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Waist Circumference Correlates with Metabolic Syndrome Indicators Better Than Percentage Fat
Article first published online: 6 SEP 2012
2006 North American Association for the Study of Obesity (NAASO)
Volume 14, Issue 4, pages 727–736, April 2006
How to Cite
Shen, W., Punyanitya, M., Chen, J., Gallagher, D., Albu, J., Pi-Sunyer, X., Lewis, C. E., Grunfeld, C., Heshka, S. and Heymsfield, S. B. (2006), Waist Circumference Correlates with Metabolic Syndrome Indicators Better Than Percentage Fat. Obesity, 14: 727–736. doi: 10.1038/oby.2006.83
- Issue published online: 6 SEP 2012
- Article first published online: 6 SEP 2012
- Received for review June 27, 2005; Accepted in final form January 27, 2006
- body composition;
- health risk indicators
Objective: Percent fat is often considered the reference for establishing the magnitude of adipose tissue accumulation and the risk of excess adiposity. However, the increasing recognition of a strong link between central adiposity and metabolic disturbances led us to test whether waist circumference (WC) is more highly correlated with metabolic syndrome components than percent fat and other related anthropometric measures such as BMI.
Research Methods and Procedures: BMI, WC, and percent fat, measured by DXA, were evaluated in 1010 healthy white and African-American men and women [age, 48.3 ± 17.2 (standard deviation) years; BMI, 27.0 ± 5.3 kg/m2]. The associations of BMI, WC, and percent fat with age and laboratory-adjusted health risk indicators (i.e., serum glucose, insulin, triglycerides, high-density lipoprotein cholesterol, blood pressure) in each sex and ethnicity group were examined.
Results: For 18 of 24 comparisons, the age- and laboratory-adjusted correlations were lowest for percent fat and in 16 of 24 comparisons were highest for WC. Fifteen of the between-method differences reached statistical significance. With health risk indicator as the dependent variable and anthropometric measures as the independent variable, the contribution of percent fat to the WC regression model was not statistically significant; in contrast, adding WC to the percent fat regression model did make a significant independent contribution for most health risk indicators.
Discussion: WC had the strongest associations with health risk indicators, followed by BMI. Although percent fat is a useful measure of overall adiposity, health risks are best represented by the simply measured WC.