Study population
The present study was conducted within the framework of Tehran Lipid and Glucose Study (TLGS), a prospective study on a representative sample of residents from district 13 of Tehran, to investigate and prevent non-communicable diseases (NCD) (13). TLGS is an ongoing community-based study that started with 15,005 individuals aged ≥3 years in 1999, and data collection is repeated every 3 years to assess any changes of NCD risk (14). For the current analysis, we recruited 1864 adult men and women (age ≥19 years), with complete data on spot urinary values (Na, K and creatinine), demographics, anthropometrics, biochemical measurements and dietary intakes in the sixth TLGS examination (2014-2017). Participants who had under-reported or over-reported energy intake (<800 kcal/d or >4200 kcal/d, respectively) were excluded from the final analysis.
Anthropometric and demographic measures
Weight was measured by digital scales (Seca, Hamburg, Germany), height and waist circumference were measured by a tape meter, and they were reported to the nearest 100 g and 0.5 cm, respectively. Waist circumference was measured at the level of the umbilicus. Subjects were minimally clothed and without shoes for anthropometric measurements. Body mass index (BMI) was calculated as weight (kg) divided by height in square (m2).
Systolic (SBP) and diastolic (DBP) blood pressures were measured using a standard mercury sphygmomanometer calibrated by the Iranian Institute of Standards and Industrial Researches (15). Blood pressure was measured on the right arm of the participants in a sitting position for two times, with at least a 30-second interval between two measurements, and a 15-minute rest before measurement. Mean of the two measurements was considered as the participant’s blood pressure.
Biochemical measures
Both blood and spot urine samples were drawn between 7:00 and 9:00 AM following overnight fasting. Urinary concentrations of Na and K were measured using flame photometry (Screen lyte, Hospitex Diagnostics, Florence, Italy). Both intra- and inter-assay coefficients of variations (CVs) were ≤ 2.8% for Na, and ≤ 4.8% for K.
Fasting serum glucose (FSG) and triglycerides (TG) levels were determined by the enzymatic colorimetric method, using glucose oxidase and glycerol phosphate oxidase, respectively. High-density lipoprotein cholesterol (HDL-C) was measured by a homogenous method (HDLC Immuno FS). Blood analysis were done using Pars Azmoon kits (Pars Azmoon Inc., Tehran, Iran) and a Selectra 2 auto-analyzer (Vital Scientific, Spankeren, The Netherlands) at the research laboratory of the TLGS. Both inter- and intra-assay coefficients of variations (CVs) were ≤ 5%.
Dietary assessment
Dietary assessment was done using a validated 147-item food frequency questionnaire (FFQ). The intake frequency of each typical food item in previous year was asked on a daily, weekly, or monthly basis in household measures, and then converted to grams (16). Since the Iranian Food Composition Table (FCT) has limited data on nutrient content of raw foods and beverages, the US Department of Agriculture’s (USDA) Food Composition Table was used to analyze foods and beverages for their energy and nutrient contents. For the traditional Iranian foods not founded in the USDA table, Iranian FCT was used as an alternative. The validity and reliability of the FFQ have previously been reported (17).
Ethical Consideration
Written informed consents were obtained from all participants. The study protocol was approved by the ethics research council of the Research Institute for Endocrine Science, Shahid Beheshti University of Medical Science.
Statistical analyses
Differences between general characteristics of participants were compared across tertiles of urinary Na/K ratio, using one-way ANOVA or Chi-square tests, for dichotomous and continues variables, respectively. The principle component analysis (PCA) with varimax rotation was conducted to derive dietary patterns, based on 18 predefined food groups (whole grains, refined grains, starched vegetables, non-starched vegetables, fruits, beans, high fat dairy, low fat dairy, red meat, poultry, vegetable oil, hydrogenated and animal fat, fast foods, salty snacks, sweet snacks, sweetened beverages, nuts and seeds, tea and coffee). We considered eigenvalues >1, the scree plot and the interpretability of the patterns, and 2 factors were obtained. Although all food groups contributed to the pattern score calculation, food groups with an absolute component loading ≥0.30 were selected to describe the pattern. The Kaiser-Mayer-Olkin statistic, measure of sampling adequacy, was 0.67 (values >0.6 indicate the usefulness of cluster analysis using our data), and the P value for Bartlett’s test of sphericity was <0.001 supporting the use of cluster analysis as an appropriate procedure. Factor scores were calculated using sum of the intake of the standardized food groups weighted by their respective factor loadings on each pattern.
Calculation of Mediterranean and DASH dietary scores
To assess the Mediterranean dietary pattern score, we used an index variable that was composed of the 8 Mediterranean food groups. If consumption of each vegetables, fruits, legumes, nuts, whole grains, fish and MUFA/SAFA was above the median consumption, we assigned score 1 and if their consumption was below the median, we assigned score 0. For total red meat, if the subjects consumed more than median, we assigned score 0 and if they consumed lower than median, score 1 was assigned. The Mediterranean dietary pattern score was obtained by summing all group scores (18).
To represent the DASH score, we used an index based on 8 components: High intakes of fruits, vegetables, nuts and legumes, low fat dairy products, and whole grains and low intakes of sodium, sweetened beverages, and red and processed meats. For each of eight components, individuals were classified into five categories according to their intake ranking. For healthy components (fruits, vegetables, nuts and legumes, low fat dairy products, and whole grains) quintile 1 assigned point 1 and quintile 5 assigned point 5. In contrast, for low recommended components (sodium, sweetened beverages, and red and processed meats) quintile 1 assigned point 5 and quintile 5 assigned point 1. The overall DASH score was obtained from the sum of 8 component scores, and ranged from 8 to 40 (19).
To assess potential association of dietary patterns scores with urinary Na/K ratio, we used linear regression models. Potential confounding variables, including age, sex, BMI, WC, SBP and DBP were entered to univariate models to determine confounders. Variables with PE < 0.2 in the univariate analyses were selected as confounders. Finally, confounders adjusted in models included sex (male or female), age (year), BMI (kg/m2), and total energy intake (kcal/d). All statistical analyses were conducted using Statistical Package for Social Science (version 20; IBM Corp., Armonk, NY, USA) and P-value < 0.05 was considered significant.