Main Features of Prevalence and Severity of Major Depressive Episode in Romania

The objectives of the current article are to present some nationally representative estimates of lifetime, 12-months prevalence of MDE the age of onset, years in episode, the effects of MDE on role impairment. The lifetime prevalence of MDE was 3.3% for “all ages”, with higher values for females than for males (4.1% versus 2.5%) and the prevalence estimates of CIDI/DSM-IV 12-months Major Depressive Episode (MDE) was 1.8% (2.2% for females and 1.4% for males).  Approximately half of those with lifetime prevalence MDE presented 12-months MDE too (53.8%).  Within the age groups “18-34”, “all ages” and “50-64”, the females have the mean onset of MDE earlier than males (a slight difference for the first two situations, a difference of about 8 years for the latter). Within the age groups “35-49” of “65 years and over”, the males have the onset of MDE earlier than the females with 3-4 years. Regarding the mean number of years in episode, for all subjects was found a value of 5.7 years. Symptom severity assessed with the Quick Inventory of Depressive Symptomatology Self Report (QIDS-SR), revealed that almost two thirds of cases with MDE were “severe” or “very severe” from clinical point of view.  Number of weeks depressed in the 365 days before the interview, expressed as mean was 30.8 for those with “severe” symptoms/domain. In the past 30 days, the highest WHODAS score was for out of role domain (36.2), then for mobility (14.6).  Regarding the number of days out of role in the last year due to depression, this was 82.1 for the age group “50-64” and 63.5 for those of “65 years old and over”.  Major Depression Episode is a seriously impairment condition. The severe consequences of the depression on functioning in labour and social areas call attention to the need for early diagnostic, proper treatment and intervention. Key words: major depressive episode, lifetime prevalence, 12-mo prevalence, Sheehan score, disability assessment schedul

Relationship of suicide rates with climate and economic variables in Europe during 2000–2012

Background 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. Methods 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. Results 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. Discussion 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

The African Global Mental Health Institute: Increasing capacity, inclusivity and translation of psychiatric research and care

The largest treatment gap for mental, neurological and substance use (MNS) disorders to date exists in Sub-Saharan Africa (e.g., South Africa, Malawi, Nigeria).  While efforts have been made to reduce the global burden of MNS disorders, there remain significant barriers to delivery of equitable mental health care in Africa and the diaspora. These barriers are deeply rooted in a lack of research structures to inform care delivery, few outlets to train in-country mental health professionals, and limited involvement of policymakers in translation of research findings. Given the demonstrated need across domains of research, education, service delivery and policy in Africa, it is in the purview of global leaders and mental health professionals to build the infrastructure necessary to make systematic, targeted strides to develop each of these areas. With this conceptual framework in mind, over fifty global leaders, psychiatrists, mental health professionals and advocates with expertise in cultural psychiatry convened at a global conference in Cape Town, South Africa in 2016 to establish the African Global Mental Health Institute (AGMHI). The AGMHI is an organizational effort that aims to reduce the global burden of mental illness through research, education and training, service delivery, and policy. Aligned with mental health initiatives posited by the World Health Organization (WHO) and the World Bank, the AGMHI represents an opportunity to explore and understand cultural nuance among populations in Africa and the diaspora. This article focuses on the AGMHI’s targeted strategies in the following actions: 1) bolstering training and education programs for clinicians and/or researchers in Africa and the diaspora to increase human capacity for mental health; 2) conducting and disseminating inclusive, culturally-relevant research (e.g., research that involves community stakeholders in its design and conduct) to meet the urgent need for a culturally-relevant evidence base;  3) identifying key stakeholders to promote sustainable mental health care and inform policy; and 4) fostering local and global collaborations (e.g., engaging local and national governments, non-governmental organizations (NGO), academic institutions, etc.) to share methods of improving access to mental health services. In concert with empirical data, these strategies were devised by members of the AGMHI, which is comprised of international leaders with decades of expertise in global psychiatry. While the MNS disorder treatment gap remains at large, the AGMHI believes these specific strategies are a step toward reducing the treatment gap and enhancing mental health care access globally

Relationship of suicide rates with climate and economic variables in Europe during 2000-2012

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. 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. 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. 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. RESULTS METHODS BACKGROUND DISCUSSIO