Sleep onset latency in students living in dormitories at Tehran University of medical sciences: A survival analysis

Difficulty Initiating Sleep is a prevalent disorder in university students. In this study, we aimed to estimate the time of going to bed to get sleep and to identify its determinants by survival analysis. This study is based on a cross-sectional study that was been performed on 277 students who lived in dormitories of Tehran University of Medical Sciences (TUMS). We used Pittsburgh Sleep Quality Index(PSQI), General Health Questionnaire(GHQ) and a demographic questionnaire for data collection. Independent t-test, One-way ANOVA and survival analysis were used for analyzing the data. Mean ± SD of time of going to bed to get sleep was 23.61±16.31 minutes. Range of this time was between 0 to 90 minutes. This time was related to sleep quality, mental health and tea drinking in univariate analysis. Cox regression model showed sleep quality, working alongside academic affairs, financial source type for living expences and effect modification between two last variables were significant determinants of sleep latency. All determinants of sleep latency in our study are changeable factors. It means educationonal programs can play a very important role in controlling of these factors and improvement of sleep status of dormitory students

Domain-Specific Face Synthesis for Video Face Recognition from a Single Sample Per Person

The performance of still-to-video FR systems can decline significantly because faces captured in unconstrained operational domain (OD) over multiple video cameras have a different underlying data distribution compared to faces captured under controlled conditions in the enrollment domain (ED) with a still camera. This is particularly true when individuals are enrolled to the system using a single reference still. To improve the robustness of these systems, it is possible to augment the reference set by generating synthetic faces based on the original still. However, without knowledge of the OD, many synthetic images must be generated to account for all possible capture conditions. FR systems may, therefore, require complex implementations and yield lower accuracy when training on many less relevant images. This paper introduces an algorithm for domain-specific face synthesis (DSFS) that exploits the representative intra-class variation information available from the OD. Prior to operation, a compact set of faces from unknown persons appearing in the OD is selected through clustering in the captured condition space. The domain-specific variations of these face images are projected onto the reference stills by integrating an image-based face relighting technique inside the 3D reconstruction framework. A compact set of synthetic faces is generated that resemble individuals of interest under the capture conditions relevant to the OD. In a particular implementation based on sparse representation classification, the synthetic faces generated with the DSFS are employed to form a cross-domain dictionary that account for structured sparsity. Experimental results reveal that augmenting the reference gallery set of FR systems using the proposed DSFS approach can provide a higher level of accuracy compared to state-of-the-art approaches, with only a moderate increase in its computational complexity

Relationship between Quality of Sleep and Mental Health among Students Living in Dormitories

Abstract: Introduction: This study was carried out to investigate the sleep quality and its relationship with mental health among students living in dormitories. Methods: In this cross-sectional study, 277 students residing in dormitories of Tehran University of Medical Sciences were selected through stratified random sampling procedure. A demographic questionnaire, Pittsburgh Sleep Quality Index (PSQI) and General Health Questionnaire (GHQ-28) were used for data collection. Chi-square, Spearman and logistic regression were used to analyze the data. Results: The prevalence of sleep disturbance was 73.3% (68.1-78.5) in this sample and the prevalence of poor mental health was 34.4% (28.7-39. 9). The findings showed a significant relationship between quality of sleep and mental health (P<0.001). Conclusion: Our study displayed a significant relationship between quality of sleep and mental health. So interventionist programs are suggested to improve the sleep quality of students ant to prevent mental health disorders among students living in dormitories

Sleep Quality of Students living in Dormitories in Tehran University of Medical Sciences (TUMS) in 2011

Background & Objectives: Sleep quality is an important factor in student life and affects in their learning process. Sleep problems are related to increased health concerns, irritability, depression, fatigue, attention and concentration difficulties, along with poor academic performance. The aim of this paper is to conduct a survey based on a questionnaire that would characterize the quality of sleep in students living in dormitories of Tehran University of Medical Sciences (TUMS). Methods: We conducted a cross-sectional study using the ..

How within-city socioeconomic disparities affect life expectancy? Results of Urban HEART in Tehran, Iran

There is substantial lack of knowledge about the role of socioeconomic status (SES) indicators on life expectancy (LE) within-cities, especially within mega-cities. We aimed to investigate the disparities of LE within city districts of Tehran, Iran, and specify how SES inequalities play role on LE.; The death and population data for 2010 by different age, gender, and residency district were obtained from the main cemetery of Tehran and statistical centre of Iran, respectively. Age-specific mortality rates and consequently LE were calculated for all 22 districts by different genders. Finally, based on the results of first Tehran's Urban Health Equity Assessment and Response Tool (Urban HEART) project in 2008, the influence of social classes (SCs), total costs, and education indicators were analyzed on LE at birth (e0).; The e0 for total males and females in Tehran were calculated as 74.6 and 78.4 years for 2010, respectively. The maximum LE of 80 years was observed in females of northern part with higher SES, and the minimum e0 of 72.7 years observed in males of southern part with lower SES. The e0 gender gap among districts was 5.5 years for females and 3.7 years for males. The highest and lowest mean of e0 observed in SC1 (highest class) and SC5 (lowest class), were 77.6 and 76.0 years, respectively. The lowest mean of e0 observed in the first group of total costs indicator and was 76.2 years. In addition, the lowest observed mean of e0 was in the first category of education indicator (illiterate) and was 76.0 years.; RESULTS indicate substantial disparities in LE within city districts. This confirms that SES disparities within-cities would have direct influences on LE

Virulence-Associated Gene Profiles of Avian Pathogenic Escherichia coli Isolated From Broilers With Colibacillosis: A Pilot Study in Iran

Background: Avian pathogenic Escherichia coli (APEC) causes economic losses in the chicken industry worldwide.Objective: In this study, virulence-associated gene profiles of APEC isolates were investigated by polymerase chain reaction (PCR).Materials and Methods: A total of 60 Escherichia coli isolates were collected from 60 colibacillosis cases from 30 broiler poultry farms in Alborz, Tehran, and Golestan provinces, Iran. After identification by biochemical tests, DNA was extracted by boiling method and 5 virulence-associated genes including: iutA, hlyF, iroN, ompT, and iss were detected by 2 multiplex PCR protocols.Results: Of the 60 APEC isolates, 26 (43.3%) isolates had at least three virulence genes from which 12 (20%) isolates were positive for all 5 virulence genes, whereas 34 (56.6%) carried no investigated virulence genes. Presence of iutA, hlyF, iroN, ompT, and iss genes in the APEC isolates were 17 (28.3%), 17 (28.3%), 24 (40%), 26 (43.3%), and 23 (38.3%), respectively.Conclusion: According to the results, four different virulence-associated gene profiles were seen in isolates, from which profile 1 with 12 (20%) isolates was predominant. These findings were in agreement with the previous reports

Dose-response meta-analysis of arsenic exposure in drinking water and intelligence quotient

Objectives: Exposure to inorganic arsenic through drinking water is a threat for public health. Using the arsenic-containing water in the long-term causes a variety of skin diseases, high blood pressure, and skin cancer. Arsenic also damages the nervous system. A wide range of studies have studied the effect of arsenic in drinking water on the level of intelligence in children. Methods: For the purpose of our research, we searched three electronic databases including Scopus, Web of Science, and Medline (PubMed) in English from 2000 to January 2018. We used the dose-response meta-analysis through applying random effect models in order to estimate the pooled association (with a 95 uncertainty) between water arsenic concentration and intelligence level. Results: Using a two-stage random effect model to investigate the dose-response association between arsenic concentration and Intelligence Quotient scale, we estimated a significant linear association as �0.08 (95 CI: �0.14, �0.01). Actually, for each unit increase in arsenic concentration (one microgram per liter), intelligence quotient scale decreases by 0.08. Conclusions: Considering the significance of the relationship between arsenic concentration in drinking water and the level of intelligence quotient as an important factor in training, the level of arsenic and its associated risks should be decreased in water resources. © 2020, Springer Nature Switzerland AG

Associations between dietary risk factors and ischemic stroke: a comparison of regression methods using data from the Multi-Ethnic Study of Atherosclerosis

OBJECTIVES We analyzed dietary patterns using reduced rank regression (RRR), and assessed how well the scores extracted by RRR predicted stroke in comparison to the scores produced by partial least squares and principal component regression models. METHODS Dietary data at baseline were used to extract dietary patterns using the 3 methods, along with 4 response variables: body mass index, fibrinogen, interleukin-6, and low-density lipoprotein cholesterol. The analyses were based on 5,468 males and females aged 45-84 years who had no clinical cardiovascular disease, using data from the Multi-Ethnic Study of Atherosclerosis. RESULTS The primary factor derived by RRR was positively associated with stroke incidence in both models. The first model was adjusted for sex and race and the second model was adjusted for the variables in model 1 as well as smoking, physical activity, family and sibling history of stroke, the use of any lipid-lowering medication, the use of any anti-hypertensive medication, hypertension, and history of myocardial infarction (model 1: hazard ratio [HR], 7.49; 95% confidence interval [CI], 1.66 to 33.69; p for trend=0.01; model 2: HR, 6.83; 95% CI, 1.51 to 30.87 for quintile 5 compared with the reference category; p for trend=0.02). CONCLUSIONS Based primarily on RRR, we identified that a dietary pattern high in fats and oils, poultry, non-diet soda, processed meat, tomatoes, legumes, chicken, tuna and egg salad, and fried potatoes and low in dark-yellow and cruciferous vegetables may increase the incidence of ischemic stroke

Global, regional, and national burden of stroke and its risk factors, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: Regularly updated data on stroke and its pathological types, including data on their incidence, prevalence, mortality, disability, risk factors, and epidemiological trends, are important for evidence-based stroke care planning and resource allocation. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) aims to provide a standardised and comprehensive measurement of these metrics at global, regional, and national levels. Methods: We applied GBD 2019 analytical tools to calculate stroke incidence, prevalence, mortality, disability-adjusted life-years (DALYs), and the population attributable fraction (PAF) of DALYs (with corresponding 95% uncertainty intervals [UIs]) associated with 19 risk factors, for 204 countries and territories from 1990 to 2019. These estimates were provided for ischaemic stroke, intracerebral haemorrhage, subarachnoid haemorrhage, and all strokes combined, and stratified by sex, age group, and World Bank country income level. Findings: In 2019, there were 12·2 million (95% UI 11·0–13·6) incident cases of stroke, 101 million (93·2–111) prevalent cases of stroke, 143 million (133–153) DALYs due to stroke, and 6·55 million (6·00–7·02) deaths from stroke. Globally, stroke remained the second-leading cause of death (11·6% [10·8–12·2] of total deaths) and the third-leading cause of death and disability combined (5·7% [5·1–6·2] of total DALYs) in 2019. From 1990 to 2019, the absolute number of incident strokes increased by 70·0% (67·0–73·0), prevalent strokes increased by 85·0% (83·0–88·0), deaths from stroke increased by 43·0% (31·0–55·0), and DALYs due to stroke increased by 32·0% (22·0–42·0). During the same period, age-standardised rates of stroke incidence decreased by 17·0% (15·0–18·0), mortality decreased by 36·0% (31·0–42·0), prevalence decreased by 6·0% (5·0–7·0), and DALYs decreased by 36·0% (31·0–42·0). However, among people younger than 70 years, prevalence rates increased by 22·0% (21·0–24·0) and incidence rates increased by 15·0% (12·0–18·0). In 2019, the age-standardised stroke-related mortality rate was 3·6 (3·5–3·8) times higher in the World Bank low-income group than in the World Bank high-income group, and the age-standardised stroke-related DALY rate was 3·7 (3·5–3·9) times higher in the low-income group than the high-income group. Ischaemic stroke constituted 62·4% of all incident strokes in 2019 (7·63 million [6·57–8·96]), while intracerebral haemorrhage constituted 27·9% (3·41 million [2·97–3·91]) and subarachnoid haemorrhage constituted 9·7% (1·18 million [1·01–1·39]). In 2019, the five leading risk factors for stroke were high systolic blood pressure (contributing to 79·6 million [67·7–90·8] DALYs or 55·5% [48·2–62·0] of total stroke DALYs), high body-mass index (34·9 million [22·3–48·6] DALYs or 24·3% [15·7–33·2]), high fasting plasma glucose (28·9 million [19·8–41·5] DALYs or 20·2% [13·8–29·1]), ambient particulate matter pollution (28·7 million [23·4–33·4] DALYs or 20·1% [16·6–23·0]), and smoking (25·3 million [22·6–28·2] DALYs or 17·6% [16·4–19·0]). Interpretation: The annual number of strokes and deaths due to stroke increased substantially from 1990 to 2019, despite substantial reductions in age-standardised rates, particularly among people older than 70 years. The highest age-standardised stroke-related mortality and DALY rates were in the World Bank low-income group. The fastest-growing risk factor for stroke between 1990 and 2019 was high body-mass index. Without urgent implementation of effective primary prevention strategies, the stroke burden will probably continue to grow across the world, particularly in low-income countries. Funding: Bill & Melinda Gates Foundation