Clinical InvestigationAccuracy of Anthropometric Parameters in Identification of High-risk Patients Predicted With Cardiovascular Risk Models
Section snippets
Study Population
Medical records of 4516 consecutive patients who visited Vali-Asr hospital diabetes, nutrition and metabolism outpatient clinic (Tehran, Iran) between June 2008 and September 2010 were reviewed. Patients’ medical data were recorded as part of their regular clinical care. No consent form was available for 204 patients. Patients with known history of CVD (n = 376), less than 18 years (n = 29), and those with missing values on any of the anthropometric measures (ie, waist circumference [WC], hip
RESULTS
Table 1 outlines the characteristics of study subjects. Women comprised the majority of study sample (70.6%). Based on UKPDS scoring scheme, 11.5% of women and 32.3% of men had a high 10-year risk for developing CHD. Also, according to SCORE, 4.3% of women and 22.5% of men were classified as high risk for CVD mortality. Finally, using Framingham equation, 13.7% of women and 32.2% of men were classified as high risk for developing CVD in the next 10 years (Table 2). Evaluation of the level of
DISCUSSION
In the present study, ability of anthropometric parameters in identification of patients being at high risk for CVD was investigated. WHR, followed by WHtR, presented better discriminatory ability compared with other indices. Along the same lines, a number of studies have reported that WHR is a better predictor of CVD risk factors. In a study of 1587 men, Yan et al27 observed that compared with BMI, WHR is a better predictor of subclinical atherosclerosis (AUC = 0.65) evaluated via carotid
REFERENCES (37)
- et al.
Dyslipidemia intervention in metabolic syndrome: emphasis on improving lipids and clinical event reduction
Am J Med Sci
(2011) Obesity cardiomyopathy: pathophysiology and evolution of the clinical syndrome
Am J Med Sci
(2001)- et al.
Obesity and cardiovascular disease: risk factor, paradox, and impact of weight loss
J Am Coll Cardiol
(2009) - et al.
Cardiovascular disease risk profiles
Am Heart J
(1991) - et al.
Waist to stature ratio is more strongly associated with cardiovascular risk factors than other simple anthropometric indices
Ann Epidemiol
(2003) - et al.
The differential association between various anthropometric indices of obesity and subclinical atherosclerosis
Atherosclerosis
(2009) - et al.
Measures of obesity and cardiovascular risk among men and women
J Am Coll Cardiol
(2008) - et al.
Obesity and the risk of myocardial infarction in 27,000 participants from 52 countries: a case-control study
Lancet
(2005) - et al.
Abdominal obesity: the cholesterol of the 21st century?
Can J Cardiol
(2008) The emerging epidemic of obesity in developing countries
Int J Epidemiol
(2006)
Obesity in adulthood and its consequences for life expectancy: a life-table analysis
Ann Intern Med
Overweight, obesity, and blood pressure: the effects of modest weight reduction
Obes Res
Overweight and obesity as determinants of cardiovascular risk: the Framingham experience
Arch Intern Med
Overweight and obesity (high body mass index)
General and abdominal adiposity and risk of death in Europe
N Engl J Med
Computer modeling of diabetes and its complications: a report on the Fourth Mount Hood Challenge Meeting
Diabetes Care
Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project
Eur Heart J
UK Prospective Diabetes Study (UKPDS). VIII. Study design, progress and performance
Diabetologia
Cited by (11)
Incidence, early case fatality and determinants of stroke in Iran: Golestan Cohort Study
2022, Journal of Stroke and Cerebrovascular DiseasesCitation Excerpt :We used the waist-to-hip ratio (WHR) as an indicator of obesity. For WHR, the cut-off points in the Iranian population were applied for categorizing “normal” and “abnormal” values (0.92 for men and 0.88 for women).23 Descriptive analyses were performed to report baseline characteristics of the population.
Evaluation of DNA damage profile in obese women and its association to risk of metabolic syndrome, polycystic ovary syndrome and recurrent preeclampsia
2018, Genes and DiseasesCitation Excerpt :The WHR is likely the major risk factor for the development of type 2 diabetes30 and it is a very important factor in determining those at high risk of prediabetes cases. Furthermore, WHR seems to be the best marker in predicting cardiovascular outcomes that result from many chronic diseases.31–33 The metabolic changes happened during hyperglycemic state might cause an increase in the reactive oxygen species (ROS) where polyol pathway is activated.
Assessment of DNA damage in obese premenopausal women with metabolic syndrome
2018, Gene ReportsCitation Excerpt :Moreover, in another study that evaluated 2261 non-diabetic rural Chinese participants, the WHR has found to be very important determining factor that indicates those at high risk of prediabetes cases. The WHR is seemingly the best marker for predicting cardiovascular outcomes secondary to many chronic diseases (Organization, 2000; Who and Consultation, 2003; Qiao and Nyamdorj, 2010; Esteghamati et al., 2013). Comet assay results of the present study are not only significantly different in MS compared to controls, but they are also positively correlated with several MS features, highlighting the value of these assays as biomarkers.
Lowered cutoff points of obesity indicators are better predictors of hypertension and diabetes mellitus in premenopausal Taiwanese women
2015, Obesity Research and Clinical PracticeCitation Excerpt :Furthermore, the WHR was significantly correlated with the risk of mortality in old-aged women [10]. A study by Esteghamati et al. [11] on 4615 individuals aged >18 years showed that the WHR is the best predictor of cardiovascular risk. The Chinese Taipei Association for the Study of Obesity [12] suggested that women with a WHR of >0.85 were more susceptible to chronic diseases, including CVD, HT, atherosclerosis, DM, and hyperlipidemia.
Evaluation of plasma MMP-8, MMP-9 and TIMP-1 identifies candidate cardiometabolic risk marker in metabolic syndrome: Results from double-blinded nested case-control study
2015, Metabolism: Clinical and ExperimentalCitation Excerpt :Diabetes subjects began their treatment by lifestyle modification, glibenclamide, and/or metformin. Multiple cross-sectional studies demonstrated the characteristics of a selected sample of the original cohort, during years of follow-up [24–29]. Surveyed population for this study was selected from 522 nondiabetic staff of a private company who were under the coverage of eastern health surveillance center (Fig. 1).
The authors declare no conflict of interest.