Estimation of 10-Year Risk of Cardiovascular Diseases Using WHO Risk Prediction Charts: A Population-Based Study in Southern Iran

Rezaei, Fatemeh; Seif, Mozhgan; Fattahi, Mohammad Reza; Gandomkar, Abdullah; Hasanzadeh, Jafar

doi:10.18502/ijph.v51i7.10101

Cited by 4 publications

(3 citation statements)

References 27 publications

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“…It is important to evaluate the agreement between two 10-year risk prediction models of CVDs, including the WHO model (a region-specific model) and Globorisk (a country-specific model). Some previous studies in Iran determined the 10-year risk of CVDs with Framingham and WHO models [17][18][19] . However, no study has been conducted to evaluate the agreement and correlation between Globorisk and WHO risk prediction models.…”

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confidence: 99%

A comparative assessment between Globorisk and WHO cardiovascular disease risk scores: a population-based study

Dehghan,

Rezaei,

Aune

2023

Sci Rep

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The Globorisk and WHO cardiovascular risk prediction models are country-specific and region-specific, respectively. The goal of this study was to assess the agreement and correlation between the WHO and Globorisk 10-year cardiovascular disease risk prediction models. The baseline data of 6796 individuals aged 40–74 years who participated in the Fasa cohort study without a history of cardiovascular disease or stroke at baseline were included. In the WHO and Globorisk models scores were calculated using age, sex, systolic blood pressure (SBP), current smoking, diabetes, and total cholesterol for laboratory-based risk and age, sex, SBP, current smoking, and body mass index (BMI) for non-laboratory-based risk (office-based or BMI-based). In Globorisk and WHO risk agreement across risk categories (low, moderate, and high) was examined using the kappa statistic. Also, Pearson correlation coefficients and scatter plots were used to assess the correlation between Globorisk and WHO models. Bland–Altman plots were presented for determination agreement between Globorisk and WHO risk scores in individual’s level. In laboratory-based models, agreement across categories was substantial in the overall population (kappa values: 0.75) and also for females (kappa values: 0.74) and males (kappa values: 0.76), when evaluated separately. In non-laboratory-based models, agreement across categories was substantial for the whole population (kappa values: 0.78), and almost perfect for among males (kappa values: 0.82) and substantial for females (kappa values: 0.73). The results showed a very strong positive correlation (r ≥ 0.95) between WHO and Globorisk laboratory-based scores for the whole population, males, and females and also a very strong positive correlation (r > 0.95) between WHO and Globorisk non-laboratory-based scores for the whole population, males, and females. In the laboratory-based models, the limit of agreements was better in males (95%CI 2.1 to − 4.2%) than females (95%CI 4.3 to − 7.3%). Also, in the non-laboratory-based models, the limit of agreements was better in males (95%CI 2.9 to − 4.0%) than females (95%CI 3.2 to − 6.1%). There was a good agreement between both the laboratory-based and the non-laboratory-based WHO models and the Globorisk models. The correlation between two models was very strongly positive. However, in the Globorisk models, more people were in high-risk group than in the WHO models. The scatter plots and Bland–Altman plots showed systematic differences between the two scores that vary according to the level of risk. So, for these models may be necessary to modify the cut points of risk groups. The validity of these models must be determined for this population.

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confidence: 99%

A comparative assessment between Globorisk and WHO cardiovascular disease risk scores: a population-based study

Dehghan,

Rezaei,

Aune

2023

Sci Rep

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“…The studies have been estimated moderate and good agreements [ 12 – 15 ]. Framingham risk score, WHO risk assessment tool, and Systematic Coronary Risk Evaluation (SCORE) have been compared in Iran [ 16 – 20 ], there is currently no studies comparing Globorisk assessment tools. It is necessary to examine the agreement between the laboratory-based and office based versions of Globorisk.…”

Section: Introductionmentioning

confidence: 99%

Laboratory-based and office-based Globorisk scores to predict 10-year risk of cardiovascular diseases among Iranians: results from the Fasa PERSIAN cohort

Jahangiry

Dehghan

Farjam

et al. 2022

BMC Med Res Methodol

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Background Globorisk is a novel risk prediction model for predicting cardiovascular disease (CVD). Globorisk is a country-specific risk prediction model that determines CVD risk for all countries. This model has two versions; laboratory-based and office-based. This study aimed to determine the agreement between laboratory-based and office-based models in a large sample of the general population. Methods Baseline data from the Fasa cohort study was used for the current study. In total, 6810 participants ≥ 40 years without any history of cardiovascular disease or stroke were included in the study. To determine the laboratory-based risk model, factors include age, sex, current smoking status, history of diabetes, systolic blood pressure (SBP), and total cholesterol. To estimate the office-based risk model, factors were age, sex, current smoking status, SBP, and body mass index (BMI). Kappa statistics was used to distinguish the agreement between grouped scores in these two models. Additionally, correlation coefficients and scatter plots were used to determine the linear correlation between the two models. Results In this study 46.53% of the participants were men. The mean age (SD) of participants was 51.08 (7.88) years. Agreements between the two models were moderate and substantial in all women and all men, respectively. The agreement between the two CVD risk groups was 90.15% (kappa = 0.717) in all men, 92.94% (kappa = 0.571) among men aged < 60 years and 77.60% (kappa = 0.645) in men aged ≥ 60 years. The agreement between the two CVD risk groups was 86.68% (kappa = 0.572) among all women, 93.96% (kappa = 0.274) among women aged < 60 years and 62.46% (kappa = 0.422) among women aged ≥ 60 years. A very strong positive correlation (r = 0.94) was found between the two risk scores in all men, and it was similar among men aged < 60 years (r = 0.84) and men aged > 60 years (r = 0.94). Among all women, there was a very strong positive correlation (r = 0.87), and the strong positive correlation remained among < 60 years old (r = 0.76) and women > 60 years old (r = 0.76). Conclusion The Globorisk office-based model which is easier to use as it does not require blood testing can determine the risk groups in this population. The Globorisk office-based model may be used for CVD risk screening in low-middle income countries where resources are limited.

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“…There are several risk factors for CVDs that are generally divided into two categories: non-modifiable (age, sex, race, and family history) and modifiable (diabetes, lipid profile, hypertension, alcohol consumption, smoking, inadequate physical activity, inappropriate diet, and obesity) [ 8 , 9 ]. Behavioral, environmental, and social factors are the other risk factors for CVDs [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Incidence and risk factors of cardiovascular disease among population aged 40–70 years: a population-based cohort study in the South of Iran

et al. 2023

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Background Cardiovascular diseases are the main cause of mortality in the world. This study aimed to estimate the incidence and identify the risk factors of these diseases. Methods This prospective cohort study was performed on 9442 individuals aged 40–70 years in Kharameh, a city in the South of Iran, in 2015–2022. The subjects were followed up for 4 years. The demographic information, behavioral habits, biological parameters, and history of some diseases were examined. The density incidence of cardiovascular disease was calculated. The log-rank test was calculated to assess the cardiovascular incidence difference between men and women. Simple and multiple Cox regression with Firth's bias reduction method were used to identify the predictors of cardiovascular disease. Results The mean ± SD age of the participants was 51.4 ± 8.04 years, and the density incidence was estimated at 1.9 cases per 100,000 person-day. The log-rank test showed that men had a higher risk of cardiovascular disease than women. The Fisher's exact test showed a statistically significant difference between the incidence of cardiovascular diseases in different age groups, education levels, diabetes, and hypertension in men and women. The results of multiple Cox regression revealed that with increasing age, the risk of developing CVDs increased. In addition, the risk of cardiovascular disease is higher in people with kidney disease (HRadj = 3.4, 95% CI 1.3 to 8.7), men (HRadj = 2.3, 95% CI 1.7 to 3.2), individuals with hypertension (HRadj = 1.6, 95% CI 1.3 to 2.1), diabetics (HRadj = 2.3, 95%c CI 1.8 to 2.9), and alcohol consumption (HRadj = 1.5, 95% CI 1.09 to 2.2). Conclusions In the present study, diabetes, hypertension, age, male gender, and alcohol consumption were identified as the risk factors for cardiovascular diseases; three variables of diabetes, hypertension and alcohol consumption were among the modifiable risk factors, so if they were removed, the incidence of cardiovascular disease could greatly reduce. Therefore, it is necessary to develop strategies for appropriate interventions to remove these risk factors.

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Estimation of 10-Year Risk of Cardiovascular Diseases Using WHO Risk Prediction Charts: A Population-Based Study in Southern Iran

Cited by 4 publications

References 27 publications

A comparative assessment between Globorisk and WHO cardiovascular disease risk scores: a population-based study

A comparative assessment between Globorisk and WHO cardiovascular disease risk scores: a population-based study

Laboratory-based and office-based Globorisk scores to predict 10-year risk of cardiovascular diseases among Iranians: results from the Fasa PERSIAN cohort

Incidence and risk factors of cardiovascular disease among population aged 40–70 years: a population-based cohort study in the South of Iran

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