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Abstract Maturity-onset diabetes of the young (MODY) is an uncommon monogenic type of diabetes mellitus. Detecting genetic variants for MODY is a necessity for precise diagnosis and treatment. The majority of MODY genetic predisposition has been documented in European populations and a lack of information is present in Iranians which leads to misdiagnosis as a consequence of defects in unknown variants. In this study, using genetic variant information of 20,002 participants from the family-based TCGS (Tehran Cardiometabolic Genetic Study) cohort, we evaluated the genetic spectrum of MODY in Iran. We concentrated on previously discovered MODY-causing genes. Genetic variants were evaluated for their pathogenicity. We discovered 6 variants that were previously reported in the ClinVar as pathogenic/likely pathogenic (P/LP) for MODY in 45 participants from 24 families (INS in 21 cases, GCK in 13, HNF1B in 8, HNF4A, HNF1A, and CEL in 1 case). One potential MODY variant with Uncertain Risk Allele in ClinVar classification was also identified, which showed complete disease penetrance (100%) in four subjects from one family. This is the first family-based study to define the genetic spectrum and estimate the prevalence of MODY in Iran. The discovered variants need to be investigated by additional studies.

Abstract Background Despite the high burden of obesity and Type 2 diabetes (T2DM) in the Middle East/West Asia region, the effect of weight change on the development of T2DM is poorly addressed. Therefore, we aimed to assess the impact of 3-year body weight change on incident of T2DM over 3-, 6-, and 9-year periods among Iranian adults. Methods A total of 6930 participants (men = 2567) aged ≥ 20 years free of T2DM or cancer at baseline were included. Weight measurements were taken at baseline (2002–2005) and approximately 3 years later. Participants were categorized based on their weight change ratio into ≥ 5% loss, stable (± 5%), and ≥ 5% gain. Generalized estimating equations (GEE), adjusted with age, sex, education levels, baseline measurements of fasting plasma glucose, weight, waist circumference, triglycerides to high-density lipoprotein cholesterol ratio, family history of diabetes, current smoker, hypertension, and prevalent cardiovascular disease were applied to estimate the Odds ratios (ORs) and 95% confidence intervals (CIs) of weight change categories for incident T2DM, considering stable weight as a reference. Results During median follow-ups of 3-, 6-, and 9-year, 295, 505, and 748 cases of T2DM occurred, respectively. Weight gain of ≥ 5%, as compared to stable weight group (± 5%), was associated with increased T2DM risk, with ORs of 1.58 (95% CI 1.16–2.14), 1.76 (1.41–2.20), and 1.70 (1.40–2.05) for the 3-, 6-, and 9-year follow-ups, respectively, in multivariable analysis; corresponding values for weight loss ≥ 5% were 0.48 (0.29–0.80), 0.57 (0.40–0.81), and 0.51 (0.38–0.68), respectively. This association persisted even after adjusting for attained weight. Subgroup analysis showed consistent associations across age, gender, and body mass index categories. Conclusion Weight gain and loss of ≥ 5% were associated with increased and decreased risks of incident T2DM, respectively, regardless of attained weight. This association was consistent over various follow-up durations among the Iranian population as recommended by guidelines.

Abstract Background & aim Cardiovascular disease (CVD) is the most important cause of death in the world and has a potential impact on health care costs, this study aimed to evaluate the performance of machine learning survival models and determine the optimum model for predicting CVD-related mortality. Method In this study, the research population was all participants in Tehran Lipid and Glucose Study (TLGS) aged over 30 years. We used the Gradient Boosting model (GBM), Support Vector Machine (SVM), Super Learner (SL), and Cox proportional hazard (Cox-PH) models to predict the CVD-related mortality using 26 features. The dataset was randomly divided into training (80%) and testing (20%). To evaluate the performance of the methods, we used the Brier Score (BS), Prediction Error (PE), Concordance Index (C-index), and time-dependent Area Under the Curve (TD-AUC) criteria. Four different clinical models were also performed to improve the performance of the methods. Results Out of 9258 participants with a mean age of (SD; range) 43.74 (15.51; 20–91), 56.60% were female. The CVD death proportion was 2.5% (228 participants). The death proportion was significantly higher in men (67.98% M, 32.02% F). Based on predefined selection criteria, the SL method has the best performance in predicting CVD-related mortality (TD-AUC > 93.50%). Among the machine learning (ML) methods, The SVM has the worst performance (TD-AUC = 90.13%). According to the relative effect, age, fasting blood sugar, systolic blood pressure, smoking, taking aspirin, diastolic blood pressure, Type 2 diabetes mellitus, hip circumference, body mss index (BMI), and triglyceride were identified as the most influential variables in predicting CVD-related mortality. Conclusion According to the results of our study, compared to the Cox-PH model, Machine Learning models showed promising and sometimes better performance in predicting CVD-related mortality. This finding is based on the analysis of a large and diverse urban population from Tehran, Iran.

Abstract Background Obesity and dyslipidemia are important risk factors for hypertension (HTN). When these two conditions coexist, they may interact in a synergistic manner and increase the risk of developing HTN and its associated complications. The aim of this study was to investigate the synergistic effect of general and central obesity with dyslipidemia on the risk of HTN. Method Data from 40,387 individuals aged 25 to 64 years were obtained from a repeated cross-sectional study examining risk factors for non-communicable diseases (STEPS) in 2007, 2011 and 2016. Body mass index (BMI) was calculated as a measure of general obesity and waist circumference (WC) as a measure of central obesity. Dyslipidemia was defined as the presence of at least one of the lipid abnormalities. Hypertension was defined as systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg or current use of antihypertensive medication. To analyze the synergistic effect between obesity and dyslipidemia and HTN, the relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and synergy index (SI) were calculated. A weighted logistic regression model was performed to estimate the odds ratios (ORs) for the risk of HTN. Results The results showed an association between obesity, dyslipidemia and hypertension. The interaction between obesity and dyslipidemia significantly influences the risk of hypertension. In hypertensive patients, the presence of general obesity increased from 14.55% without dyslipidemia to 64.36% with dyslipidemia, while central obesity increased from 13.27 to 58.88%. This interaction is quantified by RERI and AP values of 0.15 and 0.06 for general obesity and 0.24 and 0.09 for central obesity, respectively. The corresponding SI of 1.11 and 1.16 indicate a synergistic effect. The OR also show that the risk of hypertension is increased in the presence of obesity and dyslipidemia. Conclusion Obesity and dyslipidemia are risk factors for HTN. In addition, dyslipidemia with central obesity increases the risk of HTN and has a synergistic interaction effect on HTN. Therefore, the coexistence of obesity and lipid abnormalities has many clinical implications and should be appropriately monitored and evaluated in the management of HTN.

Background The aim of this study was to assess how early‐adulthood body mass index (BMI) and waist circumference (WC) relate to long‐term cardiovascular structure, function, and prognosis in individuals without obesity and with low cardiovascular risk factor (CVRF) burden. Methods and Results A total of 2024 participants aged 18 to 30 from the CARDIA (Coronary Artery Risk Development in Young Adults) study, without obesity and with low CVRFs defined as the absence of cardiovascular disease (CVD), diabetes, hypertension, current smoking, and dyslipidemia were included. A CVRF‐optimal subgroup was also defined, with blood pressure

Abstract Background Cardiovascular disease (CVD) is a major cause of death worldwide, although limited data are currently available regarding the impact of consuming ultra-processed food (UPF) on its incidence. Given the increased consumption of UPF in Iran, we aimed to investigate the association between UPF intake and CVD risk. Methods Individuals without CVD (n = 2050) aged ≥ 30 years old were recruited from the Tehran Lipid and Glucose Study (TLGS). Dietary data were collected using a validated food frequency questionnaire (FFQ) and UPF intakes were assessed based on the Nova food classification. Multivariable Cox proportional hazard models adjusted for potential confounders were used to estimate the hazard ratio (HR) and 95% confidence intervals (95% CI) for the risk of CVD across tertiles of UPF intake. Results A 10.1% incidence of CVD occurred over a median follow-up of 10.6 years, with a 22% increase in CVD risk per each 50 g/day UPF intake. Participants with the highest intake of UPF had a 68% greater incidence of CVD compared to those with the lowest intake (HR = 1.68, 95% CI=1.14–2.48) after controlling for potential confounders. Regarding sub-groups of UPF, participants in the 3rd tertile compared to the reference had a significantly increased risk of CVD (HR = 1.56, 95% CI=1.04–2.34). Nevertheless, intake of bread, fast food, sweetened beverages, sweets and desserts, high-fat dairy products, and other UPFs were not associated with greater CVD risk. Conclusion Our findings support the hypothesis that the incidence of CVD is enhanced with the higher consumption of UPF in a representative sample of the Iranian population.

Abstract Background Elevated fasting plasma glucose (FPG) and 2-hour post-challenge glucose (2hPG) levels are known to be independent risk factors for cardiovascular disease (CVD). However, there is limited data on the association of the difference between these measures and the risk of CVD. This study aims to investigate this association in normoglycemic Iranian adults, particularly in those with low-normal FPG levels. Methods This prospective cohort study included 4,594 30-65-year-old participants from the Tehran Lipid and Glucose Study. Using multivariable Cox proportional hazards regression models adjusting for age, sex, body mass index, hypertension, hypercholesterolemia, smoking, education level and FPG, hazard ratios (HRs) and 95% confidence intervals (95% CIs) were calculated for the association between 2hPG-FPG, both as continuous and categorical variables, and the CVD risk. Analyses of receiver operating characteristic curves were undertaken to determine the optimal 2hPG-FPG cut-off value. Results During a median of 17.9 years of follow-up, 459 CVD events occurred. A one-unit increase in 2hPG-FPG was significantly associated with an elevated risk of cardiovascular disease in both normoglycemic (HR 1.10, 95% CI (1.01–1.19)) and low-normal FPG individuals (HR 1.16, 95% CI (1.04–1.30)); this association resisted adjustment for Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) among normoglycemic individuals. However, those with 2hPG levels greater than FPG levels had a non-significant increased risk of incident CVD compared to those with 2hPG levels of less than or equal to FPG, with corresponding HR values of 1.18 (95% CI: 0.95–1.46) in normoglycemic and 1.32 (95% CI: 0.98–1.79) in low-normal FPG, respectively. For incident CVD, the optimal cut-off value for the 2hPG-FPG was found to be 1.06 mmol/L, which was applicable for both normoglycemic and low FPG populations; using this criterion, the corresponding risks for incident CVD were 1.36 (95% CI: 1.12–1.64) and 1.57 (95% CI: 1.22–2.03), respectively. Conclusions The difference between 2hPG and FPG levels within the normoglycemic range is related to an increased risk of CVD, an issue that was independent of HOMA-IR. A cut-off point for 2hPG-FPG > 1.06 mmol/L may stratify persons at higher risk. These findings were particularly notable in those with low-normal FPG.

Abstract Dyslipidemia, as a metabolic risk factor, with the strongest and most heritable independent cause of cardiovascular diseases worldwide. We investigated the familial transmission patterns of dyslipidemia through a longitudinal family-based cohort, the Tehran Cardiometabolic Genetic Study (TCGS) in Iran. We enrolled 18,729 individuals (45% were males) aged > 18 years (mean: 38.15 (15.82)) and observed them over five 3-year follow-up periods. We evaluated the serum concentrations of total cholesterol, triglyceride, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol with the first measurement among longitudinal measures and the average measurements (AM) of the five periods. Heritability analysis was conducted using a mixed-effect framework with likelihood-based and Bayesian approaches. The periodic prevalence and heritability of dyslipidemia were estimated to be 65.7 and 42%, respectively. The likelihood of an individual having at least one dyslipidemic parent reveals an OR = 6.94 (CI 5.28–9.30) compared to those who do not have dyslipidemic parents. The most considerable intraclass correlation of family members was for the same-sex siblings, with ICC ~ 25.5%. For serum concentrations, heritability ranged from 33.64 to 60.95%. Taken together, these findings demonstrate that familial transmission of dyslipidemia in the Tehran population is strong, especially within the same-gender siblings. According to previous reports, the heritability of dyslipidemia in this population is considerably higher than the global average.

Abstract Background The effect of obesity in different glucose tolerance statuses i.e. normoglycemia (NGT), pre-diabetes, and type 2 diabetes (T2DM) on cardiovascular disease (CVD) and mortality has been an area of ongoing debate and uncertainty. In the present study, we aimed to examine the impact of being obese, whether general or central separately, in comparison with non-obese in different glucose tolerance statuses on the above outcomes. Methods The study population included 18,184 participants aged 30–60 years (9927 women) from three longitudinal studies, including Atherosclerosis Risk in Communities, Multi-Ethnic Study of Atherosclerosis, and Tehran Lipid and Glucose Study. Glucose tolerance status was defined as NGT (fasting plasma glucose

AimWe aimed to investigate the effect of BMI variability on CVD and mortality and to explore the mediation effects of the main cardiovascular risk factors contributing to this association.MethodParticipants aged 40-65 years were pooled from three cohort studies(ARIC [Atherosclerosis Risk in Communities], MESA [Multi-ethnic Study of Atherosclerosis], and TLGS [Tehran Lipid and Glucose Study]. We employed root mean squared error of the fractional mixed model to calculate BMI variability in the measurement period. In the event assessment period, the hazard ratios for CVD and mortality were estimated using Cox proportional hazard regression models. In the next step, the mediation and interaction effects of fasting plasma glucose, total cholesterol, and systolic blood pressure were determined.ResultsA total of 19073 participants were included in this pooled analysis. During a median of 20.7 years of follow-up, 3900 (20.44%) CVD and 6480 (33.97%) all-cause mortality events were recorded. After adjusting for potential confounders, BMI variability was linked to the 1.3 (1.2-1.4) and 1.7 (1.6-1.8) increased risk of CVD and mortality, respectively. Fasting plasma glucose mediated approximately 24% and 8% of the effect of BMI variability on CVD and mortality, respectively. However, systolic blood pressure and total cholesterol did not have mediation effects in this association.ConclusionHigh BMI variability is independently associated with the development of CVD and mortality. This association is partly mediated through fasting plasma glucose. Modern cardiometabolic therapies that lower fasting glucose may reduce the risk of future CVD and mortality in individuals with high BMI variability.

Background Despite the achievements of the national program for the prevention and control of diabetes (NPPCD) over the past two decades, the available evidence indicates a high prevalence of this disease in Iran. This qualitative study aims to investigate barriers to the NPPCD by pursuing the perspectives of relevant policy-makers, planners, and healthcare workers.Methods A grounded theory approach was used to analyze participants’ perceptions and experiences. Semistructured interviews (n=23) and eight focus groups (n=109) were conducted with relevant policy-makers, planners, and healthcare workers in charge of Iran’s national diabetes management program. Of the 132 participants, ages ranged from 25 to 56 years, and 53% were female. Constant comparative analysis of the data was conducted manually, and open, axial, and selective coding was applied to the data.Results Two main themes emerged from data analysis: implementation barriers and inefficient policy-making/ planning. Insufficient financial resources, staff shortage and insufficient motivation, inadequate knowledge of some healthcare workers, and defects in the referral system were recognized as the NPPCD implementation barriers. Inappropriate program prioritizing, the lack of or poor intersectoral collaboration, and the lack of an effective evaluation system were the inefficient policy-making/planning problems.Conclusion Current results highlighted that inefficient policy-making and planning have led to several implementation problems. Moreover, the key strategies to promote this program are prioritizing the NPPCD, practical intersectoral collaboration, and utilizing a more efficient evaluation system to assess the program and staff performance.

Abstract Background Smoking is a significant public health problem, and there is a scarcity of documents regarding its severity, particularly in developing countries. This study aimed to determine factors related to the number of cigarettes consumed daily by adult smokers in Tehran. Methods This study was conducted within the framework of the longitudinal study of Tehran Lipid and Glucose Study (TLGS). The study included 786 adult smokers living during four consecutive follow-ups from 2005 to 2016. The intensity of smoking was measured by the number of cigarettes consumed daily by adult smokers. Data analysis was done longitudinally and based on the mixed effects zero-inflated discrete Weibull (ZIDW) regression model. Results The mean age of the individuals was 40.35 ± 12.68 years, and 643 (81.8%) of them were men. Also, 52.7% of individuals were daily smokers, 15.6% were occasional smokers, and 31.7% were non-smokers who became smokers during the study. Variables of age 1.005 (95%CI: 1.001–1.008), gender of male 1.196 (95%CI: 1.051–1.39), and marital status (divorced/widowed vs. single) 1.168 (95%CI: 1.015–1.39) were positively associated with smoking intensity. Education level (master and higher vs. illiterate) 0.675 (95%CI: 0.492–0.926)), employment status (student vs. unemployed) 0.683 (95%CI: 0.522–0.917), (housewife vs. unemployed) 0.742 (95%CI: 0.606–0.895), (Unemployed with income vs. unemployed) 0.804 (95%CI: 0.697, 0.923), implementation of smoking prohibition regulations (yes vs. no) 0.88 (95%CI: 0.843–0.932), and history of cardiovascular disease in male relatives (yes vs. no) 0.85 (95%CI: 0.771–0.951) were associated with lower smoking intensity. Conclusion We showed that demographic factors are associated with the intensity of smoking among adults and should be considered in policymakers’ intervention programs to reduce smoking and quit smoking.

Abstract Background The available evidence indicates that the severity of metabolic syndrome tends to worsen progressively over time. We assessed the trajectory of age and sex-specific continuous MetS severity score (cMetS-S) and its association with the development of diabetes during an 18-year follow-up. Methods In a prospective population-based Tehran Lipid and Glucose Study, 3931 eligible participants free of diabetes, aged 20–60 years, were followed at three-year intervals. We examined the trajectories of cMetS-S over nine years using latent growth mixture modeling (LGMM) and subsequent risks of incident diabetes eight years later. The prospective association of identified trajectories with diabetes was examined using the Cox proportional hazard model adjusting for age, sex, education, and family history of diabetes, physical activity, obesity (BMI ≥ 30 kg/m2), antihypertensive and lipid-lowering medication, and baseline fasting plasma glucose in a stepwise manner. Results Among 3931 participants, three cMetS-S trajectory groups of low (24.1%), medium (46.8%), and high (29.1%) were identified during the exposure period. Participants in the medium and high cMetS-S trajectory classes had HRs of 2.44 (95% CI: 1.56–3.81) and 6.81 (95% CI: 4.07–10.01) for future diabetes in fully adjusted models, respectively. Normoglycemic individuals within the high cMetS-S class had an over seven-fold increased risk of diabetes (HR: 7.12; 95% CI: 6.05–12.52). Conclusion Although most adults exhibit an unhealthy metabolic score, its severity usually remains stable throughout adulthood over ten years of follow-up. The severity score of metabolic syndrome has the potential to be utilized as a comprehensive and easily measurable indicator of cardiometabolic dysfunction. It can be employed in clinical settings to detect and track individuals at a heightened risk of developing T2DM, even if their glucose levels are normal.

Abstract Background The prevalence of metabolic syndrome is increasing worldwide. Clinical guidelines consider metabolic syndrome as an all or none medical condition. One proposed method for classifying metabolic syndrome is latent class analysis (LCA). One approach to causal inference in LCA is using propensity score (PS) methods. The aim of this study was to investigate the causal effect of smoking on latent hazard classes of metabolic syndrome using the method of latent class causal analysis. Methods In this study, we used data from the Tehran Lipid and Glucose Cohort Study (TLGS). 4857 participants aged over 20 years with complete information on exposure (smoking) and confounders in the third phase (2005–2008) were included. Metabolic syndrome was evaluated as outcome and latent variable in LCA in the data of the fifth phase (2014–2015). The step-by-step procedure for conducting causal inference in LCA included: (1) PS estimation and evaluation of overlap, (2) calculation of inverse probability-of-treatment weighting (IPTW), (3) PS matching, (4) evaluating balance of confounding variables between exposure groups, and (5) conducting LCA using the weighted or matched data set. Results Based on the results of IPTW which compared the low, medium and high risk classes of metabolic syndrome (compared to a class without metabolic syndrome), no association was found between smoking and the metabolic syndrome latent classes. PS matching which compared low and moderate risk classes compared to class without metabolic syndrome, showed that smoking increases the probability of being in the low-risk class of metabolic syndrome (OR: 2.19; 95% CI: 1.32, 3.63). In the unadjusted analysis, smoking increased the chances of being in the low-risk (OR: 1.45; 95% CI: 1.01, 2.08) and moderate-risk (OR: 1.68; 95% CI: 1.18, 2.40) classes of metabolic syndrome compared to the class without metabolic syndrome. Conclusions Based on the results, the causal effect of smoking on latent hazard classes of metabolic syndrome can be different based on the type of PS method. In adjusted analysis, no relationship was observed between smoking and moderate-risk and high-risk classes of metabolic syndrome.

Abstract Background Missing data is a pervasive problem in longitudinal data analysis. Several single-imputation (SI) and multiple-imputation (MI) approaches have been proposed to address this issue. In this study, for the first time, the function of the longitudinal regression tree algorithm as a non-parametric method after imputing missing data using SI and MI was investigated using simulated and real data. Method Using different simulation scenarios derived from a real data set, we compared the performance of cross, trajectory mean, interpolation, copy-mean, and MI methods (27 approaches) to impute missing longitudinal data using parametric and non-parametric longitudinal models and the performance of the methods was assessed in real data. The real data included 3,645 participants older than 18 years within six waves obtained from the longitudinal Tehran cardiometabolic genetic study (TCGS). The data modeling was conducted using systolic and diastolic blood pressure (SBP/DBP) as the outcome variables and included predictor variables such as age, gender, and BMI. The efficiency of imputation approaches was compared using mean squared error (MSE), root-mean-squared error (RMSE), median absolute deviation (MAD), deviance, and Akaike information criteria (AIC). Results The longitudinal regression tree algorithm outperformed based on the criteria such as MSE, RMSE, and MAD than the linear mixed-effects model (LMM) for analyzing the TCGS and simulated data using the missing at random (MAR) mechanism. Overall, based on fitting the non-parametric model, the performance of the 27 imputation approaches was nearly similar. However, the SI traj-mean method improved performance compared with other imputation approaches. Conclusion Both SI and MI approaches performed better using the longitudinal regression tree algorithm compared with the parametric longitudinal models. Based on the results from both the real and simulated data, we recommend that researchers use the traj-mean method for imputing missing values of longitudinal data. Choosing the imputation method with the best performance is widely dependent on the models of interest and the data structure.

Abstract Phosphatidylinositol-3-kinase (PI3K)/Akt signaling pathway regulates glucose and lipid metabolism. We examined the association of PI3K and Akt expression in visceral (VAT) and subcutaneous adipose tissue (SAT) with daily physical activity (PA) in non-diabetic obese and non-obese adults. In this cross-sectional study, we included 105 obese (BMI ≥ 30 kg/m2) and 71 non-obese (BMI

Abstract Metabolic syndrome (MetS), defined as the coexistence of interrelated cardiometabolic risk factors, is limited by ignoring the severity of the disease and individuals with a pre-metabolic state. We aimed to develop the first age- and sex-specific continuous MetS severity score in the adult population using confirmatory factor analysis (CFA) based on the MetS components in the Middle East. Using data from the population-based Tehran Lipid and Glucose Study (TLGS) I and II datasets, we conducted CFA of the single factor MetS on 8933 adults (20–60 years old) totally, and in age and sex subgroups. We allowed for different factor loadings across the subgroups to formulate age- and sex-specific continuous MetS severity score equations. Thereafter, we validated these equations in the dataset of TLGS III participants. Triglyceride had the highest factor loading across age and sex subgroups, indicating the most correlation with MetS. Except for women aged 40–60 years, waist circumference was the second most significant factor contributing to MetS. Systolic blood pressure was more closely related to MetS in women than in men. Systolic blood pressure and fasting plasma glucose had the weakest correlation with MetS among the 40–60 age group. Moreover, as women age, the contribution of fasting plasma glucose to MetS tended to decline, while it remained relatively constant in men. The resulting MetS severity score was correlated with age and homeostasis model assessment of insulin resistance. Furthermore, the continuous MetS severity score well predicted the traditional MetS according to receiver operating characteristic analysis in the validation dataset. The age- and sex-specific continuous MetS severity score for the West Asian adult population provides a tangible quantitative measure of MetS enabling clinicians to screen and monitor the individuals at risk and assess their metabolic trends.

Background To examine the association of blood pressure (BP) levels with coronary artery calcium and carotid intima‐media thickness (CIMT) in people with maintained BP below the hypertension range based on current definitions. Methods and Results In this post hoc analysis of the CARDIA (Coronary Artery Risk Development in Young Adults) prospective observational cohort study conducted in 4 US cities, we examined 1233 study participants (mean [SD] age at year 20 examination was 45.3 [3.5] years; 65.4% women). Participants with BP assessments across 20 years and untreated BP of 1.01 mm was ≈50% higher per 1‐SD increase in systolic BP (OR, 1.50 [95% CI, 1.19–1.88]) and pulse pressure (OR, 1.46 [95% CI, 1.19–1.79]). Similar findings for CIMT were observed among individuals with a coronary artery calcium score of 0 as well as those with maintained BP of

Introduction We evaluate which screening and diagnostic approach resulted in the greatest reduction in adverse pregnancy outcomes due to increased treatment.Research design and methods This study presents a secondary analysis of a randomized community non-inferiority trial conducted among pregnant women participating in the GULF Study in Iran. A total of 35 430 pregnant women were randomly assigned to one of the five prespecified gestational diabetes mellitus (GDM) screening protocols. The screening methods included fasting plasma glucose (FPG) in the first trimester and either a one-step or a two-step screening method in the second trimester of pregnancy. According to the results, participants were classified into 6 groups (1) First-trimester FPG: 100–126 mg/dL, GDM diagnosed at first trimester; (2) First trimester FPG: 92–99.9 mg/dL, GDM diagnosed at first trimester; (3) First trimester FPG: 92–99.9 mg/dL, GDM diagnosed at second trimester; (4) First trimester FPG: 92–99.9 mg/dL, healthy at second trimester; (5) First trimester FPG

Abstract Background The primary aim of the present study was to validate the REasons for Geographic and Racial Differences in Stroke (REGARDS) model for incident Type 2 diabetes (T2DM) in Iran. Methods Present study was a prospective cohort study on 1835 population aged ≥ 45 years from Tehran lipids and glucose study (TLGS).The predictors of REGARDS model based on Bayesian hierarchical techniques included age, sex, race, body mass index, systolic and diastolic blood pressures, triglycerides, high-density lipoprotein cholesterol, and fasting plasma glucose. For external validation, the area under the curve (AUC), sensitivity, specificity, Youden’s index, and positive and negative predictive values (PPV and NPV) were assessed. Results During the 10-year follow-up 15.3% experienced T2DM. The model showed acceptable discrimination (AUC (95%CI): 0.79 (0.76–0.82)), and good calibration. Based on the highest Youden’s index the suggested cut-point for the REGARDS probability would be ≥ 13% which yielded a sensitivity of 77.2%, specificity 66.8%, NPV 94.2%, and PPV 29.6%. Conclusions Our findings do support that the REGARDS model is a valid tool for incident T2DM in the Iranian population. Moreover, the probability value higher than the 13% cut-off point is stated to be significant for identifying those with incident T2DM.

Abstract Background To investigate the association between the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) and Homeostasis Model Assessment of Beta-cell function (HOMA-B) with the incidence of diabetes and pre-diabetes subtypes. Methods A total of 3101 normoglycemic people aged 20–70 years were included in the 6-year follow-up study. Multinomial logistic regression was used to calculate the incidence possibility of isolated Impaired Fasting Glucose (iIFG), isolated Impaired Glucose Tolerance (iIGT), Combined impaired fasting glucose & impaired glucose tolerance (CGI), and Diabetes Mellitus (DM) per standard deviation (SD) increment in HOMA-IR and HOMA-B in the crude and multivariable model. Results In the multivariate model, an increase in one SD change in HOMA-IR was associated with a 43, 42, 75, and 92% increased risk of iIFG, iIGT, CGI, and DM, respectively. There was a positive correlation between the increase in HOMA-B and the incidence of iIGT; however, after adjusting the results for metabolic syndrome components, it was inversely correlated with the incidence of iIFG [Odds Ratio = 0.86(0.75–0.99)]. Conclusions HOMA-IR is positively correlated with diabetes and pre-diabetes subtypes’ incidence, and HOMA-B is inversely correlated with the incidence of iIFG but positively correlated with iIGT incidence. However, none of these alone is a good criterion for predicting diabetes and pre-diabetes.

IntroductionThe IraPEN program is an adapted version of the WHO-PEN program designed to prevent four major non-communicable diseases in Iran. This study aimed to determine the rate of compliance and related factors among individuals participating in the IraPEN program for the prevention of cardiovascular disease.MethodIn this study, compliance was defined as timely referral to the health center as scheduled, and the researchers approached four pilot sites of IraPEN from March 2016 to March 2018. Sex-stratified logistic regressions were applied to investigate factors related to compliance. However, it is important to note that in this study, compliance was defined as compliance to revisit, not compliance to taking prescribed medications or behavioral lifestyle changes.ResultsThe total compliance rate, including timely compliance and early and late compliance, was 16.5% in men and 23.3% in women. The study found that cardiovascular risk factors such as diabetes, hypertension, hypercholesterolemia, and being underweight were associated with lower compliance. The higher calculated risk of CVD was associated with higher compliance, but after adjusting for cardiovascular risk factors, high-risk individuals showed lower compliance. There was negligible interaction between sex and other factors for compliance.ConclusionThe compliance rate with scheduled programs for cardiovascular preventive strategies was very low, and high-risk individuals were less compliant, regardless of their high level of risk factors. The study recommends further training to increase awareness and knowledge regarding the IraPEN program and the prevention of non-communicable diseases among high-risk populations.

Abstract Background We aimed to assess the gender-specific impact of 3-year changes in fasting plasma glucose (FPG) status on the risk of all-cause, cardiovascular (CV), and cancer mortality in individuals without type 2 diabetes (T2DM) during an 18-year follow-up. Methods The study population included 14,378 participants aged 30–60 years (8272 women) from three population-based cohort studies, including Atherosclerosis Risk in Communities, Multi-Ethnic Study of Atherosclerosis, and Tehran Lipid and Glucose Study. Subjects were classified into six categories based on the approximately three-year changes in FPG status: (1) normal FPG (NFG) to NFG (reference category); (2) NFG to impaired fasting glucose (IFG) (i.e., 126 > FPG ≥ 100 mg/dl); (3) NFG to T2DM; (4) IFG to NFG; (5) IFG to IFG; (6) IFG to T2DM. Multivariable stratified Cox regression, adjusting for age, body mass index (BMI), BMI-Change, smoking status, hypertension, and hypercholesterolemia was used to estimate hazard ratios (HRs (95% CI)) for all-cause and cause-specific mortality events. Women-to-men ratios of HRs (RHRs) for each category were also estimated. Results During follow-up, 2,362 all-cause mortality events were recorded. Among women, all categories of FPG change, excluding IFG-NFG (HR, 95%CI 1.24 (0.98–1.57), p = 0.07), were associated with a higher risk of all-cause mortality compared to the NFG-NFG category. Moreover, women in IFG-T2DM group were at increased risk for CV mortality (2.21 (1.42–3.44)). We also found that women in NFG-IFG (1.52 (1.20–1.91)), NFG-T2DM (2.90 (1.52–5.51)), and IFG-IFG (1.30 (1.02–1.66)) categories had a higher risk for cancer mortality. However, among men, a higher risk of all-cause mortality was found for only two groups of NFG-T2DM (1.78 (1.15–2.74)) and IFG-T2DM (1.34 (1.04–1.72)). Women with IFG-IFG had a 24% higher risk for all-cause mortality events than their men counterparts (RHR; 1.24 (1.01–1.54)). After further adjustment for physical activity, results were in line with the main findings, excluding T2DM up to six years after the measurement period and early mortality events. Conclusion In women, the IFG status, whether as incident, persistent, or converted to T2DM, had a higher risk for mortality events; however, among men, only conversion to T2DM conferred an excess risk of all-cause mortality.

Objective To assess the relationship between glucose intolerance statuses at baseline defined as normal glucose tolerance (NGT), pre-diabetes, newly diagnosed (NDM) and known diabetes mellitus (KDM) and all-cause hospitalization among Iranian men and women during 20 years of follow-up.Research design and methods This study included 8,014 individuals (3,836 men) ≥30 years from the cohort of Tehran Lipid and Glucose Study. Incidence rate ratios (IRRs) and (95% confidence interval (95% CI) for three groups of pre-diabetes, NDM and KDM was estimated using the Negative Binomial regression model, considering NGT group as reference group. Regression models were adjusted for age, body mass index, hypertension, chronic kidney disease, and cardiovascular disease (CVD).Results Among men, compared with NGT group, those with pre-diabetes, NDM and KDM had higher incidence rate for hospitalization, with IRRs (95% CI) of 1.08 (0.96–1.20), 1.38 (1.20–1.57) and 1.96 (1.66–2.26), respectively, after adjusting for confounders. The corresponding values were 1.07 (0.96–1.17), 1.40 (1.21–1.59) and 2.07 (1.72–2.42) for women. Men with diabetes, generally had a higher rate of hospitalization for CVD rather than their female counterparts (IRRs: 1.46; 1.17–1.74). In patients with diabetes, the most common causes of hospitalization were macrovascular complications (i.e. coronary heart disease and stroke). Moreover, among the individuals with diabetes, those with poor glycaemic control (fasting plasma glucose (FPG) >10 mmol/l) had 39% higher rate of hospitalization than those with fair glycaemic control (FPG

Abstract Background Identifying patterns of variation in obesity indices and other cardiometabolic risk factors before the diagnosis of type 2 diabetes could provide insight into the critical period when drastic changes occurred and facilitate targeted interventions for the prevention of diabetes. Therefore, this study sought to explore patterns of change in obesity indices and other cardiometabolic risk factors before diabetes diagnosis. Methods We investigated 6305 participants (43.7% men) aged 20–65 from the Tehran Lipid and Glucose Study (TLGS) who were free of diabetes at baseline. First, we jointly estimated developmental multi-trajectories of obesity indices using multivariate latent class growth mixed model, and then patterns of cardiometabolic risk factors within the identified multi-trajectories were assessed using mixed-effects models. Results Three patterns of change in obesity indices were identified. Most participants belonged to the “progressing” group (83.4%; n = 742), with a slight but steadily rising in obesity indices until diagnosis in both men and women. All multi-trajectory groups showed similar exponential increases in fasting and 2-h plasma glucose concentrations 6 years before diagnosis and linear increases in blood pressure and total and LDL cholesterol throughout follow-up. Patterns of triglyceride and HDL cholesterol accompanied each group’s patterns of change in obesity indices. Conclusion Three patterns of the joint progression of obesity indices before diabetes diagnosis were accompanied by similar blood glucose patterns and other cardiometabolic risk factors. These findings suggest the impact of the increasing trend of obesity indices and other metabolic factors on the incidence of diabetes and emphasize the importance of assessing the metabolic risk factors at each visit.

Abstract Previous epidemiologic studies debated the association of body mass index (BMI) trends with cardiovascular disease and mortality. This study aimed to evaluate the association of BMI variability and slope with the incidence of Type 2 diabetes mellitus (T2DM) in a sex-stratified 15.8-year follow-up in the population-based Tehran Lipid and Glucose Study (TLGS). Of 10,911 individuals aged 20–60 years, 4981 subjects were included and followed for 15.8-years. The slope coefficient of BMI in the linear regression model represented individuals’ BMI trends up to the incidence of DM. The root mean squared error (RMSE) of the BMI linear trend was selected to reflect BMI variability through six follow-ups. Cox proportional hazards regression was used to investigate the association of the baseline BMI, BMI slope and RMSE with the incidence of T2DM among men and women. Multivariable-adjusted HRs of T2DM for each SD increment in BMI slope was 1.18 (95% CI: 0.94–1.48, p = 0.161) in normal weight men and 1.26 (95% CI: 1.10–1.44, p = 0.001) in overweight and obese men. However, in women, each SD increment in BMI slope increased the risk of T2DM with a HR of 1.19 (95% CI: 1.01–1.40, p = 0.039) in normal weight, and 1.14 (95% CI: 1.08–1.19, p

Abstract Background Several studies on various bariatric surgeries involving patients with type 2 diabetes mellitus (T2DM) showed an overall rate of remission of hyperglycemia. However, there is little known about predictive factors on remission after different types of surgeries. The aim of this study was to identify the T2DM remission rate and to determine the effects of preoperative factors characteristics of remission of type 2 diabetes in Iran. Methods We conducted a retrospective analysis of 1351 patients with T2DM operated by three different types of surgeries (Roux-en-Y gastric bypass (RYGB), sleeve gastrectomy (SG), and One Anastomosis Gastric Bypass (OAGB)). Diabetes remission was defined according to the American Diabetes Association (ADA) criteria. Binary logistic regression analyses were employed. Results A total of 1351 patients, 675 patients (50.0%) undergoing OAGB, 475 (35.2%) RYGB, and 201 (14.9%) SG. 80.6%, 84.2% of OAGB, 81.7%, 82.6% of RYGB, and 77.1%, 81.5% of SG participants were in T2DM remission after 1 and 3 years, respectively. 1- and 3-year remission were associated with preoperative age, duration of T2DM, FBS and HbA1c, BMI, insulin therapy, and a family history of obesity (p

Background Recent evidence recommended stepwise screening methods for identifying individuals at high risk of type 2 diabetes to be recruited in the lifestyle intervention programs for the prevention of the disease. This study aims to assess the performance of different stepwise screening methods that combine non-invasive measurements with lab-based measurements for identifying those with 5-years incident type 2 diabetes. Methods 3037 participants aged ≥30 years without diabetes at baseline in the Tehran Lipid and Glucose Study (TLGS) were followed. Thirty-two stepwise screening methods were developed by combining a non-invasive measurement (an anthropometric measurement (waist-to-height ratio, WtHR) or a score based on a non-invasive risk score [Australian Type 2 Diabetes Risk Assessment Tool, AUSDRISK]) with a lab-based measurement (different cut-offs of fasting plasma glucose [FPG] or predicted risk based on three lab-based prediction models [Saint Antonio, SA; Framingham Offspring Study, FOS; and the Atherosclerosis Risk in Communities, ARIC]). The validation, calibration, and usefulness of lab-based prediction models were assessed before developing the stepwise screening methods. Cut-offs were derived either based on previous studies or decision-curve analyses. Results 203 participants developed diabetes in 5 years. Lab-based risk prediction models had good discrimination power (area under the curves [AUCs]: 0.80-0.83), achieved acceptable calibration and net benefits after recalibration for population’s characteristics and were useful in a wide range of risk thresholds (5%-21%). Different stepwise methods had sensitivity ranged 20%-68%, specificity 70%-98%, and positive predictive value (PPV) 14%-46%; they identified 3%-33% of the screened population eligible for preventive interventions. Conclusion Stepwise methods have acceptable performance in identifying those at high risk of incident type 2 diabetes.

Objective This study aimed to propose a data-driven framework for classification of at-risk people for cardiovascular outcomes regarding obesity and metabolic syndrome.Design A population-based prospective cohort study with a long-term follow-up.Setting Data from the Tehran Lipid and Glucose Study (TLGS) were interrogated.Participants 12 808 participants of the TLGS cohort, aged ≥20 years who have followed for over 15 years were assessed.Main outcome measures Data for 12 808 participants, aged ≥20 years who have followed for over 15 years, collected through TLGS as a prospective, population-based cohort study, were analysed. Feature engineering followed by hierarchical clustering was used to determine meaningful clusters and novel endophenotypes. Cox regression was used to demonstrate the clinical validity of phenomapping. The performance of endophenotype compared with traditional classifications was evaluated by the value of Akaike information criterion/Bayesian information criterion. R software V.4.2 was employed.Results The mean age was 42.1±14.9 years, 56.2% were female, 13.1%, 2.8% and 6.2% had experienced cardiovascular disease (CVD), CVD mortality and hard CVD, respectively. Low-risk cluster compared with the high risk had significant difference in age, body mass index, waist-to-hip ratio, 2 hours post load plasma glucose, triglyceride, triglycerides to high density lipoprotein ratio, education, marital status, smoking and the presence of metabolic syndrome. Eight distinct endophenotypes were detected with significantly different clinical characteristics and outcomes.Conclusion Phenomapping resulted in a novel classification of population with cardiovascular outcomes, which can, better, stratify individuals into homogeneous subclasses for prevention and intervention as an alternative of traditional methods solely based on either obesity or metabolic status. These findings have important clinical implications for a particular part of the Middle Eastern population for which it is a common practice to use tools/evidence derived from western populations with substantially different backgrounds and risk profiles.

ObjectivesThe aim of the study was to investigate the effect of treatment on pregnancy outcomes among women who had fasting plasma glucose (FPG) 5.1-5.6 mmol/l in the first trimester of pregnancy.MethodsWe performed a secondary-analysis of a randomized community non-inferiority trial of gestational diabetes mellitus (GDM) screening. All pregnant women with FPG values range 5.1-5.6 mmol/l in the first trimester of gestation were included in the present study (n=3297) and classified to either the (i) intervention group who received treatment for GDM along with usual prenatal care (n=1,198), (ii) control group who received usual-prenatal-care (n=2,099). Macrosomia/large for gestational age (LGA) and primary cesarean-section (C-S) were considered as primary-outcomes. A modified-Poisson-regression for binary outcome data with a log link function and robust error variance was used to RR (95%CI) for the associations between GDM status and incidence of pregnancy outcomes.ResultsThe mean maternal age and BMI of pregnant women in both study groups were similar. There were no statistically significant differences in the adjusted risks of adverse pregnancy outcomes, including macrosomia, primary C-S, preterm birth, hyperbilirubinemia, preeclampsia, NICU-admission, birth trauma, and LBW both groups.ConclusionsIt is found that treating women with first-trimester FPG values of 5.1-5.6 mmol/l could not improve adverse pregnancy outcomes including macrosomia, Primary C-S, Preterm birth, hypoglycemia, hypocalcemia, preeclampsia, NICU admission, Birth trauma and LBW. Therefore, extrapolating the FPG cut-off point of the second trimester to the first –which has been proposed by the IADPSG, might therefore not be appropriate.Clinical Trial Registrationhttps://www.irct.ir/trial/518, identifier IRCT138707081281N1.

Background: As a surrogate for all relevant risk factors, it is preferable to show trends in the mean cardiovascular disease(CVD) risk rather than to examine each risk factor trend separately. Objective(s): Using national representative data, this study aimed to determine the changes in the World Health Organization (WHO) CVD risk during the last decade considering both laboratory and non-laboratory risk scoring. Methods: We used data from five rounds of the WHO STEPwise approach to surveillance surveys (2007–2016). In all, 62,076 (31,660 women) participants aged 40–65 years were included and their absolute CVD risk were calculated. The generalized linear model was performed to assess the trend of CVD risk in men and women, and also in diabetic and non-diabetic individuals. Results: We showed significant declining trends in the mean CVD risk in the laboratory (from 10.5% to 8.8%) and non-laboratory (10.1% to 9.4%) models in men. In women, a significant reduction was observed in the laboratory-based model (from 8.4% to 7.8%). The laboratory model showed a greater decrease in men than women (P-for interaction < 0.001) and in diabetic patients (from 16.1% to 13.6%) than non-diabetic individuals (from 8.2% to 7%) (p-for interaction = 0.002). The proportion of high-risk individuals (risk ≥ 10%) decreased from 40% in 2007 to 31.5% in 2016 in men and from 29.8% to 26.1% in women based on the laboratory-model. Conclusions: During the last decade, CVD risk had a significant decrease in men and women. The reduction was more evident in men and diabetic population. However, still, one-third of our population is considered high-risk.

BackgroundIraPEN, a program developed in Iran based on the World Health Organization (WHO) package of essential noncommunicable (PEN) disease interventions for primary healthcare, was launched in 2015. Preventive interventions for cardiovascular diseases (CVDs) are based on the level of risk calculated using the WHO CVD risk chart.ObjectiveThe main objective of this study was to measure the potential cost-effectiveness (CE) of IraPEN preventive actions for CVD in comparison with the status quo.MethodsA CE analysis from a healthcare perspective was conducted. Markov models were employed for individuals with and without diabetes separately. Based on the WHO CVD risk chart, four index cohorts were constructed as low (

We aimed to review the validity of existing prediction models for cardiovascular diseases (CVDs) in Asia. In this systematic review and meta-analysis, we included studies that validated prediction models for CVD risk in the general population in Asia. Various databases, including PubMed, Web of Science conference proceedings citation index, Scopus, Global Index Medicus of the World Health Organization (WHO), and Open Access Thesis and Dissertations (OATD), were searched up to November 2022. Additional studies were identified through reference lists and related reviews. The risk of bias was assessed using the PROBAST prediction model risk of bias assessment tool. Meta-analyses were performed using the random effects model, focusing on the C-statistic as a discrimination index and the observed-to-expected ratio (OE) as a calibration index. Out of 1315 initial records, 16 studies were included, with 21 external validations of six models in Asia. The validated models consisted of Framingham models, pooled cohort equations (PCEs), SCORE, Globorisk, and WHO models, combined with the results of the first four models. The pooled C-statistic for men ranged from 0.72 (95% CI 0.70 to 0.75; PCEs) to 0.76 (95% CI 0.74 to 0.78; Framingham general CVD). In women, it varied from 0.74 (95% CI 0.22 to 0.97; SCORE) to 0.79 (95% CI 0.74 to 0.83; Framingham general CVD). The pooled OE ratio for men ranged from 0.21 (95% CI 0.018 to 2.49; Framingham CHD) to 1.11 (95%CI 0.65 to 1.89; PCEs). In women, it varied from 0.28 (95%CI 0.33 to 2.33; Framingham CHD) to 1.81 (95% CI 0.90 to 3.64; PCEs). The Framingham, PCEs, and SCORE models exhibited acceptable discrimination but poor calibration in predicting the 10-year risk of CVDs in Asia. Recalibration and updates are necessary before implementing these models in the region.

Background: Previous studies have shown that spiritual experience may reduce cardiovascular disease (CVDs). However, little is known about the relationship between spiritual health and the gender-specific risk of CVDs in communities with different cultures. Methods: A total of 3249 individuals (53.7% female, 75.0% middle-aged) participated in the Tehran Lipid and Glucose Study (TLGS) from 2015 to 2017 were included. Based on the ACC/AHA pooled cohort equation, CVD risk over ten years was examined. Spiritual health was measured using a developed tool for measuring spiritual health in Muslim populations (SHIMA-48). Linear regression models were used to assess the association between spiritual health and ACC/AHA risk scores. The natural logarithm scale was calculated to consider the normal distribution hypothesis of the regression model. Results: The current results suggest a slight but significant increase in the mean of spiritual health in women compared to men in both cognitive/emotional and behavioral dimensions (P < 0.001). In both sexes, a higher prevalence of smoking was observed in participants with lower levels of spiritual health (P < 0.004). In men, compared to those with a low level of spiritual health (the first tertile), the logarithm of the ACC-AHA risk score was reduced by 0.11 (P = 0.004) and 0.18 (P < 0.001) for those in the second and third tertiles of spiritual health, respectively. This result may be attributed to higher cigarette smoking among the latter group. Similar results were not observed in women. Conclusions: Current results indicate a gender-specific association between spiritual health and cardiovascular disease risk. Our findings imply that promoting spiritual health can be considered an effective strategy in future preventive interventions, primarily by controlling the desire to smoke in men.

BackgroundIran is one of the first few countries that was hit hard with the coronavirus disease 2019 (COVID-19) pandemic. We aimed to estimate the total number of COVID-19 related infections, deaths, and hospitalizations in Iran under different physical distancing and isolation scenarios.MethodsWe developed a susceptible-exposed-infected/infectious-recovered/removed (SEIR) model, parameterized to the COVID-19 pandemic in Iran. We used the model to quantify the magnitude of the outbreak in Iran and assess the effectiveness of isolation and physical distancing under five different scenarios (A: 0% isolation, through E: 40% isolation of all infected cases). We used Monte-Carlo simulation to calculate the 95% uncertainty intervals (UIs). ResultsUnder scenario A, we estimated 5 196 000 (UI 1 753 000-10 220 000) infections to happen till mid-June with 966 000 (UI 467 800-1 702 000) hospitalizations and 111 000 (UI 53 400-200 000) deaths. Successful implantation of scenario E would reduce the number of infections by 90% (ie, 550 000) and change the epidemic peak from 66 000 on June 9, to 9400 on March 1, 2020. Scenario E also reduces the hospitalizations by 92% (ie, 74 500), and deaths by 93% (ie, 7800).ConclusionWith no approved vaccination or therapy available, we found physical distancing and isolation that include public awareness and case-finding and isolation of 40% of infected people could reduce the burden of COVID-19 in Iran by 90% by mid-June.

Abstract Background Assessing the risk of cardiovascular disease (CVD) is crucial in preventive cardiology. We aimed to determine the trend of CVD risk among individuals with and without diabetes during two decades of follow-up in a Middle Eastern cohort. Methods We studied 8,450 individuals (55.5% women) aged 40–75 years who participated in the Tehran Lipid and Glucose Study (TLGS). Diabetes status and CVD risk factors were evaluated in six examinations from 1999 to 2018. The individual 10-year CVD risk score was calculated using the ACC/AHA recommended risk equation. We used generalized estimating equation models (GEE) to assess the time trends of CVD risk factors and CVD risk scores in diabetic and non-diabetic groups separately. Results The age-adjusted ACC/AHA risk score significantly decreased in non-diabetic women and men (from 3.2% to 1.6% in women and 6.8% to 5.0% in men; p for trend

BackgroundConsidering the importance of cardiovascular disease (CVD) risk prediction for healthcare systems and the limited information available in the Middle East, we evaluated the SCORE and Globorisk models to predict CVD death in a country of this region.MethodsWe included 24 427 participants (11 187 men) aged 40-80 years from four population-based cohorts in Iran. Updating approaches were used to recalibrate the baseline survival and the overall effect of the predictors of the models. We assessed the models’ discrimination using C-index and then compared the observed with the predicted risk of death using calibration plots. The sensitivity and specificity of the models were estimated at the risk thresholds of 3%, 5%, 7%, and 10%. An agreement between models was assessed using the intra-class correlation coefficient (ICC). We applied decision analysis to provide perception into the consequences of using the models in general practice; for this reason, the clinical usefulness of the models was assessed using the net benefit (NB) and decision curve analysis. The NB is a sensitivity penalized by a weighted false positive (FP) rate in population level.ResultsAfter 154 522 person-years of follow-up, 437 cardiovascular deaths (280 men) occurred. The 10-year observed risks were 4.2% (95% CI: 3.7%-4.8%) in men and 2.1% (1.8-2%.5%) in women. The c-index for SCORE function was 0.784 (0.756-0.812) in men and 0.780 (0.744-0.815) in women. Corresponding values for Globorisk were 0.793 (0.766-0.820) and 0.793 (0.757-0.829). The deviation of the calibration slopes from one reflected a need for recalibration; after which, the predicted-to-observed ratio for both models was 1.02 in men and 0.95 in women. Models showed good agreement (ICC 0.93 in men, and 0.89 in women). Decision curve showed that using both models results in the same clinical usefulness at the risk threshold of 5%, in both men and women; however, at the risk threshold of 10%, Globorisk had better clinical usefulness in women (Difference: 8%, 95% CI: 4%-13%).ConclusionOriginal Globorisk and SCORE models overestimate the CVD risk in Iranian populations resulting in a high number of people who need intervention. Recalibration could adopt these models to precisely predict CVD mortality. Globorisk showed better performance clinically, only among high-risk women.

Abstract Background Early detection and prediction of type two diabetes mellitus incidence by baseline measurements could reduce associated complications in the future. The low incidence rate of diabetes in comparison with non-diabetes makes accurate prediction of minority diabetes class more challenging. Methods Deep neural network (DNN), extremely gradient boosting (XGBoost), and random forest (RF) performance is compared in predicting minority diabetes class in Tehran Lipid and Glucose Study (TLGS) cohort data. The impact of changing threshold, cost-sensitive learning, over and under-sampling strategies as solutions to class imbalance have been compared in improving algorithms performance. Results DNN with the highest accuracy in predicting diabetes, 54.8%, outperformed XGBoost and RF in terms of AUROC, g-mean, and f1-measure in original imbalanced data. Changing threshold based on the maximum of f1-measure improved performance in g-mean, and f1-measure in three algorithms. Repeated edited nearest neighbors (RENN) under-sampling in DNN and cost-sensitive learning in tree-based algorithms were the best solutions to tackle the imbalance issue. RENN increased ROC and Precision-Recall AUCs, g-mean and f1-measure from 0.857, 0.603, 0.713, 0.575 to 0.862, 0.608, 0.773, 0.583, respectively in DNN. Weighing improved g-mean and f1-measure from 0.667, 0.554 to 0.776, 0.588 in XGBoost, and from 0.659, 0.543 to 0.775, 0.566 in RF, respectively. Also, ROC and Precision-Recall AUCs in RF increased from 0.840, 0.578 to 0.846, 0.591, respectively. Conclusion G-mean experienced the most increase by all imbalance solutions. Weighing and changing threshold as efficient strategies, in comparison with resampling methods are faster solutions to handle class imbalance. Among sampling strategies, under-sampling methods had better performance than others.

Abstract Aims/Introduction To examine the incidence rate of severe non‐proliferative and proliferative diabetic retinopathy (severe‐NPDR/PDR) and determine its potential risk factors. Materials and Methods The study consisted of 1,169 participants (675 women) with type 2 diabetes mellitus, aged ≥20 years. A trained interviewer collected information about the history of pan‐retinal photocoagulation as a result of diabetic retinopathy. Multivariable Cox proportional hazards regression models were applied. Results We found 187 cases (126 women) of severe‐NPDR/PDR during a median follow‐up period of 12.7 years; the corresponding incidence rate was 13.6 per 1,000 person‐years. Being overweight (hazard ratio [HR], 95% confidence interval [CI] 0.60, 0.39–0.92) and obese (HR 0.48, 95% CI 0.27–0.83) were associated with lower risk, whereas being smoker (HR 1.75, 95% CI 1.12–2.74), having fasting plasma glucose levels 7.22–10.0 mmol/L (HR 2.81, 95% CI 1.70–4.62), fasting plasma glucose ≥10 mmol/L (HR 5.87, 95% CI 3.67–9.41), taking glucose‐lowering medications (HR 2.58, 95% CI 1.87–3.56), prehypertension status (HR 1.65, 95% CI 1.05–2.58) and newly diagnosed hypertension (HR 1.96, 95% CI 1.06–3.65) increased the risk of severe‐NPDR/PDR. Among newly diagnosed diabetes patients, being male was associated with a 59% lower risk of severe‐NPDR/PDR (HR 0.41, 95% CI 0.21–0.79). Furthermore, patients who had an intermediate level of education (6–12 years) had a higher risk of developing PDR (HR 1.86, 95% CI 1.05–3.30) compared with those who had

Abstract Background Studies on knowledge, attitude, and practice (KAP) can be valuable for public health to help to develop targeted educational programs and assess the effectiveness of intervention programs. The purpose of this study was to develop and examine the validity and reliability of a questionnaire on knowledge, attitude, and practice (KAP) regarding cardiovascular diseases (CVDs), their risk factors, and symptoms among an Iranian general population. Methods This cross-sectional study was conducted on an Iranian population older than 20 years referred to some of Tehran’s healthcare centers. An initial 62-item questionnaire was developed, and the face, content, and construct validities were assessed. Results In all, 300 adults with a mean age (SD) of 39.79 (12.1) years participated in this study. Based on the results of the content validity, a questionnaire with 30 essential items was designed. Exploratory factor analysis suggested a four-factor subscale with 29 finalized items (CVD-KAP29), and acceptable goodness of fit indices was demonstrated by confirmatory factor analysis. The Cronbach’s alpha and McDonald’s ω coefficients were higher than 0.60 for all domains except the nutrition and smoking subscales. Conclusions Results provided evidence of the validity of the CVD-KAP29 for KAP studies for cardiovascular diseases in the general population.

Abstract Background Markov system dynamic (MSD) model has rarely been used in medical studies. The aim of this study was to evaluate the performance of MSD model in prediction of metabolic syndrome (MetS) natural history. Methods Data gathered by Tehran Lipid & Glucose Study (TLGS) over a 16-year period from a cohort of 12,882 people was used to conduct the analyses. First, transition probabilities (TPs) between 12 components of MetS by Markov as well as control and failure rates of relevant interventions were calculated. Then, the risk of developing each component by 2036 was predicted once by a Markov model and then by a MSD model. Finally, the two models were validated and compared to assess their performance and advantages by using mean differences, mean SE of matrices, fit of the graphs, and Kolmogorov-Smirnov two-sample test as well as R2 index as model fitting index. Results Both Markov and MSD models were shown to be adequate for prediction of MetS trends. But the MSD model predictions were closer to the real trends when comparing the output graphs. The MSD model was also, comparatively speaking, more successful in the assessment of mean differences (less overestimation) and SE of the general matrix. Moreover, the Kolmogorov-Smirnov two-sample showed that the MSD model produced equal distributions of real and predicted samples (p = 0.808 for MSD model and p = 0.023 for Markov model). Finally, R2 for the MSD model was higher than Markov model (73% for the Markov model and 85% for the MSD model). Conclusion The MSD model showed a more realistic natural history than the Markov model which highlights the importance of paying attention to this method in therapeutic and preventive procedures.

Background: This study assesses the effect of blood lipid indices and lipid ratios on cardiovascular diseases (CVDs) using inverse probability-of-exposure weighted estimation of marginal structural models (MSMs). Methods: A pooled dataset of two US representative cohort studies, including 16736 participants aged 42–84 years with complete information at baseline, was used. The effect of each lipid index, including low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglyceride (TG), ratios of TC/HDL-C, LDL-C/HDL-C, and TG/HDL-C on coronary heart disease (CHD) and stroke were estimated using weighted Cox regression. Results: There were 1638 cases of CHD and 1017 cases of stroke during a median follow-up of 17.1 years (interquartile range: 8.5 to 25.7). Compared to optimal levels, the risk of CVD outcomes increased substantially in high levels of TC, LDL-C, TC/HDL-C, and LDL-C/HDL-C. If everyone had always had high levels of TC (≥240 mg/dL), risk of CHD would have been 2.15 times higher, and risk of stroke 1.35 times higher than if they had always had optimal levels (

IntroductionStudies found that the impact of dysglycemia on microvascular, macrovascular events and mortality outcomes were different between the younger vs. older population. We aimed to investigate the age-specific association of prediabetes with clinical outcomes including type 2 diabetes (T2DM), hypertension, chronic kidney disease (CKD), cardiovascular disease (CVD), and mortality.Materials and methodsA total of 5,970 Iranians (3,829 women) aged ≥30 years, without T2DM, were included. The age-specific (

BackgroundWe aimed to determine the predictors of regression to normoglycemia and progression to diabetes among subjects with pre-diabetes in a single model concurrently.MethodsThe present study included 1329 participants aged 20 to 70 years with prediabetes from the population-based cohort of the Tehran Lipid and Glucose Study, with a 10-year follow-up. Glycemic status at follow-up was categorized as regression to normoglycemia: fasting plasma glucose [FPG] of

Abstract Background Regarding the inconclusive results of previous investigations, this study aimed to determine the association between pathology, as a possible predictor, with remission outcomes, to know the role of pathology in the personalized decision making in acromegaly patients. Methods A retrospective cohort study was performed on the consecutive surgeries for growth hormone (GH) producing pituitary adenomas from February 2015 to January 2021. Seventy-one patients were assessed for granulation patterns and prolactin co-expression as dual staining adenomas. The role of pathology and some other predictors on surgical remission was evaluated using logistic regression models. Results Among 71 included patients, 34 (47.9%) patients had densely granulated (DG), 14 (19.7%) had sparsely granulated (SG), 23 (32.4%) had dual staining pituitary adenomas. The remission rate was about 62.5% in the patients with SG and DG adenomas named single staining and 52.2% in dual staining groups. Postoperative remission was 1.53-folds higher in the single staining adenomas than dual staining-one (non-significant). The remission rate was doubled in DG group compared to two other groups (non-significant). By adjusting different predictors, cavernous sinus invasion and one-day postoperative GH levels decreased remission rate by 91% (95% CI: 0.01–0.67; p = 0.015) and 64% (95% CI: 0.19–0.69; p

Abstract Background Cardiovascular diseases (CVDs) are among the most common causes of death worldwide, including in Iran. Considering the adverse effects of CVDs on physical and psychosocial health; this study aims to investigate the association between experience of CVDs and health-related quality of life (HRQoL) in adult participants of the Tehran Lipid and Glucose Study (TLGS). Methods The participants of this cross-sectional study were 7009 adults (≥ 20 years) who participated in the TLGS during 2014–2017. Demographic information and HRQoL data was collected through validated questionnaires by trained interviewers. HRQoL was assessed by the Iranian version of the SF-12 questionnaire. Data was analyzed using the SPSS software. Results The mean age of participants was 46.8 ± 14.6 years and 46.1% of them were men. A total of 9.0% of men and 4.4% of women had CVDs. In men, the mean physical HRQoL summary score was significantly lower in those with CVDs compared to those without CVDs (46.6 ± 0.8 vs. 48.5 ± 0.7, p > 0.001). In women, the mean mental HRQoL summary scores was significantly lower in those with CVDs compared to those without CVDs (42.8 ± 1.0 vs. 45.2 ± 0.5, p = 0.009). In adjusted models, men with CVDs were more likely to report poor physical HRQoL compared to men without CVDs (OR(95%CI): 1.93(1.32–2.84), p = 0.001); whereas for women, the chance of reporting poor mental HRQoL was 68% higher in those with CVDs than those without CVDs (OR(95%CI): 1.68(1.11–2.54), p = 0.015). Conclusion The findings of the current study indicate poorer HRQoL in those who experienced CVDs compared to their healthy counterparts with a sex specific pattern. While for men, CVDs were associated with more significant impairment in the physical dimension of HRQoL, women experienced a similar impairment in the mental dimension of HRQoL.

Abstract Background Despite strong evidence demonstrating the role of estrogen as a protective factor for kidney function in women, limited data are available regarding the influence of endogenous estrogen exposure (EEE) on chronic kidney disease (CKD). The present study aimed to assess the incidence of CKD in women with various levels of EEE. Methods In a prospective population-based study over a 15-year follow-up, a total of 3043 eligible women aged 30–70 years, participating in Tehran-Lipid and Glucose-Study were recruited and divided into two groups (EEE

Abstract Background Non-participation in cohort studies, if associated with both the exposure and occurrence of the event, can introduce bias in the estimates of interest. This study aims to identify factors associated with follow-up participation in Tehran Lipid and Glucose Study, a large-scale community-based prospective study in West Asia. Methods A sample of 10,368 adults from TLGS was included in the analysis. All analyses were split according to sex and age groups (20–39, 40–59, and 60 years). The associations between socio-demographic, health, and lifestyle factors with response rate were identified using the Generalized Estimating Equations model. Results Over the median of 15.7 years of follow up the response rate was 64.5%. The highest response rate was observed in those aged 40–59 years for both sexes. Current smokers had lower odds of response in both sexes for all age groups, ranging from 0.51 to 0.74, p

Abstract Sudden cardiac death (SCD) is described as death within one hour, if observed, from the onset of symptoms, and within 24 h of being alive and well if not observe. Study population includes 3705 men and 4446 women, aged ≥ 30 years. Multivariable Cox proportional hazard models were used to determine the risk factors associated with SCD. After a median follow-up of 17.9 years, 244 SCD (165 in males) occurred. The age-standardized incidence rate (95% confidence intervals (CI)) of SCD was 2.3 (2.1–2.7) per 1000 person-year. Current smoking [Hazard ratio (HR): 2.43, 95% CI: 1.73–3.42], high waist circumference [1.49: 1.04–2.12], hypertension [1.39: 1.05–1.84], type 2 diabetes mellitus [2.78: 2.09–3.69], pulse rate ≥ 90 beats per/minute [1.72: 1.22–2.42] and prevalent cardiovascular disease [1.75: 1.26–2.45] were significant risk factors. The corresponding population attributed fractions (PAF) were 14.30, 16.58, 14.03, 19.60, 7.62, and 8.30, respectively. Being overweight [0.58: 0.40–0.83] and obese [0.61: 0.38–0.98] decreased the risk of SCD. After excluding known diabetes cases from our data analysis, the newly diagnosed diabetes still showed an HR of 2.0 (1.32–3.00) with a PAF of 7.15% in the full adjustment model. To deal with sudden death as a catastrophic outcome, multi-component strategies by policy health makers are suggested.

Abstract Background Understanding the distinct patterns (trajectories) of variation in blood lipid levels before diagnosing cardiovascular disease (CVD) might carry important implications for improving disease prevention or treatment. Methods We investigated 14,373 participants (45.5% men) aged 45–84 from two large US prospective cohort studies with a median of 23 years follow-up. First, we jointly estimated developmental trajectories of lipid indices, including low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) concentrations using group-based multi-trajectory modeling. Then, the association of identified multi-trajectories with incident CVD, heart failure, and all-cause mortality were examined using Cox proportional hazard model. Results Seven distinct multi-trajectories were identified. The majority of participants (approximately 80%) exhibited decreasing LDL-C but rising TG levels and relatively stable HDL-C levels. Compared to the individuals with healthy and stable LDL-C, HDL-C, and TG levels, those in other groups were at significant risk of incident CVD after adjusting for other conventional risk factors. Individuals with the highest but decreasing LDL-C and borderline high and rising TG levels over time were at the highest risk than those in other groups with a 2.22-fold risk of CVD. Also, those with the highest and increased triglyceride levels over time, over optimal and decreasing LDL-C levels, and the lowest HDL-C profile had a nearly 1.84 times CVD risk. Even individuals in the multi-trajectory group with the highest HDL-C, optimal LDL-C, and optimal TG levels had a significant risk (HR, 1.45; 95% CI 1.02–2.08). Furthermore, only those with the highest HDL-C profile increased the risk of heart failure by 1.5-fold (95% CI 1.07–2.06). Conclusions The trajectories and risk of CVD identified in this study demonstrated that despite a decline in LDL-C over time, a significant amount of residual risk for CVD remains. These findings suggest the impact of the increasing trend of TG on CVD risk and emphasize the importance of assessing the lipid levels at each visit and undertaking potential interventions that lower triglyceride concentrations to reduce the residual risk of CVD, even among those with the optimal LDL-C level.