Multimorbidity clusters among people with serious mental illness: a representative primary and secondary data linkage cohort study

TY - JOUR

T1 - Multimorbidity clusters among people with serious mental illness

T2 - a representative primary and secondary data linkage cohort study

AU - Ma, Ruimin

AU - Romano, Eugenia

AU - Ashworth, Mark

AU - Yadegarfar, Mohammad E.

AU - Dregan, Alexandru

AU - Ronaldson, Amy

AU - De Oliveira, Claire

AU - Jacobs, Rowena

AU - Stewart, Robert

AU - Stubbs, Brendon

N1 - Funding Information: The current paper was supported by Multiple Long term condition grant by Guys and St Thomas Charity (GSTT). Brendon Stubbs holds an NIHR Advanced fellowship (NIHR301206, 2021–2026). BS is a co-investigator for an NIHR programme Grant Supporting physical activity and severe mental illness (SPACES).This project is also supported by the UK Research and Innovation (UKRI) funding for RJ, MA, CdO, RS, BS, RM and ER (Grant ref MR/V004964/1). Funding Information: RS is part-funded by: (i) the National Institute for Health Research (NIHR) Biomedical Research Centre at the South London and Maudsley NHS Foundation Trust and King's College London; (ii) an NIHR Senior Investigator Award; (iii) the National Institute for Health Research (NIHR) Applied Research Collaboration South London (NIHR ARC South London) at King's College Hospital NHS Foundation Trust; (iv) the DATAMIND HDR UK Mental Health Data Hub (MRC grant MR/W014386). MEY acknowledges funding from King's Health Partners/Guy's and St. Thomas Charity 'MLTC Challenge Fund' (award reference: EIC180702). Publisher Copyright: Copyright © The Author(s), 2022. Published by Cambridge University Press.

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

KW - Mortality

KW - multimorbidity

KW - physical health

KW - psychosis

KW - schizophrenia

UR - http://www.scopus.com/inward/record.url?scp=85129655340&partnerID=8YFLogxK

U2 - 10.1017/S003329172200109X

DO - 10.1017/S003329172200109X

M3 - Article

AN - SCOPUS:85129655340

SN - 0033-2917

JO - Psychological Medicine

JF - Psychological Medicine

ER -