A point-score system superior to blood pressure measures alone for predicting incident hypertension: Tehran Lipid and Glucose Study

Hypertension and its determinants in Abu Dhabi population: a retrospective cohort study

BACKGROUND

Preventing high blood pressure and its complications requires identifying its risk factors. This study assessed predictors of hypertension and its associated complications among Emirati adults in Abu Dhabi, United Arab Emirates (UAE).

METHODS

This retrospective cohort study was conducted by retrieving data from the Electronic Medical Records (EMR) of Emiratis who participated in a national cardiovascular screening program between 2011 and 2013. The study cohort comprised 8456 Emirati adults (18 years and above): 4095 women and 4361 men. The average follow-up period was 9.2 years, with a maximum of 12 years.

RESULTS

The age-adjusted hypertension prevalence in Abu Dhabi increased from 24.5% at baseline to 35.2% in 2023. At baseline, 61.8% of hypertensive patients had controlled blood pressure, which increased to 74.3% in 2023. Among those free from hypertension at screening, 835 patients (12.3%) were newly diagnosed during the follow-up period. Using Cox regression, the hypertension prediction model developed included age [P value <0.001, hazard ratio 1.051, 95% confidence interval (CI) 1.046-1.056], SBP (P value <0.001, hazard ratio 1.017, 95% CI 1.011-1.023) and DBP (P value <0.001, hazard ratio 1.029, 95% CI 1.02-1.037), glycated hemoglobin (P < 0.001, hazard ratio 1.132, 95% CI 1.077-1.191), and high-density lipoprotein cholesterol (HDL-C) (P value <0.001, hazard ratio 0.662, 95% CI 0.526-0.832). This prediction model had a c-statistic of 0.803 (95% CI 0.786-0.819). Using survival analysis (Kaplan-Meier), higher blood pressure was associated with more cardiovascular events and mortality during follow-up.

CONCLUSION

Targeting population-specific predictors of hypertension can prevent its progression and inform healthcare professionals and policymakers to decrease the incidence, complications, and mortality related to hypertension.

Prognostic risk models for incident hypertension: A PRISMA systematic review and meta-analysis

OBJECTIVE

Our goal was to review the available literature on prognostic risk prediction for incident hypertension, synthesize performance, and provide suggestions for future work on the topic.

METHODS

A systematic search on PUBMED and Web of Science databases was conducted for studies on prognostic risk prediction models for incident hypertension in generally healthy individuals. Study-quality was assessed using the Prediction model Risk of Bias Assessment Tool (PROBAST) checklist. Three-level meta-analyses were used to obtain pooled AUC/C-statistic estimates. Heterogeneity was explored using study and cohort characteristics in meta-regressions.

RESULTS

From 5090 hits, we found 53 eligible studies, and included 47 in meta-analyses. Only four studies were assessed to have results with low risk of bias. Few models had been externally validated, with only the Framingham risk model validated more than thrice. The pooled AUC/C-statistics were 0.82 (0.77-0.86) for machine learning models and 0.78 (0.76-0.80) for traditional models, with high heterogeneity in both groups (I2 > 99%). Intra-class correlations within studies were 60% and 90%, respectively. Follow-up time (P = 0.0405) was significant for ML models and age (P = 0.0271) for traditional models in explaining heterogeneity. Validations of the Framingham risk model had high heterogeneity (I2 > 99%).

CONCLUSION

Overall, the quality of included studies was assessed as poor. AUC/C-statistic were mostly acceptable or good, and higher for ML models than traditional models. High heterogeneity implies large variability in the performance of new risk models. Further, large heterogeneity in validations of the Framingham risk model indicate variability in model performance on new populations. To enable researchers to assess hypertension risk models, we encourage adherence to existing guidelines for reporting and developing risk models, specifically reporting appropriate performance measures. Further, we recommend a stronger focus on validation of models by considering reasonable baseline models and performing external validations of existing models. Hence, developed risk models must be made available for external researchers.

Development of risk models of incident hypertension using machine learning on the HUNT study data

In this study, we aimed to create an 11-year hypertension risk prediction model using data from the Trøndelag Health (HUNT) Study in Norway, involving 17 852 individuals (20-85 years; 38% male; 24% incidence rate) with blood pressure (BP) below the hypertension threshold at baseline (1995-1997). We assessed 18 clinical, behavioral, and socioeconomic features, employing machine learning models such as eXtreme Gradient Boosting (XGBoost), Elastic regression, K-Nearest Neighbor, Support Vector Machines (SVM) and Random Forest. For comparison, we used logistic regression and a decision rule as reference models and validated six external models, with focus on the Framingham risk model. The top-performing models consistently included XGBoost, Elastic regression and SVM. These models efficiently identified hypertension risk, even among individuals with optimal baseline BP (< 120/80 mmHg), although improvement over reference models was modest. The recalibrated Framingham risk model outperformed the reference models, approaching the best-performing ML models. Important features included age, systolic and diastolic BP, body mass index, height, and family history of hypertension. In conclusion, our study demonstrated that linear effects sufficed for a well-performing model. The best models efficiently predicted hypertension risk, even among those with optimal or normal baseline BP, using few features. The recalibrated Framingham risk model proved effective in our cohort.

Risk Assessment Score and Chi-Square Automatic Interaction Detection Algorithm for Hypertension Among Africans: Models From the SIREN Study

BACKGROUND

This study aimed to develop a risk-scoring model for hypertension among Africans.

METHODS

In this study, 4413 stroke-free controls were used to develop the risk-scoring model for hypertension. Logistic regression models were applied to 13 risk factors. We randomly split the dataset into training and testing data at a ratio of 80:20. Constant and standardized weights were assigned to factors significantly associated with hypertension in the regression model to develop a probability risk score on a scale of 0 to 1 using a logistic regression model. The model accuracy was assessed to estimate the cutoff score for discriminating hypertensives.

RESULTS

Mean age was 59.9±13.3 years, 56.0% were hypertensives, and 8 factors, including diabetes, age ≥65 years, higher waist circumference, (BMI) ≥30 kg/m2, lack of formal education, living in urban residence, family history of cardiovascular diseases, and dyslipidemia use were associated with hypertension. Cohen κ was maximal at ≥0.28, and a total probability risk score of ≥0.60 was adopted for both statistical weighting for risk quantification of hypertension in both datasets. The probability risk score presented a good performance-receiver operating characteristic: 64% (95% CI, 61.0-68.0), a sensitivity of 55.1%, specificity of 71.5%, positive predicted value of 70.9%, and negative predicted value of 55.8%, in the test dataset. Similarly, decision tree had a predictive accuracy of 67.7% (95% CI, 66.1-69.3) for the training set and 64.6% (95% CI, 61.0-68.0) for the testing dataset.

CONCLUSIONS

The novel risk-scoring model discriminated hypertensives with good accuracy and will be helpful in the early identification of community-based Africans vulnerable to hypertension for its primary prevention.

Differential diagnosis of secondary hypertension based on deep learning

Secondary hypertension is associated with higher risks of target organ damage and cardiovascular and cerebrovascular disease events. Early aetiology identification can eliminate aetiologies and control blood pressure. However, inexperienced doctors often fail to diagnose secondary hypertension, and comprehensively screening for all causes of high blood pressure increases health care costs. To date, deep learning has rarely been involved in the differential diagnosis of secondary hypertension. Relevant machine learning methods cannot combine textual information such as chief complaints with numerical information such as the laboratory examination results in electronic health records (EHRs), and the use of all features increases health care costs. To reduce redundant examinations and accurately identify secondary hypertension, we propose a two-stage framework that follows clinical procedures. The framework carries out an initial diagnosis process in the first stage, on which basis patients are recommended for disease-related examinations, followed by differential diagnoses of different diseases based on the different characteristics observed in the second stage. We convert the numerical examination results into descriptive sentences, thus blending textual and numerical characteristics. Medical guidelines are introduced through label embedding and attention mechanisms to obtain interactive features. Our model was trained and evaluated using a cross-sectional dataset containing 11,961 patients with hypertension from January 2013 to December 2019. The F1 scores of our model were 0.912, 0.921, 0.869 and 0.894 for primary aldosteronism, thyroid disease, nephritis and nephrotic syndrome and chronic kidney disease, respectively, which are four kinds of secondary hypertension with high incidence rates. The experimental results show that our model can powerfully use the textual and numerical data contained in EHRs to provide effective decision support for the differential diagnosis of secondary hypertension.

Development and validation of hypertension prediction models: The Korean Genome and Epidemiology Study_Cardiovascular Disease Association Study (KoGES_CAVAS)

This study aimed to develop and validate the hypertension risk prediction models of the CArdioVascular disease Association Study (CAVAS). Overall, 6,186 participants without hypertension at baseline were randomly divided into derivation and internal validation sets in a 6:4 ratio. We derived two prediction models: the first used the Framingham hypertension risk prediction factors (F-CAVAS-HTN); the second considered additional risk factors identified using stepwise Weibull regression analysis (CAVAS-HTN). These models were externally evaluated among Ansan and Ansung (A&A) participants, and the external validity of the Framingham and A&A prediction models (F-HTN and A&A-HTN) were assessed using the internal validation set of CAVAS. The discrimination, calibration, and net reclassification were determined. During the 4-year follow-up, 777 new cases of hypertension were diagnosed. All four models showed good discrimination (C-statistic ≥ 0.7). Internal calibrations were good for both the coefficient-based and the risk score-based F-CAVAS-HTN models, respectively (Hosmer-Lemeshow chi-square, H-L χ² < 20, P ≥ 0.05). However, the two CAVAS models (H-L χ² ≥ 20, P < 0.05, both) as well as the F-HTN and the A&A-HTN prediction models (H-L χ² = 155.39, P < 0.0001; H-L χ² = 209.72, P < 0.0001, respectively) were not externally calibrated. The F-CAVAS-HTN may be better than models with additional risk factors or derived for another population in the view of the findings of the internal validation in the present study, although future studies to improve the external validity of the F-CAVAS-HTN are needed.

Nomogram Including Serum Ion Concentrations to Screen for New-Onset Hypertension in Rural Chinese Populations Over a Short-Term Follow-up

BACKGROUND

This study aimed to establish a clinically useful nomogram to evaluate the probability of hypertension onset in the Chinese population.

METHODS AND RESULTS

A prospective cohort study was conducted in 2012-2013 and followed up in 2015 to identify new-onset hypertension in 4,123 participants. The dataset was divided into development (n=2,748) and verification (n=1,375) cohorts. After screening risk factors by lasso regression, a multivariate Cox regression risk model and nomogram were established. Among the 4,123 participants, 818 (19.8%) developed hypertension. The model identified 10 risk factors: age, waist-to-hip ratio, systolic blood pressure, diastolic blood pressure, high pulse rate, history of diabetes, family history of hypertension and stroke, intake frequency of bean products, and intensity of physical labor. The C-indices of the model in the development and validation cohorts were 0.744 and 0.768, respectively. After the inclusion of serum calcium and magnesium concentrations, the C-indices in the development and validation cohorts were 0.764 and 0.791, respectively, with areas under the curve for the updated model of 0.907 and 0.917, respectively. The calibration curve showed that the nomogram accurately predicted the probability of hypertension. The updated nomogram was clinically beneficial across thresholds of 10-60%.

CONCLUSIONS

The newly developed nomogram has good predictive ability and may effectively assess hypertension risk in high-risk rural areas in China.

Prediction of hypertension using traditional regression and machine learning models: A systematic review and meta-analysis

OBJECTIVE

We aimed to identify existing hypertension risk prediction models developed using traditional regression-based or machine learning approaches and compare their predictive performance.

METHODS

We systematically searched MEDLINE, EMBASE, Web of Science, Scopus, and the grey literature for studies predicting the risk of hypertension among the general adult population. Summary statistics from the individual studies were the C-statistic, and a random-effects meta-analysis was used to obtain pooled estimates. The predictive performance of pooled estimates was compared between traditional regression-based models and machine learning-based models. The potential sources of heterogeneity were assessed using meta-regression, and study quality was assessed using the PROBAST (Prediction model Risk Of Bias ASsessment Tool) checklist.

RESULTS

Of 14,778 articles, 52 articles were selected for systematic review and 32 for meta-analysis. The overall pooled C-statistics was 0.75 [0.73-0.77] for the traditional regression-based models and 0.76 [0.72-0.79] for the machine learning-based models. High heterogeneity in C-statistic was observed. The age (p = 0.011), and sex (p = 0.044) of the participants and the number of risk factors considered in the model (p = 0.001) were identified as a source of heterogeneity in traditional regression-based models.

CONCLUSION

We attempted to provide a comprehensive evaluation of hypertension risk prediction models. Many models with acceptable-to-good predictive performance were identified. Only a few models were externally validated, and the risk of bias and applicability was a concern in many studies. Overall discrimination was similar between models derived from traditional regression analysis and machine learning methods. More external validation and impact studies to implement the hypertension risk prediction model in clinical practice are required.

Prediction Models for the 5- and 10-Year Incidence of Home Morning Hypertension: The Ohasama Study

BACKGROUND

We aimed to develop risk prediction models for new-onset home morning hypertension.

METHODS

We followed up 978 participants without home hypertension in the general population of Ohasama, Japan (men: 30.1%, age: 53.3 years). The participants were divided into derivation (n = 489) and validation (n = 489) cohorts by their residential area. The C-statistics and calibration plots were assessed after the 5- or 10-year follow-up.

RESULTS

In the derivation cohort, sex, age, body mass index, smoking, office systolic blood pressure (SBP), and home SBP at baseline were selected as significant risk factors for new-onset home hypertension (≥135/85 mm Hg or the initiation of antihypertensive treatment) using the Cox model. In the validation cohort, Harrell's C-statistic for the 5-/10-year home hypertension was 0.7637 (0.7195-0.8100)/0.7308 (0.6932-0.7677), when we used the full model, which included the significant risk factors in the derivation cohort. The calibration test revealed good concordance between the observed and predicted 5-/10-year home hypertension probabilities (P ≥ 0.19); the regression slope of the observed probability on the predicted probability was 1.10/1.02, and the intercept was -0.04/0.06, respectively. A model without home SBP was also developed; for the 10-year home hypertension risk, the calibration test revealed a good concordance (P = 0.19) but Harrell's C-statistic was 0.6689 (0.6266-0.7067).

CONCLUSIONS

The full model revealed good ability to predict the 5- and 10-year home morning hypertension risk. Although the model without home SBP is acceptable, the low C-statistic implies that home BP should be measured to predict home morning hypertension precisely.

Development of the Hypertension Index Model in General Adult Using the Korea National Health and Nutritional Examination Survey and the Korean Genome and Epidemiology Study

Hypertension, a risk factor for cardiovascular disease and all-cause mortality, has been increasing. Along with emphasizing awareness and control of hypertension, predicting the incidence of hypertension is important. Several studies have previously reported prediction models of hypertension. However, among the previous models for predicting hypertension, few models reflect various risk factors for hypertension. We constructed a sex-specific prediction model using Korean datasets, which included socioeconomic status, medical history, lifestyle-related variables, anthropometric status, and laboratory indices. We utilized the data from the Korea National Health and Nutrition Examination Survey from 2011 to 2015 to derive a hypertension prediction model. Participants aged 40 years or older. We constructed a sex-specific hypertension classification model using logistic regression and features obtained by literature review and statistical analysis. We constructed a sex-specific hypertension classification model including approximately 20 variables. We estimated its performance using the Korea National Health and Nutrition Examination Survey dataset from 2016 to 2018 (AUC = 0.847 in men, AUC = 0.901 in women). The performance of our hypertension model was considered significant based on the cumulative incidence calculated from a longitudinal dataset, the Korean Genome and Epidemiology Study dataset. We developed this hypertension prediction model using features that could be collected in a clinical office without difficulty. Individualized results may alert a person at high risk to modify unhealthy lifestyles.

Development of a risk prediction model for incident hypertension in Japanese individuals: the Hisayama Study

The identification of individuals at high risk of developing hypertension can be of great value to improve the efficiency of primary prevention strategies for hypertension. The objective of this study was to develop a risk prediction model for incident hypertension based on prospective longitudinal data from a general Japanese population. A total of 982 subjects aged 40-59 years without hypertension at baseline were followed up for 10 years (2002-12) for the incidence of hypertension. Hypertension was defined as systolic blood pressure (SBP) ≥ 140 mmHg, diastolic blood pressure (DBP) ≥ 90 mmHg, or the use of antihypertensive agents. The risk prediction model was developed using a Cox proportional hazards model. A simple risk scoring system was also established based on the developed model. During the follow-up period (median 10 years, interquartile range 5-10 years), 302 subjects (120 men and 182 women) developed new-onset hypertension. The risk prediction model for hypertension consisted of age, sex, SBP, DBP, use of glucose-lowering agents, body mass index (BMI), parental history of hypertension, moderate-to-high alcohol intake, and the interaction between age and BMI. The developed model demonstrated good discrimination (Harrell's C statistic=0.812 [95% confidence interval, 0.791-0.834]; optimism-corrected C statistic based on 200 bootstrap samples=0.804) and calibration (Greenwood-Nam-D'Agostino χ² statistic=12.2). This risk prediction model is a useful guide for estimating an individual's absolute risk for hypertension and could facilitate the management of Japanese individuals at high risk of developing hypertension in the future.

Development and validation of a nomogram to better predict hypertension based on a 10-year retrospective cohort study in China

Background

Hypertension is a highly prevalent disorder. A nomogram to estimate the risk of hypertension in Chinese individuals is not available.

Methods

6201 subjects were enrolled in the study and randomly divided into training set and validation set at a ratio of 2:1. The LASSO regression technique was used to select the optimal predictive features, and multivariate logistic regression to construct the nomograms. The performance of the nomograms was assessed and validated by AUC, C-index, calibration curves, DCA, clinical impact curves, NRI, and IDI.

Results

The nomogram^140/90 was developed with the parameters of family history of hypertension, age, SBP, DBP, BMI, MCHC, MPV, TBIL, and TG. AUCs of nomogram^140/90 were 0.750 in the training set and 0.772 in the validation set. C-index of nomogram^140/90 were 0.750 in the training set and 0.772 in the validation set. The nomogram^130/80 was developed with the parameters of family history of hypertension, age, SBP, DBP, RDWSD, and TBIL. AUCs of nomogram^130/80 were 0.705 in the training set and 0.697 in the validation set. C-index of nomogram^130/80 were 0.705 in the training set and 0.697 in the validation set. Both nomograms demonstrated favorable clinical consistency. NRI and IDI showed that the nomogram^140/90 exhibited superior performance than the nomogram^130/80. Therefore, the web-based calculator of nomogram^140/90 was built online.

Conclusions

We have constructed a nomogram that can be effectively used in the preliminary and in-depth risk prediction of hypertension in a Chinese population based on a 10-year retrospective cohort study.

Funding

This study was supported by the Hebei Science and Technology Department Program (no. H2018206110).

Validation of the Framingham hypertension risk score in a middle eastern population: Tehran lipid and glucose study (TLGS)

Background

The Framingham hypertension risk score is a well-known and simple model for predicting hypertension in adults. In the current study, we aimed to assess the predictive ability of this model in a Middle Eastern population.

Methods

We studied 5423 participants, aged 20–69 years, without hypertension, who participated in two consecutive examination cycles of the Tehran Lipid and Glucose Study (TLGS). We assessed discrimination based on Harrell’s concordance statistic (c-index) and calibration (graphical comparison of predicted vs. observed). We evaluated the original, recalibrated (for intercept and slope), and revised (for beta coefficients) models.

Results

Over the 3-year follow-up period, 319 participants developed hypertension. The Framingham hypertension risk score performed well in discriminating between individuals who developed hypertension and those who did not (c-index = 0.81, 95% CI: 0.79–0.83). Initially, there was a systematic underestimation of the original risk score (events predicted), which was readily corrected by a simple model revision.

Conclusions

The revised Framingham hypertension risk score can be used as a screening tool in public health and clinical practice to facilitate the targeting of preventive interventions in high-risk Middle Eastern people.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-10760-6.

Sex-Specific Incidence Rates and Risk Factors for Hypertension During 13 Years of Follow-up: The Tehran Lipid and Glucose Study

Background:

Hypertension, with a prevalence of 25.6% is a serious public health concern in Iran.

Objective:

To investigate the population-based incidence of hypertension and its potential risk factors in Tehranian adults during a median follow-up of 13.1 years.

Methods:

A total of 6,533 non-hypertensive participants (women = 3,639), aged ≥20 years participated in the study. Crude and age-standardized incidence rates per 1000 person-years were calculated for each sex, separately. Multivariable Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CI) for all potential risk factors.

Results:

The crude and age-standardized incidence rates (95% CI) of hypertension per 1000 person-years were 29.7 (27.8–31.6) and 34.9 (32.5–37.4) among men and 25.8 (24.3–27.3) and 38.7 (35.5–42.0) among women, respectively. The incidence rate of hypertension in younger age groups was higher among men. However, after the 4^th decade, the incidence rate was higher among women. Significant interactions of sex with age groups, body mass index categories, marital status, hypertriglyceridemia and glycemic categories were found in multivariable analyses (all p-values < 0.05). In the multivariable model, the risk in both sexes was found to be significantly associated with older age, obesity, and normal or high normal blood pressure (BP). Moreover, factors such as being overweight [HR: 1.20 (1.00–1.44)], former smoking [2.15 (1.52–3.04)], hypertriglyceridemia [1.23 (1.06–1.43)] and pre-diabetes status [1.19 (1.02–1.39)] were significant predictors of incident hypertension among women. Central obesity was found to be a significant predictor among men [1.26 (1.03–1.54)]. The optimism-corrected Harrell’s C index (95% CI) in the categorical adjusted model was 0.75 (0.74–0.79) among men and 0.75 (0.74–0.76) among women.

Conclusion:

In the Tehranian population, nearly 2.7% of total participants (3% of men and 2.6% of women) develop hypertension each year. Obesity and high BP levels are the main modifiable risk factors in both sexes. Hypertriglyceridemia, prediabetes and former smoking are risk factors for hypertension among women.

Prediction model and assessment of probability of incident hypertension: the Rural Chinese Cohort Study

We aimed to develop a hypertension risk-prediction model among rural Chinese people. We included data for 9034 participants aged 18-70 years without baseline hypertension, diabetes, myocardial infarction, stroke, or heart failure in a rural Chinese cohort. The sample was randomly divided into a training set (60%) and testing set (40%). We used shrinkage estimates by the least absolute shrinkage and selection operator method in fitting a logistic model to explore the possibility of predicting the risk of hypertension in the training set. On multivariable analysis, age, parental hypertension, systolic and diastolic blood pressure, body mass index (BMI), and age by BMI were significant predictors of hypertension. After bootstrap validation, the corrected C-index, calibration intercept, and calibration slope were 0.7932, -0.0041, and 0.9938, respectively for the training set. Our model also had good discrimination (C-index, 0.7914 [95% CI 0.773-0.809]) and calibration (Hosmer-Lemeshow χ² = 14.366, P = 0.073) for the testing set. Nomograms and score-based models were used to favor the clinical implementation and workability of the risk model. According to the risk score based on these factors, the cumulative risk for hypertension was <20% for 57.62% of participants, 20-40% risk for 27.24%, 40-60% for 12.19%, and >60% for 2.96% during the 6-year follow-up. The score-based area under the receiver operating characteristic curve for the present model and the Framingham risk-score model were similar (P = 0.282). The hypertension risk-prediction system we developed provides convenient approaches to identify individuals at high risk of hypertension.

Adherence to a Health Literacy and Healthy Lifestyle with Improved Blood Pressure Control in Iran

INTRODUCTION AND AIM

High blood pressure is the leading and most important modifiable risk factor for cardiovascular disease. Health literacy and lifestyle are two paramount key factors behind better control of hypertension. This study was conducted to examine the current situation of health literacy and health-promoting lifestyle and its association with blood pressure control among people affected by hypertension in the population over age 30 of Northwest Iran.

PATIENTS AND METHODS

This was a cross-sectional study conducted in October and December 2018 on the over 30-year-old population among subjects suffering from hypertension (n= 210). A self-reported questionnaire was used for assessing health literacy dimensions and lifestyle.

RESULTS

In hierarchical linear analysis, the HL explained 33.9% of the variance in healthy lifestyle. Among HL dimensions, the ability to access health information and decision-making were significantly associated with healthy lifestyle. The health literacy dimensions contributed to an additional significant increase in 4.7% of the variance explained in hypertension, furthermore, the health-promoting lifestyle items were explained an additional 14.8% of the hypertension variance. In total, lifestyle and health literacy dimensions were able to explain 21.7% of the variance in hypertension.

CONCLUSION

Our study encourages efforts to monitor health literacy in people with hypertension and investigate associations with involvement with health-promoting lifestyle.

Development and validation of prediction models for hypertension risks in rural Chinese populations

Background

Various hypertension predictive models have been developed worldwide; however, there is no existing predictive model for hypertension among Chinese rural populations.

Methods

This is a 6-year population-based prospective cohort in rural areas of China. Data was collected in 2007-2008 (baseline survey) and 2013-2014 (follow-up survey) from 8319 participants ranging in age from 35 to 74 years old. Specified gender hypertension predictive models were established based on multivariate Cox regression, Artificial Neural Network (ANN), Naive Bayes Classifier (NBC), and Classification and Regression Tree (CART) in the training set. External validation was conducted in the testing set. The estimated models were assessed by discrimination and calibration, respectively.

Results

During the follow-up period, 432 men and 604 women developed hypertension in the training set. Assessment for established models in men suggested men office-based model (M1) was better than others. C-index of M1 model in the testing set was 0.771 (95% confidence Interval (CI) = 0.750, 0.791), and calibration χ² = 6.3057 (P = 0.7090). In women, women office-based model (W1) and ANN were better than the other models assessed. The C-indexes for the W1 model and the ANN model in the testing set were 0.765 (95% CI = 0.746, 0.783) and 0.756 (95% CI = 0.737, 0.775) and the calibrations χ² were 6.7832 (P = 0.1478) and 4.7447 (P = 0.3145), respectively.

Conclusions

Not all machine-learning models performed better than the traditional Cox regression models. The W1 and ANN models for women and M1 model for men have better predictive performance which could potentially be recommended for predicting hypertension risk among rural populations.

Impact of 3-year changes in fasting insulin and insulin resistance indices on incident hypertension: Tehran lipid and glucose study

Background

To examine the association between changes in fasting insulin, homeostasis model assessment of insulin resistance (HOMA-IR), and insulin-glucose ratio (IGR) levels, over approximately 3 years with incident hypertension.

Methods

A total of 2814 Iranian participants (1123 men) without hypertension and known diabetes at baseline and the first examination were followed for a median of 6.32 years. The associations between quartiles of changes in fasting insulin and IR indices with incident hypertension were assessed using multivariate Cox proportional hazard regression analyses with first quartile as reference. The models were adjusted for baseline values of insulin or each IR index, and age, sex, smoking, physical activity, educational levels, marital status, history of cardiovascular diseases, baseline levels of systolic and diastolic blood pressures, estimated glomerular filtration rate, triglycerides, total cholesterol, high-density lipoprotein cholesterol, fasting plasma glucose (only for insulin change) and both body mass index (BMI) per se, and its change. Akaike's information criteria (AIC) was applied as indicator for goodness of fit of each predictive model. The discrimination ability of models was calculated using the Harrell's C statistic.

Results

During the study, 594 incident cases of hypertension (253 men) were identified. The 4th quartile of changes in insulin, HOMA-IR, and IGR showed hazard ratios (95% confidence interval) of 1.31 (1.01-1.69), 1.18 (0.92-1.52), and 1.53 (1.18-1.98) for hypertension, respectively, in fully-adjusted models. Changes in fasting insulin levels and IR indices showed significant increasing trends for incident hypertension, moving from 1st to 4th quartiles (all P-values < 0.05). Focusing on model fitness, no superiority was found between changes in fasting insulin, HOMA-IR, and IGR to predict incident hypertension. The discriminatory powers of changes in fasting insulin and IR indices as assessed by C index were similar (i.e. about 80%).

Conclusion

Changes in fasting insulin and IR indices were significantly associated with developing hypertension among normotensive population even after considering BMI changes.

Relationship between lifestyle pattern and blood pressure - Iranian national survey

We aimed to evaluate the relationship between different lifestyle patterns and blood pressure. This study is based on the national survey of the risk factors for non-communicable diseases in Iran in 2012. A total of 8244 people aged 25–70 years old have been enrolled in the survey. Clustering on the individual data of lifestyle factors (nutrition, physical activity, and smoking) were carried out using self-organizing neural network method. Multivariable regression models were used to determine the relationship between blood pressure and the clusters. This study revealed seven lifestyle clusters in the national survey. The first cluster had a healthier lifestyle (15%), and the rest of the clusters had at least one or more lifestyle-related risk factors. Among all the clusters, people in two clusters, i.e. one characterized by consumption of sugar-sweetened beverages, salt, and fast foods, and the other one characterized by physical inactivity, were more exposed to the risk of hypertension (odds ratios of 1.44 and 1.12, respectively). People in another cluster who were 100% smokers and had a very high level of work-related physical activity were about 30% less likely to experience elevated blood pressure. Although a lifestyle with cigarette smoking was associated with a reduction in blood pressure, this might be due to other related factors, such as work-related physical activity, which lower blood pressure. Of course, this hypothesis still needs to be further studied in the future.

Incidence and associated risk factors for premature death in the Tehran Lipid and Glucose Study cohort, Iran

Background

The incidence and associated risk factors for premature death were investigated in a population-based cohort study in Iran.

Methods

A total of 7245 participants (3216 men), aged 30–70 years, were included. We conducted Cox proportional hazards models to identify the risk factors for premature death. For each risk factor, hazard ratio (HR), 95% confidence intervals (95% CI) and population attributable fraction (PAF) were calculated.

Results

After a median follow-up of 13.8 years, 262 premature deaths (153 in men) occurred. Underlying causes of premature deaths were cardiovascular disease (CVD) (n = 126), cancer (n = 51), road injuries (n = 15), sepsis and pneumonia (n = 9) and miscellaneous reasons (n = 61). The age-standardized incident rate of premature death was 2.35 per 1000 person years based on WHO standard population. Hypertension [HR 1.40, 95% CI (1.07–1.83)], diabetes (2.53, 1.94–3.29) and current smoking (1.58, 1.16–2.17) were significant risk factors for premature mortality; corresponding PAFs were 12.3, 22.4 and 9.2%, respectively. Overweight (body mass index (BMI): 25–29.9 kg/m²) (0.65, 0.49–0.87) and obesity (BMI ≥30 kg/m²) (0.67, 0.48–0.94) were associated with decreased premature mortality. After replacing general adiposity with central adiposity, we found no significant risk for the latter (0.92, 0.71–1.18). Moreover, when we excluded current smokers, those with prevalent cancer/cardiovascular disease and those with survival of less than 3 years, the inverse association between overweight (0.59, 0.39–0.88) and obesity (0.67, 0.43–1.04), generally remained unchanged; although, diabetes still showed a significant risk (2.62, 1.84–3.72).

Conclusions

Controlling three modifiable risk factors including diabetes, hypertension and smoking might potentially reduce mortality events by over 40%, and among these, prevention of diabetes should be prioritized to decrease burden of events. We didn’t confirm a negative impact of overweight and obesity status on premature mortality events.

Tea, coffee, caffeine intake and the risk of cardio-metabolic outcomes: findings from a population with low coffee and high tea consumption

Background

This study aimed to assess the potential effects of long-term intake of caffeine and habitual consumption of coffee and tea on the occurrence of cardio-renal events among an Iranian population with low coffee and high tea consumption.

Methods

Adult participants of the Tehran Lipid and Glucose Study (2006-2008 to 2012-2014) who met the study inclusion criteria, were recruited. Habitual dietary intakes were assessed using a validated food frequency questionnaire. Demographics, anthropometrics, blood pressure, and biochemical variables were evaluated at baseline and during follow-up examinations. Multivariate Cox proportional hazard and logistic regression models adjusted for potential confounders were used to estimate the risk of cardiovascular disease (CVD), hypertension (HTN) and chronic kidney disease (CKD).

Results

During median 6 years of follow-up, the incidence rate of CVD outcomes, HTN, and CKD were 3.3%, 15.5%, and 17.9%, respectively. The risk of CVD was increased more than two-fold in the highest tertile of tea consumption (HR = 2.44, 95% confidence interval, CI = 1.40-4.27; P for trend = 0.001), and caffeine intakes (HR = 2.22, 95% CI = 1.23-4.01; P for trend = 0.005). A 42% lower incidence of CVD was observed in coffee drinkers, compared to non-drinkers (HR = 0.58, 95% CI = 0.36-0.93; P for trend = 0.023). No significant association was observed between tea, coffee or caffeine intakes and the risk of HTN or CKD.

Conclusions

Findings of our study support previous data regarding the protective effects of coffee on CVD. Contrary to the previous studies, we found that higher intakes of tea and caffeine, mainly originated from tea in our population, may increase risk of CVD events. It may be related to the type of tea and its preparation methods, additives or artificial colors in tea consumed in Iran, and sweets or sugar that mostly consumed accompanied by tea. Also, genetic variants of the liver enzymes may modify the association of dietary caffeine sources and incidence of CVD. Further prospective studies with incorporation of different population with different dietary habits and genetic backgrounds are needed to clarify the contradictions.

A Prediction Model of Essential Hypertension Based on Genetic and Environmental Risk Factors in Northern Han Chinese

Background: Essential hypertension (EH) is a chronic disease of universal high prevalence and a well-established independent risk factor for cardiovascular and cerebrovascular events. The regulation of blood pressure is crucial for improving life quality and prognoses in patients with EH. Therefore, it is of important clinical significance to develop prediction models to recognize individuals with high risk for EH. Methods: In total, 965 subjects were recruited. Clinical parameters and genetic information, namely EH related SNPs were collected for each individual. Traditional statistic methods such as t-test, chi-square test and multi-variable logistic regression were applied to analyze baseline information. A machine learning method, mainly support vector machine (SVM), was adopted for the development of the present prediction models for EH. Results: Two models were constructed for prediction of systolic blood pressure (SBP) and diastolic blood pressure (DBP), respectively. The model for SBP consists of 6 environmental factors (age, BMI, waist circumference, exercise [times per week], parental history of hypertension [either or both]) and 1 SNP (rs7305099); model for DBP consists of 6 environmental factors (weight, drinking, exercise [times per week], TG, parental history of hypertension [either and both]) and 3 SNPs (rs5193, rs7305099, rs3889728). AUC are 0.673 and 0.817 for SBP and DBP model, respectively. Conclusions: The present study identified environmental and genetic risk factors for EH in northern Han Chinese population and constructed prediction models for SBP and DBP.

Blood Pressure and Hypertension: Findings from 20 Years of the Tehran Lipid and Glucose Study (TLGS)

CONTEXT

Hypertension (HTN) is a well-known modifiable risk factor for cardiovascular disease (CVD), chronic kidney disease and mortality. Positive effects of blood pressure (BP) lowering for prevention of CVD and death have been documented in several meta-analyses of randomized controlled trials.

EVIDENCE ACQUISITION

This review focuses on the key findings derived from the Tehran lipid and glucose study (TLGS) papers on different aspects of BP and HTN.

RESULTS

A prevalence of 23% for HTN has been reported in the TLGS population, aged ≥ 20 years. Over a decade long follow-up, the crude incidence rate (95% CI) of new-onset HTN defined as systolic BP (SBP) ≥ 140 mmHg and/or diastolic BP (DBP) ≥ 90 mmHg, and not using antihypertensive medication was 33.63 (32.0 - 35.3) per 1000 person-years. Age, baseline SBP and body mass index were significant risk factors for development of isolated systolic HTN; regarding isolated diastolic HTN, baseline DBP and waist circumference were recognized as important risk factors whereas age, female gender and marriage were shown to be protective factors. SBP decreased significantly in both diabetic and non-diabetic participants; DBP showed a non-significant decrease in diabetic men and a statistically significant decrease in non-diabetic men. Among women, both those with and without diabetes (DM) generally experienced statistically significant decreases in DBP. Cox proportional hazard models showed that neither SBP nor DBP were associated with incident DM in the total population and in either gender, separately. All BP components were associated with CVD and all-cause mortality in the middle-aged population. Contribution of HTN to cerebrovascular events was also documented in the TLGS participants, aged ≥ 50 years.

CONCLUSIONS

Several important findings regarding BP/HTN have been derived from the TLGS. According to data regarding the prevalence and incidence of preHTN and HTN and their contribution to cardiovascular morbidity and mortality in the TLGS population as a representative sample of Tehranian population, it is recommended that interventions be prioritized for lifestyle modifications for the prevention and appropriate management of preHTN/HTN.

Tobacco Smoking: Findings from 20 Years of the Tehran Lipid and Glucose Study

CONTEXT

Smoking is a global public health priority and accurate data of the local population is essential to improve the health policies against its use. Hence, this study aimed to summarize the important findings available on the prevalence of smoking and its association with non-communicable diseases, documented by one of the largest prospective community-based studies of Iran.

EVIDENCE ACQUISITION

All articles derived from the Tehran Lipid and Glucose Study (TLGS) in the last two decades, from the earliest publications until 30 January 2018 were reviewed for their findings on tobacco smoking.

RESULTS

The prevalence of smoking in non-diabetic adults ≥ 20 years increased between baseline (phase I, 1999 - 2001) and follow-up (phase V, 2008 - 2011) from 25.5% to 35.4% among men and from 3.4% to 6.8% among women. In TLGS adolescents (10 - 18 years) water pipe use increased between 2003 and 2005 from 35.5% to 40.9% among boys and from 19.7% to 26.1% among girls. Regarding health hazards, smoking in men was associated with increased risk of combined impaired fasting glucose/impaired glucose tolerance [hazard ratio (HR) 1.69; confidence interval (CI) 95% 1.15 - 2.48] and hypertension (HR 1.26; CI 95% 0.98 - 1.63). Moreover, men, even smoking less than 10 cigarettes per day, were at increased risk for cardiovascular diseases by HR 2.12 (CI 95% 1.14 - 3.95). For women, the risk of chronic kidney disease dramatically increased 5.74-fold (CI 95% 2.71 - 12.15) among smokers. In the whole population, smoking contributed to 7.7% of all-cause mortality with HR 1.75 (CI 95% 1.38 - 2.22). Other health aspects of tobacco smoke, including its impact on metabolic status, thyroid function, female reproductive system and life style have also been reviewed.

CONCLUSION

Considering hazards of smoking, there is the urgency for more effective preventive measures in Iran; emphasizing the need for further local studies on the hazards of smoking with special attention to women and adolescents and the independent hazards of water pipe use.

Outcomes of a Longitudinal Population-based Cohort Study and Pragmatic Community Trial: Findings from 20 Years of the Tehran Lipid and Glucose Study

CONTEXT

The Tehran lipid and glucose study (TLGS) is one of the oldest population-based longitudinal cohort studies, providing knowledge about the incidence and risk factors of some non-communicable diseases (NCDs) in West Asia which hitherto was relatively scarce. We reviewed the methods and results related to the outcome measurements of this study.

EVIDENCE ACQUISITION

We reviewed all the TLGS papers which reported the incidence of NCDs.

RESULTS

The TLGS was initiated in 1999 - 2001 on a population in district no. 13 of Tehran with the same age distribution of the overall Tehran population and with a middle socioeconomic status. Totally, 15005 individuals, aged ≥ 3 years, participated in the first examination; reexaminations were conducted in a triennial manner and 3550 individuals were added in the second examination. All participants were also followed up annually and asked about any medical event leading to hospitalization or death. A part of participants was assigned to an educational program for lifestyle modification. High incidence of cardiovascular disease (CVD), premature CVD, diabetes and hypertension (around 19, 6, 10 and 31 in men and 11, 5, 11 and 29 in women per 1000 person-year, respectively) besides the high incidence of pre-diabetes and pre-hypertension (around 46 and 76 in men and 37 and 49 in women per 1000 person-year, respectively) showed a worrying situation. Fortunately, the results of the community interventions were promising with around 20% reduction in the risk of metabolic syndrome up to six years.

CONCLUSIONS

These precise detections of different outcomes in the TLGS provided valuable evidences for prediction and prevention of NCDs in Iran with some novelties in the middle-income countries in the world. The Tehran thyroid study (TTS) and the Tehran cardiometabolic genetic study (TCGS), conducted in the framework of the TLGS, are among few studies aiming to determine the natural course of thyroid function and to identify patterns of genetic polymorphisms related to cardiometabolic outcomes, respectively.

Blood pressure components and incident cardiovascular disease and mortality events among Iranian adults with chronic kidney disease during over a decade long follow-up: a prospective cohort study

Background

To explore the association between systolic and diastolic blood pressure (SBP and DBP respectively) and pulse pressure (PP) with cardiovascular disease (CVD) and mortality events among Iranian patients with prevalent CKD.

Methods

Patients [n = 1448, mean age: 60.9 (9.9) years] defined as those with estimated glomerular filtration rate < 60 ml/min/1.73 m², were followed from 31 January 1999 to 20 March 2014. Multivariable Cox proportional hazard models were applied to examine the associations between different components of BP with outcomes.

Results

During a median follow-up of 13.9 years, 305 all-cause mortality and 317 (100 fatal) CVD events (among those free from CVD, n = 1232) occurred. For CVD and CV-mortality, SBP and PP showed a linear relationship, while a U-shaped relationship for DBP was observed with all outcomes. Considering 120 ≤ SBP < 130 as reference, SBP ≥ 140 mmHg was associated with the highest hazard ratio (HR) for CVD [1.68 (1.2–2.34)], all-cause [1.72 (1.19–2.48)], and CV-mortality events [2.21 (1.16–4.22)]. Regarding DBP, compared with 80 ≤ DBP < 85 as reference, the level of ≥ 85 mmHg increased risk of CVD and all-cause mortality events; furthermore, DBP < 80 mmHg was associated with significant HR for CVD events [1.55 (1.08–2.24)], all-cause [1.68 (1.13–2.5)] and CV-mortality events [3.0 (1.17–7.7)]. Considering PP, the highest HR was seen in participants in the 4th quartile for all outcomes of interest; HRs for CVD events [1.92 (1.33–2.78)], all-cause [1.71 (1.11–2.63)] and CV-mortality events [2.22 (1.06–4.64)].

Conclusions

Among patients with CKD, the lowest risk of all-cause and CV-mortality as well as incident CVD was observed in those with SBP < 140, 80 ≤ DBP < 85 and PP < 64 mmHg.

Developing and validating a new precise risk-prediction model for new-onset hypertension: The Jichi Genki hypertension prediction model (JG model)

No integrated risk assessment tools that include lifestyle factors and uric acid have been developed. In accordance with the Industrial Safety and Health Law in Japan, a follow-up examination of 63 495 normotensive individuals (mean age 42.8 years) who underwent a health checkup in 2010 was conducted every year for 5 years. The primary endpoint was new-onset hypertension (systolic blood pressure [SBP]/diastolic blood pressure [DBP] ≥ 140/90 mm Hg and/or the initiation of antihypertensive medications with self-reported hypertension). During the mean 3.4 years of follow-up, 7402 participants (11.7%) developed hypertension. The prediction model included age, sex, body mass index (BMI), SBP, DBP, low-density lipoprotein cholesterol, uric acid, proteinuria, current smoking, alcohol intake, eating rate, DBP by age, and BMI by age at baseline and was created by using Cox proportional hazards models to calculate 3-year absolute risks. The derivation analysis confirmed that the model performed well both with respect to discrimination and calibration (n = 63 495; C-statistic = 0.885, 95% confidence interval [CI], 0.865-0.903; χ² statistic = 13.6, degree of freedom [df] = 7). In the external validation analysis, moreover, the model performed well both in its discrimination and calibration characteristics (n = 14 168; C-statistic = 0.846; 95%CI, 0.775-0.905; χ² statistic = 8.7, df = 7). Adding LDL cholesterol, uric acid, proteinuria, alcohol intake, eating rate, and BMI by age to the base model yielded a significantly higher C-statistic, net reclassification improvement (NRI), and integrated discrimination improvement, especially NRI_non-event (NRI = 0.127, 95%CI = 0.100-0.152; NRI_non-event  = 0.108, 95%CI = 0.102-0.117). In conclusion, a highly precise model with good performance was developed for predicting incident hypertension using the new parameters of eating rate, uric acid, proteinuria, and BMI by age.

Allium vegetable intakes and the incidence of cardiovascular disease, hypertension, chronic kidney disease, and type 2 diabetes in adults: a longitudinal follow-up study

OBJECTIVES

This study investigated the association between habitual consumption of allium vegetables (garlic and onion) and the incidence of cardiovascular disease (CVD) outcomes, hypertension (HTN), chronic kidney disease (CKD), and type 2 diabetes (T2D).

METHODS

Adult men and women, participated in the Tehran Lipid and Glucose Study (2006-2008 to 2012-2014), were recruited. Habitual dietary intakes were assessed using a validated semiquantitative food frequency questionnaire. Demographics, anthropometrics, blood pressure, and biochemical variables were evaluated at baseline and during follow-up examinations. Multivariate Cox proportional hazard regression models adjusted for potential confounders were used to estimate the development of CVD outcomes, HTN, CKD, and T2D in relation to allium vegetable intakes.

RESULTS

Mean age of participants (44.2% men) was 40.3 ± 14.3 years, at baseline. During an average of 6 years of follow-up, the incidence rate of CVD outcomes, HTN, CKD, and T2D were 3.3, 15.5, 17.9, and 6.7%, respectively. A higher habitual intake of allium vegetables was associated with a 64% reduced risk of CVD outcomes (hazard ratio = 0.36, 95% confidence interval, CI = 0.18-0.71; P for trend = 0.011), 32% lower incidence of CKD (hazard ratio = 0.69, 95% CI = 0.46-0.98; P for trend = 0.11), and 26% decreased HTN development (hazard ratio = 0.74, 95% CI = 0.54-1.00; P for trend = 0.06). No significant association was observed between allium vegetable intakes and the risk of T2D. Allium vegetable intake was related to 6 years' changes of triglyceride levels (β = -0.81, P = 0.01) and creatinine clearance (β = 0.56, P = 0.01).

CONCLUSION

Data of the current study support the available mechanistic findings regarding cardiorenal protective properties of allium vegetables.

Recent development of risk-prediction models for incident hypertension: An updated systematic review

BACKGROUND

Hypertension is a leading global health threat and a major cardiovascular disease. Since clinical interventions are effective in delaying the disease progression from prehypertension to hypertension, diagnostic prediction models to identify patient populations at high risk for hypertension are imperative.

METHODS

Both PubMed and Embase databases were searched for eligible reports of either prediction models or risk scores of hypertension. The study data were collected, including risk factors, statistic methods, characteristics of study design and participants, performance measurement, etc.

RESULTS

From the searched literature, 26 studies reporting 48 prediction models were selected. Among them, 20 reports studied the established models using traditional risk factors, such as body mass index (BMI), age, smoking, blood pressure (BP) level, parental history of hypertension, and biochemical factors, whereas 6 reports used genetic risk score (GRS) as the prediction factor. AUC ranged from 0.64 to 0.97, and C-statistic ranged from 60% to 90%.

CONCLUSIONS

The traditional models are still the predominant risk prediction models for hypertension, but recently, more models have begun to incorporate genetic factors as part of their model predictors. However, these genetic predictors need to be well selected. The current reported models have acceptable to good discrimination and calibration ability, but whether the models can be applied in clinical practice still needs more validation and adjustment.

Impact of blood pressure, cholesterol and glucose in the association between adiposity measures and coronary heart disease and stroke among Iranian population

BACKGROUND & AIMS

To determine the association of body mass index (BMI) and central adiposity measures with coronary heart disease (CHD)/stroke, and to quantify the impact of blood pressure, cholesterol and glucose as metabolic mediators on these associations.

METHODS

The study population included 4631 Iranian participants (males = 2066) aged ≥40 years. Cox proportional hazard model was used to estimate the hazard ratio (HR) of BMI and central adiposity measures, using continuous and categorical variables, on CHD/stroke, with and without adjustment for three metabolic mediators, to calculate the attenuation of excess risk after adjustment for mediators.

RESULTS

During a median follow-up of 12.1 years, 606 and 132 subjects experienced incident CHD and stroke, respectively. In the sex and confounders adjusted model, overweight and obesity were associated with increased risk for CHD (HR: 1.56; 95% CI: 1.26-1.92) and [1.53 (1.21-1.94)], respectively; however, after further adjustment for all the mediators, the result was significant only for overweight status [1.29 (1.05-1.59)]. Considering stroke, a significant risk of 70% (1.05-2.72) was found only among obese population. The percentage of risk mediated by three mediators among obese population was 75.47% and 75.71% for CHD and stroke, respectively. Blood pressure was the most important mediator of obesity, accounting for at least 50% of the excess risk for CHD and 60% for stroke. Considering central obesity measures, in the presences of all mediators, a significant risk for CHD was demonstrated; regarding stroke events, the risk was marginally significant for waist to height [1.02 (0.99-1.05)] and waist to hip ratios [1.02 (1.00-1.05)].

CONCLUSIONS

Overweight and obesity for CHD and, obesity for stroke were associated with increased risk; the negative effect of obesity was potentially ameloriated about 70% after adjustment for mediators. However, overweight status and central adiposity highlighted significant risk that did not decrease after controlling for traditional risk factors.

Association between Dietary Intakes of Nitrate and Nitrite and the Risk of Hypertension and Chronic Kidney Disease: Tehran Lipid and Glucose Study

Background and Aim: The association of habitual intakes of dietary nitrate (NO₃⁻) and nitrite (NO₂⁻) with blood pressure and renal function is not clear. Here, we investigated a potential effect of dietary NO₃⁻ and NO₂⁻ on the occurrence of hypertension (HTN) and chronic kidney disease (CKD). Methods: A total of 2799 Iranian adults aged ≥20 years, participating in the Tehran Lipid and Glucose Study (TLGS), were included and followed for a median of 5.8 years. Dietary intakes of NO₃⁻ and NO₂⁻ were estimated using a semi-quantitative food frequency questionnaire. Demographics, anthropometrics, blood pressure and biochemical variables were evaluated at baseline and during follow-up examinations. To identify the odds ratio (OR) and 95% confidence interval (CI) of HTN and CKD across tertile categories of residual energy-adjusted NO₃⁻ and NO₂⁻ intakes, multivariate logistic regression models were used. Results: Dietary intake of NO₃⁻ had no significant association with the risk of HTN or CKD. Compared to the lowest tertile category (median intake < 6.04 mg/day), the highest intake (median intake ≥ 12.7 mg/day) of dietary NO₂⁻ was accompanied with a significant reduced risk of HTN, in the fully adjusted model (OR = 0.58, 95% CI = 0.33–0.98; p for trend = 0.054). The highest compared to the lowest tertile of dietary NO₂⁻ was also accompanied with a reduced risk of CKD (OR = 0.50, 95% CI = 0.24–0.89, p for trend = 0.07). Conclusion: Our findings indicated that higher intakes of NO₂⁻ might be an independent dietary protective factor against the development of HTN and CKD, which are major risk factors for adverse cardiovascular events.

Different Combinations of Glucose Tolerance and Blood Pressure Status and Incident Diabetes, Hypertension, and Chronic Kidney Disease

Background

The impact of different combinations of glucose tolerance and blood pressure status on the development of type 2 diabetes mellitus (T2DM), hypertension (HTN), and chronic kidney disease (CKD) still needs to be investigated.

Methods and Results

A total of 12 808 Iranian adults aged ≥20 years were included in 3 separate analyses to investigate incidence of T2DM, HTN, and CKD. Multivariate Cox proportional hazard models were used to calculate hazard ratios (95% CI). During a median follow‐up of >10 years, the overall incidence rate for T2DM, HTN, and CKD was 12.2, 29.8, and 24.8 per 1000 person‐years. For incident T2DM, considering normal glucose tolerance/normal blood pressure as reference, prediabetes (PreDM)/HTN had the highest risk (hazard ratio: 7.22 [5.71–9.12]) while PreDM/normal blood pressure also showed a significant risk (5.58 [4.41–7.05]). Furthermore, risk of PreDM/HTN was higher than PreDM/normal blood pressure (P<0.05). For incident HTN, normal glucose tolerance/prehypertension was a strong predictor (3.28 [2.91–3.69]); however, addition of PreDM or T2DM did not increase the risk. For incident CKD, every category that included HTN and/or T2DM showed significant risk; this risk was marginally significant for the PreDM/HTN group (1.19 [0.98–1.43], P=0.06). In addition, PreDM/ normal blood pressure was a marginally significant risk factor for incident HTN while normal glucose tolerance/prehypertension was a significant predictor of T2DM.

Conclusions

Presence of HTN was associated with increased risk of T2DM among the PreDM population; however, dysglycemia did not increase the risk of HTN among individuals with prehypertension. For incident CKD, intensive management of HTN and T2DM, rather than their predisease states, should be considered.

Classification-based data mining for identification of risk patterns associated with hypertension in Middle Eastern population: A 12-year longitudinal study

Hypertension is a critical public health concern worldwide. Identification of risk factors using traditional multivariable models has been a field of active research. The present study was undertaken to identify risk patterns associated with hypertension incidence using data mining methods in a cohort of Iranian adult population.Data on 6205 participants (44% men) age > 20 years, free from hypertension at baseline with no history of cardiovascular disease, were used to develop a series of prediction models by 3 types of decision tree (DT) algorithms. The performances of all classifiers were evaluated on the testing data set.The Quick Unbiased Efficient Statistical Tree algorithm among men and women and Classification and Regression Tree among the total population had the best performance. The C-statistic and sensitivity for the prediction models were (0.70 and 71%) in men, (0.79 and 71%) in women, and (0.78 and 72%) in total population, respectively. In DT models, systolic blood pressure (SBP), diastolic blood pressure, age, and waist circumference significantly contributed to the risk of incident hypertension in both genders and total population, wrist circumference and 2-h postchallenge plasma glucose among women and fasting plasma glucose among men. In men, the highest hypertension risk was seen in those with SBP > 115 mm Hg and age > 30 years. In women those with SBP > 114 mm Hg and age > 33 years had the highest risk for hypertension. For the total population, higher risk was observed in those with SBP > 114 mm Hg and age > 38 years.Our study emphasizes the utility of DTs for prediction of hypertension and exploring interaction between predictors. DT models used the easily available variables to identify homogeneous subgroups with different risk pattern for the hypertension.

Hypertension phenotypes and incident cardiovascular disease and mortality events in a decade follow-up of a Middle East cohort

OBJECTIVE

To investigate the association of hypertension phenotypes, with the risk of cardiovascular disease (CVD) and mortality.

METHODS

We examined the risk of hypertension phenotypes, that is, isolated systolic hypertension (ISH), isolated diastolic hypertension (IDH), systolic-diastolic hypertension (SDH), controlled blood pressure (CBP), and uncontrolled blood pressure (UBP) among 6974 middle-aged and 882 elderly participants. Cox regression analysis was used to estimate the hazard ratio for hypertension phenotypes, considering those with normotension as the reference.

RESULTS

During more than 10 years of follow-up, in the middle-aged group, 490 CVD events and 152 deaths occurred; corresponding rates for the elderly group were 194 and 183, respectively. In middle-aged patients, ISH, SDH, and UBP increased the risk of CVD, whereas UBP increased the risk of mortality due to CVD and any cause (hazard ratio 5.67 and 2.95, respectively) and IDH increased only the risk of total mortality in the middle-aged group (hazard ratio 2.01; all P values <0.05). In elderly patients, ISH, SDH, and UBP significantly increased the risks of CVD. IDH (hazard ratio 3.20 and 2.01), SDH (hazard ratio 3.80 and 3.23) and CBP (hazard ratio 2.86 and 1.87) increased the risks of CVD and all-cause mortality in this group, respectively (all P values <0.05).

CONCLUSION

In both middle-aged and elderly population, ISH, SDH, and UBP increase the risk of CVD. Controlling of BP to less than 140/90 mmHg decreases the risk of mortality events among the middle-aged population; however, it is not suitable for the elderly as it was associated with higher risk of mortality.

Survival Regression Modeling Strategies in CVD Prediction

BACKGROUND

A fundamental part of prevention is prediction. Potential predictors are the sine qua non of prediction models. However, whether incorporating novel predictors to prediction models could be directly translated to added predictive value remains an area of dispute. The difference between the predictive power of a predictive model with (enhanced model) and without (baseline model) a certain predictor is generally regarded as an indicator of the predictive value added by that predictor. Indices such as discrimination and calibration have long been used in this regard. Recently, the use of added predictive value has been suggested while comparing the predictive performances of the predictive models with and without novel biomarkers.

OBJECTIVES

User-friendly statistical software capable of implementing novel statistical procedures is conspicuously lacking. This shortcoming has restricted implementation of such novel model assessment methods. We aimed to construct Stata commands to help researchers obtain the aforementioned statistical indices.

MATERIALS AND METHODS

We have written Stata commands that are intended to help researchers obtain the following. 1, Nam-D'Agostino X² goodness of fit test; 2, Cut point-free and cut point-based net reclassification improvement index (NRI), relative absolute integrated discriminatory improvement index (IDI), and survival-based regression analyses. We applied the commands to real data on women participating in the Tehran lipid and glucose study (TLGS) to examine if information relating to a family history of premature cardiovascular disease (CVD), waist circumference, and fasting plasma glucose can improve predictive performance of Framingham's general CVD risk algorithm.

RESULTS

The command is adpredsurv for survival models.

CONCLUSIONS

Herein we have described the Stata package "adpredsurv" for calculation of the Nam-D'Agostino X² goodness of fit test as well as cut point-free and cut point-based NRI, relative and absolute IDI, and survival-based regression analyses. We hope this work encourages the use of novel methods in examining predictive capacity of the emerging plethora of novel biomarkers.

Incidence and risk factors of isolated systolic and diastolic hypertension: a 10 year follow-up of the Tehran Lipids and Glucose Study

The objective of this study is to examine the incidence and risk factors of isolated systolic hypertension (ISH) and isolated diastolic hypertension (IDH) in a Middle Eastern population, during a median follow-up of 9.6 years. In total, 8573 subjects without hypertension, cardiovascular disease and known diabetes were recruited into the study. To calculate the incidence of ISH, those with diastolic blood pressure (DBP) ≥ 90 mmHg during follow-up, and for calculating IDH those with systolic blood pressure (SBP) ≥ 140 mmHg during follow-up, were excluded. During follow-up, 235 new cases of ISH were identified, with a crude incidence rate of 5.7/1000 person-years; the corresponding values for IDH were 470 and 10.9/1000 person-years. Using backward stepwise Cox regression analysis, older age, baseline SBP and body mass index were related to incident ISH. Regarding IDH, younger age, baseline DBP and waist circumference were associated with higher risk, whereas female gender and being married were associated with lower risk (all p < 0.05). The C-statistics for the prediction model were 0.91 for ISH and 0.76 for IDH. In conclusion, after a decade of follow-up of this Iranian population, we found an incidence of about 0.5% and 1% per year for ISH and IDH, respectively.

Identification of Hypertension Predictors and Application to Hypertension Prediction in an Urban Han Chinese Population: A Longitudinal Study, 2005-2010

Introduction

Research suggests that targeting high-risk, nonhypertensive patients for preventive intervention may delay the onset of hypertension. We aimed to develop a biomarker-based risk prediction model for assessing hypertension risk in an urban Han Chinese population.

Methods

We analyzed data from 26,496 people with hypertension to extract factors from 11 check-up biomarkers. Then, depending on a 5-year follow-up cohort, a Cox model for predicting hypertension development was built by using extracted factors as predictors. Finally, we created a hypertension synthetic predictor (HSP) by weighting each factor with its risk for hypertension to develop a risk assessment matrix.

Results

After factor analysis, 5 risk factors were extracted from data for both men and women. After a 5-year follow-up, the cohort of participants had an area under receiver operating characteristic curve (area under the curve [AUC]) with an odds ratio (OR) of 0.755 (95% confidence interval [CI], 0.746–0.763) for men and an OR of 0.801 (95% CI, 0.792–0.810) for women. After tenfold cross validation, the AUC was still high, with 0.755 (95% CI, 0.746–0.763) for men and 0.800 (95% CI, 0.791–0.810) for women. An HSP-based 5-year risk matrix provided a convenient tool for risk appraisal.

Conclusion

Hypertension could be explained by 5 factors in a population sample of Chinese urban Han. The HSP may be useful in predicting hypertension.

Prehypertension Tsunami: A Decade Follow-Up of an Iranian Adult Population

OBJECTIVE

Prehypertension is associated with cardiovascular disease (CVD). There is no study to examine the incidence and risk factors of prehypertension in a sex stratified setting. The aim of this study was to examine the effect modification of sex for different risk factors which predicts the progression from normotension to prehypertension in a Middle East population-based cohort, during a median follow-up of 9.2 years.

METHODS

A multivariate Cox analysis was performed among 1466 and 2131 Iranian men and women, respectively, who were free of prehypertension, hypertension, CVD and diabetes at baseline and free of incident hypertension without preceding prehypertension at follow-up. Incident prehypertension at follow-up was defined as systolic blood pressure (SBP) of 120-139 mmHg and/or diastolic blood pressure (DBP) of 80-89 mmHg.

RESULTS

Overall, 1440 new cases of prehypertension were identified resulting in an incidence rate of 593/10000 person-years; the corresponding values for women and men were 489/10000 and 764/10000person-years, respectively. There were significant interactions between gender with age, DBP, waist-to-hip-ratio (WHpR) and estimated glomerular filtration rate (eGFR) (all P-values <0.05) in multivariate analysis. Strong associations were found between age, body mass index (BMI) and SBP with incident prehypertension in both genders. However, the effect of DBP and WHpR was significant among women and 2-hour post challenge plasma glucose (2h-PCPG)was an independent risk factor for men. In the sex-adjusted analysis, glomerular hyperfiltration [Hazard ratio (HR) and 95%CI: 1.01 (1.00-1.01), P-value = 0.02], age, BMI, WHpR, SBP and DBP had higher risks while being female [HR (95%CI): 0.81(0.69-0.94), P-value = 0.01] had a lower risk for incident prehypertension.

CONCLUSION

According to this study results, among Iranian population with high incidence of prehypertension, general adiposity and glomerular hyperfiltration in total, 2h-PCPG in men and central adiposity in women should be emphasized as risk factors for prehypertension.

The cumulative incidence of conventional risk factors of cardiovascular disease and their population attributable risk in an Iranian population: The Isfahan Cohort Study

Background:

Cardiovascular diseases (CVDs) are the leading cause of death in Iran. The present study evaluated the 7-year incidence of CVD risk factors among the participants of Isfahan cohort study (ICS).

Materials and Methods:

ICS was a longitudinal study on adults over 35 years of age from the urban and rural areas in three counties in central Iran. Data on clinical examination and blood measurements were collected in 2001. Subjects were followed and similar data were collected in 2007. Cumulative incidence was calculated through dividing new cases of each risk factor by the population free of that risk factor at baseline. Incidence proportion was determined for major CVD risk factors including hypertension (HTN), hypercholesterolemia (HC), hypertriglyceridemia (HTg), obesity, diabetes mellitus (DM), metabolic syndrome (MetS), and smoking.

Results:

A total number of 6323 adults free of CVDs were recruited. After 7 years of follow-up, 3283 individuals were re-evaluated in 2007. The participants’ age was 49.2 ± 10.3 years in 2001 (mean ± SD). The 7-year cumulative incidence of HTN, HC, HTg, overweight, obesity, DM, MetS, and smoking was 22.8%, 37.4%, 28.0%, 26.3%, 7.4%, 9.5%, 23.9%, and 5.9% in men and 22.2%, 55.4%, 33.5%, 35.0%, 18.8%, 11.3%, 36.1%, and 0.7% in women, respectively. Among those with overweight or obesity, 14.7% of men and 7.9% of women decreased their weight up to the normal level.

Conclusions:

The present study revealed a high incidence of CVD risk factors especially dyslipidemia, obesity, MetS and HTN. Therefore, the application of life-style modification interventions seems necessary.

Development of a risk prediction model for incident hypertension in a working-age Japanese male population

The aim of this study was to develop a risk prediction model for incident hypertension in a Japanese male population. Study participants included 15,025 nonhypertensive Japanese male workers (mean age, 38.8±8.9 years) who underwent an annual medical checkup at a company. The participants were followed-up for a median of 4.0 years to determine new-onset hypertension, defined as a systolic blood pressure (BP) ⩾140 mm Hg, a diastolic BP ⩾90 mm Hg, or the initiation of antihypertensive medication. Participants were divided into the following two cohorts for subsequent analyses: the derivation cohort (n=12,020, 80% of the study population) and the validation cohort (n=3005, the remaining 20% of the study population). In the derivation cohort, a multivariate Cox proportional hazards model demonstrated that age, body mass index, systolic and diastolic BP, current smoking status, excessive alcohol intake and parental history of hypertension were independent predictors of incident hypertension. Using these variables, a risk prediction model was constructed to estimate the 4-year risk of incident hypertension. In the validation cohort, the risk prediction model demonstrated high discrimination ability and acceptable calibration, with a C-statistic of 0.861 (95% confidence interval 0.844, 0.877) and a modified Hosmer-Lemeshow χ2 statistic of 15.2 (P=0.085). A risk score sheet was constructed to enable the simple calculation of the approximate 4-year probability of incident hypertension. In conclusion, a practical risk prediction model for incident hypertension was successfully developed in a working-age Japanese male population.

Incident hypertension and its predictors: the Isfahan Cohort Study

OBJECTIVES

The present study aimed to investigate the incidence and predictors of hypertension in an Iranian adult population.

METHODS

Isfahan Cohort Study was a longitudinal population-based study that was conducted on adults aged 35 years or older, living in urban and rural areas of three districts in central Iran. After 7 years of follow-up, 3283 participants were re-evaluated using a standard protocol similar to the baseline. At both measurements, participants underwent medical interview, physical examination, and fasting blood measurements. Participants (n = 833) with prevalent hypertension were excluded from the analysis, resulting in a sample size of 2450.

RESULTS

The participants' age was 47.3 ± 9.4 years (mean ± SD) and 50.7% were men. During the follow-up period, 542 (22.1%) individuals developed hypertension, 49.6% of whom were aware of their disease, 42.4% were treated, but only 24.9% were controlled. Incidence rates have shown no sex-specific difference across age and blood pressure (BP) categories. Multivariate-adjusted model controlled for all study covariates showed that age, male sex, general and central obesity, hypertriglyceridemia, impaired fasting glucose, diabetes mellitus, baseline BP at least 120/80  mmHg (nonoptimal BP), and parental history of hypertension independently contributed to the development of hypertension. Higher education level and more than 10% decrease in waist circumference over 7-year follow-up represented protective effects. In men, weight loss decreased and weight gain increased the risk of developing hypertension. Nonoptimal BP along with central obesity and hypertriglyceridemia together were responsible for 71% of the burden of hypertension.

CONCLUSION

Our findings imply that there are other factors in addition to nonoptimal BP that deserve integrating into the risk assessment criteria for developing hypertension.

Incidence of metabolic syndrome over 9 years follow-up; the importance of sex differences in the role of insulin resistance and other risk factors

To determine, the predictors of incident metabolic syndrome (MetS) in a community-based cohort of West Asians, during a mean follow-up of 9.3 years, a sample of 2858 non-MetS Iranian adults aged ≥ 20 years were examined at baseline and followed at three year intervals during three consecutive phases. The MetS was defined using the joint interim statement. Cox proportional hazard regression was used to determine the independent variables associated with incident MetS. Overall, 1117 new cases MetS were identified resulting in an incidence rate of 550.9/10000 person years (95% CI: 519.5-584.2). The corresponding incidence rates among women and men were 433.5/10000 person years (95% CI: 398.8-471.2) and 749.2/10000 person years (95% CI: 689.9-813.5), respectively. Baseline-adjusted predictors of developing MetS included all of the MetS components, being overweight or obese in both gender, and family history of diabetes and age only in women. There were significant effect modifications of gender on age (P<0.001), high blood pressure (0.026), high waist circumference (P<0001) and obesity categories (all P ≤ 0.01) in multivariate analysis. After considering HOMA–IR in the model, among women, all of the MetS predictors as well as those with HOMA-IR ≥ 2.23 showed a significant risk for incident MetS [HR: 1.63 (1.16-2.28)]; however, among men all the MetS components (WC was marginally significant) as well as the fourth quartile of HOMA-IR [HR: 1.50 (1.03-2.17)] and being overweight showed a significant risk. Finally, in the pooled analysis, we showed that female gender had lower risk for incident MetS than male [HR: 0.58 (0.47-0.70)]. In the Iranian population, high incidence of MetS, especially among men, was shown. Our findings confirmed that sex- specific risk predictors should be considered in primary prevention for incident MetS.

Predicting changes in hypertension control using electronic health records from a chronic disease management program

OBJECTIVE

Common chronic diseases such as hypertension are costly and difficult to manage. Our ultimate goal is to use data from electronic health records to predict the risk and timing of deterioration in hypertension control. Towards this goal, this work predicts the transition points at which hypertension is brought into, as well as pushed out of, control.

METHOD

In a cohort of 1294 patients with hypertension enrolled in a chronic disease management program at the Vanderbilt University Medical Center, patients are modeled as an array of features derived from the clinical domain over time, which are distilled into a core set using an information gain criteria regarding their predictive performance. A model for transition point prediction was then computed using a random forest classifier.

RESULTS

The most predictive features for transitions in hypertension control status included hypertension assessment patterns, comorbid diagnoses, procedures and medication history. The final random forest model achieved a c-statistic of 0.836 (95% CI 0.830 to 0.842) and an accuracy of 0.773 (95% CI 0.766 to 0.780).

CONCLUSIONS

This study achieved accurate prediction of transition points of hypertension control status, an important first step in the long-term goal of developing personalized hypertension management plans.

Risk models to predict hypertension: a systematic review

Background

As well as being a risk factor for cardiovascular disease, hypertension is also a health condition in its own right. Risk prediction models may be of value in identifying those individuals at risk of developing hypertension who are likely to benefit most from interventions.

Methods and Findings

To synthesize existing evidence on the performance of these models, we searched MEDLINE and EMBASE; examined bibliographies of retrieved articles; contacted experts in the field; and searched our own files. Dual review of identified studies was conducted. Included studies had to report on the development, validation, or impact analysis of a hypertension risk prediction model. For each publication, information was extracted on study design and characteristics, predictors, model discrimination, calibration and reclassification ability, validation and impact analysis. Eleven studies reporting on 15 different hypertension prediction risk models were identified. Age, sex, body mass index, diabetes status, and blood pressure variables were the most common predictor variables included in models. Most risk models had acceptable-to-good discriminatory ability (C-statistic>0.70) in the derivation sample. Calibration was less commonly assessed, but overall acceptable. Two hypertension risk models, the Framingham and Hopkins, have been externally validated, displaying acceptable-to-good discrimination, and C-statistic ranging from 0.71 to 0.81. Lack of individual-level data precluded analyses of the risk models in subgroups.

Conclusions

The discrimination ability of existing hypertension risk prediction tools is acceptable, but the impact of using these tools on prescriptions and outcomes of hypertension prevention is unclear.

Sex-specific predictors of the prehypertension-to-hypertension progression: community-based cohort of a West-Asian population

BACKGROUND

We aimed to predict prehypertension-to-hypertension progression rate among a West-Asian adult population.

METHODS

We analyzed data on 3449 adults (mean age 41.0 years), prehypertensive at baseline, attending at least one follow-up visit, contributing 25,079 person-years follow-up. A proportional hazard regression analysis was implemented to model the interval-censored progression-free survival time data using readily-assessable, commonly-available information. Integrated discriminatory improvement (IDI) and net reclassification improvement (NRI) indices were calculated to examine whether simple clinical information could help improve prediction of prehypertension-to-hypertension progression rate based on the blood pressure measures.

RESULTS

During a median seven-year follow-up 1412 prehypertensive patients progressed to hypertension with annual progression rate (95% confidence intervals (CIs)) being 56.9 (52.9-61.2) per 1000 women and 55.7 (51.7-60.0) per 1000 men (p = 0.007). High-density lipoprotein cholesterol levels were inversely associated with prehypertension-to-hypertension progression rate only among women (hazard ratio (1-SD): 0.93, 95% CIs: 0.86-0.100). Marital status retained its predictability among women even after multivariate adjustments. In both men and women, age, blood pressure measures, waist-to-height ratio, fasting plasma glucose and a history of cardiovascular disease independently predicted prehypertension-to-hypertension rate. The absolute (0.114, 95% CIs: 0.107-0.120) and relative (2.638, 95% CIs: 2.374-2.903) IDI and cutpoint-based (0.213, 95% CIs: 0.156-0.269) and cutpoint-free NRI (0.523, 95% CIs: 0.455-0.591) indicated that the prediction of the prehypertension-to-hypertension progression was improved by multivariable-models compared with blood pressure measures alone.

DISCUSSION

Easily-assessable, commonly-available information helped improve predictability of blood pressure measures for prehypertension-to-hypertension progression. Women's psycho-social characteristics (marital status) should be considered in prevention of prehypertension-to-hypertension progression.

Incidence of chronic kidney disease and its risk factors, results of over 10 year follow up in an Iranian cohort

To examine, the predictors of incident chronic kidney disease (CKD) in a community-based cohort of Middle East population, during a mean follow-up of 9.9 years. In a sample of 3313 non-CKD Iranian adults ≥20 years the estimated glomerular filtration rate (eGFR) was calculated at baseline and at three year intervals during three consecutive phases. The eGFR <60 mL/min/1.73 m2 was defined as CKD. Multivariate Logistic regression analysis was used to determine the independent variables associated with incident CKD. The incidence density rates of CKD were 285.3 and 132.6 per 10,000 person-year, among women and men, respectively. Female gender per se was associated with higher risk of CKD, compared with males. Among women, age, eGFR, known diabetes, being single or divorced/widowed, hypertension (marginally significant) and current smoking were independent risk factors for CKD; however the intermediate degree of education and family history of diabetes decreased the risk by 40% (P<0.05). Among male subjects, independent predictors of developing CKD included aging and hypertension (with significantly higher risk than in women, P for interaction<0.05), eGFR, new diagnosed diabetes, high normal blood pressure; abdominal obesity decreased the risk of CKD about 30% which was marginally significant. In the Iranian population,>2% of individuals develops CKD each year. Our findings confirmed that sex- specific risk predictors should be considered in primary prevention for incident CKD.