Injuries in Competitive Swimming: Incidence and Risk Factors

Objective: To study the nature and incidence rate of injuries that affect collegiate competitive swimmers and to examine the relationship between these injuries and specific risk factors. Background: Minimal research has been conducted on swimming-related injuries, with most studies being retrospective in nature. Only one study reported a calculated injury rate for athletic exposures. Past research reports that the shoulder is the most commonly injured location and that overuse injuries (e.g. tendonitis) is the most common injury type. Methods: IRB approval obtained through the University of North Dakota. Swimmers from UND swim team were asked to participate. Once consent was obtained, baseline data in the form of participant information and a medical history questionnaire was gathered for each participant. Afterwards, the swimmers were followed for an entire season to report any injuries and their exposure to swimming (attendance records, yardage, etc.). Once the season was over, descriptive and analytical data analyses were completed based off information obtained from the participants. Results: Of the 34 participants, 20 sustained a total of 31 injuries during the study period. Based on data found injury rates were calculated has being 5.55 injuries per 1000 AE\u27s and 3.04 injuries per 1000 hours training. Risk factors included in this study were gender, years swimming competitively, history of any injury, and history of specific injury. Risk factors that remained significant in the multivariate analysis were history of any injury and history of specific injury. Conclusions: Injury rates reported in this study are higher than injury rates reported by previous swim-related studies. When compared to other overhead sports, swimming has a lower overall injury rate. As for distribution of injuries, the data reported in this study are similar to those that were reported in other swim-related studies

A synthesis of plant invasion effects on biodiversity across spatial scales

PREMISE OF THE STUDY: Invasive plant species are typically thought to pose a large threat to native biodiversity, and local-scale studies typically confirm this view. However, plant invaders rarely cause regional extirpations or global extinctions, causing some to suggest that invasive species\u27 influence on native biodiversity may not be so dire. We aim to synthesize the seemingly conflicting literature in plant invasion biology by evaluating the effects of invasive plant species across spatial scales. METHODS: We first conducted a meta-analysis on the effects of invasive plants on the species richness of invaded communities across a range of spatial extents. We then discuss studies that consider the role of invasive plants on regional spatial scales for which such meta-analyses are not possible. Finally, we develop a conceptual framework to synthesize the influence of invasive species across spatial scales by explicitly recognizing how invasive species alter species-occupancy distributions. KEY RESULTS: We found a negative relationship between the spatial extent of the study and the effect size of invasive plants on species richness. Our simulation models suggest that this result can occur if invaders, either proportionately or disproportionately, reduce the occupancy of common species to a greater degree than rare species. CONCLUSIONS: Future studies should consider the influence of invaders on the abundance and occupancy-level changes in native species to inform how invasive plants will influence native species richness relationships across spatial scales. This approach will allow greater predictive ability for forecasting changes in biodiversity in the face of anthropogenic biological invasions and will inform invasive species management and restoration

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

The role of networks to overcome large-scale challenges in tomography : the non-clinical tomography users research network

Our ability to visualize and quantify the internal structures of objects via computed tomography (CT) has fundamentally transformed science. As tomographic tools have become more broadly accessible, researchers across diverse disciplines have embraced the ability to investigate the 3D structure-function relationships of an enormous array of items. Whether studying organismal biology, animal models for human health, iterative manufacturing techniques, experimental medical devices, engineering structures, geological and planetary samples, prehistoric artifacts, or fossilized organisms, computed tomography has led to extensive methodological and basic sciences advances and is now a core element in science, technology, engineering, and mathematics (STEM) research and outreach toolkits. Tomorrow's scientific progress is built upon today's innovations. In our data-rich world, this requires access not only to publications but also to supporting data. Reliance on proprietary technologies, combined with the varied objectives of diverse research groups, has resulted in a fragmented tomography-imaging landscape, one that is functional at the individual lab level yet lacks the standardization needed to support efficient and equitable exchange and reuse of data. Developing standards and pipelines for the creation of new and future data, which can also be applied to existing datasets is a challenge that becomes increasingly difficult as the amount and diversity of legacy data grows. Global networks of CT users have proved an effective approach to addressing this kind of multifaceted challenge across a range of fields. Here we describe ongoing efforts to address barriers to recently proposed FAIR (Findability, Accessibility, Interoperability, Reuse) and open science principles by assembling interested parties from research and education communities, industry, publishers, and data repositories to approach these issues jointly in a focused, efficient, and practical way. By outlining the benefits of networks, generally, and drawing on examples from efforts by the Non-Clinical Tomography Users Research Network (NoCTURN), specifically, we illustrate how standardization of data and metadata for reuse can foster interdisciplinary collaborations and create new opportunities for future-looking, large-scale data initiatives

Data from: Invasive plants have scale-dependent effects on diversity by altering species-area relationships

Although invasive plant species often reduce diversity, they rarely cause plant extinctions. We surveyed paired invaded and uninvaded plant communities from three biomes. We reconcile the discrepancy in diversity loss from invaders by showing that invaded communities have lower local richness but steeper species accumulation with area than that of uninvaded communities, leading to proportionately fewer species loss at broader spatial scales. We show that invaders drive scale-dependent biodiversity loss through strong neutral sampling effects on the number of individuals in a community. We also show that nonneutral species extirpations are due to a proportionately larger effect of invaders on common species, suggesting that rare species are buffered against extinction. Our study provides a synthetic perspective on the threat of invasions to biodiversity loss across spatial scales

Relationship between species richness and area

Data for all 10 of our study sites. This data matches figure 1 in the manuscript. Columns in this excel file are: Plot size (m^2), Log plot size, number of species observed in the plot (i.e., richness), log number of species observed in the plot, site (corresponds to the figure), site number (corresponds to figure), Community (whether or not the community is in invaded or uninvaded