Reply to Ghobadi and Jafari: diet quality in relation to the risk of hypertension among Iranian adults: cross-sectional analysis of Fasa PERSIAN cohort study.

Ghobadi and Jafari have mentioned some points about our article titled "Diet quality in relation to the risk of hypertension among Iranian adults: cross-sectional analysis of Fasa PERSIAN cohort study" which was published in the Nutrition Journal. Thanks for their consideration, the following is provided as a response to their comments.

Validity and reproducibility of the PERSIAN Cohort food frequency questionnaire: assessment of major dietary patterns.

BACKGROUND: Dietary patterns, encompassing an overall view of individuals' dietary intake, are suggested as a suitable means of assessing nutrition's role in chronic disease development. The aim of this study was to evaluate the validity and reproducibility of a food frequency questionnaire (FFQ) designed for use in the Prospective Epidemiological Research Studies in IrAN (PERSIAN), by comparing major dietary patterns assessed by the FFQ with a reference method. METHODS: Study participants included men and women who enrolled in the PERSIAN Cohort Study at seven of the eighteen centers. These centers were chosen to include dietary variations observed among the different Iranian ethnic populations. Two FFQ were completed for each participant over a one-year study period (FFQ1 upon enrollment and FFQ2 at the end of the study), with 24 interviewer-administered 24-hour dietary recalls (24 h) being completed monthly in between. Spearman correlation coefficients (SCC) were used comparing FFQs 1 and 2 to the 24 h to assess validity, while FFQ1 was compared to FFQ2 to assess reproducibility of the questionnaire. RESULTS: Three major dietary patterns-Healthy, Low Protein/High Carb and Unhealthy-were identified, accounting for 70% of variance in the study population. Corrected SCC ranged from 0.31 to 0.61 in the validity and from 0.34 to 0.57 in reproducibility analyses, with the first two patterns, which accounted for over 50% of population variance, correlated at above 0.5 in both parameters, showing acceptable findings. CONCLUSIONS: The PERSIAN Cohort FFQ is suitable for identification of major dietary patterns in the populations it is used for, in order to assess diet-disease relationships.

Identifying Risk Indicators of Cardiovascular Disease in Fasa Cohort Study (FACS): An Application of Generalized Linear Mixed-Model Tree.

BACKGROUND: Today, cardiovascular disease (CVD) is the most important cause of death around the world. In this study, our main aim was to predict CVD using some of the most important indicators of this disease and present a tree-based statistical framework for detecting CVD patients according to these indicators. METHODS: We used data from the baseline phase of the Fasa Cohort Study (FACS). The outcome variable was the presence of CVD. The ordinary Tree and generalized linear mixed models (GLMM) were fitted to the data and their predictive power for detecting CVD was compared with the obtained results from the GLMM tree. Statistical analysis was performed using the RStudio software. RESULTS: Data of 9499 participants aged 35‒70 years were analyzed. The results of the multivariable mixed-effects logistic regression model revealed that participants' age, total cholesterol, marital status, smoking status, glucose, history of cardiac disease or myocardial infarction (MI) in first- and second-degree relatives, and presence of other diseases (like hypertension, depression, chronic headaches, and thyroid disease) were significantly related to the presence of CVD (P<0.05). Fitting the ordinary tree, GLMM, and GLMM tree resulted in area under the curve (AUC) values of 0.58 (0.56, 0.61), 0.81 (0.77, 0.84), and 0.80 (0.76, 0.83), respectively, among the study population. In addition, the tree model had the best specificity at 81% but the lowest sensitivity at 65% compared to the other models. CONCLUSION: Given the superior performance of the GLMM tree compared with the standard tree and the lack of significant difference with the GLMM, using this model is suggested due to its simpler interpretation and fewer assumptions. Using updated statistical models for more accurate CVD prediction can result in more precise frameworks to aid in proactive patient detection planning.

Consumption of ultra-processed foods could influence the metabolic syndrome odds: A cross-sectional study.

Metabolic syndrome (MetS) prevalence has augmented globally during recent decades. Over the past years, the consumption of ultra-processed foods (UPFs) has grown significantly worldwide. So, the present research investigated the association between UPFs and MetS in an Iranian sample. This cross-sectional research was conducted on people (n = 8841) in the Fasa cohort study, Fars province, Iran. The participants' dietary consumption over a year, UPF consumption, and MetS diagnosis were evaluated through a 125-item modified food frequency questionnaire, the NOVA food group classification, and the Adult Treatment Panel III of the National Cholesterol Education Program, respectively. The association between the quartiles (Q) of UPF intake and the odds of MetS was estimated using the backward LR method of multivariate analysis. In the multivariate model, after adjusting potential confounders, the association between UPF intake and the odds of MetS was significant (Q4: odds ratio (OR = 3.27; 95% confidence interval (CI): 2.76-3.89). Also, the odds of increasing triglycerides (TG), blood pressure, and fasting blood sugar (FBS) and decreasing high-density lipoprotein cholesterol (HDL-C) were significantly higher in the last quartile compared to the first quartile of UPFs (TG: OR = 1.71; 95% CI: 1.49-1.97, blood pressure: OR = 1.53; 95% CI: 1.30-1.79, FBS: OR = 1.30; 95% CI: 1.10-1.54, and HDL-C: OR = 1.22; 95% CI: 1.08-1.39). The current research found a relationship between UPF intake and MetS and its components, indicating a diet-containing UPFs can be related to the occurrence of noncommunicable diseases.

Comparison of atherosclerotic cardiovascular disease (ASCVD) and Framingham risk scores (FRS) in an Iranian population.

Background: Framingham risk score (FRS) and Atherosclerotic Cardiovascular Disease risk score (ASCVDrs) are widely used tools developed based on the American population. This study aimed to compare the ASCVDrs and FRS in an Iranian population. Method: The participants of the Fasa Adult Cohort Study and the patients of the cardiovascular database of Vali-Asr Hospital of Fasa, aged 40-80 years, were involved in the present cross-sectional study. After excluding non-eligible participants, the individuals with a history of myocardial infarction or admission to the cardiology ward due to heart failure were considered high-risk, and the others were considered low-risk. The discriminative ability of FRS and ASCVDrs was evaluated and compared using receiver operating characteristic curve analysis. The correlation and agreement of ASCVDrs and FRS were tested using Cohen Kappa and Spearman. Results: Finally, 8983 individuals (mean age:53.9 ± 9.5 y, 49.2 % male), including 1827 high-risk participants, entered the study. ASCVDrs detected a greater portion of participants as high-risk in comparison with FRS (28.7 % vs. 15.7 %). ASVD (AUC:0.794) had a higher discriminative ability than FRS (AUC:0.746), and both showed better discrimination in women. Optimal cut-off points for both ASCVDrs (4.36 %) and FRS (9.05 %) were lower than the original ones and in men. Compared to FRS, ASCVDrs had a higher sensitivity (79.3 % vs. 71.6 %) and lower specificity (64.5 % vs. 65.1 %). FRS and ASCVDrs had a moderate agreement (kappa:0.593,p-value<0.001) and were significantly correlated (Spearman:0.772,p-value<0.001). Conclusions: ASCVDrs had a more accurate prediction of cardiovascular events and identified a larger number of people as high-risk in the Iranian population.

The association between energy-adjusted dietary inflammatory index and 10-year cardiovascular risk: Fasa adult cohort study.

A healthy diet is dominant in cardiovascular disease (CVD) prevention. Inflammation is pivotal for CVD development. This study aimed to evaluate the association between the pro-inflammatory diet and the CVD risk. This cross-sectional study involved 10,138 Fasa adult cohort study participants. After excluding participants with missing data, the Energy-Adjusted Dietary Inflammatory Index (E-DII) was calculated to assess the inflammatory potential of diet using the recorded Food Frequency Questionnaire. Framingham risk score (FRS) was used to predict the 10-year risk of CVD. The association between E-DII and high risk for CVD was investigated using multinominal regression. After exclusion, the mean age of studied individuals (n = 10,030) was 48.6 ± 9.6 years, including 4522 men. Most participants were low risk (FRS <10%) for CVD (87.6%), while 2.7% of them were high risk (FRS ≥20%). The median FRS was 2.80 (1.70, 6.30). The E-DII ranged from -4.22 to 4.49 (mean E-DII = 0.880 ± 1.127). E-DII was significantly associated with FRS. This result persisted after adjusting for confounding factors and in both genders. This study revealed that the pro-inflammatory diet significantly increases the CVD risk. Consequently, reducing the inflammatory potential of diet should be considered an effective dietary intervention in CVD prevention.

The association between energy-adjusted dietary inflammatory index and metabolic syndrome and its mediatory role for cardiometabolic diseases: a prospective cohort study.

Background: Metabolic syndrome (MetS) is a collection of medical conditions that elevate the chance of cardiovascular disease. An unhealthy diet is a major risk factors for MetS through different mechanisms, especially systemic chronic inflammation. Objective: This study aimed to investigate the effect of dietary inflammatory potential on MetS incidence and the role of MetS in the association between Energy-adjusted dietary inflammatory index (E-DII) and cardiometabolic diseases. Methods: In this prospective cohort study, 10,138 participants were recruited. All participants were divided into MetS or non-MetS groups based on the Adult Treatment Panel III criteria. The E-DII was used to assess the inflammatory potential of diet. After excluding the participants with MetS at baseline, 2252 individuals were followed for 5 years (longitudinal phase), and the effect of E-DII on MetS incidence was investigated using logistic regression models (p-value <0.05). Results: The cohort's mean age (45.1% men) was 48.6 ± 10.0 years. E-DII ranged from -6.5 to 5.6 (mean: -0.278 ± 2.07). Higher E-DII score had a 29% (95%CI: 1.22-1.36) increased risk for incidence of MetS and its components during five-year follow-up. Also, E-DII was significantly associated with the prevalence of MetS (OR = 1.55, 95%CI: 1.51-1.59). Among MetS components, E-DII had the strongest association with waist circumference in the cross-sectional study (OR = 2.17, 95%CI: 2.08-2.25) and triglyceride in the longitudinal study (OR = 1.19, 95%CI: 1.13-1.25). The association between E-DII and MetS was consistent in both obese (OR = 1.13, 95%CI:1.05-1.21) and non-obese (OR = 1.42, 95%CI: 1.27-1.60) individuals and stronger among non-obese participants. Additionally, MetS mediated the association between E-DII and hypertension, diabetes, and myocardial infarction. Conclusion: In conclusion, a pro-inflammatory diet consumption is associated with a higher risk of MetS and its components. Furthermore, a pro-inflammatory diet increases the risk of cardiometabolic diseases. The higher E-DII had a stronger association with MetS, even among normal-weight individuals.

The High-Dietary Insulin Load Score Is Associated With Elevated Level of Fasting Blood Sugar in Iranian Adult Men: Results From Fasa PERSIAN Cohort Study.

Aim: The potential of different foods to induce postprandial hyperinsulinemia may be involved in the development of metabolic syndrome (MetS). We aimed to evaluate the association between dietary insulin indices and MetS in a large population of adults in Iran. Methods: A total of 6356 adults aged 35-70 years were included in the present cross-sectional study. A validated block-format 125-item semiquantitative food frequency questionnaire (FFQ) was used to obtain usual food intakes, and MetS was defined according to the International Diabetes Federation (IDF) and American Heart Association (AHA)/National Heart, Lung, and Blood Institute (NHLBI) criteria. Results: MetS was prevalent in 13.8% of participants. Mean age of the study participants was 46.58 ± 8.82 years, and mean body mass index (BMI) was 25.02 ± 4.60 kg/m2. Mean dietary insulin index (DII) and dietary insulin load (DIL) were 63.15 ± 7.57 and 168.253 ± 52.09, respectively. In the crude model, men in the highest DIL quartile were more likely to have hyperglycemia than those in the lowest quartile (OR: 1.75, 95% CI: 1.12-2.73, p trend = 0.04). This association remained significant and was even stronger after adjusting for potential confounders in model I (OR: 3.64, 95% CI: 1.57-8.47, p trend = 0.005) and further adjustment for BMI in model II (OR: 3.61, 95% CI: 1.55-8.44, p trend = 0.006). Conclusions: In healthy men, adherence to a high-DIL diet may be associated with a greater likelihood of having hyperglycemia. No statistically significant association was observed between insulin indices and the odds of having MetS.

Reference Interval for Non-HDL-Cholesterol, Remnant Cholesterol and Other Lipid Parameters in the Southern Iranian Population; Findings From Bandare Kong and Fasa Cohort Studies.

BACKGROUND: Growing evidence shows the undisputable role of non-HDL-C and remnant cholesterol (remnant-C) in cardiovascular disease (CVD) risk assessment and treatment. However, the reference interval (RI) for these lipid parameters is not readily available. The aim of the present investigation was to determine the age and sex-specific RIs for non-HDL-C and remnant-C as well as other lipid parameters among a healthy population in southern Iran. We also report the RI of lipid parameters in rural and urban residents, smokers and post-menopausal women. METHODS: Among 14063 participants of Bandare Kong and Fasa cohort studies, 792 healthy subjects (205 men and 578 women) aged 35-70 years were selected. Fasting blood samples were used for determination of total cholesterol (TC), triglycerides (TG) and HDL-C using colorimetric methods. Non-HDL-C and remnant-C were calculated using the valid formula. The 2.5th and 97.5th percentiles were calculated and considered as RI. RESULTS: In the total population (n=792, age 35-70), RIs for non-HDL-C and remnant-C was 74.0-206.8 and 8.0-52.7 mg/dL, respectively. Age (35-44 and≥45 years) and gender-specific RIs for serum non-HDL-C and remnant-C were determined. Remnant-C and non-HDL-C level were different between sex and age categories. The mean value of all lipid parameters except HDL-C was higher in men, urban residents, subject with age≥45 years and smokers. CONCLUSION: This is the first study in which the RIs for non-HDL-C and remnant-C in southern Iran are reported. This may help physicians to conveniently use these lipid parameters for patient care and better cardiovascular risk assessment.

A cohort study on the predictive capability of body composition for diabetes mellitus using machine learning.

Purpose: We applied machine learning to study associations between regional body fat distribution and diabetes mellitus in a population of community adults in order to investigate the predictive capability. We retrospectively analyzed a subset of data from the published Fasa cohort study using individual standard classifiers as well as ensemble learning algorithms. Methods: We measured segmental body composition using the Tanita Analyzer BC-418 MA (Tanita Corp, Japan). The following features were input to our machine learning model: fat-free mass, fat percentage, basal metabolic rate, total body water, right arm fat-free mass, right leg fat-free mass, trunk fat-free mass, trunk fat percentage, sex, age, right leg fat percentage, and right arm fat percentage. We performed classification into diabetes vs. no diabetes classes using linear support vector machine, decision tree, stochastic gradient descent, logistic regression, Gaussian naïve Bayes, k-nearest neighbors (k = 3 and k = 4), and multi-layer perceptron, as well as ensemble learning using random forest, gradient boosting, adaptive boosting, XGBoost, and ensemble voting classifiers with Top3 and Top4 algorithms. 4661 subjects (mean age 47.64 ± 9.37 years, range 35 to 70 years; 2155 male, 2506 female) were analyzed and stratified into 571 and 4090 subjects with and without a self-declared history of diabetes, respectively. Results: Age, fat mass, and fat percentages in the legs, arms, and trunk were positively associated with diabetes; fat-free mass in the legs, arms, and trunk, were negatively associated. Using XGBoost, our model attained the best excellent accuracy, precision, recall, and F1-score of 89.96%, 90.20%, 89.65%, and 89.91%, respectively. Conclusions: Our machine learning model showed that regional body fat compositions were predictive of diabetes status.

Association of Dietary Acid Load With Metabolic Syndrome and Its Components in Iranian Adults: A Cross-Sectional Study.

Introduction Metabolic syndrome (MetS) remains one of the leading health challenges worldwide. A combination of genetic and environmental factors has been implicated in the etiology of MetS. Diet is a changeable environmental risk factor, and dietary modifications could significantly reduce the incidence and mortality of numerous diseases, including MetS. Certain dietary factors may contribute to MetS by affecting the acid-base balance within the body. This study examined the association of dietary acid load (DAL) with MetS and its components in Iranian adults. Materials and methods This cross-sectional study was conducted in 2022 on 6356 Iranian adults aged 35-70 years. Potential renal acid load (PRAL) and net endogenous acid production (NEAP) as two indicators of DAL were calculated based on nutrient intake data from validated food frequency questionnaires. MetS and its components were defined according to the Adult Treatment Panel III criteria. Logistic regression analysis was used to explore the associations between DAL and MetS and its components. Age, energy intake, physical activity, education, marital status, home ownership, socioeconomic status, history of obesity-related disease, and calcium supplements were included in model I. Further adjustment in model II was made for body mass index. Results Higher NEAP scores were associated with increased odds of low high-density lipoprotein cholesterol (HDL-C) in the crude model (OR: 1.26, 95% CI: 1.01-2.56, p trend = 0.06) in women, which was confirmed in the adjusted models. In model I, women in the last quintile of NEAP had 54% greater odds of having hypertriglyceridemia compared to the first quintile (OR: 1.54, 95% CI: 1.007-2.36, p trend = 0.02). This association was still significant and even stronger after further adjustment for BMI (OR: 1.55, 95% CI: 1.01-2.40, p trend = 0.01). In addition, in model I, men in the fourth quintile of NEAP had 5.68-fold greater odds of hyperglycemia compared to the first quintile (OR: 5.68, 95% CI: 1.18-27.25, p trend = 0.11). Similar results were found in the fully adjusted model (OR: 5.89, 95% CI: 1.19-28.99, p trend = 0.54). Conclusion There was no significant association between DAL and MetS. DAL was positively associated with the odds of low HDL-C and hypertriglyceridemia in women. Moreover, moderate DAL (NEAP) was associated with an increased odds of hyperglycemia in men.