Disclosure: The authors declare no conflict of interest.
Simple anthropometrics are more correlated with health variables than are estimates of body composition in Yup'ik people
Article first published online: 10 MAY 2013
Copyright © 2012 The Obesity Society
Volume 21, Issue 9, pages E435–E438, September 2013
How to Cite
Bray, M., Pomeroy, J., Knowler, W. C., Bersamin, A., Hopkins, S., Brage, S., Stanhope, K., Havel, P. J. and Boyer, B. B. (2013), Simple anthropometrics are more correlated with health variables than are estimates of body composition in Yup'ik people. Obesity, 21: E435–E438. doi: 10.1002/oby.20125
Funding agencies: This study was supported by Award Number R01DK074842 and P20RR016430 (Boyer). Dr. Peter Havel's laboratory receives support from National Institutes of Health grants HL075675, HL091333, HL107256, AT003545, and DK097307. This work was supported in part by the Intramural Research Program of the National Institute of Diabetes and Digestive and Kidney Diseases and funding to the University of Alaska President for dedicating unrestricted funds from British Petroleum and ConocoPhillips.
- Issue published online: 23 SEP 2013
- Article first published online: 10 MAY 2013
- Accepted manuscript online: 5 NOV 2012 05:49PM EST
- Manuscript Accepted: 10 SEP 2012
- Manuscript Received: 21 DEC 2011
To (1) evaluate the relationships between several indices of obesity with obesity-related risk factors; (2) compare the accuracy of body composition estimates derived from anthropometry and bioimpedance analysis (BIA) to estimates of body composition assessed by doubly-labeled water (DLW); and (3) establish equations for estimating fat mass (FM), fat-free mass (FFM), and percent body fat (PBF) in Yup'ik people.
Design and Methods
Participants included 1,056 adult Yup'ik people from 11 communities in Southwestern Alaska. In a sub-study of 30 participants, we developed population-specific linear regression models for estimating FM, FFM, and PBF from anthropometrics, age, sex, and BIA against criterion measures derived from total body water assessed with DLW. These models were then used with the population cohort and we analyzed the relationships between obesity indices and several health-related and disease status variables: (1) fasting plasma lipids, (2) glucose, (3) HbA1c, (4) adiponectin, (5) blood pressure, (6) diabetes (DM), and (7) cerebrocoronary vascular disease (CCVD) which includes stroke and heart disease.
The best model for estimating FM in the sub-study used only three variables—sex, waist circumference (WC), and hip circumference and had multiple R2 = 0.9730. FFM and PBF were calculated from FM and body weight.
WC and other anthropometrics were more highly correlated with a number of obesity-related risk factors than were direct estimates of body composition. Body composition in Yup'ik people can be accurately estimated from simple anthropometrics.