This study was conducted in the framework of a prospective cohort study of Yazd Health Study (YaHS) with a focus on various determinants of health including nutrition. Yazd Health Study (YaHS) has been conducted since 2014 and examines the health status, chronic non-communicable diseases (NCDs), and related risk factors in adult residents of Yazd Greater Area aged 20–70 years. Also, in this study, the findings of the study of Taghzieh Mardom-e-Yazd (TAMYZ), which is a study in line with YaHS, have been used. Study design, sample selection, characteristics of participants in the study, as well as details of data collection methods, have been published in previous studies . Data collection was done in two main stages among the adult population of Yazd province. In the first phase, a questionnaire including demographics, history of chronic diseases, anthropometric measurements, quality of life, psychological status, eating habits, surgical history, and women’s health was completed for 9965 people by trained interviewers (94.9% response rate), out of this number 4010 people gave blood test samples. In the second phase of the study, the nutritional health of the people entitled Taghzieh Mardom-e-Yazd (TAMYZ) was examined using a semi-quantitative food frequency questionnaire. Information on socio-demographic characteristics, tobacco use, history of chronic disease, psychological health, and physical activity assessments and dietary evaluation was obtained by a validated questionnaire. All participants signed an informed consent form before participating in the study. In this study, the subjects are selected based on the following inclusion and exclusion criteria:
Inclusion criteria include: 1. Age 70–20 years 2. Availability of nutritional information of participants in study 3. Availability of psychological health assessment data for participants 4. Individual consent to participate in the study. Exclusion criteria: 1. Have a history of diabetes, high blood pressure, heart disease, and cancer 2. Follow a special diet 3. Under and over-reporting (less than 800 kcal and more than 6500 kcal) 4. Pregnancy.
The semi-quantitative FFQ was administered to assess the dietary foods and supplements. The original semi-quantitative FFQ contains 168 items, but 10 more questions were added on consumption of Yazd-specific frequently consumed food items, which made a total of 178 food items (included: breads and grains (n = 23); beans (n = 7); meats, fish, and shellfish (n = 19); milks and dairy products (n = 17); vegetables (n = 26); fruits (n = 40); fats and nuts (n = 13); beverages (n = 5); and snacks and sweets (n = 28). The semi-quantitative FFQ was previously validated for the Iranian population [16, 17], so the questionnaire was completed by trained interviewers. Participants were supposed to report the amount and frequency of consuming each food item per month, week, or day in the past year. Moreover, a food photograph book was used for all participants as a reference, so that they could estimate the portion size of foods as a unit accurately. Participants were also asked to report their intake frequency with regard to all food items based on 10 multiple-choice frequency response categories ranging from “never or less than once a month” to “10 or more times per day.” Later, the amount of food consumed at each intake was estimated using questions with five predefined answers. Frequency and usual amount of food items consumption were asked by participants and finally, amounts of intakes were converted to grams using guidelines of household scales .
Calculate of the MIND diet score
In order to calculate the MIND diet score, FFQ questionnaire data were used. The MIND diet model was determined based on Morris’s study . The components of MIND include 15 food items, 10 of which are known as healthy groups for the brain (green leafy vegetables, other vegetables, nuts, berries, beans, whole grains, fish, poultry, olive oil, and wine) and 5 of which are known as unhealthy food groups for the brain (red meats, butter and stick margarine, cheese, pastries and sweets, and fried/fast food). Each of these dietary components was obtained based on the total intake of the population for each item of FFQ. However, because 100% of the participants in the study reported being Muslim and not consuming wine, wine consumption was not included in the calculation of this dietary pattern. To calculate the score of this food pattern, first the participants in the study were classified based on tertile categories of food intake of 14 components of this diet pattern and then for healthy food components for the brain, the highest to lowest tertile of receiving these food items, scores 1, 2 and 3 were considered (respectively) and for unhealthy components, these scores were reversed and the lowest to highest tertile of receiving these food items, scores 1, 2 and 3 were considered, respectively. Finally, the higher the MIND score, the greater the adherence to this diet. The score range of this index is varied from 14 to 42. Then, by summarizing all these food items, the overall score of the MIND diet was obtained.
Psychological health assessment (depression ‚anxiety and stress)
An Iranian version of the pre-completed DASS 21 questionnaire was used to assess psychological stress, depression, and anxiety . The validity of DASS was measured using factor analysis and criterion validity (concurrent method). The correlation between the depression subscale and the beck depression inventory scale was + 0.70, between the anxiety subscale and Zung anxiety inventory was + 0.67, and between the stress subscale and perceived stress inventory was + 0.49. All correlations were significant. Males and females scores were significantly different on all subscales, therefore, separate norms for each gender were presented. This questionnaire consists of 3 subscales (stress ‚anxiety and depression) and 21 questions. Each of the subscales contains 7 questions, the final score of each of which was obtained through the sum of the scores of the related questions. Each question was scored from 0 (does not apply to me at all) to 3 (does not apply to me at all). Since DASS 21 is the short form of the DASS questionnaire (42 items), the accumulated scores for each subscale are multiplied by 2, and finally depression, anxiety, and stress were defined based on the scores obtained: depression: Score ≥ 10‚ anxiety: ≥ 8 points, and stress: ≥ 15 points.
Anthropometric and physical activity assessment
The weight of the participants was measured using portable and digital scales (Omron BF511 inc. Nagoya, Japan) with an accuracy of 0.1 kg and while they only had one hand on light clothing, with the legs in the middle of the scales, slightly apart. standing height using a tape measure mounted on a flat wall without shoes with an accuracy of 0.1 cm while the heels, hips, and shoulders are attached to the wall, hands on both sides of the body and the head in the Frankfurt position were measured. Body mass index was calculated by dividing weight in kilograms by height squared in meters.
To evaluate physical activity, the Iranian version of the International Physical Activity Questionnaire (IPAQ) was used. Finally, physical activity is reported on a MET/ min/week basis .
All statistical analyses were conducted using SPSS software (version 19.0; SPSS Inc, Chicago IL). The normality of variables was evaluated by Shapiro–Wilk tests. Comparisons across quartiles of MIND diet score was performed using one-way ANOVA. Mean values of more than two groups were assessed using Analysis of Variance (ANOVA) for normally distributed variables. Chi-square tests were used to compare categorical variables. The Binary Logistic regression models were used determine the separate association between MIND diet score and odds of psychological disorders and stress, in crude and covariate adjusted models. We adjusted the results in three models using a priori selected potential confounders. In the modified models, the confounders used a statistical and conceptual approach, respectively. In this way, variables with Pvalue < 0.2 were considered as possible confounders and entered into logistic regression and the chances of disease were examined. Also, in the conceptual approach of modifying confounders in the second model, potential confounders were selected based on clinical concepts as well as based on previous articles and added to other confounders. The data were presented as mean ± standard deviation and, statistical significance was accepted, a priori, at P < 0.05.
The methodology of the current study was also ethically approved by the research ethics committee of Shahid Sadoughi University of Medical Sciences (approval code: IR.SSU.SPH.REC.1396.155).