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Copyright of Retos: Nuevas Perspectivas de Educación Física, Deporte y Recreación is the property of Federacion Espanola de Asociaciones de Docentes de Educacion Fisica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study investigates the Human Development Index (HDI), a composite measure developed by the United Nations Development Program to evaluate human development through life expectancy, education, and income. This research aims to assess the health status and services across 17 cities in West Azerbaijan Province, Iran, using multi-criteria decision-making (MCDM) techniques: TOPSIS, MOORA, ARAS, and COPRAS. Eight health indicators, including primary medical care centers, laboratories, active beds, pharmacies, general practitioners, specialists, subspecialists, and dentists, were used for the ranking. The Shannon entropy method was applied to determine the weights of these indicators. The results reveal significant disparities in health service distribution, with Urmia, Khoy, and Miandoab having the best health services, while Poldasht, Chaldoran, and Chaypareh are the most deprived. The study employs the Spearman rank correlation coefficient to validate the rankings and utilizes the utility interval aggregation method to enhance reliability. Managerial insights suggest that policymakers should prioritize equitable distribution of health services to mitigate disparities and promote balanced regional development. Effective resource allocation and targeted interventions in underserved areas are crucial for improving overall human development. [ABSTRACT FROM AUTHOR]

This review paper comprehensively analyzes the prognosis of rotating machines (RMs), focusing on mechanical-flaw and remaining-useful-life (RUL) estimation in industrial and renewable energy applications. It introduces common mechanical faults in rotating machinery, their causes, and their potential impacts on RM performance and longevity, particularly in wind, wave, and tidal energy systems, where reliability is crucial. The study outlines the primary procedures for RUL estimation, including data acquisition, health indicator (HI) construction, failure threshold (FT) determination, RUL estimation approaches, and evaluation metrics, through a detailed review of published work from the past six years. A detailed investigation of HI design using mechanical-signal-based, model-based, and artificial intelligence (AI)-based techniques is presented, emphasizing their relevance to condition monitoring and fault detection in offshore and hybrid renewable energy systems. The paper thoroughly explores the use of physics-based, data-driven, and hybrid models for prognosis. Additionally, the review delves into the application of advanced methods such as transfer learning and physics-informed neural networks for RUL estimation. The advantages and disadvantages of each method are discussed in detail, providing a foundation for optimizing condition-monitoring strategies. Finally, the paper identifies open challenges in prognostics of RMs and concludes with critical suggestions for future research to enhance the reliability of these technologies. [ABSTRACT FROM AUTHOR]

The handling of the HIV pandemic in Greece has reached a critical point. Epidemiological data over the last decade show a halt in its declining rate. The Greek state established the pre-exposure prophylaxis (PrEP) hoping to boost the fight against HIV. This paper documents the necessity of implementing PrEP through analyzing the epidemiological indicators of the last decade in Greece and comparing them with other European countries, emphasizing the goals of the oint United Nations program on HIV/AIDS (UNAIDS). Strategies are then proposed to overcome the obstacles arising from the economic, political and social conditions in the implementation of PrEP in Greece. The data were searched from the international literature and from databases of the World Health Organization (WHO), the UNAIDS, the European Center for Disease Prevention (ECDC) and the National Public Health Organization of Greece (EODY). Until the definitive treatment of HIV with the preparation of the corresponding vaccine and taking under consideration the effectiveness of antiretroviral drugs, it is concluded that carrying out prevention programs is the only way to handle the pandemic further. Following the example of many EU countries by implementing prevention programs, such as PrEP, Greece can achieve the goals of the oint United Nations program until 2030. [ABSTRACT FROM AUTHOR]

Objective(s): Maternal health indicators, especially for pregnant mothers, are among the most important health indicators for any country. Given the implementation of the health transformation plan in the service delivery system in Iran, it was expected that there would be a significant improvement in the quality and quantity of services provided to mothers in recent years. Therefore, the aim of this research was to investigate the effect of implementing healthcare reform on maternal health indicators in East Azerbaijan province, Iran. Methods: This was a quasi-experimental study. The research population consisted of people living in villages in East Azerbaijan province - Tabriz district, Iran; with active health centers from 2007 to 2016, including a sample size of 200 mothers per year. Villages were randomly selected as clusters. Data collection tool was a questionnaire and all data were analyzed by SPSS version 22 statistical software. Results: The findings showed that the mean age of mothers during the study period ranged from 25 to 27 years. The number of pregnancies before the reform was 1.39 and after the reform, it was 1.20 which was statistically significant. Examination of the insurance status of pregnant mothers showed that before the reform, 6.4% of rural residents were uninsured, while after the reform, all of them were covered. In terms of laboratory services, 97.7% of mothers underwent routine tests in the first trimester, and 90.5% underwent routine tests in the second trimester. Additionally, over 99% of mothers had undergone at least one ultrasound, with an average of 2.56 ultrasound appointments. Conclusion: The implementation of the healthcare reform increased the insurance coverage of pregnant mothers and the utilization of services such as ultrasound. This initiative led to a reduction in maternal and neonatal mortality rates and a decrease in the rate of natural childbirth. [ABSTRACT FROM AUTHOR]

Copyright of Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective(s): Maternal health indicators, especially for pregnant mothers, are among the most important health indicators for any country. Given the implementation of the health transformation plan in the service delivery system in Iran, it was expected that there would be a significant improvement in the quality and quantity of services provided to mothers in recent years. Therefore, the aim of this research was to investigate the effect of implementing healthcare reform on maternal health indicators in East Azerbaijan province, Iran. Methods: This was a quasi-experimental study. The research population consisted of people living in villages in East Azerbaijan province - Tabriz district, Iran; with active health centers from 2007 to 2016, including a sample size of 200 mothers per year. Villages were randomly selected as clusters. Data collection tool was a questionnaire and all data were analyzed by SPSS version 22 statistical software. Results: The findings showed that the mean age of mothers during the study period ranged from 25 to 27 years. The number of pregnancies before the reform was 1.39 and after the reform, it was 1.20 which was statistically significant. Examination of the insurance status of pregnant mothers showed that before the reform, 6.4% of rural residents were uninsured, while after the reform, all of them were covered. In terms of laboratory services, 97.7% of mothers underwent routine tests in the first trimester, and 90.5% underwent routine tests in the second trimester. Additionally, over 99% of mothers had undergone at least one ultrasound, with an average of 2.56 ultrasound appointments. Conclusion: The implementation of the healthcare reform increased the insurance coverage of pregnant mothers and the utilization of services such as ultrasound. This initiative led to a reduction in maternal and neonatal mortality rates and a decrease in the rate of natural childbirth.

The rapid development of computer technologies has significantly impacted various sectors, including healthcare. The ability to collect, process, and visualize medical data in real time is becoming increasingly important, especially for managing chronic conditions such as epilepsy. This paper presents a web-based application designed for real-time monitoring of health indicators, enabling healthcare professionals to track patient data efficiently. The system automates the process of collecting data from fitness trackers, transmitting it via a mobile device to a server, and visualizing it in a web application. Its architecture employs a thin-client model with Node.js for backend logic and React.js for the user interface, ensuring scalability and responsiveness. Key features include real-time data visualization, historical trend analysis, and the ability to export health metrics for further examination. The system architecture follows a modular approach, with a clear separation of concerns between the client-side, server-side, and database components. MongoDB is used as the database provider, offering flexibility in handling large volumes of health data. The system underwent extensive testing in two stages. During the first stage, real-world data collection demonstrated an average data transmission time of less than 112 ms, ensuring compliance with real-time requirements. In the second stage, stress testing with up to 100 simultaneous users showed an average server response time of 145.8 ms and a 95th percentile response time of 167.1 ms. These results confirm the system’s robustness and suitability for deployment in medical facilities. Future work aims to enhance the system by incorporating advanced real-time alert mechanisms and additional health metrics, such as oxygen saturation and activity levels, to provide comprehensive monitoring. The presented solution showcases the potential of integrating modern web technologies into healthcare, contributing to improved patient outcomes and more efficient workflows for medical professionals.

ObjectiveIn order to monitor the health status of a centrifugal pump in real time, this study proposes a model for the real-time identification of the degradation state of centrifugal pumps. MethodsFirst, based on the operating parameters and degradation mechanism of the centrifugal pump, a combined weighting model using a combination of subjective and objective weights is used to calculate the combined weights, then a health index during the degradation process of the centrifugal pump is constructed. Second, based on the existing pump degradation data, a degradation identification model based on the genetic algorithm-group method of data handling (GA-GMDH) algorithm is proposed.ResultsThe reliability of the GA-GMDH monitoring model is relatively high, with a root mean square error of 0.029216 between the output values of the health index and the actual values. Based on the model's output results, the accuracy of degradation state identification is 93.333%. ConclusionThe results of this study can provide valuable references for the health monitoring and maintenance operation management of centrifugal pumps.

Abstract Background Promoting older workers’ health in the context of increasing labor force participation and skill shortages is crucial. Examining job resource profiles offers a promising approach to understanding how to promote and maintain the health of older workers within the workplace. However, it is unclear how different job resources interact within distinct worker subgroups. Thus, this study explores the association between the job resource profiles of distinct subgroups and various health indicators among older workers in Europe. Methods Data from 4,079 older workers (age range: 50–60 years, 57% female) from waves 6 and 8 of the Survey of Health, Ageing and Retirement in Europe (SHARE) were analyzed. Latent profile analysis was employed to identify distinct job resource profiles using social support, recognition, job promotion, autonomy, and development opportunities. Associations between these profiles and various health indicators were examined, alongside the sociodemographic and socioeconomic characteristics associated with each profile. Results Four distinct job resource profiles emerged: (I) average job resource workers (n = 2170, 53%), (II) high social job resource workers (n = 983, 24%), (III) low job resource workers (n = 538, 13%), and (IV) autonomous decision-making workers (n = 388, 10%). Workers in the (II) high social job resource profile had the highest socioeconomic status and reported the best self-perceived health, lowest depressive symptoms, and fewest limitations and chronic diseases. Conversely, workers in the (III) low job resource profile had the second-lowest socioeconomic status and reported the poorest health outcomes. Surprisingly, older workers with high autonomy (profile IV) had the lowest socioeconomic status and the second worst self-perceived health. This may be because they perceive themselves as autonomous while lacking support and recognition. Conclusion There is wide variation in the level and composition of resources available to older workers in the workplace. The most vulnerable subgroups, such as low job resource workers (profile III) and autonomous decision-making workers (profile IV), could benefit from tailored workplace health promotion interventions, such as support from supervisors or peers. Strengthening older workers’ job resources, including social support and recognition, can improve their health and contribute to them remaining in the workforce.

Abstract Background Previne Brasil is a new way of financing Primary Health Care (PHC) in Brazil that places users of public health services at the center of the system’s analysis and attention through the use of seven performance indicators. This study aims to analyze the performance of Primary Health Care in Brazil under the new financing model (Previne Brasil) in the period from the first four months of 2022 to the first four months of 2023. Methods This is a territorial ecological study using secondary data from the Primary Care Health Information System (SISAB). Seven performance indicators were included and analyzed according to Brazil, its regions, states and capitals. A comparative descriptive analysis was carried out between the spatial units. Results Of the seven indicators analyzed, only one (Proportion of pregnant women tested for syphilis and HIV) reached the proposed target considering the average of the four-month periods evaluated (target: 60%; Observed: 62.5%). The Northeast was the region with the best performance, surpassing the target in three of the seven indicators (prenatal consultations, tests for syphilis and HIV in pregnant women and dental care for pregnant women). The states and capitals showed progressive improvement in the performance indicators over the four quarters analyzed, although unevenly between the indicators. The indicators related to hypertension and diabetes were the worst. The Final Synthetic Indicator (FSI) showed an increase in the median over the four quarters (4.78; 5.65; 6.02 6.29), which represents an increase of 1.51 in the indicator between the first four months of 2022 and the first four months of 2023. Conclusion Although there have been improvements in the performance of Primary Health Care in Brazil, the achievement of the agreed targets for the indicators seems a long way off. The socio-spatial inequalities in the indicators reflect the country’s health complexity and reinforce the need for policies that take into account the local-regional context.

Simple Summary: Mycotoxins are secondary metabolites of molds, primarily Penicillium, Fusarium, and Aspergillus species, that may be present in food and feed. Reports indicate that up to 25% of the world's cereal crops could be contaminated with these fungal toxins. Synbiotics, products that synergistically combine probiotics and prebiotics, can reduce harmful metabolites in the gastrointestinal tract by metabolizing or adsorbing toxic substances, including mycotoxins. In the present study, turkeys were fed diets contaminated with ochratoxin A and supplemented with probiotic or synbiotic preparations. The addition of probiotic and synbiotic preparations based on lactic acid bacteria strains, inulin, and Saccharomyces cerevisiae yeast to ochratoxin A-contaminated diets in commercial turkey farming may improve health status and reduce mycotoxin accumulation in poultry organs and tissues. The aim of this study was to evaluate carcass quality and analyze gastrointestinal functional status, ochratoxin A (OTA) accumulation in tissues and organs, and the health status of turkeys fed diets contaminated with OTA and supplemented with synbiotic preparations in comparison with commercial probiotic feed additives. The research involved 120 female BIG 6 turkeys, divided into six treatment groups (five replicates, four birds per replicate). Wheat naturally contaminated with OTA (662.03 μg/kg) was used in turkey diets. Turkeys in group 1 received an OTA-contaminated diet without additives. Groups 2 and 3 received 0.4 g/kg of probiotic preparation BioPlus 2B or Cylactin. Groups 4, 5, and 6 received 0.5 g/kg of synbiotics S1, S2, or S3. The following parameters were monitored: growth performance, carcass quality, gastrointestinal tract structure and digesta pH, health status, and concentrations of OTA in the blood and tissues of turkeys. The study found no significant differences in the growth performance and carcass quality of turkey. However, the introduction of probiotics or synbiotics into OTA-contaminated feed mixtures resulted in a reduced pH of the digesta in certain sections of the turkey digestive tract (p < 0.05). Additionally, the tested synbiotic additives significantly reduced liver weight in turkeys at weeks 6 and 15 (p < 0.05). The addition of probiotic and synbiotic preparations based on lactic acid bacteria strains, inulin, and S. cerevisiae yeasts to OTA-contaminated diets in commercial turkey farming may improve health status (p < 0.05) and reduce mycotoxin accumulation in organs and tissues of poultry (p < 0.05). [ABSTRACT FROM AUTHOR]

Predicting the remaining useful life (RUL) of bearings is crucial for maintaining the reliability and availability of mechanical systems. Constructing health indicators (HIs) is a fundamental step in the methodology for predicting the RUL of rolling bearings. Traditional HI construction often involves determining the degradation stage of the bearing by extracting time–frequency domain features from raw data using a priori knowledge and setting artificial thresholds; this approach does not fully utilize the vibration information in the bearing data. In order to address the above problems, this paper proposes an Asymmetric Residual Shrinkage Convolutional Autoencoder (ARSCAE) model. The asymmetric structure of the ARSCAE model is characterized by the soft thresholding of signal features in the encoder part to achieve noise reduction. The decoder part consists of convolutional and pooling layers for data reconstruction. This model can directly construct HIs from the original vibration signals collected, and comparisons with other models show that it constructs better HIs from the original vibration signals. Finally, experiments on the FEMTO dataset show that the results indicate that the HIS constructed by the ARSCAE model has better lifetime prediction capability compared to other methods. [ABSTRACT FROM AUTHOR]

Accurately predicting the state of health (SOH) of lithium-ion batteries is crucial for optimizing battery performance and achieving efficient energy management, especially in electric vehicle applications. However, the existing incremental capacity analysis methods, which are mostly based on curve multi-parameter analysis, still have limitations in terms of computation, prediction accuracy, and adaptability to actual operating conditions. This paper conducts an in-depth analysis of the incremental capacity (IC) curve and proposes a feature parameter based on the area under the IC curve. By incorporating charge and discharge data, a weighted health indicator sequence is constructed and three mathematical models are proposed to link health indicators with cycle number, capacity, and SOH. The feasibility of using impedance as an additional input is also explored, despite the challenges of measurement, revealing its potential applications. Validation of the models with different datasets shows that the proposed method achieves both average relative error and root mean square error within 5%, outperforming other methods in terms of minimizing error and ensuring stability. The results demonstrate that the area-weighted incremental capacity method significantly enhances battery health monitoring accuracy, contributing to the development of sustainable and efficient energy storage systems. [ABSTRACT FROM AUTHOR]

To accurately predict the remaining useful life (RUL) of rolling bearings under limited data and fluctuating load conditions, we propose a new method for constructing health indicators (HI) and a transfer learning prediction framework, which integrates Convolutional Neural Networks (CNN), Gated Recurrent Units (GRU), and Multi-head attention (MHA). Firstly, we combined Convolutional Neural Networks (CNN) with Gated Recurrent Units (GRU) to fully extract temporal and spatial features from vibration signals. Then, the Multi-head attention mechanism (MHA) was added for weighted processing to improve the expression ability of the model. Finally, a new method for constructing Health indicators (HIs) was proposed in which the noise reduction and normalized vibration signals were taken as a HI, the L1 regularization method was added to avoid overfitting, and the model-based transfer learning method was used to realize the RUL prediction of bearings under small samples and variable load conditions. Experiments were conducted using the PHM2012 dataset from the FEMTO-ST research institute and XJTU-SY dataset. Three sets of 12 migration experiments were conducted under three different operating conditions on the PHM2012 dataset. The results show that the average RMSE of the proposed method was 0.0443, indicating high prediction accuracy under variable loads and small sample conditions. Three different operating conditions and two sets of four migration experiments were conducted on the XJTU-SY dataset, and the results show that the average RMSE of the proposed method was 0.0693, verifying the good generalization of the model under variable load conditions. In summary, the proposed HI construction method and prediction framework can effectively reduce the differences between features, with high stability and good generalizability. [ABSTRACT FROM AUTHOR]

Healthcare systems worldwide face escalating costs and demographic changes, necessitating effective evaluation tools to understand their underlying challenges. Switzerland's high-quality yet costly healthcare system underscores the need for robust assessment methods. Existing international rankings often lack transparency and comparability, highlighting the value of structured frameworks like the Health System Performance Assessment (HSPA) by the World Health Organization (WHO). This framework evaluates healthcare systems across multiple dimensions including governance, resource generation, financing, and service delivery. This paper aims to integrate Swiss healthcare indicators from the Swiss Health Observatory (Obsan) into the HSPA framework, addressing the central research question: How can these indicators be mapped to the HSPA framework, and what insights does this integration provide? Our methodology includes selecting and categorizing Obsan indicators, manually mapping them to HSPA sub-functions, and validating these mappings using word embeddings and cosine similarity. An R Shiny application was developed for interactive visualization. Results demonstrate accurate indicator assignment, enabling intuitive visualization and enhancing data structuring. [ABSTRACT FROM AUTHOR]

Background: Promoting older workers' health in the context of increasing labor force participation and skill shortages is crucial. Examining job resource profiles offers a promising approach to understanding how to promote and maintain the health of older workers within the workplace. However, it is unclear how different job resources interact within distinct worker subgroups. Thus, this study explores the association between the job resource profiles of distinct subgroups and various health indicators among older workers in Europe. Methods: Data from 4,079 older workers (age range: 50–60 years, 57% female) from waves 6 and 8 of the Survey of Health, Ageing and Retirement in Europe (SHARE) were analyzed. Latent profile analysis was employed to identify distinct job resource profiles using social support, recognition, job promotion, autonomy, and development opportunities. Associations between these profiles and various health indicators were examined, alongside the sociodemographic and socioeconomic characteristics associated with each profile. Results: Four distinct job resource profiles emerged: (I) average job resource workers (n = 2170, 53%), (II) high social job resource workers (n = 983, 24%), (III) low job resource workers (n = 538, 13%), and (IV) autonomous decision-making workers (n = 388, 10%). Workers in the (II) high social job resource profile had the highest socioeconomic status and reported the best self-perceived health, lowest depressive symptoms, and fewest limitations and chronic diseases. Conversely, workers in the (III) low job resource profile had the second-lowest socioeconomic status and reported the poorest health outcomes. Surprisingly, older workers with high autonomy (profile IV) had the lowest socioeconomic status and the second worst self-perceived health. This may be because they perceive themselves as autonomous while lacking support and recognition. Conclusion: There is wide variation in the level and composition of resources available to older workers in the workplace. The most vulnerable subgroups, such as low job resource workers (profile III) and autonomous decision-making workers (profile IV), could benefit from tailored workplace health promotion interventions, such as support from supervisors or peers. Strengthening older workers' job resources, including social support and recognition, can improve their health and contribute to them remaining in the workforce. [ABSTRACT FROM AUTHOR]

Gait speed is increasingly recognized as an important health indicator. However, gait analysis in clinical settings often encounters inconsistencies due to methodological variability and resource constraints. To address these challenges, GaitKeeper uses artificial intelligence (AI) and augmented reality (AR) to standardize gait speed assessments. In laboratory conditions, GaitKeeper demonstrates close alignment with the Vicon system and, in clinical environments, it strongly correlates with the Gaitrite system. The integration of a cloud-based processing platform and robust data security positions GaitKeeper as an accurate, cost-effective, and user-friendly tool for gait assessment in diverse clinical settings. [ABSTRACT FROM AUTHOR]

The macroeconomic dimensions of health production function in Greece were studied, by linking doctors’ number, per capita health expenditures, population percentage living in material deprivation conditions, pollutant emissions and alcohol consumption with health indicators. Articles were searched, by recording data from databases (Hellenic-European Statistical Service, Organisation for Economic Co-operation and Development [OECD]) and medical personnel number, per capita health expenditures, population segment living in poverty, pollutant emissions (expressed as CO2/capita) and alcohol use variation were correlated with changes in infant mortality, healthy life years and life expectancy. By above methodology, strong negative correlation of doctors’ number with infant mortality (0.90% approximately) (1960–2015) and significantly positive corresponding in life expectancy change (0.94% approximately) (2000–2015) were captured. The strong negative association of per capita health expenditure on infant mortality (84% for years 2000–2015 and 96% for years 1989–2011), 90% negative correlation of people living in material deprivation conditions with healthy life years were highlighted (2008–2015), as well as negative correlation (about 95%) of environmental pollution, expressed as per capita CO2 emitted amount, with life expectancy change (2007–2015) and the 95% approximate connection of alcohol consumption with life expectancy (2005–2014). The studied cases and correlation with longitudinal health indicators’ modification document macroeconomic dimensions of health production function and measures to mitigate negative consequences/enhance beneficial effects on life quality are proposed. [ABSTRACT FROM AUTHOR]

The effects of the Covid-19 pandemic have underscored for the Philippines, in particular, and all countries in general, the importance of a resilient health care system to be able to manage health emergencies and disasters. The study aimed to do a situational analysis of the health sector during the COVID-19 pandemic in the Central Visayas, Philippines. The study collected data from national government agencies in the Philippines. The article identifies gaps in the health care system which may have affected not only COVID-19 outcomes but other health indicators which was highlighted due to the pandemic. The study provides health managers and policymakers information that could be used to promote reforms in the health sector to be able to manage future pandemics and health emergencies both in local and national levels. [ABSTRACT FROM AUTHOR]

This paper presents the development, testing, and spatial variation of an innovative India Health Index. Unlike previous approaches that focused on specific health aspects (e.g., health resources, child health, or health coverage), our index takes a comprehensive and multi-dimensional approach. It covers indicators across various life stages: child, adolescent, and adult. It encompasses six domains influencing health: socio-cultural factors, health status, health determinants (both risk and protective factors), household environment, and health system and policy. We used data from the latest round of the National Family Health Survey and employed Principal Component Analysis for constructing the India Health Index. Subsequent statistical tests confirmed its internal reliability and construct validity. External validity was indicated by its association with under-five mortality rates, and the sub-national human development index for India. Spatial analyses revealed significant inter-district and inter-state variation in India Health Index scores. The findings underscore the utility of the India Health Index as a measurement tool and its potential for tracking progress and policy intervention for improving health equity in India. [ABSTRACT FROM AUTHOR]

Background: Previne Brasil is a new way of financing Primary Health Care (PHC) in Brazil that places users of public health services at the center of the system's analysis and attention through the use of seven performance indicators. This study aims to analyze the performance of Primary Health Care in Brazil under the new financing model (Previne Brasil) in the period from the first four months of 2022 to the first four months of 2023. Methods: This is a territorial ecological study using secondary data from the Primary Care Health Information System (SISAB). Seven performance indicators were included and analyzed according to Brazil, its regions, states and capitals. A comparative descriptive analysis was carried out between the spatial units. Results: Of the seven indicators analyzed, only one (Proportion of pregnant women tested for syphilis and HIV) reached the proposed target considering the average of the four-month periods evaluated (target: 60%; Observed: 62.5%). The Northeast was the region with the best performance, surpassing the target in three of the seven indicators (prenatal consultations, tests for syphilis and HIV in pregnant women and dental care for pregnant women). The states and capitals showed progressive improvement in the performance indicators over the four quarters analyzed, although unevenly between the indicators. The indicators related to hypertension and diabetes were the worst. The Final Synthetic Indicator (FSI) showed an increase in the median over the four quarters (4.78; 5.65; 6.02 6.29), which represents an increase of 1.51 in the indicator between the first four months of 2022 and the first four months of 2023. Conclusion: Although there have been improvements in the performance of Primary Health Care in Brazil, the achievement of the agreed targets for the indicators seems a long way off. The socio-spatial inequalities in the indicators reflect the country's health complexity and reinforce the need for policies that take into account the local-regional context. [ABSTRACT FROM AUTHOR]

Exercise and dietary habits are important ways to maintain human health, and many people hope to ensure their own physical health through reasonable exercise and maintenance methods. Sports health analysis algorithms serve this purpose, and most intelligent motion detection software is also designed based on this algorithm. This article suggested that the performance of this algorithm can be improved through efficient spatiotemporal graph convolution, which enhanced its ability to collect data from various sources, analyze user physical conditions and exercise habits, and provide reasonable suggestions. This article also verified through comparative experiments that the motion health analysis algorithm based on efficient spatiotemporal graph convolution had stronger prediction accuracy than a single motion health analysis algorithm. The average prediction accuracy of these two algorithms was 92.93% and 84.81%, respectively. The experimental results fully demonstrated that the method proposed in this paper was very suitable for assisting in the construction of sports health analysis algorithms. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The effects of the Covid-19 pandemic have underscored for the Philippines, in particular, and all countries in general, the importance of a resilient health care system to be able to manage health emergencies and disasters. The study aimed to do a situational analysis of the health sector during the COVID-19 pandemic in the Central Visayas, Philippines. The study collected data from national government agencies in the Philippines. The article identifies gaps in the health care system which may have affected not only COVID-19 outcomes but other health indicators which was highlighted due to the pandemic. The study provides health managers and policymakers information that could be used to promote reforms in the health sector to be able to manage future pandemics and health emergencies both in local and national levels.

The increase in overweight and obesity among individuals with Intellectual and Developmental Disabilities (IDD) also increases the deterioration of functionality and the risk of developing chronic diseases. Physical exercise has been identified as an effective strategy for reducing overweight and obesity and promoting health. The aim of this study was to investigate the effects of an indoor and outdoor exercise programme on individuals with IDD. Were split by convenience into three groups twenty-one adults with IDD (43.04 ± 11.18 years): i) an indoor training group (IG; N=7; 24-week machine-based gym intervention), ii) an outdoor training group (OG; N=7; 24-week outdoor intervention with low-content materials), and iii) a control group (CG; N=7). Various variables were assessed, including indicators of health and neuromuscular capacity. The Shapiro-Wilk (n

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Introduction: The aim of the study is to assess changes in body mass index (BMI), functional fitness, satisfaction with and quality of life among women 60+ years after participating in a 9-month organised health training programme. Material and methods: Research on a group of 74 women aged 60-83 years (M = 67.8; SD = 5.1) was conducted twice, at the beginning and after 9 months of the health training programme (90 minutes, twice a week). The following tools were used in the research: SECA model 764 device, Fullerton functional fitness test, the World Health Organization Quality of Life questionnaire, and the satisfaction with life scale. Calculations were performed using the Statistica 13.1 program, via Pearson's and Spearman's correlation coefficients as well as Student's t-test for dependent measurements and the Wilcoxon paired test. Interactive repeated measures analysis of variance was also used. The assumed level of significance was α = 0.05. Results: Comparing the results before and after implementing the health training programme, it was found that the average BMI value decreased (p < 0.001), while the functional fitness indicators, including the tests: 30-second chair stand (p < 0.001), 30-second arm curl (p < 0.001), back scratch (p = 0.001) and two-minute step-in-place (p = 0.002), increased. Between the first and second measurement, differences in quality of life profiles were also demonstrated, with 3 aspects of quality of life intensifying (somatic, psychological, and environmental), the psychological aspect increasing the most. Conclusions: The obtained results confirmed the positive impact of the 9-month health training programme on the BMI, functional fitness, and quality of life of women above the age of 60 years. [ABSTRACT FROM AUTHOR]

Accurately predicting the remaining useful life (RUL) is crucial for the safety and stability of battery systems. Considering the inherent challenges in directly measuring the capacity of lithium‐ion batteries during operation, this paper proposes an online hybrid cascaded data‐driven prediction algorithm for RUL. Health indicators (HIs) are extracted from the charge–discharge voltage and incremental capacity curves, following which gray correlation analysis is employed to quantitatively assess the relevance between the HIs and batteries' capacities. Redundancy of HIs is eliminated through kernel principal component analysis, which enhancing the efficiency of subsequent analysis. The proposed framework incorporates the sparrow search algorithm‐based kernel extreme learning machine (SSA‐KELM) as the first‐level prediction model, establishing the relationship between HIs and capacities. The bidirectional long short‐term memory (BiLSTM) is utilized as the secondary‐level model, which integrates the preliminary capacity predictions of SSA‐KELM. Finally, experimental validation using battery datasets from NASA and Oxford showed that the method has remarkable generalization ability and superior prediction accuracy. Quantitatively, the RMSE and MAPE of NASA batteries are within 0.03, while the errors of Oxford batteries are within 0.003. The RUL prediction errors of all lithium‐ion batteries are within two cycles. [ABSTRACT FROM AUTHOR]

Simple Summary: Natural feed additives have gained significant scientific attention as growth-promoting substances instead of synthetic antibiotics. The objectives of this study were to develop and investigate the physicochemical properties and effects of Arabic gum–nano montmorillonite (AGNM) compared to monensin as feed additives in Holstein dairy cows. However, the practical application of gum Arabic as a production enhancer for ruminant feeding has not been widely adopted. In this study, the AGNM additive showed great promise for improving rumen fermentation, increasing nutrient digestibility and utilization, and benefiting the environment. The exploration of natural alternatives to antibiotics for enhancing productivity and performance in dairy cows is a crucial objective in farm animal management. This is the first study aimed at developing and evaluating the physicochemical properties and effects of Arabic gum–nano montmorillonite (AGNM) compost compared to ionophore monensin as feed additives on rumen fermentation, blood metabolites, and milk production of Holstein dairy cows. In a replicated 4 × 4 Latin square design, four multiparous mid-lactation Holstein dairy cows with an average body weight of 520 ± 15 kg were enrolled. The dietary treatments included a control diet (basal diet without feed additives), monensin diet [a basal diet supplemented with 35 mg/kg dry matter (DM) monensin], and AGNM diets comprising basal diet supplemented with two levels: low (L-AGNM) at 1.5 g/kg DM, and high (H-AGNM) at 3 g/kg DM. AGNM as a feed additive demonstrated promising physiochemical parameters, including containing highly bioactive components (α-amyrin and lupeol), functional groups (OH and Si-O), and essential mineral contents (Mg2+). Supplementations with H-AGNM significantly improved ruminal (p = 0.031) concentrations of total volatile fatty acids (VFAs), acetic (p = 0.05) and butyric (p = 0.05), enhanced (p < 0.05) digestibility of fiber and organic matter, while decreased (p = 0.013) estimated methane production. However, an increase (p = 0.04) in blood high-density lipoprotein levels and decrease (p < 0.05) in concentrations of creatinine (CREA), bilirubin (BILT), cholesterol (CHOL), and sodium (Na) were observed with H-AGNM supplementation. Both monensin and H-AGNM improved (p = 0.008) feed efficiency compared to L-AGNM; however, neither AGNM nor monensin affected the milk composition or energy status indicators of the dairy cows. The findings of this study highlight the potential of AGNM as a natural candidate to replace monensin in enhancing ruminal VFA production, nutrient digestibility, feed efficiency, blood metabolites, and milk yield in dairy cows. [ABSTRACT FROM AUTHOR]

The development of health indicators to measure healthy life expectancy (HLE) is an active field of research aimed at summarizing the health of a population. Although many health indicators have emerged in the literature as critical metrics in public health assessments, the methods and data to conduct this evaluation vary considerably in nature and quality. Traditionally, health data collection relies on population surveys. However, these studies, typically of limited size, encompass only a small yet representative segment of the population. This limitation can necessitate the separate estimation of incidence and mortality rates, significantly restricting the available analysis methods. In this article, we leverage an extract from the French National Hospital Discharge database to define health indicators. Our analysis focuses on the resulting Disease-Free Life Expectancy (Dis-FLE) indicator, which provides insights based on the hospital trajectory of each patient admitted to hospital in France during 2008–2013. Through this research, we illustrate the advantages and disadvantages of employing large clinical datasets as the foundation for more robust health indicators. We shed light on the opportunities that such data offer for a more comprehensive understanding of the health status of a population. In particular, we estimate age-dependent hazard rates associated with sex, alcohol abuse, tobacco consumption, and obesity, as well as geographic location. Simultaneously, we delve into the challenges and limitations that arise when adopting such a data-driven approach. [ABSTRACT FROM AUTHOR]

Purpose: An adolescent health information system is a relevantly new concept, especially in humanitarian settings. This article aims to map the available adolescent health indicators collected in selected humanitarian settings, identify the available data sources, and determine the alignment between these indicators and the draft list of priority indicators for adolescent health measurement recommended by the Global Action for the Measurement of Adolescent Health Advisory Group. Methods: We selected five countries experiencing humanitarian crises- Myanmar, Nigeria, Palestine, Ukraine, and Yemen. We identified the adolescent health indicators collected in each country using document analysis and a purposive sampling approach. We reviewed the primary population-based surveys used to gather adolescent health data and noted the most recent year each survey was conducted. The identified indicators were then categorized by measurement domains and specific areas of adolescent health. Results: The Multiple Indicator Cluster Survey and Demographic Health Survey were conducted in all five countries selected, but three out of five countries have not administered either within the last five years. Yemen and Palestine only included married women in their sample sizes, and no one younger than 15 was interviewed. Indicators most commonly assess reproductive health, tobacco use, and adolescent fertility. Limited data was found on younger adolescents, males, water, sanitation, hygiene, disability, and nutrition indicators. Discussion: Adolescent health information in humanitarian crises requires more frequent surveys, including all adolescent age groups, and unique data collection methodologies. The current surveys used to measure adolescent health indicators have limited ability to be inclusive to all adolescents. It is important to establish a list of priority indicators deemed essential in humanitarian settings and relevant ways to collect them. [ABSTRACT FROM AUTHOR]

• This study examines national population data for 10 health indicators. • Only 1.05% of adult Americans are completely healthy according to population norms. • Only 5.55% are completely healthy according to clinical criteria for caseness. • These findings seem to imply an epidemic of medicalization and overdiagnosis. This study investigated the proportion of the U.S. population classified as healthy based on 10 common indicators, examined in two ways: (1) above or below (in the healthy direction) the sample median (termed "normal"), and (2) below diagnostic cut-off points for clinical caseness or high risk (termed "ideal"). Data are from the 2017-March 2020 round of the National Health and Nutrition Examination Survey (NHANES). Sample sizes ranged from 3,956 to 8,961 for respective health indicators, with a total of 3,102 respondents for two weighted multi-item measures described below. Measures included the Alameda 5 health behaviors (smoking, drinking exercising, sleeping, and body mass index) and five standard biomarkers (systolic and diastolic blood pressure, resting heart rate, fasting glucose, and total cholesterol). Besides point prevalences for the normal and ideal categories for each indicator, we also calculated the proportion healthy for all 10 indicators, again calculated both ways, termed "meta-normal" and "meta-ideal." The prevalence of meta-normality was 1.05%, suggesting that hardly any adult Americans are completely healthy according to population norms. Findings for meta-ideality showed that while most Americans are not clinical cases for any respective indicator, only 5.55% met the official criteria for being healthy according to all 10 indicators. Most Americans appear healthy according to nearly all key health indicators and biomarkers, according to "normal" or "ideal" criteria. However, the proportion healthy according to all measures is extremely small. Relatively few U.S. adults are completely healthy according to clinical criteria (meta-ideal), and even fewer are completely healthy according to population norms (meta-normal). Results are interpreted through sociological writing on medicalization. [ABSTRACT FROM AUTHOR]

IntroductionThe One Health concept has proposed an integrated and unified approach aiming for health balance and enhancement by recognizing the interdependence of human, animal, and environmental health. The COVID-19 pandemic has pushed global One Health initiatives and policy improvement toward preventive measures for future pandemics, particularly of zoonotic origin. Such a scenario may be particularly relevant for South America, which is considered highly vulnerable due to its natural biodiversity superposed to socioeconomic and environmental issues, demanding effective methods and indicators for proper One Health strategies and goals that are aligned with macroregional contexts.MethodsAccordingly, the present study aimed to assess the One Health Index (OHI) in South American countries, along with potential interactions with socioeconomic indicators. The results obtained using clustering analysis and permutational multivariate analysis of variance (PERMANOVA) have revealed a positive association between the OHI and the Human Development Index (HDI) but not with gross domestic product (GDP).ResultsAlthough South American countries with political stability, robust investment in health, and progressive policies have shown a higher OHI, better environmental health is not associated with better human and animal health. In addition, although the Amazon biome— spanning 9 of the 12 South American countries—has positively impacted environmental health, this benefit contrasts with the rudimentary local human health systems, highlighting the complexity of One Health within the South American context. The lack of stronger indicators for animal health was also considered an important weak point for a true OHI assessment. Nonetheless, countries with more developed livestock have presented better animal health, which may not reflect an overall animal health indicator, as companion and wildlife animal health indicators were not available.DiscussionAlthough lower (within-country) scale analysis such as states and metropolitan areas may better shape internal differences, the study herein has clearly shown One Health inequalities and challenges among South American countries. Equally important, forests and other natural areas in developing countries, particularly the Amazon, should receive incentives to promote sustainable economic growth. This approach would help prevent sacrificing environmental health for the benefit of human and livestock animal health.

Summary: The attainment of the noble objective of Universal Health Coverage (UHC)- ‘leaving no one behind’ necessitates sufficient financial resources, an ample supply of skilled healthcare professionals, and the availability of essential services as part of a basic package This paper presents an analysis of the health system, health seeking behaviours and health service utilization en route to UHC in Pakistan. We have used the UHC 14 tracer indicators of service coverage to see where Pakistan stands, what are the gaps and what needs to be done. Pakistan clearly is lagging behind its neighboring countries. The country's health system ought to work on health seeking behaviours and broader determinants of health. The pursuit of UHC demands a shared responsibility and collective action, with stakeholders from different sectors uniting their efforts and expertise. Together, they can establish robust systems, design comprehensive policies, allocate adequate resources, and implement interventions that transcend disciplinary boundaries.

Abstract Background Feed supplements, including essential trace elements are believed to play an important role in augmenting fish immune response. In this context, selenium nanoparticles (SeNPs) in fish diets via a green biosynthesis strategy have attracted considerable interest. In this investigation, selenium nanoparticles (SeNPs, 79.26 nm) synthesized from the green microalga Pediastrum boryanum were incorporated into Nile tilapia diets to explore its beneficial effects on the immune defense and intestinal integrity, in comparison with control basal diets containing inorganic Se source. Nile tilapia (No. 180, 54–57 g) were fed on three formulated diets at concentrations of 0, 0.75, and 1.5 mg/kg of SeNPs for 8 weeks. After the trial completion, tissue bioaccumulation, biochemical indices, antioxidant and pro-inflammatory cytokine-related genes, and intestinal histological examination were analyzed. Results Our finding revealed that dietary SeNPs significantly decreased (P

Objective(s): The use of statistical methods to reach the clustering and ranking of health in the society can give a proper view of the state of health in Iranian provinces. The aim of the current research was to cluster and rank Iranian provinces based on some health indicators. Methods: This was a descriptive study. Clustering and ranking Iranian provinces were carried out according to several items such as the number of employees working in faculties of medical sciences, doctors, paramedics, hospitals, active beds, primary health care providers, laboratories, rehabilitation centers, nuclear medicine centers, clinics and emergency centers. The data were collected from the statistical yearbooks of the provinces. Clustering analysis and data visualizations were performed in R software and ranks were obtained using Topsis software. Results: The results showed that the provinces of Ilam, Yazd, Semnan, South Khorasan, Zanjan, Ardabil, Fars, Kohgiluyeh and Boyer Ahmad, and Chaharmahal and Bakhtiari had the highest health scores and belonged to the third cluster. Their ranks were 1 to 9 respectively. In the first cluster the following provinces were observed: Qom, Tehran, Alborz, and Hamedan with scores of 0.552, 0.540, 0.460, and 0.36 respectively indicating that these provinces had the lowest health scores and their ranks were 28 to 31. The other provinces appeared on the second cluster and ranked 10 to 27 with almost equal scores. Conclusion: In order to achieve health equity, the indicators should be improved in provinces belonged to the first cluster to in order to achieve the standard per capita.

Knowledge of the health condition of urban trees is fundamental for making decisions regarding management and resource allocation. The objective of this study was to determine the current health status of the trees at the National Institute of Astrophysics, Optics, and Electronics (INAOE) in San Andres Cholula, Mexico. Five health indicators previously used in urban forests were assessed. The structure and diversity indicator indicated the existence of 2210 trees, mostly (58.8 %) of small size (< 20 cm average diameter at breast height), 20 botanical families, and 32 tree species. The crown condition and its variables indicated high foliage transparency (> 40 %) in some of its species and low percentages of dieback. Live crown ratio and crown density were moderate in eight and six species, respectively. The tree damage indicator showed the existence of 44 damaging agents in 956 trees (43.3 % of the total), highlighting the ball moss (Tillandsia recurvata), the felt fungus of evergreen ash (Septobasidium sp.) associated with an armored scale, the same fungus also affecting white cedar (Hesperocyparis lusitanica) in association with another scale (a new record), and two bark beetles, Hylesinus aztecus in evergreen ash, and Phloesinus sp. in white cedar. Regarding the mortality indicator, 75 trees (3.3 %) were recorded. Finally, the soil condition indicated that the pH was close to neutral, with electrical conductivity values above 2 dS m-1 and a low beneficial mycoflora population. All these factors, together with the imbalance in tree diversity, high planting density, compacted soils, and the presence of risky trees, are negatively affecting the health of INAOE's tree community. [ABSTRACT FROM AUTHOR]

This research aimed for the first time to identify the essential welfare problems on 46 goat dairy farms in Vojvodina,based on the goat AWIN welfare protocol. The study showed that space allowance per goat was 1.55, 1.86 and 2.50 m2/goat (large, medium, small-sized farms, respectively). Most farms possessed the soil floor and straw as a flooring material. The small and medium farms more allowed access to the outdoor area. Contrary, large-sized farms mostly kept goats in fully housed systems with reduced opportunities for the goats to express their natural behavior. Management procedures were significantly different (p < 0.05) between the investigated farms. Differences were mainly in bedding, feeding and culling strategies. Low productivity was the main cause of culling in all farm types. Small-sized farms carried out more often disbudding (42.9%) in comparison with medium (21.4%) and large-sized ones (14.3%). Group level observation showed that the main areas of concern were associated with hair coat condition and kneeling at the feeding rack (p < 0.05). Inadequate BCS, udder asymmetry and claw overgrowth were frequently recorded. The prevalence of thin and fat goats was highest in large-sized farms All farm size categories and management systems showed certain welfare weaknesses. Thus, the findings highlighted the need for higher implementation of animal welfare principles and improvement of management techniques to meet the welfare requirements of dairy goats. [ABSTRACT FROM AUTHOR]

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