Alpha-Linolenic Acid: Is It Essential to Cardiovascular Health?

There is a large body of scientific evidence that has been confirmed in randomized controlled trials indicating a cardioprotective effect for omega-3 fatty acids from fish. For alpha-linolenic acid (ALA), which is the omega-3 fatty acid from plants, the relation to cardiovascular health is less clear. We reviewed the recent literature on dietary ALA intake, ALA tissue concentrations, and cardiovascular health in humans. Short-term trials (6–12 weeks) in generally healthy participants mostly showed no or inconsistent effects of ALA intake (1.2–3.6 g/d) on blood lipids, low-density lipoprotein oxidation, lipoprotein(a), and apolipoproteins A-I and B. Studies of ALA in relation to inflammatory markers and glucose metabolism yielded conflicting results. With regard to clinical cardiovascular outcomes, there is observational evidence for a protective effect against nonfatal myocardial infarction. However, no protective associations were observed between ALA status and risk of heart failure, atrial fibrillation, and sudden death. Findings from long-term trials of ALA supplementation are awaited to answer the question whether food-based or higher doses of ALA could be important for cardiovascular health in cardiac patients and the general population

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation

Clinical Phenotypes and Comorbidity in European Sleep Apnoea Patients

Background Clinical presentation phenotypes of obstructive sleep apnoea (OSA) and their association with comorbidity as well as impact on adherence to continuous positive airway pressure (CPAP) treatment have not been established. Methods A prospective follow-up cohort of adult patients with OSA (apnoea-hypopnoea index (AHI) of 655/h) from 17 European countries and Israel (n = 6,555) was divided into four clinical presentation phenotypes based on daytime symptoms labelled as excessive daytime sleepiness ("EDS") and nocturnal sleep problems other than OSA (labelled as "insomnia"): 1) EDS (daytime+/nighttime-), 2) EDS/insomnia (daytime+/nighttime+), 3) non-EDS/noninsomnia (daytime-/nighttime-), 4) and insomnia (daytime-/nighttime+) phenotype. Results The EDS phenotype comprised 20.7%, the non-EDS/non-insomnia type 25.8%, the EDS/ insomnia type 23.7%, and the insomnia phenotype 29.8% of the entire cohort. Thus, clinical presentation phenotypes with insomnia symptoms were dominant with 53.5%, but only 5.6% had physician diagnosed insomnia. Cardiovascular comorbidity was less prevalent in the EDS and most common in the insomnia phenotype (48.9% vs. 56.8%, p<0.001) despite more severe OSA in the EDS group (AHI 35.0\ub125.5/h vs. 27.9\ub122.5/h, p<0.001, respectively). Psychiatric comorbidity was associated with insomnia like OSA phenotypes independent of age, gender and body mass index (HR 1.5 (1.188-1.905), p<0.001). The EDS phenotype tended to associate with higher CPAP usage (22.7 min/d, p = 0.069) when controlled for age, gender, BMI and sleep apnoea severity. Conclusions Phenotypes with insomnia symptoms comprised more than half of OSA patients and were more frequently linked with comorbidity than those with EDS, despite less severe OSA. CPAP usage was slightly higher in phenotypes with EDS

The Hunt for New Physics at the Large Hadron Collider

The Large Hadron Collider presents an unprecedented opportunity to probe the realm of new physics in the TeV region and shed light on some of the core unresolved issues of particle physics. These include the nature of electroweak symmetry breaking, the origin of mass, the possible constituent of cold dark matter, new sources of CP violation needed to explain the baryon excess in the universe, the possible existence of extra gauge groups and extra matter, and importantly the path Nature chooses to resolve the hierarchy problem - is it supersymmetry or extra dimensions. Many models of new physics beyond the standard model contain a hidden sector which can be probed at the LHC. Additionally, the LHC will be a top factory and accurate measurements of the properties of the top and its rare decays will provide a window to new physics. Further, the LHC could shed light on the origin of neutralino masses if the new physics associated with their generation lies in the TeV region. Finally, the LHC is also a laboratory to test the hypothesis of TeV scale strings and D-brane models. An overview of these possibilities is presented in the spirit that it will serve as a companion to the Technical Design Reports (TDRs) by the particle detector groups ATLAS and CMS to facilitate the test of the new theoretical ideas at the LHC. Which of these ideas stands the test of the LHC data will govern the course of particle physics in the subsequent decades

Using Verbal Autopsy to Measure Causes of Death: the Comparative Performance of Existing Methods.

Monitoring progress with disease and injury reduction in many populations will require widespread use of verbal autopsy (VA). Multiple methods have been developed for assigning cause of death from a VA but their application is restricted by uncertainty about their reliability. We investigated the validity of five automated VA methods for assigning cause of death: InterVA-4, Random Forest (RF), Simplified Symptom Pattern (SSP), Tariff method (Tariff), and King-Lu (KL), in addition to physician review of VA forms (PCVA), based on 12,535 cases from diverse populations for which the true cause of death had been reliably established. For adults, children, neonates and stillbirths, performance was assessed separately for individuals using sensitivity, specificity, Kappa, and chance-corrected concordance (CCC) and for populations using cause specific mortality fraction (CSMF) accuracy, with and without additional diagnostic information from prior contact with health services. A total of 500 train-test splits were used to ensure that results are robust to variation in the underlying cause of death distribution. Three automated diagnostic methods, Tariff, SSP, and RF, but not InterVA-4, performed better than physician review in all age groups, study sites, and for the majority of causes of death studied. For adults, CSMF accuracy ranged from 0.764 to 0.770, compared with 0.680 for PCVA and 0.625 for InterVA; CCC varied from 49.2% to 54.1%, compared with 42.2% for PCVA, and 23.8% for InterVA. For children, CSMF accuracy was 0.783 for Tariff, 0.678 for PCVA, and 0.520 for InterVA; CCC was 52.5% for Tariff, 44.5% for PCVA, and 30.3% for InterVA. For neonates, CSMF accuracy was 0.817 for Tariff, 0.719 for PCVA, and 0.629 for InterVA; CCC varied from 47.3% to 50.3% for the three automated methods, 29.3% for PCVA, and 19.4% for InterVA. The method with the highest sensitivity for a specific cause varied by cause. Physician review of verbal autopsy questionnaires is less accurate than automated methods in determining both individual and population causes of death. Overall, Tariff performs as well or better than other methods and should be widely applied in routine mortality surveillance systems with poor cause of death certification practices