An equitable child mental health service provides access to treatment proportionally to the need of individual demographic groups. Despite qualitative and survey-based evidence of barriers disadvantaging some demographic groups, it is not well understood how these barriers translate into quantifiable inequities. We calculated the treatment access rate for English children aged 6–16 years in 2021–2022, using the patient-level Mental Health Services Data Set and Mental Health of Children and Young People Survey.

The number of primary school children in treatment needs to increase nationally by 173%, the number of boys by 65% and the number of children from a White ethnic background by 31%, to achieve equity in treatment access. There was no evidence of inequities by area deprivation.

Child mental health services in England should not only increase overall access rates, but also pay more attention to equity in access across different demographic groups.

Despite growing awareness of the mental health damage caused by air pollution, the epidemiologic evidence on impact of air pollutants on major mental disorders (MDs) remains limited. We aim to explore the impact of various air pollutants on the risk of major MD.

This prospective study analyzed data from 170 369 participants without depression, anxiety, bipolar disorder, and schizophrenia at baseline. The concentrations of particulate matter with aerodynamic diameter ≤ 2.5 μm (PM2.5), particulate matter with aerodynamic diameter > 2.5 μm, and ≤ 10 μm (PM2.5–10), nitrogen dioxide (NO2), and nitric oxide (NO) were estimated using land-use regression models. The association between air pollutants and incident MD was investigated by Cox proportional hazard model.

During a median follow-up of 10.6 years, 9 004 participants developed MD. Exposure to air pollution in the highest quartile significantly increased the risk of MD compared with the lowest quartile: PM2.5 (hazard ratio [HR]: 1.16, 95% CI: 1.09–1.23), NO2 (HR: 1.12, 95% CI: 1.05–1.19), and NO (HR: 1.10, 95% CI: 1.03–1.17). Subgroup analysis showed that participants with lower income were more likely to experience MD when exposed to air pollution. We also observed joint effects of socioeconomic status or genetic risk with air pollution on the MD risk. For instance, the HR of individuals with the highest genetic risk and highest quartiles of PM2.5 was 1.63 (95% CI: 1.46–1.81) compared to those with the lowest genetic risk and lowest quartiles of PM2.5.

Our findings highlight the importance of air pollution control in alleviating the burden of MD.

Drug use Disorder (DUD), the risk for which is substantially influenced by both genetic and social factors, is geographically concentrated in high-risk regions. An important step toward understanding this pattern is to examine geographical distributions of the genetic liability to DUD and a key demographic risk factor – social deprivation.

We calculated the mean family genetic risk score (FGRS) for DUD ((FGRSDUD) and social deprivation for each of the 5983 areas Demographic Statistical Areas (DeSO) for all of Sweden and used geospatial techniques to analyze and map these factors.

Using 2018 data, substantial spatial heterogeneity was seen in the distribution of the genetic risk for DUD in Sweden as a whole and in its three major urban centers which was confirmed by hot-spot analyses. Across DeSOs, FGRSDUD and s.d. levels were substantially but imperfectly correlated (r = + 0.63), with more scattering at higher FGRSDUD and s.d. scores. Joint mapping across DeSOs for FGRSDUD and s.d. revealed a diversity of patterns across Sweden. The stability of the distributions of FGRSDUD and s.d. in DeSOs within Sweden over the years 2012–2018 was quite high.

The geographical distribution of the genetic risk to DUD is quite variable in Sweden. DeSO levels of s.d. and FRGSDUD were substantially correlated but also disassociated in a number of regions. The observed patterns were largely consistent with known trends in the human geography of Sweden. This effort lays the groundwork for further studies of the sources of geographic variation in rates of DUD.

In England in 2021, an estimated 274 000 people were homeless on a given night. It has long been recognised that physical and mental health of people who are homeless is poorer than for people who are housed. There are few peer-reviewed studies to inform health and social care for depression or anxiety among homeless adults in this setting.

To measure the symptoms of depression and anxiety among adults who are homeless and who have difficulty accessing healthcare, and to describe distribution of symptoms across sociodemographic, social vulnerability and health-related characteristics.

We completed structured questionnaires with 311 adults who were homeless and who had difficulty accessing healthcare in London, UK, between August and December 2021. We measured anxiety and depression symptoms using the 4-item Patient Health Questionnaire (PHQ-4) score. We compared median PHQ-4 scores across strata of the sociodemographic, social vulnerability and health-related characteristics, and tested for associations using the Kruskal–Wallis test.

The median PHQ-4 score was 8 out of 12, and 40.2% had scores suggesting high clinical need. Although PHQ-4 scores were consistently high across a range of socioeconomic, social vulnerability and health-related characteristics, they were positively associated with: young age; food insecurity; recent and historic abuse; joint, bone or muscle problems; and frequency of marijuana use. The most common (60%) barrier to accessing healthcare related to transportation.

Adults who are homeless and have difficulty accessing healthcare have high levels of depression and anxiety symptoms. Our findings support consideration of population-level, multisectoral intervention.

Knowledge on the link of individual social deprivation with dementia is incomplete. We thus aimed to see whether an association with dementia risk can be observed using a recently developed Social Deprivation Index (SoDep Index). Further, as deprivation is related to depression, we investigated the role of depression in the association.

We analysed data of 11 623 Survey of Health, Ageing and Retirement in Europe (SHARE) respondents. Social deprivation status was determined by SoDep Index score. Dementia was determined by self-reported diagnosis. Dementia risk by social deprivation status was estimated using Cox proportional hazard models, including relevant covariates (gender, marriage status, chronic conditions). Depressive symptom status was added in a second step. Further, we completed subgroup analyses by social deprivation status and analysed the relevance of depressive symptoms in dementia risk in each deprivation group. In an additional sensitivity analyses we corrected for mortality and used impaired cognitive testing performance as an alternative outcome.

High (v. low) social deprivation status was associated with an increased dementia risk (hazard ratio (HR) = 1.79 [95% CI 1.31–2.45]) in the Cox analysis adjusted for covariates only. Further adjustment for depressive symptom status indicated a largely direct association between social deprivation status and dementia risk. Moreover, compared to not having experienced depressive symptoms in the past or at baseline, those with past (HR = 1.67 [95% CI 1.23–2.25]), baseline (HR = 1.48 [95% CI 1.04–2.10]) or stable depressive symptoms (HR = 2.96 [95% CI 2.12–4.14]) had an increased dementia risk. The association between stable depressive symptom status and dementia risk was in the high social deprivation subgroup particularly pronounced. Sensitivity analyses replicated results.

Results add to a growing body of evidence indicating that a public health approach to dementia prevention must address socioeconomic inequity. Results suggest a largely direct association between social deprivation and dementia risk. Adults who experience high social deprivation appear particularly affected by detrimental effects of depressive symptomatology on dementia risk and need intervention.

Early-life interpersonal stress, particularly childhood maltreatment, is associated with neurobiological abnormalities. However, few studies have investigated the neural effects of peer victimisation.

This study examines common and specific associations between childhood maltreatment, peer victimisation and brain structural alterations in youths.

Grey matter volume (GMV) and cortical thickness data were collected from 105 age- and gender-matched youths (age range: 17–21 years). Region-of-interest and whole-brain analyses were conducted.

For the region-of-interest analyses, the childhood maltreatment group had smaller GMV than controls in left inferior frontal gyrus, bilateral anterior insula, postcentral and lingual regions, which were associated with greater emotional abuse, along with smaller insular GMV than the peer victimisation group, who had smaller left lingual and postcentral GMV than controls. At the whole-brain level, both childhood maltreatment and peer victimisation groups had smaller GMV than controls in a cluster comprising left post/precentral, inferior frontal gyrus, insula, superior parietal and supramarginal gyri. The peer victimisation group alone had increased cortical thickness in a cluster comprising left superior frontal, anterior cingulate and medial orbitofrontal gyri, which was related to greater cyberbullying.

Early-life interpersonal stress is associated with common structural alterations of the inferior frontal-limbic, sensory and lingual regions involved in cognitive control, emotion and sensory processing. The findings of childhood-maltreatment-related reduced anterior insular GMV and peer-victimisation-related increased cortical thickness in the left medial prefrontal-anterior cingulate cluster underscore the distinctive negative effects of childhood maltreatment and peer victimisation, and suggest that peer victimisation, particularly cyberbullying, could be as detrimental as childhood maltreatment.

Psychosis is associated with many forms of adversity, deprivation and living in urban areas.

To investigate whether psychosis is part of a syndemic of multiple adversities.

Drawing on UK Biobank (UKBB) data (Project ID: 57601), we sought to understand mechanisms by which childhood, recent/contemporary and place-based adversities might cluster and interact to be implicated in pathways by which psychoses evolve. We investigated the associations between adversities, potential mediating inflammatory markers and ICD-10 diagnoses (F20–F31) of psychotic disorders. We fitted logistic regression models initially including all relevant candidate variables and used backwards deletion to retain theoretically plausible and statistically significant (P < 0.05) associations with psychotic disorders. The candidate variables were entered in a partial least squares structural equation model (PLS-SEM) to test for syndemic interactions between risk factors. We tested whether the findings were sensitive to demographics, gender and ethnicity.

We fitted a PLS-SEM including psychosis as a syndemic outcome, and identified three latent constructs: lifetime adversity, current adversity and biomarkers. Factor loadings were above 0.30, and all structural paths were significant (P < 0.05). There were moderate associations between lifetime adversity and current adversity (standardised coefficient s.c. = 0.178) and between current adversity and biomarkers (s.c. = 0.227). All three latent constructs showed small but significant associations with psychosis (s.c. < 0.04). Lifetime adversity and current adversity were more strongly associated among ethnic minorities (combined) than White British people.

Our findings stress the importance of interactions between childhood and contemporary adversities in preventive and therapeutic interventions for psychotic disorders, especially among ethnic minorities.

In the UK, acute mental healthcare is provided by in-patient wards and crisis resolution teams. Readmission to acute care following discharge is common. Acute day units (ADUs) are also provided in some areas.

To assess predictors of readmission to acute mental healthcare following discharge in England, including availability of ADUs.

We enrolled a national cohort of adults discharged from acute mental healthcare in the English National Health Service (NHS) between 2013 and 2015, determined the risk of readmission to either in-patient or crisis teams, and used multivariable, multilevel logistic models to evaluate predictors of readmission.

Of a total of 231 998 eligible individuals discharged from acute mental healthcare, 49 547 (21.4%) were readmitted within 6 months, with a median time to readmission of 34 days (interquartile range 10–88 days). Most variation in readmission (98%) was attributable to individual patient-level rather than provider (trust)-level effects (2.0%). Risk of readmission was not associated with local availability of ADUs (adjusted odds ratio 0.96, 95% CI 0.80–1.15). Statistically significant elevated risks were identified for participants who were female, older, single, from Black or mixed ethnic groups, or from more deprived areas. Clinical predictors included shorter index admission, psychosis and being an in-patient at baseline.

Relapse and readmission to acute mental healthcare are common following discharge and occur early. Readmission was not influenced significantly by trust-level variables including availability of ADUs. More support for relapse prevention and symptom management may be required following discharge from acute mental healthcare.