With the fast development of blockchain technology in latest years, its application in scenarios that require privacy, such as health area, became encouraged and widely discussed. This paper presents an architecture to ensure the privacy of health-related data, which are stored and shared within a blockchain network in a decentralized manner, through the use of encryption with the RSA, ECC and AES algorithms. Evaluation tests were performed to verify the impact of cryptography on the proposed architecture in terms of computational effort, memory usage and execution time. The results demonstrate an impact mainly on the execution time and on the increase in the computational effort for sending data to the blockchain, however, justifiable considering the privacy and security provided with the architecture and encryption.

Identifying health care equity indicators is an important first step in integrating the concept of equity into assessments of health care system performance, particularly in emergency care. We conducted a systematic review of administrative data-derived health care equity indicators and their association with socio-economic determinants of health (SEDH) in emergency care settings. Following PRISMA-Equity reporting guidelines, Ovid MEDLINE, EMBASE, PUBMED and Web of Science were searched for relevant studies. The outcomes of interest were indicators of health care equity and the associated SEDH they examine. Among 29 studies identified, 14 equity indicators were identified and grouped into four categories that reflect the patient emergency care pathway. Total emergency department (ED) visits and ambulatory care sensitive condition-related ED visits were the two most frequently used equity indicators. Despite some conflicting results, all identified SEDH (social deprivation, income, education level, social class, insurance coverage and health literacy) are associated with inequalities in access to and use of emergency care. In conclusion, the use of administrative data-derived indicators combined with identified SEDH could improve healthcare equity measurement in emergency care settings across health care systems worldwide.

BACKGROUND Epidemiological sciences have been evolving at an exponential rate paralleled only by the comparable growth within the discipline of data science. Digital epidemiological studies are playing a vital role in medical science analytics for the past few decades. To date, there are no published attempts at deploying the use of real-time analytics in connection with the disciplines of Dentistry or Medicine. AIMS AND OBJECTIVES We deployed a real-time statistical analysis in connection with topics in Dental Anatomy and Dental Pathology represented by the maxillary sinus, posterior maxillary teeth, related oral pathology. The purpose is to infer the digital epidemiology based on a continuous stream of raw data retrieved from Google Trends database. MATERIALS AND METHODS Statistical analysis was carried out via Microsoft Excel 2016 and SPSS version 24. Google Trends database was used to retrieve data for digital epidemiology. Real-time analytics and the statistical inference were based on encoding a programming script using Python high-level programming language. A systematic review of the literature was carried out via PubMed-NCBI, the Cochrane Library, and Elsevier databases. RESULTS The comprehensive review of databases of the literature, based on specific keywords search, yielded 491813 published studies. These were distributed as 488884 (PubMed-NCBI), 1611 (the Cochrane Library), and 1318 (Elsevier). However, there was no single study attempting real-time analytics. Nevertheless, we succeeded in achieving an automated real-time stream of data accompanied by a statistical inference based on data extrapolated from Google Trends. CONCLUSION Real-time analytics are of considerable impact when implemented in biological and life sciences as they will tremendously reduce the required resources for research. Predictive analytics, based on artificial neural networks and machine learning algorithms, can be the next step to be deployed in continuation of the real-time systems to prognosticate changes in the temporal trends and the digital epidemiology of phenomena of interest.

This paper presents PrognosEase; a software that provides an easier way to produce different types of run-to-failure data mimicking real-world conditions to simplify prognosis studies in terms of data collection and improvement in ML degradation modelling process. Different types of degradation types made available to meet different types of applications. Besides, some primary ML tests were performed to ensure that complexity patterns of real systems could be observed in the training/testing predictions attitude. This paper also presents the impacts, limitations and potential improvements of the data generator.

During the last two years the COVID-19 pandemic has affected the world population in several ways. An important increase in mental health problems is a consequence of this pandemic that is ubiquitous worldwide. In this work we study the effect of the pandemic on the mental health of a population of teenagers and youth based on the analysis of natural language processing, machine learning algorithms and expert knowledge. The data analysed was obtained from a chat helpline called Safe time from theIt Get’s Better Foundation in Chile. The data consists of 10,986 conversations gathered from 2018 until 2020 between volunteers from the foundation and users of the platform. We compared the conversationsbefore and during the pandemic in terms of their thematic content. Our analysis found: a significantdecrease in self-image appreciation during the pandemic; a significant decrease in the quality of personalrelationships during the pandemic, and a significant increase of performance appreciation.

Physical inactivity increases the risk of many adverse health conditions, including the world’s major non-communicable diseases, such as coronary heart disease, type 2 diabetes, and breast and colon cancers, shortening life expectancy. There are minimal medical care and personal trainers’ methods to monitor a patient’s actual physical activity types. To improve activity monitoring, we propose an artificial-intelligence-based approach to classify the physical movement activity patterns. In more detail, we employ two deep learning (DL) methods, namely a deep feed-forward neural network (DNN) and a deep recurrent neural network (RNN) for this purpose. We evaluate the proposed models on two physical movement datasets collected from several volunteers who carried tri-axial accelerometer sensors. The first dataset is from the UCI machine learning repository, which contains 14 different activities-of-daily-life (ADL) and is collected from 16 volunteers who carried a single wrist-worn tri-axial accelerometer. The second dataset includes ten other ADLs and is gathered from 8 volunteers who placed the sensors on their hips. Our experiment results show that the RNN model provides the accuracy performance compared to the state-of-the-art methods in classifying the fundamental movement patterns with an overall accuracy of 84.89% and an overall F1-score of 82.56%. Our results indicate that the proposed method will provide the medical doctors and trainers a promising way to precisely track and understand a patient’s physical activities for better treatment.

Although the universal health coverage (UHC) is pursued by many countries, not all countries with UHC include dental care as their benefits. Japan, with its long-held tradition of UHC, has covered dental care as essential benefit and majority of dental care services are provided to all patients with minimal copayment. Being under the UHC, the scope of services as well as prices are regulated by the uniform fee schedule and dentists submit claims according to the uniform format and fee schedule. The author analyzes the publicly available dental health insurance claims data as well as a sampling survey on dental hygiene and illustrates how Japan’s dental care is responding to the challenges of the population ageing.

The holistic approach of One Health, which sees human, animal, plant, and environmental health as a unit, rather than discrete parts, requires not only interdisciplinary cooperation, but standardized methods for communicating and archiving data, enabling participants to easily share what they have learned and allow others to build upon their findings.Ongoing work by NCBI and the GenomeTrakr project illustrates how open data platforms can help meet the needs of federal and state regulators, public health laboratories, departments of agriculture, and universities. Here we describe how microbial pathogen surveillance can be transformed by having an open access database along with Best Practices for contributors to follow. First, we describe the open pathogen surveillance framework, hosted on the NCBI platform. We cover the current community standards for WGS quality, provide an SOP for assessing your own sequence quality and recommend QC thresholds for all submitters to follow. We then provide an overview of NCBI data submission along with step by step details. And finally, we provide curation guidance and an SOP for keeping your public data current within the database. These Best Practices can be models for other open data projects, thereby advancing the One Health goals of Findable, Accessible, Interoperable and Re-usable (FAIR) data.

During the last years, significant initiatives have been launched for the dissemination of Open Access as part of the Open Science movement. Nevertheless, the other major pillars of Open Science such as Open Research Data (ORD) and Open Peer Review (OPR) are still in an early stage of development among the communities of researchers and stakeholders. The present study sought to unveil the perceptions of a medical and health sciences community about these issues. Through the investigation of researchers’ attitude, valuable conclusions can be drawn, especially in the field of medicine and health sciences, where an explosive growth of scientific publishing exists. A quantitative survey was conducted based on a structured questionnaire, with 51.8% response rate (215 responses out of 415 electronic invitations). The participants in the survey agreed with the ORD principles However they ignored basic terms like FAIR (Findable, Accessible, Interoperable and Reusable) and appeared incentive to permit the exploitation of their data. Regarding OPR, participants expressed their agreement, implying their interest for a trustworthy evaluation system. Conclusively, researchers urge to receive proper training for both ORD principles and OPR processes which combined with a reformed evaluation system will enable them to take full advantage of the opportunities that arise from the new scholar publishing and communication landscape.

Advances in machine learning (ML) and artificial intelligence (AI) are transforming the way we treat patients in ways not even imagined a few years ago. Cancer research is at the forefront of this movement. Infertility, though not a life-threatening condition, affects around 15% of couples trying for a pregnancy. Increasing availability of large datasets from various sources creates an opportunity to introduce ML and AI into infertility prevention and treatment. At present in the field of assisted reproduction, very little is done in order to prevent infertility from arising, with the main focus put on treatment when often advanced maternal age and low ovarian reserve make it very difficult to conceive. A shift from this disease-centric model to a health centric model in infertility is already taking place with more emphasis on the patient as an active participator in the process. Poor quality and incomplete data as well as biological variability remain the main limitations in the widespread and reliable implementation of AI in the field of reproductive medicine. That said, one of the areas where this technology managed to find a foothold is identification of developmentally competent embryos. More work is required however to learn about ways to improve natural conception, the detection and diagnosis of infertility, and improve assisted reproduction treatments (ART) and ultimately, develop clinically useful algorithms able to adjust treatment regimens in order to assure a successful outcome of either fertility preservation or infertility treatment. Progress in genomics, digital technologies and advances in integrative biology has had a tremendousimpact on research and clinical medicine. With the rise of ‘big data’, artificial intelligence, and the advances in molecular profiling, there is an enormous potential to transform not only scientific research progress, but also clinical decision making towards predictive, preventive, and personalized medicine. In the field of reproductive health, there is now an exciting opportunity to leverage these technologies and develop more sophisticated approaches to diagnose and treat infertility disorders. In this review, we present a comprehensive analysis and interpretation of different innovation forces that are driving the emergence of a system approach to the infertility sector. Here we discuss recent influential work and explore the limitations of the use of Machine Learning models in this rapidly developing area.

Health self-tracking is an ongoing trend as software and hardware evolve, making the collection of personal data not only fun for users but also increasingly interesting for public health research. In a quantitative approach we studied German health self-trackers (N=919) for differences in their data disclosure behavior by comparing data showing and sharing behavior among peers and their willingness to donate data to research. In addition, we examined user characteristics that may positively influence willingness to make the self-tracked data available to research and propose a framework for structuring research related to self-measurement. Results show that users' willingness to disclose data as a "donation" more than doubled compared to their "sharing" behavior (willingness to donate= 4.5/10; sharing frequency= 2.09/10). Younger men (up to 34 years), who record their vital signs daily, are less concerned about privacy, regularly donate money, and share their data with third parties because they want to receive feedback, are most likely to donate data to research and are thus a promising target audience for health data donation appeals. The paper adds to qualitative accounts of self-tracking but also engages with discussions around data sharing and privacy.

Mental health issues can have significant impacts on individuals and communities and hence on social sustainability. There are several challenges facing mental health treatment, however, more important is to remove the root causes of mental illnesses because doing so can help prevent mental health problems from occurring or recurring. This requires a holistic approach to understanding mental health issues that are missing from the existing research. Mental health should be understood in the context of social and environmental factors. More research and awareness are needed, as well as interventions to address root causes. The effectiveness and risks of medications should also be studied. This paper proposes a big data and machine learning-based approach for the automatic discovery of parameters related to mental health from Twitter data. The parameters are discovered from three different perspectives, Drugs & Treatments, Causes & Effects, and Drug Abuse. We used Twitter to gather 1,048,575 tweets in Arabic about psychological health in Saudi Arabia. We built a big data machine learning software tool for this work. A total of 52 parameters were discovered for all three perspectives. We defined 6 macro-parameters (Diseases & Disorders, Individual Factors, Social & Economic Factors, Treatment Options, Treatment Limitations, and Drug Abuse) to aggregate related parameters. We provide a comprehensive account of mental health, causes, medicines and treatments, mental health and drug effects, and drug abuse, as seen on Twitter, discussed by the public and health professionals. Moreover, we identify their associations with different drugs. The work will open new directions for social media-based identification of drug use and abuse for mental health, as well as other micro and macro factors related to mental health. The methodology can be extended to other diseases and provides a potential for discovering evidence for forensics toxicology from social and digital media.

Abstract: Understanding social media networks and group interactions are crucial to the ad-vancement of linguistic and cultural behaviour. This includes the manner in which people ac-cessed advice on health, especially during the global lockdown periods. Some people turned to social media to access information on health where most activities were curtailed with isolation rules, especially for older generations. Facebook public pages, groups and verified profiles, using "senior citizen health", "older generations", and "healthy living" keywords were analysed over a 12-month period to analyse the engagement promoting good mental health. CrowdTangle was used to source English language status updates, photo and video sharing information which resulted in an initial 116,321 posts and 6,462,065 interactions Data analysis and visualisation were used to explore large datasets, including natural language processing for “Message” content discovery, word frequency and correlational analysis and co-word clustering. Preliminary results indicate strong links to healthy aging information shared on social media which showed correla-tions to global daily confirmed case and daily death totals. The results can be used to identify public concerns early on and address mental health issues in the senior generation on Facebook.

The present grievous situation of the tuberculosis disease can be improved by efficient case management and timely follow-up evaluations. With the advent of digital technology this can be achieved by quick summarization of the patient-centric data. The aim of our study was to assess the effectiveness of the ODK Scan paper-to-digital system during testing period of three months. A sequential, explanatory mixed-method research approach was employed to elucidate technology use. Training, smartphones, application and 3G enabled SIMs were provided to the four field workers. At the beginning, baseline measures of the data management aspects were recorded and compared with endline measures to see the impact of ODK Scan. Additionally, at the end, users’ feedback was collected regarding app usability, user interface design and workflow changes. 122 patients’ records were retrieved from the server and analysed for quality. It was found that ODK Scan recognized 99.2% of multiple choice bubble responses and 79.4% of numerical digit responses correctly. However, the overall quality of the digital data was decreased in comparison to manually entered data. Using ODK Scan, a significant time reduction is observed in data aggregation and data transfer activities, however, data verification and form filling activities took more time. Interviews revealed that field workers saw value in using ODK Scan, however, they were more concerned about the time consuming aspects of the use of ODK Scan. Therefore, it is concluded that minimal disturbance in the existing workflow, continuous feedback and value additions are the important considerations for the implementing organization to ensure technology adoption and workflow improvements.

(1) Background: New sensor technologies in wearables and other consumer health devices open up promising opportunities to collect real-world data. As cardiovascular diseases remain reason number one for disease and mortality worldwide, cardiology offers potent monitoring use-cases with patients in their out-of-hospital daily routine. Therefore, the aim of this systematic review is to investigate the status quo of studies monitoring patients with cardiovascular risks and patients suffering from cardiovascular diseases in a telemedical setting using not only a smartphone-based app, but also consumer health devices such as wearables and other sensor-based devices. (2) Methods: A literature search was conducted across five databases and the results were examined according to the study protocols, technical approaches and qualitative and quantitative parameters measured. (3) Results: Out of 166 articles, 8 studies were included in this systematic review. These cover interventional and observational monitoring approaches in the area of cardiovascular diseases, heart failure and atrial fibrillation using various app, wearable and health device combination. (4) Conclusions: Depending on the researcher’s motivation a fusion of apps, patient reported outcome measures and non-invasive sensors can be orchestrated in a meaningful way adding major contributions to monitoring concepts for both, individual patients and larger cohorts.

Health information technology has been widely used in healthcare, which has contributed a huge amount of data. Health data has four characteristics: high volume; high velocity; high variety and high value. Thus, they can be leveraged to i) discover associations between genes, diseases and drugs to implement precision medicine; ii) predict diseases and identify their corresponding causal factors to prevent or control the diseases at an earlier time; iii) learn risk factors related to clinical outcomes (e.g., patients’ unplanned readmission), to improve care quality and reduce healthcare expenditure; and iv) discover care coordination patterns representing good practice in the implementation of collaborative patient-centered care. At the same time, there are major challenges existing in data-driven healthcare research, which include: i) inefficient health data exchanges across different sources; ii) learned knowledge is biased to specific institution; iii) inefficient strategies to evaluate plausibility of the learned patterns and v) incorrect interpretation and translation of the learned patterns. In this paper, we review various types of health data, discuss opportunities and challenges existing in the data-driven healthcare research, provide solutions to solve the challenges, and state the important role of the data-driven healthcare research in the establishment of smart healthcare system.

Over the last decade, there has been a renewed interest in oral health workforce planning. The purpose of this review is to examine oral health workforce planning models on supply, demand and needs, mainly in respect to their data sources, modelling technique and use of skill mix. A search was carried out on PubMed, Web of Science, and Google Scholar databases for published scientific articles on oral health workforce planning models between 2010 to 2020. No restrictions were placed on the type of modelling philosophy, and all studies including supply, demand or needs based models were included. Rapid review methods guided the review process. Twenty-three studies from 15 different countries were included in the review. A majority were from high income countries (n=17). Dentists were the sole oral health workforce group modelled in 13 studies; only five studied included skill mix (allied dental personnel) considerations. The most common application of modelling was a workforce to population ratio or a needs-based demand weighted variant. Nearly all studies presented weaknesses in modelling process due to the limitations in data sources and/or non availability of necessary data to inform oral health workforce planning. Skill mix considerations in planning models were also limited to horizontal integration within oral health professionals. Planning for the future oral health workforce is heavily reliant on quality data being available for supply, demand and needs models. Integrated methodologies that expand skill mix considerations and account for uncertainty are essential for future planning exercises.

Currently, there are several challenges that Cloud-based health-care Systems, around the world, are facing. The most important issue is to ensure security and privacy or in other words to ensure the confidentiality, integrity and availability of the data. Although the main provisions for data security and privacy were present in the former legal framework for the protection of personal data, the General Data Protection Regulation (GDPR) introduces new concepts and new requirements. In this paper, we present the main changes and the key challenges of the General Data Protection Regulation, and also at the same time we present how the Cloud-based Security Policy methodology proposed in [1] could be modified in order to be compliant with the GDPR and how Cloud environments can assist developers to build secure and GDPR compliant Cloud-based health Systems. The major concept of this paper is, primarily, to facilitate Cloud Providers in comprehending the framework of the new General Data Protection Regulation and secondly, to identify security measures and security policy rules for the protection of sensitive data in a Cloud-based Health System, following our risk-based Security Policy Methodology that assesses the associated security risks and takes into account different requirements from patients, hospitals, and various other professional and organizational actors.

The rate of fires, and particularly residential-fires, is a serious concern in industrialized countries. However, there is considerable uncertainty regarding the reported numbers of residential-fire incidents as official figures are based on fires reported to fire response agencies only. This population-based study aims to quantify the total number of residential-fire incidents regardless of reporting status. The cohort comprised linked person-level data from Fire and Rescue New South Wales (FRNSW) and health system and death records. It includes all persons residing at a residential address in New South Wales, Australia, that experienced a fire between 1 January 2005 – 31 December 2014. Capture-Recapture method was used to estimate the underreporting number of residential fire-related incidents. Over the study period, 43,707 residential-fire incidents were reported to FRNSW and there were 2,795 residential fire-related health service utilization of which 2,380 were not reported. Using Capture-Recapture method, the total number of residential-fire incidents was estimated at 267,815 to 319,719 which is more than six times the official records. This study found that 15% of residential-fire incidents that were identified in health administrative dataset were reported. The residential-fire incidents that were not reported occurred mainly in socio-economically disadvantaged areas among the males and adults.

Background Several quantitative studies have found a decline in physical activity in response to COVID-19 pandemic restrictions. The aim of the present study was to use large-scale free text survey data to qualitatively gain a more in-depth understanding of the impact of the COVID-19 pandemic on physical activity, then map barriers and facilitators to the Capability, Opportunity, Motivation, and Behaviour (COM-B) Model of Behaviour to aid future intervention development. Methods 17,082 participants provided a response to the free text module, and data from those who mentioned physical activity in any context were included. Data were analysed using thematic analysis and key themes identified. Results 5396 participants provided 7490 quotes related to physical activity. The sample were predominately female (84%), white (97%) and aged <60 years (57%). Seven key themes were identified: the importance of outdoor space, changes in daily routine, impact of COVID-19 restrictions, perceived risks or threats to participation, the importance of physical health, the importance of physical activity for mental health and the use of technology. Conclusion Future physical activity interventions could encourage people to walk outdoors, which is low cost, flexible, and accessible to many. Developing online resources to promote and support physical activity provides a flexible way to deliver quality content to a large audience.

The novel coronavirus disease (COVID-19) pandemic is provoking a prevalent consequence on mental health because of less interaction among people, economic collapse, negativity, fear of losing jobs, and death of the near and dear ones. To express their mental state, people often are using social media as one of the preferred means. Due to reduced outdoor activities, people are spending more time on social media than usual and expressing their emotion of anxiety, fear, and depression. On a daily basis, about 2.5 quintillion bytes of data are generated on social media, analyzing this big data can become an excellent means to evaluate the effect of COVID-19 on mental health. In this work, we have analyzed data from Twitter microblog (tweets) to find out the effect of COVID-19 on peoples mental health with a special focus on depression. We propose a novel pipeline, based on recurrent neural network (in the form of long-short term memory or LSTM) and convolutional neural network, capable of identifying depressive tweets with an accuracy of 99.42%. Preprocessed using various natural language processing techniques, the aim was to find out depressive emotion from these tweets. Analyzing over 571 thousand tweets posted between October 2019 and May 2020 by 482 users, a significant rise in depressing tweets was observed between February and May of 2020, which indicates as an impact of the long ongoing COVID-19 pandemic situation.

Background: Disparity in adult mortality (AM) with reference to social dynamics and health care has not been sufficiently examined. This study aimed to identify the gap in the understanding of AM in relation to religion, political stability, economic level, and universal health coverage (UHC). Methods: A cross-national study was performed with different sources of data, using the administrative record linkage theory. We created a new data set using data from the 2013 World Bank data catalogue by region, The Economist (Political instability index 2013), Stuckler David et al. (Universal health coverage, 2010), and religious categories of all UN country members. Descriptive statistics, a t-test, an ANOVA followed by a post hoc test, and a linear regression were used where applicable. Result: The average AM rate for males and females was 0.20 ± 0.10 and 0.14 ± 0.10, respectively. AM was significantly higher in economically weak countries, countries with political instability, countries with traditional religion, without achievement of UHC, and Sub-Saharan Africa (p<0.01). There was high disparity of AM between countries with and without UHC (F = male: 61.89, female: 51.85, p<0.001) and between groups with low and high income (F = male: 36.33, female: 42.39, p<0.001). UHC and political stability would significantly reduce AMR by > 0.41 in both sexes and high economic status would reduce male AMR by 0.44, and female AMR by 0.70, in relation to countries without UHC, with political instability, and low economic status. Conclusions: Disparities in AM can be reduced after the achievement of UHC and economically productive activities for those adults affected by conflict and political unrest.

The non-contact patient monitoring paradigm moves patient care into their homes and enables long-term patient studies. The challenge, however, is to make the system non-intrusive, privacy-preserving, and low-cost. To this end, we describe an open-source edge computing and ambient data capture system, developed using low-cost and readily available hardware. We describe five applications of our ambient data capture system. Namely: (a) Estimating occupancy and human activity phenotyping; (b) Medical equipment alarm classification; (c) Geolocation of humans in a built environment; (d) Ambient light logging; and (e) Ambient temperature and humidity logging. We obtained an accuracy of 94% for estimating occupancy from video. We stress-tested the alarm note classification in the absence and presence of speech and obtained micro averaged F1 scores of 0.98 and 0.93, respectively. The geolocation tracking provided a room-level accuracy of 98.7%. The root mean square error in the temperature sensor validation task was 0.3°C and for the humidity sensor, it was 1% Relative Humidity. The low-cost edge computing system presented here demonstrated the ability to capture and analyze a wide range of activities in a privacy-preserving manner in clinical and home environments and is able to provide key insights into the healthcare practices and patient behaviors.

Telemedicine is the use of Information and Communication Technology (ICT) for clinical health care from a distance. The exchange of radiographic images and electronic patient health information/records (ePHI/R) for diagnostic purposes has the risk of confidentiality, ownership identity, and authenticity. In this paper, a data hiding technique for ePHI/R is proposed. The color information in the cover image is used for key generation, and stego-images are produced with ideal case. As a result, the whole stego-system is perfectly secure. This method includes the features of watermarking and steganography techniques. The method is applied to radiographic images. For the radiographic images, this method resembles watermarking, which is an ePHI/R data system. Experiments show promising results for the application of this method to radiographic images in ePHI/R for both transmission and storage purpose.

The Operational Remote Sensing (ORS) program leverages Landsat and MODIS data to detect forest disturbances across the conterminous United States (CONUS). The ORS program was initiated in 2014 as a collaboration between the US Department of Agriculture Forest Service Geospatial Technology and Applications Center (GTAC) and the Forest Health Assessment and Applied Sciences Team (FHAAST). The goal of the ORS program is to supplement the Insect and Disease Survey (IDS) and MODIS Real-Time Forest Disturbance (RTFD) programs with imagery-derived forest disturbance data that can be used to augment traditional IDS data. We developed three algorithms and produced ORS forest change products using both Landsat and MODIS data. These were assessed over Southern New England and the Rio Grande National Forest. Reference data were acquired using TimeSync to conduct an independent accuracy assessment of IDS, RTFD, and ORS products. Overall accuracy for all products ranged from 77.64% to 93.51% (kappa 0.09–0.59) in the Southern New England study area and 59.57% to 79.57% (kappa 0.09–0.45) in the Rio Grande National Forest study area. In general, ORS products met or exceeded the overall accuracy and kappa of IDS and RTFD products. This demonstrates the current implementation of ORS is sufficient to provide data to augment IDS data.

To identify gender- and age-related associations between adult dental checkups and unmet dental care needs, we analyzed data of 14,000 participants, ages ≥ 19, from the 7th Korea National Health and Nutrition Examination Survey (2016–2018) (KNHANES VII). Data was collected via self-report questionnaires and interviews. Complex sample chi-square test and multiple logistic regression analysis indicated 31.7% of participants had unmet dental care needs; in the prior 12months, 67.1% had not utilized dental services, and 43.3% had not received dental checkups. Odds ratios (ORs) for dental checkups and unmet dental needs were 8.87 (CI:7.80–10.09, p < 0.001) for those who used dental services and 1.28 (CI: 1.13–1.44, p < 0.001) for those who had not. Significant age-dependent associations between those not receiving dental checkups and the rate of unmet dental care include men and women aged 50–59 years (OR: 1.77; CI = 1.22–2.58 and OR: 1.43; CI: 1.02–2.02; p = 0.040, respectively) and women ≥ 70 years (OR = 1.79, CI = 1.20–2.66, p = 0.004). Reducing unmet dental care needs requires greater public health promotion and education regarding regular dental checkups; additional practical strategies could enhance dental checkup compliance.

Human infection caused by the SARS-CoV-2 virus, called COVID-19, is a new pandemic with devastating effects worldwide. Science seeks the rational and systematic explanation of phenomena. In pandemics, decisions on prevention and treatment of people should be consistently taken, supported by scientific knowledge and ethical principles to produce more good than harm. At first, prospective observational studies to systematically collect patient data, correlating protective or therapeutic interventions with outcomes to assess effectiveness and safety, should be prioritized as the most appropriate type of study. The proposed protocol in this article aims to provide doctors with information on the reduction of harm in early COVID-19 patients by applying individualized interventionist or expectant therapeutic strategies, respecting the autonomy and preferences of physicians and patients in clinical decision-making. The evaluation of the clinical status, besides laboratory confirmation of COVID-19, comprises an individualized symptom score for each patient, a global self-perception scale of the severity of the disease, a clinical progression scale developed by the WHO for clinical studies in COVID-19 and, at the first consultation, doctors´ overall impression on the clinical prognosis. The analysis of anonymized data should preferably use descriptive and inferential statistical resources. The case report form is available for free use in the protocol, along with examples of patient informed consent forms for the prescription of off-label medications and authorization to use the data. Their results may be useful to indicate interventions that are candidates for efficacy trials, in randomized controlled trials, with a higher chance of success. It respects the autonomy and preferences of doctors and patients to decide the best options for treatment in uncertain situations. It also allows the gathering of useful information for future more rigorous clinical trials, trying to link science, ethics, and personal clinical experience.

The primary purpose of this study was to determine the prevalence of drug-drug interaction (DDI) and duplicate therapy in chronic patients in a completely random study population engaged in digital health apps. In this cross-sectional study, polypharmacy checks for 100 completely anonymous patients were analyzed for the occurrence of DDIs and duplicate therapy. Logistic regression models were used to identify factors associated with DDIs and duplicate therapy. DDIs and duplicate therapy prevalence were 34% and 33%, respectively. Chi-Square test discovered a significant association between the DDIs and duplicate therapy variables. Logistic regression models showed a strong association between the number of medications taken and higher odds of DDIs occurring in our population only. In conclusion, our study shows that polypharmacy is a determining factor for the occurrence of unwanted DDIs, and the prevalence of duplicate therapy and DDIs is around 33%, increasing an issue regarding patient safety and its burden to the healthcare system.

The accurate monitoring of state of charge (SOC) and state of health (SOH) is critical for the reliable management of lithium-ion battery (LIB) systems. In this paper, the online model identification is scrutinized to achieve high modeling accuracy and robustness, and a model-based joint estimator is further proposed to estimate the SOC and SOH of LIB concurrently. Specifically, an adaptive forgetting recursive least squares (AF-RLS) method is exploited to optimize the estimation alertness and numerical stability, so as to achieve accurate online adaption of model parameters. Leveraging the online adapted battery model, a joint estimator is proposed by combining an open-circuit voltage (OCV) observer with a low-order state observer to co-estimate the SOC and capacity of LIB. Simulation and experimental studies are performed to evaluate the performance of the proposed data-model fusion method. Results suggest that the proposed method can effectively track the variation of model parameters by using the onboard measured current and voltage data. The SOC and capacity can be further estimated in real time with fast convergence, high accuracy and high stability.

Sleep deficiency impacts the quality of life and may have serious health consequences in the long run. Questionnaire-based subjective assessment of sleep deficiency has many limitations. On the other hand, objective assessment of sleep deficiency is challenging. In this study, we propose a polysomnography-based mathematical model for computing baseline sleep deficiency severity score and then investigated the estimation of sleep deficiency severity using features available only from wearable sensor data including heart rate variability and single-channel electroen-cephalography for a dataset of 500 subjects. We used Monte-Carlo Feature Selection (MCFS) and inter-dependency discovery for selecting the best features and removing multi-collinearity. For developing the Regression model we investigated both the frequentist and the Bayesian ap-proaches. An Artificial Neural Network achieved the best performance of RMSE = 5.47 and an R-squared value of 0.67 for sleep deficiency severity estimation. The developed method is com-parable to conventional methods of Functional Outcome of Sleep Questionnaire and Epworth Sleepiness Scale for assessing the impact of sleep apnea on sleep deficiency. Moreover, the results pave the way for reliable and interpretable sleep deficiency severity estimation using a wearable device in Smart Health.

(1) Background: Targeted (TT) and immune checkpoint inhibitor (ICI) therapies have become available in the routine care of metastatic melanoma in recent years. (2) Objective: We compared mortality in patients with metastatic melanoma and different systemic therapies. (3) Methods: A retrospective cohort study, based on pseudonymized health insurance data of about 2 million individuals from Saxony, Germany, was conducted for the years 2010 to 2020. Only patients with an advanced stage, i.e. distant metastases were considered for the main analysis. Relative survival since metastasis and predicted survivor curves derived from a Cox model were used to assess potential differences in mortality. (4) Results: Relative survival was highest in the subgroup with sequential use of ICI and TT. All treatments except interferon had significant hazard ratios (HR) in the Cox model with time-dependent effects indicating a protective effect after treatment initiation (HR 0.01-0.146) but decreasing over time (HR 1.351-2.310). The predicted survivor curves revealed best survival under ICI-TT treatment and worst survival under TT treatment alone. (5) Conclusions: We found real-world evidence for survival benefits of patients with metastatic melanoma who received sequential ICI and TT treatment. It is conceivable that the observed high survival differences were overestimated due to bias, such as confounding by indication.

The workforce crisis of primary care is reflected in the increasing number of general medical practices (GMP) with vacant general practitioner (GP) position, and the GPs’ ageing. Our study aimed to describe the association between this crisis and premature mortality. Age-sex-standardized mortality for 18-64 years old adults were calculated for all Hungarian GMPs annually in the period from 2006 to 2014. The relationship of premature mortality with GPs’ age and vacant GP position were evaluated by standardized linear regression controlled for list size, urbanization, geographical location, clients’ education, and type of the GMP. The clients’ education was the strongest protective factor (beta=-0175; p<0.001), followed by urban residence (beta=-0.149; p<0.001), and the bigger list size (beta1601-2000=-0.054; p<0.001; beta2001-X=-0.096; p<0.001). The geographical localization influenced significantly also the risk. Although, GMP with a GP aged older than 65 years (beta=0; p=0.995) did not affected the risk, GP vacancy was associated with higher risk (beta=0.010; p=0.033), but the corresponding number of attributable cases was 23.54 for 9 years. The vacant GP position is associated with significant but hardly detectable increased risk of premature mortality without considerable public health importance. Nevertheless, employment of GPs aged more than 65 does not impose premature mortality risk elevation.

Supporting the implementation of school food and nutrition policies (SFNPs) is an international priority to encourage healthier eating among children and youth. Schools are an important intervention setting to promote childhood nutrition, and many jurisdictions have adopted policies, guidelines, and programs to modify the school nutrition environment and promote healthier eating. The purpose of this study was to explore the association between perceived adequacy and capacity for SFNP implementation on food availability and policy adherence in the province of Nova Scotia (NS), Canada, one of the first regions in Canada to launch a comprehensive SFNP. A cross sectional online survey was conducted in 2014-15 to provide a current-state of policy implementation and adherence. Adequacy and capacity for food policy implementation was used to assess policy adherence through the availability of prohibited ‘minimum’ nutrition foods. An exploratory factor analysis was conducted on a selected of available foods and ‘slow’ and ‘quick’ service food composition measures were dichotomized for food availability. Schools with above perceived average adequacy and capacity for policy implementation had more than three times (3.62) greater odds of adhering to a lunch policy, while schools that adhered to a snack and lunch policy had 52% and 82% lower odds of serving quick service foods, respectively. This study identified the need for appropriate adequacy and capacity for policy implementation to ensure policy adherence and improve the school food environment. These findings highlight the potential of SFNPs to have a positive impact on childhood nutrition, but adequately supporting their implementation is critical to ensure their impact.

The objective of the study was to investigate the gap between data and evidence-based decisions among healthcare professionals considering the enormous amount of individual and aggregate data collected. Our study assessed the capacity, skills, and knowledge of the Ministry of Health leadership staff to understand data management, analysis, utilization, and dissemination. Three key components were assessed: 1) Knowledge through true/false questions, 2) Level of Skill (and Competency) using a Likert scale, and 3) Understanding of Key Concepts and Tools based on a Likert scale. The 183 study respondents were diverse healthcare professionals from Kenya, Tanzania, and Rwanda. Majority of respondents had not received any training on data management, analysis, interpretation, and utilization techniques, further there was a significant difference between those who had received training versus those who had not(p=0.005). The respondents were competent in work-related experiences but lacked skills and knowledge on: data concepts and tools, study designs, and types of data analysis. These findings explain the gap between data management, analysis, utilization, and dissemination among health professional’s cadre. To enhance service delivery and optimal provision of health care, it is imperative to have all health care professionals receive a well-designed training on data management, analysis, interpretation, and utilization.

Introduction: The COVID-19 pandemic overwhelmed health systems globally, and affected delivery of other health services. We conducted a study in Uganda to describe interventions for continuity of access to other health services. Methods: We reviewed documents and interviewed 21 key informants. Thematic analysis was conducted to identify themes using the World Health Organization health system building blocks as a guiding framework. Results: Governance strategies included establishment of coordination committees and development and dissemination of guidelines. Infrastructure and commodities strategies included review of drug supply plans and allowing emergency orders. Workforce strategies included provision of infection prevention and control equipment, recruitment and provision of incentives. Service delivery modifications included designation of facilities for COVID-19 management, patient self-management, dispensing drugs for longer periods and leveraging community patient networks to distribute medicines. However, multi-month drug dispensing led to drug stock-outs while community drug distribution was associated with stigma concerns. Conclusions: Health service maintenance during emergencies requires coordination to harness existing health system investments. The service continuity committee coordinated efforts to maintain services and should remain a critical element of emergency response. Self-management and leveraging patient networks should address stigma to support service continuity in similar settings and strengthen service delivery beyond the pandemic.

The study of the concentrations and effects of fine particulate matter in urban areas have been of great interest to researchers in recent times. This is due to the acknowledgment of the far-reaching impacts of fine particulate matter on public health. Remote sensing data have been used to monitor the trend of concentrations of particulate matter by deriving aerosol optical depth (AOD) from satellite images. The Center for International Earth Science Information Network (CIESIN) has released the second version of its global PM_2.5 data with improvement in spatial resolution. This paper revisits the study of spatial and temporal variations in particulate matter in Saudi Arabia by exploring the cluster analysis of the new data. Cluster analysis of the PM_2.5 values of Saudi cities is performed by using Anselin local Moran’s I statistic. Also, the analysis is carried out at the regional level by using self-organizing map (SOM). The results show an increasing trend in the concentrations of particulate matter in Saudi Arabia, especially in some selected urban areas. The eastern and south-western parts of the Kingdom have significantly clustering high values. Some of the PM2.5 values have passed the threshold indicated by the World Health Organization (WHO) standard and targets posing health risks to Saudi urban population.

Background: Internal migrants had obstacles in accessing local public health services in China. This study aimed to estimate the utilization of local public health services and its determinants among internal migrants. Methods: Data were from the 2014 and 2015 nationally representative cross-sectional survey of internal migrants in China. Multivariate logistic regressions were used to estimate the relationship between socioeconomic, migration, demographic characteristics and public health services utilization. Results: Internal migrants in more developed eastern regions used less public health services. Those with higher socioeconomic status were more likely to use public health services. The broader and shorter they migrated, the less they used public health services. Compared to migration within the city, migration across provinces is negatively associated with health records (OR=0.88, 95% CI: 0.86-0.90), health education (OR=0.97, 95% CI: 0.94-1.00), and health education on NCDs (OR=0.92, 95% CI: 0.89-0.95) or through Internet channel (OR=0.96, 95% CI: 0.94-0.99). Conclusion: Public health services coverage for internal migrants has seen great improvement due to government subsides. Internal migrants with lower socioeconomic status and across provinces need to be targeted. More attention should be given to the local government in the developed eastern regions in order to narrow the regional gaps.

Background: The COVID-19 pandemic has sped up digital health transformation across the health sectors to enable innovative health service delivery. Such transformation relies on competent managers with the capacity to lead and manage. However, the health system has not adopted a holistic approach in addressing the health management workforce development needs, with many hurdles to overcome. The objectives of this paper are to present the findings of a three-step approach in understanding the current hurdles in developing a health management workforce that can enable and maximise the benefits of digital health transformation, and to explore ways of overcoming such hurdles. Methods: A three-step, systematic approach was undertaken, including an Australian digital health policy documentary analysis, an Australian health service management postgraduate program analysis, and a scoping review of international literatures. Results: The main findings will guide the formulation of strategies in developing a digitally enabled health management workforce in the digital health era. Conclusions: With the ever-changing landscape of digital health, being able to lead and manage in times of system transformation requires a holistic approach to develop the necessary health management workforce capabilities and system-wide capacity. The evidence would support that this can be achieved with the required system, policy, educational and professional organizational enablers, which drive a digital health focused approach across all the healthcare sectors, in a coordinated and contextual manner.

Background. We aimed to assess the validity of the Mat-O-Covid Job Exposure Matrix (JEM) on SARS-CoV2 using compensation data from the French National Health Insurance compensation system for occupational-related COVID-19. Methods. Deidentified compensation data for occupational COVID-19 in France were obtained between August 2020 and August 2021. The acceptance was considered as the reference. Mat-O-Covid is an expert based French JEM on workplace exposure to SARS-CoV2. Bivariate and multivariate models were used to study the association between the exposure assessed by Mat-O-Covid and the reference, as well as the Area Under Curves (AUC), sensitivity, specificity, predictive values, and likelihood ratios. Results. In the 1140 cases included, there was a close association between the Mat-O-Covid index and the reference (p&lt;0.0001). The overall predictivity was good, with an AUC of 0.78 and an optimal threshold at 13 per thousand. Using Youden’s J statistic resulted in 0.67 sensitivity and 0.87 specificity. Both positive and negative likelihood ratios were significant: respectively 4.9 [2.4-6.4] and 0.4 [0.3-0.4]. Discussion. It was possible to assess Mat-O-Covid’s validity using data from the national compensation system for occupational COVID-19. Though further studies are needed, Mat-O-Covid exposure assessment appears to be accurate enough to be used in research.

The supply of mental health processes in primary care has gaps. This study aims to analyze the association of agreement criteria and flows between primary care teams and the Family Health Support Center (NASF) for mental health collaborative care, considering the difference between capital and non-capital cities in Brazil. This cross-sectional study was conducted based on secondary data from the Primary Care Access and Quality Improvement Program. Agreement criteria and flows were obtained from 3883 NASF teams of the matrix support or collaborative care. The Chi-square test and multiple Poisson regression were used; p &lt; 0.05 was considered statistically significant. Prevalence ratios of negative associations demonstrated protective factors for support actions: follow-up at Psychosocial Care Center, management of psychopharmacotherapy, offer of other therapeutic actions, care process for users of psychoactive substances, and offer of activities to prevent the use of psychoactive substances. Collaborative care in primary care was effective, and capital cities were a protective factor compared with non-capital cities.

The negative implications of climate change for human health are now well-established. Yet these have not been fully considered into climate change communication strategies. Research suggests that reorienting climate change communication with a health frame could be a useful communication strategy. We conducted a long-term and broad overview of existing scientific literature in order to summarize the state of research activity in this area, by extent and by nature. The methodology is based on a scoping review of scientific articles published on climate change communication and health between 1990 and mid-2016 indexed in the PubMed, ScienceDirect, and Web of Science databases. The screened citations were reviewed for inclusion and data were extracted and coded in order to conduct quantitative (e.g. frequencies) and qualitative (i.e. content analysis) analyses.Out of 2,866 identified published papers, only 24 articles were eligible for analyses. The main themes identified were effective communication of climate change (n=10, 41.7%), the role of health professionals (n=10, 41.7%) and the perception of climate change (n=4, 16.7%). We identified a large proportion of secondary research articles (n= 15, 62.5%) including reviews (n=5, 20.8%) and opinion articles (n=10, 41.7%). A significant share - 37.57% (n=9) - of the identified articles were classified as original research articles, suggesting that the number of publications in this area - particularly original research - has not grown rapidly.This scoping review identified several themes including effective communication of climate change, the role of health professionals, and the perception of climate change in the selected articles on the subject. The research literature on the communication of climate change and health is relatively recent and emerging: the first articles on the subject were published from 2008 onward only.

Interprofessional learning (IPL) is essential to prepare healthcare trainees as the future public health workforce. WHIRL was an innovative IPL intervention that engaged multi-professional teams of volunteer healthcare trainees (n=20) to deliver health checks (n=464), including tailored advice and signposting, to employees in the UK construction industry (across 21 events, 16 sites, 10 organisations) as part of an ongoing research programme called Test@Work. Volunteers undertook a four-part training and support package of trainer-led education, observations of practice, self-directed learning and clinical supervision, together with peer mentoring. In a one-group post-test only design, IPL outcomes were measured using the Inventory of Reflective Vignette - Interprofessional Learning (IRV-IPL), and the psychometric properties of the IRV-IPL tool were tested. WHIRL demonstrably improved healthcare trainees’ interprofessional skills in all five areas of collaboration, coordination, cooperation, communication, and commendation. The IRV-IPL tool was found to be a valid and reliable measure of interprofessional competencies across three scenarios; before and after health promotion activities, and as a predictor of future health promotion competence. This industry-based workplace IPL programme resulted in attainment of health check competencies, and bridged the gap between research, education and clinical practice.

This observational study was ordered by the Medical Practitioners’ Chamber in Warsaw. The objective of the study was to evaluate the health status of physicians in relation to their occupational duties. Professional burnout was considered relative to different features of personality. This study was initially carried out from 2005–2008, but further analysis of burnout and personality was carried out from 2017–2018. The research tools were anonymous, validated questionnaires. The sample size was based on the size of the population— the registry of the Regional Chamber of Medical Practitioners— and literature on burnout prevalence. The respondents’ work places were randomly selected from the Mazovian District register. The test on burnout was completed by 378 respondents, while 62 subjects completed a personality test. Results showed that burnout syndrome was an occupational problem for healthcare workers. Professional burnout affected as many as 42% of respondents(n = 158). It affected two age groups in particular: physicians up to 31 years old and individuals aged 41-50. Moreover, neuroticism was found to be significantly related to burnout syndrome. In conclusion, burnout syndrome is common among medical practitioners, and neuroticism may be correlated with burnout syndrome.

Zoonoses are diseases transmitted from (vertebrate) animals to humans. Control and prevention of these diseases require an appropriate way to measure health for prudent and well-balanced decisions in public health. We propose a framework that aims to explore, understand and open up a conversation about the non-monetary value of animals through environmental and normative ethics. As an example of its application, participants can choose what they are willing to give in exchange for curing an animal in hypothetical scenarios selecting a human health condition to suffer, the amount of money, and lifetime as a tradeoff. We believe that considering animals beyond their monetary value in public health decisions will contribute to a more rigorous assessment of the burden of zoonotic diseases, among other health decisions. This method might help us complement the existing metrics in health, adding more comprehensive values for animal and human health for the “One Health” approach.

International migrants comprised 14% of the UK population in 2020, but migrant health in the UK has rarely been studied at a population level using primary care electronic health records (EHRs). Given the difficulty of determining migration status using EHRs, this study developed a migration phenotype and assessed its validity. We developed a phenotyping algorithm using codes for country of birth, visa status, non-English main/first language and non-UK origin. It was applied to a Clinical Practice Research Datalink (CPRD) GOLD database of 16,071,111 primary care patients between 1997 and 2018. We compared the completeness and representativeness of the identified migrant population to Office for National Statistics (ONS) country of birth and 2011 census data by year, age, sex, geographic region of birth and ethnicity. Between 1997-2018, 403,768 migrants (2.51% of the CPRD GOLD population) were identified using the phenotype. 178,749 (1.11%) of these migrants were identified by codes indicating foreign country of birth or visa status, 216,731 (1.35%) a non-English main/first language, and 8,288 (0.05%) non-UK origin. The cohort was similarly distributed compared to ONS migration statistics in terms of sex and region of birth. Recording of migration improved from identifying approximately one-tenth of the expected proportion of migrants according to the ONS in 2004 to a quarter in 2018. Younger migrants were better represented than those aged 50 and over. The migration phenotype identified a large number of migrants and can be used to undertake large-scale migration health research in CPRD GOLD to inform healthcare policy, practice and action. While the cohort was representative of the UK migrant population in terms of sex and region of birth, migration status was under-recorded in earlier years and older ages, and future studies for these groups should therefore be interpreted with caution.

: Mistrust, amplified by numerous artificial intelligence (AI) related incidents, has caused the energy and industrial sectors to be amongst the slowest adopter of AI methods. Central to this issue is the black-box problem of AI, which impedes investments and fast becoming a legal hazard for users. Explainable AI (XAI) is a recent paradigm to tackle this challenge. Being the backbone of the industry, the prognostic and health management (PHM) domain has recently been introduced to XAI. However, many deficiencies, particularly lack of explanation assessment methods and uncertainty quantification, plague this young field. In this paper, we elaborate a framework on explainable anomaly detection and failure prognostic employing a Bayesian deep learning model to generate local and global explanations from the PHM tasks. An uncertainty measure of the Bayesian model is utilized as marker for anomalies expanding the prognostic explanation scope to include model’s confidence. Also, the global explanation is used to improve prognostic performance, an aspect neglected from the handful of PHM-XAI publications. The quality of the explanation is finally examined employing local accuracy and consistency properties. The method is tested on real-world gas turbine anomalies and synthetic turbofan data failure prediction. Seven out of eight of the tested anomalies were successfully identified. Additionally, the prognostic outcome showed 19% improvement in statistical terms and achieved the highest prognostic score amongst best published results on the topic.

Effectively responding to children’s nutritional status and eating behaviors in Mozambique requires a community-based care approach grounded in sound nursing research that is evidence-based. The Community Assessment, Intervention, and Empowerment Model (MAIEC) is a nursing theoretical model that bases clinical decision-making for community health nurses using communities as a unit of care. We used the MAIEC to identify a community-based nursing diagnosis to address children’s nutritional status and eating behaviors in Mozambique. Objectives: (1) To conduct a descriptive study of children’s nutritional status and eating behaviors in a school community in Mavalane, Mozambique, and (2) to identify a community-based nursing diagnosis using the MAIEC clinical decision-making matrix in the same school community. Method: A cross-sectional, quantitative study was conducted to assess the nutritional status of children using anthropometric data, including brachial perimeter and the tricipital skinfold, and standard deviation for the relation of weight-height, in a sample of 227 children. To assess community management of the problem and identify a community-based nursing diagnosis, we surveyed 176 parents/guardians and 49 education professionals, using a questionnaire based on the MAIEC clinical decision matrix as a reference. Results: Malnutrition was identified in more than half of the children (51.3%). We also identified a community-based nursing diagnosis of impaired community management related to the promotion of child health and healthy eating as evident by lack of community leadership, participation, and processing among more than 70% of the community members (parents/guardians and education professionals). Conclusion: A nursing diagnosis and diagnostic criteria for nutritional status and community management were identified. The need to intervene using a multidisciplinary public health approach is imperative, with the school community as the unit of care. In addition, reliable anthropometric data were used to complement the nursing diagnosis and guide future public health interventions.

Objective: To explore the effect of rural-urban residence on self-reported health status with UK cancer survivors. Design: A cross-sectional postal questionnaire that collected data on demographics, post-code and self-reported health status. Methods: Independent Samples t test was used to detect differences in health status between rural and urban respondents. Pearson’s χ2 was used to control for confounding variables and multivariate analysis was conducted using Stepwise linear regression. Setting: East Midlands of England. Participants: Adult cancer survivors who had undergone primary treatment in the last five years. Participants were excluded if they had recurrence or metastatic spread, started active oncology treatment in the last twelve months and were in receipt of palliative or end of life care. Main Outcome: Residence was measured using the UK ONS RUC2011 Rural-Urban Classifications and Health Status via the UK ONS self-reported health status measure. Results: 227 respondents returned a questionnaire. Forty-five per cent (N=103) were resident in a rural area and fifty-three per cent (N=120) in an urban area. Rural (4.11±0.85) respondents had significantly (p<0.001) higher self-reported health status compared to urban (3.65±0.93) respondents (MD 0.47; 95% CI 0.23, 0.70). Conclusion: Rural respondents had significantly higher self-reported health status compared to their urban counterparts. It is hoped that the results will stimulate further work in this area and that researchers will be encouraged to collect data on rural-urban residency where appropriate.

Resumo: Este estudo teve como objetivo avaliar a Saúde Mental Positiva (SPM) e a sua relação com características sociodemográficas, literacia em saúde mental e escala de vulnerabilidade psicológica (PVS) em estudantes universitários portugueses com idades compreendidas entre os 17 e os 62 anos. Foi realizado um estudo descritivo-correlacional. Uma pesquisa online foi realizada para avaliar variáveis ​​demográficas, e vários questionários foram aplicados para avaliar saúde mental positiva, vulnerabilidade psicológica e alfabetização em saúde mental. Os dados foram coletados de 1º de novembro de 2019 a 1º de setembro de 2020. No geral, 3.405 alunos participaram do estudo. Os resultados mostram que 67,8% dos alunos revelaram um alto nível de PMH, 31,6% apresentaram um nível médio de PMH e 0,6% apresentaram um nível baixo de PMH. Os estudantes do sexo masculino relataram maior satisfação pessoal (t (3170) = -2,39, p=0,017) e autonomia (t (3170) = -3,33, p=0,001), no PMH em relação ao sexo feminino. Alunos sem bolsa pontuaram mais alto (t (3.127) = -2,04, p=0,42) no PMH do que alunos com bolsa. Estudantes que não foram deslocados de casa relataram maior (t (3170) = -1,99, p=0,047) Autocontrole em PMH do que aqueles deslocados de sua casa. Estudantes universitários com resultados de PMH mais altos têm resultados de PVS mais baixos e resultados de Alfabetização mais altos. Os achados deste estudo contribuirão para identificar as necessidades de intervenção dos alunos na PMH. Estudantes universitários com resultados de PMH mais altos têm resultados de PVS mais baixos e resultados de Alfabetização mais altos. Os achados deste estudo contribuirão para identificar as necessidades de intervenção dos alunos na PMH. Estudantes universitários com resultados de PMH mais altos têm resultados de PVS mais baixos e resultados de Alfabetização mais altos. Os achados deste estudo contribuirão para identificar as necessidades de intervenção dos alunos na PMH.

The aim was to analyze the coping strategies used by primary health care (PHC) professionals. A cross-sectional, descriptive-analytical study was conducted with professionals working in primary health care units in São José do Rio Preto, a large city in the interior of São Paulo, Brazil. For data collection we used an instrument developed by the researchers, containing sociodemographic and professional variables, as well as the Problem Coping Modes Scale (EMEP). We evaluated 333 PHC professionals. A difference was observed between the scores of the four coping strategies (p<0.001), with the highest score for the problem-focused strategy (3.8) and the lowest score for the emotion-focused strategy (2.4). Physicians had the lowest scores in coping strategies focused on religious practices/fantastical thinking (p<0.001) and pursuit of social support (p=0.045), while community health agents had the highest scores in these coping strategies). Professionals working in PHC have different coping strategies for the problems and stressful situations experienced in the work environment. These strategies can involve more positive attitudes focused on confrontation and problem solving, to emotional responses that involve attitudes of avoidance and denial that involve attitudes of avoidance and denial of the problem.

Although health policy resides mainly with the government, industry can play an important role in building a health ecosystem. From March to May, we administered questionnaires to 1,200 individuals from the general Korean population asking about their perception of health-friendly labels, and if they would purchase such labeled products (foods, pharmaceuticals, etc.) and services (purifying water, preventing air pollution, etc.) at extra cost. The participants placed a high value on the importance of mental, social, spiritual, and physical health factors in terms of company’s products and services with a score of about 8 out of 10 (range, 7.74-8.33). Most respondents (72.4%) said they were interested in adopting health-friendly labels. When a health-friendly label is introduced (such as one by the Business for Social Responsiveness), 65.1% of the respondents said they intended to purchase the product or service, while 6.8% said they did not, and 75.0% said they were willing to pay extra for the health-friendly product or service. Multivariate logistic regression models showed urban residence, high education level, and good social health to be significantly associated with positive attitudes toward health-friendly labels. People with high income, no religion, or normal weight were more likely to say they intend to purchase products and services with health-friendly labels. They also had a more positive attitude toward paying more for such products and services, as did people with good spiritual health. This study provides data that illustrate the importance of health-friendly products and services to the general population and companies.

Trees provide key ecosystem services, but the health and sustainability of these plants is under increasing biotic and abiotic threat, including from the growing incidences of non-native invasive plant pests (including pathogens). The island of Ireland (Ireland and Northern Ireland) is generally accepted to have a high plant health status, in part due to its island status and because of the national and international regulations aimed at protecting plant health. To establish a baseline of the current pest threats to tree health for the island of Ireland, the literature and unpublished sources were reviewed to produce a dataset of pests of trees on the island of Ireland. The dataset contains 396 records of pests of trees on the island of Ireland, the majority of pests being arthropods and fungi, and indicating potentially more than 44 non-native pest introductions. The reliability of many (378) of the records was judged to be high, therefore the dataset provides a robust assessment of the state of pests of trees recorded on the island of Ireland. We analyse this dataset and review the history of plant pest invasions, including (i) discussion on notable native and non-native pests of trees, (ii) pest interceptions at borders and (iii) pests and climate change. The dataset establishes an important baseline for the knowledge of plant pests on the island of Ireland, and will be a valuable resource for future plant health research and policy making.

The Portuguese health system has a universal, public, general National Health Service (NHS), tending towards free healthcare access. Created in 1979, this delivery model developed from the integration and complementarity between the different response levels (primary, hospital, continuing, and palliative care). However, over these 40 years, the initially centralized system underwent a decentralization process with the creation of Regional Health Administrations in the five mainland administrative regions. Since then, the entire NHS has settled around this new organization. The most recent step started in 2018 with decentralizing primary health care skills to 190 municipalities. This paper presents the various critical issues involved in the latest gradual decentralization process in health, intending to bring services closer to the citizens, and more focused on their needs. The article identifies and discusses the implications of this experience based on the steps foreseen in the already published legal texts.

Along with environmental pollutions, urban planning has been connected to public health. The research indicates that the quality of built environments plays an important role in reducing mental disorders and overall health. The structure and shape of the city are considered as one of the factors influencing happiness and health in urban communities and the type of the daily activities of citizens. The aim of this study was to promote physical activity in the main structure of the city via urban design in a way that the main form and morphology of the city can encourage citizens to move around and have physical activity within the city. Functional, physical, cultural-social, and perceptual-visual features are regarded as the most important and effective criteria in increasing physical activities in urban spaces based on literature review. The environmental quality of urban spaces and their role in the physical activities of citizens in urban spaces were assessed by using the questionnaire tool and analytical network process (ANP) of structural equation modeling. Further, the space syntax method was utilized to evaluate the role of the spatial integration of urban spaces on improving physical activities. Based on the results, the consideration of functional diversity, spatial flexibility and integration, security, and the aesthetic and visual quality of urban spaces plays an important role in improving the physical health of citizens in urban spaces. Further, more physical activities, including motivation for walking and consequently, the sense of public health and happiness, were observed in the streets having higher linkage and space syntax indexes with their surrounding texture.

Background: Australia’s healthcare system is complex and fragmented which can create challenges in healthcare, particularly in rural and remote areas. Aboriginal people experience inequalities in healthcare treatment and outcomes. This study aimed to investigate barriers and enablers to accessing healthcare services for Aboriginal people living in rural and remote Australia. Methods: Semi-structured interviews were conducted with healthcare delivery staff and stakeholders recruited through snowball sampling. The communities were selected for their high proportion of Aboriginal people and geographical representation (coastal, rural, and border). Thematic analysis identified barriers and enablers. Results: Thirty-one interviews were conducted (n =5 coastal, n=13 remote, and n=13 border) and six themes identified: 1) Improved coordination of healthcare services; 2) Better communication between services and patients; 3) Trust in services and cultural safety; 4) Importance of prioritizing health services by Aboriginal people; 5) Importance of reliable, affordable and sustainable services; 6) Distance and transport availability. These themes were often present as both barriers and enablers to healthcare access for Aboriginal people. They were also present across the healthcare system and within all three communities. Conclusions: This study describes a pathway to better healthcare outcomes for Aboriginal Australians by providing insights into ways to improve access.

Health literacy describes skills and competencies that enable people to gain access to, understand and apply health information to positively influence their own health and the health of those in the social environment. In an increasingly media saturated and digitized world, these skill sets are necessary for accessing and navigating sources of health information and tools, such as television, the Internet, and mobile apps. The concepts of Media Health Literacy (MHL) and eHealth Literacy (eHL) describe the specific competencies such tasks require. This article introduces the two concepts, and then reviews findings on the associations of MHL and eHL with several contextual variables in the social environment such as socio-demographics, social support, and system complexity, as a structural variable. As eHL and MHL are crucial for empowering people to actively engage in their own health, a growing body of literature reports of the potential and the effectiveness of intervention initiatives to positively influence these competencies. From an ethical standpoint, equity is emphasized, stressing the importance of accessible media environments for all - including those at risk of exclusion from (digital) media sources. Alignment of micro and macro contextual spheres will ultimately facilitate both non-digital and digital media to effectively support and promote public health.

Aim: Shockwaves have been felt all over the world as a result of war, inflation, food shortages, and the COVID-19 pandemic's long tail. The aim of the study is to correlate present global conflicts, pandemic and socio-economic crises with present healthcare sustainability, identifying possible threats and visualize future global health crises if all these catastrophes persist for long. Materials and Methods: PubMed, ALTAVISTA, Embase, Scopus, Web of Science, and the Cochrane Central Registers were prioritized to collect public health issues. Results: The global economic slowdown, sharp decline in financial asset values, decline in imports and exports, contraction of industrial production, rise in inflation, decrease in wages, rise in unemployment, damage to the social security caused by numerous natural calamities, human displacement due to pandemic and ongoing conflicts tear down not only the economic sector but also the health sector. It is already late for taking corrective measure by the participation every country, community or intelligence. Only healthcare issues, highlighted in this study, if focused in the highest platforms, could compel global leaders to forego conflicts and work together. Conclusion: The global health sector will be collapsed soon, if proper initiatives are not taken right now, which has already been grossly mistreated by the pandemic.

The investment in digital e-Health services is a priority direction in the development of global health care systems. While people are increasingly using the Web for health information, it is not entirely clear what is the physicians’ attitude towards digital transformation, and the acceptance of new technologies in healthcare. The aim of this cross-sectional survey study was to investigate physicians’ self-digital skills, and their opinions on obtaining online health knowledge by patients, as well as the recognition of physicians’ attitudes towards e-Health solutions. Principal Component Analysis (PCA) was performed to emerge the variables from self-designed questionnaire, and cross-sectional analysis comparing descriptive statistics and correlations for dependent variables using the one-way ANOVA (F-test). 307 physicians participated in the study, reported using the internet mainly several times a day (66.8%). Most participants (70.4%) were familiar with new technologies and rate their e-Health literacy high, although 84.0% reported the need for additional training in this field, and reported a need to introduce a larger number of subjects shaping digital skills (75.9%) in medical studies 53.4% of physicians perceived Internet-sourced information as sometimes reliable, and in general assessed the effects of using it by their patients negatively (41.7%). Digital skills increased significantly with frequency of internet use (F = 13.167; p = 0.0001), and decreased with physicians’ age, and the need for training. Those who claimed that patients often experienced health benefits from online health showed higher digital skills (-1.06). Physicians most often recommended their patients to obtain laboratory test results online (32.2%), and to arrange medical appointments via the Internet (27.0%). Along with the deterioration of physicians’ digital skills, the recommendation of e-Health solutions decreased (r = 0.413), and lower the assessment of e-Health solutions for the patient (r = 0.449). Physicians perceive digitization as a sign of the times, and frequently use its tools in daily practice. The evaluation of Dr. Google’s phenomenon and online health is directly related to their own e-Health literacy skills, but there is still a need for practical training to deal with digital revolution.

Background: It is very important that nurses receive adequate training in Sexual and Reproductive Health (SRH). In this study, the contents of the SRH subject in the undergraduate nursing curricula of 77 Spanish universities were examined in order to determine what SRH training nursing students are receiving. Methods: The contents of the SRH subject of all the curricula that were available online were reviewed. The distribution of the contents (topics) in the two areas (reproductive health and sexual health) was analyzed, and the prevalence of each topic was established. It was also determined whether there were differences in topics between public (n=52) and private universities (n=25). Results: The training of nursing students focuses mainly on the area of Reproductive Health (15 topics). Most of the topics of this area had a prevalence greater than 50%. Although the area of Sexual Health had 14 topics, most of these topics had a low prevalence (&lt;20%), especially in private universities. Conclusions: It was found that there is considerable variation in the distribution and prevalence of SRH topics between universities. The contents of the area of Reproductive Health are usually prevalent in most of the curricula, however the contents of the area of Sexual Health are very limited in most of the universities. An organizational effort is required to determine and standardize the contents of SRH that nursing students should receive in Spain to avoid inequalities in their training.

Aedes aegypti mosquitoes are primary vectors of dengue, yellow fever, chikungunya and Zika viruses. Ae. aegypti is highly anthropophilic and relies nearly exclusively on human blood meals and habitats for reproduction. Socioeconomic factors may influence the spread of Ae. aegypti due to its close relationship with humans. This paper describes and summarizes the published literature on how socioeconomic variables influence the distribution of Ae. aegypti mosquitoes in the mainland United States. A comprehensive search of PubMed/Medline, Scopus, Web of Science, and EBSCO Academic Search Complete through June 12, 2019 was used to retrieve all articles published in English on the association of socioeconomic factors and the distribution of Ae. aegypti mosquitoes. Additionally, a hand search of mosquito control association websites was conducted in an attempt to identify relevant grey literature. Articles were screened for eligibility using the process described in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Initially, 3,493 articles were identified through the database searches and previously known literature. After checking for duplicates, 2,145 articles remained. 570 additional records were identified through the grey literature search for a total of 2,715 articles. These articles were screened for eligibility using their titles and abstracts, and 2,677 articles were excluded for not meeting the eligibility criteria. Finally, the full text for each of the remaining articles (n = 38) was read to determine eligibility. Through this screening process, 11 articles were identified for inclusion in this review. The findings for these 11 studies revealed inconsistent relationships between the studied socioeconomic factors and the distribution and abundance of Ae. aegypti. The findings of this review suggest a gap in the literature and understanding of the influence of anthropogenic factors on the distribution of Ae. aegypti that could hinder efforts to implement effective public health prevention and control strategies should a disease outbreak occur.

Health literacy is an indicator of a society’s ability to make better health judgement for themselves and the people around them. This study investigates the prevalence of health literacy among Malaysian adults and provides an overall picture of the current health literacy state of the society. The study also highlights socio-demographics markers of communities with limited health literacy which may warrant future intervention. A population based self-administered survey using the Health Literacy Survey Malaysian Questionnaire18 (HLS-M-Q18) instrument was conducted as part of the National Health Morbidity Survey 2019 in Malaysia. The nationwide survey utilized two-staged stratified random sampling method. A sample of 9478 individuals aged 18 and above participated in the study. The health literacy score was divided into three levels; limited, sufficient and excellent. Findings showed that majority Malaysian population has sufficient health literacy level, albeit leaning towards the lower end of the category with an average score of 35.5. The limited health literacy groups are associated with respondents with older age, lower education level and lower household income. Overall health literacy state for Malaysia is categorized at a lower sufficient level. Health literacy improvements should focus on communities with limited health literacy level.

The study aimed to estimate the prevalence and correlates of overweight and obesity among adults in Iraq. Data from a 2015 nationally representative cross-sectional survey of 3,916 persons 18 years and older were analysed that responded to a questionnaire, physical and biochemical measures. Multinomial logistic regression was utilized to predict determinants of overweight and obesity relative to under or normal weight. Results indicate that 3.6% of the participants were underweight (BMI <18.5 kg/m²), 30.8% had normal weight (BMI 18.5-24.9 kg/m²), 31.8% were overweight (25.0-29.9 kg/m²), and 33.9% had obesity (BMI ≥ 30.0 kg/m²). In adjusted multinomial logistic regression, aged 40-49 years (Adjusted Relative Risk Ratio-ARRR: 4.47, Confidence Interval-CI: 3.39-5.91), urban residence (ARRR: 1.28, CI: 1.14-2.18), hypertension (ARRR: 3.13, CI: 2.36-4.17) were positively, and male sex (ARRR: 0.47, CI: 0.33-0.68), having more than primary education (ARRR: 0.69, CI: 0.50-0.94), and larger household size (≥5 members) (ARRR: 0.45, CI: 0.33-0.60) were negativey associated with obesity. About two in three adult participants were overweight/obese, and sociodemographic and health risk factors were found that can be utilized in targeting interventions.

The epidemic of Coronavirus Disease 2019 (Covid-19) has brought many changes to people's life. This study aims to analysis Chinese people's psychological change and life after quarantining Wuhan and explore the influencing factors. Based on data from a web-survey after quarantining Wuhan (N=3268), the principal-component-analysis (PCA), multiple-linear-regression (MLR), propensity-score-matching (PSM) were used to explore the psychological change of people in China and the influencing factors. 83.3% of the respondents said that the impact of the epidemic on their life had increased after quarantining Wuhan. A considerable proportion of people's anxiety increased, being reflected in negative emotion, behavioral response and physiological response. The proportion of people who said their anxiety had increased in Wuhan was higher than that in other regions (p <0.05). The anxiety of people who were in medical isolation increased less than those who were not (p <0.05). All three aspects of people’s anxiety were positively related with time of medical isolation and degree of the attention on the epidemic (p＜0.05) except the effect of attention degree on the physiological response (p＝0.06). The measure of medical isolation at home should be advocated. Yet people should reduce the concern for the epidemic while paying attention to self-protection.

The COVID-19 crisis has brought unprecedented strain on healthcare systems around the world. It has perhaps taught us some key lessons that are worth considering and addressing to help build more sustainable health systems as well as improve our ability to combat future epidemics.

Recently there is a growing concern regarding potential health hazards linked with 5G deployment and radio frequency emitted by these stations. It becomes fundamentally important to scientifically address these concerns. In this paper, the health risks incorporated with 5G are discussed critically in the light of scientific work and debunk these tittle-tattles where required. We confute scientifically the “5G appeal”, discuss effects of 5G on health, its implications on privacy, pandemics, ecosystem and role of world health organization in fighting these narratives. Finally, we provide future direction to negate these false claims linked with 5G.

Abstract Issue Addressed: Men’s Sheds (‘Sheds’) have been identified as inherently health promoting and as potential settings to engage ‘hard-to-reach’ men in more structured health promotion initiatives. However, little is known about the sociodemographic or health and wellbeing characteristics of Shed members (‘Shedders’) on which such initiatives might be based. This study captures a baseline cross sectional analysis of Shedders (n=384) who participated in ‘Sheds for Life’, a health promotion initiative tailored to Sheds. Methods: Objective health measure, (body composition, blood pressure, blood lipids) captured via health screening as well as sociodemographic and health and wellbeing measures (physical activity, subjective wellbeing, mental health, social capital, cooking and diet) via questionnaires were assessed. Results: Participants were mostly over 65 years, retired with limited educational attainment. The majority were in the ‘at-risk’ categories for objective health measures, with most being referred to their GP following health screening. Older Shedders were also more likely to meet physical activity guidelines. Mental wellbeing was positively correlated with life satisfaction and increased social capital and these were also positively correlated with physical activity. Conclusions: Findings highlight the potential of Sheds in reaching a ‘hard-to-reach’ and ‘at-risk’ cohort of men. Despite a high prevalence of ‘at-risk’ objective health measures, participants report their health in positive terms. Future health promotion initiatives should capitalise on the inherent health promoting properties of Sheds. So what? Findings raise important implications for prioritising and designing health promotion initiatives in Shed settings.

Health innovations are generally oriented on a techno-economic vision. In this perspective, technologies are seen as an end in themselves, and there is no arrangement between the technical and the social values of innovation. This vision prevails in sanitary crises, in which management is carried out based on the search for punctual, reactive, and technical solutions to remedy a specific problem without a systemic/holistic, sustainable, or proactive approach. This paper attempts to contribute to the literature on the epistemological orientation of innovations in the field of public health. Taking the Covid-19 and Ebola crises as examples, the primary objective is to show how innovation in health is oriented towards a techno-economic paradigm. Second, we propose a repositioning of public health innovation towards a social paradigm that will put more emphasis on the interaction between social and health dimensions in the perspective of social change.

Individuals with low health literacy (HL) are known to have poorer health outcomes and to have higher mortality rates compared to individuals with higher HL: hence, the improvement of HL is a key outcome in modern healthcare systems. Healthcare providers are therefore asked to support patients’ literacy skills by encouraging the implementation of autonomy-supportive patient centered communication (PCC), which in turn requires the enhancement of patient engagement. Our main hypothesis is that the well-known relationship between autonomy-supportive PCC and HL is mediated by patient engagement which is known to play a role in HL promotion and that is related to PCC as well. The purpose of this study was to formulate a hypothetical structural equation model (SEM) linking PCC to patient engagement and HL. A cross-sectional survey design was employed involving 1007 Italian chronic patients. The hypothetical model was tested using SEM to verify the hypothesized mediation of patient engagement between PCC and HL. Results show that the theoretical model has a good fit indexes and that patient engagement fully mediates the relationship between PCC and HL. This finding suggests healthcare systems to implement a new paradigm where patients are supported to play an autonomous role in their own healthcare.

Background: The potential of Artificial intelligent (AI) models to process and interpret large health datasets at scale could revolutionize public health and epidemiology, providing a foundation for public health. Ethics has been recognized as a priority concern in the development and deployment of AI. Because AI technology can jeopardize patient safety, privacy, and posing a new set of ethical problems that must be addressed. Objectives: We aim to provide a holistic view on what are the different ethical and legal principles that was addressed in the included studies regarding the use of AI in public health and what are the ethical challenges that can arise.Methods: Following PRISMA guideline, five bibliographic databases were used in our search: PubMed, Scopus, JSTOR, IEEE Xplore, and Google Scholar from 2015 to February 2022. Four reviewers carried out study selection and data extraction, and the data extracted was synthesized by a narrative approach. Results: This review included 23 unique publications out of a total of 1123 items that were initially identified. Different ethical principles regarding the uses of AI in public health and community health were identified and discussed distinctly in the current review. The common ethical and legal themes that this review focused on are equity, bias, privacy and security, safety, transparency, confidentiality, accountability, social justice, and autonomy. In addition, five ethical challenges were mentioned. Conclusion: Research regarding ethical and legal principles and challenges about using AI in public health specifically consider a new filed, because all previous themes are concerning the physical and patients’ area where it focuses only on the clinical settings.

Antimicrobial resistance (AMR) is an increasingly pressing threat to human, animal, and environmental health. Reducing the use of antibiotics in agriculture has been identified as a key way to curb the spread of AMR. However, the effect of such policies on AMR prevalence, and their broader impacts on agricultural, health, and economic outcomes at the population level have proven very difficult to estimate and compare. This paper draws on and formalises ideas presented at the JPIAMR New Perspectives on Bacterial Drug Resistance workshop in June of 2022. With reference to emerging literature on the topic, it proposes a quantitative framework for estimating the relevant causal relationships needed to quantify the cross-sectoral impacts of AMR policies in agriculture, and for comparing these outcomes in like terms in a way which can feed directly into policy decision-making, notably without prohibitive data requirements. The ability of researchers to apply frameworks such as this will be increasingly necessary in order to holistically capture the impacts of AMR policies and to situate them in the broader policy context; especially where the mechanisms of transmission are opaque or complex, where data availability is limited; and where policymakers must allocate scarce resources among many competing objectives.

Objectives: This study validated the Japanese version of O’Donovan et al.’s (2020) composite measure of psychological safety scale and examined the associations of psychological safety with mental health and job-related outcomes. Methods: Online surveys were administered twice to Japanese employees with teams of more than three members. Internal consistency and test-retest reliability was tested using Cronbach’s α and intra-class correlation coefficient (ICC). Structural validity was examined using confirmatory factor analysis (CFA) and exploratory factor analysis (EFA). Convergent validity was tested. Multiple linear regression analyses were conducted to examine the relationship between psychological safety and psychological distress, work engagement, job performance, and job satisfaction. Results: Two hundred healthcare workers and 200 non-healthcare workers were analyzed. The Cronbach’s alpha of the total score was 0.92 - 0.96 and ICC was 0.88 - 0.92. CFA demonstrated poor fit, and EFA yielded a two-factor structure, suggesting one factor combined with peers and team. The scale showed good convergent validity. The total score of the scale showed significant associations with all outcomes in adjusted model in all workers. Conclusions: The Japanese version of the measure of the psychological safety scale presented good reliability and validity. Psychological safety is important for employees’ mental health and performance.

The Ministry of Health (MOH) in the Kingdom of Saudi Arabia (KSA) established a National School-based Screening Program (NSBSP) for health screening of school-going children. Students from specific grades were systematically screened for several health problems including obesity, visual and auditory problems, dental cavities, scoliosis, and attention-deficit/hyperactivity disorder (ADHD). This cross-sectional study aimed to determine the prevalence of these health problems among primary school students based on secondary data obtained from the NSBSP. We included 444,259 screened school children from the 1st and 4th grades of 50% of the selected schools (both private and public) across the KSA during the academic year 2018-2019. Among them, the most prevalent health problems identified were dental cavities (38.7%), eye refractory errors (10.9%), and overweight and obesity (10.5%); the less prevalent problems included ADHD (2.81%), auditory problems (0.6%), and scoliosis (0.48%). A greater prevalence of most health problems was observed in girls than boys. The NSBSP successfully aided the detection of health conditions with high and low prevalence among primary school students in the KSA, and thus, identification of health problems of specific concern. Implementation of effective school health services for the prevention, early detection, diagnosis, and treatment of these health problems is imperative.

COVID-19 is a potentially fatal viral infection. This study investigates geography, demography, socioeconomics, health conditions, hospital characteristics, and politics as potential explanatory variables for death rates at the state and county levels. Data from the Centers for Disease Control and Prevention, the Census Bureau, Centers for Medicare and Medicaid, Definitive Healthcare, and USAfacts.org were used to evaluate regression models. Yearly pneumonia and flu death rates (state level, 2014-2018) were evaluated as a function of the governors’ political party using repeated measures analysis. At the state and county level, spatial regression models were evaluated. At the county level, we discovered a statistically significant model that included geography, population density, racial and ethnic status, three health status variables along with a political factor. State level analysis identified health status, minority status, and the interaction between governors’ parties and health status as important variables. The political factor, however, did not appear in a subsequent analysis of 2014-2018 pneumonia and flu death rates. The pathogenesis of COVID-19 has greater and disproportionate effect within racial and ethnic minority groups, and the political influence on the reporting of COVID-19 mortality was statistically relevant at the county level and as an interaction term only at the state level.

Only 15% of the global population has access to occupational safety and health services. In Africa only 5% of employees working from major establishments, have access to occupational health services (OHS). Access to primary health care (PHC) services is addressed in many settings and inclusion of OHS in these facilities might increase efficiency in preventing occupational diseases. A cross-sectional study was conducted in four SADC countries aiming at assessing the availability of OHS at PHC facilities and the organization of OHS. We conducted a literature review to assess the provision and organization of OHS services. In addition to the review, a total of 23 doctors from PHC facilities were interviewed using questionnaires in order to determine the availability of OHS and training. Consultations with heads of ministries were done in four SADC countries. Results showed that in the SADC region, OHS are fragmented and lack a comprehensive approach. In addition, out of 23 PHC facilities only two (13%) provided occupational health and PHC. However, OHS provided at PHC facilities were limited to TB screening and audiometric testing. Our study showed a huge inadequacy of trained occupational health practitioners. This study supports the World Health Organization’s advocacy of integrating OHS at PHC level.

Dust inhalation is a huge concern in the mining environment and within all its operations. In fact, dust to be one of the most serious occupational hazards in the mining industry. Coal and crystalline silica dust are the causes of serious, sometimes fatal lung diseases such as pneumoconiosis, which affects coal miners, as well as silicosis, tuberculosis, chronic bronchitis, emphysema, chronic obstructive pulmonary disease, and chronic renal disease, which affect coal and other types of miners. The resulting effects both affect workers and nearby communities. The mining industry has in the past, employed several approaches to reduce effects of dust. But these strategies have often been ineffective because the grass withers during the dry season and sprayed water is rapidly absorbed or evaporates. This paper endeavors to review information on dust in the mining environment and how it is a nuisance to workers and communities and establish what strategies exist for this.

The WHO European Region defined the role of a new central professional for primary care, the Family and Community Nurse (FCN). The introduction of FCN in the framework of health policies highlight a key role of nurses in addressing the families’ and communities’ needs. A scoping review was conducted in order to identify and describe the available tools which has been adopted for the assessment of the community health needs by FNC. A comprehensive literature review on Embase, Cochrane Library, PubMed, CINAHL, Scopus and PsycInfo databases was conducted including all studies up to May 2021. A total of 1563 studies were identified and 36 of them were included. The literature review had made possible to identify studies employing twelve different community assessment's tools or modalities. Referring the WHO framework proposed in 2001 some common themes have been identified with an uneven distribution, as profiling the population, deciding on priorities for action and public healthcare programmes, implementing the planned activities, evaluation of health outcomes, multidisciplinary activity, flexibility and involving the community. To the best of our knowledge, this work is the first attempt to provide an overview of community assessment tools, keeping the guidance provided by the WHO as a reference.

An evaluation of emerging issues in One Health (OH) in Sub-Saharan Africa was undertaken to map the existing OH initiatives in Sub-Saharan African (SSA) countries. Desk review, expert opinions survey, limited interviews and wider consultations with selected OH stakeholders were conducted. The strengths, weaknesses, opportunities and threats to OH initiatives were identified. OH influence, interest and impacts were evaluated. One Health is transiting from multidisciplinary to transdisciplinary concepts and OH viewpoint should move from ‘proxy for zoonoses’, to include issues of climate change, nutrition and food safety, social sciences, geography, policy and planning, economics, welfare and well-being, antimicrobial resistance (AMR), vector-borne diseases, toxicosis and pesticides issues. While the identified major strengths should be boosted, the weaknesses should be addressed.OH Networks in SSA were spatially and temporally spread across SSA and stakeholders were classified as key, latent, marginal and OH defenders. Imbalance in stakeholders’ representation led to hesitation in buying-in from stakeholders who are outside the main networks. Theory of change, monitoring and evaluation frameworks, and tools to standardized evaluation of OH policies is needed for sustained future of OH and the future OH engagement should be outputs and outcomes-driven and not activity-driven.National roadmap for OH implementation and institutionalization is necessary and proofs of concepts in OH should be verified and scaled-up. Dependence on external funding is unsustainable and must be addressed. Necessary policy and legal instrument to support OH nationally and sub-nationally should be implemented taking cognizance of contemporary issues like urbanization, endemic poverty and other emerging issues. Utilizing current technologies and OH approach to address ongoing pandemic of COVID-19 and other emerging diseases is desirable. Finally, OH implementation should be anticipatory and not reactive to significantly benefit budgeting and contain disease outbreaks in animal sources before the risk of spillover to human can be envisaged.

The practice of nurse health coaching (NHC) draws from the art and science of nursing, behavioral sciences, and evidence-based health coaching methods. This secondary analysis of the audio-recorded natural language of participants during NHC sessions of our recent 8-week RCT evaluates improvement over time in cognitive-behavioral outcomes: Change Talk, Resiliency, Self-Efficacy/Independent Agency, Insight & Pattern Recognition, and Building Towards Sustainability. We developed a measurement tool for coding, Indicators of Health Behavior Change (IHBC), that was designed to allow trained health coach experts to assess the presence and frequency of the indicators in the natural language content of participants. We used a two-step method for randomly selecting the 20-minute audio-recorded session that was analyzed at each time point. Fifty-six participants had high-quality audio recordings of the NHC sessions. Twelve participants were placed in the social determinants of health (SDH) group based on the following: low income (<$20,000/year), early-onset hypertension, and social disadvantages. Our analyses significantly improved Change Talk and the other four factors over time. Our factor analyses indicated two distinct factors at each measurement point of the study, demonstrating the stability of the outcome measures over time. Our newly developed measurement tool, IHBC, proved stable in structure over time and sensitive to change. This NHC program shows promise in improving cognitive-behavioral indicators associated with health behavior change in both non-SDH and SDH individuals.

Background: During the COVID-19 pandemic some family physicians were overburdened and experienced difficulties reaching vulnerable patients and meeting the increased need for psycho-social support. This randomized controlled trial (RCT) tested whether a primary healthcare (PHC) based community health worker (CHW) intervention could tackle psychosocial suffering due to physical distancing measures in patients with limited social networks. Methods: CHWs provided 8 weeks of tailored psychosocial support to the intervention group. Control group patients received ‘care as usual’. The impact on feelings of emotional support, social isolation, social participation, anxiety and fear of COVID-19 were measured longitudinally using a face-to-face survey to determine their mean change from baseline. Self-rated change in psychosocial health at 8 weeks was determined. Results: We failed to find a significant effect of the intervention on the prespecified psychosocial health measures. However, the intervention did lead to significant improvement in self-rated change in psychosocial health. Conclusions: This study confirms partially the existing evidence on the effectiveness of CHW in-terventions as a strategy to address mental health in PHC in a COVID context. Further research is needed to elaborate the implementation of CHWs in PHC to reach vulnerable populations during and after health crises.

The present short communication aimed to determine the effects of vegetable cultivation on health. We conducted a qualitative study using responses to an open-ended question that was part of a survey on regional differences on vegetable intake. Participants in this study were residents of Gunma Prefecture, Japan, and were aged between 20–74 years. In the questionnaire, we asked: “Aside from increasing vegetable intake, how does vegetable cultivation affect your health?” We were able to categorize the answers into six subcategories related to physical health, mental health, and social well-being.

This study aims to understand the temporal and spatial characteristics of public concern for "children's mental health" in China in the context of the COVID-19 epidemic. Baidu Index is a research tool to collect and analyze massive data of Chinese netizens' behaviors. Using Baidu Index as the research tool, this paper analyzes the trend and distribution of Chinese netizens' attention to "children's mental health" from December 1st, 2019 to March 20th, 2022 from three aspects of trend research, need map, and crowd portrait. The study found that since the outbreak of COVID-19, the search trend of "children's mental health" has shown a cyclical change, peak in May and valley around the Spring Festival and National Day, and stable in other periods. "Mental health", "handwritten newspaper on mental health" and "youth mental health" are the most popular buzzwords among the public. The groups concerned of "children's mental health" is mainly distributed in Guangdong, Jiangsu, Beijing, and the majority are women between 30 and 39 years old. Meanwhile, search trend for "mental health" are like that for "children's mental health." The factors influencing the search volume change of "children's mental health" include Chinese traditional holidays, Spring Festival, National Day, Chinese Mental Health Day, and policies and instructions on children's mental health issued by the PRC Ministry of Education. The public would like to know about "mental health", "handwritten newspaper on mental health" and "adolescent mental health".

(1) Background: With continuous globalization and modernization of people's lives, lifestyle has changed dramatically, with decreased physical activity and increased unhealthy eating patterns in many nations throughout the world. With the COVID-19 pandemic and changes taking place in people’s health and lifestyles around the world, the need for rehabilitation is expected to rise in the coming years.(2)Methods: This paper analyzes the integration model of sports and health care using theoretical analysis, literature reviews, logical reasoning, and other methods.(3)Results: The integration of sports and health care in China has entered the stage of practical implementation after many years of development, forming a few representative integration patterns. Governments, communities, community hospitals, hospitals, and third-party institutions are the main participants, with the community playing an important role in the integration. Pharmacies, sports venues, and schools with sufficient staff have a relatively low participation rate.(4)Conclusion: The grading treatment has been applied in health management and sports rehabilitation, based on the development of digital medicine, a government-led grading treatment model of "health management center" can promote the participation of multiple subjects in the integration of sports and health care, solving the problems existing in the current integration process to a certain extent.

Background: It is clear that breastfeeding is the gold standard of infant feeding because of the many advantages it offers to both the child and the mother. Objective: to identity the main reasons for cessation breastfeeding declares by the mother themselves during the first year. Design: A prospective cohort study was conducted, recruiting 969 newborns in a third level hospital in Spain. The main maternal variables studied were: maternal age, parity, educational level, work occupation, smoking habit, gestational age, birth, weigh, feeding type, and duration of breastfeeding. All the participants were followed for a year to determinate the duration of breastfeeding and to know the reason of the abandonment. Results: At 6 months, the percentage of maternal lactation was cut in half and only 24.6% of these mothers maintain. Mainly 15.80% of the mothers decide to give up the exclusive maternal lactation of their own free desire, and 15.41% because they suspect hypogalactia. The work cause is the third reason of abandonment in both cases. Conclusions: Our results show the need to improve the health policies of promotion, protection and support the initiation of breastfeeding. In particular, our results show the importance of the work factor with particular emphasis on improving conciliation measures.

Since its initial outbreak in late 2019, the COVID-19 pandemic has profoundly affected the global community. In addition to the negative health consequences of contracting COVID-19, the implementation of strict quarantine and lockdown measures has also disrupted social networks and devastated the global economy. As a result, there is rising concern that the pandemic has taken a toll on the mental health of the general population. To better understand its impact, an increasing number of studies examined the effects of the pandemic on mental health and psychosocial implications of enforced quarantine and lockdown. In this article, we aim to review and summarize the findings from a variety of studies that have explored the psychosociological effects of the pandemic and its impact on the mental well-being of the general population. We will also examine how various demographic groups, such as the elderly and youth, can be more susceptible or resilient to the pandemic’s mental health effects. We hope to provide a broader understanding of the underlying causes of mental health issues triggered by the pandemic and provide recommendations that may be employed to address mental health issues in the population over the long-term.

Introduction: The majority of epidemiological reports focus on confirmed cases of COVID-19. In this study, we aim to assess the health and well-being of adults not infected with Covid-19 after two months of quarantine in Morocco. Materials and methods: Two months after the declaration of quarantine in Morocco following the Covid-19 epidemic, we carried out a descriptive cross-sectional study of 279 Moroccan citizens. We used the Short Form Health Survey (SF-12) as a determinant of quality of life, which is based on eight dimensions of health. The data were collected using an electronic questionnaire distributed online. The participants also indicated their socio-demographic data, their knowledge and practices regarding the Covid-19 pandemic and whether they had chronic health problems. Results: The quality of life of all participants was moderately disrupted during the Covid-19 pandemic with a mental health score (MCS) of 34.49 (± 6.44) and a physical health score (PCS) of 36.10 (± 5.82). Participants with chronic diseases scored lower with 29.28 (± 1.23) in mental health (MCS) and 32.51 (± 7.14) in physical health (PCS). The seriousness of COVID-19 has an impact on the quality of life and health well-being of people and this impact is more marked in people with chronic health problems. Conclusion: Our results confirm the need to pay attention to the health of people who have not been infected with the virus. Our results also point out that uninfected people with chronic illnesses may be more likely to have well-being problems due to quarantine restrictions.

Students are regarded as frequent users of mobile phones which has proven to be a convenient and acceptable method to promote healthy lifestyle. Students usually engage in relatively high levels of risky behavior and make unhealthy lifestyle choices, a study that investigates how health students access health information is necessary. The study adopted a descriptive cross-sectional study which was undertaken among third-year nursing students from three nurses training institutions in Ghana. A total of 270 students participated in the study. Most of the respondents who were currently subscribers of the health messages reported that they usually received health information on reproductive health issues, nutrition, and practicing safe sex. Most of the health students revealed that they needed more information on safe sex, diet, managing weight, and stress management. The results also show that health students are likely to remember and share short messages with friends. The findings serve as an ‘eye-opener’ for health educators and mobile service providers concerning factors that should be taken into consideration when framing health text messages that will attract health students.

Background: Drinking and smoking have economic consequences and are the main risk factors of mortality and morbidity. Disease-specific deaths attributable to using substances present the primary health indicator in this study. This analysis focuses on mortality in productive age, 15 to 64 years since those deaths are considered the highest economic burden. Method: In the analytical part, data from the Registry of deaths of the Czech Republic for 1994 to 2017 were used. The number of deaths attributable to smoking and drinking was calculated using attributable fractions, based on literature review. This research aimed to reveal the gender differences in deaths attributable to drinking and smoking, according to age, and the differences in deaths regarding smoking or drinking. Results: The mortality attributable to smoking and drinking differs across age groups and genders. The highest median share of tobacco-related deaths is in the age group, 60—64 years. The highest median share of alcoholic deaths is in the age group of 50—54 years. Conclusions: There are significant differences between genders in both, smoking and drinking. A prevention program should be targeted to different age groups.

Little research has been done on occupational health ramifications of informal electronic waste (e-waste) recycling work, which is increasingly common in low- and middle-income countries, and very little is known about this in high-income countries. Our study evaluated informal and formal e-waste recycling workers in Chile, which was recently recognized as a high-income country. In 2017 we recruited 78 informal recycling workers from two cities, and 15 formal e-waste recycling workers from one recycling facility. Participants completed a questionnaire and health assessment regarding their involvement in, and potential impacts of, e-waste recycling, among other measures. Participants were primarily male, middle-aged, married with children, and had worked in e-waste recycling for an average of 12 years. Participants generally reported good health status, and chronic disease prevalence was similar to the national prevalence. Workers commonly reported exposures to several occupational stressors, including mental health stressors and noise, as well as insufficient income. Occupational injuries were common and use of safety equipment was low. No significant differences were found between informal and formal workers. Informal e-waste workers in Chile face occupational health challenges. The extent to which these issues impact the health of informal Chilean e-waste workers is unclear and warrants further research.

Background. Perinatal depression is one of the leading causes of disability in perinatal women and is highly prevalent in disadvantaged communities in LMICs. However, care capacity remains low in most LMICs. As such, we decided to find and assess a screening program that addresses perinatal mental health problems in a resource-efficient manner. This leads us to a critically appraisal of the Perinatal Mental Health Project (PMHP), a screening program based in peri-urban Western Cape Town that stresses task sharing and stepped care intervention. Method. PubMed, Ovid Medline (1946 to 2018), and Google Scholar were searched for publications until March 2018, with data or evaluation of the PMHP. PMHP website publications were used for data and interpretation. The program’s viability was evaluated based on criteria published by UK National Screening Council. The program’s impact was analyzed using published patient outcome data. Access to care was evaluated at three barriers to accessing care proposed by Gjerdingen et al. (2007). The financial model was evaluated using the “four-pillars” of sustainable organization financial management proposed by León (2001). Findings. The PMHP’s screening program viability satisfies most criteria of the UK National Screening Council, and the program’s benefits outweigh its harms. Patient self-reports indicate successful impact with several highlights in accessibility. The program also demonstrates financial sustainability and potential for scaling-up. Interpretations. The operation model of the PMHP shows satisfactory viability and sustainability. With modifications fitting local context and government cooperation, this model offers promising potential in bringing public health and economic benefits.

Previous research suggests that the economic crisis can affect mental health. The purpose of this study was to analyse the association of risk of poor mental health with various socioeconomic, demographic, health, quality of life and social support variables; and to evaluate the contribution of socioeconomic variables most affected by the beginning of the economic crisis (employment situation and income) on the changes in the prevalence of the risk of poor mental health between 2005 and 2010. A study of prevalence evolution in adult population residents of the Valencian Community in the Spanish Mediterranean was conducted. We studied 5781 subjects in 2005 and 3479 in 2010. Logistic regression models have been adjusted to analyse the association between variables. A standardization procedure was carried out to evaluate which part of the changes in overall prevalence could be attributed to variations in the population structure by age, sex, employment status and income between the years under study. The prevalence of GHQ + increased from 2005 to 2010, in both men and women. Several variables were closely associated with the risk of poor mental health (sex, age, country of birth, number of non-mental chronic diseases, social support, disability, cohabitation in couple, employment status, and income). The changes produced as a result of the onset of the economic crisis in income and unemployment (increase in low income and in unemployment rates) contributed to the increase of poor mental health risk. This could confirm the sensitivity of mental health to the economic deterioration caused by the crisis.

The research is carried out to assess factor affecting the health condition of the elderly people in the slum areas in Sylhet City. This research was quantitative type. In Quantitative approach, primary data were collected and used from the randomly selected elderly people in the Sylhet City slum areas. The secondary data were collected from many articles, documents, newspaper, magazine etc. By analyzing the survey data, it is illustrated that the slum dwellers are deprived from the basic needs. Meanwhile, elderly people can‟t fulfill their medical treatment due to their financial condition because of their work incompatibility. This study identifies the factor affecting health condition such as financial condition, lack of knowledge about proper medical facilities, communication gap between the authority and patient, unemployment, and so on. These factors also affect their health situation. Many diseases like asthma, heart disease are occurred. This study also mentions about the livelihood of slum people are so poor in condition. Due to financial condition, aged people can‟t take their proper treatment and their family member can‟t afford it. This study also understands that the people from slum areas are getting concerned about their medical care. They are easily going to the hospital and take their service because of low pricing. On the other hand, people are meanwhile stopped their treatment of financial situation. This study finds the health situation of elderly people at slum areas in metropolitan city and their consciousness.

Environmental lead exposure is a population health concern in many low- and middle-income countries. Lead is found throughout Myanmar and prior to the 1940s, the country was the largest producer of lead worldwide. The aim of this study was to examine any potential association between lead mining and adult literacy rates at the level of the 330 townships in Myanmar. Townships were identified as lead or non-lead mining areas and 2015 census data were examined with association being identified using descriptive, analytical and spatial statistical methods. Overall, there does appear to be a significant relationship between lead mining activity and adult literacy levels (P<0.05) among townships with both low access [OR= 2.701 (1.136-6.421)] as well as townships with high access to safe sanitation [OR=18.40 (1.794-188.745)]. LISA cluster maps confirm these findings. This exploratory analysis is a first step in the examination of potential environmental lead exposure and its implications in Myanmar.

Objectives: Female genital mutilation (FGM) is a significant public health problem. It is estimated around 14,700 women affected by FGM live in Switzerland, primarily among women with a history of migration. Our qualitative research investigated the sexual health of immigrant women living with FGM in Switzerland, describing their own perception of health, reproductive life and sexuality. Methods: We conducted semi-structured, in-depth interviews with a group of eight immigrant women of African origin living in Switzerland with Type III FGM (infibulation). Results: Seven of the women were from Somalia and one from Ivory Coast. All of the Somali women were mothers and married (two separated), and the Ivorian woman was a single mother. The women in our study reported a low level of sexual satisfaction and reproductive health. They affirmed their desire to improve, or at least change, their condition. Although they rarely talk with their husbands about sexual subject matter, they would like to include them more and improve dialogue. Conclusions: Specific socio-sexual management is recommended when caring for immigrant women living with FGM in order to respond to their specific health care needs. Multidisciplinary approaches may be able to offer more comprehensive health care, including facilitated communication to improve dialogue between women and health care professionals, and eventually between women and their husbands in discussing sexual matter.

In the United States, obesity is prevalent, and it could be described as a pandemic. Obesity is excessive fat accumulation, leading to a BMI ≥ 30 (Fruh, 2017). Surveys conducted by the CDC show that the obesity prevalence in the US is on the rise, as several obese people rose from 30.5% to 41.9% between 1999 and 2020 (Bryan et al., 2021). During the same time, several people suffering from severe obesity rose from 4.7% to 9.2% (Bryan et al., 2021). Additionally, childhood obesity is on the rise. Statistics indicate that between 2017-2020 over 19.7% of children and adolescents aged 2-19 years had obesity. During the same period, obesity prevalence in children aged 2-5 years, 6-11 years, and 12-19 years olds was 12.7%, 20.7%, and 22.2%, respectively (Bryan et al., 2021). With so many people suffering from obesity, the WHO declared it a public health crisis (WHO, 2020). The COVID-19 pandemic further exacerbated the prevalence of obesity in the US. According to the surveys, there was a 4.4% increase in obesity between 2019 to March 2020 due to lifestyle changes that were put on people during the COVID-19 pandemic (Akter et al., 2022). Many comorbidities are associated with obesity. Without adequate health interventions, millions of people could suffer severe health disorders like respiratory problems, type II diabetes, psychological issues, gastrointestinal disorders, and cardiovascular diseases. It is also essential to develop health interventions to mitigate obesity due to its strain on the healthcare system. Research shows that people suffering from obesity spend $2,505 more than people with average weight on healthcare (Cawley et al., 2021). Obesity has financial ramifications in every healthcare category: inpatient, outpatient, and prescription drugs (Cawley et al., 2021). One essential action toward the efforts to mitigate the soaring obesity rates is understanding the demographic inequities across populations and how they can be resolved.

Under the dual background of underemployment and health inequality, this paper empirically analyzes the impact of education level on underemployed workers’ health based on CLDS2016 data. The results show that underemployment is significantly related to the decline of self-rated health, increased depression tendency, and morbidity in a certain period. The results indicate that underemployment can significantly reduce the health level of workers in the low education level group and the high education level group. However, it has no significant impact on workers’ health in the middle education level group; even if we change the measurement method of indicators and consider endogeneity, the research conclusion is still robust. Moreover, this kind of health inequality mainly comes from the difference in economic effect and leisure effect of underemployment to workers with different educational levels. This paper provides empirical support for increasing the labor protection mechanism of underemployed people and reducing the health inequality caused by educational level differences.

Objective: ISPOR is the leading professional society for health economics and outcomes research (HEOR) globally. Recently, it launched its Women in HEOR Initiative, that aims to serve as a catalyst for women’s leadership in the field. Therefore, we were interested to find out how well ISPOR itself is doing in terms of gender diversity at their biggest conference. Methods: We used the conference programmes of ISPOR Europe conferences in 2016, 2017 and 2018 to assess the gender distribution of speakers that participated in issue panels and plenary sessions in these years. Results: 70% of all speakers (N=346) at 85 issue panels and plenary sessions during 2016, 2017, and 2018 were male. Almost one in three panels was all-male (a ‘manel’) and 64% of all panels had mostly male speakers (>50%). In contrast, only 11% of panels had <50% female speakers. Conclusion: Despite laudable effort to support the growth, development and contribution of women in HEOR through its Women in HEOR Initiative, females appear to be severely underrepresented at ISPOR’s biggest conference. ISPOR should make gender diversity a formal requirement for issue panel abstract submissions if it wants to advance women’s leadership in HEOR.

Postpartum depression (PPD) can predispose to physical and mental health problems in women. However, PPD is associated with health and perceived social support but their causal relationship is unclear. Therefore, this study intended to evaluate the association of PPD with insomnia, mental health, and physical health. Convenience sampling technique was used to collect data from 320 (52.8 %) young and middle aged postpartum women, in the outpatient departments of obstetrics and gynecology in Government Maula Bakhsh Hospital, District Head Quarter in Sargodha, Pakistan. The Edinburgh Postnatal depression scale, Pittsburg sleep quality index, Warwick-Edinburgh mental wellbeing scale, Patient health questionnaire, and Multidimensional scale of perceived social support were used to measure study variables. Results revealed a significant positive relationship of PPD with physical health (r= .45, p=.001), while a negative relationship with insomnia (r= -.24, p<.001), and perceived social support (r= -.38, p=.001). Results further confirmed that perceived social support played a moderating role (β = .97, p=.01) in the relationship between PPD and mental health among females. This study concluded that perceived social support has an important role in PPD and women’s health. The study also concluded that poor health is a risk indicator for identifying aid in the early stages of postpartum among women.

As a result of the COVID-19 pandemic, as well as other outbreaks such as SARS and Ebola, bats are recognized as a critical species for mediating zoonotic infectious disease spillover events. While there is a growing concern of increased antimicrobial resistance (AMR) globally during this pandemic, knowledge of AMR circulating between bats and humans is limited. In this paper, we have reviewed the evidence of AMR in bats and discussed the planetary health aspect of AMR to elucidate how this is associated with the emergence, spread and persistence of antibiotic resistance at the human-animal interface. The presence of clinically significant resistant bacteria in bats and wild life has reflective and broad impact on zoonotic pandemic surveillance, disease transmission and treatment modalities. We searched MEDLINE through PubMed and Google Scholar to retrieve relevant studies (n=38) that provided data on resistant bacteria in bats till September 30, 2022. There is a substantial variability in the results from studies measuring the prevalence of AMR based on geographic location, bat types and time. We found all major groups of gram positive and gram negative bacteria in bats which are resistant to commonly used antibiotics. The most alarming issue is- recent studies have increasingly identified Methicillin Resistant Staphylococcus aureus (MRSA), ESBL producing and Colistin resistant Enterobacteriaceae in samples from bats. This evidence of superbugs abundance in both humans and wild mammals like bats, could facilitate a greater understanding of which specific pathways of exposure should be targeted. We believe that these data will also facilitate future pandemic prepareness as well as global AMR containment during the pandemic events and beyond.

Worldwide, depressive disorder is one of the leading determinants of disability-adjusted life years. Although the benefits associated with physical activity (PA), there is a lack of information related to depression, especially in countries like Czechia, where modern approaches to mental health care only recently emerged. The PA levels were associated with aspects of depression such as clinician-diagnosed history; different severities; continuous depression scores; and specific symptoms that characterize the depression. The multivariable-adjusted Poisson regression models were carried out on 2123 participants (45.3% men, median 48 years). Compared to subjects with insufficient PA, the moderate and high PA levels were inversely associated with clinician-diagnosed depression history (respectively, prevalence rate [PR]= 0.84; 95% CI 0.66-0.82 and PR=0.50; 95% CI 0.36-0.67); and with continuous depression scores (PR=0.85; 95% CI 0.75-0.97; and PR=0.79; 95%CI 0.70-0.90).; but only high PA showed association with depression categories (PR=0.75; 95%CI 0.60-0.95). Depressed mood and worthlessness were the symptoms associated with moderate and high PA. Tiredness, change in appetite, and problems with concentration only with high PA. Although only high PA was sufficient for people intending changes among depression categories, the moderate PA may be enough for slight changes in depressive symptoms, and a good strategy when starting.

Background: The COVID-19 pandemic has seen a considerable expansion in the way work settings are structured with a continuum emerging between working fully in-person and from home. The pandemic has also exacerbated many risk factors for poor mental health in the workplace, especially in public-facing jobs. Therefore, we sought to test the potential relationship between work setting and self-rated mental health. Methods: We modeled the association of work setting (only working from home, only in-person, hybrid) on self-rated mental health (Excellent/Very Good/Good vs. Fair/Poor) in an online survey of Canadian workers during the 3rd wave of COVID-19. Mediating effects of vaccination, masking, and distancing were explored due to the potential effect of COVID-19 related worries on mental health among those working in-person. Results: Among 1,576 workers, most reported hybrid work (77.2%). Most also reported good self-rated mental health (80.7%). Exclusive work from home (aOR: 2.79, 95%CI:1.90,4.07) and exclusive in-person work (aOR: 2.79, 95%CI: 1.83,4.26) were associated with poorer self-rated mental health than hybrid work. Vaccine status mediated only a small proportion of this relationship (7%), while masking and physical distancing were not mediators. Conclusion: Hybrid work arrangements were associated with positive self-rated mental health. Compliance to vaccination, masking, and distancing did not meaningfully mediate this relationship.