Iranian Journal of

---

Introduction: Cigarette smoking is a major modifiable risk factor for cardiovascular disease and it has been identified as the single most important cause of cardiovascular accident related deaths in most countries.
Methods: 1573 people who lives in 17th zone of Tehran (Population Research Center of Tehran University of Medical Sciences) were investigated by a cross- sectional study. A group of trained persons collected data by the standard questionnaire that contained demographic and smoking status characteristics. Furthermore the fasting blood samples were taken for more evaluation. Data were analyzed with SPSS software.
Results: According to this study 37/4% of men and 4/2% of women were smoker. There were relationship between cigarette smoking and serum level of homocysteine, Folic Acid, cholesterol, LDL, HDL, Uric Acid, hypertension and BMI (P<0/05). But it was no significant with vitamin B12 and TG statistically.
Conclusion: There were relationship between cigarette smoking and male gender, age, unmarried status and the level of education. So public education should be accomplished in society specially among families for prevention of cardiovascular risk factors.

---

Concept of dietary patterns is new in the filed of nutritional epidemiology. However, it has not been focused to the extent that foods or nutrients have been considered. Although, identifying the association between nutrients and foods intake with chronic diseases is valuable yet, recent evidences have shown that the clinical trials that have used nutrients are not too successful to indicate the effects of that nutrient on the disease risk. On the other hand, the studies used dietary patterns have shown the significant effects on disease risk. Therefore, using dietary patterns analysis is an efficient method to identify diet-disease relations. However, it should be kept in the mind that dietary patterns are different across gender, ethnics, cultures and regions. It is, therefore, recommended that investigators in different countries need to assess their own community dietary patterns and emphasize on these patterns when trying to reduce chronic disease risk. The current study has been conducted to review the studies that have assessed the association of dietary patterns and chronic disease risk.

---

Background: Existing studies show that a poor diet has an effect on the progression of non-alcoholic fatty liver disease (NAFLD). The aim of the present study was to systematically summarize the results of studies on the relationship between dietary intakes and NAFLD. Methods: A review of Scopus, PubMed, Cochrane Library, Magiran, Medlib and SID databases and theses in the National Library of the Islamic Republic of Iran was conducted to identify epidemiological studies concerning NAFLD, food groups and dietary patterns. Cross-sectional, case-control and cohort studies with documented in English were selected for this systematic review. Duplication, topic, type of study, study population, variables examined and quality of data reporting of articles were evaluated. Results: Of 2128 articles found in the initial search, 33 were reviewed in full-text of these 6 articles were included in the systematic review. The literature review showed patients with NAFLD consumed more red meat, fats and sweets and less whole grains, fruits and vegetables. The Western dietary pattern was positively associated with the risk of NAFLD and adherence to the Mediterranean diet was negatively correlated to hepatic steatosis. Conclusion: The results of the systematic review indicate that different dietary intakes may be associated with development of NAFLD and its related factors. Due to limited research documented on this topic, further prospective studies are recommended.

---

Background: Diabetes is such diseases that need high quality beside prevention such as correctly predict fluctuations in blood glucose levels. The main complications of the disease can be anesthesia, coma and even death. Today, in these patients, the correct dose of insulin determined based on experience or doctors knowledge, and interact between the patients and physician, although there is an inevitable human errors.

Methods: In this study based on applied method, 124 patients and 188 healthy subjects based on 12 features by Random Selection, Who had been referred to Research Center for Diabetic in Sabzevar university of Medical Science since 2006 to 2011 were studied. The proposed system has several subsystems, such as evolutionary algorithms (BPS 1) to select the most effective features, Data Mining Algorithms (SVM 2) to detect and classify the features from the non-effective features. Adaptive Neuro fuzzy systems (ANFIS 3) to estimate learn and adaptation in order to correctly predict have been used.

Results: In this study, we try to use artificial intelligence systems to determine the correct dose of insulin for diabetics. The proposed system combines the best attributes in the database in the form the interaction was able to achieve high accuracy with the lowest error. The proposed system based on best features in the database in the interaction form was able to achieve high accuracy with the lowest error. The proposed system in the form of composition and interaction with the subsystem was able to achieve carefully 84.1% in specificity, 91% in sensitivity and 92.9% in accuracy.

Conclusion: In this research, due to the importance of correct and timely determination of insulin for diabetics, a new method based on the combination of intelligent systems is presented. Thus, the results obtained in previous articles and studies provide significantly improved.

---