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Sarcopenia, obesity, or both: what is the dominant variable of the associated risks of sarcopenic obesity?
Get PDFBackground and objective: Sarcopenic obesity (SO), obesity, and sarcopenia have been related to adverse events in older adults, raising the question about the role of each component in the risk associated with SO. The objective of this manuscript is to evaluate the role of sarcopenia, obesity, and its interaction in the risks (frailty, disability, mortality) associated with sarcopenic obesity. Research Design and Methods: Data from the Toledo Study of Healthy Aging (TSHA) were used. This is a cohort-based study composed of community-dwelling adults ≥65 years. Obesity (Body Mass Index-BMI ≥30) and sarcopenia (the Foundation for the National Institutes of Health-FNIH criteria, standardized to our population) were assessed at baseline. Frailty, through the Frailty Phenotype (FP) and the Frailty Trait scale-5 (FTS5), and disability (Katz Index) were evaluated at baseline. Mortality, frailty, and disability were assessed at follow-up. Logistic (odds ratio, OR) and Cox (hazard ratio, HR) regression models were computed to assess the associations. Results: A total of 1 538 (74.73 years, 45.51% men) individuals were included. Cross-sectionally, SO, sarcopenia, and obesity were significantly associated with the risk of frailty and disability. Longitudinally, Sarcopenia was associated with all the adverse events (ORs/HRs ranged from 1.41 to 4.14, p-value < .05); whereas SO [FP, OR (95% confidence interval—CI): 4.27 (2.05, 8.93); FTS5, OR (95% CI): 6.14 (3.58, 10.51), p-value < .001] and obesity [FP, OR (95% CI): 3.10 (1.95, 4.94), p-value < 0.001; FTS5, OR (95% CI): 2.26 (1.17, 4.35), p-value 0.015] was only associated with incident frailty. Sarcopenia added risk to obesity for frailty (FP and FTS5) whereas obesity only did for frailty (FTS5) in sarcopenic individuals. The interaction between sarcopenia and obesity was not associated with any outcome.</p
Exploring the Associations Between Dysphagia and Health-Related Outcomes in Older Adults:Results from the ilSirente Study
Get PDFObjectives: The present study examined cross-sectional and longitudinal associations between dysphagia and a variety of health-related parameters, including physical performance, cognitive function, malnutrition, sarcopenia, disability, frailty, falls, hospitalization, and mortality in a cohort of octogenarians living in the mountainous Sirente region of Central Italy. Methods: Dysphagia was operationalized as the need to modify the diet to facilitate swallowing and/or the exclusive consumption of specific food consistencies due to swallowing difficulties. Physical performance, cognitive function, malnutrition, disability, falls, and hospitalizations were assessed via the Minimum Data Set for Home Care. Sarcopenia was defined as the coexistence of low muscle mass and dynapenia, while frailty was operationalized according to Fried’s phenotype. History of falls and incident falls, as well as disability, were tracked over two years, while survival status was followed for up to ten years. Results: Data of 362 older adults (men age: 85.9 ± 4.8; body mass index: 25.6 ± 4.53; women: 66.9%; multimorbidity: 21.5%; dysphagia: 6.6%) were analyzed. The results indicated that dysphagia was significantly and cross-sectionally associated with poor physical performance and reduced cognitive function. In contrast, no longitudinal associations were observed. Conclusions: Dysphagia appears to be linked to deficits in physical and cognitive domains, underscoring the value of comprehensive geriatric assessment and the development of multidomain intervention strategies.</p
Who supports the support staff? the experiences of BAME teaching assistants and supply staff
No full textWhile much research, covered elsewhere within this edited book highlights the issues that arise due to low numbers of BAME staff in teaching and leadership positions, there is little coverage of the role and potential importance of BAME members within school support staff, particularly Teaching Assistants/Learning Support Assistants and Supply Staff. By supply staff, we are focussing on individuals who are often supplied by an agency and come in to school to cover for an absent or sick teacher, in the short or longer term. The challenges faced by teachers and prospective head teachers in relation to institutional racism have been explored (Miller, 2020), but unfortunately, there is limited evidence available on whether these challenges are also faced by support staff. This chapter explores the experiences of a sample of support staff (7) from a variety of ethnic backgrounds. Through an online interview, they explore their experiences in school, how they work with students from diverse backgrounds, and their perceptions of how they are treated within the settings they have worked in. A number of participants were also Overseas Trained Teachers, and the chapter will highlight the challenges they have had in having their qualifications recognised, and the additional training they have had to do.</p
Adherence to the mediterranean diet and physical activity in relation to sarcopenia:a cross-sectional epidemiological cohort study
Get PDFBackground: Adoption of healthy lifestyle habits has been proposed as successful strategies to counteract sarcopenia. Aims: To explore the association of physical activity (PA) and adherence to the mediterranean diet (MD), individually and synergically, with sarcopenia. Methods: The present cross-sectional study examined data of the Toledo Study of Healthy Ageing. Data of community-dwelling adults aged 65 + years were analyzed. Sarcopenia was defined according to the Foundation for the National Institutes of Health, standardized to our population (sFNIH) and the European Working Group on Sarcopenia (EWGSOP2). PA levels (Physical Activity Scale for the Elderly, PASE) and adherence to the MD (MEDiterranean Diet Adherence Screener-MEDAS) were estimated using self-reported instruments. Binary regression models were conducted to test associations. Results: Data of 1457 individuals (mean age 74.68 ± 5.77 years; 54.91% women) were analyzed. Among them, 331 (22.72%, sFNIH) and 202 (13.86%, EWGSOP2) met sarcopenia criteria. PA levels (ORs: 0.91–0.95, p < 0.05) and adherence to the MD (ORs: 0.82–0.86, p < 0.05) were significantly and negatively associated with the prevalence of sarcopenia, regardless of the definition used. Nevertheless, no significant interactions were observed among healthy lifestyle habits. According to sarcopenia-related domains, PA levels and adherence to the MD were negatively associated with dynapenia, meanwhile, PA levels were associated with low lean mass (sFNIH) and adherence to the MD was inversely associated with poor mobility. Conclusions: PA and adherence to the MD are independently associated with sarcopenia. Moreover, specific associations were observed between sarcopenia domains. Nevertheless, no significant interaction was observed between them.</p
Support vector machine (SVM) based detection for volumetric bandwidth distributed denial of service (DVB-DDOS) attack within gigabit passive optical network
Get PDFThe dynamic bandwidth allocation (DBA) algorithm is highly impactful in improving the network performance of gigabit passive optical networks (GPON). Network security is an important component of today’s networks to combat security attacks, including GPON. However, the literature contains reports highlighting its vulnerability to specific attacks, thereby raising concerns. In this work, we argue that the impact of a volumetric bandwidth distributed denial of service (DVB-DDOS) attack can be mitigated by improving the dynamic bandwidth assignment (DBA) scheme, which is used in PON to manage the US bandwidth at the optical line terminal (OLT). Thus, this study uses a support vector machine (SVM), a machine learning approach, to learn the optical network unit (ONU) traffic demand patterns and presents a hybrid security-aware DBA (HSA-DBA) scheme that is capable of distinguishing malicious ONUs from normal ONUs. In this article, we consider the deployment of the HSA-DBA scheme in OMNET++ to acquire the monitoring data samples used to train the ML technique for the effective classification of ONUs. The simulation findings revealed a mean upstream delay improvement of up to 63% due to the security feature offered by the mechanism. Moreover, significant reductions in upstream delay performance, including 63% for TCONT2, 65% for TCONT3, and 95% for TCONT4, along with a reduction in frame loss rates for normal ONU traffic, were observed. This research provides a significant stride towards secure GPONs, ensuring reliable defense mechanisms are in place, which paves the way for more resilient future broadband network infrastructures.</p
Nursing autonomy and evidence-based practice in acute care:navigating power and promoting collaboration
Get PDFAim: This study explores how power dynamics between nurses and physicians in acute care settings influence nursing autonomy and the implementation of evidence-based practice (EBP). It also identifies organisational strategies that can enhance interprofessional collaboration (IPE), leadership and shared decision-making. Design: A qualitative case study approach was used, underpinned by social constructivism to explore nurses’ lived experiences within the context of acute care hierarchies. Methods: Data were collected from two large NHS acute care hospitals in the Midlands, through 33 semistructured interviews, 12 nonparticipant observations and document reviews. The sample included 37 staff nurses, ward managers, nurse managers and physicians. Braun and Clarke’s thematic analysis framework guided data analysis, supported by reflexive field notes and triangulation of data sources. Findings: Nurses reported restricted autonomy due to entrenched medical dominance and were frequently excluded from key decision-making processes. These hierarchical imbalances contributed to moral distress, burnout and disengagement from EBP. However, the study also uncovered everyday acts of resistance, including subtle negotiation and knowledge-based advocacy. Leadership training, IPE, shared governance and structural reforms were cited as effective strategies for enhancing collaboration and restoring nursing voice. Participants who experienced nurse-led initiatives and inclusive decision-making reported improved confidence and patient care outcomes. Conclusion: Hierarchical power dynamics significantly constrain nursing autonomy and hinder EBP implementation in acute care. Nurses respond with resilience and agency, often advocating for evidence use in informal ways. Organisational reforms that promote shared governance, empower nurse leaders and foster respectful collaboration are essential for shifting entrenched dynamics and improving care quality.</p
What factors from the Theoretical Domains Framework influence people with cardiovascular disease to seek help from healthcare services? A systematic review, behavioural analysis and conceptual ‘KASiE’ considerations for five types of health-seeking behaviour
Get PDFObjectiveIdentifying influences of help-seeking behaviour in people with cardiovascular diseases (CVDs) can assist with development of future intervention strategies.MethodsA systematic review synthesised qualitative, peer-reviewed literature reporting on the experiences of health service use from the perspective of people with CVDs from publications in four databases (PsycINFO, Medline, Embase, Emcare). Influences of help-seeking were mapped to the Theoretical Domains Framework (TDF) and Capability, Opportunity, Motivation – Behaviour (COM-B) Model, followed by thematic analysis.Results22 studies were included. Prominent themes related to the environment (healthcare service features, transport access, clashing life commitments), knowledge of CVDs and health service capabilities, social interactions (with social network and healthcare professionals), and emotions like fear and guilt linked to anticipated negative outcomes (e.g., fear of asking for help due to anticipation of judgement as a ‘bad patient’).ConclusionThose designing future interventions could consider the value of 1) increasing knowledge of CVD symptoms and management options, 2) improving logistical access to services, and 3) implementing strategies that promote positive social influences and challenge assumptions to address emotions such as guilt. Together, we have termed this the KASiE (Knowledge, Access, Social influence and Emotions) approach highlighting areas for public health agencies to focus
Leading evidence-based practice: nurse managers' strategies for knowledge utilisation in acute care settings
Get PDFBackground: The implementation of evidence-based practice (EBP) in nursing is essential for improving patient care outcomes, yet systemic barriers, leadership challenges, and resource limitations continue to hinder its integration into clinical practice. Nurse managers (NMs) play a crucial role in bridging the gap between policy directives and frontline implementation, yet the dynamic interplay between leadership strategies, knowledge utilisation, and organisational barriers remains underexplored, particularly in resource-constrained settings. This study examines how NMs navigate these challenges to sustain EBP adoption in acute care environments. Methods: This collective case study employed a longitudinal qualitative design across two acute care settings in the UK. Data were collected over eight months through semi-structured interviews with NMs, nonparticipant observations, and document analysis of clinical guidelines and internal reports. A thematic analysis approach was used to synthesise findings and provide a nuanced understanding of leadership strategies and systemic factors influencing EBP adoption. Findings: Six interconnected themes emerged: (1) Adaptive leadership strategies, where NMs employ a hybrid of directive and collaborative leadership approaches to drive EBP; (2) Overcoming organisational and resource barriers, including staff shortages, financial constraints, and competing priorities; (3) Knowledge utilisation and learning networks, highlighting the role of informal mentorship, structured CPD, and peer learning in sustaining EBP; (4) Digital transformation and EBP, examining the benefits and challenges of integrating digital tools and addressing IT literacy gaps; (5) Patient-centred adaptations, exploring how NMs balance evidence-based interventions with patient preferences and cultural considerations; and (6) Emotional and psychological support, underscoring the importance of managing staff resistance and mitigating change fatigue. Conclusion: Findings of this study emphasise the pivotal role of NMs in driving EBP implementation through adaptive leadership, strategic resource management, and fostering learning networks. Addressing organisational barriers requires multi-level interventions that integrate leadership actions with systemic enablers to promote sustainable, evidence-informed nursing practice. Findings provide critical insights for healthcare policymakers, hospital administrators, and educators in enhancing EBP uptake within resource-limited settings.</p
A coach’s guide to understanding and measuring stiffness Part 1: Biomechanical concepts
Get PDFAbstract: The general concept of the stretch and recoil of elastic tissue during ground contact, storing and releasing energy to enhance the propulsive phase of an action is well understood. However different stiffness measures are frequently used incorrectly and interchangably, leading to ineffective monitoring of stiffness changes, limiting the impact of training designed to enhance stiffness. The aim of this narrative review is to discuss how different structures react to ground contacts, how this behaviour can be modeled and how stiffness impacts performance. Hill’s three-compartment model highlights the need for tendon compliance and muscle stiffness in efficient force generation. However, this does not really explain slow stretch shortening cycle (SSC) actions, were both muscle and tendon stretch and recoil. Different models are used to describe a bodies ground impact behaviour, including the spring-mass model which describes centre of mass movement, the torsional spring model which describes leg fuction, with three torsional springs representing the ankle, knee and hip. These models generally link an increase in stiffness to an increase in performance in high intensity action, with vertical stiffness a predictor of high intensity sporting actions independent of sex, age or maturation. Leg stiffness initially increases with running velocity, before remaining constant at high running velocities. When joint function is reviewed ankle stiffness is linked to fast SSC actions, with knee stiffness linked to slow SSC actions. It is concluded that different measures of stiffness should not be used interchangably as different aspects of stiffness impact performance independantly
Robust sensor fault detection in wireless sensor networks using a hybrid conditional generative adversarial networks and convolutional autoencoder
Get PDFIn the rapidly growing realm of the Internet of Things (IoT), reliance on sensor-generated data has become crucial for the operation of multiple services and systems. As essential components of these systems, wireless sensor networks (WSNs) are installed in a wide range of diverse and often harsh environments. However, these networks are highly prone to a range of faults, including software bugs, communication failures, and hardware malfunctions. Such issues can lead data to data being transmitted incorrectly, endangering the security, reliability, and economic stability of the systems they support. Addressing the challenge of sensor fault detection, we propose a novel hybrid technique to enhance the classification of sensor fault data in WSNs. Our method leverages a publicly available dataset of temperature sensor readings to generate synthetic data by using a conditional generative adversarial networks. These synthetic samples closely resemble common temperature sensor data despite the introduction of artificial sensor faults in WSNs, including hardover, drift, spike, erratic, and stuck faults. In order to capture the temporal dependencies in time-series data, we transform the sensor readings into Gramian Angular Field images (GAF), retaining the temporal structure. These GAF images are then processed using a convolutional autoencoder to extract rich feature representations, followed by a three-layer artificial neural network for the multi-class classification of sensor faults. Our proposed method not only addresses the challenges of data scarcity and imbalance but also enhances accuracy in sensor fault detection. The proposed method demonstrates high accuracy, F1-score, recall, and sensitivity, achieving 95.93%, 95.84%, 95.88%, and 95.88% respectively
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