مجله علوم پیراپزشکی و بهداشت نظامی
سال سیزدهم شماره 3 (پیاپی 29، پاییز 1397)

Breast cancer is one the most common form of cancer in women all over the world. The incidence of women breast cancer is increasing in Iran. There are many risk factors involved in the risk of breast cancer so that these risk factors have been determined based on genetic, environmental, and geographical conditions in various studies. The current study aimed to evaluate the risk factors of breast cancer in women. Methods and Materials: This study has been performed in Ayatollah Khansari Hospital in Markazi province with the participation of 240 patients with breast cancer and 240 women without breast cancer. Data were collected through interviews based on a prepared questionnaire. Data were analyzed through Logistic regression method and calculation of the frequency of indicators, Chi-square test, and calculation of P values using SPSS software version 20. Statistical analysis indicated that several factors including the abortion, stillbirth, history of breast cancer, early menstruation and poor dietary pattern increase the risk of breast cancer incidence. Moreover, there were significant relationship between the age, number of children, education, and occupation with the risk of breast cancer. In contrast, there were not any significant relationship between the use of anti-pregnancy pill, late menopause, age at first birth and marriage with the risk of breast cancer. Discussion and Identifying and determining the risk factors of breast cancer and raising awareness of these risk factors can play an important role in decreasing the incidence of this disease. It is recommended to conduct further studies on this subject with consideration of other risk factors for breast cancer. In addition, it is suggested to educate the women about breast self-examination and importance of periodic clinical examinations.

Dynamic alterations of the brain are of high significance when it comes to analyze the human feelings. In this study, the hidden patterns corresponding for the emotional states have been investigated by adopting a certain Poincare’ map function inspired by the theory of chaos. The present study aimed to explore the significance relationship between the proposed methodology and the level of the emotional states. Methods and Materials: One of the well-known emotion dataset namely ‘DEAP’ was used to evaluate the performance of our methodology. DEAP is a multimodal dataset in which forty music videos lasting one minute were shown to 32 participants. Moreover, a set of 40 channels of biological signals including EEG and peripheral signals were recorded. Moreover, participants rated to each video in terms of ‘valence’, ‘arousal’, ‘dominance’, and ‘liking’. In this study we have investigated the dynamic variations of EEG signals in order to discriminate the levels of the emotional states. For describing the effect of the Poincare’ approach on the subjective ratings, we have adopted the correlation statistics by computing the Spearman correlated coefficients. The results indicate that the Poincare approach could properly discriminate the levels of valence (p<0.05), arousal (p<0.01), dominance (p<0.05), and liking (p<0.05). In other words, the statistical analysis showed the significant relationship between the levels of emotions and the Poincare’ method. Discussion and The result interpretations demonstrate and verify the success of the nonlinear and chaotic approaches in the analysis of human brain signals. Therefore, it could be a reliable methodology for studying the brain functions.

Radiation protection of patients, personnel and other people is very important in medical imaging using ionizing radiation (such as X-rays and gamma rays). These radiations can cause various biological damages such as carcinogenesis, cataracts, embryonic injuries. Therefore, the knowledge of radiation protection of radiation workers is very important and the purpose of this research is to assess the radiation protection knowledge of radiology technologists in military hospitals in Tehran. This research is descriptive-analytic and cross-sectional study. A questionnaire about the knowledge, attitude, and performance of radiation protection was distributed among the 80 radiation technologists of Tehran’s military hospitals. The data of the completed questionnaires were analyzed using one-way ANOVA, sample t-test and Spearman/Pierson correlation tests in SPSS-19 software. The mean of the obtained radiation protection knowledge score was 11.20 ± 4.28 out of 20. There was no significant difference between the radiation protection knowledge, performance knowledge and motivation among graduates of AJA and other universities as well as between men and women. There was a very weak correlation between age with knowledge of radiation protection and performance as well as between education with knowledge of radiation protection, performance knowledge and motivation. Comparison of our investigation results with previous studies showed that the level of radiation protection knowledge of Army Radiology technologists is low. It was also determined that age, gender, and work experience had no effect on the functional knowledge and radiation protection knowledge, nor did it have an impact on knowledge, performance and motivation with increasing educational level.

By increasing life expectancy in the world, especially in developed countries, Alzheimer’s disease has become one of the most important and costly diseases. It is estimated that the prevalence of dementia will double every 5 years for people over 60 years. Unfortunately, this disease and other types of dementias impose a heavy burden on the economies of societies. In this study an automated method is presented and evaluated for Alzheimer disease detection in order to assist physician diagnosis. Methods and Materials: Magnetic resonance images of 236 patients were used. First, the gray and white matter regions and cerebrospinal fluid were extracted by image processing methods and their area were calculated and considered as feature vector for classification. Then, the support vector machine and neural networks were used to classify the Alzheimer patients from healthy ones. The gray matter region areas were significantly lower in Alzheimer group than healthy one. Using the regions area as feature vector and by means of support vector machine and neural networks as classifiers, a detection accuracy of 85% was achieved. Discussion and Alzheimer disease reduces the area of gray matter in brain which this changes are irreversible. Intellectual methods can detect this changes and diagnose Alzheimer disease. This methods could be used to assist physician for detection of disease.

Universities should be concerned about the psychological, social and emotional needs of students, and create the appropriate conditions for creating a productive learning environment. A study of the learning environment is helpful in realizing this. It has been said that learning environment is considered as an important aspect for medical graduates. Regarding this issue, this study aimed to investigate the difference in perception of the quality of the learning environment from the viewpoint of continuous and discontinuous undergraduate operational room technology students of Iran University of Medical Sciences during the period of 1395-96. A descriptive study was carried out in 1395-1396. A total of 143 (50 male and 93 female) undergraduate students responded to the DDRE (Dundee Ready Education Environment Measure) questionnaire. The questionnaire has 50 items, the range of question scores were in the range of 0-200. The higher scores indicated better learning environments and lower scores indicated more unfavorable learning environments. The mean of total score of the learning environment of the undergraduate operational room students was 106 ± 22.6. The scores of non continuous graduate students assessing the quality of the learning environment (115.65±20.17) were higher compared to the continuous undergraduate students scores (102.25±20.55), which was also significant (P=0.01). This study showed that non-continuous bachelor’s students assessed the learning environment more positively in comparison with continuous bachelor students. Furtheremore, with considering all of the dimensions of the questionnaire, it is possible to improve all aspects of the learning environment.

Considering the importance of the role and function of Emergency Medical Services (EMS) in a society’s health and the need for continuously evaluating its function, especially in indices affecting the process of giving service to the patients, the present study aimed to compare time indices of providing services in EMS Shahrekord county in Iran. Methods and Materials: This study was a retrospective cross-sectional study. 600 calls, that had been resulted in patient transfer were randomly selected. Moreover, the required data were extracted from EMS forms that were filled by a medical emergency technician for each mission. Regarding to our results, the mean of delay time, response time, time to reach the scene, total of the 3 mentioned times, time to reach a hospital and total mission time were 0.01, 7, 8, 12, 17 and 50 minutes, respectively. There were only significant differences in time to reach hospital (t=3 and p=0.001) and total mission time (t=2 and p=0.009) in the studied periods. There were not any significant differences regarding other time indices. Time indices of EMS were desirable. It was the same level as national and international indices. Meanwhile, there were significant differences between two time indices namely time to reach hospital and total mission time in the years of 2015 and 2016. In contrast, there were no significant differences between the other time indices.

Abstract      In recent years, many research articles have been studied the electromagnetic fields (EMFs) effects on the human body, due to the increment of electromagnetic-based devices. In most studies, there is not an accurate analytical method for solving Maxwell’s equations and then various numerical techniques have been utilized to solve Maxwell’s equations. In this review, we first introduce Maxwell’s equations briefly and then various numerical and analytical methods used in the literature and commercial softwares have been considered in detail. Then, EMFs effects on the human body in terms of tissue distance from electromagnetic (EM) source will be investigated. Finally, we conclude the article.     Methods and Materials: In this article, various numerical and analytical methods for studying EMFs effects on the human body have been studied and investigated based on the credible scientific references.     The EMFs effects on the human body is classified in terms of tissue distance from EM source into two main categories: Far field and near field. In near field region, four categories are studied in this paper.     Discussion and In this review, Maxwell’s equations are introduced briefly and various numerical and analytical methods for solving these equations have been investigated. Then, human body models used in EMF numerical simulations have been considered, which Debye and Cole-Cole formulations are the most popular models in the literature. In these models, the electric properties of the tissue are expressed in terms of tissue conductivity and permittivity. In the following, the EMFs effects on the human body will be studied based on the tissue distance from EM source.     Keywords: Electromagnetic fields, Human body, Numerical technique, Analytical method, Specific absorption rate

Multiple sclerosis (MS) is one of the most common chronic inflammatory diseases of central nervous system that causes the demyelination of the neurons. Although the main reason of this disease has been unknown yet, different factors including genetic and environmental factors and some infectious diseases can affect the etiology of MS. Methods and Materials: The present study is a review article obtained from searching in various databases such as Pubmed, Scopus, Google Scholar, Barakatkns, SID, Magiran and relevant books in this field. Various studies have shown that infections agents, especially viruses, can cause chronic neurological disorders and play an important role in the etiology of MS with unknown mechanisms. Discussion and Some indirect mechanisms proposed that infections can induce inflammatory responses in central nervous system and therefore, contribute to the etiology of MS.