Existing research demonstrates that insomnia is common, with significant negative impacts on health and quality of life. Cognitive–behavioural therapy for insomnia (CBT-I), the first-line treatment, is highly cost-effective. However, healthcare records have not been used in the UK to establish real-world insomnia prevalence, inequalities or unmet need.

This study’s aim was to establish the above in North Central London.

Data were extracted from primary care records across three London boroughs for 765 035 patients. Prevalence was determined by identifying those with a recent code for insomnia, insomnia treatment or sleeping tablet prescription.

Insomnia prevalence was 4.3%. Prevalence increased steadily with age, and was highest for women (4.9%), those of Bangladeshi ethnicity (7.3%) and those in the most deprived quintile (5.2%). Prevalence was significantly higher in patients with comorbidities (including chronic obstructive pulmonary disease (17.5%), severe mental illness (16.6%) and depression (14.1%)). Only 1.7% of people with insomnia had been referred for CBT-I.

Findings suggested that insomnia is at least as common as illnesses receiving high levels of focus and resourcing in the UK, and that prevalence estimates were probably underestimates. Variation in prevalence by demographic factors and deprivation may represent health inequalities. Insomnia was particularly common among patients with certain comorbidities and of advancing age, indicating that those groups should be actively screened. Concerningly, referral rates for CBT-I were extremely low. This has important implications regarding population health management, commissioning and training. Prevalence and unmet need are likely to be high in many other areas and should be investigated locally.

Depression severity is a well-established risk factor for suicidal ideation, but the extent to which sociodemographic and employment-related factors contribute independently remains unclear.

Complete data from doctors (N = 4055) presenting to National Health Service Practitioner Health (NHS-PH) in 2022–2023 were used to test the hypothesis that depression severity is the largest determinant of suicide ideation risk (defined by Patient Health Questionnaire 9 (PHQ-9) question 9 score) among doctors.

Using PHQ-8 score (PHQ-9, excluding the item on suicide ideation) as a proxy for depression severity, the case–control discriminatory capacity of receiver operating characteristic curves (AUCs) were evaluated for (a) a univariable model studying modified PHQ-9 alone as the predictor of severe suicide ideation; and (b) a multivariable model integrating modified PHQ-9 and multiple sociodemographic and employment factors as the predictor of severe suicide ideation. Models were compared both descriptively and through a likelihood ratio test.

The univariable model using depression severity alone as the predictor of severe suicide ideation yielded an AUC of 0.921. The addition of sociodemographic and employment factors improved the fit significantly (likelihood ratio test with (χ2(14) = 50.26, P < 0.001), amended AUC 0.930). Having both a disability and a relationship status of ‘no partner’ was significantly independently associated with suicide ideation in the multivariable model.

In this national cohort of doctors, depression severity was strongly associated with suicidal ideation. However, disability and lack of a partner were also independently linked to increased risk, suggesting that suicidal ideation is not solely driven by symptom severity. Social and functional factors may help identify higher-risk individuals and inform targeted support.

Promoting mental health, preventing mental disorders and providing effective treatments are public health priorities. Randomized controlled trials (RCTs) frequently evaluate mental health and psychosocial support interventions to achieve one or more of these objectives. Distinguishing between RCTs focused on mental health promotion, prevention or treatment remains conceptually and methodologically challenging. No standardized tool exists to position RCTs along a promotion-to-treatment continuum in mental health. We aimed to develop and validate the VErona-LUgano Tool (VELUT) for distinguishing RCTs along the promotion-to-treatment continuum.

An interdisciplinary tool development group (TDG) was established. The Population, Intervention, Comparison and Outcome framework was used to define key constructs. Items in the tool were devised, categorized and reduced through qualitative and quantitative methods. Finally, we performed a preliminary validation of the VELUT applying item response theory (IRT) using data from 180 RCTs.

The TDG generated 33 items for the initial version of the VELUT, reduced to 16 through review, cognitive interviews and psychometric analysis. Analyses of 180 RCTs using the 16-item tool showed high internal consistency (α = 0.94) and unidimensionality. Following item reduction and IRT, a final 8-item version was retained, and IRT models confirmed strong item discrimination for the 8 items and high scale reliability (marginal reliability >0.90 across most of the range of the scale), good response distribution, item performance and alignment with the Institute of Medicine (IOM) promotion-to-treatment continuum.

The VELUT addresses methodological gaps in global mental health research by helping to position RCTs of MHPSS interventions along the IOM promotion-to-treatment continuum.

Genetic risk scores hold potential for predicting depression in the general population. These scores must be validated for their associations with relevant characteristics of depression-related phenotypes, such as severity. We validated a genome-wide risk score (GRS) and a restricted polygenic risk score (PRS) for depression based on a meta-analysis of three genome-wide association studies and assessed their associations with depression in three subcohorts of middle-aged and older adults from the Dutch population-based Rotterdam Study.

Of participants with genotype data, 9,198 had longitudinally measured data (mean follow-up: 11.3 years) on three depression-related phenotypes (depressive symptoms, depressive syndrome, and major depressive disorder). Generalized linear models estimated the associations of standardized GRS and PRS with depression phenotypes per subcohort and were then meta-analyzed. One unit of the GRS/PRS represents 1 standard deviation, following z-transformation per cohort.

A one unit higher GRS and PRS were associated with any longitudinally measured depression phenotype (odds ratio (OR)GRS = 1.20 [1.15–1.26], ORPRS = 1.10 [1.05–1.16]). Effect sizes were highest for episodes of major depressive disorder: for individuals with the 10% highest GRS and PRS, the ORs were 1.99 [1.53–2.57] and 1.51 [1.13–1.99], respectively, compared to the middle 50% of the distribution.

The GRS and PRS for depression showed modest associations across multiple depression-related phenotypes in a population-based setting. The strength of associations generally increased with the severity of the phenotype. While effect sizes were generally larger for GRS compared to PRS, the difference was mostly not statistically significant.

The healthcare system accounts for 4 percent of United Kingdom (UK) greenhouse gas (GHG) emissions annually. In response to climate change, the National Health Service (NHS) is calling for less carbon-intensive care practices through prevention. Respiratory Syncytial Virus (RSV), a leading cause of infant hospitalization, currently has no widespread immunization program in the UK. This study estimates the impact on GHG emissions generated within the care pathway from an immunization against RSV in all infants in the UK with nirsevimab, a new monoclonal antibody used in prophylaxis.

A novel approach was applied, mapping care pathway emissions from immunization and avoiding RSV-related primary and secondary care burden. Avoided healthcare resources were estimated using a published health economic model for nirsevimab versus standard of care (SoC), which is characterized as receiving palivizumab or having no immunization intervention, assuming different universal immunization scenarios. NHS England GHG emission factors were applied to each health outcome to measure the GHG emissions associated with a nirsevimab versus SoC strategy.

Compared with SoC, a universal immunization program using nirsevimab leads to avoided GHG emissions, amounting to ~22 kilotons of CO2 equivalents per year, with immunizing all UK infants at birth leading to the greatest reduction. About 40 percent of avoided emissions were from reductions in inpatient hospitalizations.

This study shows how prevention can deliver benefits to people, NHS system capacity, and the environment. However, avoided patient care pathway emissions must be considered alongside drug lifecycle emissions, which are not included here.