Hostname: page-component-7c8c6479df-ws8qp Total loading time: 0 Render date: 2024-03-28T10:43:09.599Z Has data issue: false hasContentIssue false

Generalized equations for predicting body density of men

Published online by Cambridge University Press:  09 March 2007

A. S. Jackson
Affiliation:
Wake Forest University, Winston-Salem, North Carolina and Institute of Aerobics Research, Dallas, Texas, USA
M. L. Pollock
Affiliation:
Wake Forest University, Winston-Salem, North Carolina and Institute of Aerobics Research, Dallas, Texas, USA
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

1. Skinfold thickness, body circumferences and body density were measured in samples of 308 and ninety-five adult men ranging in age from 18 to 61 years.

2. Using the sample of 308 men, multiple regression equations were calculated to estimate body density using either the quadratic or log form of the sum of skinfolds, in combination with age, waist and forearm circumference.

3. The multiple correlations for the equations exceeded 0.90 with standard errors of approximately ±0.0073 g/ml.

4. The regression equations were cross validated on the second sample of ninety-five men. The correlations between predicted and laboratory-determined body density exceeded 0.90 with standard errors of approximately 0.0077 g/ml.

5. The regression equations were shown to be valid for adult men varying in age and fatness.

Type
Papers of direct relevance to Clinical and Human Nutrition
Copyright
Copyright © The Nutrition Society 1978

References

Allen, T. H., Peng, M. T., Chen, K. P., Huang, T. F., Chang, C. & Fang, H. S. (1956). Metabolism 5, 346.Google Scholar
Behnke, A. R. & Wilmore, J. H. (1974). Evaluation and Regulation of Body Build and Composition. Engle-wood Cliffs: Prentice-Hall.Google Scholar
Brožek, J., Grande, F., Anderson, J. T. & Keys, A. (1963). Ann. N. Y. Acad. Sci. 110, 113.Google Scholar
Brožek, J. & Keys, A. (1951). Br. J. Nutr. 5, 194.Google Scholar
Chen, S., Peng, M. T., Chen, K. P., Huang, T. F., Chang, C. & Fang, H. S. (1975). J. appl. Physiol. 39, 825.Google Scholar
Durnin, J. V. G. A. & Rahaman, M. M. (1967). Br. J. Nutr. 21, 681.Google Scholar
Goldman, R. F. & Buskirk, E. R. (1961). In Techniques for Measuring Body Composition, p. 78 [Brožek, J. and Henschels, A., editors]. Washington, DC: National Academy of Science.Google Scholar
Jackson, A. S. & Pollock, M. L. (1976). Med. Sci. Sports 8, 196.Google Scholar
Katch, F. I. (1968). Research Quarterly 39, 993.Google Scholar
Katch, F. I. & McArdle, W. D. (1973). Human Biol. 45, 445.Google Scholar
Kerlinger, F. N. & Pedhazur, E. S. (1973). Multiple Regression in Behavioral Research. New York: Holt, Rinehart and Winston.Google Scholar
Keys, A. (1956) Human Biol. 28, 111.Google Scholar
Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores, pp. 285288. Reading, Mass.: Addison-Wesley.Google Scholar
Pascale, L. R., Grossman, M. I., Sloane, H. S. & Frankel, T. (1956). Human Biol. 28, 165.Google Scholar
Pollock, M. L., Hickman, T., Kendrick, Z., Jackson, A. S., Linnerud, A. C. & Dawson, G. (1976). J. appl. Physiol. 40, 300.Google Scholar
Pollock, M. L., Jackson, A. S., Ayres, J., Ward, A., Linnerud, A. & Gettman, L. (1976). Ann. N.Y. Acad. Sci. 301, 361.Google Scholar
Siri, W. E. (1961). In Techniques for Measuring Body Composition, p. 223 [Brožek, J. and Hanschels, A., editors]. Washington DC: National Academy of Science.Google Scholar
Sloan, A. W. (1967). J. appl. Physiol. 23, 311.Google Scholar
Wilmore, J. H. & Behnke, A. R. (1969). J. appl. Physiol. 27, 25.Google Scholar
Wright, H. F. & Wilmore, J. H. (1974). Aerospace Med. 45, 301.Google Scholar