Structural variation in subcortical brain regions has been linked to substance use, including the most commonly used substances nicotine and alcohol. Pre-existing differences in subcortical brain volume may affect smoking and alcohol use, but there is also evidence that smoking and alcohol use can lead to structural changes.

We assess the causal nature of the complex relationship of subcortical brain volume with smoking and alcohol use, using bi-directional Mendelian randomisation.

Mendelian randomisation uses genetic variants predictive of a certain ‘exposure’ as instrumental variables to test causal effects on an ‘outcome’. Because of random assortment at meiosis, genetic variants should not be associated with confounders, allowing less biased causal inference. We used summary-level data of genome-wide association studies of subcortical brain volumes (nucleus accumbens, amygdala, caudate, hippocampus, pallidum, putamen and thalamus; n = 50 290) and smoking and alcohol use (smoking initiation, n = 848 460; cigarettes per day, n = 216 590; smoking cessation, n = 378 249; alcoholic drinks per week, n = 630 154; alcohol dependence, n = 46 568). The main analysis, inverse-variance weighted regression, was verified by a wide range of sensitivity methods.

There was strong evidence that liability to alcohol dependence decreased amygdala and hippocampal volume, and smoking more cigarettes per day decreased hippocampal volume. From subcortical brain volumes to substance use, there was no or weak evidence for causal effects.

Our findings suggest that heavy alcohol use and smoking can causally reduce subcortical brain volume. This adds to accumulating evidence that alcohol and smoking affect the brain, and likely mental health, warranting more recognition in public health efforts.

The largest excess mortality risk has been reported for combinations of psychiatric disorders that included substance use disorders.

To study the associations of different non-substance-related in-patient psychiatric diagnoses with all-cause mortality and suicide up to 28 years of age after entering substance use treatment.

National register data on psychiatric hospital admissions and death were combined with the treatment records of over 10 000 individuals in substance use treatment between 1990 and 2009. Cox regression was used to calculate hazard ratios (HRs) with 95% CIs for all-cause and suicide-specific mortality from the time of entering substance use treatment.

Nearly one-third (31.4%; n = 3330) of the study population had died during follow-up or by their 65th birthday, with more than one in ten (n = 385) from suicide. Over half of the study population (53.2%) had undergone psychiatric in-patient care and 14.1% involuntary psychiatric care during the study period. Bipolar disorder and unipolar depression were associated with a 57% (HR 1.57, 95% CI 1.18–2.10) and 132% (HR 2.32, 95% CI 1.21–4.46) increase in risk of suicide, respectively. Involuntary psychiatric care was associated with a 40% increase in risk of suicide (HR 1.42, 95% CI 1.05–1.94).

Severe psychiatric morbidity is common among individuals seeking treatment for alcohol and/or substance use and specifically mood disorders appear to increase the risk of suicide. Treatment service planning needs to focus on integrated care for concomitant substance use and psychiatric disorders to address this risk.

Severe mental illness (SMI) is associated with increased stroke risk, but little is known about how SMI relates to stroke prognosis and receipt of acute care.

To determine the association between SMI and stroke outcomes and receipt of process-of-care quality indicators (such as timely admission to stroke unit).

We conducted a cohort study using routinely collected linked data-sets, including adults with a first hospital admission for stroke in Scotland during 1991–2014, with process-of-care quality indicator data available from 2010. We identified pre-existing schizophrenia, bipolar disorder and major depression from hospital records. We used logistic regression to evaluate 30-day, 1-year and 5-year mortality and receipt of process-of-care quality indicators by pre-existing SMI, adjusting for sociodemographic and clinical factors. We used Cox regression to evaluate further stroke and vascular events (stroke and myocardial infarction).

Among 228 699 patients who had had a stroke, 1186 (0.5%), 859 (0.4%), 7308 (3.2%) had schizophrenia, bipolar disorder and major depression, respectively. Overall, median follow-up was 2.6 years. Compared with adults without a record of mental illness, 30-day mortality was higher for schizophrenia (adjusted odds ratio (aOR) = 1.33, 95% CI 1.16–1.52), bipolar disorder (aOR = 1.37, 95% CI 1.18–1.60) and major depression (aOR = 1.11, 95% CI 1.05–1.18). Each disorder was also associated with marked increased risk of 1-year and 5-year mortality and further stroke and vascular events. There were no clear differences in receipt of process-of-care quality indicators.

Pre-existing SMI was associated with higher risks of mortality and further vascular events. Urgent action is needed to better understand and address the reasons for these disparities.

Approximately 60 000 people in England have coexisting type 2 diabetes mellitus (T2DM) and severe mental illness (SMI). They are more likely to have poorer health outcomes and require more complex care pathways compared with those with T2DM alone. Despite increasing prevalence, little is known about the healthcare resource use and costs for people with both conditions.

To assess the impact of SMI on healthcare resource use and service costs for adults with T2DM, and explore the predictors of healthcare costs and lifetime costs for people with both conditions.

This was a matched-cohort study using data from the Clinical Practice Research Datalink linked to Hospital Episode Statistics for 1620 people with comorbid SMI and T2DM and 4763 people with T2DM alone. Generalised linear models and the Bang and Tsiatis method were used to explore cost predictors and mean lifetime costs respectively.

There were higher average annual costs for people with T2DM and SMI (£1930 higher) than people with T2DM alone, driven primarily by mental health and non-mental health-related hospital admissions. Key predictors of higher total costs were older age, comorbid hypertension, use of antidepressants, use of first-generation antipsychotics, and increased duration of living with both conditions. Expected lifetime costs were approximately £35 000 per person with both SMI and T2DM. Extrapolating nationally, this would generate total annual costs to the National Health Service of around £250 m per year.

Our estimates of resource use and costs for people with both T2DM and SMI will aid policymakers and commissioners in service planning and resource allocation.

Depression is associated with an increased dementia risk, but the nature of the association in the long-term remains unresolved, and the role of sociodemographic factors mainly unexplored.

To assess whether a history of clinical depression is associated with dementia in later life, controlling for observed sociodemographic factors and unobserved factors shared by siblings, and to test whether gender, educational level and marital status modify the association.

We conducted a national cohort study of 1 616 321 individuals aged 65 years or older between 2001 and 2018 using administrative healthcare data. A history of depression was ascertained from the national hospital register in the period 15–30 years prior to dementia follow-up. We used conventional and sibling fixed-effects Cox regression models to analyse the association between a history of depression, sociodemographic factors and dementia.

A history of depression was related to an adjusted hazard ratio of 1.27 (95% CI 1.23–1.31) for dementia in the conventional Cox model and of 1.55 (95% CI 1.09–2.20) in the sibling fixed-effects model. Depression was related to an elevated dementia risk similarly across all levels of education (test for interaction, P = 0.84), but the association was weaker for the widowed than for the married (P = 0.003), and stronger for men than women (P = 0.006). The excess risk among men attenuated following covariate adjustment (P = 0.10).

This study shows that a history of depression is consistently associated with later-life dementia risk. The results support the hypothesis that depression is an aetiological risk factor for dementia.

Coronavirus disease 2019 (COVID-19) has disproportionately affected people with mental health conditions.

We investigated the association between receiving psychotropic drugs, as an indicator of mental health conditions, and COVID-19 vaccine uptake.

We conducted a cross-sectional analysis of a prospective cohort of the Northern Ireland adult population using national linked primary care registration, vaccination, secondary care and pharmacy dispensing data. Univariable and multivariable logistic regression analyses investigated the association between anxiolytic, antidepressant, antipsychotic, and hypnotic use and COVID-19 vaccination status, accounting for age, gender, deprivation and comorbidities. Receiving any COVID-19 vaccine was the primary outcome.

There were 1 433 814 individuals, of whom 1 166 917 received a COVID-19 vaccination. Psychotropic medications were dispensed to 267 049 people. In univariable analysis, people who received any psychotropic medication had greater odds of receiving COVID-19 vaccination: odds ratio (OR) = 1.42 (95% CI 1.41–1.44). However, after adjustment, psychotropic medication use was associated with reduced odds of vaccination (ORadj = 0.90, 95% CI 0.89–0.91). People who received anxiolytics (ORadj = 0.63, 95% CI 0.61–0.65), antipsychotics (ORadj = 0.75, 95% CI 0.73–0.78) and hypnotics (ORadj = 0.90, 95% CI 0.87–0.93) had reduced odds of being vaccinated. Antidepressant use was not associated with vaccination (ORadj = 1.02, 95% CI 1.00–1.03).

We found significantly lower odds of vaccination in people who were receiving treatment with anxiolytic and antipsychotic medications. There is an urgent need for evidence-based, tailored vaccine support for people with mental health conditions.