Season, weather, and suicide:Further evidence for ecological complexity

Background: easonality in suicide is reported worldwide, and peaks in late spring. Despite the potential connection to the weather, associations between meteorological variables and suicide does not explain seasonality. Studies testing for seasonality while controlling for the weather show patterns that are more complex than a straightforward link between spring-like weather and suicide. Methods: We tested whether seasonality in suicide was due to meteorological variation (hours of sunshine, rainfall, or temperature) in a novel population (Scotland; 2003–2013). We also sought to further explore the ecological complexity demonstrated in previous work by testing associations at a single location (Tay Road Bridge; 1968–2017). RESULTS: We found peaks in suicidal behavior in June at the bridge, but no seasonality for Scotland as a whole. Seasonality was reduced when we controlled for maximum temperature and hours of sunshine. We found patterns to be dependent upon sex, with stronger seasonal and meteorological effects amongst men. Limitations: Our study was exploratory and relies on population-level data. Conclusions: Seasonal and meteorological effects on suicide are dependent upon local and individual context, with significant effects apparent at the Tay Road Bridge and not across Scotland as a whole. Men may be more sensitive to season and weather. In order to determine whether seasonality in suicide is due to meteorological variation, future research should test patterns in small geographical units, in men and women, and for different suicide methods, and seek to identify the social and physical factors which predict variation in patterns

Seasonal patterns of suicides over the period of socio-economic transition in Lithuania

BACKGROUND: In Lithuania, suicides are a grave public health problem, requiring more extensive investigation. The aim of the study was to assess the seasonal variations of suicides in Lithuania throughout the years 1993–2002, describing patterns by gender, age and method of suicide. METHODS: The study material consisted of all registered suicides (n = 16,147) committed throughout 1993–2002 in Lithuania. Smoothed trends were inspected. The seasonal effect was explored using monthly ratio statistics and spectral analysis. RESULTS: Suicides in Lithuania have a distinct annual rhythm with peaks in summer and troughs in December. The December frequencies fell by more than 23% in men and 30% in women, while June peak reached nearly 23% in men and July peak exceeded 29% in women, compare with the average levels, (p < 0.05). Hanging was the most common method of suicide both in men and women comprising up to 90% among all suicides in 1998–2002. Among different methods, only hanging suicides showed significant seasonal variations, especially in men. The seasonal amplitude has decreased over time. CONCLUSION: Substantial seasonal variations in suicides were associated with a high proportion of hanging. Extremely high suicide rates in Lithuania require further extensive studies and urgent preventive programs, taking into account the suggestions of this survey

Multi-Scale Motility Amplitude Associated with Suicidal Thoughts in Major Depression

Major depression occurs at high prevalence in the general population, often starts in juvenile years, recurs over a lifetime, and is strongly associated with disability and suicide. Searches for biological markers in depression may have been hindered by assuming that depression is a unitary and relatively homogeneous disorder, mainly of mood, rather than addressing particular, clinically crucial features or diagnostic subtypes. Many studies have implicated quantitative alterations of motility rhythms in depressed human subjects. Since a candidate feature of great public-health significance is the unusually high risk of suicidal behavior in depressive disorders, we studied correlations between a measure (vulnerability index [VI]) derived from multi-scale characteristics of daily-motility rhythms in depressed subjects (n = 36) monitored with noninvasive, wrist-worn, electronic actigraphs and their self-assessed level of suicidal thinking operationalized as a wish to die. Patient-subjects had a stable clinical diagnosis of bipolar-I, bipolar-II, or unipolar major depression (n = 12 of each type). VI was associated inversely with suicidal thinking (r =  –0.61 with all subjects and r =  –0.73 with bipolar disorder subjects; both p<0.0001) and distinguished patients with bipolar versus unipolar major depression with a sensitivity of 91.7% and a specificity of 79.2%. VI may be a useful biomarker of characteristic features of major depression, contribute to differentiating bipolar and unipolar depression, and help to detect risk of suicide. An objective biomarker of suicide-risk could be advantageous when patients are unwilling or unable to share suicidal thinking with clinicians

Association of temporal factors and suicides in the United States, 2000–2004

The purpose of the study was to examine the association of temporal factors, in particular days of the week and seasons of the year and death from suicide in the United States. Data were pooled from the Multiple Cause of Death Files. Hierarchical logistic regression models were fitted to all deaths occurring in 2000 through 2004 by suicide. The incidence of suicide was significantly higher on Wednesdays, compared to Sunday. Specifically, individuals were 99% more likely to kill themselves on Wednesday than on Sunday. Suicides were more prevalent in the summer months, and they were less likely to occur in winter. The state suicide rate significantly elevated individual suicide risk. The results held even after controlling for the potentially confounding effects of socio-economic and demographic variables at both the individual and state levels. It was concluded that the observed association between seasonality and suicide cannot be discounted as a mere coincidence. Future research ought to focus on integrating individual level data and contextual variables when testing for seasonality effects

Factors Associated with Work Participation and Work Functioning in Depressed Workers: A Systematic Review

Background Depression is associated with negative work outcomes such as reduced work participation (WP) (e.g., sick leave duration, work status) and work functioning (WF) (e.g., loss of productivity, work limitations). For the development of evidence-based interventions to improve these work outcomes, factors predicting WP and WF have to be identified. Methods This paper presents a systematic literature review of studies identifying factors associated with WP and WF of currently depressed workers. Results A total of 30 studies were found that addressed factors associated with WP (N = 19) or WF (N = 11). For both outcomes, studies reported most often on the relationship with disorder-related factors, whereas personal factors and work-related factors were less frequently addressed. For WP, the following relationships were supported: strong evidence was found for the association between a long duration of the depressive episode and work disability. Moderate evidence was found for the associations between more severe types of depressive disorder, presence of co-morbid mental or physical disorders, older age, a history of previous sick leave, and work disability. For WF, severe depressive symptoms were associated with work limitations, and clinical improvement was related to work productivity (moderate evidence). Due to the cross-sectional nature of about half of the studies, only few true prospective associations could be identified. Conclusion Our study identifies gaps in knowledge regarding factors predictive of WP and WF in depressed workers and can be used for the design of future research and evidence-based interventions. We recommend undertaking more longitudinal studies to identify modifiable factors predictive of WP and WF, especially work-related and personal factors

Simulation numérique de la fonderie d’aciers : détermination et optimisation des paramètres de calage pour lesaciers faiblement alliés coulés en moule sable à vert.

The company SAFE Metal uses digital foundry simulation in its production process to meet the needs of its customers and produce quality steel parts. This tool is used to size mold impressions to obtain flawless parts. However, there are sometimes differences between the results given by the simulation and the parts produced in the factory. This variance often results in additional costs that could be avoided through a simulation closer to reality.The objective of this work is to improve the predictive quality of the simulation of low alloy steel foundry moulded in silico-clay sand.Foundry software developers provide algorithmic tools to digitally reproduce physical phenomena. They also provide a set of data on the materials used in the simulation. There are thus two approaches to try to improve the predictive character of the simulation: either act on algorithms and calculations, or optimize the input data of the software. Whether for the mould or steel, SAFE Metal uses its own materials and therefore wanted to refine the knowledge on these materials whose properties could be transferable to any software in the future.These materials are, during the foundry process, brought to temperatures up to 1630°C, making any measurement relatively complex.With regard to steel, the precise grade was first determined by spark spectrometry, which enabled the CALPHAD method to access the temperature variation of certain physical properties: mass heat capacity, density and latent heat. Regarding thermal conductivity, the law was obtained via JMatPro software and compared to experimental values measured by the «Laser Flash» method.For sand, the mass heat capacity was measured by differential scanning calorimetry (DSC), density by experimental measurement (volume and mass as a function of temperature) and thermal conductivity by heat flux measurement (experience of the semi-infinite plate).All these «corrected» data were then implemented into the NovaFlow&Solid software database to simulate the cooling of a piece of steel in a silico-clay mould. It has been shown that these corrections allow a significant approximation to the experimental curves. This improvement is a necessary prerequisite for the simulation of foundry defects such as rebates and porosities (voids created during solidification of the metal) but it does not yet allow to determine with accuracy the position and the volume of these defects; this remains to be developed in future studies.L’entreprise SAFE Metal utilise dans son processus de production la simulation numérique de fonderie pour répondre aux besoins de ses clients et produire des pièces de qualité en acier. Cet outil sert à dimensionner les empreintes des moules dans le but d’obtenir des pièces exemptes de défauts. Cependant, il est parfois observé des différences entre les résultats donnés par la simulation et les pièces réalisées en usine. Cet écart entraîne souvent des coûts supplémentaires qui pourraient être évités grâce à une simulation plus proche de la réalité.L’objectif de ce travail consiste à améliorer la qualité prédictive de la simulation de fonderie d’acier faiblement allié moulé en sable silico-argileux.Les développeurs de logiciels de fonderie fournissent des outils algorithmiques permettant de reproduire numériquement des phénomènes physiques. Ils mettent également à disposition un ensemble de données concernant les matériaux utilisés dans la simulation. Il existe donc deux approches pour tenter d’améliorer le caractère prédictif de la simulation : soit agir sur les algorithmes et les calculs, soit optimiser les données d’entrée des logiciels. Que ce soit pour le moule ou pour l’acier, SAFE Metal utilise des matériaux qui lui sont propres et a donc souhaité affiner les connaissances sur ces matériaux dont les propriétés pourront être transférables à n’importe quel logiciel à l’avenir.Ces matériaux sont, au cours du processus de fonderie portés à des températures pouvant atteindre 1630°C, ce qui rend toute mesure relativement complexe.En ce qui concerne l’acier, dans un premier temps, la nuance précise a été déterminé par spectrométrie à étincelle, ce qui a permis grâce à la méthode CALPHAD d’accéder à la variation en fonction de la température de certaines propriétés physiques : capacité calorifique massique, masse volumique et chaleur latente. En ce qui concerne la conductivité thermique, la loi a été obtenue via le logiciel JMatPro et comparée à des valeurs expérimentales mesurées par la méthode « Laser Flash ».En ce qui concerne le sable, la capacité calorifique massique a été mesurée par calorimétrie différentielle à balayage (DSC), la masse volumique par mesure expérimentale (volume et masse en fonction de la température) et la conductivité thermique par mesure de flux de chaleur (expérience de « la plaque semi-infinie »).Toutes ces données « corrigées » ont ensuite été implantées dans la base de données du logiciel NovaFlow&Solid pour simuler le refroidissement d’un lopin d’acier dans un moule silico-argileux. Il a été montré que ces corrections permettent de se rapprocher significativement des courbes expérimentales. Cette amélioration est un préalable nécessaire à la simulation de défauts de fonderie tel que les retassures et les porosités (vides créés lors de la solidification du métal) mais elle ne permet pas encore de déterminer avec exactitude la position et le volume de ces défauts ; ceci reste à développer dans de futures études

Rythmes circadiens et depression

SIGLECNRS T Bordereau / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc