Use of Loglinear Models to Investigate the Patterns of Association among Fitness Test Performances

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. Use of Loglinear Models to Investigate the Patterns of Association among Fitness Test Performances. American Journal of Sports Science and Medicine. 2018; 6(3):84-88. doi: 10.12691/AJSSM-6-3-4

Abstract

Background: Physical fitness tests are often administered as a battery, allowing for several different fitness scores. Furthermore, fitness scores are generally considered outcome variables, with no one test causing the performance of another. Therefore, using loglinear models to examine the relationship between fitness test performances is appropriate. Methods: This study used data from a campus-based fitness study of college students. Four physical fitness measures were used in the analysis. Cardiorespiratory fitness (CRF) was assessed by a multi-stage running test (VO2_max, ml/kg/min). Lower-body power was assessed by a countermovement vertical jump (VJ) test (inches). Muscular endurance was assessed by a maximal push-up (PU) test (repetitions). Muscular strength was assessed by a 1RM bench press (BP) test. Participants were categorized into high or low fitness groups using each sex-specific fitness score median. Results: Results of the initial hierarchical loglinear models indicated no significant four-way or three-way interactions. A simplified loglinear model with all two-factor interactions provided adequate fit to the data. The odds of high BP performance were much greater with high PU (OR=3.2) and VJ (OR=2.3) performance. The odds of high CRF performance were also greater with high PU (OR=2.4) and VJ (OR=2.7) performance. Finally, odds of high PU performance were much greater with high VJ (OR=3.6) performance. CRF and BP were statistically independent. Conclusion: Results from this study indicate that the performance on a fitness test can be related to at least one other fitness test performance.

Keywords

physical fitness, loglinear models, human performance, mosaic plot

Copyright

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/

References

[1]	Oja, P., & Tuxworth, B. (Eds.). (1995). Eurofit for adults: Assessment of health-related fitness. Council of Europe.
[2]	Suni, J., Husu, P., & Rinne, M. (2009). Fitness for health: the ALPHA-FIT test battery for adults aged 18–69. Tester’s Manual. Tampare, Finland: Published by European Union DS, and the UKK Institute for Health Promotion Research.
[3]	Lemmink, K. A., Han, K., de Greef, M. H., Rispens, P., & Stevens, M. (2001). Reliability of the Groningen fitness test for the elderly. Journal of Aging and Physical Activity, 9(2), 194-212.
[4]	Rikli, R. E., & Jones, C. J. (1999). Development and validation of a functional fitness test for community-residing older adults. Journal of aging and physical activity, 7(2), 129-161.
[5]	Eurofit, C. O. E. (1993). Handbook for the Eurofit test on physical fitness. Strasbourg: Council of Europe.
[6]	Welk, G., & Meredith, M. D. (Eds.). (2010). Fitnessgram and activitygram test administration manual-updated 4th edition. Human Kinetics.
[7]	Knapik, J. (1989). The Army Physical Fitness Test (APFT): a review of the literature. Military medicine, 154(6), 326-329.
[8]	Bohnker, B. K., Sack, D. M., Wedierhold, L., & Malakooti, M. (2005). Navy physical readiness test scores and body mass index (spring 2002 cycle). Military medicine, 170(10), 851-854.
[9]	Rhodes, E. C., & Farenholtz, D. W. (1992). Police Officer's Physical Abilities Test compared to measures of physical fitness. Canadian journal of sport sciences, 17(3), 228-233.
[10]	U.S. Customs and Border Protection. (2015). Border Patrol Agent Pre-employment Fitness Test-1 Physical Readiness Program, U.S. DHS.
[11]	American College of Sports Medicine, editor. ACSM’s health-related physical fitness assessment manual. Lippincott Williams & Wilkins. 2013.
[12]	Nindl, B. C., Alvar, B. A., Dudley, J. R., Favre, M. W., Martin, G. J., Sharp, M. A., ... & Kraemer, W. J. (2015). Executive summary from The National strength and conditioning association's second blue ribbon panel on military physical readiness: military physical performance testing. The Journal of Strength & Conditioning Research, 29, S216-S220.
[13]	American College of Sports Medicine. ACSM’s Resources for the Exercise Physiologist, 2nd. Philadelphia, Md.: Lippincott Williams & Wilkins. 2017.
[14]	Raven P, Wasserman D, Squires W, Murray T. Exercise Physiology. Nelson Education. 2012.
[15]	Hart, P. D., Benavidez, G., Detomasi, N., Potter, A., Rech, K., Budak, C., Faupel, N., Thompson, J., Schwenke, L., Jericoff, G., Manuel, M., Lee, T., Edmonson, W., Auzenne, C., Kirkaldie, T., Lonebear, M., & Miller, L. (2017). A multitrait-multimethod (MTMM) study of fitness assessments in college students. SM Journal of Sports Medicine and Therapy. 1(1): 1002.
[16]	Ramsbottom R, Brewer J, Williams C. A Progressive Shuttle Run Test to Estimate Maximal Oxygen Uptake. Br Sports Med. 1988; 22: 141-144.
[17]	Haff, G. G., & Triplett, N. T. (Eds.). (2015). Essentials of strength training and conditioning 4th edition. Human kinetics.
[18]	American College of Sports Medicine. (2018). ACSM's guidelines for exercise testing and prescription. Lippincott Williams & Wilkins.
[19]	American College of Sports Medicine. (2012). ACSM's resource manual for guidelines for exercise testing and prescription. Lippincott Williams & Wilkins.
[20]	Stokes, M. E., Davis, C. S., & Koch, G. G. (2012). Categorical data analysis using SAS. SAS institute.
[21]	Cody, R. P., & Smith, J. K. (2006). Applied Statistics & SAS Programming. Prentice Hall.
[22]	Matthews, T. D., & Kostelis, K. T. (2011). Designing and conducting research in health and human performance. John Wiley & Sons.