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BackgroundThis study examined how socio-demographic characteristics constructs derived from the health promotion model (HPM) influence the level of physical activity (PA) women in Bojnourd, North East of Iran.MethodThis cross-sectional study has been carried out through multi-stage sampling design on 356 women aged 18–60 years living in Iran. Data was collected through reliable and valid questionnaire survey women who were selected from their homes.ResultsMost of participants (53.40%) had a low level of physical activity behaviors with minimal physical activity (PA) scores. Using regression analysis showed that 23.22% of the total variance in PA behaviors was predicted by socio-demographic variables, whilst 40.81% of the variance in PA behaviors was predicted by constructs from the HPM. The results from Path modeling indicated that prior behavior, interpersonal influences, perceived self-efficacy, perceived barriers and commitment to PA, were significant predictors for PA behaviors with 86.93% of total effects on PA, whereas, activity-related affect and situational influences had no significant effect on the PA behaviors.ConclusionsWe found that constructs derived from the HPM are determinants of PA among Iranian women and may be important in developing educational intervention programs to facilitate a physically active lifestyle in this population.

Objective:The relative contribution of health promotion models (HPM) to improve health-related behaviours in intervention programmes is still limited. Here, we tested whether Pender’s HPM operationalised in the educational intervention was effective to modify nutrition and physical activity (PA) behaviours among Iranian women.Design:A randomised controlled field trial evaluating the efficacy of an educational intervention based on Pender’s HPM to improve PA and nutrition behaviours from August 2016 to October 2016. R version 3.0.2 and SPSS version 16 were used to conduct multiple statistical analyses.Setting:Ten public healthcare centres in Bojnourd, Iran were randomly divided into intervention and control groups. The experimental group received the full intervention programme, which included nine 4-h training sessions and consulting support via phone contact and social media group. The control group did not receive any intervention.Participants:Women aged 4–6 years (n 202) were randomised to intervention (n 102) and control conditions (n 100) and completed baseline and 3-month follow-up.Results:In the experimental group, the intervention programme had a significant effect (P < 0·05) on all construct of Pender’s HPM and behaviour outcome, and the estimates for prior behaviours, self-efficacy, interpersonal influences, feeling, perceived benefits and barriers, commitment and behaviour outcomes in the intervention group were 0·72 (95 % CI 0·31, 0·98), 0·54 (95 % CI 0·27, 0·71), 0·74 (95 % CI 0·27, 0·91), 0·52 (95 % CI 0·19, 0·75), 0·62 (95 % CI 0·22, 0·91), 0·63 (95 % CI 0·30, 0·86) and 0·56 (95 % CI 0·37, 0·85), respectively.Conclusions:Educational intervention based on Pender’s HPM was feasible and highly acceptable to modify PA and nutrition behaviours in the women population.

Data on how the complex cognitive processes, personal, and social factors influence health promoting behaviors of women are very limited and the results have been inconsistent. Here, we examine how prior behaviors, behavior-specific cognition (perceived benefits/barriers, self efficacy, and activity-related affect), situational and interpersonal factors (social support, modeling, and norms) associated with the level of dietary behaviors in Iranian women. A cross sectional survey of 356 women aged 18–60 years from health care centers in Iran was undertaken from October 2015 to September 2016. Multiple analytical models and Pender’s health promotion model (HPM) were implemented to examine the effectiveness of HPM and its potential constructs on PA behaviors. The instruments used were designed using Pender’s HPM as a basis. The path model fitted data and accounted for 51% of the variance in dietary behaviors; and prior behavior, perceived self-efficacy, interpersonal influences, and commitment to plan were significantly associated with dietary behavior. We found that constructs from the HPM are empirically improved dietary behavior among the women population. This result provides a suitable source for designing strategies of a nutrition education intervention for improving the frequency and nutrient intake of breakfast consumption among female students.

Background\ud Cardiovascular disease (CVD) is the most common cause of morbidity and mortality globally. Despite progress being made in the diagnosis and treatment of CVDs, one third of deaths are due to CVDs. We have investigated the association between the rs1333049 polymorphism of the cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) gene with CVD outcomes in a population sample recruited as part of the Mashhad-Stroke and Heart-Atherosclerotic-Disorders (MASHAD) cohort.\ud \ud Methods and results\ud Five hundred and nine individuals who had a median follow-up period of 10 years were recruited as part of the MASHAD cohort. Anthropometric, and biochemical parameters were assessed followed by genotyping using TaqMan-real-time-PCR based method. Our data showed that carriers of the GG genotype were significantly more likely to develop CVD, compared to those with a CC or CG genotypes (OR: 4.77, 95%CI: 2.62–8.68, p = 0.001). Similar result we also found in second population which were follow up for 10 years. In particular cases who had an event in recessive genetic model (CC vs CG + GG) had a higher risk of developing CVD (OR: 5.57, 95%CI: 2.80–11.06, p = 0.001).\ud \ud Conclusion\ud We have found that carriers of the GG genotype of the CDKN2A/B gene locus were at increased risk of CVD in a representative population-based cohort, indicating further functional analysis to explore the value of emerging marker as a risk stratification biomarker to identify high risk cases.

BACKGROUND: Cardiovascular disease is one of the most common causes of morbidity and mortality worldwide. The Proline and Serine Rich Coiled-Coil 1 gene in 1p13.3 locus has been reported to be associated with low density lipoprotein cholesterol (LDL-C) and coronary artery disease (CAD). The objective of this study was to investigate the association between the rs599839 polymorphism of the Proline and Serine Rich Coiled-Coil 1 (PSRC1) gene with CVD outcomes in a population sample recruited as part of the Mashhad-Stroke and Heart-Atherosclerotic-Disorders (MASHAD) cohort. METHODS: Five hundred and nine individuals who had an average follow-up period of 10 years were enrolled as part of the MASHAD cohort. DNA was extracted and genotyped using the TaqMan-real-time-PCR based method. RESULTS: The study found individuals with GA/GG genotypes were at a higher risk of CVDs (OR= 4.7; 95% CI, 2.5-8.7; p< 0.001) in comparison to those with AA genotype; however, the result was not significant for GG genotype data. CONCLUSION: The results suggest that the GA/GG genotypes of the PSRC1gene locus were at increased risk of CVD in a representative population-based cohort, demonstrating further functional analysis to discover the value of emerging marker as a risk stratification biomarker to recognize high risk cases.

Introduction: Coronary heart disease (CHD) is the leading cause of morbidity and mortality globally, and specially in Iran. An accurate assessment of the incidence of coronary heart disease (CHD) is very important for public health. In current study we aimed to investigate the incidence of CHD and importance of several classical modifiable and un-modifiable risk factors for CHD among an urban population in eastern Iran after 6 years follow-up. Methods: The population of MASHAD cohort study were followed up for 6 years, every 3 years initially by phone and those who reported symptoms of cardiovascular disease (CVD) were asked to attend for a cardiac examination. An estimate of the incidence of CHD was determined with 95% confidence interval (95% CI) and multiple logistic regression analysis was performed to assess the association of several baseline characteristics with the incidence of a CHD event. Evaluation of goodness-of-fit was undertaken using ROC analysis. CHD cases were divided into four different categories: stable angina, unstable angina pectoris, myocardial infarction and sudden cardiac death. Results: In the six years of follow-up of the Mashhad study participants, the incidence density of CHD events in men and women in 1000 person-year with 95% confidence intervals were 19.20 (8.10-30.30) and 11.60 (7.30-15.90), respectively. The areas under ROC curve (AUC), based on multiple logistic regression model of CHD outcome, was determined to be 0.783. Conclusion: Our findings indicated that the incidence rate of coronary heart diseases in MASHAD cohort study increases with age, and our final model was able to predict approximately 78% of CHD events in this Iranian population.

Metabolic syndrome (MetS) is a clustering of metabolic abnormalities that is associated with increased risk of developing cardiovascular disease and type 2 diabetes. There is growing body of data showing the associations of genetic variants of the genes involved in the PI3K/AKT/mTOR pathway with diabetes and obesity. We aimed to investigate the association between MetS and its components with the genetic polymorphism in AKT1, rs1130233 (T > C). Total of 618 participants, recruited from Mashhad stroke and heart atherosclerosis disorder cohort (MASHAD study). Patients with MetS were defined by using international diabetes federation (IDF) criteria (n = 326) and those without MetS (n = 261) were recruited. Anthropometric and biochemical parameters were measured in all subjects. Genetic analysis for the rs1130233 polymorphism was performed, using the ABI-StepOne instruments with SDS version-2.0 software. Individuals with MetS had a significantly higher levels of BMI, waist-circumference, total cholesterol, triglyceride, high sensitivity-c reactive protein (hs-CRP) and blood-pressure, and lower concentrations of high density lipoprotein (HDL-C), compared to non-MetS individuals (P C) polymorphism was associated with major components of MetS such as hs-CRP, and BMI, indicating further investigation in a multi-center setting to explore its value as an emerging biomarker of risk stratification marker.

Background The role of dietary patterns in metabolic syndrome has not been investigated sufficiently among Iranian population. The aim of this study is to investigate the association of major dietary patterns with the risk of metabolic syndrome and its components among healthy individuals of Iran. Methods This is a cross-sectional study that was performed on 5895 men and women who participated in MASHAD study project. Factor analysis was employed to determine major dietary patterns with regard to a validated 65-item food frequency questionnaire. Metabolic syndrome was diagnosed using international diabetes federation (IDF). Logistic regression analysis was used to evaluate the association between dietary patterns and metabolic syndrome risk to generate odds ratios (ORs) and 95% confidence intervals (CI). Results Three major dietary patterns (Balanced, Western and high carbohydrate) were identified. The Western pattern showed a positive association with metabolic syndrome (OR [95%CI] for highest vs. lowest tertile: 1.58 [1.21–2.06]; p value = 0.001). The high carbohydrate dietary pattern was associated with higher metabolic syndrome risk (OR [95%CI] for highest vs. lowest tertile: 1.17 [1.02–1.33]; P value = 0.022). The Balanced dietary pattern was unrelated to metabolic syndrome, but was related to some individual risk factors for metabolic syndrome. Conclusions These results suggest that the Western and high carbohydrate patterns are associated with an increased risk for metabolic syndrome among Iranian adults. The causality of these associations needs to be confirmed.

Serum high-sensitivity C-reactive protein (hs-CRP) is predictive of coronary artery disease (CAD). The aim of this study was to examine the possible association of hs-CRP with presence and severity of CAD and traditional CAD risk factors. This case-control study was carried out on 2,346 individuals from September 2011 to May 2013. Of these 1,187 had evidence of coronary disease, and were subject to coronary angiography, and the remainder were healthy controls (n = 1,159). Characteristics were determined using standard laboratory techniques and serum Hs-CRP levels were estimated using enzyme-linked immunosorbent assay (ELISA) kits, and severity of CAD was assessed according to the score of obstruction in coronary artery. Serum hs-CRP levels were higher in those with severe coronary disease, who had stenosis ≥ 50% stenosis of at least one coronary artery (all p < 0.001 vs. individuals in healthy control), and correlated significantly with the score for coronary artery disease (all p < 0.01). After adjustment for conventional risk factors, regression analysis revealed that smoking habits, fasting blood glucose, total cholesterol, high-density lipoprotein, hs-CRP, blood pressure, anxiety, dietary intake of vitamin E, and cholesterol remained as independent determinants for angiographic severity of CAD. The area under the receiving operating characteristic (ROC) curve for serum hs-CRP was 0.869 (CI 95% 0.721-0.872, p < 0.001). The optimal values for the cut-off point was a serum hs-CRP of 2.78 mg/l (sensitivity 80.20%, specificity 85%) to predict severity of CAD. Increased serum hs-CRP levels are significantly associated with angiographic severity of CAD, suggesting its value as a biomarkers for predicting CAD.

Background: Increasing the prevalence of type 2 diabetes has given rise to a global health burden and a concern among health service providers and health administrators. The current study aimed at developing and comparing some statistical models to identify the risk factors associated with type 2 diabetes. In this light, artificial neural network (ANN), support vector machines (SVMs), and multiple logistic regression (MLR) models were applied, using demographic, anthropometric, and biochemical characteristics, on a sample of 9528 individuals from Mashhad City in Iran. Methods: This study has randomly selected 6654 (70%) cases for training and reserved the remaining 2874 (30%) cases for testing. The three methods were compared with the help of ROC curve. Results: The prevalence rate of type 2 diabetes was 14% in our population. The ANN model had 78.7% accuracy, 63.1% sensitivity, and 81.2% specificity. Also, the values of these three parameters were 76.8%, 64.5%, and 78.9%, for SVM and 77.7%, 60.1%, and 80.5% for MLR. The area under the ROC curve was 0.71 for ANN, 0.73 for SVM, and 0.70 for MLR. Conclusion: Our findings showed that ANN performs better than the two models (SVM and MLR) and can be used effectively to identify the associated risk factors of type 2 diabetes.

Hypertension is a common cardiovascular risk factor within the Iranian population, and this may be improved through changes in lifestyle. We aimed at improving hypertension outcomes and health literacy skills among hypertensive patients through communication skills training targeting health providers.A randomized controlled trial method was used to enroll 35 health providers and 240 hypertensive patients attending community-based healthcare practices in the Mashhad, Iran. We evaluated the effects of a communication skills intervention for primary care providers compared to usual care controls, on the hypertension outcomes, patient medication adherence, and self-efficacy, assessed at baseline and post-intervention. Bivariate analysis and the regression model were used to assess whether the health provider training improved outcomes.Majority of participating patients were female (77.3%), less than high school education (80.3%), married (82.3%), and low income (82.3%), with mean age of 37 years. Following the educational intervention, there was a significant improvement (p 0.05) in patient communication skills, self-efficacy, adherence to medication, and hypertension outcomes in the intervention compared to the control group.The brief communication skills training for health care providers appear to be an efficient way to improve patient-provider communication skills and hypertension outcome among patients with uncontrolled BP.

Aim The determinants of serum vitamin D seems to be the environmental factors (dietary and supplementary intake and exposure to ultraviolet light) and genetic factors. We aimed to study the relationship between a vitaminD‐associated genetic polymorphism and serum 25(OH)D concentrations in healthy adolescent girls in Iran, and its effects on a high‐dose supplement of vitamin D. Material and method A total of 616 healthy adolescent girls with mean age 15 received 50,000 IU of vitamin D3 weekly over 9 weeks. Serum vitamin D levels and other metabolic factors were measured at baseline and after the intervention. The genotyping of the CYP2R1 variant (rs10741657) was performed by TaqMan genotyping assays. Results Regardless of the genetic background, at baseline, 87% of adolescent girls were vitamin D deficient (serum 25(OH)D level ptrend = 0.1), the response to supplementation appeared to be modulated by this variant (ptrend pvalue = 0.002). Conclusion Based on our findings, it appears that the rs10741657 variant of the CYP2R1 gene modulates the response to high‐dose of vitamin D supplementation.

INTRODUCTION: Preeclampsia is the most common medical complication in pregnancy; along with bleeding and infection, it is one of the three causes of death in pregnant women. Most of these deaths were due to delays in the diagnosis and improper midwifery management and care. On the other hand, the quality of midwifery education has a profound effect on the proper provision of services. Therefore, the present study has been done to compare the effect of simulation-, blended-, and lecture-based education on simulated midwife performance in the management of preeclampsia and eclampsia. MATERIALS AND METHODS: This three-group clinical trial study was performed on 90 midwives of selected hospitals in Mashhad in 2016. Midwives were divided into three groups of simulation-, blended-, and lecture-based education using the random number table. The simulation group was trained for 6 h at the Center for Clinical Skills, the blended group was trained for 4 h by lecture, and 6 weeks through the educational website, and the lecture group was trained for 6 h through lecture. An objective structured clinical test was performed before and 2 weeks after the intervention. Data were analyzed using SPSS Version 16 software and descriptive statistics, paired t-test, one-way ANOVA, and Wilcoxon and Kruskal–Wallis tests. Significance level was considered to be P < 0.05 in all cases. RESULTS: The mean score of midwives' performance was not statistically significant before education in all three groups (P < 0.05). The mean score of midwives' performance was significantly increased in all three groups 2 weeks after education (P < 0.001), and the results of intergroup comparison showed that the mean score of performance in the simulation group was significantly higher than the blended group and the lecture group (P < 0.001), and it was higher in the blended group compared to the lecture group (P < 0.001). CONCLUSION: Education increased the midwives' simulated performance in preeclampsia and eclampsia. The performance of the management of preeclampsia and eclampsia in the simulation educational group is more than that of the blended and lecture groups, so we can use the simulation education which is a self-centered method.

Associated risk factors of CAD using decision tree.Sensitivity, specificity, accuracy of 96%, 87%, 94% and respectively.Serum hs-CRP levels as most important variable associated with CAD.Model is accurate, specific and sensitive for investigating risk factors of CAD. Background and aimsCoronary heart disease (CHD) is an important public health problem globally. Algorithms incorporating the assessment of clinical biomarkers together with several established traditional risk factors can help clinicians to predict CHD and support clinical decision making with respect to interventions. Decision tree (DT) is a data mining model for extracting hidden knowledge from large databases. We aimed to establish a predictive model for coronary heart disease using a decision tree algorithm. MethodsHere we used a dataset of 2346 individuals including 1159 healthy participants and 1187 participant who had undergone coronary angiography (405 participants with negative angiography and 782 participants with positive angiography). We entered 10 variables of a total 12 variables into the DT algorithm (including age, sex, FBG, TG, hs-CRP, TC, HDL, LDL, SBP and DBP). ResultsOur model could identify the associated risk factors of CHD with sensitivity, specificity, accuracy of 96%, 87%, 94% and respectively. Serum hs-CRP levels was at top of the tree in our model, following by FBG, gender and age. ConclusionOur model appears to be an accurate, specific and sensitive model for identifying the presence of CHD, but will require validation in prospective studies.

Cytokines play a key role in the pathogenesis of coronary artery disease (CAD). The aim of current study was to investigate the relationship between the serum concentrations of 12 cytokines with mortality and extent of CAD in individuals undergoing angiography and healthy controls. 342 CAD patients were recruited and divided into 2 groups: those with ≥50% occlusion in at least one coronary artery [Angiography (+)] or 2.16 pg/mL IL-6 had a > 94% sensitivity and 70% specificity in predicting 2 years mortality in the subjects with a serum MCP-1 > 61.95 pg/ mL, and patients having IL-6/MCP-1 combination had a shorter survival.Our findings demonstrate that CAD patients with serum MCP-1 and IL-6 levels of >61.95 and >2.16 pg/mL had a higher mortality with 94.1% sensitivity and 70.5% specificity for predicting mortality in CAD patients.

Introduction: Type 2 diabetes (T2DM) shows increasing prevalence and global health burden, causing a concern among health service providers and health administrators. The current study is aimed at developing and comparing some statistical models that are useful in measuring or establishing such associations. The three particular statistical methods investigated in this study are artificial neural network (ANN), support vector machines (SVM) and multivariate logistic regression (MLR) using demographic, anthropometric and biochemical characteristics on a sample of 9528 individuals from Mashhad city. Methods: The statistical methods involved in this study are also known as machine learning algorithms and require dividing the available data in to training and testing dataset. This study has randomly selected 70% cases (6654 cases) for training and reserved the remaining 30% (2874 cases) for testing. The three methods are compared with help of the receiver operating characteristic (ROC) curve. Results: The prevalence rate of T2DM is 14% in our population. The ANN model has 78.7% , accuracy, 63.1% sensitivity and 81.2% specificity. Values of these three parameters are 76.8%, 64.5% and 78.9% respectively for SVM and 77.7%, 60.1% and 80.5%, respectively for MLR. The area under the ROC curve (AUC) is 0.71 for ANN, in SVM model was 0.73 for SVM, and 0.70 for MLR. Conclusion: The overall conclusion is that ANN performs better than two models and can be used effectively to identify associated risk factors of T2DM.

Introduction: The aim of current study was to create a prediction model using data mining approach, decision tree technique, to identify low risk individuals for incidence of Type 2 diabetes (T2DM), using the Mashhad Stroke and Heart Atherosclerotic Disorders (MASHAD) Study program. Methods: a prediction model was developed using classification by the decision tree method on 9528 subjects recruited from MASHAD database. Moreover, the receiver operating characteristic (ROC) curve was applied. Results: The prevalence rate of T2DM was ~14% in our population. For decision tree model, the accuracy, sensitivity, and specificity value for identifying the related factors with T2DM were 78.7%, 47.8% and 83%, respectively. In addition, the area under the ROC curve (AUC) value for recognizing the risk factors associated with T2DM was 0.64. Moreover, we found that subjects with family history of T2DM, age>=48, SBP>=130, DBP>=81, HDL>=29, LDL>=148 and occupation=other have more than 59% chance of this disorder, while the chance of T2DM in subjects without history with TG>=184, age>=48 and hs-CRP>=2.2, have approximately 51% chance. Conclusion: Our findings demonstrated that decision tree analysis, using routine demographic, clinical, anthropometric and biochemical measurements, which combined with other risk score models, could create a simple strategy to predict individuals at low risk for type 2 diabetes in order to decrease substantially the number of subjects needing for screening and recognition of subject at high risk.

Background: There is an increasing trend in the prevalence of coronary artery disease (CAD) in Iran. Objectives: The present study aimed to investigate the relationship of anxiety, depression, diabetes and coronary artery disease among patients undergoing angiography in Ghaem Hospital, Mashhad, Iran. Patients and Methods: This case-control study was conducted between September 2011 and August 2012 among 200 patients undergoing coronary angiography for symptoms of coronary disease at Ghaem Hospital, Mashhad, Iran. The control group consisted of 697 healthy adults recruited from the individuals who attended the clinic for routine medical checkups or pre-employment examinations. The Beck anxiety and depression inventory scores and fasting blood glucose results were assessed in all the subjects. Data were analyzed using SPSS version 16. P < 0.05 was regarded as statistically significant. Results: The mean age of patients was 57.52 ± 9.33 years old and for the control group it was 55.35 ± 8.45 years; there was no significant difference between the subjects (P = 0.647) regarding age. There was also no significant difference in gender distribution between the patients and control groups (P = 0.205). There was however a significant difference in anxiety and depression scores between the patients and healthy controls (P < 0.001). There was a significant positive correlation between anxiety score and depression score in both groups when data were analyzed by Pearson test. (P < 0.001, r = 0.604 and r = 0.521). Moreover, there was a significant positive linear correlation between the depression/anxiety scores and fasting blood glucose concentrations in the patients group (r = 0.3, P < 0.001) and a weak negative correlation in the healthy controls (r = -0.096, P < 0.05). Conclusions: Depression and anxiety are potentially important factors among patients with angiographically-defined CAD. There appear to be significant associations between glucose tolerance and anxiety and depression in these patients.

Lifestyle-modification programs including physical activity are essential for both treatment and prevention of Type 2 Diabetes Mellitus (T2DM). However, factors associated with physical activity among patients are poorly understood. This study applied Social-Cognitive Theory (SCT) for predicting determinants of physical activity among women with T2DM in Iran, 2013.In this cross-sectional study, partial least square path modeling (PLS-PM) was used as an estimation technique for structural equation model. This model specified hypotheses between components of Social-cognitive Theory on physical activity behavior. A random sample of 300 women with T2DM was selected, and completed SCT constructs instrument. Data were analyzed using statistical software WarpPLS Ver. 4.0.The model explained 26% of the variance in physical activity. Self-regulation, task self-efficacy and barrier self-efficacy were significantly direct predictors of physical activity among women with T2DM. Task self-efficacy, social support and modeling had significantly indirect effects on physical activity behavior (P0.001).Our findings showed evidence for adequacy of a theoretical framework that could be used to predict physical activity behavior among women with T2DM.

Background: Severe depression may be accompanied by immune dysregulation and is also associated with increased risk of coronary artery disease (CAD). Objectives: We investigated serum levels of 10 cytokines and their relationship with depression in patients with cardiovascular diseases as well as healthy subjects in northeast of Iran. Patients and Methods: The study was carried out on 462 subjects (120 healthy subjects and 342 candidates undergoing angiography). The healthy subjects were referred for routine annual checkups or pre-employment examinations; they did not have clinically evident CAD. A questionnaire was used to obtain demographic data and the Beck depression inventory (BDI) was applied to assess depression. The Evidence Investigator ® platform was used for cytokines assays for IL-1α, IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, TNF-α, MCP-1 and IFN-γ, using sandwich chemiluminescent method. The statistical analysis was performed using SPSS version 11.5. Results: The mean age was 53.3 ± 11.5, 54.8 ± 11.3, and 59.5 ± 11.3 in healthy, angiography (-), and angiography (+) subjects, respectively (P < 0.05). There were significant differences in serum levels of IL-4, IL-6, IL-10, and MCP-1 cytokines, comparing subjects with CAD and healthy persons (P < 0.05). When all subjects were divided to with and without depression regardless of their cardiovascular status, there was a significant difference in serum levels of IL-8 and IL-6 between the groups (P < 0.05). When the subgroup with features of CAD was selected and divided to those with and without depression, there was also a significant difference in serum levels of IL-8 and TNF- α (P < 0.05). Conclusions: The positive interaction between depression and CAD was probably mediated by inflammatory mechanisms.

OBJECTIVE: The aim of this study was to investigate the relationship between dietary intake and biomarkers of cardiovascular risk in individuals with and without angiographically defined coronary artery disease. SUBJECTS/METHODS: Coronary angiography was undertaken in 445 individuals who were divided into those with significant disease (>50% occlusion) (Angio + (n = 273)) and those with

Users of hospital information system (HIS) use these systems dur-ing working day and know its problems better than others know. Studying their views is very important and can be espe-cially effective in the development of the in-formation system. The aim of this study was to investigate the users' views to-wards the qual-ity of hospital information system in the training hospitals of Mash-had University of medical sciences.The current study was an applied research in Training Hos-pitals of Mash-had (East of Iran), which was conducted with de-scriptive cross-sectional method. A four-section questionnaire was de-signed for data collection consisting of: characteristics of informa-tion quality, reasons of low quality of information, accessi-bility of infor-mation and decision support. Validity and reliability were tested and SPSS was used for data analysis. 62.8% of users explained that one of reasons of low qual-ity information was a problem related to obtaining information. 47.7% of them were unsatisfied with hospital information system abil-ity for decision-making support. In general, 53.2% of users were slightly satisfied with the overall quality information of the sys-tem.There are some problems concerning information qual-ity of HIS in Mashhad training hospitals. These problems in-clude inappropriate information qual-ity of the system and incom-patibility with user needs which leads to de-creased satisfaction of us-ers towards the system.