Appropriate cutoff values of anthropometric variables to predict cardiovascular outcomes: 7.6 years follow-up in an Iranian population

Hadaegh, Farzad; Zabetian, Azadeh; Sarbakhsh, Parvin; Khalili, Davood; James, W. P. T.; Azizi, Fereidoun

doi:10.1038/ijo.2009.180

Cited by 110 publications

(93 citation statements)

References 42 publications

(47 reference statements)

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“…According to our findings, remarkable portion of obesity effect appears to operate through the mediators (high excess risk), a phenomenon that has also been shown by other studies (18)(19)(20). Consequently, although fully adjusted models including mediators are subject to over-adjustment, proper cut-off points should not be determined without taking into account other metabolic risks.…”

Section: Discussionsupporting

confidence: 68%

“…In Iran, two published cross-sectional studies resulted in contradictory findings regarding both values and gender differences that were 91.5/85.5 cm versus 89/91 cm in men/women (1; 23). The only report that was based on longitudinal data recommended 94.5 cm for both men and women (18). Based on these studies, the Ministry of Health in Iran has recently declared that the cut-off values for central obesity in men and women would be 95 cm for preventive purposes (6).…”

Section: Discussionmentioning

confidence: 99%

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Appropriate Cut-off Values of Waist Circumference to Predict Cardiovascular Outcomes: 7-year Follow-up in an Iranian Population

et al. 2012

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Objective Due to the lack of compelling evidence for waist circumference (WC) as a cardiovascular disease (CVD) risk factor in many ethnic groups, the need for local research has been expressed by international authorities. This study was undertaken to determine the optimal cut-off points of WC for predicting incident CVD and metabolic syndrome in an Iranian population. Materials and Methods A total of 6,504 participants from three areas in central Iran were followed over 7 years. Receiver operating characteristics (ROC) and area under the curve (AUC) were used to identify the maximum value of sensitivity and specificity combinations corresponding to the appropriate cut-off points of WC for the detection of the metabolic syndrome and CVD events. The optimal cut-off values were defined as the point at which the value of "sensitivity+specificity-1" reached the maximum value. Finally, Cox proportional hazard modeling was used to determine which cut-off point was better fit in the CVD risk prediction model. Results After 394,418 person-years of follow-up, 427 incident primary CVD events (233 men) were identified. Considering CVD, the optimum cut-off points were 99/103.5 cm (men/women) but these had a low sensitivity (AUC: 0.59, 95%CI 0.55-0.63 in both men and women). The second highest values for discriminating CVD were 93/97 cm that resulted in acceptable sensitivity. Regarding the metabolic syndrome, 92.6/97.8 cm were identified as optimum (AUC: 0.67, 95%CI 0.65-0.69 in men and 0.65, 95%CI 0.63-0.67 in women). The best cut-off values that fit in the Cox regression model were 90/97 cm. Conclusion International recommended WC cut-off values for the Middle East are not appropriate compared to the locally defined cut-off values in Iran.

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Section: Discussionsupporting

confidence: 68%

Section: Discussionmentioning

confidence: 99%

Appropriate Cut-off Values of Waist Circumference to Predict Cardiovascular Outcomes: 7-year Follow-up in an Iranian Population

et al. 2012

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“…A number of studies have suggested that WC is a good indicator for predicting the risk of cardiovascular disease (28,29), while other studies have shown that waisthip ratio is a better indicator for predicting the risk of cardiovascular disease compared to WC and BMI (30). Yusuf and colleagues reported in their study that, waist-toheight ratio as an indicator of central obesity is a better predictor of cardiovascular events compared to WC and BMI in both sexes (31).…”

Section: Discussionmentioning

confidence: 98%

Anthropometric Indices and Their Relationship With Coronary Artery Diseases

et al. 2015

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Background: Despite efforts made by the medical community and public health officials for combating 76 obesity, the prevalence of overweight and obesity has increased over the past 20 years. 77 Obesity was associated with some cardiovascular risk factors and increased the incidence of 78 cardiovascular disease. Diagnosis of Coronary Artery Disease (CAD) in patients with obesity 79 will affect secondary prevention of the disease and management programs; for this reason it is 80 necessary to use a suitable method for determining obesity Objectives: The current study aimed to investigate the relationship between some anthropometric indices and Coronary Artery Disease (CAD) risk factors and also to determine predictive factors of CAD among the indices. Patients and Methods:This cross-sectional study was performed on 300 men and nonpregnant woman with CAD aged 18 -60 years referred to Hazrate Rasool Hospital in Tehran, Iran. Anthropometric indices, including waist circumference, waist-to-height ratio, Neck Circumference (NC), body mass index and Abdominal Volume Index (AVI) and hematological factors were measured using the standard methods. According to angiography reports, the participants were divided into patients with or without CAD. To evaluate the possible correlations between anthropometric indices and CAD risk factors, Pearson correlation coefficients were used. The Receiver operating characteristic (ROC) curve was used to determine the sensitivity and specificity and the best cut-off point of anthropometric indices. Results: The mean age of the CAD-positive group was 53.43 ± 4.96 years and the mean age of the CAD-negative group was 49.9 ± 6.83 years (P > 0.05). All of the anthropometric indices and cardiovascular risk factors were higher in the CAD-positive group, while there was a significance correlation between HDL-c (High-density lipoprotein) and these risk factors (P < 0.05). The area under the curve of AVI had the highest value (0.722) compared to other anthropometric indices. The results of multiple-regression analysis showed that NC was a better predictor of the risk of CAD compared to other anthropometric indices (P = 0.46, OR = 1.207 and CI = 1.004 -1.451). Conclusions: According to the results of the study, abdominal obesity is as a risk factor for atherosclerosis. Therefore, the use of a simple, low cost and high precision method for determining visceral obesity and preventing the CAD is warranted.

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“…is not straightforward. In Tehran Lipid and Glucose Study, there was no difference between central obesity variables in predicting CVD in males, but in females WHpR and WHtR were better than WC and BMI [29]. In another paper from the same country, BMI or WHpR predicted the onset of diabetes mellitus after 3.6 years of follow-up in subjects aged less than 60 years.…”

Section: Which Anthropometric Index Is the Best?mentioning

confidence: 86%

Editorial-Body Mass Index, Waist-to-Height Ratio, Cardiometabolic Risk Factors and Diseases in a New Obesity Classification Proposal

Can¹

2011

TOOBESJ

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Abstract:In this mini-hot topic issue, methods of body composition analysis are reviewed, a new shape chart based on waist-to-height ratio is presented and a new obesity classification system is proposed. Anthropometric indices are surrogate measures of body fat and are cost-free, practical and easy to interpret for health care providers and lay people. The answer to the question of "the best anthropometric index" varies according to study design, geographic area, characteristics of the study population and the outcome assessed. Recent studies suggest using measures of general obesity and abdominal obesity for assessment of excess body fat. The use of waist-to-height ratio as a global anthropometric index for children and adults is suggested in this mini-hot topic. Anthropometric indices have a good performance in predicting health risks in epidemiologic studies, but by themselves have limited use in treatment decisions of individual obese patients. Body mass index is strongly correlated with total body adipose tissue mass and is a measure of general obesity. Current classification of obesity is based on body mass index, an anthropometric index that does not inform about body fat distribution, is not a powerful discriminator of cardiometabolic risk factors and does not convey information about the presence of risk factors or co-morbidities. Therefore, a new obesity classification system is needed. I suggest this should be based on body mass index, waist-to-height ratio and obesity associated risk factors and diseases. Future studies should focus on seeing how the proposed obesity classification system works in different populations.

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Appropriate cutoff values of anthropometric variables to predict cardiovascular outcomes: 7.6 years follow-up in an Iranian population

Cited by 110 publications

References 42 publications

Appropriate Cut-off Values of Waist Circumference to Predict Cardiovascular Outcomes: 7-year Follow-up in an Iranian Population

Appropriate Cut-off Values of Waist Circumference to Predict Cardiovascular Outcomes: 7-year Follow-up in an Iranian Population

Anthropometric Indices and Their Relationship With Coronary Artery Diseases

Editorial-Body Mass Index, Waist-to-Height Ratio, Cardiometabolic Risk Factors and Diseases in a New Obesity Classification Proposal

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