Variation of subclinical psychosis across 16 sites in Europe and Brazil: findings from the multi-national EU-GEI study.

BACKGROUND: Incidence of first-episode psychosis (FEP) varies substantially across geographic regions. Phenotypes of subclinical psychosis (SP), such as psychotic-like experiences (PLEs) and schizotypy, present several similarities with psychosis. We aimed to examine whether SP measures varied across different sites and whether this variation was comparable with FEP incidence within the same areas. We further examined contribution of environmental and genetic factors to SP. METHODS: We used data from 1497 controls recruited in 16 different sites across 6 countries. Factor scores for several psychopathological dimensions of schizotypy and PLEs were obtained using multidimensional item response theory models. Variation of these scores was assessed using multi-level regression analysis to estimate individual and between-sites variance adjusting for age, sex, education, migrant, employment and relational status, childhood adversity, and cannabis use. In the final model we added local FEP incidence as a second-level variable. Association with genetic liability was examined separately. RESULTS: Schizotypy showed a large between-sites variation with up to 15% of variance attributable to site-level characteristics. Adding local FEP incidence to the model considerably reduced the between-sites unexplained schizotypy variance. PLEs did not show as much variation. Overall, SP was associated with younger age, migrant, unmarried, unemployed and less educated individuals, cannabis use, and childhood adversity. Both phenotypes were associated with genetic liability to schizophrenia. CONCLUSIONS: Schizotypy showed substantial between-sites variation, being more represented in areas where FEP incidence is higher. This supports the hypothesis that shared contextual factors shape the between-sites variation of psychosis across the spectrum.

Immune-neuroendocrine patterning and response to stress. A latent profile analysis in the English longitudinal study of ageing.

Psychosocial stress exposure can disturb communication signals between the immune, nervous, and endocrine systems that are intended to maintain homeostasis. This dysregulation can provoke a negative feedback loop between each system that has high pathological risk. Here, we explore patterns of immune-neuroendocrine activity and the role of stress. Using data from the English Longitudinal Study of Ageing (ELSA), we first identified the latent structure of immune-neuroendocrine activity (indexed by high sensitivity C-reactive protein [CRP], fibrinogen [Fb], hair cortisol [cortisol], and insulin growth-factor-1 [IGF-1]), within a population-based cohort using latent profile analysis (LPA). Then, we determined whether life stress was associated with membership of different immune-neuroendocrine profiles. We followed 4,934 male and female participants, with a median age of 65 years, over a four-year period (2008-2012). A three-class LPA solution offered the most parsimonious fit to the underlying immune-neuroendocrine structure in the data, with 36 %, 40 %, and 24 % of the population belonging to profiles 1 (low-risk), 2 (moderate-risk), and 3 (high-risk), respectively. After adjustment for genetic predisposition, sociodemographics, lifestyle, and health, higher exposure to stress was associated with a 61 % greater risk of belonging to the high-risk profile (RRR: 1.61; 95 %CI = 1.23-2.12, p = 0.001), but not the moderate-risk profile (RRR = 1.10, 95 %CI = 0.89-1.35, p = 0.401), as compared with the low-risk profile four years later. Our findings extend existing knowledge on psychoneuroimmunological processes, by revealing how inflammation and neuroendocrine activity cluster in a representative sample of older adults, and how stress exposure was associated with immune-neuroendocrine responses over time.

Refugee status and the incidence of affective psychotic disorders and non-psychotic bipolar disorder: A register-based cohort study of 1.3m people in Sweden.

BACKGROUND: Refugees are at increased risk of non-affective psychotic disorders, but it is unclear whether this extends to affective psychotic disorders [APD] or non-psychotic bipolar disorder [NPB]. METHODS: We conducted a nationwide cohort study in Sweden of all refugees, non-refugee migrants and the Swedish-born population, born 1 Jan 1984-31 Dec 2016. We followed participants from age 14 years until first ICD-10 diagnosis of APD or NPB. We fitted Cox proportional hazards models to estimate hazard ratios [HR] and 95 % confidence intervals [95%CI], adjusted for age, sex and family income. Models were additionally stratified by region-of-origin. RESULTS: We followed 1.3 million people for 15.1 million person-years, including 2428 new APD cases (rate: 16.0 per 100,000 person-years; 95%CI: 15.4-16.7) and 9425 NPB cases (rate: 63.8; 95%CI: 62.6-65.1). Rates of APD were higher in refugee (HRadjusted: 2.07; 95%CI: 1.55-2.78) and non-refugee migrants (HRadjusted: 1.40; 95%CI: 1.16-1.68), but lower for NPBs for refugee (HRadjusted: 0.24; 95%CI: 0.16-0.38) and non-refugee migrants (HRadjusted: 0.34; 95%CI: 0.28-0.41), compared with the Swedish-born. APD rates were elevated for both migrant groups from Asia and sub-Saharan Africa, but not other regions. Migrant groups from all regions-of-origin experienced lower rates of NPB. LIMITATIONS: Income may have been on the causal pathway making adjustment inappropriate. CONCLUSIONS: Refugees experience elevated rates of APD compared with Swedish-born and non-refugee migrants, but lower rates of NPB. This specificity of excess risk warrants clinical and public health investment in appropriate psychosis care for these vulnerable populations.

The effect of immigration policy reform on mental health in people from minoritised ethnic groups in England: an interrupted time series analysis of longitudinal data from the UK Household Longitudinal Study cohort.

BACKGROUND: In 2012, the UK Government announced a series of immigration policy reforms known as the hostile environment policy, culminating in the Windrush scandal. We aimed to investigate the effect of the hostile environment policy on mental health for people from minoritised ethnic backgrounds. We hypothesised that people from Black Caribbean backgrounds would have worse mental health relative to people from White ethnic backgrounds after the Immigration Act 2014 and the Windrush scandal media coverage in 2017, since they were particularly targeted. METHODS: Using data from the UK Household Longitudinal Study, we performed a Bayesian interrupted time series analysis, accounting for fixed effects of confounders (sex, age, urbanicity, relationship status, number of children, education, physical or mental health impairment, housing, deprivation, employment, place of birth, income, and time), and random effects for residual temporal and spatial variation. We measured mental ill health using a widely used, self-administered questionnaire on psychological distress, the 12-item General Health Questionnaire (GHQ-12). We compared mean differences (MDs) and 95% credible intervals (CrIs) in mental ill health among people from minoritised ethnic groups (Black Caribbean, Black African, Indian, Bangladeshi, and Pakistani) relative to people of White ethnicity during three time periods: before the Immigration Act 2014, after the Immigration Act 2014, and after the start of the Windrush scandal media coverage in 2017. FINDINGS: We included 58 087 participants with a mean age of 45·0 years (SD 34·6; range 16-106), including 31 168 (53·6%) female and 26 919 (46·3%) male participants. The cohort consisted of individuals from the following ethnic backgrounds: 2519 (4·3%) Black African, 2197 (3·8%) Black Caribbean, 3153 (5·4%) Indian, 1584 (2·7%) Bangladeshi, 2801 (4·8%) Pakistani, and 45 833 (78·9%) White. People from Black Caribbean backgrounds had worse mental health than people of White ethnicity after the Immigration Act 2014 (MD in GHQ-12 score 0·67 [95% CrI 0·06-1·28]) and after the 2017 media coverage (1·28 [0·34-2·21]). For Black Caribbean participants born outside of the UK, mental health worsened after the Immigration Act 2014 (1·25 [0·11-2·38]), and for those born in the UK, mental health worsened after the 2017 media coverage (2·00 [0·84-3·15]). We did not observe effects in other minoritised ethnic groups. INTERPRETATION: Our finding that the hostile environment policy worsened the mental health of people from Black Caribbean backgrounds in the UK suggests that sufficient, appropriate mental health and social welfare support should be provided to those affected. Impact assessments of new policies on minority mental health should be embedded in all policy making. FUNDING: Wellcome Trust.

Association of early-life exposure to air and noise pollution with youth mental health: findings from the ALSPAC cohort.

BACKGROUND: Increasing evidence suggests that air pollution exposure contributes to the development of mental health problems, including psychosis and depression. However, little is known about the importance of early-life exposure, nor the potential role of noise pollution, a correlate of air pollution. We examined the association of exposure to air and noise pollution from pregnancy to age 12 years with three mental health problems assessed at ages 12, 18, and 24 years. METHODS: Data were from the Avon Longitudinal Study of Parents and Children (ALSPAC), which tracks the development of about 14 000 babies who had expected delivery dates between April 1, 1991, and Dec 31, 1992, in Avon, UK. This was linked with novel data on nitrogen dioxide, PM2·5, and noise pollution in pregnancy, childhood (ages 1-9 years), and adolescence (ages 10-12 years). Psychotic experiences, depression, and anxiety were measured at ages 12, 18, and 24 years. Logistic regression models were controlled for individual-level, family-level, and area-level confounders, and e-values were calculated to estimate residual confounding. FINDINGS: Participants exposed to higher PM2.5, particularly during pregnancy, had greater odds for psychotic experiences (adjusted odds ratio 1·17 [95% CI 1·05-1·30]) and depression (1·11 [1·01-1·22]). There was little evidence associating nitrogen dioxide or noise pollution with psychotic experiences or depression. Conversely, higher nitrogen dioxide (but not PM2·5) exposure in pregnancy (1·16 [1·01-1·33]), and higher noise pollution in childhood (1·20 [1·06-1·37]) and adolescence (1·17 [1·02-1·35]), were associated with greater odds for anxiety. INTERPRETATION: Our study builds on evidence linking air pollution to psychosis and depression and provides rare longitudinal evidence linking noise pollution to anxiety. Our findings indicate that air pollution exposure earlier in development (eg, during pregnancy) might be particularly important, and suggest a degree of specificity in terms of pollutant-outcome associations. If causal, our findings suggest that interventions to reduce air pollution would improve global mental health. FUNDING: Wellcome Trust, UK Medical Research Council-Wellcome, and University of Bristol.

Air and Noise Pollution Exposure in Early Life and Mental Health From Adolescence to Young Adulthood.

Importance: Growing evidence associates air pollution exposure with various psychiatric disorders. However, the importance of early-life (eg, prenatal) air pollution exposure to mental health during youth is poorly understood, and few longitudinal studies have investigated the association of noise pollution with youth mental health. Objectives: To examine the longitudinal associations of air and noise pollution exposure in pregnancy, childhood, and adolescence with psychotic experiences, depression, and anxiety in youths from ages 13 to 24 years. Design, Setting, and Participants: This cohort study used data from the Avon Longitudinal Study of Parents and Children, an ongoing longitudinal birth cohort founded in 1991 through 1993 in Southwest England, United Kingdom. The cohort includes over 14 000 infants with due dates between April 1, 1991, and December 31, 1992, who were subsequently followed up into adulthood. Data were analyzed October 29, 2021, to March 11, 2024. Exposures: A novel linkage (completed in 2020) was performed to link high-resolution (100 m2) estimates of nitrogen dioxide (NO2), fine particulate matter under 2.5 µm (PM2.5), and noise pollution to home addresses from pregnancy to 12 years of age. Main outcomes and measures: Psychotic experiences, depression, and anxiety were measured at ages 13, 18, and 24 years. Logistic regression models controlled for key individual-, family-, and area-level confounders. Results: This cohort study included 9065 participants who had any mental health data, of whom (with sample size varying by parameter) 51.4% (4657 of 9051) were female, 19.5% (1544 of 7910) reported psychotic experiences, 11.4% (947 of 8344) reported depression, and 9.7% (811 of 8398) reported anxiety. Mean (SD) age at follow-up was 24.5 (0.8) years. After covariate adjustment, IQR increases (0.72 µg/m3) in PM2.5 levels during pregnancy (adjusted odds ratio [AOR], 1.11 [95% CI, 1.04-1.19]; P = .002) and during childhood (AOR, 1.09 [95% CI, 1.00-1.10]; P = .04) were associated with elevated odds for psychotic experiences. Pregnancy PM2.5 exposure was also associated with depression (AOR, 1.10 [95% CI, 1.02-1.18]; P = .01). Higher noise pollution exposure in childhood (AOR, 1.19 [95% CI, 1.03-1.38]; P = .02) and adolescence (AOR, 1.22 [95% CI, 1.02-1.45]; P = .03) was associated with elevated odds for anxiety. Conclusions and Relevance: In this longitudinal cohort study, early-life air and noise pollution exposure were prospectively associated with 3 common mental health problems from adolescence to young adulthood. There was a degree of specificity in terms of pollutant-timing-outcome associations. Interventions to reduce air and noise pollution exposure (eg, clean air zones) could potentially improve population mental health. Replication using quasi-experimental designs is now needed to shed further light on the underlying causes of these associations.

The social determinants of mental health and disorder: evidence, prevention and recommendations.

People exposed to more unfavourable social circumstances are more vulnerable to poor mental health over their life course, in ways that are often determined by structural factors which generate and perpetuate intergenerational cycles of disadvantage and poor health. Addressing these challenges is an imperative matter of social justice. In this paper we provide a roadmap to address the social determinants that cause mental ill health. Relying as far as possible on high-quality evidence, we first map out the literature that supports a causal link between social determinants and later mental health outcomes. Given the breadth of this topic, we focus on the most pervasive social determinants across the life course, and those that are common across major mental disorders. We draw primarily on the available evidence from the Global North, acknowledging that other global contexts will face both similar and unique sets of social determinants that will require equitable attention. Much of our evidence focuses on mental health in groups who are marginalized, and thus often exposed to a multitude of intersecting social risk factors. These groups include refugees, asylum seekers and displaced persons, as well as ethnoracial minoritized groups; lesbian, gay, bisexual, transgender and queer (LGBTQ+) groups; and those living in poverty. We then introduce a preventive framework for conceptualizing the link between social determinants and mental health and disorder, which can guide much needed primary prevention strategies capable of reducing inequalities and improving population mental health. Following this, we provide a review of the evidence concerning candidate preventive strategies to intervene on social determinants of mental health. These interventions fall broadly within the scope of universal, selected and indicated primary prevention strategies, but we also briefly review important secondary and tertiary strategies to promote recovery in those with existing mental disorders. Finally, we provide seven key recommendations, framed around social justice, which constitute a roadmap for action in research, policy and public health. Adoption of these recommendations would provide an opportunity to advance efforts to intervene on modifiable social determinants that affect population mental health.

Implementing and Evaluating a National Integrated Digital Registry and Clinical Decision Support System in Early Intervention in Psychosis Services (Early Psychosis Informatics Into Care): Co-Designed Protocol.

BACKGROUND: Early intervention in psychosis (EIP) services are nationally mandated in England to provide multidisciplinary care to people experiencing first-episode psychosis, which disproportionately affects deprived and ethnic minority youth. Quality of service provision varies by region, and people from historically underserved populations have unequal access. In other disease areas, including stroke and dementia, national digital registries coupled with clinical decision support systems (CDSSs) have revolutionized the delivery of equitable, evidence-based interventions to transform patient outcomes and reduce population-level disparities in care. Given psychosis is ranked the third most burdensome mental health condition by the World Health Organization, it is essential that we achieve the same parity of health improvements. OBJECTIVE: This paper reports the protocol for the program development phase of this study, in which we aimed to co-design and produce an evidence-based, stakeholder-informed framework for the building, implementation, piloting, and evaluation of a national integrated digital registry and CDSS for psychosis, known as EPICare (Early Psychosis Informatics into Care). METHODS: We conducted 3 concurrent work packages, with reciprocal knowledge exchange between each. In work package 1, using a participatory co-design framework, key stakeholders (clinicians, academics, policy makers, and patient and public contributors) engaged in 4 workshops to review, refine, and identify a core set of essential and desirable measures and features of the EPICare registry and CDSS. Using a modified Delphi approach, we then developed a consensus of data priorities. In work package 2, we collaborated with National Health Service (NHS) informatics teams to identify relevant data currently captured in electronic health records, understand data retrieval methods, and design the software architecture and data model to inform future implementation. In work package 3, observations of stakeholder workshops and individual interviews with representative stakeholders (n=10) were subject to interpretative qualitative analysis, guided by normalization process theory, to identify factors likely to influence the adoption and implementation of EPICare into routine practice. RESULTS: Stage 1 of the EPICare study took place between December 2021 and September 2022. The next steps include stage 2 building, piloting, implementation, and evaluation of EPICare in 5 demonstrator NHS Trusts serving underserved and diverse populations with substantial need for EIP care in England. If successful, this will be followed by stage 3, in which we will seek NHS adoption of EPICare for rollout to all EIP services in England. CONCLUSIONS: By establishing a multistakeholder network and engaging them in an iterative co-design process, we have identified essential and desirable elements of the EPICare registry and CDSS; proactively identified and minimized potential challenges and barriers to uptake and implementation; and addressed key questions related to informatics architecture, infrastructure, governance, and integration in diverse NHS Trusts, enabling us to proceed with the building, piloting, implementation, and evaluation of EPICare. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/50177.

The Role of Social Deprivation and Cannabis Use in Explaining Variation in the Incidence of Psychotic Disorders: Findings From the EU-GEI Study.

BACKGROUND AND HYPOTHESIS: Recent findings suggest the incidence of first-episode psychotic disorders (FEP) varies according to setting-level deprivation and cannabis use, but these factors have not been investigated together. We hypothesized deprivation would be more strongly associated with variation in FEP incidence than the prevalence of daily or high-potency cannabis use between settings. STUDY DESIGN: We used incidence data in people aged 18-64 years from 14 settings of the EU-GEI study. We estimated the prevalence of daily and high-potency cannabis use in controls as a proxy for usage in the population at-risk; multiple imputations by chained equations and poststratification weighting handled missing data and control representativeness, respectively. We modeled FEP incidence in random intercepts negative binomial regression models to investigate associations with the prevalence of cannabis use in controls, unemployment, and owner-occupancy in each setting, controlling for population density, age, sex, and migrant/ethnic group. STUDY RESULTS: Lower owner-occupancy was independently associated with increased FEP (adjusted incidence rate ratio [aIRR]: 0.76, 95% CI: 0.61-0.95) and non-affective psychosis incidence (aIRR: 0.68, 95% CI: 0.55-0.83), after multivariable adjustment. Prevalence of daily cannabis use in controls was associated with the incidence of affective psychoses (aIRR: 1.53, 95% CI: 1.02-2.31). We found no association between FEP incidence and unemployment or high-potency cannabis use prevalence. Sensitivity analyses supported these findings. CONCLUSIONS: Lower setting-level owner-occupancy and increased prevalence of daily cannabis use in controls independently contributed to setting-level variance in the incidence of different psychotic disorders. Public health interventions that reduce exposure to these harmful environmental factors could lower the population-level burden of psychotic disorders.

Development and Validation of Predictive Model for a Diagnosis of First Episode Psychosis Using the Multinational EU-GEI Case-control Study and Modern Statistical Learning Methods.

Background and Hypothesis: It is argued that availability of diagnostic models will facilitate a more rapid identification of individuals who are at a higher risk of first episode psychosis (FEP). Therefore, we developed, evaluated, and validated a diagnostic risk estimation model to classify individual with FEP and controls across six countries. Study Design: We used data from a large multi-center study encompassing 2627 phenotypically well-defined participants (aged 18-64 years) recruited from six countries spanning 17 research sites, as part of the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions study. To build the diagnostic model and identify which of important factors for estimating an individual risk of FEP, we applied a binary logistic model with regularization by the least absolute shrinkage and selection operator. The model was validated employing the internal-external cross-validation approach. The model performance was assessed with the area under the receiver operating characteristic curve (AUROC), calibration, sensitivity, and specificity. Study Results: Having included preselected 22 predictor variables, the model was able to discriminate adults with FEP and controls with high accuracy across all six countries (rangesAUROC = 0.84-0.86). Specificity (range = 73.9-78.0%) and sensitivity (range = 75.6-79.3%) were equally good, cumulatively indicating an excellent model accuracy; though, calibration slope for the diagnostic model showed a presence of some overfitting when applied specifically to participants from France, the UK, and The Netherlands. Conclusions: The new FEP model achieved a good discrimination and good calibration across six countries with different ethnic contributions supporting its robustness and good generalizability.

Neighborhood-Level Predictors of Age-at-First-Diagnosis of Psychotic Disorders: A Swedish Register-Based Cohort Study.

The relationship between neighborhood-level factors and the incidence of psychotic disorders is well established. However, it is unclear whether neighborhood characteristics are also associated with age-at-first-diagnosis of these disorders. We used linked Swedish register data to identify a cohort of persons first diagnosed with an ICD-10 non-affective or affective psychotic disorder (F20-33) between 1997 and 2016. Using multilevel mixed-effect linear modelling, we investigated whether neighborhood deprivation and population density at birth were associated with age-at-first diagnosis of a psychotic disorder. Our final cohort included 13,440 individuals, with a median age-at-first-diagnosis of 21.8 years for women (interquartile range [IQR]: 19.0-25.5) and 22.9 years for men (IQR: 20.1-26.1; P < .0001). In an unadjusted model, we found no evidence of an association between neighborhood deprivation and age-at-first-diagnosis of psychotic disorder (P = .07). However, after multivariable adjustment, age-at-first-diagnosis increased by .13 years (95% CI: .05 to .21; P = .002) for a one standard deviation increase in neighborhood deprivation. This was equivalent to a later diagnosis of 47 days (95% CI: 18 to 77). We found no evidence of a different relationship for non-affective versus affective psychoses [LRT χ 2(1) = .14; P = .71]. Population density was not associated with age-at-first-diagnosis in unadjusted (P = .81) or adjusted (P = .85) models. Later age-at-first-diagnosis for individuals born in more deprived neighborhoods suggests structural barriers in accessing equitable psychiatric care.