HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Full Text Full Text (PDF) Purchase Article View Shopping Cart Alert me when this article is cited Alert me if a correction is posted Citation Map Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Janssen, I. Articles by Ross, R. Search for Related Content PubMed PubMed Citation Articles by Janssen, I. Articles by Ross, R. Agricola Articles by Janssen, I. Articles by Ross, R.

Body mass index and waist circumference independently contribute to the prediction of nonabdominal, abdominal subcutaneous, and visceral fat^1,2,3

¹ From the School of Physical and Health Education, Queen's University, Kingston, Canada (IJ and RR); the Obesity Research Center, St Luke's– Roosevelt Hospital, Institute of Human Nutrition, Columbia University, College of Physicians and Surgeons, New York (SBH, DBA, and DPK); and the Department of Biostatistics and Center for Research on Clinical Nutrition, University of Alabama at Birmingham (DBA).

Background: It is unknown whether the ability of waist circumference (WC) to predict health risk beyond that predicted by body mass index (BMI) alone is explained in part by the ability of WC to identify those with elevated concentrations of total or abdominal fat.

Objective: We sought to determine whether BMI and WC independently contribute to the prediction of nonabdominal (total fat - abdominal fat), abdominal subcutaneous, and visceral fat.

Design: Fat distribution was measured by magnetic resonance imaging in 341 white men and women. Multiple regression analysis was performed to measure whether the combination of BMI and WC explained a greater variance in nonabdominal, abdominal subcutaneous, and visceral fat than did BMI or WC alone. These fat depots were also compared after a subdivision of the cohort into 3 BMI (normal, overweight, and class I obese) and 3 WC (low, intermediate, and high) categories according to the classification system used to identify associations between BMI, WC, and health risk.

Results: Independent of age and sex, the combination of BMI and WC explained a greater variance in nonabdominal, abdominal subcutaneous, and visceral fat than did either BMI or WC alone (P < 0.05). For nonabdominal and abdominal subcutaneous fat, BMI was the strongest correlate; thus, by adding BMI to WC, the variance accrued was greater than when WC was added to BMI. However, when WC was added to BMI, the added variance explained for visceral fat was greater than when BMI was added to WC. Furthermore, within each of the 3 BMI categories studied, an increase in the WC category was associated with an increase in visceral fat (P < 0.05).

Conclusions: BMI and WC independently contribute to the prediction of nonabdominal, abdominal subcutaneous, and visceral fat in white men and women. These observations reinforce the importance of using both BMI and WC in clinical practice.

Key Words: Body mass index • waist circumference • body fat • abdominal fat • visceral fat