLTC classes and multinominal logistic regression examined associations between demographic/clinical characteristics and latent class membership. RESULTS: The sample included 1924 patients (mean (s.d.) age 48.2 (17.3) years). Five latent classes were identified: 'substance related' (24.9%), 'atopic' (24.2%), 'pure affective' (30.4%), 'cardiovascular' (14.1%), and 'complex multimorbidity' (6.4%). Patients had on average 7-9 LTCs in each cluster. Males were at increased odds of MLTCs in all four clusters, compared to the 'pure affective'. Compared to the largest cluster ('pure affective'), the 'substance related' and the 'atopic' clusters were younger [odds ratios (OR) per year increase 0.99 (95% CI 0.98-1.00) and 0.96 (0.95-0.97) respectively], and the 'cardiovascular' and 'complex multimorbidity' clusters were older (ORs 1.09 (1.07-1.10) and 1.16 (1.14-1.18) respectively). The 'substance related' cluster was more likely to be White, the 'cardiovascular' cluster more likely to be Black (compared to White; OR 1.75, 95% CI 1.10-2.79), and both more likely to have schizophrenia, compared to other clusters. CONCLUSION: The current study identified five latent class MLTC clusters among patients with SMI. An integrated care model for treating MLTCs in this population is recommended to improve multimorbidity care.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)