Real-time air pollution and bipolar disorder symptoms: remote-monitored cross-sectional study

Air pollution is associated with unipolar depression and other mental health problems. We assessed the real-time association between localised mean air quality index and the severity of depression and mania symptoms in people with bipolar disorder. We found that as air quality worsened, symptoms of depression increased. We found no association between air quality and mania symptoms

Identifying influential spreaders and efficiently estimating infection numbers in epidemic models: a walk counting approach

We introduce a new method to efficiently approximate the number of infections resulting from a given initially-infected node in a network of susceptible individuals. Our approach is based on counting the number of possible infection walks of various lengths to each other node in the network. We analytically study the properties of our method, in particular demonstrating different forms for SIS and SIR disease spreading (e.g. under the SIR model our method counts self-avoiding walks). In comparison to existing methods to infer the spreading efficiency of different nodes in the network (based on degree, k-shell decomposition analysis and different centrality measures), our method directly considers the spreading process and, as such, is unique in providing estimation of actual numbers of infections. Crucially, in simulating infections on various real-world networks with the SIR model, we show that our walks-based method improves the inference of effectiveness of nodes over a wide range of infection rates compared to existing methods. We also analyse the trade-off between estimate accuracy and computational cost, showing that the better accuracy here can still be obtained at a comparable computational cost to other methods.Comment: 6 page

The temporal relationship between severe mental illness diagnosis and chronic physical comorbidity: a UK primary care cohort study of disease burden over 10 years

BACKGROUND: Despite increased rates of physical health problems in people with schizophrenia, bipolar disorder, and other psychotic illnesses, the temporal relationship between physical disease acquisition and diagnosis of a severe mental illness remains unclear. We aimed to determine the cumulative prevalence of 24 chronic physical conditions in people with severe mental illness from 5 years before to 5 years after their diagnosis. METHODS: In this cohort study, we used the UK Clinical Practice Research Datalink (CPRD) to identify patients aged 18-100 years who were diagnosed with severe mental illness between Jan 1, 2000, and Dec 31, 2018. Each patient with severe mental illness was matched with up to four individuals in the CPRD without severe mental illness by sex, 5-year age band, primary care practice, and year of primary care practice registration. Individuals in the matched cohort were assigned an index date equal to the date of severe mental illness diagnosis in the patient with severe mental illness to whom they were matched. Our primary outcome was the cumulative prevalence of 24 physical health conditions, based on the Charlson and Elixhauser comorbidity indices, at 5 years, 3 years, and 1 year before and after severe mental illness diagnosis and at the time of diagnosis. We used logistic regression to compare people with severe mental illness with the matched cohort, adjusting for key variables such as age, sex, and ethnicity. FINDINGS: We identified 68 789 patients diagnosed with a severe mental illness between Jan 1, 2000, and Dec 31, 2018, and we matched them to 274 827 patients without a severe mental illness diagnosis. In both cohorts taken together, the median age was 40·90 years (IQR 29·46-56·00), 175 138 (50·97%) people were male, and 168 478 (49·03%) were female. The majority of patients were of White ethnicity (59 867 [87·03%] patients with a severe mental illness and 244 566 [88·99%] people in the matched cohort). The most prevalent conditions at the time of diagnosis in people with severe mental illness were asthma (10 581 [15·38%] of 68 789 patients), hypertension (8696 [12·64%]), diabetes (4897 [7·12%]), neurological disease (3484 [5·06%]), and hypothyroidism (2871 [4·17%]). At diagnosis, people with schizophrenia had increased odds of five of 24 chronic physical conditions compared with matched controls, and nine of 24 conditions were diagnosed less frequently than in matched controls. Individuals with bipolar disorder and other psychoses had increased odds of 15 conditions at diagnosis. At 5 years after severe mental illness diagnosis, these numbers had increased to 13 conditions for schizophrenia, 19 for bipolar disorder, and 16 for other psychoses. INTERPRETATION: Elevated odds of multiple conditions at the point of severe mental illness diagnosis suggest that early intervention on physical health parameters is necessary to reduce morbidity and premature mortality. Some physical conditions might be under-recorded in patients with schizophrenia relative to patients with other severe mental illness subtypes. FUNDING: UK Office For Health Improvement and Disparities

Clustering of physical health multimorbidity in people with severe mental illness: An accumulated prevalence analysis of United Kingdom primary care data

BACKGROUND: People with severe mental illness (SMI) have higher rates of a range of physical health conditions, yet little is known regarding the clustering of physical health conditions in this population. We aimed to investigate the prevalence and clustering of chronic physical health conditions in people with SMI, compared to people without SMI. METHODS AND FINDINGS: We performed a cohort-nested accumulated prevalence study, using primary care data from the Clinical Practice Research Datalink (CPRD), which holds details of 39 million patients in the United Kingdom. We identified 68,783 adults with a primary care diagnosis of SMI (schizophrenia, bipolar disorder, or other psychoses) from 2000 to 2018, matched up to 1:4 to 274,684 patients without an SMI diagnosis, on age, sex, primary care practice, and year of registration at the practice. Patients had a median of 28.85 (IQR: 19.10 to 41.37) years of primary care observations. Patients with SMI had higher prevalence of smoking (27.65% versus 46.08%), obesity (24.91% versus 38.09%), alcohol misuse (3.66% versus 13.47%), and drug misuse (2.08% versus 12.84%) than comparators. We defined 24 physical health conditions derived from the Elixhauser and Charlson comorbidity indices and used logistic regression to investigate individual conditions and multimorbidity. We controlled for age, sex, region, and ethnicity and then additionally for health risk factors: smoking status, alcohol misuse, drug misuse, and body mass index (BMI). We defined multimorbidity clusters using multiple correspondence analysis (MCA) and K-means cluster analysis and described them based on the observed/expected ratio. Patients with SMI had higher odds of 19 of 24 conditions and a higher prevalence of multimorbidity (odds ratio (OR): 1.84; 95% confidence interval [CI]: 1.80 to 1.88, p < 0.001) compared to those without SMI, particularly in younger age groups (males aged 30 to 39: OR: 2.49; 95% CI: 2.27 to 2.73; p < 0.001; females aged 18 to 30: OR: 2.69; 95% CI: 2.36 to 3.07; p < 0.001). Adjusting for health risk factors reduced the OR of all conditions. We identified 7 multimorbidity clusters in those with SMI and 7 in those without SMI. A total of 4 clusters were common to those with and without SMI; 1, heart disease, appeared as one cluster in those with SMI and 3 distinct clusters in comparators; and 2 small clusters were unique to the SMI cohort. Limitations to this study include missing data, which may have led to residual confounding, and an inability to investigate the temporal associations between SMI and physical health conditions. CONCLUSIONS: In this study, we observed that physical health conditions cluster similarly in people with and without SMI, although patients with SMI had higher burden of multimorbidity, particularly in younger age groups. While interventions aimed at the general population may also be appropriate for those with SMI, there is a need for interventions aimed at better management of younger-age multimorbidity, and preventative measures focusing on diseases of younger age, and reduction of health risk factors

Real-time air pollution and bipolar disorder symptoms: remote-monitored cross-sectional study

Air pollution is associated with unipolar depression and other mental health problems. We assessed the real-time association between localised mean air quality index and the severity of depression and mania symptoms in people with bipolar disorder. We found that as air quality worsened, symptoms of depression increased. We found no association between air quality and mania symptoms

The incidence rate of planned and emergency physical health hospital admissions in people diagnosed with severe mental illness: a cohort study

BACKGROUND: 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. METHODS: 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. RESULTS: 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). CONCLUSION: 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

Association between visual impairment and psychosis: A longitudinal study and nested case-control study of adults

BACKGROUND: Theories propose that visual impairment might increase the risk of psychosis, and vice versa. We aimed to investigate the relationship between visual impairment and psychosis in the UK Biobank cohort. STUDY DESIGN: In a nested case control study of ~116,000 adults, we tested whether a Schizophrenia Spectrum Disorder (SSD) diagnosis as exposure was associated with visual impairment. We also tested longitudinally whether poorer visual acuity, and thinner retinal structures on Optical Coherence Tomography (OCT) scans in 2009 were associated with psychotic experiences in 2016. We adjusted for age, sex, depression and anxiety symptoms; and socioeconomic variables and vascular risk factors where appropriate. We compared complete case with multiple imputation models, designed to reduce bias potentially introduced by missing data. RESULTS: People with visual impairment had greater odds of SSD than controls in multiply imputed data (Adjusted Odds Ratio [AOR] 1.42, 95 % Confidence Interval [CI] 1.05–1.93, p = 0.021). We also found evidence that poorer visual acuity was associated with psychotic experiences during follow-up (AOR per 0.1 point worse visual acuity score 1.06, 95 % CI 1.01–1.11, p = 0.020; and 1.04, 95 % CI 1.00–1.08, p = 0.037 in right and left eye respectively). In complete case data (15 % of this cohort) we found no clear association, although confidence intervals included the multiple imputation effect estimates. OCT measures were not associated with psychotic experiences. CONCLUSIONS: Our findings highlight the importance of eye care for people with psychotic illnesses. We could not conclude whether visual impairment is a likely causal risk factor for psychosis

Association between quetiapine use and self-harm outcomes among people with recorded personality disorder in UK primary care: A self-controlled case series analysis

BACKGROUND: Quetiapine is frequently prescribed to people with personality disorder diagnoses, but this is not supported by evidence or treatment guidelines. AIMS: To examine associations between periods of quetiapine prescribing and self-harm events in people with personality disorder. METHOD: Self-controlled case series using linked primary care and hospital records covering the period 2007-2017. We calculated incidence rates and incidence rate ratios (IRRs) for self-harm events during periods when people were prescribed (exposed to) quetiapine, as well as periods when they were unexposed or pre-exposed to quetiapine. RESULTS: We analysed data from 1,082 individuals with established personality disorder diagnoses, all of whom had at least one period of quetiapine prescribing and at least one self-harm episode. Their baseline rate of self-harm (greater than 12 months before quetiapine treatment) was 0.52 episodes per year. Self-harm rates were elevated compared to the baseline rate in the month after quetiapine treatment was commenced (IRR 1.85; 95% confidence interval (CI) 1.46-2.34) and remained raised throughout the year after quetiapine treatment was started. However, self-harm rates were highest in the month prior to quetiapine initiation (IRR 3.59; 95% CI 2.83-4.55) and were elevated from 4 months before quetiapine initiation, compared to baseline. CONCLUSION: Self-harm rates were elevated throughout the first year of quetiapine prescribing, compared to the baseline rate. However, rates of self-harm reduced in the month after patients commenced quetiapine, compared to the month before quetiapine was initiated. Self-harm rates gradually dropped over a year of quetiapine treatment. Quetiapine may acutely reduce self-harm. Longer-term use and any potential benefits need to be balanced with the risk of adverse events

Long-term stability in obsessive thoughts and compulsive behavior in the general population: a longitudinal study in Sweden

OBJECTIVE: Obsessive thoughts and compulsive behavior and their related disorder Obsessive-Compulsive Disorder (OCD) commonly occur in the general population. Clinical populations indicate a high level of stability, although there are few longitudinal studies in the general population. The recommended drug treatments are SSRIs/TCAs. However, there are few long-term follow up studies. The goal of this study was to 1) examine the occurrence and stability of obsessions, compulsions, and OCD in a longitudinal population-based survey, 2) investigate the use of SSRI and TCA and the potential effect on symptoms. METHODS: A ten-year longitudinal general population in Stockholm was used (2000 and 2010, n = 5650) Obsessional washing, checking, intrusive unpleasant thoughts and the level of suffering due to these symptoms were measured by self-report. Information on use of SSRIs and TCAs by these individuals was obtained from registers. Stability was examined using contingency tables and multinomial logistic regression. RESULTS: At baseline, 2.1, 11.7 and 11.9% reported obsessional washing, checking and intrusive thoughts. A total of 5% reported considerable suffering from these (i.e. OCD). Based on psychiatric interview only 0.4% had OCD. Ten years later a quarter of OCD cases were still classified as having OCD, one quarter reported any obsessive or compulsive symptom and half were classified as symptom-free. Treatment receipt was low and controlling for medication did not change the stability. CONCLUSION: Obsessive thoughts and compulsive behavior are common and stable. While this group is potentially undertreated, there is no indication that those treated display a different pattern of recovery