The trend towards organic foods as an alternative has recently increased. Several individual, environmental, and behavioural factors can affect this situation. This study was conducted with 1417 participants to examine the factors affecting attitudes, purchase intention (PI), and actual purchasing behaviour towards organic foods. Consequently, a two-part questionnaire was used to query participants’ sociodemographic information and their attitudes and preferences towards organic foods. Data were analysed using multiple regression analysis, Pearson’s correlation, and structural equation modelling. Our findings confirmed that health consciousness, the knowledge of organic foods, subjective norms, perceived price, values (health and safety), nutritional content, naturalness, availability, monetary barriers, risk barriers, and trust affect attitudes towards organic products. These findings indicate that increasing consumers’ knowledge and awareness about organic foods, encouraging their consumption by society, accessibility them in the food market and making them affordable can affect the attitude towards these products. Furthermore, we determined the direct effect of the attitude on actual buying behaviour with the mediating role of PI. Additionally, we noted that marital status, employment status, disease diagnosis in the last 12 months, and the presence of a baby at home affect actual buying behaviour. In conclusion, they can help food marketers target consumers to their sociodemographic status and develop new sales strategies.

In the global world, plant-based milk alternatives have taken an important place in the food industry and have attracted great interest from consumers. This study was conducted to determine the main reasons why individuals prefer plant-based milk alternatives and the driving factors affecting their purchasing behavior towards plant-based milk alternatives. For this purpose, the sociodemographic characteristics, and general nutritional habits of 895 participants were questioned. In addition, the status of consuming plant-based milk alternatives of the participants in the last year was questioned and the purchasing decisions of the participants who reported that they consume these products and the factors that drive them to buy these products were evaluated. 796 women (88.9%) and 99 men (11.1%) participated in the study. The mean age of the participants is 31.17±9.62. Most of the participants (36.4% of women and 72.7% of men) reported that they never consumed plant-based milk alternatives. The most consumed plant-based milk alternatives were determined as almond milk (80.9%), coconut milk (60.2%), and soy milk (51.2%). The most frequent reason why consumers choose plant-based milk alternatives is determined as "Non-dairy milk contains good fat". The participants reported that dieticians have the most influence on their choices (x̄=3.35±1.27) and these products were mostly purchased from supermarkets and online channels. In addition, considering that drinking plant-based milk is beneficial for health (OR=1.978) and exercising regularly (OR=1.337) increases the odds of being a regular consumer. In conclusion, it is determined that consumer acceptance of plant-based milk alternatives is affected by the consumer's perception of healthy food, marketing strategies, and consumer expectations.

Monitoring glycemic control status is the cornerstone of diabetes management. This study aimed to reveal whether moderate-carbohydrate (CHO) diets increase the risk of free fatty acid (FFA) levels, and it presents the short-term effects of four different diet models on blood sugar, glycemic variability (GV), and FFA levels. This crossover study included 17 patients with type 1 diabetes mellitus to identify the effects of four diets with different CHO contents and glycemic index (GI) on GV and plasma FFA levels. Diet 1 (D1) contained 40% CHO with a low GI, diet 2 (D2) contained 40% CHO with a high GI, diet 3 (D3) contained 60% CHO with a low GI, and diet 4 (D4) contained 60% CHO with a high GI. Interventions were performed with sensor monitoring in four-day periods and completed in four weeks. No statistical difference was observed among the groups in terms of blood glucose area under the curve (p = 0.78), mean blood glucose levels (p = 0.28), GV (p = 0.59), and time in range (p = 0.567). FFA and total triglyceride levels were higher in the D1 group (p < 0.014 and p = 0.002, respectively). Different diets may increase the risk of cardiovascular diseases by affecting GI, FFA, and blood glucose levels.

Objective: To evaluate the effect of nutrition education supported by MOtiVE mobile application on weight loss and quality of life (QoL). Methods: In this pilot randomized-controlled study, 79 overweight/obese patients who presented to University Hospital between March-September 2018 to consult a dietitian, were included. All the participants were provided with a weight-loss diet program. Then, participants were randomized to experimental and control groups. During the first interview, all participants completed the questionnaire and anthropometric measurements were done. BMI, the scores obtained from different QoL scales, and Healthy Eating Index (HEI) were the dependent variables. Daily messages were sent to cases for 3 months via MOtiVE mobile application. All the participants were asked to be present three months later for a follow-up appointment. Using SPSS 25.0, change in BMI, QoL scores, and other variables within both groups were assessed via Wilcoxon signed-rank test and McNemar chi-square test. Results: 20 cases and 18 controls completed the study. The mean BMI decreased significantly in both groups being more predominant in cases (p=.001 for cases and p=.006 for controls). Waist circumference decreased (p=.029), self-esteem (p=.035) and healthy eating scores (p=.007) increased only in cases. Hence there were significant improvements in cases, in the final evaluation, there were no significant differences between the groups (p>.05). Conclusions: Nutrition education supported by MOtiVE mobile application improved anthropometric measurements, self-esteem, quality of life, and healthy eating habits of the overweight/obese participants. Free mobile applications can be used in increasing motivation to adopt new behaviors to tackle obesity.

Aim: This study aimed to evaluate atherogenic index with abdominal obesity/adiposity indicators associated with insulin resistance in individuals with type 2 diabetes mellitus (DM). Subjects and Methods: This cross-sectional study was conducted on 100 patients with type 2 DM aged 18-65 years. The general and health information of individuals was obtained by a questionnaire. Anthropometric and body composition measurements of individuals were applied by the researchers in accordance with its rules. Biochemical findings (fasting glucose, fasting insulin, glycated haemoglobin (HbA1c), and blood lipid parameters) were taken. Waist hip ratio and waist to height ratio were calculated for evaluating abdominal obesity. Visceral adiposity index (VAI) and conicity index (CI) were calculated for evaluating abdominal adiposity and body adiposity index (BAI) was also calculated. Serum atherogenic index (AI) was used for assessment of atherosclerosis risk. Homeostasis model assessment of insulin resistance (HOMA-IR) was calculated for evaluation of insulin resistance. Results: Almost all of the men (91.2%) and women (98.5%) were obese. Accordingly depending on waist to height ratio, all of women (100%) and 94.1% of men had high risk of disease. Overall 85.3% of men and 83.3% of women were in high atherosclerosis risk group according to atherogenic index classification. There was a positive correlation between insulin resistance and BMI (r: 0.212; p: 0.035), waist circumference (r=0.222; p=0.027), VAI (r=0.323; p=0.001), AI (r=0.318; p=0.001), visceral adiposity (r=0.201, p=0.044), HbA1c (r=0.297, p=0.003) and triglyceride levels (r=0.289, p= 0.004). There was a positive correlation between AI and age (r=0.414, p=0.015), VAI (r=0.778; p=0.000) in males and waist to hip ratio (r=0.250, p=0.043), waist to height ratio (r=0.264, p=0.032), VAI (r=0.708, p=0.000) and fasting insulin value (r=0.271, p=0.006) in females. Conclusion: Increased AI is associated with increased risk of type 2 DM and it adversely affects the development of cardiovascular disease. AI can be used as an objective indicator in predicting cardiovascular disease risk in individuals with type 2 DM. However, further studies are needed to find the best risk prediction for cardiovascular diseases in individuals with type 2 DM.