Different amount of training affects body composition and performance in High-Intensity Functional Training participants.

• Main Authors: Valentina Cavedon, Chiara Milanese, Alessandro Marchi, Carlo Zancanaro
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2020-01-01
• Series: PLoS ONE
• Online Access: https://doi.org/10.1371/journal.pone.0237887

The effects of High-Intensity Functional Training (HIFT) on body composition and the relationship of the latter with performance are not well defined. In this work we investigated, by means of Dual-energy X-ray Absorptiometry, the relative proportions of fat-, lean soft tissue-, and mineral mass in CrossFit® (CF, a popular mode of HIFT) participants (n = 24; age, 28.2 ± 3.39 y; BMI, 25.3 ± 2.04 kg/m2) with at least 1 year of CF training experience and weekly amount of training > 10 h/w (n = 13; Higher Training, HT) or < 10 h/w (n = 11; Lower Training, LT) as well as age- matched and BMI-matched physically active controls (CHT, CLT). Performance was assessed in the "Fran" workout. Data were analyzed by one-way or repeated measures ANOVA where needed. Association between variables was assessed with the Pearson's correlation coefficient r. Partial correlation was used where needed. Results showed that HT performed better than LT in the "Fran" (P < 0.001) and they had higher whole-body bone mineral density (P = 0.026) and higher lean soft mass (P = 0.002), and borderline lower percent fat mass (P = 0.050). The main difference between CF participants (HT, LT) and their respective controls (CHT, CLT) was a lower adiposity in the former. In CF participants, performance positively correlated with appendicular lean soft tissue mass (P = 0.030). It can be concluded that, in CF participants, a higher amount of weekly training improves most notably lean body mass and increases performance in association with increased skeletal muscle mass. CF participation is especially effective in reducing fat mass vs. age- and BMI-matched physically active controls.