Population-wide restrictions during the COVID-19 pandemic may create barriers to mental health diagnosis. This study aims to examine changes in the number of incident cases and the incidence rates of mental health diagnoses during the COVID-19 pandemic.

By using electronic health records from France, Germany, Italy, South Korea and the UK and claims data from the US, this study conducted interrupted time-series analyses to compare the monthly incident cases and the incidence of depressive disorders, anxiety disorders, alcohol misuse or dependence, substance misuse or dependence, bipolar disorders, personality disorders and psychoses diagnoses before (January 2017 to February 2020) and after (April 2020 to the latest available date of each database [up to November 2021]) the introduction of COVID-related restrictions.

A total of 629,712,954 individuals were enrolled across nine databases. Following the introduction of restrictions, an immediate decline was observed in the number of incident cases of all mental health diagnoses in the US (rate ratios (RRs) ranged from 0.005 to 0.677) and in the incidence of all conditions in France, Germany, Italy and the US (RRs ranged from 0.002 to 0.422). In the UK, significant reductions were only observed in common mental illnesses. The number of incident cases and the incidence began to return to or exceed pre-pandemic levels in most countries from mid-2020 through 2021.

Healthcare providers should be prepared to deliver service adaptations to mitigate burdens directly or indirectly caused by delays in the diagnosis and treatment of mental health conditions.

To examine the relationships between baseline gray matter volumes, diagnostic status, and executive function performance at 24-month follow-up, and the relative importance of predictors of executive function in a cohort of non-demented older adults.

The study sample included 147 participants from the Alzheimer’s Disease Neuroimaging Initiative (mean age = 70.6, SD = 6.4; mean education = 17 years, SD = 2.4). At baseline, 49 participants were diagnosed as cognitively normal (CN), 60 as early mild cognitive impairment (EMCI), and 38 as late mild cognitive impairment (LMCI). Magnetic resonance imaging (MRI) data were collected at baseline. A composite score of executive function and FreeSurfer-derived gray matter regions-of-interest (ROI; whole brain, superior frontal gyrus, middle frontal gyrus, inferior frontal gyrus, orbitofrontal cortex, anterior cingulate cortex, superior parietal lobule, inferior parietal lobule, hippocampus) were examined. Hierarchical linear regression models were employed to assess whether brain volume predicted executive function at 24-month follow-up and interaction effects between baseline ROI volume and diagnostic status. Age, gender, education, Mini-Mental State Examination scores, and APOE-e4 allele status were included as control variables in each model. Relative importance metrics, which quantifies an individual regressor’s contribution to a multiple regression model, were computed using the Lindemen, Merenda, and Gold (lmg) method to assess the relative contribution of each variable in predicting executive function performance.

Across all participants, baseline gray matter ROI volume accounted for a significant amount of variance in executive function at 24-months after accounting for control variables. Specifically, anterior cingulate cortex and superior parietal lobule accounted for an additional 7% and 6% of variance in executive function at 24-months. Significant brain region X diagnostic status interaction effects were observed in executive function performance at 24-months. Relative importance metrics within each group indicated that age is the most important predictor of executive function at 24-months for CN, anterior cingulate cortex is most important for EMCI, and Mini-Mental Examination score is most important for LMCI.

Our findings implicate frontoparietal gray matter regions as significant predictors of executive function performance at 24-months, and that this relationship is moderated by diagnostic status. Our results indicate that the value of specific variables to predict executive function performance varies based on diagnostic status. Specifically, anterior cingulate cortex was a significant predictor of executive function performance across all participants and was the most important variable in predicting performance in the earliest stage of mild cognitive impairment. These results support previous studies examining gray matter correlates of executive function and extend the literature by exploring predictors of executive function in early and late stages of mild cognitive impairment.

Cognitive reserve and health-related fitness are associated with favorable cognitive aging, but Black/African American older adults are underrepresented in extant research. Our objective was to explore the relative contributions and predictive value of cognitive reserve and health-related fitness metrics on cognitive performance at baseline and cognitive status at a 4-year follow up in a large sample of Black/African American older adults.

Participants aged 65 years and older from the Health and Retirement Study (HRS) who identified as Black/African American and completed baseline and follow-up interviews (including physical, health, and cognitive assessments) were included in the study. The final sample included 321 Black/African American older adults (mean age = 72.8; sd = 4.8; mean years of education = 12.3; sd = 2.9; mean body mass index (BMI) = 29.1; sd = 5.2; 60.4% identified as female). A cross-sectional analysis of relative importance – a measure of partitioned variance controlling for collinearity and model order – was first used to explore predictor variables and inform the hierarchical model order. Next, hierarchical multiple regression was used to examine cross-sectional relationships between cognitive reserve (years of education), health-related fitness variables (grip strength, lung capacity, gait speed, BMI), and global cognition. Multiple logistic regression was used to examine prospective relationships between predictors and longitudinal cognitive status (maintainers versus decliners). Control variables in all models included age, gender identity, and a chronic disease index score.

Cross-sectional relative importance analyses identified years of education and gait speed as important predictors of global cognition. The cross-sectional hierarchical regression model explained 33% of variance in baseline global cognition. Education was the strongest predictor of cognitive performance (β = 0.48, p < 0.001). Holding all other variables constant, gait speed was significantly associated with baseline cognitive performance and accounted for a significant additional amount of explained variance (ΔR = 0.01, p = 0.032). In a prospective analysis dividing the sample into cognitive maintainers and decliners, a single additional year of formal education increased chances of being classified as a cognitive maintainer (OR = 1.30, 95% CI = 1.17-1.45). There were no significant relationships between rate of change in health-related fitness and rate of change in cognition.

Education, a proxy for cognitive reserve, was a robust predictor of global cognition at baseline and was associated with increased odds of maintaining cognitive ability at 4-year follow up in Black/African American older adults. Of the physical performance metrics, gait speed was associated with cognitive performance at baseline. The lack of observed association between other fitness variables and cognition may be attributable to the brief assessment procedures implemented in this large-scale study.

To examine the feasibility of implementing a cardiorespiratory exercise stimulus during functional Magnetic Resonance Imaging (fMRI).

12 young adults (age: 18-22 years) completed progressive maximal exercise testing and a brain MRI scan. During scanning, participants completed three runs of functional MRI (volumes = 619; TR = 800 ms; multiband = 4; voxel size = 3 mm3). During each 8 minute fMRI run, participants completed an exercise challenge consisting of alternating blocks of exercise and rest. Exercise was implemented with a cardiostepper, an MRI-compatible device (similar to a Stairmaster) capable of generating a cardiorespiratory exercise stimulus. During exercise blocks, participants stepped at a rate of 60 Hz with pedal resistance determined by participants' fitness level. Heart rate and respiration data were collected during MRI. fMRI data were processed and analyzed using FMRIB Software Library (FSL). The ARtifact Detection Toolbox (ART) software was also used to identify volumes with significant artifact, and ICA-AROMA was used to remove motion-related BOLD signal components.

During exercise blocks, heart rate increased (mean = 131 beats per minute) compared to rest (mean = 87 beats per minute; t(34) = 4.3; p < .001). The mean heart rate during exercise blocks corresponds to an exercise intensity in the light to moderate intensity range for this age group. Motion (median framewise displacement) was significantly higher during exercise (mean = .53 mm) than rest (mean = .36 mm). Across all blocks, ART classified 19.8% of brain volumes as artifact-containing outliers, with 69% of the outliers occurring during exercise blocks. Although greater head motion was observed during exercise, the use of ICA-AROMA reduced the impact of motion considerably, recovering an additional 25% of the task-related signal, relative to noise. Comparison of fMRI activity during exercise versus rest revealed significant associations with primary and supplementary motor cortices, hippocampus, and the insula, among other regions.

The current study demonstrates the feasibility of eliciting light to moderate intensity cardiorespiratory exercise (using a lower body stepping exercise) during functional MRI. Although increased head motion was observed during exercise compared to rest, the degree of head motion was roughly approximate to the values published in previous fMRI studies and post image acquisition processing improved task-related signal. During exercise, increased brain activation was observed in regions associated with the central command network, which regulates autonomic nervous system and musculoskeletal function during exercise.

The current study had two primary objectives: 1) To assess the dose-response relationship between acute bouts of aerobic exercise intensity and performance in multiple cognitive domains (episodic memory, attention, and executive function) and 2) To replicate and extend the literature by examining the dose-response relationship between aerobic exercise intensity and pattern separation.

18 young adults (mean age = 21.6, sd = 2.6; mean education = 13.9, sd = 3.4; 50% female) were recruited from The Ohio State University and surrounding area (Columbus, OH). Participants completed control (no exercise), light intensity, and vigorous intensity exercise conditions across three counterbalanced appointments. For each participant, all three appointments occurred at approximately the same time of day with at least 2 days between appointments. Following the rest or exercise conditions and after an approximately 7 minute delay, participants completed a Mnemonic Similarity Task (MST; Stark et al., 2019) to assess pattern separation. This task was always administered first as we attempted to replicate previous studies and further clarify the relationship between acute bouts of aerobic exercise and pattern separation by implementing an exercise stimulus that varied in intensity. After the MST, three brief cognitive tasks (roughly 5 min each) were administered in a counterbalanced order: a gradual-onset continuous performance task (gradCPT; Esterman et al., 2013), the flanker task from the NIH toolbox, and a face-name episodic memory task. Here we report results from the gradCPT, which assesses sustained attention and inhibitory control. Heart rate and ratings of perceived exertion were collected to validate the rest and exercise conditions. Repeated-measures ANOVAs were used to assess the relationship between exercise condition and dependent measures of sustained attention and inhibitory control and pattern separation.

One-way repeated-measures ANOVAs revealed a main effect of exercise condition on gradCPT task performance for task discrimination ability (d') and commission error rate (p’s < .05). Pairwise comparisons revealed task discrimination ability was significantly higher following the light intensity exercise condition versus the control condition. Commission error rate was significantly lower for both the light and vigorous exercise conditions compared to the control condition. For the MST, two-way repeated-measures ANOVAs revealed an expected significant main effect of lure similarity on task performance; however, there was not a significant main effect of exercise intensity on task performance (or a significant interaction).

The current study indicated that acute bouts of exercise improve both sustained attention and inhibitory control as measured with the gradCPT. We did not replicate previous work reporting that acute bouts of exercise improve pattern separation in young adults. Our results further indicate that vigorous exercise did not detrimentally impact or improve pattern separation performance. Our results indicate that light intensity exercise is sufficient to enhance sustained attention and inhibitory control, as there were no significant differences in performance following light versus vigorous exercise.

To identify the relative contributions and importance of modifiable fitness and demographic variables to cognitive performance in a cohort of healthy older adults.

Metrics of modifiable fitness (gait speed, respiratory function, grip strength, and body mass index (BMI)) and cognition (executive function, episodic memory, and processing speed) were assessed in 619 older adults from the Health and Retirement Study 2016 wave (mean age = 74.9, sd = 6.9; mean education = 13.4 years, sd = 2.6; 42% female). General linear models were employed to assess the contribution of modifiable fitness variables in predicting three domains of cognition: executive function, episodic memory, and processing speed. Demographics (age, sex, education, time between appointments, and a chronic disease score) were entered as covariates for each model. Relative importance metrics were computed for all variables in each model using Lindeman, Merenda, and Gold (lmg) analysis, a technique which decomposes a given model’s explained variance to describe the average contribution of each predictor variable, independent of its position in the linear model.

When all variables were entered into the general linear model, demographic and modifiable fitness variables explained 35%, 24%, and 26% of the variance in executive function, episodic memory, and processing speed, respectively (all three models were significant, p <0.001). Age, education, respiratory function, and walking speed had higher relative importance values (all lmgs > 1.8) compared to BMI, grip strength, and other covariates in all three models (all lmgs < 1.3). Gender was also relatively important in the executive function (lmg = 4.2) and episodic memory models (lmg = 5.0). Of the modifiable fitness variables, walking speed and respiratory function had the greatest lmg values (5.8 and 6.4 respectively) in the executive function model, similar to demographic variables age (lmg = 6.0) and education (lmg = 8.9). When demographic variables were entered as covariates, modifiable fitness variables collectively accounted for an additional 9.7%, 6.3%, and 6.0% variance in the executive function, episodic memory, and processing speed models respectively (all three models were significant, p <0.001).

Our findings indicate that walking speed and respiratory function are of similar importance compared to “traditional” demographic variables such as age and education in predicting cognitive performance in a cohort of healthy older adults. Moreover, modifiable fitness variables accounted for unique variance in executive function, episodic memory, and processing speed after accounting for age and education. Modifiable fitness variables explained the most unique variance in executive function. These results extend the current literature by demonstrating that modifiable fitness variables, even when assessed with brief and relatively coarse measures of physical performance, may be useful in predicting cognitive function. Moreover, the results highlight the need to assess metrics of cognitive reserve, such as education, as well as modifiable fitness variables and their respective roles in accounting for cognitive performance. The data further suggest that relative contributions of physical performance metrics may vary by cognitive domain in healthy older adults.

People with severe mental illness (SMI) have more physical health conditions than the general population, resulting in higher rates of hospitalisations and mortality. In this study, we aimed to determine the rate of emergency and planned physical health hospitalisations in those with SMI, compared to matched comparators, and to investigate how these rates differ by SMI diagnosis.

We used Clinical Practice Research DataLink Gold and Aurum databases to identify 20,668 patients in England diagnosed with SMI between January 2000 and March 2016, with linked hospital records in Hospital Episode Statistics. Patients were matched with up to four patients without SMI. Primary outcomes were emergency and planned physical health admissions. Avoidable (ambulatory care sensitive) admissions and emergency admissions for accidents, injuries and substance misuse were secondary outcomes. We performed negative binomial regression, adjusted for clinical and demographic variables, stratified by SMI diagnosis.

Emergency physical health (aIRR:2.33; 95% CI 2.22–2.46) and avoidable (aIRR:2.88; 95% CI 2.60–3.19) admissions were higher in patients with SMI than comparators. Emergency admission rates did not differ by SMI diagnosis. Planned physical health admissions were lower in schizophrenia (aIRR:0.80; 95% CI 0.72–0.90) and higher in bipolar disorder (aIRR:1.33; 95% CI 1.24–1.43). Accident, injury and substance misuse emergency admissions were particularly high in the year after SMI diagnosis (aIRR: 6.18; 95% CI 5.46–6.98).

We found twice the incidence of emergency physical health admissions in patients with SMI compared to those without SMI. Avoidable admissions were particularly elevated, suggesting interventions in community settings could reduce hospitalisations. Importantly, we found underutilisation of planned inpatient care in patients with schizophrenia. Interventions are required to ensure appropriate healthcare use, and optimal diagnosis and treatment of physical health conditions in people with SMI, to reduce the mortality gap due to physical illness.

There is emerging evidence of heterogeneity within treatment-resistance schizophrenia (TRS), with some people not responding to antipsychotic treatment from illness onset and a smaller group becoming treatment-resistant after an initial response period. It has been suggested that these groups have different aetiologies. Few studies have investigated socio-demographic and clinical differences between early and late onset of TRS.

This study aims to investigate socio-demographic and clinical correlates of late-onset of TRS.

Using data from the electronic health records of the South London and Maudsley, we identified a cohort of people with TRS. Regression analyses were conducted to identify correlates of the length of treatment to TRS. Analysed predictors include gender, age, ethnicity, positive symptoms severity, problems with activities of daily living, psychiatric comorbidities, involuntary hospitalisation and treatment with long-acting injectable antipsychotics.

We observed a continuum of the length of treatment until TRS presentation. Having severe hallucinations and delusions at treatment start was associated shorter duration of treatment until the presentation of TRS.

Our findings do not support a clear cut categorisation between early and late TRS, based on length of treatment until treatment resistance onset. More severe positive symptoms predict earlier onset of treatment resistance.

DFdF, GKS, EF and IR have received research funding from Janssen and H. Lundbeck A/S. RDH and HS have received research funding from Roche, Pfizer, Janssen and Lundbeck. SES is employed on a grant held by Cardiff University from Takeda Pharmaceutical Comp

Ethnic disparities in treatment with clozapine, the antipsychotic recommended for treatment-resistant schizophrenia (TRS), have been reported. However, these investigations frequently suffer from potential residual confounding. For example, few studies have restricted the analyses to TRS samples and none has controlled for benign ethnic neutropenia.

This study investigated if service-users’ ethnicity influenced clozapine prescription in a cohort of people with TRS.

Information from the clinical records of South London and Maudsley NHS Trust was used to identify a cohort of service-users with TRS between 2007 and 2017. In this cohort, we used logistic regression to investigate any association between ethnicity and clozapine prescription while adjusting for potential confounding variables, including sociodemographic factors, psychiatric multimorbidity, substance use, benign ethnic neutropenia, and inpatient and outpatient care received.

We identified 2239 cases that met the criteria for TRS. Results show that after adjusting for confounding variables, people with Black African ethnicity had half the odds of being treated with clozapine and people with Black Caribbean or Other Black background had about two-thirds the odds of being treated with clozapine compared White British service-users. No disparities were observed regarding other ethnic groups, namely Other White background, South Asian, Other Asian, or any other ethnicity.

There was evidence of inequities in care among Black ethnic groups with TRS. Interventions targeting barriers in access to healthcare are recommended.

During the conduction of the study, DFdF, GKS, and RH received funds from the NIHR Maudsley Biomedical Research Centre. For other activities outside the submitted work, DFdF received research funding from the UK Department of Health and Social Care, Janss

Studies have shown ethnic inequalities in health, with a higher incidence of illnesses among people of some minoritised ethnic groups. Furthermore, it has been observed that people with severe mental illnesses have a higher risk for multimorbidity. However, no study has investigated ethnic disparities in comorbidity in people with a schizophrenia spectrum disorder.

This study investigates potential ethnic disparities in physical health comorbidity in a cohort of people with psychosis.

Using a cross-sectional design, we identified service-users of the South London and Maudsley NHS Trust who were diagnosed with a schizophrenia spectrum disorder between 2007 and 2020. We assessed the prevalence of asthma, bronchitis, diabetes, hypertension, low blood pressure, overweight or obesity, and rheumatoid arthritis. Latent class analyses were used to investigate distinct profiles of comorbidity. Multinomial regression was then used to investigate ethnic disparities in these profiles. The regression model was adjusted for gender, age, neighbourhood deprivation, smoking and duration of care.

On a sample of 23,418 service-users with psychosis, we identified two classes of comorbidity: low comorbidity and multiple comorbidities. Compared to the White British ethnicity, a higher risk for multiple comorbidities was observed for people with any Black background, Indian, Pakistani, Asian British, and mixed-race ethnicities. Furthermore, Black African women had a significantly higher risk for multiple comorbidities than their male counterparts.

Ethnic disparities are observed in multiple comorbidities among people with psychosis. Further research is needed to understand the impact of these disparities, especially in relation to mortality.

No significant relationships.

Patients with bipolar disorder (BPD) are prone to engage in risk-taking behaviours and self-harm, contributing to higher risk of traumatic injuries requiring medical attention at the emergency room (ER).We hypothesize that pharmacological treatment of BPD could reduce the risk of traumatic injuries by alleviating symptoms but evidence remains unclear. This study aimed to examine the association between pharmacological treatment and the risk of ER admissions due to traumatic injuries.

Individuals with BPD who received mood stabilizers and/or antipsychotics were identified using a population-based electronic healthcare records database in Hong Kong (2001–2019). A self-controlled case series design was applied to control for time-invariant confounders.

A total of 5040 out of 14 021 adults with BPD who received pharmacological treatment and had incident ER admissions due to traumatic injuries from 2001 to 2019 were included. An increased risk of traumatic injuries was found 30 days before treatment [incidence rate ratio (IRR) 4.44 (3.71–5.31), p < 0.0001]. After treatment initiation, the risk remained increased with a smaller magnitude, before returning to baseline [IRR 0.97 (0.88–1.06), p = 0.50] during maintenance treatment. The direct comparison of the risk during treatment to that before and after treatment showed a significant decrease. After treatment cessation, the risk was increased [IRR 1.34 (1.09–1.66), p = 0.006].

This study supports the hypothesis that pharmacological treatment of BPD was associated with a lower risk of ER admissions due to traumatic injuries but an increased risk after treatment cessation. Close monitoring of symptoms relapse is recommended to clinicians and patients if treatment cessation is warranted.

Research shows persistent ethnic inequities in mental health experiences and outcomes, with a higher incidence of illnesses among minoritised ethnic groups. People with psychosis have an increased risk of multiple long-term conditions (MLTC; multimorbidity). However, there is limited research regarding ethnic inequities in multimorbidity in people with psychosis. This study investigates ethnic inequities in physical health multimorbidity in a cohort of people with psychosis.

In this retrospective cohort study, using the Clinical Records Interactive Search (CRIS) system, we identified service-users of the South London and Maudsley NHS Trust with a schizophrenia spectrum disorder, and then additional diagnoses of diabetes, hypertension, low blood pressure, overweight or obesity and rheumatoid arthritis. Logistic and multinomial logistic regressions were used to investigate ethnic inequities in odds of multimorbidity (psychosis plus one physical health condition), and multimorbidity severity (having one or two physical health conditions, or three or more conditions), compared with no additional health conditions (no multimorbidity), respectively. The regression models adjusted for age and duration of care and investigated the influence of gender and area-level deprivation.

On a sample of 20 800 service-users with psychosis, aged 13–65, ethnic differences were observed in the odds for multimorbidity. Controlling for sociodemographic factors and duration of care, compared to White British people, higher odds of multimorbidity were found for people of Black African [adjusted Odds Ratio = 1.41, 95% Confidence Intervals (1.23–1.56)], Black Caribbean [aOR = 1.79, 95% CI (1.58–2.03)] and Black British [aOR = 1.64, 95% CI (1.49–1.81)] ethnicity. Reduced odds were observed among people of Chinese [aOR = 0.61, 95% CI (0.43–0.88)] and Other ethnic [aOR = 0.67, 95% CI (0.59–0.76)] backgrounds. Increased odds of severe multimorbidity (three or more physical health conditions) were also observed for people of any Black background.

Ethnic inequities are observed for multimorbidity among people with psychosis. Further research is needed to understand the aetiology and impact of these inequities. These findings support the provision of integrated health care interventions and public health preventive policies and actions.