Epidemiology and Psychiatric Sciences最新文献

Aim: Opioid use disorder (OUD) is a medical condition associated with problematic opioid use, leading to addiction and severe life impairments. This research delivers an in-depth evaluation of OUD burden and trends at global, regional and national levels.

Methods: This study analysed the global burden of OUD from 1990 to 2021 using data from the 2021 Global Burden of Diseases, Injuries, and Risk Factors Study. Key metrics included age-standardized prevalence, incidence, mortality and disability-adjusted life years (DALYs), disaggregated by gender, age, region, country and socio-demographic index (SDI) quintiles. The average annual percentage change described trends, while the age-period-cohort model evaluated age, period and cohort effects. A Bayesian Age-period-cohort model predicted future OUD trends from 2022 to 2040.

Results: In 2021, the global burden of OUD remained substantial, with a total of 16,164,876 cases and a prevalence of 154.59 cases per 100,000 population (95% uncertainty interval [UI]: 131.06-181.26). In 2021, the global incidence of OUD reached 1,942,525 cases (95% UI: 1,643,342-2,328,363), and its global mortality reached 99,555 deaths (95% UI: 92,948-108,050), with DALYs amounting to 11,218,519 (95% UI: 9,188,658-13,159,551). Regionally, high SDI regions, particularly in the High-income North America, exhibited the greatest burden. Among countries, the United States faced the most severe burden and increase, with the highest prevalence (2014.62 per 100,000), incidence (151.84 per 100,000), mortality (15.37 per 100,000) and DALYs (1594.63 per 100,000), and all APPC values exceeding 5%. Males aged 20-39 years were the most affected demographic. However, forecasts indicate that the OUD burden among females will significantly increase over the next 20 years, with the prevalence and incidence expected to rise by 39% and 49%, respectively.

Conclusions: The global burden of OUD has statistically significantly increased from 1990 to 2021. There are marked disparities across regions, countries and SDI levels. High-SDI regions, particularly High-income North America, bear the heaviest burden, with young males (aged 20-39 years) being the most affected groups. However, caution should be exercised regarding the female population, as the number of affected individuals is rapidly increasing.

Background: Previous studies have estimated the lifetime incidence, age of onset and prevalence of mental disorders, but none have used nationwide data covering both primary and secondary care, even though mental disorders are commonly treated in primary care. We aimed to determine lifetime incidence, age-specific incidence, age of onset and service utilization for diagnosed mental disorders.

Methods: This register-based cohort study followed the entire population of Finland from 2000 to 2020. We estimated the cumulative incidence of diagnosed mental disorders with the Aalen-Johansen estimator, accounting for competing risks such as death and emigration. We also calculated age-specific incidence and 12-month service utilization as of 31 December 2019, providing diagnosis-, age- and gender-specific estimates.

Results: We followed 6.4 million individuals for 98.5 million person-years. By age 100, lifetime incidence of any diagnosed mental disorder was 76.7% (95% CI, 76.6-76.7) in women and 69.7% (69.6-69.8) in men; in psychiatric secondary care, it was 39.7% (39.6-39.8) and 31.5% (31.4-31.6). At age 75, stricter estimates for non-organic disorders (ICD-10: F10-F99) were 65.6% (65.5-65.7) for women and 60.0% (59.9-60.1). Anxiety disorders (F40-F48) had the highest cumulative incidence. Median age of onset of non-organic mental disorders was 24.1 (interquartile range, 14.8-43.3 years) in women and 20.0 (interquartile range, 7.3-42.2 years) in men. Service utilization within 12 months was 9.0% for women and 7.7% for men.

Conclusions: Most, though not all, individuals experience at least one type of mental disorder, often during youth. Capturing the overall occurrence of mental disorders requires including both primary and secondary care data.

Aims: The literature on persistent antidepressant withdrawal symptoms is sparse. This systematic review is the first to examine the prevalence, duration, severity, risk/protective factors and treatment strategies for post-acute withdrawal syndrome (PAWS) following the discontinuation of antidepressant medications.

Methods: We searched PubMed, Web of Science and PsycInfo, focusing on newer-generation antidepressants. The electronic database search was complemented with handsearching reference lists of pivotal studies. We included original studies in adults reporting on PAWS and providing data about epidemiology and clinical management of withdrawal symptoms persisting for at least 6 weeks.

Results: The literature search yielded 1286 results, with 26 records assessed for eligibility, and seven studies fulfilled our selection criteria. Prevalence data were sparse, with one small cohort study reporting a 15% prevalence rate for PAWS in patients with panic disorder and agoraphobia. The duration of PAWS varied considerably across studies, ranging from 1.5 to 166 months. Long-term paroxetine use emerged as a potential risk factor for the development of PAWS. There was no reliable evidence to support the effectiveness of various treatment strategies, including the reinstatement of antidepressant medication, the use of benzodiazepines and the provision of cognitive-behavioral therapy.

Conclusions: The current evidence on PAWS is sparse and predominantly of low certainty. The presence of withdrawal symptoms, lasting several months and possibly even years in some patients, underscores the need for further research with rigorous methodology. Large prospective cohort studies are needed to assess the epidemiology of PAWS, while randomized controlled trials are quired to test the efficacy of clinical interventions to treat PAWS.

Prospero registration: CRD42023461793.

Aims: Studies conducted during the COVID-19 pandemic found high occurrence of suicidal thoughts and behaviours (STBs) among healthcare workers (HCWs). The current study aimed to (1) develop a machine learning-based prediction model for future STBs using data from a large prospective cohort of Spanish HCWs and (2) identify the most important variables in terms of contribution to the model's predictive accuracy.

Methods: This is a prospective, multicentre cohort study of Spanish HCWs active during the COVID-19 pandemic. A total of 8,996 HCWs participated in the web-based baseline survey (May-July 2020) and 4,809 in the 4-month follow-up survey. A total of 219 predictor variables were derived from the baseline survey. The outcome variable was any STB at the 4-month follow-up. Variable selection was done using an L1 regularized linear Support Vector Classifier (SVC). A random forest model with 5-fold cross-validation was developed, in which the Synthetic Minority Oversampling Technique (SMOTE) and undersampling of the majority class balancing techniques were tested. The model was evaluated by the area under the Receiver Operating Characteristic (AUROC) curve and the area under the precision-recall curve. Shapley's additive explanatory values (SHAP values) were used to evaluate the overall contribution of each variable to the prediction of future STBs. Results were obtained separately by gender.

Results: The prevalence of STBs in HCWs at the 4-month follow-up was 7.9% (women = 7.8%, men = 8.2%). Thirty-four variables were selected by the L1 regularized linear SVC. The best results were obtained without data balancing techniques: AUROC = 0.87 (0.86 for women and 0.87 for men) and area under the precision-recall curve = 0.50 (0.55 for women and 0.45 for men). Based on SHAP values, the most important baseline predictors for any STB at the 4-month follow-up were the presence of passive suicidal ideation, the number of days in the past 30 days with passive or active suicidal ideation, the number of days in the past 30 days with binge eating episodes, the number of panic attacks (women only) and the frequency of intrusive thoughts (men only).

Conclusions: Machine learning-based prediction models for STBs in HCWs during the COVID-19 pandemic trained on web-based survey data present high discrimination and classification capacity. Future clinical implementations of this model could enable the early detection of HCWs at the highest risk for developing adverse mental health outcomes.

Study registration: NCT04556565.

Aims: Multimorbidity, especially physical-mental multimorbidity, is an emerging global health challenge. However, the characteristics and patterns of physical-mental multimorbidity based on the diagnosis of mental disorders in Chinese adults remain unclear.

Methods: A cross-sectional study was conducted from November 2004 to April 2005 among 13,358 adults (ages 18-65years) residing in Liaoning Province, China, to evaluate the occurrence of physical-mental multimorbidity. Mental disorders were assessed using the Composite International Diagnostic Interview (version 1.0) with reference to the Diagnostic and Statistical Manual of Mental Disorders (3rd Edition Revised), while physical diseases were self-reported. Physical-mental multimorbidity was assessed based on a list of 16 physical and mental morbidities with prevalence ≥1% and was defined as the presence of one mental disorder and one physical disease. The chi-square test was used to calculate differences in the prevalence and comorbidity of different diseases between the sexes. A matrix heat map was generated of the absolute number of comorbidities for each disease. To identify complex associations and potential disease clustering patterns, a network analysis was performed, constructing a network to explore the relationships within and between various mental disorders and physical diseases.

Results: Physical-mental multimorbidity was confirmed in 3.7% (498) of the participants, with a higher prevalence among women (4.2%, 282) than men (3.3%, 216). The top three diseases with the highest comorbidity rate and average number of comorbidities were dysphoric mood (86.3%; 2.86), social anxiety disorder (77.8%; 2.78) and major depressive disorder (77.1%; 2.53). A physical-mental multimorbidity network was visually divided into mental and physical domains. Additionally, four distinct multimorbidity patterns were identified: 'Affective-addiction', 'Anxiety', 'Cardiometabolic' and 'Gastro-musculoskeletal-respiratory', with the digestive-respiratory-musculoskeletal pattern being the most common among the total sample. The affective-addiction pattern was more prevalent in men and rural populations. The cardiometabolic pattern was more common in urban populations.

Conclusions: The physical-mental multimorbidity network structure and the four patterns identified in this study align with previous research, though we observed notable differences in the proportion of these patterns. These variations highlight the importance of tailored interventions that address specific multimorbidity patterns while maintaining broader applicability to diverse populations.

Aim: HOPE (National Institute for Health and Care Research Global Health Research Group on Homelessness and Mental Health in Africa) aims to develop and evaluate interventions that address the unmet needs of people who are homeless and have severe mental illness (SMI) living in three African countries in ways that are rights-based, contextually grounded, scalable and sustainable.

Methods: We will work in the capital city (Addis Ababa) in Ethiopia, a regional city (Tamale) in Ghana, and the capital city (Nairobi) and a rural county (Makueni) in Kenya to understand different approaches to intervention needed across varied settings.We will be guided by the MRC/NIHR framework on complex interventions and implementation frameworks and emphasise co-production. Formative work will include synthesis of global evidence (systematic review, including grey literature, and a Delphi consensus exercise) on interventions and approaches to homelessness and SMI. We will map contexts; conduct focused ethnography to understand lived experiences of homelessness and SMI; carry out a cross-sectional survey of people who are homeless (n = 750 Ghana/Ethiopia; n = 350 Kenya) to estimate prevalence of SMI and identify prioritised needs; and conduct in-depth interviews and focus group discussions with key stakeholders to understand experiences, challenges and opportunities for intervention. This global and local evidence will feed into Theory of Change (ToC) workshops with stakeholders to establish agreement about valued primary outcomes, map pathways to impact and inform selection and implementation of interventions. Intervention packages to address prioritised needs will be co-produced, piloted and optimised for feasibility and acceptability using participatory action research. We will use rights-based approaches and focus on community-based care to ensure sustainability. Realist approaches will be employed to analyse how contextual variation affects mechanisms and outcomes to inform methods for a subsequent evaluation of larger scale implementation. Extensive capacity-strengthening activities will focus on equipping early career researchers and peer researchers. People with lived experience of SMI and policymakers are an integral part of the research team. Community engagement is supported by working closely with multisectoral Community Advisory Groups.

Conclusions: HOPE will develop evidence to support action to respond to the needs and preferences of people experiencing homelessness and SMI in diverse settings in Africa. We are creating a new partnership of researchers, policymakers, community members and people with lived experience of SMI and homelessness to enable African-led solutions. Key outputs will include contextually relevant practice and policy guidance that supports achievement of inclusive development.

Aims: A systematic review and meta-analysis was conducted to investigate the prevalence and antecedents/outcomes of loneliness and social isolation among individuals with severe mental disorders (SMD), such as schizophrenia, schizoaffective disorder, bipolar disorder or major depressive disorder.

Methods: Five well-known electronic databases (PubMed, PsycINFO, CINAHL, Web of Science and Scopus) were searched (plus a hand search). Observational studies that report the prevalence and, if available, antecedents and consequences of loneliness/isolation among individuals with SMD were included. Key characteristics were extracted, and a meta-analysis was performed. Our systematic review was preregistered on PROSPERO (ID: CRD42024559043). The PRISMA guidelines were followed. The Joanna Briggs Institute (JBI) standardized critical appraisal tool developed for prevalence studies was applied to assess the quality of the included studies.

Results: The initial search yielded 4506 records, and after duplicate removal and screening, a total of 10 studies were finally included. The studies included used data from Europe, Asia, North America, and Oceania. Two studies employed a longitudinal design, while all other studies had a cross-sectional design. Most of the studies included between 100 and 500 individuals with SMD. All studies involved both male and female participants, with women typically comprising about 40% of the sample. The average age of participants often ranged from approximately 30 to 40 years. The estimated prevalence of loneliness was 59.1% (95% CI: 39.6% to 78.6%, I² = 99.3, P < .001) among individuals with any diagnosis of SMD. Furthermore, the estimated prevalence of objective social isolation was 63.0% (95% CI: 58.6% to 67.4%) among individuals with schizophrenia or schizophrenia spectrum disorder. The quality of the studies was moderate to good. Subjective well-being and depressive symptoms in particular were found to contribute to loneliness in the included studies.

Conclusions: The present systematic review with meta-analysis identified high levels of loneliness and objective social isolation among those with SMD. These findings stress the importance of monitoring and addressing social needs in this vulnerable group, which may have a positive effect on the life quality of individuals with SMD. Future research in neglected regions (e.g. South America and Africa) is recommended. Different diagnoses within severe mental disorders should be distinguished in future studies. Furthermore, additional longitudinal studies are required to explore the antecedents and consequences of loneliness and social isolation among individuals with SMD.

Aims: Only little empirical evidence exists on mental health in LGBTIQ+ refugees. In the present study, trauma exposure, experiences of sexual violence and current treatment needs for physical and mental health were investigated in association with symptoms of anxiety, depression, post-traumatic stress disorder (PTSD) and somatic symptom burden in LGBTIQ+ asylum-seekers resettled in Germany and seeking psychosocial support.

Methods: Data was collected in cooperation with a counselling centre for LGBTIQ+ asylum-seekers between Mai 2018 and March 2024, with a total of 120 completed questionnaires of adult clients. The questionnaire (11 different languages) included sociodemographic and flight-related questions as well as standardized instruments for assessing PTSD (PCL-5), depression (PHQ-9), somatic symptom burden (SSS-8), and anxiety (HSCL-25). Prevalence rates were calculated according to the cut-off scores of each questionnaire. Four logistic regression analyses were conducted to test for potential associations between being screened positive for anxiety, depression, somatic symptom burden or PTSD and the number of traumatic events, experiences of sexual violence as well as current treatment needs for physical and mental health.

Results: The great majority, 74.2% (95% CI: 66-82) of the respondents, screened positive for at least one of the mental disorders investigated, with 45% (95% CI: 36-54) suffering from somatic symptom burden, 44.2% (95% CI: 35-53) from depression, 58.3% (95% CI: 50-67) from PTSD, and 62.5% (95% CI: 54-71) from anxiety; 69.5% participants reported having been exposed to sexual violence. Current treatment needs for physical health problems were reported by 47% and for mental health problems by 56.7%. Participants with experiences of sexual violence were more likely to be screened positive for depression (OR: 6.787, 95% CI: 1.45-31.65) and PTSD (OR: 6.121, 95% CI: 1.34-27.95).

Conclusions: The study provides initial insights on mental health and associated factors in a highly burdened and hard-to-reach population. The findings are important for healthcare systems and political authorities in terms of assuring better protection and healthcare for LGBTIQ+ refugees and asylum-seekers.