Body shape and performance on the US Army Combat Fitness Test: Insights from a 3D body image scanner
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Authors
Smith, Maria
Turner, Dusty
Spencer, Charlotte
Gist, Nicholas
Ferreira, Sarah
Quigley, Kevin
Walsh, Tyson
Clark, Nicholas J.
Boldt, William
Espe, Justin
Issue Date
2023
Type
journal-article
Language
Keywords
US Army Combat Fitness Test (ACFT)
Alternative Title
Abstract
Objective: To identify relationships between body shape, body composition, sex and performance on the new US Army Combat Fitness Test (ACFT).
Methods: Two hundred and thirty-nine United States Military Academy cadets took the ACFT between February and April of 2021. The cadets were imaged with a Styku 3D scanner that measured circumferences at 20 locations on the body. A correlation analysis was conducted between body site measurements and ACFT event performance and evaluated using Pearson correlation coefficients and p-values. A k-means cluster analysis was performed over the circumference data and ACFT performance were evaluated between clusters using t-tests with a Holm-Bonferroni correction.
Results: The cluster analysis resulted in 5 groups: 1. “V” shaped males, 2. larger males, 3. inverted “V” shaped males and females, 4. “V” shaped smaller males and females, and 5. smallest males and females. ACFT performance was the highest in Clusters 1 and 2 on all events except the 2-mile run. Clusters 3 and 4 had no statistically significant differences in performance but both clusters performed better than Cluster 5.
Conclusions: The association between ACFT performance and body shape is more detailed and informative than considering performance solely by sex (males and females). These associations may provide novel ways to design training programs from baseline shape measurements.
Description
Citation
Smith M, Turner D, Spencer C, Gist N, Ferreira S, Quigley K, et al. (2023) Body shape and performance on the US Army Combat Fitness Test: Insights from a 3D body image scanner. PLoS ONE 18(5): e0283566. https://doi.org/10.1371/journal.pone.0283566
Publisher
PLoS ONE
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Volume
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PubMed ID
ISSN
1932-6203