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Gender diversity in STEM remains a significant issue, as the field continues to be a male dominated one, despite increased attention on the subject. This article examines the interplay between gender diversity on projects funded by a major UK research council, the Engineering and Physical Sciences Research Council, and the publication activity of a project, as measured by the average journal quality of project publication output, over a 10-year period. The proportion of female representation and leadership on these projects remains very low. For the projects examined as part of this study, over 70% of these projects have no female representation, and less than 15% have a female lead. This study does not find a significant relationship between gender diversity and journal quality output. This study highlights that an important avenue for future work is the development of alternative metrics to assess the performance of research projects in a discipline characterized by very low levels of gender diversity, to fully unpack the impact of project team gender diversity on project output activity. [ABSTRACT FROM AUTHOR]

The UK's Engineering and Physical Sciences Research Council supported a series of meetings in 2021 to develop a roadmap for future research in Quantitative Modelling in Cleaning and Decontamination. Quantitative modelling in this context is the development of numerical and predictive tools, based on scientific principles, which can support design, operation and decision making associated with cleaning and decontamination. The activity involved identifying past and current activities on this topic across a range of different fields, including food and drink, consumer goods, healthcare, pharmaceuticals, nuclear, civil defence and biofilms. Input was received from operators, manufacturing companies, government agencies and researchers. The exercise identified a series of common needs which span sectors, and the challenges which need to be addressed to facilitate transfer of knowledge between sectors and develop the expertise required to tackle new challenges including those posed by sustainability. [ABSTRACT FROM AUTHOR]

Computer programming is a key component of any physical science or engineering degree and is a skill sought by employers. Coding can be very appealing to these students as it is logical and another setting where they can solve problems. However, many students can often be reluctant to engage with the material as it might not interest them or they might not see how it applies to their wider study. Here, I present lessons I have learned and recommendations to increase participation in programming courses for students majoring in the physical sciences or engineering. The discussion and examples are taken from my second-year core undergraduate physics module, Introduction to Programming for Physicists, taught at The University of Manchester, UK. Teaching this course, I have developed successful solutions that can be applied to undergraduate STEM courses. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Dynamic patterning of microparticles with acoustic impulse control" published in Scientific Reports. The correction addresses the omission of the Funding section in the original article. The authors express gratitude to the UK Engineering and Physical Science Research Council and Ultraleap Ltd for their funding support. The correction has been made to the original article. The authors of the article are Luke Cox, Anthony Croxford, and Bruce W. Drinkwater. [Extracted from the article]

Although water quality from freshwater recreational aquatic environments (RAEs) has been long analyzed worldwide, little information is available about their sediments. The aim of this work was to study the physicochemical and bacteriological quality of water and sediment under different seasonal events. For that, Wierna River (WR) and General Belgrano reservoir (GB) were used as freshwater RAEs models. A total of 33 water and 33 sediment samples (15 from WR and 18 from GB from each phase) were collected and analyzed. Physicochemical variables in water (pH, turbidity, dissolved oxygen, temperature, conductivity, alkalinity, hardness) and sediments (organic matter, humidity, ash, and conductivity) were measured. For the bacteriological characterization, total aerobic mesophiles, total and thermotolerant coliforms, E. coli, enteroccocci, Salmonella spp., and Pseudomonas aeruginosa were evaluated using culture-based methods. Universal and human Bacteroides were also quantified by real-time PCR. Univariate (Kruskall-Wallis), bivariate (Spearman correlation), and multivariate (cluster analysis, principal component analysis) statistical techniques were applied for data analysis. All bacterial indicators were almost two-logs higher in sediments than in water, for both RAEs. Also, due to rainfall events and recreational activities, sediments were resuspended in surface water exceeding in most cases the limit values established by international regulation for bacteria. Significant correlation was observed between culturable bacteria and turbidity (p < 0.05) supporting this. We found that while physicochemical variables clustered samples by geographical location in water and sediments, microbiological aggrupation in water was mostly driven by seasonal events. No aggrupation was observed when using microbiological variables in sediments. Thus, geographical location, type of water and sediments, and seasonal events influenced on RAEs quality. Including sediment analysis during RAEs monitoring campaigns is essential as it will allow knowing the real health risk to which bathers are exposed and proposing solutions to mitigate it. [ABSTRACT FROM AUTHOR]

The European Emission Trading System (EU ETS) is commonly regarded as the key pillar of the European climate policy and as the main unifying tool to create a unique carbon price all over Europe. The UK has always played a crucial role in the EU ETS, being one of the most active national registry and a crucial hub for the exchange of allowances in the market. Brexit, therefore, could deeply modify the number and directions of such exchanges as well as the centrality of the other countries in this system. To investigate these issues, the present paper exploits network analysis tools to compare the structure of the EU ETS market in its first two phases with and without the UK, investigating a few different scenarios that might emerge from a possible reallocation of the transactions that have involved UK partners. We find that without the UK the EU ETS network would become in general much more homogeneous, though results may change focusing on the type of accounts involved in the transactions. [ABSTRACT FROM AUTHOR]

Background: Lynch syndrome is a hereditary cancer syndrome caused by constitutional pathogenic variants in the DNA mismatch repair (MMR) system, leading to increased risk of colorectal, endometrial and other cancers. The study aimed to identify the incremental costs and consequences of strategies to identify Lynch syndrome in women with endometrial cancer. Methods: A decision-analytic model was developed to evaluate the relative cost-effectiveness of reflex testing strategies for identifying Lynch syndrome in women with endometrial cancer taking the NHS perspective and a lifetime horizon. Model input parameters were sourced from various published sources. Consequences were measured using quality-adjusted life years (QALYs). A cost-effectiveness threshold of £20 000/QALY was used. Results: Reflex testing for Lynch syndrome using MMR immunohistochemistry and MLH1 methylation testing was cost-effective versus no testing, costing £14 200 per QALY gained. There was uncertainty due to parameter imprecision, with an estimated 42% chance this strategy is not cost-effective compared with no testing. Age had a significant impact on cost-effectiveness, with testing not predicted to be cost-effective in patients aged 65 years and over. Conclusions: Testing for Lynch syndrome in younger women with endometrial cancer using MMR immunohistochemistry and MLH1 methylation testing may be cost-effective. Age cut-offs may be controversial and adversely affect implementation. [ABSTRACT FROM AUTHOR]

Background: Systematic reviews of randomised controlled trials (RCTs) have suggested that maternal vitamin D (25[OH]D) and calcium supplementation increase birth weight. However, limitations of many trials were highlighted in the reviews. Our aim was to combine genetic and RCT data to estimate causal effects of these two maternal traits on offspring birth weight.Methods and Findings: We performed two-sample mendelian randomisation (MR) using genetic instrumental variables associated with 25(OH)D and calcium that had been identified in genome-wide association studies (GWAS; sample 1; N = 122,123 for 25[OH]D and N = 61,275 for calcium). Associations between these maternal genetic variants and offspring birth weight were calculated in the UK Biobank (UKB) (sample 2; N = 190,406). We used data on mother-child pairs from two United Kingdom birth cohorts (combined N = 5,223) in sensitivity analyses to check whether results were influenced by fetal genotype, which is correlated with the maternal genotype (r ≈ 0.5). Further sensitivity analyses to test the reliability of the results included MR-Egger, weighted-median estimator, 'leave-one-out', and multivariable MR analyses. We triangulated MR results with those from RCTs, in which we used randomisation to supplementation with vitamin D (24 RCTs, combined N = 5,276) and calcium (6 RCTs, combined N = 543) as an instrumental variable to determine the effects of 25(OH)D and calcium on birth weight. In the main MR analysis, there was no strong evidence of an effect of maternal 25(OH)D on birth weight (difference in mean birth weight -0.03 g [95% CI -2.48 to 2.42 g, p = 0.981] per 10% higher maternal 25[OH]D). The effect estimate was consistent across our MR sensitivity analyses. Instrumental variable analyses applied to RCTs suggested a weak positive causal effect (5.94 g [95% CI 2.15-9.73, p = 0.002] per 10% higher maternal 25[OH]D), but this result may be exaggerated because of risk of bias in the included RCTs. The main MR analysis for maternal calcium also suggested no strong evidence of an effect on birth weight (-20 g [95% CI -44 to 5 g, p = 0.116] per 1 SD higher maternal calcium level). Some sensitivity analyses suggested that the genetic instrument for calcium was associated with birth weight via exposures that are independent of calcium levels (horizontal pleiotropy). Application of instrumental variable analyses to RCTs suggested that calcium has a substantial effect on birth weight (178 g [95% CI 121-236 g, p = 1.43 × 10-9] per 1 SD higher maternal calcium level) that was not consistent with any of the MR results. However, the RCT instrumental variable estimate may have been exaggerated because of risk of bias in the included RCTs. Other study limitations include the low response rate of UK Biobank, which may bias MR estimates, and the lack of suitable data to test whether the effects of genetic instruments on maternal calcium levels during pregnancy were the same as those outside of pregnancy.Conclusions: Our results suggest that maternal circulating 25(OH)D does not influence birth weight in otherwise healthy newborns. However, the effect of maternal circulating calcium on birth weight is unclear and requires further exploration with more research including RCT and/or MR analyses with more valid instruments. [ABSTRACT FROM AUTHOR]

Freshwater ecosystems rank among the most endangered ecosystems in the world and are under increasing threat from aquatic invasive species (AIS). Understanding the range expansion of AIS is key for mitigating their impacts. Most approaches rely on Species Distribution Models (SDMs) to predict the expansion of AIS, using mainly environmental variables, yet ignore the role of human activities in favouring the introduction and range expansion of AIS. In this study, we use five SDM algorithms (independently and in ensemble) and two accuracy measures (TSS, AUC), combined with a null modelling approach, to assess the predictive performance of the models and to quantify which predictors (environmental and anthropogenic from the native and introduced regions) best explain the distribution of nine freshwater invasive species (including fish, arthropods, molluscs, amphibians and reptiles) in a large island (Great Britain), and which species characteristics affect model performance. Our results show that the distribution of invasive species is difficult to predict by SDMs, even in cases when TSS and AUC model accuracy values are high. Our study strongly advocates the use of null models for testing SDMs performance and the inclusion of information from the native area and a variety of both human-related and environmental predictors for a more accurate modelling of the range expansion of AIS. Otherwise, models that only include climatic variables, or rely only on standard accuracy measures or a single algorithm, might result in mismanagement of AIS. [ABSTRACT FROM AUTHOR]

Introduction: The UK Biobank (UKB) is a resource that includes detailed health-related data on about 500,000 individuals and is available to the research community. However, several obstacles limit immediate analysis of the data: data files vary in format, may be very large, and have numerical codes for column names. Results: ukbtools removes all the upfront data wrangling required to get a single dataset for statistical analysis. All associated data files are merged into a single dataset with descriptive column names. The package also provides tools to assist in quality control by exploring the primary demographics of subsets of participants; query of disease diagnoses for one or more individuals, and estimating disease frequency relative to a reference variable; and to retrieve genetic metadata. Conclusion: Having a dataset with meaningful variable names, a set of UKB-specific exploratory data analysis tools, disease query functions, and a set of helper functions to explore and write genetic metadata to file, will rapidly enable UKB users to undertake their research. [ABSTRACT FROM AUTHOR]

Background: Identifying people at risk of cardiovascular diseases (CVD) is a cornerstone of preventative cardiology. Risk prediction models currently recommended by clinical guidelines are typically based on a limited number of predictors with sub-optimal performance across all patient groups. Data-driven techniques based on machine learning (ML) might improve the performance of risk predictions by agnostically discovering novel risk predictors and learning the complex interactions between them. We tested (1) whether ML techniques based on a state-of-the-art automated ML framework (AutoPrognosis) could improve CVD risk prediction compared to traditional approaches, and (2) whether considering non-traditional variables could increase the accuracy of CVD risk predictions. Methods and findings: Using data on 423,604 participants without CVD at baseline in UK Biobank, we developed a ML-based model for predicting CVD risk based on 473 available variables. Our ML-based model was derived using AutoPrognosis, an algorithmic tool that automatically selects and tunes ensembles of ML modeling pipelines (comprising data imputation, feature processing, classification and calibration algorithms). We compared our model with a well-established risk prediction algorithm based on conventional CVD risk factors (Framingham score), a Cox proportional hazards (PH) model based on familiar risk factors (i.e, age, gender, smoking status, systolic blood pressure, history of diabetes, reception of treatments for hypertension and body mass index), and a Cox PH model based on all of the 473 available variables. Predictive performances were assessed using area under the receiver operating characteristic curve (AUC-ROC). Overall, our AutoPrognosis model improved risk prediction (AUC-ROC: 0.774, 95% CI: 0.768-0.780) compared to Framingham score (AUC-ROC: 0.724, 95% CI: 0.720-0.728, p < 0.001), Cox PH model with conventional risk factors (AUC-ROC: 0.734, 95% CI: 0.729-0.739, p < 0.001), and Cox PH model with all UK Biobank variables (AUC-ROC: 0.758, 95% CI: 0.753-0.763, p < 0.001). Out of 4,801 CVD cases recorded within 5 years of baseline, AutoPrognosis was able to correctly predict 368 more cases compared to the Framingham score. Our AutoPrognosis model included predictors that are not usually considered in existing risk prediction models, such as the individuals’ usual walking pace and their self-reported overall health rating. Furthermore, our model improved risk prediction in potentially relevant sub-populations, such as in individuals with history of diabetes. We also highlight the relative benefits accrued from including more information into a predictive model (information gain) as compared to the benefits of using more complex models (modeling gain). Conclusions: Our AutoPrognosis model improves the accuracy of CVD risk prediction in the UK Biobank population. This approach performs well in traditionally poorly served patient subgroups. Additionally, AutoPrognosis uncovered novel predictors for CVD disease that may now be tested in prospective studies. We found that the “information gain” achieved by considering more risk factors in the predictive model was significantly higher than the “modeling gain” achieved by adopting complex predictive models. [ABSTRACT FROM AUTHOR]

Vaginal lubricants are commonly used by couples trying-to-conceive. However, most vaginal lubricants are sperm toxic and therefore should not be used by couples trying-to-conceive. Despite this, lubricant sperm toxicity is insufficiently reported and guidance for healthcare professionals (HCPs) is absent. In this study, lubricant-related practices of fertility-based HCPs in Scotland were sampled via an online survey. Lubricants identified as being utilised in the fertility setting were subsequently incubated with prepared sperm samples to establish effects on sperm motility. HCP recommendations (n = 32) on lubricant use were varied although knowledge related to sperm toxicity was generally poor. HCPs infrequently asked about lubricant use and were unaware of guidance in this area. Aquagel, the only prescribed lubricant identified in this study, reduced sperm progressive motility to 49% of control after 10 minutes, even at concentrations as low as 5%. Vitality testing suggested the deterioration in progressive motility with Aquagel was not as a result of cell death. Conversely, Pré Vaginal Lubricant, a ‘sperm-safe’ lubricant, did not significantly affect any markers of sperm function assessed. Development of clinical guidance in this area is recommended to ensure HCPs deliver informed advice as lubricant use in couples trying-to-conceive may inadvertently contribute to delay in conception. [ABSTRACT FROM AUTHOR]

Background: Seizures are the main cause of maternal death in women with epilepsy, but there are no tools for predicting seizures in pregnancy. We set out to develop and validate a prognostic model, using information collected during the antenatal booking visit, to predict seizure risk at any time in pregnancy and until 6 weeks postpartum in women with epilepsy on antiepileptic drugs.Methods and Findings: We used datasets of a prospective cohort study (EMPiRE) of 527 pregnant women with epilepsy on medication recruited from 50 hospitals in the UK (4 November 2011-17 August 2014). The model development cohort comprised 399 women whose antiepileptic drug doses were adjusted based on clinical features only; the validation cohort comprised 128 women whose drug dose adjustments were informed by serum drug levels. The outcome was epileptic (non-eclamptic) seizure captured using diary records. We fitted the model using LASSO (least absolute shrinkage and selection operator) regression, and reported the performance using C-statistic (scale 0-1, values > 0.5 show discrimination) and calibration slope (scale 0-1, values near 1 show accuracy) with 95% confidence intervals (CIs). We determined the net benefit (a weighted sum of true positive and false positive classifications) of using the model, with various probability thresholds, to aid clinicians in making individualised decisions regarding, for example, referral to tertiary care, frequency and intensity of monitoring, and changes in antiepileptic medication. Seizures occurred in 183 women (46%, 183/399) in the model development cohort and in 57 women (45%, 57/128) in the validation cohort. The model included age at first seizure, baseline seizure classification, history of mental health disorder or learning difficulty, occurrence of tonic-clonic and non-tonic-clonic seizures in the 3 months before pregnancy, previous admission to hospital for seizures during pregnancy, and baseline dose of lamotrigine and levetiracetam. The C-statistic was 0.79 (95% CI 0.75, 0.84). On external validation, the model showed good performance (C-statistic 0.76, 95% CI 0.66, 0.85; calibration slope 0.93, 95% CI 0.44, 1.41) but with imprecise estimates. The EMPiRE model showed the highest net proportional benefit for predicted probability thresholds between 12% and 99%. Limitations of this study include the varied gestational ages of women at recruitment, retrospective patient recall of seizure history, potential variations in seizure classification, the small number of events in the validation cohort, and the clinical utility restricted to decision-making thresholds above 12%. The model findings may not be generalisable to low- and middle-income countries, or when information on all predictors is not available.Conclusions: The EMPiRE model showed good performance in predicting the risk of seizures in pregnant women with epilepsy who are prescribed antiepileptic drugs. Integration of the tool within the antenatal booking visit, deployed as a simple nomogram, can help to optimise care in women with epilepsy. [ABSTRACT FROM AUTHOR]

According to the social heuristics hypothesis, people intuitively cooperate or defect depending on which behavior is beneficial in their interactions. If cooperation is beneficial, people intuitively cooperate, but if defection is beneficial, they intuitively defect. However, deliberation promotes defection. Here, we tested two novel predictions regarding the role of trust in the social heuristics hypothesis. First, whether trust promotes intuitive cooperation. Second, whether preferring to think intuitively or deliberatively moderates the effect of trust on cooperation. In addition, we examined whether deciding intuitively promotes cooperation, compared to deciding deliberatively. To evaluate these predictions, we conducted a lab study in Colombia and an online study in the United Kingdom (N = 1,066; one study was pre-registered). Unexpectedly, higher trust failed to promote intuitive cooperation, though higher trust promoted cooperation. In addition, preferring to think intuitively or deliberatively failed to moderate the effect of trust on cooperation, although preferring to think intuitively increased cooperation. Moreover, deciding intuitively failed to promote cooperation, and equivalence testing confirmed that this null result was explained by the absence of an effect, rather than a lack of statistical power (equivalence bounds: d = -0.26 and 0.26). An intuitive cooperation effect emerged when non-compliant participants were excluded, but this effect could be due to selection biases. Taken together, most results failed to support the social heuristics hypothesis. We conclude by discussing implications, future directions, and limitations. The materials, data, and code are available on the Open Science Framework (). [ABSTRACT FROM AUTHOR]

England’s national Improving Access to Psychological Therapies (IAPT) programme advocates stepped care as its organizational delivery of psychological therapies to common mental health problems. There is limited evidence regarding the efficacy of stepped care as a service delivery model, heterogeneity of definition and differences in model implementation in both research and routine practice, hence outcome comparison in terms of effectiveness of model is difficult. Despite sound evidence of the efficacy of low intensity interventions there appears to be a perpetuation of the notion that severity and complexity should only be treated by a high intensity intervention through the continuation of a stratified care model. Yet no psychotherapy treatment is found to be more superior to another, and not enough is known about what works for whom to aid the matching of treatment decision. In the absence of understanding precise treatment factors optimal for recovery, it may be useful to better understand the impact of a service delivery model, and whether different models achieve different outcomes. This study aims to contribute to the discussion regarding the stepped care definition and delivery, and explores the impact on clinical outcomes where different types of stepped care have been implemented within the same service. An observational cohort study analysed retrospective data (n = 16,723) over a 4 year period, in a single IAPT service, where delivery changed from one type of stepped care model to another. We compared the outcomes of treatment completers with a stratified care model and a progression care model. We also explored the assumption that patients who score severe on psychological measures, and therefore are potentially complex, would achieve better outcomes in a stratified model. Outcomes in each model type were compared, alongside baseline factor variables. A significant association was observed between a recovery outcome and model type, with patients 1.5 times more likely to recover in the progression delivery model. The potential implications are that with a progression stepped care model of service delivery, more patients can be treated with a lower intensity intervention, even with initial severe presentations, ensuring that only those that need high intensity CBT or equivalent are stepped up. This could provide services with an effective clinical model that is efficient and potentially more cost effective. [ABSTRACT FROM AUTHOR]

Recently we have witnessed a number of rapid shifts toward populism in the rhetoric and policies of major political parties, as exemplified in the 2016 Brexit Referendum, 2016 US Election, and 2017 UK General Election. Our perspective here is to focus on understanding the underlying societal processes behind these recent political shifts. We use novel methods to study social dynamics behind the 2016 Presidential election. This is done by using network science methods to identify key groups associated with the US right-wing during the election. We investigate how the groups grew on Twitter, and how their associated accounts changed their following behaviour over time. We find a new external faction of Trump supporters took a strong influence over the traditional Republican Party (GOP) base during the election campaign. The new group dominated the GOP group in terms of new members and endorsement via Twitter follows. Growth of new accounts for the GOP party all but collapsed during the campaign. While the Alt-right group was growing exponentially, it has remained relatively isolated. Counter to the mainstream view, we detected an unexpectedly low number of automated ‘bot’ accounts and accounts associated with foreign intervention in the Trump-supporting group. Our work demonstrates a powerful method for tracking the evolution of societal groups and reveals complex social processes behind political changes. [ABSTRACT FROM AUTHOR]

Introduction: In a society that perpetuates the strive for a perfect appearance, a fit body has become synonymous with success, but simultaneously hard to achieve. This represents a fertile ground for the development of Exercise Addiction (EA) alongside other disorders, such as Body Dysmorphic Disorder (BDD). This study aims to explore the diffusion of EA in fitness settings in the United Kingdom, Italy, Netherlands, Hungary and the previously unexplored association with appearance anxiety, BDD, self-esteem and the use of fitness supplements. Methods: A large cross-sectional sample (N = 1711) was surveyed in fitness settings using the Exercise Addiction Inventory (EAI), Appearance Anxiety Inventory (AAI) and Rosenberg’s Self Esteem Scale (RSE) in addition to questions surrounding the use of fitness supplements. Results: Compulsive exercise, appearance anxiety and low self-esteem were present in this sample according to the psychometric measures used (EAI, AAI, RSE). 11.7% scored over the cut off for EA, with alarming peaks in the Netherlands (20.9%) and the United Kingdom (16.1%). 38.5% were found at risk of BDD, mainly female (47.2%). 39.8% used fitness enhancing supplements without medical consultation (95.5%). This cohort of supplement users scored higher in both EAI and AAI. The logistic regression model revealed a strong association between the consumption of sport products and the level of EA across the sample with an odds ratio (OR) of 3.03. Other co-variable factors among female were appearance anxiety (AAI; OR 1.59) and to a lesser extent self-esteem (RSE) (OR 1.08). Conclusions: This study identified a high risk of EA, appearance anxiety and BDD amongst a cohort of gym users internationally. The previously-unexplored association between these disorders and the unsupervised use of a variety of fitness products, including illicit drugs, highlights the need for informed and integrated responses targeting such vulnerable individuals. [ABSTRACT FROM AUTHOR]

Nutrition apps have great potential to support people to improve their diets, but few apps give automated validated personalised nutrition advice. A web app capable of delivering automated personalised food-based nutrition advice (eNutri) was developed. The aims of this study were to i) evaluate and optimise the personalised nutrition report provided by the app and ii) compare the personalised food-based advice with nutrition professionals’ standards to aid validation. A study with nutrition professionals (NP) compared the advice provided by the app against professional Registered Dietitians (RD) (n = 16) and Registered Nutritionists (RN) (n = 16) standards. Each NP received two pre-defined scenarios, comprising an individual’s characteristics and dietary intake based on an analysis of a food frequency questionnaire, along with the nutrition food-based advice that was automatically generated by the app for that individual. NPs were asked to use their professional judgment to consider the scenario, provide their three most relevant recommendations for that individual, then consider the app’s advice and rate their level of agreement via 5-star scales (with 5 as complete agreement). NPs were also asked to comment on the eNutri recommendations, scores generated and overall impression. The mean scores for the appropriateness, relevance and suitability of the eNutri diet messages were 3.5, 3.3 and 3.3 respectively. [ABSTRACT FROM AUTHOR]

Many disciplines of scholarship are interested in the Relative Age Effect (RAE), whereby age-banding confers advantages on older members of the cohort over younger ones. Most research does not test this relationship in a manner consistent with theory (which requires a decline in frequency across the cohort year), instead resorting to non-parametric, non-directional approaches. In this article, the authors address this disconnect, provide an overview of the benefits associated with Poisson regression modelling, and two managerially useful measures for quantifying RAE bias, namely the Indices of Discrimination and Wastage. In a tutorial-like exposition, applications and extensions of this approach are illustrated using data on professional soccer players competing in the top two tiers of the “Big Five” European football leagues in the search to identify paragon clubs, leagues, and countries from which others may learn to mitigate this form of age-discrimination in the talent identification process. As with OLS regression, Poisson regression may include more than one independent variable. In this way we test competing explanations of RAE; control for unwanted sources of covariation; model interaction effects (that different clubs and countries may not all be subject to RAE to the same degree); and test for non-monotonic versions of RAE suggested in the literature. [ABSTRACT FROM AUTHOR]

Understanding spatial distributions of fish species is important to those seeking to manage fisheries and advise on marine developments. Distribution patterns, habitat use, and aggregative behaviour often vary throughout the life cycle and can increase the vulnerability of certain life stages to anthropogenic impacts. Here we investigate distribution changes during the life cycle of whiting (Merlangius merlangus) to the west of the UK. Density distributions for age-0, age-1 and mature fish were modelled as functions of environmental variables using generalised additive mixed effects models. The greatest densities of age-0 whiting occurred over finer sediments where temperatures were between 12 to 13°C. Age-0 whiting densities decreased with increasing depth. Higher densities of age-1 whiting were also associated with fine sediments and peaked at 60 m, but this influence was also dependent on proximity to shore. Mature fish, while showing no association with any particular sediment type, were strongly associated with depths >60 m. Geostatistical aggregation curves were used to classify space use and showed persistent aggregations of age-0 whiting occupying inshore waters while age-1 and mature fish were more dispersed and differed among years. The differences in distributions among life stages suggested a general coastal to offshore shift as cohorts developed with mature whiting mainly occupying deep offshore waters. The spatial dynamics and areas of persistent life stage aggregation identified here could enable informed targeting and avoidance of specific age-class whiting to aid bycatch reduction. Given that landing obligation legislation is counterproductive unless it encourages greater fishing selectivity, the ability to avoid this species and undersized individuals would aid conservation measures and fishermen alike. [ABSTRACT FROM AUTHOR]

Background: Prognostic modelling using standard methods is well-established, particularly for predicting risk of single diseases. Machine-learning may offer potential to explore outcomes of even greater complexity, such as premature death. This study aimed to develop novel prediction algorithms using machine-learning, in addition to standard survival modelling, to predict premature all-cause mortality. Methods: A prospective population cohort of 502,628 participants aged 40–69 years were recruited to the UK Biobank from 2006–2010 and followed-up until 2016. Participants were assessed on a range of demographic, biometric, clinical and lifestyle factors. Mortality data by ICD-10 were obtained from linkage to Office of National Statistics. Models were developed using deep learning, random forest and Cox regression. Calibration was assessed by comparing observed to predicted risks; and discrimination by area under the ‘receiver operating curve’ (AUC). Findings: 14,418 deaths (2.9%) occurred over a total follow-up time of 3,508,454 person-years. A simple age and gender Cox model was the least predictive (AUC 0.689, 95% CI 0.681–0.699). A multivariate Cox regression model significantly improved discrimination by 6.2% (AUC 0.751, 95% CI 0.748–0.767). The application of machine-learning algorithms further improved discrimination by 3.2% using random forest (AUC 0.783, 95% CI 0.776–0.791) and 3.9% using deep learning (AUC 0.790, 95% CI 0.783–0.797). These ML algorithms improved discrimination by 9.4% and 10.1% respectively from a simple age and gender Cox regression model. Random forest and deep learning achieved similar levels of discrimination with no significant difference. Machine-learning algorithms were well-calibrated, while Cox regression models consistently over-predicted risk. Conclusions: Machine-learning significantly improved accuracy of prediction of premature all-cause mortality in this middle-aged population, compared to standard methods. This study illustrates the value of machine-learning for risk prediction within a traditional epidemiological study design, and how this approach might be reported to assist scientific verification. [ABSTRACT FROM AUTHOR]

Objectives: Maternal lifestyles, including diet, have been linked to infant birthweight. However, customised birthweight centiles (CBWC), which more accurately identify small babies that have increased fetal growth restriction and are at higher risk of newborn morbidity and later life health complications, are rarely considered when studying maternal diet. This study investigated maternal dietary patterns and their impact on infant CBWC within a cohort of women living in South Wales. Methods: This study utilised cross-sectional data from the longitudinal Grown in Wales (GiW) cohort. Women 18–45 years old were recruited the morning prior to an elective caesarean section (ELCS). Women completed a food frequency questionnaire (FFQ). Additional data on pregnancy and birth outcomes was extracted from medical notes. Data from 303 participants was analysed. Results: ‘Western’ and ‘Health conscious dietary patterns were identified. The ‘Health Conscious’ dietary pattern was significantly associated with maternal BMI, age, education, income and exercise. Adjusted regression analyses indicated that greater adherence to a ‘Health Conscious’ dietary pattern was significantly associated with increased CBWC (AOR = 4.75 [95% CI: 1.17, 8.33] p = .010) and reduced risk of delivering a small-for-gestational age (SGA) infant (AOR = .51 [95% CI: .26, .99] p = .046). Conclusion: A healthier diet was significantly associated with higher birthweight using CBWC and a reduced risk of delivering an SGA infant suggesting that birthweight will be improved in areas of Wales by focused support encouraging healthier dietary habits. [ABSTRACT FROM AUTHOR]

Background: Centile curves and standard scores are common in epidemiological research. However, standardised norms and centile growth curves for language disorder that reflect the entire UK local school population do not exist. Methods: Scores on six language indices assessing receptive and expressive functioning of children were obtained from the SCALES population survey. Monolingual English speaking participants were aged between five and nine years. Children who attended special schools at study intake, or who were learning English as an additional language were excluded. We constructed language norms using the LMS method of standardisation which allows for skewed measurements. We made use of probability weights that were produced from a two-step logistic model. Distributions of estimated standard scores from an intensively assessed sub-population and from the full population were contrasted to demonstrate the role of weights. Results: Non-overlapping centile curves and standardised scores at each age were obtained for the six language indices. The use of weights was essential at retrieving the target distribution of the scores. An online calculator that estimates standardised scores for the measures was constructed and made freely available. Conclusions: The findings highlight the usefulness and flexibility of the LMS method at dealing with the standardisation of linguistic and educational measures that are sufficiently continuous. The paper adds to the existing literature by providing population norms for a number of language tests that were calculated from the same group of individuals. [ABSTRACT FROM AUTHOR]

Background: Psoriasis is a common inflammatory skin disease that has been reported to be associated with obesity. We aimed to investigate a possible causal relationship between body mass index (BMI) and psoriasis.Methods and Findings: Following a review of published epidemiological evidence of the association between obesity and psoriasis, mendelian randomization (MR) was used to test for a causal relationship with BMI. We used a genetic instrument comprising 97 single-nucleotide polymorphisms (SNPs) associated with BMI as a proxy for BMI (expected to be much less confounded than measured BMI). One-sample MR was conducted using individual-level data (396,495 individuals) from the UK Biobank and the Nord-Trøndelag Health Study (HUNT), Norway. Two-sample MR was performed with summary-level data (356,926 individuals) from published BMI and psoriasis genome-wide association studies (GWASs). The one-sample and two-sample MR estimates were meta-analysed using a fixed-effect model. To test for a potential reverse causal effect, MR analysis with genetic instruments comprising variants from recent genome-wide analyses for psoriasis were used to test whether genetic risk for this skin disease has a causal effect on BMI. Published observational data showed an association of higher BMI with psoriasis. A mean difference in BMI of 1.26 kg/m2 (95% CI 1.02-1.51) between psoriasis cases and controls was observed in adults, while a 1.55 kg/m2 mean difference (95% CI 1.13-1.98) was observed in children. The observational association was confirmed in UK Biobank and HUNT data sets. Overall, a 1 kg/m2 increase in BMI was associated with 4% higher odds of psoriasis (meta-analysis odds ratio [OR] = 1.04; 95% CI 1.03-1.04; P = 1.73 × 10(-60)). MR analyses provided evidence that higher BMI causally increases the odds of psoriasis (by 9% per 1 unit increase in BMI; OR = 1.09 (1.06-1.12) per 1 kg/m2; P = 4.67 × 10(-9)). In contrast, MR estimates gave little support to a possible causal effect of psoriasis genetic risk on BMI (0.004 kg/m2 change in BMI per doubling odds of psoriasis (-0.003 to 0.011). Limitations of our study include possible misreporting of psoriasis by patients, as well as potential misdiagnosis by clinicians. In addition, there is also limited ethnic variation in the cohorts studied.Conclusions: Our study, using genetic variants as instrumental variables for BMI, provides evidence that higher BMI leads to a higher risk of psoriasis. This supports the prioritization of therapies and lifestyle interventions aimed at controlling weight for the prevention or treatment of this common skin disease. Mechanistic studies are required to improve understanding of this relationship. [ABSTRACT FROM AUTHOR]

Background: Antimicrobial resistance is a global public health problem with some socially patterned drivers. The objective of the study was to investigate associations between use of and trust in the Internet as a source of health-related information and the public’s knowledge, attitudes, and behaviours regarding antibiotics. Methods: Two representative cross-sectional surveys (the 2015 Wellcome Monitor (n = 1524) and UK segment (n = 1330) of the 2016 Eurobarometer 85.1) covering knowledge about antibiotics and antibiotic consumption were analysed. Knowledge, attitude, and behaviour variables were analysed using regression in relation to demographic characteristics and use and trust in the Internet as a source of information. Results: The key findings of the analysis are that both use of the Internet as a source of medical research information (variable from the Wellcome Monitor) and trust in the Internet as a source of information about antibiotics (variable from the Eurobarometer) were independently and positively associated with knowledge, attitude, and behaviour regarding antibiotics. Additionally, knowledge about antibiotics was positively associated with behaviour with antibiotics (Wellcome Monitor) and attitude towards finishing antibiotic prescriptions (Eurobarometer). Higher levels of education were associated with better knowledge about antibiotics in both datasets. Older age was positively associated with behaviour and attitude regarding antibiotic consumption. Conclusions: The Internet is a resource for disseminating quality health information that has the potential to improve stewardship of antibiotics in the community. This study suggests that members of the UK public that use the Internet as a source of health-related information are more likely to be better informed about, and be more responsible with, antibiotics. This mode of information dissemination should be capitalised on to improve antimicrobial stewardship, and further research should examine what the most effective online information sources are in the UK and to what extent their association with behaviour is causal. [ABSTRACT FROM AUTHOR]

Potato blackleg and soft rot caused by Pectobacterium and Dickeya species are among the most significant bacterial diseases affecting potato production globally. In this study we estimate the impact of future temperatures on establishment of non-indigenous but confirmed Pectobacterium and Dickeya species in Great Britain (GB). The calculations are based on probabilistic climate change data and a model fitted to disease severity data from a controlled environment tuber assay with the dominant potato blackleg and soft rot-causing species in GB (P. atrosepticum), and three of the main causative agents in Europe (P. carotovorum subsp. brasiliense, P. parmentieri, Dickeya solani). Our aim was to investigate if the European strains could become stronger competitors in the GB potato ecosystem as the climate warms, on the basis of their aggressiveness in tubers at different temperatures. Principally, we found that the tissue macerating capacity of all four pathogens will increase in GB under all emissions scenarios. The predominant Pectobacterium and Dickeya species in Europe are able to cause disease in tubers under field conditions currently seen in GB but are not expected to become widely established in the future, at least on the basis of their aggressiveness in tubers relative to P. atrosepticum under GB conditions. Our key take-home messages are that the GB potato industry is well positioned to continue to thrive via current best management practices and continued reinforcement of existing legislation. [ABSTRACT FROM AUTHOR]

Background: A modal shift to cycling has the potential to reduce greenhouse gas emissions and provide health co-benefits. Methods, models, and tools are needed to estimate the potential for cycling uptake and communicate to policy makers the range of impacts this would have.Methods and Findings: The Impacts of Cycling Tool (ICT) is an open source model with a web interface for visualising travel patterns and comparing the impacts of different scenarios of cycling uptake. It is currently applied to England. The ICT allows users to visualise individual and trip-level data from the English National Travel Survey (NTS), 2004-2014 sample, 132,000 adults. It models scenarios in which there is an increase in the proportion of the population who cycle regularly, using a distance-based propensity approach to model which trips would be cycled. From this, the model estimates likely impact on travel patterns, health, and greenhouse gas emissions. Estimates of nonoccupational physical activity are generated by fusing the NTS with the English Active People Survey (APS, 2013-2014, 559,515 adults) to create a synthetic population. Under 'equity' scenarios, we investigate what would happen if cycling levels increased equally among all age and gender categories, as opposed to in proportion to the profile of current cyclists. Under electric assist bike (pedelecs or 'e-bike') scenarios, the probability of cycling longer trips increases, based on the e-bike data from the Netherlands, 2013-2014 Dutch Travel Survey (50,868 adults).Outcomes are presented across domains including transport (trip duration and trips by mode), health (physical activity levels, years of life lost), and car transport-related CO2 emissions. Results can be visualised for the whole population and various subpopulations (region, age, gender, and ethnicity). The tool is available at www.pct.bike/ict. If the proportion of the English population who cycle regularly increased from 4.8% to 25%, then there would be notable reductions in car miles and passenger related CO2 emissions (2.2%) and health benefits (2.1% reduction in years of life lost due to premature mortality). If the new cyclists had access to e-bikes, then mortality reductions would be similar, while the reduction in car miles and CO2 emissions would be larger (2.7%). If take-up of cycling occurred equally by gender and age (under 80 years), then health benefits would be marginally greater (2.2%) but reduction in CO2 slightly smaller (1.8%). The study is limited by the quality and comparability of the input data (including reliance on self-report behaviours). As with all modelling studies, many assumptions are required and potentially important pathways excluded (e.g. injury, air pollution, and noise pollution).Conclusion: This study demonstrates a generalisable approach for using travel survey data to model scenarios of cycling uptake that can be applied to a wide range of settings. The use of individual-level data allows investigation of a wide range of outcomes, and variation across subgroups. Future work should investigate the sensitivity of results to assumptions and omissions, and if this varies across setting. [ABSTRACT FROM AUTHOR]

Objective: Despite poor clinic communication and staff treatment being reported by donors, high rates of overall satisfaction are still reported in surveys. This study will evaluate the importance of communication and interaction between donors and fertility clinic staff in gamete donor care. Methods: We report on 120 egg and sperm donors’ responses to a UK-wide online satisfaction survey. The survey focused on donors’ interactions with fertility clinic staff pre-, during, and post- donation. Basic cross-tabulation was performed on the data using online survey software. Textual data was read and extracts identified, which illustrated and expanded on the findings from the numerical data. Diagrammatic modeling was also utilised to analyse the textual data, with particular focus to relationships between the donors and clinic staff, the main activities within the gamete donation process, and how these activities may affect donor satisfaction with the gamete donation process. Results: Donors expressed concern for the infertile couple and the resulting child; conveyed frustration at not receiving information on the expenses they could claim; felt lost in the system regarding the ease of making clinic appointments, and once made they were routinely not seen on time for these appointments. Donors also negatively commented on aftercare, the location and condition of the donation room, and information on contraception. In addition, Ovarian Hyperstimulation Syndrome was frequently reported, with these egg donors believing that clinic staff were not concerned with their physical or emotional well-being, but were instead disproportionately focused on extracting the eggs. Conclusions: The multifaceted notion of donors highlights the complexity inherent to the gamete donation process, which comprises various aspects of uncertainty in the donation system, and ambiguity in the donation process. Categorising donors as Altruist, Customer, and Patient, conveys the particular importance of staff communication and treatment in donor care. These categories are not mutually exclusive however, in that an individual donor may experience more than one of these perspectives during the course of their gamete donation journey. Finally, there were a number of exemplar cases, where donors reported high satisfaction throughout, and these correlated with them being given a single point of contact at the clinic. Subject to resource constraints, we suggest that this practice should be implemented throughout clinics in the UK, so that donors have access to dedicated clinic staff who not only support them emotionally and physically throughout the gamete donation process, but also ensure that communication is open, clear, timely, and consistent. [ABSTRACT FROM AUTHOR]

Background: Air pollution damages health by promoting the onset of some non-communicable diseases (NCDs), putting additional strain on the National Health Service (NHS) and social care. This study quantifies the total health and related NHS and social care cost burden due to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) in England.Method and Findings: Air pollutant concentration surfaces from land use regression models and cost data from hospital admissions data and a literature review were fed into a microsimulation model, that was run from 2015 to 2035. Different scenarios were modelled: (1) baseline 'no change' scenario; (2) individuals' pollutant exposure is reduced to natural (non-anthropogenic) levels to compute the disease cases attributable to PM2.5 and NO2; (3) PM2.5 and NO2 concentrations reduced by 1 μg/m3; and (4) NO2 annual European Union limit values reached (40 μg/m3). For the 18 years after baseline, the total cumulative cost to the NHS and social care is estimated at £5.37 billion for PM2.5 and NO2 combined, rising to £18.57 billion when costs for diseases for which there is less robust evidence are included. These costs are due to the cumulative incidence of air-pollution-related NCDs, such as 348,878 coronary heart disease cases estimated to be attributable to PM2.5 and 573,363 diabetes cases estimated to be attributable to NO2 by 2035. Findings from modelling studies are limited by the conceptual model, assumptions, and the availability and quality of input data.Conclusions: Approximately 2.5 million cases of NCDs attributable to air pollution are predicted by 2035 if PM2.5 and NO2 stay at current levels, making air pollution an important public health priority. In future work, the modelling framework should be updated to include multi-pollutant exposure-response functions, as well as to disaggregate results by socioeconomic status. [ABSTRACT FROM AUTHOR]

Background: Aiming to contribute to prevention of cardiovascular disease (CVD), the National Health Service (NHS) Health Check programme has been implemented across England since 2009. The programme involves cardiovascular risk stratification-at 5-year intervals-of all adults between the ages of 40 and 74 years, excluding any with preexisting vascular conditions (including CVD, diabetes mellitus, and hypertension, among others), and offers treatment to those at high risk. However, the cost-effectiveness and equity of population CVD screening is contested. This study aimed to determine whether the NHS Health Check programme is cost-effective and equitable in a city with high levels of deprivation and CVD.Methods and Findings: IMPACTNCD is a dynamic stochastic microsimulation policy model, calibrated to Liverpool demographics, risk factor exposure, and CVD epidemiology. Using local and national data, as well as drawing on health and social care disease costs and health-state utilities, we modelled 5 scenarios from 2017 to 2040: Scenario (A): continuing current implementation of NHS Health Check;Scenario (B): implementation 'targeted' toward areas in the most deprived quintile with increased coverage and uptake;Scenario (C): 'optimal' implementation assuming optimal coverage, uptake, treatment, and lifestyle change;Scenario (D): scenario A combined with structural population-wide interventions targeting unhealthy diet and smoking;Scenario (E): scenario B combined with the structural interventions as above. We compared all scenarios with a counterfactual of no-NHS Health Check. Compared with no-NHS Health Check, the model estimated cumulative incremental cost-effectiveness ratio (ICER) (discounted £/quality-adjusted life year [QALY]) to be 11,000 (95% uncertainty interval [UI] -270,000 to 320,000) for scenario A, 1,500 (-91,000 to 100,000) for scenario B, -2,400 (-6,500 to 5,700) for scenario C, -5,100 (-7,400 to -3,200) for scenario D, and -5,000 (-7,400 to -3,100) for scenario E. Overall, scenario A is unlikely to become cost-effective or equitable, and scenario B is likely to become cost-effective by 2040 and equitable by 2039. Scenario C is likely to become cost-effective by 2030 and cost-saving by 2040. Scenarios D and E are likely to be cost-saving by 2021 and 2023, respectively, and equitable by 2025. The main limitation of the analysis is that we explicitly modelled CVD and diabetes mellitus only.Conclusions: According to our analysis of the situation in Liverpool, current NHS Health Check implementation appears neither equitable nor cost-effective. Optimal implementation is likely to be cost-saving but not equitable, while targeted implementation is likely to be both. Adding structural policies targeting cardiovascular risk factors could substantially improve equity and generate cost savings. [ABSTRACT FROM AUTHOR]

Background: Street imagery is a promising and growing big data source providing current and historical images in more than 100 countries. Studies have reported using this data to audit road infrastructure and other built environment features. Here we explore a novel application, using Google Street View (GSV) to predict travel patterns at the city level. Methods: We sampled 34 cities in Great Britain. In each city, we accessed 2000 GSV images from 1000 random locations. We selected archived images from time periods overlapping with the 2011 Census and the 2011–2013 Active People Survey (APS). We manually annotated the images into seven categories of road users. We developed regression models with the counts of images of road users as predictors. The outcomes included Census-reported commute shares of four modes (combined walking plus public transport, cycling, motorcycle, and car), as well as APS-reported past-month participation in walking and cycling. Results: We found high correlations between GSV counts of cyclists (‘GSV-cyclists’) and cycle commute mode share (r = 0.92)/past-month cycling (r = 0.90). Likewise, GSV-pedestrians was moderately correlated with past-month walking for transport (r = 0.46), GSV-motorcycles was moderately correlated with commute share of motorcycles (r = 0.44), and GSV-buses was highly correlated with commute share of walking plus public transport (r = 0.81). GSV-car was not correlated with car commute mode share (r = –0.12). However, in multivariable regression models, all outcomes were predicted well, except past-month walking. The prediction performance was measured using cross-validation analyses. GSV-buses and GSV-cyclists are the strongest predictors for most outcomes. Conclusions: GSV images are a promising new big data source to predict urban mobility patterns. Predictive power was the greatest for those modes that varied the most (cycle and bus). With its ability to identify mode of travel and capture street activity often excluded in routinely carried out surveys, GSV has the potential to be complementary to new and traditional data. With half the world’s population covered by street imagery, and with up to 10 years historical data available in GSV, further testing across multiple settings is warranted both for cross-sectional and longitudinal assessments. [ABSTRACT FROM AUTHOR]

Background: Reduced lung function is common and associated with increased cardiovascular morbidity and mortality, even in asymptomatic individuals without diagnosed respiratory disease. Previous studies have identified relationships between lung function and cardiovascular structure in individuals with pulmonary disease, but the relationships in those free from diagnosed cardiorespiratory disease have not been fully explored. Methods: UK Biobank is a prospective cohort study of community participants in the United Kingdom. Individuals self-reported demographics and co-morbidities, and a subset underwent cardiovascular magnetic resonance (CMR) imaging and spirometry. CMR images were analysed to derive ventricular volumes and mass. The relationships between CMR-derived measures and spirometry and age were modelled with multivariable linear regression, taking account of the effects of possible confounders. Results: Data were available for 4,975 individuals, and after exclusion of those with pre-existing cardiorespiratory disease and unacceptable spirometry, 1,406 were included in the analyses. In fully-adjusted multivariable linear models lower FEV1 and FVC were associated with smaller left ventricular end-diastolic (−5.21ml per standard deviation (SD) change in FEV1, −5.69ml per SD change in FVC), end-systolic (−2.34ml, −2.56ml) and stroke volumes (−2.85ml, −3.11ml); right ventricular end-diastolic (−5.62ml, −5.84ml), end-systolic (−2.47ml, −2.46ml) and stroke volumes (−3.13ml, −3.36ml); and with lower left ventricular mass (−2.29g, −2.46g). Changes of comparable magnitude and direction were observed per decade increase in age. Conclusions: This study shows that reduced FEV1 and FVC are associated with smaller ventricular volumes and reduced ventricular mass. The changes seen per standard deviation change in FEV1 and FVC are comparable to one decade of ageing. [ABSTRACT FROM AUTHOR]

Health psychology formally came of age in the United Kingdom in the 1980s, but it was prefigured by much discussion about challenges to the dominance of biomedicine in healthcare and debates. This articles focuses on what could be termed the pre-history of health psychology in the UK. This was the period in the earlier 20th century when psychological approaches were dominated by psychoanalysis which was followed by behaviourism and then cognitivism. Review of this pre-history provides the backdrop for the rise of health psychology in the UK and also reveals the tensions between the different theoretical perspectives. [ABSTRACT FROM AUTHOR]

Background: Multiple sclerosis (MS) has a varied and uncertain trajectory. The recent development of analytical processing tools that draw on large longitudinal patient databases facilitates personalised long-term prognosis estimates. This has the potential to improve both shared treatment decision-making and psychological adjustment. However, there is limited research on how people with MS feel about prognosis communication and forecasting. This study investigated the prognosis communication experiences and preferences of people with MS and explored whether clinical, demographic and psychological factors are associated with prognosis information preferences. Methods: 3175 UK MS Register members (59% of those with active accounts) completed an online survey containing 17 questions about prognosis communication experiences, attitudes and preferences. Participants also completed validated questionnaires measuring coping strategies, tendencies to seek out (‘monitor’) or avoid (‘blunt’) information in threatening situations, and MS risk perceptions and reported their clinical and sociodemographic characteristics. Data already held on the MS Register about participants’ quality of life, anxiety and depression symptoms and MS impact were obtained and linked to the survey data. Results: 53.1% of participants had never discussed long-term prognosis with healthcare professionals. 54.2% lacked clarity about their long-term prognosis. 76% had strong preferences for receiving long-term prognosis information. 92.8% were interested in using tools that generate personalised predictions. Most participants considered prognostication useful for decision-making. Participants were more receptive to receiving prognosis information at later time-points, versus at diagnosis. A comprehensive set of sociodemographic, clinical and psychological variables predicted only 7.9% variance in prognosis information preferences. Conclusions: People with MS have an appetite for individualised long-term prognosis forecasting and their need for information is frequently unmet. Clinical studies deploying and evaluating interventions to support prognostication in MS are now needed. This study indicates suitable contexts and patient preferences for initial trials of long-term prognosis tools in clinical settings. [ABSTRACT FROM AUTHOR]

Nutrition security describes the adequacy of the food supply to meet not only energy but also macronutrient and micronutrient requirements for the population. The aim of this study was to develop a method to assess trends in national nutrition security and the contribution of imports to nutrition security, using the UK as a case study. Food supply data from FAO food balance sheets and national food composition tables were used to estimate the nutrient content of domestically produced food, imported food and exported food. Nutrition security was defined as the total nutrient supply (domestic production, minus exports, plus imports) to meet population-level nutrient requirements. The results showed that the UK was nutrition secure over the period 1961–2011 for energy, macronutrients and key micronutrients, with the exception of total carbohydrates and fibre, which may be due to the loss of fibre incurred by processing cereals into refined products. The supply of protein exceeded population requirements and could be met with domestic production alone. Even excluding all meat there was sufficient protein for population requirements. The supply of total fat, saturated fat and sugar considerably exceeded the current dietary recommendation. As regards nutrition security in 2010, the UK was reliant on imported foods to meet energy, fibre, total carbohydrate, iron, zinc and vitamin A requirements. This analysis demonstrates the importance of including nutrients other than energy to determine the adequacy of the food supply. The methodology also provides an alternative perspective on food security and self-sufficiency by assessing the dependency on imports to meet population level nutritional requirements. [ABSTRACT FROM AUTHOR]

Type 2 diabetes (T2D) is a complex disorder characterized by high blood sugar, insulin resistance, and relative lack of insulin. The collective effects of genome wide minor alleles of common SNPs, or the minor allele content (MAC) in an individual, have been linked with quantitative variations of complex traits and diseases. Here we studied MAC in T2D using previously published SNP datasets and found higher MAC in cases relative to matched controls. A set of 357 SNPs was found to have the best predictive accuracy in a British population. A weighted risk score calculated by using this set produced an area under the curve (AUC) score of 0.86, which is comparable to risk models built by phenotypic markers. These results identify a novel genetic risk element in T2D susceptibility and provide a potentially useful genetic method to identify individuals with high risk of T2D. [ABSTRACT FROM AUTHOR]

Objective: To examine trends in patient experience and consistency between hospital trusts and settings. Methods: Observational study of publicly available patient experience surveys of three hospital settings (inpatients (IP), accident and emergency (A&E) and outpatients (OP)) of 130 acute NHS hospital trusts in England between 2004/05 and 2014/15. Results: Overall patient experience has been good, showing modest improvements over time across the three hospital settings. Individual questions with the biggest improvement across all three settings are cleanliness (IP: +7.1, A&E: +6.5, OP: +4.7) and information about danger signals (IP: +3.8, A&E: +3.9, OP: +4.0). Trust performance has been consistent over time: 71.5% of trusts ranked in the same cluster for more than five years. There is some consistency across settings, especially between outpatients and inpatients. The lowest-scoring questions, regarding information at discharge, are the same in all years and all settings. Conclusions: The greatest improvement across all three settings has been for cleanliness, which has seen national policies and targets. Information about danger signals and medication side-effects showed least consistency across settings and scores have remained low over time, despite information about danger signals showing a big increase in score. Patient experience of aspects of access and waiting have declined, as has experience of discharge delay, likely reflecting known increases in pressure on England’s NHS. [ABSTRACT FROM AUTHOR]

Objectives: Socioeconomic status has been shown to be associated with sexual activity, contraceptive-use, pregnancy and abortion among young people. Less is known about whether the strength of the association differs for each outcome, between men and women, or cross-nationally. We investigate this using contemporaneous national probability survey data from Britain and France. Methods: Data were analysed for 17–29 year-olds in Britain’s third National Survey of Sexual Attitudes and Lifestyles (Natsal-3, n = 5959) undertaken 2010–2012, and the 2010 French Fertility, Contraception and Sexual Dysfunction survey (FECOND, n = 3027). For each country, we estimated the gender-specific prevalence of sex before-16, contraceptive-use, conception before-20, and abortion in the event of conception, and used logistic regression to examine associations between two measures of socioeconomic status–educational-level and parental socioeconomic-group–and each outcome. We tested for interactions between socioeconomic characteristics and country, and socioeconomic characteristics and gender, for each outcome. Results: For each outcome, Britain and France differed with regard to prevalence but associations with socioeconomic characteristics were similar. Respondents of higher educational level, and, less consistently, with parents from higher socioeconomic-groups, were less likely to report sex before-16 (Britain, men: adjusted OR (aOR) 0.5, women: aOR 0.5; France, men: aOR 0.5, women: aOR 0.5), no contraception at first sex (Britain, men: aOR 0.4, women: aOR 0.6; France, men: aOR 0.4, women: aOR 0.4), pregnancy before-20 (Britain: aOR 0.3; France: aOR 0.1), and in Britain, a birth rather than an abortion in the event of conception (Britain: aOR 3.1). We found no strong evidence of variation in the magnitude of the associations with socioeconomic characteristics by country or gender. Conclusions: Population level differences in conception and abortion rates between the two countries may partly be driven by the larger proportion of the population that is disadvantaged in Britain. This research highlights the role intra-country comparisons can play in understanding young people’s sexual and reproductive behaviours. [ABSTRACT FROM AUTHOR]

The science of biology has been transforming dramatically and so the need for a stronger mathematical background for biology students has increased. Biological students reaching the senior or post-graduate level often come to realize that their mathematical background is insufficient. Similarly, students in a mathematics programme, interested in biological phenomena, find it difficult to master the complex systems encountered in biology. In short, the biologists do not have enough mathematics and the mathematicians are not being taught enough biology. The need for interdisciplinary curricula that includes disciplines such as biology, physical science, and mathematics is widely recognized, but has not been widely implemented. In this paper, it is suggested that students develop a skill set of ecology, mathematics and technology to encourage working across disciplinary boundaries. To illustrate such a skill set, a predator–prey model that contains self-limiting factors for both predator and prey is suggested. The general idea of dynamics, is introduced and students are encouraged to discover the applicability of this approach to more complex biological systems. The level of mathematics and technology required is not advanced; therefore, it is ideal for inclusion in a senior-level or introductory graduate-level course for students interested in mathematical biology. [ABSTRACT FROM AUTHOR]

Background: Health care systems in OECD countries are increasingly facing economic challenges and funding pressures. These normally demand interventions (political, financial and organisational) aimed at improving the efficiency of the health system as a whole and its single components. In 2009, the English NHS Chief Executive, Sir David Nicholson, warned that a potential funding gap of £20 billion should be met by extensive efficiency savings by March 2015. Our study investigates possible drivers of differential Trust performance (productivity) for the financial years 2010/11-2012/13. Methods: Following accounting practice, we define Productivity as the ratio of Outputs over Inputs. We analyse variation in both Total Factor and Labour Productivity using ordinary least squares regressions. We explicitly included in our analysis factors of differential performance highlighted in the Nicholson challenge as the sources were the efficiency savings should come from. Explanatory variables include efficiency in resource use measures, Trust and patient characteristics, and quality of care. Results: We find that larger Trusts and Foundation Trusts are associated with lower productivity, as are those treating a greater proportion of both older and/or younger patients. Surprisingly treating more patients in their last year of life is associated with higher Labour Productivity. [ABSTRACT FROM AUTHOR]

Supplementary feeding of garden birds generally has benefits for both bird populations and human wellbeing. Birds have excellent colour vision, and show preferences for food items of particular colours, but research into colour preferences associated with artificial feeders is limited to hummingbirds. Here, we investigated the colour preferences of common UK garden birds foraging at seed-dispensing artificial feeders containing identical food. We presented birds simultaneously with an array of eight differently coloured feeders, and recorded the number of visits made to each colour over 370 30-minute observation periods in the winter of 2014/15. In addition, we surveyed visitors to a garden centre and science festival to determine the colour preferences of likely purchasers of seed feeders. Our results suggest that silver and green feeders were visited by higher numbers of individuals of several common garden bird species, while red and yellow feeders received fewer visits. In contrast, people preferred red, yellow, blue and green feeders. We suggest that green feeders may be simultaneously marketable and attractive to foraging birds. [ABSTRACT FROM AUTHOR]

In this paper we explore a relational understanding of landscape qualities. We asked three independent groups of human observers to assess the expressive qualities of a range of landscapes in the UK and in Spain, either by means of personal visits or from a projected digital image. We employed a Free Choice Profiling (FCP) methodology, in which observers generated their own descriptive terminologies and then used these to quantify perceived landscape qualities on visual analogue scales. Data were analysed using Generalised Procrustes Analysis, a multivariate statistical technique that does not rely on fixed variables to identify underlying dimensions of assessment. The three observer groups each showed significant agreement, and generated two main consensus dimensions that suggested landscape ‘health’ and ‘development in time’ as common perceived themes of landscape expressivity. We critically discuss these outcomes in context of the landscape assessment literature, and suggest ways forward for further development and research. [ABSTRACT FROM AUTHOR]

Background: Wrist-worn accelerometers are emerging as the most common instrument for measuring physical activity in large-scale epidemiological studies, though little is known about the relationship between wrist acceleration and physical activity energy expenditure (PAEE). Methods: 1695 UK adults wore two devices simultaneously for six days; a combined sensor and a wrist accelerometer. The combined sensor measured heart rate and trunk acceleration, which was combined with a treadmill test to yield a signal of individually-calibrated PAEE. Multi-level regression models were used to characterise the relationship between the two time-series, and their estimations were evaluated in an independent holdout sample. Finally, the relationship between PAEE and BMI was described separately for each source of PAEE estimate (wrist acceleration models and combined-sensing). Results: Wrist acceleration explained 44–47% between-individual variance in PAEE, with RMSE between 34–39 J•min-1•kg-1. Estimations agreed well with PAEE in cross-validation (mean bias [95% limits of agreement]: 0.07 [-70.6:70.7]) but overestimated in women by 3% and underestimated in men by 4%. Estimation error was inversely related to age (-2.3 J•min-1•kg-1 per 10y) and BMI (-0.3 J•min-1•kg-1 per kg/m2). Associations with BMI were similar for all PAEE estimates (approximately -0.08 kg/m2 per J•min-1•kg-1). Conclusions: A strong relationship exists between wrist acceleration and PAEE in free-living adults, such that irrespective of the objective method of PAEE assessment, a strong inverse association between PAEE and BMI was observed. [ABSTRACT FROM AUTHOR]

A present challenge in fire ecology is to optimize management techniques so that ecological services are maximized and C emissions minimized. Here, we modeled the effects of different prescribed-burning rotation intervals and wildfires on carbon emissions (present and future) in British moorlands. Biomass-accumulation curves from four Calluna-dominated ecosystems along a north-south gradient in Great Britain were calculated and used within a matrix-model based on Markov Chains to calculate above-ground biomass-loads and annual C emissions under different prescribed-burning rotation intervals. Additionally, we assessed the interaction of these parameters with a decreasing wildfire return intervals. We observed that litter accumulation patterns varied between sites. Northern sites (colder and wetter) accumulated lower amounts of litter with time than southern sites (hotter and drier). The accumulation patterns of the living vegetation dominated by Calluna were determined by site-specific conditions. The optimal prescribed-burning rotation interval for minimizing annual carbon emissions also differed between sites: the optimal rotation interval for northern sites was between 30 and 50 years, whereas for southern sites a hump-backed relationship was found with the optimal interval either between 8 to 10 years or between 30 to 50 years. Increasing wildfire frequency interacted with prescribed-burning rotation intervals by both increasing C emissions and modifying the optimum prescribed-burning interval for minimum C emission. This highlights the importance of studying site-specific biomass accumulation patterns with respect to environmental conditions for identifying suitable fire-rotation intervals to minimize C emissions. [ABSTRACT FROM AUTHOR]

Bovine tuberculosis is an important disease affecting the UK livestock industry. Controlling bovine tuberculosis (TB) is made more complex by the presence of a wildlife host, the Eurasian badger, Meles meles. Repeated large-scale badger culls implemented in the Randomised Badger Culling Trial (RBCT) were associated with decreased cattle risks inside the culling area, but also with increased cattle risks up to the 2km outside the culling area. Intermediate reductions in badger density, as achieved by localised reactive culling in the RBCT, significantly increased cattle TB. Using a matched-pairs case-control study design (n = 221 pairs of cattle herds), we investigated the spatial scale over which localised badger culling had its biggest impact. We found that reactive badger culling had a significant positive association with the risk of cattle TB at distances of 1-3km and 3-5km, and that no such association existed over shorter distances (<1km). These findings indicate that localised badger culls had significant negative effects, not on the land on which culling took place, but, perhaps more importantly, on adjoining lands and farms. [ABSTRACT FROM AUTHOR]

Online bingo has seen significant growth in recent years. This study sought to increase understanding of this growth by exploring the appeal of online bingo. Our aim was to examine the content of ten online bingo websites in the UK and analyse a qualitative secondary dataset of 12 female bingo players to investigate the appeal of online bingo. Using two distinct data sources allowed us to assess how the key messages online websites are trying to convey compare with actual players’ motivation to play bingo. Our analysis of bingo websites found a common theme where websites were easy to navigate and structured to present a light-hearted, fun, reassuring, social image of gambling. In addition, the design decisions reflected in the bingo sites had the effect of positioning online bingo as a benign, child-like, homely, women-friendly, social activity. Comparison of the website content with our participants’ reasons to play bingo showed congruence between the strategies used by the bingo websites and the motivations of bingo players themselves and the benefits which they seek; suggesting that bingo websites strive to replicate and update the sociability of traditional bingo halls. Online bingo differs from traditional forms of bingo in its ability to be played anywhere and at any time, and its capacity to offer a deeply immersive experience. The potential for this type of online immersion in gambling to lead to harm is only just being investigated and further research is required to understand how the industry is regulated, as well as the effects of online bingo on individual gambling ‘careers.’ [ABSTRACT FROM AUTHOR]

Repeated behaviours in stable contexts can become automatic habits. Habits are resistant to information-based techniques to change behaviour, but are contextually cued, so a change in behaviour context (e.g., location) weakens habit strength and can facilitate greater consideration of the behaviour. This idea was demonstrated in previous work, whereby people with strong environmental attitudes have lower car use, but only after recently moving home. We examine the habit discontinuity hypothesis by analysing the Understanding Society dataset with 18,053 individuals representative of the UK population, measuring time since moving home, travel mode to work, and strength of environmental attitudes. Results support previous findings where car use is significantly lower among those with stronger environmental views (but only after recently moving home), and in addition, demonstrate a trend where this effects decays as the time since moving home increases. We discuss results in light of moving into a new home being a potential ‘window of opportunity’ to promote pro-environmental behaviours. [ABSTRACT FROM AUTHOR]

UK Biobank includes 502,649 middle- and older-aged adults from the general population who have undergone detailed phenotypic assessment. The majority of participants completed tests of cognitive functioning, and on average four years later a sub-group of N = 20,346 participants repeated most of the assessment. These measures will be used in a range of future studies of health outcomes in this cohort. The format and content of the cognitive tasks were partly novel. The aim of the present study was to validate and characterize the cognitive data: to describe the inter-correlational structure of the cognitive variables at baseline assessment, and the degree of stability in scores across longitudinal assessment. Baseline cognitive data were used to examine the inter-correlational/factor-structure, using principal components analysis (PCA). We also assessed the degree of stability in cognitive scores in the subsample of participants with repeat data. The different tests of cognitive ability showed significant raw inter-correlations in the expected directions. PCA suggested a one-factor solution (eigenvalue = 1.60), which accounted for around 40% of the variance. Scores showed varying levels of stability across time-points (intraclass correlation range = 0.16 to 0.65). UK Biobank cognitive data has the potential to be a significant resource for researchers looking to investigate predictors and modifiers of cognitive abilities and associated health outcomes in the general population. [ABSTRACT FROM AUTHOR]