Ryan D. Burns^1,, You Fu², Timothy A. Brusseau¹, Nora Constantino²

Because health-related fitness consists of several domains, understanding clustering of scores from a testing battery can help practitioners derive exercise programs. The purpose of this study was to explore the clustering of health-related fitness test scores in college students and to validate the solution against criterion measures. Participants were college students (Mean age = 19.2 ±0.6 years; N = 523; 342 females, 181 males) recruited from a university in the southwestern U.S. The health-related fitness assessments consisted of BMI, estimated VO_{2 Peak} from the Astrand-Ryhming cycle ergometer test, and a standard push-up test. Criterion measures consisted of DXA-assessed percent body fat (%BF), measured VO_{2 Peak} from a maximal treadmill test, and a 1-Repetition Maximum (1-RM) bench press score. A hierarchical cluster analysis was performed to derive groupings. One-way ANOVA tests were used to explore the differences among the derived cluster groups on each criterion measure. Six cluster groups were formed representing various fitness “phenotypes” (Pseudo-F = 179.7). The cluster groups differed in %BF (F(5, 517) = 44.6, p < 0.001, eta-squared = 0.31), measured VO_{2 Peak} (F(5, 517) = 49.7, p < 0.001, eta-squared = 0.33), and 1-RM bench press scores (F(5, 517) = 17.0, p < 0.001, eta-squared = 0.12), providing validation evidence. Six cluster groups were formed from a health-related fitness test battery in college students that were validated against criterion measures of health-related fitness. The cluster groups can be used to inform current fitness status and for derivation of exercise programs.

exercise, fitness, health, young adult