Prevalence of malnutrition in hospitalized patients in Taleghani hospital in Tehran

Background and Objective: Malnutrition in hospital increases the mortality of patients. The aim of this study was to investigate the prevalence of malnutrition and related risk factors in hospitalized patients. Materials and Methods: This descriptive study was carried out on 446 patients (217 males, 229 females) during 6 months, admitted to the Taleghani hospital in Tehran, Iran during 2005. Anthropometric measurements and previous admission to hospital in previous 6 months for each patient was recorded. Mild, moderate and severe malnutrition were considered as BMI=18-20 kg/m2 and TSF, or MAMC10% in previous 6 months respectively. Results: The prevalence rate of malnutrition as a general was 52% with following subdivision: 14%, 10% and 28% in mild, moderate and severe, respectively. The highest prevalence of malnutrition observed in gastrointestinal ward, males, those aged 18-29 year and patients with secondary and high school education. In malnourished patients, the prevalence of TSF, MAC and MAMC <5th were significantly more than of well-nourished subjects (P<0.05). Increase BMI per unit decreased the risk of malnutrition by 17% (OR: 0.83 CI: 0.79-0.87). Malnutrition was 64% higher in patients with 1≥ gastrointestinal disturbances, compared with those without it and 2.1 higher in patients with 2≥-hospitalized readmission, compared with subjects without readmission in previous 6 month. Odds ratio of at least one hospitalized admission in previous 6 month was 1.64 in patients with MAC <5th, compared with those with MAC 50-75th (P<0.017). Conclusion: This study showed that Malnutrition upon hospitalization is common in Tehran. BMI, gastrointestinal disturbances, and readmission were associated with malnutrition

Association between glycemic index, glycemic load and cardiovascular risk factors in adults

Background and Objective: Limited studies on the relation between the cardiovascular diseases (CVDs) risk factors and dietary glycemic index (GI) and glycemic load (GL) are available. This study was done to determine the association between glycemic index, glycemic load and cardiovascular risk factors in adults. Materials and Methods: This descriptive study was carried out on 2284 subjects (1327 males, 957 females) with 19-84 age in Tehran, Iran during 2005-08. Dietary GI and GL were assessed using a validated semi quantitative food-frequency questionnaire. Blood pressure, Anthropometric, fasting blood of glucose and lipid profiles including total cholesterol, triglyceride, high density lipoprotein (HDL) and low density lipoprotein (LDL) as a CVDs risk factors were measured. The mean intake of nutrient, adjusted for energy production, gender, age, according to GI and GL, using general linear model analysis covariance test was measured. Data were analyzed using SPSS-15, one-way analysis variance, Chi-Square, partial correlation and Linear regression. Results: The mean intakes of glycemic index and glycemic load were 68.3 and 244.8, respectively. Dietary GI and GL was inversely associated with whole grain and positively associated with refined grained, fruits, dairy products and simple sugar. After adjustment for lifestyle and dietary variables, dietary GI was inversely associated with triglyceride and HDL cholesterol concentrations among obese subjects. Dietary GL was inversely associated with fasting and 2-h blood glucose among non-obese subjects after adjustment for confounders. Conclusion: GI in obese men associated with serum increase triglyceride and reduced HDL-C. Glycemic load in a non-obese man is correlated with reducing fasting blood glucose

Additional file 1 of Effect of TCF7L2 on the relationship between lifestyle factors and glycemic parameters: a systematic review

Additional file 1: Table S1. Details of the search strategy in electronic databases. Table S2. Quality assessment of studies based on gene-lifestyle interaction on glycaemic parameters. Table S3. Quality assessment of cohort studies by using the Rob2 tool. Table S4. Quality assessment of cross-sectional studies by using the Newcastle Ottawa Scale. Table S5. Quality assessment of cohort studies by using the Newcastle Ottawa Scal