http://jbe.tums.ac.ir/index.php/jbe/issue/feed Journal of Biostatistics and Epidemiology 2019-07-23T09:17:13+0430 Dr. Hojjat Zeraati jbe@tums.ac.ir Open Journal Systems http://jbe.tums.ac.ir/index.php/jbe/article/view/224 Assessing the Effective Factors on Depression in Khuzestan Women 2019-06-24T10:33:06+0430 Mojtaba Sepandi msepandi@gmail.com Maryam Taghdir mtaghdir@gmail.com Isa Akarzadeh isa.king2012@gmail.com Farzad Khodamoradi f_khodamoradi@yahoo.com Yousef Alimohamadi y.alimohamadi67@gmail.com <p><strong>Introduction:</strong> Depression is one of the main problems and disrupting daily life activities in women. Due to the important role of women in society and the effect of depression on this group activity the aims of the current study was to investigate of the identification effective factors on women's depression in Khuzestan province.<br> <strong>Method:</strong> In this cross-sectional study, 899 women who referred to health centers in Ahwaz were selected by cluster sampling method. For analysis purpose, multivariate and univariate linear regression was used. All analysis performed by SPSS version 19 with regarding α: 0.05 for the significant level.<br><strong>Results:</strong> in case of effective factors on depression score, number of Education Years, Competence score, Relatedness score, Autonomy score, Presence of Meaning in Life score, Search for Meaning in Life score had the significant effect on depression score (p&lt;0.001).<br><strong>Conclusion:</strong> Education level, marital status, education level, Social Competence, relatedness, Autonomy; Presence of meaning in life, Search for meaning in life and Depression are effective factors on depression so focusing on this factors can have the very important role in prevention programs.</p> 2019-03-13T14:49:07+0330 ##submission.copyrightStatement## http://jbe.tums.ac.ir/index.php/jbe/article/view/232 Linear Mixed Effect Model with Application to Random Blood Sugar Data 2019-07-17T09:17:26+0430 Melkamu Ayana Zeru melkamu.ayana@gmail.com <p><strong>Background &amp; aim:</strong> Diabetes mellitus is a common, chronic, metabolic syndrome characterized by hyperglycemia as a cardinal biochemical feature. Type-1 diabetes is a continuing hormonal deficiency disorder that has significant short-term impacts on health and lifestyle and is associated with major long-term complications like heart failure, kidney, hypertension, eye damage, etc. which reduced life expectancy. The main objective of this study was to assess the risk factor that increase prevalence of type-1 diabetes mellitus and to determine their relationship with outcome of type-1 diabetes mellitus over time.<br><strong>Methods &amp; materials:</strong> To address this objective linear mixed effect model was applied using the random blood sugar of 970 diabetic patient children during treatment period of 3 years at Hiwot Fana hospital which have been implemented in statistical packages STATA, SAS and R.</p> <p><strong>Result:</strong> This study found that the mean progression of random blood sugar level of diabetic children was decreased over time after they starts their follow up and medications. The linear distribution also accounts 92 % variability of the data was explained by the covariates which were included in the study. The variable age, residence, family history, nutrition status, early diet, body mass index, electrolytes and renal function test had significant effect on the change of sugar level (p &lt; 0.05).<br><strong>Conclusion:</strong> The cumulative incidence of type-1 diabetes mellitus disease was increased due to presence of co-infections and decreased with pharmacological diabetes treatment. The linear mixed effects model fitted was appropriate for the estimation of sugar levels based on the risk factor variables for type-1 diabetes mellitus patient children. ABBREVIATIONS:RBS = Random blood sugar; FH = Family history; UM = under malnutrition; OM = Over malnutrition; RFT= Renal function test; NS=Nutritional status</p> 2019-03-13T14:35:38+0330 ##submission.copyrightStatement## http://jbe.tums.ac.ir/index.php/jbe/article/view/219 Partial Least Square Path analysis of knowledge, Attitude and Practice Regarding Dengue 2019-07-23T09:17:13+0430 Lamidi-Sarumoh Alaba Ajibola lalabaajibolasarulam@gmail.com Shamarina Shohaimi shamarina@upm.edu.my Mohd BakriAdam bakr@upm.edu.my Mohd Noor Hisham Mohd Nadzir mnhisham@upm.edu.my Oguntade Emmanuel Segun oguntadeemmanuel2015@gmail.com <p><strong>Introduction:</strong> Knowledge, attitude and practices regarding dengue are latent variables which are substantiated through manifest variables. The manifest variables that form the indicative construct of knowledge, attitude and practice can be factored into sub-constructs such that the impact of each indicative variable can be verified. <br><strong>Method:</strong> Evaluation of the sub-constructs of knowledge, attitude and practices regarding dengue using a Partial least square path models with R programming language. <br><strong>Result:</strong> The measurement model revealed the sub-constructs that are negatively affecting the latent variables and the ones that are having low impact. <br><strong>Conclusion:</strong> This analysis gives the possibility of observing the exact knowledge, attitude and practices regarding dengue that are inadequate among respondents. The result from this methodological approach can be used as an aid for the community health programs and campaigns on how to enlighten the populace of interest on the required awareness about dengue, attitude towards dengue and the preventive practices that are deficient among them.</p> 2019-03-13T14:31:38+0330 ##submission.copyrightStatement## http://jbe.tums.ac.ir/index.php/jbe/article/view/218 Gestational diabetes : Worrisome Prevalence 2019-06-24T10:36:08+0430 Mahmoud Parham mahmoud51dr@yahoo.com Mohammad Bagherzadeh mohammad.bagherzadeh1395@gmail.com Mohammad Hossein Ghasembeglou mghasembegloo@yahoo.com Jamshid Vafaeimanesh jvafaeemanesh@yahoo.com <p><strong>Background &amp; Aim:</strong> Gestational diabetes mellitus (GDM) is the most common metabolic disorder in pregnancy which is caused due to insulin resistance and carries several risks for the mother and neonate. So, an updated data from its prevalence in different geographical areas is important.<br><strong>Methods &amp; Materials:</strong> This cross-sectional analytic study was performed on pregnant women referring health centers in Qom city from June 2013 to September 2014 for prenatal care. In week 10 of pregnancy, fasting blood sugar (FBS) was checked for all participants and those who had FBS &gt;126mg/dL for 2 times were excluded from the study and all participants who remained in the study underwent oral glucose tolerance test with 75 gr glucose at 24-28weeks of gestation. Gestational diabetes was diagnosed on the basis of at least one abnormal responses of glucose≥92mg/dL, 1-hour glucose ≥180 mg/dL or 2-hour glucose ≥153mg/dL.<br><strong>Results:</strong> A total of 4988 pregnant women enrolled the study. Based on 75g oral glucose tolerance (OGT) test results at 24-28 weeks of gestation, 1036 women (20.76%) had gestational diabetes. Gestational diabetes was significantly associated with maternal age, body mass index, history of gestational diabetes, a family history of type II diabetes in first-degree relatives, history of preterm labor, known hypothyroidism before pregnancy and history of macrosomia.<br><strong>Conclusion:</strong> Gestational diabetes has a high prevalence in Qom city, and it seems that new studies are needed to determine its prevalence in other regions.</p> 2019-03-13T14:29:59+0330 ##submission.copyrightStatement## http://jbe.tums.ac.ir/index.php/jbe/article/view/233 Fuzzy Analysis of Knowledge Management 2019-07-17T09:14:03+0430 Amir Najafi asdnjf@gmail.com Reza Taghikhani asdnjf@gmail.com <p><strong> Background &amp; Aim:</strong> Knowledge Management (KM) is widely known as a critical issue in offices, factories and organizations. The present study intends to predict the success or failure of KM implementation in the automotive industry.<br><strong>Methods &amp; Materials:</strong> we have tried to analyze and predict the degree to which how successfully we can implement KM in the automotive industry using fuzzy inference method (FIS). In this regard, after data collection, and employed FIS software to analyze our results.<br><strong>Results:</strong> As our results show, the projected level for the implementation of KM in Iran Khodro was about 58%. Given that this study was conducted in five different, but related parts in Iran Khodro as well as these five sectors were less similar in terms of structure, individual and usage of technology, we should not expect similar results about the rate of implementing knowledge management.<br><strong>Conclusion:</strong> Our results would be important and interesting, because they will provide the basis for how successfully establish KM in the automotive industry and similar organizations in order to improve the efficiency and productivity in organizations.</p> 2019-03-13T14:27:20+0330 ##submission.copyrightStatement##