Health-related fitness traits vary greatly in general populations, ranging from very low to very high levels. However, less is known regarding fitness trait clustering,
Purpose: The purpose of this study was to determine if health-related fitness traits cluster in a college student population.
Methods: Data for this research came from a larger fitness measurement study and included N=131 college students attending a rural public university. Ten (10) fitness variables were used in this study. The first set of five variables represented each component of fitness and were used to construct the latent clusters. The second set of five variables were used to validate the identified clusters. All variables were T-score transformed before analysis. Cluster analysis was performed using the k-means method.
Results: Four clusters of individuals were identified in the analysis: 1) Anaerobic and Fit, 2) Aerobic and Fit, 3) Overweight and Unfit, and 4) Normal weight and Unfit. The original set of fitness variables all had significantly different (ps<.001) means across the four cluster groups. The validation tests also showed all five variables with significantly different (ps<.05) means across clusters.
Conclusion: Results from this study show that health-related fitness attributes in college students form four specific clusters. These findings may have implications for health promotion marketing of physical activity programs to college students.