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The association of COVID-19 with death in people with severe mental illness (SMI), and associations with multimorbidity and ethnicity, are unclear.
To determine all-cause mortality in people with SMI following COVID-19 infection, and assess whether excess mortality is affected by multimorbidity or ethnicity.
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.
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).
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.
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.
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.
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.
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.
Concerns persist that some ethnic minority groups experience longstanding mental health inequalities in England. It is unclear if these have changed over time.
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.
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.
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).
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.
Research suggests that an increased risk of physical comorbidities might have a key role in the association between severe mental illness (SMI) and disability. We examined the association between physical multimorbidity and disability in individuals with SMI.
Data were extracted from the clinical record interactive search system at South London and Maudsley Biomedical Research Centre. Our sample (n = 13,933) consisted of individuals who had received a primary or secondary SMI diagnosis between 2007 and 2018 and had available data for Health of Nations Outcome Scale (HoNOS) as disability measure. Physical comorbidities were defined using Chapters II–XIV of the International Classification of Diagnoses (ICD-10).
More than 60 % of the sample had complex multimorbidity. The most common organ system affected were neurological (34.7%), dermatological (15.4%), and circulatory (14.8%). All specific comorbidities (ICD-10 Chapters) were associated with higher levels of disability, HoNOS total scores. Individuals with musculoskeletal, skin/dermatological, respiratory, endocrine, neurological, hematological, or circulatory disorders were found to be associated with significant difficulties associated with more than five HoNOS domains while others had a lower number of domains affected.
Individuals with SMI and musculoskeletal, skin/dermatological, respiratory, endocrine, neurological, hematological, or circulatory disorders are at higher risk of disability compared to those who do not have those comorbidities. Individuals with SMI and physical comorbidities are at greater risk of reporting difficulties associated with activities of daily living, hallucinations, and cognitive functioning. Therefore, these should be targeted for prevention and intervention programs.
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.
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.
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).
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.
Climate change is already having unequal effects on the mental health of individuals and communities and will increasingly compound pre-existing mental health inequalities globally. Psychiatrists have a vital part to play in improving both awareness and scientific understanding of structural mechanisms that perpetuate these inequalities, and in responding to global calls for action to promote climate justice and resilience, which are central foundations for good mental and physical health.
Research on sickness absence has typically focussed on single diagnoses, despite increasing recognition that long-term health conditions are highly multimorbid and clusters comprising coexisting mental and physical conditions are associated with poorer clinical and functional outcomes. The digitisation of sickness certification in the UK offers an opportunity to address sickness absence in a large primary care population.
Lambeth Datanet is a primary care database which collects individual-level data on general practitioner consultations, prescriptions, Quality and Outcomes Framework diagnostic data, sickness certification (fit note receipt) and demographic information (including age, gender, self-identified ethnicity, and truncated postcode). We analysed 326 415 people's records covering a 40-month period from January 2014 to April 2017.
We found significant variation in multimorbidity by demographic variables, most notably by self-defined ethnicity. Multimorbid health conditions were associated with increased fit note receipt. Comorbid depression had the largest impact on first fit note receipt, more than any other comorbid diagnoses. Highest rates of first fit note receipt after adjustment for demographics were for comorbid epilepsy and rheumatoid arthritis (HR 4.69; 95% CI 1.73–12.68), followed by epilepsy and depression (HR 4.19; 95% CI 3.60–4.87), chronic pain and depression (HR 4.14; 95% CI 3.69–4.65), cardiac condition and depression (HR 4.08; 95% CI 3.36–4.95).
Our results show striking variation in multimorbid conditions by gender, deprivation and ethnicity, and highlight the importance of multimorbidity, in particular comorbid depression, as a leading cause of disability among working-age adults.
How neighbourhood characteristics affect the physical safety of people with mental illness is unclear.
To examine neighbourhood effects on physical victimisation towards people using mental health services.
We developed and evaluated a machine-learning-derived free-text-based natural language processing (NLP) algorithm to ascertain clinical text referring to physical victimisation. This was applied to records on all patients attending National Health Service mental health services in Southeast London. Sociodemographic and clinical data, and diagnostic information on use of acute hospital care (from Hospital Episode Statistics, linked to Clinical Record Interactive Search), were collected in this group, defined as ‘cases’ and concurrently sampled controls. Multilevel logistic regression models estimated associations (odds ratios, ORs) between neighbourhood-level fragmentation, crime, income deprivation, and population density and physical victimisation.
Based on a human-rated gold standard, the NLP algorithm had a positive predictive value of 0.92 and sensitivity of 0.98 for (clinically recorded) physical victimisation. A 1 s.d. increase in neighbourhood crime was accompanied by a 7% increase in odds of physical victimisation in women and an 13% increase in men (adjusted OR (aOR) for women: 1.07, 95% CI 1.01–1.14, aOR for men: 1.13, 95% CI 1.06–1.21, P for gender interaction, 0.218). Although small, adjusted associations for neighbourhood fragmentation appeared greater in magnitude for women (aOR = 1.05, 95% CI 1.01–1.11) than men, where this association was not statistically significant (aOR = 1.00, 95% CI 0.95–1.04, P for gender interaction, 0.096). Neighbourhood income deprivation was associated with victimisation in men and women with similar magnitudes of association.
Neighbourhood factors influencing safety, as well as individual characteristics including gender, may be relevant to understanding pathways to physical victimisation towards people with mental illness.
Across international contexts, people with serious mental illnesses (SMI) experience marked reductions in life expectancy at birth. The intersection of ethnicity and social deprivation on life expectancy in SMI is unclear. The aim of this study was to assess the impact of ethnicity and area-level deprivation on life expectancy at birth in SMI, defined as schizophrenia-spectrum disorders, bipolar disorders and depression, using data from London, UK.
Abridged life tables to calculate life expectancy at birth, in a cohort with clinician-ascribed ICD-10 schizophrenia-spectrum disorders, bipolar disorders or depression, managed in secondary mental healthcare. Life expectancy in the study population with SMI was compared with life expectancy in the general population and with those residing in the most deprived areas in England.
Irrespective of ethnicity, people with SMI experienced marked reductions in life expectancy at birth compared with the general population; from 14.5 years loss in men with schizophrenia-spectrum and bipolar disorders, to 13.2 years in women. Similar reductions were noted for people with depression. Across all diagnoses, life expectancy at birth in people with SMI was lower than the general population residing in the most deprived areas in England.
Irrespective of ethnicity, reductions in life expectancy at birth among people with SMI are worse than the general population residing in the most deprived areas in England. This trend in people with SMI is similar to groups who experience extreme social exclusion and marginalisation. Evidence-based interventions to tackle this mortality gap need to take this into account.
A higher incidence of psychotic disorders has been consistently reported among black and other minority ethnic groups, particularly in northern Europe. It is unclear whether these rates have changed over time.
We identified all individuals with a first episode psychosis who presented to adult mental health services between 1 May 2010 and 30 April 2012 and who were resident in London boroughs of Lambeth and Southwark. We estimated age-and-gender standardised incidence rates overall and by ethnic group, then compared our findings to those reported in the Aetiology and Ethnicity of Schizophrenia and Other Psychoses (ÆSOP) study that we carried out in the same catchment area around 10 years earlier.
From 9109 clinical records we identified 558 patients with first episode psychosis. Compared with ÆSOP, the overall incidence rates of psychotic disorder in southeast London have increased from 49.4 (95% confidence interval (CI) 43.6–55.3) to 63.1 (95% CI 57.3–69.0) per 100 000 person-years at risk. However, the overall incidence rate ratios (IRR) were reduced in some ethnic groups: for example, IRR (95% CI) for the black Caribbean group reduced from 6.7 (5.4–8.3) to 2.8 (2.1–3.6) and the ‘mixed’ group from 2.7 (1.8–4.2) to 1.4 (0.9–2.1). In the black African group, there was a negligible difference from 4.1 (3.2–5.3) to 3.5 (2.8–4.5).
We found that incidence rates of psychosis have increased over time, and the IRR varied by the ethnic group. Future studies are needed to investigate more changes over time and determinants of change.
Depression is associated with increased mortality, however, little is known about its variation by ethnicity.
We conducted a cohort study of individuals with ICD-10 unipolar depression from secondary mental healthcare, from an ethnically diverse location in southeast London, followed for 8 years (2007–2014) linked to death certificates. Age- and sex- standardised mortality ratios (SMRs), with the population of England and Wales as a standard population were derived. Hazard ratios (HRs) for mortality were derived through multivariable regression procedures.
Data from 20 320 individuals contributing 91 635 person-years at risk with 2366 deaths were used for analyses. SMR for all-cause mortality in depression was 2.55(95% CI 2.45–2.65), with similar trends by ethnicity. Within the cohort with unipolar depression, adjusted HR (aHRs) for all-cause mortality in ethnic minority groups relative to the White British group were 0.62(95% CI 0.53–0.74) (Black Caribbean), 0.53(95% CI 0.39–0.72) (Black African) and 0.69(95% CI 0.52–0.90) (South Asian). Male sex and alcohol/substance misuse were associated with an increased all-cause mortality risk [aHR:1.94 (95% CI 1.68–2.24) and aHR:1.18 (95% CI 1.01–1.37) respectively], whereas comorbid anxiety was associated with a decreased risk [aHR: 0.72(95% CI 0.58–0.89)]. Similar associations were noted for natural-cause mortality. Alcohol/substance misuse and male sex were associated with a near-doubling in unnatural-cause mortality risk, whereas Black Caribbean individuals with depression had a reduced unnatural-cause mortality risk, relative to White British people with depression.
Although individuals with depression experience an increased mortality risk, marked heterogeneity exists by ethnicity. Research and practice should focus on addressing tractable causes underlying increased mortality in depression.
This article looks at the use of large datasets of health records, typically linked with other data sources, in mental health research. The most comprehensive examples of this kind of ‘big data’ are typically found in Scandinavian countries, although there are also many useful sources in the UK. There are a number of promising methodological innovations from studies using big data in UK mental health research, including: hybrid study designs, data linkage and enhanced study recruitment. It is, however, important to be aware of the limitations of research using big data, particularly the various pitfalls in analysis. We therefore caution against abandoning traditional research designs, and argue that other data sources are equally valuable and, ideally, research should incorporate data from a range of sources.
• Be aware of major big data resources relevant to mental health research
• Be aware of key advantages and innovative study designs using these data sources
• Understand the inherent limitations to studies reliant on big data alone
In this issue, Lorant et al. confirm a social gradient in risk of suicide, across 15 European countries, over a period of marked social change. Understanding contextual and life-course factors, and acknowledging under-funding for mental health and failures to implement national mental health policies, may provide the reasons for these disparities.
Material and social environmental stressors affect mental health in
adolescence. Protective factors such as social support from family and
friends may help to buffer the effects of adversity.
The association of violence exposure and emotional disorders was examined
in Cape Town adolescents.
A total of 1034 Grade 8 high school students participated from seven
government co-educational schools in Cape Town, South Africa. Exposure to
violence in the past 12 months and post-traumatic stress disorder (PTSD)
symptoms were measured by the Harvard Trauma Questionnaire, depressive
and anxiety symptoms by the Short Moods and Feelings Questionnaire and
the Self-Rating Anxiety Scale.
Exposure to violence was associated with high scores on depressive (odds
ratio (OR)=6.23, 95% CI 4.2–9.2), anxiety (OR=5.40, 95% CI 2.4–12.4) and
PTSD symptoms (OR=8.93, 95% CI 2.9–27.2) and increased risk of self-harm
(OR=5.72, 95% CI 1.2–25.9) adjusting for gender and social support.
We found that high exposure to violence was associated with high levels
of emotional disorders in adolescents that was not buffered by social
support. There is an urgent need for interventions to reduce exposure to
violence in young people in this setting.
Despite increased ethnic diversity in more economically developed countries it is unclear whether residential concentration of ethnic minority people (ethnic density) is detrimental or protective for mental health. This is the first systematic review and meta-analysis covering the international literature, assessing ethnic density associations with mental health outcomes.
We systematically searched Medline, PsychINFO, Sociological Abstracts, Web of Science from inception to 31 March 2016. We obtained additional data from study authors. We conducted random-effects meta-analysis taking into account clustering of estimates within datasets. Meta-regression assessed heterogeneity in studies due to ethnicity, country, generation, and area-level deprivation. Our main exposure was ethnic density, defined as the residential concentration of own racial/ethnic minority group. Outcomes included depression, anxiety and the common mental disorders (CMD), suicide, suicidality, psychotic experiences, and psychosis.
We included 41 studies in the review, with meta-analysis of 12 studies. In the meta-analyses, we found a large reduction in relative odds of psychotic experiences [odds ratio (OR) 0.82 (95% confidence interval (CI) 0.76–0.89)] and suicidal ideation [OR 0.88 (95% CI 0.79–0.98)] for each 10 percentage-point increase in own ethnic density. For CMD, depression, and anxiety, associations were indicative of protective effects of own ethnic density; however, results were not statistically significant. Findings from narrative review were consistent with those of the meta-analysis.
The findings support consistent protective ethnic density associations across countries and racial/ethnic minority populations as well as mental health outcomes. This may suggest the importance of the social environment in patterning detrimental mental health outcomes in marginalized and excluded population groups.
People with severe mental illness (SMI) experience a reduction in life expectancy of 15–20 years. Physical health and mortality experience may be even worse for ethnic minority groups with SMI, but evidence is limited. We suggest clinical, policy and research recommendations to address this inequality.
Aetiological mechanisms underlying ethnic density associations with
psychosis remain unclear.
To assess potential mechanisms underlying the observation that minority
ethnic groups experience an increased risk of psychosis when living in
neighbourhoods of lower own-group density.
Multilevel analysis of nationally representative community-level data
(from the Ethnic Minorities Psychiatric Illness Rates in the Community
survey), which included the main minority ethnic groups living in
England, and a White British group. Structured instruments assessed
discrimination, chronic strains and social support. The Psychosis
Screening Questionnaire ascertained psychotic experiences.
For every ten percentage point reduction in own-group density, the
relative odds of reporting psychotic experiences increased 1.07 times
(95% CI 1.01–1.14, P = 0.03 (trend)) for the total
minority ethnic sample. In general, people living in areas of lower
own-group density experienced greater social adversity that was in turn
associated with reporting psychotic experiences.
People resident in neighbourhoods of higher own-group density experience
‘buffering’ effects from the social risk factors for psychosis.