The Tehran Lipid and Glucose Study (TLGS) is an ongoing, community-based, prospective study initiated from 1990 to 2001 by enrolling 15,005 individuals aged 3 to 69 years in Tehran district13. Following the initial examination, participants were followed up and updated every 3 years. Dietary data for Study 3 (2005–2008) were collected using the Food Frequency Questionnaire (FFQ). Of the 12125 individuals aged 18 years or older (considered the baseline phase of the current analysis) at study 3 or 4 (2008–2011), information was missing to define her HTN status at baseline or follow-up. people (n = 1504), HTN prevalent (n = 1730), pregnant and lactating women (n= 260), corticosteroid users (n= 108), and those lacking information on dietary assessment (n= 5487) was excluded. In addition, we excluded individuals with implausible energy expenditure according to gender-specific 1st and 99th percentiles of energy intake (n= 60) and those for whom the covariate was missing (n= 271). Finally, 2706 individuals were followed up to the end of Study 6 (2014–2018), with a median follow-up he of 7.4 years (Fig. 1). For TLGS, a subsample of participants was randomly selected to complete dietary information. Comparing participant characteristics with and without dietary data at the third or fourth test, men, smokers, family history of cardiovascular disease, college education, and level of physical activity It was shown that the proportions of between two groups.However, the age and body mass index (BMI) of the individual who completed her FFQ on the fourth trial was slightly lower than the individual without dietary data (40.8 ± 14.1 vs. 44.8 ± 17.1 years and 27.3 ± 4.9 vs. 27.7 ±5.2kg/meter2Each) [8, 13]All methods in this study were performed in accordance with the Declaration of Helsinki. This study was approved by the Ethics Committee of the Institute of Endocrine Science, Shahid Beheshti Medical College (IR.SBMU.ENDOCRINE.REC.1400.098). Written informed consent forms were obtained from all individuals (Figure 1).
Demographics, anthropometrics, and physical activity assessment
Data on age, gender, education level, smoking status, medical history, and drug use were collected by questionnaire. We classified individuals into two groups by educational attainment: <12 years or >12 years (educational attainment), and three groups by smoking status: never smokers, former smokers, and current smokers. Incidence of cardiovascular disease in a family member of a female in her first grade aged 65 years or younger or in a family member of a male in her first grade aged 55 years or younger was considered to have an early family history of cardiovascular disease. .
Weight was measured in light clothing to the nearest 0.1 kg using a digital scale (Seca 707; Seca Corporation, Hanover, Maryland; range, 0.1–150 kg). Height was assessed to the nearest 0.1 cm with him standing using a stadiometer, but with his shoes off and his shoulders in normal position. Body mass index (BMI) was calculated by dividing body weight (Kg) by her square of height (m).2).
Physical activity over the past year was assessed using the Modifiable Activity Questionnaire (MAQ). The MAQ consists of two types of questions based on leisure activities and work-related activities. Participants reported how often and how much time they spent doing all activities in each category based on four levels of intensity (light, moderate, hard, and very hard). Physical activity was expressed as metabolic equivalent minutes per week (MET-min/wk).
After an overnight fast of approximately 12 to 14 hours, blood samples were taken from all participants in a sitting position between 7:00 and 9:00 am. Samples were immediately centrifuged within 30–45 min. Fasting serum glucose (FSG), total cholesterol (TC), and triglycerides (TG) were assessed using an enzymatic colorimetric method. Serum high-density lipoprotein-cholesterol (HDL-C) was assessed after precipitation of apolipoprotein B-containing lipoproteins with phosphotungstic acid. The inter-/intra-assay coefficient variation (CV) was 2.2% for FSG, 0.5 and 2% for TC and HDL-C, and 0.6 and 1.6% for TG, respectively). Serum creatinine levels were measured using the kinetic colorimetric method Jaffe with a sensitivity of 0.2 mg/dL (range, 18–1330 µmol/L (0.2–15 mg/dL)), with intra- and inter-assay All CVs were less than 3.1%. Blood samples were analyzed at the TLGS laboratory at the time of collection using a Selectra 2 automated analyzer (Vital Scientific, Spankeren, The Netherlands). Biochemical measurements were performed using commercial kits (Pars Azmoon Inc., Tehran, Iran). was performed using
Participants’ dietary intake was examined by a trained nutritionist using a semi-quantitative FFQ.
Validity and reliability of FFQ have already been evaluated Participants were asked to estimate their consumption of each food item over the previous year using daily, weekly, or monthly frequencies and pre-determined portion sizes. Portions of all foods ingested were converted to grams using home measurements. Absolute consumption of dietary components was used to estimate each dietary score. A higher score for any dietary indicator indicates better adherence.
MED scores were calculated using the approach published by Trichopoulou et al. The method includes nine components: vegetables, legumes, fruits and nuts, grains, fish, meat and meat products, dairy products, monounsaturated fatty acid (MUFA) to saturated fatty acid (SFA) ratios, and alcohol. included. Due to lack of information, we did not consider alcohol consumption as a food component. A value of 0 or 1 was assigned to each component using the gender-specific median as cutoff. Thus, for the five predicted beneficial ingredients (vegetables, legumes, fruits and nuts, grains, and fish), individuals whose consumption is equal to or above the median for their sex are assigned a value of 1, and a value of 0 is assigned. Individuals with below median consumption. Similarly, MUFA to SFA ratios equal to or greater than the gender-specific median were assigned a value of 1, while consumption below the median was assigned a value of 0. For ingredients presumed to be harmful (meat or meat products and dairy products), a point of 1 was assigned if intake was below the gender-specific median, and participants with intakes above the median A value of 0 was assigned. Total MED scores ranged from 0 to 8.
DASH scores were calculated by Epstein et al. Based on intake of 10 food ingredients: % Energy Intake from Total Grains, Fruits, Vegetables, Nuts, Seeds, Dried Beans, Dairy, Meat, Poultry, Fish, Total Fat, Saturated Fat, Sweets, Sodium. Energy intake from % . Based on the recommended number of servings, each of the 10 dietary components was assigned a score of 1, 0.5, or 0, and the scores were summed. The DASH score was between 0 and 10.
The MIND score was developed by Morris et al. Our FFQ did not investigate consumption of major oils and alcohol, so these dietary ingredients were excluded from the calculation of the MIND score. group was considered. snack. A score of 1, 0.5, or 0 was assigned to each component according to the recommended number of servings. These scores were then combined. MIND scores ranged from 0 to 13.
Blood pressure assessment and disease definition
A trained physician used a mercury sphygmomanometer to measure blood pressure in the right arm twice at 1-minute intervals in a sitting position. Before the evaluation, all participants were asked to rest for 15 minutes while they were seated. The average of the two measurements was taken as the final blood pressure measurement.
In the absence of antihypertensive drugs, prehypertension was defined as SBP 120-139 mmHg and/or DBP 80-89 mmHg. HTN was defined based on the Seventh Report of the Joint National Commission on the Prevention, Detection, Evaluation, and Treatment of Hypertension (JNC-VII).  Systolic blood pressure (SBP) ≥ 140 mmHg or diastolic blood pressure (DBP) ≥ 90 mmHg, or use of antihypertensive agents. Pre-tested questionnaires were used to assess the use of antihypertensive agents such as diuretics, beta-blockers, angiotensin-converting enzyme inhibitors, calcium channel blockers and angiotensin receptor blockers at baseline and throughout follow-up visits. evaluated in
Type 2 diabetes mellitus (T2DM) was defined as FSG ≥ 126 mg/dl or plasma glucose ≥ 200 mg/dl 2 hours post-challenge, or taking antidiabetic medications. Chronic kidney disease (CKD) was defined based on calculation of estimated glomerular filtration rate (eGFR) using the CKD Epidemiology Collaboration (CKD-EPI) formula. Dyslipidemia was also described as having one or more of the following criteria: serum TG ≥ 200 mg/dL, TC ≥ 240 mg/dL, HDL-C < 40 mg/dL, or lipid taking depressant drugs .
We examined the histogram charts to assess whether the distribution of the variables was approximately normal. Participants’ baseline characteristics across quartile categories for each diet score were compared using analysis of variance (ANOVA) for continuous variables and chi-square tests for categorical variables. Non-normally distributed variables such as physical activity, FSG, TG, caffeine and olive intake were natural-log transformed before analysis. Data were presented as mean ± standard deviation (SD) for normally distributed variables, median (interquartile range) for skewed variables and percent for categorical variables. Cox proportional hazards regression analysis was used to examine the association between the dietary index and his risk of HTN. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated for each 1-unit change for each diet score (as a continuous variable) and across quartile categories, considering the first group as a reference .Associations were adjusted for age (continuous) and sex for model 1, physical activity (continued), educational attainment (yes/no), early family history of cardiovascular disease (yes/no), smoking (smoker, baseline BMI, type 2 diabetes mellitus (yes/no), CKD (yes/no), prehypertension (yes/no), dyslipidemia (yes/no), aspirin intake (yes/no), dietary intake of total energy (continuously), and olive oil (continuously).The median was assigned to each quartile and calculated treated as a continuous variable. P.on trend. An interaction term was included in the multivariable Cox model to explore the interaction of gender with BMI and dietary scores for risk of HTN. The proportional hazards assumption of the multivariable Cox model was evaluated using Schoenfeld’s global test of residuals.
Event times for HTN were interval-censored due to the uncertainty of the exact start time, even though the event could occur between two exam appointments. Therefore, midpoint censoring was utilized for the analysis of interval censoring results. According to midpoint censoring, the event date of HTN was defined as the midpoint between the follow-up examination data when HTN was first identified and the most recent follow-up examination data prior to diagnosis. Follow-up time was also calculated based on the difference between the estimated median date and the date the individual entered the study. Survival time was the interval between the first and last examination dates in censored individuals.
Several sensitivity analyzes were performed to identify early diagnosis of 1-HTN (<2 years), late diagnosis of 2-HTN (>10 years), and 3-prehypertension at baseline, 4-T2DM, and 5 Excluded individuals. – CKD at baseline. All analyzes were performed using IBM SPSS for Windows version 20 (IBM, New York, USA). P.Values < 0.05 are considered significant.