Abstract
Background: CrossFit® involves high-intensity functional movements and research has shown that the program increases metabolic rates in participants. Objective: To measure resting energy expenditure (REE) in CrossFit® participants using indirect calorimetry (IC) and to verify the most appropriate predictive equation to estimate REE. Methods: Overall, 142 CrossFit® participants (18–59 years; 91 [64.1%], women) underwent weight, height, waist circumference, and body mass index (BMI) measurements. Body composition was evaluated using a portable ultrasound system (BodyMetrix®). REEs were measured (mREE) by IC and predicted by six different equations (pREE): Harris-Benedict, World Health Organization (WHO), Henry and Rees, Cunningham (1980 and 1991), and Mifflin–St. Jeor. Results: The mean age was 33.0 (6.3) years, with no significant difference between men and women; mean mREE, 1583.2(404.4) kcal/d; and pREE, 1455.5(230.9) to 1711.3(285.5) kcal/d. The best REE predictive equations for this population were Cunningham (1991) (P=0.338), WHO (P=0.494), and Harris-Benedict (P=0.705) equations. The Harris-Benedict equation presented a smaller difference compared with IC [12.9(307.6) kcal], the Cunningham (1991) equation showed improved adequacy (102.5%), and the WHO equation presented highest accuracy (59.9%). The equations that were closest to the mREE were the Harris-Benedict for women and the WHO equation for men. Conclusion: Therefore, for CrossFit® participants, the REE can accurately be predicted with the Cunningham (1991), WHO, and Harris-Benedict equations.
Highlights
CrossFit®, a high-intensity functional training model created by Greg Glessman, requires cardiovascular physical ability and capacity, endurance, strength, flexibility, power, speed, coordination, agility, balance, and precision in participants
For this reason, resting energy expenditure (REE) is utilized since it is simpler to evaluate than the basal energy expenditure (BEE), presents a very small difference (3 to 10%) from the basal condition and it can be evaluated with the volunteer resting in a thermoneutral room (Levine, 2005)
The REE evaluated by indirect calorimetry (IC) was defined as the measured REE and it was compared with six predictive equations that are commonly used to evaluate this parameter (Table 1)
Summary
CrossFit®, a high-intensity functional training model created by Greg Glessman, requires cardiovascular physical ability and capacity, endurance, strength, flexibility, power, speed, coordination, agility, balance, and precision in participants. The BEE corresponds to basal energy expended by the body, representing 60–75% of the TEE in sedentary people or 45–60% of the TEE in athletes and participants of physical activity, approximately (Levine, 2005; Oshima et al, 2017). This basal condition is hard to assess in clinical practice. IJKSS 9(2): the gold-standard strategy (Delsoglio et al, 2019) It is a non-invasive technique that assesses the REE by analyzing oxygen and carbon dioxide gases. Our objective was to evaluate REE by IC in CrossFit® participants and to determine the safe and reliable REE predictive equations in these individuals
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