Diseases due to unhealthy environments: an updated estimate of the global burden of disease attributable to environmental determinants of health

The update of the global burden of disease attributable to the environment is presented. The study focuses on modifiable risks to show the potential health impact from environmental interventions.; Systematic literature reviews on 133 diseases and injuries were performed. Comparative risk assessments were complemented by more limited epidemiological estimates, expert opinion and information on disease transmission pathways. Population attributable fractions were used to calculate global deaths and global disease burden from environmental risks.; Twenty-three percent (95% CI: 13-34%) of global deaths and 22% (95% CI: 13-32%) of global disability adjusted life years (DALYs) were attributable to environmental risks in 2012. Sixty-eight percent of deaths and 56% of DALYs could be estimated with comparative risk assessment methods. The global disease burden attributable to the environment is now dominated by noncommunicable diseases. Susceptible ages are children under five and adults between 50 and 75 years. Country level data are presented.; Nearly a quarter of global disease burden could be prevented by reducing environmental risks. This analysis confirms that eliminating hazards and reducing environmental risks will greatly benefit our health, will contribute to attaining the recently agreed Sustainable Development Goals and will systematically require intersectoral collaboration to be successful

Assessing the impact of drinking water and sanitation on diarrhoeal disease in low- and middle-income settings: Systematic review and meta-regression

Objective: To assess the impact of inadequate water and sanitation on diarrhoeal disease in low- and middle-income settings. Methods: The search strategy used Cochrane Library, MEDLINE & PubMed, Global Health, Embase and BIOSIS supplemented by screening of reference lists from previously published systematic reviews, to identify studies reporting on interventions examining the effect of drinking water and sanitation improvements in low- and middle-income settings published between 1970 and May 2013. Studies including randomised controlled trials, quasi-randomised trials with control group, observational studies using matching techniques and observational studies with a control group where the intervention was well defined were eligible. Risk of bias was assessed using a modified Ottawa-Newcastle scale. Study results were combined using meta-analysis and meta-regression to derive overall and intervention-specific risk estimates. Results: Of 6819 records identified for drinking water, 61 studies met the inclusion criteria, and of 12 515 records identified for sanitation, 11 studies were included. Overall, improvements in drinking water and sanitation were associated with decreased risks of diarrhoea. Specific improvements, such as the use of water filters, provision of high-quality piped water and sewer connections, were associated with greater reductions in diarrhoea compared with other interventions. Conclusions: The results show that inadequate water and sanitation are associated with considerable risks of diarrhoeal disease and that there are notable differences in illness reduction according to the type of improved water and sanitation implemented

Interpreting the Global Enteric Multicenter Study (GEMS) Findings on Sanitation, Hygiene, and Diarrhea

Sanitation and hygiene are global concerns, as reflected in international development and human rights policy . The Sustainable Development Goals (SDGs) include target 6.2: to “achieve access to adequate and equitable sanitation and hygiene for all and end open defecation”. Globally, about 2.5 billion people do not use improved sanitation, of whom 1 billion defecate in the open. Fecal contamination of the environment and poor handwashing are responsible for an estimated 577,000 deaths annually. This is likely an underestimation: there is emerging evidence that poor sanitation and hygiene contribute to undernutrition and could be responsible for approximately half of all child stunting. Much of the health impact of inadequate sanitation and hygiene is attributed to diarrheal disease and its secondary effects. However, diarrhea is difficult to measure, and sanitation and hygiene are difficult to link to health outcomes

Impact of drinking water, sanitation and handwashing with soap on childhood diarrhoeal disease: updated meta‐analysis and meta‐regression

Objectives: Safe drinking water, sanitation and hygiene are protective against diarrhoeal disease; a leading cause of child mortality. The main objective was an updated assessment of the impact of unsafe water, sanitation and hygiene (WaSH) on childhood diarrhoeal disease.  Methods: We undertook a systematic review of articles published between 1970 and February 2016. Study results were combined and analysed using meta‐analysis and meta‐regression.  Results: A total of 135 studies met the inclusion criteria. Several water, sanitation and hygiene interventions were associated with lower risk of diarrhoeal morbidity. Point‐of‐use filter interventions with safe storage reduced diarrhoea risk by 61% (RR = 0.39; 95% CI: 0.32, 0.48); piped water to premises of higher quality and continuous availability by 75% and 36% (RR = 0.25 (0.09, 0.67) and 0.64 (0.42, 0.98)), respectively compared to a baseline of unimproved drinking water; sanitation interventions by 25% (RR = 0.75 (0.63, 0.88)) with evidence for greater reductions when high sanitation coverage is reached; and interventions promoting handwashing with soap by 30% (RR = 0.70 (0.64, 0.77)) vs. no intervention. Results of the analysis of sanitation and hygiene interventions are sensitive to certain differences in study methods and conditions. Correcting for non‐blinding would reduce the associations with diarrhoea to some extent.  Conclusions: Although evidence is limited, results suggest that household connections of water supply and higher levels of community coverage for sanitation appear particularly impactful which is in line with targets of the Sustainable Development Goals

Internet-based, culturally sensitive, problem-solving therapy for turkish migrants with depression: Randomized controlled trial

Background: Turkish migrants living in the Netherlands have a high prevalence of depressive disorders, but experience considerable obstacles to accessing professional help. Providing easily accessible Internet treatments may help to overcome these barriers. Objective: The aim of this study was to evaluate the effectiveness of a culturally sensitive, guided, self-help, problem-solving intervention through the Internet for reducing depressive symptoms in Turkish migrants. Methods: A two-armed randomized controlled trial was conducted. The primary outcome measure was the severity of depressive symptoms; secondary outcome measures were somatic symptoms, anxiety, quality of life, and satisfaction with the treatment. Participants were assessed online at baseline, posttest (6 weeks after baseline), and 4 months after baseline. Posttest results were analyzed on the intention-to-treat sample. Missing values were estimated by means of multiple imputation. Differences in clinical outcome between groups were analyzed with a t test. Cohen's d was used to determine the between-groups effect size at posttreatment and follow-up. Results: Turkish adults (N=96) with depressive symptoms were randomized to the experimental group (n=49) or to a waitlist control group (n=47). High attrition rates were found among the 96 participants of which 42% (40/96) did not complete the posttest (6 weeks) and 62% (59/96) participants did not complete the follow-up assessment at 4 months. No significant difference between the experimental group and the control group was found for depression at posttest. Recovery occurred significantly more often in the experimental group (33%, 16/49) than in the control group (9%, 4/47) at posttest (P=.02). Because of the high attrition rate, a completers-only analysis was conducted at follow-up. The experimental group showed significant improvement in depression compared to the control group both at posttest (P=.01) and follow-up (P=.01). Conclusions: The results of this study did not show a significant effect on the reduction of depressive symptoms. However, the effect size at posttest was high, which might be an indicator of the possible effectiveness of the intervention when assessed in a larger sample and robust trial. Future research should replicate our study with adequately powered samples. © Burçin Ünlü Ince, Pim Cuijpers, Edith van 't Hof, Wouter van Ballegooijen, Helen Christensen, Heleen Riper

Do regional brain volumes and major depressive disorder share genetic architecture?:A study of Generation Scotland (<i>n</i>=19,762), UK Biobank (<i>n</i>=24,048) and the English Longitudinal Study of Ageing (<i>n</i>=5,766)

Major depressive disorder (MDD) is a heritable and highly debilitating condition. It is commonly associated with subcortical volumetric abnormalities, the most replicated of these being reduced hippocampal volume. Using the most recent published data from Enhancing Neuroimaging Genetics through Meta-analysis (ENIGMA) consortium's genome-wide association study of regional brain volume, we sought to test whether there is shared genetic architecture between seven subcortical brain volumes and intracranial volume (ICV) and MDD. We explored this using linkage disequilibrium score regression, polygenic risk scoring (PRS) techniques, Mendelian randomisation (MR) analysis and BUHMBOX. Utilising summary statistics from ENIGMA and Psychiatric Genomics Consortium, we demonstrated that hippocampal volume was positively genetically correlated with MDD (rG=0.46, P=0.02), although this did not survive multiple comparison testing. None of the other six brain regions studied were genetically correlated and amygdala volume heritability was too low for analysis. Using PRS analysis, no regional volumetric PRS demonstrated a significant association with MDD or recurrent MDD. MR analysis in hippocampal volume and MDD identified no causal association, however, BUHMBOX analysis identified genetic subgrouping in GS:SFHS MDD cases only (P=0.00281). In this study, we provide some evidence that hippocampal volume and MDD may share genetic architecture in a subgroup of individuals, albeit the genetic correlation did not survive multiple testing correction and genetic subgroup heterogeneity was not replicated. In contrast, we found no evidence to support a shared genetic architecture between MDD and other regional subcortical volumes or ICV

Kinome-wide interaction modelling using alignment-based and alignment-independent approaches for kinase description and linear and non-linear data analysis techniques

<p>Abstract</p> <p>Background</p> <p>Protein kinases play crucial roles in cell growth, differentiation, and apoptosis. Abnormal function of protein kinases can lead to many serious diseases, such as cancer. Kinase inhibitors have potential for treatment of these diseases. However, current inhibitors interact with a broad variety of kinases and interfere with multiple vital cellular processes, which causes toxic effects. Bioinformatics approaches that can predict inhibitor-kinase interactions from the chemical properties of the inhibitors and the kinase macromolecules might aid in design of more selective therapeutic agents, that show better efficacy and lower toxicity.</p> <p>Results</p> <p>We applied proteochemometric modelling to correlate the properties of 317 wild-type and mutated kinases and 38 inhibitors (12,046 inhibitor-kinase combinations) to the respective combination's interaction dissociation constant (K_d). We compared six approaches for description of protein kinases and several linear and non-linear correlation methods. The best performing models encoded kinase sequences with amino acid physico-chemical z-scale descriptors and used support vector machines or partial least- squares projections to latent structures for the correlations. Modelling performance was estimated by double cross-validation. The best models showed high predictive ability; the squared correlation coefficient for new kinase-inhibitor pairs ranging P²= 0.67-0.73; for new kinases it ranged P²_kin= 0.65-0.70. Models could also separate interacting from non-interacting inhibitor-kinase pairs with high sensitivity and specificity; the areas under the ROC curves ranging AUC = 0.92-0.93. We also investigated the relationship between the number of protein kinases in the dataset and the modelling results. Using only 10% of all data still a valid model was obtained with P²= 0.47, P²_kin= 0.42 and AUC = 0.83.</p> <p>Conclusions</p> <p>Our results strongly support the applicability of proteochemometrics for kinome-wide interaction modelling. Proteochemometrics might be used to speed-up identification and optimization of protein kinase targeted and multi-targeted inhibitors.</p