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Showing 6 results for Abadi

Alireza Abadi, Bagher Pahlavanzade, Keramat Nourijelyani, Seyed Mostafa Hosseini,
Volume 3, Issue 1 (5-2015)

Background & Objective: Inability to measure exact exposure in epidemiological studies is a common problem in many studies, especially cross-sectional studies. Depending on the extent of misclassification, results may be affected. Existing methods for solving this problem require a lot of time and money and it is not practical for some of the exposures. Recently, new methods have been proposed in 1:1 matched case–control studies that have solved these problems to some extent. In the present study we have aimed to extend the existing Bayesian method to adjust for misclassification in matched case–control Studies with 1:2 matching.

Methods: Here, the standard Dirichlet prior distribution for a multinomial model was extended to allow the data of exposure–disease (OR) parameter to be imported into the model excluding other parameters. Information that exist in literature about association between exposure and disease were used as prior information about OR. In order to correct the misclassification Sensitivity Analysis was accomplished and the results were obtained under three Bayesian Methods.

Results: The results of naïve Bayesian model were similar to the classic model. The second Bayesian model by employing prior information about the OR, was heavily affected by these information.

The third proposed model provides maximum bias adjustment for the risk of heavy metals, smoking and drug abuse. This model showed that heavy metals are not an important risk factor although raw model (logistic regression Classic) detected this exposure as an influencing factor on the incidence of lung cancer. Sensitivity analysis showed that third model is robust regarding to different levels of Sensitivity and Specificity.

Conclusion: The present study showed that although in most of exposures the results of the second and third model were similar but the proposed model would be able to correct the misclassification to some extent.

Soheila Meimanat Abadi, Dr Fazlullah Ghofranipour, Dr Faegh Yousefi, Farhad Moradpour,
Volume 4, Issue 1 (5-2016)

Background and Objectives: Damages caused by accidents are accounted as a major cause of death for children under 5 years old. To design preventive programs, health education theories could be employed. This study aimed to determine the effect of educational intervention based on health belief model on the damage caused by accidents in children less than 5 years in 1392 in Qorveh city.

Methods: The present randomized field trial study was conducted on 120 mothers with children less than 5 years who were supported by four different health centers. These centers were randomly divided into two groups of intervention and control. The effect of intervention was investigated using a standardized questionnaire including 85 items of health belief model structures. The questionnaires were completed using interviews by trained interviewers. Statistical analysis was done using SPSS 19.0, independent and two-tailed samples t-test.

Results: We found that there were positive and significant differences in terms of knowledge, intensity, perceived barriers and self-efficacy between two groups after intervention (P<0.05). Average differences before and after the intervention and the average scores were significantly different in all cases (P<0.05). There was a significant difference regarding the mild injuries among children under five years between the two groups after intervention (P=0.023).

Conclusion: Our results showed that education on the basis of health belief model, as one of the theories of health education, has positive effects on the promotion of safety knowledge, attitude change and improving the function of mothers over damaged children lower than 5 years and consequently the promotion of health and safety among children.

Masoomeh Gholami, Majid Najafzadeh, Naser Behnampour, Zahra Abdollahi, Farzaneh Sadeghi Ghotbabadi, Farhad Lashkarboluki, Mohammad Reza Honarvar,
Volume 7, Issue 3 (9-2019)

Background and objectives: Iran was reported in the high-risk group of World Food Security Map in 2008 .Identifying food insecurity is first step for executing interventions. Measuring household food security is its cornerstone. SAMAT System was designed to provide a variety of GIS-based reports to policy makers and managers in the field of food security.
Methods and Materials: SAMAT system was developed by a team working with various specialties. The system was analyzed using Rational Unified Process methodology and after optimization and normalization process, centralized database was formed. SQL Server 2014 software was used for its implementation. SharpMap open source engine was used to render spatial data and display maps on the web, and many parts of the engine were coded specifically to meet different organizational needs. The system was designed using the WEB GIS engine.
 Results: SAMAT system was executed in nine provinces of the country in different periods. SAMAT dashboard provides a variety of information for executive managers. Based on demographic data, the state of food insecurity can be identified at different levels from city to village, in a variety of graphs. A spectrum from the urban distribution to the local distribution of food insecurity can be identified on the GIS map. Zooming in on different areas can help to identify more food insecure neighborhoods within the village or town, thus giving managers the priority of food insecurity interventions at the neighborhood or village level. One can view household characteristics and the results of questionnaire information .
Conclusion:  SAMAT system can be useful for managing food security at the national, provincial, city and even rural or urban levels. we recommend periodically prioritizing points, Identifying the provinces and re-evaluating the effectiveness of interventions through the SAMAT-based system after comprehensive implementation of food insecurity reduction 

Sayede Shadi Nazari , Solmaz Norouzi, Mohammad Asghari Jafar-Abadi,
Volume 8, Issue 1 (3-2020)

Background and objective: Prevalence and the spread of novel Coronavirus (2019-ncov) cause significant life and financial destruction worldwide and is the cause of severe respiratory infection in humans. The present study briefly reviews the latest information on how the virus is distributed around the world. The main question of the study are: 1- In which geographic regions of the world is the Coronavirus more concentrated? 2- Is the distribution of the Coronavirus geographically stable?
Material and Methods: To answer these questions, we first began collecting and studying the available scientific resources. The required data was obtained from a daily report of confirmed, recovered, and deaths by the Coronavirus separated by state which was collected from January 22, 2020 to Jun 19, 2020. Based on analyzing available patterns in spatial statistics tool in ArcGIS and geostatistical models, we examined how the Coronavirus was distributed around the world.
Results: The spread of the disease is increasing all over the world. Using the results of Map 1, it is seen that the spread of Corona virus has a trend and starts in China and then spreads to the Middle East, Europe and the United States in a linear manner. The results also show that the prevalence of mortality is higher than that of recovery. Central mean and median for all types (Confirmed, Recovered and death) are close to each other. Death mean and median was close to Western countries and Recovered mean and median was close to Eastern countries, while confirmed mean and median was located in the center.
Conclusion: Based on spatial statistics tool in ArcGIS and geostatistical models, we examined how the Coronavirus was distributed around the world. Our results showed that the spread of Corona virus had a trend and started in China and then spread to the Middle East, Europe and the United States in a likely linear manner.

Abdossaleh Zar, Fatemeh Ahmadi, Hamid Reza Sadeghipour, Abolfazl Shayan Nooshabadi,
Volume 8, Issue 2 (7-2020)

Background and objective: Tobacco consumption is one of the hazardous factors that affect people’s quality of life and quality of sleep. This study aimed to compare components quality of sleep in physically active and inactive people tobacco consumers.
Methods: Tobacco consumers in Shiraz were the statistical population of this comparative study. That 470 people of them Participated in the study. Pittsburgh sleep quality questionnaire (PSQI) was used for data collection.
Results: physically active tobacco consumers compared with inactive tobacco consumers obtained significantly better scores in total PSQI score (p = 0.006) and subscales such as daytime dysfunction (p = 0.007), sleep duration (p = 0.002), sleep latency (p = 0.01), subjective sleep quality (p = 0.03).
Conclusion: Exercise and physical activity can have a positive effect on the quality of sleep in tobacco consumers. Findings can inform interventions designed to improve sleep quality via increasing opportunities for exercise among smokers.

Batol Amini Najafabadi, Saeed Keshavarz, Sedigheh Asgary, Mehrdad Azarbarzin,
Volume 8, Issue 3 (10-2020)

Background and objective: The effect of aerobic exercise (AE) on cardiovascular (CVD) related risk factors are still debatable. Therefore this randomized controlled clinical trial (RCT) was performed with unique and specific AE protocol to investigate the effect of eight-week AE only on female subjects with type 2 diabetes.
Material And Method: A controlled RCT was performed on 30 women with type 2 diabetes aged 30 - 50. They were randomly divided into two groups, intervention and control by block randomization method. The intervention group received an incremental AE for eight weeks, three sessions per week, max heart rate (55-75%) and rating of perceived exertion (RPE) 12-13 for 150 minutes per week. Blood samples were taken before and after each intervention for both groups to be evaluated for fasting blood sugar (FBS), hemoglobin A1c (HbA1c), lipid profile [triglyceride (TG), total cholesterol (TC), low density lipoprotein cholesterol (LDL-C) and high density lipoprotein cholesterol (HDL-C)].
Result: Eight-week AE intervention led to a significant decrease in HbA1c, FBS levels (p = 0.025, p=0.003) in experimental group compared to control however no significant differences was observed in terms of lipid profile (total cholesterol (TC), triglyceride (TG), LDL-C and HDL-C) between control and experimental group (p> 0.05). The results of paired t-test showed that FBS, TC and HbA1c levels were significantly reduced within experimental group after intervention compared to pre-test (p = 0.038, p = 0.05, p = 0.002, respectively). There was no significant difference between TG, LDL-C, and HDL-C levels within experimental group between pre and post-test (p>0.05).
Conclusion: It can be concluded that AE has been effectively reduce FBS, HbA1c and TC in women type 2 diabetes.

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