Joint Disease Mapping of Two Digestive Cancers in Golestan Province, Iran Using a Shared Component Model

Objectives: Recent studies have suggested the occurrence patterns and related diet factor of esophagus cancer (EC) and gastric cancer (GC). Incidence of these cancers was mapped either in general and stratified by sex. The aim of this study was to model the geographical variation in incidence of these two related cancers jointly to explore the relative importance of an intended risk factor, diet low in fruit and vegetable intake, in Golestan, Iran. Methods: Data on the incidence of EC and GC between 2004 and 2008 were extracted from Golestan Research Center of Gastroenterology and Hepatology, Hamadan, Iran. These data were registered as new observations in 11 counties of the province yearly. The Bayesian shared component model was used to analyze the spatial variation of incidence rates jointly and in this study we analyzed the data using this model. Joint modeling improved the precision of estimations of underlying diseases pattern, and thus strengthened the relevant results. Results: From 2004 to 2008, the joint incidence rates of the two cancers studied were relatively high (0.8-1.2) in the Golestan area. The general map showed that the northern part of the province was at higher risk than the other parts. Thus the component representing diet low in fruit and vegetable intake had larger effect of EC and GC incidence rates in this part. This incidence risk pattern was retained for female but for male was a little different. Conclusion: Using a shared component model for joint modeling of incidence rates leads to more precise estimates, so the common risk factor, a diet low in fruit and vegetables, is important in this area and needs more attention in the allocation and delivery of public health policies. © 2015

Modeling of Individual and Organizational Factors Affecting Traumatic Occupational Injuries Based on the Structural Equation Modeling: A Case Study in Large Construction Industries

Background: Individual and organizational factors are the factors influencing traumatic occupational injuries. Objectives: The aim of the present study was the short path analysis of the severity of occupational injuries based on individual and organizational factors. Materials and Methods: The present cross-sectional analytical study was implemented on traumatic occupational injuries within a ten-year timeframe in 13 large Iranian construction industries. Modeling and data analysis were done using the structural equation modeling (SEM) approach and the IBM SPSS AMOS statistical software version 22.0, respectively. Results: The mean age and working experience of the injured workers were 28.03 ± 5.33 and 4.53 ± 3.82 years, respectively. The portions of construction and installation activities of traumatic occupational injuries were 64.4% and 18.1%, respectively. The SEM findings showed that the individual, organizational and accident type factors significantly were considered as effective factors on occupational injuries’ severity (P < 0.05). Conclusions: Path analysis of occupational injuries based on the SEM reveals that individual and organizational factors and their indicator variables are very influential on the severity of traumatic occupational injuries. So, these should be considered to reduce occupational accidents’ severity in large construction industries

Supervised wavelet method to predict patient survival from gene expression data.

In microarray studies, the number of samples is relatively small compared to the number of genes per sample. An important aspect of microarray studies is the prediction of patient survival based on their gene expression profile. This naturally calls for the use of a dimension reduction procedure together with the survival prediction model. In this study, a new method based on combining wavelet approximation coefficients and Cox regression was presented. The proposed method was compared with supervised principal component and supervised partial least squares methods. The different fitted Cox models based on supervised wavelet approximation coefficients, the top number of supervised principal components, and partial least squares components were applied to the data. The results showed that the prediction performance of the Cox model based on supervised wavelet feature extraction was superior to the supervised principal components and partial least squares components. The results suggested the possibility of developing new tools based on wavelets for the dimensionally reduction of microarray data sets in the context of survival analysis

Investigating the status of public health in Iran: A systematic review and meta-analysis

Public health is an aspect of the health overall concept and is one of the most important factors in human evolution and improvement which relies on methods and strategies to prevent the development of mental illness and treatment and rehabilitation for them. This study was aimed at estimating the status of public health in Iran using the metaanalysis method. The search was conducted using keywords of health, mental health, general health, GHQ-28 and Iran in international databases including Pubmed, Scopus, ISI, Google Scholar, and national databases of Sid, Med lib, Iranmedex, Magiran. Data were analyzed using meta-analysis (random effects model) by STATA Ver.11 software. Heterogeneity of studies was assessed using I2 index. The GHQ-28 questionnaire was used in all studies. In 79 reviewed studies with a sample of 31765 people during the years 1999 to 2015, good general health in Iran was 50 (95 CI, 42-58), 40 of individuals had poor general health and 30 of individuals had fairly acceptable public health. Also, poor general health was 47 among women and 36 among men. A significant percentage of Iranians suffer from poor general health. Hence, noticing the state of public health and providing the basis for the realization of a dynamic and healthy life for community members seems essential

Prevalence of vancomycin resistance among isolates of enterococci in Iran: a systematic review and meta-analysis

Introduction: Enterococcus is responsible for 10 of hospital-acquired infections. The purpose of this review was to evaluate the prevalence of vancomycin-resistant Enterococcus (VRE) isolates in Iran using a meta-analysis method. Materials and methods: Iranian databases, including Magiran and IranDoc, and international databases, including PubMed and MedLib, were examined carefully, and a total of 20 articles published between 2000 and 2011 were extracted. The data were subjected to meta-analysis and random-effects models. In addition, heterogeneous studies were assessed using the I-2 index. Finally, the data were analyzed using R and STATA software. Results: The results showed that the strain of Enterococcus faecalis had been more common than Enterococcus faecium in clinical infection (69 vs 28). However, resistance to vancomycin was higher among strains of E. faecium compared with strains of E. faecalis (33 vs 3). The complete resistance, intermediate resistance, and sensitivity to vancomycin among Enterococcus isolates were 14 (95 CI: 11, 18), 14 (95 CI: 5, 23), and 74 (95 CI: 65, 83), respectively. The resistance patterns, depending on the sample type, did not show a significant difference. In addition, the resistance of isolated strains to vancomycin in outpatients was significantly higher than that in inpatients (16 vs 1). Moreover, 80-86 of resistant strains were genotype van A and 14-20 of resistant strains were genotype van B. Conclusion: The findings of the present review show that there is a high frequency of resistant Enterococcus in Iran. Therefore, consideration of the prevalence and frequency of subjected resistant strains can be helpful for decision makers to implement proper health policies in this direction

Quantitative Assessment of Resilience in the operatives unitsof National Iranian Drilling Company (regional study: Khuzestan)

Introduction: Resilience engineering is a new approach in safety science. Its goal is to maintain organizational capacity in an acceptable level to help system in managing the crisis. Indeed, resilience engineering rely on systems abilities instead of weaknesses, and try to find indicators that help the system durability. .Material and Method: In this study,first, 6 resilience engineering factors were chosen and sent toexperts in the form of paired comparison sheets. On the other hand, a valid standard questionnaire distributed among drilling rigs operational workers for measuring the NIDC resilience level. Finally,the priority of corrective actionswas determinedaccording to the score of the two analyzedquestionnaires. .Results: The results of resilience engineering factors weighting showed that the management commitment has the highest value andthe second place belonged to the correct culture. The indicators’scores,based on the distributed questionnaires among workers, showed that all of the six factors had similar scoreswhich can be evaluated as fairly good. Finally, the results of prioritization of indicators ofresilience engineering, basedon the combination ofthe questionnaire and experts opinions showed that management commitment is the most effective resilience factor in the organization. ..Conclusion: Management commitment and the current culture are the most importantcontributing factorsin company resilience level. Experienced workforce was the best strengthof the company and the effect of financial issues on resilience and safety was the biggest problem ahead