Physiological profile comparison between high intensity functional training, endurance and power athletes

Author(s):  
P. E. Adami ◽  
J. E. Rocchi ◽  
N. Melke ◽  
G. De Vito ◽  
M. Bernardi ◽  
...  
2020 ◽  
Vol 16 (3) ◽  
Author(s):  
Paolo Emilio Adami ◽  
Jacopo Emanuele Rocchi ◽  
Negassi Melke ◽  
Andrea Macaluso

2014 ◽  
Vol 46 ◽  
pp. 859
Author(s):  
Katie M. Heinrich ◽  
Sarah J. Stevenson ◽  
Taran Carlisle ◽  
Jacob Frye ◽  
Jennifer Hauser ◽  
...  

2018 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Brian Kliszczewicz ◽  
Chad D. Markert ◽  
Emily Bechke ◽  
Cassie Williamson ◽  
Khala N. Clemons ◽  
...  

Author(s):  
Douglas Daniel Costa Santiago ◽  
Jaqueline Santos Silva Lopes ◽  
Aníbal Monteiro de Magalhães Neto ◽  
Claudia Marlise Balbinotti Andrade

Introduction: Aerobic training with an acyclic and intermittent character triggers high metabolic stress, responsible for generating alterations in several blood biomarkers. Thus, investigations that clarify understanding of metabolic behavior in response to exercise seem pertinent, when considering the dynamics of prescription of physical training and recovery. Objective: Demonstrate and discuss the behavior of blood biomarkers in response to High Intensity Interval Training (HIIT) and High Intensity Functional Training (HIFT). Methods: The PubMed/MEDLINE, Scielo, Lilacs, Bireme, Google Scholar, and Scopus databases were searched from the oldest records available until January 16, 2020. The search was carried out by combining descriptors related to the terms: “HIIT”, “HIFT”, and “blood biomarkers”. To be included, studies were required to: 1) have a clinical trial design; 2) evaluate the effects of an HIIT and/or HIFT protocol; and 3) measure blood biomarkers before and after the training protocol. No restrictions were applied to the characteristics of the participants regarding health condition, age, sex, and level of training. Results: In total, seven studies were included (n=221 participants, aged between 18 and 63 years) that analyzed different population profiles such as athletes, sedentary young people, patients with breast cancer, and diabetics. The biomarkers evaluated included analysis of muscle damage (C Reactive protein and CK); oxidative stress (antioxidant capacity); kidney injury (creatinine and urea); hormones (testosterone and cortisol); cytokines (TNF-α, IL-6, IL-1β, IL-10, IL-4, and IF-γ); and hemogram. In general, the results demonstrated specific patterns for the investigated markers. Thus, there were increases in muscle damage markers, while in the inflammatory markers, there was a reduction in pro-inflammatory cytokines and an increase in anti-inflammatory cytokines. Despite the reduced values of the general blood count, markers such as neutrophils and basophils did not demonstrate statistically significant alterations. Serum testosterone levels were higher and cortisol was lower in the post-exercise period when compared to pre-exercise. Conclusion: These data are of practical relevance when demonstrating patterns of physiological responses, which also characterize knowledge and understanding essential to determine adequate periodization.


2021 ◽  
Vol 53 (8S) ◽  
pp. 32-32
Author(s):  
Tomás Ponce-García ◽  
José Ramón Alvero-Cruz ◽  
Jerónimo García-Romero ◽  
Javier Benítez-Porres

2017 ◽  
Vol 49 (5S) ◽  
pp. 423
Author(s):  
Katie M. Heinrich ◽  
Sarah J. Cosgrove ◽  
Yuri Feito

2019 ◽  
Vol 44 (2) ◽  
pp. 172-178 ◽  
Author(s):  
Matthew M. Schubert ◽  
Elyse A. Palumbo

CrossFit (CF; CrossFit Inc., Washington, DC, USA) is a form of high-intensity functional training that focuses on training across the entire spectrum of physical fitness. CF has been shown to improve a number of indicators of health but little information assessing energy balance exists. The purpose of the present study was to investigate energy balance during 1 week of CF training. Men and women (n = 21; mean ± SD; age, 43.5 ± 8.4 years; body mass index, 27.8 ± 4.9 kg·m−2), with ≥3 months CF experience, had body composition assessed via air displacement plethysmography before and after 1 week of CF training. Participants wore ActiHeart monitors to assess total energy expenditure (TEE), activity energy expenditure, and CF energy expenditure (CF EE). Energy intake was assessed from TEE and Δ body composition. CF EE averaged 605 ± 219 kcal per 72 ± 10 min session. Weekly CF EE was 2723 ± 986 kcal. Participants were in an energy deficit (TEE: 3674 ± 855 kcal·day−1; energy intake: 3167 ± 1401 kcal·day−1). Results of the present study indicate that CF training can account for a significant portion of daily activity energy expenditure. The weekly expenditure is within levels shown to induce clinically meaningful weight loss in overweight/obese populations.


2018 ◽  
Vol 36 (16) ◽  
pp. 1872-1879 ◽  
Author(s):  
Brian Kliszczewicz ◽  
Cassie Williamson ◽  
Emily Bechke ◽  
Michael McKenzie ◽  
Wade Hoffstetter

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