Fitness Test Research Articles

A model for predicting AKI after cardiopulmonary bypass surgery in Chinese patients with normal preoperative renal function

ObjectiveTo develop and validate a predictive model for acute kidney injury (AKI) after cardiopulmonary bypass (CPB) surgery in Chinese patients with normal preoperative renal function.MethodFrom January 1, 2015, to September 1, 2022, a total of 1003 patients were included in the analysis as a development cohort. We used the ratio of 7:3 to divide the patients into a training group (n = 703) and a testing group (n = 300). In addition, a total of 178 patients were collected as an external validation cohort from January 1, 2023, to May 1, 2023. In the training group, independent risk factors for postoperative AKI were identified through the least absolute shrinkage and selection operator (LASSO) regression and multifactor logistic regression analysis. A nomogram predictive model was then established. The area under the curve (AUC) of receiver operating characteristic (ROC) curve, as well as calibration curve and decision curve, were used for validation of the model.ResultsAge, body mass index (BMI), emergent surgery, CPB time, intraoperative use of adrenaline, and postoperative procalcitonin (PCT) were identified as important risk factors for AKI after CPB surgery (P < 0.05). The nomogram predictive model demonstrated good discrimination (AUC: 0.772 (95%CI: 0.735 − 0.809), 0.780 (95% CI: 0.724 − 0.835), and 0.798 (95% CI: 0.731 − 0.865)), calibration (Hosmer and Lemeshow goodness of fit test: P-value 0.6941, 0.9539, and 0.2358), and clinical utility (the threshold probability values in the decision curves are respectively > 12%, > 10%, and 16% ~ 75%) in the training, testing, and external validation groups.ConclusionThe predictive model, which was established in Chinese patients with normal preoperative renal function, has high accuracy, calibration, and clinical utility. Clinicians can utilize this model to predict and potentially reduce the incidence of AKI after CPB surgery in the Chinese population.

Change in Cardiorespiratory Fitness and the Risk of Colorectal and Prostate Cancer Incidence in Men.

The aim of this prospective cohort study was to investigate the associations between changes in cardiorespiratory fitness (CRF) and the risk of colorectal and prostate cancer in men. Data from men who completed a health assessment both in military conscription in youth and an occupational health profile assessment (HPA) later in life were used. CRF was assessed as estimated V̇O2max, using a cycle ergometer fitness test at both time points. We linked the assessment data to national register data on colorectal and prostate cancer incidence, and hazard ratios and confidence intervals were estimated using Cox proportional hazard regression. 139,764 men with a mean age of 18 (SD 0.6) at conscription and 43 (SD 8.9) at HPA were included. The average time between the two assessments was 25.9 (SD 9.0) years and mean follow-up time following HPA test was 10.0 (SD 5.6) years for prostate and colorectal cancer. Annual percentage change in relative and absolute V̇O2max from conscription to HPA was inversely associated with the risk of colorectal cancer incidence, hazard ratio of 0.83 (95% CI [0.72-0.94]) and 0.88 (95% CI [0.79-0.99]), respectively. These associations were driven by data from individuals in the lowest and moderate level fitness tertials at conscription. Change in CRF was not associated with prostate cancer incidence risk. Changes in, not only level of, CRF from youth to adulthood are related to colorectal cancer incidence risk and therefore, improving CRF should be considered as an important colorectal cancer risk reduction strategy.

ANÁLISE DA COMPOSIÇÃO CORPORAL E APTIDÃO FÍSICA DE ATLETAS PARALÍMPICOS DE RIO BRANCO ACRE

Introduction: Sports training techniques have sparked interest in detailing the physical and physiological characteristics of athletes to prescribe training specifically tailored to their goals. Objective: This study aimed to analyze body composition and its relationship with physical fitness in Paralympic athletes from Rio Branco, Acre. Method: The sample consisted of 33 athletes from the Paralympic Reference Center of Rio Branco, aged between 11 and 54 years, including 20 with intellectual disabilities, 11 with physical disabilities, and 2 with visual disabilities. Measurements included body mass, height, circumferences, and skinfold thickness. Physical performance was evaluated through handgrip strength (using a hydraulic hand dynamometer in kilograms), speed (30-meter test), upper limb power (medicine ball throw test), and maximum oxygen consumption (beep test). Results: Statistical analysis included Pearson’s correlation coefficient and the Kruskal-Wallis test, with significance set at p&lt;0.05, using SPSS software (version 29.0). Body mass index (BMI) and body mass were significantly different between athletes with physical and intellectual disabilities. A negative correlation was observed between aerobic performance (VO2max) and variables such as age (r= -0.441, p= 0.010), BMI (r= -0.590, p&lt;0.001), body mass (r= -0.376, p= 0.031), and body fat index (BFI) (r= -0.688, p&lt;0.001). Additionally, BFI showed a positive correlation with speed performance (r= 0.603, p= 0.001). Conclusion: Body composition significantly influences physical performance variables, indicating that factors such as BMI, body mass, and BFI impact the sports performance of Paralympic athletes.

The effect of High Intensity Interval Training (HIIT) tuja shuttle run model on agility and speed of female volleyball school athletes bank Jatim Surabaya

This study aims to evaluate the effectiveness of high-intensity interval training (HIIT) using the Tuja Shuttle Run model in enhancing agility and speed among volleyball athletes. The research employs a quasi-experimental non-equivalent control group design, involving 24 female volleyball athletes from Bank Jatim Surabaya, consisting of 12 athletes in the treatment group and 12 in the control group. Data were collected through pre-test and post-test assessments to measure changes in agility and speed variables. Data analysis was conducted using paired sample t-test and independent sample t-test. The results indicate that the treatment group experienced an average increase in agility of 3.31% and speed of 5.76% following the HIIT Tuja Shuttle Run intervention, while the control group showed no significant changes. These findings conclude that the HIIT Tuja Shuttle Run model is effective in improving agility and speed among athletes (particularly in speed), thereby supporting the application of this method within training programmed to optimize volleyball athlete performance.

The factors affecting aerobics athletes’ performance using artificial intelligence neural networks with sports nutrition assistance

This work aims to comprehensively explore the influencing factors of aerobics athletes’ performance by integrating sports nutrition assistance and artificial intelligence neural networks. First, a personalized assessment and analysis of athletes’ nutritional needs are conducted, collecting various data including fitness tests, physiological monitoring, and surveys to establish a personalized nutritional needs model for athletes. In order to gain a more comprehensive understanding of the characteristics and requirements of aerobic athletes, exercise data are integrated with nutritional data, and deep learning analysis is performed using neural network algorithms. Moreover, in terms of artificial intelligence technology, optimization algorithms such as ShuffleNet V3 and Inception V3 are employed based on the complexity and characteristics of aerobic exercise. Besides, a channel attention mechanism is introduced to enhance the model’s recognition accuracy. Lastly, a ShuffleNet V3-based aerobic exercise classification and recognition model is proposed. It achieves accurate classification and recognition of aerobic exercise by integrating exercise nutrition, ShuffleNet V3, and attention mechanisms. The results reveal that this model outperforms the Convolutional Neural Network (CNN) baseline algorithm on accuracy and F1 score. On the MultiSports dataset, the proposed model achieves an accuracy of 95.11%, surpassing other models by 2.66%. On the self-built dataset, the accuracy reaches 96.73%, outperforming other algorithms by 2.56%. This indicates that the proposed model demonstrates significant accuracy in aerobics movement classification recognition with sports nutrition assistance, contributing to a more comprehensive intersection of deep learning and sports science research.

Development and validation of a nomogram for predicting motoric cognitive risk syndrome among community-dwelling older adults in China: a cross-sectional study

BackgroundMotoric cognitive risk (MCR) syndrome is characterized by slow gait speed and subjective cognitive complaints (SCC) and increases the risk of dementia and mortality.ObjectiveThis study aimed to examine the clinical risk factors and prevalence of MCR in community-dwelling older adults, with the goal of developing and validating a nomogram model for developing prevention strategies against MCR.MethodsWe enrolled community-dwelling participants aged 60–85 years at Guangwai Community Health Service Center between November 2023 and January 2024. A total of 1,315 older adults who met the criteria were randomly divided into a training set (n = 920) and a validation set (n = 395). By using univariate and stepwise logistic regression analysis in the training set, the MCR nomogram prediction model was developed. The area under the receiver operator characteristic curve (AUC), calibration plots, and Hosmer-Lemeshow goodness of fit test were used to evaluate the nomogram model’s predictive performance, while decision curve analysis (DCA) was used to evaluate the model’s clinical utility.ResultsEducation, physical exercise, hyperlipoidemia, osteoarthritis, depression, and Time Up and Go (TUG) test time were identified as independent risk factors and were included to develop a nomogram model. The model exhibited high accuracy with AUC values of 0.909 and 0.908 for the training and validation sets, respectively. Calibration curves confirmed the model’s reliability, and DCA highlighted its clinical utility.ConclusionThis study constructs a nomogram model for MCR with high predictive accuracy, which provides a reference for large-scale early identification and screening of high-risk groups for MCR.

Psychological Resilience and Complex Movement Coordination Predict the Risk of Falls in Older Adults

AbstractThe prevalence of falls in older individuals worldwide is around 26.5%. There is an urgent need to identify factors antagonistic to advanced age-related falls regarding personal safety, family or nursing care time, and healthcare costs. The aim of the study was to examine the relationship between functional fitness, mental health indicators, and the risk of falling (ROF) in older adults. Thirty-eight older adults (60–94 years; 66% female) were tested individually with the Fullerton Functional Fitness Test (FFFT) after completing five instruments gauging resilience, well-being, satisfaction with life, happiness, and perceived stress. We measured the ROF with the Berg Balance Test. All objective and subjective measures correlated significantly with the ROF. Bayesian linear regressions revealed that complex movement coordination accounted for 68.8%, while resilience accounted for 48.5% of the variance in the ROF. Moreover, resilience was also a mediator between complex movement coordination and ROF. These results suggest that complex movement coordination-developing and resilience-enhancing training strategies might be beneficial in reducing the ROF in older adults.

A Multi-Model Survival Analysis of Lung Cancer Using Parametric Techniques

Lung cancer remains one of the leading causes of cancer-related mortality worldwide, underscoring the critical need for effective prognostic tools. This study utilizes survival analysis to explore the factors that influence the survival outcomes of North Central Cancer Treatment data related to lung cancer. The main goal of this study is to compare and contrast various statistical models, including the Weibull, Exponential, Log-gaussian, Gumbel, and Rayleigh models. We have computed important functions, such as the survival function, the hazard function, and the cumulative hazard function, for all the considered distributions. The Anderson-Darling and Cramer Von-Mises tests, which are Goodness of fit tests, effectively compare and assess various parametric regression survival models. The Weibull survival model is interpreted to be the most effective and efficient way to study the lung cancer dataset, which is concluded upon evaluating the results of Anderson-Darling statistic 0.28745, Cramer Von-Mises statistic 0.0450, Mean Survival Probability 0.9697, Mean Cumulative Survival Probability 0.0303, Akaike Information Criterion 1,650.753 and Bayesian Information Criterion 1623.329 of the Weibull, Exponential, Log-gaussian, Gumbel, and Rayleigh parametric regression survival models.

Improving the Bickel–Rosenblatt global measure of deviation and goodness-of-fit test

We propose a zero-centered version of the Bickel–Rosenblatt statistic and use it to construct goodness of fit tests. We derive the null distributions and power functions of these tests along with their consistency results. A simulation study is carried out to show how the new tests outperform traditional ones.

Binary Logistic Regression Modeling on Household Poverty Status in Bengkulu Province

Binary logistic regression is a statistical method used to analyze the relationship between one or more predictor variables and a binary or dichotomous response variable. Poverty is an issue in every province in Indonesia. One of the provinces with a relatively high poverty rate is Bengkulu Province, ranking seventh in Indonesia with a poverty rate of 14.62%. The Central Bureau of Statistics of Bengkulu Province (2023) explains that efforts to reduce poverty must involve all levels of society. Various government programs and policies in various fields such as health, social, and other areas are continuously being implemented to reduce the number of households classified as poor. Identifying the characteristics of households in Bengkulu Province by poverty status is important to study, as it serves as a reference to ensure that government programs are implemented according to the target. One method that can be used to identify household characteristics is binary logistic regression. This study aims to model the poverty status of households in Bengkulu Province using binary logistic regression and to identify the factors that influence it. The data used are social and economic household data from March 2022. The response variable used is household poverty status (poor and not poor), while the predictor variables include the ownership of toilet facilities, the source of lighting, floor area, family size, and per capita calorie consumption. Modeling is done using binary logistic regression with simultaneous and partial parameter significance tests, as well as model fit tests. The analysis results show that the factors significantly influencing household poverty status in Bengkulu Province are the ownership of toilet facilities, the source of household lighting, floor area, family size, and per capita calorie consumption. The formed binary logistic regression model has a classification accuracy of 89.98% with a sensitivity of 18.34% and a specificity of 98.61%.

Prevalence and correlates of meeting 24-hour movement guidelines and its associations with physical fitness and depressive symptoms among adults: a provincial surveillance in China

Background24-hour movement behaviors integrating physical activity (PA), sedentary behavior (SB), and sleep are important components influencing adults’ health. Canadian 24-hour movement guidelines for adults were launched in 2020. However, there is little evidence on the prevalence and correlates of guideline compliance and its associations with health outcomes among Chinese adults. The purposes of this study were to investigate the prevalence and correlates of meeting 24-hour movement guidelines and examine its association with physical fitness and depressive symptoms among Chinese adults.MethodsA total of 7059 adults (45.73 ± 14.56 years, age range: 20–79 years, 52% female) were recruited by stratified cluster random sampling from health surveillance of Hubei, China, between 25-Jul and 19-Nov 2020 during the COVID-19 pandemic. Participants completed a self-reported questionnaire including movement behaviors (PA, SB, and sleep), depressive symptoms, and demographic information. In addition, eight objectively measured physical fitness tests (body mass index, waist-hip ratio, body fat percentage, vital capacity, handgrip strength, flexibility, balance, and choice reaction time) were conducted. SPSS 28.0 was used to perform Generalized Linear Mixed Models analysis to examine the correlates of movement guidelines and its association with fitness and depressive symptoms.Results25.54% of participants met all three movement guidelines, while 48.62% met only two, 23.10% met one, and 2.75% met none. Participants who were older adults (OR = 2.24; P = .017), unmarried (OR = 0.21; P < .001), and living near PA facilities (OR = 1.58; P = .017) were more likely to meet all three movement guidelines. Meeting more movement recommendations was associated with less likelihood of depressive symptoms (OR = 0.41; P < .001), while no significant associations were observed between meeting 24-hour movement guidelines and physical fitness indicators (P > .05).ConclusionsThe findings of this study indicate the need to promote adherence to all movement guidelines among Chinese adults. Future promoting strategies to meet movement guidelines should emphasize the demographic differences of the targeting population, especially age, marital status, and accessibility of PA facilities. Future interventions should be applied to affirm the effects of compliance with overall 24-hour movement guidelines to mitigate depressive symptoms among adults.

A study to determine the three-dimensional (3D) facial shape characteristics for a successful FFP3 mask fit

A reported 20% of dental staff will fail their fit test for a disposable FFP3 respirator. This needs to be factored into future pandemic workforce and PPE supply planning. At present there are no scientifically or universally accepted facial shape criteria to design and produce facial masks that will fit the entire work force. This study presents differences in facial shape, volume and surface area between individuals who passed on several FFP3 masks (pass group) and participants who passed on only one FFP3 mask (fail group). Three dimensional images of 50 individuals, 25 in each group, were taken at rest and at maximum smile using a DI4D SNAP 6200 camera system. The images were processed, and four “average faces” were produced—pass group at rest, fail group at rest, pass group at maximum smile and fail group at maximum smile. Simple Euclidian linear and angular measurements, geodesic surface distances and volume and surface area enclosed within the mask were analysed. The results of the study show that individuals who are more likely to pass a mask fit test have longer faces, wider mouths, greater geodesic surface distances and a greater volume and surface area of soft tissue enclosed within the mask boundary. This would suggest that some manufactures masks may be too large, and they need to reduce the size of their masks or produce a category of sizes, accepting the fact that one size does not fit all.

The real-time application and effectiveness assessment of an intelligent physical fitness testing system in physical training

An intelligent physical fitness testing system leverages advanced technologies to monitor and evaluate individuals’ fitness levels accurately. It integrates real-time data acquisition, and analysis, to support personalized physical training and health management. This study aims to evaluate the practical application and effectiveness of an intelligent system for real-time physical fitness testing in the context of physical training. Our suggested model employs portable sensing devices and we proposed a novel Northern Goshawk optimization-driven Gate Customized Long Short-Term Memory (NG-GC-LSTM) for enhancing accuracy in evaluating the individuals’ physical fitness levels. Data acquisition involves gathering bio-sensing data from 25 individuals during diverse physical training activities. The Min-Max Scaling algorithm is utilized to pre-process the obtained sensor data. We employed a Short-Time Fourier Transform (STFT) for extracting crucial features from the processed data. In our proposed framework, the NG optimization algorithm iteratively fine-tunes the GC-LSTM architecture for the accurate evaluation of an established intelligent physical fitness testing system. The recommended model is executed in Python software. During the result analysis phase, we assess the efficacy of our model’s performance across a variety of parameters. Additionally, we conduct comparative analyses with existing methodologies. The obtained outcomes demonstrate the efficacy and superiority of the suggested framework.

A Review of the Interpretation of the Canadian Test for Fitness to Stand Trial.

In 1991, Canada introduced Bill C-30 to amend the Criminal Code (mental disorder). Bill C-30 codified accumulated law specifying the criteria for fitness to stand trial. This test was clarified in a landmark case, R v. Taylor, which appeared to accept the limited cognitive capacity test. This explanation has guided the assessment of fitness to stand trial in courts across Canada for three decades. It was recently tested in an Ontario Court of Appeal case, R v. Bharwani, which ruled that the common interpretation of Taylor was insufficient. The court ruled there is one test for fitness, which is contextual and nuanced, and this test is spelled out in the Criminal Code. This will likely change the test and manner for assessing fitness to stand trial in Canada from how it has evolved over the last three decades.

The Safety, Feasibility, and Efficacy of a Structured Individual Exercise Program for Community-Dwelling Stroke Patients.

Stroke is a leading cause of mortality and long-term disability worldwide, often resulting in low levels of physical activity post-discharge. A comprehensive exercise program could be a safe method to increase stroke patients' physical activity and exercise volume. This pilot study examines the effectiveness, safety, and feasibility of a comprehensive exercise regimen for stroke patients residing in the community after discharge. This single-group pilot study included patients who received inpatient rehabilitation for motor impairment following a stroke. Community-dwelling participants engaged in a comprehensive exercise program, which was structured and individualized, consisting of stretching, aerobic exercise, strength training, and balance exercises, conducted under the supervision of a health exercise specialist in a dedicated living lab within the hospital. The program involved 20 sessions, each lasting 50 min, conducted three to five times weekly. The pre- and post-intervention evaluations were comprehensive, including safety and validity assessments, along with physical function tests such as cardiopulmonary exercise testing and various fitness tests (6 min walk test, timed up and go test, chair stand test, figure-of-8 walk test, grip strength test, and sit-and-reach test). Depression levels were assessed using the Geriatric Depression Scale (GDS). A total of 22 subjects were recruited, with 21 completing the study after one dropout due to fatigue and visiting distance. Among the 21 completers, one subject experienced a mild adverse event (hypoglycemia), which was not serious, confirming the program's safety. The exercise participation rate was 95.5%, and the adherence rate averaged 95.2%, with all completers achieving over 80% adherence. Significant improvements were observed in VO2 peak (p = 0.000), 6 min walk test (p = 0.000), timed up and go test (p = 0.000), chair stand test (p = 0.000), figure-of-8 walk test (p = 0.000), and grip strength (p = 0.001). However, changes in the peak respiratory exchange ratio (p = 0.078), sit-and-reach test (p = 0.228) and GDS scores (p = 0.275) were not significant. This study demonstrates that the comprehensive exercise program is sufficiently safe and valid for stroke rehabilitation patients. The program significantly enhances cardiopulmonary endurance, walking ability, balance, muscle strength, muscle endurance, and coordination. Further research with larger sample sizes and control groups is needed to confirm these findings and explore additional benefits.

Optimization of Acetylcholinesterase and Sucrose Concentration using Response Surface Methodology (RSM) Approach in the Development of Paper-Based Biosensor for Pesticides Detection

Excessive use of pesticides, particularly organophosphate pesticides (OPs), to increase agricultural productivity may give a risk to consumers if consumed as these pesticides are neurotoxic substances. To increase agricultural productivity, fruits and vegetables are frequently treated with excessive pesticides, particularly organophosphate pesticides (OPs). Several methods have been studied and developed to identify pesticide residue in crops, however the standard laboratory procedures for OPs analysis involves the use of HPLC or GC-MS. These methods are complex in sample preparation and require expert labor to operate. Paper-based biosensors are low-cost platforms for fast detection in the field, offering an easy and reusable option. In this study, a colorimetric paper-based biosensor based on immobilizing acetylcholinesterase (AChE) using sol-gel silica matrices and indoxyl acetate is developed. The Response Surface Methodological (RSM) approach was used to optimize AChE concentration and sucrose as a stabilizer, allowing simultaneous optimization of multiple variables using smaller-size datasets. This study used the central composite design (CCD) fractional factorial design using Design Expert 7.0 software. A quadratic model was selected to represent both immobilization yield and relative AChE activity responses. The model was evaluated using ANOVA values and Lack of Fit test which confirmed that the quadratic models for both responses are suitable for experimental data. Validation of the model demonstrates that the predictive model accurately represents of the validation research. The Limit of Detection (LoD) of the biosensor for pure profenofos pesticide after a 20-minute incubation time is 1 ppm, as indicated by a 32.55 % decrease in color intensity. After a week of storage at 4 °C, the biosensor showed a loss of 5.92 % on immobilization yield and 2.55 % on relative activity indicating a good storage stability. The mean value of lettuce samples was 200.60 ± 1.2 a.u, with pesticide concentration of 2.57 ± 1.2 ppm (n=3). HIGHLIGHTS Incorporating AChE into the sol gel matrices is a great way to enhance the stability of the enzymatic colorimetric pesticide detection. Response Surface Methodology (RSM) is considered as useful for optimizing response level of AChE and sucrose. Combination of optimum AChE and sucrose concentration show beneficial effect on the stability of the biosensor. GRAPHICAL ABSTRACT

Acute Effects of Squat and Ballistic Jump Exercises on Judo-Specific Performance, Handgrip Strength, and Perceived Exertion in Young Male Judokas

This study aimed to examine the acute effects of squat and ballistic jump exercises during warm-ups on judo-specific performance in young male judokas. Using a randomized crossover design, 10 sub-junior male judokas (age: 12.9 ± 0.7 years) completed three conditions: a controlled warm-up with only judo-specific exercises and two experimental warm-ups including either a three-repetition maximum (RM) back squat (with ~90% 1RM load) or ballistic jumps (squat jumps, scissor jumps, and double-leg bounds) in addition to judo-specific warm-ups. Following each warm-up condition, participants performed the Special Judo Fitness Test (SJFT), with heart rate measured immediately and one minute post-test. Handgrip strength and ratings of perceived exertion (RPE) were recorded after the SJFT. Both squat and ballistic jump exercises significantly improved judo-specific performance compared to the control condition, with large effect sizes (ESs). The number of throws in set 2 (p = 0.001, ηp2 = 0.65, large ES), total throws (p &lt; 0.001, ηp2 = 0.70, large ES), and the SJFT index (p &lt; 0.001, ηp2= 0.65, large ES) all showed significant improvements. Regarding the throw in set 2, significant improvements were observed after both squat (p = 0.003, Hedge’s g = 1.78, large ES) and ballistic jump exercises (p = 0.010, Hedge’s g = 1.44, large ES) compared to the control condition. Similarly, total throws were significantly higher in the squat (p = 0.003, Hedge’s g = 1.51, large ES) and ballistic jump (p &lt; 0.001, Hedge’s g = 1.37, large ES) conditions compared to the control condition. Furthermore, the SJFT index showed notable improvements following squat (p = 0.010, Hedge’s g = 0.80, moderate ES) and ballistic jump (p &lt; 0.001, Hedge’s g = 0.90, moderate ES) conditions compared to control conditions. However, squat exercises led to a significant reduction in right-hand grip strength (p &lt; 0.001, ηp2 = 0.58, large ES) [p = 0.008, Hedge’s g = 0.19, trivial ES for squat vs. control; p = 0.014, Hedge’s g = 0.23, small ES for squat vs. ballistic jump], with no differences observed in left-hand grip strength or RPE scores (p &gt; 0.05). In conclusion, the integration of squat and ballistic jump exercises into warm-up protocols has been shown to significantly improve judo-specific performance in young male judokas without eliciting an increase in RPE values. However, careful consideration should be given when incorporating squat exercises, as they may lead to localized handgrip fatigue (reduced grip strength due to muscle exhaustion), which could affect performance in grip-dependent techniques.

Impact of New York City’s 4-year multi-component natural experiment to improve elementary school physical education on student cardiorespiratory fitness

BackgroundSchool physical education is an important population-level health intervention for improving youth fitness. This study estimated the impact of New York City’s PE Works program - which included providing PE teachers, training for classroom teachers, and administrative/ teacher support for PE - on student cardiorespiratory fitness as measured by the FitnessGram’s 15-meter PACER test for aerobic capacity.MethodsThis longitudinal study (2014/15-2018/19) includes 581 elementary schools (n = 315,999 4th /5th -grade students; 84% non-white; 74% who qualify for free or reduced-price meals, a proxy for socioeconomic status). We apply the parametric g-formula to address schools’ time-varying exposure to intervention components and time-varying confounding.ResultsAfter four years of staggered PE Works implementation, 49.7% of students/school (95% CI: 42.6%, 54.2%) met age/sex-specific Healthy Fitness Zone (HFZ) aerobic capacity standards set by the FitnessGram. Had PE Works not been implemented, we estimate 45.7% (95% CI: 36.9%, 52.1%) would have met aerobic capacity HFZ standards. Had PE Works been fully implemented in all schools from the program’s inception, we estimate 57.4% (95% CI: 49.1%, 63.3%) would have met aerobic capacity HFZ standards. Adding a PE teacher, alone, had the largest impact (6.4% (95% CI: 1.0, 12.0) increase).ConclusionPE Works positively impacted student cardiorespiratory fitness. Mandating and funding multicomponent PE programs is an important public health intervention to increase children’s cardiorespiratory fitness.

Development of Physical Fitness Evaluation Criteria for Women in Compulsory Isolation for Drug Rehabilitationn in Compulsory Isolation for Drug Rehabilitation

Background: The issue of physical and mental rehabilitation for drug users lacks a comprehensive and reliable system for evaluating it difficult to conduct a reasonable assessment of their physical fitness.The establishment of physical fitness evaluation criteria specifically tailored for female drug users serves as the fundamental basis for developing precise and individualized exercise prescriptions.Methods:This study used the national physical fitness test method to assess the physical fitness of female drug addicts undergoing mandatory rehabilitation. The principal component analysis method was employed to calculate the weight of each individual physical fitness test indicator, which was then combined with the indicator T score to obtain a comprehensive evaluation of the physical fitness of these individuals.On this basis, a single physical fitness index T-score scoring equation was determined for two groups of women (with and without diseases) undergoing compulsory isolation and drug rehabilitation, stratified by age (under 30 years old, 31-40 years old, 41-50 years old, 51-60 years old).Results: The weights of various indicators and the combined weights of secondary indicators in the physical fitness evaluation index system for female addicts undergoing compulsory isolation for detoxification have been established. Conclusion:Based on the total score calculated by combining the T-score of each individual physical fitness indicator with its corresponding weight, a comprehensive rating system with four levels - "excellent, good, qualified, and unqualified" - has been set.

Assessment of the Psychometric Properties of the Mask Usability Scale: A Measure of the Perceived Usability of N95 Respirators Among Healthcare Students and Staff.

To test the reliability and construct validity of the Mask Usability Scale in healthcare students and staff. A methodological study involving repeated measures. The study included two batches of participants: (1) 283 university nursing students and (2) 1753 participants composed of students (61%) and clinical staff (39%). All participants underwent N95 respirator fit tests and user seal checks. They also responded to the Mask Usability Scale, which comprises 11 items evaluated using Likert scales. The internal consistency was assessed using Cronbach's alpha and item-total correlation test. Test-retest reliability was evaluated by the intraclass correlation coefficient (ICC). The factor structure was initially identified through exploratory factor analysis (EFA), laying the groundwork for the model. This approach was followed by confirmatory factor analysis (CFA) to ensure the model fits with the standardised solution. Excluding items 9, 10 and 11, the study showed satisfactory internal consistency, evidenced by a Cronbach's alpha of 0.842 for the eight-item scale from the combined samples. Factors, such as 'Heat', 'Breathability', 'Tightness' and 'Ease in talking' showed moderate to strong correlations. The test-retest reliability in the batch one sample was acceptable with ICCs ranging between 0.69 and 0.71 for different models. The EFA and fit indices supported a two-factor structure. The first factor 'Comfort and Usage' included 'Heat', 'Breathability', 'Tightness', 'Ease in talking' and 'Prolonged use', which were keys for the usability of N95 respirators. The second factor 'Suitability' encompassed 'Itchy', 'Easily displaced' and 'Ear soreness'. The variance explained by the first and second factors was 49% and 12%, respectively, with a strong inter-factor correlation. The CFA results were satisfactory with fit metrics (NFI = 0.967, IFI = 0.969, TLI = 0.952, CFI = 0.969, RMSEA = 0.078 with 90% CI [0.069, 0.086] and p < 0.001) and a chi-squared to df ratio of 13.58. The eight-item mask usability scale exhibited satisfactory internal consistency and construct validity in both healthcare student and staff samples. The primary concern in the purchase policy of N95 respirators for clinical use is to strike the right balance between usability and fit rate (passing % of fit testing). Our study solidified the concept of quantifying the usability of respirators. With that mask usabilityscale measurement, a provision of benchmark and reference for the design and selection of respirators would be possible. This validated scale has significant implications for senior management in clinical settings and respirator manufacturers regarding the N95 respirator purchase policy and design. The results indicatedthe psychometric propertiesof mask usability scale in measuring the usability of N95 respirators. This scale is particularly valuable for assessing the perceptions of healthcare students and staff of factors, namely, 'Heat', 'Breathability', 'Tightness', 'Ease in talking', 'Prolonged use', 'Itchy', 'Easily displaced' and 'Ear soreness' concerning the use of N95 respirators. We adhered to EQUATOR guidelines following the STROBE statement. No patient or public contribution. ISRCTN registry: ISRCTN40115047.