Are waist circumference, sagittal abdominal diameter, and waist-to-height ratio better predictors of cardiovascular risk than BMI?

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2018-03-14

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Nandy, Karabi
Khan, Mahbuba

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Purpose: Diseases of the heart are the leading causes of death in the US for adults. Obesity, having excess body fat, is one of the major risk factors for heart diseases. Body mass index (BMI) is one of the popular surrogate measures of excess body fat, and it is established as a predictor of cardiovascular risk. However, ethnicity, age, and sex may also influence the association of BMI and excess fat. While abdominal obesity is associated with metabolic syndrome (a composite risk factor for heart disease), BMI does not account abdominal fat; rather it accounts for the overall excess fat. The purpose of this study was to evaluate waist circumference, sagittal abdominal diameter, and waist-to-hip ratio as surrogate measures of abdominal obesity, and compare their performance with BMI as a predictor of heart disease risk. Methods: We used data from National Health and Nutrition Examination Survey (NHANES) 2013-2014 for this study. A total of 5,033 adult subjects (mean age 50.85 years and 54% female) participated the survey. We used high-density lipoprotein (HDL) as a risk factor for heart diseases. Univariate analyses were carried out to assess the strength of association between HDL and waist circumference, sagittal abdominal diameter, waist-to-hip ratio, and BMI. We will estimate the strength of different body fat measures separately to predict the heart disease risk (HDL Results: Average HDL was 52.79 mg/dL and nearly one-fifth of the participants were at risk of heart diseases (HDL/dL). Average BMI, waist circumference and sagittal abdominal diameter were 29.05 kg/m2, 98.93 cm, 22.65 cm, respectively. Our preliminary, unadjusted and unweighted, findings suggested that sagittal abdominal diameter was a slightly better predictor of low HDL than waist circumference and BMI; Pearson correlation coefficients were -0.35, -0.34, and -0.27, respectively. We will further estimate the predictability of waist circumference, sagittal abdominal diameter, waist-to-height ratio, and BMI using logistic regression after adjusting for demographic and socioeconomic status. Conclusions: Findings of this study will help health practitioners to use a better predictor to screen people who are at risk of heart diseases.

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