Clustering of physical health multimorbidity in 68,392 people with severe mental illness and matched comparators: a lifetime prevalence analysis of United Kingdom primary care data
Abstract:Objective: To investigate the clustering of physical health multimorbidity in people with severe mental illness (SMI) compared to matched comparators.
Design: A cohort-nested analysis of lifetime diagnoses of physical health conditions.
Setting: Over 1,800 UK general practices (GP) contributing to Clinical Practice Research DataLink (CPRD) Gold or Aurum databases.
Participants: 68,392 adult patients with a diagnosis of SMI between 2000 and 2018, with at least one year of follow up data, matched 1:4 to patients… Show more
“…People with severe mental illness (SMI) have more physical health comorbidities [1][2][3][4][5] and poorer prognoses from those comorbidities [6] than the general population. Physical health comorbidities can lead to reduced quality of life [7], worsening mental health [8], and drives excess mortality in people with SMI [9,10].…”
Background
People with severe mental illness (SMI) are at higher risk of physical health conditions compared to the general population, however, the impact of specific underlying health conditions on the use of secondary care by people with SMI is unknown. We investigated hospital use in people managed in the community with SMI and five common physical long-term conditions: cardiovascular diseases, COPD, cancers, diabetes and liver disease.
Methods
We performed a systematic review and meta-analysis (Prospero: CRD42020176251) using terms for SMI, physical health conditions and hospitalisation. We included observational studies in adults under the age of 75 with a diagnosis of SMI who were managed in the community and had one of the physical conditions of interest. The primary outcomes were hospital use for all causes, physical health causes and related to the physical condition under study. We performed random-effects meta-analyses, stratified by physical condition.
Results
We identified 5,129 studies, of which 50 were included: focusing on diabetes (n = 21), cardiovascular disease (n = 19), COPD (n = 4), cancer (n = 3), liver disease (n = 1), and multiple physical health conditions (n = 2). The pooled odds ratio (pOR) of any hospital use in patients with diabetes and SMI was 1.28 (95%CI:1.15–1.44) compared to patients with diabetes alone and pooled hazard ratio was 1.19 (95%CI:1.08–1.31). The risk of 30-day readmissions was raised in patients with SMI and diabetes (pOR: 1.18, 95%CI:1.08–1.29), SMI and cardiovascular disease (pOR: 1.27, 95%CI:1.06–1.53) and SMI and COPD (pOR:1.18, 95%CI: 1.14–1.22) compared to patients with those conditions but no SMI.
Conclusion
People with SMI and five physical conditions are at higher risk of hospitalisation compared to people with that physical condition alone. Further research is warranted into the combined effects of SMI and physical conditions on longer-term hospital use to better target interventions aimed at reducing inappropriate hospital use and improving disease management and outcomes.
“…People with severe mental illness (SMI) have more physical health comorbidities [1][2][3][4][5] and poorer prognoses from those comorbidities [6] than the general population. Physical health comorbidities can lead to reduced quality of life [7], worsening mental health [8], and drives excess mortality in people with SMI [9,10].…”
Background
People with severe mental illness (SMI) are at higher risk of physical health conditions compared to the general population, however, the impact of specific underlying health conditions on the use of secondary care by people with SMI is unknown. We investigated hospital use in people managed in the community with SMI and five common physical long-term conditions: cardiovascular diseases, COPD, cancers, diabetes and liver disease.
Methods
We performed a systematic review and meta-analysis (Prospero: CRD42020176251) using terms for SMI, physical health conditions and hospitalisation. We included observational studies in adults under the age of 75 with a diagnosis of SMI who were managed in the community and had one of the physical conditions of interest. The primary outcomes were hospital use for all causes, physical health causes and related to the physical condition under study. We performed random-effects meta-analyses, stratified by physical condition.
Results
We identified 5,129 studies, of which 50 were included: focusing on diabetes (n = 21), cardiovascular disease (n = 19), COPD (n = 4), cancer (n = 3), liver disease (n = 1), and multiple physical health conditions (n = 2). The pooled odds ratio (pOR) of any hospital use in patients with diabetes and SMI was 1.28 (95%CI:1.15–1.44) compared to patients with diabetes alone and pooled hazard ratio was 1.19 (95%CI:1.08–1.31). The risk of 30-day readmissions was raised in patients with SMI and diabetes (pOR: 1.18, 95%CI:1.08–1.29), SMI and cardiovascular disease (pOR: 1.27, 95%CI:1.06–1.53) and SMI and COPD (pOR:1.18, 95%CI: 1.14–1.22) compared to patients with those conditions but no SMI.
Conclusion
People with SMI and five physical conditions are at higher risk of hospitalisation compared to people with that physical condition alone. Further research is warranted into the combined effects of SMI and physical conditions on longer-term hospital use to better target interventions aimed at reducing inappropriate hospital use and improving disease management and outcomes.
“…Where ethnicity data were missing, individuals were coded as White, in line with previous research. 1 , 14 Our previous work has shown multiple imputation of ethnicity results in similar physical health condition estimates. 1 …”
Section: Methodsmentioning
confidence: 89%
“… 1 , 14 Our previous work has shown multiple imputation of ethnicity results in similar physical health condition estimates. 1 …”
Section: Methodsmentioning
confidence: 89%
“…We identified patients in the CPRD with a first diagnosis of severe mental illness between Jan 1, 2000, and Dec 31, 2018, via medical codes for schizophrenia, bipolar disorder, or other non-affective psychotic illnesses, as recorded in primary care (code lists are in the appendix pp 5–157 ). 1 These diagnoses will have been made by psychiatrists in secondary care using ICD criteria and communicated to primary care physicians. Where patients had more than one severe mental illness diagnosis during the study period, we took the most recent because this diagnosis was likely to represent the most accurate given a more complete clinical history.…”
Section: Methodsmentioning
confidence: 99%
“…It is well established that individuals with severe mental illness, including schizophrenia, bipolar disorder, and other non-organic psychotic illness, have increased prevalences of a range of chronic physical health problems. 1 , 2 These health issues contribute to the reduced life expectancy of people with severe mental illness. 3 The 2019 Lancet Psychiatry Commission on physical health in people with mental illness outlined the need to “focus not only on ‘adding years to life’ but also on ‘adding life to years’—specifically by preventing and reducing the incidence and impact of chronic health conditions”.…”
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.
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