Zobrazení zdroje stránky Macgregorholm4190

Although major dietary patterns and sleep quality independently affect psychiatric disorders, their interactive association on depression is not clear. This study assesses the independent association of dietary patterns and sleep quality on depression, and also investigates their interactive associations on depression among overweight and obese women in Iran.<br /><br /> Cross-sectional study was conducted among 304 participants, age 18 and above in 2018 at Tehran Iran. Usual dietary intake was collected with 174-FFQ. Participants' biochemical parameters and depression were measured using standard protocol. Major dietary patterns were extracted by factor analysis and grouped into Fruits&amp;Vegetable group (healthy dietary pattern), High Fat diary&amp;Red Meat group (unhealthy dietary pattern) and Crackers&amp;High Energy Drinks group (western dietary patterns).<br /><br /> After adjusting for confounders poor sleep was associated with moderate and high depression; AOR (95%CI) 0.41(0.19-0.90) and 0.29(0.13-0.60) respectively. However, healthy dietary patterns (tertiles 2<br /><br /> and 3<br /><br /> ) interact with sleep for depression; AOR (95%CI) 4.168(1.166-14.992) and 2.966(1.068-8.234) respectively. Unhealthy dietary pattern tertiles 2<br /><br /> and 3<br /><br /> interact with sleep for depression; AOR (95%CI) 2.925(1.055-8.113) and 4.216(1.182-15.042) respectively and Western dietary pattern tertile 3<br /><br /> interacts with sleep for depression; AOR (95%CI) 4.264(1.494-12.169).<br /><br /> Sleep deprivation could be associated with depression. However, sleep quality could interacts with dietary patterns to be associate with depression among overweight and obese people.<br /><br />Sleep deprivation could be associated with depression. However, sleep quality could interacts with dietary patterns to be associate with depression among overweight and obese people.<br /><br /> Chemokines are proinflammatory cytokines that play key roles in development of cardiovascular diseases (CVD). Chemokine-induced recruitment of peripheral leucocytes to tissues is a crucial step in the CVD progression. CC chemokines ligand 5, 2 (CCL5 and CCL2), have been characterized as emerging inflammatory biomarkers of atherosclerotic CVD. The aim of this study was to find out whether genetic polymorphisms of CCL5 -403 G&gt;A (rs2107538) and CCL2 -927 G&gt;C, (rs3760396) were associated with the risk of CVD.<br /><br /> In this case-control study, 500 Iranian individuals including 250 CVD patients and 250 healthy subjects as the control group participated in 2017. Genotyping of CCL5 -403 G&gt;A and CCL2 -927 G&gt;C polymorphisms were executed using Tetra-ARMS PCR method.<br /><br /> At genotypic level both CCL5 -403 G&gt;A and CCL2 -927 G&gt;C polymorphisms were not associated with the risk of CVD (<br /><br /> &gt;0.05), even after adjustment by age, sex, race, and history of hypertension, DM and smoking. However, the CCL2 -927 C allele was associated with an increased risk of CVD (OR=1.42, <br /><br /> =0.050) with a higher prevalence in CVD patient than in controls (17% vs. 12%). Moreover, the haplotype analysis revealed that CCL5/CCL2 haplotype (G/C) was a risk factor for CVD (OR=2.13, <br /><br /> =0.001), and that carriers of this haplotype were at 2.13-fold higher risk of CVD than subjects with G/G haplotype.<br /><br /> CCL2 -927 C variant and CCL5/CCL2 haplotype (G/C) were associated with susceptibility to CVD, and were risk factors for CVD in our population but more studies with large sample size are recommended.<br /><br />CCL2 -927 C variant and CCL5/CCL2 haplotype (G/C) were associated with susceptibility to CVD, and were risk factors for CVD in our population but more studies with large sample size are recommended.<br /><br /> Paying attention to the issue of mental health in the workplace, especially with current pandemic conditions of COVID-19 is of significant importance. Therefore, this study aimed to determine the factors affecting occupational burnout among health care center staff during the pandemic of coronavirus infection.<br /><br /> The present study was a case-control study carried out in the first half of the year 2020 on medical staff working in hospitals in Tehran. The sample size was 324 individuals, including 175 employees working in general (non-COVID) wards and 149 people working in COVID-19 wards. Demographic characteristics questionnaire and two standard questionnaires of Maslach Burnout Inventory and Parker and DeCotiis Job Stress Scale were distributed.<br /><br /> Total score of job stress and its two dimensions (time and pressure) had a significant relationship with different levels of occupational burnout. Logistic regression analyses showed significant relations between job stress with emotional exhaustion (95% CI, 1.11-1.19, OR=1.15) and depersonalization. Participants in both wards experienced statistically significant increasing trends given the different components of occupational burnout concurrently by increasing their total stress score.<br /><br /> Hospital staff's levels of stress and occupational burnout regardless of where they worked (COVID-19 wards or general wards) were not significantly different and existed among the members of both groups. On the other hand, job stress and its dimensions (time pressure and anxiety) had a significant relationship with the main dimensions of occupational burnout.<br /><br />Hospital staff's levels of stress and occupational burnout regardless of where they worked (COVID-19 wards or general wards) were not significantly different and existed among the members of both groups. On the other hand, job stress and its dimensions (time pressure and anxiety) had a significant relationship with the main dimensions of occupational burnout.<br /><br /> We aimed to provide data regarding COVID-19 infection and mortality rates within different specialties of physicians and general medical practitioners in a longitudinal nationwide study and to compare the results with general population.<br /><br /> Data on COVID-19 infection and mortality of medical physicians in Iran was actively gathered through the Iranian Medical Council (IRIMC). Population COVID-19 cumulative incidence and mortality data were extracted from WHO situation analysis reports and data on Iranian population were obtained from the Statistical Center of Iran.<br /><br /> As of Jul 27<br /><br /> 2020, COVID-19 infection and mortality rates were 0.680% and 0.0396% among 131223 physicians. The highest cumulative infection rates as of 27<br /><br /> July 2020, were observed in specialists of infectious diseases (3.14%) followed by neurology (2.18%), and internal medicine (2.13%). The highest cumulative mortality rates as of Nov 3<br /><br /> 2020 were observed in specialties of forensic medicine (0.314%), anesthesiology (0.277%), urology (0.237%), and infectious diseases (0.20%). Male physicians comprised 95% of cumulative mortality as of Nov 3<br /><br /> . The physicians' COVID-19 mortality in July and November were 49% and 23% higher than the general population respectively.<br /><br /> Infection and mortality rates in Iranian physicians were higher than the general population, however the magnitude of difference was narrowing in longitudinal investigation. Provision of personnel protective equipment should be prioritized to specialists of infectious diseases, forensic medicine, anesthesiology, internal and emergency medicine, and urology.<br /><br />Infection and mortality rates in Iranian physicians were higher than the general population, however the magnitude of difference was narrowing in longitudinal investigation. Provision of personnel protective equipment should be prioritized to specialists of infectious diseases, forensic medicine, anesthesiology, internal and emergency medicine, and urology.<br /><br /> We aimed to explore the influencing factors of clinical adverse blood transfusion reactions, to provide theoretical basis and support for clinical safe blood transfusion, and to minimize the occurrence of adverse blood transfusion reactions.<br /><br /> The method was to retrospectively analyze the report of adverse blood transfusion reports from 6 hospitals in Linyi area, Shandong, China to the blood station in Linyi City center from 2013 to 2020. We aimed to classify factors, analyze the occurrence of adverse transfusion reactions, and discuss the correlation between the occurrence of adverse transfusion reactions and the above factors.<br /><br /> Overall, 248 patients (77.98%) had a history of blood transfusion. The difference between this group and the group with no history was statistically significant (<br /><br /> &lt;0.05). The incidence of adverse transfusion reactions in middle-aged and elderly patients was relatively high, especially for those over 50 yr old, with an adverse reaction of 135, for example, the proportion reached 42.45%. In addition, a retrospective analysis found that the occurrence of adverse transfusion reactions was mostly concentrated from Mar to Sep, a total of 228 cases, accounting for 71.69% of all adverse reactions, which was the highest incidence of adverse transfusion reactions.<br /><br /> The main adverse reactions of transfusion were allergic reactions, followed by non-hemolytic febrile reactions, mainly caused by transfusion of suspended red blood cells.<br /><br />The main adverse reactions of transfusion were allergic reactions, followed by non-hemolytic febrile reactions, mainly caused by transfusion of suspended red blood cells.<br /><br /> We aimed to compare the prediction efficiency of back propagation (BP) network and grey model (GM) (1.1) for mumps infectious diseases and compare the application effect of the two models.<br /><br /> By calculating the average incidence rate of mumps in January 2014 -2016, we conducted the modeling of the BP time series, GM (1,1) grey model and the combination models of them, and predicted the incidence rate in June 2016 in comparison with the actual one. We compared the quarterly incidence rate to test the two prediction models, and compared the advantages and disadvantages of these models.<br /><br /> R value of BP model was 68.45%, for GM (1,1) was 58.49%, and for combined forecasting model was 86.95%. [https://www.selleckchem.com/products/ABT-263.html Navitoclax] We used the principal component analysis clustering method to control the samples, and found that the samples were close to the population mean. We found that the GM (1.1) model was more suitable for the prediction of mumps infection mode. We carried out dimension reduction analysis on the model data, and the accuracy of the data after dimension reduction is within the range of Da. For the discrete degree of the data in the combined model, matlab pipeline was used to verify the reliability of the data and results. By calculation after manifold optimization small error probability was <br /><br /> =0.875 and semi mean relative error 2.43%.<br /><br /> BP, GM (1,1) is a better method for modeling the epidemic trend of mumps in China, but the efficiency of prediction is not as high as the combination of them.<br /><br />BP, GM (1,1) is a better method for modeling the epidemic trend of mumps in China, but the efficiency of prediction is not as high as the combination of them.<br /><br /> To explore the effects of predictive nursing intervention among patients with acute stroke.<br /><br /> One hundred and sixty participants were included. They were hospitalized in the Department of Neurology of a third-level first-class hospital in Changsha, Hunan Province, from January to August 2019. They were categorized into control group and intervention group by random number table, with 80 patients in each group. General nursing for patients in Neurology Department was offered to the control group. On the basis of general nursing, predictive nursing intervention was offered to the intervention group. The effectiveness of predictive nursing intervention were evaluated by disparity in neurologic function, movement function, daily life ability and sleep quality before intervention and 2 weeks after intervention. The neurologic function, movement function, daily life ability and sleep quality were evaluated by National Institute of Health acute stroke scale (NIHSS), Fugl-Meyer scale, Barthel indicator, and Pittsburgh sleep quality indicator (PSQI), respectively.