239 research outputs found
Party identification and party closeness in comparative perspective
The present analysis uses data from 1974 and 1981 U. S. cross sections, which incorporate a panel, to compare the standard NES measure of party identification (ID) with a measure of partisanship derived from a party closeness question widely employed in cross-national research. Important features of the two scales are examined by transforming the closeness measure into a scale of very close, fairly close, not very close, and no preference corresponding to the seven-point ID scale. The scales are highly correlated and are similar in their reliability. More than 75% of the “independents” in the ID scale choose a party in the closeness version, and over half of these select the “fairly close” category. Respondents do not volunteer that they are independents when that alternative is not stated in the question.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45482/1/11109_2004_Article_BF00990552.pd
The origins of redistributive policy preferences: political socialisation with and without a welfare state
Research on the impact of the macroeconomy on individual-level preferences for redistribution has produced varying results. This paper presents a new theory on the presence of an expansive welfare state during one’s formative years as a source of heterogeneity in the effect that macroeconomic conditions have on individuals’ preferences for redistributive policy. This theory is tested using cohort analysis via the British Social Attitudes surveys (1983–2010), with generations coming of age between the end of World War I and today. Findings confirm that cohorts that were socialised before and after the introduction of the welfare state react differently to economic crises: the former become less supportive of redistribution, while the latter become more supportive. The research sheds light on the long-term shifts of support for the welfare state due to generational replacement
American political affiliation, 2003–43: a cohort component projection
The recent rise and stability in American party identification has focused interest on the long-term dynamics of party bases. Liberal commentators cite immigration and youth as forces which will produce a natural Democratic advantage in the future while conservative writers highlight the importance of high Republican fertility in securing Republican growth. These concerns foreground the neglect of demography within political science. This paper addresses this omission by conducting the first ever cohort component projection of American partisan populations to 2043 based on survey and census data. A number of scenarios are modeled, but, on current trends, we predict that American partisanship will shift much less than the nation’s ethnic composition because the parties’ age structures are similar. Still, our projections find that the Democrats gain two to three percentage points from the Republicans by 2043, mainly through immigration, though Republican fertility may redress the balance in the very long term
Exploring Late Bronze Age systems of bronzework production in Switzerland through Network Science
YesMany hundreds of Bronze Age bronze artefacts are known from excavations in Switzerland, yet the interpretation of production networks from the object find locations remain problematic. It is proposed that the decorative elements used on items, such as ring-jewellery, can be used as elements to assist in the identification of artisanal traditions and ‘schools’, and also regional or community preference and selection of specific designs. Combining the analysis of over 1700 items of ring-jewellery from Switzerland with approaches from network science has facilitated the identification of regional clustering of design elements, comparable with cultural typologies in the area. It is also possible to identify potential instances of cultural differentiation through decoration within the broader regional cultural traditions. The study highlights important facets of bronzework production in the region of Switzerland, while also demonstrating future potential directions which could build upon the European wide dataset of prehistoric bronzework.Primary research conducted under previous funding at University of Basel, Switzerland – SNF gran
Effects of Short-Term Continuous Montmorency Tart Cherry Juice Supplementation in Participants with Metabolic Syndrome
© 2020 Springer-Verlag. The final publication is available at Springer via https://doi.org/10.1007/s00394-020-02355-5Purpose: Metabolic Syndrome (MetS) augments the incidence of cardiovascular disease by two-fold and type II diabetes mellitus by five-fold. Montmorency tart cherries are rich in phytochemicals shown to improve biomarkers related to cardio-metabolic health in humans. This study aimed to examine cardio-metabolic responses after 7-days Montmorency tart cherry juice (MTCJ) supplementation and also acute on short-term supplementation responses to a single bolus, in humans with MetS. Methods: In a randomised, single-blind, placebo-controlled, crossover trial, 12 participants with MetS (50 ± 10 years; 6M/6F), consumed MTCJ or placebo (PLA) for 7 days. Blood-based and functional cardio-metabolic biomarkers were measured pre- and post-supplementation, and acute responses measured pre-bolus and up to 5 h post-bolus on the 7th day. Results: 24-h ambulatory systolic (P = 0.016), diastolic (P = 0.009) blood pressure and mean arterial pressure (P = 0.041) were significantly lower after 7-days MTCJ supplementation compared to PLA. Glucose (P = 0.038), total cholesterol (P = 0.036), LDL (P = 0.023) concentrations, total cholesterol:HDL ratio (P = 0.004) and respiratory exchange ratio values (P = 0.009) were significantly lower after 6-days MTCJ consumption compared to PLA. Conclusions: This study revealed for the first time in humans that MTCJ significantly improved 24-h BP, fasting glucose, total cholesterol and total cholesterol:HDL ratio, and also lowered resting respiratory exchange ratio compared to a control group. Responses demonstrated clinically relevant improvements on aspects of cardio-metabolic function, emphasising the potential efficacy of MTCJ in preventing further cardio-metabolic dysregulation in participants with MetS. Registered at clinicaltrials.gov (NCT03619941).Peer reviewedFinal Accepted Versio
Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis
BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London
Integrating data types to estimate spatial patterns of avian migration across the Western Hemisphere
For many avian species, spatial migration patterns remain largely undescribed, especially across hemispheric extents. Recent advancements in tracking technologies and high-resolution species distribution models (i.e., eBird Status and Trends products) provide new insights into migratory bird movements and offer a promising opportunity for integrating independent data sources to describe avian migration. Here, we present a three-stage modeling framework for estimating spatial patterns of avian migration. First, we integrate tracking and band re-encounter data to quantify migratory connectivity, defined as the relative proportions of individuals migrating between breeding and nonbreeding regions. Next, we use estimated connectivity proportions along with eBird occurrence probabilities to produce probabilistic least-cost path (LCP) indices. In a final step, we use generalized additive mixed models (GAMMs) both to evaluate the ability of LCP indices to accurately predict (i.e., as a covariate) observed locations derived from tracking and band re-encounter data sets versus pseudo-absence locations during migratory periods and to create a fully integrated (i.e., eBird occurrence, LCP, and tracking/band re-encounter data) spatial prediction index for mapping species-specific seasonal migrations. To illustrate this approach, we apply this framework to describe seasonal migrations of 12 bird species across the Western Hemisphere during pre- and postbreeding migratory periods (i.e., spring and fall, respectively). We found that including LCP indices with eBird occurrence in GAMMs generally improved the ability to accurately predict observed migratory locations compared to models with eBird occurrence alone. Using three performance metrics, the eBird + LCP model demonstrated equivalent or superior fit relative to the eBird-only model for 22 of 24 species–season GAMMs. In particular, the integrated index filled in spatial gaps for species with over-water movements and those that migrated over land where there were few eBird sightings and, thus, low predictive ability of eBird occurrence probabilities (e.g., Amazonian rainforest in South America). This methodology of combining individual-based seasonal movement data with temporally dynamic species distribution models provides a comprehensive approach to integrating multiple data types to describe broad-scale spatial patterns of animal movement. Further development and customization of this approach will continue to advance knowledge about the full annual cycle and conservation of migratory birds
Unequal at the starting line: Creating participatory inequalities across generations and among groups
Whole-genome sequencing reveals host factors underlying critical COVID-19
Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease
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