a1 National Institute on Aging, NIA/NIH-IRP, NIH Biomedical Research Center, 251 Bayview Blvd, Suite 100–Room 04B118, Baltimore, MD 21224, USA
a2 Department of Health, Nutrition and Exercise Sciences, University of Delaware, Newark, DE, USA
a3 Center for Human Nutrition, Department of International Health, Johns Hopkins University, Baltimore, MD, USA
a4 Statistical Information Systems, MedStar Research Institute, Baltimore, MD, USA
Objective To assess the predictive values of various adiposity indices for metabolic syndrome (MetS) among adults using baseline data from the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) cohort.
Design In a cross-sectional study, BMI, waist circumference (WC), body composition by dual-energy X-ray absorptiometry (DEXA) and metabolic risk factors such as TAG, HDL cholesterol, blood pressure, fasting glucose and insulin, uric acid and C-reactive protein were measured. Receiver-operating characteristic (ROC) curves and logistic regression analyses were conducted.
Setting Baltimore, Maryland.
Subjects White and African-American US adults (n 1981), aged 30–64 years.
Results In predicting risk of MetS using obesity-independent National Cholesterol Education Program Adult Treatment Panel III criteria, percentage total body fat mass (TtFM) assessed using DEXA measuring overall adiposity had no added value over WC. This was true among both men (area under the ROC curve (AUC) = 0·680 v. 0·733 for TtFM and WC, respectively; P < 0·05) and women (AUC = 0·581 v. 0·686). Percentage rib fat mass (RbFM) was superior to TtFM only in women for MetS (AUC = 0·701 and 0·581 for RbFM and TtFM, respectively; P < 0·05), particularly among African-American women. Elevated percentage leg fat mass (LgFM) was protective against MetS among African-American men. Among white men, BMI was inferior to WC in predicting MetS. Optimal WC cut-off points varied across ethnic–sex groups and differed from those recommended by the National Institutes of Health/North American Association for the Study of Obesity.
Conclusions The study provides evidence that WC is among the most powerful tools to predict MetS, and that optimal cut-off points for various indices including WC may differ by sex and race.
(Received March 31 2010)
(Accepted August 07 2010)
(Online publication September 21 2010)
† Co-senior authors.