Exploring experiences with alcohol and how drinking has changed over time among minority ethnic groups with a diagnosed mental health problem.

INTRODUCTION: Minority ethnic groups are more likely to experience poor mental health but less likely to seek formal support. Mental health problems and alcohol use (including non-drinking) co-occur, the reasons for this among minority ethnic groups are not well understood. This study explored i) alcohol use among minority ethnic individuals with a mental health problem,ii) how alcohol was used before individuals received support for their mental health,iii) how alcohol changed whilst and after individuals received treatment for their mental health. METHODS: Participants were purposively sampled through community/online mental health organisations. Participants took part if they i)were not White British, ii) had a mental health diagnosis, iii) drank at hazardous and above levels or former drinkers. Telephone/online semi-structured interviews were conducted. Data were analysed using framework analysis with an intersectional lens. RESULTS: 25 participants took part. Four themes were developed; "drinking motivations", "mental health literacy and implications on drinking behaviour", "cultural expectations and its influence on mental health problems and drinking practices", and "reasons for changes in drinking". Themes reflect reasons for drinking and the role of understanding the range of mental health problems and implicit cultural expectations. An intersectional lens indicated gendered, ethnic and religious nuances in experiences with alcohol and seeking support. Engaging with formal support prompted changes in drinking which were facilitated through wider support. CONCLUSION: There were specific reasons to cope among minority ethnic individuals who have a mental health problem. Applying an intersectional lens provided an insight into the role of cultural and gendered expectations on mental health and drinking practices. Mental health literacy and implicit cultural expectations within specific minority ethnic groups can affect both mental health and drinking practices. Healthcare professionals and wider community play an important role in prompting changes in drinking among minority ethnic groups who have a mental health problem.

Impact of inconsistent ethnicity recordings on estimates of inequality in child health and education data: a data linkage study of Child and Adolescent Mental Health Services in South London.

OBJECTIVES: Ethnicity data are critical for identifying inequalities, but previous studies suggest that ethnicity is not consistently recorded between different administrative datasets. With researchers increasingly leveraging cross-domain data linkages, we investigated the completeness and consistency of ethnicity data in two linked health and education datasets. DESIGN: Cohort study. SETTING: South London and Maudsley NHS Foundation Trust deidentified electronic health records, accessed via Clinical Record Interactive Search (CRIS) and the National Pupil Database (NPD) (2007-2013). PARTICIPANTS: N=30 426 children and adolescents referred to local Child and Adolescent Mental Health Services. PRIMARY AND SECONDARY OUTCOME MEASURES: Ethnicity data were compared between CRIS and the NPD. Associations between ethnicity as recorded from each source and key educational and clinical outcomes were explored with risk ratios. RESULTS: Ethnicity data were available for 79.3% from the NPD, 87.0% from CRIS, 97.3% from either source and 69.0% from both sources. Among those who had ethnicity data from both, the two data sources agreed on 87.0% of aggregate ethnicity categorisations overall, but with high levels of disagreement in Mixed and Other ethnic groups. Strengths of associations between ethnicity, educational attainment and neurodevelopmental disorder varied according to which data source was used to code ethnicity. For example, as compared with White pupils, a significantly higher proportion of Asian pupils achieved expected educational attainment thresholds only if ethnicity was coded from the NPD (RR=1.46, 95% CI 1.29 to 1.64), not if ethnicity was coded from CRIS (RR=1.11, 0.98 to 1.26). CONCLUSIONS: Data linkage has the potential to minimise missing ethnicity data, and overlap in ethnicity categorisations between CRIS and the NPD was generally high. However, choosing which data source to primarily code ethnicity from can have implications for analyses of ethnicity, mental health and educational outcomes. Users of linked data should exercise caution in combining and comparing ethnicity between different data sources.

Interventions targeting social determinants of mental disorders and the Sustainable Development Goals: a systematic review of reviews.

Globally, mental disorders account for almost 20% of disease burden and there is growing evidence that mental disorders are socially determined. Tackling the United Nations Sustainable Development Goals (UN SDGs), which address social determinants of mental disorders, may be an effective way to reduce the global burden of mental disorders. We conducted a systematic review of reviews to examine the evidence base for interventions that map onto the UN SDGs and seek to improve mental health through targeting known social determinants of mental disorders. We included 101 reviews in the final review, covering demographic, economic, environmental events, neighborhood, and sociocultural domains. This review presents interventions with the strongest evidence base for the prevention of mental disorders and highlights synergies where addressing the UN SDGs can be beneficial for mental health.

Understanding social and clinical associations with unemployment for people with schizophrenia and bipolar disorders: large-scale health records study.

PURPOSE: People with severe mental illness (SMI) experience high levels of unemployment. We aimed to better understand the associations between clinical, social, and demographic inequality indicators and unemployment. METHODS: Data were extracted from de-identified health records of people with SMI in contact with secondary mental health services in south London, UK. A Natural Language Processing text-mining application was applied to extract information on unemployment in the health records. Multivariable logistic regression was used to assess associations with unemployment, in people with SMI. RESULTS: Records from 19,768 service users were used for analysis, 84.9% (n = 16,778) had experienced unemployment. In fully adjusted models, Black Caribbean and Black African service users were more likely to experience unemployment compared with White British service users (Black Caribbean: aOR 1.62, 95% CI 1.45-1.80; Black African: 1.32, 1.15-1.51). Although men were more likely to have experienced unemployment relative to women in unadjusted models (OR 1.36, 95% CI 1.26-1.47), differences were no longer apparent in the fully adjusted models (aOR 1.05, 95% CI 0.97-1.15). The presence of a non-affective (compared to affective) diagnosis (1.24, 1.13-1.35), comorbid substance use (2.02, 1.76-2.33), previous inpatient admissions (4.18, 3.71-4.70), longer inpatient stays (78 + days: 7.78, 6.34-9.54), and compulsory admissions (3.45, 3.04-3.92) were associated with unemployment, in fully adjusted models. CONCLUSION: People with SMI experience high levels of unemployment, and we found that unemployment was associated with several clinical and social factors. Interventions to address low employment may need to also address these broader inequalities.

Improving our understanding of the social determinants of mental health: a data linkage study of mental health records and the 2011 UK census.

OBJECTIVES: To address the lack of individual-level socioeconomic information in electronic healthcare records, we linked the 2011 census of England and Wales to patient records from a large mental healthcare provider. This paper describes the linkage process and methods for mitigating bias due to non-matching. SETTING: South London and Maudsley NHS Foundation Trust (SLaM), a mental healthcare provider in Southeast London. DESIGN: Clinical records from SLaM were supplied to the Office of National Statistics for linkage to the census through a deterministic matching algorithm. We examined clinical (International Classification of Disease-10 diagnosis, history of hospitalisation, frequency of service contact) and socio-demographic (age, gender, ethnicity, deprivation) information recorded in Clinical Record Interactive Search (CRIS) as predictors of linkage success with the 2011 census. To assess and adjust for potential biases caused by non-matching, we evaluated inverse probability weighting for mortality associations. PARTICIPANTS: Individuals of all ages in contact with SLaM up until December 2019 (N=459 374). OUTCOME MEASURES: Likelihood of mental health records' linkage to census. RESULTS: 220 864 (50.4%) records from CRIS linked to the 2011 census. Young adults (prevalence ratio (PR) 0.80, 95% CI 0.80 to 0.81), individuals living in more deprived areas (PR 0.78, 95% CI 0.78 to 0.79) and minority ethnic groups (eg, Black African, PR 0.67, 0.66 to 0.68) were less likely to match to census. After implementing inverse probability weighting, we observed little change in the strength of association between clinical/demographic characteristics and mortality (eg, presence of any psychiatric disorder: unweighted PR 2.66, 95% CI 2.52 to 2.80; weighted PR 2.70, 95% CI 2.56 to 2.84). CONCLUSIONS: Lower response rates to the 2011 census among people with psychiatric disorders may have contributed to lower match rates, a potential concern as the census informs service planning and allocation of resources. Due to its size and unique characteristics, the linked data set will enable novel investigations into the relationship between socioeconomic factors and psychiatric disorders.

A quantitative approach to the intersectional study of mental health inequalities during the COVID-19 pandemic in UK young adults.

PURPOSE: Mental health inequalities across social identities/positions during the COVID-19 pandemic have been mostly reported independently from each other or in a limited way (e.g., at the intersection between age and sex or gender). We aim to provide an inclusive socio-demographic mapping of different mental health measures in the population using quantitative methods that are consistent with an intersectional perspective. METHODS: Data included 8,588 participants from two British cohorts (born in 1990 and 2000-2002, respectively), collected in February/March 2021 (during the third UK nationwide lockdown). Measures of anxiety and depressive symptomatology, loneliness, and life satisfaction were analysed using Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) models. RESULTS: We found evidence of large mental health inequalities across intersectional strata. Large proportions of those inequalities were accounted for by the additive effects of the variables used to define the intersections, with some of the largest gaps associated with sexual orientation (with sexual minority groups showing substantially worse outcomes). Additional inequalities were found by cohort/generation, birth sex, racial/ethnic groups, and socioeconomic position. Intersectional effects were observed mostly in intersections defined by combinations of privileged and marginalised social identities/positions (e.g., lower-than-expected life satisfaction in South Asian men in their thirties from a sexual minority and a disadvantaged childhood social class). CONCLUSION: We found substantial inequalities largely cutting across intersectional strata defined by multiple co-constituting social identities/positions. The large gaps found by sexual orientation extend the existing evidence that sexual minority groups were disproportionately affected by the pandemic. Study implications and limitations are discussed.

Differences in the impact of the COVID-19 pandemic in the long-term trajectories of life satisfaction by sex in the UK: a prospective cohort study.

BACKGROUND: The COVID-19 pandemic has disproportionately affected women's mental health, with most evidence focused on mental ill-health outcomes. Previous research suggests that differences in time-use might explain this disparity, as women generally spent more time doing psychologically taxing activities than men. We investigated (1) sex differences in the impact of the pandemic in the long-term trajectories of life satisfaction and (2) whether time-use differences partly explained that differential impact. METHODS: In this prospective cohort study, we used the 1970 British Cohort Study, a birth cohort representing people born in Great Britain in 1970. Since 1970, information has been collected for all cohort members every 4-10 years (ten sweeps). Additional data were collected at three timepoints during the pandemic (May 2020, September-October 2020, February-March 2021) as part of the COVID-19 Survey. Response rates within the target population ranged between 23·6% (May, 2020) and 32·5% (March, 2021) in the COVID-19 Survey. We used non-response weights to restore sample representativeness to the target population (cohort members alive and residing in the UK during the pandemic). Life satisfaction was prospectively assessed at ages 26 (1996), 30, 34, 42, 46, 50, 50·5, and 51 years (2021) using a single question with responses ranging from 0 (lowest life satisfaction) to 10 (highest life satisfaction). We used multiple-group piecewise latent growth curve models grouped by sex assigned at birth. Additional models were adjusted for self-reported number of hours spent working, volunteering, home-schooling children, taking care of children and other people, and doing housework during the pandemic. Participants provided verbal informed consent. Ethics approval was not sought as non-sensitive, open-access data with minimal risk of identification was used. FINDINGS: We analysed data from 6766 adults (3799 [56·2%] women and 2967 [43·8%] men). Compared with men, women had consistently higher levels of life satisfaction before the pandemic (Δintercept,unadjusted = 0·213, 95% CI 0·087 to 0·340, p=0·0009), and experienced a more accelerated decline with its onset (Δquad2,unadjusted = -0·018, -0·026 to -0·011; p<0·0001), even after accounting for time use (Δquad2,adjusted = -0·016, -0·031 to -0·001; p=0·0348). Results were robust to adjustment for concurrent financial and occupational situation (Δquad2,adjustedfull = -0·019, -0·035 to -0·004; p=0·0158). INTERPRETATION: Our study shows sex inequalities in the impact of the pandemic on the long-term life satisfaction trajectories of adults in their 50s. Self-reported time-use differences did not account for these inequalities. One of the limitations is that we relied on self-reported time-use and were not able to include factors like the so-called mental load (being responsible for organising or monitoring activities, regardless of being involved in their execution), which might partly explain these results. FUNDING: Economic and Social Research Council (ESRC) Centre for Society and Mental Health at King's College London.

Severe mental illness, race/ethnicity, multimorbidity and mortality following COVID-19 infection: nationally representative cohort study.

BACKGROUND: The association of COVID-19 with death in people with severe mental illness (SMI), and associations with multimorbidity and ethnicity, are unclear. AIMS: To determine all-cause mortality in people with SMI following COVID-19 infection, and assess whether excess mortality is affected by multimorbidity or ethnicity. METHOD: This was a retrospective cohort study using primary care data from the Clinical Practice Research Database, from February 2020 to April 2021. Cox proportional hazards regression was used to estimate the effect of SMI on all-cause mortality during the first two waves of the COVID-19 pandemic. RESULTS: Among 7146 people with SMI (56% female), there was a higher prevalence of multimorbidity compared with the non-SMI control group (n = 653 024, 55% female). Following COVID-19 infection, the SMI group experienced a greater risk of death compared with controls (adjusted hazard ratio (aHR) 1.53, 95% CI 1.39-1.68). Black Caribbean/Black African people were more likely to die from COVID-19 compared with White people (aHR = 1.22, 95% CI 1.12-1.34), with similar associations in the SMI group and non-SMI group (P for interaction = 0.73). Following infection with COVID-19, for every additional multimorbidity condition, the aHR for death was 1.06 (95% CI 1.01-1.10) in the SMI stratum and 1.16 (95% CI 1.15-1.17) in the non-SMI stratum (P for interaction = 0.001). CONCLUSIONS: Following COVID-19 infection, patients with SMI were at an elevated risk of death, further magnified by multimorbidity. Black Caribbean/Black African people had a higher risk of death from COVID-19 than White people, and this inequity was similar for the SMI group and the control group.

Associations between air pollution and mental health service use in dementia: a retrospective cohort study.

BACKGROUND: Little is known about the role of air pollution in how people with dementia use mental health services. OBJECTIVE: We examined longitudinal associations between air pollution exposure and mental health service use in people with dementia. METHODS: In 5024 people aged 65 years or older with dementia in South London, high resolution estimates of nitrogen dioxide (NO2) and particulate matter (PM2.5 and PM10) levels in ambient air were linked to residential addresses. Associations between air pollution and Community Mental Health Team (CMHT) events (recorded over 9 years) were examined using negative binomial regression models. Cognitive function was measured using the Mini Mental State Examination (MMSE) and health and social functioning was measured using the Health of the Nation Outcomes Scale (HoNOS65+). Associations between air pollution and both MMSE and HoNOS65+ scores were assessed using linear regression models. FINDINGS: In the first year of follow-up, increased exposure to all air pollutants was associated with an increase in the use of CMHTs in a dose-response manner. These associations were strongest when we compared the highest air pollution quartile (quartile 4: Q4) with the lowest quartile (Q1) (eg, NO2: adjusted incidence rate ratio (aIRR) 1.27, 95% CI 1.11 to 1.45, p<0.001). Dose-response patterns between PM2.5 and CMHT events remained at 5 and 9 years. Associations were strongest for patients with vascular dementia. NO2 levels were linked with poor functional status, but not cognitive function. CONCLUSIONS: Residential air pollution exposure is associated with increased CMHT usage among people with dementia. CLINICAL IMPLICATIONS: Efforts to reduce pollutant exposures in urban settings might reduce the use of mental health services in people with dementia, freeing up resources in already considerably stretched psychiatric services.

Gone Too Soon: priorities for action to prevent premature mortality associated with mental illness and mental distress.

Globally, too many people die prematurely from suicide and the physical comorbidities associated with mental illness and mental distress. The purpose of this Review is to mobilise the translation of evidence into prioritised actions that reduce this inequity. The mental health research charity, MQ Mental Health Research, convened an international panel that used roadmapping methods and review evidence to identify key factors, mechanisms, and solutions for premature mortality across the social-ecological system. We identified 12 key overarching risk factors and mechanisms, with more commonalities than differences across the suicide and physical comorbidities domains. We also identified 18 actionable solutions across three organising principles: the integration of mental and physical health care; the prioritisation of prevention while strengthening treatment; and the optimisation of intervention synergies across social-ecological levels and the intervention cycle. These solutions included accessible, integrated high-quality primary care; early life, workplace, and community-based interventions co-designed by the people they should serve; decriminalisation of suicide and restriction of access to lethal means; stigma reduction; reduction of income, gender, and racial inequality; and increased investment. The time to act is now, to rebuild health-care systems, leverage changes in funding landscapes, and address the effects of stigma, discrimination, marginalisation, gender violence, and victimisation.

Long-term psychological distress trajectories and the COVID-19 pandemic in three British birth cohorts: A multi-cohort study.

BACKGROUND: Growing evidence suggests that population mental health outcomes have worsened since the pandemic started. The extent that these changes have altered common age-related trends in psychological distress, where distress typically rises until midlife and then falls after midlife in both sexes, is unknown. We aimed to analyse whether long-term pre-pandemic psychological distress trajectories were disrupted during the pandemic, and whether these changes have been different across cohorts and by sex. METHODS AND FINDINGS: We used data from three nationally representative birth cohorts comprising all people born in Great Britain in a single week of 1946 (National Survey of Health and Development, NSHD), 1958 (National Child Development Study, NCDS), or 1970 (British Cohort Study, BCS70). The follow-up data used spanned 39 years in NSHD (1982 to 2021), 40 years in NCDS (1981 to 2001), and 25 years in BCS70 (1996 to 2021). We used psychological distress factor scores, as measured by validated self-reported questionnaires (NSHD: Present State Examination, Psychiatric Symptoms Frequency, and 28- and 12-item versions of General Health Questionnaire; NCDS and BCS70: Malaise Inventory; all: 2-item versions of Generalized Anxiety Disorder scale and Patient Health Questionnaire). We used a multilevel growth curve modelling approach to model the trajectories of distress across cohorts and sexes and obtained estimates of the differences between the distress levels observed during the pandemic and those observed at the most recent pre-pandemic assessment and at the peak in the cohort-specific pre-pandemic distress trajectory, located at midlife. We further analysed whether pre-existing cohort and sex inequalities had changed with the pandemic onset using a difference-in-differences (DiD) approach. The analytic sample included 16,389 participants. By September/October 2020, distress levels had reached or exceeded the levels of the peak in the pre-pandemic life-course trajectories, with larger increases in younger cohorts (standardised mean differences [SMD] and 95% confidence intervals of SMDNSHD,pre-peak = -0.02 [-0.07, 0.04], SMDNCDS,pre-peak = 0.05 [0.02, 0.07], and SMDBCS70,pre-peak = 0.09 [0.07, 0.12] for the 1946, 1958, and 1970 birth cohorts, respectively). Increases in distress were larger among women than men, widening pre-existing sex inequalities (DiD and 95% confidence intervals of DiDNSHD,sex,pre-peak = 0.17 [0.06, 0.28], DiDNCDS,sex,pre-peak = 0.11 [0.07, 0.16], and DiDBCS70,sex,pre-peak = 0.11 [0.05, 0.16] when comparing sex inequalities in the pre-pandemic peak in midlife to those observed by September/October 2020). As expected in cohort designs, our study suffered from high proportions of attrition with respect to the original samples. Although we used non-response weights to restore sample representativeness to the target populations (those born in the United Kingdom in 1946, 1958, and 1970, alive and residing in the UK), results may not be generalisable to other sections within the UK population (e.g., migrants and ethnic minority groups) and countries different than the UK. CONCLUSIONS: Pre-existing long-term psychological distress trajectories of adults born between 1946 and 1970 were disrupted during the COVID-19 pandemic, particularly among women, who reached the highest levels ever recorded in up to 40 years of follow-up data. This may impact future trends of morbidity, disability, and mortality due to common mental health problems.

Ethnicity and survival after a dementia diagnosis: a retrospective cohort study using electronic health record data.

BACKGROUND: Individuals from minority ethnic groups in the UK are thought to be at higher risk of developing dementia while facing additional barriers to receiving timely care. However, few studies in the UK have examined if there are ethnic disparities in survival once individuals receive a dementia diagnosis. METHODS: We conducted a retrospective cohort study using electronic health record data of individuals diagnosed with dementia from a large secondary mental healthcare provider in London. Patients from Black African, Black Caribbean, South Asian, White British, and White Irish ethnic backgrounds were followed up for a 10-year period between 01 January 2008 and 31 December 2017. Data were linked to death certificate data from the Office of National Statistics to determine survival from dementia diagnosis. Standardised mortality ratios were calculated to estimate excess deaths in each ethnicity group as compared to the gender- and age-standardised population of England and Wales. We used Cox regression models to compare survival after dementia diagnosis across each ethnicity group. RESULTS: Mortality was elevated at least twofold across all ethnicity groups with dementia compared to the general population in England and Wales. Risk of death was lower in Black Caribbean, Black African, White Irish, and South Asian groups as compared to the White British population, even after adjusting for age, gender, neighbourhood-level deprivation, indicators of mental and physical comorbidities. Risk of death remained lower after additionally accounting for those who emigrated out of the cohort. CONCLUSIONS: While mortality in dementia is elevated across all ethnic groups as compared to the general population, reasons for longer survival in minority ethnic groups in the UK as compared to the White British group are unclear and merit further exploration. Implications of longer survival, including carer burden and costs, should be considered in policy and planning to ensure adequate support for families and carers of individuals with dementia.

Predicting type 2 diabetes prevalence for people with severe mental illness in a multi-ethnic East London population.

BACKGROUND AND AIMS: Prevalence of type two diabetes mellitus (T2DM) in people with severe mental illness (SMI) is 2-3 times higher than in general population. Predictive modelling has advanced greatly in the past decade, and it is important to apply cutting-edge methods to vulnerable groups. However, few T2DM prediction models account for the presence of mental illness, and none seemed to have been developed specifically for people with SMI. Therefore, we aimed to develop and internally validate a T2DM prevalence model for people with SMI. METHODS: We utilised a large cross-sectional sample representative of a multi-ethnic population from London (674,000 adults); 10,159 people with SMI formed our analytical sample (1,513 T2DM cases). We fitted a linear logistic regression and XGBoost as stand-alone models and as a stacked ensemble. Age, sex, body mass index, ethnicity, area-based deprivation, past hypertension, cardiovascular diseases, prescribed antipsychotics, and SMI illness were the predictors. RESULTS: Logistic regression performed well while detecting T2DM presence for people with SMI: area under the receiver operator curve (ROC-AUC) was 0.83 (95 % CI 0.79-0.87). XGBoost and LR-XGBoost ensemble performed equally well, ROC-AUC 0.83 (95 % CI 0.79-0.87), indicating a negligible contribution of non-linear terms to predictive power. Ethnicity was the most important predictor after age. We demonstrated how the derived models can be utilised and estimated a 2.14 % (95 %CI 2.03 %-2.24 %) increase in T2DM prevalence in East London SMI population in 20 years' time, driven by the projected demographic changes. CONCLUSIONS: Primary care data, the setting where prediction models could be most fruitfully used, provide enough information for well-performing T2DM prevalence models for people with SMI. We demonstrated how thorough internal cross-validation of an ensemble of a linear and machine-learning model can quantify the predictive value of non-linearity in the data.

Generational, sex, and socioeconomic inequalities in mental and social wellbeing during the COVID-19 pandemic: prospective longitudinal observational study of five UK cohorts.

BACKGROUND: Research suggests that there have been inequalities in the impact of the coronavirus disease 2019 (COVID-19) pandemic and related non-pharmaceutical interventions on population mental health. We explored generational, sex, and socioeconomic inequalities during the first year of the pandemic using nationally representative cohorts from the UK. METHODS: We analysed data from 26772 participants from five longitudinal cohorts representing generations born between 1946 and 2000, collected in May 2020, September-October 2020, and February-March 2021 across all five cohorts. We used a multilevel growth curve modelling approach to investigate generational, sex, and socioeconomic differences in levels of anxiety and depressive symptomatology, loneliness, and life satisfaction (LS) over time. RESULTS: Younger generations had worse levels of mental and social wellbeing throughout the first year of the pandemic. Whereas these generational inequalities narrowed between the first and last observation periods for LS [-0.33 (95% CI -0.51 to -0.15)], they became larger for anxiety [0.22 (0.10, 0.33)]. Generational inequalities in depression and loneliness did not change between the first and last observation periods, but initial depression levels of the youngest cohort were worse than expected if the generational inequalities had not accelerated. Women and those experiencing financial difficulties had worse initial mental and social wellbeing levels than men and those financially living comfortably, respectively, and these gaps did not substantially differ between the first and last observation periods. CONCLUSIONS: By March 2021, mental and social wellbeing inequalities persisted in the UK adult population. Pre-existing generational inequalities may have been exacerbated with the pandemic onset. Policies aimed at protecting vulnerable groups are needed.

Lack of fit with the neighbourhood social environment as a risk factor for psychosis - a national cohort study.

BACKGROUND: Many studies report an ethnic density effect whereby psychosis incidence among ethnic minority groups is higher in low co-ethnic density areas. It is unclear whether an equivalent density effect applies with other types of socioeconomic disadvantages. METHODS: We followed a population cohort of 2 million native Danes comprising all those born on 1st January 1965, or later, living in Denmark on their 15th birthday. Socioeconomic disadvantage, based on parents' circumstances at age 15 (low income, manual occupation, single parent and unemployed), was measured alongside neighbourhood prevalence of these indices. RESULTS: Each indicator was associated with a higher incidence of non-affective psychosis which remained the same, or was slightly reduced, if neighbourhood levels of disadvantage were lower. For example, for individuals from a low-income background there was no difference in incidence for those living in areas where a low-income was least common [incidence rate ratio (IRR) 1.01; 95% confidence interval (CI) 0.93-1.10 v. those in the quintile where a low income was most common. Typically, differences associated with area-level disadvantage were the same whether or not cohort members had a disadvantaged background; for instance, for those from a manual occupation background, incidence was lower in the quintile where this was least v. most common (IRR 0.83; 95% CI 0.71-0.97), as it was for those from a non-manual background (IRR 0.77; 95% CI 0.67-0.87). CONCLUSION: We found little evidence for group density effects in contrast to previous ethnic density studies. Further research is needed with equivalent investigations in other countries to see if similar patterns are observed.

A comparison of neighbourhood level variation and risk factors for affective versus non-affective psychosis.

BACKGROUND: Studies typically highlight area level variation in the incidence of non-affective but not affective psychoses. We compared neighbourhood-level variation for both types of disorder, and the specific effects of neighbourhood urbanicity and ethnic density, using Danish national registry data. METHODS: Population based cohort (2,224,464 people) followed from 1980 to 2013 with neighbourhood exposure measured at age 15 and incidence modelled using multilevel Poisson regression. RESULTS: Neighbourhood variation was similar for both disorders with an adjusted median risk ratio of 1.37 (95% CI 1.34-1.39) for non-affective psychosis and 1.43 (1.38-1.49) for affective psychosis. Associations with neighbourhood urbanicity differed: living in the most compared to the least urban quintile at age 15 was associated with a minimal increase in subsequent affective psychosis, IRR 1.13 (1.01-1.27) but a substantial increase in rates of non-affective psychosis, IRR 1.66 (1.57-1.75). Mixed results were found for neighbourhood ethnic density: for Middle Eastern migrants there was an increased average incidence of both affective, IRR 1.54 (1.19-1.99), and non-affective psychoses, 1.13 (1.04-1.23) associated with each decrease in ethnic density quintile, with a similar pattern for African migrants, but for European migrants ethnic density appeared to be associated with non-affective psychosis only. CONCLUSIONS: While overall variation and the effect of neighbourhood ethnic density were similar for both types of disorder, associations with urbanicity were largely confined to non-affective psychosis. This may reflect differences in aetiological pathways although the mechanism behind these differences remains unknown.

A comparison of single and intersectional social identities associated with discrimination and mental health service use: data from the 2014 Adult Psychiatric Morbidity Survey in England.

Inequities in mental health service use (MHSU) and treatment are influenced by social stratification processes linked to socially contextualised interactions between individuals, organisations and institutions. These complex relations underpin observed inequities and their experience by people at the intersections of social statuses. Discrimination is one important mechanism influencing such differences. We compared inequities in MHSU/treatment through single and intersectional status analyses, accounting for need. We assessed whether past-year discrimination differentially influences MHSU/treatment across single and intersecting statuses. Data came from a population survey (collected 2014-2015) nationally representative of English households (N = 7546). We used a theory and datadriven approach (latent class analysis) which identified five intersectional groups in the population comprising common combinations of social statuses. Single status analyses identified characteristics associated with MHSU/treatment (being a sexual minority (adjusted odds ratio (AOR) 1.65 95% CI:1.09-2.50), female (AOR 1.71, 95% CI:1.45-2.02), economically inactive (AOR 2.02, 95% CI:1.05-3.90), in the most deprived quintile (AOR 1.33, 95% CI:1.02-1.74), and Black (AOR 0.36 95% CI:0.20-0.66)). Intersectional analyses detected patterns not apparent from single status analyses. Compared to the most privileged group ("White British, highly educated, employed, high social class"), "Retired White British" had greater odds of MHSU/treatment (AOR 1.88, 95% CI:1.53-2.32) while "Employed migrants" had lower odds (AOR 0.39, 95% CI:0.27-0.55). Past-year discrimination was associated with certain disadvantaged social statuses and greater MHSU/treatment but-except for sexual minorities-adjusting for discrimination had little influence using either analytic approach. Observing patterns only by single social statuses masks potentially unanticipated and contextually varying inequities. The latent class approach offers policy-relevant insights into patterns and mechanisms of inequity but may mask other key intersectional patterns by statuses less common or under represented in surveys (e.g. UK-born ethnic minority groups). We propose multiple, context-relevant, theory-driven approaches to intersectional understanding of mental health inequalities.

Prevalence of common mental disorders and treatment receipt for people from ethnic minority backgrounds in England: repeated cross-sectional surveys of the general population in 2007 and 2014.

BACKGROUND: Concerns persist that some ethnic minority groups experience longstanding mental health inequalities in England. It is unclear if these have changed over time. AIMS: To assess the prevalence of common mental disorders (CMDs) and treatment receipt by ethnicity, and changes over time, using data from the nationally representative probability sample in the Adult Psychiatric Morbidity Surveys. METHOD: We used survey data from 2007 (n = 7187) and 2014 (n = 7413). A Clinical Interview Schedule - Revised score of ≥12 indicated presence of a CMD. Treatment receipt included current antidepressant use; any counselling or therapy; seeing a general practitioner about mental health; or seeing a community psychiatrist, psychologist or psychiatric nurse, in the past 12 months. Multivariable logistic regression assessed CMD prevalence and treatment receipt by ethnicity. RESULTS: CMD prevalence was highest in the Black group; ethnic variation was explained by demographic and socioeconomic factors. After adjustment for these factors and CMDs, odds ratios for treatment receipt were lower for the Asian (0.62, 95% CI 0.39-1.00) and White Other (0.58, 95% CI 0.38-0.87) groups in 2014, compared with the White British group; for the Black group, this inequality appeared to be widening over time (2007 treatment receipt odds ratio 0.68, 95% CI 0.38-1.23; 2014 treatment receipt odds ratio 0.23, 95% CI 0.13-0.40; survey year interaction P < 0.0001). CONCLUSIONS: Treatment receipt was lower for all ethnic minority groups compared with the White British group, and lowest among Black people, for whom inequalities appear to be widening over time. Addressing socioeconomic inequality could reduce ethnic inequalities in mental health problems, but this does not explain pronounced treatment inequalities.

Mapping multimorbidity in individuals with schizophrenia and bipolar disorders: evidence from the South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLAM BRC) case register.

OBJECTIVES: The first aim of this study was to design and develop a valid and replicable strategy to extract physical health conditions from clinical notes which are common in mental health services. Then, we examined the prevalence of these conditions in individuals with severe mental illness (SMI) and compared their individual and combined prevalence in individuals with bipolar (BD) and schizophrenia spectrum disorders (SSD). DESIGN: Observational study. SETTING: Secondary mental healthcare services from South London PARTICIPANTS: Our maximal sample comprised 17 500 individuals aged 15 years or older who had received a primary or secondary SMI diagnosis (International Classification of Diseases, 10th edition, F20-31) between 2007 and 2018. MEASURES: We designed and implemented a data extraction strategy for 21 common physical comorbidities using a natural language processing pipeline, MedCAT. Associations were investigated with sex, age at SMI diagnosis, ethnicity and social deprivation for the whole cohort and the BD and SSD subgroups. Linear regression models were used to examine associations with disability measured by the Health of Nations Outcome Scale. RESULTS: Physical health data were extracted, achieving precision rates (F1) above 0.90 for all conditions. The 10 most prevalent conditions were diabetes, hypertension, asthma, arthritis, epilepsy, cerebrovascular accident, eczema, migraine, ischaemic heart disease and chronic obstructive pulmonary disease. The most prevalent combination in this population included diabetes, hypertension and asthma, regardless of their SMI diagnoses. CONCLUSIONS: Our data extraction strategy was found to be adequate to extract physical health data from clinical notes, which is essential for future multimorbidity research using text records. We found that around 40% of our cohort had multimorbidity from which 20% had complex multimorbidity (two or more physical conditions besides SMI). Sex, age, ethnicity and social deprivation were found to be key to understand their heterogeneity and their differential contribution to disability levels in this population. These outputs have direct implications for researchers and clinicians.