فهرست مطالب

Jundishapur Journal of Health Sciences - Volume:11 Issue:3, 2019
  • Volume:11 Issue:3, 2019
  • تاریخ انتشار: 1398/05/15
  • تعداد عناوین: 6
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  • Elham Asrari *, Maryam Paydar Page 1
    Background
    In the recent era, air pollution is a major global concern that affects human health. The emission proportion of air pollutants is increased in many cities of Iran such as Mashhad. Particular matters (i.e. PM2.5) are one of the five air pollutants known to be responsible for polluting the air in Mashhad. Nowadays, fuzzy neural intelligent systems, which are capable of solving nonlinear and complex problems, are widely used in the air pollution problem to determine the amount of the particles and dust in the air.
    Methods
    In the current study, the air quality data consisting of daily average concentrations of air pollutants and the meteorological data including the minimum temperature, precipitation, humidity, wind direction, and daily wind speed recorded by city monitoring stations from 2011 to 2017. The daily average pollutants concentration was used to study the relationship between PM2.5 and the other air pollutants such SO2, O3, NO2, PM10, and CO. SPSS was used for data analysis. Linear regression, multilayer perceptron (MLP) neural network, and fuzzy neural network using MATLAB 2017 software were employed for modeling. Performance of the models was evaluated using root mean square error (RMSE) and coefficient of determination (R2).
    Results
    Based on the obtained results, among the employed models, MLP neural network with R2 = 0.598, RMSE = 0.088, and MSE = 0.0079 was better than linear regression, and the ANFIS model combining particle swarm optimization (PSO) algorithm with R2 = 0.804, RMSE = 0.055, and MSE = 0.0031 had the best performance in the prediction of PM2.5.
    Conclusions
    The ANFIS network correctly fitted more than 80% of total data; given that there were non-linear and complicated models in meteorological systems, this figure can indicate the high strength of ANFIS network through PSO-based combinational training methods for modeling nonlinear data.
    Keywords: PM2.5, Gas, Mashhad, Regression, Fuzzy, Neural Networks
  • Mandana Kianpor, Khoshnaz Payandeh *, Navid Ghanavati Page 2
    Background
    High concentrations of heavy metals in street dust are considered to be a serious risk to human health and the environment. Therefore, investigating the concentration of heavy metals to monitor pollution and preserve the quality of the environment is essential.
    Objectives
    This study aimed to examine the concentration, enrichment factor (EF), pollution index (PI), and Nemrow integrated pollution index (NIPI) of potentially heavy metals including Cr, Cu, Cd, Pb, Zn, Ni, V, As, and Co in street dust in the industrial areas of Ahvaz.
    Methods
    A total of 29 dust samples were collected from sidewalks of main streets of industrial areas of Ahvaz and were analyzed by the inductively coupled spectroscopy (ICP-OES) method.
    Results
    The average concentration of heavy metals in Pb, Zn, Cu, Cr, Cd, Ni, V, As, and Co was respectively: 86, 999, 50, 57, 0.3, 58, 184, 6, and 13 (mg/kg), respectively. The mean concentration of all heavy metals in the samples of dust in the industrial areas of Ahvaz was several times higher than that of baseline values. Based on the average EF in the study area, Zn and Pb have extremely high enrichment. In addition, Zn, V, and Pb, with the highest PI average, displayed high pollution. In addition, the evaluation of NIPI showed that 100% of samples have high pollution.
    Conclusions
    The source of pollution of studied metals was anthropogenic, such as urban industrial facilities, transport, vehicle traffic, and burning of fossil fuels in the studied area. Generally, some protective protocol are proposed to reduce the level of heavy metals pollution in the city of Ahvaz, such as environmental control of gases produced by industries and factories, increase of green space, conversion of liquid fuel to gaseous, and use of public transportation.
    Keywords: Air Pollution, Heavy Metals, Nemrow Integrated Pollution Index, Street Dust
  • Rozita Firouznia *, Hossein Dargahi, Tohid Jafari Koshki, Zeinab Khaledian Page 3
    Background
    Maternal health program is one of the most important programs in Iran primary health care (PHC). Considering the necessity of its continuous quality improvement, the present study was designed to identify the challenges of Iran maternal health program from the midwives’ perspectives.
    Methods
    This is a qualitative study with 27 midwives working in East Azerbaijan province PHC system. The sampling method was purposeful and the inclusion criterion for participants included at least 5 years of experience in the maternal health program. The researchers conducted eight individual and group unstructured interviews and the content analysis method was used for data analysis.
    Results
    This study identified 9 themes, 16 subthemes, and 39 items related to the challenges of the maternal health program from the midwives’ perspectives. The main identified themes were human resources, information management, service continuity, cultural barriers, legal and administrative barriers, care facilities, medical equipment, monitoring and evaluation, and geographic access.
    Conclusions
    The study results indicated that there are significant challenges to the maternal health program, which implies the urgent attention of the managers and policymakers to designing and implementing effective interventions.
    Keywords: Challenge, Maternal Health Program, Midwife, Iran
  • Ali Souri, Samira Ghiyasi *, Mahmoud Heidari Page 4
    Objectives
    This study aimed to investigate the knowledge, attitude, and performance in safety (safety-KAP) among firefighters operating throughout all fire stations in Tehran.
    Methods
    The statistical population (N) of this study is 420. The Morgan table was used to select the sample size, and 200 individuals completed the questionnaire and returned it. The main instrument of this study was a researcher-made questionnaire consisting of three parts. To determine the validity of the questionnaire, it was provided to the supervisors and consultants and they were asked about the research questions. After applying their views and making the necessary amendments, the final form of the questionnaire was compiled and employed. The reliability of the research was confirmed by Cronbach’s alpha (a > 85). The main method of this study was the descriptive-correlational method, and data analysis was done using SPSS software version 19.
    Results
    The results showed that the intensity of correlation between the two variables of knowledge, and attitude with the performance was 0.755 and 0.689, which indicates the direct relationship between the two variables. The amount of multi-correlation coefficient (R) of knowledge and attitude with the staff performance of the operational units in the firefighting department of Tehran is equal to 0.766, which implies a high correlation between knowledge and attitude with the performance of employees in the operational units of the firefighting department of Tehran. The coefficient of determination (R2) is 0.586. In addition, the results showed that there is a positive and significant relationship between the independent variables of age, education, and background of job title with the level of knowledge, attitude, and performance of the staff in operational units of Tehran. Therefore, the age of people between 30 and 40, with a bachelor’s degree or higher and high job background, also with a good job title, has an impact on their attitude, knowledge, and performance.
    Conclusions
    According to the job characteristics of firefighters, this study was designed. Considering safety knowledge, attitude, and performance for firefighters are very important for those that are working in a very high-risk situation and condition.
    Keywords: Knowledge, Attitude, Performance, HSE Management, Firefighters
  • Hossein Abbaslou, Ali Karimi* Page 5
    Background
    Ammonia is a commonly used chemical in the process industries. Chemical leakage is one of the main problems threatening the staff, facilities, and the environment in the process industries.
    Objectives
    The aim of this study was to model the emission of ammonia and its consequences in the petrochemical industry.
    Methods
    In this study, three accident scenarios of the most probable ones were chosen, including toxic vapor cloud, jet fire, and boiling liquid expanding vapor explosion (BLEVE). Then, the scenario modeling was done using areal locations of hazardous atmospheres (ALOHA) software.
    Results
    In the first scenario, the total released ammonia is 81,316 kg. The concentration of ammonia toxic vapor is greater than 1,100 ppm (AEGL-3 region) at a distance of 1 km, which might cause death in 60 seconds. The overpressure never exceeds 3.5 psi; thus, there is no possibility of serious injury or destruction of buildings. In the third scenario, the thermal radiation of BLEVE is greater than 10 kW/m2 at a distance of 376 m, which is potentially lethal within 60 seconds.
    Conclusions
    One of the main risks in petrochemical companies is the leakage of ammonia. The toxicity of ammonia is the most significant threat to people. The overpressure of vapor cloud explosion does not cause serious injury or of building destruction. The thermal radiation from jet fire and fireball has no effect on the city while it may cause death to the staff within 60 seconds. Thus, safety precautions should be considered to prevent the consequences of leakage accidents.
    Keywords: Modeling, ALOHA, Ammonia Emission, Petrochemical Industry
  • Ali Almasi, Behzad Hajimoradi, Mitra Mohammadi* Page 6
    Background
    This study aimed to evaluate reduced drug consumption, risky behaviors, depression, and anxiety and improved quality of life in addicts on methadone maintenance therapy (MMT) at baseline and six months after therapy.
    Methods
    In this descriptive cross-sectional study, 275 addicts were selected by a random sampling method in 2017. The data collection tools consisted of four questionnaires including a demographic information questionnaire, the Beck depression inventory questionnaire, WHOQOL-26, and Spielberger Anxiety Inventory. Data analysis was done by SPSS20 software at a confidence level of 95%.
    Results
    Based on the obtained results, after six months, MMT efficiency was 50.5% and no cases of intravenous injection were reported. The consumption of other drugs was significantly reduced (P < 0.05). The highest prevalence of depression was observed in cannabis and opium users. Depression decreased from 85.81% to 63.27%. The mean scores of quality of life and anxiety after MMT increased to 89.6 and 20.41, respectively. The most improvement was in the physical health domain (mean score of 64.11).
    Conclusions
    The results showed improvements in all the four domains of physical health, psychological health, social relationship, and environment and reductions in depression and anxiety.
    Keywords: High-Risk Behavior, Depression, Anxiety, Quality of Life, Methadone Maintenance Therapy, Kermanshah