Prevalence of multimorbidity in people with and without severe mental illness: a systematic review and meta-analysis.

BACKGROUND: People with severe mental illness, such as schizophrenia-spectrum disorder and bipolar disorder, face poorer health outcomes from multiple chronic illnesses. Physical multimorbidity, the coexistence of two or more chronic physical conditions, and psychiatric multimorbidity, the coexistence of three or more psychiatric disorders, are both emerging concepts useful in conceptualising disease burden. However, the prevalence of physical and psychiatric multimorbidity in this cohort is unknown. This study aimed to estimate the absolute prevalence of both physical and psychiatric multimorbidity in people with severe mental illness, and also compare the odds of physical multimorbidity prevalence against people without severe mental illness. METHODS: We searched CINAHL, EMBASE, PubMed, and PsycINFO from inception until Feb 15, 2024, for observational studies that measured multimorbidity prevalence. To be included, studies had to have an observational study design, be conducted in an adult population (mean age ≥18 years) diagnosed with either schizophrenia-spectrum disorder or bipolar disorder, and include a measurement of occurrence of either physical multimorbidity (≥2 physical health conditions) or psychiatric multimorbidity (≥3 psychiatric conditions total, including the severe mental illness). From control studies, a random-effects meta-analysis compared odds of physical multimorbidity between people with and without severe mental illness. Absolute prevalence of physical and psychiatric multimorbidity in people with severe mental illness was also calculated. Sensitivity and meta-regression analyses tested an array of demographic, diagnostic, and methodological variables. FINDINGS: From 11 144 citations we included 82 observational studies featuring 1 623 773 individuals with severe mental illness (specifically schizophrenia-spectrum disorder or bipolar disorder), of which 21 studies featured 13 235 882 control individuals without severe mental illness (descriptive data for the entire pooled cohorts were not available for numbers of males and females, age, and ethnicity). This study did not feature involvement of people with lived experience. The odds ratio (OR) of physical multimorbidity between people with and without severe mental illness was 2·40 (95% CI 1·57-3·65, k=11, p=0·0009). This ratio was higher in younger severe mental illness populations (mean age ≤40 years, OR 3·99, 95% CI 1·43-11·10) compared with older populations (mean age >40 years, OR 1·55, 95% CI 0·96-2·51; subgroup differences p=0·0013). For absolute prevalence, 25% of those with severe mental illness have physical multimorbidity (95% CI 0·19-0·32, k=29) and 14% have psychiatric multimorbidity (95% CI 0·08-0·23, k=21). INTERPRETATION: This is the first meta-analysis to estimate physical alongside psychiatric multimorbidity prevalence, showing that these are common in people with schizophrenia-spectrum disorder and bipolar disorder. The greater burden of physical multimorbidity in people with severe mental illness compared with those without is higher for younger cohorts, reflecting a need for earlier intervention. Our findings speak to the utility of multimorbidity for characterising the disease burden associated with severe mental illness, and the importance of facilitating integrated physical and mental health care. FUNDING: None.

Management of dyslipidaemia in individuals with severe mental illness: a population-based study in the Greater Copenhagen Area.

Background: Severe mental illness (SMI) is associated with increased cardiovascular risk. Dyslipidaemia is a potentially modifiable risk factor, which may be inadequately managed in patients with SMI. Objectives: To assess management of dyslipidaemia in patients with SMI versus healthy controls (HCs) in 2005 and 2015. Design and methods: Using Danish registers, we identified adult patients with SMI in the Greater Copenhagen Area (schizophrenia spectrum disorders or bipolar disorder) with ⩾1 general practitioner contact in the year before 2005 and 2015, respectively, and HCs without SMI matched on age and gender (1:5). Outcomes were lipid-profile measurements, presence of dyslipidaemia and redemption of lipid-lowering pharmacotherapy. Differences in outcomes between patients with SMI and controls were measured with multivariable logistic regression. Results: We identified 7217 patients with SMI in 2005 and 9939 in 2015. After 10 years, patients went from having lower odds of lipid measurements to having higher odds of lipid measurements compared with HCs [odds ratio (OR)2005 0.70 (99% confidence interval (CI) 0.63-0.78) versus OR2015 1.34 (99% CI 1.24-1.44); p2005versus2015 < 0.01]. Patients had higher odds of dyslipidaemia during both years [OR2005 1.43 (99% CI 1.10-1.85) and OR2015 1.23 (99% CI 1.08-1.41)]. Patients went from having lower odds of receiving lipid-lowering pharmacotherapy to having higher odds of receiving lipid-lowering pharmacotherapy [OR2005 0.77 (99% CI 0.66-0.89) versus OR2015 1.37 (99% CI 1.24-1.51); p2005versus2015 < 0.01]. However, among persons at high cardiovascular risk, patients had lower odds of receiving lipid-lowering pharmacotherapy during both years, including subsets with previous acute coronary syndrome [OR2005 0.30 (99% CI 0.15-0.59) and OR2015 0.44 (99% CI 0.24-0.83)] and ischaemic stroke or transient ischaemic attack (TIA) [OR2005 0.43 (99% CI 0.26-0.69) and OR 2015 0.61 (99% CI 0.41-0.89)]. Conclusion: These results imply an increased general awareness of managing dyslipidaemia among patients with SMI in the primary prophylaxis of cardiovascular disease. However, secondary prevention with lipid-lowering drugs in patients with SMI at high cardiovascular risk may be lacking.