Scinovex
article

Profiling physical fitness attributes in college students: A cluster analysis

Abstract

Background: 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

Obesity, Physical Activity, DietEating Disorders and BehaviorsPhysical Activity and HealthTraitOverweightPhysical fitnessCluster analysisCluster (spacecraft)ReplicatePsychologyStatisticsPopulationLatent class model
Citations
1
FWCI
0.00
field-weighted impact
References
9
Percentile
39%
vs. same field & year
References
A progressive shuttle run test to estimate maximal oxygen uptake.
British Journal of Sports Medicine · 1988 · 768 citations
Physical Activity and Public Health
Circulation · 2007 · 6,525 citations
Citation Network

How this paper connects to the literature. Drag to explore, click any node to open that paper.

Profiling physical fitness attributes in college students: A cluster analysis · Scinovex