Equivalence Reliability and Convergent Validity of Percent Body Fat Prediction Equations

Peter D. Hart^{1, 2,}

¹Health Promotion Program, Montana State University - Northern, Havre, MT 59501

²Kinesmetrics Lab, Montana State University - Northern, Havre, MT 59501

Cite this paper:
Peter D. Hart. Equivalence Reliability and Convergent Validity of Percent Body Fat Prediction Equations. American Journal of Sports Science and Medicine. 2019; 7(2):45-50. doi: 10.12691/ajssm-7-2-4

Abstract

Background: The fitness professional may often benefit from the use of a simple equation in determining a health outcome for an individual in lieu of a more complicated or expensive procedure. Therefore, the purpose of this study was to examine the reliability and validity of several standard prediction equations for percent body fat (PBF). Methods: Data used for this study came from a body composition assessment of N = 131 college students. Five different PBF prediction equations were used, with body mass index (BMI), age, and sex as inputs for each (PBFEQ1 thru PBFEQ5). Additionally, PBF using a bioelectric impedance (BIA) handheld device (PBFHH) was measured for each participant. Equivalence reliability was examined across the five PBF prediction equations using different analysis of variance (ANOVA) models of the intraclass correlation coefficient (ICC). Convergent validity between the prediction equations and PBFHH was determined by examining Pearson correlation coefficients and Bland and Altman limits of agreement (LOA). Reliability and validity was also examined for obesity classification using the Kappa statistic. Results: Reliability across the five PBF prediction equations was excellent for all ICC models in both female (ICCs > .985) and male (ICCs > .976) analyses. PBFHH scores adequately converged with scores from each prediction equation in both female (rs > .913) and male (rs > .817) analyses. LOA between PBFHH and PBFEQ5 indicate small to moderate bias of 4.0 ± 5.1% and 4.7 ± 7.9% in female and male analyses, respectively. Finally, reliability and validity of the prediction equations to classify participants into obese and non-obese categories ranged from moderate to almost perfect. Conclusion: This study provides psychometric evidence supporting the use of PBF prediction equations in a college student population.

Keywords:
Body composition (BC) Percent body fat (PBF) obesity prediction equations

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Figures

References:

[1]	Kenney, W.L., Wilmore, J.H. and Costill, D.L., 2015. Physiology of sport and exercise. Human kinetics.
[2]	Morrow Jr, J.R., Mood, D., Disch, J. and Kang, M., 2015. Measurement and Evaluation in Human Performance, 5E. Human Kinetics.
[3]	Mittal, R., Goyal, M.M., Dasude, R.C., Quazi, S.Z. and Basak, A., 2011. Measuring obesity: results are poles apart obtained by BMI and bio-electrical impedance analysis. Journal of Biomedical Science and Engineering, 4(11), p.677.
[4]	Kanellakis, S., Skoufas, E., Khudokonenko, V., Apostolidou, E., Gerakiti, L., Andrioti, M.C., Bountouvi, E. and Manios, Y., 2017. Development and validation of two equations based on anthropometry, estimating body fat for the Greek adult population. Obesity, 25(2), pp.408-416.
[5]	Deurenberg, P., Weststrate, J.A. and Seidell, J.C., 1991. Body mass index as a measure of body fatness: age-and sex-specific prediction formulas. British journal of nutrition, 65(2), pp.105-114.
[6]	Deurenberg, P., Yap, M. and Van Staveren, W.A., 1998. Body mass index and percent body fat: a meta-analysis among different ethnic groups. International journal of obesity, 22(12), p.1164.
[7]	Gallagher, D., Visser, M., Sepulveda, D., Pierson, R.N., Harris, T. and Heymsfield, S.B., 1996. How useful is body mass index for comparison of body fatness across age, sex, and ethnic groups?. American journal of epidemiology, 143(3), pp.228-239.
[8]	Jackson, A.S., Pollock, M.L. and Ward, A.N.N., 1980. Generalized equations for predicting body density of women. Medicine and science in sports and exercise, 12(3), pp.175-181.
[9]	Jackson, A.S., Stanforth, P.R., Gagnon, J., Rankinen, T., Leon, A.S., Rao, D.C., Skinner, J.S., Bouchard, C. and Wilmore, J.H., 2002. The effect of sex, age and race on estimating percentage body fat from body mass index: The Heritage Family Study. International journal of obesity, 26(6), p.789.
[10]	American College of Sports Medicine. (2013). ACSM's guidelines for exercise testing and prescription. Lippincott Williams & Wilkins.
[11]	Omron Fat Loss Monitor. (2012). Model HBF-306C. Omron Healthcare Co., Ltd.
[12]	Shrout, P.E. and Fleiss, J.L., 1979. Intraclass correlations: uses in assessing rater reliability. Psychological bulletin, 86(2), p.420.
[13]	McGraw, K.O. and Wong, S.P., 1996. Forming inferences about some intraclass correlation coefficients. Psychological methods, 1(1), p.30.
[14]	Bland, J.M. and Altman, D., 1986. Statistical methods for assessing agreement between two methods of clinical measurement. The lancet, 327(8476), pp.307-310.
[15]	Guido, J.J., 2007. Guido’s Guide to PROC FREQ–A Tutorial for Beginners Using the SAS® System. In Proceedings of the 20th annual North East SAS Users Group Conference, Baltimore, MD.
[16]	Chen, B., Zaebst, D. and Seel, L., 2005, April. A macro to calculate kappa statistics for categorizations by multiple raters. In Proceeding of the 30th Annual SAS Users Group International Conference (pp. 155-30).
[17]	Koo, T.K. and Li, M.Y., 2016. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. Journal of chiropractic medicine, 15(2), pp.155-163.
[18]	Landis, J.R. and Koch, G.G., 1977. The measurement of observer agreement for categorical data. biometrics, pp.159-174.
[19]	Carlson, K.D. and Herdman, A.O., 2012. Understanding the impact of convergent validity on research results. Organizational Research Methods, 15(1), pp.17-32.
[20]	Cody, R. and Smith, J., 2005. Applied statistics and the SAS programming language. 403 p.
[21]	Hart, P. D. (2017). Test-retest stability of four common body composition assessments in college students. Journal of Physical Fitness, Medicine & Treatment in Sports. 1(2): 555561.