Mental disorders during the pandemic of a new coronavirus infection: causes and predisposing factors.

Objective: to study the causes and predictors of mental disorders during the COVID-19 epidemic in those who turned to psychiatrist for the first time, as well as in patients with already diagnosed mental illness. Patients and methods. We examined 100 patients who turned to a psychiatrist due to a deterioration in their mental state during the pandemic, 50 patients were newly diagnosed (Group 1) and 50 with previously diagnosed mental disorders (Group 2). The study was carried out by a clinical method using a specially designed map, followed by statistical processing of the obtained data. Results and discussion. Mental disorders caused by the COVID-19 pandemic more often occurred at a young age, in patients with higher and secondary specialized education, and in single patients. In the 1st group, as a result of exposure to psychogenic factors (the influence of the media, quarantine, economic changes), anxiety (36.8%) and depressive (21.1%) disorders occurred more often, and after the coronavirus infection, depressive disorders were in the first place (54.2%). The 2nd group mostly included patients with endogenous disorders (bipolar affective disorder - 24%, recurrent depressive disorder - 20%, schizophrenia - 20%), which were exacerbated more often as a result of COVID-19, to a lesser extent - psychogenic (experiences associated with a change in material status and illness of relatives). Obsessive-compulsive disorder, generalized anxiety disorder, somatoform disorders have been associated with epidemic factors. Conclusion. The results obtained indicate that there are differences between the mental disorders that first appeared during the pandemic and the exacerbations of the condition in mentally ill patients, which relate to the predictors, causes and clinical manifestations of these disorders.Copyright © 2022 Ima-Press Publishing House. All rights reserved.

Meeting the challenge of gender inequality through gender transformative research: lessons from research in Africa, Asia, and Latin America

While the global development agenda has prioritized gender equality, many challenges remain, and the COVID-19 crisis has exacerbated inequalities. Gender transformative approaches to social change have the potential to address the underlying causes of inequality. This paper draws insights from studies funded by Canada's International Development Research Centre to understand how integrating gender transformative approaches to research can support social change. The findings suggest that gender transformative research is most successful in supporting change when it analyzes and addresses the multiple causes of inequality, takes an intersectional and structural approach, embeds the research in local contexts, and engages power holders and perpetrators of inequality.Alternate :RÉSUMÉSi les objectifs de développement mondial ont donné la priorité à l'égalité des genres, il y a encore de nombreux défis à relever dans ce domaine et la crise de la COVID-19 a exacerbé les inégalités. Les approches transformatrices du genre nous permettent de faire face aux causes sous-jacentes de ces inégalités. Cet article base son analyse sur des études financées par le Centre de recherches pour le développement international, au Canada, et vise à mieux comprendre comment l'adoption d'approches transformatrices du genre dans le contexte de la recherche peut appuyer le changement social. Nos résultats suggèrent que la recherche se basant sur une approche transformatrice du genre a de meilleurs chances d'inciter des changements sociaux lorsqu'elle analyse et répond aux différentes causes des inégalités, lorsqu'elle adopte une approche intersectionnelle et structurelle, lorsqu'elle intègre la recherche dans des contextes locaux et lorsqu'elle confronte les détenteurs du pouvoir et les responsables des inégalités.

Agility in supply chain planning and execution

For variability that can be described by a distribution function or estimated using frequency of occurrence, the combination of new digital sources of data and advanced analytics/optimization techniques is the subject of a lot of recent work in academia. However, not much has been written on the design and implementation of decision systems to detect and respond to "special," uncertain, and non-predictable causes of variation. The recent COVID-19 pandemic is an all too real example of how disruptive this variation can be to the unprepared. Clearly, structurally flexible and short lead time supply chains can help. Beyond this flexibility, we introduce the concept of agile supply chain planning, which deals with early detection and quick and effective decision-making. This chapter describes how agile supply chain planning systems can complement the advances made in dealing with normal variation by successfully dealing with "special" events and lead to significant impact both for drastic, generalized crises or less dramatic occasions. Keywords: agile;decision making;planning;execution;uncertainty, special causes of variation;digital fact based. © Springer Nature Switzerland AG 2023. All rights reserved.

Advances in Management of the Stroke Etiology One-Percenters.

PURPOSE OF REVIEW: Uncommon causes of stroke merit specific attention; when clinicians have less common etiologies of stoke in mind, the diagnosis may come more easily. This is key, as optimal management will in many cases differs significantly from "standard" care. RECENT FINDINGS: Randomized controlled trials (RCT) on the best medical therapy in the treatment of cervical artery dissection (CeAD) have demonstrated low rates of ischemia with both antiplatelet and vitamin K antagonism. RCT evidence supports the use of anticoagulation with vitamin K antagonism in "high-risk" patients with antiphospholipid antibody syndrome (APLAS), and there is new evidence supporting the utilization of direct oral anticoagulation in malignancy-associated thrombosis. Migraine with aura has been more conclusively linked not only with increased risk of ischemic and hemorrhagic stroke, but also with cardiovascular mortality. Recent literature has surprisingly not provided support the utilization of L-arginine in the treatment of patients with mitochondrial encephalopathy, lactic acidosis, and stroke-like episodes (MELAS); however, there is evidence at this time that support use of enzyme replacement in patients with Fabry disease. Additional triggers for reversible cerebral vasoconstriction syndrome (RCVS) have been identified, such as capsaicin. Imaging of cerebral blood vessel walls utilizing contrast-enhanced MRA is an emerging modality that may ultimately prove to be very useful in the evaluation of patients with uncommon causes of stroke. A plethora of associations between cerebrovascular disease and COVID-19 have been described. Where pertinent, authors provide additional tips and guidance. Less commonly encountered conditions with updates in diagnosis, and management along with clinical tips are reviewed.

Mental disorders during the pandemic of a new coronavirus infection: causes and predisposing factors

Objective: to study the causes and predictors of mental disorders during the COVID-19 epidemic in those who turned to psychiatrist for the first time, as well as in patients with already diagnosed mental illness. Patients and methods. We examined 100 patients who turned to a psychiatrist due to a deterioration in their mental state during the pandemic, 50 patients were newly diagnosed (Group 1) and 50 with previously diagnosed mental disorders (Group 2). The study was carried out by a clinical method using a specially designed map, followed by statistical processing of the obtained data. Results and discussion. Mental disorders caused by the COVID-19 pandemic more often occurred at a young age, in patients with higher and secondary specialized education, and in single patients. In the 1st group, as a result of exposure to psychogenic factors (the influence of the media, quarantine, economic changes), anxiety (36.8%) and depressive (21.1%) disorders occurred more often, and after the coronavirus infection, depressive disorders were in the first place (54.2%). The 2nd group mostly included patients with endogenous disorders (bipolar affective disorder - 24%, recurrent depressive disorder - 20%, schizophrenia - 20%), which were exacerbated more often as a result of COVID-19, to a lesser extent - psychogenic (experiences associated with a change in material status and illness of relatives). Obsessive-compulsive disorder, generalized anxiety disorder, somatoform disorders have been associated with epidemic factors. Conclusion. The results obtained indicate that there are differences between the mental disorders that first appeared during the pandemic and the exacerbations of the condition in mentally ill patients, which relate to the predictors, causes and clinical manifestations of these disorders.Copyright © 2022 Ima-Press Publishing House. All rights reserved.

Adolescent obesity and its main causes - analysis and review

The prevalence of adolescent obesity has risen globally, and it still shows an increasing trend. Adolescent obesity is also related to many chronic diseases, such as metabolic syndrome and cardiovascular disease. Obesity at a young age may also lead to psychological problems in teenagers. It's important to identify the causes of adolescent obesity to better prevent and treat it. This article focuses on finding different factors that lead to adolescent obesity using the previous data and research results. It is found that individual factors, social factors, and COVID-19 can all affect adolescent obesity. Individual factors include genetics, gut microbiota, hormones, and physical activities. Adolescent obesity can also be influenced by social factors such as diets, psychology, and eating behaviors. During the pandemic, COVID-19, lockdown, and quarantine all contributed to adolescent obesity. © 2023 SPIE.

Mental disorders during the pandemic of a new coronavirus infection: causes and predisposing factors.

Objective: to study the causes and predictors of mental disorders during the COVID-19 epidemic in those who turned to psychiatrist for the first time, as well as in patients with already diagnosed mental illness. Patients and methods. We examined 100 patients who turned to a psychiatrist due to a deterioration in their mental state during the pandemic, 50 patients were newly diagnosed (Group 1) and 50 with previously diagnosed mental disorders (Group 2). The study was carried out by a clinical method using a specially designed map, followed by statistical processing of the obtained data. Results and discussion. Mental disorders caused by the COVID-19 pandemic more often occurred at a young age, in patients with higher and secondary specialized education, and in single patients. In the 1st group, as a result of exposure to psychogenic factors (the influence of the media, quarantine, economic changes), anxiety (36.8%) and depressive (21.1%) disorders occurred more often, and after the coronavirus infection, depressive disorders were in the first place (54.2%). The 2nd group mostly included patients with endogenous disorders (bipolar affective disorder - 24%, recurrent depressive disorder - 20%, schizophrenia - 20%), which were exacerbated more often as a result of COVID-19, to a lesser extent - psychogenic (experiences associated with a change in material status and illness of relatives). Obsessive-compulsive disorder, generalized anxiety disorder, somatoform disorders have been associated with epidemic factors. Conclusion. The results obtained indicate that there are differences between the mental disorders that first appeared during the pandemic and the exacerbations of the condition in mentally ill patients, which relate to the predictors, causes and clinical manifestations of these disorders.Copyright © 2022 Ima-Press Publishing House. All rights reserved.

Assessment of shifts in mortality age profile of adult population in Moscow during pandemic

Introduction. The COVID-19 pandemic induced the global crisis of mortality. Delayed medical care and reduced availability under quarantine restrictions have led to an increase in mortality not only from COVID-19, but also from chronic non-communicable diseases, affecting men and women of different ages to varying degrees. The study purpose is to assess shifts in mortality age profile of population aged 20+ in Moscow during COVID-19 pandemic. Materials and methods. Official vital statistics of Rosstat, operational information from civil registration database on death causes in Moscow. Results. The gain in mortality rate caused primarily by deaths from COVID-19 interrupted in 2020 the positive demographic dynamics that had developed over the previous years. In 2021, the increase in the mortality rate continued, but the loss of life expectancy was lower due to a decrease in mortality in older ages and the return of most indicators to the level of 2019. However, from a socio-economic point of view, the situation in 2021 developed more negatively, since the age structure of life expectancy losses is younger than in 2020. Limitations. The study results are based on operational information of the Moscow civil registration office and could be used for the development of managerial decisions for Moscow only. Conclusion. Against the pandemic demographic situation in Moscow has worsened. Due to mortality gain in the Russia's capital first in the past years recorded natural population decline. © 2022 Izdatel'stvo Meditsina. All rights reserved.

Personalized, context-aware, and adaptable persuasive approach for encouraging physical activity among older adults

Seclusion and sedentary lifestyle are the main causes of many psychological and physical health problems. They may be among the top 10 causes of death and disability in the world. The pandemic crisis context of COVID has deepened these problems, especially for older adults who have been isolated, deprived of their relatives and of doing physical activities. In this paper, we introduce an adaptive, personalized, and context-aware persuasive platform to stimulate physical activities of older adults without deception or coercion. Our persuasion approach is customizable, in the sense that every older adult has its personal profile. It is also adaptive because it can use a persuasion loop to change the persuasion strategy when the older adult does not adhere to the proposed persuasion strategy. Furthermore, our persuasion approach is context-aware as it takes account of contextual location and weather information in the provision of the persuasion strategy. To validate our approach, we implemented "ActiveSenior”. Then, we carried out a large-scale challenge for one month to approve the results of our persuasive approach. The evaluation of the acceptance of our ActiveSenior system was encouraging as most of the interviewed participants were satisfied. In addition, the obtained results showed a marked improvement in the physical activity of older adults, quantified by the number of steps taken per day. © 2023 Elsevier B.V.

COVID-19 vaccine rejection causes based on Twitter people's opinions analysis using deep learning.

According to the World Health Organization, vaccine hesitancy was one of the ten major threats to global health in 2019, including the COVID-19 vaccine. The availability of vaccines does not always mean utilization. This is because, people have less confidence in vaccines, which resulted in vaccination hesitancy and developing global decline in vaccine intake and has caused viral disease outbreaks worldwide. Therefore, there is a need to understand people's perceptions about the COVID-19 vaccine to help the manufacturing companies of the vaccine to improve their marketing strategy based on the rejection causes. In this paper, we used multi-class Sentiment Analysis to classify people's opinions from extracted tweets about COVID-19 vaccines, using firstly different Machine Learning (ML) classifiers such as Logistic Regression (LR), Stochastic Gradient Descent, Support Vector Machine, K-Nearest Neighbors, Decision Tree (DT), Multinomial Naïve Bayes, Random Forest and Gradient Boosting and secondly various Deep Learning (DL) models such as Recurrent Neural Network (RNN), Long Short Term Memory (LSTM), Gated Recurrent Unit (GRU), RNN-LSTM and RNN-GRU. Then, we investigated the analysis of the negative tweets to identify the causes of rejection using the Latent Dirichlet Allocation (LDA) technique. Finally, we classified these negative tweets according to the rejection causes for all the vaccines using the same selected ML and DL models. The result of SA showed that DT gives the best performance with an accuracy of 92.26% and for DL models, GRU achieved 96.83%. Then, we identified five causes: Lack of safety, Side effect, Production problem, Fake news and Misinformation, and Cost. Furthermore, for the classification of the negative tweets according to the identified rejection causes, the LR achieved the best result with an accuracy of 89.97%. For DL models, the LSTM model showed the best result with an accuracy of 91.66%.

Reactive surveillance of suicides during the COVID-19 pandemic in France, 2020 to March 2022.

AIMS: Mitigation actions during the COVID-19 pandemic may impact mental health and suicide in general populations. We aimed to analyse the evolution in suicide deaths from 2020 to March 2022 in France. METHODS: Using free-text medical causes in death certificates, we built an algorithm, which aimed to identify suicide deaths. We measured its retrospective performances by comparing suicide deaths identified using the algorithm with deaths which had either a Tenth revision of the International Classification of Diseases (ICD-10) code for 'intentional self-harm' or for 'external cause of undetermined intent' as the underlying cause. The number of suicide deaths from January 2020 to March 2022 was then compared with the expected number estimated using a generalized additive model. The difference and the ratio between the observed and expected number of suicide deaths were calculated on the three lockdown periods and for periods between lockdowns and after the third one. The analysis was stratified by age group and gender. RESULTS: The free-text algorithm demonstrated high performances. From January 2020 to mid-2021, suicide mortality declined during France's three lockdowns, particularly in men. During the periods between and after the two first lockdowns, suicide mortality remained comparable to the expected values, except for men over 85 years old and in 65-84 year-old age group, where a small number of excess deaths was observed in the weeks following the end of first lockdown, and for men aged 45-64 years old, where the decline continued after the second lockdown ended. After the third lockdown until March 2022, an increase in suicide mortality was observed in 18-24 year-old age group for both genders and in men aged 65-84 years old, while a decrease was observed in the 25-44 year-old age group. CONCLUSIONS: This study highlighted the absence of an increase in suicide mortality during France's COVID-19 pandemic and a substantial decline during lockdown periods, something already observed in other countries. The increase in suicide mortality observed in 18-24 year-old age group and in men aged 65-84 years old from mid-2021 to March 2022 suggests a prolonged impact of COVID-19 on mental health, also described on self-harm hospitalizations and emergency department's attendances in France. Further studies are required to explain the factors for this change. Reactive monitoring of suicide mortality needs to be continued since mental health consequences and the increase in suicide mortality may be continued in the future with the international context.

COVID-19 Mortality in the Colorado Center for Personalized Medicine Biobank.

Over 6.37 million people have died from COVID-19 worldwide, but factors influencing COVID-19-related mortality remain understudied. We aimed to describe and identify risk factors for COVID-19 mortality in the Colorado Center for Personalized Medicine (CCPM) Biobank using integrated data sources, including Electronic Health Records (EHRs). We calculated cause-specific mortality and case-fatality rates for COVID-19 and common pre-existing health conditions defined by diagnostic phecodes and encounters in EHRs. We performed multivariable logistic regression analyses of the association between each pre-existing condition and COVID-19 mortality. Of the 155,859 Biobank participants enrolled as of July 2022, 20,797 had been diagnosed with COVID-19. Of 5334 Biobank participants who had died, 190 were attributed to COVID-19. The case-fatality rate was 0.91% and the COVID-19 mortality rate was 122 per 100,000 persons. The odds of dying from COVID-19 were significantly increased among older men, and those with 14 of the 61 pre-existing conditions tested, including hypertensive chronic kidney disease (OR: 10.14, 95% CI: 5.48, 19.16) and type 2 diabetes with renal manifestations (OR: 5.59, 95% CI: 3.42, 8.97). Male patients who are older and have pre-existing kidney diseases may be at higher risk for death from COVID-19 and may require special care.

A Lightweight CNN Architecture for Chest X-ray Images Analysis to Facilitate Early Stage Detection of Lung Diseases

Lung-related diseases are one of the significant causes of death among infants and children. However, the mortality rate can be reduced by the detection of lung abnormality at an early stage. Traditionally, radiologists identify irregularities by interpreting chest x-ray images which is time-consuming. Therefore, researchers have proposed many automated systems for diagnosing pneumonia and other lung-related diseases. Due to the remarkable performance of Convolutional Neural Networks(CNN) in image classification, it has gained immense popularity in chest x-ray image analysis. Most of the research has utilized famous pre-trained Imagenet models for more accurate analysis of Chest X-ray images. However, the problem with these architectures is that they have many parameters that increase the training time, which makes the detection process lengthy. This paper introduces a lightweight, compact, and well-tuned CNN architecture with far fewer parameters than the pre-trained model to analyze two of the most common lung diseases, pneumonia and Covid-19. We have evaluated our model on two benchmark datasets. Experimental results show that our lightweight CNN model has far fewer hyperparameters than other state-of-the-art models but achieves similar results. We have achieved an accuracy of 90.38% on the kermany dataset and 96.90% on the Covid-19 Radiography dataset. © 2022 IEEE.

IoT-Based Heart Monitoring System Implementation and Analysis

This paper presents an IoT-based heart monitoring system using 8266 NodeMCU. According to the Malaysian Department of Statistics, ischemic heart disease is the leading cause of death, accounting for 15.0% of the 109,164 medically certified deaths in 2019. The coronary heart is a vital organ that pumps oxygen and blood across the body. Meanwhile, if the heart is not getting sufficient oxygen, the patient will experience chest pain, typically on the left side of the body, which can be mistaken for a heart problem. During the Covid-19 pandemic, a patient cannot attend regular treatment at the hospital as it is operating at full capacity. During this phase, the hospital can only focus on the critical and high-risk patient. The proposed heart monitoring system monitors the patient by measuring the heart rate and oxygen level in the comforts of home. Therefore, the patient can provide his current health record for the doctor's evaluation. The idea behind this proposed system is to construct an IOT-based system that automatically monitors the health condition in terms of heartbeat and oxygen detection. The prototype provides data to the Blynk for the patient and the I-Heart web-based application for the medical practitioner. © 2022 IEEE.

Analysis of Causes of Maternal Death in East Java Province, Indonesia

BACKGROUND: The maternal mortality rate is an indicator that reflects the mother's health status, especially the risk of death for the mother during pregnancy and childbirth. Measles, Mumps, and Rubella (MMR) has a close relationship with efforts to increase human development. Therefore, efforts are needed to reduce MMR by identifying the factors that influence MMR. AIM: The aim of the study was to analyze the factors causing the incidence of Maternal Death in East Java Province. METHOD(S): The research design used in this research is a quantitative research using descriptive-analytical. The population of this research is districts/cities in East Java Province, with a sample of 38 districts/cities. The research period starts from August to September 2021. Data analysis using grouping and percentage of cases. RESULT(S): The results of the study found that cases of maternal death in East Java due to postpartum hemorrhage in 2021 were 131 cases. Cases due to hypertension as many as 115 cases. Cases due to infection as many as 25 cases. The incidence of maternal death due to abortion is 1 case. There were 13 cases of maternal death due to blood disorders. There were 6 cases of maternal death due to metabolic disorders - cases of maternal death due to Heart as many as 54 cases. Maternal deaths due to COVID-19 were 793 cases. CONCLUSION(S): Factors causing maternal death in East Java Province, namely, hypertension bleeding, infection, abortion, blood disorders, heart metabolic disorders, and COVID-19. The most influential factor in maternal mortality in 2021 is COVID-19.Copyright © 2023 Maharani Maharani, Sutrisno Sutrisno.

Analysis of lethal outcomes in COVID-19 convalescents in multidisciplinary hospital

Health status of COVID-19 convalescents poses a serious burden on the healthcare system due to frequent decompensation of existing diseases and high mortality after episode of infection. This requires an analysis of not only the causes of death, but also the time of occurrence of complications in order to implement preventive measures and potentially reduce mortality Aim. The aim of the study was to carry out a clinical and pathoanatomical analysis of fatal outcomes in convalescents of COVID-19 in a multidisciplinary hospital. Material and Methods. The medical documentation of 67 deceased patients with a documented history of COVID-19 was analyzed. Patients were divided into five groups based on the nosological principle. Results. The study showed that the absolute majority of fatal outcomes occurred within one to two months (chi2 = 15.53;p = 0.001;df = 1);after that, the mortality rate gradually decreased over time. The rate of patients who died from acute and chronic decompensated cardiac diseases was 63%, which may be attributed to the specifics of the hospital. The number of neglected oncological diseases was 21% in our sample, which also should be considered a negative impact of the pandemic. In our study, the neglected oncological diseases were observed in 45% of patients, which was probably due to the profile of the hospital. The incidence rate of pulmonary embolism and other thrombotic complications was significantly higher in women (chi2 = 30.73;p < 0.001;df = 1). While comparing the time between recovery from COVID-19 and onset of death, we found that thrombotic complications occurred more often either immediately or within one to two months after recovery from COVID-19;sometimes patients already had a formed lung infarction, but in these cases the interval was longer (four to six months), which suggested the beginning of thrombosis during the acute stage of disease. Conclusion. At the early stage, it is necessary to analyze basic information about the epidemiology of post-COVID-19 syndrome taking into account patient age and comorbidities. Given the high frequency of deaths, most often associated with thrombotic events or disorders of the cardiovascular system, it is necessary to plan clinical and laboratory tests, appropriate registries and clinical trials in order to properly assess thee risks and prepare for the long-term consequences of COVID-19. © 2022 Tomsk State University. All rights reserved.

CAUSES OF DEATH IN TURKEY: HOW THE INCREASE IN THE BURDEN OF COMMUNICABLE DISEASES VARY BY SEX AND AGE?

Causes of death statistics are essential tools for public health, but Turkey lags in the number of studies on causes and trends of death. This study measures causes and trends of death in Turkey for the 2013-2019 period, with special emphasis on the increase in communicable diseases (CDs). This study has a representative research design based on the national population and cause of death registration systems. Causes of death with International Classification of Diseases, Tenth Revision (ICD-10) codes were grouped and garbage codes were determined and redistributed. To understand how the increase in the burden of CDs vary by sex and age, modal age at death, age-specific death rates, probability of eventual death, years of life lost (YLL) due to three main causes of death were calculated by using discrete absorbing Markov chain model. According to results, modal age at death among male population shifted to older ages, the share of respiratory infectious diseases and other infectious and parasitic diseases increased rapidly between 2013 and 2019, just before the onset of COVID-19 pandemic. Overall, our results suggest that burden of CDs increased for both sexes, and elderly male population was among the most effected group. Since non-communicable diseases were still the leading causes of death, increasing rate of CDs may create an extra burden on health system.Alternate abstract: Ölüm nedeni istatistikleri, halk sağlığı için çok önemli araçlardır, ancak Türkiye ölüm nedenleri ve eğilimlerine ilişkin yapılan çalışmalarda geride kalmaktadır. Bu çalışma, bulaşıcı hastalıklardaki (BH'lerdeki) artışa özel bir vurgu yaparak, 2013-2019 döneminde Türkiye'deki ölüm nedenlerini ve eğilimlerini değerlendirmektedir. Çalışma, ulusal nüfus ve ölüm nedeni kayıt sistemlerine dayalı temsili araştırma tasarımına sahiptir. Uluslararası Hastalık Sınıflandırması Onuncu Revizyon (UHS-10) kodlarına sahip tüm ölüm nedenleri gruplandırılmış ve çöp kodlar belirlenerek ölüm nedenleri içinde yeniden dağıtılmıştır. BH yükündeki artışın cinsiyete ve yaşa göre nasıl değiştiğini anlamak için ayrık Markov zinciri modellemesi kullanılmış ve en fazla ölümün meydana geldiği yaş, üç ana ölüm nedenine göre yaşa özel ölüm oranları, ölüm olasılıkları ve kaybedilen yaşam yılları hesaplanmıştır. Çalışmanın sonuçlarına göre, erkek nüfusta en fazla ölümün meydana geldiği yaş daha ileri yaşlara kaymış;her iki cinsiyette de 2013-2019 yılları arasında- COVID-19 pandemisinin başlamasından hemen önce- solunum yolu enfeksiyon hastalıkları ile diğer bulaşıcı ve parazit hastalıkların payı hızla artmıştır. Genel olarak, sonuçlarımız her iki cinsiyet için de BH yükünün arttığını ve yaşlı erkek nüfusunun en çok etkilenen grup arasında olduğunu göstermektedir. Bulaşıcı olmayan hastalıklar hala önde gelen ölüm nedenleri olduğundan, artan BH oranları sağlık sistemi üzerinde fazladan bir yük oluşturabilir.

Impact of a new coronavirus infection on causes of death in Moscow and St. Petersburg.

The distribution of causes and mortality rates in Moscow and St. Petersburg (SPb) are different. Objective. To analyze changes in the distribution of causes of death in Moscow and St. Petersburg related to the COVID-19 pandemic. Material and methods. The data were used on the annual average population and the annual number of deaths in one-year age groups according to Rosstat for 2019-2021. Standardized mortality rates based on the European standard were calculated. An ABC analysis of the deaths and causes of death in the two cities was performed. Results. Despite the new coronavirus infection, mortality rates in St. Petersburg exceeded those in Moscow by 20% for three years. ABC analysis of the cause of death distribution showed a sharp decrease in the number of causes responsible for 80% of deaths. The 50 leading causes of death in St. Petersburg were more consistent. In the list of causes, mortality due to malignant neoplasms of various localizations in Moscow has shifted down by 3-11 positions, and in St. Petersburg, it increased by 10 positions. The proportion of malignant neoplasms exceeds half of the deaths due to gastrointestinal and respiratory diseases. Mortality from cardiovascular diseases in Moscow was 30% lower in 2021. Mortality from diseases associated with the gastrointestinal tract tended to decrease in both cities. Mortality from respiratory diseases was 15-20% lower in Moscow. The changing distribution of causes of death during a pandemic was expected for several reasons. In Moscow, compared to St. Petersburg in 2020, the <<coronavirus infection>> diagnosis was apparently used more <<cautiously>> as a cause of death. Conclusion. The coronavirus pandemic had a significant impact on mortality rates and distribution. The trends of mortality changes during the analyzed period were often inconsistent;however, mortality from leading causes in St. Petersburg remained higher than in Moscow.Copyright © 2023, Media Sphera Publishing Group. All rights reserved.

A retrospective study to find out factors affecting maternal mortality in a tertiary care hospital in Ahmedabad city, Gujarat

Background : Data pertaining to preventable causes of maternal mortality are valuable in each set up to design interventional steps for the significant reduction of the maternal mortality ratio. Objectives : (1) To study the trend on Maternal Mortality Rate (MMR);(2) To find out the factors for the Maternal Mortality. Material and Methods : A retrospective cross-sectional study of maternal death was conducted in the Obstetrics Department of Tertiary Care Hospital of Ahmedabad city. The data of total 9 years from 1st April 2013 to 31st January 2021 were taken in the study. Epidemiological factors and causes affecting maternal mortality were assessed through pretested questionnaire that includes parity, duration between admission and mortality etc. Results: Maternal Mortality Rate (MMR) was 180.2 per 1 lac live births during the study period. Young mothersaged 20 to 30 years (78.5%), and rural residence (76.6%), multiparous mothers (66.7%)were at risk for Maternal Mortality. Obstetric haemorrhage (25.8%) was the most common cause whereas COVID-19 pandemic later on were indirect causes contributing to Maternal Mortality. Conclusion: Great Care should be taken for high-risk pregnancy like young age, multiparous women and also of postpartum women. Postpartum haemorrhage was the commonest direct cause of Maternal Mortality. Strengthening of existing obstetric care facilities, facility for easy transport, appropriate referral linkages are keys to reduce Maternal Mortality to further extent.

Neonatal mortality in Ukraine against COVID-19 pandemic: do not lose vigilance

Purpose - to highlight the peculiarities of mortality of children in the first year of life (absolute number and level by individual causes and gender) in Ukraine in 2019-2020;to find out whether there have been changes during the year of the COVID-19 pandemic in the country that could hinder the achievement of the SDGs in the area of reducing child mortality. Materials and methods. The information base of the study was the official data from the State Statistics Service of Ukraine regarding the distribution of deceased children by sex, age groups, place of residence and causes of death in 2019-2020. For comparative analysis were used a data from the Statistics Poland and World Population Review (USA) databases. In the course of the analysis were used the following methods: systematic approach, bibliosemantic, epidemiological, statistical, graphical representation. Results. It has been shown that approximately 80% in the structure of mortality under the age of 1 year in Ukraine are accounted for by two main causes: certain conditions that occur in the perinatal period - 58.5% (in 2019 - 54%) and congenital malformations - 22.3% (in 2019 - 25%). The focus is on preventable causes (first of all, external causes and infectious diseases). In 2020 were reported six deaths under the age of 1 year due to COVID-19 firstly. Despite the decline in infant mortality in 2019-2020 from 7.0 to 6.7 per 1000 live births, indicates the likelihood of a negative impact of the COVID-19 pandemic on infant mortality in Ukraine, primarily as a result of the influence of indirect factors, and the need for actions to eliminate or minimize such influence. Conclusions. An analysis of the spectrum and weight of the contribution of the causes of death is a tool for determining the lines and scope of intervention to prevent them on the way to Ukraine achieving by 2030 the declared indicator of infant mortality in children aged 0-4 years old of 6.7 per 1000 live births. © 2022 Group of Companies Med Expert, LLC. All rights reserved.