Suchergebnisse

Funding Funding for this work was received from Public Health Wales NHS Trust as part of a report on migration and health. Support for the report was also received from the National Centre for Population Health and Wellbeing Research (NCPHWR). The eCATALYsT multiagency dataset and the baseline survey was supported by the Wales Office of Research and Development (SCC99/1/105 and R00/1/017). The follow-up survey was supported by a Welsh Assembly Government/Medical Research Council Health Research Partnership Award (H07-3-030), and the electronic cohort is supported by a National Institute for Social Care and Health Research Welsh Assembly Government Translational Health Research Platform Award (TPR08-020). Data availability statement Data may be obtained from a third party and are not publicly available. The electronic cohort is securely stored and maintained on the Secure Anonymised Information Linkage (SAIL) databank at Swansea University Medical School. The authors welcome general enquiries and ideas for new collaborations. Readers with an interest in further details should contact Professor Shantini Paranjothy, Principal Investigator. ; Peer reviewed ; Publisher PDF

The authors would like to thank the clinical teams of the Royal Aberdeen Infirmary for their support, in particular Dr German Guzman-Guttierez, Mr Paddy Ashcroft, Dr Tanja Gagliardi, Prof Steven Heys, Prof Alison Murray and Prof Graeme Murray. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 668119 (project "IDentIFY"). ; Peer reviewed ; Publisher PDF

Maternal and child mortality rates are still unacceptably high in South Africa. The health status of women in peri-urban areas has been influenced by political and socio-economic factors. Examining socio-economic variables (SEV) in a population aids in the explanation of the impact of social structures on an individual. Risk factors can then be established and pregnant women in these higher risk groups can be identified and given additional support during pregnancy. The aim of this study was to investigate the association between SEV and gestational Body Mass Index (GBMI) in a peri-urban settlement, South Africa. This was a sub-study of the Philani Mentor Mothers' Study (2009–2010). Maternal anthropometry and SEV were obtained from 1,145 participants. Multinomial regression was used to analyse the data. Household income was the only SEV that was significantly associated with GBMI. The odds of being underweight rather than normal weight during pregnancy increase by a factor of 2.145 (P < 0.05) for those who had a household income lower than R2000 per month. All other SEV were not significant. Logistic regression was therefore not carried out. Women who had a lower income were at risk of having a lower GBMI during pregnancy. This can lead to adverse birth outcomes such as premature birth, low birth weight, height and head circumference. Public health policy needs to be developed to include optimal nutrition health promotion strategies targeting women with a low income ante and post-natally. Once implemented, they need to be evaluated to assess the impact on maternal and child mortality.

In this article, we draw from our experiences as UK and US-based 'dialogue event' practitioners and researchers/ evaluators to suggest that these existing evaluative criteria are insufficient to explore the role and value of ISI-based 'dialogue events'. Instead, we suggest that it may be productive to research and evaluate these ISI-based 'dialogue events' as sites of learning. Secondly, however, we show through a discussion of our own research frameworks that understanding these 'dialogue events' as sites of learning does not intuitively provide a framework for understanding what counts as success for these efforts. Instead, research on the role of 'dialogue' within the educational literature – and the connections between 'dialogue' and competing understandings of the nature of science and society – offers a multiplicity of approaches to defining the terms and goals of these events. Finally, we identify two broader implications of researching and evaluating these 'dialogue events' as sites of learning for ISIs and all efforts to increase public engagement with science and technology.

Background: Hospitalisation during the last weeks of life when there is no medical need or desire to be there is distressing and expensive. This study sought palliative care initiatives which may avoid or shorten hospital stay at the end of life and analysed their success in terms reducing bed days. Methods: Part 1 included a search of literature in PubMed and Google Scholar between 2013 and 2018, an examination of governmental and organisational publications plus discussions with external and co-author experts regarding other sources. This initial sweep sought to identify and categorise relevant palliative care initiatives. In Part 2, we looked for publications providing data on hospital admissions and bed days for each category. Results: A total of 1252 abstracts were reviewed, resulting in ten broad classes being identified. Further screening revealed 50 relevant publications describing a range of multi-component initiatives. Studies were generally small and retrospective. Most researchers claim their service delivered benefits. In descending frequency, benefits identified were support in the community, integrated care, out-of-hours telephone advice, care home education and telemedicine. Nurses and hospices were central to many initiatives. Barriers and factors underpinning success were rarely addressed. Conclusions: A wide range of initiatives have been introduced to improve end-of-life experiences. Formal evidence supporting their effectiveness in reducing inappropriate/non-beneficial hospital bed days was generally limited or absent.

This study presents a first attempt to assess the mechanisms and potential controls behind past residential mobility through the integration of isotopic data from human inhumations and spatial infrastructural information pertaining to the settlement containing these inhumations. Strontium ( 87 Sr/ 86 Sr) and oxygen (δ 18 O PDB ) isotope data are derived from 200 (post)medieval individuals from the town of Oldenzaal in the present-day Netherlands. Reconstructions of historical route networks show that Oldenzaal was well-connected interregionally throughout the Middle Ages and early-modern times (ca. AD 800–1600). Although the working hypothesis was that in the past a high degree of spatial connectivity of settlements must have been positively related to a highly variable geographical origin of its inhabitants, the isotopic data from Oldenzaal indicate a population characterized by a low variability in terms of their origin. This unexpected result may be caused by (a combination of) various factors, related to (1) biases in the isotopic dataset, (2) interpretative limitations regarding the results of isotopic analyses and (3) the impact of broader socio-cultural factors that cannot be traced through isotopic analyses, such as infrastructural connectivity, socio-economics and political factors. The human oxygen isotope dataset presented here provides a first step towards a δ 18 O PDB reference dataset, against which future samples can be compared without the need to convert the data. This paper establishes that although in archaeology a biomolecular approach potentially provides a detailed reconstruction of the development of past populations in terms of palaeodemography and geographical/cultural origin, such studies should be performed in a transdisciplinary context in order to increase the understanding of the wider controlling factors of past population change.

This article is based upon work from COST Action CA15209, supported by COST (European Cooperation in Science and Technology). M. Bödenler, C. Gösweiner and H. Scharfetter acknowledge the financial support by the European Commission in the frame of the H2020 Future and Emerging Technologies (FET-open) under grant agreement 665172, project 'CONQUER'. L. de Rochefort acknowledges the France Life Imaging network (Grant ANR-11-INBS-0006) that partially funded the small animal FFC-MRI system. D.J. Lurie, L.M. Broche and P.J. Ross acknowledge funding from the European Union's H2020 research and innovation programme under grant agreement No 668119, project 'IDentIFY'. ; Peer reviewed ; Publisher PDF

Copyright © 2020 The Authors. ; Meiotic reductional division depends on the synaptonemal complex (SC), a supramolecular protein assembly that mediates homologous chromosomes synapsis and promotes crossover formation. The mammalian SC has eight structural components, including SYCE1, the only central element protein with known causative mutations in human infertility. We combine mouse genetics, cellular, and biochemical studies to reveal that SYCE1 undergoes multivalent interactions with SC component SIX6OS1. The N terminus of SIX6OS1 binds and disrupts SYCE1's core dimeric structure to form a 1:1 complex, while their downstream sequences provide a distinct second interface. These interfaces are separately disrupted by SYCE1 mutations associated with nonobstructive azoospermia and premature ovarian failure (POF), respectively. Mice harboring SYCE1's POF mutation and a targeted deletion within SIX6OS1's N terminus are infertile with failure of chromosome synapsis. We conclude that both SYCE1-SIX6OS1 binding interfaces are essential for SC assembly, thus explaining how SYCE1's reported clinical mutations give rise to human infertility. ; O.R.D. is a Sir Henry Dale Fellow jointly funded by the Wellcome Trust and Royal Society (grant number 104158/Z/14/Z). This work was supported by MINECO (BFU2017-89408-R) and by Junta de Castilla y Leon (CSI239P18). F.S.-S., L.G.-H., and N.F.-M. are supported by European Social Fund/JCyLe grants (EDU/556/2019, EDU/1083/2013, and EDU/310/2015). CIC-IBMCC is supported by the Programa de Apoyo a Planes Estratégicos de Investigación de Estructuras de Investigación de Excelencia cofunded by the Castilla–León autonomous government and the European Regional Development Fund (CLC–2017–01).

Background: We aimed to estimate the causal effect of health conditions and risk factors on social and socioeconomic outcomes in UK Biobank. Evidence on socioeconomic impacts is important to understand because it can help governments, policy makers and decision makers allocate resources efficiently and effectively. Methods: We used Mendelian randomization to estimate the causal effects of eight health conditions (asthma, breast cancer, coronary heart disease, depression, eczema, migraine, osteoarthritis, type 2 diabetes) and five health risk factors [alcohol intake, body mass index (BMI), cholesterol, systolic blood pressure, smoking] on 19 social and socioeconomic outcomes in 336 997 men and women of White British ancestry in UK Biobank, aged between 39 and 72 years. Outcomes included annual household income, employment, deprivation [measured by the Townsend deprivation index (TDI)], degree-level education, happiness, loneliness and 13 other social and socioeconomic outcomes. Results: Results suggested that BMI, smoking and alcohol intake affect many socioeconomic outcomes. For example, smoking was estimated to reduce household income [mean difference = -£22 838, 95% confidence interval (CI): -£31 354 to -£14 321] and the chance of owning accommodation [absolute percentage change (APC) = -20.8%, 95% CI: -28.2% to -13.4%], of being satisfied with health (APC = -35.4%, 95% CI: -51.2% to -19.5%) and of obtaining a university degree (APC = -65.9%, 95% CI: -81.4% to -50.4%), while also increasing deprivation (mean difference in TDI = 1.73, 95% CI: 1.02 to 2.44, approximately 216% of a decile of TDI). There was evidence that asthma decreased household income, the chance of obtaining a university degree and the chance of cohabiting, and migraine reduced the chance of having a weekly leisure or social activity, especially in men. For other associations, estimates were null. Conclusions: Higher BMI, alcohol intake and smoking were all estimated to adversely affect multiple social and socioeconomic outcomes. Effects were not detected between health conditions and socioeconomic outcomes using Mendelian randomization, with the exceptions of depression, asthma and migraines. This may reflect true null associations, selection bias given the relative health and age of participants in UK Biobank, and/or lack of power to detect effects.

Background To estimate the causal effect of health conditions and risk factors on social and socioeconomic outcomes in UK Biobank. Evidence on socioeconomic impacts is important to understand because it can help governments, policy-makers and decision-makers allocate resources efficiently and effectively. Methods We used Mendelian randomization to estimate the causal effects of eight health conditions (asthma, breast cancer, coronary heart disease, depression, eczema, migraine, osteoarthritis, type 2 diabetes) and five health risk factors (alcohol intake, body mass index [BMI], cholesterol, systolic blood pressure, smoking) on 19 social and socioeconomic outcomes in 336,997 men and women of white British ancestry in UK Biobank, aged between 39 and 72 years. Outcomes included annual household income, employment, deprivation (measured by the Townsend deprivation index [TDI]), degree level education, happiness, loneliness, and 13 other social and socioeconomic outcomes. Results Results suggested that BMI, smoking and alcohol intake affect many socioeconomic outcomes. For example, smoking was estimated to reduce household income (mean difference = -£22,838, 95% confidence interval (CI): -£31,354 to -£14,321), the chance of owning accommodation (absolute percentage change [APC] = -20.8%, 95% CI: -28.2% to -13.4%), being satisfied with health (APC = -35.4%, 95% CI: -51.2% to -19.5%), and of obtaining a university degree (APC = -65.9%, 95% CI: -81.4% to -50.4%), while also increasing deprivation (mean difference in TDI = 1.73, 95% CI: 1.02 to 2.44, approximately 216% of a decile of TDI). There was evidence that asthma decreased household income, the chance of obtaining a university degree and the chance of cohabiting, and migraine reduced the chance of having a weekly leisure or social activity, especially in men. For other associations, estimates were null. Conclusions Higher BMI, alcohol intake and smoking were all estimated to adversely affect multiple social and socioeconomic outcomes. Effects were not detected between health conditions and socioeconomic outcomes using Mendelian randomization, with the exceptions of depression, asthma and migraines. This may reflect true null associations, selection bias given the relative health and age of participants in UK Biobank, and/or lack of power to detect effects.

Objectives: To estimate the causal effect of health conditions and risk factors on social and socioeconomic outcomes in UK Biobank. Evidence on socioeconomic impacts is important to understand because it can help governments, policy-makers and decision-makers allocate resources efficiently and effectively. Design: We used Mendelian randomization to estimate the causal effects of eight health conditions (asthma, breast cancer, coronary heart disease, depression, eczema, migraine, osteoarthritis, type 2 diabetes) and five health risk factors (alcohol intake, body mass index [BMI], cholesterol, systolic blood pressure, smoking) on 19 social and socioeconomic outcomes. Setting: UK Biobank. Participants: 337,009 men and women of white British ancestry, aged between 39 and 72 years. Main outcome measures: Annual household income, employment, deprivation (measured by the Townsend deprivation index [TDI]), degree level education, happiness, loneliness, and 13 other social and socioeconomic outcomes. Results: Results suggested that BMI, smoking and alcohol intake affect many socioeconomic outcomes. For example, smoking was estimated to reduce household income (mean difference = -24,394, 95% confidence interval (CI): -33,403 to -15,384), the chance of owning accommodation (absolute percentage change [APC] = -21.5%, 95% CI: -29.3% to -13.6%), being satisfied with health (APC = -32.4%, 95% CI: -48.9% to -15.8%), and of obtaining a university degree (APC = -73.8%, 95% CI: -90.7% to -56.9%), while also increasing deprivation (mean difference in TDI = 1.89, 95% CI: 1.13 to 2.64, approximately 236% of a decile of TDI). There was evidence that asthma increased deprivation and decreased both household income and the chance of obtaining a university degree, and migraine reduced the chance of having a weekly leisure or social activity, especially in men. For other associations, estimates were null. Conclusions: Higher BMI, alcohol intake and smoking were all estimated to adversely affect multiple social and socioeconomic outcomes. Effects were not detected between health conditions and socioeconomic outcomes using Mendelian randomization, with the exceptions of depression, asthma and migraines. This may reflect true null associations, selection bias given the relative health and age of participants in UK Biobank, and/or lack of power to detect effects.