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Monitoring of the mental health status of the population and assessment of its determinants are 2 of the most relevant pillars of public mental health, and data from population health surveys could be instrumental to support them. Although these surveys could be an important and suitable resource for these purposes, due to different limitations and challenges, they are often relegated to the background behind other data sources, such as electronic health records. These limitations and challenges include those related to measurement properties and cross-cultural validity of the tools used for the assessment of mental disorders, their degree of representativeness, and possible difficulties in the linkage with other data sources. Successfully addressing these limitations could significantly increase the potential of health surveys in the monitoring of mental disorders and ultimately maximize the impact of the relevant policies to reduce their burden at the population level. The widespread use of data from population health surveys, ideally linked to electronic health records data, would enhance the quality of the information available for research, public mental health decision-making, and ultimately addressing the growing burden of mental disorders.

Summary: Background: The 8-item version of the Patient Health Questionnaire (PHQ-8) is one of the self-reported questionnaires most frequently used worldwide for the screening and severity assessment of depression. However, in some European countries its reliability is unknown, and it is unclear whether its psychometric properties vary between European countries. Therefore, the aim of this study was to assess the internal structure, reliability and cross-country equivalence of the PHQ-8 in Europe. Methods: All participants from the 27 countries included in the second wave of the European Health Interview Survey (EHIS-2) between 2014 and 2015 with complete information on the PHQ-8 were included (n = 258,888). The internal structure of the PHQ-8 was assessed using confirmatory factor analyses (CFA) for categorical items. Additionally, the reliability of the questionnaire was assessed based on the internal consistency, Item Response Theory information functions, and item-discrimination (using Graded Response Models), and the cross-country equivalence based on multi-group CFA. Findings: The PHQ-8 shows high internal consistency for all countries. The countries in which the PHQ-8 was more reliable were Romania, Bulgaria and Cyprus and less reliable were Iceland, Norway and Austria. The PHQ-8 item with highest discrimination was item 2 (feeling down, depressed, or hopeless) in 24 of the 27 countries. Measurement invariance between countries in Europe was observed from multigroup CFA at the configural, metric and scalar levels. Interpretation: The results from our study, likely the largest study to the date assessing the internal structure, reliability and cross-country comparability of a self-reported mental health assessment measure, shows that the PHQ-8 has an adequate reliability and cross-country equivalence across the 27 European countries included. These results highlight the suitability of the comparisons of the PHQ-8 scores in Europe. They could be helpful to improve the screening and severity assessment of depressive symptoms at the European level. Funding: This work was partially funded by CIBER Epidemiology and Public Health (CIBERESP) as part of the Intramural call of 2021 (ESP21PI05).

BackgroundLong-term exposure to air pollution concentrations is known to be adversely associated with a broad range of single non-communicable diseases, but its role in multimorbidity has not been investigated in the UK. We aimed to assess associations between long-term air pollution exposure and multimorbidity status, severity, and patterns using the UK Biobank cohort.MethodsMultimorbidity status was calculated based on 41 physical and mental conditions. We assessed cross-sectional associations between annual modeled particulate matter (PM)2.5, PMcoarse, PM10, and nitrogen dioxide (NO2) concentrations (μg/m3–modeled to residential address) and multimorbidity status at the baseline assessment (2006–2010) in 364,144 people (mean age: 52.2 ± 8.1 years, 52.6% female). Air pollutants were categorized into quartiles to assess dose-response associations. Among those with multimorbidity (≥2 conditions; n = 156,395) we assessed associations between air pollutant exposure levels and multimorbidity severity and multimorbidity patterns, which were identified using exploratory factor analysis. Associations were explored using generalized linear models adjusted for sociodemographic, behavioral, and environmental indicators.ResultsHigher exposures to PM2.5, and NO2 were associated with multimorbidity status in a dose-dependent manner. These associations were strongest when we compared the highest air pollution quartile (quartile 4: Q4) with the lowest quartile (Q1) [PM2.5: adjusted odds ratio (adjOR) = 1.21 (95% CI = 1.18, 1.24); NO2: adjOR = 1.19 (95 % CI = 1.16, 1.23)]. We also observed dose-response associations between air pollutant exposures and multimorbidity severity scores. We identified 11 multimorbidity patterns. Air pollution was associated with several multimorbidity patterns with strongest associations (Q4 vs. Q1) observed for neurological (stroke, epilepsy, alcohol/substance dependency) [PM2.5: adjOR = 1.31 (95% CI = 1.14, 1.51); NO2: adjOR = 1.33 (95% CI = 1.11, 1.60)] and respiratory patterns (COPD, asthma) [PM2.5: adjOR = 1.24 (95% CI = 1.16, 1.33); NO2: adjOR = 1.26 (95% CI = 1.15, 1.38)].ConclusionsThis cross-sectional study provides evidence that exposure to air pollution might be associated with having multimorbid, multi-organ conditions. Longitudinal studies are needed to further explore these associations.

Background The association of COVID-19 infection with death in people with severe mental illnesses (SMI), and the relationship to multimorbidities/ underlying health conditions ethnicity is unclear. Health records linked to COVID-19 tests data could help to inform this knowledge gap. Objective To determine the risk of death in people with SMI following COVID-19 infection compared to reference groups and assess whether excess mortality is accounted through underlying health conditions or further elevated in minority ethnic groups. Design, setting and participants Nationally representative cohort study using primary care data from the Clinical Practice Research Database (CPRD), with participants followed from the start of the pandemic in 2020, for 1.5 years, covering England, Wales and Northern Ireland. For consenting practices, CPRD data was linked to COVID-19 data Public Health England (PHE) Second Generation Surveillance System (SGSS), PHE COVID-19 Hospitalisation in England Surveillance System (CHESS), and Intensive Care National Audit and Research Centre (ICNARC) data on COVID-10 intensive care admissions. The cohort comprised 795,836 individuals, with 7,493 individuals with SMI and a positive COVID-19 test (“SMI/COVID-19”). Comparison groups were: 2,325 individuals with SMI/ testing negative for COVID-19 (“SMI/ non COVID-19”), 657,414 individuals from a non-SMI group/ testing positive for COVID-19 (“non-SMI/ COVID-19”), and 128,604 individuals from a non-SMI group/ testing negative for COVID-19 (“non-SMI/ non-COVID-19”). Exposures SMI defined as the presence of schizophrenia, schizoaffective disorder, bipolar disorder, or affective disorders with psychosis, according to the International Classification of Mental Disorders (ICD-10). COVID-19 diagnoses identified through confirmed laboratory tests and clinical diagnoses. Outcomes All-cause mortality Results A higher proportion of SMI patients with COVID-19 were obese (37% versus 22% in the non-SMI/non-COVID-19 group), current smokers (27% versus 23% in the non-SMI/non-COVID-19 group), had underlying health conditions, and were Black Caribbean/ Black African (5% versus 1% in the non-SMI/non-COVID-19 group). Relative to the non-SMI/ non-COVID-19 group, the SMI/ COVID-19 group had an elevated risk of death (age and sex-adjusted hazard ratio (aHR) 5.03 (95%CI: 4.61-5.54)). This was elevated to a lesser extent, in the SMI/ non COVID-19 group (aHR: 1.93 (95%CI: 1.54-2.41)) and in the non-SMI/ COVID-19 group (aHR: 2.85 (95%CI: 2.72-2.98). Excess risk persisted after adjusting for tobacco use, weight and comorbidities. Mortality trends were similar across groups by ethnicity. Risk of death was highest for the SMI/ COVID-19 group during the first wave of infection in the UK, however excess mortality was still evident and substantially elevated at the second wave also. Conclusions People living with SMI are at an increased risk of death compared to population controls; this excess risk is further elevated following COVID-19 infection, with similar trends by ethnicity. Underlying health conditions only partially account for deaths following COVID-19 infection in this group.

BackgroundThe effect of antibiotics on the human microbiome is now well established, but their indirect effect on the related immune response is less clear. The possible association of Herpes zoster, which involves a reactivation of a previous varicella zoster virus infection, with prior antibiotic exposure might indicate a potential link with the immune response.MethodsA case-control study was carried out using a clinical database, the UK's Clinical Practice Research Datalink. A total of 163,754 patients with varicella zoster virus infection and 331,559 age/sex matched controls were identified and their antibiotic exposure over the previous 10 years, and longer when data permitted, was identified. Conditional logistic regression was used to identify the association between antibiotic exposure and subsequent infection in terms of volume and timing.ResultsThe study found an association of antibiotic prescription and subsequent risk of varicella zoster virus infection (adjusted odds ratio of 1.50; 95%CIs: 1.42-1.58). The strongest association was with a first antibiotic over 10 years ago (aOR: 1.92; 95%CIs: 1.88-1.96) which was particularly pronounced in the younger age group of 18 to 50 (aOR 2.77; 95%CIs: 1.95-3.92).ConclusionsBy finding an association between prior antibiotics and Herpes zoster this study has shown that antibiotics may be involved in the reactivation of the varicella zoster virus. That effect, moreover, may be relatively long term. This indirect effect of antibiotics on viruses, possibly mediated through their effect on the microbiome and immune system, merits further study.

ABSTRACT: BACKGROUND: People with mental disorders and intellectual disabilities experience excess mortality compared with the general population. The impact of COVID-19 on exacerbating this, and in widening ethnic inequalities, is unclear. METHODS: Prospective data (N=167,122) from a large mental healthcare provider in London, UK, with deaths from 2019 to 2020, used to assess age- and gender-standardised mortality ratios (SMRs) across nine psychiatric conditions (schizophrenia-spectrum disorders, affective disorders, somatoform/ neurotic disorders, personality disorders, learning disabilities, eating disorders, substance use disorders, pervasive developmental disorders, dementia) and by ethnicity. FINDINGS: Prior to the World Health Organization (WHO) declaring COVID-19 a public health emergency on 30th January 2020, all-cause SMRs across all psychiatric cohorts were more than double the general population. By the second quarter of 2020, when the UK experienced substantial peaks in COVID-19 deaths, all-cause SMRs increased further, with COVID-19 SMRs elevated across all conditions (notably: learning disabilities: SMR: 9.24 (95% CI: 5.98-13.64), pervasive developmental disorders: 5.01 (95% CI: 2.40-9.20), eating disorders: 4.81 (95% CI: 1.56-11.22), schizophrenia-spectrum disorders: 3.26 (95% CI: 2.55-4.10), dementia: 3.82 (95% CI: 3.42, 4.25) personality disorders 4.58 (95% CI: 3.09-6.53)). Deaths from other causes remained at least double the population average over the whole year. Increased SMRs were similar across ethnic groups. INTERPRETATION: People with mental disorders and intellectual disabilities were at a greater risk of deaths relative to the general population before, during and after the first peak of COVID-19 deaths, with similar risks by ethnicity. Mortality from non-COVID-19/ other causes was elevated before/ during the pandemic, with higher COVID-19 mortality during the pandemic. FUNDING: ESRC (JD, CM), NIHR (JD, RS, MH), Health Foundation (JD), GSK, Janssen, Takeda (RS).

Summary: Background: We aimed to estimate the prevalence of current depressive disorder in 27 European countries, and to explore differences in prevalence between European countries and by gender. Methods: In this population-based study, we analysed data from respondents living in 27 European countries who were included in the second wave of the European Health Interview Survey, collected between 2013 and 2015. We assessed the prevalence of current depressive disorder using the eight-item Patient Health Questionnaire (PHQ-8), with depressive disorder defined as a PHQ-8 score of 10 or higher. Prevalence estimates and 95% CIs were calculated for all 27 countries overall and for each country individually. We assessed variation in prevalence (country vs the rest of Europe) using crude and adjusted prevalence ratios obtained from negative binomial regression models. We did all analyses for the total sample and stratified by gender. Findings: Our analysis sample comprised 258 888 individuals, of whom 117 310 (weighted proportion 47·8%) were men and 141 578 (52·2%) were women. The overall prevalence of current depressive disorder was 6·38% (95% CI 6·24–6·52) with important variation across countries, ranging from 2·58% (2·14–3·02) in the Czech Republic to 10·33% (9·33–11·32) in Iceland. Prevalence was higher in women (7·74% [7·53–7·95]) than in men (4·89% [4·71–5·08]), with clear gender differences for all countries except Finland and Croatia. Compared with the other European countries in our sample, those with the highest adjusted prevalence ratios were Germany (1·80 [1·71–1·89]) and Luxembourg (1·50 [1·35–1·66]), and those with the lowest adjusted prevalence ratios were Slovakia (0·28 [0·24–0·33]) and the Czech Republic (0·32 [0·27–0·38]). Interpretation: Depressive disorders, although common across Europe, vary substantially in prevalence between countries. These results could be a baseline for monitoring the prevalence of current depressive disorder both at a country level in Europe and for planning health-care resources and services. Funding: UK Medical Research Council and CIBER Epidemiology and Public Health (CIBERESP).

BackgroundTo estimate the potential gain in life expectancy from addressing modifiable risk factors for all-cause mortality (excluding suicide and deaths from accidents or violence) across specific serious mental illness (SMI) subgroups, namely schizophrenia, schizoaffective disorders, and bipolar disorders in a Western population.MethodsWe have used relative risks from recent meta-analyses to estimate the population attribution fraction (PAF) due to specific modifiable risk factors known to be associated with all-cause mortality within SMI. The potential gain in life expectancy at birth, age 50 and age 65 years were assessed by estimating the combined effect of modifiable risk factors from different contextual levels (behavioural, healthcare, social) and accounting for the effectiveness of existing interventions tackling these factors. Projections for annual gain in life expectancy at birth during a two-decade was estimated using the Annual Percentage Change (APC) formula. The predicted estimates were based on mortality rates for year 2014-2015.ResultsBased on the effectiveness of existing interventions targeting these modifiable risk factors, we estimated potential gain in life expectancy at birth of four (bipolar disorders), six (schizoaffective disorders), or seven years (schizophrenia). The gain in life expectancy at age 50 years was three (bipolar disorders) or five (schizophrenia and schizoaffective disorders) years. The projected gain in life expectancy at age 65 years was three (bipolar disorders) or four (schizophrenia and schizoaffective disorders) years.ConclusionsThe implementation of existing interventions targeting modifiable risk factors could narrow the current mortality gap between the general and the SMI populations by 24% (men) to 28% (women). These projections represent ideal circumstances and without the limitation of overestimation which often comes with PAFs.

Typologies of sleep problems have usually relied on identifying underlying causes or symptom clusters. In this study the value of using the patient's own reasons for sleep disturbance are explored. Using secondary data analysis of a nationally representative psychiatric survey the patterning of the various reasons respondents provided for self-reported sleep problems were examined. Over two thirds (69.3%) of respondents could identify a specific reason for their sleep problem with worry (37.9%) and illness (20.1%) representing the most commonly reported reasons. And while women reported more sleep problems for almost every reason compared with men, the patterning of reasons by age showed marked variability. Sleep problem symptoms such as difficulty getting to sleep or waking early also showed variability by different reasons as did the association with major correlates such as worry, depression, anxiety and poor health. While prevalence surveys of 'insomnia' or 'poor sleep' often assume the identification of an underlying homogeneous construct there may be grounds for recognising the existence of different sleep problem types particularly in the context of the patient's perceived reason for the problem.

This study aimed to evaluate mortality within 365 days of HbA1c values of 9.0% in participants with clinical type 2 diabetes mellitus. A matched nested case-control study was implemented, within a cohort of participants with type 2 diabetes from 2000 to 2008. Conditional logistic regression was used to model the odds ratio for mortality adjusting for comorbidity and drug utilisation. There were 97,450 participants with type 2 diabetes; 16,585 cases that died during follow up were matched to 16,585 controls. The most recent HbA1c value was 9.0% for 9.0% of cases and 7.7% of controls. In a complete case analysis, the adjusted odds ratio (AOR) for mortality associated with most recent HbA1c 9.0% of 1.51 (CI: 1.33, 1.70), in the multiple imputation analysis this was 1.29 (1.17,1.41). The risk associated with HbA1c 9.0% may be associated with increased mortality within one year in clinical type 2 diabetes. Relative risks may be higher at younger ages.