Area deprivation, urbanicity, severe mental illness and social drift — A population-based linkage study using routinely collected primary and secondary care data

We investigated whether associations between area deprivation, urbanicity and elevated risk of severe mental illnesses (SMIs, including schizophrenia and bipolar disorder) is accounted for by social drift or social causation. We extracted primary and secondary care electronic health records from 2004 to 2015 from a population of 3.9 million. We identified prevalent and incident individuals with SMIs and their level of deprivation and urbanicity using the Welsh Index of Multiple Deprivation (WIMD) and urban/rural indicator. The presence of social drift was determined by whether odds ratios (ORs) from logistic regression is greater than the incidence rate ratios (IRRs) from Poisson regression. Additionally, we performed longitudinal analysis to measure the proportion of change in deprivation level and rural/urban residence 10 years after an incident diagnosis of SMI and compared it to the general population using standardised rate ratios (SRRs). Prevalence and incidence of SMIs were significantly associated with deprivation and urbanicity (all ORs and IRRs significantly > 1). ORs and IRRs were similar across all conditions and cohorts (ranging from 1.1 to 1.4). Results from the longitudinal analysis showed individuals with SMIs are more likely to move compared to the general population. However, they did not preferentially move to more deprived or urban areas. There was little evidence of downward social drift over a 10-year period. These findings have implications for the allocation of resources, service configuration and access to services in deprived communities, as well as, for broader public health interventions addressing poverty, and social and environmental contexts

Understanding Suicide Clusters Through Exploring Self Harm Behaviors: a 10-year data-linkage cohort follow-up study of a Suicide Cluster using the Secure Anonymised Information Linkage (SAIL) Databank

Background: There is little information about characteristics and long-term outcomes of individuals who self-harm during a suicide cluster. Aims: To compare characteristics of individuals who self-harmed during a suicide cluster in South Wales (~10 deaths between Dec 2007 and Mar 2008) with others who self-harmed prior to the cluster, and to evaluate 10-year self-harm and mortality outcomes. Method: Using records from the hospital serving the catchment area of the suicide cluster, enhanced by national routinely collected linked data, we created two groups: individuals who self-harmed a) during the suicide cluster, and b) one year before. We compared individuals’ characteristics and performed logistic regression to compute odds ratios of 10-year self-harm and mortality outcomes. Results: Individuals who self-harmed during the cluster were less likely to be hospitalized or have a mental health history than those who self-harmed prior to the cluster. No significant group differences were found for 10-year self-harm outcomes, but all-cause mortality was higher for males. Limitations: Sample size was small, and data were lacking on psychological and social proximity to individuals who died during the suicide cluster. Conclusion: Our findings highlight the importance of long-term healthcare follow-up of those who self-harm during a suicide cluster, particularly males

Loneliness, coping, suicidal thoughts and self-harm during the COVID-19 pandemic: a repeat cross-sectional UK population survey

Objectives: There has been speculation on the impact of the COVID-19 pandemic and the associated lockdown on suicidal thoughts and self-harm and the factors associated with any change. We aimed to assess the effects and change in effects of risk factors including loneliness and coping, as well as pre-existing mental health conditions on suicidal thoughts and self-harm during the COVID-19 pandemic. Design: This study was a repeated cross-sectional online population-based survey. Participants and measures: Non-probability quota sampling was adopted on the UK adult population and four waves of data were analysed during the pandemic (17 March 2020 to 29 May 2020). Outcomes were suicidal thoughts and self-harm associated with the pandemic while loneliness, coping, pre-existing mental health conditions, employment status and demographics were covariates. We ran binomial regressions to evaluate the adjusted risks of the studied covariates as well as the changes in effects over time. Results: The proportion of individuals who felt lonely increased sharply from 9.8% to 23.9% after the UK lockdown began. Young people (aged 18–24 years), females, students, those who were unemployed and individuals with pre-existing mental health conditions were more likely to report feeling lonely and not coping well. 7.7%–10.0% and 1.9%–2.2% of respondents reported having suicidal thoughts and self-harm associated with the pandemic respectively throughout the period studied. Results from cross-tabulation and adjusted regression analyses showed young adults, coping poorly and with pre-existing mental health conditions were significantly associated with suicidal thoughts and self-harm. Loneliness was significantly associated with suicidal thoughts but not self-harm. Conclusions: The association between suicidality, loneliness and coping was evident in young people during the early stages of the pandemic. Developing effective interventions designed and coproduced to address loneliness and promote coping strategies during prolonged social isolation may promote mental health and help mitigate suicidal thoughts and self-harm associated with the pandemic

Self-harm, in-person bullying and cyberbullying in secondary school-aged children: a data linkage study in Wales

Introduction Although the evidence base on bullying victimization and self-harm in young people has been growing, most studies were cross-sectional, relied on self-reported non-validated measures of self-harm, and did not separate effects of in-person and cyberbullying. This study aimed to assess associations of self-harm following in-person bullying at school and cyberbullying victimization controlling for covariates. Methods School survey data from 11 to 16 years pupils collected in 2017 from 39 Welsh secondary schools were linked to routinely collected data. Inverse probability weighting was performed to circumvent selection bias. Survival analyses for recurrent events were conducted to evaluate relative risks (adjusted hazard ratios [AHR]) of self-harm among bullying groups within 2 years following survey completion. Results A total of 35.0% (weighted N = 6813) of pupils reported being bullied, with 18.1%, 6.4% and 10.5% being victims of in-person bullying at school only, cyberbullying only and both in-person bullying at school and cyberbullying respectively. Adjusting for covariates, effect sizes for self-harm were significant after being in-person bullied at school only (AHR = 2.2 [1.1–4.3]) and being both in-person bullied at school and cyberbullied (AHR = 2.2 [1.0–4.7]) but not being cyberbullied only (AHR = 1.2 [0.4–3.3]). Feeling lonely during recent summer holidays was also a robust predictor (AHR = 2.2 [1.2–4.0]). Conclusions We reaffirm the role of in-person bullying victimization on self-harm. Pupils were twice as likely to self-harm following in-person bullying as their nonvictimised peers. Interventions for young people that minimize the potential impacts of bullying on self-harm should also include strategies to prevent loneliness

A National Population-Based E-cohort of People with Psychosis (PsyCymru) Linkage of Phenotypical and Genetic Data to Routinely Collected Records

Introduction PsyCymru was established to investigate the feasibility of linking a prospectively ascertained, well characterised (linked clinical cohort) of people with psychosis in Wales, UK with large amounts of anonymised routinely collected health record data. We are now additionally linking genetic data. Objectives and Approach PsyCymru aimed to create a research platform for psychosis research in Wales by establishing two cohorts. The first was a well-characterised clinically assessed cohort with genetic data. Consented individuals underwent structured interviews using well-validated questionnaires and gave blood sample for DNA extraction, sequencing, and candidate gene identification. This data was then linked to routinely collected health and social datasets with identity encryption. The second is a larger e-cohort of prevalent psychosis cases created using a validated algorithm applied to anonymised routine data. Both cohorts were tracked prospectively and retrospectively in the Secure Anonymised Information Linkage (SAIL) databank. Results In total, data from 958 individuals for the clinical cohort were imported to SAIL. Among these individuals, genetic data for 740 were analysed. The genetic data included robust loci for schizophrenia, pathogenic copy-number variations (CNVs) for various conditions (e.g., autism, intellectual disability, congenital malformations), polygenic risks scores for schizophrenia, as well as pathogenic/non-pathogenic duplications or deletions of chromosome spanning more than 500kb or 1Mb. For the e-cohort, 29,797 individuals were found having a psychosis diagnosis from primary and secondary care between 2004 to 2013. Social demographic data for both cohorts were also analysed based on sex, age, area deprivation, urbanicity, and employment status. Conclusion/Implications This unique platform pooled data together from multiple sources; linking clinical, psychological, biological, genetic, and health care factors to address assorted research questions. This resource will continue to expand over the coming years in size, breadth and depth of data, with continued recruitment and additional measures planned

Premature Mortality among People with Severe Mental Illness – New Evidence from Linked Primary Care Data

Introduction Studies assessing premature mortality in people with severe mental illness (SMI) are often based in one setting, hospital (secondary care inpatients and/or outpatients) or community (primary care). This may lead to ascertainment bias. Objectives and Approach This study aimed to estimate standardised mortality ratios (SMRs) for all-cause and cause-specific mortality in people with SMI drawn from linked primary and secondary care populations compared to the general population. Standardised mortality ratios (SMRs) were calculated using the indirect method for a United Kingdom population of almost four million between 2004-2013. Results The all-cause SMR was higher in the cohort identified from secondary care hospital admissions (SMR: 2.9; 95% CI: 2.8-3.0) than from primary care (SMR: 2.2; 95% CI: 2.1-2.3) when compared to the general population. The SMR for the combined cohort was 2.6 (95% CI: 2.5-2.6). Solely hospital admission based studies may somewhat over-estimate premature mortality in those with SMI. However, there is no doubt this remains a major health inequality. Cause specific SMRs in the combined cohort were particularly elevated in those with SMI relative to the general population for ill-defined and unknown causes, suicide, and substance abuse, as well as a number of other causes. Conclusion/Implications The ability to combine cohorts electronically from primary and secondary care is more representative of the whole population. Comprehensive characterisation of mortality is important to inform policy and practice and to discriminate settings to allow for proportionate interventions to address this health injustice