Gastric and esophageal cancers incidence mapping in Golestan Province, Iran: Using Bayesian-Gibbs sampling

Objectives: Recent studies of esophageal cancer (EC) and gastric cancer (GC) have been reported to have high incidence rates of these cancers in Golestan Province of Iran. The present study describes the geographical patterns of EC and GC incidence based on cancer registry data and display statistically significant regions within this province. Methods: In order to map the distribution of upper gastrointestinal cancer, relative risk (RR) were calculated. Therefore, to estimate a more reliable RR, Poisson regression models were used. The adjusted models (adjusted to urban-rural area, sex, and grouped age proportion) were utilized. We considered two-component random effects for each observation, an unstructured (noncorrelated) and a group of "neighbor" (correlated) heterogeneities. We estimated the model parameters using Gibbs sampling and empirical Bayes method. We used EC and GC data that were registered with Golestan Research Center of Gastroenterology and Hepatology in the years 2004-2008. Results: The EC and GC maps were drawn for 2004-2008 in the province. Kalaleh and Minoodasht counties have a high RR of EC and GC in the years of study. In almost all years, the areas with a high RR were steady. Conclusion: The EC and GC maps showed significant spatial patterns of risk in Golestan province of Iran. Further study is needed to multivariate clustering and mapping of cancers RRs with considering diet and socioeconomic factors. © 2015 Korea Centers for Disease Control and Prevention

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

HSE Risk Management Systems Analysis and Modeling its Relationship with Occupational Accidents in the Construction Industry

Introduction:Risk of occupational accidents in construction industry and sites is very high and dangerous. The establishment of an effective and efficient risk management system is an important step in prevention of construction accidents. The purpose of this study was to analyze the HSE risk management systems in large construction sites and their association with the occupational accidents. Methods: This study was an analytical cross-sectional review that analysis the risk management system and its relation to the accidents of 88-92 years that has been occurred in the construction large sites. Study data includes information about the all HSE risk management systems and human accidents that occurred within 5 years in the various construction sites. Data collection was performed according to the accident report form in construction sites. Data analysis was performed using SPSS software version 16. The level of significance in this study was considered as p=0.05. Results: The mean accident severity rate (ASR) was 1.51&times;103&plusmn;1.05&times;104. The results showed that,risk management system has been established in 18.4% of the studied sites, and the share of the risk management system components and indicators including hazard identification, periodic risk assessment and the implementation of control procedures which was estimated&nbsp; 16.4%, 16.6% and 10.2% respectively.In addition, all indicators of risk management were significantly associated with ASR (p<0.05). Conclusion:ASR Regression analysis based on the risk management Indicators, &nbsp;showed that demographic and job parameters such as work experience and career type, as well as, risk management indicators such as the risk management system establishment,HAZID, periodic risk assessment, HSE training and Housekeeping have been significant associated with accidents consequence severity in the construction industry

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