Analysis of Food Insecurity and Surveillance Based on the FANP Method in the northwest of Iran

Food insecurity is frequent in both developed and developing countries, affecting from 5% to 25% of the general population. It has considerable health impacts on the physical, social, and psychological status of individuals in communities suffering from food insecurity. In this paper, we seek to use the Fuzzy analytical network process (FANP) for analysis of food insecurity surveillance and selecting the best strategies for improving it. This cross-sectional study was conductedon 300 subjects (132 male and 168 female) selected randomly in the Asadabadi area of the northwest of Iran.The method is validated using the structural validation approach

Serum calcium, magnesium, phosphorous and lipid profile in healthy Iranian premenopausal women

Introduction: Recent epidemiological evidence suggests that alteration in calcium, phosphorous or magnesium metabolism may have direct cardiovascular consequences. However, it is unknown whether variations in serum values of these minerals are in relationship with lipid profile and adiposity as metabolic risk factors of cardiovascular events in premenopausal women independent of confoun-ders. The aim of this study was to investigate the relationship between serum calcium, magnesium and phosphorous with lipid profile in healthy premenopausal women. Materials and methods: This study was performed on 82 reproductive age women aged 17-50 who were randomly selected from general population of Tabriz, Iran. They were assigned into obese and none-obese groups. Weight and height for BMI calculation were measured using a calibrated Seca scale and cotton ruler which was attached to the wall. Body composition was analyzed by bioelectrical impedance analysis (BIA). Serum magnesium, calcium and phosphorous were measured colorimetrically; fasting blood glucose (FBG) and serum lipids were assessed by enzymatic methods. Results: Obese woman had significantly lower serum magnesium (P = 0.035) and significantly higher fasting blood glucose (P = 0.028), total cholesterol (P = 0.035), triglyceride (P = 0.019), low density lipoprotein (P=0.003) and parathyroid hormone concentrations (P = 0.031) compared to non obese women. In correlation coefficient analysis, serum calcium concentrations had a positive weak relati-onship with total cholesterol (r = 0.267, P = 0.013) and triglyceride (r = 0.301, P = 0.005) concentrations in all participants; whereas in separate analysis of subjects as obese and non obese groups, the-se relationships lost their significance. Serum phosphorous had a weak positive relationship with total cholesterol (r = 0.31, P = 0.002) and an inverse weak relationship with parathyroid hormone (r = - 0.32, P = 0.002). After adjusting for confounding variables by multiple regression analysis, the positive relationship between serum calcium, triglyceride, high density lipoprotein and low density lipoprotein cholesterol were significant. Conclusion: Our results indicate that abnormality in serum calcium and phosphorous is significantly correlated with serum lipids. Further studies are warranted for interpretation of these associations and understanding the underlying mechanisms

Analysis of Food Insecurity and Surveillance Based on the FANP Method in the northwest of Iran

Food insecurity is frequent in both developed and developing countries, affecting from 5% to 25% of the general population. It has considerable health impacts on the physical, social, and psychological status of individuals in communities suffering from food insecurity. In this paper, we seek to use the Fuzzy analytical network process (FANP) for analysis of food insecurity surveillance and selecting the best strategies for improving it. This cross-sectional study was conductedon 300 subjects (132 male and 168 female) selected randomly in the Asadabadi area of the northwest of Iran.The method is validated using the structural validation approach

Nutritional Status in Patients with Major Depressive Disorders: A Pilot Study in Tabriz, Iran

Introduction: This study was conducted to assess the nutritional status in Iranian major depres-sive disorder patients. We also determined the relationship between nutrients intake with depres-sion severity.Methods: Seventy major depressive patients were selected randomly from outpatient depressive subjects, referred to Razi Psychiatry Hospital in Tabriz, Iran in 2007. Dietary intakes were rec-orded and compared with dietary reference intakes (DRIs). Definition of the disease and its se-verity were according to DSM-IV-TR and Hamilton Depression Rating Scale, respectively. Nu-tritionist III program, Chi-square, correlation and t-test were used for data analyses. Demo-graphic, clinical and laboratory data were analyzed using SPSS software for windows (ver-sion13.0).Results: According to dietary analysis, 11.4% and 55% of patients had dietary protein and energy deficiency, respectively. 97.1% and 95.7% of patients had less folate and B12 intakes than recom-mended dietary allowances. The mean (Mean ± SD) for plasma folate and B12 was 5.18±6.11 ng/ml and 389.05±346.9 pg/ml, respectively. Low plasma folate and B12 was observed in 51.4% and 50.0 % of patients, respectively. There was no significant relationship between blood folate and B12 levels with depression severity. Similarly, nutrients intake had no effect on depression se-verity.Conclusions: Low plasma concentrations and low dietary intakes of folate and B12 are common among Tabrizian depressive patients. It seems that nutritional intervention for increasing folate and vitamin B12 intake must be considered as health promotive and preventative program for pa-tients suffering from depression disorders

Using the Hopfield– Fuzzy C Means Algorithm for Clustering of People based on Food Insecurity and Obesity in the Northwest of Iran

It is commonly recognized that food insecurity and obesity is the major sections of academic researches, but the activities' rate of food insecurity and surveillance is always Low. Based on food insecurity and obesity’ characteristics, in this paper attempt are made to present a model based on Hopfield– fuzzy C Means clustering algorithm. Firstly, it is capable of identifying the reasons behind the emergence of the present status. Secondly, the suggested model must represent the clustering of the people based on food insecurity and surveillance in different levels. Finally, it tests the validity of the suggested model with comparing by other models (Hopfield–K-Means, K-Means, and fuzzy C Means)