مسعود میرزایی

Ischemic heart diseases are one of the most common diseases that cause high mortality worldwide. This article has identified various factors affecting heart disease and identified susceptible people using various machine learning methods.

The current research was conducted on the Yazd Health Study (YaHS) database. YaHS was conducted on adults aged 20-70 years who were residents of Yazd Greater Area and collected information on the health and various diseases of nearly 10,000 people in the form of a questionnaire with 300 different questions. In this research, by using the correlation of questions with heart disease, the most important factors of heart disease have been identified. By using the identified factors and machine learning algorithms, susceptible people with heart disease have been identified.

The results of the evaluations have shown that factors such as age, family history of heart disease, blood pressure, diabetes, blood cholesterol, stress, anxiety, depression, quality of life, quality of sleep, physical activity, smoking, and diet have an effect on heart disease. Likewise, among the different machine learning methods, the nearest neighbor method, the deep neural network method, and the multi-layer perceptron method with a recall criterion of 99.94%, 99.88%, and 99.11% have performed the best in the identifying sick people, respectively.

According to the findings of the research, it can be understood that by controlling factors such as blood pressure, diabetes, blood cholesterol, stress, anxiety, and depression, changing factors such as quality of life, sleep status, physical activity, and eating patterns of people and quitting smoking, it is possible to move towards improving the health of society. On the other hand, the identification of people prone to heart disease using machine learning methods is done faster and at a lower cost than the traditional methods that are done by referring to medical centers and doctors and performing various tests.

This research was conducted with the aim of the effectiveness of resilience training on cognitive impairment, self-control, and the motivation to progress in male students of the first secondary school. It was a semi-experimental research with a pre-test and post-test design with two experimental and control groups. The statistical population consisted of all the male students studying in the first secondary level of Ravansar city in 2021-2022 in the number of 870 people, 30 male students were assigned in two equal groups of 15 people with regular random sampling. For the people of the experimental group, 8 weekly sessions of the resilience training program (in the form of 1-hour weekly sessions) were implemented, but the people of the control group did not receive this program. Data collection was done with Gillanders et al.'s cognitive impairment questionnaire (2014), Tangeni et al.'s (2004) self-control questionnaire, and Hermans' achievement motivation questionnaire (1970). Data analysis was done with descriptive statistics methods, statistical assumptions test and covariance analysis (multivariate and univariate) with SPSS version 26 statistical software. The results showed that in the post-test stage, there is a statistically significant difference between the average score of cognitive impairment and self-control of the subjects of the two experimental and control groups (p<0.05). Also, the results showed that in the post-test stage, the achievement motivation score improved in the experimental group. It is suggested that counselors and school administrators use the resilience training program in order to improve mental performance and also increase the motivation of students to progress.

During the COVID-19 pandemic, the greatest focus was on the respiratory system, but recently awareness has increased about the cardiovascular manifestations of the COVID-19 disease and the adverse effect of cardiovascular involvement on its prognosis. Since so far no comprehensive study has investigated electrocardiogram changes in patients with COVID-19 in Iran, the purpose of this study is to assess electrocardiogram changes in adults aged 20-70 with and without a history of COVID-19.

The current study was a cohort study conducted on two groups of working people with a history of COVID-19 and controls without a history of COVID-19. The case and control subjects were selected randomly from the participants of the Yazd Health study and the Shahdieh cohort study. ECG was taken from both groups before and after Covid-19 and then QTc interval and ST segment measurements were recorded and interpreted.

In the present study, 77 patients including 45 patients with COVID-19 (58.4%) and 32 non-COVID-19 patients (41.6%) were selected. Heart rate/min before and after COVID-19 was 69.08±10.89 and 73.5±14.05, respectively (P<0.01). There was a non-significant difference before and after COVID-19 in terms of QTi, and QTc (P>0.05).

According to the results of the present study, COVID-19 disease is associated with a change in heart rate in the two studies' participants, but no effect was observed on the parameters of QTi, and QTC. Therefore, it seems that echocardiography is not necessary in patients with COVID-19.

Transportation systems tend to be unstable and this instability affects the reliability indices of transportation systems. To improve reliability, control strategies can be used. One of the control strategies is holding the buses at the stops. In this study, the holding control strategy in all rolling horizon stops is used. For holding control strategy, two scenarios of possible overtaking and impossible overtaking for the buses are studied. For each of these scenarios, an exclusive mathematical model is presented. In these mathematical models, the effect of holding control strategy on passengers’ waiting time on the bus and at the station is analyzed. Afterward, an example is assumed in order to solve the model, and sensitivity analysis is conducted on some of the model’s parameters. According to the results, employing control strategy leads to a 3-4.5 percent decline in passengers’ waiting time, compared to the state in which no control strategy is implemented.

Cardiovascular diseases, including ischemic heart disease (IHD), are one of the main cause of mortality and morbidity worldwide and are currently one of the top ten causes of death. Ischemic heart disease is a type of heart disease that is caused by narrowing of arteries feeding the heart itself. The present study aimed to use data mining algorithms in screening and early prediction of IHD according to the patient's characteristics and risk factors.

In this research, data of the first phase of Yazd Health Study (YaHS), focusing on 21 characteristics of 10,000 participants aged 20-70 years such as age, type of chest pain, blood sugar level, body mass index, employment status, etc. which have been collected since 2013 were analyzed.

Data analysis was conducted using Random Forest and Naive Bayes algorithms which showed 74.51% accuracy in predicting IHD.

The study findings revealed that via applying Random Forest and Naive Bayes algorithms, ischemic heart disease can be predicted with high accuracy. Moreover, early screening and timely treatment in the early stages of disease may reduce mortality and morbidity.

Occurrence of road accidents in terms of severity and loss of life and property in various environmental and geometric conditions has always been studied and considered. In this study, a multilayer perceptron model with different architectures including one and two hidden layers with different numbers of neurons has been used to estimate the number of road accidents. In modelling of independent variables (input data) including horizontal arc radius, time of the accident, age of the driver causing the accident, gender, having a driving license, type of vehicle, weather conditions, average daily traffic, ambient light, cause of accident, severity and location of accident used. The dependent variable (model output), the number of accidents was divided into four classes (first class equal to one accident, second class equal to 2 accidents, third class equal to 3 accidents, and fourth class equal to 4 accidents). In this regard, the reports of accidents on the Tehran-Pardis freeway between January 2017 and August 2019, which were received from the Tehran-Pardis freeway company, have been used. The number of accidents that occurred during this period was equal to 368 cases, of which 44 cases were excluded due to lack of recorded information and the neural models were constructed using 324 reports. The results show that the hidden two-layer neural network model with 14 neurons each with an accuracy of 83.3% for training data and a total accuracy of 83.3% showed the best performance in estimating the number of accidents.

There is evidence that COVID-19 may have some long-term effects on the patients' blood biochemical and hematological factors. The purpose of this study was to investigate and compare the changes in biochemical and hematological factors in adults with and without past history of COVID-19.

The present study is a cross-sectional study including 72 cases with a past history of COVID-19 (PCR+ test) and 52 controls without a history of COVID-19. All participants were from two prospective cohort studies, namely Yazd Health Study (YaHS) and Shahedieh Cohort Study. Biochemical parameters such as blood glucose, lipid profiles, liver, kidney and hematological factors of cases and controls were extracted from the databases and analyzed.

The mean red blood cell count in patients with COVID-19 was significantly higher than in non-COVID-19 patients (p<0.05), and mean corpuscular volume (MCV) was significantly lower in patients with COVID-19 (p>0.001). However, no significant difference was found between the two groups in terms of lipid and kidney profiles and liver enzymes.

No significant difference was found between the two groups of patients exposed to COVID-19 and patients not exposed to COVID-19 in terms of liver enzymes, lipid and kidney profiles, which probably indicate that COVID-19 has no long-term effect on these variables. However, a significant difference was observed between the two groups (p<0.05) regarding the number of red blood cells and MCV.

Background & objectives:

 Oral health is an indicator of the whole body that affects individuals' mental and functional aspects. Deterioration of oral health is one of the most critical challenges facing health policies, and improving social factors is one of the ways to overcome this problem. This study aimed to investigate the socioeconomic factors affecting DMFT in adults in Shahdiyeh in a cohort study in 1395.

 This study was based on the cohort protocol of Shahedieh Yazd and was performed on adults aged 35-70 years. Socioeconomic variables were extracted from the relevant questionnaire, and their relationship with the DMFT index was examined.

 The mean age is 48.48. The average DMFT is 19.77, and the marital status is not related to the DMFT index, but there is a significant relationship with the number of decayed teeth. The lowest DMFT index is in the group with a Ph.D. level. Brushing has a meaningful and direct association with the DMFT index. The highest average number of restored teeth was found in the group with high salt intake, and the DMFT index has a significant relationship with the frequency of dental floss.

 Dental caries is a multifactorial illness with many factors affecting it. However, the role of education and socioeconomic status as factors influencing oral and dental health as the main factor in reducing this disease is fundamental and directly increases the level of awareness, attitude, and practice of individuals and subsequently improves the situation of oral hygiene.

Rokniyeh School was one of the largest and most important schools of Yazd during 14th and 15th centuries built in 1324 AD by Seyyed-Rokn-al-Din Abul-Makaram Mohammad Qazi Hosseini-Yazdi. Few remnants of this school have been left behind, known as Seyyed-Rokn-al-Din Mausoleum. This study aims to determine the boundaries and area of the school and to visualize it.

In this study, with the aid of historical sources and aerial maps, as well as the map of old schools of the same era, the possible boundaries and area of the school was determined and illustrated by Adobe Illustrator Version 2020. Also, a model of the school was visualized. Additionally, details about the budget and function of the school’s clinic (Dar-al-Shefa) and pharmacy (Beit-al-Advieh) was investigated using its historical endowment and other resources.

Based on the length and width of the specified space in the west, east and north of Seyyed Rokn-al-Din mausoleum, the area of the school was estimated to be about 4000 to 5000 m2. A view of the school building and movement mechanism of the water clock including its possible water path were illustrated.

Rokniyeh School was the most important school in old Yazd, which had different parts, such as a library, mosque, clinic, guest house, monastery, water clock and observatory. Considering the current position of Yazd in higher education of Iran, it is suggested to establish a link between the history and its current position in higher education to inform students and academics about the historical background of higher education in Yazd.

Transdisciplinary education is necessary for the improvement of life quality and social sustainable development. The convergence of science also provides the opportunity to achieve this goal through collaborative learning and by crossing imaginary boundaries of various fields of knowledge. This study was part of a project titled "Application of artificial intelligence for developing tools for virtual education and counseling for prevention, diagnosis, treatment and self-care of cardiac patients" The aim was to share the experiences of professors and students participating in this transdisciplinary health oriented activity.

We used a qualitative method in this study. Purposive sampling and data collection was performed through a focused group discussion session and three individual semi-structured interviews. The process of data analysis was based on the Granham and Lundman method, and the accuracy of our data was examined with Guba and Lincoln criteria.

The participants included 22 students and faculty members of various disciplines of medical sciences, engineering and art. Classes and members of qualitative analysis included "individual development" (self-directed learning, self-confidence, responsibility) and "social development" (transdisciplinary vision, academic leadership and social responsibility).

Many of the themes, such as self-directed learning, self-confidence, responsibility and transdisciplinary vision, are hidden curriculum components that students learn through participating in team and problem-solving activities. Interdisciplinary activities are also effective for empowering faculty members in areas like academic leadership and creating a multidisciplinary perspective to respond to the needs of society.

Due to significant social, economic, cultural, and lifestyle changes in Iran during past decades and the relationship among the unstable social and economic status and mental complications the study of psychiatric disorders has become important and necessary, the aim of this study was epidemiology of psychiatric disorders in children and adolescents.

A total of 1035 children aged 6-18 years from Yazd Province, Iran were enrolled in this cross-sectional study in 2017 using a multistage cluster sampling method. Data were collected using the following inventories for school-age children (6-18 years): Kiddie-SADS-Present and Lifetime Version (K-SAD-SPL). Logistic regression and SPSS version 16 software were used for data analysis.

44.1% of participants were boys and 55.9% were girls. The mean age of the participants was 11.3±3.9 years. The prevalence of psychiatric disorders in children and adolescents was 35.5%. Meanwhile, anxiety disorders had the highest prevalence rate (22.2%) and among anxiety disorders, separation anxiety disorder (8.7%) and generalized anxiety (8.6%) were the most prevalent. There was a significant difference in all psychiatric disorders based on gender, more evident in the high rate of obsessive-compulsive disorder, enuresis, tic, attention deficit hyperactivity disorder, hyperactivity, oppositional defiant disorder, conduct disorder, smoking disorder, and epilepsy were more evident in boys (P-value < 0.05).

The prevalence rate of psychiatric disorders in young population of Yazd Province is relatively high and because of its impact on individuals' social and personal function, it could have substantial implications for mental health services.

The inter-disciplinary approach in education includes the integration of educational capacities and competencies of different disciplines for a specific purpose or creating a new product with appropriate methodological techniques to improve knowledge and acquire competencies. In fact, the starting point of convergence of sciences is turning to an interdisciplinary approach. Convergence of sciences provides the integration of competencies specified in different professions and sciences, taking into account professional standards and the latest technological trends.پIn this letter we describe our experience of a cooperative learning team consisted of 12 under-graduate and post-graduate students from various medical sciences, engineering and art discipline who were successful in designing and launching a health promotion mobile application called HOMATAB.

Spring 2022

Disruption of the sleep cycle can disrupt the activity of the hormonal rhythms. Given that diabetes mellitus (DM) is the most common endocrine disease, and few studies have been conducted to investigate its relationship with sleep quality, the present study aimed to investigate the relationship between sleep disorders and diabetes mellitus.

The present study was a descriptive, cross-sectional study. In this study, all adults aged 35-70 years from Shahedieh, Ashkezar, and Zarch Cities were investigated. The data used in this study included demographics, sleep variables, and fasting blood sugar level. Data were analyzed using SPSS V. 16 and Chi-square, T-test, ANOVA and regression.

The results showed that the prevalence of sleep less than 6 hours was significantly higher in people with diabetes type2, and also, the sleep latency increased with increasing blood sugar level (R=0.06, P=0.001). The results of regression analysis indicated that the chance of diabetes in people with a sleep duration of less than 6 hours was 12%, in people with a sleep latency of more than 15 minutes was 11%, in people who used sleep medications continuously was 15% and in people who nap during the day was 27% higher than other people.

According to the findings of this study, the prevalence of sleep disorders was higher in people with diabetes and sleep was a strong predictor for diabetes type2.

Drug use not only affects a person's physical and mental health, but also affects the health of others in the community. Various variables, including demographic and social factors, affect drug use. The present study was conducted to investigate the prevalence of drug use and related factors in the participants of Shahedieh Cohort Study.

A descriptive study was performed using the first phase of Shahedieh cohort study on 10194 adult residents of Shahdieh, Zarch, and Ashkezar in 2015-2016. The aim of the cohort study was to assess the prevalence of non-communicable diseases and their risk factors in adults aged 35-70 years. Data were analyzed with the SPSS 20 using chi-square and logistic regression.

The prevalence of illicit drug use in the present study was 15.5% with a mean age of onset of 31.5 ± 9.2 years. The most common drug was opium (98.2%). The most common method of drug use was inhalation (98.1%). The logistic regression showed that male gender (P< 0.001), age 40 to 49 years (P<0.001), low education (below high school diploma) (P<0.001), positive history of smoking (P<0.001) and alcohol consumption (P<0.001) were the most important factors associated with drug use. In addition, a positive history of ischemic heart disease (P=0.007) and psychiatric disorders (P=0.02) were the diseases related to drug use.

The prevalence of drug use was high in the study population. There is an urgent need for intervention and preventive measures to solve this complex social problem.