Venous thromboembolism (VTE) is a fatal condition affecting older people. This study aims to identify specific risk factors for VTE in older psychiatric in-patients within mental hospital settings. Using predefined search terms, we searched five databases to capture studies evaluating risk factors associated with the occurrence of deep vein thrombosis and pulmonary embolism in older psychiatric in-patients.

Thirteen studies were identified, and a narrative synthesis performed. Increasing age was a consistent risk factor for VTE. Diagnosis and psychotropic medication use were inconsistent. Depression, catatonia and use of restraint in people with dementia were associated with higher risks.

Older psychiatric in-patients differ from medical and surgical in-patients in their risk profiles. Screening tools used in general hospital patients are of limited use among older adults in psychiatric hospital settings. An exclusive screening tool to identify VTE risk factors in older psychiatric in-patients is needed.

Diabetes is a global health concern, and early identification of high-risk individuals is crucial for preventive interventions. Finnish Diabetes Risk Score (FINDRISC) is a widely accepted non-invasive tool that estimates the 10-year diabetes risk. This study aims to validate the FINDRISC in the Turkish population and develop a specific model using data from a nationwide cohort.

The study used data of 12249 participants from the Türkiye Chronic Diseases and Risk Factors Survey. Data included sociodemographic variables, lifestyle factors, and anthropometric measurements. Multivariable logistic regression was employed using FINDRISC variables to predict incident type 2 diabetes mellitus (T2DM). Two country-specific models, one incorporating the waist-to-hip ratio (WHR model) and the other waist circumference (WC model), were developed. The least absolute shrinkage and selection operator (LASSO) algorithm was used for variable selection in the final models, and model discrimination indexes were compared.

The optimal FINDRISC cut-off was 8.5, with an area under the curve (AUC) of 0.76, demonstrating good predictive performance in identifying T2DM cases in the Turkish population. Both WHR and WC models showed similar predictive accuracy (AUC: 0.77). Marital status and education were associated with increased diabetes risk in both country-specific models.

The study found that the FINDRISC tool is effective in predicting the risk of type 2 diabetes in the Turkish population. Models using WHR and WC showed similar predictive performance to FINDRISC. Sociodemographic factors may play a role in diabetes risk. These findings highlight the need to consider population-specific characteristics when evaluating diabetes risk.

Climate change is significantly altering our planet, with greenhouse gas emissions and environmental changes bringing us closer to critical tipping points. These changes are impacting species and ecosystems worldwide, leading to the urgent need for understanding and mitigating climate change risks. In this study, we examined global research on assessing climate change risks to species and ecosystems. We found that interest in this field has grown rapidly, with researchers identifying key factors such as species' vulnerability, adaptability, and exposure to environmental changes. Our work highlights the importance of developing better tools to predict risks and create effective protect strategies.

The rising concentration of greenhouse gases, coupled with environmental changes such as albedo shifts, is accelerating the approach to critical climate tipping points. These changes have triggered significant biological responses on a global scale, underscoring the urgent need for robust climate change risk assessments for species and ecosystems. We conducted a systematic literature review using the Web of Science database. Our bibliometric analysis shows an exponential growth in publications since 2000, with over 200 papers published annually since 2019. Our bibliometric analysis reveals that the number of studies has exponentially increased since 2000, with over 200 papers published annually since 2019. High-frequency keywords such as ‘impact’, ‘risk’, ‘vulnerability’, ‘response’, ‘adaptation’, and ‘prediction’ were prevalent, highlighting the growing importance of assessing climate change risks. We then identified five universally accepted concepts for assessing the climate change risk on species and ecosystems: exposure, sensitivity, adaptivity, vulnerability, and response. We provided an overview of the principles, applications, advantages, and limitations of climate change risk modeling approaches such as correlative approaches, mechanistic approaches, and hybrid approaches. Finally, we emphasize that the emerging trends of risk assessment of climate change, encompass leveraging the concept of telecoupling, harnessing the potential of geography, and developing early warning mechanisms.

Climate change risks to biodiversity and ecosystem: key insights, modeling approaches, and emerging strategies.

An improved understanding of the factors associated with self-harm in young people who die by suicide can inform suicide prevention measures.

To describe sociodemographic and clinical characteristics and service utilisation related to self-harm in a national sample of young people who died by suicide.

We carried out a descriptive study of self-harm in a national consecutive case series (N = 544) of 10- to 19-year-olds who died by suicide over 3 years (2014–2016) in the UK as identified from national mortality data. Information was collected from coroner inquest hearings, child death investigations, criminal justice system and National Health Service serious incident reports.

Almost half (49%) of these young people had harmed themselves at some point in their lives, a quarter (26%) in the 3 months before death. Girls were twice as likely as boys to have recent self-harm (40 v. 20%; P < 0.001). Compared to the no self-harm group, young people with recent self-harm were more likely to have a mental illness diagnosis (63 v. 23%; P < 0.001); misused alcohol (19 v. 9%; P = 0.07); experienced physical, sexual or emotional abuse (17 v. 3%; P < 0.01); and recent life adversity (95 v. 75%; P < 0.001). Furthermore, they were more likely to be in contact with mental health services (60 v. 10%), or emergency departments or general physicians for a mental health condition (52 v. 10%) in the 3 months before death.

Presentation to services in young people who self-harm is an important opportunity to intervene through comprehensive psychosocial assessment and treatment of underlying conditions.

Early worsening of plasma lipid levels (EWL; ≥5% change after 1 month) induced by at-risk psychotropic treatments predicts considerable exacerbation of plasma lipid levels and/or dyslipidaemia development in the longer term.

We aimed to determine which clinical and genetic risk factors could predict EWL.

Predictive values of baseline clinical characteristics and dyslipidaemia-associated single nucleotide polymorphisms (SNPs) on EWL were evaluated in a discovery sample (n = 177) and replicated in two samples from the same cohort (PsyMetab; n1 = 176; n2 = 86).

Low baseline levels of total cholesterol, low-density lipoprotein cholesterol (LDL-C) and triglycerides, and high baseline levels of high-density lipoprotein cholesterol (HDL-C), were risk factors for early increase in total cholesterol (P = 0.002), LDL-C (P = 0.02) and triglycerides (P = 0.0006), and early decrease in HDL-C (P = 0.04). Adding genetic parameters (n = 17, 18, 19 and 16 SNPs for total cholesterol, LDL-C, HDL-C and triglycerides, respectively) improved areas under the curve for early worsening of total cholesterol (from 0.66 to 0.91), LDL-C (from 0.62 to 0.87), triglycerides (from 0.73 to 0.92) and HDL-C (from 0.69 to 0.89) (P ≤ 0.00003 in discovery sample). The additive value of genetics to predict early worsening of LDL-C levels was confirmed in two replication samples (P ≤ 0.004). In the combined sample (n ≥ 203), adding genetics improved the prediction of new-onset dyslipidaemia for total cholesterol, LDL-C and HDL-C (P ≤ 0.04).

Clinical and genetic factors contributed to the prediction of EWL and new-onset dyslipidaemia in three samples of patients who started at-risk psychotropic treatments. Future larger studies should be conducted to refine SNP estimates to be integrated into clinically applicable predictive models.

The Russian–Ukrainian War of 2022 (RUW-2022) was accompanied by the subsequent risk of accidents at a nuclear power plant in Ukraine. This study investigated posttraumatic stress (PTS) symptoms related to media reports of an attack on a Ukrainian nuclear power plant during the RUW-2022 among victims of the Fukushima nuclear disaster and revealed their association with radiation risk perception (RRP) of the accident.

This cross-sectional study targeted 1193 residents of Naraha Town in Fukushima Prefecture. PTS symptoms were measured using the Japanese version of the Impact of Events Scale-Revised (IES-R). Univariate and multivariate analyses explored the association between IES-R scores and background factors, particularly RRP.

Participants with higher RRP showed significantly higher IES-R scores; furthermore, the proportion of disruption because of radiation anxiety was significantly larger among higher RRP residents. Radiation anxiety mediated the association between RRP and PTS symptoms (total IES-R score and sub-item of intrusion).

People with higher RRP in Fukushima may continue to be at risk of persistent, unwanted PTS symptoms due to future nuclear crises. Therefore, mental health practitioners need to continue providing support in affected areas for a longer period than anticipated. Moreover, a population-based approach to cope with these stressors from media reports is essential.