Introduction: Over the past 20 years the WHO has considerably improved world mortality data. There are still shortcomings but more countries now report data and world-wide estimates are regularly made. Methods: Data about mortality have been retrieved from the WHO world database. Worldwide injury mortality estimates for 2008 as well as trends of the suicide rate from 1950 to 2009 were analysed. Results: Suicides in the world amount to 782 thousand in 2008 according to the WHO estimate, which is 1.4% of total mortality and 15% of injury mortality. The suicide rate for the world as a whole is estimated at 11.6 per 100,000 inhabitants. The male–female rate ratio of suicide is estimated to be highest in the European Region (4.0) and the lowest in the Eastern Mediterranean region (1.1). Among males the highest suicide rate in the 15–29 age group is in the SE Asian region, in the 45–59 age group in European males and for ages above 60 in the Western Pacific region. Females from SE Asia have a remarkably high suicide rate among 15–29-year-olds and from age 45 in the Western Pacific region. The leading country is currently Lithuania, with a suicide rate of 34.1 per 100,000 inhabitants. Also among males the suicide rate is the highest in Lithuania at 61.2. Among females South Korea with 22.1 is at the top of world suicide rates. Conclusions: During the past six decades, according to the WHO Japan, Hungary, and Lithuania have topped the list of world countries by suicide rate, but if the current trends continue South Korea will overtake all others in a few years. The heart of the problem of suicide mortality has shifted from Western Europe to Eastern Europe and now seems to be shifting to Asia. China and India are the biggest contributors to the absolute number of suicides in the world.

Risk-behaviors are a major contributor to the leading causes of morbidity among adolescents and young people; however, their association with pathological Internet use (PIU) is relatively unexplored, particularly within the European context. The main objective of this study is to investigate the association between risk-behaviors and PIU in European adolescents. This cross-sectional study was conducted within the framework of the FP7 European Union project: Saving and Empowering Young Lives in Europe (SEYLE). Data on adolescents were collected from randomized schools within study sites across eleven European countries. PIU was measured using Young’s Diagnostic Questionnaire (YDQ). Risk-behaviors were assessed using questions procured from the Global School-Based Student Health Survey (GSHS). A total of 11,931 adolescents were included in the analyses: 43.4% male and 56.6% female (M/F: 5179/6752), with a mean age of 14.89 ± 0.87 years. Adolescents reporting poor sleeping habits and risk-taking actions showed the strongest associations with PIU, followed by tobacco use, poor nutrition and physical inactivity. Among adolescents in the PIU group, 89.9% were characterized as having multiple risk-behaviors. The significant association observed between PIU and risk-behaviors, combined with a high rate of co-occurrence, underlines the importance of considering PIU when screening, treating or preventing high-risk behaviors among adolescents.

The Awareness program was designed as a part of the EU-funded Saving and Empowering Young Lives in Europe (SEYLE) intervention study to promote mental health of adolescents in 11 European countries by helping them to develop problem-solving skills and encouraging them to self-recognize the need for help as well as how to help peers in need.

Background: Adolescents and young adults are among the most frequent Internet users, and accumulating evidence suggests that their Internet behaviors might affect their mental health. Internet use may impact mental health because certain Web-based content could be distressing. It is also possible that excessive use, regardless of content, produces negative consequences, such as neglect of protective offline activities. Objective: The objective of this study was to assess how mental health is associated with (1) the time spent on the Internet, (2) the time spent on different Web-based activities (social media use, gaming, gambling, pornography use, school work, newsreading, and targeted information searches), and (3) the perceived consequences of engaging in those activities. Methods: A random sample of 2286 adolescents was recruited from state schools in Estonia, Hungary, Italy, Lithuania, Spain, Sweden, and the United Kingdom. Questionnaire data comprising Internet behaviors and mental health variables were collected and analyzed cross-sectionally and were followed up after 4 months. Results: Cross-sectionally, both the time spent on the Internet and the relative time spent on various activities predicted mental health (P<.001), explaining 1.4% and 2.8% variance, respectively. However, the consequences of engaging in those activities were more important predictors, explaining 11.1% variance. Only Web-based gaming, gambling, and targeted searches had mental health effects that were not fully accounted for by perceived consequences. The longitudinal analyses showed that sleep loss due to Internet use (ß=.12, 95% CI=0.05-0.19, P=.001) and withdrawal (negative mood) when Internet could not be accessed (ß=.09, 95% CI=0.03-0.16, P<.01) were the only consequences that had a direct effect on mental health in the long term. Perceived positive consequences of Internet use did not seem to be associated with mental health at all. Conclusions: The magnitude of Internet use is negatively associated with mental health in general, but specific Web-based activities differ in how consistently, how much, and in what direction they affect mental health. Consequences of Internet use (especially sleep loss and withdrawal when Internet cannot be accessed) seem to predict mental health outcomes to a greater extent than the specific activities themselves. Interventions aimed at reducing the negative mental health effects of Internet use could target its negative consequences instead of the Internet use itself. Trial Registration: International Standard Randomized Controlled Trial Number (ISRCTN): 65120704; http://www.isrctn.com/ISRCTN65120704?q=&filters=recruitmentCountry:Lithuania&sort=&offset= 5&totalResults=32&page=1&pageSize=10&searchType=basic-search (Archived by WebCite at http://www.webcitation/abcdefg)

It is well known that suicidal rates vary considerably among European countries and the reasons for this are unknown, although several theories have been proposed. The effect of economic variables has been extensively studied but not that of climate. Data from 29 European countries covering the years 2000–2012 and concerning male and female standardized suicidal rates (according to WHO), economic variables (according World Bank) and climate variables were gathered. The statistical analysis included cluster and principal component analysis and categorical regression. The derived models explained 62.4 % of the variability of male suicidal rates. Economic variables alone explained 26.9 % and climate variables 37.6 %. For females, the respective figures were 41.7, 11.5 and 28.1 %. Male suicides correlated with high unemployment rate in the frame of high growth rate and high inflation and low GDP per capita, while female suicides correlated negatively with inflation. Both male and female suicides correlated with low temperature. The current study reports that the climatic effect (cold climate) is stronger than the economic one, but both are present. It seems that in Europe suicidality follows the climate/temperature cline which interestingly is not from south to north but from south to north-east. This raises concerns that climate change could lead to an increase in suicide rates. The current study is essentially the first successful attempt to explain the differences across countries in Europe; however, it is an observational analysis based on aggregate data and thus there is a lack of control for confounders.

Mental health problems and risk behaviours among young people are of great public health concern. Consequently, within the VII Framework Programme, the European Commission funded the Saving and Empowering Young Lives in Europe (SEYLE) project. This Randomized Controlled Trial (RCT) was conducted in eleven European countries, with Sweden as the coordinating centre, and was designed to identify an effective way to promote mental health and reduce suicidality and risk taking behaviours among adolescents. To describe the methodological and field procedures in the SEYLE RCT among adolescents, as well as to present the main characteristics of the recruited sample. Analyses were conducted to determine: 1) representativeness of study sites compared to respective national data; 2) response rate of schools and pupils, drop-out rates from baseline to 3 and 12 month follow-up, 3) comparability of samples among the four Intervention Arms; 4) properties of the standard scales employed: Beck Depression Inventory, Second Edition (BDI-II), Zung Self-Rating Anxiety Scale (Z-SAS), Strengths and Difficulties Questionnaire (SDQ), World Health Organization Well-Being Scale (WHO-5). Participants at baseline comprised 12,395 adolescents (M/F: 5,529/6,799; mean age=14.9±0.9) from Austria, Estonia, France, Germany, Hungary, Ireland, Israel, Italy, Romania, Slovenia and Spain. At the 3 and 12 months follow up, participation rates were 87.3% and 79.4%, respectively. Demographic characteristics of participating sites were found to be reasonably representative of their respective national population. Overall response rate of schools was 67.8%. All scales utilised in the study had good to very good internal reliability, as measured by Cronbach’s alpha (BDI-II: 0.864; Z-SAS: 0.805; SDQ: 0.740; WHO-5: 0.799). SEYLE achieved its objective of recruiting a large representative sample of adolescents within participating European countries. Analysis of SEYLE data will shed light on the effectiveness of important interventions aimed at improving adolescent mental health and well-being, reducing risk-taking and self-destructive behaviour and preventing suicidality. US National Institute of Health (NIH) clinical trial registry ( NCT00906620 ) and the German Clinical Trials Register ( DRKS00000214 ).