The decision-making strategy discussed in this study increases objectivity when selecting aerobic TI and, consequently, broadens the use of V̇O2max for prescribing exercise. Furthermore, a comparison of the EEActual to the ACSM guidelines facilitates the prescription of different EE adjustments because it uses current information about an activity (volume and intensity) and the characteristics of the subject who is undergoing a training routine (V̇O2max and BM).
The objective result of the proposed approach is not a substitute for health and fitness professionals and should be taken as a suggestion and not as a rule. Using canned training criteria alone does not seem to increase the probability of success during individual adherence to a training program (24). Adjusting TI based on personal preferences, particularly for subjects with moderate prior exercise experience, has been shown to be adequate for configuring aerobic training (9,16). Therefore, the EEActual technically and conceptually enhances individual prescriptions for aerobic exercise; however, one should be free to adjust TI to make training an enjoyable activity and improve exercise compliance.
Of the advantages of the present approach, the utility of individualizing EE is noteworthy. Presently, there is a disassociation between the EEActual (Table 2) and EEACSM (Table 1). This difference can probably be explained by the fact that the EEACSM does not consider the influence of subject BM, aerobic fitness, and proportional capacity on TI tolerance (3). The integration of these variables establishes a curvilinear pattern of EE response as a function of V̇O2max and BM that differs from the EEACSM, as can be observed in Figure 1. For example, there are differences ranging from ≈56% (100 vs. 44 kcal·session−1) for lower levels of aerobic fitness to 18% for higher levels of aerobic fitness (800 vs. 946 kcal·session−1), when comparing a suggested EE between the EEACSM and EEActual for subjects with a 60-kg BM. For subjects with a 100-kg BM, the differences range from ≈26% (100 vs. 74 kcal·session−1) to 97% (800 vs. 1,576 kcal·session−1) (Tables 1 and 2 and Figure 1). These differences can be confirmed by the effect size comparisons that are presented in Table 3.
Another practical application of the present proposal is to the design of a combined program of strength training and aerobic exercise (concurrent training). Although resistance training is known to improve endurance (17), in both athletes (34) and nonathletes (28), guidelines for the combination of both exercise modalities have not yet been published. When preceded by strength training, aerobic activity increases hemodynamic responses, perceived exertion (5,7), and lactate concentration (22); however, it is not associated with increased oxygen uptake (22). In the converse exercise scheme (aerobic exercise followed by resistance), the maximum number of repetitions could be compromised if endurance exercise is performed at a high intensity (above anaerobic threshold) and with the same muscle groups (8). Given the possible equivalence of the training intensity determined in Table 1 and the anaerobic threshold (either conceptually or in a didactic scenario that involves clients and instructors), the present proposal could be used to set higher or lower TI depending on a subject's V̇O2max and training sequence (strength followed by endurance or endurance followed by strength). Future studies should address this question.
Even with the advantages of this study and its similarities to the ACSM guidelines, there are no recommendations for configuring interval training, especially at supramaximal intensities. In recent years, considerable evidence has demonstrated the benefits of interval training on aerobic performance, related variables (V̇O2max, aerobic enzymatic activity, etc.), health indicators (glucose control, lipid profile, blood pressure, etc.) (11-13,15,32), and the adherence of subjects to an exercise program when compared to less intense routines (18). Despite the criticism of this approach (9), high-intensity stimuli have been shown to be safe and efficient (29,33) and are options for the diversification of aerobic activities that are not included in the ACSM guidelines.
Other limitations must be addressed. Based on the available literature regarding aerobic exercise guidelines and the somewhat imprecise and indirect methods that are used to predict body fat and lean BM, body composition was not used as an independent training variable, although it is important. Body composition should be considered in future studies so as to refine training recommendations. Variables aside from V̇O2max have been shown to influence the ability to perform aerobic exercise (economy of movement, metabolic thresholds, critical power or velocity, lactic and alactic anaerobic power, strength and muscular elastic capacity, thermoregulatory and anticipatory ability, etc.) (14,19-21,30); however, as an isolated and easily assessed criterion, we believe that V̇O2max is the variable that best expresses a subject's aerobic potential because it determines the other variables that compose TI; however, the model presented herein still requires validation and possibly modification, especially regarding the mathematical approach that was used in its development because the linear relationship pattern between the variables may not express the most accurate relationship. This hypothesis should be examined in future experimental investigations.
In light of the aforementioned limitations, we conclude that the suggested approach facilitates a more objective and coherent selection of aerobic TI and more precise EE, namely the EEActual. Its application should be understood as a tool for individualized decision making within the “art of exercise prescription”. Despite the need for validation and future modification, the present approach is a strategy for more objective, EE-based TI decision making for aerobic exercise prescription and weight-loss program design.
The primary advancement achieved by this study is the introduction of the first individualized method for determining aerobic training variables based on V̇O2max, including equations for practical use on spreadsheets or specialized software. For example, if a subject has a V̇O2max of 34 ml·kg−1·min−1, based on Table 1, he or she should exercise at 52%R for 36 minutes and 4 d·wk−1. This strategy facilitates appropriate decision making for the prescription of aerobic exercise. Furthermore, we improved the EE choice by considering the real volume and intensity training adjustments in association with subject V̇O2max and body weight. In conclusion, the approach proposed here provided criteria for adjusting aerobic training variables (e.g., volume, intensity, week frequency and EE) consistent with subject capacity, thus diminishing the risk of the imprecise prescription of aerobic exercise programs and its consequences.
We would especially like to thank the reviewers for their important suggestions. The authors declare that they have no conflicts of interest. No external financial support was required for this project. Tony Meireles dos Santos was sponsored by a grant from the Rio de Janeiro Research Foundation (FAPERJ E-26/110.153/2010 e E-26/190.127/2010). Bruno Ribeiro Ramalho Oliveira was sponsored by a scholarship from the Rio de Janeiro Research Foundation (FAPERJ E-26/100.088/2010) and from National Council of Scientific and Technological Development (CNPq 130310/2011-5). Paulo S. C. Gomes is supported by CNPq.
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