The relation between dietary phytochemical index and metabolic syndrome and its components in a large sample of Iranian adults: a population-based study

This cross-sectional study was carried out on data obtained from recruitment phase of Yazd Health Study (YaHS) and Taghzieh Mardom-e-YaZd (TAMYZ) conducted from 2014 to 2016. YaHS is a population-based prospective cohort study of 10,000 people aged 20–70 years who randomly selected from 200 clusters (50 each, 25 men and 25 women and 5 persons in each ten years age groups) of Yazd greater area according to the city post codes. TAMYZ was a nutrition sub-study of YaHS which was conducted on the same 10,000 participants, however only 8000 of them were participated. Over 100 trained interviewers visited the participants at their residence after set up meeting time and then filled a validated questionnaire with 300 questions including dietary intakes demographics and physical activity. All participants were invited to attend a referral laboratory within two weeks from the interview date to provide fasting blood sample for biochemical assessments. The profile of the studies was published elsewhere [27].

Almost 40% of the YaHs participants gave consent for fasting blood sampling and biochemical assessment; there was no significant difference between those who attends and those who do not attend in terms of major SES factors. Out of 3748 available cases with data on dietary intakes, blood tests and main variables associated with MetS, the subjects with following conditions were excluded: having history of diseases such as diabetes mellitus, cardiovascular diseases, stroke and cancer or persons whose total daily energy intake was less than 800 or higher than 6500 kcal and missing data. Finally, 2326 subjects were included in this analysis. Flowchart of the data collection process is shown in Fig. 1.

Written informed consent was obtained from all participants. Ethical approval was obtained from the Ethics Committee of Shahid Sadoughi University of Medical Sciences, IR.SSU.SPH.REC.1399.051. YaHS database is not publically available. The authors assess the data according to the study protocol and agreement with the CI of study Professor Masoud Mirzaei who critically read and comment on this manuscript.

Dietary intakes were assessed through a validated (FFQ) consisting of 178 food items which was modified version of a previously validated 168-item FFQ. Additional 10 questions relating to consumption of Yazd-specific food items were added to the original FFQ that were collected by trained interviewers [27, 28]. Participants were asked about the frequency and usual amount consumption of food items in the past year then were converted to grams using guidelines of household scales [29].

The DPI was calculated based on the method developed by McCarty in 2004; [[DPI = (daily energy derived from phytochemical-rich foods (kcal)/total daily energy intake (kcal)) × 100) [17]. Fruits, vegetables, legumes, whole grains, nuts, soy products, seeds and extra virgin olive oil were considered as phytochemical-rich foods. Coffee and tea, as free energy sources, were not contributed. Potatoes were not included as vegetables because of their low phytochemicals content. Natural fruit and vegetable juices as well as tomato sauces were included in the fruit and vegetable groups because of their high phytochemical content [16, 17, 22].

Weight was measured using Omron BF-511 portable digital scales to the nearest 0.1 kg with minimum clothing and in standing position on scale. Height was measured using tape measure on a straight wall to the nearest 0.1 cm, in a standing position without shoes by touching shoulders, buttocks and heels to the wall and head in Frankfurt position. Waist circumference (WC) was measured to the nearest 0.5 cm using non-stretch tape meter, while it is middle of the iliac crown and lowest rib in the standing position. Also, hip circumference was measured from the largest part of the buttocks with an accuracy 0.5 cm. Body mass index (BMI) is calculated by dividing weight (kg) to the square of height (m²).

The short form International Physical Activity Questionnaire (IPAQ) was used to assess frequency and time spent on sedentary, moderate, intensity activities, according to the list of common activities of daily life, over the past week. Activity levels were expressed as Metabolic Equivalent (MET) hours per week [30].

MetS was diagnosed according to National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III). Participants who had at least three of following criteria were diagnosed as participant with MetS: Serum triglycerides ≥150 mg/dL; Serum high-density lipoprotein cholesterol (HDL-C) < 40 mg dL for men and HDL-C < 50 mg/dL for women; Fasting blood glucose ≥100 mg/dL; Blood pressure ≥ 130/85 mmHg and waist circumference ≥ 102 cm for men and > 88 cm for women [31].

Laboratory measurements included of fasting blood glucose, HDL-C and triglycerides were measured according to a standard laboratory protocol using Pars Azmoon kits (Tehran, Iran) and calibrated Ciba Corning (Switzerland) auto-analysers.

Blood pressure was measured in a sitting position three times with a 5-min interval between each measurement. Other data including age, gender, marital status, education, job status and history of chronic diseases were collected by trained interviewers.

DPI was categorized based on quartiles ranges. Characteristics of participants were compared throughout quartiles of DPI using one-way analysis for continuous variables and Chi-squared test for non-continuous. To estimate odds ratio and 95% confidence interval (OR (95%CIs)) of MetS and its components in each quartile DPI and overall trend was used binary logistic regressions in crude and multivariable-adjusted models. Analysis stratified by sex were conducted in crude and multivariable-adjusted models. Possible confounders which were considered in models were age (y), sex (men/women) and total energy intake (kcal/day) in the first model. Marital status (married/single/divorce/widowed), physical activity level (sedentary/moderate/active), smoking status (never/former/current), family history of chronic disease (yes/no), educational level (less than high school diploma/college/ university), job status (not employed/employed), house status (owner/not owner), family size (less than 4/more than five), house in square meters (less than 100 square meters/ between 100 to 200 square meters/more than 200 square meters), ethnicity (Native or non-native) in the second model. Along with other variables of the second model, BMI (kg/m²) was considered in the third model. Statistical analyses were performed by SPSS statistical software (version 23). P values less than 0.05 was statistically considered for significant level.

Mean dietary intakes of participants across quartiles of DPI are provided in Table 2. Participants in the upper quartile of DPI have higher intakes of whole grain, vegetables, fruits, legumes, nuts, vitamins C, vitamin A, folic acid, pantothenic acid, iron and potassium compare with those in the bottom quartile (p < 0.001). Participants in the highest DPI compare to the lowest, have lower intake of energy, total fat, monounsaturated fatty acids (MUFA), saturated fatty acids (SFA), polyunsaturated fatty acids (PUFA), cholesterol, total fiber, vitamin E, zinc, calcium, magnesium (p < 0.001). No significant difference was observed across quartiles of DPI for Docosahexaenoic acid (DHA) and Eicosapentaenoic acid (EPA) intake.

The odds ratio and (95% CIs) of MetS and its components across quartiles of DPI are presented in Table 3. After adjustment for age, sex and energy intake, the risk of MetS (OR: 0.72, 95% CI = 0.55–0.93, P = 0.01) and abdominal obesity (OR: 0.70, 95% CI = 0.53–0.93, P = 0.01) decreased significantly in the second quartiles of DPI compared to the first. Also odds of abdominal obesity in the fourth quartiles of DPI compared to the first, was significantly decreased (OR: 0.75, 95% CI = 0.58–0.99, P = 0.04). In addition to the risk of MetS (OR: 0.58, 95% CI = 0.38–0.88, P = 0.01) and elevated blood pressure (OR: 0.59, 95% CI = 0.38–0.92, P = 0.02) decreased in the second quartile of DPI compared to the first after further adjustments for marriage status, physical activity, education level, Smoking, job status, house status, family size, house in meters, ethnicity, hypercholesterolemia, chronic disease family history. In the third model, the risk of MetS (OR: 0.63, 95% CI = 0.41–0.96, P = 0.03) and elevated blood pressure (OR: 0.62, 95% CI = 0.40–0.96, P = 0.03) significantly decreased in the second quartile of DPI compared to the first in full adjustmens. There was not any significant relationship between DPI and other components of MetS in crud and full adjustments model (data are not shown).

Odds ratio (95% CIs) of MetS across different categories of DPI stratified by sex are shown in Table 4. In women, after adjustment for confounders, risk of MetS significantly decreased in the highest quartile of DPI as compared to the lowest (OR: 0.41, 95% CI = 0.22–0.76, P = 0.005). There was not any significant relationship between DPI and MetS components stratified by sex (data are not shown).