Are tibial angles measured with inertial sensors useful surrogates for frontal plane projection angles using 2-dimensional video analysis during single leg squat tasks? A reliability and agreement analysis in elite football (soccer) players

During single leg squats (SLS), tibial angle (TA) quantification using inertial measurement units (IMU) may offer a practical alternative to frontal plane projection angle (FPPA) measurement using 2-dimensional (2D) video analysis. This study determined: (i) the reliability of IMUs and 2D video analysis for TA measurement, and 2D video analysis for FPPA measurement; (ii) the agreement between IMU TA and both 2D video TA and FPPA measurements during single leg squats in elite footballers. 18 players were tested on consecutive days. Absolute TA (ATA) and relative TA (RTA) were measured with IMUs. ATA and FPPA were measured concurrently using 2D video analysis. Within-session reliability for all measurements varied across days (intraclass correlation coefficient (ICC) range=0.27–0.83, standard error of measurement (SEM) range=2.12–6.23°, minimal detectable change (MDC) range=5.87–17.26°). Between-sessions, ATA reliability was good for both systems (ICCs=0.70–0.74, SEMs=1.64–7.53°, MDCs=4.55–7.01°), while IMU RTA and 2D FPPA reliability ranged from poor to good (ICCs=0.39–0.72, SEMs=2.60–5.99°, MDCs=7.20–16.61°). All limits of agreement exceeded a 5° acceptability threshold. Both systems were reliable for between-session ATA, although agreement was poor. IMU RTA and 2D video FPPA reliability was variable. For SLS assessment, IMU derived TAs are not useful surrogates for 2D video FPPA measures in this population

Informing investment to reduce inequalities: a modelling approach

Background: Reducing health inequalities is an important policy objective but there is limited quantitative information about the impact of specific interventions. Objectives: To provide estimates of the impact of a range of interventions on health and health inequalities. Materials and methods: Literature reviews were conducted to identify the best evidence linking interventions to mortality and hospital admissions. We examined interventions across the determinants of health: a ‘living wage’; changes to benefits, taxation and employment; active travel; tobacco taxation; smoking cessation, alcohol brief interventions, and weight management services. A model was developed to estimate mortality and years of life lost (YLL) in intervention and comparison populations over a 20-year time period following interventions delivered only in the first year. We estimated changes in inequalities using the relative index of inequality (RII). Results: Introduction of a ‘living wage’ generated the largest beneficial health impact, with modest reductions in health inequalities. Benefits increases had modest positive impacts on health and health inequalities. Income tax increases had negative impacts on population health but reduced inequalities, while council tax increases worsened both health and health inequalities. Active travel increases had minimally positive effects on population health but widened health inequalities. Increases in employment reduced inequalities only when targeted to the most deprived groups. Tobacco taxation had modestly positive impacts on health but little impact on health inequalities. Alcohol brief interventions had modestly positive impacts on health and health inequalities only when strongly socially targeted, while smoking cessation and weight-reduction programmes had minimal impacts on health and health inequalities even when socially targeted. Conclusions: Interventions have markedly different effects on mortality, hospitalisations and inequalities. The most effective (and likely cost-effective) interventions for reducing inequalities were regulatory and tax options. Interventions focused on individual agency were much less likely to impact on inequalities, even when targeted at the most deprived communities

A study protocol for the development and internal validation of a multivariable prognostic model to determine lower extremity muscle injury risk in elite football (soccer) players, with further exploration of prognostic factors

Background: Indirect muscle injuries (IMIs) are a considerable burden to elite football (soccer) teams, and prevention of these injuries offers many benefits. Preseason medical, musculoskeletal and performance screening (termed periodic health examination (PHE)) can be used to help determine players at risk of injuries such as IMIs, where identification of PHE-derived prognostic factors (PF) may inform IMI prevention strategies. Furthermore, using several PFs in combination within a multivariable prognostic model may allow individualised IMI risk estimation and specific targeting of prevention strategies, based upon an individual's PF profile. No such models have been developed in elite football and the current IMI prognostic factor evidence is limited. This study aims to (1) develop and internally validate a prognostic model for individualised IMI risk prediction within a season in elite footballers, using the extent of the prognostic evidence and clinical reasoning; and (2) explore potential PHE-derived PFs associated with IMI outcomes in elite footballers, using available PHE data from a professional team. Methods: This is a protocol for a retrospective cohort study. PHE and injury data were routinely collected over 5 seasons (1 July 2013 to 19 May 2018), from a population of elite male players aged 16-40 years old. Of 60 candidate PFs, 15 were excluded. Twelve variables (derived from 10 PFs) will be included in model development that were identified from a systematic review, missing data assessment, measurement reliability evaluation and clinical reasoning. A full multivariable logistic regression model will be fitted, to ensure adjustment before backward elimination. The performance and internal validation of the model will be assessed. The remaining 35 candidate PFs are eligible for further exploration, using univariable logistic regression to obtain unadjusted risk estimates. Exploratory PFs will also be incorporated into multivariable logistic regression models to determine risk estimates whilst adjusting for age, height and body weight. Discussion: This study will offer insights into clinical usefulness of a model to predict IMI risk in elite football and highlight the practicalities of model development in this setting. Further exploration may identify other relevant PFs for future confirmatory studies and model updating, or influence future injury prevention research

Can prognostic factors for indirect muscle injuries in elite football (soccer) players be identified using data from preseason screening? An exploratory analysis using routinely-collected periodic health examination records

ABSTRACTThis study used periodic health examination (PHE) data from 134 outfield elite male football players, over 5 seasons (1st July 2013 to 19th May 2018). Univariable and multivariable logistic regression models were used to determine prognostic associations between 36 variables and time-loss, lower extremity index indirect muscle injuries (I-IMIs). Non-linear associations were explored using fractional polynomials. During 317 participant-seasons, 138 I-IMIs were recorded. Univariable associations were determined for previous calf indirect muscle injury (IMI) frequency (OR=1.80, 95% confidence interval (CI) = 1.09 to 2.97), hamstring IMI frequency (OR=1.56, 95% CI=1.17 to 2.09), if the most recent hamstring IMI occurred &gt; 12 months but &lt; 3 years prior to PHE (OR= 2.95, 95% CI = 1.51 to 5.73) and age (OR =1.12 per 1-year increase, 95% CI = 1.06 to 1.18). Multivariable analyses demonstrated that if a player’s most recent previous hamstring IMI was &gt;12 months but &lt;3 years prior to PHE (OR= 2.24, 95% CI = 1.11 to 4.53), then this was the only variable with added prognostic value over and above age (OR=1.12 per 1-year increase, 95%CI = 1.05 to 1.18). Allowing non-linear associations conferred no advantage over linear ones. Therefore, PHE has limited use for injury risk prediction.</jats:p

Phytochemicals as antibiotic alternatives to promote growth and enhance host health

There are heightened concerns globally on emerging drug-resistant superbugs and the lack of new antibiotics for treating human and animal diseases. For the agricultural industry, there is an urgent need to develop strategies to replace antibiotics for food-producing animals, especially poultry and livestock. The 2nd International Symposium on Alternatives to Antibiotics was held at the World Organization for Animal Health in Paris, France, December 12-15, 2016 to discuss recent scientific developments on strategic antibiotic-free management plans, to evaluate regional differences in policies regarding the reduction of antibiotics in animal agriculture and to develop antibiotic alternatives to combat the global increase in antibiotic resistance. More than 270 participants from academia, government research institutions, regulatory agencies, and private animal industries from >25 different countries came together to discuss recent research and promising novel technologies that could provide alternatives to antibiotics for use in animal health and production; assess challenges associated with their commercialization; and devise actionable strategies to facilitate the development of alternatives to antibiotic growth promoters (AGPs) without hampering animal production. The 3-day meeting consisted of four scientific sessions including vaccines, microbial products, phytochemicals, immune-related products, and innovative drugs, chemicals and enzymes, followed by the last session on regulation and funding. Each session was followed by an expert panel discussion that included industry representatives and session speakers. The session on phytochemicals included talks describing recent research achievements, with examples of successful agricultural use of various phytochemicals as antibiotic alternatives and their mode of action in major agricultural animals (poultry, swine and ruminants). Scientists from industry and academia and government research institutes shared their experience in developing and applying potential antibiotic-alternative phytochemicals commercially to reduce AGPs and to develop a sustainable animal production system in the absence of antibiotics.Fil: Lillehoj, Hyun. United States Department of Agriculture. Agricultural Research Service; ArgentinaFil: Liu, Yanhong. University of California; Estados UnidosFil: Calsamiglia, Sergio. Universitat Autònoma de Barcelona; EspañaFil: Fernandez Miyakawa, Mariano Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Patobiología; ArgentinaFil: Chi, Fang. Amlan International; Estados UnidosFil: Cravens, Ron L.. Amlan International; Estados UnidosFil: Oh, Sungtaek. United States Department of Agriculture. Agricultural Research Service; ArgentinaFil: Gay, Cyril G.. United States Department of Agriculture. Agricultural Research Service; Argentin

Microbial diversity and community composition of caecal microbiota in commercial and indigenous Indian chickens determined using 16s rDNA amplicon sequencing

Different alpha diversity indices for each sample of university farm data estimated using QIIME for primer pair P2 data. OTUs were clustered at > 97% similarity. (XLSX 12 kb