Predicting waist circumference from body mass
Being overweight or obese increases risk for cardiometabolic disorders. Although both bodymass index (BMI) and waist circumference (WC) measure the level of overweight andobesity, WC may be more important because of its closer relationship to total body fat.Because WC is typically not assessed in clinical practice, this study sought to develop andverify a model to predict WC from BMI and demographic data, and to use the predicted WCto assess cardiometabolic risk.
Data were obtained from the Third National Health and Nutrition Examination Survey(NHANES) and the Atherosclerosis Risk in Communities Study (ARIC).
We developedlinear regression models for men and women using NHANES data, fitting waistcircumference as a function of BMI. For validation, those regressions were applied to ARICdata, assigning a predicted WC to each individual.
We used the predicted WC to assessabdominal obesity and cardiometabolic risk.
The model correctly classified 88.4% of NHANES subjects with respect to abdominalobesity. Median differences between actual and predicted WC were 0.07 cm for men and0.11 cm for women.
In ARIC, the model closely estimated the observed WC (mediandifference: 0.34 cm for men, + 3.94 cm for women), correctly classifying 86.1% of ARICsubjects with respect to abdominal obesity and 91.5% to 99.5% as to cardiometabolic risk.The model is generalizable to Caucasian and African-American adult populations because itwas constructed from data on a large, population-based sample of men and women in theUnited States, and then validated in a population with a larger representation of African-Americans.
The model accurately estimates WC and identifies cardiometabolic risk. It should be usefulfor health care practitioners and public health officials who wish to identify individuals andpopulations at risk for cardiometabolic disease when WC data are unavailable.
Author: Sam R BozemanDavid C HoaglinTanya M BurtonChris L PashosRami H Ben-JosephChristopher S Hollenbeak Credits/Source: BMC Medical Research Methodology 2012, 12:115
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