Suicide Prevention for Older Adults in Residential Communities: Implications for Policy and Practice

Examining an often under-appreciated area, Carol Podgorski and colleagues discuss the suicide risk and opportunities for suicide prevention in seniors' residential communities

Prediction and prevention of suicide in patients with unipolar depression and anxiety

Epidemiological data suggest that between 59 and 87% of suicide victims suffered from major depression while up to 15% of these patients will eventually commit suicide. Male gender, previous suicide attempt(s), comorbid mental disorders, adverse life-situations, acute psycho-social stressors etc. also constitute robust risk factors. Anxiety and minor depression present with a low to moderate increase in suicide risk but anxiety-depression comorbidity increases this risk dramatically Contrary to the traditional psychoanalytic approach which considers suicide as a retrospective murder or an aggression turned in-wards, more recent studies suggest that the motivations to commit suicide may vary and are often too obscure. Neurobiological data suggest that low brain serotonin activity might play a key role along with the tryptophan hydroxylase gene. Social factors include social support networks, religion etc. It is proven that most suicide victims had asked for professional help just before committing suicide, however they were either not diagnosed (particularly males) or the treatment they received was inappropriate or inadequate. The conclusion is that promoting suicide prevention requires the improving of training and skills of both psychiatrists and many non-psychiatrists and especially GPs in recognizing and treating depression and anxiety. A shift of focus of attention is required in primary care to detect potentially suicidal patients presenting with psychological problems. The proper use of antidepressants, after a careful diagnostic evaluation, is important and recent studies suggest that successful acute and long-term antidepressant pharmacotherapy reduces suicide morbidity and mortality

Understanding animal fears: a comparison of the cognitive vulnerability and harm-looming models

Background: The Cognitive Vulnerability Model holds that both clinical and sub-clinical manifestations of animal fears are a result of how an animal is perceived, and can be used to explain both individual differences in fear acquisition and the uneven distribution of fears in the population. This study looked at the association between fear of a number of animals and perceptions of the animals as uncontrollable, unpredictable, dangerous and disgusting. Also assessed were the perceived loomingness, prior familiarity, and negative evaluation of the animals as well as possible conditioning experiences. Methods: 162 first-year University students rated their fear and perceptions of four high-fear and four low-fear animals. Results: Perceptions of the animals as dangerous, disgusting and uncontrollable were significantly associated with fear of both high- and low-fear animals while perceptions of unpredictability were significantly associated with fear of high-fear animals. Conditioning experiences were unrelated to fear of any animals. In multiple regression analyses, loomingness did not account for a significant amount of the variance in fear beyond that accounted for by the cognitive vulnerability variables. However, the vulnerability variables accounted for between 20% and 51% of the variance in all animals fears beyond that accounted for by perceptions of the animals as looming. Perceptions of dangerousness, uncontrollability and unpredictability were highly predictive of the uneven distribution of animal fears. Conclusion: This study provides support for the Cognitive Vulnerability Model of the etiology of specific fears and phobias and brings into question the utility of the harm-looming model in explaining animal fearJason M Armfiel

Melanism in Peromyscus Is Caused by Independent Mutations in Agouti

Identifying the molecular basis of phenotypes that have evolved independently can provide insight into the ways genetic and developmental constraints influence the maintenance of phenotypic diversity. Melanic (darkly pigmented) phenotypes in mammals provide a potent system in which to study the genetic basis of naturally occurring mutant phenotypes because melanism occurs in many mammals, and the mammalian pigmentation pathway is well understood. Spontaneous alleles of a few key pigmentation loci are known to cause melanism in domestic or laboratory populations of mammals, but in natural populations, mutations at one gene, the melanocortin-1 receptor (Mc1r), have been implicated in the vast majority of cases, possibly due to its minimal pleiotropic effects. To investigate whether mutations in this or other genes cause melanism in the wild, we investigated the genetic basis of melanism in the rodent genus Peromyscus, in which melanic mice have been reported in several populations. We focused on two genes known to cause melanism in other taxa, Mc1r and its antagonist, the agouti signaling protein (Agouti). While variation in the Mc1r coding region does not correlate with melanism in any population, in a New Hampshire population, we find that a 125-kb deletion, which includes the upstream regulatory region and exons 1 and 2 of Agouti, results in a loss of Agouti expression and is perfectly associated with melanic color. In a second population from Alaska, we find that a premature stop codon in exon 3 of Agouti is associated with a similar melanic phenotype. These results show that melanism has evolved independently in these populations through mutations in the same gene, and suggest that melanism produced by mutations in genes other than Mc1r may be more common than previously thought

Variation in Childhood Diarrheal Morbidity and Mortality in Africa, 2000-2015

Background Diarrheal diseases are the third leading cause of disease and death in children younger than 5 years of age in Africa and were responsible for an estimated 30 million cases of severe diarrhea (95% credible interval, 27 million to 33 million) and 330,000 deaths (95% credible interval, 270,000 to 380,000) in 2015. The development of targeted approaches to address this burden has been hampered by a paucity of comprehensive, fine-scale estimates of diarrhea-related disease and death among and within countries. Methods We produced annual estimates of the prevalence and incidence of diarrhea and diarrhea-related mortality with high geographic detail (5 km2) across Africa from 2000 through 2015. Estimates were created with the use of Bayesian geostatistical techniques and were calibrated to the results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016. Results The results revealed geographic inequality with regard to diarrhea risk in Africa. Of the estimated 330,000 childhood deaths that were attributable to diarrhea in 2015, more than 50% occurred in 55 of the 782 first-level administrative subdivisions (e.g., states). In 2015, mortality rates among first-level administrative subdivisions in Nigeria differed by up to a factor of 6. The case fatality rates were highly varied at the national level across Africa, with the highest values observed in Benin, Lesotho, Mali, Nigeria, and Sierra Leone. Conclusions Our findings showed concentrated areas of diarrheal disease and diarrhea-related death in countries that had a consistently high burden as well as in countries that had considerable national-level reductions in diarrhea burden. (Funded by the Bill and Melinda Gates Foundation.

The global burden of tuberculosis: results from the Global Burden of Disease Study 2015

Background: An understanding of the trends in tuberculosis incidence, prevalence, and mortality is crucial to tracking of the success of tuberculosis control programmes and identification of remaining challenges. We assessed trends in the fatal and non-fatal burden of tuberculosis over the past 25 years for 195 countries and territories. Methods: We analysed 10 691 site-years of vital registration data, 768 site-years of verbal autopsy data, and 361 site-years of mortality surveillance data using the Cause of Death Ensemble model to estimate tuberculosis mortality rates. We analysed all available age-specific and sex-specific data sources, including annual case notifications, prevalence surveys, and estimated cause-specific mortality, to generate internally consistent estimates of incidence, prevalence, and mortality using DisMod-MR 2.1, a Bayesian meta-regression tool. We assessed how observed tuberculosis incidence, prevalence, and mortality differed from expected trends as predicted by the Socio-demographic Index (SDI), a composite indicator based on income per capita, average years of schooling, and total fertility rate. We also estimated tuberculosis mortality and disability-adjusted life-years attributable to the independent effects of risk factors including smoking, alcohol use, and diabetes. Findings: Globally, in 2015, the number of tuberculosis incident cases (including new and relapse cases) was 10·2 million (95% uncertainty interval 9·2 million to 11·5 million), the number of prevalent cases was 10·1 million (9·2 million to 11·1 million), and the number of deaths was 1·3 million (1·1 million to 1·6 million). Among individuals who were HIV negative, the number of incident cases was 8·8 million (8·0 million to 9·9 million), the number of prevalent cases was 8·9 million (8·1 million to 9·7 million), and the number of deaths was 1·1 million (0·9 million to 1·4 million). Annualised rates of change from 2005 to 2015 showed a faster decline in mortality (–4·1% [–5·0 to –3·4]) than in incidence (–1·6% [–1·9 to –1·2]) and prevalence (–0·7% [–1·0 to –0·5]) among HIV-negative individuals. The SDI was inversely associated with HIV-negative mortality rates but did not show a clear gradient for incidence and prevalence. Most of Asia, eastern Europe, and sub-Saharan Africa had higher rates of HIV-negative tuberculosis burden than expected given their SDI. Alcohol use accounted for 11·4% (9·3–13·0) of global tuberculosis deaths among HIV-negative individuals in 2015, diabetes accounted for 10·6% (6·8–14·8), and smoking accounted for 7·8% (3·8–12·0). Interpretation: Despite a concerted global effort to reduce the burden of tuberculosis, it still causes a large disease burden globally. Strengthening of health systems for early detection of tuberculosis and improvement of the quality of tuberculosis care, including prompt and accurate diagnosis, early initiation of treatment, and regular follow-up, are priorities. Countries with higher than expected tuberculosis rates for their level of sociodemographic development should investigate the reasons for lagging behind and take remedial action. Efforts to prevent smoking, alcohol use, and diabetes could also substantially reduce the burden of tuberculosis

Mapping inequalities in exclusive breastfeeding in low- and middle-income countries, 2000–2018

Exclusive breastfeeding (EBF)-giving infants only breast-milk for the first 6 months of life-is a component of optimal breastfeeding practices effective in preventing child morbidity and mortality. EBF practices are known to vary by population and comparable subnational estimates of prevalence and progress across low- and middle-income countries (LMICs) are required for planning policy and interventions. Here we present a geospatial analysis of EBF prevalence estimates from 2000 to 2018 across 94 LMICs mapped to policy-relevant administrative units (for example, districts), quantify subnational inequalities and their changes over time, and estimate probabilities of meeting the World Health Organization's Global Nutrition Target (WHO GNT) of ≥70% EBF prevalence by 2030. While six LMICs are projected to meet the WHO GNT of ≥70% EBF prevalence at a national scale, only three are predicted to meet the target in all their district-level units by 2030.This work was primarily supported by grant no. OPP1132415 from the Bill & Melinda Gates Foundation. Co-authors used by the Bill & Melinda Gates Foundation (E.G.P. and R.R.3) provided feedback on initial maps and drafts of this manuscript. L.G.A. has received support from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brasil (CAPES), Código de Financiamento 001 and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) (grant nos. 404710/2018-2 and 310797/2019-5). O.O.Adetokunboh acknowledges the National Research Foundation, Department of Science and Innovation and South African Centre for Epidemiological Modelling and Analysis. M.Ausloos, A.Pana and C.H. are partially supported by a grant from the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project no. PN-III-P4-ID-PCCF-2016-0084. P.C.B. would like to acknowledge the support of F. Alam and A. Hussain. T.W.B. was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, funded by the German Federal Ministry of Education and Research. K.Deribe is supported by the Wellcome Trust (grant no. 201900/Z/16/Z) as part of his international intermediate fellowship. C.H. and A.Pana are partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project no. PN-III-P2-2.1-SOL-2020-2-0351. B.Hwang is partially supported by China Medical University (CMU109-MF-63), Taichung, Taiwan. M.Khan acknowledges Jatiya Kabi Kazi Nazrul Islam University for their support. A.M.K. acknowledges the other collaborators and the corresponding author. Y.K. was supported by the Research Management Centre, Xiamen University Malaysia (grant no. XMUMRF/2020-C6/ITM/0004). K.Krishan is supported by a DST PURSE grant and UGC Centre of Advanced Study (CAS II) awarded to the Department of Anthropology, Panjab University, Chandigarh, India. M.Kumar would like to acknowledge FIC/NIH K43 TW010716-03. I.L. is a member of the Sistema Nacional de Investigación (SNI), which is supported by the Secretaría Nacional de Ciencia, Tecnología e Innovación (SENACYT), Panamá. M.L. was supported by China Medical University, Taiwan (CMU109-N-22 and CMU109-MF-118). W.M. is currently a programme analyst in Population and Development at the United Nations Population Fund (UNFPA) Country Office in Peru, which does not necessarily endorses this study. D.E.N. acknowledges Cochrane South Africa, South African Medical Research Council. G.C.P. is supported by an NHMRC research fellowship. P.Rathi acknowledges support from Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, India. Ramu Rawat acknowledges the support of the GBD Secretariat for supporting the reviewing and collaboration of this paper. B.R. acknowledges support from Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal. A.Ribeiro was supported by National Funds through FCT, under the programme of ‘Stimulus of Scientific Employment—Individual Support’ within the contract no. info:eu-repo/grantAgreement/FCT/CEEC IND 2018/CEECIND/02386/2018/CP1538/CT0001/PT. S.Sajadi acknowledges colleagues at Global Burden of Diseases and Local Burden of Disease. A.M.S. acknowledges the support from the Egyptian Fulbright Mission Program. F.S. was supported by the Shenzhen Science and Technology Program (grant no. KQTD20190929172835662). A.Sheikh is supported by Health Data Research UK. B.K.S. acknowledges Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal for all the academic support. B.U. acknowledges support from Manipal Academy of Higher Education, Manipal. C.S.W. is supported by the South African Medical Research Council. Y.Z. was supported by Science and Technology Research Project of Hubei Provincial Department of Education (grant no. Q20201104) and Outstanding Young and Middle-aged Technology Innovation Team Project of Hubei Provincial Department of Education (grant no. T2020003). The funders of the study had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication. All maps presented in this study are generated by the authors and no permissions are required to publish them

The Effect of Obesity on Medical Students' Approach to Patients with Abdominal Pain

Because widely held stereotypes characterize obese people as less intelligent, unhappy, lacking in self control and more prone to psychological problems, we tested whether obese appearance alone would affect medical students' decisions about the diagnosis and management of simulated patients. We videotaped 4 patient simulators presenting each of 4 cases in 2 states: normal and obese (by using padding and bulky clothing). Seventy-two clinical students at 2 medical schools viewed the cases and answered questions about diagnostic tests and management. We found the expected biases toward patients when in their obese form as well as pessimism about patient compliance and success of therapy, but there were no significant differences in tests or treatments ordered except where appropriate for an obese patient (e.g., weight reduction diet). Thus, the appearance of obesity alone biased the students' impressions of the patients, but did not affect diagnostic test ordering